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In the dynamic landscape of mobile applications, optimizing User Experience (UX) is crucial for app success. This study investigates the user experience of mobile applications through rigorous testing methodologies, focusing on aspects such as design, functionality, navigation, performance, and overall usability. Utilizing the Net Promoter Score (NPS) as a quantitative metric, the study aims to evaluate user satisfaction and loyalty. The process consists of five phases, i.e., defining the object, determining participants, collecting data, using the NPS formula, and NPS analysis. The analysis of data was conducted on a sample of 50 participants. Findings reveal a favorable NPS score of 52, indicating positive user sentiment and a higher proportion of promoters than detractors. The statement suggests that conducting UX testing for mobile applications yields advantageous outcomes. However, The interpretation of the score is contingent upon the specific industry and contextual factors. It is imperative to recognize that the application of NPS should not be utilized in isolation but rather in conjunction with other usability measures to attain a more comprehensive understanding of user experience. The inclusion of qualitative feedback in conjunction with NPS has the potential to aid in the identification of specific areas that may benefit from improvement. Future research can include advanced analytics integration and exploration of emerging technologies. Overall, this study underscores the importance of NPS analysis in driving strategic decision-making and enhancing user satisfaction in the competitive realm of mobile application development.

In the ever-evolving landscape of information and communication, text mining plays a pivotal role in extracting valuable insights from vast textual data. While sentiment analysis has garnered substantial attention, this research delves into the broader spectrum of text mining, aiming to uncover emerging trends, challenges, and contemporary approaches that extend beyond traditional sentiment analysis. The study begins by scrutinizing the background of sentiment analysis in capturing the nuanced landscape of language, prompting an exploration into the types and classifications and compiling the available work of sentiment analysis based on text from the lexical approach to the deep learning approach. Researchers and practitioners grapple with multifaceted challenges that involve navigating the complexities of context, sarcasm, and ambiguity. This underscores the necessity for more advanced methodologies to effectively address the evolving intricacies of language. By synthesizing insights from the analysis of current trends and challenges, this research contributes to the ongoing dialogue in text mining, offering a comprehensive perspective beyond sentiment analysis. The findings of this study are anticipated to inform researchers, practitioners, and industry professionals in navigating the intricate landscape of text mining, fostering innovation and responsible deployment in an increasingly data-driven society.

The selection of skilled employees has become an intimidating task for human resource management and any other job openings recruitment because a job opening has more than thousands of applicants during a recruitment period. It becomes an incredibly challenging job to check all resumes for every applicant. To solve this, a resume screening technology of artificial intelligence may take place. The use of natural language processing and text mining as resume screening technology could ease this daunting task of the recruitment process. Applicants’ resumes will be read by the system instead of human recruiter teams and the model would work to classify the resume based on the organization’s requirements. Related Key terms and keywords will be stored in the system. The system will search the pre-defined keyword throughout the resume and a score will be given based on keyword match between resume and system, and a clear visualization will be done by decomposing the applicant’s resume according to requirement matched. Through this, the model will show the total score earned by each resume as well as the individual score earned by each area. As a result, recruiters may take the decision about the right talent acquisition by looking into the result.

'School Coders' is a unique Youth Hub initiative that stands out for its commitment to promoting STEM (science, technology, engineering, and mathematics) education in Malaysia. It is designed to build inclusive communities by empowering students from diverse backgrounds, including all races and ethnicities, irrespective of religion as well as social status, including people with disabilities from rural, urban, and indigenous communities. The initiative aims to foster a culture of creativity, critical thinking, and problem-solving, and empower students and educators through technology. It is implemented in schools across Malaysia, targeting primary and secondary-level students and educators, and is inclusive of students of all abilities, including those with special needs. The initiative utilizes a combination of curriculum-based coding education, hands-on activities, and practical projects to engage students in STEM learning. The program also emphasizes the importance of diversity and inclusion in the field of STEM, encouraging students to embrace diversity and foster an inclusive mindset. The "School Coders" initiative aims to address the disparities in STEM education by making it accessible to all students, regardless of their socio-economic background or geographical location (SDG 10). The program is implemented through partnerships with schools, local communities, government and non-government organizations, and industry experts to ensure a holistic approach to STEM education (SDG 17). It provides opportunities for students to develop their coding skills, explore STEM career pathways, and connect them with mentors from the industry (SDG 8). Furthermore, "School Coders" focuses on the capacity building of educators by providing professional development opportunities to enhance their pedagogical skills in effectively delivering STEM education (SDG 4). The initiative is working towards creating a sustainable ecosystem for STEM education in Malaysia by advocating for policy changes and fostering collaborations between academia, industry, and government agencies (SDG 17). The anticipated outcomes of the "School Coders" initiative include improved STEM literacy among students, increased participation of students from diverse backgrounds in STEM fields, and a more inclusive and equitable society. By promoting STEM education and inclusivity, "School Coders" aims to contribute to Malaysia's economic growth and social development by preparing the next generation of innovators and problem-solvers to thrive in the digital age.

Fruit quality, including color, texture, size, and defects, significantly influences their market value and customer preference. Conventional manual fruit quality assessment methods are both time-consuming and laborintensive. Image processing methods, particularly convolutional neural networks (CNNs), have proven to be efficient in automating fruit quality recognition to address this issue. This study compares various CNN models' accuracy in classifying images of fresh and rotten apples, bananas, and oranges. We assessed three pre-trained CNN models—MobileNet V2, ResNet50, and VGG19—alongside the K-Nearest Neighbors (KNN) algorithm. The findings suggest that VGG19 achieved the highest accuracy at 99.56%, followed by MobileNet V2 at 98.37%, and ResNet50 at 94.21%. The accuracy of the KNN algorithm, however, was notably lower at 68.18%. This study sheds light on the effectiveness of different CNN models for assessing fruit quality and offers direction for future research in fruit image classification.

Prior research highlights the limitations in current mainstream troubleshooting techniques used to assess accidents and ensure future safety. This study proposes a methodology to promote safety in sky sports and discusses its effectiveness and future research directions. The System of System Failures (SOSF) and Failure Factors Structuring Methodology (FFSM), categorized and distributed under the SOSF, are applied to sky sports safety. The three dimensions of the SOSF are represented by the coupling of the system (tight vs. loose), the degree of interaction with the external environment (linear vs. complex), and the frequency of failures. These dimensions allow the SOSF to be configured as a three-dimensional space. By introducing the distance phase (i.e., topological metrics), the risk trajectories of the system can be quantitatively visualized. This allows each instance of failure to be represented as a point in the SOSF space as a System Risk Location. Therefore, the system risk situation can be quantitatively discussed for comparisons between and within systems and learning from other systems. Stakeholders can thus share the recognition of failure cases and discuss problem-solving. The FFSM facilitates double-loop learning by structuring the complex factors that lead to failure and visualizing the trajectory of failure in the SOSF space, thereby clarifying the overall and precise countermeasures. Specifically, the study clarifies the insights that promote safety in sky sports and identifies directions for future data accumulation. Therefore, we demonstrated the possibility of expanding the SOSF and FFSM utilized in this study to other fields (human activity systems).

In today's digital era, maintaining cognitive health is increasingly essential, especially as the global population ages and children experience heightened screen time. This research, "Brain Boosters," seeks to address these challenges by developing a mobile game designed to enhance cognitive functions across different age groups, specifically targeting young children and the elderly. The game integrates educational and brain-stimulating activities to promote memory, problem-solving skills, and mental agility. Through interactive and enjoyable gameplay, "Brain Boosters" aims to offer a constructive alternative to traditional mobile games, fostering cognitive development while providing entertainment. This research outlines the design, development, and evaluation phases necessary to create a mobile game that bridges generational gaps and contributes positively to cognitive well-being

Despite debate, challenges and promised benefits of artificial intelligence has opened new opportunities for Higher Education Institutions with dynamic environment. Systematic literature review revealed the research concerning artificial intelligence capability on HEIs performance still relatively scanty and need for further investigation. To address the gap, we proposed artificial intelligence capability model underpinning on Resources- Based View and Dynamic Capability in Higher Education Institutions. This paper contributes theoretically to the academic literatures, stakeholders and managerial practice by extending resources-based view and dynamic capability view to create better understanding of advanced artificial intelligence in Higher Education Institutions context.

The proposed transformer was designed with flexible spirals, similar to the Archimedes spiral design, to achieve a thin transformer structure. Soft layered magnetic materials were produced by stacking two or more sets of spiral coils on a plane at a short distance from each other and using suitable spacer materials between these coil sets. Accordingly, an innovative, thin, flat, and flexible transformer was created, and its functionality was ensured. The specifications of the spiral coils were as follows: wire diameter = 20 mil, the gap between turns = 20 mil, number of turns = 40, and thickness = 1 OZ. The transformer was designed with a one-layer or two-layer structure for conducting experiments. Coils were stacked directly to change the coil ratio of the transformer. The substrate material was polyimide, which is flexible and can generate a sound when interacting with magnets. The performance of the developed transformer was examined under two coil ratios: 1:1 and 1:2. Different magnetic materials were used between the coil sets to examine the effects of these materials on the transformer performance. Five settings (A–E) were adopted in this study, and the optimal experimental results were obtained in Setting E, and the second-best results were obtained in Setting C. A silicon steel/primary coil/secondary coil/silicon steel structure was used in Setting E. The output voltage and current were 0.22 V and 12.6 mA, respectively, at a coil ratio of 1:1, as well as 0.49 V and 8.7 mA, respectively, at a coil ratio of 1:2. In Setting C, a magnet/primary coil/secondary coil/magnet structure was used, and the output voltage and current were 0.20 V and 9.27 mA, respectively, at a coil ratio of 1:1 as well as 0.46 V and 7.45 mA, respectively, at a coil ratio of 1:2. The experimental results revealed that the performance of a flat transformer is mainly affected by the spacing between the primary and secondary coils and not by the magnetic material between two coil sets. The secondary coils generate the maximum voltage and current when the primary and secondary coils tightly fit together without any spacer material.

The pandemic of COVID-19 resulted in the closure of universities and colleges worldwide, making the Learning Management System (LMS) an ideal approach for delivering education. Online LMS can provide a smooth communication channel between teachers and students. The LMS should be designed in such a way that it can address the challenges of distance learning while also assisting communities in learning during lockdowns. A LMS can be described as an online education hub that includes a comprehensive collection of educational activities such as classroom instruction and distance education. This paper will discuss the usability of LMS that focus on interactivity and efficiency among two LMS, blackboard and moodle. Primary data was collected from 87 learners, all of whom were university students at Bath Spa University RAK, through a questionnaire. The collected data was sorted and organized through SPSS. The paired t-testing was applied with a 95% interval level that compares the p-value with 0.05 to evaluate if the efficiency and interactivity of moodle and blackboard are the same. According to the result, it was concluded that they're not the same in terms of efficiency and interactivity. With the experiment results, we found that moodle is more efficient and interactive than blackboard for Bath Spa University academic center RAK students.

The purpose of this research is for interdisciplinary students, with the theme of smart city space, how to conduct collaborative learning on thinking, identification, and strategies for programming and visualization issues, to develop an intelligent interactive interface between users and environmental data. We have set up an interdisciplinary course on “Interactive Smart Space Design”, which combines the fields of interactive design, engineering, electrical machinery, and electronics, trying to introduce unmanned aerial vehicle simulation path, modular programming, and information visualization modules into the course to conduct programming and computational thinking learning, guiding students to conceive and design, and in-depth development of programs and development practices. Finally, analyze and evaluate the learning effect through the work report and Expert assessment. The results show that the modular programming method is more suitable for students with low information ability, and the information visualization performs better in the later stage of the project, reflecting the actual staged division of labour in the industry. The interdisciplinary collaborative learning process can reflect and revise problem points in the process of thematic decision-making, but coordination and division of labour impact team cooperation.

High-tech inventions and advances in smartphones and wireless communications have revolutionized learning technologies such as ubiquitous learning, mobile learning, and electronic learning. Ubiquitous learning is an innovative state-of-the-art technology for learning at your will, anytime, anywhere, using mobile or handheld devices. By providing flexibility and multiple learning mediums, Ubiquitous learning students can overcome obstacles such as poor classroom facilities, cultural and religious barriers, and busy personal and professional lives. This study aims to study the factors influencing whether students accept and use these new technologies, like ubiquitous learning. This research spread the prevailing study on the UTAUT2 and developed a theoretical model of ubiquitous learning acceptance. Furthermore, this study is also expected to help guide learners in crafting and employing courses and executing courses aimed at seamlessly integrating technology. This research adopts quantitative research methods to achieve the desired results, and data for this study will be gathered through a cross-sectional survey. Therefore, the total population is 600, and data collected from four provinces of Pakistan and six university students responded with 301 data to validate the proposed model using an innovative PLS approach and cluster technique. According to the results, context awareness, self-directed learning, hedonic motivation, personal innovativeness, personal compatibility, performance expectancy, and facilitating conditions affected behavioural intention with an R-square variance of 52.8%. These empirical findings identify several influences as the most critical factors affecting ubiquitous learning adoption. They make several theoretical contributions to help higher education institutions promote students' adoption of ubiquitous learning while enhancing their practical value.

This review comprehensively covers the research accomplished in the field of laser color marking process for various industrial applications. Laser color marking technology in recent years has been envisaged for numerous applications of all types of solid materials in a single step process. Likewise, the traditional laser marking process generally produces contrast marks which are often monochromatic. Therefore, there is more interest in color marking by laser processing for decoration and visual attraction in recent years. It is currently the most studied research to observe the effect of laser irradiation process parameters and external environmental factors on the formation of different colors on metals and non-metallic surfaces. This paper presents a detailed review of the recent advancement in laser coloring technologies. Furthermore, the process of laser color marking has been discussed based on the compatible parameters of the color mark and laser types. Moreover, the effect of laser processing parameters on microstructural features and the corresponding metallurgical defects encountered such as cracks and chemical composition are recapped. Finally, this article summarizes the present-day applications of the laser color marking technique used in many industrial sectors.

The quality оf any prоduct is clоsely assоciated with maintenance strategies оf any industry. Tоtal Prоductive maintenance is a unique tооl tо enhance the perfоrmance оf a manufacturing industry by prоducing quality prоduct due tо reduced dоwntime. The purpоse оf this paper is tо evaluate the оutput results оf implementing Tоtal Prоductive Maintenance techniques in a Yunus Textile Mill industry. Effectiveness оf TPM implementatiоn is validated and evaluated thrоugh Оverall Equipment Efficiency. The study prоved that the cоmpany has strоng pоtential tо enhance its perfоrmance and оverall prоduct quality thrоugh successful implementatiоn оf TPM methоdоlоgies.

The rapid growth of Artificial Intelligence (AI) with the evolution of network technology has improved and progressed to meet the needs of people. Big data place an important role in the field of AI due to enhanced utilization in computer networks. Many applications are used for big data-based AI in a computer network environment. The problems and the attacks (such as Ransomware, Phishing attacks, and AI attacks) occurring in Network Technology are widely associated with AI as big data along with the solutions such as detection and identification of given attacks and malicious activities. The computer network technology environment is used on a large scale and varies widely with the use of AI in the context of Big Data. However, more advanced technologies are applied with AI to ensure the security of Computer networks. Due to the vast amount of traffic occurring in networks, the result leads to the occurrence of damage in the network, and intrusion detection is a process that proved to be the most essential to ensure the security provided to the system. The defined attacks are specified as the main issues and will prevent vulnerable and malicious activities. The network requires a system to detect intrusions, which is further used to observe and identify the system and networks for anomalies and malicious intrusions as Intrusion Detection System (IDS), Firewall, Encryption, and Anti-spam technologies are used to identify any malicious activity and prevent it. For these attacks, Long Short Term Memory (LSTM) is used in deep learning, and many other technologies such as Machine learning and Data mining are associated with LSTM to detect intrusions. The computer networks with the application of big data as AI were made highly secure and efficient systems by implementing the proposed LSTM method.

In this paper a review is made of the History, Fundamental principle, and Architecture of Instrument Landing System (ILS) RF Circuits in the Receiver and Transmitter Antenna Array. The study was motivated by a need to cater to the increasing availability and use of aerial vehicles such as drones and that the conventional landing system is insufficient and risks being overwhelmed, thus this study aims to explore alternative paths and particularly the option of the MLS as a possible cure. The paper describes the Localizer and Glide path of the System. This paper gives small introduction of Microwave Landing System (MLS) and Enhance ILS Category-I Category-II Category-III is used. An additional purpose served by this study is to layout the requirements that an MLS would require in regard to its implementation and what factors would need to be considered by any organization willing to implement the system. The argument is built up by first assessing the existing infrastructure of landing systems; their origins and effectiveness, following this, the advances system such as the MLS are introduced, their current applications and potential are discussed. A comparison is made between the two to highlight the superiority of the MLS. The study carried out in this paper finds the limitations in the ILS method as they are only capable of carrying out landing in a straight path and further limited by geography. MLS on the other hand is more versatile and is capable of carrying out multiple landing approaches across multiple curved paths for a single installation. The study examines the advantages of implementing the MLS system in Pakistan.

The purpose of this chapter is to introduce a powerful class of mathematical models: the artificial neural networks. This is a very general term that includes many different systems and various types of approaches, both from statistics and computer science. The analogy is not very detailed, but it serves to introduce the concept of parallel and distributed computing. Neural networks explain and give the proper demonstration for the applications of neural networks and wireless network. The artificial network and wireless network have strong connection and can be investigated and explained properly. There are also some models which are called mathematical models which can explain and demonstrate the artificial and wireless networks in detail. There are many organizations which are using artificial neural networks by using sensor technology for wide range of purpose. Then we analyze in detail a widely applied type of artificial neural network: the feed-forward network with error back-propagation algorithm. We illustrate the architecture of the models, the main learning methods and data representation, showing how to build a typical artificial neural network. Our aim is not to examine them all (it would be a very long discussion), but to understand the basic functionality and the possible implementations of this powerful tool. We initially introduce neural networks, by analogy with the human brain.

As a new rapid prototyping technology, Single Point Incremental Forming (SPIF) gains considerable investigation and development as its simple manufacturing tools, low cost, etc. To predict the quality of the manufacturing finished products and reduce experimental costs, many scholars and companies applied and investigated numerical simulation of SPIF. However, many problems emerge like extremely long simulation time, difficulties in forecasting profile geometry and thickness variation, etc. A long way needs to explore to improve the accuracy of SPIF simulation. Focus on this target, and this paper studied the influences of shell thickness integration rules (Simpson and Gauss), sheet thickness, and element types (with reduction and full reduction) on simulation accuracy. For the experiment, a top diameter of 115 mm, bottom diameter of 12mm, and 27 mm high cone part was formed on a customized three-axis CNC milling machine. Contourgraph was used to obtain profile geometry. Then the deformed part was cut, and a micrometer was used to obtain thickness distribution along with the profile of the formed sheet, respectively. For simulation, shell elements were employed to simulate SPIF explicit simulation. Furthermore, Simpson and Gauss rules integral in thickness direction were used for simulating the same geometry part, and the results were compared. Average Absolute Relative Error (AARE) was used to compare all the profiles and thickness from simulations and experiments, and it can be found that element types with reduction integration can get more accurate results and cost less time. Furthermore, the Gauss integration rule along shell thickness is more accurate than the Simpson rule. Therefore, to achieve greater accuracy, it is recommended to use the Gauss integration rule and reduction integration element (S4R) to predict the profile geometry and thickness prediction in SPIF dynamic explicit simulation.

The accurate bus arrival time information is crucial to passengers for reducing waiting times at the bus stop and improve the attractiveness of public transport. GPS-equipped buses can be considered as mobile sensors showing traffic flows on road surfaces. In this paper, we present an approach that predicts bus arrival time using historical bus GPS information and real-time situation on the road. In this study, we divide bus arrival time into bus dwelling time at bus stops and bus travel time between stations and predict each of them separately. The clustering approach used to predict the travel time between stations, and then for each cluster, we apply LSTM NN to predict walking time between stations. The latency at each bus stop we evaluate by historical dwelling time and using location analysis to find the importance of the bus stop as a point of interest during prediction time. The study is trained and tested on GPS data collected from 1200 buses in a period of 3 months. According to tests results our method show small mean absolute error for buses that not far from departure station. The outcomes of this work can be used as an additional information for bus passengers to know possible bus coming time and to estimate possible travel time in bus journey. The method for arrival time prediction proposed in this research has several advantages. It considers historical bus travel time information, real time information, bus dwelling time, riding time, traffic lights and city facilities.

AI has paved the way which has enabled us to produce machines resembling human intelligence. Because of AI it is now possible that machines learn from experience and perform real thinking and tasks. For which this has been possible is named Machine Learning which has various sections under it. There are four different types of this area – Supervised Learning, Unsupervised Learning, Semi-supervised Learning and Reinforcement Learning. Machine Learning basically focuses on the learning of computers and performing tasks by themselves. Unsupervised learning is the one where no labelled input is there so, machine only identifies patterns in data and separate them into different clusters. Data clustering algorithm is an unsupervised type of machine learning where clusters get created from scattered data of any shape from unlabelled input. In this paper, some renowned data clustering algorithms to date and their applications will be analysed and discussed comparatively. And also, will provide an insight into helping them to be used in applications on the research field of Covid-19. Studying and analysing the Data Clustering Algorithms and their applications and utilising that to help in research field of Contagious diseases like, Covid-19 has been discussed and proposed in our research. Literature survey has been conducted to carry out this paper work. Google web search engine and Google Scholar search engine have been used to conduct research. Comparatively studying the Data Clustering Algorithms and their applications gave us insight that these can be employed into the research field of Covid-19 analysis. As have been discussed in the proposed hypothesises, this paper can widely be operated in the field of Biotech or Medicine, in genome research, or also, getting statistical data like infection regions, infection patterns, infected population etc. can be covered which will finally help in mitigating the impact of this disease, Covid-19. This is our expectation that with this review of data clustering algorithms as a future work, the hypothesises proposed here shall be researched more into experiments which will help measure the impact and effectiveness of Covid-19 like contagious diseases.

Absorption Refrigeration System can play a vital role in electrical energy conservation because they can be operated on waste heat energy. The intermittent nature of solar power may be a dominant think about exploring well-designed thermal energy storages for consistent operation of solar thermal-powered vapor absorption systems. Our goal is to design the cooling unit based on a vapor absorption system. For this purpose, we have done a literature survey, mathematical modeling, simulations, and made computer-aided design models of our unit. We verified our component operating conditions.Thermal energy storage acts as a buffer and moderator between so- lar thermal collectors and generators of absorption chillers and significantly improves the system performance. Vapor absorption chillers are available in half, single, double, and triple-effect modes of operation and operate at temperatures starting from 75 to 220^oC to supply a cooling effect with COPs starting from 0.3 to 1.8. Thus, the choice of appropriate solar collectors and thermal energy storages are two significant decisions affecting the consistency of output of a vapor absorption cooling system. This review covers all the major aspects of such systems. It also covers the research work done on this subject till now. Though there is still room for a lot of research work in this area of refrigeration systems. Moreover, the conclusions and recommendations are also discussed.

The quality of mobile applications is a very important and essential factor for their success among the users otherwise users will reject and discard the applications due to insufficient quality assurance. Mobile applications are becoming popular among the users and due to the peculiarities of mobile applications, there is also a need for quality assurance in the applications to focus and maintain the challenges faced by the users. This paper will identify the main points and expose different approaches which will address the problems and issues of quality assurance for mobile applications. There are research questions and according to those goals are derived. The quality of the mobile application is a very important factor for their success among the users. This depends on the users how they like the applications of the mobiles and successfulness of the mobiles directly depends on the users if the quality assurance for the mobiles for the mobile application should be the best quality. Different popular mobile in the market like I phone, Samsung, Nokia and Motorola are popular mobiles and brands model among the people because of their quality assurance for mobiles applications. FIT4 apps are represented by which quality assurance can be accessed for the mobile’s applications for quality purposes. If the quality level is low the brands and models of the mobile are straight way discarded by the users. Two steps empirical evaluation is done for the quality assurance purpose. The basic purpose of the experiment and a case study about the quality assurance of the mobile is performed as post mortem analysis. All mobiles’ applications require quality assurance approaches due to context approaches awareness and platform diversity. Some characteristics need to be addressed for quality assurance. There are some budgets restrictions which are sometimes become hindrances in software development.

The present age is the age of science and innovation. Robots have long borne the planned to conquer any hindrance between the automized world (the web of things) and the physical world. As the most reassuring possibility to subject the following major modern upset after the present third (computerized) mechanical upheaval, apply autonomy is set to play an ever progressively huge job in the public arena for its impact in each part of life. Counting prescription and medicinal services, building administration, fabricating, nourishment creation, coordination and transportation. The present century is likewise the century for Asia, or more noteworthy China specifically. China has turned into the greatest and quickest creating nation in the worldwide modern robot showcase for its changing assembling condition and improving nature of-expectations for everyday comforts, with anticipatable interest of robots in the assembling business, yet in addition other administration and societal segments. With its solid convention in innovation and close connections to overall research wildernesses, Hong Kong at present holds a main edge in parts, for example, medicinal, coordination, and household administration robots. Not with standing, with its total size, money related duty, and solid modern establishment, the Terrain is quickly grabbing pace, particularly in the mechanical and amusement divisions. It is subsequently a basic minute for scientists to join endeavors and structure a minimum amount in automated research to keep up the provincial, and towards overall lead in administration mechanical research. Hong Kong analysts, chipping away at the front line of mechanical autonomy that is intently connected with the future economy. Have many top-level work for mechanical careful help, call the board, assembling, and warehousing the executives, prompting exceedingly translational and gainful results that would help build up and flourish the Hong Kong one of a kind industry in restorative and administration robots, supplemented by a huge creation center and great market in the Territory. After deep study about the countries who are well developed in robotic world. We can have summed up with an idea that those countries who are using technology from this modern age are not only just getting advantage also building their national character amongst the other nation.it becomes mandatory to make our generation acknowledgement about this global automized technology and provides the platform to the industry to use such robotic autonomous system so that under developing countries should take advantage from them. Today the technology which is very popular amongst the scientific society according to latest research is the knowledge of AI. Inspire from NASA we research about the latest technology beneficial for human beings come up with an idea that as far the question of Industrial manufacturing is concerned we all know that accuracy and quality of work is possible through the machinery as compare the human work is referencing.

This investigated the flow and heat transfer of two-dimensional biomagnetic fluid (blood) flow over a non-linear stretching sheet in the presence of magnetic dipole. It is assumed that the magnetic field is sufficiently strong enough to saturate the ferrofluid, and a linear function of temperature difference can approximate variation of magnetization with temperature. The fluid viscosity is assumed to vary as an inverse linear function of the temperature. The governing boundary layer equations with boundary conditions are simplified to a couple of higherorder equations using the usual transformation. Numerical solutions are obtained by using the bvp4c function technique in MATLAB software. The acquired results are shown graphically and were examined for several values of the dimensionless parameters. It is observed that for different ferromagnetic interaction parameters and variable viscosity parameters, the velocity distribution decreases while temperature distribution increases. The magnitude of skin friction coefficient and the rate of heat transfer decrease with the increasing values of radiation parameter and Prandtl number. The results are also compared for specific values of the parameters with others documented in the literature.

This study aims to develop a framework for the factors that influence the adoption of Information Communication Technology (ICT) in Saudi Universities.COVID-19 pandemic quickly led to the closure of universities and colleges worldwide. The provision and usage of E-Learning, Learning Management System (LMS), Blackboard, and other online education platforms are becoming the main challenge for many universities during this pandemic. The needed to fast delivery of knowledge and information, anytime and anywhere, a catalyst factor for the growth of E-Learning worldwide. E-Learning system has several great features that would be valuable for use during this pandemic was changed the way of teaching and learning takes place in educational institutions. However, some barriers influence the use of this technology. This study employed a systematic analysis review of the relevant literature published between 2005 and 2020 to determine the significant contexts that affect the Adoption of LMS. The methodology adopted was the searching of scholarly databases. Following the criteria established for collecting this data, studies were reviewed and included in the review. As a result, this study attempts to review and analyze surveys that have investigated the critical internal and external obstacles to educational members' use of Technology in Saudi universities to improve ICT adoption in Saudi Universities.

In this study, the web traffic was analyzed via machine learning (ML) support, and incoming traffic was visualized after real-time classification, prioritizing stability and performance, which are indispensable for real-time applications. Websocket technology was used for instantaneous and fast data transfer. Processes may be blocked due to asynchronous operating structure when Hyper-Text Transfer Protocol (HTTP) traffic is intensive. Synchronous operation of the system was causing both delays and negatively affecting the efficiency of the application. To overcome this bottleneck, the developed application used asynchronous libraries instead of synchronous ones. The essential features of the study were the analysis of HTTP packets captured in real-time, classifying the packets according to whether they are safe or suspicious using ML algorithms, and real-time display of the acquired results. In this way, incoming traffic was classified smartly without getting lost in thousands of log files. A success rate of 96.49% was attained using the logistic regression model, which is very successful in classification.

Nowadays, textile industries are working to maximize profit by using lean tools. This paper describes various Cost of Quality procedures to determine COQ in the organization. Still, it was felt that it could be improved and simplified to make a standard format for finding quality for different departments. A Quality Cost procedure was refined and implemented in the textile industry. COQ program was implemented in the production department of a textile product manufacturer. Prevention, Appraisal, Failure & Opportunity Cost model was employed. The total COQ of the manufacturing textile unit was 6.8% concerning sales, which was later reduced to 4.5% after implementing lean and sustainable initiatives. The cost of quality was calculated for four departments. Internal failure is found to the maximum in all the departments. The major reason for high internal failure cost is the production loss (Target unachieved). There is a huge gap in the implementation and understanding of COQ concepts in the textile industries in Pakistan. This paper provides awareness to calculate COQ in the textile sector for all developing countries. The same procedure for COQ calculation can be followed in any textile industry, and COQ can be reduced easily.

NWe present details of a project to build an inexpensive AI-based home surveillance system using Raspberry Pi. We used a Raspberry Pi and a USB webcam to record a live environment and take photos when motion is detected. The proposed security system allows multiple cameras and users. Users have access to a control center where they can login and select the appropriate camera. The website interface encrypts the user’s account information and stores them in a database. Further, an improved setup using Pi-based camera is shown and discussed. The proposed system uses IBM’s Internet of Things software library to implement several features via node-red flows. Two flows are created. The first flow triggers the camera to take pictures when motion is detected. The picture is then sent to visual recognition node for processing. If there are people detected, an email is sent with the link to the streaming. If people are not detected, there is no further action. The second flow is used to analyze the picture with AI-based visual recognition node. The picture is passed to the visual recognizer for analysis. Then the result is sent to a template node for display as a table.

The development of big and large scale software is a complicated process. Bugs, errors and faults can occurred at any stage of development and these errors and bugs can be fixed as early as possible to sort out the problems. The process stops the propagation and reduces the costs of verification which might be happened. The engineers those who are able to maintain quality of the software can avoid from bugs in the system. Tasks can be done and veri􀅫ied earlier as while developing the code. The product deployment can be easy if the codes are done properly in the maintenance stage. Developing the codes and testing the software this can be effective for the codes testing schemes. In this research paper we are going to test software testing process which can lead to the deployment and testing of the software. The testing of software leads to the characteristics of the testing of software properly. The quality activities are involved with two steps. The first problem is discussed as revealing the faults and then the other one is accessing the faults. One process is ended, the quality cannot be measured. The quality can be measured at the earliest stage of the development of the software. But the quality is forced to maintain during the whole development process. Sometimes important classes with faults are difficult to find out. Software is excellent from which all errors and bugs are removed.

Conventionally, the metal joining process used to be carried out using fasteners and rivets. Since the advancements in technology, the metal joining process is now performed via welding. Because welding affects the mechanical properties, the importance of welding parameters to determine the mechanical properties of welded plates is considered. This research reviews the impact of Shielded Metal Arc Welding (SMAW) parameters on the mechanical properties of low-carbon, mild, and stainless-steel welded joints. It is necessary to understand the welding parameters to get the product of desired quality. In the past, the studies, the welding parameters: welding speed and current, were considered to find the impact via destructive testing (DT), including hardness and tensile tests. The present study aims to review the impact of welding parameters on hardness and tensile tests carried out in the past.

Current communication technology can ease sharing multimedia data such as images, text, graphics, audio, and videos online or offline. A multimedia editing tool can be downloaded freely and used efficiently to be editing the content of video clips. To solve integrity and originality, video clips are very challenging and require some complex methods. How to ensure that the content or the structure of the video provided or downloaded from the internet is original and just as recorded? Video forgery is a technique to generate fake videos with malicious intent by inserting, deleting, duplication their contents. Therefore, the video's originality can be questioned and need to be verified. Video forgery detection is intended to determine the originality of video content, whether the video has undergone any unethical change. The video forgery detection technique has two approaches, active and passive. This study focuses on the detection of tampering video using a passive approach because it is not dependent on pre-embedded information to determine the originality of the video. The passive approach will be extracting this feature from the video and analyzing them for different forgery detection. A passive approach is better than the active one as it relies on fake video available and features and its properties without needing the original video. The research focus was to apply a passive approach to develop a new model for video forgery detection. This model will be used to build a powerful tool for detecting video authenticity. Therefore, it can help certain parties, especially those involved in legal activities.

Automatic water meter reading recognition is the key feature of this paper from different environmental conditions. To do so, we have proposed a real-time automatic water meter reading recognition model in this research paper. Initially, from the meter image, the largest circular blob is extracted by creating a mask. As the water meter reading region can be tilted at a certain angle, the Hough transform is used to detect and correct the tilted angle. After tilt correction, to find out the circular meter region, the image masking technique is used following the largest blob finding technique. The corrected RGB meter image is converted to a grayscale image to reduce the computational cost for further processing. To improve the quality of the grayscale image, global histogram equalization is used. Using the Otsu threshold method, a gray image is converted to the binary image automatically. We have overcome the challenges of clipping the region of interest (ROI) extraction region. Applying horizontal and vertical projection, the region of interest (reading region) is extracted. At this point, a morphological operation has been implemented to reduce noise. To segment the digit image, a vertical projection algorithm is used. These segmented digits are then matched with template digit images following the correlation coefficient values. This work will overcome the problem of traditional water billing procedures and will be helpful to run a central water billing management.

At present, numerous people watch prerecorded TV programs as daily leisure. Concerning soap operas or sports, the viewers may not want to be informed about the results before watching the programs; however, they may check tweets on devices, such as smartphones, which can accidentally include contents referring to spoilers. To avoid reading such content, several approaches were proposed to detect spoilers in texts (both long and short ones), including tweets. In the study by Jeon et al. focused on detecting spoilers in tweets, only one person attached labels to tweets, and the labeled tweets were used to train detectors. The trained detector was tuned for one person and, therefore, could be unsuitable for others. A tweet published in the middle of a baseball game can be considered a spoiler by some people and not by others; therefore, a personalized detection method is preferred. However, to the best of our knowledge, none of the related studies has considered such a personalized approach. To address this problem, we propose a semi-supervised approach to detect spoilers in tweets using a support vector machine (SVM) in which each user attaches labels to tweets. After that, SVM executes the same procedure for other unlabeled tweets through bootstrapping. To verify the suitability of the proposed approach to personalize detectors, we conducted an experiment in which two participants were asked to attach labels to tweets. The experimental results indicate that this approach is efficient for personalized detection based on the Mann-Whitney U test.

This paper provides an efficient and reliable networked optimal control design of a two-wheeled inverted pendulum system to achieve wide-range system stabilization. Linear quadratic regulator (LQR) theory and its modified version with exponential term are initially cast into the LMI framework to guarantee stabilization as a selfbalancing robot. Next, an integral action is inserted into the LQR performance index to decrease the error substantially. Finally, the event-based policy is applied alongside LQR to decrease communication congestion over the network. An observer-based control is used; once the states are estimated, an optimal control law is generated to regulate the torque of the motors. Simulation results demonstrate that the system performance still optimal while the event-based regime is used.

The fluctuating interests of a fast and convenient lifestyle in the 21st century are on the rise, especially Fast Moving Consumer Goods' (FMCG) food sector. Manufacturers are under extreme pressure of squeezed margins due to heightened maintenance costs and complicated procedures of unstable and growing demand. More services and replacement of machine parts increases costs, planned downtime, and disruption to operations. This study presents a way 5G enables factory machines appliances to fulfill demand uncertainty by adapting to the environment and business process through machine-to-machine communication. It is possible by establishing higher flexibility, efficiency, and shorter lead times for factory floor production and layout changes [1]. How does 5G matters for manufacturing in the FMCG food sector for firms to sustain competitive advantage? Two perspectives of stakeholder based competition and resource based promote the maximization of profit. With direct involvement between machines, 5G build up efficiency and error detection ability of manufacturing. The most noticeable advantage of 5G is reliable communication protocols, sensors, accurate detection of machine maintenances, and faults. 5G is the future direction for the modernization of manufacturing; however, massive investment price indicates the commercial success of 5G in manufacturing is not expected in the next several years until the required cost of expenditure reduces. This research shows 5G in food manufacturing with big data application negatively correlate to efficiency for the near future. Later, food manufacturers can continuously enhance the knowledge and technology to acquire the best benefit of 5G at a beneficial cost and returns to a company's sustained competitive advantage.

Container transportation had become an important way for carrying cargo in the world because containers can be transported between ports and delivered to destinations conveniently by intermodal services. Container transportation is accomplished not only by ships but also by various handling operations at terminals and other vehicles such as trains and trucks. In the liner shipping industry, container terminals play important roles responsible for handling, storage, and loading/ unloading containers at the shipside. In response to handling the large number of containers brought by modern huge ships, most container terminals have been devoting to improve operating efficiency and the capacity of facilities and enhance the whole service quality to keep their competitiveness in the shipping industry. Therefore, the efficiency of terminal operations is crucial because the results can directly reflect the status of the terminal operation and indicate the direction for operators to take measures for improvement. This study intended to evaluate the efficiency of container terminals in the same port. The Data Envelopment Analysis (DEA) approach was used to measure the efficiency of CCR and BCC models to examine the relative efficiency and the scale efficiency. We defined container terminals in a Taiwanese port as the decision-making units (DMUs), and the items used in the models included six input items (number of berths, length of berth, design draft, number of gantry cranes, annual rental, and container terminal area) and five output items (container throughput, number of services, number of vessels in below 5500 TEU, number of vessels in 5500-10000TEU and number of vessels in more than 10,000 TEU) to estimate the efficiency of terminals. The result indicates useful information, which is helpful for terminal operators to adjust their input items for reducing waste and increase the output in an appropriate direction.

Global navigation satellite system (GNSS) ultra-fast orbit is an important parameter for near-real-time positioning, and its timeliness and accuracy are the key issues to be solved the phenomenon of reduced accuracy in the later stage of ultra-fast orbit observation an orbit refinement model based on orbit parameter accuracy of attenuation factor (DOP) is proposed. First, based on the orbit observation data information criterion is used to construct and optimize the DOP value prediction model; then, the DOP value is used as the independent variable to establish a function model between it and the orbit state parameters then the DOP with high precision prediction The value is substituted into the function model to realize the optimization of the orbit accuracy in the later period of observation. To verify the orbit refinement model, the observation data function and length model were analyzed separately. The results show that the orbit model refinement is optimal based on 1 d of observation data, and there is no clear difference between different function models. The multi-system ultra-fast orbit experiment based on continuous ten days shows that the refined model in the later stage of ultra-fast orbit observation can improve the orbit accuracy by 12.4%≈22.0%. Consequently, this model can perceive the refinement of the ultra-fast observation orbit, which is of great significance to improving the ultra-fast orbit of the analysis center.

Small and medium enterprises (SMEs) are fast becoming a driver of innovation in technology, and they play an important role in the economic development of a growing country. Businesses that acquire modernization cannot fully function without the help of information technology, which is essential for the survival and growth of economies in general. Adapting a data management system for a business firm is a big factor that can be used for fast and easy business transactions and processing results but considering its current price in the market, it may not be affordable for startup businesses. The study focused on a data management system configurable web-based application that can handle data based on the required set of procedures. This study integrated the concepts of distributed system algorithms in the developed data management system to define and find a solution for handling data responsibilities and techniques that can be used to solve the challenges encountered in this algorithm.

To increase accuracy for dynamic detection obstacles, this paper presents a Kalman filter observation error model based on 77 GHz middle range radar (MRR). In recently, the vehicle equips advanced driver assistance system (ADAS), which becomes more popular. Among these, the accuracy of the obstacle information, such as distance, relative speed, and position, is the most important purpose. However, radar is one of the main detection sensors, but its data transmission delay, including millimeter-wave reflection, the analogy to digital signal conversion, and data process, would influence radar tracking correction. Therefore, algorithm of the proposed model adopts detection time and a dynamic estimated model of an obstacle to compensate detection delay, such that the dynamic correction means error can be reduced. Next, the testing condition sets RTK-GPS as the real-world reference frame, the experimental would be realized with the dynamic scene. According to the above results, when the target distance closer 100 meter, our model's dynamic correction mean error was improved 59%, 74%, 78% during in 20kph, 40kph, and 60kph relatively speed, respectively.

This study presents the results of an analysis carried to compare the dimensional quality of parts built at different orientations and identify causes of dimensional inaccuracies of electron beam melting (EBM) parts built in different scenarios. The scenarios considered reflect common overhanging positions of part features built in the EBM machine. The results show that the parts built on the support structure had the optimum dimensional accuracy. Furthermore, there are close quality characteristics of the cylindrical features built in the X and Y direction, i.e., perpendicular to the build direction, due to the alternating scanning direction adopted by the EBM machine.

In the era of Industry 4.0, where factory efficiency is highly desired, knowledge about the position of the objects like tools, materials, and employees is indefensible for improving the processes and reducing idle times within the Smart Factory. The Smart Factory requires the real-time collection, distribution, and access of manufacturing relevant information anytime and anywhere. Indoor positioning systems (IPSs) can track objects such as assets or people in real-time and play a vital role. However, it is not easy to deploy such a system in a factory due to the obstacles and challenging environment. This paper shares the real experience of deploying Ultra-wideband (UWB) IPS in a manufacturing factory. The positioning system contains UWB anchors, tags, a backend system, and a frontend GUI. The deployment challenges and methods to overcome the challenges in factory environments are discussed. Techniques to improve accuracy such as implementing Kalman Filter, best practice of tag wearing and battery life consideration are also shared. Generally, a solution of providing indoor positioning in a smart factory is shared.

Study on the biological effects of irradiation becomes important nowadays. Mathematical modeling is one of the interests among researchers due to its ability to explain the dynamics process of irradiation. Some physical parameters cannot be evaluated from the empirical data. Therefore, the aim of this work to estimate parameters of the model of irradiation effects to bystander cells using optimization approaches. We employ two algorithms: Nelder-Mead Simplex (a local optimizer) and Particle Swarm (a global optimizer). We compare the efficiency of two optimization algorithms in optimizing the parameter values of the model. 50 sets of parameters have been estimated, and all sets can match the model simulation and the experimental data with the least sum-squared error (SSE). The graph of model simulation using a set of the estimated parameter from both optimization algorithms shows a good fit with the experimental data. The overall results indicate that Nelder-Mead Simplex (NMS) is better than Particle Swarm (PS) optimization in the aspect of time computing. At the same time, there is no significant difference in the score of SSE and converging iteration to the least SSE.

Throughout the evolution of the Internet and social networks, forums and online platforms have a vital role in sharing information, along with the creation and engagement of virtual communities. Such websites represent great resources, and they are the first step in the adoption of e-health services. When the persons are ill, many of them use search engines for self-diagnosis and gather possible treatment ideas before asking for a doctor's opinion. This takes a lot of time because the information is scattered across various forums and websites. In this paper is presented an application that aims to provide an online self-diagnosis and drug recommendation tool based on natural language processing of the symptoms described by the user. Over 2,200 medicines are stored in the database, each having a set of keywords according to their usage. Thus, the platform automates the search process, and provides the user with the most relevant information, eliminating the need for manual data interpretation. The results are ranked according to the confidence score obtained after the execution of the fuzzy search algorithm. The platform does not provide medical advice. Thus it is intended for informational purposes only. The developed platform is not a substitute for professional medical advice, diagnosis or treatment. Another feature of the platform is that it enables users to find hospitals and clinics around them, so that they can receive professional healthcare service. The field of medicine is a sensitive topic due to the fact that one mistake could lead to the loss of countless human lives. It was a long and difficult journey to reach the current state of medicine, but technology was and will remain essential to the evolution of the healthcare system. The proposed solution of this paper is customized for Romania but it can be adapted for other countries by replacing the drug database.

Contactless vital signs monitoring, such as respiration and heartbeat, can be a significant tool for applications in the fields of health care, surveillance and emergency. Among vital signs detection methods, Doppler Radar (Radio Detection and Ranging) has shown promising performance in various applications. Doppler Radar detects vital signs by transmitting a Radio Frequency (RF) signal towards the human body. Transmitted RF signal is phase modulated by the periodic movements caused by different body parts including chest and heart movements. Then, the Radar receiver captures the reflected signal and demodulates it to extract the vital signs' components. Since RF signals could easily be affected by every movement in the environment, studies in this area have reported limited accuracy, especially for heartbeat detection. This study presents a novel solution for this problem by developing a non-contact, non-invasive and unconstrained vital sign monitoring system. A low-cost prototype system using 24 GHz Continuous Wave (CW) Doppler radar is developed. By sampling the Radar signal for every 40 milliseconds, a time series signal is generated, and then is further divided into 30 seconds-length windows. First, for each window, an adaptive threshold method is used to filter noises generated either by random body movements or electronics artifacts. Then, convolution with a plank taper window -the frequency bands are taken as [0.7, 2.5] for the heartbeat, and [0.1, 0.5] for respiration- is applied. Finally, a peak detection algorithm is used to calculate heartbeat and respiration rates. Experiments are performed according to different daily life scenarios considering different sides of healthy subjects at different distances, up to 2 meters, from the system. A total of 100 minutes of recordings from 10 healthy subjects were used to validate the proposed system and its ability to measure vital signs for different subjects. The proposed system achieves 97.7 accuracies for respiration detection and 95.3 accuracy for heartbeat detection. The accuracy is determined by comparing the system results in highly accurate biometric sensors. By the end of this study, it has been proved that with this very low-cost design, a highly accurate vital signs detection system can be developed. Such a system could be utilized as a fundamental subsystem in a variety of applications; especially those designed for daily home usage.

In recent times the Software Defined Network (SDN), Network Functions Virtualization (NFV), Mobile Edge Computing (MEC), and Cloud Radio Access Network (C-RAN) have evolved as emerging technologies with high performance computing capabilities for the deployment of network functions such as mobile Evolved Packet Core (EPC), firewalls, local cache, virtual base station, etc. Also the of the abstractions provided by Software Networks technologies (essentially SDN and NFV) to support an abstracted model for any 5G network function, independent of its nature (network, computational, storage) and the implied resources (optical, wireless, satellite, cloud, etc). The growth in telecommunications has also led to increased deployment of Mobile Internet Protocol (IP) technology besides General Packet Radio Services (GPRS), 3G and 4G Cellular networks for high-end data or packet switched calls. Mobile IP is an outcome of convergence of cellular communication with the IP networks as a Next Generation Network application on traditional networks to support real-time multimedia services, network mobility and 2-way access. However, there are limitations with the Mobile IP which has its own challenges for implementing in the network which includes Security issues like Denial-of-Service attack, Theft of information Passive Eaves Dropping, insider attack, etc. Further, in Mobile IP there exist triangulation problems between the sending and receiving nodes along with latency issues during handoff for the mobile nodes causing huge burden in the network. This paper will try to compare some of the existing deployments of Mobile IP and make comparative analysis with the SDN implementation models for the Cellular Network for the Handoff mechanism.

Lane detection is key to advanced driver assistance systems to avoid traffic accidents caused by driver’s negligence, thereby improving driver’s safety. However, most lane detection algorithms are prone to error in challenging conditions when maneuvering in high curvature lanes, strong backlighting environment, low contrast night, and heavy rain condition, rendering unreliable and hazardous detection motion. This work proposes a lane detection algorithm by robust binary lane marking identification for lane feature extraction. The algorithm combines the median local threshold, line segment detector, and binary line segment filter to remove the noise generated when operating in the above challenging conditions. After correct lane feature extraction, Hough transformed and optimized random sample consensus parabola fitting are applied to detect lane markings. Experiment results show that the proposed algorithm outperforms the previous work in achieving correct detection rate at 95% in real-time.

This paper presents a technique to reduce positional errors in redundant Wheeled Mobile Robots (WMRs) with omnidirectional wheels. The errors could originate from different resources during the process of design to fabrication of a WMR including modelling inaccuracy, backlash/joint deflection, and misalignment. The technique is explained based on the kinematic equations of WMRs, and could potentially be used to correct both the lateral and longitudinal errors observed during the movement of a non-holonomic mobile robot. The major advantages of this method are simplicity, time efficiency, and use of simple-to-understand kinematics equations. In addition, it uses the linear regression method – that is easy to use – to quantify the contribution of each wheel on observed errors. The effectiveness of the method was investigated by testing a prototype three-wheeled omnidirectional robot. According to the test results, the movements of the tested robot was improved, and the systematic errors decreased by at least 74%.

This paper presents a developed web-based decision support system that implements a multi-criteria decision analysis, the Analytic Network Process (ANP) as a modeling tool in screening and selecting an agency’s priority projects for inclusion in the annual budget proposal. Screening and selecting priority projects for inclusion in the annual budget proposal of the government is complex decision-making that involves many stakeholders with conflicting priorities and dynamic preferences and limited technical information. Government decision-making becomes more complicated because of the complexities carried by the people involved in the process and other factors contributing to balancing political, technical, and economic considerations. The application of Multi-Criteria Decision Analysis (MCDA) methods for decision-makers helps them facilitate the systematic treatment of information, inform those involved in the process, and develop effective decisions in complex circumstances. The development of a decision support system that implements MCDA tools such as Analytic Network Process (ANP) modeling techniques in screening and selecting priority projects helps manage this complexity and makes decision-making efficient, effective, and transparent. The study used a pre-defined set of criteria identified during the progress of the study.

This paper proposes a software platform for correlating re-al-time physiological data using microservices and time series analysis with machine learning. We use a devops type architecture with multiple containers governing specific aspects of our platform. Several micro-services had been designed to orchestrate and process multiple data streams in real time to run the analytics and correlation protocol. The data ingested by our platform is provided in an intuitive data visualization interface that binds together digital elevation models and geospatial data with the blood oxygen saturation and heart rate of a subject. The platform provides an accurate representation of a subject's physical performance in high altitude/low oxygen environments.

Since the early 1990s, when frequent commercial use of the Internet started, academic researchers and website practitioners have actively conducted research on websites. The research's three broad categories are Web content mining, Web structure mining, and Web usage mining; apart from those, some research on coloring, placement technique of images, texts, and links on each page. This paper focuses on the difference between two cluster structures of websites, one induced from the link-based property and the other from the term-based property. The link-based property is stable until a new link is added, but the term-based one varies depending on the items for searching. We propose an evaluation method for the website by comparing the structures of clusters resulted from these properties. Here we adopt kernel k-means method as the clustering method and compare partial clusters derived from term-based property depending on the given sequence of particular terms to definite partial clusters from the link-based property. To distinguish them, we try to adopt spectral analysis.

This paper introduces a novel, advanced approach to evaluate and benchmark different types of state-of-the-art rotor position sensors for electric drive train systems. It has been well recognized that the reduction of overall emissions produced by transportation systems plays an important role. Cars containing an electrical powertrain are getting more and more widespread in different markets worldwide. Research nowadays is concerned with developing more efficient electrified powertrain systems that can reduce CO2- and harmful emissions. For an efficient and optimized motor control, it is crucial to measure the electric machine's exact rotor angular position and speed. The state-of-the-art rotor position sensor technology used in electric drive trains represents the resolver, which is the investigated sensor type in this research work. To find the most suitable resolver type for a specific powertrain application and so to optimize the overall propulsion control, various kinds of multispeed resolvers from different manufacturers are gauged regarding electrical parameters, that the producer does not define by default. Electrical measurement principles are applied, e.g. to determine the sensor’s input and output impedance, establish the transfer function based on the transformer equivalent circuit, specify the phase delay, and the electrical characteristic's temperature behavior. These evaluations are done on a unique, highly accurate sensor test bench and extend the state-of-the-art rotor position sensor characterization [1-4]. The mentioned test bench enables to gauge various kinds of sensors under different mechanical-, speed- and temperature conditions. The new, advanced approach enables a detailed determination of all relevant sensor parameters that are needed to operate an efficient motor control. Furthermore, the methods supports detailed benchmark with the target to determine the most accurate resolver. In addition, the resulting knowledge of the sensor parameters enables further innovative investigations e.g. to determine indirect measured quantities.

With the development and popularity of smart devices, streaming data is continually generated at the network's edge. Under those edge scenarios, it takes high latency to process the streaming data by cloud computing. And uploading the raw data to cloud servers by networks faces data privacy issues. Streaming edge computing provides an opportunity to fill the gap between the real-time process and data privacy protection by conducting the major computing at the edge of networks where the streaming data is generated. In the paper, we propose and build SCCS, a Streaming data Cooperative Computing System suitable for an edge environment. This system (i) cooperatively conducts data analysis tasks on several servers at the edge of network topology; (ii) utilizes the geographically distributed data set; and (iii) protects data privacy and data value. A case study of analyzing real shared bicycle distribution demonstrates how edge nodes servers cooperate with others to process streaming data on real-time.

Analysis and forecasting of the life cycle of vegetation are essential in planning agricultural work and monitoring crops and forecasting their productivity. In practice, vegetation indices are often used that are calculated from the values of satellite image pixels like normalized difference vegetation index (NDVI). Forecasting this index in precision agriculture allows indicating problems related to agricultural crop growth in time and making timely decisions about necessary measures to fix these problems. In the paper transferring approach for data preprocessing parameters and forecasting model is developed that provides forecasting of other normalized vegetation index time series without new preprocessing and training if the Euclidean distance between the time series used in the training and the time series using the data processing parameters and the forecasting model is small enough.

Manufacturing of eco-friendly composites has been increased due to recyclability and biodegradability factors. The effect of fiber volume fraction on tensile strength in composites polyester-reinforced sugar palm fiber (SPF) has been studied experimentally. This study aim is to investigate the effect of fiber volume fraction on tensile strength of composites polyester-reinforced sugar palm fiber (SPF) and fracture failure after tensile testing, and then these data results can be used as references on manufacturing industries such as boat building, which are expected can be replaced with composite polyester reinforced by SPF. Sugar palm fiber (SPF) is soaked in an alkaline solution of 5% NaOH for 2 hours, then composites laminate with five different fiber volume fractions were fabricated with hand lay-up and press molding and tested under tensile loads respectively, for the tensile test specimen, refer to the standard ASTM D-638. The test result showed that the highest tensile strength was obtained in the fiber volume fraction of 40%, amounting to 24.65 MPa and the elongation has obtained 7.73%, while the lowest tensile strength has obtained in the fiber volume fraction of 20% amounting to 17.55 MPa and the elongation has obtained 4.41%. Based on the result and analysis use single-way ANOVA, it can be concluded that the composite polyester-reinforced sugar palm fiber (SPF) has the optimum tensile strength on the fiber volume fraction of 40% and fiber volume fraction has an influence on the tensile strength of composite polyester-reinforced SPF. After tensile testing, fracture failure and cross-sectional shape of composite material showed that there are two types of failure, namely fiber pull out and delamination that indicates the bond between fiber and matrix is weak.

Multiple interventions and innovations in geometric layouts on the road reduce travel time, reduce traffic congestion, and increase mobility flow. One of these improvements is the introduction of protected U-turns at junctions. With the implementation of this technique, the through-moving traffic is given priority as they traverse without any obstruction. Such a system is beneficial if the designer aims to design the junction signal-free and it lessens the travel time to some extent. Although it is practical, certain implications and consequences arise with the execution of such an unconventional layout. Pakistan currently utilizes this idea in designing its roads currently. This paper aims to highlight the potential consequences as well as the advantages of this arrangement. To better understand these phenomena, some existing examples are given of Lahore in this paper to pinpoint the pressing issues at large, i.e., obstructions to pedestrians, land acquisition issues in urban areas, need to provide pedestrian bridges which ultimately increase the cost of the project. The contribution of this research will aid the geometric designers and traffic engineers to take multiple considerations in the planning/designing the stage from all ends before instigating this pattern on roads.

Analyzing the thermal conductivity of soil as a function of other parameters is necessary to understand the flow of heat around the earth-to-water heat exchanger. Thermal conductivity depends on several parameters, including soil composition, water content, compaction level, and porosity. The effect of the above parameters on thermal conductivity was investigated through laboratory studies. Samples were collected at a depth of 2 meters below ground level from an area located within the American University of Sharjah Campus. The thermal conductivity of the prepared specimens was measured using a C-Therm Technologies analyzer. The results indicate that increasing the water content and dry density increase the thermal conductivity of the soil. However, it was noticed that the initial water has a higher effect on thermal conductivity than the initial dry density. Additionally, it was found that porosity affects the hydraulic conductivity of the sand. The results of this study can be used to investigate the geothermal potential in the GCC region further.

The surging call for SMEs in the private transportation domain to apply data analytics in its business is evidential. However, to date, there is a lack of specific data mining methodology or framework customized to meet the demand of the private transportation domain. Considered as a de-facto data mining methodology by the industry to date, the Cross-Industry Standard Process for Data Mining (CRISP-DM) consists of a six-phase process that is extendable in the framework – from generic to specialized tasks. The traditional CRISP-DM methodology exemplifies the DM application area, issues identifications, technical, tools and technique requirements. Through this study, an Enhanced CRISP-DM for SME Coach Operator (ECSMCO) methodology was developed. The extended methodology aims to curb the existing application limitation identified in the small and medium-sized enterprises (SMEs) by proposing an enhancement to the existing CRISP-DM activities. To evaluate the novel ECSMCO’s acceptability, three UK SME coach operators were identified to apply and evaluate the ECSMCO methodology. The outcome of this paper will ascertain the users’ acceptability outcome of the applied ECMSCO methodology.

Venipuncture is a common practice performed in medical institutions. It now relies on the well-trained medical staff. The work is inherently risky, requiring skills, experience, and a high degree of focus to avoid discomfort or even danger to the staff themselves or the patients. The proper insertion point for venipuncture is sometimes difficult to recognize. In recent years, many applications of machine vision and image processing technologies have been used to help physicians, nurses, and other medical practitioners determine the patients' physical conditions, make the appropriate diagnosis, and reduce fatigue or other human factors causing misdiagnosis. In this paper, the implement machine vision technologies to assist the recognition of venipuncture insertion points is studied. Two industrial CMOS cameras are used with an infrared light source. The two cameras are placed apart and tilted at a certain angle relative to each other to achieve the stereo vision of the arm. Light filters are also installed on the lens of the two cameras. The cameras are calibrated beforehand to eliminate distortion. Two images of the arm, one by each camera, are captured. The images are then processed through image binarization and morphological algorithms. Afterimage processing, the best needle insertion position, puncture depth, and angle are determined. The developed system can improve the efficiency of venipuncture, and reduce the risk to medical staff and patients.

In this paper, a new passive filtration system that utilises gravitational force for unfiltered splash lubricated gearbox is presented and analyzed. This filtration system is based on the combination of different types of Shape Memory alloy (SMA) for the controlling of filtration layers’ deflection under different conditions. The primary SMA wires are biased by a bending force created by another type of SMA wires that exhibit super-elastic behavior. These wires are embedded in a silicone rubber film. The phase transformation of SMA wires is induced by the change of lubricant temperature. Finite element model based on ABAQUS is developed to simulate the thermo-mechanical behaviors of the filtration layers. A prototype passive filtration system is made. The experimental observations on the thermo-mechanical behaviors of the prototype are shown to be in a good agreement with the numerical simulation results. This shows the capability of the numerical model for estimating the mechanical behavior of filtration layers with embedded SMA wires at different temperatures.

Sustainability is regarded as the keyword of the 21st century. The topic of resource conservation is now more relevant than ever. Above all, the automotive industry, which is the most important industry in terms of turnover and the growth engine for Germany, has to deal more intensively with sustainable development and the associated effects and challenges. Automotive manufacturers are under pressure to comply with both political guidelines and internal specifications and constantly changing individual customer wishes. For the automotive industry, electric motors, lightweight construction, and CO2 emission reduction are key issues. Nevertheless, the car’s interior cannot be ignored. After all, the interior is the part of a car most frequently seen by the driver and must therefore be practical, aesthetically pleasing, and at the same time weight saving. The use of natural fibers as alternative materials in the interior plays an important role and further steps towards greater sustainability. Consequently, the following research question arises: How do the three pillars of sustainability (economical, ecological, and social issues) influence automotive interior development at volume brand and premium brand manufacturers, and how do customers accept sustainable solutions? The contribution focuses on premium and volume brand manufacturers and identifies significant differences between both customer groups. Based on a literature review on sustainability in the automotive industry, previous efforts to increase sustainability in the automotive interior are highlighted. Subsequently, an empirical study is used to determine the expectations on the customer side regarding more sustainability in the automotive industry in general and in the interior sector in particular and to derive corresponding challenges and potentials for original equipment manufacturers and suppliers. The empirical study is based on an online survey with randomly selected persons via social media. The survey was conducted via Survey monkey. All persons with a minimum age of 18 years were considered. Almost 400 participants fulfilled the desired characteristics.

In this paper, the design and simulation of the QPSK transmitter using HDL code in MATLAB are presented. Different applications in DSP require mathematical modeling for investigation and analysis due to the complexity of HDL code language. The idea of design the HDL-SIMULINK form using MATLAB is to offer enough facility to modify and improve the wireless communication systems. Implementing any DSP model in real time based on FPGA platforms requires translating the MATLAB-SIMULINK model to HDL code before the bit generation is downloaded to this board. The floating-point implementation should be transferred to a fixed point for a high dynamic range of applications. An alternative approach has been proposed based on HDL code, and the property of simulation environments in MATLAB is designed. The data transfer, synchronization, and driving sample between Simulink and HDL language are explained in this paper.

The evaluation and selection of recycling technologies presents one of the most important operational management problems. In this paper, a new fuzzy model to evaluate recycling technologies with respect to numerous criteria, simultaneously, taking into account the type of each criteria and its relative importance. The relative importance of criteria and their values are modelled by interval triangular fuzzy numbers type-2. Determining the criteria weights is stated as a fuzzy group decision making problem. The ranking of considered recycling technologies is obtained by applying modified ELECTRE. A case study with real-life data which come from reverse supply chain existing in the Republic Serbia is presented to illustrate the proposed method. The presented solution enables the ranking of recycling technologies and provides base for successful improvement of reverse supply chain management.

This paper considers the vast development in sensor technology such as embedded systems, GPS, wireless communications, and wireless sensor applications. In recent years an efficient design of a Wireless Sensor Network has become a leading area of research for semi-ballistic uncrewed Aerial Vehicle (UAV). A sensor network is a device that responds and detects some type of input from both the physical or environmental conditions, such as pressure, heat, light, etc. The sensor's output is generally an electrical condition that is transmitted to the controller for further processing. Wireless sensor network has been widely used. Its design has become an important field of control engineering and provides a real-time communication system in surveillance, tracking, and monitoring applications. In this paper, the development of a wireless sensor network for targeting and control system of a semi-ballistic UAV for rapid and precise search and rescue operations is being presented and discussed. The developed system is composed of two sections: Air Section and Ground Section. The Air Section consists of Magnetic Compass Sensor, Micro-Electro-Mechanical Sensors (MEMs), GPS, Camera, Servo Motor, and Parachute Controllers. The latter consists of Video Recording, Receiver, and Monitoring. The system will help in locating the exact location at the centralized level. In effect, it increases the response efficiency. Furthermore, this system helps control and protect the naval, ground and arm forces in any search and rescue operation locations. The wireless sensor network system can collect, store, and analyze data from several devices embedded in the vehicle. Results show that multi-sensor fusion and integration play a critical role in the semi-ballistic uncrewed aerial vehicle's overall design and performance enhancement.

Water is a basic necessity in our daily activities. Therefore, there should be enough supply of water to meet our demands. On average, in Cebu City, the Philippines alone, 24 cubic meters per household per month is used [1]. To meet the demand, water has to be properly distributed considering several factors, which are: (1) temperature, (2) precipitation, (3) population, (4) water rates, (5) historical water use, (6) water supply, and (7) socioeconomic profile. This study developed an Artificial Neural Network (ANN) water distribution decision support system that predicted water demand. The ANN was trained using historical records of the factors mentioned above and provided municipal and barangay water demand predictions with accuracy above 90%.

The West Surabaya Sailing Route (APBS) is a shipping lane that is an in and out access port of Tanjung Perak Surabaya. The location of the APBS, which is the estuary of several rivers, has resulted in the sediment rate being high, so dredging activities need to be done regularly. In contrast to the dredging activities in other places, the dredging carried out along the APBS must be carried out carefully because it is a mined area. A gas pipeline belongs to Kodeco and PLN's high-voltage undersea cable that runs along the APBS line. As a result of the higher hazard potential of dredging sites elsewhere, more comprehensive risk analysis needs to be carried out to reduce the risk of dredging. From some risk identification found in the APBS, it is known that the major risk with the highest risk value based on qualitative calculations using FGD is the risk of ship collisions. By calculating the cost index (ICAF), the best mitigation to reduce the risk of ship crashing is to install a buoy as a barrier and shipping signs. After obtaining the best mitigation based on costs, then quantitatively performed by numerical simulation to determine how much influence mitigation on the probability of ship accidents. From the simulation calculation obtained the mitigation effectiveness to reduce the risk of ship accidents. The biggest decrease in the probability of a ship accident due to overtaking of 100%, followed by a decrease in the probability of a ship accident due to a head-on collision by 54%. Furthermore, the decrease in the probability of ship accidents due to crossing and the probability of ship accidents due to each stranding decreased by 17% and 12%.

This study investigates the flame transition velocities at various intercylinder separation distances for side-by-side dual blowing cylindrical burners. The flame transition velocity is defined as the airflow velocity at which the envelope flames over the two burners transform into two separate wake flames. The transition velocity increases as L decreases through the range of 1.2D ≦ L ≦ 2.5D (D is diameter of cylindrical burner). When L > 2.5D, the transition velocity remains constant because the two flames do not interact with each other.

The pertinent characteristics of Field Programmable Arrays (FPGA), such as parallelism, low-power consumption, programmability, and low cost, make FPGA convenient for real-time applications, time-consuming algorithms as well, and services (MWS). Once built on FPGA, MWS becomes much less vulnerable to software attacks. Although FPGA technology implies lower performance and higher dimensions than Application Specific Integrated Circuits (ASIC), FPGA offers the advantages of programmability, reduced design costs and time-to-market. Indeed, multimedia Web services on FPGA are becoming common due to the availability different design tools as well as opensource modules. In this article, we are particularly interested in designing multimedia Web services with high Quality of Service (QoS) that employ substantial processing and memory resources.

Procurement of Government Goods/Services has an important role in the realization of national development to improve public services and the development of the national economy. Implementation of contractor tender selection by the Government Procurement Service Unit must be implemented quickly and produce effective decisions. Usually, a decision of Working Group Selection is not following the wishes of the Project Owner, and Project Owner needs contractors who can fulfill the specifications, have a correct methodology, have sufficient workers, have reasonable prices, and complete on time. This research was conducted to develop a method of selecting contractors by integrating the AHP and QFD. The result of this research is an application that can be used as tools selection. This application contains "Voice of Owner,” which is calculated using the AHP, and weights of technical responses are modeled with HOQ. Fifty priority technical responses must be fulfilled by the Working Group when doing the contractor evaluation. It is expected that these applications will help the Working Group select contractors according to the wishes of the owner.

Nowadays, contemporary consumers look for engaging, robust, compelling, and memorable experience services so that competent service is not enough; services need to provide a good customer experience as a competitive advantage. In this research, the quality of service experience will be improved based on the Customer Experience Quality model integrated with Quality Function Deployment (QFD) method. This research will be conducted on a telecommunication companies in South Surabaya, Indonesia, which has decreased the number of Wifi Broadband Services users. Customer perceptions and importances of each Customer Experience Quality attribute in every customer touch point will be processed to identify which attributes are prioritized for improvement with the Important-Performance Analysis method. Then those priority attributes further processed using QFD to design the improvements and the technical recommendations. By improving quality of service based on Customer Experience Quality, it is expected increasing services in providing good experience for customer. Framework integration of Customer Experience Quality (EXQ) model and Importance-Performance Analysis into QFD will be developed in this study.

Multi-modal artifact metrics is an anti-counterfeiting technique and was created based on the concept of multimodal biometrics. This method adds additives (functional materials) to the artifact during the manufacturing process to provide multiple feature information. Hence, the certainty of authenticity and difficulty of counterfeiting could be enhanced. We developed a new type of glass phosphor to provide two kinds of characteristic optical information (emission intensity and hue) into the artifact. This is a novel approach since up-conversion phosphors with a different hue and emission intensity by optical excitation at each observation point have never been reported. In this paper, we report the development of this glass phosphor, especially the production method and results of the fundamental experiments. The developed glass phosphor emitted as intended and demonstrated the validity of our approach.

Flow characteristics around/behind a porous circular cylinder and porous sphere in a wind tunnel are studied. The parameters are incoming flow velocity (Uin), air ejection velocity (Vw) from the surface of cylinder/sphere, and dimension/shape of cylinder/sphere. This study is divided into dual parts. First part deals with flow field with no air ejection from the surface of cylinder/sphere, and the second one deals with the flow field for air ejection from cylinder/sphere surface. Finally, for each cylinder/sphere, Vw and critical Uin that causes the wake returns to the rear of cylinder/sphere are correlated into equations, respectively.

Industry 4.0 or smart manufacturing uses digitalization to change manufacturing methods. However, there is little empirical research into the benefits of smart manufacturing, though some studies point out that latecomers will lose competitiveness. This research uses a case study to explore how an aerospace company implemented smart manufacturing in practice. The company uses emerging technology to build up the smart manufacturing process and vertical integration. In its vertical integration, the company uses sensors to collect the manufacturing data for analysis. The results can be displayed on a mobile system immediately for managers and operators controlling the manufacturing process and productivity. The company faced challenges in launching its vertical integration in smart manufacturing, including operators’ Information Communication Technology (ICT) skills and knowledge, linking the ICT systems of new and old facilities, and big data analysis capabilities.

The competitive pressure induced by progressing globalization has forced companies to find new ways of differentiation. Industry 4.0, as the synonym for the next significant step in value creation advancement, offers new technologies and procedures to obtain further improvements in competitiveness. The real-time networking of people, machines, and objects is not only an opportunity to leverage productivity potentials; it also enables new data-driven business models to achieve an increase in revenues. Although the concept and enablers of industry 4.0 are widely known across the producing industry, companies struggle with its successful and sustainable implementation. Due to the often insufficient embedding of individual solutions in a coherent overall concept, implemented solutions cannot exploit potential synergies within the company. The presented paper introduces a framework to control and synchronize Industry 4.0 activities within a company centrally. By integrating bottom-up and top-down perceptions, the framework facilitates the early identification and assessment of potential industry 4.0 applications and efficient development of specific solutions up to the implementation in series production. Consisting of an operationalization process and an organizational model optimized for horizontal and vertical exchange within the company, the framework enables faster and more robust implementation of industry 4.0.

Image feature extraction is a step of object extraction information in an image to recognize or distinguish it from other objects. The method used for feature extraction is the Gray Level Co-Occurance Matrix (GLCM). This research is related to features calculation from the melanoma cancer and non-melanoma images using GLCM based on variations of gray level, which are 4, 8, 16, 32, and 64, and angles of GLCM orientation consisting of 4 and 8-way. The used features are angular second moment, contrast, correlation, entropy, inverse moment, and variance. Then, the feature values are used as input parameters to classify melanoma cancer by utilizing an artificial neural network (ANN). This experiment is conducted by using 45 datasets of images from www.skinvision.com. Generally, all of the experiment types’ results accurately predict melanoma and non-melanoma classification by ANN more than 93%. By inputting six parameters from GLCM feature extraction using (1) 4th degree of gray level and 4-way orientation angles and (2) 16th-degree gray level and 8-way orientation angles, we can obtain the accuracy of ANN classification by 100%.

The major concerned objective of this paper is to suggest more detailed analytical methods to simulate the projectile impact on concrete target using the finite element analysis software of ANSYS LS-DYNA. The concrete is a principal material that has been comprehensively used in the field of civil and architectural engineering including from high-rise structures to long-span bridges. Not only these typically representative buildings, but other structures and national major facilities, such as nuclear power plants, also have mainly adopted concrete in various ways. These concrete structures should be designed against severe accidents causing structural failure. In this regard, the structural safety of each concrete structure should be evaluated meticulously. Detailed analytical methods are suggested by establishing numerical models in the software, which are used to simulate actual experiments in the past, F-4D jet impact experiments conducted by Sandia National Laboratories in 1988.

Fatty acid is an important intermediate substance in oleochemical industry. The demand of fatty acid is predicted to increase significantly in the future due to increasing demand of oleochemical products, specifically biofuel production through decarboxylation of fatty acids. For decades, fatty acid has been commercially produced via thermal hydrolysis of triglyceride, which requires high temperature and high pressure. Technology of fatty acid production in mild temperature and low energy consumption is currently developing through enzymatic triglyceride hydrolysis, which is also known as lipolysis. The economic feasibility of this technology is enhanced by immobilization of lipolytic enzymes, which frequently utilizes hydrophobic beads as immobilization supports. The aim of this research is to investigate the effect of hydrophobic beads on non-enzymatic hydrolysis of triglyceride. Experimental data suggest that higher conversion of triglyceride hydrolysis was attained with the use of several hydrophobic beads: polypropylene, polyethylene, and polystyrene. This phenomenon was not shown in utilization of hydrophilic materials, such as silica gel, silica stone, and rice bran acetone powder. It is hypothesized that the higher hydrolysis conversion is caused by mass transfer facilitated by hydrophobic beads, while in hydrophilic materials, water substrate was adsorbed and lowered the hydrolysis conversion. Experimental data show that performance of solids in triglyceride hydrolysis is not only affected by hydrophobicity, but also strongly affected by pH and surface area. Utilization of hydrophobic beads provides a low-cost and low-energy consumption to initiate triglyceride hydrolysis at room temperature, in the presence or the absence of lipolytic enzymes.

Open source has gradually gained prevalence in the architectural industry in recent years. The earliest concept of open source has been observed in vernacular architecture. However, obvious discrepancies can be discerned between vernacular and modern architecture, such as the use of currency in acquiring resources for contemporary, the complex piping, wiring, and electrical machinery of the modern building, and the high specialization of modern society. A literature review and a case study approach were adopted in the present study to collate three models that were sequentially developed and implemented from the beginning of human civilization, specifically, the collaborative construction employed by the common people in traditional settlements, the general contractor and the Co-operative Housing adopted following the Industrial Revolution, and the organization of humanitarian architecture applied in modern society. These models were analyzed to determine resource acquisition methods, collaborative construction methods, and life collaborative methods. The present study also conducted a preliminary analysis to develop a feasible collaborative construction model for modern open source architecture based on existing construction procedures. The proposed model contains the following three features: (1) it is a sharing economy platform for architecture; (2) it incorporates non-professional collaboration to restructure a professioncentered construction process; (3) and it adopts a time dollar concept to create a system of service sharing.

This study is focused on evaluating newly developed chilled-emulsion Minimum Quantity Lubrication (MQL) method on machining hard-to-cut metals. Previous research work revealed that, aerosol at 150C provides the optimal tool life and generates the least surface roughness when machining AISI P20 and D2 tool steels at a given cutting speed. In that context, the influence of varying cutting speeds with MQL aerosol at 15 0C is further studied in this paper. Three cutting speeds were used as per the tool manufacturer’s recommendations. For the aforementioned cutting conditions, tool nose wear were measured and topologies of worn cutting edges were observed and compared. The experimental results revealed that tool wear rate and other forms of damages such as chipping and plastic deformation for different work material have contrasting responses. This indicates that MQL aerosol performance is notably sensitive to work material properties and its benefits as a cutting fluid should be further investigated over wider range of materials.

The purpose of this research is to obtain optimized sailplane wing design, which contributes to better performance in terms of range and endurance. This paper presents aerostructural design optimization using Multidisciplinary Design Optimization approach (MDO). This is carried out using Open Aero Struct (OAS), an open-source low-fidelity aerostructural analysis and optimization tool written in Python and developed in NASA’s Open MDAO framework. The aerostructural model in OAS coupled a Vortex Lattice Method for aerodynamic with a 1-D Finite- Element Analysis for structure, to model the sailplane wing. An aerostructural optimization problem was formulated to minimize the Sink Speed, as the objective function, with varying twelve design variables, and subjected to two constraints. An initial simple wing design is used as baseline for the optimization. The findings of the aerostructural optimization indicated that the optimized wing exhibited improvements in both disciplines, resulting a better cross-country performance for the sailplane in terms of range and endurance. The optimized wing achieved increase of 37% in endurance and 27% in range.

The aim of this study is to investigate the small amplitude transverse vibration characteristics of an annular thin plate (disk) which rotates about its axis with the rotational speed. The disk is clamped at the inner circumference and free at the outer circumference. This study contains two sections, first one is the experimental investigation of the transverse dynamical behavior of the disk at various rotational speeds, the second section includes modelling the disk numerically using Finite Element Method (FEM). For the experimental part of the study, a Hard Disk Drive (HDD) is used. The disk is rotated with various rotational speeds and measurements are made using non-contacting systems for each rotational speed value. For the numerical part, a finite element model is built and the natural frequencies with the related mode shapes are obtained. The natural frequencies are plotted for various rotational speeds. Using the data obtained from the results of the study Campbell diagrams are drawn. In order to validate the results of this study, the numerical and experimental results are compared to each other and also to the literature.

Traffic flow is one of the most important information elements in intelligent traffic transportation engineering. This study developed a vehicle type classification system using a neural network technique. The architecture of this study is divided into two parts, vehicle pictures are collected first, and then divided into motorcycles, sedans, recreation vehicles, buses and trucks to build a contrast database. The image processing techniques included median filtering and edge detection used to de-noise to improve recognition efficiency. The second stage is processing the previous data stage into the system identification database. All data created by the database were then input into the classifier for calculation. The classification recognition rate was finally obtained. This study uses the Generalized Regression Shallow Learning Neural Network (GRNN), Deep Neural Network (DNN) and Convolutional Neural Network (CNN) classification algorithms. The results show that vehicle classification using the convolutional neural network is better than that obtained with the deep neural network using the restricted Boltzmann machine. Both types of neural networks produced much higher classification than the generalized neural network. The deep learning technique was shown better than the shallow learning approach in this study.

This study provides scientific evidence on the catchability of low-powered incandescent light and LED light traps in catching crustaceans and fish from highly turbid water in Barito River, South Kalimantan. The experimental conditions encompassed highly turbid water, slow flowing, blocked water, and rarely vegetated habitat with water depths ranging from 2 to 4 m. The traps used were collapsible box-shaped trap, wire-square trap, acrylic-square trap, PVC box-shaped trap, wire fish trap, bamboo fish trap and minnow nets. The light traps were deployed randomly with an interval distance of 2.5 m using 1-night soaking time. Light traps sampling accounted for 343 shrimps (1 family), 53 fishes (6 families) and 2 crabs (1 family). The catches were dominated by Macrobrachium sp (98.54%) and Glossogobius giuris (36.54%). Collapsible trap fishing with incandescent lights was as effective at sampling as wire square trap fishing with LED lights. The minnow nets were excellent in catching shrimp and fish as compared with PVC box-shaped trap and wire/bamboo fish traps. Colour of light had strong effects on the number of shrimp and fish collected. For future applications in using LED light for trap fishing, a more comprehensive study on its efficiency for catching juveniles of target and non-target species is strongly recommended.

Humanoid robots are extensively becoming an essential part of the social life with the development and implementation of Human-Like behaviors such as walking, grasping, standing up, and sitting down. For generating natural Human-Like behaviors, the desired motion should be controlled properly in the dynamic and unstructured environments. This paper presents a Sit-to-Stand (STS) motion algorithm developed to lead autonomous Human-Like motion. The proposed algorithm has two main steps; where in the first one, horizontal distances of the humanoid robot for sitting down or standing up motions are identified to determine the corresponding joint angles, and in the second stage, the initial joint angles of the robot have been driven to the target joint angle states. Although this algorithm can be adopted to all humanoid robots, in this paper, it has been specifically applied to the NAO humanoid robot. Results show that the NAO humanoid robot is able to autonomously achieve halfway standing up and sitting down from chairs having heights between 9.5 and 11.5 cm. The developed STS algorithm will be combined with chair recognition and selection algorithms in the future, which will significantly enhance the capabilities of autonomous humanoid robots.

One of the most common methods for the removal of iron from water is oxidation of the ferrous iron to the ferric form by atmospheric oxygen. Ferric hydroxide yielding from hydrolysis of ferric iron precipitates which is settled and filtered out from the water. The oxidation rate of the ferrous iron is affected by several factors such as the concentrations of Fe2+, Fe3+, and oxygen, pH, temperature, organic matter, and other ions present in the solution. Considerable concentrations of dissolved iron can be preserved in aerobic aquatic systems in the presence of organic species of natural origin. Organic species such as tannic acid, gallic acid, and others can completely retard the oxidation of Fe2+ for several days, even under an oxygen partial pressure of 0.21 atm. In this study, the effect of Fe3+ on Fe2+ oxidation in water containing pyrogallol was simulated and investigated experimentally in two stages. In the first stage, catalytic effect of Fe3+ on Fe2+ oxidation has been investigated, experimentally. In the second stage, it has been studied how pyrogallol affects the oxidation of Fe2+ and the catalytic effect of Fe3+. Without pyrogallol, the oxidation rate of Fe2+ was enhanced by increasing Fe3+ concentration. The catalytic effect of Fe3+ clearly decreased and almost vanished in the presence of pyrogallol. This is considered to be a result of pyrogallol-forming complexes with Fe3+.

In Turkey, municipal solid wastes are primarily disposed in landfills. The infiltrated water in the landfill affects the chemical composition of leachate. The filtration, adsorption, dissolution, precipitation, ion exchange, and biochemical processes occur between the compacted clay soil and leachate. In this study, batch and continuous reactors are used to inveatigate permeability and adsorption of compacted clay soil. The clay soil, obtained from the Kemerburgaz-Odayeri landfill area on the European side of Istanbul, is put through standard and modified proctor compaction tests. The effects of Total Phosphorus (TP) and Total Kjeldahl Nitrogen (TKN) in the influent and effluent have been analyzed to determine the treatment capability for batch and continuous reactors of the compacted clay soil. The results of the permeability measurements using leachate show that the permeability in the compacted clay soil associated with the contamination is slightly increased. Removal efficiencies of TP in clay soil were obtained as 72% for standard compaction and 77% for modified compaction in continuous reactor. Also, TKN in clay soil was obtained as 60% for standard compaction and 81% for modified compaction in continuous reactor. Optimum adsorption time of TKN was 5 hours in batch reactor.

Many cities in Turkey use groundwater in order to meet their need of drinking water. Municipal solid waste landfills in all of the cities are major threat for groundwater. Low permeability clay soils by landfill operators are used as a standard practice. However, it has been shown that certain contaminants change the structure of clay soils, making them highly permeable. A lot of investigators have demonstrated that concentrated organic chemicals can alter compacted clays and cause increase in permeability. In this study, the effects of leachates on permeability and the treatment capabilities of the natural, compacted-consolidated, and compacted clay soil have been investigated. Clay soil samples were obtained from the Sile-Komurcuoda landfill area on the Asian side of Istanbul. In the experimental studies, Standard Proctor compaction tests and consolidation tests were applied to the clay soil obtained from the same area. The clay soil samples have permeability k of between 1.10^-7 and 1.10sup>-9/sup> m/s. In order to determine the removal rate of the natural, compacted-consolidated, and compacted clay soil, Pb, Cr, Mn, and Fe are measured in the influent and effluent of the lab-scale reactor. The effects of leachates on the permeability of the natural, compacted-consolidated, and compacted clay soil samples have been analyzed. Initially, some decrease has been observed in the clay soil permeability associated with the contamination. The suspended solid matters in the leachates have filled the spaces between the particles of the clay soil pores and this caused a decrease in the permeability. After some time, it is shown that leachates may cause increase in the permeability. The treatment capabilities of the natural, compacted-consolidated, and compacted clay soil samples were quite high. The highest removal rates and the lowest permeability are obtained in natural clay, compacted-consolidated clay, and compacted clay, respectively.

The performance of three different numerical methods for predicting the large separated flow over a hump model and its control using steady suction and techniques is investigated. Unsteady Reynolds Averaged Navier-Stokes (URANS), Detached Eddy Simulation (DES) and Delayed Detached Eddy Simulation (DDES) approaches are developed and applied to determine the proficiency of these approaches in predicting such degree of separation and assess their applicability to capture the turbulent flow structures in the separated flowfield. Active flow control techniques are applied by means of two-dimensional slot located at x/c ≈ 0.65 along the model spanwise with an opening of 0.00187c, directly upstream on the concave surface. The novelty of the present work is that the dynamic grid technique is formulated to model the repeated motion of the synthetic jet membrane instead of using the oscillating boundary conditions at the jet exit. Dynamic grid is found to be useful in providing more insight into the physical mechanism that drive the interface between the plenum flow and separated boundary layer flow. The numerical results obtained from the baseline and controlled cases are validated against the measurements and compared with published numerical results in terms of mean flow quantities. Despite the fact that URANS and DES methods provide good agreement with the measurements for the uncontrolled and steady suction controlled cases, only DES showed the flow unsteadiness, however the DDES method failed to predict the mean flow quantities or the turbulent flow features. The dynamic grid technique successfully simulated the cavity flow, showed up the existence of two counter rotating vortices inside the plenum move up and down during the control cycle and finally energized the boundary layer in the separated flow region.

Public acceptance in low energy hydronic radiant cooling system is almost none in country like Malaysia. This is due to the low awareness of the performance and benefit of such system in the country as well as higher initial construction cost. With the aim of long term energy and cost saving this study looks into the performance of custom built radiant cooling surface panel that was retrofitted in a test room located in Kuching Sarawak. In climate condition like Malaysia where only cooling is required, the radiant panel needs only to be a cooling surface unlike its overseas counterpart that heats or cools interchangeably according to the changing seasons. This allows the use of alternative low cost material such as PVC to replace the more common radiant tubing like copper or cross-linked Polyethylene (PEX) tube. A test room was retrofitted with PVC tubing radiant ceiling panel and connected to a chill water tank. The water was passively cooled during the night using the pitch roof as a heat exchanger to chill the water to as low as 24⁰C. The water was then used to charge the hydronic ceiling radiant panel during the day time when the outdoor temperature exceeds 30⁰C. The experiment shows that the system was able to maintain an indoor temperature to about 30⁰C when the outdoor temperature peaked to 34⁰C while providing acceptable thermal comfort. The experiment showed that the use of the hydronic radiant panel with free night cooled water as its coolant have significant energy saving potential while at the same time provide an acceptable room thermal comfort. The locally built radiant panel and easy to install night cooling rig could be an attractive choice as a Malaysian building cooling system that complies to a bioclimatic building principle.

Data analysis in real-world application domains is a very challenging issue. For example, Thousand Gigabytes of multimedia data get poured into Social media each and every minute. Since social media and most of the organizations are dealing with Big Data, tools like Hadoop and Spark system are more appropriate for dealing with those data. Hadoop and Map Reduce analyze the data only in batch mode. This makes it difficult for the real-time analysis because it increases latency. In order to solve the above problem, we used Spark streaming to do real-time data analysis. Spark streaming helps to iterate through the data much faster due to its in-memory processing. This paper presents an online machine learning system for real-time data. Using Spark streaming, data from online messaging system is streamed into the local system. Streaming K-means algorithm is applied to cluster the different languages of the people from various countries. Results show that predictions of the incoming data are accurate and faster than when Apache spark is used. Our results and methods are compared with other articles which have used spark streaming for real-time data processing. Queries like total word count and segregation based on keywords are done and the results are presented. The data are then stored in the local disk for future querying process.

This research uses an approach in Data Mining techniques to analyze historical data of students. The goal is to predict and investigate factors affecting student leavers using university admission (pre-admission variables) and educational achievement indicators (post-admission variables) on at-risk freshmen students in higher institution. Feature selection as preprocessing methods are utilized for 30 potential predictors to identify the most relevant factors. With the aim to evaluate the significant predictors contributing to at-risk students, this research compares predictive models. The models were implemented using various data mining algorithms and it is found that kNN gives 80.50% accuracy, CART with 89.70%, Adaptive Boosting using Decision Tree with 92.20% and Logistic Regression with 92.09%. The models were trained using records from student dataset collected from the Mindanao State University – Marawi, academic year 2010-2015. In addition, this research also verified the precision of the models through 10-fold cross validation, which can give veracity about what kind of data mining models works best in HEI data mining analysis. It would predict the class label ‘Result’ as categorical value, AtRisk or NotAtRisk. Benefits of the prediction model includes improving student retention and graduation rates.

This paper presents a numerical investigation on the effects of inlet airflow angle on the airflow, temperature and CO2 concentration fields in a three-row airliner cabin. The computations are conducted using Ansys-Fluent and the numerical results were compared against published experimental data. The inlet airflow is supplied into the aircraft cabin at six different directions of A (0°, 180°), B (355°, 185°), C (350°, 190°), D (340°, 200°), E (330°, 210°) and F (315°, 225°). The numerical results showed that flow pattern, temperature distributions and CO2 levels are improved significantly inside the whole cabin and at passengers’ breathing zones in case of changing the inlet airflow angle. The performance of mixing-air distribution system for the whole aircraft cabin is enhanced remarkably in case of using small inlet angles. Angles B (5°) and C (10°) provided the best ventilation performance among the six tested angles within the whole cabin and at local breath zones of passengers in terms of thermal and health comfort. Moreover, inlet airflow angle C (10°) showed high constancy and stability in the pattern of the flow field and temperature and low CO2 level in cabin centre area compared to inlet airflow angle B (5°) for both the whole aircraft cabin and local breathing zones.

The main objective of present study is to understand the vortical structure development and evolution of a low-speed rectangular jet via smoke flow visualization. The side- and front-view near the jet exit are utilized simultaneously to know the development relationship in detail. Results not only confirm the development of vortex ring but also indicate this process has strong relationship with the vortical structure development in a plane jet.

This paper focuses on a machine learning problem that is especially relevant for the automation of graph-based conceptual design. In this field, graph-rewriting systems can be used to facilitate design automation. The present work deals with the automatic induction of production rules for graph-rewriting systems from example design graphs. An approach to this is presented and empirically evaluated in the context of prototypical applications for functional design. The approach suffices the requirement that the learned rules have to fit an existing rule set, but the inspection of existing rule definitions is prohibited. The results suggest that the proposed approach is able to achieve reasonable, but sometimes unexpected learning results.

This study was carried out to investigate the effect of steam curing condition on the early and later age strength of mortar, which was added various dosages of Calcium Nitrite-Based accelerator. The study was performed on the specimens, which were subjected to the three different pre-curing time and exposed to the two different keeping curing times at the 45 °C steam curing temperature. High early strength cement was used in this research experiment. From the obtained result, it was observed that the early (8-hour) strength of specimens exposed to the long keeping curing time (4.5, hour) is higher than the strength of specimens subjected to the short keeping curing time, (3 hours). Adversely, it is obtained that by increasing the ages of specimens, the strength gain goes up for the specimens exposed to short keeping curing time (3 hours), compared to the strength of the specimens exposed to longer keeping curing time (4.5 hours). Moreover, the obtained result indicates that the higher early and later ages strength of specimens was observed from the specimens which accompanied the pre-curing cycle of 90 minutes, compared to the strength of specimens, exposed to pre-curing cycle of 30 and 150 minutes. For all the cases, the result showed that by increasing the dosage of the accelerator admixture, the strength increased at the early and later ages.

The seat structure of the Sports Utility Vehicle (SUV) has gained more attention in developing lightweight design using available materials different in grades and their strengths. The SUV industry has drastically shown an incessant growth in the present. By this scenario, safety issues are of interest mainly for the users. This work, therefore, simulates and analyzes an SUV’s seat for stress distribution and deformation of its structure using finite element method. The seat is situated in the SUV where it is crashed in the front by oblique angle from 0 degree to 15 degrees adjacent to the straight direction in both right and left sides. This type of collision is considered to be an accident of vehicle resulting in serious injuries. The analysis employs an explicit dynamic simulation during the real frontal impact and includes a direct contact of Asia-EvaRID (ER) model with the backrest. Under the test by simulation conforming to the industrial standards, ECE standards in particular, the seat structure parts of the backrest relative to the sled were measured in displacement of deformation with a minimum interval time of accident, for the velocity ranging from 60 km/h to 100 km/h. The results have explored that the seat structure withstanding the stress distribution and deformation under static load evaluation testing was affected by vehicle velocity and crash direction in an accident. The analysis of the left and right side impact when fastened seat belt generated the maximum stress in the direction of 12.85 degrees head and 6.04 degrees chest from the lateral axis and 4.28 degrees head and 2.01 degrees chest from the lateral axis, respectively. The unfastened seat belt case has shown the maximum distribution at 9 degrees head and degree chest directions over the peak time.

Recent trends of Short-Term Load Forecasting (STLF) is a key issue to regulate power in the electricity market. Many researchers have performed research in this area but it still needs an accurate and robust load forecast method. In this paper, we propose a novel Artificial Immune Network (AIN)-based approach to predict forecast load depending on last three days’ mean actual load. The approach creates an immune memory using time series to forecast one-day ahead hourly loads. The method takes hourly loads separately as an individual daily time series and considers it as an antigen, an affinity is calculated between an antigen and antibody in Immune Networks (INs). A cross-reactivity threshold is used to find the appropriate cluster for an antigen in an immune network. The historical dataset of Poland is trained and tested by this method which predicts more accurately compared to the most recently existing STLF methods, such as simple Nearest Neighbor (NN), Multilayer Perceptron (MLP), Fuzzy Estimators (FE), and Artificial Immune System (AIS).

The main aims of this paper are to analyse the short circuit transient behaviour of a grid connected hybrid power system (wind farm) and to offer suggestions for short circuits damages to be less affected. The hybrid power system in which conventional power system is integrated with wind farm is studied. In this research ATP/EMTP software is used for modelling of hybrid system integrated with wind generator and to simulate transient analysis of the 3-Φ Short Circuit Fault (SCF), line to ground fault and effect of fault resistance on conventional system and at Wind farm. The resulting transient over-voltages and currents has been computed & plotted. The effect of Wind farm on conventional power system during faults has also been studied.

Typhoon disasters risk assessment is needed for small-scale residential houses with less than two stories or less than 500 square meters, since they accounted for about 55% of total buildings in Korea. Therefore, this study was focused on the evaluation of wind fragility for this small-scale lightweight steel frame structure when subjected to lateral wind loads. For this purpose, Monte Carlo Simulation technique was used to derive wind fragility based on random wind load parameters and experimental data of resistance capacity of the connection in this type of structure. Finally, the structural safety of a small-scale lightweight steel house was evaluated, and the fragility was derived. Results show that wind direction parallel to long dimension of structure was the most critical condition. Additionally, the median probability of failure occurs at a very high wind speed. Further research should focus on study with detail structural analysis to narrow down the uncertainty in this study.

Electrochemotherapy is a combined use of a chemotherapeutic drug and short intense electric field for cancer treatment. The applied electric field increases the permeability of the cell membrane thereby increasing the free entrance of the drug into the cancer cell for effective treatment at minimal drug dose. However, patients undergoing electrochemotherapy in clinical trial complain of unpleasant sensation due to muscle contraction during the pulse delivery (usually 1000V/cm, 100μs, and 8 numbers of pulses). This unpleasant sensation is caused because of the high amplitude of pulse or due to the low repetition frequency of the pulse (1Hz). Hence, in this paper, a low voltage amplitude (600V/cm) electric pulse at relatively higher pulse durations ranging from 500μs to 20ms was used in electroporating cells in vitro. The percentage of cell permeabilization and viability of the different pulse durations were measured. The result revealed that 500μs duration stimulates the cell proliferation and 20ms result in 90% of cell death. On the other hand 5ms pulse duration resulted in 65% permeabilization and 80% viability. Hence the study suggested that 600V/cm at 5ms duration can be used for electrochemotherapy to potentially eliminate the unpleasant sensation associated with high amplitude pulse.

In the paper carried out was modeling of cutting parameters in face milling process of Semi Solid Metal alloys. As input parameters in the process of modeling were taken: cutting speed v, the feed per tooth and depth of cut, while for the output characteristics of the process were taken arithmetic mean surface roughness Ra and maximum roughness height Rmax. Modeling was done in two ways. The first model was made with the help of mathematical and statistical method- factorial experiment DoE, where it was used model with parameters’ interaction. The second model was made by artificial intelligence and as a tool was chosen fuzzy logic.

Security has become a primary concern not only for researchers, but also for many users. Wireless Sensor Networks (WSNs) are susceptible to various kinds of attacks, so the need to protect such networks has been increased. There are a number of challenges in WSN security design. Resource constraints such as the ability of processing, low battery life, small memory size and unsecured transmissions make various attacks more dangerous for these networks. Our attention of this paper concentrates on the most typical routing attacks and their capabilities which influence network layer. The attackers can potentially compromise one or more of security goals of the network they attack. This paper is expressing a comparison between routing attacks to find the purpose of the attackers on WSNs' functionality. It classifies and compares them extensively based on different features such as goals, the threat nature, attack function, WSNs' threat site and according to disruption of the route or consumption of the resources. This paper also gives a better understanding of future direction for researchers for designing secure WSNs.

This search aims to explore the issues in developing the User Interface in mobile devices applications which is known as Human-Computer Interaction (HCI). The challenges that face the designers in developing the mobile UI are how to create usable and efficient UI and what are the guidelines or principles they should take into account to make interactive and interaction design. In addition, the software and hardware limitations they are encountered with, and also how they involve the users and their experience in designing process according to User-Centered Design (UCD) principles are considered. I gave the concepts for user interface, HCI, UCD, and usability issue and its relationship to designing process. Also I mentioned the general guidelines which are known as "Shneiderman's Eight Golden Rules of Interface Design" that should be considered. Moreover I explored that each platform nowadays has its own guidelines for best development of interaction process and that is why the applications of specific stage have the same layout. And I conclude that there is need for new methodologies and strategies of designing user interface that differs from methods used for developing traditional user interfaces due to enormous evolution of mobile devices and people's preference of such technology.

Orthogonal Frequency Division Multiplexing (OFDM) system is a multicarrier system used to transfer data at high rate. One of the drawbacks of OFDM is the high value of Peak to Average Power Ratio (PAPR). High PAPR values will mitigate the efficacy of the power amplifier. This paper discusses the Wavelet-OFDM with Partial Transmit Sequence. The use of wavelet transformation on the OFDM system provides several advantages compared to Fourier transform. These advantages include high efficiency due to the loss of guard interval (GI). The proposed Wavelet-PTS system reduces the PAPR significantly, which can achieve a reduction of 8 dB PAPR compared with the conventional OFDM system.

A new age assessment technique based on proposed geometric mean transform by using dental X-Ray Imagery analysis has been proposed in this study. Topology segmentation and content-based shape analysis by using image transforms have been proposed to extract the feature vectors of dental imagery. Then, the accumulated feature vectors have been classified to age classes by using Artificial Neural Networks (ANN). The proposed technique has been evaluated in the standard images sourced from faculty of dentistry, USIM, Malaysia. The evaluation results indicate the robustness of the technique to different types of dental images available in the dataset.

A flash code is a coding mechanism used to store and retrieve information in a flash memory, which is simply an array of flash cells. Because of the write asymmetry property of flash cells, a flash code has to be designed carefully in order to efficiently make use of the limited number of program-erase cycles that the flash cells can physically tolerate. From the initial studies on unibit update flash codes, more recent researches have introduced the multibit update mechanism for more efficient flash codes. In this paper, we propose three different new multibit update flash codes. These flash codes were simulated in Java and compared against existing multibit update flash codes using the mean data update count as the main metric for evaluation. The results show that the proposed flash codes are very competitive with the existing multibit update flash codes, with the third proposed new flash code having superior performance for some range of data vector lengths. This indicates that the proposed flash codes make very efficient use of the Flash memory cells and, thus, may be helpful in extending the lifetime of flash devices.

The study was conducted at the natural reserve wetland, named Lung Ngoc Hoang, from August to December, 2015 to build the database on the current status of distribution and diversity of fungi groups. The results provide useful information to assess the biodiversity at Lung Ngoc Hoang and build a list of fungi species. In addition, species distribution, frequency and diversity index were assessed. The study results showed that 63 species have identified, belonging to 42 genera, 27 families, 12 orders, 6 classes, and 2 phyla. In which, Basidiomycota phylum dominated with 98.97%, while Ascomycota phylum accounted for 1.03% in total. Besides, Agaricomycetes class prevailed with 93%, followed by the class Basidiomycetes with 86.67%. In 12 orders, Agaricales was the most dominant, followed by the Polyporales and the Auriculariales. Moreover, Polyporaceae family occupied the highest percentage of 83.33% with the most dominance of genus Pycnoporus. In 63 fungi species, species Pycnoporus sanguineus had the highest diversity with 23 individuals collected, accounting for 7.87% in total. This species was dominant with 43.33% frequency of appearance. Besides, there were 18 species that were found rarely with the proportion of 1.67% in total. These species had the lowest frequency of appearance, having 0.70% compared to other identified species.

This paper presents the effective management of handover process in mobile communication networks, aims to determine effective utilization of signaling channels in mobile communication network to avoid incessant of handover drop calls in the mobile network. Data were obtained from the Operation and Maintenance Centre (OMC). Analytical method known as Markovian chain analysis of continuous time and discrete space was used in the modeling, of handover blocking probability in mobile communication network. In addition, it was validated using MATLAB software. The causes of handover calls failure were analysis in network B. It was observed that handover blocking probability increases as the number of offered traffic load in erlang increases with a given number of transmission channels (V+g). Handover call blocking probability traffic model performance of the system is function of offered traffic in erlang and number of transmission channels (Pb = f(A,(V+g)). The handover blocking probability decreases, as both number of transmission channels (V+g) and traffic load in erlang increase. In order, to obtain satisfactory handover blocking probability the number of channels must be increased in proportion to offered traffic load in erlang.

Currently, the number of outpatients at one of the public hospitals has been rising. The 3-month data showed that the average total time of each outpatient is 92.884 minutes. This research aims to improve this figure by applying lean technique. Current business process is mapped into simulation model. The model is built based on the fitted data that are collected from each process. The result from running simulation model shows that the maximum number of work in process takes place at payment unit by 43.26 people. The blood test unit yields the highest waiting time at 31.57 minutes. Two approaches are proposed for improvement. From the simulation result, the first approach can reduce the average total time by 6.34% and the average number of patients at the payment process to 78.36%. Similarly, the second approach can reduce the average total time by 1.63% and the waiting time at the blood test unit by 21.25%. When two approaches are both applied together, the results show that the average total time, the average number of patients at the payment process reduces by 6.28 and 63.15 percent respectively.

Numerical simulations of laminar flow complex for convective heat transfer through a 2D channel wall forward facing steps using different type of nanofluids having a baffle. The Finite Volume Method (FVM) solved by equations, momentum, continuity and energy equations and the SIMPLIC calculation plan is connected to look at the impacts of the baffle wall in flow, characteristics, and convective thermal enhancement. Four distinct sorts of nanofluids [Al2O3, SiO2, CuO, and ZnO], with various volumes of particles in the scope of 0.01 to 0.04 scattered in the base liquid (water) are utilized. The effects of height Hb and width Wb of baffles, on Nusselt number variety are numerically simulated. The results demonstrate that SiO2 has the most astounding Nu contrasted and different nanofluids. The distribution district and Nu increment as the volume of nanoparticle increments and it diminishes as the particle’s diameter increments.

The aim of this study is to harness the great potential of image processing techniques which have evolved significantly in the last years, to build an automatic system to detect and diagnose breast cancer in the digital mammographic images in order to help those interested people in this domain, such as radiologists and specialists in oncology and to improve their performance by reducing error rates of breast cancer diagnosis. As long as segmentation and extracting the effective features of mammograms play a major role to isolate and classify suspicious regions which can be subject to cancer, in this work, we focus on abnormality detection using multi-thresholding OTSU's method to segment the Region Of Interest (ROI). Then the texture features of the segmented ROI are extracted which are used to classify the ROI as normal or abnormal tissue by using an Artificial Neural Network (ANN). This system can correctly classify the tested region by a rate of 93.80%.

This research proposed and developed a multimedia courseware in Information Technology (IT) Fundamentals based on the dynamic learning environment which provides self-paced learning material for IT Fundamentals students. Further, this study asked the participation of faculty members to contribute lecture materials and recommend presentation for each lecture material that were suggested while past students were tapped to contribute localized questions and problems that were included in the quiz database. In addition, this research addresses the challenges in creating a learning module that caters the needs of different types of learners in a student-centered environment employing educational materials that were displayed in various formats which enable students to interact with the materials being presented as needed in their own time. The proponents utilized the descriptive and developmental research design. Descriptive was used to define the needed requirements as an input in the development of the proposed multimedia courseware. These requirements were processed through different phases using developmental research namely: (1) planning phase, (2) development phase, (3) validation phase, (4) acceptance phase, and (5) output phase. The result of the validity and acceptability showed that faculty members and students agree on the content and features of the proposed multimedia courseware. The validity and acceptability test indicate positive acceptance from both faculty members and students, however, there are still rooms for improvement before gaining maximum acceptance from the students.

This study was to evaluate saltwater interface and upconing caused by the intrusion of saltwater into coastal aquifers. There are many coastal areas in the around the world where the issue of seawater intrusionis troublesome.This was an experimental study using a hydraulic model to observe characteristics of the interface between freshwater and saltwater caused by the difference in density, as well as to research the formation of upconing, a seawater wedge occurred when drain in a well. Results of the experiment showed that the boundary between saltwater and freshwater in a coastal aquifer isproportional to the hydraulic gradient in dynamic state and inversely proportional to the density of fluid, so it is formed at a position lower than the sea level. It was confirmed that the upconing caused by excessive pumping was related to the depth to the saltwater-freshwater boundaryin the bottom of a pumping well. It was also confirmed that the time duration required for the saltwater-freshwater boundary to restore its original state was more than twice the duration of upconing. By using the hydraulic model, it was possible to observe the formation of saltwater-freshwater boundary and upconing phenomenon in coastal aquifers distributed around islands or coastal areas. The purpose of this study was to obtain basic information such as the position of wells and pumping capacity to obtain groundwater more securely, which is not contaminated owing to seawater intrusion which may occur when pumping in coastal aquifer.

The problem of exceeding the posted speed limit on roads typically leads to a high percentage of accidents and fatalities each year in most developed countries. Unless the vehicle's speed can be limited or controlled, drivers are able to drive at dangerously high speeds, risk lives, and attract costly speeding fines after being photographed by a ‘speed camera’. This may happen due to lack of awareness of the current speed limit in a particular area, or drivers not being careful enough to check their current vehicle speed. This paper describes a prototype system that can help reduce the over-speeding problem by fitting a transmitter on road signs and a receiver on vehicles. A maximum speed limit data signal is broadcasted continuously from a road sign, and a vehicle fitted with a wireless receiver module can detect the speed limit signal. The system can compare the vehicle's current speed with the speed limit and trigger an audible alarm (and alert message) to indicate that the speed limit has been exceeded. A working prototype has been designed, built and tested successfully using an 8-bit embedded microcontroller. Using appropriate transceiver modules, it is possible to implement Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communications in order to implement a wide range of different and useful functions, including collision detection, vehicle identification and even the processing of fines for traffic rule violations. This paper describes the design details of an over-speeding warning system and addresses several other practical applications of wireless technologies for improving road safety. It is hoped that this research will encourage further research into V2V and V2I applications by demonstrating how low-cost wireless communications modules and low-cost microcontrollers can be used to perform several different useful functions. If products like the devices described in this paper are marketed and sold, they could save lives and promote safer driving by simply annoying or constantly warning drivers who exceed the current speed limit, using a loud audible alarm which cannot be disabled by the driver, and warning of nearby dangers.

Sentence classification of shortened text such as single sentences of movie review is a hard subject because of the limited finite information that they normally contain. We present a Convolutional Neural Network (CNN) architecture and better hyper-parameter values for learning sentence classification with no preprocessing on small sized data. The CNN used in this work have multiple stages. First the input layer consist of sentence concatenated word embedding. Then followed by convolutional layer with different filter sizes for learning sentence level features, followed by max-pooling layer which concatenate features to form final feature vector. Lastly a softmax classifier is used. In our work we allow network to handle arbitrarily batch size with different dropout ratios, which is gave us an excellent way to regularize our CNN and block neurons from co-adapting and impose them to learn useful features. By using CNN with multi filter sizes we can detect specific features such as existence of negations like “not amazing”. Our approach achieves state-of-the-art result for sentence sentiment prediction in both binary positive/negative classification.

This paper proposed the analysis of interference between Drone (Unmanned Aircraft System) and Fixed Service (FS) by considering the factor of rain attenuation. The analysis of interference is the use of same frequency by two different systems between UAS and FS. The frequency sharing or the compatibility between the two systems (UAS and FS) is modelled by the interference between those two systems. The main problem of the Unmanned Aircraft (UA) or Unmanned Aerial Vehicle (UAV) deployment is the compatibility with the other UAV and incumbent system. One of the allocation FSS spectrums in the region 3 (Asia and Oceania Region) is in the band 12.5 - 12.75 GHz. This frequency band is shared with the frequency of FS (Fixed Service). This paper analyzes the interference by calculating and simulating the scenario of interference with rain attenuation. The scenario of interference is observed when some of UAVs or UA flights are above the area of FS. The simulation is conducted to investigate the interference from the UAV emission into the FS receiver. The results of simulation should present that the interference from the UAV is not harmful to the FS.

Contouring of breast region is an important step in computer aided analysis of Magnetic Resonance Imaging (MRI). The volume of breast region is helpful to physician in surgical operation. During the operation, physicians have to estimate the volume of the breast they removed by experience, then put the same weight of normal saline bag or silica gel in human body. Automatic contouring for breast region may assist physicians in making correct decision at surgical operation. However, automatic segmentation is difficult due to several resembling tissues around the breast region in MRI images. As breast MRI becomes more widespread, a functional automatic contouring method is essential and its clinical application is becoming urgent. For this purpose, this study presents a precise method to segment the breast region on each image slice. Then the obtained contour is used to estimate the volume of the breast. The pre-processing of proposed method reduces plenty of noises but still preserves the shape of breast. By using horizontal and vertical projection to extract the region of interest (ROI), the proposed method could obtain a precise contour of breast region.

This paper presents the development of hybrid composites' mechanical properties. In the experiments carried out, Polypropylene (PP), Rice Husk (RH), and short E-Glass (EG) fibers are prepared through the process of melt-mixing technique at 1750 C for 8 minutes and 50rpm rotor speed using an internal mixer (Haake Rheomixer Machine). The hybrid composites made are prepared in various ratios of fiber weight fractions varying up to 60% where the treatment of rice husk using 2% concentration of Sodium Hydroxide (NaOH) to improve the interaction and adhesion between the nonpolar matrix and the polar lignocellulosic fibers. The specimens are analyzed by different techniques, such as tensile test, impact test, hardness test, and Scanning Electron Microscopy (SEM). The presence of NaOH in rice husk for 15% indicates higher tensile strength and impact strength, while the tensile modulus and hardness strength are, however, reduced. The morphology results support the tensile properties that indicated the interaction between the PP and fibers with NaOH. These results recommend that rice husk and E-Glass fibers are a viable alternative to hybrid-based reinforcing fibers as long as the right processing conditions are applied and used in the applications.

Previous studies have indicated the possibility of a relationship between adverse weather conditions and flight delays. Various methods had been employed to determine the effect of adverse weather conditions on flight delays, such as the directed acyclic graph and Autoregressive Integrated Moving Average (ARIMA) model [4], [5]. In this case study for Singapore, linear and square root regression methods were used as a preliminary step to determine and understand this relationship which had not been done before. The SAAM software from EUROCONTROL was also used to illustrate the effect of weather on flights. By comparing the R squared values obtained, it was determined that the square root model was better for representing the relationship between adverse weather conditions and flight delays. The models and results from this case study could be applied to modeling and optimization studies of airports and airspace on a macroscopic level in Singapore or the other nations in Southeast Asia with similar climate and other areas such as forecasting and sectorization. Future research could also be done using more advanced methodologies or models.

Over the past few years, the modeling approach is widely used to discover the complex and dynamic relationship between various profitable variables. This paper focuses on the modeling of gold and silver rates concerning a certain period and predicting the gold and silver rates. In this paper, with the assistance of the Particle Swarm Optimization (PSO) algorithm, the BOX JENKINS and the Auto-Regressive Integrated Moving Average(ARIMA) models are developed for the considered economic variables. A comparative study is also presented to assure the model's accuracy. Following that, the PSO-based KALMAN FILTER DESIGN approach is implemented on the gold and silver rates to forecast market prices. In today's unpredictable world, investors believe that gold can act as a hedge against unexpected disasters, both natural and economic. Therefore forecasting the price of gold has been of the highest interest. The major advantage of the proposed PSO-based modeling and prediction approach is that it is a fully automated method which results in higher flexibility and greater accuracy. This study also confirms that the PSO-based ARIMA model yields a better result than the PSO-based BOX JENKINS model. The proposed PSO-based KALMAN FILTER approach also provides better predictions.

A study was conducted to determine the effects of different plant growth hormones towards in vitro regeneration of a new Malaysian Rice Variety (Oryza Oryza sativa L. Var. MRIA 1. L. Var. MRIA 1). Stem explants of 4-week-old aseptic seedlings were selected, and a total of 16 different combinations of NAA, IBA, BAP, and Kn were utilized. The most suitable plant growth hormones for in vitro regeneration of Oryza Oryza sativa L. var. MRIA 1. L. Var. MRIA 1 was obtained from MS (Murashige and Skoog) media supplemented with 1.0 mg/l NAA and 0.5 mg/l Kn with an average of 8.90 ± 1.79 number of shoots, 114.00 ± 18.90 number of roots, 10.70 ± 2.62 cm length of shoots, and 8.70 ± 1.64 number of leaves per explant. It was proved that the in vitro regeneration of Oryza Oryza sativa L. var. MRIA 1. L. Var. MRIA 1 from stem explants was achieved without entering the intermediate callus phase within four weeks of culture. Thus, laborious subculturing processes were not required to regenerate the multiple shoots. These findings provided an optimum plant growth hormone concentration for the tissue culture system of Oryza Oryza sativa L. var. MRIA 1. L. Var. MRIA 1. Acclimatization of regenerated plantlets of Oryza Oryza sativa L. var. MRIA 1. L. Var. MRIA 1 is recommended to serve as a complete in vitro regeneration protocol for the variety.

This paper presents the flexible pavement of selected highways in Odo Otin Local Government Area, Osun State, Southwestern Nigeria. To achieve this, the study involved site observation, Pavement Condition Rating (labeled TP1-TP7), identification of types of failures or distress on the pavement, drainage assessment, and geotechnical studies of the selected Highways. Soil samples were collected from both the unfailed and failed section of the selected roads. The samples were subjected to the following laboratory tests; natural moisture content, sieve analysis, atterberg limit, specific gravity, compaction test using West African standard, unconfined compressive strength, and California bearing ratio. The study revealed that PCR rating scales for TP4, TP6, and TP7 were in good condition because there was less distress on the road. TP3 and TP were in satisfactory condition. TP1 and TP2 were observed to be in poor condition. Only road TP6 and TP7 have effective drainage, but it can be predicted for them to have a blockage or erode other roads in the nearest future due to no discharge outlet. They have no drainage for other roads, leading to major causes of some distress all around those roads. The unconfined compressed strength ranges between 41kN/m2 and 181kN/m2, and the CBR value between 26.8% and 59.6%. The result, therefore, shows that most of the failures are caused by the following: design inadequacies, inadequate drainage facilities, infiltration of surface runoff into the underlying course, growth of shrubs, and base failure.

This paper investigated the flow and heat transfer characteristics of supercritical carbon dioxide (SC-CO2) and supercritical water (SC-H2O) in horizontal microchannels using a CFD approach. A straight, circular pipe of stainless steel with internal and external radii of, and, respectively, and a heated length of 55 mm were considered. For the simulation, carbon dioxide and water at supercritical pressures of 9.5 MPa and 22.07 MPa were used, while uniform heat was applied on the outer surface of the tube. The thermodynamic properties for both fluids were obtained from the NIST Chemistry Webbook. The simulated temperature and heat transfer coefficient variation was compared with experimental results from the literature. In general, the simulation results were close to the experiment. Both the simulation and experimental results showed that the wall temperature increased along the tube length. As expected, the heat transfer coefficient values for both supercritical fluids decreased as the length of the tube. This was because a maximum and dominant convection heat transfer occurred at the entrance of the heated section of the pipe. This study could assist in decisions regarding the use of supercritical fluids in industries that involve heat transfer.

As we know, remembering where a car is parked in a large parking port is very difficult. Even with an indoor positioning system, if we don’t mark the car’s position previously, it can be hard to get back to the car. This paper presents a solution based on magnetic information matching and Pedestrian Dead Reckoning (PDR) to improve the situation. By recording the user’s moving trace with pedestrian dead reckoning and using magnetic information matching to find the right turning direction at the turning point, this paper brings up a new way to find the user’s car in a car park without using pre-deployed infrastructure or radio signals. The experiments show that the new solution can navigate the user back to the car successfully.

The subject of research is the new construction of a wind-driven generator with a flux concentrator. Tasks to research air flow motion in swirling wind turbines, to develop the methodology of wind turbine calculation and determination of its capacity with initial and boundary conditions are stated in the article. In the work literature, patent review and analysis of mathematical methods of existing hydro turbine constructions were made. As a result of the research calculation methods of wind turbine and determination of its capacity with initial and boundary conditions were developed. Also, an experimental stand was made. Main constructive and technical, and operational characteristics: concentrator’s convergent channels are curvilinear in view and are described by logarithmic dependence. The construction's novelty consists of a flow concentrator with curvilinear convergent channels tangentially connected with a ventilation pipe.

Text document clustering is a technique that groups documents into several clusters based on similarities. Most clustering algorithms build disjoint clusters, but clusters should be overlapped because documents may belong to two or more categories in the real world. For example, an article discussing the Apple Watch may be categorized into either 3C, Fashion, or Clothing and Shoes. This paper proposes an overlapping clustering algorithm by using the Formal Concept Analysis, which could make a document assigned to two or more clusters. Moreover, our algorithm reduced the vector space dimensions and performed more efficiently than existing clustering methods.

The decolorization and Chemical Oxygen Demand (COD) removal of Biogas Production Wastewater (BPW) were investigated by using electrocoagulation (EC) in a batch experiment. Iron and aluminum electrodes were compared. Variations of current density (20, 35, 50 A/m²), initial pH (4.5, natural, 8.5), and electrolysis time (30, 50, 100 minutes) were conducted for decolorization and COD removal efficiency of BPW. The result showed that decolorization efficiency and COD removal are 31% and 28% for aluminum electrodes at natural pH with 100 minutes of electrolysis time and a current density of 35 A/m². However, using iron electrodes could not remove color, and only 15.70% of COD could be removed at natural pH, 100 minutes of electrolysis time, and a current density of 50 A/m².

Recently, many countries are interested in the development of high-speed trains. However, compared to high-speed train technology developing, the high-speed train infra system is not verified. Furthermore, in the case of bridge-earthwork transition zone that is the most complicated in railroad facility track, bridge-earthwork is connected complicatedly. Disorder and destruction of track can be occurred by rigidity transition. To apply a high-speed train with 430km/h, it is needed to evaluate the stability of behavior condition of bridge-earthwork transition zone by instrumentation system and the construction methods that are accurately and consistently verifiable. In this study, vertical displacement of bridge-earthwork that connects pre-stressed concrete box bridge and earthwork zone is calculated theoretically and evaluates stability compared with measurement of wheel load, strain, displacement data with estimation data, and measurement criteria. Therefore, compared to wheel load, strain, displacement data with estimation data and measurement criteria, the stability showed favorable results.

Forming limit diagrams (FLDs) are constructed to describe the strain rates at which a highly localized zone of thinning or necking becomes visible on the surface of sheet metal. Austenitic Stainless Steel (ASS) 304 sheets are increasingly used for making different parts because of their high corrosion-resistivity, good appearance, and superior formability. However, the austenitic phase gets transformed into martensite during forming, revealing its highly unstable nature. This preliminary study investigates the formability and behavior of ASS 304 by plotting forming limit diagram, strain distribution, limiting dome height, and forming ratio. It is shown that enhancement of formability is largest on the biaxial side of the FLD because the fraction martensite transformed depends on the thickness strain. Future work on the formability of ASS 304 is also discussed.

ISO 50001 is a systematic approach that puts forth some principles and requirements to establish a standard energy management system to increase energy performance by efficient use of energy. However, it is a guide to form objectives and tasks, which doesn’t include specific measurements for evaluating energy performance. Hence, additional energy maturity models are required to evaluate the progress of the businesses in energy performance. In this study, the adaptation process of the ISO 50001 will be explained, and how a business can achieve better organizational performance by applying the energy management models that will be integrated into the ISO 50001 will be examined. With the assumption that ISO 50001 and additional energy management models cover each other and cannot be considered separately, the purpose of this study is to find out whether the businesses can obtain optimum performance while saving energy. In the scope of this purpose, applying an integrated energy management system based on ISO 50001 is assumed as more effective than implementing ISO 50001 by merely following its guidance since the organization can measure its performance level more accurately. At the end of the research, the effect of the energy management system will be clarified on organization performance.

Cryogenic vacuum jacket valves are used to supply smooth cryogenic gas and minimize generation of BOG (Boil-off Gas) by intercepting intrusion of heat being generated inside valves in liquefied flow supply of cryogenic equipment through the use of a vacuum system. This research focused on the interception of heat exchange with the outside environment. It also considered heat transfer properties on changes in pressure of a vacuum part, a radius of a jacket, and jacket length, which can reduce heat exchange for effective heat transmission control. Therefore, by using the design of the experiment, one of the optimization strategies for the design of cryogenic vacuum jacket valve, we selected the combination of main design factors. For qualifying the design technology, we compared and analyzed the results using numerical analysis.

Various studies are being conducted recently on land piping for supplying and carrying cryogenic (‐163 °C) LNG to ships. In transportation through land piping, however, the problem of BOG (Boil Off Gas) happens frequently due to difficulty in insulating the outside of the pipe. One of the methods for minimizing the occurrence of BOG is using double pipe in piping. However, research has not been made enough to minimize heat loss by inserting an insulator with high insulation performance inside the double pipe and vacuum. Thus, in planning vacuum insulated piping, this study selected the optimal combination of design factors for vacuum insulated piping using experimental design among optimal design techniques. In addition, numerical analysis was conducted to test the combination of design factors, and the results are expected to provide basic information for vacuum insulated piping design.

Cloud computing systems are large-scale distributed systems so that they focus more on large-scale resource sharing, cooperation of several organizations, and their use in new applications. One of the main challenges in this realm is resource allocation. There are many different ways of resource allocation in cloud computing. One of the common methods of resource allocation is economic methods. Among these methods, the auctionbased method has greater prominence compared with the Fixed-Price method. The double combinatorial auction is one of the proper ways of resource allocation in cloud computing. This method includes two phases: winner determination and resource allocation. This paper presents a new method to determine the winner in double combinatorial auctionbased resource allocation using the Imperialist Competitive Algorithm (ICA). The experimental results show that the number of winner users is higher than the genetic algorithm in our new proposed method. On the other hand, in the proposed algorithm, the number of winner providers is higher in the genetic algorithm.

Traditional form for concrete pouring in the slab of the girder bridge is timeconsuming and requires a lot of human resources. In addition, there are safety problems when installing and removing the forms and damage of materials, leading to an increase in cost. SMART from Purlin support system developed to solve these problems is to install support in the upper flange of the girder to support the forms of the slab. However, the complicated support structure of forms resulted in various problems, including increased production and transport costs and decreased use on-site owing to the lifting method. To supplement such problems, the SMART form Purlin hanging system was developed. This study aims to develop a form system for concrete pouring in the slab of the girder bridge. In addition, it is to check whether the formwork cost is reduced when the SMART form purlin hanging system is adopted through a cost analysis by comparing with the traditional form.

The demand for free-form buildings has increased. Yet, it has several issues, including the increased cost and duration and decreased constructability, owing to difficulties in producing and installing members of the building surface. To solve these problems, a technology to produce FCP using a CNC machine was developed. The technology delivers the free-form building information to the CNC machine and creates PCM shapes by delivering information. Such PCM acts as a mold to produce FCP. The efficiency of FCP production installation is critical in applying this technology since the construction site, duration, and project costs are limited. Thus, the purpose of this study is on four cases of production-installation simulation for Free-Form Concrete Panels. The factors that influence FCP production installation are analyzed, and four simulation models are proposed using the equation to estimate the time required for FCP production installation. The factor that has the biggest influence on FCP production-installation can be identified through simulations, which is likely to reduce the construction duration when the technology is adopted on-site. Further simulations considering the construction duration and cost and quality are needed, and such should be verified through technology application on-site.

With immense pleasure, I am delighted to announce the inaugural issue of Journal of Advances in Technology and Engineering Research (JATER). I would like to thank our editorial team, authors, reviewers, and all the volunteers who contributed in the successful launch of this journal. JATER is aimed at providing a platform to scholars to showcase their research work and highlight the advances in technology and engineering field. The inaugural issue covers diverse topics including artificial neural networks, wireless technologies, hybrid systems, and harmonics analysis of plant-wide faults. These topics address significant areas in technology and engineering domain. I would like to take this opportunity to invite scholars to submit their original research to JATER. With the support of authors, editorial team and reviewers, this journal aims at serving the science and technology filed. I thank all of the contributors once again and hope for a bright future for JATER.
A/Professor Akbar A. Khatibi
Editor
Journal of Advances in Technology and Engineering Research (JATER)

In this study, a feed-forward multilayer back propagation with Levenberg- Marquardt training algorithm Artificial Neural Network (ANN) was developed to predict the particle size from the extraction of ginger rhizome using super-critical carbon dioxide in Rapid Expansion Super-critical Solution (RESS). Solid oil particle formation analysis is carried out using Scanning Electron Microscopy (SEM) and Image processing and analysis software, ImageJ. The ANN model accounts for extraction temperature (40, 45, 50, 55, 60, 65, and 70°C) and pressure (3000, 4000, 5000, 6000, and 7000psi) the size of the particle. A two-layer ANN with two input variables (extraction temperature and pressure) and one output (particle size) with 35 experimental data was used for the modeling purpose. Different networks were trained and tested by changing the number of neurons in the hidden layer. Using validation data set, the network having the highest (nearest to the value of one) regression coefficient (R) of 0.99721 and the lowest (nearest to the value of zero) Mean Square Error (MSE) of 0.00031 was selected as an optimum ANN model. The suitable ANN model is found to be one hidden layer with seven hidden neurons.

This study talks about the experiments involving sub-critical carbon dioxide extraction of palm oil from treated palm mesocarp to determine palm oil yield and concentration of beta-carotene. For comparison, the conventional method of Soxhlet Extraction with six different solvents was used. The overall oil yield was measured as the weight of oil per weight of the sample, while antioxidant activity was determined using the 2,2-diphenyl-1-picrylhydrazyl radical scavenging method. The sub-critical extraction was conducted at a constant temperature of 30˚C and four different pressures of 10 MPa, 15 MPa, 20 MPa, and 25 MPa. The sub-critical extraction produced high concentration of beta-carotene than Soxhlet extraction, even though the oil yield was lower. Furthermore, the anti-oxidant analysis showed a similar trend as the concentration of beta carotene. The best condition of sub-critical extraction was obtained at 25 MPa and 30˚C.

The study is based on 3G feasibility in the M-Healthcare system. It also addresses the aging problem, which becomes severe day by day. At first, a survey was conducted by visiting eight upazilla hospitals and six union community clinics in different districts of Bangladesh to observe the real scenario of the m-Health system and used technologies. Both remote monitoring and interactive service mode of the m-Health system were examined there. In addition, by interviewing the patients who already got services through the 2G m-Health system, we found out the practical lacking and limitations of the present infrastructures. After that, we proposed a modified health infrastructure using 3G in remote and Optical Fiber in the backbone side with a wide range of services like video conferencing through VoIP and Skype, M.M.S. diagnostic reports, drug prescriptions, mobile purchase, and home delivery, etc. Analysis shows that 3G needs less transmission time than 4s for medical image upload and transmit. The interactive video visual quality is also better than the existing m-Health service based on 2.7G, monitoring vital signals like E.C.G. signal, heart rate, bone fracture, etc. The feasibility test shows that huge initial costs and poor I.C.T. healthcare professionals make a barrier to a ubiquitous m-Health system. Moreover, the handling of the Hi-tech devices comfortably by villagers also puts a barrier to the smooth running of the system.

Highly complex and integrated modern chemical process plants are susceptible to disturbances propagate throughout the plant from one unit to other interconnected units and create plantwide oscillations. These persisting oscillations are originated due to various faults such as sensor faults, valve faults, process faults, and controller tuning faults. A fundamental frequency and its harmonics can characterize these types of nonlinear faults. This paper demonstrates a novel datadriven off-line time-domain method to identify the root cause of plantwide or unitwide disturbances to troubleshoot plantwide disturbances using harmonics analysis. The successful application of the proposed method has been demonstrated through simulated data.

This paper presents a piecewise affine (PWA) modeling of hybrid control systems in Solar Cell-Battery-Super capacitors. This model aims to design continuous dynamics and discrete dynamics of hybrid systems using PWA, a special model. A hybrid system is a combination of a continuous and discrete system that consists of a continuous interaction between the dynamics represented with differential equations and discrete dynamics represented by automata or network Petri. Current research is about developing a hybrid control in which the hybrid system is viewed as a graph, where edges represent discrete transition and vertices represent continuous activity. In contrast, discrete dynamics occur when there is a transition between the vertices. A hybrid control invariant set for the PWA model of the system is computed. At the PWA, models have been developed through the modeling program MATLAB using the languages HYSDEL (Hybrid Systems Description Language). This guarantees that the proposed model always provides safe evolutions of the system.