Search results for: Learning Tool

Authors: Ekachai Phaisangittisagul, Rapeepol Chongprachawat

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Obtaining labeled data in supervised learning is often difficult and expensive, and thus the trained learning algorithm tends to be overfitting due to small number of training data. As a result, some researchers have focused on using unlabeled data which may not necessary to follow the same generative distribution as the labeled data to construct a high-level feature for improving performance on supervised learning tasks. In this paper, we investigate the impact of the relationship between unlabeled and labeled data for classification performance. Specifically, we will apply difference unlabeled data which have different degrees of relation to the labeled data for handwritten digit classification task based on MNIST dataset. Our experimental results show that the higher the degree of relation between unlabeled and labeled data, the better the classification performance. Although the unlabeled data that is completely from different generative distribution to the labeled data provides the lowest classification performance, we still achieve high classification performance. This leads to expanding the applicability of the supervised learning algorithms using unsupervised learning.

Keywords: Autoencoder, high-level feature, MNIST dataset, selftaught learning, supervised learning.

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Authors: Amit Gil, Helman Stern, Yael Edan

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A cognitive collaborative reinforcement learning algorithm (CCRL) that incorporates an advisor into the learning process is developed to improve supervised learning. An autonomous learner is enabled with a self awareness cognitive skill to decide when to solicit instructions from the advisor. The learner can also assess the value of advice, and accept or reject it. The method is evaluated for robotic motion planning using simulation. Tests are conducted for advisors with skill levels from expert to novice. The CCRL algorithm and a combined method integrating its logic with Clouse-s Introspection Approach, outperformed a base-line fully autonomous learner, and demonstrated robust performance when dealing with various advisor skill levels, learning to accept advice received from an expert, while rejecting that of less skilled collaborators. Although the CCRL algorithm is based on RL, it fits other machine learning methods, since advisor-s actions are only added to the outer layer.

Keywords: Robot learning, human-robot collaboration, motion planning, reinforcement learning.

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Authors: Anna Angelini, Enrica Gentile, Paola Plantamura, Vito Leonardo Plantamura

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A suitable e-learning system management needs to carry out a web-information system in order to allow integrated fruition of data and metadata concerning the activities typical of elearning environment. The definition of a “web information system" for e-learning takes advantage of the potentialities of Web technologies both as for the access to metadata present on the several platforms, and as for the implementation of courseware which make up the relative didactic environment. What information systems have in common is the technological environment on which they are generally implemented and the use of metadata in order to structure information at all cognitive and organization levels. In this work we are going to define a methodology for the implementation of a specific web information system for an e-learning environment.

Keywords: e-learning, information systems, coursemanagement, web-based system.

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Authors: Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang

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2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn  features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.

Keywords: Artificial Intelligence, machine learning, deep learning, convolutional neural networks.

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Authors: S. Silverstone, J. Phadungtin

Abstract:

Today-s Wi Fi generation utilize the latest technology in their daily lives. Instructors at National University, the second largest non profit private institution of higher learning in California, are incorporating these new tools to modify their Online class formats to better accommodate these new skills in their distance education delivery modes. The University provides accelerated learning in a one-course per month format both Onsite and Online. Since there has been such a significant increase in Online classes over the past three years, and it is expected to grow even more over the over the next five years, Instructors cannot afford to maintain the status quo and not take advantage of these new options. It is at the discretion of the instructors which accessory they use and how comfortable and familiar they are with the technology. This paper explores the effects and summarizes students- comments of some of these new technological options which have been recently provided in order to make students- online learning experience more exciting and meaningful.

Keywords: Asynchronous chats, synchronous learning, VoIP.

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Authors: M. Chaoui, M-T. Laskri

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The evolution of information and communication technology has made a very powerful support for the improvement of online learning platforms in creation of courses. This paper presents a study that attempts to explore new web architecture for creating an adaptive online learning system to profiles of learners, using the Web as a source for the automatic creation of courses for the online training platform. This architecture will reduce the time and decrease the effort performed by the drafters of the current e-learning platform, and direct adaptation of the Web content will greatly enrich the quality of online training courses.

Keywords: Web Content, e-Learning, Educational Content, LMS, Profiles of Learners

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Authors: Shashank N. Mathur, Anil K. Ahlawat, Virendra P. Vishwakarma

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In this paper, a comparative study of application of supervised and unsupervised learning algorithms on illumination invariant face recognition has been carried out. The supervised learning has been carried out with the help of using a bi-layered artificial neural network having one input, two hidden and one output layer. The gradient descent with momentum and adaptive learning rate back propagation learning algorithm has been used to implement the supervised learning in a way that both the inputs and corresponding outputs are provided at the time of training the network, thus here is an inherent clustering and optimized learning of weights which provide us with efficient results.. The unsupervised learning has been implemented with the help of a modified Counterpropagation network. The Counterpropagation network involves the process of clustering followed by application of Outstar rule to obtain the recognized face. The face recognition system has been developed for recognizing faces which have varying illumination intensities, where the database images vary in lighting with respect to angle of illumination with horizontal and vertical planes. The supervised and unsupervised learning algorithms have been implemented and have been tested exhaustively, with and without application of histogram equalization to get efficient results.

Keywords: Artificial Neural Networks, back propagation, Counterpropagation networks, face recognition, learning algorithms.

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Authors: Melvin A. Ballera

Abstract:

Prior literature in the field of adaptive and personalized learning sequence in e-learning have proposed and implemented various mechanisms to improve the learning process such as individualization and personalization, but complex to implement due to expensive algorithmic programming and need of extensive and prior data. The main objective of personalizing learning sequence is to maximize learning by dynamically selecting the closest teaching operation in order to achieve the learning competency of learner. In this paper, a revolutionary technique has been proposed and tested to perform individualization and personalization using modified reversed roulette wheel selection algorithm that runs at O(n). The technique is simpler to implement and is algorithmically less expensive compared to other revolutionary algorithms since it collects the dynamic real time performance matrix such as examinations, reviews, and study to form the RWSA single numerical fitness value. Results show that the implemented system is capable of recommending new learning sequences that lessens time of study based on student's prior knowledge and real performance matrix.

Keywords: E-learning, fitness value, personalized learning sequence, reversed roulette wheel selection algorithms.

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Authors: Farhad Kolahan, Mohsen Manoochehri, Abbas Hosseini

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Machining is an important manufacturing process used to produce a wide variety of metallic parts. Among various machining processes, turning is one of the most important one which is employed to shape cylindrical parts. In turning, the quality of finished product is measured in terms of surface roughness. In turn, surface quality is determined by machining parameters and tool geometry specifications. The main objective of this study is to simultaneously model and optimize machining parameters and tool geometry in order to improve the surface roughness for AISI1045 steel. Several levels of machining parameters and tool geometry specifications are considered as input parameters. The surface roughness is selected as process output measure of performance. A Taguchi approach is employed to gather experimental data. Then, based on signal-to-noise (S/N) ratio, the best sets of cutting parameters and tool geometry specifications have been determined. Using these parameters values, the surface roughness of AISI1045 steel parts may be minimized. Experimental results are provided to illustrate the effectiveness of the proposed approach.

Keywords: Taguchi method, turning parameters, tool geometry specifications, S/N ratio, statistical analysis.

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Authors: S. Rawashdi, D. Bshouty

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This paper aimed at discussing how to urge middle and high school Arab students in Israel to be aware of the importance of and investing in learning mathematics. In the first phase of the study, three questionnaires were passed to two nine-grade classes, one on Awareness, one on Awakeness and one on Learning. One of the two classes was an outstanding class from a public school (PUBS) of 31 students, and the other a heterogeneous class from a private school (PRIS) with 31 students. The Learning questionnaire which was administrated to the Awareness and Awareness topics was passed to PRIS and the Awareness and Awareness Questionnaires were passed to the PUBS class After two months we passed the post-questionnaire to both classes to validate the long-term impact of the study. The findings of the study show that awakeness and awareness processes have an effect on the math learning process, on its context in students' daily lives and their growing interest in learning math.

Keywords: Awakeness, awareness, learning mathematics, pupils.

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Authors: Martina Holenko Dlab, Natasa Hoic-Bozic, Ivica Boticki

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This paper presents technologically innovative and scalable mobile learning solution within the SCOLLAm project (“Opening up education through Seamless and COLLAborative mobile learning on tablet computers”). The main research method applied during the development of the SCOLLAm mobile learning system is design-based research. It assumes iterative refinement of the system guided by collaboration between researches and practitioners. Following the identification of requirements, a multiplatform mobile learning system SCOLLAm [in]Form was developed. Several experiments were designed and conducted in the first and second grade of elementary school. SCOLLAm [in]Form system was used to design learning activities for math classes during which students practice calculation. System refinements were based on experience and interaction data gathered during class observations. In addition to implemented improvements, the data were used to outline possible improvements and deficiencies of the system that should be addressed in the next phase of the SCOLLAm [in]Form development.

Keywords: Adaptation, collaborative learning, educational technology, mobile learning, tablet computers.

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Authors: Jamshaid ur Rehman, Shahida Wizarat

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The principal focus of this study is on the measurement and analysis of labor learnings in Pakistan. The study at the aggregate economy level focus on the labor productivity movements and at large-scale manufacturing level focus on the cost structure, with isolating the contribution of the learning curve. The analysis of S-shaped curve suggests that learnings are only below one half of aggregate learning curve and other half shows the retardation in learning, hence retardation in productivity movements. The study implies the existence of learning economies in term of cost reduction that is input cost per unit produced decreases by 0.51 percent every time the cumulative production output doubles.

Keywords: Cost, Inflection Point, Learning Curve, Minima, Maxima, and Productivity

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Authors: Rasimah Che Mohd Yusoff, Halimah Badioze Zaman, Azlina Ahmad

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Mixed Reality (MR) is one of the newest technologies explored in education. It promises the potential to promote teaching and learning and making learners- experience more “engaging". However, there still lack of research on designing a virtual learning environment using MR technology. In this paper, we describe the Mixed Reality technology, the characteristics of situated learning as instructional design for virtual environment using mixed reality technology. We also explain a case study that implemented those design and also the system overview.

Keywords: authentic activity. authentic context, mixed reality, situated learning

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Authors: Ying Zhao

Abstract:

Keystroke authentication is a new access control system to identify legitimate users via their typing behavior. In this paper, machine learning techniques are adapted for keystroke authentication. Seven learning methods are used to build models to differentiate user keystroke patterns. The selected classification methods are Decision Tree, Naive Bayesian, Instance Based Learning, Decision Table, One Rule, Random Tree and K-star. Among these methods, three of them are studied in more details. The results show that machine learning is a feasible alternative for keystroke authentication. Compared to the conventional Nearest Neighbour method in the recent research, learning methods especially Decision Tree can be more accurate. In addition, the experiment results reveal that 3-Grams is more accurate than 2-Grams and 4-Grams for feature extraction. Also, combination of attributes tend to result higher accuracy.

Keywords: Keystroke Authentication, Pattern recognition, MachineLearning, Instance-based Learning, Bayesian, Decision Tree.

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Authors: Mohamed E. Seliaman, M. S. Al-Turki

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This paper investigates the use of mobile phones and tablets for learning purposes among university students in Saudi Arabia. For this purpose, an extended Technology Acceptance Model (TAM) is proposed to analyze the adoption of mobile devices and smart phones by Saudi university students for accessing course materials, searching the web for information related to their discipline, sharing knowledge, conducting assignments etc.

Keywords: Saudi Arabia, TAM, Mobile learning, e-learning, smart phones.

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Authors: C. Kumjeera, T. Unchim, B. Marungsri, A. Oonsivilai

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The study of piezoelectric material in the past was in T-Domain form; however, no one has studied piezoelectric material in the S-Domain form. This paper will present the piezoelectric material in the transfer function or S-Domain model. S-Domain is a well known mathematical model, used for analyzing the stability of the material and determining the stability limits. By using S-Domain in testing stability of piezoelectric material, it will provide a new tool for the scientific world to study this material in various forms.

Keywords: Hard disk drive, failure analysis, tool, time

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Authors: Asia Majeed

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This paper will investigate a form of learning mathematics by integrating technology in mathematics specifically for the university first-year calculus class to support students’ engagement in learning which influences students' conceptual and procedural understanding of the calculus content in a better way. The students with good grades in high school calculus generally struggle in first-year university calculus classes in learning mathematical analysis concepts. This problem has to be addressed. If this problem is not resolved, then most likely students with less ability to do mathematics might not able to complete their degrees. In this work, MATLAB is used to help students in learning and in improving calculus concepts.

Keywords: Calculus, first-year university students, teaching strategies, MATLAB.

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Authors: Kornchanok Chidchaisuwan

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This project is a study of learning activities of creating experience from actual work performance to enhance career skills and technological usage abilities for uses in advertising career work performance for undergraduate students who enroll in the Creative Strategies for Advertising Course. The instructional model consisted of two learning approaches: (1) simulation-based learning, which is the learning with the use of simulations of working in various sections of creative advertisement work with their own work process and steps as well as the virtual technology learning in advertising companies; and (2) project-based learning, which is the learning that the learners engage in actual work performance based on the process of creating and producing creative advertisement works to be present on new media channels. The results of learning management showed that the effects on the students in various aspects were as follows: (1) the students had experience in the advertising process at the higher level; and (2) the students had work performance skills from the actual work performance that enabled them to possess the abilities to create and present their own work; also, they had created more efficient work outcomes and disseminated them on new media channels at a better level.

Keywords: Technical literacy, career skill, experience, simulation-based learning.

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Authors: Y. Benjelloun Touimi, N. Faddouli, S. Bennani, M. Khalidi Idrissi

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The pedagogy project has been proven as an active learning method, which is used to develop learner-s skills and knowledge.The use of technology in the learning world, has filed several gaps in the implementation of teaching methods, and online evaluation of learners. However, the project methodology presents challenges in the assessment of learners online. Indeed, interoperability between E-learning platforms (LMS) is one of the major challenges of project-based learning assessment. Firstly, we have reviewed the characteristics of online assessment in the context of project-based teaching. We addressed the constraints encountered during the peer evaluation process. Our approach is to propose a meta-model, which will describe a language dedicated to the conception of peer assessment scenario in project-based learning. Then we illustrate our proposal by an instantiation of the meta-model through a business process in a scenario of collaborative assessment on line.

Keywords: Online project based learning, meta-model, peer assessment process.

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Authors: Horng-Jyh Chen, Yi-Fang Chen, Chien-Liang Lin

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In this paper, the authors try to investigate the determinants of behavioral intention of the blended E-learning course for senior students at the Active Ageing University in Taiwan. Due to lower proficiency in the use of computers and less experience on learning styles of the blended E-learning course for senior students will be expected quite different from those for most young students. After more than five weeks course for two years the questionnaire survey is executed to collect data for statistical analysis in order to understand the determinants of the behavioral intention for senior students. The object of this study is at one of the Active Ageing University in Taiwan total of 84 senior students in the blended E-learning for the ceramics teaching course. The research results show that only the perceived usefulness of the blended E-learning course has significant positive relationship with the behavioral intention.

Keywords: Active Aging University, blended E-learning, ceramics teaching course, behavioral intention

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Authors: Jan Stodt, Christoph Reich

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The usage of machine learning models for prediction is growing rapidly and proof that the intended requirements are met is essential. Audits are a proven method to determine whether requirements or guidelines are met. However, machine learning models have intrinsic characteristics, such as the quality of training data, that make it difficult to demonstrate the required behavior and make audits more challenging. This paper describes an ML audit framework that evaluates and reviews the risks of machine learning applications, the quality of the training data, and the machine learning model. We evaluate and demonstrate the functionality of the proposed framework by auditing an steel plate fault prediction model.

Keywords: Audit, machine learning, assessment, metrics.

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Authors: Juris Porozovs, Daina Voita, Anda Kauliņa, Toms Voits, Evita Vaļēviča

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Integrative teaching methodology is based on connecting and summarizing knowledge from different subjects in order to create better understanding of different disciplines and improvement of competences in general. Integrative teaching methodology was implemented and realised during one academic year in 17 Latvian schools according with specially worked out programme by specialists of different fields for adaptation in social environment of children and young people with learning, cognitive functions and motor disorders. Implemented integrative teaching methodology consisted from three subsections which were specialised for adaptation in social environment, improvement of cognitive functions and improvement and harmonization of personality. The results of investigation showed that the use of integrative teaching methodology is an effective way for improvement of learning motivation and negotiation of learning disorders of different age schoolchildren.

Keywords: Adaptation in social environment, integrative teaching methodology, learning disorders, learning motivation.

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Authors: Bella Llego

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This study aims to investigate the motivating and de-motivating factors that affect the learning ability of students attending the English Learning Center in Thailand. The subjects of this research were 20 students from the Hana Semiconductor Co., Limited. The data were collected by using questionnaire and analyzed using the SPSS program for the percentage, mean and standard deviation. The research results show that the main motivating factor in learning English at Hana Semiconductor Co., Ltd. is that it would help the employees to communicate with foreign customers and managers. Other reasons include the need to read and write e-mails, and reports in English, as well as to increase overall general knowledge. The main de-motivating factor is that there is a lot of vocabulary to remember when learning English. Another de-motivating factor is that when homework is given, the students have no time to complete the tasks required of them at the end of the working day.

Keywords: Motivating, demotivating, English learning center, student communicate.

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Authors: Yuan L. Lai, Jian H. Chen, Jui P. Hung

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Owning to the high-speed feed rate and ultra spindle speed have been used in modern machine tools, the tool-path generation plays a key role in the successful application of a High-Speed Machining (HSM) system. Because of its importance in both high-speed machining and tool-path generation, approximating a contour by NURBS format is a potential function in CAD/CAM/CNC systems. It is much more convenient to represent an ellipse by parametric form than to connect points laboriously determined in a CNC system. A new approximating method based on optimum processes and NURBS curves of any degree to the ellipses is presented in this study. Such operations can be the foundation of tool-radius compensation interpolator of NURBS curves in CNC system. All operating processes for a CAD tool is presented and demonstrated by practical models.

Keywords: Ellipse, Approximation, NURBS, Optimum.

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Authors: Xiaodong Li, Peng Gao, Chao-Jung Huang, Shiying Hao, Xuefeng B. Ling, Yongxia Han, Yaqi Zhang, Le Zheng, Chengyin Ye, Modi Liu, Minjie Xia, Changlin Fu, Bo Jin, Karl G. Sylvester, Eric Widen

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Predicting the risk of Pancreatic Adenocarcinoma (PA) in advance can benefit the quality of care and potentially reduce population mortality and morbidity. The aim of this study was to develop and prospectively validate a risk prediction model to identify patients at risk of new incident PA as early as 3 months before the onset of PA in a statewide, general population in Maine. The PA prediction model was developed using Deep Neural Networks, a deep learning algorithm, with a 2-year electronic-health-record (EHR) cohort. Prospective results showed that our model identified 54.35% of all inpatient episodes of PA, and 91.20% of all PA that required subsequent chemoradiotherapy, with a lead-time of up to 3 months and a true alert of 67.62%. The risk assessment tool has attained an improved discriminative ability. It can be immediately deployed to the health system to provide automatic early warnings to adults at risk of PA. It has potential to identify personalized risk factors to facilitate customized PA interventions.

Keywords: Cancer prediction, deep learning, electronic health records, pancreatic adenocarcinoma.

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Authors: Jose J.CarreñoZagarra, Rodolfo Villamizar Mejía

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This work describes a CACSD tool for automatic design of robust controllers for hydraulic turbines. The tool calculates the optimal
 controller using the MATLAB hinfopt function and it serves as a practical and effective solution for the laborious task of designing a different controller for each type of turbine and generator, and different parameters and conditions of the plant. Results of the simulation of a generating unit subject to parameters variation show the accuracy and efficiency of the obtained robust controllers.

Keywords: Robust Control, Hydroelectric System Turbine, Control H∞, CACSD

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Authors: Carlos Oliveira

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This paper is a criticism of the traditional model of teaching and presents alternative teaching methods, different from the traditional lecture. These methods are accompanied by reports of experience of their application in a class. It was concluded that in the lecture, the student has a low learning rate and that other methods should be used to make the most engaging learning environment for the student, contributing (or facilitating) his learning process. However, the teacher should not use a single method, but rather a range of different methods to ensure the learning experience does not become repetitive and fatiguing for the student.

Keywords: Educational practices, experience report, IT in education, teaching methods.

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Authors: Chin-Pin Chen, David W.S. Tai, Wen-Jong Chen, Hui-Min Lai

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This study aims to analyze the effect of e-learning on photonics technology and daily livings among college students. The course contents of photonics technology and daily livings are first drafted based on research discussions and expert interviews. Having expert questionnaires with Delphi Technique for three times, the knowledge units and items for the course of photonics technology and daily livings are established. The e-learning materials and the drafts of instructional strategies, academic achievement, and learning attitude scales are then developed. With expert inspection, reliability and validity test, and experimental instructions, the scales and the material are further revised. Finally, the formal instructions are implemented to test the effect of different instructional methods on the academic achievement of photonics technology and daily livings among students in universities of technology. The research results show that e-learning could effectively promote academic achievement and learning attitude, and the students with e-learning obviously outperform the ones with trandition instructions.

Keywords: E-learning, Photonics Technology and Daily Livings, Academic Achievement

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Authors: Thuy Thi Nguyen, Nguyen Dang Binh, Horst Bischof

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In this work, we present a novel active learning approach for learning a visual object detection system. Our system is composed of an active learning mechanism as wrapper around a sub-algorithm which implement an online boosting-based learning object detector. In the core is a combination of a bootstrap procedure and a semi automatic learning process based on the online boosting procedure. The idea is to exploit the availability of classifier during learning to automatically label training samples and increasingly improves the classifier. This addresses the issue of reducing labeling effort meanwhile obtain better performance. In addition, we propose a verification process for further improvement of the classifier. The idea is to allow re-update on seen data during learning for stabilizing the detector. The main contribution of this empirical study is a demonstration that active learning based on an online boosting approach trained in this manner can achieve results comparable or even outperform a framework trained in conventional manner using much more labeling effort. Empirical experiments on challenging data set for specific object deteciton problems show the effectiveness of our approach.

Keywords: Computer vision, object detection, online boosting, active learning, labeling complexity.

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Authors: David Downey

Abstract:

With the introduction of additive manufacturing (3D printing) to produce titanium (Ti6Al4V) components in the medical, aerospace and automotive industries, intricate geometries can be produced with virtually complete design freedom. However, the consideration of microstructural anisotropy resulting from the additive manufacturing process becomes necessary due to this design flexibility and the need to print a geometric shape that can consist of numerous angles, radii, and swept surfaces. A femoral knee implant serves as an example of a 3D-printed near-net-shaped product. The mechanical properties of the printed components, and consequently, their machinability, are affected by microstructural anisotropy. Currently, finish-machining operations performed on titanium printed parts using selective laser melting (SLM) utilize the same cutting tools employed for processing wrought titanium components. Cutting forces for components manufactured through SLM can be up to 70% higher than those for their wrought counterparts made of Ti6Al4V. Moreover, temperatures at the cutting interface of 3D printed material can surpass those of wrought titanium, leading to significant tool wear. Although the criteria for tool wear may be similar for both 3D printed and wrought materials, the rate of wear during the machining process may differ. The impact of these issues on the choice of cutting tool material and tool lifetimes will be discussed.

Keywords: Additive manufacturing, build orientation, microstructural anisotropy, printed titanium Ti6Al4V, tool wear.

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