Search results for: digital learning

Authors: F. Lazzeri, I. Reiter

Abstract:

Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: Time-series, features engineering methods for forecasting, energy demand forecasting, Azure machine learning.

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Authors: S. Rawangwong, J. Chatthong, W. Boonchouytan

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The objective of the research was to study of foot anthropometry of children aged 7-12 years in the South of Thailand Thirty-three dimensions were measured on 305 male and 295 female subjects with 3 age ranges (7-12 years old). The instrumentation consists of four types of anthropometer, digital vernier caliper, digital height gauge and measuring tape. The mean values and standard deviations of average age, height, and weight of the male subjects were 9.52(±1.70) years, 137.80(±11.55) cm, and 37.57(±11.65) kg. Female average age, height, and weight subjects were 9.53(±1.70) years, 137.88(±11.55) cm, and 34.90(±11.57) kg respectively. The comparison of the 33 comparison measured anthropometric. Between male and female subjects were sexual differences in size on women in almost all areas of significance (p<0.05). The comparison of size and proportion elementary school students 11-12 years old men in Southern of Thailand with Thai boys aged 11-12 years of industrial standards at stage 4 year A.D. 2000-2001 Number nine ratio. Concluded that students male in Southern of Thailand has a size different from the proportions of research Industrial Standards. Ministry of Industry, Phase 4, when every year from A.D. 2000-2001 ratio was significantly (p<0.05).All of the feet studied were classified into 4 categories according to the ratios of diagonal foot breadth to the maximum foot length and heel breadth to the foot breadth. They were short but thick, small but long, small, and large. The numbers of the males feet classified in these categories were 86, 64, 40, and 115 persons or 28.20, 20.98, 13.11, and 37.70% respectively. For the female feet, the same values were 46, 59, 81, and 109 persons or 15.59, 20.00, 27.46, and 36.95% respectively.

Keywords: Ergonomics, foot anthropometry, male and female, primary school children

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Authors: Vishnu Pratap Singh Kirar

Abstract:

The main aim of a communication system is to achieve maximum performance. In Cognitive Radio any user or transceiver has ability to sense best suitable channel, while channel is not in use. It means an unlicensed user can share the spectrum of a licensed user without any interference. Though, the spectrum sensing consumes a large amount of energy and it can reduce by applying various artificial intelligent methods for determining proper spectrum holes. It also increases the efficiency of Cognitive Radio Network (CRN). In this survey paper we discuss the use of different learning models and implementation of Artificial Neural Network (ANN) to increase the learning and decision making capacity of CRN without affecting bandwidth, cost and signal rate.

Keywords: Artificial Neural Network, Cognitive Radio, Cognitive Radio Networks, Back Propagation, Spectrum Sensing.

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Authors: Nameer N. EL-Emam

Abstract:

In this paper, we construct and implement a new Steganography algorithm based on learning system to hide a large amount of information into color BMP image. We have used adaptive image filtering and adaptive non-uniform image segmentation with bits replacement on the appropriate pixels. These pixels are selected randomly rather than sequentially by using new concept defined by main cases with sub cases for each byte in one pixel. According to the steps of design, we have been concluded 16 main cases with their sub cases that covere all aspects of the input information into color bitmap image. High security layers have been proposed through four layers of security to make it difficult to break the encryption of the input information and confuse steganalysis too. Learning system has been introduces at the fourth layer of security through neural network. This layer is used to increase the difficulties of the statistical attacks. Our results against statistical and visual attacks are discussed before and after using the learning system and we make comparison with the previous Steganography algorithm. We show that our algorithm can embed efficiently a large amount of information that has been reached to 75% of the image size (replace 18 bits for each pixel as a maximum) with high quality of the output.

Keywords: Adaptive image segmentation, hiding with high capacity, hiding with high security, neural networks, Steganography.

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Authors: Weidong Xia, Malgorzata Kolotylo, Xuan Tan

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This study examines the key factors that influence general practitioners’ learning and transfer of specialized arthritis knowledge and self-care techniques to patients during normal patient visits. Drawing on the theory of planed behavior and using matched survey data collected from general practitioners before and after training sessions provided by specialized orthopedic physicians, the study suggests that the general practitioner’s intention to use and transfer learned knowledge was influenced mainly by intrinsic motivation, organizational learning culture and absorptive capacity, but was not influenced by extrinsic motivation. The results provide both theoretical and practical implications.

Keywords: Empirical study, healthcare knowledge management, patient self-care, physician knowledge transfer.

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Authors: Kazunari Meguro, Shinichi Motomura, Takao Kawamura, Kazunori Sugahara

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In this paper, backup and recovery technique for Peer to Peer applications, such as a distributed asynchronous Web-Based Training system that we have previously proposed. In order to improve the scalability and robustness of this system, all contents and function are realized on mobile agents. These agents are distributed to computers, and they can obtain using a Peer to Peer network that modified Content-Addressable Network. In the proposed system, although entire services do not become impossible even if some computers break down, the problem that contents disappear occurs with an agent-s disappearance. As a solution for this issue, backups of agents are distributed to computers. If a failure of a computer is detected, other computers will continue service using backups of the agents belonged to the computer.

Keywords: Distributed Multimedia Systems, e-Learning, P2P, Mobile Agent

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Authors: Yi-Ju Lee

Abstract:

This study identified the hypothesised relationship between creative experience, and revisit intention of handmade oriental parasol umbrella in Kaohsiung, Taiwan. A face-to-face questionnaire survey was administered in Meinong town, Kaohsiung. The components of creative experience were found as “sense of achievement”, “unique learning” and “interaction with instructors” in creative tourism. The result also revealed significant positive relationships between creative experience and revisit intention in handmade activities. This paper provides additional suggestions for enhancing revisit intention and guidance regarding creative tourism.

Keywords: Creative tourism, Sense of achievement, Unique learning, Interaction with instructors, Folk art.

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Authors: Z. Zainuddin, N. Mahat, Y. Abu Hassan

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Since the presentation of the backpropagation algorithm, a vast variety of improvements of the technique for training a feed forward neural networks have been proposed. This article focuses on two classes of acceleration techniques, one is known as Local Adaptive Techniques that are based on weightspecific only, such as the temporal behavior of the partial derivative of the current weight. The other, known as Dynamic Adaptation Methods, which dynamically adapts the momentum factors, α, and learning rate, η, with respect to the iteration number or gradient. Some of most popular learning algorithms are described. These techniques have been implemented and tested on several problems and measured in terms of gradient and error function evaluation, and percentage of success. Numerical evidence shows that these techniques improve the convergence of the Backpropagation algorithm.

Keywords: Backpropagation, Dynamic Adaptation Methods, Local Adaptive Techniques, Neural networks.

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Authors: Rajneesh Sharma, M. Gopal

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Markov games are a generalization of Markov decision process to a multi-agent setting. Two-player zero-sum Markov game framework offers an effective platform for designing robust controllers. This paper presents two novel controller design algorithms that use ideas from game-theory literature to produce reliable controllers that are able to maintain performance in presence of noise and parameter variations. A more widely used approach for controller design is the H∞ optimal control, which suffers from high computational demand and at times, may be infeasible. Our approach generates an optimal control policy for the agent (controller) via a simple Linear Program enabling the controller to learn about the unknown environment. The controller is facing an unknown environment, and in our formulation this environment corresponds to the behavior rules of the noise modeled as the opponent. Proposed controller architectures attempt to improve controller reliability by a gradual mixing of algorithmic approaches drawn from the game theory literature and the Minimax-Q Markov game solution approach, in a reinforcement-learning framework. We test the proposed algorithms on a simulated Inverted Pendulum Swing-up task and compare its performance against standard Q learning.

Keywords: Reinforcement learning, Markov Decision Process, Matrix Games, Markov Games, Smooth Fictitious play, Controller, Inverted Pendulum.

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Authors: Mario R. Acevedo Amaya, Fernanda M. Martinez Reyes

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Through the time, the higher education has changed the learning system since mother tongue to bilingual, and in this new century has been coming develop a multilingual education. All as part of globalization process of the countries and the education. Nevertheless, this change only has been effectively in countries of the first world, the rest have been lagging. Therefore, these countries require strengthen their higher education systems through models that give way to multilingual and bilingual education. In this way, shows a new model adapted from a systemic form to allow a higher bilingual and multilingual education in Latin America. This systematization aims to increase the skills and competencies student’s, decrease the time learning of a second tongue, add to multilingualism in the American Latin Universities, also, contribute to position the region´s countries in a better global status, and stimulate the development of new research in this area.

Keywords: Bilingual Education, Higher Education, Multilingual Education, Multilingual Education Model

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Authors: Aqsa Ali, Aleem Mushtaq, Attaullah Memon, Monna

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In this paper, we present a low cost design for a smart glove that can perform sign language recognition to assist the speech impaired people. Specifically, we have designed and developed an Assistive Hand Gesture Interpreter that recognizes hand movements relevant to the American Sign Language (ASL) and translates them into text for display on a Thin-Film-Transistor Liquid Crystal Display (TFT LCD) screen as well as synthetic speech. Linear Bayes Classifiers and Multilayer Neural Networks have been used to classify 11 feature vectors obtained from the sensors on the glove into one of the 27 ASL alphabets and a predefined gesture for space. Three types of features are used; bending using six bend sensors, orientation in three dimensions using accelerometers and contacts at vital points using contact sensors. To gauge the performance of the presented design, the training database was prepared using five volunteers. The accuracy of the current version on the prepared dataset was found to be up to 99.3% for target user. The solution combines electronics, e-textile technology, sensor technology, embedded system and machine learning techniques to build a low cost wearable glove that is scrupulous, elegant and portable.

Keywords: American sign language, assistive hand gesture interpreter, human-machine interface, machine learning, sensing glove.

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Authors: Olaf Henniger, Karim Lafou, Dirk Scheuermann, Bruno Struif

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This paper presents a smart-card applet that is able to verify X.509 certificates and to use the public key contained in the certificate for verifying digital signatures that have been created using the corresponding private key, e.g. for the purpose of authenticating the certificate owner against the card. The approach has been implemented as an operating prototype on Java cards.

Keywords: Public key cryptographic applications, smart cards.

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Authors: D. Vlachopoulos, G. Tsokkas

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Although it is not intended to identify distance education students as a homogeneous group, recent research has demonstrated that there are some demographic and personality common traits among most of them that provide the basis for the description of a typical distance learning student. The purpose of this paper is to describe these common traits and to facilitate their learning journey within a distance education program. The described research is an initiative of the Distance Education Unit at the European University Cyprus (Laureate International Universities) in the context of its action for the improvement of the students’ performance.

Keywords: Distance education students, successful student performance, European University Cyprus, common traits.

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Authors: Nebi Gedik

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Heart disease threatens the lives of a great number of people every year around the world. Heart issues lead to many of all deaths; therefore, early diagnosis and treatment are critical. The diagnosis of heart disease is complicated due to several factors affecting health such as high blood pressure, raised cholesterol, an irregular pulse rhythm, and more. Artificial intelligence has the potential to assist in the early detection and treatment of diseases. Improving heart failure prediction is one of the primary goals of research on heart disease risk assessment. This study aims to determine the features that provide the most successful classification prediction in detecting cardiovascular disease. The performances of each feature are compared using the K-Nearest Neighbor machine learning method. The feature that gives the most successful performance has been identified.

Keywords: Cardiovascular disease, feature extraction, supervised learning, k-NN.

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Authors: Kari Björn

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Introduction of games has expanded the application area of computer-aided learning tools to wide variety of age groups of learners. Serious games engage the learners into a real-world -type of simulation and potentially enrich the learning experience. Institutional background of a Bachelor’s level engineering program in Information and Communication Technology is introduced, with detailed focus on one of its majors, Health Technology. As part of a Customer Oriented Software Application thematic semester, one particular course of “eHealth Business and Solutions” is described and reflected in a gamified framework. Learning a consistent view into vast literature of business management, strategies, marketing and finance in a very limited time enforces selection of topics relevant to the industry. Health Technology is a novel and growing industry with a growing sector in consumer wearable devices and homecare applications. The business sector is attracting new entrepreneurs and impatient investor funds. From engineering education point of view the sector is driven by miniaturizing electronics, sensors and wireless applications. However, the market is highly consumer-driven and usability, safety and data integrity requirements are extremely high. When the same technology is used in analysis or treatment of patients, very strict regulatory measures are enforced. The paper introduces a course structure using gamification as a tool to learn the most essential in a new market: customer value proposition design, followed by a market entry game. Students analyze the existing market size and pricing structure of eHealth web-service market and enter the market as a steering group of their company, competing against the legacy players and with each other. The market is growing but has its rules of demand and supply balance. New products can be developed with an R&D-investment, and targeted to market with unique quality- and price-combinations. Product cost structure can be improved by investing to enhanced production capacity. Investments can be funded optionally by foreign capital. Students make management decisions and face the dynamics of the market competition in form of income statement and balance sheet after each decision cycle. The focus of the learning outcome is to understand customer value creation to be the source of cash flow. The benefit of gamification is to enrich the learning experience on structure and meaning of financial statements. The paper describes the gamification approach and discusses outcomes after two course implementations. Along the case description of learning challenges, some unexpected misconceptions are noted. Improvements of the game or the semi-gamified teaching pedagogy are discussed. The case description serves as an additional support to new game coordinator, as well as helps to improve the method. Overall, the gamified approach has helped to engage engineering student to business studies in an energizing way.

Keywords: Engineering education, integrated curriculum, learning experience, learning outcomes.

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Authors: Marcos Devaner, Marcela Alves, Cledson Braga, Fabiano Alves, Wilton Bezerra

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This article discusses the inclusion of people with disabilities in the process of testing an accessible system solution for distance education. The accessible system, team profile, methodologies and techniques covered in the testing process are presented. The testing process shown in this paper was designed from the experience with user. The testing process emerged from lessons learned from past experiences and the end user is present at all stages of the tests. Also, lessons learned are reported and how it was possible the maturing of the team and the methods resulting in a simple, productive and effective process.

Keywords: Experience report, accessible systems, software testing, testing process, systems, e-learning.

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Authors: Ramin Javadzadeh, Emad Javadzadeh

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Locating the critical slip surface with the minimum factor of safety for a rock slope is a difficult problem. In recent years, some modern global optimization methods have been developed with success in treating various types of problems, but very few of such methods have been applied to rock mechanical problems. In this paper, use of hybrid model based on artificial immune system and cellular learning automata is proposed. The results show that the algorithm is an effective and efficient optimization method with a high level of confidence rate.

Keywords: CLA-AIS, failure surface, optimization methods, rock slope.

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Authors: Manolo Dulva Hina, Clement Thierry, Assia Soukane, Amar Ramdane-Cherif

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In this paper, we presented our innovative way of determining the driving context for a driving assistance system. We invoke the fusion of all parameters that describe the context of the environment, the vehicle and the driver to obtain the driving context. We created a training set that stores driving situation patterns and from which the system consults to determine the driving situation. A machine-learning algorithm predicts the driving situation. The driving situation is an input to the fission process that yields the action that must be implemented when the driver needs to be informed or assisted from the given the driving situation. The action may be directed towards the driver, the vehicle or both. This is an ongoing work whose goal is to offer an alternative driving assistance system for safe driving, green driving and comfortable driving. Here, ontologies are used for knowledge representation.

Keywords: Cognitive driving, intelligent transportation system, multimodal system, ontology, machine learning.

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Authors: Marziyeh Yousefi, Hossein Nassaji

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This paper reports the results of a meta-analysis of studies on the effects of instruction mode on learning second language pragmatics during the last decade (from 2006 to 2016). After establishing related inclusion/ exclusion criteria, 39 published studies were retrieved and included in the present meta-analysis. Studies were later coded for face-to-face and computer-assisted mode of instruction. Statistical procedures were applied to obtain effect sizes. It was found that Computer-Assisted-Language-Learning studies generated larger effects than Face-to-Face instruction.

Keywords: Meta-analysis, effect size, pragmatics, computer-assisted language learnin, face-to-face instruction, comprehensive meta-analysis software.

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Authors: Michael Johnson, Vincenzo Oliveri

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This work considers an interdisciplinary Problem-Based Learning (PBL) project developed by lecturers from the Aeronautical and Electronic and Computer Engineering departments at the University of Limerick. This “CANSAT” project utilises the CanSat can-sized satellite platform in order to allow students from aeronautical and electronic engineering to engage in a mixed format (online/face-to-face), interdisciplinary PBL assignment using a real-world platform and application. The project introduces students to the design, development, and construction of the CanSat system over the course of a single semester, enabling student(s) to apply their aeronautical and technical skills/capabilities to the realisation of a working CanSat system. In this case study, the CanSat kits are used to pivot the real-world, discipline-relevant PBL goal of designing, building, and testing the CanSat system with payload(s) from a traditional module-based setting to an online PBL setting. Feedback, impressions, benefits, and challenges identified through the semester are presented. Students found the project to be interesting and rewarding, with the interdisciplinary nature of the project appealing to them. Challenges and difficulties encountered are also addressed, with solutions developed between the students and facilitators to overcoming these discussed.

Keywords: Problem-Based Learning, Online PBL, Electronic Engineering, Aeronautical Engineering, Interdisciplinary Project, CanSat.

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Authors: Rekha Kandwal, Kamal K.Bharadwaj

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Knowledge is indispensable but voluminous knowledge becomes a bottleneck for efficient processing. A great challenge for data mining activity is the generation of large number of potential rules as a result of mining process. In fact sometimes result size is comparable to the original data. Traditional data mining pruning activities such as support do not sufficiently reduce the huge rule space. Moreover, many practical applications are characterized by continual change of data and knowledge, thereby making knowledge voluminous with each change. The most predominant representation of the discovered knowledge is the standard Production Rules (PRs) in the form If P Then D. Michalski & Winston proposed Censored Production Rules (CPRs), as an extension of production rules, that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: If P Then D Unless C, where C (Censor) is an exception to the rule. Such rules are employed in situations in which the conditional statement 'If P Then D' holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence, are tight or there is simply no information available as to whether it holds or not. Thus the 'If P Then D' part of the CPR expresses important information while the Unless C part acts only as a switch changes the polarity of D to ~D. In this paper a scheme based on Dempster-Shafer Theory (DST) interpretation of a CPR is suggested for discovering CPRs from the discovered flat PRs. The discovery of CPRs from flat rules would result in considerable reduction of the already discovered rules. The proposed scheme incrementally incorporates new knowledge and also reduces the size of knowledge base considerably with each episode. Examples are given to demonstrate the behaviour of the proposed scheme. The suggested cumulative learning scheme would be useful in mining data streams.

Keywords: Censored production rules, cumulative learning, data mining, machine learning.

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Authors: Motonobu Hattori, Rina Suzuki

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In neural networks, when new patters are learned by a network, they radically interfere with previously stored patterns. This drawback is called catastrophic forgetting. We have already proposed a biologically inspired dual-network memory model which can much reduce this forgetting for static patterns. In this model, information is first stored in the hippocampal network, and thereafter, it is transferred to the neocortical network using pseudopatterns. Because temporal sequence learning is more important than static pattern learning in the real world, in this study, we improve our conventional  dual-network memory model so that it can deal with temporal sequences without catastrophic forgetting. The computer simulation results show the effectiveness of the proposed dual-network memory model.  

Keywords: Catastrophic forgetting, dual-network, temporal sequences.

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Authors: Lee Bih Ni, Zulfhikar Rabe, Nurul Asyikin Hassan

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The Ministry of Education Malaysia dynamically and drastically made the subject of History mandatory to be in force in 2013. This is in recognition of the nation's heritage and treasures in maintaining true facts and information for future generations of the State. History reveals the civilization of a nation and the fact of national cultural heritage. Civilization needs to be preserved as a legacy of sovereign heritage. Today's generation is the catalyst for future heirs who will support the principle and direction of the country. In line with the National Education Philosophy that aims to shape the potential development of individuals holistically and uniquely in order to produce a balanced and harmonious student in terms of intellectual, spiritual, emotional and physical. Hence, understanding the importance of studying the history subject as a pillar of identity and the history of nationhood is to be a priority in the pursuit of knowledge and empowering the spirit of statehood that is nurtured through continuous learning at school. Judging from the aspect of teacher leadership role in integrating history in a combined way based on Teacher Education Philosophy. It empowers the teaching profession towards the teacher to support noble character. It also supports progressive and scientific views. Teachers are willing to uphold the State's aspirations and celebrate the country's cultural heritage. They guarantee individual development and maintain a united, democratic, progressive and disciplined society. Teacher's role as a change and leadership agent in education begins in the classroom through formal or informal educational processes. This situation is expanded in schools, communities and countries. The focus of this paper is on the role of teacher leadership influencing the effectiveness of teaching and learning history in the classroom environment. Leadership guides to teachers' perceptions on the role of teacher leadership, teaching leadership, and the teacher leadership role and effective teacher leadership role. Discussions give emphasis on aspects of factors affecting the classroom environment, forming the classroom agenda, effective classroom implementation methods, suitable climate for historical learning and teacher challenges in implicating the effectiveness of teaching and learning processes.

Keywords: Teacher leadership, leadership lessons, effective classroom, effective teacher.

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Authors: Melissa C. LaDuke

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This systematic literature review sought to explore the dimensions of diversity that can affect classroom learning. This review is significant as it can aid educators in reaching more of their diverse student population and creating supportive classrooms for teachers and students. For this study, peer-reviewed articles were found and compiled using Google Scholar. Key terms used in the search include student individuality, classroom equality, student development, teacher development, and teacher individuality. Relevant educational standards such as Common Core and Partnership for the 21st Century were also included as part of this review. Student and teacher individuality and equality is discussed as well as methods to grow both within educational settings. Embracing student and teacher individuality was found to be key as it may affect how each person interacts with given information. One method to grow individuality and equality in educational settings included drafting and employing revised teaching standards which include various Common Core and US State standards. Another was to use educational theories such as constructivism, cognitive learning, and Experiential Learning Theory. However, barriers to growing individuality, such as not acknowledging differences in a population’s dimensions of diversity, still exist. Studies found preserving the dimensions of diversity owned by both teachers and students yielded more positive and beneficial classroom experiences.

Keywords: Classroom equality, student development, student individuality, teacher development, teacher individuality.

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Authors: Pei Wen Liao, Tsung Hau Jen

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the data of Taiwanese 8th grader in the 4th cycle of Trends in International Mathematics and Science Study (TIMSS) are analyzed to examine the influence of the science teachers- preference in experimental teaching on the relationships between the affective variables ( the perceived usefulness of science, ease of using science and science learning interest) and the academic achievement in science. After dealing with the missing data, 3711 students and 145 science teacher-s data were analyzed through a Hierarchical Linear Modeling technique. The major objective of this study was to determine the role of the experimental teaching moderates the relationship between perceived usefulness and achievement.

Keywords: TIMSS database, Science achievement, Experimental teaching, Perceived Usefulness, Perceived Ease of Use

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Authors: Vishal D. Pandya

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A great deal of perceptible change has been taking place in the way our institutions of higher learning are being managed in India today. It is believed that managers, whose intuition proves to be accurate, often tend to be the most successful, and this is what makes them almost like entrepreneurs. A certain entrepreneurial spirit is what is expected and requires a degree of insight of the manager to be successful depending upon the situational and more importantly, the heterogeneity as well as the socio-cultural aspect. Teachers in Higher Education have to play multiple roles to make sure that the Learning-Teaching process becomes effective in the real sense of the term. This paper makes an effort to take a close look at that, especially in the context of the management of English language teaching in Higher Education and, therefore, focuses on the management of English language teaching in higher education by understanding target situation analyses at the socio-cultural level.

Keywords: Management, language teaching, English language teaching, higher education.

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Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

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‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.

Keywords: Deep learning network, smart metering, water end use, water-energy data.

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Authors: Andrew Chimpololo

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Open and distance learning is a fairly new concept in Malawi. The major public provider, the Malawi College of Distance Education, rolled out its activities only about 40 years ago. Over the years, the demand for distance education has tremendously increased. The present government has displayed positive political will to uplift ODL as outlined in the Malawi Growth and Development Strategy as well as the National Education Sector Plan. A growing national interest in education coupled with political stability and a booming ICT industry also raise hope for success. However, a fragile economy with a GNI per capita of -US$ 200 over the last decade, poor public funding, erratic power supply and lack of expertise put strain on efforts towards the promotion of ODL initiatives. Despite the challenges, the nation appears determined to go flat out and explore all possible avenues that could revolutionise education access and equity through ODL.

Keywords: challenges, distance education, Malawi, openlearning, prospects.

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Authors: L. Bih Ni, D. Norizah Ag Kiflee, T. Choon Keong, R. Talip, S. Singh Bikar Singh, M. Noor Mad Japuni, R. Talin

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The purpose of this study is to determine the effectiveness of video clips to enhance students' achievement and motivation towards learning and facilitating of history. We use narrative literature studies to illustrate the current state of the two art and science in focused areas of inquiry. We used experimental method. The experimental method is a systematic scientific research method in which the researchers manipulate one or more variables to control and measure any changes in other variables. For this purpose, two experimental groups have been designed: one experimental and one groups consisting of 30 lower secondary students. The session is given to the first batch using a computer presentation program that uses video clips to be considered as experimental group, while the second group is assigned as the same class using traditional methods using dialogue and discussion techniques that are considered a control group. Both groups are subject to pre and post-trial in matters that are handled by the class. The findings show that the results of the pre-test analysis did not show statistically significant differences, which in turn proved the equality of the two groups. Meanwhile, post-test analysis results show that there was a statistically significant difference between the experimental group and the control group at an importance level of 0.05 for the benefit of the experimental group.

Keywords: Video clips, Historical Learning and Facilitation, Achievement, Motivation.

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Authors: Jasmin Velagic, Nedim Osmic, Bakir Lacevic

Abstract:

In this paper the neural network-based controller is designed for motion control of a mobile robot. This paper treats the problems of trajectory following and posture stabilization of the mobile robot with nonholonomic constraints. For this purpose the recurrent neural network with one hidden layer is used. It learns relationship between linear velocities and error positions of the mobile robot. This neural network is trained on-line using the backpropagation optimization algorithm with an adaptive learning rate. The optimization algorithm is performed at each sample time to compute the optimal control inputs. The performance of the proposed system is investigated using a kinematic model of the mobile robot.

Keywords: Mobile robot, kinematic model, neural network, motion control, adaptive learning rate.

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