Search results for: autonomous learning system
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 23034

Search results for: autonomous learning system

18174 Diagnosis of the Lubrification System of a Gas Turbine Using the Adaptive Neuro-Fuzzy Inference System

Authors: H. Mahdjoub, B. Hamaidi, B. Zerouali, S. Rouabhia

Abstract:

The issue of fault detection and diagnosis (FDD) has gained widespread industrial interest in process condition monitoring applications. Accordingly, the use of neuro-fuzzy technic seems very promising. This paper treats a diagnosis modeling a strategic equipment of an industrial installation. We propose a diagnostic tool based on adaptive neuro-fuzzy inference system (ANFIS). The neuro-fuzzy network provides an abductive diagnosis. Moreover, it takes into account the uncertainties on the maintenance knowledge by giving a fuzzy characterization of each cause. This work was carried out with real data of a lubrication circuit from the gas turbine. The machine of interest is a gas turbine placed in a gas compressor station at South Industrial Centre (SIC Hassi Messaoud Ouargla, Algeria). We have defined the zones of good and bad functioning, and the results are presented to demonstrate the advantages of the proposed method.

Keywords: fault detection and diagnosis, lubrication system, turbine, ANFIS, training, pattern recognition

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18173 Numerical Study of Fatigue Crack Growth at a Web Stiffener of Ship Structural Details

Authors: Wentao He, Jingxi Liu, De Xie

Abstract:

It is necessary to manage the fatigue crack growth (FCG) once those cracks are detected during in-service inspections. In this paper, a simulation program (FCG-System) is developed utilizing the commercial software ABAQUS with its object-oriented programming interface to simulate the fatigue crack path and to compute the corresponding fatigue life. In order to apply FCG-System in large-scale marine structures, the substructure modeling technique is integrated in the system under the consideration of structural details and load shedding during crack growth. Based on the nodal forces and nodal displacements obtained from finite element analysis, a formula for shell elements to compute stress intensity factors is proposed in the view of virtual crack closure technique. The cracks initiating from the intersection of flange and the end of the web-stiffener are investigated for fatigue crack paths and growth lives under water pressure loading and axial force loading, separately. It is found that the FCG-System developed by authors could be an efficient tool to perform fatigue crack growth analysis on marine structures.

Keywords: crack path, fatigue crack, fatigue live, FCG-system, virtual crack closure technique

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18172 Rationalized Haar Transforms Approach to Design of Observer for Control Systems with Unknown Inputs

Authors: Joon-Hoon Park

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The fundamental concept of observability is important in both theoretical and practical points of modern control systems. In modern control theory, a control system has criteria for determining the design solution exists for the system parameters and design objectives. The idea of observability relates to the condition of observing or estimating the state variables from the output variables that is generally measurable. To design closed-loop control system, the practical problems of implementing the feedback of the state variables must be considered and implementing state feedback control problem has been existed in this case. All the state variables are not available, so it is requisite to design and implement an observer that will estimate the state variables form the output parameters. However sometimes unknown inputs are presented in control systems as practical cases. This paper presents a design method and algorithm for observer of control system with unknown input parameters based on Rationalized Haar transform. The proposed method is more advantageous than the other numerical method.

Keywords: orthogonal functions, rationalized Haar transforms, control system observer, algebraic method

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18171 Estimating Poverty Levels from Satellite Imagery: A Comparison of Human Readers and an Artificial Intelligence Model

Authors: Ola Hall, Ibrahim Wahab, Thorsteinn Rognvaldsson, Mattias Ohlsson

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The subfield of poverty and welfare estimation that applies machine learning tools and methods on satellite imagery is a nascent but rapidly growing one. This is in part driven by the sustainable development goal, whose overarching principle is that no region is left behind. Among other things, this requires that welfare levels can be accurately and rapidly estimated at different spatial scales and resolutions. Conventional tools of household surveys and interviews do not suffice in this regard. While they are useful for gaining a longitudinal understanding of the welfare levels of populations, they do not offer adequate spatial coverage for the accuracy that is needed, nor are their implementation sufficiently swift to gain an accurate insight into people and places. It is this void that satellite imagery fills. Previously, this was near-impossible to implement due to the sheer volume of data that needed processing. Recent advances in machine learning, especially the deep learning subtype, such as deep neural networks, have made this a rapidly growing area of scholarship. Despite their unprecedented levels of performance, such models lack transparency and explainability and thus have seen limited downstream applications as humans generally are apprehensive of techniques that are not inherently interpretable and trustworthy. While several studies have demonstrated the superhuman performance of AI models, none has directly compared the performance of such models and human readers in the domain of poverty studies. In the present study, we directly compare the performance of human readers and a DL model using different resolutions of satellite imagery to estimate the welfare levels of demographic and health survey clusters in Tanzania, using the wealth quintile ratings from the same survey as the ground truth data. The cluster-level imagery covers all 608 cluster locations, of which 428 were classified as rural. The imagery for the human readers was sourced from the Google Maps Platform at an ultra-high resolution of 0.6m per pixel at zoom level 18, while that of the machine learning model was sourced from the comparatively lower resolution Sentinel-2 10m per pixel data for the same cluster locations. Rank correlation coefficients of between 0.31 and 0.32 achieved by the human readers were much lower when compared to those attained by the machine learning model – 0.69-0.79. This superhuman performance by the model is even more significant given that it was trained on the relatively lower 10-meter resolution satellite data while the human readers estimated welfare levels from the higher 0.6m spatial resolution data from which key markers of poverty and slums – roofing and road quality – are discernible. It is important to note, however, that the human readers did not receive any training before ratings, and had this been done, their performance might have improved. The stellar performance of the model also comes with the inevitable shortfall relating to limited transparency and explainability. The findings have significant implications for attaining the objective of the current frontier of deep learning models in this domain of scholarship – eXplainable Artificial Intelligence through a collaborative rather than a comparative framework.

Keywords: poverty prediction, satellite imagery, human readers, machine learning, Tanzania

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18170 Solar-Powered Adsorption Cooling System: A Case Study on the Climatic Conditions of Al Minya

Authors: El-Sadek H. Nour El-deen, K. Harby

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Energy saving and environment friendly applications are turning out to be one of the most important topics nowadays. In this work, a simulation analysis using TRNSYS software has been carried out to study the benefit of employing a solar adsorption cooling system under the climatic conditions of Al-Minya city, Egypt. A theoretical model was carried out on a two bed adsorption cooling system employing granular activated carbon-HFC-404A as working pair. Temporal and averaged history of solar collector, adsorbent beds, evaporator and condenser has been shown. System performance in terms of daily average cooling capacity and average coefficient of performance around the year has been investigated. The results showed that maximum yearly average coefficient of performance (COP) and cooling capacity are about 0.26 and 8 kW respectively. The maximum value of the both average cooling capacity and COP cyclic is directly proportional to the maximum solar radiation. The system performance was found to be increased with the average ambient temperature. Finally, the proposed solar powered adsorption cooling systems can be used effectively under Al-Minya climatic conditions.

Keywords: adsorption, cooling, Egypt, environment, solar energy

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18169 Impacts of School-Wide Positive Behavioral Interventions and Supports on Student Academics, Behavior and Mental Health

Authors: Catherine Bradshaw

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Educators often report difficulty managing behavior problems and other mental health concerns that students display at school. These concerns also interfere with the learning process and can create distraction for teachers and other students. As such, schools play an important role in both preventing and intervening with students who experience these types of challenges. A number of models have been proposed to serve as a framework for delivering prevention and early intervention services in schools. One such model is called Positive Behavioral Interventions and Supports (PBIS), which has been scaled-up to over 26,000 schools in the U.S. and many other countries worldwide. PBIS aims to improve a range of student outcomes through early detection of and intervention related to behavioral and mental health symptoms. PBIS blends and applies social learning, behavioral, and organizational theories to prevent disruptive behavior and enhance the school’s organizational health. PBIS focuses on creating and sustaining tier 1 (universal), tier 2 (selective), and tier 3 (individual) systems of support. Most schools using PBIS have focused on the core elements of the tier 1 supports, which includes the following critical features. The formation of a PBIS team within the school to lead implementation. Identification and training of a behavioral support ‘coach’, who serves as a on-site technical assistance provider. Many of the individuals identified to serve as a PBIS coach are also trained as a school psychologist or guidance counselor; coaches typically have prior PBIS experience and are trained to conduct functional behavioral assessments. The PBIS team also identifies a set of three to five positive behavioral expectations that are implemented for all students and by all staff school-wide (e.g., ‘be respectful, responsible, and ready to learn’); these expectations are posted in all settings across the school, including in the classroom, cafeteria, playground etc. All school staff define and teach the school-wide behavioral expectations to all students and review them regularly. Finally, PBIS schools develop or adopt a school-wide system to reward or reinforce students who demonstrate those 3-5 positive behavioral expectations. Staff and administrators create an agreed upon system for responding to behavioral violations that include definitions about what constitutes a classroom-managed vs. an office-managed discipline problem. Finally, a formal system is developed to collect, analyze, and use disciplinary data (e.g., office discipline referrals) to inform decision-making. This presentation provides a brief overview of PBIS and reports findings from a series of four U.S. based longitudinal randomized controlled trials (RCTs) documenting the impacts of PBIS on school climate, discipline problems, bullying, and academic achievement. The four RCTs include 80 elementary, 40 middle, and 58 high schools and results indicate a broad range of impacts on multiple student and school-wide outcomes. The session will highlight lessons learned regarding PBIS implementation and scale-up. We also review the ways in which PBIS can help educators and school leaders engage in data-based decision-making and share data with other decision-makers and stakeholders (e.g., students, parents, community members), with the overarching goal of increasing use of evidence-based programs in schools.

Keywords: positive behavioral interventions and supports, mental health, randomized trials, school-based prevention

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18168 Investigating the Contemporary Architecture Education Challenges in India

Authors: Vriddhi Prasad

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The paper briefly outlines the nature of contemporary Architecture Education in India and its present challenges with theoretically feasible solutions. It explores in detail the arduous position of architecture education owing to, privatization of higher education institutes in India, every changing demand of the technology driven industry and discipline, along with regional and cultural resources that should be explored academically for the enrichment of graduates. With the government's education policy of supporting privatization, a comprehensive role for the regulating body of Architecture Education becomes imperative. The paper provides key insights through empirical research into the nature of these roles and the areas which need attention in light of the problems. With the aid of critically acclaimed education model like Design Build, contextual retrofits for Indian institutes can be stressed for inclusion in the curriculum. The pairing of a private institute and public industry/research body and vice versa can lead to pro-economic and pro-social research environment. These reforms if stressed by an autonomous nationwide regulating body rather than the state will lead to uniformity and flexibility of curriculum which promotes the creation of fresh graduates who are adaptable to the changing needs.

Keywords: architecture education, building information modelling, design build, pedagogy

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18167 Internet of Things for Smart Dedicated Outdoor Air System in Buildings

Authors: Dararat Tongdee, Surapong Chirarattananon, Somchai Maneewan, Chantana Punlek

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Recently, the Internet of Things (IoT) is the important technology that connects devices to the network and people can access real-time communication. This technology is used to report, collect, and analyze the big data for achieving a purpose. For a smart building, there are many IoT technologies that enable management and building operators to improve occupant thermal comfort, indoor air quality, and building energy efficiency. In this research, we propose monitoring and controlling performance of a smart dedicated outdoor air system (SDOAS) based on IoT platform. The SDOAS was specifically designed with the desiccant unit and thermoelectric module. The designed system was intended to monitor, notify, and control indoor environmental factors such as temperature, humidity, and carbon dioxide (CO₂) level. The SDOAS was tested under the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE 62.2) and indoor air quality standard. The system will notify the user by Blynk notification when the status of the building is uncomfortable or tolerable limits are reached according to the conditions that were set. The user can then control the system via a Blynk application on a smartphone. The experimental result indicates that the temperature and humidity of indoor fresh air in the comfort zone are approximately 26 degree Celsius and 58% respectively. Furthermore, the CO₂ level was controlled lower than 1000 ppm by indoor air quality standard condition. Therefore, the proposed system can efficiently work and be easy to use for buildings.

Keywords: internet of things, indoor air quality, smart dedicated outdoor air system, thermal comfort

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18166 Participation of Students and Lecturers in Social Networking for Teaching and Learning in Public Universities in Rivers State, Nigeria

Authors: Nkeiruka Queendarline Nwaizugbu

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The use of social media and mobile devices has become acceptable in virtually all areas of today’s world. Hence, this study is a survey that was carried out to find out if students and lecturers in public universities in Rivers State use social networking for educational purposes. The sample of the study comprised of 240 students and 99 lecturers from the University of Port Harcourt and the Rivers State University of science and Technology. The study had five research questions, two hypotheses and the instrument for data collection was a 4-point Likert-type rating scale questionnaire. The data was analysed using mean, standard deviation and z-test. The findings gotten from the analysed data shows that students participate in social networking using different types of web applications but they hardly use them for educational purposes. Some recommendations were also made.

Keywords: internet access, mobile learning, participation, social media, social networking, technology

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18165 Theoretical and ML-Driven Identification of a Mispriced Credit Risk

Authors: Yuri Katz, Kun Liu, Arunram Atmacharan

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Due to illiquidity, mispricing on Credit Markets is inevitable. This creates huge challenges to banks and investors as they seek to find new ways of risk valuation and portfolio management in a post-credit crisis world. Here, we analyze the difference in behavior of the spread-to-maturity in investment and high-yield categories of US corporate bonds between 2014 and 2023. Deviation from the theoretical dependency of this measure in the universe under study allows to identify multiple cases of mispriced credit risk. Remarkably, we observe mispriced bonds in both categories of credit ratings. This identification is supported by the application of the state-of-the-art machine learning model in more than 90% of cases. Noticeably, the ML-driven model-based forecasting of a category of bond’s credit ratings demonstrate an excellent out-of-sample accuracy (AUC = 98%). We believe that these results can augment conventional valuations of credit portfolios.

Keywords: credit risk, credit ratings, bond pricing, spread-to-maturity, machine learning

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18164 Technical Determinants of the Success of the Quality Management Systems Implementation in Automotive Industry

Authors: Agnieszka Misztal

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The popularity of the quality management system models continues to grow despite the transitional crisis in 2008. Their development is associated with the demands of the new requirements for entrepreneurs, such as risk analysis projects and more emphasis on supervision of outsourced processes. In parallel appropriate to focus attention on the selection of companies aspiring to quality management system. This is particularly important in the automotive supplier industry, where requirements transferred to the levels in the supply chain should be clear, transparent and fairly satisfied. The author has carried out series of researches aimed at finding the factors that allow for the effective implementation of the quality management system in automotive companies. The research was focused on four groups of companies: 1) manufacturing (parts and assemblies for the purpose of sale or for vehicle manufacturers), 2) service (repair and maintenance of the car), 3) services for the transport of goods or people, 4) commercial (auto parts and vehicles). Identified determinants were divided in two types of criteria into: internal and external, as well as: hard and soft. The article presents hard - technical factors that automotive company must meet in order to achieve the goal of the quality management system implementation.

Keywords: automotive industry, quality management system, automotive technology, automotive company

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18163 Modifying Byzantine Fault Detection Using Disjoint Paths

Authors: Mehmet Hakan Karaata, Ali Hamdan, Omer Yusuf Adam Mohamed

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Consider a distributed system that delivers messages from a process to another. Such a system is often required to deliver each message to its destination regardless of whether or not the system components experience arbitrary forms of faults. In addition, each message received by the destination must be a message sent by a system process. In this paper, we first identify the necessary and sufficient conditions to detect some restricted form of Byzantine faults referred to as modifying Byzantine faults. An observable form of a Byzantine fault whose effect is limited to the modification of a message metadata or content, timing and omission faults, and message replay is referred to as a modifying Byzantine fault. We then present a distributed protocol to detect modifying Byzantine faults using optimal number of messages over node-disjoint paths.

Keywords: Byzantine faults, distributed systems, fault detection, network pro- tocols, node-disjoint paths

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18162 Innovating Translation Pedagogy: Maximizing Teaching Effectiveness by Focusing on Cognitive Study

Authors: Dawn Tsang

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This paper aims at synthesizing the difficulties in cognitive processes faced by translation majors in mainland China. The purpose is to develop possible solutions and innovation in terms of translation pedagogy, curriculum reform, and syllabus design. This research will base its analysis on students’ instant feedback and interview after training in translation and interpreting courses, and translation faculty’s teaching experiences. This research will take our translation majors as the starting point, who will be one of the focus groups. At present, our Applied Translation Studies Programme is offering translation courses in the following areas: practical translation and interpreting, translation theories, culture and translation, and internship. It is a four-year translation programme, and our students would start their introductory courses since Semester 1 of Year 1. The medium of instruction of our College is solely in English. In general, our students’ competency in English is strong. Yet in translation and especially interpreting classes, no matter it is students’ first attempt or students who have taken university English courses, students find class practices very challenging, if not mission impossible. Their biggest learning problem seems to be weakening cognitive processes in terms of lack of intercultural competence, incomprehension of English language and foreign cultures, inadequate aptitude and slow reaction, and inapt to utilize one’s vocabulary bank etc. This being so, the research questions include: (1) What specific and common cognitive difficulties are students facing while learning translation and interpreting? (2) How to deal with such difficulties, and what implications can be drawn on curriculum reform and syllabus design in translation? (3) How significant should cognitive study be placed on translation curriculum, i.e., the proportion of cognitive study in translation/interpreting courses and in translation major curriculum? and (4) What can we as translation educators do to maximize teaching and learning effectiveness by incorporating the latest development of cognitive study?. We have collected translation students’ instant feedback and conduct interviews with both students and teaching staff, in order to draw parallels as well as distinguishing from our own current teaching practices at United International College (UIC). We have collected 500 questionnaires for now. The main learning difficulties include: poor vocabulary bank, lack of listening and reading comprehension skills in terms of not fully understanding the subtext, aptitude in translation and interpreting etc. This being so, we propose to reform and revitalize translation curriculum and syllabi to address to these difficulties. The aim is to maximize teaching effectiveness in translation by addressing the above-mentioned questions with a special focus on cognitive difficulties faced by translation majors.

Keywords: cognitive difficulties, teaching and learning effectiveness, translation curriculum reform, translation pedagogy

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18161 The Design, Control and Dynamic Performance of an Interior Permanent Magnet Synchronous Generator for Wind Power System

Authors: Olusegun Solomon

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This paper describes the concept for the design and maximum power point tracking control for an interior permanent magnet synchronous generator wind turbine system. Two design concepts are compared to outline the effect of magnet design on the performance of the interior permanent magnet synchronous generator. An approximate model that includes the effect of core losses has been developed for the machine to simulate the dynamic performance of the wind energy system. An algorithm for Maximum Power Point Tracking control is included to describe the process for maximum power extraction.

Keywords: permanent magnet synchronous generator, wind power system, wind turbine

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18160 Attendance Management System Implementation Using Face Recognition

Authors: Zainab S. Abdullahi, Zakariyya H. Abdullahi, Sahnun Dahiru

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Student attendance in schools is a very important aspect in school management record. In recent years, security systems have become one of the most demanding systems in school. Every institute have its own method of taking attendance, many schools in Nigeria use the old fashion way of taking attendance. That is writing the students name and registration number in a paper and submitting it to the lecturer at the end of the lecture which is time-consuming and insecure, because some students can write for their friends without the lecturer’s knowledge. In this paper, we propose a system that takes attendance using face recognition. There are many automatic methods available for this purpose i.e. biometric attendance, but they all waste time, because the students have to follow a queue to put their thumbs on a scanner which is time-consuming. This attendance is recorded by using a camera attached in front of the class room and capturing the student images, detect the faces in the image and compare the detected faces with database and mark the attendance. The principle component analysis was used to recognize the faces detected with a high accuracy rate. The paper reviews the related work in the field of attendance system, then describe the system architecture, software algorithm and result.

Keywords: attendance system, face detection, face recognition, PCA

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18159 Exploration of Competitive Athletes’ Superstition in Taiwan: "Miracle" and "Coincidence"

Authors: Shieh Shiow-fang

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Superstitious thoughts or actions often occur during athletic competitions. Often "superstitious rituals" have a positive impact on the performance of competitive athletes. Athletes affirm the many psychological benefits of religious beliefs mostly in a positive way. Method: By snowball sampling, we recruited 10 experienced competitive athletes as participants. We used in-person and online one-to-one in-depth interview to collect their experiences about sport superstition. The total interview time was 795 minutes. We analyzed the raw data with the grounded theory processes suggested by Strauss and Corbin (1990). Results: The factors affecting athlete performance are ritual beliefs, taboo awareness, learning norms, and spontaneous attribution behaviors. Conclusion: We concluded that sports superstition reflects several psychological implications. The analysis results of this paper can provide another research perspective for the future study of sports superstition behavior.

Keywords: superstition, taboo awareness, learning norms, competitive athlete

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18158 An Overview of the Islamic Banking Development in the United Kingdom, Malaysia, Saudi Arabia, Iran, Nigeria, Kenya and Uganda

Authors: Pradeep Kulshrestha, Maulana Ayoub Ali

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The level of penetration of Islamic banking products and services has recorded a reasonable growth at an exponential rate in many parts of the world. There are many factors which have contributed to this growth including, but not limited to the rapid growth of number of Muslims who are uncomfortable with the conventional ways of banking, interest and higher interest rates scheduled by conventional banks and financial institutions as well as the financial inclusion campaign conducted in many countries. The system is facing legal challenges which open the research fdoor for practitioners and academicians for the sake of finding out solutions to those challenges. This paper tries to investigate the development of the Islamic banking system in the United Kingdom (UK), Saudi Arabia, Malaysia, Iran, Kenya, Nigeria and Uganda in order to understand the modalities which have been employed to run an Islamic banking system in the aforementioned countries. The methodology which has been employed in doing this research paper is Doctrinal, of which legislations, policies and other legal tools have been carefully studied and analysed. Again, papers from academic journals, books and financial reports have been deeply analysed for the purpose of enriching the paper and come up with a tangible results. The paper found that in Asia, Malaysia has created the smoothest legal platform for Islamic banking system to work properly in the country. The United Kingdom has tried harder to smooth the banking system without affecting the conventional banking methods and without favouring the operations of Islamic banks. It also tries harder to make UK as an Islamic banking and finance hub in Europe. The entire banking system in Iran is Islamic, while Nigeria has undergone several legal reforms to suit Islamic banking system in the country. Kenya and Uganda are at a different pace in making Islamic Banking system work alongside the conventional banking system.  

Keywords: shariah, Islamic banking, law, alternative banking

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18157 An Internet of Things-Based Weight Monitoring System for Honey

Authors: Zheng-Yan Ruan, Chien-Hao Wang, Hong-Jen Lin, Chien-Peng Huang, Ying-Hao Chen, En-Cheng Yang, Chwan-Lu Tseng, Joe-Air Jiang

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Bees play a vital role in pollination. This paper focuses on the weighing process of honey. Honey is usually stored at the comb in a hive. Bee farmers brush bees away from the comb and then collect honey, and the collected honey is weighed afterward. However, such a process brings strong negative influences on bees and even leads to the death of bees. This paper therefore presents an Internet of Things-based weight monitoring system which uses weight sensors to measure the weight of honey and simplifies the whole weighing procedure. To verify the system, the weight measured by the system is compared to the weight of standard weights used for calibration by employing a linear regression model. The R2 of the regression model is 0.9788, which suggests that the weighing system is highly reliable and is able to be applied to obtain actual weight of honey. In the future, the weight data of honey can be used to find the relationship between honey production and different ecological parameters, such as bees’ foraging behavior and weather conditions. It is expected that the findings can serve as critical information for honey production improvement.

Keywords: internet of things, weight, honey, bee

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18156 Collaborative Platform for Learning Basic Programming (Algorinfo)

Authors: Edgar Mauricio Ruiz Osuna, Claudia Yaneth Herrera Bolivar, Sandra Liliana Gomez Vasquez

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The increasing needs of professionals with skills in software development in industry are incremental, therefore, the relevance of an educational process in line with the strengthening of these competencies, are part of the responsibilities of universities with careers related to the area of Informatics and Systems. In this sense, it is important to consider that in the National Science, Technology and Innovation Plan for the development of the Electronics, Information Technologies and Communications (2013) sectors, it is established as a weakness in the SWOT Analysis of the Software sector and Services, Deficiencies in training and professional training. Accordingly, UNIMINUTO's Computer Technology Program has addressed the analysis of students' performance in software development, identifying various problems such as dropout in programming subjects, academic averages, as well as deficiencies in strategies and competencies developed in the area of programming. As a result of this analysis, it was determined to design a collaborative learning platform in basic programming using heat maps as a tool to support didactic feedback. The pilot phase allows to evaluate in a programming course the ALGORINFO platform as a didactic resource, through an interactive and collaborative environment where students can develop basic programming practices and in turn, are fed back through the analysis of time patterns and difficulties frequent in certain segments or program cycles, by means of heat maps. The result allows the teacher to have tools to reinforce and advise critical points generated on the map, so that students and graduates improve their skills as software developers.

Keywords: collaborative platform, learning, feedback, programming, heat maps

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18155 The Use of Nuclear Generation to Provide Power System Stability

Authors: Heather Wyman-Pain, Yuankai Bian, Furong Li

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The decreasing use of fossil fuel power stations has a negative effect on the stability of the electricity systems in many countries. Nuclear power stations have traditionally provided minimal ancillary services to support the system but this must change in the future as they replace fossil fuel generators. This paper explains the development of the four most popular reactor types still in regular operation across the world which have formed the basis for most reactor development since their commercialisation in the 1950s. The use of nuclear power in four countries with varying levels of capacity provided by nuclear generators is investigated, using the primary frequency response provided by generators as a measure for the electricity networks stability, to assess the need for nuclear generators to provide additional support as their share of the generation capacity increases.

Keywords: frequency control, nuclear power generation, power system stability, system inertia

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18154 Research on Low interfacial Tension Viscoelastic Fluid Oil Displacement System in Unconventional Reservoir

Authors: Long Long Chen, Xinwei Liao, Shanfa Tang, Shaojing Jiang, Ruijia Tang, Rui Wang, Shu Yun Feng, Si Yao Wang

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Unconventional oil reservoirs have the characteristics of strong heterogeneity and poor injectability, and traditional chemical flooding technology is not effective in such reservoirs; polymer flooding in the production of heavy oil reservoirs is difficult to handle produced fluid and easy to block oil wells, etc. Therefore, a viscoelastic fluid flooding system with good adaptability, low interfacial tension, plugging, and diverting capabilities was studied. The viscosity, viscoelasticity, surface/interfacial activity, wettability, emulsification, and oil displacement performance of the anionic Gemini surfactant flooding system were studied, and the adaptability of the system to the reservoir environment was evaluated. The oil displacement effect of the system in low-permeability and high-permeability (heavy oil) reservoirs was investigated, and the mechanism of the system to enhance water flooding recovery was discussed. The results show that the system has temperature resistance and viscosity increasing performance (65℃, 4.12mPa•s), shear resistance and viscoelasticity; at a lower concentration (0.5%), the oil-water interfacial tension can be reduced to ultra-low (10-3mN/m); has good emulsifying ability for heavy oil, and is easy to break demulsification (4.5min); has good adaptability to reservoirs with high salinity (30000mg/L). Oil flooding experiments show that this system can increase the water flooding recovery rate of low-permeability homogeneous and heterogeneous cores by 13% and 15%, respectively, and can increase the water-flooding recovery rate of high-permeability heavy oil reservoirs by 40%. The anionic Gemini surfactant flooding system studied in this paper is a viscoelastic fluid, has good emulsifying and oil washing ability, can effectively improve sweep efficiency, reduce injection pressure, and has broad application in unconventional reservoirs to enhance oil recovery prospect.

Keywords: oil displacement system, recovery factor, rheology, interfacial activity, environmental adaptability

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18153 Fault Tolerant Control System Using a Multiple Time Scale SMC Technique and a Geometric Approach

Authors: Ghodbane Azeddine, Saad Maarouf, Boland Jean-Francois, Thibeault Claude

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This paper proposes a new design of an active fault-tolerant flight control system against abrupt actuator faults. This overall system combines a multiple time scale sliding mode controller for fault compensation and a geometric approach for fault detection and diagnosis. The proposed control system is able to accommodate several kinds of partial and total actuator failures, by using available healthy redundancy actuators. The overall system first estimates the correct fault information using the geometric approach. Then, and based on that, a new reconfigurable control law is designed based on the multiple time scale sliding mode technique for on-line compensating the effect of such faults. This approach takes advantages of the fact that there are significant difference between the time scales of aircraft states that have a slow dynamics and those that have a fast dynamics. The closed-loop stability of the overall system is proved using Lyapunov technique. A case study of the non-linear model of the F16 fighter, subject to the rudder total loss of control confirms the effectiveness of the proposed approach.

Keywords: actuator faults, fault detection and diagnosis, fault tolerant flight control, sliding mode control, multiple time scale approximation, geometric approach for fault reconstruction, lyapunov stability

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18152 Simulation as a Problem-Solving Spotter for System Reliability

Authors: Wheyming Tina Song, Chi-Hao Hong, Peisyuan Lin

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An important performance measure for stochastic manufacturing networks is the system reliability, defined as the probability that the production output meets or exceeds a specified demand. The system parameters include the capacity of each workstation and numbers of the conforming parts produced in each workstation. We establish that eighteen archival publications, containing twenty-one examples, provide incorrect values of the system reliability. The author recently published the Song Rule, which provides the correct analytical system-reliability value; it is, however, computationally inefficient for large networks. In this paper, we use Monte Carlo simulation (implemented in C and Flexsim) to provide estimates for the above-mentioned twenty-one examples. The simulation estimates are consistent with the analytical solution for small networks but is computationally efficient for large networks. We argue here for three advantages of Monte Carlo simulation: (1) understanding stochastic systems, (2) validating analytical results, and (3) providing estimates even when analytical and numerical approaches are overly expensive in computation. Monte Carlo simulation could have detected the published analysis errors.

Keywords: Monte Carlo simulation, analytical results, leading digit rule, standard error

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18151 ESL Material Evaluation: The Missing Link in Nigerian Classrooms

Authors: Abdulkabir Abdullahi

Abstract:

The paper is a pre-use evaluation of grammar activities in three primary English course books (two of which are international primary English course books and the other a popular Nigerian primary English course book). The titles are - Cambridge Global English, Collins International Primary English, and Nigeria Primary English – Primary English. Grammar points and grammar activities in the three-course books were identified, grouped, and evaluated. The grammar activity which was most common in the course books, simple past tense, was chosen for evaluation, and the units which present simple past tense activities were selected to evaluate the extent to which the treatment of simple past tense in each of the course books help the young learners of English as a second language in Nigeria, aged 8 – 11, level A1 to A2, who lack the basic grammatical knowledge, to know grammar/communicate effectively. A bespoke checklist was devised, through the modification of existing checklists for the purpose of the evaluation, to evaluate the extent to which the grammar activities promote the communicative effectiveness of Nigerian learners of English as a second language. The results of the evaluation and the analysis of the data reveal that the treatment of grammar, especially the treatment of the simple past tense, is evidently insufficient. While Cambridge Global English’s, and Collins International Primary English’s treatment of grammar, the simple past tense, is underpinned by state-of-the-art theories of learning, language learning theories, second language learning principles, second language curriculum-syllabus design principles, grammar learning and teaching theories, the grammar load is insignificantly low, and the grammar tasks do not promote creative grammar practice sufficiently. Nigeria Primary English – Primary English, on the other hand, treats grammar, the simple past tense, in the old-fashioned direct way. The book does not favour the communicative language teaching approach; no opportunity for learners to notice and discover grammar rules for themselves, and the book lacks the potency to promote creative grammar practice. The research and its findings, therefore, underscore the need to improve grammar contents and increase grammar activity types which engage learners effectively and promote sufficient creative grammar practice in EFL and ESL material design and development.

Keywords: evaluation, activity, second language, activity-types, creative grammar practice

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18150 Knowing Where the Learning is a Shift from Summative to Formative Assessment

Authors: Eric Ho

Abstract:

Pedagogical approaches in Asia nowadays are imported from the West. In Confucian Heritage Culture (CHC), however, there is a dichotomy between the perceived benefits of Western pedagogies and the real classroom practices in Chinese societies. The success of Hong Kong students in large-scale international assessments has proved that both the strengths of both Western pedagogies and CHC educational approaches should be integrated for the sake of the students. University students aim to equip themselves with employability skills upon graduation. Formative assessments allow students to receive detailed, positive, and timely feedback and they can identify their strengths and weaknesses before they start working. However, there remains a question of whether university year 1 students who come from an examination-driven secondary education background are ready to respond to more formative assessments. The findings show that year 1 students are less concerned about competition in the university and more open to new teaching approaches that will allow them to improve as professionals in their major study areas.

Keywords: formative assessment, higher education, learning styles, Confucian heritage cultures

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18149 A Computer-Aided System for Detection and Classification of Liver Cirrhosis

Authors: Abdel Hadi N. Ebraheim, Eman Azomi, Nefisa A. Fahmy

Abstract:

This paper designs and implements a computer-aided system (CAS) to help detect and diagnose liver cirrhosis in patients with Chronic Hepatitis C. Our system reduces the required features (tests) the patient is asked to do to tests to their minimal best most informative subset of tests, with a diagnostic accuracy above 99%, and hence saving both time and costs. We use the Support Vector Machine (SVM) with cross-validation, a Multilayer Perceptron Neural Network (MLP), and a Generalized Regression Neural Network (GRNN) that employs a base of radial functions for functional approximation, as classifiers. Our system is tested on 199 subjects, of them 99 Chronic Hepatitis C.The subjects were selected from among the outpatient clinic in National Herpetology and Tropical Medicine Research Institute (NHTMRI).

Keywords: liver cirrhosis, artificial neural network, support vector machine, multi-layer perceptron, classification, accuracy

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18148 Microgrid Design Under Optimal Control With Batch Reinforcement Learning

Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

Abstract:

Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

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18147 Student Researchers and Industry Partnerships Improve Health Management with Data Driven Decisions

Authors: Carole A. South-Winter

Abstract:

Research-based learning gives students the opportunity to experience problems that require critical thinking and idea development. The skills they gain in working through these problems 'hands-on,' develop into attributes that benefit their careers in the professional field. The partnerships developed between students and industries give advantages to both sides. The students gain knowledge and skills that will increase their likelihood of success in the future and the industries are given research on new advancements that will give them a competitive advantage in their given field of work. The future of these partnerships is dependent on the success of current programs, enabling the enhancement and improvement of the research efforts. Once more students can complete research, there will be an increase in reliability of the results for each industry. The overall goal is to continue the support for research-based learning and the partnerships formed between students and industries.

Keywords: global healthcare, industry partnerships, research-driven decisions, short-term study abroad

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18146 Semi-automatic Design and Fabrication of Ring-Bell Control by IoT

Authors: Samart Rungjarean, Benchalak Muangmeesri, Dechrit Maneetham

Abstract:

Monks' and Novices' chimes may have some restrictions, such as during the rain when a structure or location chimes or at a certain period. Alternately, certain temple bells may be found atop a tall, difficult-to-reach bell tower. As a result, the concept of designing a brass bell for use with a mobile phone over great distances was proposed. The Internet of Things (IoT) system will be used to regulate the bell by testing each of the three beatings with a wooden head. A stone-beating head and a steel beater. The sound resonates nicely, with the distance and rhythm of the hit contributing to this. An ESP8266 microcontroller is used by the control system to manage its operations and will communicate with the pneumatic system to convey a signal. Additionally, a mobile phone will be used to operate the entire system. In order to precisely direct and regulate the rhythm, There is a resonance of roughly 50 dB for this test, and the operating distance can be adjusted. Timing and accuracy were both good.

Keywords: automatic ring-bell, microcontroller, ring-bell, iot

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18145 Thermodynamic Analysis of a Vapor Absorption System Using Modified Gouy-Stodola Equation

Authors: Gulshan Sachdeva, Ram Bilash

Abstract:

In this paper, the exergy analysis of vapor absorption refrigeration system using LiBr-H2O as working fluid is carried out with the modified Gouy-Stodola approach rather than the classical Gouy-Stodola equation and effect of varying input parameters is also studied on the performance of the system. As the modified approach uses the concept of effective temperature, the mathematical expressions for effective temperature have been formulated and calculated for each component of the system. Various constraints and equations are used to develop program in EES to solve these equations. The main aim of this analysis is to determine the performance of the system and the components having major irreversible loss. Results show that exergy destruction rate is considerable in absorber and generator followed by evaporator and condenser. There is an increase in exergy destruction in generator, absorber and condenser and decrease in the evaporator by the modified approach as compared to the conventional approach. The value of exergy determined by the modified Gouy Stodola equation deviates maximum i.e. 26% in the generator as compared to the exergy calculated by the classical Gouy-Stodola method.

Keywords: exergy analysis, Gouy-Stodola, refrigeration, vapor absorption

Procedia PDF Downloads 387