WorldWideScience

Sample records for learning systems based

  1. Web-Based Learning Support System

    Science.gov (United States)

    Fan, Lisa

    Web-based learning support system offers many benefits over traditional learning environments and has become very popular. The Web is a powerful environment for distributing information and delivering knowledge to an increasingly wide and diverse audience. Typical Web-based learning environments, such as Web-CT, Blackboard, include course content delivery tools, quiz modules, grade reporting systems, assignment submission components, etc. They are powerful integrated learning management systems (LMS) that support a number of activities performed by teachers and students during the learning process [1]. However, students who study a course on the Internet tend to be more heterogeneously distributed than those found in a traditional classroom situation. In order to achieve optimal efficiency in a learning process, an individual learner needs his or her own personalized assistance. For a web-based open and dynamic learning environment, personalized support for learners becomes more important. This chapter demonstrates how to realize personalized learning support in dynamic and heterogeneous learning environments by utilizing Adaptive Web technologies. It focuses on course personalization in terms of contents and teaching materials that is according to each student's needs and capabilities. An example of using Rough Set to analyze student personal information to assist students with effective learning and predict student performance is presented.

  2. A Web-Based Learning Support System for Inquiry-Based Learning

    Science.gov (United States)

    Kim, Dong Won; Yao, Jingtao

    The emergence of the Internet and Web technology makes it possible to implement the ideals of inquiry-based learning, in which students seek truth, information, or knowledge by questioning. Web-based learning support systems can provide a good framework for inquiry-based learning. This article presents a study on a Web-based learning support system called Online Treasure Hunt. The Web-based learning support system mainly consists of a teaching support subsystem, a learning support subsystem, and a treasure hunt game. The teaching support subsystem allows instructors to design their own inquiry-based learning environments. The learning support subsystem supports students' inquiry activities. The treasure hunt game enables students to investigate new knowledge, develop ideas, and review their findings. Online Treasure Hunt complies with a treasure hunt model. The treasure hunt model formalizes a general treasure hunt game to contain the learning strategies of inquiry-based learning. This Web-based learning support system empowered with the online-learning game and founded on the sound learning strategies furnishes students with the interactive and collaborative student-centered learning environment.

  3. Component-Based Approach in Learning Management System Development

    Science.gov (United States)

    Zaitseva, Larisa; Bule, Jekaterina; Makarov, Sergey

    2013-01-01

    The paper describes component-based approach (CBA) for learning management system development. Learning object as components of e-learning courses and their metadata is considered. The architecture of learning management system based on CBA being developed in Riga Technical University, namely its architecture, elements and possibilities are…

  4. Intelligent Web-Based Learning System with Personalized Learning Path Guidance

    Science.gov (United States)

    Chen, C. M.

    2008-01-01

    Personalized curriculum sequencing is an important research issue for web-based learning systems because no fixed learning paths will be appropriate for all learners. Therefore, many researchers focused on developing e-learning systems with personalized learning mechanisms to assist on-line web-based learning and adaptively provide learning paths…

  5. A Situated Cultural Festival Learning System Based on Motion Sensing

    Science.gov (United States)

    Chang, Yi-Hsing; Lin, Yu-Kai; Fang, Rong-Jyue; Lu, You-Te

    2017-01-01

    A situated Chinese cultural festival learning system based on motion sensing is developed in this study. The primary design principle is to create a highly interactive learning environment, allowing learners to interact with Kinect through natural gestures in the designed learning situation to achieve efficient learning. The system has the…

  6. Evaluating Web-Based Learning Systems

    Science.gov (United States)

    Pergola, Teresa M.; Walters, L. Melissa

    2011-01-01

    Accounting educators continuously seek ways to effectively integrate instructional technology into accounting coursework as a means to facilitate active learning environments and address the technology-driven learning preferences of the current generation of students. Most accounting textbook publishers now provide interactive, web-based learning…

  7. 3D Game-Based Learning System for Improving Learning Achievement in Software Engineering Curriculum

    Science.gov (United States)

    Su,Chung-Ho; Cheng, Ching-Hsue

    2013-01-01

    The advancement of game-based learning has encouraged many related studies, such that students could better learn curriculum by 3-dimension virtual reality. To enhance software engineering learning, this paper develops a 3D game-based learning system to assist teaching and assess the students' motivation, satisfaction and learning achievement. A…

  8. Digital case-based learning system in school.

    Science.gov (United States)

    Gu, Peipei; Guo, Jiayang

    2017-01-01

    With the continuing growth of multi-media learning resources, it is important to offer methods helping learners to explore and acquire relevant learning information effectively. As services that organize multi-media learning materials together to support programming learning, the digital case-based learning system is needed. In order to create a case-oriented e-learning system, this paper concentrates on the digital case study of multi-media resources and learning processes with an integrated framework. An integration of multi-media resources, testing and learning strategies recommendation as the learning unit is proposed in the digital case-based learning framework. The learning mechanism of learning guidance, multi-media materials learning and testing feedback is supported in our project. An improved personalized genetic algorithm which incorporates preference information and usage degree into the crossover and mutation process is proposed to assemble the personalized test sheet for each learner. A learning strategies recommendation solution is proposed to recommend learning strategies for learners to help them to learn. The experiments are conducted to prove that the proposed approaches are capable of constructing personalized sheets and the effectiveness of the framework.

  9. Digital case-based learning system in school.

    Directory of Open Access Journals (Sweden)

    Peipei Gu

    Full Text Available With the continuing growth of multi-media learning resources, it is important to offer methods helping learners to explore and acquire relevant learning information effectively. As services that organize multi-media learning materials together to support programming learning, the digital case-based learning system is needed. In order to create a case-oriented e-learning system, this paper concentrates on the digital case study of multi-media resources and learning processes with an integrated framework. An integration of multi-media resources, testing and learning strategies recommendation as the learning unit is proposed in the digital case-based learning framework. The learning mechanism of learning guidance, multi-media materials learning and testing feedback is supported in our project. An improved personalized genetic algorithm which incorporates preference information and usage degree into the crossover and mutation process is proposed to assemble the personalized test sheet for each learner. A learning strategies recommendation solution is proposed to recommend learning strategies for learners to help them to learn. The experiments are conducted to prove that the proposed approaches are capable of constructing personalized sheets and the effectiveness of the framework.

  10. Adaptive Landmark-Based Navigation System Using Learning Techniques

    DEFF Research Database (Denmark)

    Zeidan, Bassel; Dasgupta, Sakyasingha; Wörgötter, Florentin

    2014-01-01

    The goal-directed navigational ability of animals is an essential prerequisite for them to survive. They can learn to navigate to a distal goal in a complex environment. During this long-distance navigation, they exploit environmental features, like landmarks, to guide them towards their goal. In...... hexapod robots. As a result, it allows the robots to successfully learn to navigate to distal goals in complex environments.......The goal-directed navigational ability of animals is an essential prerequisite for them to survive. They can learn to navigate to a distal goal in a complex environment. During this long-distance navigation, they exploit environmental features, like landmarks, to guide them towards their goal....... Inspired by this, we develop an adaptive landmark-based navigation system based on sequential reinforcement learning. In addition, correlation-based learning is also integrated into the system to improve learning performance. The proposed system has been applied to simulated simple wheeled and more complex...

  11. An E-learning System based on Affective Computing

    Science.gov (United States)

    Duo, Sun; Song, Lu Xue

    In recent years, e-learning as a learning system is very popular. But the current e-learning systems cannot instruct students effectively since they do not consider the emotional state in the context of instruction. The emergence of the theory about "Affective computing" can solve this question. It can make the computer's intelligence no longer be a pure cognitive one. In this paper, we construct an emotional intelligent e-learning system based on "Affective computing". A dimensional model is put forward to recognize and analyze the student's emotion state and a virtual teacher's avatar is offered to regulate student's learning psychology with consideration of teaching style based on his personality trait. A "man-to-man" learning environment is built to simulate the traditional classroom's pedagogy in the system.

  12. Personalized E- learning System Based on Intelligent Agent

    Science.gov (United States)

    Duo, Sun; Ying, Zhou Cai

    Lack of personalized learning is the key shortcoming of traditional e-Learning system. This paper analyzes the personal characters in e-Learning activity. In order to meet the personalized e-learning, a personalized e-learning system based on intelligent agent was proposed and realized in the paper. The structure of system, work process, the design of intelligent agent and the realization of intelligent agent were introduced in the paper. After the test use of the system by certain network school, we found that the system could improve the learner's initiative participation, which can provide learners with personalized knowledge service. Thus, we thought it might be a practical solution to realize self- learning and self-promotion in the lifelong education age.

  13. Applications of learning based systems at AREVA group

    International Nuclear Information System (INIS)

    Jeanmart, F.; Leclerc, C.

    2006-01-01

    As part of its work on advanced information systems, AREVA is exploring the use of computerized tools based on 'machine learning' techniques. Some of these studies are being carried out by EURIWARE - continuing on from previous work done by AREVA NC - focused on the supervision of complex systems. Systems based on machine learning techniques are one of the possible solutions being investigated by AREVA: knowing that the stakes are high and involve better anticipation and control and high financial considerations. (authors)

  14. LBS Mobile Learning System Based on Android Platform

    Directory of Open Access Journals (Sweden)

    Zhang Ya-Li

    2017-01-01

    Full Text Available In the era of mobile internet, PC-end internet services can no long satisfy people’s demands, needs for App and services on mobile phones are more urgent than ever. With increasing social competition, the concept of lifelong learning becomes more and more popular and accepted, making full use of spare time to learn at any time and any place meets updating knowledge desires of modern people, Location Based System (LBS mobile learning system based on Android platform was created under such background. In this Paper, characteristics of mobile location technology and intelligent terminal were introduced and analyzed, mobile learning system which will fulfill personalized needs of mobile learners was designed and developed on basis of location information, mobile learning can be greatly promoted and new research ideas can be expanded for mobile learning.

  15. Rule based systems for big data a machine learning approach

    CERN Document Server

    Liu, Han; Cocea, Mihaela

    2016-01-01

    The ideas introduced in this book explore the relationships among rule based systems, machine learning and big data. Rule based systems are seen as a special type of expert systems, which can be built by using expert knowledge or learning from real data. The book focuses on the development and evaluation of rule based systems in terms of accuracy, efficiency and interpretability. In particular, a unified framework for building rule based systems, which consists of the operations of rule generation, rule simplification and rule representation, is presented. Each of these operations is detailed using specific methods or techniques. In addition, this book also presents some ensemble learning frameworks for building ensemble rule based systems.

  16. Internet-based Interactive Construction Management Learning System.

    Science.gov (United States)

    Sawhney, Anil; Mund, Andre; Koczenasz, Jeremy

    2001-01-01

    Describes a way to incorporate practical content into the construction engineering and management curricula: the Internet-based Interactive Construction Management Learning System, which uses interactive and adaptive learning environments to train students in the areas of construction methods, equipment and processes using multimedia, databases,…

  17. Fixed Point Learning Based Intelligent Traffic Control System

    Science.gov (United States)

    Zongyao, Wang; Cong, Sui; Cheng, Shao

    2017-10-01

    Fixed point learning has become an important tool to analyse large scale distributed system such as urban traffic network. This paper presents a fixed point learning based intelligence traffic network control system. The system applies convergence property of fixed point theorem to optimize the traffic flow density. The intelligence traffic control system achieves maximum road resources usage by averaging traffic flow density among the traffic network. The intelligence traffic network control system is built based on decentralized structure and intelligence cooperation. No central control is needed to manage the system. The proposed system is simple, effective and feasible for practical use. The performance of the system is tested via theoretical proof and simulations. The results demonstrate that the system can effectively solve the traffic congestion problem and increase the vehicles average speed. It also proves that the system is flexible, reliable and feasible for practical use.

  18. The Office Software Learning and Examination System Design Based on Fragmented Learning Idea

    Directory of Open Access Journals (Sweden)

    Xu Ling

    2016-01-01

    Full Text Available Fragmented learning is that through the segmentation of learning content or learning time, make learners can use the fragmented time for learning fragmentated content, have the characteristics of time flexibility, learning targeted and high learning efficiency. Based on the fragmented learning ideas, combined with the teaching idea of micro class and interactive teaching, comprehensive utilization of flash animation design software, .NET development platform, VSTO technology, multimedia development technology and so on, design and develop a system integrated with learning, practice and examination of the Office software, which is not only conducive to the effective and personalized learning of students, but also conducive to the understanding the students’ situation of teachers, and liberate teachers from the heavy labor of mechanical, focus on promoting the formation of students’ knowledge system.

  19. Informed Systems: Enabling Collaborative Evidence Based Organizational Learning

    Directory of Open Access Journals (Sweden)

    Mary M. Somerville

    2015-12-01

    Full Text Available Objective – In response to unrelenting disruptions in academic publishing and higher education ecosystems, the Informed Systems approach supports evidence based professional activities to make decisions and take actions. This conceptual paper presents two core models, Informed Systems Leadership Model and Collaborative Evidence-Based Information Process Model, whereby co-workers learn to make informed decisions by identifying the decisions to be made and the information required for those decisions. This is accomplished through collaborative design and iterative evaluation of workplace systems, relationships, and practices. Over time, increasingly effective and efficient structures and processes for using information to learn further organizational renewal and advance nimble responsiveness amidst dynamically changing circumstances. Methods – The integrated Informed Systems approach to fostering persistent workplace inquiry has its genesis in three theories that together activate and enable robust information usage and organizational learning. The information- and learning-intensive theories of Peter Checkland in England, which advance systems design, stimulate participants’ appreciation during the design process of the potential for using information to learn. Within a co-designed environment, intentional social practices continue workplace learning, described by Christine Bruce in Australia as informed learning enacted through information experiences. In addition, in Japan, Ikujiro Nonaka’s theories foster information exchange processes and knowledge creation activities within and across organizational units. In combination, these theories promote the kind of learning made possible through evolving and transferable capacity to use information to learn through design and usage of collaborative communication systems with associated professional practices. Informed Systems therein draws from three antecedent theories to create an original

  20. Usability Evaluation of a Web-Based Learning System

    Science.gov (United States)

    Nguyen, Thao

    2012-01-01

    The paper proposes a contingent, learner-centred usability evaluation method and a prototype tool of such systems. This is a new usability evaluation method for web-based learning systems using a set of empirically-supported usability factors and can be done effectively with limited resources. During the evaluation process, the method allows for…

  1. Adaptive E- Learning System Based on Personalized Learning Style

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... motivation to this research is to improve the learner performance and achieve the ... valuable factor for enhancing learning process by adopting an effective .... Video. Reflective Intuitive. Primer Test. Verbal Sequential. Tutorial.

  2. The Design and Analysis of Learning Effects for a Game-based Learning System

    OpenAIRE

    Wernhuar Tarng; Weichian Tsai

    2010-01-01

    The major purpose of this study is to use network and multimedia technologies to build a game-based learning system for junior high school students to apply in learning “World Geography" through the “role-playing" game approaches. This study first investigated the motivation and habits of junior high school students to use the Internet and online games, and then designed a game-based learning system according to situated and game-based learning theories. A teaching experiment was conducted to...

  3. Review of Recommender Systems Algorithms Utilized in Social Networks based e-Learning Systems & Neutrosophic System

    Directory of Open Access Journals (Sweden)

    A. A. Salama

    2015-03-01

    Full Text Available In this paper, we present a review of different recommender system algorithms that are utilized in social networks based e-Learning systems. Future research will include our proposed our e-Learning system that utilizes Recommender System and Social Network. Since the world is full of indeterminacy, the neutrosophics found their place into contemporary research. The fundamental concepts of neutrosophic set, introduced by Smarandache in [21, 22, 23] and Salama et al. in [24-66].The purpose of this paper is to utilize a neutrosophic set to analyze social networks data conducted through learning activities.

  4. Personalised Learning Object System Based on Self-Regulated Learning Theories

    Directory of Open Access Journals (Sweden)

    Ali Alharbi

    2014-06-01

    Full Text Available Self-regulated learning has become an important construct in education research in the last few years. Selfregulated learning in its simple form is the learner’s ability to monitor and control the learning process. There is increasing research in the literature on how to support students become more self-regulated learners. However, the advancement in the information technology has led to paradigm changes in the design and development of educational content. The concept of learning object instructional technology has emerged as a result of this shift in educational technology paradigms. This paper presents the results of a study that investigated the potential educational effectiveness of a pedagogical framework based on the self-regulated learning theories to support the design of learning object systems to help computer science students. A prototype learning object system was developed based on the contemporary research on self-regulated learning. The system was educationally evaluated in a quasi-experimental study over two semesters in a core programming languages concepts course. The evaluation revealed that a learning object system that takes into consideration contemporary research on self-regulated learning can be an effective learning environment to support computer science education.

  5. The Effectiveness of the Gesture-Based Learning System (GBLS and Its Impact on Learning Experience

    Directory of Open Access Journals (Sweden)

    Moamer Ali Shakroum

    2016-06-01

    Full Text Available Several studies and experiments have been conducted in recent years to examine the value and the advantage of using the Gesture-Based Learning System (GBLS.The investigation of the influence of the GBLS mode on the learning outcomes is still scarce. Most previous studies did not address more than one category of learning outcomes (cognitive, affective outcomes, etc. at the same time when used to understand the impact of GBLS. Moreover, none of these studies considered the difference in students’ characteristics such as learning styles and spatial abilities. Therefore, a comprehensive empirical research on the impact of the GBLS mode on learning outcomes is needed. The purpose of this paper is to fill in the gap and to investigate the effectiveness of the GBLS mode on learning using Technology Mediated Learning (TML models. This study revealed that the GBLS mode has greater positive impact on students’ learning outcomes (cognitive and affective outcomes when compared with other two learning modes that are classified as Computer Simulation Software Learning (CSSL mode and conventional learning mode. In addition, this study also found that the GBLS mode is capable of serving all students with different learning styles and spatial ability levels. The results of this study revealed that the GBLS mode outperformed the existing learning methods by providing a unique learning experience that considers the differences between students. The results have also shown that the Kinect user interface can create an interactive and an enjoyable learning experience.

  6. Estimating Students’ Satisfaction with Web Based Learning System in Blended Learning Environment

    Directory of Open Access Journals (Sweden)

    Sanja Bauk

    2014-01-01

    Full Text Available Blended learning became the most popular educational model that universities apply for teaching and learning. This model combines online and face-to-face learning environments, in order to enhance learning with implementation of new web technologies and tools in learning process. In this paper principles of DeLone and Mclean success model for information system are applied to Kano two-dimensional model, for categorizing quality attributes related to satisfaction of students with web based learning system used in blended learning model. Survey results are obtained among the students at “Mediterranean” University in Montenegro. The (dysfunctional dimensions of Kano model, including Kano basic matrix for assessment of the degree of students’ satisfaction level, have been considered in some more detail through corresponding numerical, graphical, and statistical analysis.

  7. Recommendation System Based On Association Rules For Distributed E-Learning Management Systems

    Science.gov (United States)

    Mihai, Gabroveanu

    2015-09-01

    Traditional Learning Management Systems are installed on a single server where learning materials and user data are kept. To increase its performance, the Learning Management System can be installed on multiple servers; learning materials and user data could be distributed across these servers obtaining a Distributed Learning Management System. In this paper is proposed the prototype of a recommendation system based on association rules for Distributed Learning Management System. Information from LMS databases is analyzed using distributed data mining algorithms in order to extract the association rules. Then the extracted rules are used as inference rules to provide personalized recommendations. The quality of provided recommendations is improved because the rules used to make the inferences are more accurate, since these rules aggregate knowledge from all e-Learning systems included in Distributed Learning Management System.

  8. Machine Learning-based Intelligent Formal Reasoning and Proving System

    Science.gov (United States)

    Chen, Shengqing; Huang, Xiaojian; Fang, Jiaze; Liang, Jia

    2018-03-01

    The reasoning system can be used in many fields. How to improve reasoning efficiency is the core of the design of system. Through the formal description of formal proof and the regular matching algorithm, after introducing the machine learning algorithm, the system of intelligent formal reasoning and verification has high efficiency. The experimental results show that the system can verify the correctness of propositional logic reasoning and reuse the propositional logical reasoning results, so as to obtain the implicit knowledge in the knowledge base and provide the basic reasoning model for the construction of intelligent system.

  9. The use of a mobile assistant learning system for health education based on project-based learning.

    Science.gov (United States)

    Wu, Ting-Ting

    2014-10-01

    With the development of mobile devices and wireless technology, mobile technology has gradually infiltrated nursing practice courses to facilitate instruction. Mobile devices save manpower and reduce errors while enhancing nursing students' professional knowledge and skills. To achieve teaching objectives and address the drawbacks of traditional education, this study presents a mobile assistant learning system to help nursing students prepare health education materials. The proposed system is based on a project-based learning strategy to assist nursing students with internalizing professional knowledge and developing critical thinking skills. Experimental results show that the proposed mobile system and project-based learning strategy can promote learning effectiveness and efficiency. Most nursing students and nursing educators showed positive attitudes toward this mobile learning system and looked forward to using it again in related courses in the future.

  10. An Android malware detection system based on machine learning

    Science.gov (United States)

    Wen, Long; Yu, Haiyang

    2017-08-01

    The Android smartphone, with its open source character and excellent performance, has attracted many users. However, the convenience of the Android platform also has motivated the development of malware. The traditional method which detects the malware based on the signature is unable to detect unknown applications. The article proposes a machine learning-based lightweight system that is capable of identifying malware on Android devices. In this system we extract features based on the static analysis and the dynamitic analysis, then a new feature selection approach based on principle component analysis (PCA) and relief are presented in the article to decrease the dimensions of the features. After that, a model will be constructed with support vector machine (SVM) for classification. Experimental results show that our system provides an effective method in Android malware detection.

  11. A Parametric Learning and Identification Based Robust Iterative Learning Control for Time Varying Delay Systems

    Directory of Open Access Journals (Sweden)

    Lun Zhai

    2014-01-01

    Full Text Available A parametric learning based robust iterative learning control (ILC scheme is applied to the time varying delay multiple-input and multiple-output (MIMO linear systems. The convergence conditions are derived by using the H∞ and linear matrix inequality (LMI approaches, and the convergence speed is analyzed as well. A practical identification strategy is applied to optimize the learning laws and to improve the robustness and performance of the control system. Numerical simulations are illustrated to validate the above concepts.

  12. A deep-learning-based emergency alert system

    Directory of Open Access Journals (Sweden)

    Byungseok Kang

    2016-06-01

    Full Text Available Emergency alert systems serve as a critical link in the chain of crisis communication, and they are essential to minimize loss during emergencies. Acts of terrorism and violence, chemical spills, amber alerts, nuclear facility problems, weather-related emergencies, flu pandemics, and other emergencies all require those responsible such as government officials, building managers, and university administrators to be able to quickly and reliably distribute emergency information to the public. This paper presents our design of a deep-learning-based emergency warning system. The proposed system is considered suitable for application in existing infrastructure such as closed-circuit television and other monitoring devices. The experimental results show that in most cases, our system immediately detects emergencies such as car accidents and natural disasters.

  13. Genetic learning in rule-based and neural systems

    Science.gov (United States)

    Smith, Robert E.

    1993-01-01

    The design of neural networks and fuzzy systems can involve complex, nonlinear, and ill-conditioned optimization problems. Often, traditional optimization schemes are inadequate or inapplicable for such tasks. Genetic Algorithms (GA's) are a class of optimization procedures whose mechanics are based on those of natural genetics. Mathematical arguments show how GAs bring substantial computational leverage to search problems, without requiring the mathematical characteristics often necessary for traditional optimization schemes (e.g., modality, continuity, availability of derivative information, etc.). GA's have proven effective in a variety of search tasks that arise in neural networks and fuzzy systems. This presentation begins by introducing the mechanism and theoretical underpinnings of GA's. GA's are then related to a class of rule-based machine learning systems called learning classifier systems (LCS's). An LCS implements a low-level production-system that uses a GA as its primary rule discovery mechanism. This presentation illustrates how, despite its rule-based framework, an LCS can be thought of as a competitive neural network. Neural network simulator code for an LCS is presented. In this context, the GA is doing more than optimizing and objective function. It is searching for an ecology of hidden nodes with limited connectivity. The GA attempts to evolve this ecology such that effective neural network performance results. The GA is particularly well adapted to this task, given its naturally-inspired basis. The LCS/neural network analogy extends itself to other, more traditional neural networks. Conclusions to the presentation discuss the implications of using GA's in ecological search problems that arise in neural and fuzzy systems.

  14. Natural Interaction Based Online Military Boxing Learning System

    Science.gov (United States)

    Yang, Chenglei; Wang, Lu; Sun, Bing; Yin, Xu; Wang, Xiaoting; Liu, Li; Lu, Lin

    2013-01-01

    Military boxing, a kind of Chinese martial arts, is widespread and health beneficial. In this paper, the authors introduce a military boxing learning system realized by 3D motion capture, Web3D and 3D interactive technologies. The interactions with the system are natural and intuitive. Users can observe and learn the details of each action of the…

  15. A Web-Based Learning System for Software Test Professionals

    Science.gov (United States)

    Wang, Minhong; Jia, Haiyang; Sugumaran, V.; Ran, Weijia; Liao, Jian

    2011-01-01

    Fierce competition, globalization, and technology innovation have forced software companies to search for new ways to improve competitive advantage. Web-based learning is increasingly being used by software companies as an emergent approach for enhancing the skills of knowledge workers. However, the current practice of Web-based learning is…

  16. A service based adaptive U-learning system using UX.

    Science.gov (United States)

    Jeong, Hwa-Young; Yi, Gangman

    2014-01-01

    In recent years, traditional development techniques for e-learning systems have been changing to become more convenient and efficient. One new technology in the development of application systems includes both cloud and ubiquitous computing. Cloud computing can support learning system processes by using services while ubiquitous computing can provide system operation and management via a high performance technical process and network. In the cloud computing environment, a learning service application can provide a business module or process to the user via the internet. This research focuses on providing the learning material and processes of courses by learning units using the services in a ubiquitous computing environment. And we also investigate functions that support users' tailored materials according to their learning style. That is, we analyzed the user's data and their characteristics in accordance with their user experience. We subsequently applied the learning process to fit on their learning performance and preferences. Finally, we demonstrate how the proposed system outperforms learning effects to learners better than existing techniques.

  17. A Service Based Adaptive U-Learning System Using UX

    Directory of Open Access Journals (Sweden)

    Hwa-Young Jeong

    2014-01-01

    Full Text Available In recent years, traditional development techniques for e-learning systems have been changing to become more convenient and efficient. One new technology in the development of application systems includes both cloud and ubiquitous computing. Cloud computing can support learning system processes by using services while ubiquitous computing can provide system operation and management via a high performance technical process and network. In the cloud computing environment, a learning service application can provide a business module or process to the user via the internet. This research focuses on providing the learning material and processes of courses by learning units using the services in a ubiquitous computing environment. And we also investigate functions that support users’ tailored materials according to their learning style. That is, we analyzed the user’s data and their characteristics in accordance with their user experience. We subsequently applied the learning process to fit on their learning performance and preferences. Finally, we demonstrate how the proposed system outperforms learning effects to learners better than existing techniques.

  18. Developing a Mobile Learning Management System for Outdoors Nature Science Activities Based on 5E Learning Cycle

    Science.gov (United States)

    Lai, Ah-Fur; Lai, Horng-Yih; Chuang, Wei-Hsiang; Wu, Zih-Heng

    2015-01-01

    Traditional outdoor learning activities such as inquiry-based learning in nature science encounter many dilemmas. Due to prompt development of mobile computing and widespread of mobile devices, mobile learning becomes a big trend on education. The main purpose of this study is to develop a mobile-learning management system for overcoming the…

  19. Paired-Associate and Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems

    OpenAIRE

    Li, Kaiyun; Fu, Qiufang; Sun, Xunwei; Zhou, Xiaoyan; Fu, Xiaolan

    2016-01-01

    It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed...

  20. An Adaptive E-Learning System Based on Students' Learning Styles: An Empirical Study

    Science.gov (United States)

    Drissi, Samia; Amirat, Abdelkrim

    2016-01-01

    Personalized e-learning implementation is recognized as one of the most interesting research areas in the distance web-based education. Since the learning style of each learner is different one must fit e-learning with the different needs of learners. This paper presents an approach to integrate learning styles into adaptive e-learning hypermedia.…

  1. The Effect of Incorporating Good Learners' Ratings in e-Learning Content-Based Recommender System

    Science.gov (United States)

    Ghauth, Khairil Imran; Abdullah, Nor Aniza

    2011-01-01

    One of the anticipated challenges of today's e-learning is to solve the problem of recommending from a large number of learning materials. In this study, we introduce a novel architecture for an e-learning recommender system. More specifically, this paper comprises the following phases i) to propose an e-learning recommender system based on…

  2. Exploring nursing e-learning systems success based on information system success model.

    Science.gov (United States)

    Chang, Hui-Chuan; Liu, Chung-Feng; Hwang, Hsin-Ginn

    2011-12-01

    E-learning is thought of as an innovative approach to enhance nurses' care service knowledge. Extensive research has provided rich information toward system development, courses design, and nurses' satisfaction with an e-learning system. However, a comprehensive view in understanding nursing e-learning system success is an important but less focused-on topic. The purpose of this research was to explore net benefits of nursing e-learning systems based on the updated DeLone and McLean's Information System Success Model. The study used a self-administered questionnaire to collected 208 valid nurses' responses from 21 of Taiwan's medium- and large-scale hospitals that have implemented nursing e-learning systems. The result confirms that the model is sufficient to explore the nurses' use of e-learning systems in terms of intention to use, user satisfaction, and net benefits. However, while the three exogenous quality factors (system quality, information quality, and service quality) were all found to be critical factors affecting user satisfaction, only information quality showed a direct effect on the intention to use. This study provides useful insights for evaluating nursing e-learning system qualities as well as an understanding of nurses' intentions and satisfaction related to performance benefits.

  3. An Augmented Reality-Based Mobile Learning System to Improve Students' Learning Achievements and Motivations in Natural Science Inquiry Activities

    Science.gov (United States)

    Chiang, Tosti H. C.; Yang, Stephen J. H.; Hwang, Gwo-Jen

    2014-01-01

    In this study, an augmented reality-based mobile learning system is proposed for conducting inquiry-based learning activities. An experiment has been conducted to examine the effectiveness of the proposed approach in terms of learning achievements and motivations. The subjects were 57 fourth graders from two classes taught by the same teacher in…

  4. A Distance Instructional System with Learning Performance Evaluation Mechanism: Moodle-Based Educational System Design

    Science.gov (United States)

    Lee, Ying-Chen; Terashima, Nobuyoshi

    2012-01-01

    In this paper, a Moodle-based educational system has been constructed by providing friendly interface to fit most students in e-learning. For the website implementation, the authors take the course "Multimedia Implementation Using JAVA" as a case study. From the modified Moodle-based educational system, the browsing time of each web page for…

  5. Deep learning-based Diabetic Retinopathy assessment on embedded system.

    Science.gov (United States)

    Ardiyanto, Igi; Nugroho, Hanung Adi; Buana, Ratna Lestari Budiani

    2017-07-01

    Diabetic Retinopathy (DR) is a disease which affect the vision ability. The observation by an ophthalmologist usually conducted by analyzing the retinal images of the patient which are marked by some DR features. However some misdiagnosis are usually found due to human error. Here, a deep learning-based low-cost embedded system is established to assist the doctor for grading the severity of the DR from the retinal images. A compact deep learning algorithm named Deep-DR-Net which fits on a small embedded board is afterwards proposed for such purposes. In the heart of Deep-DR-Net, a cascaded encoder-classifier network is arranged using residual style for ensuring the small model size. The usage of different types of convolutional layers subsequently guarantees the features richness of the network for differentiating the grade of the DR. Experimental results show the capability of the proposed system for detecting the existence as well as grading the severity of the DR symptomps.

  6. An Empirical Study of Instructor Adoption of Web-Based Learning Systems

    Science.gov (United States)

    Wang, Wei-Tsong; Wang, Chun-Chieh

    2009-01-01

    For years, web-based learning systems have been widely employed in both educational and non-educational institutions. Although web-based learning systems are emerging as a useful tool for facilitating teaching and learning activities, the number of users is not increasing as fast as expected. This study develops an integrated model of instructor…

  7. SVM and PCA Based Learning Feature Classification Approaches for E-Learning System

    Science.gov (United States)

    Khamparia, Aditya; Pandey, Babita

    2018-01-01

    E-learning and online education has made great improvements in the recent past. It has shifted the teaching paradigm from conventional classroom learning to dynamic web based learning. Due to this, a dynamic learning material has been delivered to learners, instead ofstatic content, according to their skills, needs and preferences. In this…

  8. A Lecture Supporting System Based on Real-Time Learning Analytics

    Science.gov (United States)

    Shimada, Atsushi; Konomi, Shin'ichi

    2017-01-01

    A new lecture supporting system based on real-time learning analytics is proposed. Our target is on-site classrooms where teachers give their lectures, and a lot of students listen to teachers' explanation, conduct exercises etc. We utilize not only an e-Learning system, but also an e-Book system to collect real-time learning activities during the…

  9. Model of Recommendation System for for Indexing and Retrieving the Learning Object based on Multiagent System

    Directory of Open Access Journals (Sweden)

    Ronaldo Lima Rocha Campos

    2012-07-01

    Full Text Available This paper proposes a multiagent system application model for indexing, retrieving and recommendation learning objects stored in different and heterogeneous repositories. The objects within these repositories are described by filled fields using different metadata standards. The searching mechanism covers several different learning object repositories and the same object can be described in these repositories by the use of different types of fields. Aiming to improve accuracy and coverage in terms of recovering a learning object and improve the signification of the results we propose an information retrieval model based on the multiagent system approach and an ontological model to describe the knowledge domain covered.

  10. Designing an Adaptive Web-Based Learning System Based on Students' Cognitive Styles Identified Online

    Science.gov (United States)

    Lo, Jia-Jiunn; Chan, Ya-Chen; Yeh, Shiou-Wen

    2012-01-01

    This study developed an adaptive web-based learning system focusing on students' cognitive styles. The system is composed of a student model and an adaptation model. It collected students' browsing behaviors to update the student model for unobtrusively identifying student cognitive styles through a multi-layer feed-forward neural network (MLFF).…

  11. A Coupled User Clustering Algorithm Based on Mixed Data for Web-Based Learning Systems

    Directory of Open Access Journals (Sweden)

    Ke Niu

    2015-01-01

    Full Text Available In traditional Web-based learning systems, due to insufficient learning behaviors analysis and personalized study guides, a few user clustering algorithms are introduced. While analyzing the behaviors with these algorithms, researchers generally focus on continuous data but easily neglect discrete data, each of which is generated from online learning actions. Moreover, there are implicit coupled interactions among the data but are frequently ignored in the introduced algorithms. Therefore, a mass of significant information which can positively affect clustering accuracy is neglected. To solve the above issues, we proposed a coupled user clustering algorithm for Wed-based learning systems by taking into account both discrete and continuous data, as well as intracoupled and intercoupled interactions of the data. The experiment result in this paper demonstrates the outperformance of the proposed algorithm.

  12. Interactive and collaborative learning in the classroom at the medical school Automated response systems and team-based learning.

    Science.gov (United States)

    Nasr, Rihab; Antoun, Jumana; Sabra, Ramzi; Zgheib, Nathalie K

    2016-01-01

    There has been a pedagogic shift in higher education from the traditional teacher centered to the student centered approach in teaching, necessitating a change in the role of the teacher from a supplier of information to passive receptive students into a more facilitative role. Active learning activities are based on various learning theories such as self-directed learning, cooperative learning and adult learning. There exist many instructional activities that enhance active and collaborative learning. The aim of this manuscript is to describe two methods of interactive and collaborative learning in the classroom, automated response systems (ARS) and team-based learning (TBL), and to list some of their applications and advantages. The success of these innovative teaching and learning methods at a large scale depends on few elements, probably the most important of which is the support of the higher administration and leadership in addition to the availability of “champions” who are committed to lead the change.

  13. A Game Based e-Learning System to Teach Artificial Intelligence in the Computer Sciences Degree

    Science.gov (United States)

    de Castro-Santos, Amable; Fajardo, Waldo; Molina-Solana, Miguel

    2017-01-01

    Our students taking the Artificial Intelligence and Knowledge Engineering courses often encounter a large number of problems to solve which are not directly related to the subject to be learned. To solve this problem, we have developed a game based e-learning system. The elected game, that has been implemented as an e-learning system, allows to…

  14. Adding Learning to Knowledge-Based Systems: Taking the "Artificial" Out of AI

    Science.gov (United States)

    Daniel L. Schmoldt

    1997-01-01

    Both, knowledge-based systems (KBS) development and maintenance require time-consuming analysis of domain knowledge. Where example cases exist, KBS can be built, and later updated, by incorporating learning capabilities into their architecture. This applies to both supervised and unsupervised learning scenarios. In this paper, the important issues for learning systems-...

  15. Content Classification and Context-Based Retrieval System for E-Learning

    Science.gov (United States)

    Mittal, Ankush; Krishnan, Pagalthivarthi V.; Altman, Edward

    2006-01-01

    A recent focus in web based learning systems has been the development of reusable learning materials that can be delivered as personalized courses depending of a number of factors such as the user's background, his/her learning preferences, current knowledge based on previous assessments, or previous browsing patterns. The student is often…

  16. Feedback authoring possibilities in web-based learning systems

    NARCIS (Netherlands)

    Vasilyeva, E.; De Bra, P.M.E.; Pechenizkiy, M.; Bonk, C.J.; et al., xx

    2008-01-01

    This paper surveys and analyses the feedback authoring possibilities in online assessment modules of the most popular Learning Management Systems (LMS) including Moodle, Sakai, and Blackboard. We consider the problem of authoring and support of tailored and personalized feedback and demonstrate how

  17. Project-Based Learning to Enhance Teaching Embedded Systems

    Science.gov (United States)

    Sababha, Belal H.; Alqudah, Yazan A.; Abualbasal, Abdelraheem; AlQaralleh, Esam A.

    2016-01-01

    Exposing engineering students during their education to real-world problems and giving them the chance to apply what they learn in the classroom is a vital element of engineering education. The Embedded Systems course at Princess Sumaya University for Technology (PSUT) is one of the main courses that bridge the gap between theoretical electrical…

  18. Mobile Learning Environment System (MLES): The Case of Android-based Learning Application on Undergraduates' Learning

    OpenAIRE

    Hanafi, Hafizul Fahri; Samsudin, Khairulanuar

    2012-01-01

    Of late, mobile technology has introduced new, novel environment that can be capitalized to further enrich the teaching and learning process in classrooms. Taking cognizance of this promising setting, a study was undertaken to investigate the impact of such an environment enabled by android platform on the learning process among undergraduates of Sultan Idris Education University, Malaysia; in particular, this paper discusses critical aspects of the design and implementation of the android le...

  19. Students' perception towards the problem based learning tutorial session in a system-based hybrid curriculum.

    Science.gov (United States)

    Al-Drees, Abdulmajeed A; Khalil, Mahmoud S; Irshad, Mohammad; Abdulghani, Hamza M

    2015-03-01

    To evaluate students' perception towards the problem based learning (PBL) session in a system-based hybrid curriculum. We conducted a cross-sectional study in the College of Medicine, King Saud University, Saudi Arabia at the end of the 2012-2013 academic year. The survey questionnaire was self-administered, and examined perceptions of PBL session benefits, appropriate running of sessions, and tutor's roles. Out of 510 students, 275 (53.9%) completed the questionnaire. Most of the students reported that PBL sessions were helpful in understanding basic sciences concepts (p=0.04). In addition, they agreed that PBL sessions increased their knowledge of basic sciences (p=0.01). Most students reported that PBL sessions encouraged self-directed learning, collaborative learning, and improved decision making skills. However, 54.5% of students reported lack of proper training before starting the PBL sessions, and only 25.1% of students agreed that the teaching staff are well prepared to run the sessions. Most students used the internet (93.1%), lecture notes (76.7%), and books (64.4%) as learning resources. Most students reported repetition of topics between PBL sessions and lectures (p=0.07). The study highlighted the significant role of PBL in a system-based hybrid curriculum and helped students improve their knowledge and different learning skills. Students and staff training is required before the utilizing the PBL as an instructional method.

  20. Virk: An Active Learning-based System for Bootstrapping Knowledge Base Development in the Neurosciences

    Directory of Open Access Journals (Sweden)

    Kyle H. Ambert

    2013-12-01

    Full Text Available The frequency and volume of newly-published scientific literature is quickly making manual maintenance of publicly-available databases of primary data unrealistic and costly. Although machine learning can be useful for developing automated approaches to identifying scientific publications containing relevant information for a database, developing such tools necessitates manually annotating an unrealistic number of documents. One approach to this problem, active learning, builds classification models by iteratively identifying documents that provide the most information to a classifier. Although this approach has been shown to be effective for related problems, in the context of scientific databases curation, it falls short. We present Virk, an active learning system that, while being trained, simultaneously learns a classification model and identifies documents having information of interest for a knowledge base. Our approach uses a support vector machine classifier with input features derived from neuroscience-related publications from the primary literature. Using our approach, we were able to increase the size of the Neuron Registry, a knowledge base of neuron-related information, by a factor of 90%, a knowledge base of neuron-related information, in 3 months. Using standard biocuration methods, it would have taken between 1-2 years to make the same number of contributions to the Neuron Registry. Here, we describe the system pipeline in detail, and evaluate its performance against other approaches to sampling in active learning.

  1. The Conceptual Mechanism for Viable Organizational Learning Based on Complex System Theory and the Viable System Model

    Science.gov (United States)

    Sung, Dia; You, Yeongmahn; Song, Ji Hoon

    2008-01-01

    The purpose of this research is to explore the possibility of viable learning organizations based on identifying viable organizational learning mechanisms. Two theoretical foundations, complex system theory and viable system theory, have been integrated to provide the rationale for building the sustainable organizational learning mechanism. The…

  2. The Construction of an Online Competitive Game-Based Learning System for Junior High School Students

    Science.gov (United States)

    Cheng, Yuh-Ming; Kuo, Sheng-Huang; Lou, Shi-Jer; Shih, Ru-Chu

    2012-01-01

    The purpose of this study aimed to construct an online competitive game-based learning system by using freeware for junior high school students and to assess its effectiveness. From the learning standpoints, game mechanisms including learning points, competition mechanism, training room mechanism, questioning & answering mechanism, tips, and…

  3. Effective Trust-Aware E-learning Recommender System Based on Learning Styles and Knowledge Levels

    Science.gov (United States)

    Dwivedi, Pragya; Bharadwaj, Kamal K.

    2013-01-01

    In the age of information explosion, e-learning recommender systems (ELRSs) have emerged as the most essential tool to deliver personalized learning resources to learners. Due to enormous amount of information on the web, learner faces problem in searching right information. ELRSs deal with the problem of information overload effectively and…

  4. Acceptance of Competency-Based Workplace e-Learning Systems: Effects of Individual and Peer Learning Support

    Science.gov (United States)

    Cheng, Bo; Wang, Minhong; Yang, Stephen J. H.; Kinshuk; Peng, Jun

    2011-01-01

    Current endeavors to integrate competency-based learning approaches with e-learning systems designed for delivery of training to adult learners in the workplace are growing. However, academic efforts in examining learners' perceptions of, and reactions toward, this technology-delivered pedagogical innovation are limited. Drawing together…

  5. E-Learning and Personalized Learning Path: A Proposal Based on the Adaptive Educational Hypermedia System

    Directory of Open Access Journals (Sweden)

    Francesco Colace

    2014-03-01

    Full Text Available The E-Learning is becoming an effective approach for the improving of quality of learning. Many institutions are adopting this approach both to improve their traditional courses both to increase the potential audience. In the last period great attention is paid in the introduction of methodologies and techniques for the adaptation of learning process to the real needs of students. In this scenario the Adaptive Educational Hypermedia System can be an effective approach. Adaptive hypermedia is a promising area of research at the crossroads of hypermedia and adaptive systems. One of the most important fields where this approach can be applied is just the e-Learning. In this context the adaptive learning resources selection and sequencing is recognized as among one of the most interesting research questions. An Adaptive Educational Hypermedia System is composed by services for the management of the Knowledge Space, the definition of a User Model, the observation of student during his learning period and, as previously said, the adaptation of the learning path according to the real needs of the students. In particular the use of ontologyཿs formalism for the modeling of the ཿknowledge space࿝ related to the course can increase the sharable of learning objects among similar courses or better contextualize their role in the course. This paper addresses the design problem of an Adaptive hypermedia system by the definition of methodologies able to manage each its components, In particular an original user, learning contents, tracking strategies and adaptation model are developed. The proposed Adaptive Educational Hypermedia System has been integrated in an e-Learning platform and an experimental campaign has been conducted. In particular the proposed approach has been introduced in three different blended courses. A comparison with traditional approach has been described and the obtained results seem to be very promising.

  6. E-Learning System Overview Based on Semantic Web

    Science.gov (United States)

    Alsultanny, Yas A.

    2006-01-01

    The challenge of the semantic web is the provision of distributed information with well-defined meaning, understandable for different parties. e-Learning is efficient task relevant and just-in-time learning grown from the learning requirements of the new dynamically changing, distributed business world. In this paper we design an e-Learning system…

  7. Location Based Services for Outdoor Ecological Learning System: Design and Implementation

    Science.gov (United States)

    Hsiao, Hsien-Sheng; Lin, Chih-Cheng; Feng, Ruei-Ting; Li, Kun Jing

    2010-01-01

    This paper aimed to demonstrate how location-based services were implemented in ubiquitous outdoor ecological learning system. In an elementary school in northern Taiwan, two fifth grade classes on an ecology project were randomly selected: The experimental group could access the ecological learning system on hand-held devices while the control…

  8. Course Ontology-Based User's Knowledge Requirement Acquisition from Behaviors within E-Learning Systems

    Science.gov (United States)

    Zeng, Qingtian; Zhao, Zhongying; Liang, Yongquan

    2009-01-01

    User's knowledge requirement acquisition and analysis are very important for a personalized or user-adaptive learning system. Two approaches to capture user's knowledge requirement about course content within an e-learning system are proposed and implemented in this paper. The first approach is based on the historical data accumulated by an…

  9. A Project-Based Laboratory for Learning Embedded System Design with Industry Support

    Science.gov (United States)

    Lee, Chyi-Shyong; Su, Juing-Huei; Lin, Kuo-En; Chang, Jia-Hao; Lin, Gu-Hong

    2010-01-01

    A project-based laboratory for learning embedded system design with support from industry is presented in this paper. The aim of this laboratory is to motivate students to learn the building blocks of embedded systems and practical control algorithms by constructing a line-following robot using the quadratic interpolation technique to predict the…

  10. E-Learning System Using Segmentation-Based MR Technique for Learning Circuit Construction

    Science.gov (United States)

    Takemura, Atsushi

    2016-01-01

    This paper proposes a novel e-Learning system using the mixed reality (MR) technique for technical experiments involving the construction of electronic circuits. The proposed system comprises experimenters' mobile computers and a remote analysis system. When constructing circuits, each learner uses a mobile computer to transmit image data from the…

  11. Development and Evaluation of Mechatronics Learning System in a Web-Based Environment

    Science.gov (United States)

    Shyr, Wen-Jye

    2011-01-01

    The development of remote laboratory suitable for the reinforcement of undergraduate level teaching of mechatronics is important. For the reason, a Web-based mechatronics learning system, called the RECOLAB (REmote COntrol LABoratory), for remote learning in engineering education has been developed in this study. The web-based environment is an…

  12. Recent Trends in Minicomputer-Based Integrated Learning Systems for Reading and Language Arts Instruction.

    Science.gov (United States)

    Balajthy, Ernest

    This paper discusses minicomputer-based ILSs (integrated learning systems), i.e., computer-based systems of hardware and software. An example of a minicomputer-based system in a school district (a composite of several actual districts) considers hardware, staffing, scheduling, reactions, problems, and training for a subskill-oriented reading…

  13. Using Knowledge-Based Systems to Support Learning of Organizational Knowledge: A Case Study

    Science.gov (United States)

    Cooper, Lynne P.; Nash, Rebecca L.; Phan, Tu-Anh T.; Bailey, Teresa R.

    2003-01-01

    This paper describes the deployment of a knowledge system to support learning of organizational knowledge at the Jet Propulsion Laboratory (JPL), a US national research laboratory whose mission is planetary exploration and to 'do what no one has done before.' Data collected over 19 weeks of operation were used to assess system performance with respect to design considerations, participation, effectiveness of communication mechanisms, and individual-based learning. These results are discussed in the context of organizational learning research and implications for practice.

  14. On Logical Characterisation of Human Concept Learning based on Terminological Systems

    DEFF Research Database (Denmark)

    Badie, Farshad

    2018-01-01

    The central focus of this article is the epistemological assumption that knowledge could be generated based on human beings' experiences and over their conceptions of the world. Logical characterisation of human inductive learning over their produced conceptions within terminological systems and ...... and analysis of actual human inductive reasoning (and learning). This research connects with the topics 'logic & learning', 'cognitive modelling' and 'terminological knowledge representation'.......The central focus of this article is the epistemological assumption that knowledge could be generated based on human beings' experiences and over their conceptions of the world. Logical characterisation of human inductive learning over their produced conceptions within terminological systems...

  15. The Establishment of an e-Learning System Based on SDT

    Directory of Open Access Journals (Sweden)

    Mihyang Bang

    2014-06-01

    Full Text Available This study established an elementary-school English e-learning system on the basis of theory-based motivation strategies, and verified the effectiveness of the motivation strategies through educational practice and the applicability of traditional motivation theories in e-learning environments. Six motivation strategies were deducted, two from each of the three psychological needs (Autonomy, Competence, Relatedness presupposed as preconditions that increase human motivation based on the Self-Determination Theory. Next, the e-learning system intended to increase intrinsic motivation for English learning was established based on the motivation strategies. Then, this system was used for year-long educational practice in 115 private educational institutes nationwide. Finally, a survey was conducted with 2,300 students to determine whether the e-learning system applying the motivation strategies satisfied the three psychological needs of elementary-school English learners, and whether it improved intrinsic motivation for English studies. Moreover, this study analysed the correlation among motivation strategies, three psychological needs, and five motivation groups. The results revealed that the motivation strategies applied to the e-learning system had a significant influence on the three psychological needs, and those needs had a significant influence on the five motivation groups. This proved the effectiveness of motivation strategies applied to the e-learning system. It was found that SDT, the traditional motivation theory that has been applied to face-to-face classes, is also effective in the e-learning environment. Finally, even in the e-learning environment focusing on individual learning, learners were found to value relationships with others, in addition to competence, which has been studied relatively often in the past. The significance of this study is that it established a theory-based e-learning system and that it is an empirical study

  16. Multi-viewpoint Smartphone AR-based Learning System for Solar Movement Observations

    Directory of Open Access Journals (Sweden)

    Ke Tian

    2014-06-01

    Full Text Available Understanding solar movement (e.g., solar diurnal motion is difficult for those are beginning to learn about astronomy. Previous research has revealed that observation-based learning can help make astronomical phenomena clearer to understand for such learners. In this research, Smartphone Augmented Reality (AR technology and 3D content were used to develop a multi-viewpoint Smartphone AR-based learning system (M-VSARLS for solar movement observations that can be used in the real-world environment. The goal of this research is to assess the usefulness of the system, usability of the AR function and 3D content, and the overall effect of the system on the learner’s motivation through task-based experiments with follow-up questionnaires. The results show that the M-VSARL system is effective in improving the observational skills and learning ability of learners, and in enhancing their motivation to learn about solar movement.

  17. Web based Interactive 3D Learning Objects for Learning Management Systems

    Directory of Open Access Journals (Sweden)

    Stefan Hesse

    2012-02-01

    Full Text Available In this paper, we present an approach to create and integrate interactive 3D learning objects of high quality for higher education into a learning management system. The use of these resources allows to visualize topics, such as electro-technical and physical processes in the interior of complex devices. This paper addresses the challenge of combining rich interactivity and adequate realism with 3D exercise material for distance elearning.

  18. Adaptation Provisioning with Respect to Learning Styles in a Web-Based Educational System: An Experimental Study

    Science.gov (United States)

    Popescu, E.

    2010-01-01

    Personalized instruction is seen as a desideratum of today's e-learning systems. The focus of this paper is on those platforms that use learning styles as personalization criterion called learning style-based adaptive educational systems. The paper presents an innovative approach based on an integrative set of learning preferences that alleviates…

  19. A self-learning rule base for command following in dynamical systems

    Science.gov (United States)

    Tsai, Wei K.; Lee, Hon-Mun; Parlos, Alexander

    1992-01-01

    In this paper, a self-learning Rule Base for command following in dynamical systems is presented. The learning is accomplished though reinforcement learning using an associative memory called SAM. The main advantage of SAM is that it is a function approximator with explicit storage of training samples. A learning algorithm patterned after the dynamic programming is proposed. Two artificially created, unstable dynamical systems are used for testing, and the Rule Base was used to generate a feedback control to improve the command following ability of the otherwise uncontrolled systems. The numerical results are very encouraging. The controlled systems exhibit a more stable behavior and a better capability to follow reference commands. The rules resulting from the reinforcement learning are explicitly stored and they can be modified or augmented by human experts. Due to overlapping storage scheme of SAM, the stored rules are similar to fuzzy rules.

  20. A New Profile Learning Model for Recommendation System based on Machine Learning Technique

    Directory of Open Access Journals (Sweden)

    Shereen H. Ali

    2016-03-01

    Full Text Available Recommender systems (RSs have been used to successfully address the information overload problem by providing personalized and targeted recommendations to the end users. RSs are software tools and techniques providing suggestions for items to be of use to a user, hence, they typically apply techniques and methodologies from Data Mining. The main contribution of this paper is to introduce a new user profile learning model to promote the recommendation accuracy of vertical recommendation systems. The proposed profile learning model employs the vertical classifier that has been used in multi classification module of the Intelligent Adaptive Vertical Recommendation (IAVR system to discover the user’s area of interest, and then build the user’s profile accordingly. Experimental results have proven the effectiveness of the proposed profile learning model, which accordingly will promote the recommendation accuracy.

  1. Strategies for adding adaptive learning mechanisms to rule-based diagnostic expert systems

    Science.gov (United States)

    Stclair, D. C.; Sabharwal, C. L.; Bond, W. E.; Hacke, Keith

    1988-01-01

    Rule-based diagnostic expert systems can be used to perform many of the diagnostic chores necessary in today's complex space systems. These expert systems typically take a set of symptoms as input and produce diagnostic advice as output. The primary objective of such expert systems is to provide accurate and comprehensive advice which can be used to help return the space system in question to nominal operation. The development and maintenance of diagnostic expert systems is time and labor intensive since the services of both knowledge engineer(s) and domain expert(s) are required. The use of adaptive learning mechanisms to increment evaluate and refine rules promises to reduce both time and labor costs associated with such systems. This paper describes the basic adaptive learning mechanisms of strengthening, weakening, generalization, discrimination, and discovery. Next basic strategies are discussed for adding these learning mechanisms to rule-based diagnostic expert systems. These strategies support the incremental evaluation and refinement of rules in the knowledge base by comparing the set of advice given by the expert system (A) with the correct diagnosis (C). Techniques are described for selecting those rules in the in the knowledge base which should participate in adaptive learning. The strategies presented may be used with a wide variety of learning algorithms. Further, these strategies are applicable to a large number of rule-based diagnostic expert systems. They may be used to provide either immediate or deferred updating of the knowledge base.

  2. Perceptions of the Effectiveness of System Dynamics-Based Interactive Learning Environments: An Empirical Study

    Science.gov (United States)

    Qudrat-Ullah, Hassan

    2010-01-01

    The use of simulations in general and of system dynamics simulation based interactive learning environments (SDILEs) in particular is well recognized as an effective way of improving users' decision making and learning in complex, dynamic tasks. However, the effectiveness of SDILEs in classrooms has rarely been evaluated. This article describes…

  3. The MORPG-Based Learning System for Multiple Courses: A Case Study on Computer Science Curriculum

    Science.gov (United States)

    Liu, Kuo-Yu

    2015-01-01

    This study aimed at developing a Multiplayer Online Role Playing Game-based (MORPG) Learning system which enabled instructors to construct a game scenario and manage sharable and reusable learning content for multiple courses. It used the curriculum of "Introduction to Computer Science" as a study case to assess students' learning…

  4. Problem-Based Learning in Communication Systems: Student Perceptions and Achievement

    Science.gov (United States)

    Mitchell, John E.; Canavan, Brian; Smith, Jan

    2010-01-01

    The paper presents a curriculum design for, and subsequent evaluation of, a communications systems course using problem-based learning (PBL) as the instructional methodology. It details the rationale for implementing PBL as well as reporting intended learning outcomes and assessing the students' achievements. (Contains 2 figures and 4 tables.)

  5. A Computer-Assisted Learning Model Based on the Digital Game Exponential Reward System

    Science.gov (United States)

    Moon, Man-Ki; Jahng, Surng-Gahb; Kim, Tae-Yong

    2011-01-01

    The aim of this research was to construct a motivational model which would stimulate voluntary and proactive learning using digital game methods offering players more freedom and control. The theoretical framework of this research lays the foundation for a pedagogical learning model based on digital games. We analyzed the game reward system, which…

  6. Experiences with establishing and implementing learning management system and computer-based test system in medical college.

    Science.gov (United States)

    Park, Joo Hyun; Son, Ji Young; Kim, Sun

    2012-09-01

    The purpose of this study was to establish an e-learning system to support learning in medical education and identify solutions for improving the system. A learning management system (LMS) and computer-based test (CBT) system were established to support e-learning for medical students. A survey of 219 first- and second-grade medical students was administered. The questionnaire included 9 forced choice questions about the usability of system and 2 open-ended questions about necessary improvements to the system. The LMS consisted of a class management, class evaluation, and class attendance system. CBT consisted of a test management, item bank, and authoring tool system. The results of the survey showed a high level of satisfaction in all system usability items except for stability. Further, the advantages of the e-learning system were ensuring information accessibility, providing constant feedback, and designing an intuitive interface. Necessary improvements to the system were stability, user control, readability, and diverse device usage. Based on the findings, suggestions for developing an e-learning system to improve usability by medical students and support learning effectively are recommended.

  7. Development of cyberblog-based intelligent tutorial system to improve students learning ability algorithm

    Science.gov (United States)

    Wahyudin; Riza, L. S.; Putro, B. L.

    2018-05-01

    E-learning as a learning activity conducted online by the students with the usual tools is favoured by students. The use of computer media in learning provides benefits that are not owned by other learning media that is the ability of computers to interact individually with students. But the weakness of many learning media is to assume that all students have a uniform ability, when in reality this is not the case. The concept of Intelligent Tutorial System (ITS) combined with cyberblog application can overcome the weaknesses in neglecting diversity. An Intelligent Tutorial System-based Cyberblog application (ITS) is a web-based interactive application program that implements artificial intelligence which can be used as a learning and evaluation media in the learning process. The use of ITS-based Cyberblog in learning is one of the alternative learning media that is interesting and able to help students in measuring ability in understanding the material. This research will be associated with the improvement of logical thinking ability (logical thinking) of students, especially in algorithm subjects.

  8. Challenge Study: A Project-Based Learning on a Wireless Communication System at Technical High School

    Science.gov (United States)

    Terasawa, Ikuo

    2016-01-01

    The challenge study is a project based learning curriculum at Technical High School aimed at the construction of a wireless communication system. The first period was engineering issues in the construction of an artificial satellite and the second period was a positional locating system based on the general purpose wire-less device--ZigBee device.…

  9. Evaluation Framework Based on Fuzzy Measured Method in Adaptive Learning Systems

    Science.gov (United States)

    Ounaies, Houda Zouari; Jamoussi, Yassine; Ben Ghezala, Henda Hajjami

    2008-01-01

    Currently, e-learning systems are mainly web-based applications and tackle a wide range of users all over the world. Fitting learners' needs is considered as a key issue to guaranty the success of these systems. Many researches work on providing adaptive systems. Nevertheless, evaluation of the adaptivity is still in an exploratory phase.…

  10. Computer-Assisted English Learning System Based on Free Conversation by Topic

    Science.gov (United States)

    Choi, Sung-Kwon; Kwon, Oh-Woog; Kim, Young-Kil

    2017-01-01

    This paper aims to describe a computer-assisted English learning system using chatbots and dialogue systems, which allow free conversation outside the topic without limiting the learner's flow of conversation. The evaluation was conducted by 20 experimenters. The performance of the system based on a free conversation by topic was measured by the…

  11. Emotion-based learning systems and the development of morality.

    Science.gov (United States)

    Blair, R J R

    2017-10-01

    In this paper it is proposed that important components of moral development and moral judgment rely on two forms of emotional learning: stimulus-reinforcement and response-outcome learning. Data in support of this position will be primarily drawn from work with individuals with the developmental condition of psychopathy as well as fMRI studies with healthy individuals. Individuals with psychopathy show impairment on moral judgment tasks and a pronounced increased risk for instrumental antisocial behavior. It will be argued that these impairments are developmental consequences of impaired stimulus-aversive conditioning on the basis of distress cue reinforcers and response-outcome learning in individuals with this disorder. Copyright © 2017. Published by Elsevier B.V.

  12. Brain Computer Interface Learning for Systems Based on Electrocorticography and Intracortical Microelectrode Arrays

    Directory of Open Access Journals (Sweden)

    Shivayogi V Hiremath

    2015-06-01

    Full Text Available A brain-computer interface (BCI system transforms neural activity into control signals for external devices in real time. A BCI user needs to learn to generate specific cortical activity patterns to control external devices effectively. We call this process BCI learning, and it often requires significant effort and time. Therefore, it is important to study this process and develop novel and efficient approaches to accelerate BCI learning. This article reviews major approaches that have been used for BCI learning, including computer-assisted learning, co-adaptive learning, operant conditioning, and sensory feedback. We focus on BCIs based on electrocorticography and intracortical microelectrode arrays for restoring motor function. This article also explores the possibility of brain modulation techniques in promoting BCI learning, such as electrical cortical stimulation, transcranial magnetic stimulation, and optogenetics. Furthermore, as proposed by recent BCI studies, we suggest that BCI learning is in many ways analogous to motor and cognitive skill learning, and therefore skill learning should be a useful metaphor to model BCI learning.

  13. Brain computer interface learning for systems based on electrocorticography and intracortical microelectrode arrays.

    Science.gov (United States)

    Hiremath, Shivayogi V; Chen, Weidong; Wang, Wei; Foldes, Stephen; Yang, Ying; Tyler-Kabara, Elizabeth C; Collinger, Jennifer L; Boninger, Michael L

    2015-01-01

    A brain-computer interface (BCI) system transforms neural activity into control signals for external devices in real time. A BCI user needs to learn to generate specific cortical activity patterns to control external devices effectively. We call this process BCI learning, and it often requires significant effort and time. Therefore, it is important to study this process and develop novel and efficient approaches to accelerate BCI learning. This article reviews major approaches that have been used for BCI learning, including computer-assisted learning, co-adaptive learning, operant conditioning, and sensory feedback. We focus on BCIs based on electrocorticography and intracortical microelectrode arrays for restoring motor function. This article also explores the possibility of brain modulation techniques in promoting BCI learning, such as electrical cortical stimulation, transcranial magnetic stimulation, and optogenetics. Furthermore, as proposed by recent BCI studies, we suggest that BCI learning is in many ways analogous to motor and cognitive skill learning, and therefore skill learning should be a useful metaphor to model BCI learning.

  14. GA-based fuzzy reinforcement learning for control of a magnetic bearing system.

    Science.gov (United States)

    Lin, C T; Jou, C P

    2000-01-01

    This paper proposes a TD (temporal difference) and GA (genetic algorithm)-based reinforcement (TDGAR) learning method and applies it to the control of a real magnetic bearing system. The TDGAR learning scheme is a new hybrid GA, which integrates the TD prediction method and the GA to perform the reinforcement learning task. The TDGAR learning system is composed of two integrated feedforward networks. One neural network acts as a critic network to guide the learning of the other network (the action network) which determines the outputs (actions) of the TDGAR learning system. The action network can be a normal neural network or a neural fuzzy network. Using the TD prediction method, the critic network can predict the external reinforcement signal and provide a more informative internal reinforcement signal to the action network. The action network uses the GA to adapt itself according to the internal reinforcement signal. The key concept of the TDGAR learning scheme is to formulate the internal reinforcement signal as the fitness function for the GA such that the GA can evaluate the candidate solutions (chromosomes) regularly, even during periods without external feedback from the environment. This enables the GA to proceed to new generations regularly without waiting for the arrival of the external reinforcement signal. This can usually accelerate the GA learning since a reinforcement signal may only be available at a time long after a sequence of actions has occurred in the reinforcement learning problem. The proposed TDGAR learning system has been used to control an active magnetic bearing (AMB) system in practice. A systematic design procedure is developed to achieve successful integration of all the subsystems including magnetic suspension, mechanical structure, and controller training. The results show that the TDGAR learning scheme can successfully find a neural controller or a neural fuzzy controller for a self-designed magnetic bearing system.

  15. Thutmose - Investigation of Machine Learning-Based Intrusion Detection Systems

    Science.gov (United States)

    2016-06-01

    monitoring. This analyzed payload is within the application layer of the OSI model . The analysis tries to establish whether or not the payload is...24 3.2.5 Model Drift Experiments...ADVERSARIAL ENVIRONMENTS (SPIE DSS 2014) .................................................. 58 APPENDIX C - EVALUATING MODEL DRIFT IN MACHINE LEARNING

  16. Web-based e-learning and virtual lab of human-artificial immune system.

    Science.gov (United States)

    Gong, Tao; Ding, Yongsheng; Xiong, Qin

    2014-05-01

    Human immune system is as important in keeping the body healthy as the brain in supporting the intelligence. However, the traditional models of the human immune system are built on the mathematics equations, which are not easy for students to understand. To help the students to understand the immune systems, a web-based e-learning approach with virtual lab is designed for the intelligent system control course by using new intelligent educational technology. Comparing the traditional graduate educational model within the classroom, the web-based e-learning with the virtual lab shows the higher inspiration in guiding the graduate students to think independently and innovatively, as the students said. It has been found that this web-based immune e-learning system with the online virtual lab is useful for teaching the graduate students to understand the immune systems in an easier way and design their simulations more creatively and cooperatively. The teaching practice shows that the optimum web-based e-learning system can be used to increase the learning effectiveness of the students.

  17. Fuzzy OLAP association rules mining-based modular reinforcement learning approach for multiagent systems.

    Science.gov (United States)

    Kaya, Mehmet; Alhajj, Reda

    2005-04-01

    Multiagent systems and data mining have recently attracted considerable attention in the field of computing. Reinforcement learning is the most commonly used learning process for multiagent systems. However, it still has some drawbacks, including modeling other learning agents present in the domain as part of the state of the environment, and some states are experienced much less than others, or some state-action pairs are never visited during the learning phase. Further, before completing the learning process, an agent cannot exhibit a certain behavior in some states that may be experienced sufficiently. In this study, we propose a novel multiagent learning approach to handle these problems. Our approach is based on utilizing the mining process for modular cooperative learning systems. It incorporates fuzziness and online analytical processing (OLAP) based mining to effectively process the information reported by agents. First, we describe a fuzzy data cube OLAP architecture which facilitates effective storage and processing of the state information reported by agents. This way, the action of the other agent, not even in the visual environment. of the agent under consideration, can simply be predicted by extracting online association rules, a well-known data mining technique, from the constructed data cube. Second, we present a new action selection model, which is also based on association rules mining. Finally, we generalize not sufficiently experienced states, by mining multilevel association rules from the proposed fuzzy data cube. Experimental results obtained on two different versions of a well-known pursuit domain show the robustness and effectiveness of the proposed fuzzy OLAP mining based modular learning approach. Finally, we tested the scalability of the approach presented in this paper and compared it with our previous work on modular-fuzzy Q-learning and ordinary Q-learning.

  18. Fidelity-Based Ant Colony Algorithm with Q-learning of Quantum System

    Science.gov (United States)

    Liao, Qin; Guo, Ying; Tu, Yifeng; Zhang, Hang

    2018-03-01

    Quantum ant colony algorithm (ACA) has potential applications in quantum information processing, such as solutions of traveling salesman problem, zero-one knapsack problem, robot route planning problem, and so on. To shorten the search time of the ACA, we suggest the fidelity-based ant colony algorithm (FACA) for the control of quantum system. Motivated by structure of the Q-learning algorithm, we demonstrate the combination of a FACA with the Q-learning algorithm and suggest the design of a fidelity-based ant colony algorithm with the Q-learning to improve the performance of the FACA in a spin-1/2 quantum system. The numeric simulation results show that the FACA with the Q-learning can efficiently avoid trapping into local optimal policies and increase the speed of convergence process of quantum system.

  19. Iterative learning-based decentralized adaptive tracker for large-scale systems: a digital redesign approach.

    Science.gov (United States)

    Tsai, Jason Sheng-Hong; Du, Yan-Yi; Huang, Pei-Hsiang; Guo, Shu-Mei; Shieh, Leang-San; Chen, Yuhua

    2011-07-01

    In this paper, a digital redesign methodology of the iterative learning-based decentralized adaptive tracker is proposed to improve the dynamic performance of sampled-data linear large-scale control systems consisting of N interconnected multi-input multi-output subsystems, so that the system output will follow any trajectory which may not be presented by the analytic reference model initially. To overcome the interference of each sub-system and simplify the controller design, the proposed model reference decentralized adaptive control scheme constructs a decoupled well-designed reference model first. Then, according to the well-designed model, this paper develops a digital decentralized adaptive tracker based on the optimal analog control and prediction-based digital redesign technique for the sampled-data large-scale coupling system. In order to enhance the tracking performance of the digital tracker at specified sampling instants, we apply the iterative learning control (ILC) to train the control input via continual learning. As a result, the proposed iterative learning-based decentralized adaptive tracker not only has robust closed-loop decoupled property but also possesses good tracking performance at both transient and steady state. Besides, evolutionary programming is applied to search for a good learning gain to speed up the learning process of ILC. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

  20. Paired-Associate and Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems.

    Science.gov (United States)

    Li, Kaiyun; Fu, Qiufang; Sun, Xunwei; Zhou, Xiaoyan; Fu, Xiaolan

    2016-01-01

    It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed that the optimal accuracy in the PA condition was significantly decreased when the training time was reduced from 7 to 3 s, but this did not occur in the FB condition, although shortened training time impaired the acquisition of explicit knowledge in both conditions. The results of Experiment 2 showed that the concurrent working memory task impaired the optimal accuracy and the acquisition of explicit knowledge in the PA condition but did not influence the optimal accuracy or the acquisition of self-insight knowledge in the FB condition. The apparent dissociation results between the FB and PA conditions suggested that a non-declarative or procedural learning system is involved in the FB-WPT and provided new evidence for the multiple-systems theory of human category learning.

  1. Using an improved association rules mining optimization algorithm in web-based mobile-learning system

    Science.gov (United States)

    Huang, Yin; Chen, Jianhua; Xiong, Shaojun

    2009-07-01

    Mobile-Learning (M-learning) makes many learners get the advantages of both traditional learning and E-learning. Currently, Web-based Mobile-Learning Systems have created many new ways and defined new relationships between educators and learners. Association rule mining is one of the most important fields in data mining and knowledge discovery in databases. Rules explosion is a serious problem which causes great concerns, as conventional mining algorithms often produce too many rules for decision makers to digest. Since Web-based Mobile-Learning System collects vast amounts of student profile data, data mining and knowledge discovery techniques can be applied to find interesting relationships between attributes of learners, assessments, the solution strategies adopted by learners and so on. Therefore ,this paper focus on a new data-mining algorithm, combined with the advantages of genetic algorithm and simulated annealing algorithm , called ARGSA(Association rules based on an improved Genetic Simulated Annealing Algorithm), to mine the association rules. This paper first takes advantage of the Parallel Genetic Algorithm and Simulated Algorithm designed specifically for discovering association rules. Moreover, the analysis and experiment are also made to show the proposed method is superior to the Apriori algorithm in this Mobile-Learning system.

  2. Aberrant Learning Achievement Detection Based on Person-Fit Statistics in Personalized e-Learning Systems

    Science.gov (United States)

    Liu, Ming-Tsung; Yu, Pao-Ta

    2011-01-01

    A personalized e-learning service provides learning content to fit learners' individual differences. Learning achievements are influenced by cognitive as well as non-cognitive factors such as mood, motivation, interest, and personal styles. This paper proposes the Learning Caution Indexes (LCI) to detect aberrant learning patterns. The philosophy…

  3. A Chatbot for a Dialogue-Based Second Language Learning System

    Science.gov (United States)

    Huang, Jin-Xia; Lee, Kyung-Soon; Kwon, Oh-Woog; Kim, Young-Kil

    2017-01-01

    This paper presents a chatbot for a Dialogue-Based Computer-Assisted second Language Learning (DB-CALL) system. A DB-CALL system normally leads dialogues by asking questions according to given scenarios. User utterances outside the scenarios are normally considered as semantically improper and simply rejected. In this paper, we assume that raising…

  4. Instituting systems-based practice and practice-based learning and improvement: a curriculum of inquiry

    Directory of Open Access Journals (Sweden)

    Andrew P. Wilper

    2013-09-01

    Full Text Available Background : The Accreditation Council for Graduate Medical Education (ACGME requires that training programs integrate system-based practice (SBP and practice-based learning and improvement (PBLI into internal medicine residency curricula. Context and setting : We instituted a seminar series and year-long-mentored curriculum designed to engage internal medicine residents in these competencies. Methods : Residents participate in a seminar series that includes assigned reading and structured discussion with faculty who assist in the development of quality improvement or research projects. Residents pursue projects over the remainder of the year. Monthly works in progress meetings, protected time for inquiry, and continued faculty mentorship guide the residents in their project development. Trainees present their work at hospital-wide grand rounds at the end of the academic year. We performed a survey of residents to assess their self-reported knowledge, attitudes and skills in SBP and PBLI. In addition, blinded faculty scored projects for appropriateness, impact, and feasibility. Outcomes : We measured resident self-reported knowledge, attitudes, and skills at the end of the academic year. We found evidence that participants improved their understanding of the context in which they were practicing, and that their ability to engage in quality improvement projects increased. Blinded faculty reviewers favorably ranked the projects’ feasibility, impact, and appropriateness. The ‘Curriculum of Inquiry’ generated 11 quality improvement and research projects during the study period. Barriers to the ongoing work include a limited supply of mentors and delays due to Institutional Review Board approval. Hospital leadership recognizes the importance of the curriculum, and our accreditation manager now cites our ongoing work. Conclusions : A structured residency-based curriculum facilitates resident demonstration of SBP and practice-based learning and

  5. White blood cells identification system based on convolutional deep neural learning networks.

    Science.gov (United States)

    Shahin, A I; Guo, Yanhui; Amin, K M; Sharawi, Amr A

    2017-11-16

    White blood cells (WBCs) differential counting yields valued information about human health and disease. The current developed automated cell morphology equipments perform differential count which is based on blood smear image analysis. Previous identification systems for WBCs consist of successive dependent stages; pre-processing, segmentation, feature extraction, feature selection, and classification. There is a real need to employ deep learning methodologies so that the performance of previous WBCs identification systems can be increased. Classifying small limited datasets through deep learning systems is a major challenge and should be investigated. In this paper, we propose a novel identification system for WBCs based on deep convolutional neural networks. Two methodologies based on transfer learning are followed: transfer learning based on deep activation features and fine-tuning of existed deep networks. Deep acrivation featues are extracted from several pre-trained networks and employed in a traditional identification system. Moreover, a novel end-to-end convolutional deep architecture called "WBCsNet" is proposed and built from scratch. Finally, a limited balanced WBCs dataset classification is performed through the WBCsNet as a pre-trained network. During our experiments, three different public WBCs datasets (2551 images) have been used which contain 5 healthy WBCs types. The overall system accuracy achieved by the proposed WBCsNet is (96.1%) which is more than different transfer learning approaches or even the previous traditional identification system. We also present features visualization for the WBCsNet activation which reflects higher response than the pre-trained activated one. a novel WBCs identification system based on deep learning theory is proposed and a high performance WBCsNet can be employed as a pre-trained network. Copyright © 2017. Published by Elsevier B.V.

  6. Learners' Ensemble Based Security Conceptual Model for M-Learning System in Malaysian Higher Learning Institution

    Science.gov (United States)

    Mahalingam, Sheila; Abdollah, Faizal Mohd; Sahib, Shahrin

    2014-01-01

    M-Learning has a potential to improve efficiency in the education sector and has a tendency to grow advance and transform the learning environment in the future. Yet there are challenges in many areas faced when introducing and implementing m-learning. The learner centered attribute in mobile learning implies deployment in untrustworthy learning…

  7. Learning Experiences Reuse Based on an Ontology Modeling to Improve Adaptation in E-Learning Systems

    Science.gov (United States)

    Hadj M'tir, Riadh; Rumpler, Béatrice; Jeribi, Lobna; Ben Ghezala, Henda

    2014-01-01

    Current trends in e-Learning focus mainly on personalizing and adapting the learning environment and learning process. Although their increasingly number, theses researches often ignore the concepts of capitalization and reuse of learner experiences which can be exploited later by other learners. Thus, the major challenge of distance learning is…

  8. EVALUATION OF THE LEARNING SYSTEM BASED ON RESEARCH (SABI IN THE CICS UMA IPN BIOCHEMISTRY UNIT

    Directory of Open Access Journals (Sweden)

    Blanca Elisa Pérez-Magaña

    2014-07-01

    Full Text Available Learning is a steward, permanent, and participatory process where: the apprentice, teacher, classmates, institution and other social factors where the student performs. As detonator of learning is research, which is made from real events that are addressed on the basis of the scientific development of the State of the art. One of the key elements in the professional training of students is the method that is used. Research-based learning system is an educational innovation (SABI, which was used in the learning of basic sciences of the Cardiovascular apparatus in generations unit 33rd, 34th, 35th, 36th and 37th generations in the years of 2008 to 2012's career in medicine and as a result was a decrease in the number of students reproachedimproving achievement. This method is an excellent alternative in the teaching-learning process and can be used both in groups with a variable number of students.

  9. Learning Content Management Systems

    Directory of Open Access Journals (Sweden)

    Tache JURUBESCU

    2008-01-01

    Full Text Available The paper explains the evolution of e-Learning and related concepts and tools and its connection with other concepts such as Knowledge Management, Human Resources Management, Enterprise Resource Planning, and Information Technology. The paper also distinguished Learning Content Management Systems from Learning Management Systems and Content Management Systems used for general web-based content. The newest Learning Content Management System, very expensive and yet very little implemented is one of the best tools that helps us to cope with the realities of the 21st Century in what learning concerns. The debates over how beneficial one or another system is for an organization, can be driven by costs involved, efficiency envisaged, and availability of the product on the market.

  10. Using Web-Based, Group Communication Systems to Support Case Study Learning at a Distance

    Directory of Open Access Journals (Sweden)

    Liam Rourke

    2002-10-01

    Full Text Available This study explored the capacity of Web-based, group communication systems to support case-based teaching and learning. Eleven graduate students studying at a distance were divided into three groups to collaborate on a case study using either a synchronous voice, an asynchronous voice, or a synchronous text communication system. Participants kept a detailed log of the time they spent on various activities, wrote a 1,500-word reflection on their experience, and participated in a group interview. Analysis of these data reveals that each group supplemented the system that had been assigned to them with additional communication systems in order to complete the project. Each of these systems were used strategically: email was used to share files and arrange meetings, and synchronous voice systems were used to brainstorm and make decisions. Learning achievement was high across groups and students enjoyed collaborating with others on a concrete task.

  11. Evaluation framework based on fuzzy measured method in adaptive learning systems

    OpenAIRE

    Houda Zouari Ounaies, ,; Yassine Jamoussi; Henda Hajjami Ben Ghezala

    2008-01-01

    Currently, e-learning systems are mainly web-based applications and tackle a wide range of users all over the world. Fitting learners’ needs is considered as a key issue to guaranty the success of these systems. Many researches work on providing adaptive systems. Nevertheless, evaluation of the adaptivity is still in an exploratory phase. Adaptation methods are a basic factor to guaranty an effective adaptation. This issue is referred as meta-adaptation in numerous researches. In our research...

  12. An Expert System-based Context-Aware Ubiquitous Learning Approach for Conducting Science Learning Activities

    Science.gov (United States)

    Wu, Po-Han; Hwang, Gwo-Jen; Tsai, Wen-Hung

    2013-01-01

    Context-aware ubiquitous learning has been recognized as being a promising approach that enables students to interact with real-world learning targets with supports from the digital world. Several researchers have indicated the importance of providing learning guidance or hints to individual students during the context-aware ubiquitous learning…

  13. New Functions for Stimulating Learners' Motivation in a Web-Based e-Learning System

    Science.gov (United States)

    Matsuo, Keita; Barolli, Leonard; Xhafa, Fatos; Koyama, Akio; Durresi, Arjan

    2008-01-01

    Due to the opportunities provided by the Internet, people are taking advantage of e-learning courses and during the last few years enormous research efforts have been dedicated to the development of e-learning systems. So far, many e-learning systems are proposed and used practically. However, in these systems the e-learning completion rate is…

  14. Students Learn Systems-Based Care and Facilitate System Change as Stakeholders in a Free Clinic Experience

    Science.gov (United States)

    Colbert, Colleen Y.; Ogden, Paul E.; Lowe, Darla; Moffitt, Michael J.

    2010-01-01

    Systems-based practice (SBP) is rarely taught or evaluated during medical school, yet is one of the required competencies once students enter residency. We believe Texas A&M College of Medicine students learn about systems issues informally, as they care for patients at a free clinic in Temple, TX. The mandatory free clinic rotation is part of…

  15. An Interactive Web-based Learning System for Assisting Machining Technology Education

    Directory of Open Access Journals (Sweden)

    Min Jou

    2008-05-01

    Full Text Available The key technique of manufacturing methods is machining. The degree of technique of machining directly affects the quality of the product. Therefore, the machining technique is of primary importance in promoting student practice ability during the training process. Currently, practical training is applied in shop floor to discipline student’s practice ability. Much time and cost are used to teach these techniques. Particularly, computerized machines are continuously increasing in use. The development of educating engineers on computerized machines becomes much more difficult than with traditional machines. This is because of the limitation of the extremely expensive cost of teaching. The quality and quantity of teaching cannot always be promoted in this respect. The traditional teaching methods can not respond well to the needs of the future. Therefore, this research aims to the following topics; (1.Propose the teaching strategies for the students to learning machining processing planning through web-based learning system. (2.Establish on-line teaching material for the computer-aided manufacturing courses including CNC coding method, CNC simulation. (3.Develop the virtual machining laboratory to bring the machining practical training to web-based learning system. (4.Integrate multi-media and virtual laboratory in the developed e-learning web-based system to enhance the effectiveness of machining education through web-based system.

  16. Antecedents of Continued Usage Intentions of Web-Based Learning Management System in Tanzania

    Science.gov (United States)

    Lwoga, Edda Tandi; Komba, Mercy

    2015-01-01

    Purpose: The purpose of this paper is to examine factors that predict students' continued usage intention of web-based learning management systems (LMS) in Tanzania, with a specific focus on the School of Business of Mzumbe University. Specifically, the study investigated major predictors of actual usage and continued usage intentions of…

  17. Critical Success Factors for Adoption of Web-Based Learning Management Systems in Tanzania

    Science.gov (United States)

    Lwoga, Edda Tandi

    2014-01-01

    This paper examines factors that predict students' continual usage intention of web-based learning content management systems in Tanzania, with a specific focus at Muhimbili University of Health and Allied Science (MUHAS). This study sent a questionnaire surveys to 408 first year undergraduate students, with a rate of return of 66.7. This study…

  18. Game-Based Experiential Learning in Online Management Information Systems Classes Using Intel's IT Manager 3

    Science.gov (United States)

    Bliemel, Michael; Ali-Hassan, Hossam

    2014-01-01

    For several years, we used Intel's flash-based game "IT Manager 3: Unseen Forces" as an experiential learning tool, where students had to act as a manager making real-time prioritization decisions about repairing computer problems, training and upgrading systems with better technologies as well as managing increasing numbers of technical…

  19. Problem-based learning in teaching chemistry: enthalpy changes in systems

    Science.gov (United States)

    Ayyildiz, Yildizay; Tarhan, Leman

    2018-01-01

    Problem-based learning (PBL) as a teaching strategy has recently become quite widespread in especially chemistry classes. Research has found that students, from elementary through college, have many alternative conceptions regarding enthalpy changes in systems. Although there are several studies focused on identifying student alternative conceptions and misunderstandings of this subject, studies on preventing the formation of these alternative conceptions are limited.

  20. Integrating Soft Skill Competencies through Project-Based Learning across the Information Systems Curriculum

    Science.gov (United States)

    Woodward, Belle S.; Sendall, Patricia; Ceccucci, Wendy

    2010-01-01

    Contemporary Information Systems graduates will be more marketable in the workplace upon graduation if they have combined competencies in both technical and soft skills: interpersonal communication, teamwork, time management, planning and organizational skills. Team and project-based learning can be used to incorporate soft skill competencies with…

  1. Anforderungen von Studierenden an e-Learning-Systeme und an die Gestaltung elektronischer Fallbeispiele [Student’s specifications of e-learning systems for case-based teaching

    Directory of Open Access Journals (Sweden)

    von Müller, Lutz

    2013-11-01

    Full Text Available [english] Evolution of case-based teaching (CBT is influenced by student’s specifications and also by improvement of computer-based e-learning systems. In the present single center study of the University of Saarland Medical Center the medical students in the third year compared two case-based e-learning systems. CAMPUS-Classic-Player is an open system with almost unrestricted decision trees whereas the CAMPUS-Card-Player represents an educational structured e-learning platform. Learning from patients and also learning from students will be introduced as our pivotal principle for development of new e-learning strategies.A significantly better evaluation was found for the more structured CAMPUS-Card-Player with respect to profile, clarity, didactics, learning effects, and relevance for exam preparation. The student’s intentions for CBT were clearly focused on usability for preparation of future exams which can be better achieved by the help of more structured e-learning systems. The time to process and answer the cases was about for both players. We therefore propose that the time schedule for most users is limited per case irrespective of the complexity of decision trees, cases or e-learning systems. This remains to be mentioned for the design of future cases. [german] Die Weiterentwicklung von fallbasiertem Lernen wird durch die Anregungen der Studierenden („user“ und durch neue technische Entwicklungen und Möglichkeiten von e-Learning-Systemen bestimmt. In dieser prospektiven monozentrischen Studie am Universitätsklinikum des Saarlandes wurde von Studierenden des 1. und 2. klinischen Semesters Medizin eine offene (CAMPUS-Classic-Player und ein strukturierte e-Learning-Plattform (CAMPUS-Card-Player für die Darstellung elektronischer Fallbeispiele verglichen und bewertet. Signifikant besser evaluiert wurde der CAMPUS-Card-Player in Bezug auf Form, Übersichtlichkeit, Zusatzmaterialien, Didaktik, Lerneffekt, Prüfungsrelevanz und

  2. Ontology-Based User Profiling for Personalized Acces to Information within Collaborative Learning System

    Directory of Open Access Journals (Sweden)

    Mohammed Amine Alimam

    2014-06-01

    Full Text Available The use of modern educational technology methods has become an important area of research in order to support learning as well as collaboration. This is especially evident with the rise of internet and web 2.0 platforms that have transformed users’ role from mere content consumers to fully content consumers-producers. Furthermore, people engaged in collaborative learning capitalize on one another’s resources and skills, unlike individual learning. This paper proceeds with a categorization of the main tools and functions that characterize the personalization learning aspect, in order to discuss their trade-offs with collaborative learning systems. It proposes a framework of a personalized information research (IR within a collaborative learning system, incorporating the characterization of the research type carried by the query, as well as modeling and constructing semantic users’ profiles. We use the context of the user query into a prediction mechanism of the search type, based on a previous identification of users’ levels and interests. The paper is concluded by presenting experiment results, revealing that the use of the subject ontology extension approach satisfyingly contributes to improvement in the accuracy of system recommendations.

  3. Algorithm for personal identification in distance learning system based on registration of keyboard rhythm

    Science.gov (United States)

    Nikitin, P. V.; Savinov, A. N.; Bazhenov, R. I.; Sivandaev, S. V.

    2018-05-01

    The article describes the method of identifying a person in distance learning systems based on a keyboard rhythm. An algorithm for the organization of access control is proposed, which implements authentication, identification and verification of a person using the keyboard rhythm. Authentication methods based on biometric personal parameters, including those based on the keyboard rhythm, due to the inexistence of biometric characteristics without a particular person, are able to provide an advanced accuracy and inability to refuse authorship and convenience for operators of automated systems, in comparison with other methods of conformity checking. Methods of permanent hidden keyboard monitoring allow detecting the substitution of a student and blocking the key system.

  4. Design of a Microlecture Mobile Learning System Based on Smartphone and Web Platforms

    Science.gov (United States)

    Wen, Chuanxue; Zhang, Junfei

    2015-01-01

    This paper first analyzes the concept and features of microlecture, mobile learning, and ubiquitous learning, then presents the combination of microlecture and mobile learning, to propose a novel way of micro-learning through mobile terminals. Details are presented of a microlecture mobile learning system (MMLS) that can support multiplatforms,…

  5. Two spatiotemporally distinct value systems shape reward-based learning in the human brain.

    Science.gov (United States)

    Fouragnan, Elsa; Retzler, Chris; Mullinger, Karen; Philiastides, Marios G

    2015-09-08

    Avoiding repeated mistakes and learning to reinforce rewarding decisions is critical for human survival and adaptive actions. Yet, the neural underpinnings of the value systems that encode different decision-outcomes remain elusive. Here coupling single-trial electroencephalography with simultaneously acquired functional magnetic resonance imaging, we uncover the spatiotemporal dynamics of two separate but interacting value systems encoding decision-outcomes. Consistent with a role in regulating alertness and switching behaviours, an early system is activated only by negative outcomes and engages arousal-related and motor-preparatory brain structures. Consistent with a role in reward-based learning, a later system differentially suppresses or activates regions of the human reward network in response to negative and positive outcomes, respectively. Following negative outcomes, the early system interacts and downregulates the late system, through a thalamic interaction with the ventral striatum. Critically, the strength of this coupling predicts participants' switching behaviour and avoidance learning, directly implicating the thalamostriatal pathway in reward-based learning.

  6. Problem-based learning: a strategic learning system design for the education of healthcare professionals in the 21st century.

    Science.gov (United States)

    Gwee, Matthew Choon-Eng

    2009-05-01

    Problem-based learning (PBL) was first implemented by McMaster University medical school in 1969 as a radical, innovative, and alternative pathway to learning in medical education, thus setting a new educational trend. PBL has now spread widely across the globe and beyond the healthcare disciplines, and has prevailed for almost four decades. PBL is essentially a strategic learning system design, which combines several complementary educational principles for the delivery of instruction. PBL is specifically aimed at enhancing and optimizing the educational outcomes of learner-centered, collaborative, contextual, integrated, self-directed, and reflective learning. The design and delivery of instruction in PBL involve peer teaching and learning in small groups through the social construction of knowledge using a real-life problem case to trigger the learning process. Therefore, PBL represents a major shift in the educational paradigm from the traditional teacher-directed (teacher-centered) instruction to student-centered (learner-centered) learning. PBL is firmly underpinned by several educational theories, but problems are often encountered in practice that can affect learning outcomes. Educators contemplating implementing PBL in their institutions should have a clear understanding of its basic tenets, its practice and its philosophy, as well as the issues, challenges, and opportunities associated with its implementation. Special attention should be paid to the training and selection of PBL tutors who have a critical role in the PBL process. Furthermore, a significant change in the mindsets of both students and teachers are required for the successful implementation of PBL. Thus, effective training programs for students and teachers must precede its implementation. PBL is a highly resource-intensive learning strategy and the returns on investment (i.e. the actual versus expected learning outcomes) should be carefully and critically appraised in the decision

  7. Empirical investigation to explore factors that achieve high quality of mobile learning system based on students’ perspectives

    Directory of Open Access Journals (Sweden)

    Mohammed Amin Almaiah

    2016-09-01

    Full Text Available This study presents three frameworks for mobile learning system based on quality factors derived from the updated DeLone and McLean information system success model. This study used the questionnaire as a quantitative method to explore quality factors for mobile learning system based on perspectives of 392 students. This study opens future work for using the identified quality factors as guidelines for researchers and designers to design and develop mobile learning applications.

  8. Web-Based Reading Annotation System with an Attention-Based Self-Regulated Learning Mechanism for Promoting Reading Performance

    Science.gov (United States)

    Chen, Chih-Ming; Huang, Sheng-Hui

    2014-01-01

    Due to the rapid development of information technology, web-based learning has become a dominant trend. That is, learners can often learn anytime and anywhere without being restricted by time and space. Autonomic learning primarily occurs in web-based learning environments, and self-regulated learning (SRL) is key to autonomic learning…

  9. The Simulation Computer Based Learning (SCBL) for Short Circuit Multi Machine Power System Analysis

    Science.gov (United States)

    Rahmaniar; Putri, Maharani

    2018-03-01

    Strengthening Competitiveness of human resources become the reply of college as a conductor of high fomal education. Electrical Engineering Program UNPAB (Prodi TE UNPAB) as one of the department of electrical engineering that manages the field of electrical engineering expertise has a very important part in preparing human resources (HR), Which is required by where graduates are produced by DE UNPAB, Is expected to be able to compete globally, especially related to the implementation of Asean Economic Community (AEC) which requires the active participation of graduates with competence and quality of human resource competitiveness. Preparation of HR formation Competitive is done with the various strategies contained in the Seven (7) Higher Education Standard, one part of which is the implementation of teaching and learning process in Electrical system analysis with short circuit analysis (SCA) This course is a course The core of which is the basis for the competencies of other subjects in the advanced semester at Development of Computer Based Learning model (CBL) is done in the learning of interference analysis of multi-machine short circuit which includes: (a) Short-circuit One phase, (B) Two-phase Short Circuit Disruption, (c) Ground Short Circuit Disruption, (d) Short Circuit Disruption One Ground Floor Development of CBL learning model for Electrical System Analysis course provides space for students to be more active In learning in solving complex (complicated) problems, so it is thrilling Ilkan flexibility of student learning how to actively solve the problem of short-circuit analysis and to form the active participation of students in learning (Student Center Learning, in the course of electrical power system analysis.

  10. Web-Based Learning Information System for Web 3.0

    Science.gov (United States)

    Rego, Hugo; Moreira, Tiago; García-Peñalvo, Francisco Jose

    With the emergence of Web/eLearning 3.0 we have been developing/adjusting AHKME in order to face this great challenge. One of our goals is to allow the instructional designer and teacher to access standardized resources and evaluate the possibility of integration and reuse in eLearning systems, not only content but also the learning strategy. We have also integrated some collaborative tools for the adaptation of resources, as well as the collection of feedback from users to provide feedback to the system. We also provide tools for the instructional designer to create/customize specifications/ontologies to give structure and meaning to resources, manual and automatic search with recommendation of resources and instructional design based on the context, as well as recommendation of adaptations in learning resources. We also consider the concept of mobility and mobile technology applied to eLearning, allowing access by teachers and students to learning resources, regardless of time and space.

  11. Lessons Learned from A System-Wide Evidence-Based Practice Program Implementation

    Science.gov (United States)

    2017-04-25

    incorporating scientific evidence, clinical expertise and the patient’s values and preferences to provide quality healthcare . Despite growing...MEMORANDUM FOR ST DEPARTMENT OF THE AIR FORCE 59TH MEDICAL WING (AETC) JOINT BASE SAN ANTONIO - LACKLAND TEXAS ATTN: LT COL JACQUELINE KILLIAN...FROM: 59 MDW/SGVU SUBJECT: Professional Presentation Approval 14 FEB 2017 1. Your paper, entitled Lesson Learned From A System-Wide Evidence- Based

  12. A Fuzzy Logic-Based Personalized Learning System for Supporting Adaptive English Learning

    Science.gov (United States)

    Hsieh, Tung-Cheng; Wang, Tzone-I; Su, Chien-Yuan; Lee, Ming-Che

    2012-01-01

    As a nearly global language, English as a Foreign Language (EFL) programs are essential for people wishing to learn English. Researchers have noted that extensive reading is an effective way to improve a person's command of English. Choosing suitable articles in accordance with a learner's needs, interests and ability using an e-learning system…

  13. Enhancing Collaborative Learning in Web 2.0-Based E-Learning Systems: A Design Framework for Building Collaborative E-Learning Contents

    Science.gov (United States)

    El Mhouti, Abderrahim; Nasseh, Azeddine; Erradi, Mohamed; Vasquèz, José Marfa

    2017-01-01

    Today, the implication of Web 2.0 technologies in e-learning allows envisaging new teaching and learning forms, advocating an important place to the collaboration and social interaction. However, in e-learning systems, learn in a collaborative way is not always so easy because one of the difficulties when arranging e-learning courses can be that…

  14. Interorganizational learning systems

    DEFF Research Database (Denmark)

    Hjalager, Anne-Mette

    1999-01-01

    The occurrence of organizational and interorganizational learning processes is not only the result of management endeavors. Industry structures and market related issues have substantial spill-over effects. The article reviews literature, and it establishes a learning model in which elements from...... organizational environments are included into a systematic conceptual framework. The model allows four types of learning to be identified: P-learning (professional/craft systems learning), T-learning (technology embedded learning), D-learning (dualistic learning systems, where part of the labor force is exclude...... from learning), and S-learning (learning in social networks or clans). The situation related to service industries illustrates the typology....

  15. Rule-bases construction through self-learning for a table-based Sugeno-Takagi fuzzy logic control system

    Directory of Open Access Journals (Sweden)

    C. Boldisor

    2009-12-01

    Full Text Available A self-learning based methodology for building the rule-base of a fuzzy logic controller (FLC is presented and verified, aiming to engage intelligent characteristics to a fuzzy logic control systems. The methodology is a simplified version of those presented in today literature. Some aspects are intentionally ignored since it rarely appears in control system engineering and a SISO process is considered here. The fuzzy inference system obtained is a table-based Sugeno-Takagi type. System’s desired performance is defined by a reference model and rules are extracted from recorded data, after the correct control actions are learned. The presented algorithm is tested in constructing the rule-base of a fuzzy controller for a DC drive application. System’s performances and method’s viability are analyzed.

  16. Mobile Inquiry Based Learning

    NARCIS (Netherlands)

    Specht, Marcus

    2012-01-01

    Specht, M. (2012, 8 November). Mobile Inquiry Based Learning. Presentation given at the Workshop "Mobile inquiry-based learning" at the Mobile Learning Day 2012 at the Fernuniversität Hagen, Hagen, Germany.

  17. Fast Conflict Resolution Based on Reinforcement Learning in Multi-agent System

    Institute of Scientific and Technical Information of China (English)

    PIAOSonghao; HONGBingrong; CHUHaitao

    2004-01-01

    In multi-agent system where each agen thas a different goal (even the team of agents has the same goal), agents must be able to resolve conflicts arising in the process of achieving their goal. Many researchers presented methods for conflict resolution, e.g., Reinforcement learning (RL), but the conventional RL requires a large computation cost because every agent must learn, at the same time the overlap of actions selected by each agent results in local conflict. Therefore in this paper, we propose a novel method to solve these problems. In order to deal with the conflict within the multi-agent system, the concept of potential field function based Action selection priority level (ASPL) is brought forward. In this method, all kinds of environment factor that may have influence on the priority are effectively computed with the potential field function. So the priority to access the local resource can be decided rapidly. By avoiding the complex coordination mechanism used in general multi-agent system, the conflict in multi-agent system is settled more efficiently. Our system consists of RL with ASPL module and generalized rules module. Using ASPL, RL module chooses a proper cooperative behavior, and generalized rule module can accelerate the learning process. By applying the proposed method to Robot Soccer, the learning process can be accelerated. The results of simulation and real experiments indicate the effectiveness of the method.

  18. E-Learning Recommender System Based on Collaborative Filtering and Ontology

    OpenAIRE

    John Tarus; Zhendong Niu; Bakhti Khadidja

    2017-01-01

    In recent years, e-learning recommender systems has attracted great attention as a solution towards addressing the problem of information overload in e-learning environments and providing relevant recommendations to online learners. E-learning recommenders continue to play an increasing educational role in aiding learners to find appropriate learning materials to support the achievement of their learning goals. Although general recommender systems have recorded significant success in solving ...

  19. LEARNING STYLES BASED ADAPTIVE INTELLIGENT TUTORING SYSTEMS: DOCUMENT ANALYSIS OF ARTICLES PUBLISHED BETWEEN 2001. AND 2016.

    Directory of Open Access Journals (Sweden)

    Amit Kumar

    2017-12-01

    Full Text Available Actualizing instructional intercessions to suit learner contrasts has gotten extensive consideration. Among these individual contrast factors, the observational confirmation in regards to the academic benefit of learning styles has been addressed, yet the examination on the issue proceeds. Late improvements in web-based executions have driven researchers to re-examine the learning styles in adaptive tutoring frameworks. Adaptivity in intelligent tutoring systems is strongly influenced by the learning style of a learner. This study involved extensive document analysis of adaptive tutoring systems based on learning styles. Seventy-eight studies in literature from 2001 to 2016 were collected and classified under select parameters such as main focus, purpose, research types, methods, types and levels of participants, field/area of application, learner modelling, data gathering tools used and research findings. The current studies reveal that majority of the studies defined a framework or architecture of adaptive intelligent tutoring system (AITS while others focused on impact of AITS on learner satisfaction and academic outcomes. Currents trends, gaps in literature and ications were discussed.

  20. Interactive Learning Environment: Web-based Virtual Hydrological Simulation System using Augmented and Immersive Reality

    Science.gov (United States)

    Demir, I.

    2014-12-01

    Recent developments in internet technologies make it possible to manage and visualize large data on the web. Novel visualization techniques and interactive user interfaces allow users to create realistic environments, and interact with data to gain insight from simulations and environmental observations. The hydrological simulation system is a web-based 3D interactive learning environment for teaching hydrological processes and concepts. The simulation systems provides a visually striking platform with realistic terrain information, and water simulation. Students can create or load predefined scenarios, control environmental parameters, and evaluate environmental mitigation alternatives. The web-based simulation system provides an environment for students to learn about the hydrological processes (e.g. flooding and flood damage), and effects of development and human activity in the floodplain. The system utilizes latest web technologies and graphics processing unit (GPU) for water simulation and object collisions on the terrain. Users can access the system in three visualization modes including virtual reality, augmented reality, and immersive reality using heads-up display. The system provides various scenarios customized to fit the age and education level of various users. This presentation provides an overview of the web-based flood simulation system, and demonstrates the capabilities of the system for various visualization and interaction modes.

  1. The Learning Tutor: A Web based Authoring System to Support Distance Tutoring

    Directory of Open Access Journals (Sweden)

    Omar Abou Khaled

    2000-01-01

    Full Text Available In distance learning contexts, such as those are being widely promoted and developed with the extensive use of ICT (Information and Communication Technology some important issues have to be carefully addressed, in order to make education more effective and available. Distant students have to face sound organizational problems concerning the working time-management and the regulation of all the learning process. These are far more complex at a distance because of the difficulties to understand and objectively evaluate how the study is progressing in term of knowledge and competence acquisition, both for the students themselves and for the teacher who is supposed to adjust the teaching process in case of need. Moreover, the absence of clear indication for the student of the relative level of importance of each piece of information available comes to be another key issue in distance education. This paper describes a Web-based authoring system, the Learning Tutor, conceived to cover these issues. The environment is composed by several interconnected authoring systems: “The Course Description, the Guiding Thread and the Agenda”, “The Work Plan and Themes Reviewer”, and “The Quizzes self-evaluation facility”. This model of combined tools aims at providing the suitable support for organization, work and time management in distance learning processes using well documented mastery learning principles.

  2. Knowledge bases, clinical decision support systems, and rapid learning in oncology.

    Science.gov (United States)

    Yu, Peter Paul

    2015-03-01

    One of the most important benefits of health information technology is to assist the cognitive process of the human mind in the face of vast amounts of health data, limited time for decision making, and the complexity of the patient with cancer. Clinical decision support tools are frequently cited as a technologic solution to this problem, but to date useful clinical decision support systems (CDSS) have been limited in utility and implementation. This article describes three unique sources of health data that underlie fundamentally different types of knowledge bases which feed into CDSS. CDSS themselves comprise a variety of models which are discussed. The relationship of knowledge bases and CDSS to rapid learning health systems design is critical as CDSS are essential drivers of rapid learning in clinical care. Copyright © 2015 by American Society of Clinical Oncology.

  3. Recommender System for E-Learning Based on Semantic Relatedness of Concepts

    Directory of Open Access Journals (Sweden)

    Mao Ye

    2015-08-01

    Full Text Available Digital publishing resources contain a lot of useful and authoritative knowledge. It may be necessary to reorganize the resources by concepts and recommend the related concepts for e-learning. A recommender system is presented in this paper based on the semantic relatedness of concepts computed by texts from digital publishing resources. Firstly, concepts are extracted from encyclopedias. Information in digital publishing resources is then reorganized by concepts. Secondly, concept vectors are generated by skip-gram model and semantic relatedness between concepts is measured according to the concept vectors. As a result, the related concepts and associated information can be recommended to users by the semantic relatedness for learning or reading. History data or users’ preferences data are not needed for recommendation in a specific domain. The technique may not be language-specific. The method shows potential usability for e-learning in a specific domain.

  4. Problem-based learning in communication systems using MATLAB and Simulink

    CERN Document Server

    Choi, Kwonhue

    2016-01-01

    Designed to help teach and understand communication systems using a classroom-tested, active learning approach. This book covers the basic concepts of signals, and analog and digital communications, to more complex simulations in communication systems. Problem-Based Learning in Communication Systems Using MATLAB and Simulink begins by introducing MATLAB and Simulink to prepare readers who are unfamiliar with these environments in order to tackle projects and exercises included in this book. Discussions on simulation of signals, filter design, sampling and reconstruction, and analog communications are covered next. The book concludes by covering advanced topics such as Viterbi decoding, OFDM and MIMO. In addition, this book contains examples of how to convert waveforms, constructed in simulation, into electric signals. It also includes problems illustrating how to complete actual wireless communications in the band near ultrasonic frequencies. A content-m pping table is included in this book to help instruc...

  5. Multi-agent system for Knowledge-based recommendation of Learning Objects

    Directory of Open Access Journals (Sweden)

    Paula Andrea RODRÍGUEZ MARÍN

    2015-12-01

    Full Text Available Learning Object (LO is a content unit being used within virtual learning environments, which -once found and retrieved- may assist students in the teaching - learning process. Such LO search and retrieval are recently supported and enhanced by data mining techniques. In this sense, clustering can be used to find groups holding similar LOs so that from obtained groups, knowledge-based recommender systems (KRS can recommend more adapted and relevant LOs. In particular, prior knowledge come from LOs previously selected, liked and ranked by the student to whom the recommendation will be performed. In this paper, we present a KRS for LOs, which uses a conventional clustering technique, namely K-means, aimed at finding similar LOs and delivering resources adapted to a specific student. Obtained promising results show that proposed KRS is able to both retrieve relevant LO and improve the recommendation precision.Learning Object (LO is a content unit being used within virtual learning environments, which -once found and retrieved- may assist students in the teaching - learning process. Such LO search and retrieval are recently supported and enhanced by data mining techniques. In this sense, clustering can be used to find groups holding similar LOs so that from obtained groups, knowledge-based recommender systems (KRS can recommend more adapted and relevant LOs. In particular, prior knowledge come from LOs previously selected, liked and ranked by the student to whom the recommendation will be performed. In this paper, we present a KRS for LOs, which uses a conventional clustering technique, namely K-means, aimed at finding similar LOs and delivering resources adapted to a specific student. Obtained promising results show that proposed KRS is able to both retrieve relevant LO and improve the recommendation precision.

  6. A neural network-based exploratory learning and motor planning system for co-robots

    Directory of Open Access Journals (Sweden)

    Byron V Galbraith

    2015-07-01

    Full Text Available Collaborative robots, or co-robots, are semi-autonomous robotic agents designed to work alongside humans in shared workspaces. To be effective, co-robots require the ability to respond and adapt to dynamic scenarios encountered in natural environments. One way to achieve this is through exploratory learning, or learning by doing, an unsupervised method in which co-robots are able to build an internal model for motor planning and coordination based on real-time sensory inputs. In this paper, we present an adaptive neural network-based system for co-robot control that employs exploratory learning to achieve the coordinated motor planning needed to navigate toward, reach for, and grasp distant objects. To validate this system we used the 11-degrees-of-freedom RoPro Calliope mobile robot. Through motor babbling of its wheels and arm, the Calliope learned how to relate visual and proprioceptive information to achieve hand-eye-body coordination. By continually evaluating sensory inputs and externally provided goal directives, the Calliope was then able to autonomously select the appropriate wheel and joint velocities needed to perform its assigned task, such as following a moving target or retrieving an indicated object.

  7. A neural network-based exploratory learning and motor planning system for co-robots.

    Science.gov (United States)

    Galbraith, Byron V; Guenther, Frank H; Versace, Massimiliano

    2015-01-01

    Collaborative robots, or co-robots, are semi-autonomous robotic agents designed to work alongside humans in shared workspaces. To be effective, co-robots require the ability to respond and adapt to dynamic scenarios encountered in natural environments. One way to achieve this is through exploratory learning, or "learning by doing," an unsupervised method in which co-robots are able to build an internal model for motor planning and coordination based on real-time sensory inputs. In this paper, we present an adaptive neural network-based system for co-robot control that employs exploratory learning to achieve the coordinated motor planning needed to navigate toward, reach for, and grasp distant objects. To validate this system we used the 11-degrees-of-freedom RoPro Calliope mobile robot. Through motor babbling of its wheels and arm, the Calliope learned how to relate visual and proprioceptive information to achieve hand-eye-body coordination. By continually evaluating sensory inputs and externally provided goal directives, the Calliope was then able to autonomously select the appropriate wheel and joint velocities needed to perform its assigned task, such as following a moving target or retrieving an indicated object.

  8. Semi-active control of magnetorheological elastomer base isolation system utilising learning-based inverse model

    Science.gov (United States)

    Gu, Xiaoyu; Yu, Yang; Li, Jianchun; Li, Yancheng

    2017-10-01

    Magnetorheological elastomer (MRE) base isolations have attracted considerable attention over the last two decades thanks to its self-adaptability and high-authority controllability in semi-active control realm. Due to the inherent nonlinearity and hysteresis of the devices, it is challenging to obtain a reasonably complicated mathematical model to describe the inverse dynamics of MRE base isolators and hence to realise control synthesis of the MRE base isolation system. Two aims have been achieved in this paper: i) development of an inverse model for MRE base isolator based on optimal general regression neural network (GRNN); ii) numerical and experimental validation of a real-time semi-active controlled MRE base isolation system utilising LQR controller and GRNN inverse model. The superiority of GRNN inverse model lays in fewer input variables requirement, faster training process and prompt calculation response, which makes it suitable for online training and real-time control. The control system is integrated with a three-storey shear building model and control performance of the MRE base isolation system is compared with bare building, passive-on isolation system and passive-off isolation system. Testing results show that the proposed GRNN inverse model is able to reproduce desired control force accurately and the MRE base isolation system can effectively suppress the structural responses when compared to the passive isolation system.

  9. Design a Learning-Oriented Fall Event Reporting System Based on Kirkpatrick Model.

    Science.gov (United States)

    Zhou, Sicheng; Kang, Hong; Gong, Yang

    2017-01-01

    Patient fall has been a severe problem in healthcare facilities around the world due to its prevalence and cost. Routine fall prevention training programs are not as effective as expected. Using event reporting systems is the trend for reducing patient safety events such as falls, although some limitations of the systems exist at current stage. We summarized these limitations through literature review, and developed an improved web-based fall event reporting system. The Kirkpatrick model, widely used in the business area for training program evaluation, has been integrated during the design of our system. Different from traditional event reporting systems that only collect and store the reports, our system automatically annotates and analyzes the reported events, and provides users with timely knowledge support specific to the reported event. The paper illustrates the design of our system and how its features are intended to reduce patient falls by learning from previous errors.

  10. MO-DE-BRA-02: From Teaching to Learning: Systems-Based-Practice and Practice-Based-Learning Innovations in Medical Physics Education Programs

    Energy Technology Data Exchange (ETDEWEB)

    Kapur, A [North Shore-LIJ Health System, New Hyde Park, NY (United States)

    2015-06-15

    Purpose: The increasing complexity in the field of radiation medicine and concomitant rise in patient safety concerns call for enhanced systems-level training for future medical physicists and thus commensurate innovations in existing educational program curricula. In this work we report on the introduction of three learning opportunities to augment medical physics educational programs towards building systems-based practice and practice-based learning competencies. Methods: All initiatives were introduced for senior -level graduate students and physics residents in an institution with a newly established medical-physics graduate program and therapeutic-physics residency program. The first, centered on incident learning, was based on a spreadsheet tool that incorporated the reporting structure of the Radiation Oncology-incident Learning System (ROILS), included 120 narratives of published incidents and enabled inter-rater variability calculations. The second, centered on best-practices, was a zero-credit seminar course, where students summarized select presentations from the AAPM virtual library on a weekly basis and moderated class discussions using a point/counterpoint approach. Presentation styles were critiqued. The third; centered on learning-by-teaching, required physics residents to regularly explain fundamental concepts in radiological physics from standard textbooks to board certified physics faculty members. Results: Use of the incident-learning system spreadsheet provided a platform to recast known accidents into the framework of ROILS, thereby increasing awareness of factors contributing to unsafe practice and appreciation for inter-rater variability. The seminar course enhanced awareness of best practices, the effectiveness of presentation styles and encouraged critical thinking. The learn-by-teaching rotation allowed residents to stay abreast of and deepen their knowledge of relevant subjects. Conclusion: The incorporation of systems

  11. MO-DE-BRA-02: From Teaching to Learning: Systems-Based-Practice and Practice-Based-Learning Innovations in Medical Physics Education Programs

    International Nuclear Information System (INIS)

    Kapur, A

    2015-01-01

    Purpose: The increasing complexity in the field of radiation medicine and concomitant rise in patient safety concerns call for enhanced systems-level training for future medical physicists and thus commensurate innovations in existing educational program curricula. In this work we report on the introduction of three learning opportunities to augment medical physics educational programs towards building systems-based practice and practice-based learning competencies. Methods: All initiatives were introduced for senior -level graduate students and physics residents in an institution with a newly established medical-physics graduate program and therapeutic-physics residency program. The first, centered on incident learning, was based on a spreadsheet tool that incorporated the reporting structure of the Radiation Oncology-incident Learning System (ROILS), included 120 narratives of published incidents and enabled inter-rater variability calculations. The second, centered on best-practices, was a zero-credit seminar course, where students summarized select presentations from the AAPM virtual library on a weekly basis and moderated class discussions using a point/counterpoint approach. Presentation styles were critiqued. The third; centered on learning-by-teaching, required physics residents to regularly explain fundamental concepts in radiological physics from standard textbooks to board certified physics faculty members. Results: Use of the incident-learning system spreadsheet provided a platform to recast known accidents into the framework of ROILS, thereby increasing awareness of factors contributing to unsafe practice and appreciation for inter-rater variability. The seminar course enhanced awareness of best practices, the effectiveness of presentation styles and encouraged critical thinking. The learn-by-teaching rotation allowed residents to stay abreast of and deepen their knowledge of relevant subjects. Conclusion: The incorporation of systems

  12. The Multimedia-Based Learning System Improved Cognitive Skills and Motivation of Disabled Children with a Very High Rate

    Science.gov (United States)

    Saad, Sawsan; Dandashi, Amal; Aljaam, Jihad M.; Saleh, Moataz

    2015-01-01

    A multimedia-based learning system to teach children with intellectual disabilities (ID) the basic living and science concepts is proposed. The tutorials' development is pedagogically based on Mayer's Cognitive Theory of Multimedia Learning combined with Skinner's Operant Conditioning Model. Two types of tutorials are proposed. In the first type;…

  13. A Web-based Multilingual Intelligent Tutor System based on Jackson's Learning Styles Profiler and Expert Systems

    OpenAIRE

    Ghadirli, Hossein Movafegh; Rastgarpour, Maryam

    2013-01-01

    Nowadays, Intelligent Tutoring Systems (ITSs) are so regarded in order to improve education quality via new technologies in this area. One of the problems is that the language of ITSs is different from the learner's. It forces the learners to learn the system language. This paper tries to remove this necessity by using an Automatic Translator Component in system structure like Google Translate API. This system carry out a pre-test and post-test by using Expert System and Jackson Model before ...

  14. Interactive Web-based e-learning for Studying Flexible Manipulator Systems

    Directory of Open Access Journals (Sweden)

    Abul K. M. Azad

    2008-03-01

    Full Text Available Abstract— This paper presents a web-based e-leaning facility for simulation, modeling, and control of flexible manipulator systems. The simulation and modeling part includes finite difference and finite element simulations along with neural network and genetic algorithm based modeling strategies for flexible manipulator systems. The controller part constitutes a number of open-loop and closed-loop designs. Closed loop control designs include the classical, adaptive, and neuro-model based strategies. Matlab software package and its associated toolboxes are used to implement these. The Matlab web server is used as the gateway between the facility and web-access. ASP.NET technology and SQL database are utilized to develop web applications for access control, user account and password maintenance, administrative management, and facility utilization monitoring. The reported facility provides a flexible but effective approach of web-based interactive e-learning facility of an engineering system. This can be extended to incorporate additional engineering systems within the e-learning framework.

  15. Systemic impediments to the implementation of Project Based Learning in middle and high school settings

    Science.gov (United States)

    Bouilly, Delphine

    This study examines the potential structural impediments to the reform movement of Project Based Learning (PBL) that are presented to teachers by the inherent nature of the school system, as well as the ways in which teachers address these systemic barriers when attempting to implement PBL in their classrooms. Much of the current research that is aimed at investigating the transition from traditional teacher-centered learning to student-centered PBL---whether PBL as problem based or project based learning---has focused on the transition issues at the level of individual teacher/student. Systemic barriers, on the other hand, are those features that are inherent to the structure of the system, and that pose---by their very nature---physical and/or political circumstances that are inconsistent with the student-centered and collaborative goals of PBL. It is not enough for teachers, parents, students, and administrators to be philosophically aligned with PBL, if the encompassing school system is structurally incompatible with the method. This study attempts to make the structural impediments to PBL explicit, to determine whether or not the existing school system is amenable to the successful implementation of PBL. Because the universal features of PBL coupled with the ubiquity of factory-model schools is likely to create recurring themes, it is plausible that this study may in fact be analytically generalizable to situations beyond those described by the populations and contexts in this set of purposive, multiple cases. One of the themes that emerged from this study was the role of rural poverty as an underlying cause of student apathy. More research may be needed to see whether science, as taught through PBL and in collaboration with practical arts courses, might be able to address some of the social, gendered, and educational needs of impoverished rural students and their families.

  16. Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System

    Directory of Open Access Journals (Sweden)

    Guofeng Tong

    2014-04-01

    Full Text Available This paper proposes an adaptive iterative learning control strategy integrated with saturation-based robust control for uncertain robot system in presence of modelling uncertainties, unknown parameter, and external disturbance under alignment condition. An important merit is that it achieves adaptive switching of gain matrix both in conventional PD-type feedforward control and robust adaptive control in the iteration domain simultaneously. The analysis of convergence of proposed control law is based on Lyapunov's direct method under alignment initial condition. Simulation results demonstrate the faster learning rate and better robust performance with proposed algorithm by comparing with other existing robust controllers. The actual experiment on three-DOF robot manipulator shows its better practical effectiveness.

  17. iCBLS: An interactive case-based learning system for medical education.

    Science.gov (United States)

    Ali, Maqbool; Han, Soyeon Caren; Bilal, Hafiz Syed Muhammad; Lee, Sungyoung; Kang, Matthew Jee Yun; Kang, Byeong Ho; Razzaq, Muhammad Asif; Amin, Muhammad Bilal

    2018-01-01

    Medical students should be able to actively apply clinical reasoning skills to further their interpretative, diagnostic, and treatment skills in a non-obtrusive and scalable way. Case-Based Learning (CBL) approach has been receiving attention in medical education as it is a student-centered teaching methodology that exposes students to real-world scenarios that need to be solved using their reasoning skills and existing theoretical knowledge. In this paper, we propose an interactive CBL System, called iCBLS, which supports the development of collaborative clinical reasoning skills for medical students in an online environment. The iCBLS consists of three modules: (i) system administration (SA), (ii) clinical case creation (CCC) with an innovative semi-automatic approach, and (iii) case formulation (CF) through intervention of medical students' and teachers' knowledge. Two evaluations under the umbrella of the context/input/process/product (CIPP) model have been performed with a Glycemia study. The first focused on the system satisfaction, evaluated by 54 students. The latter aimed to evaluate the system effectiveness, simulated by 155 students. The results show a high success rate of 70% for students' interaction, 76.4% for group learning, 72.8% for solo learning, and 74.6% for improved clinical skills. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Web-Based Learning System for Developing and Assessing Clinical Diagnostic Skills for Dermatology Residency Program

    Science.gov (United States)

    Kuo, Fan-Ray; Chin, Yi-Ying; Lee, Chao-Hsien; Chiu, Yu-Hsien; Hong, Chien-Hu; Lee, Kuang-Lieh; Ho, Wen-Hsien; Lee, Chih-Hung

    2016-01-01

    Few studies have explored the learning difficulties and misconceptions that students encounter when using information and communication technology for e-learning. To address this issue, this research developed a system for evaluating the learning efficiency of medical students by applying two-tier diagnosis assessment. The effectiveness of the…

  19. Addressing Electronic Communications System Learning through a Radar-Based Active Learning Project

    Science.gov (United States)

    Hernandez-Jayo, Unai; López-Garde, Juan-Manuel; Rodríguez-Seco, J. Emilio

    2015-01-01

    In the Master's of Telecommunication Engineering program at the University of Deusto, Spain, courses in communication circuit design, electronic instrumentation, advanced systems for signal processing and radiocommunication systems allow students to acquire concepts crucial to the fields of electronics and communication. During the educational…

  20. Application of Project-Based Learning (PBL) to the Teaching of Electrical Power Systems Engineering

    Science.gov (United States)

    Hosseinzadeh, N.; Hesamzadeh, M. R.

    2012-01-01

    Project-based learning (PBL), a learning environment in which projects drive learning, has been successfully used in various courses in the educational programs of different disciplines. However, concerns have been raised as to the breadth of the content covered and, in particular, whether PBL can be applied to specialized subjects without…

  1. Creating Usage Context-Based Object Similarities to Boost Recommender Systems in Technology Enhanced Learning

    Science.gov (United States)

    Niemann, Katja; Wolpers, Martin

    2015-01-01

    In this paper, we introduce a new way of detecting semantic similarities between learning objects by analysing their usage in web portals. Our approach relies on the usage-based relations between the objects themselves rather then on the content of the learning objects or on the relations between users and learning objects. We then take this new…

  2. VLSI Design of SVM-Based Seizure Detection System With On-Chip Learning Capability.

    Science.gov (United States)

    Feng, Lichen; Li, Zunchao; Wang, Yuanfa

    2018-02-01

    Portable automatic seizure detection system is very convenient for epilepsy patients to carry. In order to make the system on-chip trainable with high efficiency and attain high detection accuracy, this paper presents a very large scale integration (VLSI) design based on the nonlinear support vector machine (SVM). The proposed design mainly consists of a feature extraction (FE) module and an SVM module. The FE module performs the three-level Daubechies discrete wavelet transform to fit the physiological bands of the electroencephalogram (EEG) signal and extracts the time-frequency domain features reflecting the nonstationary signal properties. The SVM module integrates the modified sequential minimal optimization algorithm with the table-driven-based Gaussian kernel to enable efficient on-chip learning. The presented design is verified on an Altera Cyclone II field-programmable gate array and tested using the two publicly available EEG datasets. Experiment results show that the designed VLSI system improves the detection accuracy and training efficiency.

  3. A Machine Learning-based Rainfall System for GPM Dual-frequency Radar

    Science.gov (United States)

    Tan, H.; Chandrasekar, V.; Chen, H.

    2017-12-01

    Precipitation measurement produced by the Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) plays an important role in researching the water circle and forecasting extreme weather event. Compare with its predecessor - Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), GRM DPR measures precipitation in two different frequencies (i.e., Ku and Ka band), which can provide detailed information on the microphysical properties of precipitation particles, quantify particle size distribution and quantitatively measure light rain and falling snow. This paper presents a novel Machine Learning system for ground-based and space borne radar rainfall estimation. The system first trains ground radar data for rainfall estimation using rainfall measurements from gauges and subsequently uses the ground radar based rainfall estimates to train GPM DPR data in order to get space based rainfall product. Therein, data alignment between space DPR and ground radar is conducted using the methodology proposed by Bolen and Chandrasekar (2013), which can minimize the effects of potential geometric distortion of GPM DPR observations. For demonstration purposes, rainfall measurements from three rain gauge networks near Melbourne, Florida, are used for training and validation purposes. These three gauge networks, which are located in Kennedy Space Center (KSC), South Florida Water Management District (SFL), and St. Johns Water Management District (STJ), include 33, 46, and 99 rain gauge stations, respectively. Collocated ground radar observations from the National Weather Service (NWS) Weather Surveillance Radar - 1988 Doppler (WSR-88D) in Melbourne (i.e., KMLB radar) are trained with the gauge measurements. The trained model is then used to derive KMLB radar based rainfall product, which is used to train GPM DPR data collected from coincident overpasses events. The machine learning based rainfall product is compared against the GPM standard products

  4. Implementing Practical Based Courses under Open and Distance Learning System: A Study of the Perception of Learners and Counsellors

    Science.gov (United States)

    Basantia, Tapan Kumar

    2018-01-01

    Implementing practical based courses under Open and Distance Learning (ODL) system is a very difficult and challenging task as the teaching of practical based courses involves intensive practical work. For removing the difficulties and challenges in implementing the practical based courses under ODL system, there is a need to study the existing…

  5. Web 2.0 systems supporting childhood chronic disease management: design guidelines based on information behaviour and social learning theories.

    Science.gov (United States)

    Ekberg, Joakim; Ericson, Leni; Timpka, Toomas; Eriksson, Henrik; Nordfeldt, Sam; Hanberger, Lena; Ludvigsson, Johnny

    2010-04-01

    Self-directed learning denotes that the individual is in command of what should be learned and why it is important. In this study, guidelines for the design of Web 2.0 systems for supporting diabetic adolescents' every day learning needs are examined in light of theories about information behaviour and social learning. A Web 2.0 system was developed to support a community of practice and social learning structures were created to support building of relations between members on several levels in the community. The features of the system included access to participation in the culture of diabetes management practice, entry to information about the community and about what needs to be learned to be a full practitioner or respected member in the community, and free sharing of information, narratives and experience-based knowledge. After integration with the key elements derived from theories of information behaviour, a preliminary design guideline document was formulated.

  6. Web-based newborn screening system for metabolic diseases: machine learning versus clinicians.

    Science.gov (United States)

    Chen, Wei-Hsin; Hsieh, Sheau-Ling; Hsu, Kai-Ping; Chen, Han-Ping; Su, Xing-Yu; Tseng, Yi-Ju; Chien, Yin-Hsiu; Hwu, Wuh-Liang; Lai, Feipei

    2013-05-23

    A hospital information system (HIS) that integrates screening data and interpretation of the data is routinely requested by hospitals and parents. However, the accuracy of disease classification may be low because of the disease characteristics and the analytes used for classification. The objective of this study is to describe a system that enhanced the neonatal screening system of the Newborn Screening Center at the National Taiwan University Hospital. The system was designed and deployed according to a service-oriented architecture (SOA) framework under the Web services .NET environment. The system consists of sample collection, testing, diagnosis, evaluation, treatment, and follow-up services among collaborating hospitals. To improve the accuracy of newborn screening, machine learning and optimal feature selection mechanisms were investigated for screening newborns for inborn errors of metabolism. The framework of the Newborn Screening Hospital Information System (NSHIS) used the embedded Health Level Seven (HL7) standards for data exchanges among heterogeneous platforms integrated by Web services in the C# language. In this study, machine learning classification was used to predict phenylketonuria (PKU), hypermethioninemia, and 3-methylcrotonyl-CoA-carboxylase (3-MCC) deficiency. The classification methods used 347,312 newborn dried blood samples collected at the Center between 2006 and 2011. Of these, 220 newborns had values over the diagnostic cutoffs (positive cases) and 1557 had values that were over the screening cutoffs but did not meet the diagnostic cutoffs (suspected cases). The original 35 analytes and the manifested features were ranked based on F score, then combinations of the top 20 ranked features were selected as input features to support vector machine (SVM) classifiers to obtain optimal feature sets. These feature sets were tested using 5-fold cross-validation and optimal models were generated. The datasets collected in year 2011 were used as

  7. Design and Implementation of Mobile Learning System for Soldiers’ Vocational Skill Identification Based on Android

    Science.gov (United States)

    Ma, Jinqiang

    2017-09-01

    To carry out the identification of the professional skills of the soldiers is to further promote the regularization of the needs of the fire brigade, in accordance with the “public security active forces soldiers professional skills identification implementation approach” to meet the needs of candidates for mobile learning to solve the paper learning materials bring a lot of inconvenience; This article uses the Android technology to develop a set of soldiers professional skills Identification Theory learning app, the learning software based on mobile learning, learning function is perfect, you can learn to practice, to achieve the goal of learning at any time, to enhance the soldier's post ability has a good practical value.

  8. Reinforcement learning design-based adaptive tracking control with less learning parameters for nonlinear discrete-time MIMO systems.

    Science.gov (United States)

    Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip; Li, Dong-Juan

    2015-01-01

    Based on the neural network (NN) approximator, an online reinforcement learning algorithm is proposed for a class of affine multiple input and multiple output (MIMO) nonlinear discrete-time systems with unknown functions and disturbances. In the design procedure, two networks are provided where one is an action network to generate an optimal control signal and the other is a critic network to approximate the cost function. An optimal control signal and adaptation laws can be generated based on two NNs. In the previous approaches, the weights of critic and action networks are updated based on the gradient descent rule and the estimations of optimal weight vectors are directly adjusted in the design. Consequently, compared with the existing results, the main contributions of this paper are: 1) only two parameters are needed to be adjusted, and thus the number of the adaptation laws is smaller than the previous results and 2) the updating parameters do not depend on the number of the subsystems for MIMO systems and the tuning rules are replaced by adjusting the norms on optimal weight vectors in both action and critic networks. It is proven that the tracking errors, the adaptation laws, and the control inputs are uniformly bounded using Lyapunov analysis method. The simulation examples are employed to illustrate the effectiveness of the proposed algorithm.

  9. IMPROVING THE EDUCATIONAL PROCESS BASED ON THE USE OF INFORMATION LEARNING MANAGEMENT SYSTEMS

    Directory of Open Access Journals (Sweden)

    Aleksandra B. Kriger

    2015-01-01

    Full Text Available The paper considers with the development of effective educational process, using leaning management system. The analysis of the results of the use Blackboard Learning System for the organization of educational activities to the university students. Built process models of learning (ideal and real on the basis of their proposals on the improvement of the educational process. 

  10. A SCORM Thin Client Architecture for E-Learning Systems Based on Web Services

    Science.gov (United States)

    Casella, Giovanni; Costagliola, Gennaro; Ferrucci, Filomena; Polese, Giuseppe; Scanniello, Giuseppe

    2007-01-01

    In this paper we propose an architecture of e-learning systems characterized by the use of Web services and a suitable middleware component. These technical infrastructures allow us to extend the system with new services as well as to integrate and reuse heterogeneous software e-learning components. Moreover, they let us better support the…

  11. Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs.

    Science.gov (United States)

    Li, Zhixi; He, Yifan; Keel, Stuart; Meng, Wei; Chang, Robert T; He, Mingguang

    2018-03-02

    To assess the performance of a deep learning algorithm for detecting referable glaucomatous optic neuropathy (GON) based on color fundus photographs. A deep learning system for the classification of GON was developed for automated classification of GON on color fundus photographs. We retrospectively included 48 116 fundus photographs for the development and validation of a deep learning algorithm. This study recruited 21 trained ophthalmologists to classify the photographs. Referable GON was defined as vertical cup-to-disc ratio of 0.7 or more and other typical changes of GON. The reference standard was made until 3 graders achieved agreement. A separate validation dataset of 8000 fully gradable fundus photographs was used to assess the performance of this algorithm. The area under receiver operator characteristic curve (AUC) with sensitivity and specificity was applied to evaluate the efficacy of the deep learning algorithm detecting referable GON. In the validation dataset, this deep learning system achieved an AUC of 0.986 with sensitivity of 95.6% and specificity of 92.0%. The most common reasons for false-negative grading (n = 87) were GON with coexisting eye conditions (n = 44 [50.6%]), including pathologic or high myopia (n = 37 [42.6%]), diabetic retinopathy (n = 4 [4.6%]), and age-related macular degeneration (n = 3 [3.4%]). The leading reason for false-positive results (n = 480) was having other eye conditions (n = 458 [95.4%]), mainly including physiologic cupping (n = 267 [55.6%]). Misclassification as false-positive results amidst a normal-appearing fundus occurred in only 22 eyes (4.6%). A deep learning system can detect referable GON with high sensitivity and specificity. Coexistence of high or pathologic myopia is the most common cause resulting in false-negative results. Physiologic cupping and pathologic myopia were the most common reasons for false-positive results. Copyright © 2018 American Academy of Ophthalmology. Published by

  12. The New School-Based Learning (SBL) to Work-Based Learning (WBL) Transition Module: A Practical Implementation in the Technical and Vocational Education (TVE) System in Bahrain

    Science.gov (United States)

    Alseddiqi, M.; Mishra, R.; Pislaru, C.

    2012-05-01

    This paper diagnoses the implementation of a new engineering course entitled 'school-based learning (SBL) to work-based learning (WBL) transition module' in the Bahrain Technical and Vocational Education (TVE) learning environment. The module was designed to incorporate an innovative education and training approach with a variety of learning activities that are included in various learning case studies. Each case study was based on with learning objectives coupled with desired learning outcomes. The TVE students should meet the desired outcomes after the completion of the learning activities and assessments. To help with the implementation phase of the new module, the authors developed guidelines for each case study. The guidelines incorporated learning activities to be delivered in an integrated learning environment. The skills to be transferred were related to cognitive, affective, and technical proficiencies. The guidelines included structured instructions to help students during the learning process. In addition, technology was introduced to improve learning effectiveness and flexibility. The guidelines include learning indicators for each learning activity and were based on their interrelation with competencies to be achieved with respect to modern industrial requirements. Each learning indicator was then correlated against the type of learning environment, teaching and learning styles, examples of mode of delivery, and assessment strategy. Also, the learning activities were supported by technological features such as discussion forums for social perception and engagement and immediate feedback exercises for self-motivation. Through the developed module, TVE teachers can effectively manage the teaching and learning process as well as the assessment strategy to satisfy students' individual requirements and enable them to meet workplace requirements.

  13. Differentiation of Enhancing Glioma and Primary Central Nervous System Lymphoma by Texture-Based Machine Learning.

    Science.gov (United States)

    Alcaide-Leon, P; Dufort, P; Geraldo, A F; Alshafai, L; Maralani, P J; Spears, J; Bharatha, A

    2017-06-01

    Accurate preoperative differentiation of primary central nervous system lymphoma and enhancing glioma is essential to avoid unnecessary neurosurgical resection in patients with primary central nervous system lymphoma. The purpose of the study was to evaluate the diagnostic performance of a machine-learning algorithm by using texture analysis of contrast-enhanced T1-weighted images for differentiation of primary central nervous system lymphoma and enhancing glioma. Seventy-one adult patients with enhancing gliomas and 35 adult patients with primary central nervous system lymphomas were included. The tumors were manually contoured on contrast-enhanced T1WI, and the resulting volumes of interest were mined for textural features and subjected to a support vector machine-based machine-learning protocol. Three readers classified the tumors independently on contrast-enhanced T1WI. Areas under the receiver operating characteristic curves were estimated for each reader and for the support vector machine classifier. A noninferiority test for diagnostic accuracy based on paired areas under the receiver operating characteristic curve was performed with a noninferiority margin of 0.15. The mean areas under the receiver operating characteristic curve were 0.877 (95% CI, 0.798-0.955) for the support vector machine classifier; 0.878 (95% CI, 0.807-0.949) for reader 1; 0.899 (95% CI, 0.833-0.966) for reader 2; and 0.845 (95% CI, 0.757-0.933) for reader 3. The mean area under the receiver operating characteristic curve of the support vector machine classifier was significantly noninferior to the mean area under the curve of reader 1 ( P = .021), reader 2 ( P = .035), and reader 3 ( P = .007). Support vector machine classification based on textural features of contrast-enhanced T1WI is noninferior to expert human evaluation in the differentiation of primary central nervous system lymphoma and enhancing glioma. © 2017 by American Journal of Neuroradiology.

  14. Designing electronic module based on learning content development system in fostering students’ multi representation skills

    Science.gov (United States)

    Resita, I.; Ertikanto, C.

    2018-05-01

    This study aims to develop electronic module design based on Learning Content Development System (LCDS) to foster students’ multi representation skills in physics subject material. This study uses research and development method to the product design. This study involves 90 students and 6 physics teachers who were randomly chosen from 3 different Senior High Schools in Lampung Province. The data were collected by using questionnaires and analyzed by using quantitative descriptive method. Based on the data, 95% of the students only use one form of representation in solving physics problems. Representation which is tend to be used by students is symbolic representation. Students are considered to understand the concept of physics if they are able to change from one form to the other forms of representation. Product design of LCDS-based electronic module presents text, image, symbolic, video, and animation representation.

  15. Students learn systems-based care and facilitate system change as stakeholders in a free clinic experience.

    Science.gov (United States)

    Colbert, Colleen Y; Ogden, Paul E; Lowe, Darla; Moffitt, Michael J

    2010-10-01

    Systems-based practice (SBP) is rarely taught or evaluated during medical school, yet is one of the required competencies once students enter residency. We believe Texas A&M College of Medicine students learn about systems issues informally, as they care for patients at a free clinic in Temple, TX. The mandatory free clinic rotation is part of the Internal Medicine clerkship and does not include formal instruction in SBP. During 2008-2009, a sample of students (n = 31) on the IMED clerkship's free clinic rotation participated in a program evaluation/study regarding their experiences. Focus groups (M = 5 students/group) were held at the end of each outpatient rotation. Students were asked: "Are you aware of any system issues which can affect either the delivery of or access to care at the free clinic?" Data saturation was reached after six focus groups, when investigators noted a repetition of responses. Based upon investigator consensus opinion, data collection was discontinued. Based upon a content analysis, six themes were identified: access to specialists, including OB-GYN, was limited; cost containment; lack of resources affects delivery of care; delays in care due to lack of insurance; understanding of larger healthcare system and free clinic role; and delays in tests due to language barriers. Medical students were able to learn about SBP issues during free clinic rotations. Students experienced how SBP issues affected the health care of uninsured individuals. We believe these findings may be transferable to medical schools with mandatory free clinic rotations.

  16. Applied learning-based color tone mapping for face recognition in video surveillance system

    Science.gov (United States)

    Yew, Chuu Tian; Suandi, Shahrel Azmin

    2012-04-01

    In this paper, we present an applied learning-based color tone mapping technique for video surveillance system. This technique can be applied onto both color and grayscale surveillance images. The basic idea is to learn the color or intensity statistics from a training dataset of photorealistic images of the candidates appeared in the surveillance images, and remap the color or intensity of the input image so that the color or intensity statistics match those in the training dataset. It is well known that the difference in commercial surveillance cameras models, and signal processing chipsets used by different manufacturers will cause the color and intensity of the images to differ from one another, thus creating additional challenges for face recognition in video surveillance system. Using Multi-Class Support Vector Machines as the classifier on a publicly available video surveillance camera database, namely SCface database, this approach is validated and compared to the results of using holistic approach on grayscale images. The results show that this technique is suitable to improve the color or intensity quality of video surveillance system for face recognition.

  17. BASED DESIGN MOBILE LEARNING COURSE ON ANDROID OPERATING SYSTEM IN INDONESIA STMIK PADANG

    Directory of Open Access Journals (Sweden)

    Liranti Rahmelina

    2017-09-01

    Full Text Available This research in the wake of the habit among students and lecturers in the uses smartphones, mostly only used to access social networks such as facebook and twitter and have yet to take an important role in education. This study aims to produce a system design mobile learning courses Operating Systems in STMIK Indonesia Padang, preferably in the learning process in the subject of the Operating System, the nature of memorization to books and teaching conventional. These mobile devices have a degree of flexibility and portability that enable high students can access materials, referrals and information related to learning anytime and anywhere. mobile learning android ased Operating System. This material requires a solid understanding and so we need learning support media and can be repeated whenever and wherever students need. The design of supporting mobile learning media is expected to facilitate the needs of students and teachers to learn the material at any time without any limitation of time and place. This study uses SDLC (System Development Life Cycle is a method that describes the system development life cycle in the design and development of information systems. The programming language used is Java, using Eclipse IDE.

  18. Smart-system of distance learning of visually impaired people based on approaches of artificial intelligence

    Science.gov (United States)

    Samigulina, Galina A.; Shayakhmetova, Assem S.

    2016-11-01

    Research objective is the creation of intellectual innovative technology and information Smart-system of distance learning for visually impaired people. The organization of the available environment for receiving quality education for visually impaired people, their social adaptation in society are important and topical issues of modern education.The proposed Smart-system of distance learning for visually impaired people can significantly improve the efficiency and quality of education of this category of people. The scientific novelty of proposed Smart-system is using intelligent and statistical methods of processing multi-dimensional data, and taking into account psycho-physiological characteristics of perception and awareness learning information by visually impaired people.

  19. A Web-based Peer Assessment System for Assigning Student Scores in Cooperative Learning

    Directory of Open Access Journals (Sweden)

    Anon Sukstrienwong

    2017-11-01

    Full Text Available Working in groups has become increasingly important in order to develop students' skills. However, it can be more successful when peers cooperate and are involved in the assigned tasks. However, several educators firmly show disadvantages when all peers received the same reward, regardless of individual contribution. Some teachers also considering peer assessment to be time and effort consuming because preparation and monitoring are needed. In order to overcome these problems, we have developed a web-based peer assessment referred to as the ‘Scoring by Peer Assessment System’ (SPAS that allows teachers to set up the process of peer assessment, in order to assign scores that reflect the contribution of each student. Moreover, a web-based application allows students to evaluate their peers regarding their individual contribution where cooperative learning and peer assessment are used. The paper describes the system design and the implementation of our peer assessment application.

  20. Innovation in a Learning Health Care System: Veteran-Directed Home- and Community-Based Services.

    Science.gov (United States)

    Garrido, Melissa M; Allman, Richard M; Pizer, Steven D; Rudolph, James L; Thomas, Kali S; Sperber, Nina R; Van Houtven, Courtney H; Frakt, Austin B

    2017-11-01

    A path-breaking example of the interplay between geriatrics and learning healthcare systems is the Veterans Health Administration's (VHA's) planned roll-out of a program for providing participant-directed home- and community-based services to veterans with cognitive and functional limitations. We describe the design of a large-scale, stepped-wedge, cluster-randomized trial of the Veteran-Directed Home- and Community-Based Services (VD-HCBS) program. From March 2017 through December 2019, up to 77 Veterans Affairs Medical Centers will be randomized to times to begin offering VD-HCBS to veterans at risk of nursing home placement. Services will be provided to community-dwelling participants with support from Aging and Disability Network Agencies. The VHA Partnered Evidence-based Policy Resource Center (PEPReC) is coordinating the evaluation, which includes collaboration from operational stakeholders from the VHA and Administration for Community Living and interdisciplinary researchers from the Center of Innovation in Long-Term Services and Supports and the Center for Health Services Research in Primary Care. For older veterans with functional limitations who are eligible for VD-HCBS, we will evaluate health outcomes (hospitalizations, emergency department visits, nursing home admissions, days at home) and healthcare costs associated with VD-HCBS availability. Learning healthcare systems facilitate diffusion of innovation while enabling rigorous evaluation of effects on patient outcomes. The VHA's randomized rollout of VD-HCBS to veterans at risk of nursing home placement is an example of how to achieve these goals simultaneously. PEPReC's experience designing an evaluation with researchers and operations stakeholders may serve as a framework for others seeking to develop rapid, rigorous, large-scale evaluations of delivery system innovations targeted to older adults. © 2017, Copyright the Authors Journal compilation © 2017, The American Geriatrics Society.

  1. Using a Dialogue System Based on Dialogue Maps for Computer Assisted Second Language Learning

    Science.gov (United States)

    Choi, Sung-Kwon; Kwon, Oh-Woog; Kim, Young-Kil; Lee, Yunkeun

    2016-01-01

    In order to use dialogue systems for computer assisted second-language learning systems, one of the difficult issues in such systems is how to construct large-scale dialogue knowledge that matches the dialogue modelling of a dialogue system. This paper describes how we have accomplished the short-term construction of large-scale and…

  2. SU-E-T-524: Web-Based Radiation Oncology Incident Reporting and Learning System (ROIRLS)

    International Nuclear Information System (INIS)

    Kapoor, R; Palta, J; Hagan, M; Grover, S; Malik, G

    2014-01-01

    Purpose: Describe a Web-based Radiation Oncology Incident Reporting and Learning system that has the potential to improve quality of care for radiation therapy patients. This system is an important facet of continuing effort by our community to maintain and improve safety of radiotherapy.Material and Methods: The VA National Radiation Oncology Program office has embarked on a program to electronically collect adverse events and near miss data of radiation treatment of over 25,000 veterans treated with radiotherapy annually. Software used for this program is deployed on the VAs intranet as a Website. All data entry forms (adverse event or near miss reports, work product reports) utilize standard causal, RT process step taxonomies and data dictionaries defined in AAPM and ASTRO reports on error reporting (AAPM Work Group Report on Prevention of Errors and ASTROs safety is no accident report). All reported incidents are investigated by the radiation oncology domain experts. This system encompasses the entire feedback loop of reporting an incident, analyzing it for salient details, and developing interventions to prevent it from happening again. The operational workflow is similar to that of the Aviation Safety Reporting System. This system is also synergistic with ROSIS and SAFRON. Results: The ROIRLS facilitates the collection of data that help in tracking adverse events and near misses and develop new interventions to prevent such incidents. The ROIRLS electronic infrastructure is fully integrated with each registered facility profile data thus minimizing key strokes and multiple entries by the event reporters. Conclusions: OIRLS is expected to improve the quality and safety of a broad spectrum of radiation therapy patients treated in the VA and fulfills our goal of Effecting Quality While Treating Safely The Radiation Oncology Incident Reporting and Learning System software used for this program has been developed, conceptualized and maintained by TSG Innovations

  3. SU-E-T-524: Web-Based Radiation Oncology Incident Reporting and Learning System (ROIRLS)

    Energy Technology Data Exchange (ETDEWEB)

    Kapoor, R; Palta, J; Hagan, M [Virginia Commonwealth University, Richmond, VA (United States); National Radiation Oncology Program (10P4H), Richmond, VA (United States); Grover, S; Malik, G [TSG Innovations Inc., Richmond, VA (United States)

    2014-06-01

    Purpose: Describe a Web-based Radiation Oncology Incident Reporting and Learning system that has the potential to improve quality of care for radiation therapy patients. This system is an important facet of continuing effort by our community to maintain and improve safety of radiotherapy.Material and Methods: The VA National Radiation Oncology Program office has embarked on a program to electronically collect adverse events and near miss data of radiation treatment of over 25,000 veterans treated with radiotherapy annually. Software used for this program is deployed on the VAs intranet as a Website. All data entry forms (adverse event or near miss reports, work product reports) utilize standard causal, RT process step taxonomies and data dictionaries defined in AAPM and ASTRO reports on error reporting (AAPM Work Group Report on Prevention of Errors and ASTROs safety is no accident report). All reported incidents are investigated by the radiation oncology domain experts. This system encompasses the entire feedback loop of reporting an incident, analyzing it for salient details, and developing interventions to prevent it from happening again. The operational workflow is similar to that of the Aviation Safety Reporting System. This system is also synergistic with ROSIS and SAFRON. Results: The ROIRLS facilitates the collection of data that help in tracking adverse events and near misses and develop new interventions to prevent such incidents. The ROIRLS electronic infrastructure is fully integrated with each registered facility profile data thus minimizing key strokes and multiple entries by the event reporters. Conclusions: OIRLS is expected to improve the quality and safety of a broad spectrum of radiation therapy patients treated in the VA and fulfills our goal of Effecting Quality While Treating Safely The Radiation Oncology Incident Reporting and Learning System software used for this program has been developed, conceptualized and maintained by TSG Innovations

  4. Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

    Science.gov (United States)

    Williams-Hayes, Peggy S.

    2004-01-01

    The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.

  5. The Effect of the Instructional Media Based on Lecture Video and Slide Synchronization System on Statistics Learning Achievement

    Directory of Open Access Journals (Sweden)

    Partha Sindu I Gede

    2018-01-01

    Full Text Available The purpose of this study was to determine the effect of the use of the instructional media based on lecture video and slide synchronization system on Statistics learning achievement of the students of PTI department . The benefit of this research is to help lecturers in the instructional process i to improve student's learning achievements that lead to better students’ learning outcomes. Students can use instructional media which is created from the lecture video and slide synchronization system to support more interactive self-learning activities. Students can conduct learning activities more efficiently and conductively because synchronized lecture video and slide can assist students in the learning process. The population of this research was all students of semester VI (six majoring in Informatics Engineering Education. The sample of the research was the students of class VI B and VI D of the academic year 2016/2017. The type of research used in this study was quasi-experiment. The research design used was post test only with non equivalent control group design. The result of this research concluded that there was a significant influence in the application of learning media based on lectures video and slide synchronization system on statistics learning result on PTI department.

  6. Accelerated Monte Carlo system reliability analysis through machine-learning-based surrogate models of network connectivity

    International Nuclear Information System (INIS)

    Stern, R.E.; Song, J.; Work, D.B.

    2017-01-01

    The two-terminal reliability problem in system reliability analysis is known to be computationally intractable for large infrastructure graphs. Monte Carlo techniques can estimate the probability of a disconnection between two points in a network by selecting a representative sample of network component failure realizations and determining the source-terminal connectivity of each realization. To reduce the runtime required for the Monte Carlo approximation, this article proposes an approximate framework in which the connectivity check of each sample is estimated using a machine-learning-based classifier. The framework is implemented using both a support vector machine (SVM) and a logistic regression based surrogate model. Numerical experiments are performed on the California gas distribution network using the epicenter and magnitude of the 1989 Loma Prieta earthquake as well as randomly-generated earthquakes. It is shown that the SVM and logistic regression surrogate models are able to predict network connectivity with accuracies of 99% for both methods, and are 1–2 orders of magnitude faster than using a Monte Carlo method with an exact connectivity check. - Highlights: • Surrogate models of network connectivity are developed by machine-learning algorithms. • Developed surrogate models can reduce the runtime required for Monte Carlo simulations. • Support vector machine and logistic regressions are employed to develop surrogate models. • Numerical example of California gas distribution network demonstrate the proposed approach. • The developed models have accuracies 99%, and are 1–2 orders of magnitude faster than MCS.

  7. Machine Learning-based discovery of closures for reduced models of dynamical systems

    Science.gov (United States)

    Pan, Shaowu; Duraisamy, Karthik

    2017-11-01

    Despite the successful application of machine learning (ML) in fields such as image processing and speech recognition, only a few attempts has been made toward employing ML to represent the dynamics of complex physical systems. Previous attempts mostly focus on parameter calibration or data-driven augmentation of existing models. In this work we present a ML framework to discover closure terms in reduced models of dynamical systems and provide insights into potential problems associated with data-driven modeling. Based on exact closure models for linear system, we propose a general linear closure framework from viewpoint of optimization. The framework is based on trapezoidal approximation of convolution term. Hyperparameters that need to be determined include temporal length of memory effect, number of sampling points, and dimensions of hidden states. To circumvent the explicit specification of memory effect, a general framework inspired from neural networks is also proposed. We conduct both a priori and posteriori evaluations of the resulting model on a number of non-linear dynamical systems. This work was supported in part by AFOSR under the project ``LES Modeling of Non-local effects using Statistical Coarse-graining'' with Dr. Jean-Luc Cambier as the technical monitor.

  8. Deep Learning-Based Gaze Detection System for Automobile Drivers Using a NIR Camera Sensor

    Directory of Open Access Journals (Sweden)

    Rizwan Ali Naqvi

    2018-02-01

    Full Text Available A paradigm shift is required to prevent the increasing automobile accident deaths that are mostly due to the inattentive behavior of drivers. Knowledge of gaze region can provide valuable information regarding a driver’s point of attention. Accurate and inexpensive gaze classification systems in cars can improve safe driving. However, monitoring real-time driving behaviors and conditions presents some challenges: dizziness due to long drives, extreme lighting variations, glasses reflections, and occlusions. Past studies on gaze detection in cars have been chiefly based on head movements. The margin of error in gaze detection increases when drivers gaze at objects by moving their eyes without moving their heads. To solve this problem, a pupil center corneal reflection (PCCR-based method has been considered. However, the error of accurately detecting the pupil center and corneal reflection center is increased in a car environment due to various environment light changes, reflections on glasses surface, and motion and optical blurring of captured eye image. In addition, existing PCCR-based methods require initial user calibration, which is difficult to perform in a car environment. To address this issue, we propose a deep learning-based gaze detection method using a near-infrared (NIR camera sensor considering driver head and eye movement that does not require any initial user calibration. The proposed system is evaluated on our self-constructed database as well as on open Columbia gaze dataset (CAVE-DB. The proposed method demonstrated greater accuracy than the previous gaze classification methods.

  9. Deep Learning-Based Gaze Detection System for Automobile Drivers Using a NIR Camera Sensor.

    Science.gov (United States)

    Naqvi, Rizwan Ali; Arsalan, Muhammad; Batchuluun, Ganbayar; Yoon, Hyo Sik; Park, Kang Ryoung

    2018-02-03

    A paradigm shift is required to prevent the increasing automobile accident deaths that are mostly due to the inattentive behavior of drivers. Knowledge of gaze region can provide valuable information regarding a driver's point of attention. Accurate and inexpensive gaze classification systems in cars can improve safe driving. However, monitoring real-time driving behaviors and conditions presents some challenges: dizziness due to long drives, extreme lighting variations, glasses reflections, and occlusions. Past studies on gaze detection in cars have been chiefly based on head movements. The margin of error in gaze detection increases when drivers gaze at objects by moving their eyes without moving their heads. To solve this problem, a pupil center corneal reflection (PCCR)-based method has been considered. However, the error of accurately detecting the pupil center and corneal reflection center is increased in a car environment due to various environment light changes, reflections on glasses surface, and motion and optical blurring of captured eye image. In addition, existing PCCR-based methods require initial user calibration, which is difficult to perform in a car environment. To address this issue, we propose a deep learning-based gaze detection method using a near-infrared (NIR) camera sensor considering driver head and eye movement that does not require any initial user calibration. The proposed system is evaluated on our self-constructed database as well as on open Columbia gaze dataset (CAVE-DB). The proposed method demonstrated greater accuracy than the previous gaze classification methods.

  10. The «PBL WORKING ENVIRONMENT» as interactive and expert system to learn the problem-based learning method

    Directory of Open Access Journals (Sweden)

    Susana Correnti

    2016-01-01

    Full Text Available The «PBL working environment» is a virtual environment developed in the framework of SCENE project (profeSsional development for an effeCtive PBL approach: a practical experiENce through ICT-enabled lEarning solution, co-funded by the European Lifelong Learning Program. The «PBL working environment» is devoted to prepare headmasters and teachers of secondary and vocational schools to use Problem-Based Learning (PBL pedagogy effectively. It is a student-centered pedagogy where learners are «actively» engaged in real world problems to solve or challenges to meet. Students develop problem-solving, self-directed learning and team skills. The «PBL working environment» is an virtual tool including three main elements: e-learning platform, virtual facilitator and PBL repository. Teachers, trainers and headmasters/school managers learn the PBL pedagogy by attending an on-line course (e-learning platform delivered through the «inductive method». It allows learners to experience PBL approach, by practicing it stage by stage, and then learn to turn practice into theory by abstracting their experience to build a theoretical understanding. Since generating the proper scenario is the most critical aspect of PBL, after benefiting from the on-line course, users can benefit from a further support: the Virtual Facilitator. It provides tips and hints on how correctly design a problem scenario and by asking questions to collect data on user's specific needs. The Virtual Facilitator is able to provide a/or more suitable example(s which match as closest as possible the teacher/trainer need. Finally, users can share problem scenarios and projects of different subjects of studies and with different characteristics uploaded and downloaded in the PBL repository.

  11. Strengths-based Learning

    DEFF Research Database (Denmark)

    Ledertoug, Mette Marie

    -being. The Ph.D.-project in Strength-based learning took place in a Danish school with 750 pupils age 6-16 and a similar school was functioning as a control group. The presentation will focus on both the aware-explore-apply processes and the practical implications for the schools involved, and on measurable......Strength-based learning - Children͛s Character Strengths as Means to their Learning Potential͛ is a Ph.D.-project aiming to create a strength-based mindset in school settings and at the same time introducing strength-based interventions as specific tools to improve both learning and well...

  12. An Analysis on a Negotiation Model Based on Multiagent Systems with Symbiotic Learning and Evolution

    Science.gov (United States)

    Hossain, Md. Tofazzal

    This study explores an evolutionary analysis on a negotiation model based on Masbiole (Multiagent Systems with Symbiotic Learning and Evolution) which has been proposed as a new methodology of Multiagent Systems (MAS) based on symbiosis in the ecosystem. In Masbiole, agents evolve in consideration of not only their own benefits and losses, but also the benefits and losses of opponent agents. To aid effective application of Masbiole, we develop a competitive negotiation model where rigorous and advanced intelligent decision-making mechanisms are required for agents to achieve solutions. A Negotiation Protocol is devised aiming at developing a set of rules for agents' behavior during evolution. Simulations use a newly developed evolutionary computing technique, called Genetic Network Programming (GNP) which has the directed graph-type gene structure that can develop and design the required intelligent mechanisms for agents. In a typical scenario, competitive negotiation solutions are reached by concessions that are usually predetermined in the conventional MAS. In this model, however, not only concession is determined automatically by symbiotic evolution (making the system intelligent, automated, and efficient) but the solution also achieves Pareto optimal automatically.

  13. The Process, Dialogues, and Attitudes of Vocational Engineering High School Students in a Web Problem-Based Learning (WPBL) System

    Science.gov (United States)

    Tseng, Kuo-Hung; Chang, Chi-Cheng; Lou, Shi-Jer

    2012-01-01

    This study aims to explore how high school students collaboratively solve problems in a web problem-based learning (WPBL) system in an 8-week digital logic course using discourse analysis. Employing in-depth interviews, this study also investigated the students' attitudes toward the WPBL system. The number of teaching assistants' responses had a…

  14. The Evaluation of the Cognitive Learning Process of the Renewed Bloom Taxonomy Using a Web Based Expert System

    Science.gov (United States)

    Goksu, Idris

    2016-01-01

    The aim of this study is to develop the Web Based Expert System (WBES) which provides analyses and reports based on the cognitive processes of Renewed Bloom Taxonomy (RBT), and to put forward the impact of the supportive education provided in line with these reports, on the academic achievement and mastery learning state of the students. The study…

  15. A Classification Model and an Open E-Learning System Based on Intuitionistic Fuzzy Sets for Instructional Design Concepts

    Science.gov (United States)

    Güyer, Tolga; Aydogdu, Seyhmus

    2016-01-01

    This study suggests a classification model and an e-learning system based on this model for all instructional theories, approaches, models, strategies, methods, and technics being used in the process of instructional design that constitutes a direct or indirect resource for educational technology based on the theory of intuitionistic fuzzy sets…

  16. Problem Based Learning

    DEFF Research Database (Denmark)

    de Graaff, Erik; Guerra, Aida

    , the key principles remain the same everywhere. Graaff & Kolmos (2003) identify the main PBL principles as follows: 1. Problem orientation 2. Project organization through teams or group work 3. Participant-directed 4. Experiental learning 5. Activity-based learning 6. Interdisciplinary learning and 7...... model and in general problem based and project based learning. We apply the principle of teach as you preach. The poster aims to outline the visitors’ workshop programme showing the results of some recent evaluations.......Problem-Based Learning (PBL) is an innovative method to organize the learning process in such a way that the students actively engage in finding answers by themselves. During the past 40 years PBL has evolved and diversified resulting in a multitude in variations in models and practices. However...

  17. Hybrid attribute-based recommender system for learning material using genetic algorithm and a multidimensional information model

    Directory of Open Access Journals (Sweden)

    Mojtaba Salehi

    2013-03-01

    Full Text Available In recent years, the explosion of learning materials in the web-based educational systems has caused difficulty of locating appropriate learning materials to learners. A personalized recommendation is an enabling mechanism to overcome information overload occurred in the new learning environments and deliver suitable materials to learners. Since users express their opinions based on some specific attributes of items, this paper proposes a hybrid recommender system for learning materials based on their attributes to improve the accuracy and quality of recommendation. The presented system has two main modules: explicit attribute-based recommender and implicit attribute-based recommender. In the first module, weights of implicit or latent attributes of materials for learner are considered as chromosomes in genetic algorithm then this algorithm optimizes the weights according to historical rating. Then, recommendation is generated by Nearest Neighborhood Algorithm (NNA using the optimized weight vectors implicit attributes that represent the opinions of learners. In the second, preference matrix (PM is introduced that can model the interests of learner based on explicit attributes of learning materials in a multidimensional information model. Then, a new similarity measure between PMs is introduced and recommendations are generated by NNA. The experimental results show that our proposed method outperforms current algorithms on accuracy measures and can alleviate some problems such as cold-start and sparsity.

  18. Recommendation System for Adaptive Learning.

    Science.gov (United States)

    Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Ying, Zhiliang

    2018-01-01

    An adaptive learning system aims at providing instruction tailored to the current status of a learner, differing from the traditional classroom experience. The latest advances in technology make adaptive learning possible, which has the potential to provide students with high-quality learning benefit at a low cost. A key component of an adaptive learning system is a recommendation system, which recommends the next material (video lectures, practices, and so on, on different skills) to the learner, based on the psychometric assessment results and possibly other individual characteristics. An important question then follows: How should recommendations be made? To answer this question, a mathematical framework is proposed that characterizes the recommendation process as a Markov decision problem, for which decisions are made based on the current knowledge of the learner and that of the learning materials. In particular, two plain vanilla systems are introduced, for which the optimal recommendation at each stage can be obtained analytically.

  19. Understanding Motivational System in Open Learning: Learners' Engagement with a Traditional Chinese-Based Open Educational Resource System

    Science.gov (United States)

    Huang, Wenhao David; Wu, Chorng-Guang

    2017-01-01

    Learning has embraced the "open" process in recent years, as many educational resources are made available for free online. Existing research, however, has not provided sufficient evidence to systematically improve open learning interactions and engagement in open educational resource (OER) systems. This deficiency presents two…

  20. A Social Learning Management System Supporting Feedback for Incorrect Answers Based on Social Network Services

    Science.gov (United States)

    Son, Jiseong; Kim, Jeong-Dong; Na, Hong-Seok; Baik, Doo-Kwon

    2016-01-01

    In this research, we propose a Social Learning Management System (SLMS) enabling real-time and reliable feedback for incorrect answers by learners using a social network service (SNS). The proposed system increases the accuracy of learners' assessment results by using a confidence scale and a variety of social feedback that is created and shared…

  1. ANALYSIS OF EFFECTIVENESS OF METHODOLOGICAL SYSTEM FOR PROBABILITY AND STOCHASTIC PROCESSES COMPUTER-BASED LEARNING FOR PRE-SERVICE ENGINEERS

    Directory of Open Access Journals (Sweden)

    E. Chumak

    2015-04-01

    Full Text Available The author substantiates that only methodological training systems of mathematical disciplines with implementation of information and communication technologies (ICT can meet the requirements of modern educational paradigm and make possible to increase the educational efficiency. Due to this fact, the necessity of developing the methodology of theory of probability and stochastic processes computer-based learning for pre-service engineers is underlined in the paper. The results of the experimental study for analysis of the efficiency of methodological system of theory of probability and stochastic processes computer-based learning for pre-service engineers are shown. The analysis includes three main stages: ascertaining, searching and forming. The key criteria of the efficiency of designed methodological system are the level of probabilistic and stochastic skills of students and their learning motivation. The effect of implementing the methodological system of probability theory and stochastic processes computer-based learning on the level of students’ IT literacy is shown in the paper. The expanding of the range of objectives of ICT applying by students is described by author. The level of formation of students’ learning motivation on the ascertaining and forming stages of the experiment is analyzed. The level of intrinsic learning motivation for pre-service engineers is defined on these stages of the experiment. For this purpose, the methodology of testing the students’ learning motivation in the chosen specialty is presented in the paper. The increasing of intrinsic learning motivation of the experimental group students (E group against the control group students (C group is demonstrated.

  2. Teaching Biochemistry at a Medical Faculty with a Problem-Based Learning System.

    Science.gov (United States)

    Rosing, Jan

    1997-01-01

    Highlights the differences between classical teaching methods and problem-based learning. Describes the curriculum and problem-based approach of the Faculty of Medicine at the Maastricht University and gives an overview of the implementation of biochemistry in the medical curriculum. Discusses the procedure for student assessment and presents…

  3. Consensus-based distributed cooperative learning from closed-loop neural control systems.

    Science.gov (United States)

    Chen, Weisheng; Hua, Shaoyong; Zhang, Huaguang

    2015-02-01

    In this paper, the neural tracking problem is addressed for a group of uncertain nonlinear systems where the system structures are identical but the reference signals are different. This paper focuses on studying the learning capability of neural networks (NNs) during the control process. First, we propose a novel control scheme called distributed cooperative learning (DCL) control scheme, by establishing the communication topology among adaptive laws of NN weights to share their learned knowledge online. It is further proved that if the communication topology is undirected and connected, all estimated weights of NNs can converge to small neighborhoods around their optimal values over a domain consisting of the union of all state orbits. Second, as a corollary it is shown that the conclusion on the deterministic learning still holds in the decentralized adaptive neural control scheme where, however, the estimated weights of NNs just converge to small neighborhoods of the optimal values along their own state orbits. Thus, the learned controllers obtained by DCL scheme have the better generalization capability than ones obtained by decentralized learning method. A simulation example is provided to verify the effectiveness and advantages of the control schemes proposed in this paper.

  4. Ontology-based concept map learning path reasoning system using SWRL rules

    Energy Technology Data Exchange (ETDEWEB)

    Chu, K.-K.; Lee, C.-I. [National Univ. of Tainan, Taiwan (China). Dept. of Computer Science and Information Learning Technology

    2010-08-13

    Concept maps are graphical representations of knowledge. Concept mapping may reduce students' cognitive load and extend simple memory function. The purpose of this study was on the diagnosis of students' concept map learning abilities and the provision of personally constructive advice dependant on their learning path and progress. Ontology is a useful method with which to represent and store concept map information. Semantic web rule language (SWRL) rules are easy to understand and to use as specific reasoning services. This paper discussed the selection of grade 7 lakes and rivers curriculum for which to devise a concept map learning path reasoning service. The paper defined a concept map e-learning ontology and two SWRL semantic rules, and collected users' concept map learning path data to infer implicit knowledge and to recommend the next learning path for users. It was concluded that the designs devised in this study were feasible and advanced and the ontology kept the domain knowledge preserved. SWRL rules identified an abstraction model for inferred properties. Since they were separate systems, they did not interfere with each other, while ontology or SWRL rules were maintained, ensuring persistent system extensibility and robustness. 15 refs., 1 tab., 8 figs.

  5. Mechatronic control engineering and electro-mechanical system design - two mechatronic curricula at Aalborg University based on problem oriented and project based learning

    DEFF Research Database (Denmark)

    Pedersen, Henrik C.; Andersen, Torben Ole; Rasmussen, Peter Omand

    2009-01-01

    , it is addressed how a mechatronic education is structured so courses and projects are aligned, to utilize the full benefits of the Problem Oriented Project Based Learning (POPBL) system practiced at AalborgUniversity (AAU). This is followed by a presentation of the two complementary educations in Mechatronicsat...... using a subsystem based approach. The challenges related to teaching and learning mechatronics are addressed, discussing how mechatronics is typically taught around the world also illustrating the trends and applications of mechatronic engineering and research. This is followed by an outline...... Based Learning environment....

  6. Recommender Systems for Learning

    CERN Document Server

    Manouselis, Nikos; Verbert, Katrien; Duval, Erik

    2013-01-01

    Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning practices of both individuals and organisations. It is therefore an application domain that generally covers technologies that support all forms of teaching and learning activities. Since information retrieval (in terms of searching for relevant learning resources to support teachers or learners) is a pivotal activity in TEL, the deployment of recommender systems has attracted increased interest. This brief attempts to provide an introduction to recommender systems for TEL settings, as well as to highlight their particularities compared to recommender systems for other application domains.

  7. An automated, high-throughput plant phenotyping system using machine learning-based plant segmentation and image analysis.

    Science.gov (United States)

    Lee, Unseok; Chang, Sungyul; Putra, Gian Anantrio; Kim, Hyoungseok; Kim, Dong Hwan

    2018-01-01

    A high-throughput plant phenotyping system automatically observes and grows many plant samples. Many plant sample images are acquired by the system to determine the characteristics of the plants (populations). Stable image acquisition and processing is very important to accurately determine the characteristics. However, hardware for acquiring plant images rapidly and stably, while minimizing plant stress, is lacking. Moreover, most software cannot adequately handle large-scale plant imaging. To address these problems, we developed a new, automated, high-throughput plant phenotyping system using simple and robust hardware, and an automated plant-imaging-analysis pipeline consisting of machine-learning-based plant segmentation. Our hardware acquires images reliably and quickly and minimizes plant stress. Furthermore, the images are processed automatically. In particular, large-scale plant-image datasets can be segmented precisely using a classifier developed using a superpixel-based machine-learning algorithm (Random Forest), and variations in plant parameters (such as area) over time can be assessed using the segmented images. We performed comparative evaluations to identify an appropriate learning algorithm for our proposed system, and tested three robust learning algorithms. We developed not only an automatic analysis pipeline but also a convenient means of plant-growth analysis that provides a learning data interface and visualization of plant growth trends. Thus, our system allows end-users such as plant biologists to analyze plant growth via large-scale plant image data easily.

  8. Learning Object Retrieval and Aggregation Based on Learning Styles

    Science.gov (United States)

    Ramirez-Arellano, Aldo; Bory-Reyes, Juan; Hernández-Simón, Luis Manuel

    2017-01-01

    The main goal of this article is to develop a Management System for Merging Learning Objects (msMLO), which offers an approach that retrieves learning objects (LOs) based on students' learning styles and term-based queries, which produces a new outcome with a better score. The msMLO faces the task of retrieving LOs via two steps: The first step…

  9. An IoT-Enabled Stroke Rehabilitation System Based on Smart Wearable Armband and Machine Learning.

    Science.gov (United States)

    Yang, Geng; Deng, Jia; Pang, Gaoyang; Zhang, Hao; Li, Jiayi; Deng, Bin; Pang, Zhibo; Xu, Juan; Jiang, Mingzhe; Liljeberg, Pasi; Xie, Haibo; Yang, Huayong

    2018-01-01

    Surface electromyography signal plays an important role in hand function recovery training. In this paper, an IoT-enabled stroke rehabilitation system was introduced which was based on a smart wearable armband (SWA), machine learning (ML) algorithms, and a 3-D printed dexterous robot hand. User comfort is one of the key issues which should be addressed for wearable devices. The SWA was developed by integrating a low-power and tiny-sized IoT sensing device with textile electrodes, which can measure, pre-process, and wirelessly transmit bio-potential signals. By evenly distributing surface electrodes over user's forearm, drawbacks of classification accuracy poor performance can be mitigated. A new method was put forward to find the optimal feature set. ML algorithms were leveraged to analyze and discriminate features of different hand movements, and their performances were appraised by classification complexity estimating algorithms and principal components analysis. According to the verification results, all nine gestures can be successfully identified with an average accuracy up to 96.20%. In addition, a 3-D printed five-finger robot hand was implemented for hand rehabilitation training purpose. Correspondingly, user's hand movement intentions were extracted and converted into a series of commands which were used to drive motors assembled inside the dexterous robot hand. As a result, the dexterous robot hand can mimic the user's gesture in a real-time manner, which shows the proposed system can be used as a training tool to facilitate rehabilitation process for the patients after stroke.

  10. Employing UMLS for generating hints in a tutoring system for medical problem-based learning.

    Science.gov (United States)

    Kazi, Hameedullah; Haddawy, Peter; Suebnukarn, Siriwan

    2012-06-01

    While problem-based learning has become widely popular for imparting clinical reasoning skills, the dynamics of medical PBL require close attention to a small group of students, placing a burden on medical faculty, whose time is over taxed. Intelligent tutoring systems (ITSs) offer an attractive means to increase the amount of facilitated PBL training the students receive. But typical intelligent tutoring system architectures make use of a domain model that provides a limited set of approved solutions to problems presented to students. Student solutions that do not match the approved ones, but are otherwise partially correct, receive little acknowledgement as feedback, stifling broader reasoning. Allowing students to creatively explore the space of possible solutions is exactly one of the attractive features of PBL. This paper provides an alternative to the traditional ITS architecture by using a hint generation strategy that leverages a domain ontology to provide effective feedback. The concept hierarchy and co-occurrence between concepts in the domain ontology are drawn upon to ascertain partial correctness of a solution and guide student reasoning towards a correct solution. We describe the strategy incorporated in METEOR, a tutoring system for medical PBL, wherein the widely available UMLS is deployed and represented as the domain ontology. Evaluation of expert agreement with system generated hints on a 5-point likert scale resulted in an average score of 4.44 (Spearman's ρ=0.80, p<0.01). Hints containing partial correctness feedback scored significantly higher than those without it (Mann Whitney, p<0.001). Hints produced by a human expert received an average score of 4.2 (Spearman's ρ=0.80, p<0.01). Copyright © 2012 Elsevier Inc. All rights reserved.

  11. Learning based particle filtering object tracking for visible-light systems.

    Science.gov (United States)

    Sun, Wei

    2015-10-01

    We propose a novel object tracking framework based on online learning scheme that can work robustly in challenging scenarios. Firstly, a learning-based particle filter is proposed with color and edge-based features. We train a. support vector machine (SVM) classifier with object and background information and map the outputs into probabilities, then the weight of particles in a particle filter can be calculated by the probabilistic outputs to estimate the state of the object. Secondly, the tracking loop starts with Lucas-Kanade (LK) affine template matching and follows by learning-based particle filter tracking. Lucas-Kanade method estimates errors and updates object template in the positive samples dataset, and learning-based particle filter tracker will start if the LK tracker loses the object. Finally, SVM classifier evaluates every tracked appearance to update the training set or restart the tracking loop if necessary. Experimental results show that our method is robust to challenging light, scale and pose changing, and test on eButton image sequence also achieves satisfactory tracking performance.

  12. Professional Practice of Medical Training in the E-Learning System: The Conceptual Model Based on a Critical Review

    Directory of Open Access Journals (Sweden)

    Zohrehsadat Mirmoghtadaie

    2017-04-01

    Full Text Available Background and Purpose: In education of medical science courses, there has been a growing orientation towards replacing traditional teaching in with E-learning education. Since the modern system of education is based on self-directed learning, e-learning requires special powers to deal with new-emerging challenges and professionally encounter the learning environment. The purpose of the present research is to explain and provide a conceptual model for professional competency in this system.Methods: In this review, different internet and library resources, indexed in Scirus, Pre Quest, Scopus, IEEE, SID, Magiran, Eric, Taylor and Francis, and Google Scholar from 1990 to 2015 were searched using the following keywords: function, manner, ethics, conduct disposition, netiquette, values, academic fraud, moral professionalism, and behavior ine-learning in combination and separately. The Critical Review methodology and Carnwell and Randolph structures were used. The most recent and richest resources that were more relevant to the issue were selected and their information was extracted.Results: Among review of 98 articles, documents of 34 relevant and valid articles were extracted. Based on the results, Digital Literacy, study skills, Cyber Ethics, and Netiquette were considered the main components of scientific and ethical competency in e-learning. 40 components were included in these dimensions.Conclusions: Although there is general interest in e-learning, the target population (learners are not prepared to use such an environment and require strong support. In this paper, we provided a summarized scheme and conceptual pattern fore-learners to move towards promotion of learning.Keywords: PROFESSIONAL FUNCTION, E-LEARNER, E-LEARNING, CRITICAL REVIEW

  13. Problem-based learning

    NARCIS (Netherlands)

    Loyens, Sofie; Kirschner, Paul A.; Paas, Fred

    2010-01-01

    Loyens, S. M. M., Kirschner, P. A., & Paas, F. (2011). Problem-based learning. In S. Graham (Editor-in-Chief), A. Bus, S. Major, & L. Swanson (Associate Editors), APA educational psychology handbook: Vol. 3. Application to learning and teaching (pp. 403-425). Washington, DC: American Psychological

  14. A Matlab/Simulink-Based Interactive Module for Servo Systems Learning

    Science.gov (United States)

    Aliane, N.

    2010-01-01

    This paper presents an interactive module for learning both the fundamental and practical issues of servo systems. This module, developed using Simulink in conjunction with the Matlab graphical user interface (Matlab-GUI) tool, is used to supplement conventional lectures in control engineering and robotics subjects. First, the paper introduces the…

  15. The Role of Peer Influence and Perceived Quality of Teaching in Faculty Acceptance of Web-Based Learning Management Systems

    Science.gov (United States)

    Salajan, Florin D.; Welch, Anita G.; Ray, Chris M.; Peterson, Claudette

    2015-01-01

    This study's primary investigation is the impact of "peer influence" and "perceived quality of teaching" on faculty members' usage of web-based learning management systems within the Technology Acceptance Model (TAM) framework. These factors are entered into an extended TAM as external variables impacting on the core constructs…

  16. The Use of System Thinking Concepts in Order to Assure Continuous Improvement of Project Based Learning Courses

    Science.gov (United States)

    Arantes do Amaral, Joao Alberto; Gonçalves, Paulo

    2015-01-01

    This case study describes a continuous improvement experience, conducted from 2002 to 2014 in Sao Paulo, Brazil, within 47 Project-Based Learning MBA courses, involving approximately 1,400 students. The experience report will focus on four themes: (1) understanding the main dynamics present in MBA courses; (2) planning a systemic intervention in…

  17. On the Development of a Web-Based M-Learning System for Dual Screen Handheld Game Consoles

    Directory of Open Access Journals (Sweden)

    Hend S. Al-Khalifa

    2011-04-01

    Full Text Available This paper presents our experience on the design and development of an M-Learning web-based system for the Nintendo DSi game console. The paper starts by addressing the difficulties that emerged from the lack of resources on design guidelines for dual screen devices also the absence of adequate techniques and methods to support the design decisions. Then it explains how we overcame these challenges by adopting a design decision suitable for the screen requirements of the Nintendo DSi console. Finally, we present the components of our M-Learning system and the results of a preliminary usability evaluation.

  18. Development of a Computer-Based Visualised Quantitative Learning System for Playing Violin Vibrato

    Science.gov (United States)

    Ho, Tracy Kwei-Liang; Lin, Huann-shyang; Chen, Ching-Kong; Tsai, Jih-Long

    2015-01-01

    Traditional methods of teaching music are largely subjective, with the lack of objectivity being particularly challenging for violin students learning vibrato because of the existence of conflicting theories. By using a computer-based analysis method, this study found that maintaining temporal coincidence between the intensity peak and the target…

  19. Problem Solving Method Based on E-Learning System for Engineering Education

    Science.gov (United States)

    Khazaal, Hasan F.

    2015-01-01

    Encouraging engineering students to handle advanced technology with multimedia, as well as motivate them to have the skills of solving the problem, are the missions of the teacher in preparing students for a modern professional career. This research proposes a scenario of problem solving in basic electrical circuits based on an e-learning system…

  20. Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning

    Science.gov (United States)

    Xu, Tao; Xiao, Na; Zhai, Xiaolong; Chan, Pak Kwan; Tin, Chung

    2018-02-01

    Objective. Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). Approach. The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. Main results. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. Significance. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

  1. Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

    Science.gov (United States)

    Xu, Tao; Xiao, Na; Zhai, Xiaolong; Kwan Chan, Pak; Tin, Chung

    2018-02-01

    Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

  2. Continued use of an interactive computer game-based visual perception learning system in children with developmental delay.

    Science.gov (United States)

    Lin, Hsien-Cheng; Chiu, Yu-Hsien; Chen, Yenming J; Wuang, Yee-Pay; Chen, Chiu-Ping; Wang, Chih-Chung; Huang, Chien-Ling; Wu, Tang-Meng; Ho, Wen-Hsien

    2017-11-01

    This study developed an interactive computer game-based visual perception learning system for special education children with developmental delay. To investigate whether perceived interactivity affects continued use of the system, this study developed a theoretical model of the process in which learners decide whether to continue using an interactive computer game-based visual perception learning system. The technology acceptance model, which considers perceived ease of use, perceived usefulness, and perceived playfulness, was extended by integrating perceived interaction (i.e., learner-instructor interaction and learner-system interaction) and then analyzing the effects of these perceptions on satisfaction and continued use. Data were collected from 150 participants (rehabilitation therapists, medical paraprofessionals, and parents of children with developmental delay) recruited from a single medical center in Taiwan. Structural equation modeling and partial-least-squares techniques were used to evaluate relationships within the model. The modeling results indicated that both perceived ease of use and perceived usefulness were positively associated with both learner-instructor interaction and learner-system interaction. However, perceived playfulness only had a positive association with learner-system interaction and not with learner-instructor interaction. Moreover, satisfaction was positively affected by perceived ease of use, perceived usefulness, and perceived playfulness. Thus, satisfaction positively affects continued use of the system. The data obtained by this study can be applied by researchers, designers of computer game-based learning systems, special education workers, and medical professionals. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. Engaging Students with a Mobile Game-Based Learning System in University Education

    Directory of Open Access Journals (Sweden)

    Alexander Bartel

    2014-10-01

    Full Text Available In this contribution we present a game-based learning concept which is based on mobile devices. It focuses a joyful stabilization of knowledge and the engagement of students using the Gamification approach and its game mechanics. Previous findings how to promote students’ motivation are adapted in the mobile context and discussed. A pre-evaluation of the prototype is described with its findings.

  4. Natural disaster risk analysis for critical infrastructure systems: An approach based on statistical learning theory

    International Nuclear Information System (INIS)

    Guikema, Seth D.

    2009-01-01

    Probabilistic risk analysis has historically been developed for situations in which measured data about the overall reliability of a system are limited and expert knowledge is the best source of information available. There continue to be a number of important problem areas characterized by a lack of hard data. However, in other important problem areas the emergence of information technology has transformed the situation from one characterized by little data to one characterized by data overabundance. Natural disaster risk assessments for events impacting large-scale, critical infrastructure systems such as electric power distribution systems, transportation systems, water supply systems, and natural gas supply systems are important examples of problems characterized by data overabundance. There are often substantial amounts of information collected and archived about the behavior of these systems over time. Yet it can be difficult to effectively utilize these large data sets for risk assessment. Using this information for estimating the probability or consequences of system failure requires a different approach and analysis paradigm than risk analysis for data-poor systems does. Statistical learning theory, a diverse set of methods designed to draw inferences from large, complex data sets, can provide a basis for risk analysis for data-rich systems. This paper provides an overview of statistical learning theory methods and discusses their potential for greater use in risk analysis

  5. Designing self-monitoring warm-up strategy with blog-based learning system to support knowledge building

    Directory of Open Access Journals (Sweden)

    James Chan

    2012-03-01

    Full Text Available Preparing lessons before class is widely recognized as an effective means of increasing student motivation for classroom activities and learning outcome. However, the unclear status of lesson preparation generally discourages teachers and students from maintaining this effective learning strategy. This study applied the self-explanation theory and reading comprehension strategies to design a lesson warm-up mechanism that scaffolds knowledge building. A set of corresponding supporting tools were developed into a blog-based learning system (BBLS to implement the warm-up process. Results of a teaching experiment reveal positive effects of the tools on learning achievement, recall of old knowledge, connection between old and new knowledge, and understanding of new knowledge.

  6. Development of a Lunar-Phase Observation System Based on Augmented Reality and Mobile Learning Technologies

    Directory of Open Access Journals (Sweden)

    Wernhuar Tarng

    2016-01-01

    Full Text Available Observing the lunar phase requires long-term involvement, and it is often obstructed by bad weather or tall buildings. In this study, a lunar-phase observation system is developed using the augmented reality (AR technology and the sensor functions of GPS, electronic compass, and 3-axis accelerometer on mobile devices to help students observe and record lunar phases easily. By holding the mobile device towards the moon in the sky, the screen will show the virtual moon at the position of the real moon. The system allows the user to record the lunar phase, including its azimuth/elevation angles and the observation date and time. In addition, the system can shorten the learning process by setting different dates and times for observation, so it can solve the problem of being unable to observe and record lunar phases due to a bad weather or the moon appearing late in the night. Therefore, it is an effective tool for astronomy education in elementary and high schools. A teaching experiment has been conducted to analyze the learning effectiveness of the system and the results show that it is effective in learning the lunar concepts. The questionnaire results reveal that students considered the system easy to operate and it is useful in locating the moon and recording the lunar data.

  7. Design, Analysis and User Acceptance of Architectural Design Education in Learning System Based on Knowledge Management Theory

    Science.gov (United States)

    Wu, Yun-Wu; Lin, Yu-An; Wen, Ming-Hui; Perng, Yeng-Hong; Hsu, I-Ting

    2016-01-01

    The major purpose of this study is to develop an architectural design knowledge management learning system with corresponding learning activities to help the students have meaningful learning and improve their design capability in their learning process. Firstly, the system can help the students to obtain and share useful knowledge. Secondly,…

  8. Machine learning systems

    Energy Technology Data Exchange (ETDEWEB)

    Forsyth, R

    1984-05-01

    With the dramatic rise of expert systems has come a renewed interest in the fuel that drives them-knowledge. For it is specialist knowledge which gives expert systems their power. But extracting knowledge from human experts in symbolic form has proved arduous and labour-intensive. So the idea of machine learning is enjoying a renaissance. Machine learning is any automatic improvement in the performance of a computer system over time, as a result of experience. Thus a learning algorithm seeks to do one or more of the following: cover a wider range of problems, deliver more accurate solutions, obtain answers more cheaply, and simplify codified knowledge. 6 references.

  9. Social software: E-learning beyond learning management systems

    DEFF Research Database (Denmark)

    Dalsgaard, Christian

    2006-01-01

    The article argues that it is necessary to move e-learning beyond learning management systems and engage students in an active use of the web as a resource for their self-governed, problem-based and collaborative activities. The purpose of the article is to discuss the potential of social software...... to move e-learning beyond learning management systems. An approach to use of social software in support of a social constructivist approach to e-learning is presented, and it is argued that learning management systems do not support a social constructivist approach which emphasizes self-governed learning...... activities of students. The article suggests a limitation of the use of learning management systems to cover only administrative issues. Further, it is argued that students' self-governed learning processes are supported by providing students with personal tools and engaging them in different kinds of social...

  10. Cardiac e-learning: Development of a web-based implantable cardioverter defibrillator educational system.

    Science.gov (United States)

    Hickey, Kathleen T; Johnson, Mary P; Biviano, Angelo; Aboelela, Sally; Thomas, Tami; Bakken, Suzanne; Garan, Hasan; Zimmerman, John L; Whang, William

    2011-04-01

    The objective of this study was to design a Web-based implantable cardioverter defibrillator (ICD) module that would allow greater access to learning which could occur at an individual's convenience outside the fast-paced clinical environment. A Web-based ICD software educational program was developed to provide general knowledge of the function of the ICD and the interpretation of the stored electrocardiograms. This learning tool could be accessed at any time via the Columbia University Internet server, using a unique, password protected login. A series of basic and advanced ICD terms were presented using actual ICD screenshots and videos that simulated scenarios the practitioner would most commonly encounter in the fast-paced clinical setting. To determine the usefulness of the site and improve the module, practitioners were asked to complete a brief (less than 5 min) online survey at the end of the module. Twenty-six practitioners have logged into our Web site: 20 nurses/nurse practitioners, four cardiac fellows, and two other practitioners. The majority of respondents rated the program as easy to use and useful. The success of this module has led to it becoming part of the training for student nurse practitioners before a clinical electrophysiology rotation, and the module is accessed by our cardiac entry level fellows before a rotation in the intensive care unit or electrophysiology service. Remote electronic arrhythmia learning is a successful example of the melding of technology and education to enhance clinical learning.

  11. Web-Based Evaluation System to Measure Learning Effectiveness in Kampo Medicine

    Directory of Open Access Journals (Sweden)

    Norio Iizuka

    2016-01-01

    Full Text Available Measuring the learning effectiveness of Kampo Medicine (KM education is challenging. The aim of this study was to develop a web-based test to measure the learning effectiveness of KM education among medical students (MSs. We used an open-source Moodle platform to test 30 multiple-choice questions classified into 8-type fields (eight basic concepts of KM including “qi-blood-fluid” and “five-element” theories, on 117 fourth-year MSs. The mean (±standard deviation [SD] score on the web-based test was 30.2±11.9 (/100. The correct answer rate ranged from 17% to 36%. A pattern-based portfolio enabled these rates to be individualized in terms of KM proficiency. MSs with scores higher (n=19 or lower (n=14 than mean ± 1SD were defined as high or low achievers, respectively. Cluster analysis using the correct answer rates for the 8-type field questions revealed clear divisions between high and low achievers. Interestingly, each high achiever had a different proficiency pattern. In contrast, three major clusters were evident among low achievers, all of whom responded with a low percentage of or no correct answers. In addition, a combination of three questions accurately classified high and low achievers. These findings suggest that our web-based test allows individual quantitative assessment of the learning effectiveness of KM education among MSs.

  12. Optimal and Learning-Based Demand Response Mechanism for Electric Water Heater System

    Directory of Open Access Journals (Sweden)

    Bo Lin

    2017-10-01

    Full Text Available This paper investigates how to develop a learning-based demand response approach for electric water heater in a smart home that can minimize the energy cost of the water heater while meeting the comfort requirements of energy consumers. First, a learning-based, data-driven model of an electric water heater is developed by using a nonlinear autoregressive network with external input (NARX using neural network. The model is updated daily so that it can more accurately capture the actual thermal dynamic characteristics of the water heater especially in real-life conditions. Then, an optimization problem, based on the NARX water heater model, is formulated to optimize energy management of the water heater in a day-ahead, dynamic electricity price framework. A genetic algorithm is proposed in order to solve the optimization problem more efficiently. MATLAB (R2016a is used to evaluate the proposed learning-based demand response approach through a computational experiment strategy. The proposed approach is compared with conventional method for operation of an electric water heater. Cost saving and benefits of the proposed water heater energy management strategy are explored.

  13. Scheduled power tracking control of the wind-storage hybrid system based on the reinforcement learning theory

    Science.gov (United States)

    Li, Ze

    2017-09-01

    In allusion to the intermittency and uncertainty of the wind electricity, energy storage and wind generator are combined into a hybrid system to improve the controllability of the output power. A scheduled power tracking control method is proposed based on the reinforcement learning theory and Q-learning algorithm. In this method, the state space of the environment is formed with two key factors, i.e. the state of charge of the energy storage and the difference value between the actual wind power and scheduled power, the feasible action is the output power of the energy storage, and the corresponding immediate rewarding function is designed to reflect the rationality of the control action. By interacting with the environment and learning from the immediate reward, the optimal control strategy is gradually formed. After that, it could be applied to the scheduled power tracking control of the hybrid system. Finally, the rationality and validity of the method are verified through simulation examples.

  14. Improving Learning Tasks for Mentally Handicapped People Using AmI Environments Based on Cyber-Physical Systems

    Directory of Open Access Journals (Sweden)

    Diego Martín

    2018-01-01

    Full Text Available A prototype to improve learning tasks for mentally handicapped people is shown in this research paper using ambient intelligence techniques and based on cyber-physical systems. The whole system is composed of a worktable, a cyber-glove (both with several RFID and NFC detection zones, and an AmI software application for modeling and workflow guidance. A case study was carried out by the authors where sixteen mentally handicapped people and 3 trainers were involved in the experiment. The experiment consisted in the execution of several memorization tasks of movements of objects using the approach presented in this paper. The results obtained were very interesting, indicating that this kind of solutions are feasible and allow the learning of complex tasks to some types of mentally handicapped people. In addition, at the end of the paper are presented some lessons learned after performing the experimentation.

  15. Avatar Web-Based Self-Report Survey System Technology for Public Health Research: Technical Outcome Results and Lessons Learned.

    Science.gov (United States)

    Savel, Craig; Mierzwa, Stan; Gorbach, Pamina M; Souidi, Samir; Lally, Michelle; Zimet, Gregory; Interventions, Aids

    2016-01-01

    This paper reports on a specific Web-based self-report data collection system that was developed for a public health research study in the United States. Our focus is on technical outcome results and lessons learned that may be useful to other projects requiring such a solution. The system was accessible from any device that had a browser that supported HTML5. Report findings include: which hardware devices, Web browsers, and operating systems were used; the rate of survey completion; and key considerations for employing Web-based surveys in a clinical trial setting.

  16. Learning Object Metadata in a Web-Based Learning Environment

    NARCIS (Netherlands)

    Avgeriou, Paris; Koutoumanos, Anastasios; Retalis, Symeon; Papaspyrou, Nikolaos

    2000-01-01

    The plethora and variance of learning resources embedded in modern web-based learning environments require a mechanism to enable their structured administration. This goal can be achieved by defining metadata on them and constructing a system that manages the metadata in the context of the learning

  17. Sign Learning Kink-based (SiLK) Quantum Monte Carlo for molecular systems

    Energy Technology Data Exchange (ETDEWEB)

    Ma, Xiaoyao [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70803 (United States); Hall, Randall W. [Department of Natural Sciences and Mathematics, Dominican University of California, San Rafael, California 94901 (United States); Department of Chemistry, Louisiana State University, Baton Rouge, Louisiana 70803 (United States); Löffler, Frank [Center for Computation and Technology, Louisiana State University, Baton Rouge, Louisiana 70803 (United States); Kowalski, Karol [William R. Wiley Environmental Molecular Sciences Laboratory, Battelle, Pacific Northwest National Laboratory, Richland, Washington 99352 (United States); Bhaskaran-Nair, Kiran; Jarrell, Mark; Moreno, Juana [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70803 (United States); Center for Computation and Technology, Louisiana State University, Baton Rouge, Louisiana 70803 (United States)

    2016-01-07

    The Sign Learning Kink (SiLK) based Quantum Monte Carlo (QMC) method is used to calculate the ab initio ground state energies for multiple geometries of the H{sub 2}O, N{sub 2}, and F{sub 2} molecules. The method is based on Feynman’s path integral formulation of quantum mechanics and has two stages. The first stage is called the learning stage and reduces the well-known QMC minus sign problem by optimizing the linear combinations of Slater determinants which are used in the second stage, a conventional QMC simulation. The method is tested using different vector spaces and compared to the results of other quantum chemical methods and to exact diagonalization. Our findings demonstrate that the SiLK method is accurate and reduces or eliminates the minus sign problem.

  18. Sign Learning Kink-based (SiLK) Quantum Monte Carlo for molecular systems

    Energy Technology Data Exchange (ETDEWEB)

    Ma, Xiaoyao [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70803, USA; Hall, Randall W. [Department of Natural Sciences and Mathematics, Dominican University of California, San Rafael, California 94901, USA; Department of Chemistry, Louisiana State University, Baton Rouge, Louisiana 70803, USA; Löffler, Frank [Center for Computation and Technology, Louisiana State University, Baton Rouge, Louisiana 70803, USA; Kowalski, Karol [William R. Wiley Environmental Molecular Sciences Laboratory, Battelle, Pacific Northwest National Laboratory, Richland, Washington 99352, USA; Bhaskaran-Nair, Kiran [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70803, USA; Center for Computation and Technology, Louisiana State University, Baton Rouge, Louisiana 70803, USA; Jarrell, Mark [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70803, USA; Center for Computation and Technology, Louisiana State University, Baton Rouge, Louisiana 70803, USA; Moreno, Juana [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, Louisiana 70803, USA; Center for Computation and Technology, Louisiana State University, Baton Rouge, Louisiana 70803, USA

    2016-01-07

    The Sign Learning Kink (SiLK) based Quantum Monte Carlo (QMC) method is used to calculate the ab initio ground state energies for multiple geometries of the H2O, N2, and F2 molecules. The method is based on Feynman’s path integral formulation of quantum mechanics and has two stages. The first stage is called the learning stage and reduces the well-known QMC minus sign problem by optimizing the linear combinations of Slater determinants which are used in the second stage, a conventional QMC simulation. The method is tested using different vector spaces and compared to the results of other quantum chemical methods and to exact diagonalization. Our findings demonstrate that the SiLK method is accurate and reduces or eliminates the minus sign problem.

  19. Sign Learning Kink-based (SiLK) Quantum Monte Carlo for molecular systems

    International Nuclear Information System (INIS)

    Ma, Xiaoyao; Hall, Randall W.; Löffler, Frank; Kowalski, Karol; Bhaskaran-Nair, Kiran; Jarrell, Mark; Moreno, Juana

    2016-01-01

    The Sign Learning Kink (SiLK) based Quantum Monte Carlo (QMC) method is used to calculate the ab initio ground state energies for multiple geometries of the H 2 O, N 2 , and F 2 molecules. The method is based on Feynman’s path integral formulation of quantum mechanics and has two stages. The first stage is called the learning stage and reduces the well-known QMC minus sign problem by optimizing the linear combinations of Slater determinants which are used in the second stage, a conventional QMC simulation. The method is tested using different vector spaces and compared to the results of other quantum chemical methods and to exact diagonalization. Our findings demonstrate that the SiLK method is accurate and reduces or eliminates the minus sign problem

  20. Using Game-Based Cooperative Learning to Improve Learning Motivation: A Study of Online Game Use in an Operating Systems Course

    Science.gov (United States)

    Jong, Bin-Shyan; Lai, Chien-Hung; Hsia, Yen-Teh; Lin, Tsong-Wuu; Lu, Cheng-Yu

    2013-01-01

    Many researchers have studied the use of game-based learning. Game-based learning takes many forms, including virtual reality, role playing, and performing tasks. For students to learn specific course content, it is important that the selected game be suited to the course. Thus far, no studies have investigated the use of game-based cooperative…

  1. STEM based learning to facilitate middle school students’ conceptual change, creativity and collaboration in organization of living system topic

    Science.gov (United States)

    Rustaman, N. Y.; Afianti, E.; Maryati, S.

    2018-05-01

    A study using one group pre-post-test experimental design on Life organization system topic was carried out to investigate student’s tendency in learning abstract concept, their creativity and collaboration in designing and producing cell models through STEM-based learning. A number of seventh grade students in Cianjur district were involved as research subjects (n=34). Data were collected using two tier test for tracing changes in student conception before and after the application of STEM-based learning, and rubrics in creativity design (adopted from Torrance) and product on cell models (individually, in group), and rubric for self-assessment and observed skills on collaboration adapted from Marzano’s for life-long learning. Later the data obtained were analyzed qualitatively by interpreting the tendency of data presented in matrix sorted by gender. Research findings showed that the percentage of student’s scientific concept mastery is moderate in general. Their creativity in making a cell model design varied in category (expressing, emergent, excellent, not yet evident). Student’s collaboration varied from excellent, fair, good, less once, to less category in designing cell model. It was found that STEM based learning can facilitate students conceptual change, creativity and collaboration.

  2. Precursor systems analyses of automated highway systems. Knowledge based systems and learning methods for AHS. Volume 10. Final report, September 1993-February 1995

    Energy Technology Data Exchange (ETDEWEB)

    Schmoltz, J.; Blumer, A.; Noonan, J.; Shedd, D.; Twarog, J.

    1995-06-01

    Managing each AHS vehicle and the AHS system as a whole is an extremely complex yndertaking. The authors have investigated and now report on Artificial Intelligence (AI) approaches that can help. In particular, we focus on AI technologies known as Knowledge Based Systems (KBSs) and Learning Methods (LMs). Our primary purpose is to identify opportunities: we identify several problems in AHS and AI technologies that can solve them. Our secondary purpose is to examine in some detail a subset of these opportunities: we examine how KBSs and LMs can help in controlling the high level movements--e.g., keep in lane, change lanes, speed up, slow down--of an automated vehicle. This detailed examination includes the implementation of a prototype system having three primary components. The Tufts Automated Highway System Kit(TAHSK) discrete time micro-level traffic simulator is a generic AHS simulator. TAHSK interfaces with the Knowledge Based Controller (KBCon) knowledge based high level controller, which controls the high level actions of individual AHS vehicles. Finally, TAHSK also interfaces with a Reinforcement learning (RL) module that was used to explore the possibilities of RL techniques in an AHS environment.

  3. Assessing Student Learning About Climate Change With Earth System Place-Based Geospatial Data

    Science.gov (United States)

    Zalles, D. R.; Krumhansl, R. A.; Acker, J. G.; Manitakos, J.; Elston, A.

    2012-12-01

    Powerful web-based data sets about geospatially situated Earth system phenomena are now available for analysis by the general public, including for any teacher or set of students who have the requisite skills to partake in the analyses. Unfortunately there exist impediments to successful use of these data. Teachers and students may lack (1) readiness to use the software interfaces for querying and representing the data, (2) needed scientific practice skills such as interpreting geographic information system-based maps and time series plots, and (3) needed understandings of the fundamental scientific concepts to make sense of the data. Hence, to evaluate any program designed to engage students and teachers with these data resources, there need to be assessment strategies to check for understanding. Assessment becomes the key to identifying learning needs and intervening appropriately with additional task scaffolding or other forms of instructional support. The paper will describe contrasting assessment strategies being carried out in two climate change education projects funded by NASA and NSF. The NASA project, Data Enhanced Investigations for Climate Change Education (DICCE), brings data from NASA satellite missions to the classroom. A bank of DICCE assessment items is being developed to measure students' abilities to transfer their skills in analyzing data about their local region to other regions of the world. Teachers choose pre-post assessment items for variables of Earth system phenomena that they target in their instruction. The data vary depending on what courses the teachers are teaching. For example, Earth science teachers are likely to choose data about atmospheric phenomena and biology teachers are more likely to choose land cover data. The NSF project, Studying Topography, Orographic Rainfall, and Ecosystems with Geospatial Information Technology (STORE), provides to teachers recent climatological and vegetation data about "study areas" in Central

  4. Learning model of eye movement system based on anatomical structure; Kaibogakuteki kozo ni motozuita gakushu kino wo motsu gankyu undo system to sono tokusei

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, X.; Wakamatsu, H. [Tokyo Medical and Dental University, Tokyo (Japan)

    1998-07-01

    A learning system is proposed to explain the adaptive function of an eye movement consisting of compensatory and optokinetic reflex, and pursuit movements based on the brain anatomy and physiology. Thereby, the learning system is synthesized as an artificial neural network based on the structure and function of the biological neural network of flocculus. The role of neural paths into flocculus from stretch receptors of ocular muscles are discussed in detail from the viewpoint of system control engineering. The mathematical learning process is also shown taking into account the adaptive mechanism and the anatomical structure of vestibular nuclei. The experimental results through simulation confirm the validity of the hypothesis and the appropriateness of the inference process in connection with the proposed mathematical model. 18 refs., 11 figs.

  5. The Effectiveness of the Game-Based Learning System for the Improvement of American Sign Language Using Kinect

    Science.gov (United States)

    Kamnardsiri, Teerawat; Hongsit, Ler-on; Khuwuthyakorn, Pattaraporn; Wongta, Noppon

    2017-01-01

    This paper investigated students' achievement for learning American Sign Language (ASL), using two different methods. There were two groups of samples. The first experimental group (Group A) was the game-based learning for ASL, using Kinect. The second control learning group (Group B) was the traditional face-to-face learning method, generally…

  6. A Sun Path Observation System Based on Augment Reality and Mobile Learning

    Directory of Open Access Journals (Sweden)

    Wernhuar Tarng

    2018-01-01

    Full Text Available This study uses the augmented reality technology and sensor functions of GPS, electronic compass, and three-axis accelerometer on mobile devices to develop a Sun path observation system for applications in astronomy education. The orientation and elevation of the Sun can be calculated by the system according to the user’s location and local time to simulate the Sun path. When holding the mobile device toward the sky, the screen will show the virtual Sun at the same position as that of the real Sun. The user can record the Sun path and the data of observation date, time, longitude, and latitude using the celestial hemisphere and the pole shadow on the system. By setting different observation times and locations, it can be seen that the Sun path changes with seasons and latitudes. The system provides contextual awareness of the Sun path concepts, and it can convert the observation data into organized and meaningful astronomical knowledge to enable combination of situated learning with spatial cognition. The system can solve the problem of being not able to record the Sun path due to a bad weather or topographical restrictions, and therefore it is helpful for elementary students when conducting observations. A teaching experiment has been conducted to analyze the learning achievement of students after using the system, and the results show that it is more effective than traditional teaching aids. The questionnaire results also reveal that the system is easy to operate and useful in recording the Sun path data. Therefore, it is an effective tool for astronomy education in elementary schools.

  7. Development of Remote Monitoring and a Control System Based on PLC and WebAccess for Learning Mechatronics

    OpenAIRE

    Wen-Jye Shyr; Te-Jen Su; Chia-Ming Lin

    2013-01-01

    This study develops a novel method for learning mechatronics using remote monitoring and control, based on a programmable logic controller (PLC) and WebAccess. A mechatronics module, a Web‐CAM and a PLC were integrated with WebAccess software to organize a remote laboratory. The proposed system enables users to access the Internet for remote monitoring and control of the mechatronics module via a web browser, thereby enhancing work flexibility by enabling personnel to control mechatronics equ...

  8. Comparing problem-based learning and lecture as methods to teach whole-systems design to engineering students

    Science.gov (United States)

    Dukes, Michael Dickey

    The objective of this research is to compare problem-based learning and lecture as methods to teach whole-systems design to engineering students. A case study, Appendix A, exemplifying successful whole-systems design was developed and written by the author in partnership with the Rocky Mountain Institute. Concepts to be tested were then determined, and a questionnaire was developed to test students' preconceptions. A control group of students was taught using traditional lecture methods, and a sample group of students was taught using problem-based learning methods. After several weeks, the students were given the same questionnaire as prior to the instruction, and the data was analyzed to determine if the teaching methods were effective in correcting misconceptions. A statistically significant change in the students' preconceptions was observed in both groups on the topic of cost related to the design process. There was no statistically significant change in the students' preconceptions concerning the design process, technical ability within five years, and the possibility of drastic efficiency gains with current technologies. However, the results were inconclusive in determining that problem-based learning is more effective than lecture as a method for teaching the concept of whole-systems design, or vice versa.

  9. Automatic semantic role labelling using a memory-based learning system

    Directory of Open Access Journals (Sweden)

    Roser Morante

    2008-05-01

    Full Text Available In this paper we present a semantic role labelling system. The main component of the system is a memory-based classifier. The system has been trained with the Cast3LB-CoNLL-SemRol. The features encode information from dependency syntax. The results (F1 0.86 are comparable with state-of-the-art results (F1 around 0.86 from systems that use information from constituent syntax.

  10. Java problem-based learning

    Directory of Open Access Journals (Sweden)

    Goran P, Šimić

    2012-01-01

    Full Text Available The paper describes the self-directed problem-based learning system (PBL named Java PBL. The expert module is the kernel of Java PBL. It involves a specific domain model, a problem generator and a solution generator. The overall system architecture is represented in the paper. Java PBL can act as the stand-alone system, but it is also designed to provide support to learning management systems (LMSs. This is provided by a modular design of the system. An LMS can offer the declarative knowledge only. Java PBL offers the procedural knowledge and the progress of the learner programming skills. The free navigation, unlimited numbers of problems and recommendations represent the main pedagogical strategies and tactics implemented into the system.

  11. [Problem based learning by distance education and analysis of a training system].

    Science.gov (United States)

    Dury, Cécile

    2004-12-01

    This article presents and analyses a training system aiming at acquiring skills in nursing cares. The aims followed are the development: --of an active pedagogic method: learning through problems (LTP); --of the interdisciplinary and intercultural approach, the same problems being solves by students from different disciplines and cultures; --of the use of the new technologies of information and communication (NTIC) so as to enable a maximal "distance" cooperation between the various partners of the project. The analysis of the system shows that the pedagogic aims followed by LTP are reached. The pluridisciplinary and pluricultural approach, to be optimal, requires great coordination between the partners, balance between the groups of students from different countries and disciplines, training and support from the tutors in the use of the distance teaching platform.

  12. Learning-Based Adaptive Optimal Tracking Control of Strict-Feedback Nonlinear Systems.

    Science.gov (United States)

    Gao, Weinan; Jiang, Zhong-Ping; Weinan Gao; Zhong-Ping Jiang; Gao, Weinan; Jiang, Zhong-Ping

    2018-06-01

    This paper proposes a novel data-driven control approach to address the problem of adaptive optimal tracking for a class of nonlinear systems taking the strict-feedback form. Adaptive dynamic programming (ADP) and nonlinear output regulation theories are integrated for the first time to compute an adaptive near-optimal tracker without any a priori knowledge of the system dynamics. Fundamentally different from adaptive optimal stabilization problems, the solution to a Hamilton-Jacobi-Bellman (HJB) equation, not necessarily a positive definite function, cannot be approximated through the existing iterative methods. This paper proposes a novel policy iteration technique for solving positive semidefinite HJB equations with rigorous convergence analysis. A two-phase data-driven learning method is developed and implemented online by ADP. The efficacy of the proposed adaptive optimal tracking control methodology is demonstrated via a Van der Pol oscillator with time-varying exogenous signals.

  13. Design and Implementation of English for Academic Purpose Online Learning System Based on Browser/Server Framework

    Directory of Open Access Journals (Sweden)

    Yan Gong

    2018-03-01

    Full Text Available Today, with the rapid development of the information age, the education reform tends to be internationalized. The tertiary-level EFL education in colleges and universities has also changed its original model with focuses on cultivating gen-eral-purpose linguistic skills to one on students' English for Academic Purpose (EAP. EAP English instruction has been vigorously popularized in research-based universities. To achieve the informationized and standardized management for EAP English instruction work in the universities, in this paper, we design and develop a EAP English online learning system with B / S as the system develop-ment framework by which the system's overall functions are designed. MySQL is chosen as a database development tool used to implement the main object mod-ule, while JSP technology is used to support the cross-platform mechanism in order to access to diversified data sources. It is proved by the test on system op-eration that this system features operability, easy to use and maintain, and enables to meet the needs of university students for EAP English learning and teaching management, improves the students’ EAP English learning model and efficiency.

  14. Practice and effectiveness of web-based problem-based learning approach in a large class-size system: A comparative study.

    Science.gov (United States)

    Ding, Yongxia; Zhang, Peili

    2018-06-12

    Problem-based learning (PBL) is an effective and highly efficient teaching approach that is extensively applied in education systems across a variety of countries. This study aimed to investigate the effectiveness of web-based PBL teaching pedagogies in large classes. The cluster sampling method was used to separate two college-level nursing student classes (graduating class of 2013) into two groups. The experimental group (n = 162) was taught using a web-based PBL teaching approach, while the control group (n = 166) was taught using conventional teaching methods. We subsequently assessed the satisfaction of the experimental group in relation to the web-based PBL teaching mode. This assessment was performed following comparison of teaching activity outcomes pertaining to exams and self-learning capacity between the two groups. When compared with the control group, the examination scores and self-learning capabilities were significantly higher in the experimental group (P web-based PBL teaching approach. In a large class-size teaching environment, the web-based PBL teaching approach appears to be more optimal than traditional teaching methods. These results demonstrate the effectiveness of web-based teaching technologies in problem-based learning. Copyright © 2018. Published by Elsevier Ltd.

  15. Exploring the Learning Mechanism of Web-Based Question-Answering Systems and Their Design

    Science.gov (United States)

    Zhang, Yin

    2010-01-01

    In recent years, a number of models concerning question-answering (QA) systems have been put forward. But many of them stress technology and neglect the research of QA itself. In this paper, we analyse the essence of QA and discuss the relationship between technology and QA. On that basis, we propose that when designing web-based QA systems, more…

  16. An integrated information management system based DSS for problem solving and decision making in open & distance learning institutions of India

    Directory of Open Access Journals (Sweden)

    Pankaj Khanna

    2014-04-01

    Full Text Available An integrated information system based DSS is developed for Open and Distance Learning (ODL institutions in India. The system has been web structured with the most suitable newly developed modules. A DSS model has been developed for solving semi-structured and unstructured problems including decision making with regard to various programmes and activities operating in the ODLIs. The DSS model designed for problem solving is generally based on quantitative formulas, whereas for problems involving imprecision and uncertainty, a fuzzy theory based DSS is employed. The computer operated system thus developed would help the ODLI management to quickly identify programmes and activities that require immediate attention. It shall also provide guidance for obtaining the most appropriate managerial decisions without any loss of time. As a result, the various subsystems operating in the ODLI are able to administer its activities more efficiently and effectively to enhance the overall performance of the concerned ODL institution to a new level.

  17. Exploring Lecturers' Perceptions of Learning Management System: An Empirical Study Based on TAM

    Directory of Open Access Journals (Sweden)

    Wei Wei Goh

    2014-06-01

    Full Text Available With the pervasive take-up and presence of digital technologies, learning management system (LMS is popular for its open accessibility and its interactive nature. Implementation of LMS has become part of the strategic plan in higher education institution to enhance the flexibility in teaching and learning. It is essential to explore the perceptions of users in using the LMS in order to inform stakeholders the positive influencing aspects and improve the negative factors in the future. This study investigates the perception of lecturers in using LMS in term of perceived usefulness and perceived ease of use for teaching purposes. Technology Acceptance Model (TAM is used as the research framework to design the questionnaire. An online questionnaire was created to address the research questions. The results reveal that lecturers do not react positively towards perceived ease of use of Moodle for teaching. Lecturers treat Moodle as content repository and do not fully utilize the interactive features in Moodle. It was found that usability issues, interaction and communication issues had a negative impact on the lecturers' perception.

  18. Factors that influence acceptance of web-based e-learning systems for the in-service education of junior high school teachers in Taiwan.

    Science.gov (United States)

    Chen, Hong-Ren; Tseng, Hsiao-Fen

    2012-08-01

    Web-based e-learning is not restricted by time or place and can provide teachers with a learning environment that is flexible and convenient, enabling them to efficiently learn, quickly develop their professional expertise, and advance professionally. Many research reports on web-based e-learning have neglected the role of the teacher's perspective in the acceptance of using web-based e-learning systems for in-service education. We distributed questionnaires to 402 junior high school teachers in central Taiwan. This study used the Technology Acceptance Model (TAM) as our theoretical foundation and employed the Structure Equation Model (SEM) to examine factors that influenced intentions to use in-service training conducted through web-based e-learning. The results showed that motivation to use and Internet self-efficacy were significantly positively associated with behavioral intentions regarding the use of web-based e-learning for in-service training through the factors of perceived usefulness and perceived ease of use. The factor of computer anxiety had a significantly negative effect on behavioral intentions toward web-based e-learning in-service training through the factor of perceived ease of use. Perceived usefulness and motivation to use were the primary reasons for the acceptance by junior high school teachers of web-based e-learning systems for in-service training. Copyright © 2011 Elsevier Ltd. All rights reserved.

  19. An Extreme Learning Machine-Based Neuromorphic Tactile Sensing System for Texture Recognition.

    Science.gov (United States)

    Rasouli, Mahdi; Chen, Yi; Basu, Arindam; Kukreja, Sunil L; Thakor, Nitish V

    2018-04-01

    Despite significant advances in computational algorithms and development of tactile sensors, artificial tactile sensing is strikingly less efficient and capable than the human tactile perception. Inspired by efficiency of biological systems, we aim to develop a neuromorphic system for tactile pattern recognition. We particularly target texture recognition as it is one of the most necessary and challenging tasks for artificial sensory systems. Our system consists of a piezoresistive fabric material as the sensor to emulate skin, an interface that produces spike patterns to mimic neural signals from mechanoreceptors, and an extreme learning machine (ELM) chip to analyze spiking activity. Benefiting from intrinsic advantages of biologically inspired event-driven systems and massively parallel and energy-efficient processing capabilities of the ELM chip, the proposed architecture offers a fast and energy-efficient alternative for processing tactile information. Moreover, it provides the opportunity for the development of low-cost tactile modules for large-area applications by integration of sensors and processing circuits. We demonstrate the recognition capability of our system in a texture discrimination task, where it achieves a classification accuracy of 92% for categorization of ten graded textures. Our results confirm that there exists a tradeoff between response time and classification accuracy (and information transfer rate). A faster decision can be achieved at early time steps or by using a shorter time window. This, however, results in deterioration of the classification accuracy and information transfer rate. We further observe that there exists a tradeoff between the classification accuracy and the input spike rate (and thus energy consumption). Our work substantiates the importance of development of efficient sparse codes for encoding sensory data to improve the energy efficiency. These results have a significance for a wide range of wearable, robotic

  20. Utilizing Learners' Negative Ratings in Semantic Content-Based Recommender System for e-Learning Forum

    Science.gov (United States)

    Albatayneh, Naji Ahmad; Ghauth, Khairil Imran; Chua, Fang-Fang

    2018-01-01

    Nowadays, most of e-learning systems embody online discussion forums as a medium for collaborative learning that supports knowledge sharing and information exchanging between learners. The exponential growth of the available shared information in e-learning online discussion forums has caused a difficulty for learners in discovering interesting…

  1. Authoring Systems Delivering Reusable Learning Objects

    Directory of Open Access Journals (Sweden)

    George Nicola Sammour

    2009-10-01

    Full Text Available A three layer e-learning course development model has been defined based on a conceptual model of learning content object. It starts by decomposing the learning content into small chunks which are initially placed in a hierarchic structure of units and blocks. The raw content components, being the atomic learning objects (ALO, were linked to the blocks and are structured in the database. We set forward a dynamic generation of LO's using re-usable e-learning raw materials or ALO’s In that view we need a LO authoring/ assembling system fitting the requirements of interoperability and reusability and starting from selecting the raw learning content from the learning materials content database. In practice authoring systems are used to develop e-learning courses. The company EDUWEST has developed an authoring system that is database based and will be SCORM compliant in the near future.

  2. [Acceptance of case-based, interactive e-learning in veterinary medicine on the example of the CASUS system].

    Science.gov (United States)

    Börchers, M; Tipold, A; Pfarrer, Ch; Fischer, M R; Ehlers, J P

    2010-01-01

    New teaching methods such as e-learning, are increasingly used to support common methods such as lectures, seminars and practical training in universities providing education in veterinary medicine. In the current study, the acceptance of e-learning in the example of the CASUS system by veterinarians as well as students of veterinary medicine of all German-speaking universities was analyzed. Material und methods: For this purpose an online evaluation questionnaire was developed. Members of the target groups were informed by e-mail and references in professional journals, as well as through veterinarian exchange platforms on the internet. Additionally, 224 students' final anatomy marks were compared and correlated to the utilization of CASUS to gain an important insight for the development of new teaching practices in the teaching of veterinary medicine. In total 1581 questionnaires were evaluated. A good acceptance regarding new teaching practices was found, although the classical textbook is still the most important instrument for imparting knowledge. The degree of utilization of e-learning strongly depends on its integration into the teaching content. CASUS is regarded as an efficient teaching method, with over 90% of the respondents indicating a strong desire to expand the number of case studies. Due to the present low degree of integration into the teaching content, no significant correlation could be found between the utilization of anatomy case studies and the final anatomy mark. However, based on their subjective perception, the students reported a high level of success in their study results with the likely effect of supporting increasing self-assurance in the situation of examinations. With the help of e-learning, educational objectives can be achieved that are not attainable by traditional teaching methods, e.g. the review of individual improvements by using the integrated feedback-function of e-learning programs. However, e-learning is not able to

  3. An Internet of Things System for Underground Mine Air Quality Pollutant Prediction Based on Azure Machine Learning.

    Science.gov (United States)

    Jo, ByungWan; Khan, Rana Muhammad Asad

    2018-03-21

    The implementation of wireless sensor networks (WSNs) for monitoring the complex, dynamic, and harsh environment of underground coal mines (UCMs) is sought around the world to enhance safety. However, previously developed smart systems are limited to monitoring or, in a few cases, can report events. Therefore, this study introduces a reliable, efficient, and cost-effective internet of things (IoT) system for air quality monitoring with newly added features of assessment and pollutant prediction. This system is comprised of sensor modules, communication protocols, and a base station, running Azure Machine Learning (AML) Studio over it. Arduino-based sensor modules with eight different parameters were installed at separate locations of an operational UCM. Based on the sensed data, the proposed system assesses mine air quality in terms of the mine environment index (MEI). Principal component analysis (PCA) identified CH₄, CO, SO₂, and H₂S as the most influencing gases significantly affecting mine air quality. The results of PCA were fed into the ANN model in AML studio, which enabled the prediction of MEI. An optimum number of neurons were determined for both actual input and PCA-based input parameters. The results showed a better performance of the PCA-based ANN for MEI prediction, with R ² and RMSE values of 0.6654 and 0.2104, respectively. Therefore, the proposed Arduino and AML-based system enhances mine environmental safety by quickly assessing and predicting mine air quality.

  4. An Internet of Things System for Underground Mine Air Quality Pollutant Prediction Based on Azure Machine Learning

    Directory of Open Access Journals (Sweden)

    ByungWan Jo

    2018-03-01

    Full Text Available The implementation of wireless sensor networks (WSNs for monitoring the complex, dynamic, and harsh environment of underground coal mines (UCMs is sought around the world to enhance safety. However, previously developed smart systems are limited to monitoring or, in a few cases, can report events. Therefore, this study introduces a reliable, efficient, and cost-effective internet of things (IoT system for air quality monitoring with newly added features of assessment and pollutant prediction. This system is comprised of sensor modules, communication protocols, and a base station, running Azure Machine Learning (AML Studio over it. Arduino-based sensor modules with eight different parameters were installed at separate locations of an operational UCM. Based on the sensed data, the proposed system assesses mine air quality in terms of the mine environment index (MEI. Principal component analysis (PCA identified CH4, CO, SO2, and H2S as the most influencing gases significantly affecting mine air quality. The results of PCA were fed into the ANN model in AML studio, which enabled the prediction of MEI. An optimum number of neurons were determined for both actual input and PCA-based input parameters. The results showed a better performance of the PCA-based ANN for MEI prediction, with R2 and RMSE values of 0.6654 and 0.2104, respectively. Therefore, the proposed Arduino and AML-based system enhances mine environmental safety by quickly assessing and predicting mine air quality.

  5. Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system.

    Science.gov (United States)

    Al-Masni, Mohammed A; Al-Antari, Mugahed A; Park, Jeong-Min; Gi, Geon; Kim, Tae-Yeon; Rivera, Patricio; Valarezo, Edwin; Choi, Mun-Taek; Han, Seung-Moo; Kim, Tae-Seong

    2018-04-01

    Automatic detection and classification of the masses in mammograms are still a big challenge and play a crucial role to assist radiologists for accurate diagnosis. In this paper, we propose a novel Computer-Aided Diagnosis (CAD) system based on one of the regional deep learning techniques, a ROI-based Convolutional Neural Network (CNN) which is called You Only Look Once (YOLO). Although most previous studies only deal with classification of masses, our proposed YOLO-based CAD system can handle detection and classification simultaneously in one framework. The proposed CAD system contains four main stages: preprocessing of mammograms, feature extraction utilizing deep convolutional networks, mass detection with confidence, and finally mass classification using Fully Connected Neural Networks (FC-NNs). In this study, we utilized original 600 mammograms from Digital Database for Screening Mammography (DDSM) and their augmented mammograms of 2,400 with the information of the masses and their types in training and testing our CAD. The trained YOLO-based CAD system detects the masses and then classifies their types into benign or malignant. Our results with five-fold cross validation tests show that the proposed CAD system detects the mass location with an overall accuracy of 99.7%. The system also distinguishes between benign and malignant lesions with an overall accuracy of 97%. Our proposed system even works on some challenging breast cancer cases where the masses exist over the pectoral muscles or dense regions. Copyright © 2018 Elsevier B.V. All rights reserved.

  6. Feedback Design Patterns for Math Online Learning Systems

    Science.gov (United States)

    Inventado, Paul Salvador; Scupelli, Peter; Heffernan, Cristina; Heffernan, Neil

    2017-01-01

    Increasingly, computer-based learning systems are used by educators to facilitate learning. Evaluations of several math learning systems show that they result in significant student learning improvements. Feedback provision is one of the key features in math learning systems that contribute to its success. We have recently been uncovering feedback…

  7. Discovering the Power of Individual-Based Modelling in Teaching and Learning: The Study of a Predator-Prey System

    Science.gov (United States)

    Ginovart, Marta

    2014-08-01

    The general aim is to promote the use of individual-based models (biological agent-based models) in teaching and learning contexts in life sciences and to make their progressive incorporation into academic curricula easier, complementing other existing modelling strategies more frequently used in the classroom. Modelling activities for the study of a predator-prey system for a mathematics classroom in the first year of an undergraduate program in biosystems engineering have been designed and implemented. These activities were designed to put two modelling approaches side by side, an individual-based model and a set of ordinary differential equations. In order to organize and display this, a system with wolves and sheep in a confined domain was considered and studied. With the teaching material elaborated and a computer to perform the numerical resolutions involved and the corresponding individual-based simulations, the students answered questions and completed exercises to achieve the learning goals set. Students' responses regarding the modelling of biological systems and these two distinct methodologies applied to the study of a predator-prey system were collected via questionnaires, open-ended queries and face-to-face dialogues. Taking into account the positive responses of the students when they were doing these activities, it was clear that using a discrete individual-based model to deal with a predator-prey system jointly with a set of ordinary differential equations enriches the understanding of the modelling process, adds new insights and opens novel perspectives of what can be done with computational models versus other models. The complementary views given by the two modelling approaches were very well assessed by students.

  8. An overload behavior detection system for engineering transport vehicles based on deep learning

    Science.gov (United States)

    Zhou, Libo; Wu, Gang

    2018-04-01

    This paper builds an overloaded truck detect system called ITMD to help traffic department automatically identify the engineering transport vehicles (commonly known as `dirt truck') in CCTV and determine whether the truck is overloaded or not. We build the ITMD system based on the Single Shot MultiBox Detector (SSD) model. By constructing the image dataset of the truck and adjusting hyper-parameters of the original SSD neural network, we successfully trained a basic network model which the ITMD system depends on. The basic ITMD system achieves 83.01% mAP on classifying overload/non-overload truck, which is a not bad result. Still, some shortcomings of basic ITMD system have been targeted to enhance: it is easy for the ITMD system to misclassify other similar vehicle as truck. In response to this problem, we optimized the basic ITMD system, which effectively reduced basic model's false recognition rate. The optimized ITMD system achieved 86.18% mAP on the test set, which is better than the 83.01% mAP of the basic ITMD system.

  9. Sitting Posture Monitoring System Based on a Low-Cost Load Cell Using Machine Learning

    Directory of Open Access Journals (Sweden)

    Jongryun Roh

    2018-01-01

    Full Text Available Sitting posture monitoring systems (SPMSs help assess the posture of a seated person in real-time and improve sitting posture. To date, SPMS studies reported have required many sensors mounted on the backrest plate and seat plate of a chair. The present study, therefore, developed a system that measures a total of six sitting postures including the posture that applied a load to the backrest plate, with four load cells mounted only on the seat plate. Various machine learning algorithms were applied to the body weight ratio measured by the developed SPMS to identify the method that most accurately classified the actual sitting posture of the seated person. After classifying the sitting postures using several classifiers, average and maximum classification rates of 97.20% and 97.94%, respectively, were obtained from nine subjects with a support vector machine using the radial basis function kernel; the results obtained by this classifier showed a statistically significant difference from the results of multiple classifications using other classifiers. The proposed SPMS was able to classify six sitting postures including the posture with loading on the backrest and showed the possibility of classifying the sitting posture even though the number of sensors is reduced.

  10. Exploring Academic Teachers' Continuance toward the Web-Based Learning System: The Role of Causal Attributions

    Science.gov (United States)

    Hung, Ming-Chien; Chang, I.-Chiu; Hwang, Hsin-Ginn

    2011-01-01

    The Expectation Confirmation Model (ECM) is a popular model used to explain the continuance of information system usage. However, past studies have found that the ECM, based on extrinsic motivations (e.g. perceived usefulness, user satisfaction), has limitations insofar as people often have both intrinsic and extrinsic motivations simultaneously.…

  11. An Autonomous Learning System of Bengali Characters Using Web-Based Intelligent Handwriting Recognition

    Science.gov (United States)

    Khatun, Nazma; Miwa, Jouji

    2016-01-01

    This research project was aimed to develop an intelligent Bengali handwriting education system to improve the literacy level in Bangladesh. Due to the socio-economical limitation, all of the population does not have the chance to go to school. Here, we developed a prototype of web-based (iPhone/smartphone or computer browser) intelligent…

  12. Establishment of a Learning Management System

    International Nuclear Information System (INIS)

    Han, K. W.; Kim, Y. T.; Lee, E. J.; Min, B. J.

    2006-01-01

    A web-based learning management system (LMS) has been established to address the need of customized education and training of Nuclear Training Center (NTC) of KAERI. The LMS is designed to deal with various learning types (e.g. on-line, off-line and blended) and a practically comprehensive learning activity cycle (e.g. course preparation, registration, learning, and postlearning) as well as to be user-friendly. A test with an example course scenario on the established system has shown its satisfactory performance. This paper discusses details of the established webbased learning management system in terms of development approach and functions of the LMS

  13. Application of Q-learning with temperature variation for bidding strategies in market based power systems

    International Nuclear Information System (INIS)

    Naghibi-Sistani, M.B.; Akbarzadeh-Tootoonchi, M.R.; Javidi-Dashte Bayaz, M.H.; Rajabi-Mashhadi, H.

    2006-01-01

    The electric power industry is confronted with restructuring in which the operation scheduling is going to be decided based on a competitive market. In this new arrangement, bidding strategy has become a major issue. Participants in this deregulated energy market place may be able to compete better by choosing a suitable bidding strategy for trading electricity. Different classical methods for decision making in the uncertain environment of the market can be applied to select a suitable strategy. Most of these methods, such as game theory, that insure reaching the best solution for all market participants, require a lot of information about the other market players and the market. However, in the real market place only a little information, such as the spot price, is available for all participants. In this paper, a modified reinforcement learning based on temperature variation has been first proposed and then applied to determine the optimal strategy for a power supplier in the electricity market. A Pool-Co model has been considered here, and the simulation results are shown to be the same as those of standard game theory. Adaptation of the method in the presence of parameter variation has been verified as well. The main advantage of the proposed method is that no information about other participants is required. Furthermore, our investigation shows that even if all participants use this method, they will stay in Nash equilibrium. (author)

  14. The Effects of Students' Learning Anxiety and Motivation on the Learning Achievement in the Activity Theory Based Gamified Learning Environment

    Science.gov (United States)

    Su, Chung-Ho

    2017-01-01

    The advancement of mobile game-based learning has encouraged many related studies, which has enabled students to learn more and faster. To enhance the clinical path of cardiac catheterization learning, this paper has developed a mobile 3D-CCGBLS (3D Cardiac Catheterization Game-Based Learning System) with a learning assessment for cardiac…

  15. The Picmonic® Learning System: enhancing memory retention of medical sciences, using an audiovisual mnemonic Web-based learning platform

    Directory of Open Access Journals (Sweden)

    Yang A

    2014-05-01

    Full Text Available Adeel Yang,1,* Hersh Goel,1,* Matthew Bryan,2 Ron Robertson,1 Jane Lim,1 Shehran Islam,1 Mark R Speicher2 1College of Medicine, The University of Arizona, Tucson, AZ, USA; 2Arizona College of Osteopathic Medicine, Midwestern University, Glendale, AZ, USA *These authors contributed equally to this work Background: Medical students are required to retain vast amounts of medical knowledge on the path to becoming physicians. To address this challenge, multimedia Web-based learning resources have been developed to supplement traditional text-based materials. The Picmonic® Learning System (PLS; Picmonic, Phoenix, AZ, USA is a novel multimedia Web-based learning platform that delivers audiovisual mnemonics designed to improve memory retention of medical sciences. Methods: A single-center, randomized, subject-blinded, controlled study was conducted to compare the PLS with traditional text-based material for retention of medical science topics. Subjects were randomly assigned to use two different types of study materials covering several diseases. Subjects randomly assigned to the PLS group were given audiovisual mnemonics along with text-based materials, whereas subjects in the control group were given the same text-based materials with key terms highlighted. The primary endpoints were the differences in performance on immediate, 1 week, and 1 month delayed free-recall and paired-matching tests. The secondary endpoints were the difference in performance on a 1 week delayed multiple-choice test and self-reported satisfaction with the study materials. Differences were calculated using unpaired two-tailed t-tests. Results: PLS group subjects demonstrated improvements of 65%, 161%, and 208% compared with control group subjects on free-recall tests conducted immediately, 1 week, and 1 month after study of materials, respectively. The results of performance on paired-matching tests showed an improvement of up to 331% for PLS group subjects. PLS group

  16. High-Throughput Automatic Training System for Odor-Based Learned Behaviors in Head-Fixed Mice

    Directory of Open Access Journals (Sweden)

    Zhe Han

    2018-02-01

    Full Text Available Understanding neuronal mechanisms of learned behaviors requires efficient behavioral assays. We designed a high-throughput automatic training system (HATS for olfactory behaviors in head-fixed mice. The hardware and software were constructed to enable automatic training with minimal human intervention. The integrated system was composed of customized 3D-printing supporting components, an odor-delivery unit with fast response, Arduino based hardware-controlling and data-acquisition unit. Furthermore, the customized software was designed to enable automatic training in all training phases, including lick-teaching, shaping and learning. Using HATS, we trained mice to perform delayed non-match to sample (DNMS, delayed paired association (DPA, Go/No-go (GNG, and GNG reversal tasks. These tasks probed cognitive functions including sensory discrimination, working memory, decision making and cognitive flexibility. Mice reached stable levels of performance within several days in the tasks. HATS enabled an experimenter to train eight mice simultaneously, therefore greatly enhanced the experimental efficiency. Combined with causal perturbation and activity recording techniques, HATS can greatly facilitate our understanding of the neural-circuitry mechanisms underlying learned behaviors.

  17. Supervised Learning for Dynamical System Learning.

    Science.gov (United States)

    Hefny, Ahmed; Downey, Carlton; Gordon, Geoffrey J

    2015-01-01

    Recently there has been substantial interest in spectral methods for learning dynamical systems. These methods are popular since they often offer a good tradeoff between computational and statistical efficiency. Unfortunately, they can be difficult to use and extend in practice: e.g., they can make it difficult to incorporate prior information such as sparsity or structure. To address this problem, we present a new view of dynamical system learning: we show how to learn dynamical systems by solving a sequence of ordinary supervised learning problems, thereby allowing users to incorporate prior knowledge via standard techniques such as L 1 regularization. Many existing spectral methods are special cases of this new framework, using linear regression as the supervised learner. We demonstrate the effectiveness of our framework by showing examples where nonlinear regression or lasso let us learn better state representations than plain linear regression does; the correctness of these instances follows directly from our general analysis.

  18. Short-Term Distribution System State Forecast Based on Optimal Synchrophasor Sensor Placement and Extreme Learning Machine

    Energy Technology Data Exchange (ETDEWEB)

    Jiang, Huaiguang; Zhang, Yingchen

    2016-11-14

    This paper proposes an approach for distribution system state forecasting, which aims to provide an accurate and high speed state forecasting with an optimal synchrophasor sensor placement (OSSP) based state estimator and an extreme learning machine (ELM) based forecaster. Specifically, considering the sensor installation cost and measurement error, an OSSP algorithm is proposed to reduce the number of synchrophasor sensor and keep the whole distribution system numerically and topologically observable. Then, the weighted least square (WLS) based system state estimator is used to produce the training data for the proposed forecaster. Traditionally, the artificial neural network (ANN) and support vector regression (SVR) are widely used in forecasting due to their nonlinear modeling capabilities. However, the ANN contains heavy computation load and the best parameters for SVR are difficult to obtain. In this paper, the ELM, which overcomes these drawbacks, is used to forecast the future system states with the historical system states. The proposed approach is effective and accurate based on the testing results.

  19. Factors Affecting University Instructors' Adoption of Web-Based Learning Systems: Case Study of Iran

    Science.gov (United States)

    Motaghian, Hediyeh; Hassanzadeh, Alireza; Moghadam, Davood Karimzadgan

    2013-01-01

    In many societies e-learning has become the main mechanism supporting distance education. Although e-learning efforts are considered to be a significant corporate investment, many surveys indicate high drop-out rates or failures. This research uses an integrated model in order to assessing the influence of IS-oriented, psychological and behavioral…

  20. Development of a Mobile Learning System Based on a Collaborative Problem-Posing Strategy

    Science.gov (United States)

    Sung, Han-Yu; Hwang, Gwo-Jen; Chang, Ya-Chi

    2016-01-01

    In this study, a problem-posing strategy is proposed for supporting collaborative mobile learning activities. Accordingly, a mobile learning environment has been developed, and an experiment on a local culture course has been conducted to evaluate the effectiveness of the proposed approach. Three classes of an elementary school in southern Taiwan…

  1. Sensitivity-based self-learning fuzzy logic control for a servo system

    NARCIS (Netherlands)

    Balenovic, M.

    1998-01-01

    Describes an experimental verification of a self-learning fuzzy logic controller (SLFLC). The SLFLC contains a learning algorithm that utilizes a second-order reference model and a sensitivity model related to the fuzzy controller parameters. The effectiveness of the proposed controller has been

  2. A Linked Data-Based Collaborative Annotation System for Increasing Learning Achievements

    Science.gov (United States)

    Zarzour, Hafed; Sellami, Mokhtar

    2017-01-01

    With the emergence of the Web 2.0, collaborative annotation practices have become more mature in the field of learning. In this context, several recent studies have shown the powerful effects of the integration of annotation mechanism in learning process. However, most of these studies provide poor support for semantically structured resources,…

  3. An Improved Pathological Brain Detection System Based on Two-Dimensional PCA and Evolutionary Extreme Learning Machine.

    Science.gov (United States)

    Nayak, Deepak Ranjan; Dash, Ratnakar; Majhi, Banshidhar

    2017-12-07

    Pathological brain detection has made notable stride in the past years, as a consequence many pathological brain detection systems (PBDSs) have been proposed. But, the accuracy of these systems still needs significant improvement in order to meet the necessity of real world diagnostic situations. In this paper, an efficient PBDS based on MR images is proposed that markedly improves the recent results. The proposed system makes use of contrast limited adaptive histogram equalization (CLAHE) to enhance the quality of the input MR images. Thereafter, two-dimensional PCA (2DPCA) strategy is employed to extract the features and subsequently, a PCA+LDA approach is used to generate a compact and discriminative feature set. Finally, a new learning algorithm called MDE-ELM is suggested that combines modified differential evolution (MDE) and extreme learning machine (ELM) for segregation of MR images as pathological or healthy. The MDE is utilized to optimize the input weights and hidden biases of single-hidden-layer feed-forward neural networks (SLFN), whereas an analytical method is used for determining the output weights. The proposed algorithm performs optimization based on both the root mean squared error (RMSE) and norm of the output weights of SLFNs. The suggested scheme is benchmarked on three standard datasets and the results are compared against other competent schemes. The experimental outcomes show that the proposed scheme offers superior results compared to its counterparts. Further, it has been noticed that the proposed MDE-ELM classifier obtains better accuracy with compact network architecture than conventional algorithms.

  4. Learning-Based Algal Bloom Event Recognition for Oceanographic Decision Support System Using Remote Sensing Data

    Directory of Open Access Journals (Sweden)

    Weilong Song

    2015-10-01

    Full Text Available This paper describes the use of machine learning methods to build a decision support system for predicting the distribution of coastal ocean algal blooms based on remote sensing data in Monterey Bay. This system can help scientists obtain prior information in a large ocean region and formulate strategies for deploying robots in the coastal ocean for more detailed in situ exploration. The difficulty is that there are insufficient in situ data to create a direct statistical machine learning model with satellite data inputs. To solve this problem, we built a Random Forest model using MODIS and MERIS satellite data and applied a threshold filter to balance the training inputs and labels. To build this model, several features of remote sensing satellites were tested to obtain the most suitable features for the system. After building the model, we compared our random forest model with previous trials based on a Support Vector Machine (SVM using satellite data from 221 days, and our approach performed significantly better. Finally, we used the latest in situ data from a September 2014 field experiment to validate our model.

  5. A Mobile Gamification Learning System for Improving the Learning Motivation and Achievements

    Science.gov (United States)

    Su, C-H.; Cheng, C-H.

    2015-01-01

    This paper aims to investigate how a gamified learning approach influences science learning, achievement and motivation, through a context-aware mobile learning environment, and explains the effects on motivation and student learning. A series of gamified learning activities, based on MGLS (Mobile Gamification Learning System), was developed and…

  6. System modeling based on machine learning for anomaly detection and predictive maintenance in industrial plants

    OpenAIRE

    Kroll, Björn; Schaffranek, David; Schriegel, Sebastian; Niggemann, Oliver

    2014-01-01

    Electricity, water or air are some Industrial energy carriers which are struggling under the prices of primary energy carriers. The European Union for example used more 20.000.000 GWh electricity in 2011 based on the IEA Report [1]. Cyber Physical Production Systems (CPPS) are able to reduce this amount, but they also help to increase the efficiency of machines above expectations which results in a more cost efficient production. Especially in the field of improving industrial plants, one of ...

  7. Intersections of Critical Systems Thinking and Community Based Participatory Research: A Learning Organization Example with the Autistic Community.

    Science.gov (United States)

    Raymaker, Dora M

    2016-10-01

    Critical systems thinking (CST) and community based participatory research (CBPR) are distinct approaches to inquiry which share a primary commitment to holism and human emancipation, as well as common grounding in critical theory and emancipatory and pragmatic philosophy. This paper explores their intersections and complements on a historical, philosophical, and theoretical level, and then proposes a hybrid approach achieved by applying CBPR's principles and considerations for operationalizing emancipatory practice to traditional systems thinking frameworks and practices. This hybrid approach is illustrated in practice with examples drawn from of the implementation of the learning organization model in an action research setting with the Autistic community. Our experience of being able to actively attend to, and continuously equalize, power relations within an organizational framework that otherwise has great potential for reinforcing power inequity suggests CBPR's principles and considerations for operationalizing emancipatory practice could be useful in CST settings, and CST's vocabulary, methods, and clarity around systems thinking concepts could be valuable to CBPR practioners.

  8. A Digital Architecture for a Network-Based Learning Health System: Integrating Chronic Care Management, Quality Improvement, and Research.

    Science.gov (United States)

    Marsolo, Keith; Margolis, Peter A; Forrest, Christopher B; Colletti, Richard B; Hutton, John J

    2015-01-01

    We collaborated with the ImproveCareNow Network to create a proof-of-concept architecture for a network-based Learning Health System. This collaboration involved transitioning an existing registry to one that is linked to the electronic health record (EHR), enabling a "data in once" strategy. We sought to automate a series of reports that support care improvement while also demonstrating the use of observational registry data for comparative effectiveness research. We worked with three leading EHR vendors to create EHR-based data collection forms. We automated many of ImproveCareNow's analytic reports and developed an application for storing protected health information and tracking patient consent. Finally, we deployed a cohort identification tool to support feasibility studies and hypothesis generation. There is ongoing uptake of the system. To date, 31 centers have adopted the EHR-based forms and 21 centers are uploading data to the registry. Usage of the automated reports remains high and investigators have used the cohort identification tools to respond to several clinical trial requests. The current process for creating EHR-based data collection forms requires groups to work individually with each vendor. A vendor-agnostic model would allow for more rapid uptake. We believe that interfacing network-based registries with the EHR would allow them to serve as a source of decision support. Additional standards are needed in order for this vision to be achieved, however. We have successfully implemented a proof-of-concept Learning Health System while providing a foundation on which others can build. We have also highlighted opportunities where sponsors could help accelerate progress.

  9. Evolutionary strategy to develop learning-based decision systems. Application to breast cancer and liver fibrosis stadialization.

    Science.gov (United States)

    Gorunescu, Florin; Belciug, Smaranda

    2014-06-01

    The purpose of this paper is twofold: first, to propose an evolutionary-based method for building a decision model and, second, to assess and validate the model's performance using five different real-world medical datasets (breast cancer and liver fibrosis) by comparing it with state-of-the-art machine learning techniques. The evolutionary-inspired approach has been used to develop the learning-based decision model in the following manner: the hybridization of algorithms has been considered as "crossover", while the development of new variants which can be thought of as "mutation". An appropriate hierarchy of the component algorithms was established based on a statistically built fitness measure. A synergetic decision-making process, based on a weighted voting system, involved the collaboration between the selected algorithms in making the final decision. Well-established statistical performance measures and comparison tests have been extensively used to design and implement the model. Finally, the proposed method has been tested on five medical datasets, out of which four publicly available, and contrasted with state-of-the-art techniques, showing its efficiency in supporting the medical decision-making process. Copyright © 2014 Elsevier Inc. All rights reserved.

  10. New Ideas on the Design of the Web-Based Learning System Oriented to Problem Solving from the Perspective of Question Chain and Learning Community

    Science.gov (United States)

    Zhang, Yin; Chu, Samuel K. W.

    2016-01-01

    In recent years, a number of models concerning problem solving systems have been put forward. However, many of them stress on technology and neglect the research of problem solving itself, especially the learning mechanism related to problem solving. In this paper, we analyze the learning mechanism of problem solving, and propose that when…

  11. A New Learning Control System for Basketball Free Throws Based on Real Time Video Image Processing and Biofeedback

    Directory of Open Access Journals (Sweden)

    R. Sarang

    2018-02-01

    Full Text Available Shooting free throws plays an important role in basketball. The major problem in performing a correct free throw seems to be inappropriate training. Training is performed offline and it is often not that persistent. The aim of this paper is to consciously modify and control the free throw using biofeedback. Elbow and shoulder dynamics are calculated by an image processing technique equipped with a video image acquisition system. The proposed setup in this paper, named learning control system, is able to quantify and provide feedback of the above parameters in real time as audio signals. Therefore, it yielded to performing a correct learning and conscious control of shooting. Experimental results showed improvements in the free throw shooting style including shot pocket and locked position. The mean values of elbow and shoulder angles were controlled approximately on 89o and 26o, for shot pocket and also these angles were tuned approximately on 180o and 47o respectively for the locked position (closed to the desired pattern of the free throw based on valid FIBA references. Not only the mean values enhanced but also the standard deviations of these angles decreased meaningfully, which shows shooting style convergence and uniformity. Also, in training conditions, the average percentage of making successful free throws increased from about 64% to even 87% after using this setup and in competition conditions the average percentage of successful free throws enhanced about 20%, although using the learning control system may not be the only reason for these outcomes. The proposed system is easy to use, inexpensive, portable and real time applicable.

  12. How to Evaluate Competencies in Game-Based Learning Systems Automatically?

    OpenAIRE

    Thomas , Pradeepa; Labat , Jean-Marc; Muratet , Mathieu; Yessad , Amel

    2012-01-01

    International audience; Serious games are increasingly used in schools, universities or in vocational training. When they are used in the classroom, teachers often have to deal with the lack of tools for monitoring the students during the game and assessing them after the game. So they often tend to add assessment questionnaires to the fun sequence of " learning by playing " , to ensure that students have learned during the session. Our goal is to enable the teacher to do without this type of...

  13. ENGINEERING OF UNIVERSITY INTELLIGENT LEARNING SYSTEMS

    Directory of Open Access Journals (Sweden)

    Vasiliy M. Trembach

    2016-01-01

    Full Text Available In the article issues of engineering intelligent tutoring systems of University with adaptation are considered. The article also dwells on some modern approaches to engineering of information systems. It shows the role of engineering e-learning devices (systems in system engineering. The article describes the basic principles of system engineering and these principles are expanded regarding to intelligent information systems. The structure of intelligent learning systems with adaptation of the individual learning environments based on services is represented in the article.

  14. Classification of Suicide Attempts through a Machine Learning Algorithm Based on Multiple Systemic Psychiatric Scales

    Directory of Open Access Journals (Sweden)

    Jihoon Oh

    2017-09-01

    Full Text Available Classification and prediction of suicide attempts in high-risk groups is important for preventing suicide. The purpose of this study was to investigate whether the information from multiple clinical scales has classification power for identifying actual suicide attempts. Patients with depression and anxiety disorders (N = 573 were included, and each participant completed 31 self-report psychiatric scales and questionnaires about their history of suicide attempts. We then trained an artificial neural network classifier with 41 variables (31 psychiatric scales and 10 sociodemographic elements and ranked the contribution of each variable for the classification of suicide attempts. To evaluate the clinical applicability of our model, we measured classification performance with top-ranked predictors. Our model had an overall accuracy of 93.7% in 1-month, 90.8% in 1-year, and 87.4% in lifetime suicide attempts detection. The area under the receiver operating characteristic curve (AUROC was the highest for 1-month suicide attempts detection (0.93, followed by lifetime (0.89, and 1-year detection (0.87. Among all variables, the Emotion Regulation Questionnaire had the highest contribution, and the positive and negative characteristics of the scales similarly contributed to classification performance. Performance on suicide attempts classification was largely maintained when we only used the top five ranked variables for training (AUROC; 1-month, 0.75, 1-year, 0.85, lifetime suicide attempts detection, 0.87. Our findings indicate that information from self-report clinical scales can be useful for the classification of suicide attempts. Based on the reliable performance of the top five predictors alone, this machine learning approach could help clinicians identify high-risk patients in clinical settings.

  15. Classification of Suicide Attempts through a Machine Learning Algorithm Based on Multiple Systemic Psychiatric Scales.

    Science.gov (United States)

    Oh, Jihoon; Yun, Kyongsik; Hwang, Ji-Hyun; Chae, Jeong-Ho

    2017-01-01

    Classification and prediction of suicide attempts in high-risk groups is important for preventing suicide. The purpose of this study was to investigate whether the information from multiple clinical scales has classification power for identifying actual suicide attempts. Patients with depression and anxiety disorders ( N  = 573) were included, and each participant completed 31 self-report psychiatric scales and questionnaires about their history of suicide attempts. We then trained an artificial neural network classifier with 41 variables (31 psychiatric scales and 10 sociodemographic elements) and ranked the contribution of each variable for the classification of suicide attempts. To evaluate the clinical applicability of our model, we measured classification performance with top-ranked predictors. Our model had an overall accuracy of 93.7% in 1-month, 90.8% in 1-year, and 87.4% in lifetime suicide attempts detection. The area under the receiver operating characteristic curve (AUROC) was the highest for 1-month suicide attempts detection (0.93), followed by lifetime (0.89), and 1-year detection (0.87). Among all variables, the Emotion Regulation Questionnaire had the highest contribution, and the positive and negative characteristics of the scales similarly contributed to classification performance. Performance on suicide attempts classification was largely maintained when we only used the top five ranked variables for training (AUROC; 1-month, 0.75, 1-year, 0.85, lifetime suicide attempts detection, 0.87). Our findings indicate that information from self-report clinical scales can be useful for the classification of suicide attempts. Based on the reliable performance of the top five predictors alone, this machine learning approach could help clinicians identify high-risk patients in clinical settings.

  16. Time series analytics using sliding window metaheuristic optimization-based machine learning system for identifying building energy consumption patterns

    International Nuclear Information System (INIS)

    Chou, Jui-Sheng; Ngo, Ngoc-Tri

    2016-01-01

    Highlights: • This study develops a novel time-series sliding window forecast system. • The system integrates metaheuristics, machine learning and time-series models. • Site experiment of smart grid infrastructure is installed to retrieve real-time data. • The proposed system accurately predicts energy consumption in residential buildings. • The forecasting system can help users minimize their electricity usage. - Abstract: Smart grids are a promising solution to the rapidly growing power demand because they can considerably increase building energy efficiency. This study developed a novel time-series sliding window metaheuristic optimization-based machine learning system for predicting real-time building energy consumption data collected by a smart grid. The proposed system integrates a seasonal autoregressive integrated moving average (SARIMA) model and metaheuristic firefly algorithm-based least squares support vector regression (MetaFA-LSSVR) model. Specifically, the proposed system fits the SARIMA model to linear data components in the first stage, and the MetaFA-LSSVR model captures nonlinear data components in the second stage. Real-time data retrieved from an experimental smart grid installed in a building were used to evaluate the efficacy and effectiveness of the proposed system. A k-week sliding window approach is proposed for employing historical data as input for the novel time-series forecasting system. The prediction system yielded high and reliable accuracy rates in 1-day-ahead predictions of building energy consumption, with a total error rate of 1.181% and mean absolute error of 0.026 kW h. Notably, the system demonstrates an improved accuracy rate in the range of 36.8–113.2% relative to those of the linear forecasting model (i.e., SARIMA) and nonlinear forecasting models (i.e., LSSVR and MetaFA-LSSVR). Therefore, end users can further apply the forecasted information to enhance efficiency of energy usage in their buildings, especially

  17. Patterns of Use of an Agent-Based Model and a System Dynamics Model: The Application of Patterns of Use and the Impacts on Learning Outcomes

    Science.gov (United States)

    Thompson, Kate; Reimann, Peter

    2010-01-01

    A classification system that was developed for the use of agent-based models was applied to strategies used by school-aged students to interrogate an agent-based model and a system dynamics model. These were compared, and relationships between learning outcomes and the strategies used were also analysed. It was found that the classification system…

  18. Development and Testing of a M-Learning System for the Professional Development of Academics through Design-Based Action Research

    Science.gov (United States)

    Keskin, Nilgun Ozdamar; Kuzu, Abdullah

    2015-01-01

    In the present study, a mobile learning system for the professional development of academics was developed by design based action research, and the perceptions and experiences of the academics using this system were examined. In the first phase of this design-based action research, the research question was defined. In the second phase, a…

  19. Machine-learning-based real-bogus system for the HSC-SSP moving object detection pipeline

    Science.gov (United States)

    Lin, Hsing-Wen; Chen, Ying-Tung; Wang, Jen-Hung; Wang, Shiang-Yu; Yoshida, Fumi; Ip, Wing-Huen; Miyazaki, Satoshi; Terai, Tsuyoshi

    2018-01-01

    Machine-learning techniques are widely applied in many modern optical sky surveys, e.g., Pan-STARRS1, PTF/iPTF, and the Subaru/Hyper Suprime-Cam survey, to reduce human intervention in data verification. In this study, we have established a machine-learning-based real-bogus system to reject false detections in the Subaru/Hyper-Suprime-Cam Strategic Survey Program (HSC-SSP) source catalog. Therefore, the HSC-SSP moving object detection pipeline can operate more effectively due to the reduction of false positives. To train the real-bogus system, we use stationary sources as the real training set and "flagged" data as the bogus set. The training set contains 47 features, most of which are photometric measurements and shape moments generated from the HSC image reduction pipeline (hscPipe). Our system can reach a true positive rate (tpr) ˜96% with a false positive rate (fpr) ˜1% or tpr ˜99% at fpr ˜5%. Therefore, we conclude that stationary sources are decent real training samples, and using photometry measurements and shape moments can reject false positives effectively.

  20. The Picmonic(®) Learning System: enhancing memory retention of medical sciences, using an audiovisual mnemonic Web-based learning platform.

    Science.gov (United States)

    Yang, Adeel; Goel, Hersh; Bryan, Matthew; Robertson, Ron; Lim, Jane; Islam, Shehran; Speicher, Mark R

    2014-01-01

    Medical students are required to retain vast amounts of medical knowledge on the path to becoming physicians. To address this challenge, multimedia Web-based learning resources have been developed to supplement traditional text-based materials. The Picmonic(®) Learning System (PLS; Picmonic, Phoenix, AZ, USA) is a novel multimedia Web-based learning platform that delivers audiovisual mnemonics designed to improve memory retention of medical sciences. A single-center, randomized, subject-blinded, controlled study was conducted to compare the PLS with traditional text-based material for retention of medical science topics. Subjects were randomly assigned to use two different types of study materials covering several diseases. Subjects randomly assigned to the PLS group were given audiovisual mnemonics along with text-based materials, whereas subjects in the control group were given the same text-based materials with key terms highlighted. The primary endpoints were the differences in performance on immediate, 1 week, and 1 month delayed free-recall and paired-matching tests. The secondary endpoints were the difference in performance on a 1 week delayed multiple-choice test and self-reported satisfaction with the study materials. Differences were calculated using unpaired two-tailed t-tests. PLS group subjects demonstrated improvements of 65%, 161%, and 208% compared with control group subjects on free-recall tests conducted immediately, 1 week, and 1 month after study of materials, respectively. The results of performance on paired-matching tests showed an improvement of up to 331% for PLS group subjects. PLS group subjects also performed 55% greater than control group subjects on a 1 week delayed multiple choice test requiring higher-order thinking. The differences in test performance between the PLS group subjects and the control group subjects were statistically significant (P<0.001), and the PLS group subjects reported higher overall satisfaction with the

  1. Motion Learning Based on Bayesian Program Learning

    Directory of Open Access Journals (Sweden)

    Cheng Meng-Zhen

    2017-01-01

    Full Text Available The concept of virtual human has been highly anticipated since the 1980s. By using computer technology, Human motion simulation could generate authentic visual effect, which could cheat human eyes visually. Bayesian Program Learning train one or few motion data, generate new motion data by decomposing and combining. And the generated motion will be more realistic and natural than the traditional one.In this paper, Motion learning based on Bayesian program learning allows us to quickly generate new motion data, reduce workload, improve work efficiency, reduce the cost of motion capture, and improve the reusability of data.

  2. Feature selection in wind speed prediction systems based on a hybrid coral reefs optimization – Extreme learning machine approach

    International Nuclear Information System (INIS)

    Salcedo-Sanz, S.; Pastor-Sánchez, A.; Prieto, L.; Blanco-Aguilera, A.; García-Herrera, R.

    2014-01-01

    Highlights: • A novel approach for short-term wind speed prediction is presented. • The system is formed by a coral reefs optimization algorithm and an extreme learning machine. • Feature selection is carried out with the CRO to improve the ELM performance. • The method is tested in real wind farm data in USA, for the period 2007–2008. - Abstract: This paper presents a novel approach for short-term wind speed prediction based on a Coral Reefs Optimization algorithm (CRO) and an Extreme Learning Machine (ELM), using meteorological predictive variables from a physical model (the Weather Research and Forecast model, WRF). The approach is based on a Feature Selection Problem (FSP) carried out with the CRO, that must obtain a reduced number of predictive variables out of the total available from the WRF. This set of features will be the input of an ELM, that finally provides the wind speed prediction. The CRO is a novel bio-inspired approach, based on the simulation of reef formation and coral reproduction, able to obtain excellent results in optimization problems. On the other hand, the ELM is a new paradigm in neural networks’ training, that provides a robust and extremely fast training of the network. Together, these algorithms are able to successfully solve this problem of feature selection in short-term wind speed prediction. Experiments in a real wind farm in the USA show the excellent performance of the CRO–ELM approach in this FSP wind speed prediction problem

  3. Mining Web-based Educational Systems to Predict Student Learning Achievements

    Directory of Open Access Journals (Sweden)

    José del Campo-Ávila

    2015-03-01

    Full Text Available Educational Data Mining (EDM is getting great importance as a new interdisciplinary research field related to some other areas. It is directly connected with Web-based Educational Systems (WBES and Data Mining (DM, a fundamental part of Knowledge Discovery in Databases. The former defines the context: WBES store and manage huge amounts of data. Such data are increasingly growing and they contain hidden knowledge that could be very useful to the users (both teachers and students. It is desirable to identify such knowledge in the form of models, patterns or any other representation schema that allows a better exploitation of the system. The latter reveals itself as the tool to achieve such discovering. Data mining must afford very complex and different situations to reach quality solutions. Therefore, data mining is a research field where many advances are being done to accommodate and solve emerging problems. For this purpose, many techniques are usually considered. In this paper we study how data mining can be used to induce student models from the data acquired by a specific Web-based tool for adaptive testing, called SIETTE. Concretely we have used top down induction decision trees algorithms to extract the patterns because these models, decision trees, are easily understandable. In addition, the conducted validation processes have assured high quality models.

  4. Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features.

    Science.gov (United States)

    Zhang, Xin; Yan, Lin-Feng; Hu, Yu-Chuan; Li, Gang; Yang, Yang; Han, Yu; Sun, Ying-Zhi; Liu, Zhi-Cheng; Tian, Qiang; Han, Zi-Yang; Liu, Le-De; Hu, Bin-Quan; Qiu, Zi-Yu; Wang, Wen; Cui, Guang-Bin

    2017-07-18

    Current machine learning techniques provide the opportunity to develop noninvasive and automated glioma grading tools, by utilizing quantitative parameters derived from multi-modal magnetic resonance imaging (MRI) data. However, the efficacies of different machine learning methods in glioma grading have not been investigated.A comprehensive comparison of varied machine learning methods in differentiating low-grade gliomas (LGGs) and high-grade gliomas (HGGs) as well as WHO grade II, III and IV gliomas based on multi-parametric MRI images was proposed in the current study. The parametric histogram and image texture attributes of 120 glioma patients were extracted from the perfusion, diffusion and permeability parametric maps of preoperative MRI. Then, 25 commonly used machine learning classifiers combined with 8 independent attribute selection methods were applied and evaluated using leave-one-out cross validation (LOOCV) strategy. Besides, the influences of parameter selection on the classifying performances were investigated. We found that support vector machine (SVM) exhibited superior performance to other classifiers. By combining all tumor attributes with synthetic minority over-sampling technique (SMOTE), the highest classifying accuracy of 0.945 or 0.961 for LGG and HGG or grade II, III and IV gliomas was achieved. Application of Recursive Feature Elimination (RFE) attribute selection strategy further improved the classifying accuracies. Besides, the performances of LibSVM, SMO, IBk classifiers were influenced by some key parameters such as kernel type, c, gama, K, etc. SVM is a promising tool in developing automated preoperative glioma grading system, especially when being combined with RFE strategy. Model parameters should be considered in glioma grading model optimization.

  5. Project-based learning applied to spacecraft power systems: a long-term engineering and educational program at UPM University

    Science.gov (United States)

    Pindado, Santiago; Cubas, Javier; Roibás-Millán, Elena; Sorribes-Palmer, Félix

    2018-03-01

    The IDR/UPM Institute is the research center responsible for the Master in Space Systems (MUSE) of Universidad Politécnica de Madrid (UPM). This is a 2-year (120 ECTS) master's degree focused on space technology. The UPMSat-2 satellite program has become an excellent educational framework in which the academic contents of the master are trained through project-based learning and following a multidisciplinary approach. In the present work, the educational projects developed and carried out in relation to spacecraft power systems at the IDR/UPM Institute are described. These projects are currently being developed in the framework represented by the aforementioned MUSE master's program and UPMSat-2.

  6. The Action Research Program: Experiential Learning in Systems-Based Practice for First-Year Medical Students.

    Science.gov (United States)

    Ackerman, Sara L; Boscardin, Christy; Karliner, Leah; Handley, Margaret A; Cheng, Sarah; Gaither, Thomas W; Hagey, Jill; Hennein, Lauren; Malik, Faizan; Shaw, Brian; Trinidad, Norver; Zahner, Greg; Gonzales, Ralph

    2016-01-01

    Systems-based practice focuses on the organization, financing, and delivery of medical services. The American Association of Medical Colleges has recommended that systems-based practice be incorporated into medical schools' curricula. However, experiential learning in systems-based practice, including practical strategies to improve the quality and efficiency of clinical care, is often absent from or inconsistently included in medical education. A multidisciplinary clinician and nonclinician faculty team partnered with a cardiology outpatient clinic to design a 9-month clerkship for 1st-year medical students focused on systems-based practice, delivery of clinical care, and strategies to improve the quality and efficiency of clinical operations. The clerkship was called the Action Research Program. In 2013-2014, 8 trainees participated in educational seminars, research activities, and 9-week clinic rotations. A qualitative process and outcome evaluation drew on interviews with students, clinic staff, and supervising physicians, as well as students' detailed field notes. The Action Research Program was developed and implemented at the University of California, San Francisco, an academic medical center in the United States. All educational activities took place at the university's medical school and at the medical center's cardiology outpatient clinic. Students reported and demonstrated increased understanding of how care delivery systems work, improved clinical skills, growing confidence in interactions with patients, and appreciation for patients' experiences. Clinicians reported increased efficiency at the clinic level and improved performance and job satisfaction among medical assistants as a result of their unprecedented mentoring role with students. Some clinicians felt burdened when students shadowed them and asked questions during interactions with patients. Most student-led improvement projects were not fully implemented. The Action Research Program is a

  7. Reinforcement-Learning-Based Robust Controller Design for Continuous-Time Uncertain Nonlinear Systems Subject to Input Constraints.

    Science.gov (United States)

    Liu, Derong; Yang, Xiong; Wang, Ding; Wei, Qinglai

    2015-07-01

    The design of stabilizing controller for uncertain nonlinear systems with control constraints is a challenging problem. The constrained-input coupled with the inability to identify accurately the uncertainties motivates the design of stabilizing controller based on reinforcement-learning (RL) methods. In this paper, a novel RL-based robust adaptive control algorithm is developed for a class of continuous-time uncertain nonlinear systems subject to input constraints. The robust control problem is converted to the constrained optimal control problem with appropriately selecting value functions for the nominal system. Distinct from typical action-critic dual networks employed in RL, only one critic neural network (NN) is constructed to derive the approximate optimal control. Meanwhile, unlike initial stabilizing control often indispensable in RL, there is no special requirement imposed on the initial control. By utilizing Lyapunov's direct method, the closed-loop optimal control system and the estimated weights of the critic NN are proved to be uniformly ultimately bounded. In addition, the derived approximate optimal control is verified to guarantee the uncertain nonlinear system to be stable in the sense of uniform ultimate boundedness. Two simulation examples are provided to illustrate the effectiveness and applicability of the present approach.

  8. A New Approach of an Intelligent E-Learning System Based on Learners' Skill Level and Learners' Success Rate

    Science.gov (United States)

    Mohamed, Hafidi; Lamia, Mahnane

    2015-01-01

    Learners usually meet cognitive overload and disorientation problems when using e-learning system. At present, most of the studies in e-learning either concentrate on the technological aspect or focus on adapting learner's interests or browsing behaviors, while, learner's skill level and learners' success rate is usually neglected. In this paper,…

  9. Individualized Teaching and Autonomous Learning: Developing EFL Learners' CLA in a Web-Based Language Skills Training System

    Science.gov (United States)

    Lu, Zhihong; Wen, Fuan; Li, Ping

    2012-01-01

    Teaching listening and speaking in English in China has been given top priority on the post-secondary level. This has lead to the question of how learners develop communicative language ability (CLA) effectively in computer-assisted language learning (CALL) environments. The authors demonstrate a self-developed language skill learning system with…

  10. Community-Based Research: Learning about Attitudes towards the Criminal Justice System

    Science.gov (United States)

    Marche, Tammy A.; Briere, Jennifer L.

    2012-01-01

    Research points to the pedagogical value of an engaged and community service-learning approach to developing understanding of course content (Astin, Vogelgesang, Ikeda, & Yee, 2000). To help students achieve a better understanding of how the discipline of psychology contributes to the discipline of law, some students in a second year…

  11. Cross Cultural Analysis of the Use and Perceptions of Web-Based Learning Systems

    Science.gov (United States)

    Arenas-Gaitan, Jorge; Ramirez-Correa, Patricio E.; Rondan-Cataluna, F. Javier

    2011-01-01

    The main objective of this paper is to examine cultural differences and technology acceptances from students of two universities, one is from a European country: Spain, and the other is in Latin America: Chile. Both of them provide their students with e-learning platforms. The technology acceptance model (TAM) and Hofstede's cultural dimensions…

  12. Teaching Problem Based Learning as Blended Learning

    DEFF Research Database (Denmark)

    Kolbæk, Ditte; Nortvig, Anne-Mette

    2018-01-01

    Problem-based and project organized learning (PBL) was originally developed for collaboration between physically present students, but political decisions at many universities require that collaboration, dialogues, and other PBL activities take place online as well. With a theoretical point...... of departure in Dewey and a methodological point of departure in netnography, this study focuses on an online module at Aalborg University where teaching is based on PBL. With the research question ‘How can teachers design for PBL online,’ this study explores the teacher’s role in a six weeks’ blended learning...... program, and we present suggestions for designs for blended learning PBL based on case studies from two PBL courses...

  13. Automatic generation control of multi-area power systems with diverse energy sources using Teaching Learning Based Optimization algorithm

    Directory of Open Access Journals (Sweden)

    Rabindra Kumar Sahu

    2016-03-01

    Full Text Available This paper presents the design and analysis of Proportional-Integral-Double Derivative (PIDD controller for Automatic Generation Control (AGC of multi-area power systems with diverse energy sources using Teaching Learning Based Optimization (TLBO algorithm. At first, a two-area reheat thermal power system with appropriate Generation Rate Constraint (GRC is considered. The design problem is formulated as an optimization problem and TLBO is employed to optimize the parameters of the PIDD controller. The superiority of the proposed TLBO based PIDD controller has been demonstrated by comparing the results with recently published optimization technique such as hybrid Firefly Algorithm and Pattern Search (hFA-PS, Firefly Algorithm (FA, Bacteria Foraging Optimization Algorithm (BFOA, Genetic Algorithm (GA and conventional Ziegler Nichols (ZN for the same interconnected power system. Also, the proposed approach has been extended to two-area power system with diverse sources of generation like thermal, hydro, wind and diesel units. The system model includes boiler dynamics, GRC and Governor Dead Band (GDB non-linearity. It is observed from simulation results that the performance of the proposed approach provides better dynamic responses by comparing the results with recently published in the literature. Further, the study is extended to a three unequal-area thermal power system with different controllers in each area and the results are compared with published FA optimized PID controller for the same system under study. Finally, sensitivity analysis is performed by varying the system parameters and operating load conditions in the range of ±25% from their nominal values to test the robustness.

  14. LaSVM-based big data learning system for dynamic prediction of air pollution in Tehran.

    Science.gov (United States)

    Ghaemi, Z; Alimohammadi, A; Farnaghi, M

    2018-04-20

    Due to critical impacts of air pollution, prediction and monitoring of air quality in urban areas are important tasks. However, because of the dynamic nature and high spatio-temporal variability, prediction of the air pollutant concentrations is a complex spatio-temporal problem. Distribution of pollutant concentration is influenced by various factors such as the historical pollution data and weather conditions. Conventional methods such as the support vector machine (SVM) or artificial neural networks (ANN) show some deficiencies when huge amount of streaming data have to be analyzed for urban air pollution prediction. In order to overcome the limitations of the conventional methods and improve the performance of urban air pollution prediction in Tehran, a spatio-temporal system is designed using a LaSVM-based online algorithm. Pollutant concentration and meteorological data along with geographical parameters are continually fed to the developed online forecasting system. Performance of the system is evaluated by comparing the prediction results of the Air Quality Index (AQI) with those of a traditional SVM algorithm. Results show an outstanding increase of speed by the online algorithm while preserving the accuracy of the SVM classifier. Comparison of the hourly predictions for next coming 24 h, with those of the measured pollution data in Tehran pollution monitoring stations shows an overall accuracy of 0.71, root mean square error of 0.54 and coefficient of determination of 0.81. These results are indicators of the practical usefulness of the online algorithm for real-time spatial and temporal prediction of the urban air quality.

  15. Machine learning-based assessment tool for imbalance and vestibular dysfunction with virtual reality rehabilitation system.

    Science.gov (United States)

    Yeh, Shih-Ching; Huang, Ming-Chun; Wang, Pa-Chun; Fang, Te-Yung; Su, Mu-Chun; Tsai, Po-Yi; Rizzo, Albert

    2014-10-01

    Dizziness is a major consequence of imbalance and vestibular dysfunction. Compared to surgery and drug treatments, balance training is non-invasive and more desired. However, training exercises are usually tedious and the assessment tool is insufficient to diagnose patient's severity rapidly. An interactive virtual reality (VR) game-based rehabilitation program that adopted Cawthorne-Cooksey exercises, and a sensor-based measuring system were introduced. To verify the therapeutic effect, a clinical experiment with 48 patients and 36 normal subjects was conducted. Quantified balance indices were measured and analyzed by statistical tools and a Support Vector Machine (SVM) classifier. In terms of balance indices, patients who completed the training process are progressed and the difference between normal subjects and patients is obvious. Further analysis by SVM classifier show that the accuracy of recognizing the differences between patients and normal subject is feasible, and these results can be used to evaluate patients' severity and make rapid assessment. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  16. A Survey of Technologies Supporting Virtual Project Based Learning

    DEFF Research Database (Denmark)

    Dirckinck-Holmfeld, Lone

    2002-01-01

    This paper describes a survey of technologies and to what extent they support virtual project based learning. The paper argues that a survey of learning technologies should be related to concrete learning tasks and processes. Problem oriented project pedagogy (POPP) is discussed, and a framework...... for evaluation is proposed where negotiation of meaning, coordination and resource management are identified as the key concepts in virtual project based learning. Three e-learning systems are selected for the survey, Virtual-U, Lotus Learningspace and Lotus Quickplace, as each system offers different strategies...... for e-learning. The paper concludes that virtual project based learning may benefit from facilities of all these systems....

  17. A Novel Approach for Enhancing Lifelong Learning Systems by Using Hybrid Recommender System

    Science.gov (United States)

    Kardan, Ahmad A.; Speily, Omid R. B.; Modaberi, Somayyeh

    2011-01-01

    The majority of current web-based learning systems are closed learning environments where courses and learning materials are fixed, and the only dynamic aspect is the organization of the material that can be adapted to allow a relatively individualized learning environment. In this paper, we propose an evolving web-based learning system which can…

  18. From particle systems to learning processes. Comment on "Collective learning modeling based on the kinetic theory of active particles" by Diletta Burini, Silvana De Lillo, and Livio Gibelli

    Science.gov (United States)

    Lachowicz, Mirosław

    2016-03-01

    The very stimulating paper [6] discusses an approach to perception and learning in a large population of living agents. The approach is based on a generalization of kinetic theory methods in which the interactions between agents are described in terms of game theory. Such an approach was already discussed in Ref. [2-4] (see also references therein) in various contexts. The processes of perception and learning are based on the interactions between agents and therefore the general kinetic theory is a suitable tool for modeling them. However the main question that rises is how the perception and learning processes may be treated in the mathematical modeling. How may we precisely deliver suitable mathematical structures that are able to capture various aspects of perception and learning?

  19. Cloud-Based Mobile Learning

    Directory of Open Access Journals (Sweden)

    Alexandru BUTOI

    2013-01-01

    Full Text Available As the cloud technologies are largely studied and mobile technologies are evolving, new di-rections for development of mobile learning tools deployed on cloud are proposed.. M-Learning is treated as part of the ubiquitous learning paradigm and is a pervasive extension of E-Learning technologies. Development of such learning tools requires specific development strategies for an effective abstracting of pedagogical principles at the software design and implementation level. Current paper explores an interdisciplinary approach for designing and development of cloud based M-Learning tools by mapping a specific development strategy used for educational programs to software prototyping strategy. In order for such instruments to be user effective from the learning outcome point of view, the evaluation process must be rigorous as we propose a metric model for expressing the trainee’s overall learning experience with evaluated levels of interactivity, content presentation and graphical user interface usability.

  20. STUDENT SATISFACTION PROCESS IN VIRTUAL LEARNING SYSTEM:Considerations Based In Information And Service Quality from Brazil’s Experience

    Directory of Open Access Journals (Sweden)

    Fábio Nazareno MACHADO-DA-SILVA

    2014-07-01

    Full Text Available Distance learning has undergone great changes, especially since the advent of the Internet and communication and information technology. Questions have been asked following the growth of this mode of instructional activity. Researchers have investigated methods to assess the benefits of e-learning from a number of perspectives. This survey assesses the associations among the system quality, information quality, and service quality on student satisfaction and use of systems in virtual learning environments using the e-learning success model adapted by Holsapple and Lee-Post from the Delone and McLean (1992, 2003 model as a theoretical basis. The survey was carried out by means of an online program offered to 291 students from public and private institutions from several regions of Brazil. Confirmatory Factor Analysis and Structural Equation Modeling were used for data analysis in order to understand the student satisfaction process in virtual learning system. Findings show that variations in system quality, information quality, and service quality influence the use of the system, and the User Satisfaction construct had 89% of variance explained by Information Quality and Service Quality. Many of the benefits of distance learning programs are related to students’ satisfaction and the intensity with which they make use of the learning system. With awareness of the indicators that are antecedents of these variables, education executives can plan investments that meet the most significant demands and use the information to deal with one of the major problems in distance learning: the dropout rate. Future researches should study this subject longitudinally.

  1. Underspecification-Based Grammatical Feedback Generation Tailored to the Learner's Current Acquisition Level in an e-Learning System for German as Second Language

    Science.gov (United States)

    Harbusch, Karin; Cameran, Christel-Joy; Härtel, Johannes

    2014-01-01

    We present a new feedback strategy implemented in a natural language generation-based e-learning system for German as a second language (L2). Although the system recognizes a large proportion of the grammar errors in learner-produced written sentences, its automatically generated feedback only addresses errors against rules that are relevant at…

  2. Development of Remote Monitoring and a Control System Based on PLC and WebAccess for Learning Mechatronics

    Directory of Open Access Journals (Sweden)

    Wen-Jye Shyr

    2013-02-01

    Full Text Available This study develops a novel method for learning mechatronics using remote monitoring and control, based on a programmable logic controller (PLC and WebAccess. A mechatronics module, a Web-CAM and a PLC were integrated with WebAccess software to organize a remote laboratory. The proposed system enables users to access the Internet for remote monitoring and control of the mechatronics module via a web browser, thereby enhancing work flexibility by enabling personnel to control mechatronics equipment from a remote location. Mechatronics control and long-distance monitoring were realized by establishing communication between the PLC and WebAccess. Analytical results indicate that the proposed system is feasible. The suitability of this system is demonstrated in the department of industrial education and technology at National Changhua University of Education, Taiwan. Preliminary evaluation of the system was encouraging and has shown that it has achieved success in helping students understand concepts and master remote monitoring and control techniques.

  3. [Remote intelligent Brunnstrom assessment system for upper limb rehabilitation for post-stroke based on extreme learning machine].

    Science.gov (United States)

    Wang, Yue; Yu, Lei; Fu, Jianming; Fang, Qiang

    2014-04-01

    In order to realize an individualized and specialized rehabilitation assessment of remoteness and intelligence, we set up a remote intelligent assessment system of upper limb movement function of post-stroke patients during rehabilitation. By using the remote rehabilitation training sensors and client data sampling software, we collected and uploaded the gesture data from a patient's forearm and upper arm during rehabilitation training to database of the server. Then a remote intelligent assessment system, which had been developed based on the extreme learning machine (ELM) algorithm and Brunnstrom stage assessment standard, was used to evaluate the gesture data. To evaluate the reliability of the proposed method, a group of 23 stroke patients, whose upper limb movement functions were in different recovery stages, and 4 healthy people, whose upper limb movement functions were normal, were recruited to finish the same training task. The results showed that, compared to that of the experienced rehabilitation expert who used the Brunnstrom stage standard table, the accuracy of the proposed remote Brunnstrom intelligent assessment system can reach a higher level, as 92.1%. The practical effects of surgery have proved that the proposed system could realize the intelligent assessment of upper limb movement function of post-stroke patients remotely, and it could also make the rehabilitation of the post-stroke patients at home or in a community care center possible.

  4. e-Learning strategies in occupational legal medicine based on problem solving through "CASUS" system.

    Science.gov (United States)

    Martínez-Jarreta, B; Monsó, E; Gascón, S; Casalod, Y; Abecia, E; Kolb, S; Reichert, J; Radon, K

    2009-04-01

    The use of online teaching tools facilitate the incorporation of self-learning methods. With a view to encouraging convergence in teaching tools and methods in Occupational Legal Medicine, an initiative was set up within the classes of Legal and Forensic Medicine at Saragossa University, as part of the EU funded NetWoRM project, which has been led since 1999 by Ludwig-Maximilians-Universität in Munich (Germany). The interest of medical students in Occupational Legal Medicine has so far been low and in addition different aspects complicate the teaching of Occupational Legal Medicine at medical schools: One reason for the low interest is the limited availability of bedside teaching, one of the students' most favourite and effective way to learn. The reason for that is that most medical schools with occupational departments only have outpatient clinics. "Interesting" patients who be need for educational purposes are therefore only available for a limited part of the day. However, in order to recognize and prevent occupational disorders each medical student and physician needs profound clinical knowledge in Occupational Legal Medicine. This project has proven to be highly efficient in permitting the creation and validation of teaching tools which cover and improve the traditional training of the Occupational Legal Medicine programme imparted in the degree of Medicine.

  5. Building machine learning systems with Python

    CERN Document Server

    Richert, Willi

    2013-01-01

    This is a tutorial-driven and practical, but well-grounded book showcasing good Machine Learning practices. There will be an emphasis on using existing technologies instead of showing how to write your own implementations of algorithms. This book is a scenario-based, example-driven tutorial. By the end of the book you will have learnt critical aspects of Machine Learning Python projects and experienced the power of ML-based systems by actually working on them.This book primarily targets Python developers who want to learn about and build Machine Learning into their projects, or who want to pro

  6. Patterns for Designing Learning Management Systems

    NARCIS (Netherlands)

    Avgeriou, Paris; Retalis, Symeon; Papasalouros, Andreas

    2003-01-01

    Learning Management Systems are sophisticated web-based applications that are being engineered today in increasing numbers by numerous institutions and companies that want to get involved in e-learning either for providing services to third parties, or for educating and training their own people.

  7. Process Systems Engineering Education: Learning by Research

    Science.gov (United States)

    Abbas, A.; Alhammadi, H. Y.; Romagnoli, J. A.

    2009-01-01

    In this paper, we discuss our approach in teaching the final-year course Process Systems Engineering. Students are given ownership of the course by transferring to them the responsibility of learning. A project-based group environment stimulates learning while solving a real engineering problem. We discuss postgraduate student involvement and how…

  8. A Distributed Intelligent E-Learning System

    Science.gov (United States)

    Kristensen, Terje

    2016-01-01

    An E-learning system based on a multi-agent (MAS) architecture combined with the Dynamic Content Manager (DCM) model of E-learning, is presented. We discuss the benefits of using such a multi-agent architecture. Finally, the MAS architecture is compared with a pure service-oriented architecture (SOA). This MAS architecture may also be used within…

  9. Modeling learning technology systems as business systems

    NARCIS (Netherlands)

    Avgeriou, Paris; Retalis, Symeon; Papaspyrou, Nikolaos

    2003-01-01

    The design of Learning Technology Systems, and the Software Systems that support them, is largely conducted on an intuitive, ad hoc basis, thus resulting in inefficient systems that defectively support the learning process. There is now justifiable, increasing effort in formalizing the engineering

  10. Problem Based Learning Online

    DEFF Research Database (Denmark)

    Kolbæk, Ditte

    2018-01-01

    “How do two online learning designs affect student engagement in the PBL online modules?” The empirical data were collected and analyzed using a netnographic approach. The study finds that concepts such as self-directed learning and active involvement may be perceived very differently from the students...

  11. Adaptive polymeric system for Hebbian type learning

    OpenAIRE

    2011-01-01

    Abstract We present the experimental realization of an adaptive polymeric system displaying a ?learning behaviour?. The system consists on a statistically organized networks of memristive elements (memory-resitors) based on polyaniline. In a such network the path followed by the current increments its conductivity, a property which makes the system able to mimic Hebbian type learning and have application in hardware neural networks. After discussing the working principle of ...

  12. Lexmeter: validation of an automated system for the assessment of lexical competence of medical students as a base for an adaptive e-learning system

    Directory of Open Access Journals (Sweden)

    Fabrizio eConsorti

    2015-02-01

    Full Text Available Distance learning is used in medical education, even if some recent meta-analyses indicated that it is no more effective than traditional methods. To exploit the technological capabilities, adaptive distance learning systems aim to bridge the gap between the educational offer and the learner’s need. A decrease of lexical competence has been noted in many western countries, so lexical competence could be a possible target for adaptation. The Adaptive message learning project (Am-learning is aimed at designing and implementing an adaptive e-learning system, driven by lexical competence. The goal of the project is to modulate texts according to the estimated skill of learners, to allow a better comprehension. Lexmeter is the first of the four modules of the Am-learning system. It outlines an initial profile of the learner’s lexical competence and can also produce cloze tests, a test based on a completion task.A validation test of Lexmeter was run on 443 medical students of the 1st, 3rd and 6th year at the University Sapienza of Rome. Six cloze tests were automatically produced, with ten gaps each. The tests were different for each year and with varying levels of difficulty. A last cloze test was manually created as a control. The difference of the mean score between the easy tests and the tests with a medium level of difficulty was statistically significant for the 3rd year students but not for 1st and 6th year. The score of the automatically generated tests showed a slight but significant correlation with the control test. The reliability (Cronbach alpha of the different tests fluctuated under and above .60, as an acceptable level. In fact, classical item analysis revealed that the tests were on the average too simple.Lexical competence is a relevant outcome and its assessment allows an early detection of students at risk. Cloze tests can also be used to assess specific knowledge of technical jargon and to train reasoning skill.

  13. Intravenous catheter training system: computer-based education versus traditional learning methods.

    Science.gov (United States)

    Engum, Scott A; Jeffries, Pamela; Fisher, Lisa

    2003-07-01

    Virtual reality simulators allow trainees to practice techniques without consequences, reduce potential risk associated with training, minimize animal use, and help to develop standards and optimize procedures. Current intravenous (IV) catheter placement training methods utilize plastic arms, however, the lack of variability can diminish the educational stimulus for the student. This study compares the effectiveness of an interactive, multimedia, virtual reality computer IV catheter simulator with a traditional laboratory experience of teaching IV venipuncture skills to both nursing and medical students. A randomized, pretest-posttest experimental design was employed. A total of 163 participants, 70 baccalaureate nursing students and 93 third-year medical students beginning their fundamental skills training were recruited. The students ranged in age from 20 to 55 years (mean 25). Fifty-eight percent were female and 68% percent perceived themselves as having average computer skills (25% declaring excellence). The methods of IV catheter education compared included a traditional method of instruction involving a scripted self-study module which involved a 10-minute videotape, instructor demonstration, and hands-on-experience using plastic mannequin arms. The second method involved an interactive multimedia, commercially made computer catheter simulator program utilizing virtual reality (CathSim). The pretest scores were similar between the computer and the traditional laboratory group. There was a significant improvement in cognitive gains, student satisfaction, and documentation of the procedure with the traditional laboratory group compared with the computer catheter simulator group. Both groups were similar in their ability to demonstrate the skill correctly. CONCLUSIONS; This evaluation and assessment was an initial effort to assess new teaching methodologies related to intravenous catheter placement and their effects on student learning outcomes and behaviors

  14. Developing and Deploying an XML-based Learning Content Management System at the FernUniversität Hagen

    Directory of Open Access Journals (Sweden)

    Gerd Steinkamp

    2005-02-01

    Full Text Available This paper is a report about the FuXML project carried out at the FernUniversität Hagen. FuXML is a Learning Content Management System (LCMS aimed at providing a practical and efficient solution for the issues attributed to authoring, maintenance, production and distribution of online and offline distance learning material. The paper presents the environment for which the system was conceived and describes the technical realisation. We discuss the reasons for specific implementation decisions and also address the integration of the system within the organisational and technical infrastructure of the university.

  15. Towards synergy between learning management systems and educational server applications

    OpenAIRE

    Hartog, R.J.M.; Schaaf, van der, H.; Kassahun, A.

    2008-01-01

    Most well-known Learning Management Systems (LMS) are based on a paradigm of learning objects to be uploaded into the system. Most formulations of this paradigm implicitly assume that the learning objects are self contained learning objects such as FLASH objects or JAVA applets or presentational learning objects such as slide presentations. These are typically client side objects. However, a demand for learning support that activates the student can often be satisfied better with a server app...

  16. Dimensions of problem based learning

    DEFF Research Database (Denmark)

    Nielsen, Jørgen Lerche; Andreasen, Lars Birch

    2013-01-01

    The article contributes to the literature on problem based learning and problem-oriented project work, building on and reflecting the experiences of the authors through decades of work with problem-oriented project pedagogy. The article explores different dimensions of problem based learning such...... and Learning (MIL). We discuss changes in the roles of the teachers as supervisors within this learning environment, and we explore the involvement of students as active participants and co-designers of how course and project activities unfold....

  17. Video Feedforward for Rapid Learning of a Picture-Based Communication System

    Science.gov (United States)

    Smith, Jemma; Hand, Linda; Dowrick, Peter W.

    2014-01-01

    This study examined the efficacy of video self modeling (VSM) using feedforward, to teach various goals of a picture exchange communication system (PECS). The participants were two boys with autism and one man with Down syndrome. All three participants were non-verbal with no current functional system of communication; the two children had long…

  18. Learning Management Systems and E-Learning within Cyprus Universities

    Directory of Open Access Journals (Sweden)

    Amirkhanpour, Monaliz

    2011-01-01

    Full Text Available This paper presents an extensive research study and results on the use of existing open-source Learning Management Systems, or LMS within the public and private universities of Cyprus. The most significant objective of this research is the identification of the different types of E-Learning, i.e. Computer-Based Training (CBT, Technology-Based Learning (TBL, and Web-Based Training (WBT within Cyprus universities. The paper identifies the benefits and limitations of the main learning approaches used in higher educational institutions, i.e. synchronous and asynchronous learning, investigates the open-source LMS used in the Cypriot universities and compares their features with regards to students’ preferences for a collaborative E-Learning environment. The required data for this research study were collected from undergraduate and graduate students, alumni, faculty members, and IT professionals who currently work and/or study at the public and private universities of Cyprus. The most noteworthy recommendation of this study is the clear indication that most of the undergraduate students that extensively use the specific E-Learning platform of their university do not have a clear picture of the differences between an LMS and a VLE. This gap has to be gradually diminished in order to make optimum use of the different features offered by the specific E-Learning platform.

  19. Detecting Dutch political tweets : A classifier based on voting system using supervised learning

    NARCIS (Netherlands)

    de Mello Araújo, Eric Fernandes; Ebbelaar, Dave

    The task of classifying political tweets has been shown to be very difficult, with controversial results in many works and with non-replicable methods. Most of the works with this goal use rule-based methods to identify political tweets. We propose here two methods, being one rule-based approach,

  20. Effects of asymmetry and learning on phonotaxis in a robot based on the lizard auditory system

    DEFF Research Database (Denmark)

    Zhang, L.; Hallam, J.; Christensen-Dalsgaard, J.

    2012-01-01

    Lizards have strong directional hearing across a broad band of frequencies. The directionality can be attributed to the acoustical properties of the ear, especially the strong acoustical coupling of the two eardrums. The peripheral auditory system of the lizard has previously been modeled...... and magnitude of their intrinsic bias. To attain effective directional hearing, the bias in the peripheral system should be compensated. In this article, with the peripheral models, we design a decision model and a behavior model, a virtual robot, to simulate the auditory system of the lizard in software...

  1. Discovering the Power of Individual-Based Modelling in Teaching and Learning: The Study of a Predator-Prey System

    Science.gov (United States)

    Ginovart, Marta

    2014-01-01

    The general aim is to promote the use of individual-based models (biological agent-based models) in teaching and learning contexts in life sciences and to make their progressive incorporation into academic curricula easier, complementing other existing modelling strategies more frequently used in the classroom. Modelling activities for the study…

  2. A Pathological Brain Detection System based on Extreme Learning Machine Optimized by Bat Algorithm.

    Science.gov (United States)

    Lu, Siyuan; Qiu, Xin; Shi, Jianping; Li, Na; Lu, Zhi-Hai; Chen, Peng; Yang, Meng-Meng; Liu, Fang-Yuan; Jia, Wen-Juan; Zhang, Yudong

    2017-01-01

    It is beneficial to classify brain images as healthy or pathological automatically, because 3D brain images can generate so much information which is time consuming and tedious for manual analysis. Among various 3D brain imaging techniques, magnetic resonance (MR) imaging is the most suitable for brain, and it is now widely applied in hospitals, because it is helpful in the four ways of diagnosis, prognosis, pre-surgical, and postsurgical procedures. There are automatic detection methods; however they suffer from low accuracy. Therefore, we proposed a novel approach which employed 2D discrete wavelet transform (DWT), and calculated the entropies of the subbands as features. Then, a bat algorithm optimized extreme learning machine (BA-ELM) was trained to identify pathological brains from healthy controls. A 10x10-fold cross validation was performed to evaluate the out-of-sample performance. The method achieved a sensitivity of 99.04%, a specificity of 93.89%, and an overall accuracy of 98.33% over 132 MR brain images. The experimental results suggest that the proposed approach is accurate and robust in pathological brain detection. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  3. Can Learning Motivation Predict Learning Achievement? A Case Study of a Mobile Game-Based English Learning Approach

    Science.gov (United States)

    Tsai, Chia-Hui; Cheng, Ching-Hsue; Yeh, Duen-Yian; Lin, Shih-Yun

    2017-01-01

    This study applied a quasi-experimental design to investigate the influence and predictive power of learner motivation for achievement, employing a mobile game-based English learning approach. A system called the Happy English Learning System, integrating learning material into a game-based context, was constructed and installed on mobile devices…

  4. A Sun Path Observation System Based on Augment Reality and Mobile Learning

    OpenAIRE

    Tarng, Wernhuar; Ou, Kuo-Liang; Lu, Yun-Chen; Shih, Yi-Syuan; Liou, Hsin-Hun

    2018-01-01

    This study uses the augmented reality technology and sensor functions of GPS, electronic compass, and three-axis accelerometer on mobile devices to develop a Sun path observation system for applications in astronomy education. The orientation and elevation of the Sun can be calculated by the system according to the user’s location and local time to simulate the Sun path. When holding the mobile device toward the sky, the screen will show the virtual Sun at the same position as that of the rea...

  5. Expanding the Space of Plausible Solutions in a Medical Tutoring System for Problem-Based Learning

    Science.gov (United States)

    Kazi, Hameedullah; Haddawy, Peter; Suebnukarn, Siriwan

    2009-01-01

    In well-defined domains such as Physics, Mathematics, and Chemistry, solutions to a posed problem can objectively be classified as correct or incorrect. In ill-defined domains such as medicine, the classification of solutions to a patient problem as correct or incorrect is much more complex. Typical tutoring systems accept only a small set of…

  6. Greek Students Research the Effects of Fire on the Soil System through Project-Based Learning

    Science.gov (United States)

    Kioupi, Vasiliki; Arianoutsou, Margarita

    2016-01-01

    This study is focused on the development, implementation and evaluation of an environmental education programme for secondary education students. The programme was entitled "?he effects of fire on the soil system" and it was implemented during the school period of 2008. Twenty-four (24) students (aged from 15 to 20) coming from Lidoriki…

  7. Learning Diagnostic Diagrams in Transport-Based Data-Collection Systems

    DEFF Research Database (Denmark)

    Tran, Vu The; Eklund, Peter; Cook, Chris

    2014-01-01

    Insights about service improvement in a transit network can be gained by studying transit service reliability. In this paper, a general procedure for constructing a transit service reliability diagnostic (Tsrd) diagram based on a Bayesian network is proposed to automatically build a behavioural...

  8. An XML Based Knowledge Management System for e-Collaboration and e-Learning

    Directory of Open Access Journals (Sweden)

    Varun Gopalakrishna

    2004-02-01

    Full Text Available This paper presents the development, key features, and the implementation principles of a sustainable and scaleable knowledge management system (KMS prototype for creating, capturing, organizing, and managing digital information in the form of Extensible Markup Language (XML documents and other popular file formats. It is aimed to provide a platform for global, instant, and secure access to and dissemination of information within a knowledge-intensive organization or a cluster of organizations through Internet or intranet. A three-tier system architecture was chosen for the KMS to provide performance and scalability while enabling future development that supports global, secure, real-time, and multi-media communication of information and knowledge among team members separated by great distance. An XML Content Server has been employed in this work to store, index, and retrieve large volumes of XML and binary content.

  9. A novel computer-aided diagnosis system for breast MRI based on feature selection and ensemble learning.

    Science.gov (United States)

    Lu, Wei; Li, Zhe; Chu, Jinghui

    2017-04-01

    Breast cancer is a common cancer among women. With the development of modern medical science and information technology, medical imaging techniques have an increasingly important role in the early detection and diagnosis of breast cancer. In this paper, we propose an automated computer-aided diagnosis (CADx) framework for magnetic resonance imaging (MRI). The scheme consists of an ensemble of several machine learning-based techniques, including ensemble under-sampling (EUS) for imbalanced data processing, the Relief algorithm for feature selection, the subspace method for providing data diversity, and Adaboost for improving the performance of base classifiers. We extracted morphological, various texture, and Gabor features. To clarify the feature subsets' physical meaning, subspaces are built by combining morphological features with each kind of texture or Gabor feature. We tested our proposal using a manually segmented Region of Interest (ROI) data set, which contains 438 images of malignant tumors and 1898 images of normal tissues or benign tumors. Our proposal achieves an area under the ROC curve (AUC) value of 0.9617, which outperforms most other state-of-the-art breast MRI CADx systems. Compared with other methods, our proposal significantly reduces the false-positive classification rate. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. A New Design Approach to Game-Based learning

    DEFF Research Database (Denmark)

    Larsen, Lasse Juel

    2012-01-01

    to ground the student’s reason to learn. This paper proposes a different approach: using visualisation in immersive 3D worlds as both documentation of learning progress and as a reward system which motivates further learning. The overall design idea is to build a game based learning system from three......This paper puts forward a new design perspective for gamebased learning. The general idea is to abandon the long sought-after dream of designing a closed learning system, where students in both primary and secondary school could learn – without the interference of teachers – whatever subject......-based learning system, but will also confront aspects of modern learning theory, especially the notion of reference between the content of an assignment and the reality with which it should or could be connected (situated learning). The second idea promotes a way of tackling the common experience of the average...

  11. Reinforcement Learning Based Artificial Immune Classifier

    Directory of Open Access Journals (Sweden)

    Mehmet Karakose

    2013-01-01

    Full Text Available One of the widely used methods for classification that is a decision-making process is artificial immune systems. Artificial immune systems based on natural immunity system can be successfully applied for classification, optimization, recognition, and learning in real-world problems. In this study, a reinforcement learning based artificial immune classifier is proposed as a new approach. This approach uses reinforcement learning to find better antibody with immune operators. The proposed new approach has many contributions according to other methods in the literature such as effectiveness, less memory cell, high accuracy, speed, and data adaptability. The performance of the proposed approach is demonstrated by simulation and experimental results using real data in Matlab and FPGA. Some benchmark data and remote image data are used for experimental results. The comparative results with supervised/unsupervised based artificial immune system, negative selection classifier, and resource limited artificial immune classifier are given to demonstrate the effectiveness of the proposed new method.

  12. Development of a Lunar-Phase Observation System Based on Augmented Reality and Mobile Learning Technologies

    OpenAIRE

    Tarng, Wernhuar; Lin, Yu-Sheng; Lin, Chiu-Pin; Ou, Kuo-Liang

    2016-01-01

    Observing the lunar phase requires long-term involvement, and it is often obstructed by bad weather or tall buildings. In this study, a lunar-phase observation system is developed using the augmented reality (AR) technology and the sensor functions of GPS, electronic compass, and 3-axis accelerometer on mobile devices to help students observe and record lunar phases easily. By holding the mobile device towards the moon in the sky, the screen will show the virtual moon at the position of the r...

  13. A sequence-based dynamic ensemble learning system for protein ligand-binding site prediction

    KAUST Repository

    Chen, Peng

    2015-12-03

    Background: Proteins have the fundamental ability to selectively bind to other molecules and perform specific functions through such interactions, such as protein-ligand binding. Accurate prediction of protein residues that physically bind to ligands is important for drug design and protein docking studies. Most of the successful protein-ligand binding predictions were based on known structures. However, structural information is not largely available in practice due to the huge gap between the number of known protein sequences and that of experimentally solved structures

  14. A sequence-based dynamic ensemble learning system for protein ligand-binding site prediction

    KAUST Repository

    Chen, Peng; Hu, ShanShan; Zhang, Jun; Gao, Xin; Li, Jinyan; Xia, Junfeng; Wang, Bing

    2015-01-01

    Background: Proteins have the fundamental ability to selectively bind to other molecules and perform specific functions through such interactions, such as protein-ligand binding. Accurate prediction of protein residues that physically bind to ligands is important for drug design and protein docking studies. Most of the successful protein-ligand binding predictions were based on known structures. However, structural information is not largely available in practice due to the huge gap between the number of known protein sequences and that of experimentally solved structures

  15. Learning Companion Systems, Social Learning Systems, and the Global Social Learning Club.

    Science.gov (United States)

    Chan, Tak-Wai

    1996-01-01

    Describes the development of learning companion systems and their contributions to the class of social learning systems that integrate artificial intelligence agents and use machine learning to tutor and interact with students. Outlines initial social learning projects, their programming languages, and weakness. Future improvements will include…

  16. Problem-Based Learning in Formal and Informal Learning Environments

    Science.gov (United States)

    Shimic, Goran; Jevremovic, Aleksandar

    2012-01-01

    Problem-based learning (PBL) is a student-centered instructional strategy in which students solve problems and reflect on their experiences. Different domains need different approaches in the design of PBL systems. Therefore, we present one case study in this article: A Java Programming PBL. The application is developed as an additional module for…

  17. Learning second language vocabulary: neural dissociation of situation-based learning and text-based learning.

    Science.gov (United States)

    Jeong, Hyeonjeong; Sugiura, Motoaki; Sassa, Yuko; Wakusawa, Keisuke; Horie, Kaoru; Sato, Shigeru; Kawashima, Ryuta

    2010-04-01

    Second language (L2) acquisition necessitates learning and retrieving new words in different modes. In this study, we attempted to investigate the cortical representation of an L2 vocabulary acquired in different learning modes and in cross-modal transfer between learning and retrieval. Healthy participants learned new L2 words either by written translations (text-based learning) or in real-life situations (situation-based learning). Brain activity was then measured during subsequent retrieval of these words. The right supramarginal gyrus and left middle frontal gyrus were involved in situation-based learning and text-based learning, respectively, whereas the left inferior frontal gyrus was activated when learners used L2 knowledge in a mode different from the learning mode. Our findings indicate that the brain regions that mediate L2 memory differ according to how L2 words are learned and used. Copyright 2009 Elsevier Inc. All rights reserved.

  18. Extending E-Book with Contextual Knowledge Recommender for Reading Support on a Web-Based Learning System

    Science.gov (United States)

    Chen, Gwo-Dong; Wei, Fu-Hsiang; Wang, Chin-Yeh; Lee, Jih-Hsien

    2007-01-01

    Reading content of the Web is increasingly popular. When students read the same material, each student has a unique comprehension of the text and requires individual support from appropriate references. Most references in typical web learning systems are unorganized. Students are often required to disrupt their reading to locate references. This…

  19. Combining Correlation-Based and Reward-Based Learning in Neural Control for Policy Improvement

    DEFF Research Database (Denmark)

    Manoonpong, Poramate; Kolodziejski, Christoph; Wörgötter, Florentin

    2013-01-01

    Classical conditioning (conventionally modeled as correlation-based learning) and operant conditioning (conventionally modeled as reinforcement learning or reward-based learning) have been found in biological systems. Evidence shows that these two mechanisms strongly involve learning about...... associations. Based on these biological findings, we propose a new learning model to achieve successful control policies for artificial systems. This model combines correlation-based learning using input correlation learning (ICO learning) and reward-based learning using continuous actor–critic reinforcement...... learning (RL), thereby working as a dual learner system. The model performance is evaluated by simulations of a cart-pole system as a dynamic motion control problem and a mobile robot system as a goal-directed behavior control problem. Results show that the model can strongly improve pole balancing control...

  20. Online Reflective Writing Mechanisms and Its Effects on Self-Regulated Learning: A Case of Web-Based Portfolio Assessment System

    Science.gov (United States)

    Liang, Chaoyun; Chang, Chi-Cheng; Shu, Kuen-Ming; Tseng, Ju-Shih; Lin, Chun-Yu

    2016-01-01

    The purpose of the present study was to design reflective writing mechanisms in a web-based portfolio assessment system and evaluate its effects on self-regulated learning. Participants were two classes of juniors majoring in data processing and taking a course called "Website design" at a vocational high school in Taiwan. One class was…

  1. Project-Based Learning with an Online Peer Assessment System in a Photonics Instruction for Enhancing LED Design Skills

    Science.gov (United States)

    Chang, Shu-Hsuan; Wu, Tsung-Chih; Kuo, Yen-Kuang; You, Li-Chih

    2012-01-01

    This study proposed a novel instructional approach, a two-stage LED simulation of Project-based learning (PBL) course with online peer assessment (OPA), and explored how to apply OPA to the different structured problems in a PBL course to enhance students' professional skills in LED design as well as meta-cognitive thinking. The participants of…

  2. Mastication Evaluation With Unsupervised Learning: Using an Inertial Sensor-Based System

    Science.gov (United States)

    Lucena, Caroline Vieira; Lacerda, Marcelo; Caldas, Rafael; De Lima Neto, Fernando Buarque

    2018-01-01

    There is a direct relationship between the prevalence of musculoskeletal disorders of the temporomandibular joint and orofacial disorders. A well-elaborated analysis of the jaw movements provides relevant information for healthcare professionals to conclude their diagnosis. Different approaches have been explored to track jaw movements such that the mastication analysis is getting less subjective; however, all methods are still highly subjective, and the quality of the assessments depends much on the experience of the health professional. In this paper, an accurate and non-invasive method based on a commercial low-cost inertial sensor (MPU6050) to measure jaw movements is proposed. The jaw-movement feature values are compared to the obtained with clinical analysis, showing no statistically significant difference between both methods. Moreover, We propose to use unsupervised paradigm approaches to cluster mastication patterns of healthy subjects and simulated patients with facial trauma. Two techniques were used in this paper to instantiate the method: Kohonen’s Self-Organizing Maps and K-Means Clustering. Both algorithms have excellent performances to process jaw-movements data, showing encouraging results and potential to bring a full assessment of the masticatory function. The proposed method can be applied in real-time providing relevant dynamic information for health-care professionals. PMID:29651365

  3. Mastication Evaluation With Unsupervised Learning: Using an Inertial Sensor-Based System.

    Science.gov (United States)

    Lucena, Caroline Vieira; Lacerda, Marcelo; Caldas, Rafael; De Lima Neto, Fernando Buarque; Rativa, Diego

    2018-01-01

    There is a direct relationship between the prevalence of musculoskeletal disorders of the temporomandibular joint and orofacial disorders. A well-elaborated analysis of the jaw movements provides relevant information for healthcare professionals to conclude their diagnosis. Different approaches have been explored to track jaw movements such that the mastication analysis is getting less subjective; however, all methods are still highly subjective, and the quality of the assessments depends much on the experience of the health professional. In this paper, an accurate and non-invasive method based on a commercial low-cost inertial sensor (MPU6050) to measure jaw movements is proposed. The jaw-movement feature values are compared to the obtained with clinical analysis, showing no statistically significant difference between both methods. Moreover, We propose to use unsupervised paradigm approaches to cluster mastication patterns of healthy subjects and simulated patients with facial trauma. Two techniques were used in this paper to instantiate the method: Kohonen's Self-Organizing Maps and K-Means Clustering. Both algorithms have excellent performances to process jaw-movements data, showing encouraging results and potential to bring a full assessment of the masticatory function. The proposed method can be applied in real-time providing relevant dynamic information for health-care professionals.

  4. The immune system, adaptation, and machine learning

    Science.gov (United States)

    Farmer, J. Doyne; Packard, Norman H.; Perelson, Alan S.

    1986-10-01

    The immune system is capable of learning, memory, and pattern recognition. By employing genetic operators on a time scale fast enough to observe experimentally, the immune system is able to recognize novel shapes without preprogramming. Here we describe a dynamical model for the immune system that is based on the network hypothesis of Jerne, and is simple enough to simulate on a computer. This model has a strong similarity to an approach to learning and artificial intelligence introduced by Holland, called the classifier system. We demonstrate that simple versions of the classifier system can be cast as a nonlinear dynamical system, and explore the analogy between the immune and classifier systems in detail. Through this comparison we hope to gain insight into the way they perform specific tasks, and to suggest new approaches that might be of value in learning systems.

  5. Indirect learning control for nonlinear dynamical systems

    Science.gov (United States)

    Ryu, Yeong Soon; Longman, Richard W.

    1993-01-01

    In a previous paper, learning control algorithms were developed based on adaptive control ideas for linear time variant systems. The learning control methods were shown to have certain advantages over their adaptive control counterparts, such as the ability to produce zero tracking error in time varying systems, and the ability to eliminate repetitive disturbances. In recent years, certain adaptive control algorithms have been developed for multi-body dynamic systems such as robots, with global guaranteed convergence to zero tracking error for the nonlinear system euations. In this paper we study the relationship between such adaptive control methods designed for this specific class of nonlinear systems, and the learning control problem for such systems, seeking to converge to zero tracking error in following a specific command repeatedly, starting from the same initial conditions each time. The extension of these methods from the adaptive control problem to the learning control problem is seen to be trivial. The advantages and disadvantages of using learning control based on such adaptive control concepts for nonlinear systems, and the use of other currently available learning control algorithms are discussed.

  6. Unmanned Aerial System (UAS)-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine

    Science.gov (United States)

    Maimaitijiang, Maitiniyazi; Ghulam, Abduwasit; Sidike, Paheding; Hartling, Sean; Maimaitiyiming, Matthew; Peterson, Kyle; Shavers, Ethan; Fishman, Jack; Peterson, Jim; Kadam, Suhas; Burken, Joel; Fritschi, Felix

    2017-12-01

    Estimating crop biophysical and biochemical parameters with high accuracy at low-cost is imperative for high-throughput phenotyping in precision agriculture. Although fusion of data from multiple sensors is a common application in remote sensing, less is known on the contribution of low-cost RGB, multispectral and thermal sensors to rapid crop phenotyping. This is due to the fact that (1) simultaneous collection of multi-sensor data using satellites are rare and (2) multi-sensor data collected during a single flight have not been accessible until recent developments in Unmanned Aerial Systems (UASs) and UAS-friendly sensors that allow efficient information fusion. The objective of this study was to evaluate the power of high spatial resolution RGB, multispectral and thermal data fusion to estimate soybean (Glycine max) biochemical parameters including chlorophyll content and nitrogen concentration, and biophysical parameters including Leaf Area Index (LAI), above ground fresh and dry biomass. Multiple low-cost sensors integrated on UASs were used to collect RGB, multispectral, and thermal images throughout the growing season at a site established near Columbia, Missouri, USA. From these images, vegetation indices were extracted, a Crop Surface Model (CSM) was advanced, and a model to extract the vegetation fraction was developed. Then, spectral indices/features were combined to model and predict crop biophysical and biochemical parameters using Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), and Extreme Learning Machine based Regression (ELR) techniques. Results showed that: (1) For biochemical variable estimation, multispectral and thermal data fusion provided the best estimate for nitrogen concentration and chlorophyll (Chl) a content (RMSE of 9.9% and 17.1%, respectively) and RGB color information based indices and multispectral data fusion exhibited the largest RMSE 22.6%; the highest accuracy for Chl a + b content estimation was

  7. Model-based machine learning.

    Science.gov (United States)

    Bishop, Christopher M

    2013-02-13

    Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications.

  8. Error modeling for surrogates of dynamical systems using machine learning: Machine-learning-based error model for surrogates of dynamical systems

    International Nuclear Information System (INIS)

    Trehan, Sumeet; Carlberg, Kevin T.; Durlofsky, Louis J.

    2017-01-01

    A machine learning–based framework for modeling the error introduced by surrogate models of parameterized dynamical systems is proposed. The framework entails the use of high-dimensional regression techniques (eg, random forests, and LASSO) to map a large set of inexpensively computed “error indicators” (ie, features) produced by the surrogate model at a given time instance to a prediction of the surrogate-model error in a quantity of interest (QoI). This eliminates the need for the user to hand-select a small number of informative features. The methodology requires a training set of parameter instances at which the time-dependent surrogate-model error is computed by simulating both the high-fidelity and surrogate models. Using these training data, the method first determines regression-model locality (via classification or clustering) and subsequently constructs a “local” regression model to predict the time-instantaneous error within each identified region of feature space. We consider 2 uses for the resulting error model: (1) as a correction to the surrogate-model QoI prediction at each time instance and (2) as a way to statistically model arbitrary functions of the time-dependent surrogate-model error (eg, time-integrated errors). We then apply the proposed framework to model errors in reduced-order models of nonlinear oil-water subsurface flow simulations, with time-varying well-control (bottom-hole pressure) parameters. The reduced-order models used in this work entail application of trajectory piecewise linearization in conjunction with proper orthogonal decomposition. Moreover, when the first use of the method is considered, numerical experiments demonstrate consistent improvement in accuracy in the time-instantaneous QoI prediction relative to the original surrogate model, across a large number of test cases. When the second use is considered, results show that the proposed method provides accurate statistical predictions of the time- and well

  9. CLASSIFICATION OF LEARNING MANAGEMENT SYSTEMS

    Directory of Open Access Journals (Sweden)

    Yu. B. Popova

    2016-01-01

    Full Text Available Using of information technologies and, in particular, learning management systems, increases opportunities of teachers and students in reaching their goals in education. Such systems provide learning content, help organize and monitor training, collect progress statistics and take into account the individual characteristics of each user. Currently, there is a huge inventory of both paid and free systems are physically located both on college servers and in the cloud, offering different features sets of different licensing scheme and the cost. This creates the problem of choosing the best system. This problem is partly due to the lack of comprehensive classification of such systems. Analysis of more than 30 of the most common now automated learning management systems has shown that a classification of such systems should be carried out according to certain criteria, under which the same type of system can be considered. As classification features offered by the author are: cost, functionality, modularity, keeping the customer’s requirements, the integration of content, the physical location of a system, adaptability training. Considering the learning management system within these classifications and taking into account the current trends of their development, it is possible to identify the main requirements to them: functionality, reliability, ease of use, low cost, support for SCORM standard or Tin Can API, modularity and adaptability. According to the requirements at the Software Department of FITR BNTU under the guidance of the author since 2009 take place the development, the use and continuous improvement of their own learning management system.

  10. A New Design Approach to game or play based learning

    DEFF Research Database (Denmark)

    Larsen, Lasse Juel

    to ground the students sense of meaning. This paper proposes another approach: using visualization in immersive 3D-worlds as documentation of learning progress while at the same time constituting a reward system which motivate further learning. The overall design idea is to build a game based learning......Abstract: The present paper proposes a new design perspective for game based learning. The general idea is to abandon the long and sought after dream of designing a closed learning system, where students from elementary school to high school without teachers’ interference could learn whatever...... game based learning system, but also confront aspects of modern learning theory especially the notion of reference between content of an assignment and the reality with which it should or could be connected (situated learning). The second idea promotes a way to tackle the common experience...

  11. An Architecture for Online Laboratory E-Learning System

    Science.gov (United States)

    Duan, Bing; Hosseini, Habib Mir M.; Ling, Keck Voon; Gay, Robert Kheng Leng

    2006-01-01

    Internet-based learning systems, or e-learning, are widely available in institutes, universities, and industrial companies, hosting regular or continuous education programs. The dream of teaching and learning from anywhere and at anytime becomes a reality due to the construction of e-learning infrastructure. Traditional teaching materials and…

  12. Intelligent fractions learning system: implementation

    CSIR Research Space (South Africa)

    Smith, Andrew C

    2011-05-01

    Full Text Available Conference Proceedings Paul Cunningham and Miriam Cunningham (Eds) IIMC International Information Management Corporation, 2011 ISBN: 978-1-905824-24-3 An Intelligent Fractions Learning System: Implementation Andrew Cyrus SMITH1, Teemu H. LAINE2 1CSIR... to fractions. Our aim with the current research project is to extend the existing UFractions learning system to incorporate automatic data capturing. ?Intelligent UFractions? allows a teacher to remotely monitor the children?s progress during...

  13. The organization of an autonomous learning system

    Science.gov (United States)

    Kanerva, Pentti

    1988-01-01

    The organization of systems that learn from experience is examined, human beings and animals being prime examples of such systems. How is their information processing organized. They build an internal model of the world and base their actions on the model. The model is dynamic and predictive, and it includes the systems' own actions and their effects. In modeling such systems, a large pattern of features represents a moment of the system's experience. Some of the features are provided by the system's senses, some control the system's motors, and the rest have no immediate external significance. A sequence of such patterns then represents the system's experience over time. By storing such sequences appropriately in memory, the system builds a world model based on experience. In addition to the essential function of memory, fundamental roles are played by a sensory system that makes raw information about the world suitable for memory storage and by a motor system that affects the world. The relation of sensory and motor systems to the memory is discussed, together with how favorable actions can be learned and unfavorable actions can be avoided. Results in classical learning theory are explained in terms of the model, more advanced forms of learning are discussed, and the relevance of the model to the frame problem of robotics is examined.

  14. Using a Touch-Based, Computer-Assisted Learning System to Promote Literacy and Math Skills for Low-Income Preschoolers

    OpenAIRE

    Mark H McManis; Lilla D McManis

    2016-01-01

    The use of touch-based technologies by young children to improve academic skills has seen growth outpacing empirical evidence of its effectiveness. Due to the educational challenges low-income children face, the stakes for providing instructional technology with demonstrated efficacy are high. The current work presents an empirical study of the use of a touch-based, computer-assisted learning system by low-income preschoolers. A description of the system’s design is provided with attention to...

  15. Using a Touch-Based, Computer-Assisted Learning System to Promote Literacy and Math Skills for Low-Income Preschoolers

    Directory of Open Access Journals (Sweden)

    Mark H McManis

    2016-08-01

    Full Text Available The use of touch-based technologies by young children to improve academic skills has seen growth outpacing empirical evidence of its effectiveness. Due to the educational challenges low-income children face, the stakes for providing instructional technology with demonstrated efficacy are high. The current work presents an empirical study of the use of a touch-based, computer-assisted learning system by low-income preschoolers. A description of the system’s design is provided with attention to young children’s interaction with touch devices, learner engagement, and pedagogically-based delivery of academic content. Children in 18 low-income child-care preschool classrooms were assessed on literacy and math skills in the fall and again in the spring. Target children used the iStartSmart learning system throughout the academic year, while control children did not have access to the system. Compared to controls, children using the learning system made significant gains on external standardized measures of literacy and math. Children who spent more time using the system and those who reached the upper levels of skill understanding showed the strongest improvement in test scores. The findings contribute to the currently sparse literature by illuminating that for at-risk early learners, touch-based, computer-assisted instructional technology shows promise as an educational tool.

  16. Factors that Influence Acceptance of Web-Based E-Learning Systems for the In-Service Education of Junior High School Teachers in Taiwan

    Science.gov (United States)

    Chen, Hong-Ren; Tseng, Hsiao-Fen

    2012-01-01

    Web-based e-learning is not restricted by time or place and can provide teachers with a learning environment that is flexible and convenient, enabling them to efficiently learn, quickly develop their professional expertise, and advance professionally. Many research reports on web-based e-learning have neglected the role of the teacher's…

  17. An Analytics-Based Approach to Managing Cognitive Load by Using Log Data of Learning Management Systems and Footprints of Social Media

    Science.gov (United States)

    Yen, Cheng-Huang; Chen, I-Chuan; Lai, Su-Chun; Chuang, Yea-Ru

    2015-01-01

    Traces of learning behaviors generally provide insights into learners and the learning processes that they employ. In this article, a learning-analytics-based approach is proposed for managing cognitive load by adjusting the instructional strategies used in online courses. The technology-based learning environment examined in this study involved a…

  18. Development of a Relational Database for Learning Management Systems

    Science.gov (United States)

    Deperlioglu, Omer; Sarpkaya, Yilmaz; Ergun, Ertugrul

    2011-01-01

    In today's world, Web-Based Distance Education Systems have a great importance. Web-based Distance Education Systems are usually known as Learning Management Systems (LMS). In this article, a database design, which was developed to create an educational institution as a Learning Management System, is described. In this sense, developed Learning…

  19. Towards an intelligent learning management system under blended learning trends, profiles and modeling perspectives

    CERN Document Server

    Dias, Sofia B; Hadjileontiadis, Leontios J

    2013-01-01

    This book offers useful information that evokes initiatives towards rethinking of the value, efficiency, inclusiveness, effectiveness and personalization of the intelligent learning management systems-based blended-learning environment.

  20. A functional-dependencies-based Bayesian networks learning method and its application in a mobile commerce system.

    Science.gov (United States)

    Liao, Stephen Shaoyi; Wang, Huai Qing; Li, Qiu Dan; Liu, Wei Yi

    2006-06-01

    This paper presents a new method for learning Bayesian networks from functional dependencies (FD) and third normal form (3NF) tables in relational databases. The method sets up a linkage between the theory of relational databases and probabilistic reasoning models, which is interesting and useful especially when data are incomplete and inaccurate. The effectiveness and practicability of the proposed method is demonstrated by its implementation in a mobile commerce system.

  1. A Hybrid Model through the Fusion of Type-2 Fuzzy Logic Systems and Sensitivity-Based Linear Learning Method for Modeling PVT Properties of Crude Oil Systems

    Directory of Open Access Journals (Sweden)

    Ali Selamat

    2012-01-01

    Full Text Available Sensitivity-based linear learning method (SBLLM has recently been used as a predictive tool due to its unique characteristics and performance, particularly its high stability and consistency during predictions. However, the generalisation capability of SBLLM is sometimes limited depending on the nature of the dataset, particularly on whether uncertainty is present in the dataset or not. Since it made use of sensitivity analysis in relation to the data sets used, it is surely very prone to being affected by the nature of the dataset. In order to reduce the effects of uncertainties in SBLLM prediction and improve its generalisation ability, this paper proposes a hybrid system through the unique combination of type-2 fuzzy logic systems (type-2 FLSs and SBLLM; thereafter the hybrid system was used to model PVT properties of crude oil systems. Type-2 FLS has been choosen in order to better handle uncertainties existing in datasets beyond the capability of type-1 fuzzy logic systems. In the proposed hybrid, the type-2 FLS is used to handle uncertainties in reservoir data so that the cleaned data from type-2 FLS is then passed to the SBLLM for training and then final prediction using testing dataset follows. Comparative studies have been carried out to compare the performance of the newly proposed T2-SBLLM hybrid system with each of the constituent type-2 FLS and SBLLM. Empirical results from simulation show that the proposed T2-SBLLM hybrid system has greatly improved upon the performance of SBLLM, while also maintaining a better performance above that of the type-2 FLS.

  2. Prototype-based models in machine learning.

    Science.gov (United States)

    Biehl, Michael; Hammer, Barbara; Villmann, Thomas

    2016-01-01

    An overview is given of prototype-based models in machine learning. In this framework, observations, i.e., data, are stored in terms of typical representatives. Together with a suitable measure of similarity, the systems can be employed in the context of unsupervised and supervised analysis of potentially high-dimensional, complex datasets. We discuss basic schemes of competitive vector quantization as well as the so-called neural gas approach and Kohonen's topology-preserving self-organizing map. Supervised learning in prototype systems is exemplified in terms of learning vector quantization. Most frequently, the familiar Euclidean distance serves as a dissimilarity measure. We present extensions of the framework to nonstandard measures and give an introduction to the use of adaptive distances in relevance learning. © 2016 Wiley Periodicals, Inc.

  3. A Controller Design with ANFIS Architecture Attendant Learning Ability for SSSC-Based Damping Controller Applied in Single Machine Infinite Bus System

    Directory of Open Access Journals (Sweden)

    A. Khoshsaadat

    2014-09-01

    Full Text Available Static Synchronous Series Compensator (SSSC is a series compensating Flexible AC Transmission System (FACTS controller for maintaining to the power flow control on a transmission line by injecting a voltage in quadrature with the line current and in series mode with the line. In this work, an Adaptive Network-based Fuzzy Inference System controller (ANFISC has been proposed for controlling of the SSSC-based damping system and applied to a Single Machine Infinite Bus (SMIB power system. For implementation of the learning process in this controller, we use of the one approach of the learning ability that named as Forward Signal and Backward Error Back-Propagation (FSBEBP method for improving of the system efficiency. This artificial intelligence-based control model leads to a controller with adaptive structure, improved correctness, high damping ability and dynamic performance. System implementation is easy and it requires 49 fuzzy rules for inference engine of the system. As compared with the other complex neuro-fuzzy systems, this controller has medium number of the fuzzy rules and low number of layers, but it has high accuracy. In order to demonstrate of the proposed controller ability, it is simulated and its output compared with that of classic Lead-Lag-based Controller (LLC and PI controller.

  4. The effect of application of contextual teaching and learning (CTL model-based on lesson study with mind mapping media to assess student learning outcomes on chemistry on colloid systems

    Directory of Open Access Journals (Sweden)

    Annisa Fadillah

    2017-08-01

    Full Text Available The research was conducted to determine the effect of the application of CTL learning model based on lesson study with mind mapping media to the learning outcomes of students on colloid systems. The population of this research was all students of grade XI of SMA N 1 Sunggal. The sample was taken using on the purposive random sampling. The Experiment class was taught with Contextual Teaching and Learning (CTL model based on Lesson Study with Mind Mapping media and the control class taught with conventional learning model. The data was collected using an objective test was consisting of 20 questions which validity, reliability, level of difficulty and power of difference had been tested. T test results showed that tcalculate = 2.1 and ttable = 1.6697 thus tcalculate> ttable which means that Ha is accepted and Ho is rejected. The enhancement of the student learning outcomes showed that the results of experiment class are g = 72.88%, while the control class is 68.97%. From the percentage, it can be seen that learning outcomes of the experiment class are greater than the control class. The analysis of developing cognitive aspects pointed out that C1 = 70.02%, C2 = 73.58%, C3 = 68.63%, Thus the domain of cognitive level are on the cognitive aspects of C2. The result of Lesson Study Analysis showed the results of 71.09% at the first lesson and 88.28% at the second lesson. It means that there is increasing adherence to the indicators after two lessons. Based on the above results, it can be concluded that the result of studying chemistry of the students of class XI of SMA Negeri I Sunggal TA 2014/2015 taught by a CTL model based  on Lesson Study with Mind Mapping media was higher (72.88% than those taught by conventional learning models (68.97% in the subject matter of colloids System.

  5. Characteristics of the Web-Based Learning Environment in Distance Education: Students' Perceptions of Their Learning Needs

    Science.gov (United States)

    Atan, Hanafi; Rahman, Zuraidah; Idrus, Rozhan M.

    2004-01-01

    A study was conducted regarding students' perceptions on the characteristics of the learning requirements in a web-based learning environment. Various aspects of on-line learning were studied including the general web-based support system for the students, the learning materials, instructional strategies of the learning materials and the learning…

  6. A systemic examination of the introduction of an outdoor learning-based science curriculum to students, their teacher, and the school principal

    Science.gov (United States)

    Yunker, Molly Louis

    The outdoor environment has been under-utilized as a legitimate setting for learning within the formal school context, resulting in few examples of curriculum materials that integrate the indoors and outdoors. This systemic problem is explored holistically through investigation of key sets of players in the school system. The overarching research question is "What is the role and value of integrated outdoor learning experiences within the school system?" I developed an eight-week Earth systems science unit grounded in research-based design principles. One teacher enacted the unit with 111 sixth graders, whose learning gains and perspectives of the role and value of integrated outdoor learning experiences were explored using a mixed-methods approach in a pre-post study design, including individual interviews, and instruments regarding students' perspectives of the outdoor component of the curricular enactment. I conducted six interviews with the participating teacher and one interview with the school principal, to explore their perspectives of the role of outdoor learning experiences, and their personal roles in the unit. The main finding from this study was that the outdoor component of the curriculum enhanced coherence---connectedness across science concepts, activities, and learning environments. Higher ability students were more aware of connections than lower ability students. Field experiences were seen as a tool for learning, and all students achieved substantial learning gains. The teacher viewed the role of the outdoor experiences as a way to engage students, and promote connections across the unit through firsthand and relevant experiences. The school principal viewed his role as supporting teachers in their practice and encouraging risk-taking and creativity in instructional approaches. This study is a valuable contribution to the field as it (1) identifies outdoor learning experiences as one way to enhance intraunit coherence, and (2) highlights

  7. E-learning: Web-based education.

    Science.gov (United States)

    Sajeva, Marco

    2006-12-01

    This review introduces state-of-the-art Web-based education and shows how the e-learning model can be applied to an anaesthesia department using Open Source solutions, as well as lifelong learning programs, which is happening in several European research projects. The definition of the term e-learning is still a work in progress due to the fact that technologies are evolving every day and it is difficult to improve teaching methodologies or to adapt traditional methods to a new or already existing educational model. The European Community is funding several research projects to define the new common market place for tomorrow's educational system; this is leading to new frontiers like virtual Erasmus inter-exchange programs based on e-learning. The first step when adapting a course to e-learning is to re-define the educational/learning model adopted: cooperative learning and tutoring are the two key concepts. This means that traditional lecture notes, books and exercises are no longer effective; teaching files must use rich multimedia content and have to be developed using the new media. This can lead to several pitfalls that can be avoided with an accurate design phase.

  8. Prototype-based models in machine learning

    NARCIS (Netherlands)

    Biehl, Michael; Hammer, Barbara; Villmann, Thomas

    2016-01-01

    An overview is given of prototype-based models in machine learning. In this framework, observations, i.e., data, are stored in terms of typical representatives. Together with a suitable measure of similarity, the systems can be employed in the context of unsupervised and supervised analysis of

  9. LONS: Learning Object Negotiation System

    Science.gov (United States)

    García, Antonio; García, Eva; de-Marcos, Luis; Martínez, José-Javier; Gutiérrez, José-María; Gutiérrez, José-Antonio; Barchino, Roberto; Otón, Salvador; Hilera, José-Ramón

    This system comes up as a result of the increase of e-learning systems. It manages all relevant modules in this context, such as the association of digital rights with the contents (courses), management and payment processing on rights. There are three blocks:

  10. Characteristics of Problem-Based Learning

    DEFF Research Database (Denmark)

    Kolmos, Anette

    2003-01-01

    Problem BAsed LEarning (PBL) is widely regarded as a successful and innovative method for engineering education. The article highlights the Dutch approach of directing the learning process throuogh problem analysis and the Danish model of project-organised learning...

  11. Improved Academic Performance and Student Perceptions of Learning through Use of a Cell Phone-Based Personal Response System

    Science.gov (United States)

    Ma, Sihui; Steger, Daniel G.; Doolittle, Peter E.; Stewart, Amanda C.

    2018-01-01

    Personal response systems, such as clickers, have been widely used to improve the effectiveness of teaching in various classroom settings. Although hand-held clicker response systems have been the subject of multiple prior studies, few studies have focused on the use of cell phone-based personal response system (CPPRS) specifically. This study…

  12. Learning in Artificial Neural Systems

    Science.gov (United States)

    Matheus, Christopher J.; Hohensee, William E.

    1987-01-01

    This paper presents an overview and analysis of learning in Artificial Neural Systems (ANS's). It begins with a general introduction to neural networks and connectionist approaches to information processing. The basis for learning in ANS's is then described, and compared with classical Machine learning. While similar in some ways, ANS learning deviates from tradition in its dependence on the modification of individual weights to bring about changes in a knowledge representation distributed across connections in a network. This unique form of learning is analyzed from two aspects: the selection of an appropriate network architecture for representing the problem, and the choice of a suitable learning rule capable of reproducing the desired function within the given network. The various network architectures are classified, and then identified with explicit restrictions on the types of functions they are capable of representing. The learning rules, i.e., algorithms that specify how the network weights are modified, are similarly taxonomized, and where possible, the limitations inherent to specific classes of rules are outlined.

  13. A Simple and Effective Remedial Learning System with a Fuzzy Expert System

    Science.gov (United States)

    Lin, C.-C.; Guo, K.-H.; Lin, Y.-C.

    2016-01-01

    This study aims at implementing a simple and effective remedial learning system. Based on fuzzy inference, a remedial learning material selection system is proposed for a digital logic course. Two learning concepts of the course have been used in the proposed system: number systems and combinational logic. We conducted an experiment to validate…

  14. Collaborative Inquiry-based Learning

    NARCIS (Netherlands)

    Suarez, Angel

    2017-01-01

    This thesis presents the results of the conducted research and development of applications to support collaborative inquiry-based learning, with a special focus on leveraging learners’ agency. The reported results are structured into three parts: the theoretical foundations, the design and

  15. An Online Q-learning Based Multi-Agent LFC for a Multi-Area Multi-Source Power System Including Distributed Energy Resources

    Directory of Open Access Journals (Sweden)

    H. Shayeghi

    2017-12-01

    Full Text Available This paper presents an online two-stage Q-learning based multi-agent (MA controller for load frequency control (LFC in an interconnected multi-area multi-source power system integrated with distributed energy resources (DERs. The proposed control strategy consists of two stages. The first stage is employed a PID controller which its parameters are designed using sine cosine optimization (SCO algorithm and are fixed. The second one is a reinforcement learning (RL based supplementary controller that has a flexible structure and improves the output of the first stage adaptively based on the system dynamical behavior. Due to the use of RL paradigm integrated with PID controller in this strategy, it is called RL-PID controller. The primary motivation for the integration of RL technique with PID controller is to make the existing local controllers in the industry compatible to reduce the control efforts and system costs. This novel control strategy combines the advantages of the PID controller with adaptive behavior of MA to achieve the desired level of robust performance under different kind of uncertainties caused by stochastically power generation of DERs, plant operational condition changes, and physical nonlinearities of the system. The suggested decentralized controller is composed of the autonomous intelligent agents, who learn the optimal control policy from interaction with the system. These agents update their knowledge about the system dynamics continuously to achieve a good frequency oscillation damping under various severe disturbances without any knowledge of them. It leads to an adaptive control structure to solve LFC problem in the multi-source power system with stochastic DERs. The results of RL-PID controller in comparison to the traditional PID and fuzzy-PID controllers is verified in a multi-area power system integrated with DERs through some performance indices.

  16. Intelligent data analysis for e-learning enhancing security and trustworthiness in online learning systems

    CERN Document Server

    Miguel, Jorge; Xhafa, Fatos

    2016-01-01

    Intelligent Data Analysis for e-Learning: Enhancing Security and Trustworthiness in Online Learning Systems addresses information security within e-Learning based on trustworthiness assessment and prediction. Over the past decade, many learning management systems have appeared in the education market. Security in these systems is essential for protecting against unfair and dishonest conduct-most notably cheating-however, e-Learning services are often designed and implemented without considering security requirements. This book provides functional approaches of trustworthiness analysis, modeling, assessment, and prediction for stronger security and support in online learning, highlighting the security deficiencies found in most online collaborative learning systems. The book explores trustworthiness methodologies based on collective intelligence than can overcome these deficiencies. It examines trustworthiness analysis that utilizes the large amounts of data-learning activities generate. In addition, as proc...

  17. Design and Implementation of a Cooperative Learning System for Digital Content Design Curriculum: Investigation on Learning Effectiveness and Social Presence

    Science.gov (United States)

    Huang, Ming-Shang; Hsiao, Wei-Hung; Chang, Tsung-Sheng; Hu, Mei-Huei

    2012-01-01

    The purpose of this paper is to investigate the learning effectiveness of cooperative learning system based on social presence theory. We develop a web-based cooperative learning system which contains personal module, admin module, course module, communication module, and learning records module to support the implementation of cooperative…

  18. Web-Based Instruction, Learning Effectiveness and Learning Behavior: The Impact of Relatedness

    Science.gov (United States)

    Shieh, Chich-Jen; Liao, Ying; Hu, Ridong

    2013-01-01

    This study aims to discuss the effects of Web-based Instruction and Learning Behavior on Learning Effectiveness. Web-based Instruction contains the dimensions of Active Learning, Simulation-based Learning, Interactive Learning, and Accumulative Learning; and, Learning Behavior covers Learning Approach, Learning Habit, and Learning Attitude. The…

  19. A Methodological Approach to Encourage the Service-Oriented Learning Systems Development

    Science.gov (United States)

    Diez, David; Malizia, Alessio; Aedo, Ignacio; Diaz, Paloma; Fernandez, Camino; Dodero, Juan-Manuel

    2009-01-01

    The basic idea of service-oriented learning is that a learning environment should be conceived as a set of independent units of learning packaged as learning services. The design, development and deployment of a learning system based on integrating different learning services needs both a technological platform to support the system as well as a…

  20. Instance-based Policy Learning by Real-coded Genetic Algorithms and Its Application to Control of Nonholonomic Systems

    Science.gov (United States)

    Miyamae, Atsushi; Sakuma, Jun; Ono, Isao; Kobayashi, Shigenobu

    The stabilization control of nonholonomic systems have been extensively studied because it is essential for nonholonomic robot control problems. The difficulty in this problem is that the theoretical derivation of control policy is not necessarily guaranteed achievable. In this paper, we present a reinforcement learning (RL) method with instance-based policy (IBP) representation, in which control policies for this class are optimized with respect to user-defined cost functions. Direct policy search (DPS) is an approach for RL; the policy is represented by parametric models and the model parameters are directly searched by optimization techniques including genetic algorithms (GAs). In IBP representation an instance consists of a state and an action pair; a policy consists of a set of instances. Several DPSs with IBP have been previously proposed. In these methods, sometimes fail to obtain optimal control policies when state-action variables are continuous. In this paper, we present a real-coded GA for DPSs with IBP. Our method is specifically designed for continuous domains. Optimization of IBP has three difficulties; high-dimensionality, epistasis, and multi-modality. Our solution is designed for overcoming these difficulties. The policy search with IBP representation appears to be high-dimensional optimization; however, instances which can improve the fitness are often limited to active instances (instances used for the evaluation). In fact, the number of active instances is small. Therefore, we treat the search problem as a low dimensional problem by restricting search variables only to active instances. It has been commonly known that functions with epistasis can be efficiently optimized with crossovers which satisfy the inheritance of statistics. For efficient search of IBP, we propose extended crossover-like mutation (extended XLM) which generates a new instance around an instance with satisfying the inheritance of statistics. For overcoming multi-modality, we

  1. Technology based Education System

    DEFF Research Database (Denmark)

    Kant Hiran, Kamal; Doshi, Ruchi; Henten, Anders

    2016-01-01

    Abstract - Education plays a very important role for the development of the country. Education has multiple dimensions from schooling to higher education and research. In all these domains, there is invariably a need for technology based teaching and learning tools are highly demanded in the acad......Abstract - Education plays a very important role for the development of the country. Education has multiple dimensions from schooling to higher education and research. In all these domains, there is invariably a need for technology based teaching and learning tools are highly demanded...... in the academic institutions. Thus, there is a need of comprehensive technology support system to cater the demands of all educational actors. Cloud Computing is one such comprehensive and user-friendly technology support environment that is the need of an hour. Cloud computing is the emerging technology that has...

  2. Recommender systems for technology enhanced learning research trends and applications

    CERN Document Server

    Manouselis, Nikos; Verbert, Katrien

    2014-01-01

    Presents cutting edge research from leading experts in the growing field of Recommender Systems for Technology Enhanced Learning (RecSys TEL) International contributions are included to demonstrate the merging of various efforts and communities Topics include: Linked Data and the Social Web as Facilitators for TEL Recommender Systems in Research and Practice, Personalised Learning-Plan Recommendations in Game-Based Learning and Recommendations from Heterogeneous Sources in a Technology Enhanced Learning Ecosystem

  3. The system evaluation for report writing skills of summary by HGA-SVM with Ontology: Medical case study in problem based learning

    Science.gov (United States)

    Yenaeng, Sasikanchana; Saelee, Somkid; Samai, Wirachai

    2018-01-01

    The system evaluation for report writing skills of summary by Hybrid Genetic Algorithm-Support Vector Machines (HGA-SVM) with Ontology of Medical Case Study in Problem Based Learning (PBL) is a system was developed as a guideline of scoring for the facilitators or medical teacher. The essay answers come from medical student of medical education courses in the nervous system motion and Behavior I and II subject, a third year medical student 20 groups of 9-10 people, the Faculty of Medicine in Prince of Songkla University (PSU). The audit committee have the opinion that the ratings of individual facilitators are inadequate, this system to solve such problems. In this paper proposes a development of the system evaluation for report writing skills of summary by HGA-SVM with Ontology of medical case study in PBL which the mean scores of machine learning score and humans (facilitators) score were not different at the significantly level .05 all 3 essay parts contain problem essay part, hypothesis essay part and learning objective essay part. The result show that, the average score all 3 essay parts that were not significantly different from the rate at the level of significance .05.

  4. Machine learning paradigms applications in recommender systems

    CERN Document Server

    Lampropoulos, Aristomenis S

    2015-01-01

    This timely book presents Applications in Recommender Systems which are making recommendations using machine learning algorithms trained via examples of content the user likes or dislikes. Recommender systems built on the assumption of availability of both positive and negative examples do not perform well when negative examples are rare. It is exactly this problem that the authors address in the monograph at hand. Specifically, the books approach is based on one-class classification methodologies that have been appearing in recent machine learning research. The blending of recommender systems and one-class classification provides a new very fertile field for research, innovation and development with potential applications in “big data” as well as “sparse data” problems. The book will be useful to researchers, practitioners and graduate students dealing with problems of extensive and complex data. It is intended for both the expert/researcher in the fields of Pattern Recognition, Machine Learning and ...

  5. Assessment of Web-Based Authentication Methods in the U.S.: Comparing E-Learning Systems to Internet Healthcare Information Systems

    Science.gov (United States)

    Mattord, Herbert J.

    2012-01-01

    Organizations continue to rely on password-based authentication methods to control access to many Web-based systems. This research study developed a benchmarking instrument intended to assess authentication methods used in Web-based information systems (IS). It developed an Authentication Method System Index (AMSI) to analyze collected data from…

  6. Increasing participation in the Earth sciences through engagement of K-12 educators in Earth system science analysis, inquiry and problem- based learning and teaching

    Science.gov (United States)

    Burrell, S.

    2012-12-01

    Given low course enrollment in geoscience courses, retention in undergraduate geoscience courses, and granting of BA and advanced degrees in the Earth sciences an effective strategy to increase participation in this field is necessary. In response, as K-12 education is a conduit to college education and the future workforce, Earth science education at the K-12 level was targeted with the development of teacher professional development around Earth system science, inquiry and problem-based learning. An NSF, NOAA and NASA funded effort through the Institute for Global Environmental Strategies led to the development of the Earth System Science Educational Alliance (ESSEA) and dissemination of interdisciplinary Earth science content modules accessible to the public and educators. These modules formed the basis for two teacher workshops, two graduate level courses for in-service teachers and two university course for undergraduate teacher candidates. Data from all three models will be presented with emphasis on the teacher workshop. Essential components of the workshop model include: teaching and modeling Earth system science analysis; teacher development of interdisciplinary, problem-based academic units for implementation in the classroom; teacher collaboration; daily workshop evaluations; classroom observations; follow-up collaborative meetings/think tanks; and the building of an on-line professional community for continued communication and exchange of best practices. Preliminary data indicate increased understanding of Earth system science, proficiency with Earth system science analysis, and renewed interest in innovative delivery of content amongst teachers. Teacher-participants reported increased student engagement in learning with the implementation of problem-based investigations in Earth science and Earth system science thinking in the classroom, however, increased enthusiasm of the teacher acted as a contributing factor. Teacher feedback on open

  7. Constructivism Based Blended Learning in Higher Education

    OpenAIRE

    Al-Huneidi, Ahmad

    2011-01-01

    Blended Learning, which is a mix of online and face-to-face learning, can combine the benefits of both, traditional classroom learning and e-learning environments.3 The aim of this thesis is to explore how to design and implement Blended Learning environment based on Constructivism theory, which focuses on students’ experience to construct the knowledge, in order to increase learning outcomes, performance, and quality in academic institutions. An affective and successful learni...

  8. [Verification of Learning Effects by Team-based Learning].

    Science.gov (United States)

    Ono, Shin-Ichi; Ito, Yoshihisa; Ishige, Kumiko; Inokuchi, Norio; Kosuge, Yasuhiro; Asami, Satoru; Izumisawa, Megumi; Kobayashi, Hiroko; Hayashi, Hiroyuki; Suzuki, Takashi; Kishikawa, Yukinaga; Hata, Harumi; Kose, Eiji; Tabata, Kei-Ichi

    2017-11-01

     It has been recommended that active learning methods, such as team-based learning (TBL) and problem-based learning (PBL), be introduced into university classes by the Central Council for Education. As such, for the past 3 years, we have implemented TBL in a medical therapeutics course for 4-year students. Based upon our experience, TBL is characterized as follows: TBL needs fewer teachers than PBL to conduct a TBL module. TBL enables both students and teachers to recognize and confirm the learning results from preparation and reviewing. TBL grows students' responsibility for themselves and their teams, and likely facilitates learning activities through peer assessment.

  9. A strategy learning model for autonomous agents based on classification

    Directory of Open Access Journals (Sweden)

    Śnieżyński Bartłomiej

    2015-09-01

    Full Text Available In this paper we propose a strategy learning model for autonomous agents based on classification. In the literature, the most commonly used learning method in agent-based systems is reinforcement learning. In our opinion, classification can be considered a good alternative. This type of supervised learning can be used to generate a classifier that allows the agent to choose an appropriate action for execution. Experimental results show that this model can be successfully applied for strategy generation even if rewards are delayed. We compare the efficiency of the proposed model and reinforcement learning using the farmer-pest domain and configurations of various complexity. In complex environments, supervised learning can improve the performance of agents much faster that reinforcement learning. If an appropriate knowledge representation is used, the learned knowledge may be analyzed by humans, which allows tracking the learning process

  10. An Intelligent System for Determining Learning Style

    Science.gov (United States)

    Ozdemir, Ali; Alaybeyoglu, Aysegul; Mulayim, Naciye; Uysal, Muhammed

    2018-01-01

    In this study, an intelligent system which determines learning style of the students is developed to increase success in effective and easy learning. The importance of the proposed software system is to determine convenience degree of the student's learning style. Personal information form and Dunn Learning Style Preference Survey are used to…

  11. Computerized adaptive testing item selection in computerized adaptive learning systems

    NARCIS (Netherlands)

    Eggen, Theodorus Johannes Hendrikus Maria; Eggen, T.J.H.M.; Veldkamp, B.P.

    2012-01-01

    Item selection methods traditionally developed for computerized adaptive testing (CAT) are explored for their usefulness in item-based computerized adaptive learning (CAL) systems. While in CAT Fisher information-based selection is optimal, for recovering learning populations in CAL systems item

  12. Learning Management Systems and Comparison of Open Source Learning Management Systems and Proprietary Learning Management Systems

    Directory of Open Access Journals (Sweden)

    Yücel Yılmaz

    2016-04-01

    Full Text Available The concept of learning has been increasingly gaining importance for individuals, businesses and communities in the age of information. On the other hand, developments in information and communication technologies take effect in the field of learning activities. With these technologies, barriers of time and space against the learning activities largely disappear and these technologies make it easier to carry out these activities more effectively. There remain a lot of questions regarding selection of learning management system (LMS to be used for the management of e-learning processes by all organizations conducing educational practices including universities, companies, non-profit organizations, etc. The main questions are as follows: Shall we choose open source LMS or commercial LMS? Can the selected LMS meet existing needs and future potential needs for the organization? What are the possibilities of technical support in the management of LMS? What kind of problems may be experienced in the use of LMS and how can these problems be solved? How much effective can officials in the organization be in the management of LMS? In this study, primarily e-learning and the concept of LMS will be discussed, and in the next section, as for answers to these questions, open source LMSs and centrally developed LMSs will be examined and their advantages and disadvantages relative to each other will be discussed.

  13. An Intelligent Mobile Location-Aware Book Recommendation System that Enhances Problem-Based Learning in Libraries

    Science.gov (United States)

    Chen, Chih-Ming

    2013-01-01

    Despite rapid and continued adoption of mobile devices, few learning modes integrate with mobile technologies and libraries' environments as innovative learning modes that emphasize the key roles of libraries in facilitating learning. In addition, some education experts have claimed that transmitting knowledge to learners is not the only…

  14. IoT Security Techniques Based on Machine Learning

    OpenAIRE

    Xiao, Liang; Wan, Xiaoyue; Lu, Xiaozhen; Zhang, Yanyong; Wu, Di

    2018-01-01

    Internet of things (IoT) that integrate a variety of devices into networks to provide advanced and intelligent services have to protect user privacy and address attacks such as spoofing attacks, denial of service attacks, jamming and eavesdropping. In this article, we investigate the attack model for IoT systems, and review the IoT security solutions based on machine learning techniques including supervised learning, unsupervised learning and reinforcement learning. We focus on the machine le...

  15. BEBP: An Poisoning Method Against Machine Learning Based IDSs

    OpenAIRE

    Li, Pan; Liu, Qiang; Zhao, Wentao; Wang, Dongxu; Wang, Siqi

    2018-01-01

    In big data era, machine learning is one of fundamental techniques in intrusion detection systems (IDSs). However, practical IDSs generally update their decision module by feeding new data then retraining learning models in a periodical way. Hence, some attacks that comprise the data for training or testing classifiers significantly challenge the detecting capability of machine learning-based IDSs. Poisoning attack, which is one of the most recognized security threats towards machine learning...

  16. Measuring the influence of Cooperative Learning and Project Based Learning on problem solvin skill.

    OpenAIRE

    García Martín, Javier; Pérez Martínez, Jorge Enrique

    2011-01-01

    The aim of this study is to evaluate the effects obtained after applying two active learning methodologies (cooperative learning and project based learning) to the achievement of the competence problem solving. This study was carried out at the Technical University of Madrid, where these methodologies were applied to two Operating Systems courses. The first hypothesis tested was whether the implementation of active learning methodologies favours the achievement of ?problem solving?. The secon...

  17. Features and Characteristics of Problem Based Learning

    Science.gov (United States)

    Ceker, Eser; Ozdamli, Fezile

    2016-01-01

    Throughout the years, there appears to be an increase in Problem Based Learning applications in education; and Problem Based Learning related research areas. The main aim of this research is to underline the fundamentals (basic elements) of Problem Based Learning, investigate the dimensions of research approached to PBL oriented areas (with a look…

  18. Automata learning algorithms and processes for providing more complete systems requirements specification by scenario generation, CSP-based syntax-oriented model construction, and R2D2C system requirements transformation

    Science.gov (United States)

    Hinchey, Michael G. (Inventor); Margaria, Tiziana (Inventor); Rash, James L. (Inventor); Rouff, Christopher A. (Inventor); Steffen, Bernard (Inventor)

    2010-01-01

    Systems, methods and apparatus are provided through which in some embodiments, automata learning algorithms and techniques are implemented to generate a more complete set of scenarios for requirements based programming. More specifically, a CSP-based, syntax-oriented model construction, which requires the support of a theorem prover, is complemented by model extrapolation, via automata learning. This may support the systematic completion of the requirements, the nature of the requirement being partial, which provides focus on the most prominent scenarios. This may generalize requirement skeletons by extrapolation and may indicate by way of automatically generated traces where the requirement specification is too loose and additional information is required.

  19. The Credentials of Brain-Based Learning

    Science.gov (United States)

    Davis, Andrew

    2004-01-01

    This paper discusses the current fashion for brain-based learning, in which value-laden claims about learning are grounded in neurophysiology. It argues that brain science cannot have the authority about learning that some seek to give it. It goes on to discuss whether the claim that brain science is relevant to learning involves a category…

  20. Foundations of Game-Based Learning

    Science.gov (United States)

    Plass, Jan L.; Homer, Bruce D.; Kinzer, Charles K.

    2015-01-01

    In this article we argue that to study or apply games as learning environments, multiple perspectives have to be taken into account. We first define game-based learning and gamification, and then discuss theoretical models that describe learning with games, arguing that playfulness is orthogonal to learning theory. We then review design elements…

  1. Working Together for Better Student Learning: A Multi-University, Multi-Federal Partner Program for Asynchronous Learning Module Development for Radar-Based Remote Sensing Systems

    Science.gov (United States)

    Yeary, M. B.; Yu, T.; Palmer, R. D.; Monroy, H.; Ruin, I.; Zhang, G.; Chilson, P. B.; Biggerstaff, M. I.; Weiss, C.; Mitchell, K. A.; Fink, L. D.

    2010-01-01

    Students are not exposed to enough real-life data. This paper describes how a community of scholars seeks to remedy this deficiency and gives the pedagogical details of an ongoing project that commenced in the Fall 2004 semester. Fostering deep learning, this multiyear project offers a new active-learning, hands-on interdisciplinary laboratory…

  2. VIRTUAL LABORATORY IN DISTANCE LEARNING SYSTEM

    Directory of Open Access Journals (Sweden)

    Е. Kozlovsky

    2011-11-01

    Full Text Available Questions of designing and a choice of technologies of creation of virtual laboratory for the distance learning system are considered. Distance learning system «Kherson Virtual University» is used as illustration.

  3. Intelligent e-Learning Systems: An Educational Paradigm Shift

    Directory of Open Access Journals (Sweden)

    Suman Bhattacharya

    2016-12-01

    Full Text Available Learning is the long process of transforming information as well as experience into knowledge, skills, attitude and behaviors. To make up the wide gap between the demand of increasing higher education and comparatively limited resources, more and more educational institutes are looking into instructional technology. Use of online resources not only reduces the cost of education but also meet the needs of society. Intelligent e-learning has become one of the important channels to reach out to students exceeding geographic boundaries. Besides this, the characteristics of e-learning have complicated the process of education, and have brought challenges to both instructors and students. This paper will focus on the discussion of different discipline of intelligent e-learning like scaffolding based e-learning, personalized e-learning, confidence based e-learning, intelligent tutoring system, etc. to illuminate the educational paradigm shift in intelligent e-learning system.

  4. Combatting nonlinear phase noise in coherent optical systems with an optimized decision processor based on machine learning

    Science.gov (United States)

    Wang, Danshi; Zhang, Min; Cai, Zhongle; Cui, Yue; Li, Ze; Han, Huanhuan; Fu, Meixia; Luo, Bin

    2016-06-01

    An effective machine learning algorithm, the support vector machine (SVM), is presented in the context of a coherent optical transmission system. As a classifier, the SVM can create nonlinear decision boundaries to mitigate the distortions caused by nonlinear phase noise (NLPN). Without any prior information or heuristic assumptions, the SVM can learn and capture the link properties from only a few training data. Compared with the maximum likelihood estimation (MLE) algorithm, a lower bit-error rate (BER) is achieved by the SVM for a given launch power; moreover, the launch power dynamic range (LPDR) is increased by 3.3 dBm for 8 phase-shift keying (8 PSK), 1.2 dBm for QPSK, and 0.3 dBm for BPSK. The maximum transmission distance corresponding to a BER of 1 ×10-3 is increased by 480 km for the case of 8 PSK. The larger launch power range and longer transmission distance improve the tolerance to amplitude and phase noise, which demonstrates the feasibility of the SVM in digital signal processing for M-PSK formats. Meanwhile, in order to apply the SVM method to 16 quadratic amplitude modulation (16 QAM) detection, we propose a parameter optimization scheme. By utilizing a cross-validation and grid-search techniques, the optimal parameters of SVM can be selected, thus leading to the LPDR improvement by 2.8 dBm. Additionally, we demonstrate that the SVM is also effective in combating the laser phase noise combined with the inphase and quadrature (I/Q) modulator imperfections, but the improvement is insignificant for the linear noise and separate I/Q imbalance. The computational complexity of SVM is also discussed. The relatively low complexity makes it possible for SVM to implement the real-time processing.

  5. Principles of e-learning systems engineering

    CERN Document Server

    Gilbert, Lester

    2008-01-01

    The book integrates the principles of software engineering with the principles of educational theory, and applies them to the problems of e-learning development, thus establishing the discipline of E-learning systems engineering. For the first time, these principles are collected and organised into the coherent framework that this book provides. Both newcomers to and established practitioners in the field are provided with integrated and grounded advice on theory and practice. The book presents strong practical and theoretical frameworks for the design and development of technology-based mater

  6. Comparison of Natural Language Processing Rules-based and Machine-learning Systems to Identify Lumbar Spine Imaging Findings Related to Low Back Pain.

    Science.gov (United States)

    Tan, W Katherine; Hassanpour, Saeed; Heagerty, Patrick J; Rundell, Sean D; Suri, Pradeep; Huhdanpaa, Hannu T; James, Kathryn; Carrell, David S; Langlotz, Curtis P; Organ, Nancy L; Meier, Eric N; Sherman, Karen J; Kallmes, David F; Luetmer, Patrick H; Griffith, Brent; Nerenz, David R; Jarvik, Jeffrey G

    2018-03-28

    To evaluate a natural language processing (NLP) system built with open-source tools for identification of lumbar spine imaging findings related to low back pain on magnetic resonance and x-ray radiology reports from four health systems. We used a limited data set (de-identified except for dates) sampled from lumbar spine imaging reports of a prospectively assembled cohort of adults. From N = 178,333 reports, we randomly selected N = 871 to form a reference-standard dataset, consisting of N = 413 x-ray reports and N = 458 MR reports. Using standardized criteria, four spine experts annotated the presence of 26 findings, where 71 reports were annotated by all four experts and 800 were each annotated by two experts. We calculated inter-rater agreement and finding prevalence from annotated data. We randomly split the annotated data into development (80%) and testing (20%) sets. We developed an NLP system from both rule-based and machine-learned models. We validated the system using accuracy metrics such as sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). The multirater annotated dataset achieved inter-rater agreement of Cohen's kappa > 0.60 (substantial agreement) for 25 of 26 findings, with finding prevalence ranging from 3% to 89%. In the testing sample, rule-based and machine-learned predictions both had comparable average specificity (0.97 and 0.95, respectively). The machine-learned approach had a higher average sensitivity (0.94, compared to 0.83 for rules-based), and a higher overall AUC (0.98, compared to 0.90 for rules-based). Our NLP system performed well in identifying the 26 lumbar spine findings, as benchmarked by reference-standard annotation by medical experts. Machine-learned models provided substantial gains in model sensitivity with slight loss of specificity, and overall higher AUC. Copyright © 2018 The Association of University Radiologists. All rights reserved.

  7. The Effect of Recommendation Systems on Internet-Based Learning for Different Learners: A Data Mining Analysis

    Science.gov (United States)

    Liu, Chen-Chung; Chang, Chia-Jung; Tseng, Jui-Min

    2013-01-01

    A general challenge facing Internet-based learners is how to identify information objects which are helpful in expanding their understanding of important information in a domain. Recommendation systems may assist learners in identifying potentially helpful information objects. However, the recent literature mainly focuses on the technical…

  8. Adaptive Management of Communication in the Chamilo System of Distant Learning

    OpenAIRE

    Yatsenko Roman Nikolaevich; Polevich Olesya V.

    2012-01-01

    The article considers the communication management within an adaptive system of distance learning. We present two-circuit interaction system of the adaptive system. We consider the implementation of management communication in distance learning system based on the platform Chamilo.

  9. e-Learning Management System (eLMS) -

    Data.gov (United States)

    Department of Transportation — DOT's electronic Learning Management System (eLMS) is a state-of-the-art web-based system that meets the needs of training administrators, learners, and managers and...

  10. System light-loading technology for mHealth: Manifold-learning-based medical data cleansing and clinical trials in WE-CARE Project.

    Science.gov (United States)

    Huang, Anpeng; Xu, Wenyao; Li, Zhinan; Xie, Linzhen; Sarrafzadeh, Majid; Li, Xiaoming; Cong, Jason

    2014-09-01

    Cardiovascular disease (CVD) is a major issue to public health. It contributes 41% to the Chinese death rate each year. This huge loss encouraged us to develop a Wearable Efficient teleCARdiology systEm (WE-CARE) for early warning and prevention of CVD risks in real time. WE-CARE is expected to work 24/7 online for mobile health (mHealth) applications. Unfortunately, this purpose is often disrupted in system experiments and clinical trials, even if related enabling technologies work properly. This phenomenon is rooted in the overload issue of complex Electrocardiogram (ECG) data in terms of system integration. In this study, our main objective is to get a system light-loading technology to enable mHealth with a benchmarked ECG anomaly recognition rate. To achieve this objective, we propose an approach to purify clinical features from ECG raw data based on manifold learning, called the Manifold-based ECG-feature Purification algorithm. Our clinical trials verify that our proposal can detect anomalies with a recognition rate of up to 94% which is highly valuable in daily public health-risk alert applications based on clinical criteria. Most importantly, the experiment results demonstrate that the WE-CARE system enabled by our proposal can enhance system reliability by at least two times and reduce false negative rates to 0.76%, and extend the battery life by 40.54%, in the system integration level.

  11. Project Based Learning in Multi-Grade Class

    Science.gov (United States)

    Ciftci, Sabahattin; Baykan, Ayse Aysun

    2013-01-01

    The purpose of this study is to evaluate project based learning in multi-grade classes. This study, based on a student-centered learning approach, aims to analyze students' and parents' interpretations. The study was done in a primary village school belonging to the Centre of Batman, already adapting multi-grade classes in their education system,…

  12. Personalization and Contextualization of Learning Experiences based on Semantics

    Directory of Open Access Journals (Sweden)

    Nicola Capuano

    2014-04-01

    Full Text Available Context-aware e-learning is an educational model that foresees the selection of learning resources to make the e-learning content more relevant and suitable for the learner in his/her situation. The purpose of this paper is to demonstrate that an ontological approach can be used to define leaning contexts and to allow contextualizing learning experiences finding out relevant topics for each context. To do that, we defined a context model able to formally describe a learning context, an ontology-based model enabling the representation of a teaching domain (including context information and a methodology to generate personalized and context-aware learning experiences starting from them. Based on these theoretical components we improved an existing system for personalized e-learning with contextualisation features and experimented it with real users in two University courses. The results obtained from this experimentation have been compared with those achieved by similar systems.

  13. Technological learning in bioenergy systems

    International Nuclear Information System (INIS)

    Junginger, Martin; Visser, Erika de; Hjort-Gregersen, Kurt; Koornneef, Joris; Raven, Rob; Faaij, Andre; Turkenburg, Wim

    2006-01-01

    The main goal of this article is to determine whether cost reductions in different bioenergy systems can be quantified using the experience curve approach, and how specific issues (arising from the complexity of biomass energy systems) can be addressed. This is pursued by case studies on biofuelled combined heat and power (CHP) plants in Sweden, global development of fluidized bed boilers and Danish biogas plants. As secondary goal, the aim is to identify learning mechanisms behind technology development and cost reduction for the biomass energy systems investigated. The case studies reveal large difficulties to devise empirical experience curves for investment costs of biomass-fuelled power plants. To some extent, this is due to lack of (detailed) data. The main reason, however, are varying plant costs due to differences in scale, fuel type, plant layout, region etc. For fluidized bed boiler plants built on a global level, progress ratios (PRs) for the price of entire plants lies approximately between 90-93% (which is typical for large plant-like technologies). The costs for the boiler section alone was found to decline much faster. The experience curve approach delivers better results, when the production costs of the final energy carrier are analyzed. Electricity from biofuelled CHP-plants yields PRs of 91-92%, i.e. an 8-9% reduction of electricity production costs with each cumulative doubling of electricity production. The experience curve for biogas production displays a PR of 85% from 1984 to the beginning of 1990, and then levels to approximately 100% until 2002. For technologies developed on a local level (e.g. biogas plants), learning-by-using and learning-by-interacting are important learning mechanism, while for CHP plants utilizing fluidized bed boilers, upscaling is probably one of the main mechanisms behind cost reductions

  14. Student Satisfaction Process in Virtual Learning System: Considerations Based in Information and Service Quality from Brazil's Experience

    Science.gov (United States)

    Machado-Da-Silva, Fábio Nazareno; Meirelles, Fernando de Souza; Filenga, Douglas; Filho, Marino Brugnolo

    2014-01-01

    Distance learning has undergone great changes, especially since the advent of the Internet and communication and information technology. Questions have been asked following the growth of this mode of instructional activity. Researchers have investigated methods to assess the benefits of e-learning from a number of perspectives. This survey…

  15. Analysis of Selected Aspects of Students' Performance and Satisfaction in a Moodle-Based E-Learning System Environment

    Science.gov (United States)

    Umek, Lan; Aristovnik, Aleksander; Tomaževic, Nina; Keržic, Damijana

    2015-01-01

    The use of e-learning techniques in higher education is becoming ever more frequent. In some institutions, e-learning has completely replaced the traditional teaching methods, while in others it supplements classical courses. The paper presents a study conducted in a member institution of the University of Ljubljana that provides public…

  16. Implementation of a school-based social and emotional learning intervention: understanding diffusion processes within complex systems.

    Science.gov (United States)

    Evans, Rhiannon; Murphy, Simon; Scourfield, Jonathan

    2015-07-01

    Sporadic and inconsistent implementation remains a significant challenge for social and emotional learning (SEL) interventions. This may be partly explained by the dearth of flexible, causative models that capture the multifarious determinants of implementation practices within complex systems. This paper draws upon Rogers (2003) Diffusion of Innovations Theory to explain the adoption, implementation and discontinuance of a SEL intervention. A pragmatic, formative process evaluation was conducted in alignment with phase 1 of the UK Medical Research Council's framework for Developing and Evaluating Complex Interventions. Employing case-study methodology, qualitative data were generated with four socio-economically and academically contrasting secondary schools in Wales implementing the Student Assistance Programme. Semi-structured interviews were conducted with 15 programme stakeholders. Data suggested that variation in implementation activity could be largely attributed to four key intervention reinvention points, which contributed to the transformation of the programme as it interacted with contextual features and individual needs. These reinvention points comprise the following: intervention training, which captures the process through which adopters acquire knowledge about a programme and delivery expertise; intervention assessment, which reflects adopters' evaluation of an intervention in relation to contextual needs; intervention clarification, which comprises the cascading of knowledge through an organisation in order to secure support in delivery; and intervention responsibility, which refers to the process of assigning accountability for sustainable delivery. Taken together, these points identify opportunities to predict and intervene with potential implementation problems. Further research would benefit from exploring additional reinvention activity.

  17. The Role of a Commander in Military Lessons Learned Systems

    Directory of Open Access Journals (Sweden)

    Zenon Waliński

    2015-06-01

    Full Text Available The aim of the paper is to investigate the role of a commander in military Lessons Learned systems. In order to achieve the aim, the paper presents (1 the architecture of the Lessons Learned capabilities in the U.S. Army, NATO and the Polish Armed Forces, (2 the commander’s role in the Lessons Learned process (3 the commander’s role in fostering Lessons Learned organisation culture. The paper is based on multiple case study analysis including Lessons Learned systems in NATO, the U.S. Army and the Polish Armed Forces.

  18. Conceptualizing Debates in Learning and Educational Research: Toward a Complex Systems Conceptual Framework of Learning

    Science.gov (United States)

    Jacobson, Michael J.; Kapur, Manu; Reimann, Peter

    2016-01-01

    This article proposes a conceptual framework of learning based on perspectives and methodologies being employed in the study of complex physical and social systems to inform educational research. We argue that the contexts in which learning occurs are complex systems with elements or agents at different levels--including neuronal, cognitive,…

  19. Learning Management Systems on Blended Learning Courses

    DEFF Research Database (Denmark)

    Kuran, Mehmet Şükrü; Pedersen, Jens Myrup; Elsner, Raphael

    2017-01-01

    LMSes, Moodle, Blackboard Learn, Canvas, and Stud.IP with respect to these. We explain how these features were utilized to increase the efficiency, tractability, and quality of experience of the course. We found that an LMS with advanced features such as progress tracking, modular course support...

  20. Project based learning for reactor engineering education

    International Nuclear Information System (INIS)

    Narabayashi, Tadashi; Tsuji, Masashi; Shimazu, Yoichiro

    2009-01-01

    Trial in education of nuclear engineering in Hokkaido University has proved to be quite attractive for students. It is an education system called Project Based Learning (PBL), which is not based on education by lecture only but based mostly on practice of students in the classroom. The system was adopted four years ago. In the actual class, we separated the student into several groups of the size about 6 students. In the beginning of each class room time, a brief explanations of the related theory or technical bases. Then the students discuss in their own group how to precede their design calculations and do the required calculation and evaluation. The target reactor type of each group was selected by the group members for themselves at the beginning of the semester as the first step of the project. The reactor types range from a small in house type to that for a nuclear ship. At the end of the semester, each group presents the final design. The presentation experience gives students a kind of fresh sensation. Nowadays the evaluation results of the subject by the students rank in the highest in the faculty of engineering. Based on the considerations above, we designed the framework of our PBL for reactor engineering. In this paper, we will present some lessons learned in this PBL education system from the educational points of view. The PBL education program is supported by IAE/METI in Japan for Nuclear Engineering Education. (author)

  1. System Quality Characteristics for Selecting Mobile Learning Applications

    Directory of Open Access Journals (Sweden)

    Mohamed SARRAB

    2015-10-01

    Full Text Available The majority of M-learning (Mobile learning applications available today are developed for the formal learning and education environment. These applications are characterized by the improvement in the interaction between learners and instructors to provide high interaction and flexibility to the learning process. M-learning is gaining increased recognition and adoption by different organizations. With the high number of M-learning applications available today, making the right decision about which, application to choose can be quite challenging. To date there is no complete and well defined set of system characteristics for such M-learning applications. This paper presents system quality characteristics for selecting M-learning applications based on the result of a systematic review conducted in this domain.

  2. A system for learning statistical motion patterns.

    Science.gov (United States)

    Hu, Weiming; Xiao, Xuejuan; Fu, Zhouyu; Xie, Dan; Tan, Tieniu; Maybank, Steve

    2006-09-01

    Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy K-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction.

  3. Music Learning Based on Computer Software

    Directory of Open Access Journals (Sweden)

    Baihui Yan

    2017-12-01

    Full Text Available In order to better develop and improve students’ music learning, the authors proposed the method of music learning based on computer software. It is still a new field to use computer music software to assist teaching. Hereby, we conducted an in-depth analysis on the computer-enabled music learning and the music learning status in secondary schools, obtaining the specific analytical data. Survey data shows that students have many cognitive problems in the current music classroom, and yet teachers have not found a reasonable countermeasure to them. Against this background, the introduction of computer music software to music learning is a new trial that can not only cultivate the students’ initiatives of music learning, but also enhance their abilities to learn music. Therefore, it is concluded that the computer software based music learning is of great significance to improving the current music learning modes and means.

  4. Problem Based Learning and sustainability

    DEFF Research Database (Denmark)

    Pizzol, Massimo; Løkke, Søren; Schmidt, Jannick Højrup

    and challenges that the PBL model offers for developing five key competences in sustainability: (i) system thinking, (ii) interpersonal competence, (iii) anticipatory competence, (iv) strategic competence, (v) normative competences. The study draws on the experiences from PBL activities performed at Aalborg...... University (AAU), Denmark, and focuses on the teaching of Life Cycle Assessment as a method for sustainability assessment. The objective is providing recommendations for future LCA teaching and learning. PBL activites performed at AAU were evaluated critically to detemine to what extent they addressed...... of how PBL-approaches were used to develop five specific competences in sustainability. It is concluded that -for the case fo LCA teaching at AAU- the PBL model included activities to develop system thinking, interpersonal competence, and normative competence. However, the PBL approach should...

  5. E-Learning Systems, Environments and Approaches

    OpenAIRE

    Isaias, P.; Spector, J.M.; Ifenthaler, D.; Sampson, D.G.

    2015-01-01

    The volume consists of twenty-five chapters selected from among peer-reviewed papers presented at the CELDA (Cognition and Exploratory Learning in the Digital Age) 2013 Conference held in Fort Worth, Texas, USA, in October 2013 and also from world class scholars in e-learning systems, environments and approaches. The following sub-topics are included: Exploratory Learning Technologies (Part I), e-Learning social web design (Part II), Learner communities through e-Learning implementations (Par...

  6. Which Recommender System Can Best Fit Social Learning Platforms?

    OpenAIRE

    Fazeli, Soude; Loni, Babak; Drachsler, Hendrik; Sloep, Peter

    2014-01-01

    In this presentation, we present a study that aims to develop a recommender system for social learning platforms that combine traditional learning management systems with commercial social networks like Facebook. We therefore take into account social interactions of users to make recommendations on learning resources. We propose to make use of graph-walking methods for improving performance of the well-known baseline algorithms. We evaluate the proposed graph-based approach in terms of their ...

  7. Learning Theory Foundations of Simulation-Based Mastery Learning.

    Science.gov (United States)

    McGaghie, William C; Harris, Ilene B

    2018-06-01

    Simulation-based mastery learning (SBML), like all education interventions, has learning theory foundations. Recognition and comprehension of SBML learning theory foundations are essential for thoughtful education program development, research, and scholarship. We begin with a description of SBML followed by a section on the importance of learning theory foundations to shape and direct SBML education and research. We then discuss three principal learning theory conceptual frameworks that are associated with SBML-behavioral, constructivist, social cognitive-and their contributions to SBML thought and practice. We then discuss how the three learning theory frameworks converge in the course of planning, conducting, and evaluating SBML education programs in the health professions. Convergence of these learning theory frameworks is illustrated by a description of an SBML education and research program in advanced cardiac life support. We conclude with a brief coda.

  8. Minimizing Barriers in Learning for On-Call Radiology Residents-End-to-End Web-Based Resident Feedback System.

    Science.gov (United States)

    Choi, Hailey H; Clark, Jennifer; Jay, Ann K; Filice, Ross W

    2018-02-01

    Feedback is an essential part of medical training, where trainees are provided with information regarding their performance and further directions for improvement. In diagnostic radiology, feedback entails a detailed review of the differences between the residents' preliminary interpretation and the attendings' final interpretation of imaging studies. While the on-call experience of independently interpreting complex cases is important to resident education, the more traditional synchronous "read-out" or joint review is impossible due to multiple constraints. Without an efficient method to compare reports, grade discrepancies, convey salient teaching points, and view images, valuable lessons in image interpretation and report construction are lost. We developed a streamlined web-based system, including report comparison and image viewing, to minimize barriers in asynchronous communication between attending radiologists and on-call residents. Our system provides real-time, end-to-end delivery of case-specific and user-specific feedback in a streamlined, easy-to-view format. We assessed quality improvement subjectively through surveys and objectively through participation metrics. Our web-based feedback system improved user satisfaction for both attending and resident radiologists, and increased attending participation, particularly with regards to cases where substantive discrepancies were identified.

  9. Making sense of the shadows: priorities for creating a learning healthcare system based on routinely collected data.

    Science.gov (United States)

    Deeny, Sarah R; Steventon, Adam

    2015-08-01

    Socrates described a group of people chained up inside a cave, who mistook shadows of objects on a wall for reality. This allegory comes to mind when considering 'routinely collected data'-the massive data sets, generated as part of the routine operation of the modern healthcare service. There is keen interest in routine data and the seemingly comprehensive view of healthcare they offer, and we outline a number of examples in which they were used successfully, including the Birmingham OwnHealth study, in which routine data were used with matched control groups to assess the effect of telephone health coaching on hospital utilisation.Routine data differ from data collected primarily for the purposes of research, and this means that analysts cannot assume that they provide the full or accurate clinical picture, let alone a full description of the health of the population. We show that major methodological challenges in using routine data arise from the difficulty of understanding the gap between patient and their 'data shadow'. Strategies to overcome this challenge include more extensive data linkage, developing analytical methods and collecting more data on a routine basis, including from the patient while away from the clinic. In addition, creating a learning health system will require greater alignment between the analysis and the decisions that will be taken; between analysts and people interested in quality improvement; and between the analysis undertaken and public attitudes regarding appropriate use of data. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  10. IMPROVING CAUSE DETECTION SYSTEMS WITH ACTIVE LEARNING

    Data.gov (United States)

    National Aeronautics and Space Administration — IMPROVING CAUSE DETECTION SYSTEMS WITH ACTIVE LEARNING ISAAC PERSING AND VINCENT NG Abstract. Active learning has been successfully applied to many natural language...

  11. Obstacle Recognition Based on Machine Learning for On-Chip LiDAR Sensors in a Cyber-Physical System

    Directory of Open Access Journals (Sweden)

    Fernando Castaño

    2017-09-01

    Full Text Available Collision avoidance is an important feature in advanced driver-assistance systems, aimed at providing correct, timely and reliable warnings before an imminent collision (with objects, vehicles, pedestrians, etc.. The obstacle recognition library is designed and implemented to address the design and evaluation of obstacle detection in a transportation cyber-physical system. The library is integrated into a co-simulation framework that is supported on the interaction between SCANeR software and Matlab/Simulink. From the best of the authors’ knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip light detection and ranging sensors in a cyber-physical system, for traffic scenarios, is presented. The cyber-physical system is designed and implemented in SCANeR. Secondly, three specific artificial intelligence-based methods for obstacle recognition libraries are also designed and applied using a sensory information database provided by SCANeR. The computational library has three methods for obstacle detection: a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods under different weather conditions is presented, with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and foggy conditions, the support vector machine in rainy conditions and the self-organized map in snowy conditions.

  12. Obstacle Recognition Based on Machine Learning for On-Chip LiDAR Sensors in a Cyber-Physical System.

    Science.gov (United States)

    Castaño, Fernando; Beruvides, Gerardo; Haber, Rodolfo E; Artuñedo, Antonio

    2017-09-14

    Collision avoidance is an important feature in advanced driver-assistance systems, aimed at providing correct, timely and reliable warnings before an imminent collision (with objects, vehicles, pedestrians, etc.). The obstacle recognition library is designed and implemented to address the design and evaluation of obstacle detection in a transportation cyber-physical system. The library is integrated into a co-simulation framework that is supported on the interaction between SCANeR software and Matlab/Simulink. From the best of the authors' knowledge, two main contributions are reported in this paper. Firstly, the modelling and simulation of virtual on-chip light detection and ranging sensors in a cyber-physical system, for traffic scenarios, is presented. The cyber-physical system is designed and implemented in SCANeR. Secondly, three specific artificial intelligence-based methods for obstacle recognition libraries are also designed and applied using a sensory information database provided by SCANeR. The computational library has three methods for obstacle detection: a multi-layer perceptron neural network, a self-organization map and a support vector machine. Finally, a comparison among these methods under different weather conditions is presented, with very promising results in terms of accuracy. The best results are achieved using the multi-layer perceptron in sunny and foggy conditions, the support vector machine in rainy conditions and the self-organized map in snowy conditions.

  13. The Role of Corticostriatal Systems in Speech Category Learning.

    Science.gov (United States)

    Yi, Han-Gyol; Maddox, W Todd; Mumford, Jeanette A; Chandrasekaran, Bharath

    2016-04-01

    One of the most difficult category learning problems for humans is learning nonnative speech categories. While feedback-based category training can enhance speech learning, the mechanisms underlying these benefits are unclear. In this functional magnetic resonance imaging study, we investigated neural and computational mechanisms underlying feedback-dependent speech category learning in adults. Positive feedback activated a large corticostriatal network including the dorsolateral prefrontal cortex, inferior parietal lobule, middle temporal gyrus, caudate, putamen, and the ventral striatum. Successful learning was contingent upon the activity of domain-general category learning systems: the fast-learning reflective system, involving the dorsolateral prefrontal cortex that develops and tests explicit rules based on the feedback content, and the slow-learning reflexive system, involving the putamen in which the stimuli are implicitly associated with category responses based on the reward value in feedback. Computational modeling of response strategies revealed significant use of reflective strategies early in training and greater use of reflexive strategies later in training. Reflexive strategy use was associated with increased activation in the putamen. Our results demonstrate a critical role for the reflexive corticostriatal learning system as a function of response strategy and proficiency during speech category learning. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  14. Collaborative Learning Framework in Business Management Systems

    Directory of Open Access Journals (Sweden)

    Vladimir GRIGORE

    2008-01-01

    Full Text Available This paper presents a solution based on collaboration with experts and practitioner from university and ERP companies involved in process learning by training and learning by working. The solution uses CPI test to establish proper team for framework modules: Real-Time Chat Room, Discussion Forum, E-mail Support and Learning through Training. We define novice, practitioner and expert competence level based on CORONET train methodology. ERP companies have own roles for mentoring services to knowledge workers and evaluate the performance of learning process with teachers’ cooperation in learning by teaching and learning by working module.

  15. The Effectiveness of E-Learning Systems: A Review of the Empirical Literature on Learner Control

    Science.gov (United States)

    Sorgenfrei, Christian; Smolnik, Stefan

    2016-01-01

    E-learning systems are considerably changing education and organizational training. With the advancement of online-based learning systems, learner control over the instructional process has emerged as a decisive factor in technology-based forms of learning. However, conceptual work on the role of learner control in e-learning has not advanced…

  16. Learning-based diagnosis and repair

    NARCIS (Netherlands)

    Roos, Nico

    2017-01-01

    This paper proposes a new form of diagnosis and repair based on reinforcement learning. Self-interested agents learn locally which agents may provide a low quality of service for a task. The correctness of learned assessments of other agents is proved under conditions on exploration versus

  17. Critical Points in Distance Learning System

    Directory of Open Access Journals (Sweden)

    Airina Savickaitė

    2013-08-01

    Full Text Available Purpose – This article presents the results of distance learning system analysis, i.e. the critical elements of the distance learning system. The critical points of distance learning are a part of distance education online environment interactivity/community process model. The most important is the fact that the critical point is associated with distance learning participants. Design/methodology/approach – Comparative review of articles and analysis of distance learning module. Findings – A modern man is a lifelong learner and distance learning is a way to be a modern person. The focus on a learner and feedback is the most important thing of learning distance system. Also, attention should be paid to the lecture-appropriate knowledge and ability to convey information. Distance system adaptation is the way to improve the learner’s learning outcomes. Research limitations/implications – Different learning disciplines and learning methods may have different critical points. Practical implications – The information of analysis could be important for both lecturers and students, who studies distance education systems. There are familiar critical points which may deteriorate the quality of learning. Originality/value – The study sought to develop remote systems for applications in order to improve the quality of knowledge. Keywords: distance learning, process model, critical points. Research type: review of literature and general overview.

  18. Signifikansi Brain Based Learning Pendidikan Anak Usia Dini

    OpenAIRE

    Jazariyah

    2017-01-01

    This study based on the reality of learning in the early childhood level and the system has not noticed the potential of the brain learners. The potential and the working system of the brain is very important in early childhood. This paper aims to reveal the importance of brain-based learning in Early Childhood Education (ECD). The problem in this study is what the nature of early childhood education and how to use the potential and work system of the brain in early childhood learning. This s...

  19. A model reference and sensitivity model-based self-learning fuzzy logic controller as a solution for control of nonlinear servo systems

    NARCIS (Netherlands)

    Kovacic, Z.; Bogdan, S.; Balenovic, M.

    1999-01-01

    In this paper, the design, simulation and experimental verification of a self-learning fuzzy logic controller (SLFLC) suitable for the control of nonlinear servo systems are described. The SLFLC contains a learning algorithm that utilizes a second-order reference model and a sensitivity model

  20. Features and characteristics of problem based learning

    Directory of Open Access Journals (Sweden)

    Eser Ceker

    2016-12-01

    Full Text Available Throughout the years, there appears to be an increase in Problem Based Learning applications in education; and Problem Based Learning related research areas. The main aim of this research is to underline the fundamentals (basic elements of Problem Based Learning, investigate the dimensions of research approached to PBL oriented areas (with a look for the latest technology supported tools of Problem Based Learning. This research showed that the most researched characteristics of PBL are; teacher and student assessments on Problem Based Learning, Variety of disciplines in which Problem Based Learning strategies were tried and success evaluated, Using Problem Based Learning alone or with other strategies (Hybrid or Mix methods, Comparing Problem Based Learning with other strategies, and new trends and tendencies in Problem Based Learning related research. Our research may help us to identify the latest trends and tendencies referred to in the published studies related to “problem based learning” areas. In this research, Science Direct and Ulakbim were used as our main database resources. The sample of this study consists of 150 articles.

  1. PatterNet: a system to learn compact physical design pattern representations for pattern-based analytics

    Science.gov (United States)

    Lutich, Andrey

    2017-07-01

    This research considers the problem of generating compact vector representations of physical design patterns for analytics purposes in semiconductor patterning domain. PatterNet uses a deep artificial neural network to learn mapping of physical design patterns to a compact Euclidean hyperspace. Distances among mapped patterns in this space correspond to dissimilarities among patterns defined at the time of the network training. Once the mapping network has been trained, PatterNet embeddings can be used as feature vectors with standard machine learning algorithms, and pattern search, comparison, and clustering become trivial problems. PatterNet is inspired by the concepts developed within the framework of generative adversarial networks as well as the FaceNet. Our method facilitates a deep neural network (DNN) to learn directly the compact representation by supplying it with pairs of design patterns and dissimilarity among these patterns defined by a user. In the simplest case, the dissimilarity is represented by an area of the XOR of two patterns. Important to realize that our PatterNet approach is very different to the methods developed for deep learning on image data. In contrast to "conventional" pictures, the patterns in the CAD world are the lists of polygon vertex coordinates. The method solely relies on the promise of deep learning to discover internal structure of the incoming data and learn its hierarchical representations. Artificial intelligence arising from the combination of PatterNet and clustering analysis very precisely follows intuition of patterning/optical proximity correction experts paving the way toward human-like and human-friendly engineering tools.

  2. Inquiry based learning as didactic model in distant learning

    NARCIS (Netherlands)

    Rothkrantz, L.J.M.

    2015-01-01

    Recent years many universities are involved in development of Massive Open Online Courses (MOOCs). Unfortunately an appropriate didactic model for cooperated network learning is lacking. In this paper we introduce inquiry based learning as didactic model. Students are assumed to ask themselves

  3. Problem Based Learning for engineering.

    Science.gov (United States)

    Kumar, Dinesh; Radcliffe, Pj

    2017-07-01

    the role of Problem Based Learning (PBL) is relative clear in domains such as medicine but its efficacy in engineering is as yet less certain. To clarify the role of PBL in engineering, a 3 day workshop was conducted for senior Brazilian engineering academics where they were given the theory and then an immersive PBL experience. One major purpose for running this workshop was for them to identify suitable courses where PBL could be considered. During this workshop, they were split in teams and given a diverse range of problems. At the conclusion of the workshop, a quantifiable survey was conducted and the results show that PBL can deliver superior educational outcomes providing the student group is drawn from the top 5% of the year 12 students, and that significantly higher resources are made available. Thus, any proposed PBL program in engineering must be able to demonstrate that it can meet these requirements before it can move forward to implementation.

  4. Saul: Towards Declarative Learning Based Programming.

    Science.gov (United States)

    Kordjamshidi, Parisa; Roth, Dan; Wu, Hao

    2015-07-01

    We present Saul , a new probabilistic programming language designed to address some of the shortcomings of programming languages that aim at advancing and simplifying the development of AI systems. Such languages need to interact with messy, naturally occurring data, to allow a programmer to specify what needs to be done at an appropriate level of abstraction rather than at the data level, to be developed on a solid theory that supports moving to and reasoning at this level of abstraction and, finally, to support flexible integration of these learning and inference models within an application program. Saul is an object-functional programming language written in Scala that facilitates these by (1) allowing a programmer to learn, name and manipulate named abstractions over relational data; (2) supporting seamless incorporation of trainable (probabilistic or discriminative) components into the program, and (3) providing a level of inference over trainable models to support composition and make decisions that respect domain and application constraints. Saul is developed over a declaratively defined relational data model, can use piecewise learned factor graphs with declaratively specified learning and inference objectives, and it supports inference over probabilistic models augmented with declarative knowledge-based constraints. We describe the key constructs of Saul and exemplify its use in developing applications that require relational feature engineering and structured output prediction.

  5. Music Learning Based on Computer Software

    OpenAIRE

    Baihui Yan; Qiao Zhou

    2017-01-01

    In order to better develop and improve students’ music learning, the authors proposed the method of music learning based on computer software. It is still a new field to use computer music software to assist teaching. Hereby, we conducted an in-depth analysis on the computer-enabled music learning and the music learning status in secondary schools, obtaining the specific analytical data. Survey data shows that students have many cognitive problems in the current music classroom, and yet teach...

  6. Learner Open Modeling in Adaptive Mobile Learning System for Supporting Student to Learn English

    Directory of Open Access Journals (Sweden)

    Van Cong Pham

    2011-10-01

    Full Text Available This paper represents a personalized context-aware mobile learning architecture for supporting student to learn English as foreign language in order to prepare for TOEFL test. We consider how to apply open learner modeling techniques to adapt contents for different learners based on context, which includes location, amount of time to learn, the manner as well as learner's knowledge in learning progress. Through negotiation with system, the editable learner model will be updated to support adaptive engine to select adaptive contents meeting learner's demands. Empirical testing results for students who used application prototype indicate that interaction user modeling is helpful in supporting learner to learn adaptive materials.

  7. Students' learning processes during school-based learning and workplace learning in vocational education : a review

    NARCIS (Netherlands)

    Dr. Harmen Schaap; Dr. Liesbeth Baartman; Prof.Dr. Elly de Bruijn

    2012-01-01

    This article reviews 24 articles in order to get a structured view on student's learning processes when dealing with a combination of school-based learning and workplace learning in vocational education. It focuses on six main themes: students' expertise development, students' learning styles,

  8. The Effects of Concept Map-Oriented Gesture-Based Teaching System on Learners' Learning Performance and Cognitive Load in Earth Science Course

    Science.gov (United States)

    Hsieh, Sheng-Wen; Ho, Shu-Chun; Wu, Min-ping; Ni, Ci-Yuan

    2016-01-01

    Gesture-based learning have particularities, because learners interact in the learning process through the actual way, just like they interact in the nondigital world. It also can support kinesthetic pedagogical practices to benefit learners with strong bodily-kinesthetic intelligence. But without proper assistance or guidance, learners' learning…

  9. Assessing the Success Rate of Students Using a Learning Management System Together with a Collaborative Tool in Web-Based Teaching of Programming Languages

    Science.gov (United States)

    Cavus, Nadire; Ibrahim, Dogan

    2007-01-01

    The development of collaborative studies in learning has led to a renewed interest in the field of Web-based education. In this experimental study a highly interactive and collaborative virtual teaching environment has been created by supporting Moodle LMS with collaborative learning tool GREWPtool. The aim of this experimental study has been to…

  10. The difference between presence-based education and distance learning

    OpenAIRE

    Fernández Rodríguez, Mònica

    2002-01-01

    Attempts to define distance learning always involve comparisons with presence-based education, as the latter is the most direct reference that the former has. It is on this basis that the convergent points, similarities and differences of the two types of approach are established. This article opens with such a comparison, before going on to focus mainly on distance learning and to examine methodological strategies that should be borne in mind when implementing an e-learning system.

  11. Problem-based learning and radiology

    International Nuclear Information System (INIS)

    Thurley, P.; Dennick, R.

    2008-01-01

    The Royal College of Radiologists recently published documents setting out guidelines to improve the teaching of radiology to medical students. These included recommendations that clinicians who teach radiology should be aware of newer educational techniques, such as problem-based learning, and should be involved in the development of curricula and assessment in medical schools. This review aims to introduce the educational theories behind problem-based learning and describe how a problem-based learning tutorial is run. The relevance of problem-based learning to radiology and the potential advantages and disadvantages are discussed

  12. Active Learning of Markov Decision Processes for System Verification

    DEFF Research Database (Denmark)

    Chen, Yingke; Nielsen, Thomas Dyhre

    2012-01-01

    deterministic Markov decision processes from data by actively guiding the selection of input actions. The algorithm is empirically analyzed by learning system models of slot machines, and it is demonstrated that the proposed active learning procedure can significantly reduce the amount of data required...... demanding process, and this shortcoming has motivated the development of algorithms for automatically learning system models from observed system behaviors. Recently, algorithms have been proposed for learning Markov decision process representations of reactive systems based on alternating sequences...... of input/output observations. While alleviating the problem of manually constructing a system model, the collection/generation of observed system behaviors can also prove demanding. Consequently we seek to minimize the amount of data required. In this paper we propose an algorithm for learning...

  13. Distance learning, problem based learning and dynamic knowledge networks.

    Science.gov (United States)

    Giani, U; Martone, P

    1998-06-01

    This paper is an attempt to develop a distance learning model grounded upon a strict integration of problem based learning (PBL), dynamic knowledge networks (DKN) and web tools, such as hypermedia documents, synchronous and asynchronous communication facilities, etc. The main objective is to develop a theory of distance learning based upon the idea that learning is a highly dynamic cognitive process aimed at connecting different concepts in a network of mutually supporting concepts. Moreover, this process is supposed to be the result of a social interaction that has to be facilitated by the web. The model was tested by creating a virtual classroom of medical and nursing students and activating a learning session on the concept of knowledge representation in health sciences.

  14. Merging Problem-Based Learning with Simulation-Based Learning in the Medical Undergraduate Curriculum: The PAIRED Framework for Enhancing Lifelong Learning

    Science.gov (United States)

    Koh, Jansen

    2016-01-01

    Lifelong learning is an essential trait that is expected of every physician. The CanMeds 2005 Physician Competency Framework emphasizes lifelong learning as a key competency that physicians must achieve in becoming better physicians. However, many physicians are not competent at engaging in lifelong learning. The current medical education system is deficient in preparing medical students to develop and carry out their own lifelong learning curriculum upon graduation. Despite understanding how physicians learn at work, medical students are not trained to learn while working. Similarly, although barriers to lifelong learning are known, medical students are not adequately skilled in overcoming these barriers. Learning to learn is just as important, if not more, as acquiring the skills and knowledge required of a physician. The medical undergraduate curriculum lacks a specific learning strategy to prepare medical students in becoming an adept lifelong learner. In this article, we propose a learning strategy for lifelong learning at the undergraduate level. In developing this novel strategy, we paid particular attention to two parameters. First, this strategy should be grounded on literature describing a physician’s lifelong learning process. Second, the framework for implementing this strategy must be based on existing undergraduate learning strategies to obviate the need for additional resources, learner burden, and faculty time. In this paper, we propose a Problem, Analysis, Independent Research Reporting, Experimentation Debriefing (PAIRED) framework that follows the learning process of a physician and serves to synergize the components of problem-based learning and simulation-based learning in specifically targeting the barriers to lifelong learning. PMID:27446767

  15. Repetitive learning control of continuous chaotic systems

    International Nuclear Information System (INIS)

    Chen Maoyin; Shang Yun; Zhou Donghua

    2004-01-01

    Combining a shift method and the repetitive learning strategy, a repetitive learning controller is proposed to stabilize unstable periodic orbits (UPOs) within chaotic attractors in the sense of least mean square. If nonlinear parts in chaotic systems satisfy Lipschitz condition, the proposed controller can be simplified into a simple proportional repetitive learning controller

  16. Expert Students in Social Learning Management Systems

    Science.gov (United States)

    Avogadro, Paolo; Calegari, Silvia; Dominoni, Matteo Alessandro

    2016-01-01

    Purpose: A social learning management system (social LMS) is a tool which favors social interactions and allows scholastic institutions to supervise and guide the learning process. The inclusion of the social feature to a "normal" LMS leads to the creation of educational social networks (EduSN), where the students interact and learn. The…

  17. Student Modelling in Adaptive E-Learning Systems

    Directory of Open Access Journals (Sweden)

    Clemens Bechter

    2011-09-01

    Full Text Available Most e-Learning systems provide web-based learning so that students can access the same online courses via the Internet without adaptation, based on each student's profile and behavior. In an e-Learning system, one size does not fit all. Therefore, it is a challenge to make e-Learning systems that are suitably “adaptive”. The aim of adaptive e-Learning is to provide the students the appropriate content at the right time, means that the system is able to determine the knowledge level, keep track of usage, and arrange content automatically for each student for the best learning result. This study presents a proposed system which includes major adaptive features based on a student model. The proposed system is able to initialize the student model for determining the knowledge level of a student when the student registers for the course. After a student starts learning the lessons and doing many activities, the system can track information of the student until he/she takes a test. The student’s knowledge level, based on the test scores, is updated into the system for use in the adaptation process, which combines the student model with the domain model in order to deliver suitable course contents to the students. In this study, the proposed adaptive e-Learning system is implemented on an “Introduction to Java Programming Language” course, using LearnSquare software. After the system was tested, the results showed positive feedback towards the proposed system, especially in its adaptive capability.

  18. Intrinsically motivated action-outcome learning and goal-based action recall: a system-level bio-constrained computational model.

    Science.gov (United States)

    Baldassarre, Gianluca; Mannella, Francesco; Fiore, Vincenzo G; Redgrave, Peter; Gurney, Kevin; Mirolli, Marco

    2013-05-01

    Reinforcement (trial-and-error) learning in animals is driven by a multitude of processes. Most animals have evolved several sophisticated systems of 'extrinsic motivations' (EMs) that guide them to acquire behaviours allowing them to maintain their bodies, defend against threat, and reproduce. Animals have also evolved various systems of 'intrinsic motivations' (IMs) that allow them to acquire actions in the absence of extrinsic rewards. These actions are used later to pursue such rewards when they become available. Intrinsic motivations have been studied in Psychology for many decades and their biological substrates are now being elucidated by neuroscientists. In the last two decades, investigators in computational modelling, robotics and machine learning have proposed various mechanisms that capture certain aspects of IMs. However, we still lack models of IMs that attempt to integrate all key aspects of intrinsically motivated learning and behaviour while taking into account the relevant neurobiological constraints. This paper proposes a bio-constrained system-level model that contributes a major step towards this integration. The model focusses on three processes related to IMs and on the neural mechanisms underlying them: (a) the acquisition of action-outcome associations (internal models of the agent-environment interaction) driven by phasic dopamine signals caused by sudden, unexpected changes in the environment; (b) the transient focussing of visual gaze and actions on salient portions of the environment; (c) the subsequent recall of actions to pursue extrinsic rewards based on goal-directed reactivation of the representations of their outcomes. The tests of the model, including a series of selective lesions, show how the focussing processes lead to a faster learning of action-outcome associations, and how these associations can be recruited for accomplishing goal-directed behaviours. The model, together with the background knowledge reviewed in the paper

  19. Linear System Control Using Stochastic Learning Automata

    Science.gov (United States)

    Ziyad, Nigel; Cox, E. Lucien; Chouikha, Mohamed F.

    1998-01-01

    This paper explains the use of a Stochastic Learning Automata (SLA) to control switching between three systems to produce the desired output response. The SLA learns the optimal choice of the damping ratio for each system to achieve a desired result. We show that the SLA can learn these states for the control of an unknown system with the proper choice of the error criteria. The results of using a single automaton are compared to using multiple automata.

  20. Micro Learning: A Modernized Education System

    Directory of Open Access Journals (Sweden)

    Omer Jomah

    2016-03-01

    Full Text Available Learning is an understanding of how the human brain is wired to learning rather than to an approach or a system. It is one of the best and most frequent approaches for the 21st century learners. Micro learning is more interesting due to its way of teaching and learning the content in a small, very specific burst. Here the learners decide what and when to learn. Content, time, curriculum, form, process, mediality, and learning type are the dimensions of micro learning. Our paper will discuss about micro learning and about the micro-content management system. The study will reflect the views of different users, and will analyze the collected data. Finally, it will be concluded with its pros and cons. 

  1. Measuring Learner's Performance in E-Learning Recommender Systems

    Science.gov (United States)

    Ghauth, Khairil Imran; Abdullah, Nor Aniza

    2010-01-01

    A recommender system is a piece of software that helps users to identify the most interesting and relevant learning items from a large number of items. Recommender systems may be based on collaborative filtering (by user ratings), content-based filtering (by keywords), and hybrid filtering (by both collaborative and content-based filtering).…

  2. YF22 Model With On-Board On-Line Learning Microprocessors-Based Neural Algorithms for Autopilot and Fault-Tolerant Flight Control Systems

    National Research Council Canada - National Science Library

    Napolitano, Marcello

    2002-01-01

    This project focused on investigating the potential of on-line learning 'hardware-based' neural approximators and controllers to provide fault tolerance capabilities following sensor and actuator failures...

  3. Multimedia Based E-learning : Design and Integration of Multimedia Content in E-learning

    Directory of Open Access Journals (Sweden)

    Abdulaziz Omar Alsadhan

    2014-05-01

    Full Text Available The advancement in multimedia and information technologies also have impacted the way of imparting education. This advancement has led to rapid use of e learning systems and has enabled greater integration of multimedia content into e learning systems. This paper present a model for development of e learning systems based on multimedia content. The model is called “Multimedia based e learning” and is loosely based on waterfall software development model. This model consists of three distinct phases; Multimedia Content Modelling, Multimedia content Development, Multimedia content Integration. These three phases are further sub divided into 7 different activities which are analysis, design, technical requirements, content development, content production & integration, implementation and evaluation. This model defines a general framework that can be applied for the development of e learning systems across all disciplines and subjects.

  4. A Learning Object Approach To Evidence based learning

    OpenAIRE

    Zabin Visram; Bruce Elson; Patricia Reynolds

    2005-01-01

    This paper describes the philosophy, development and framework of the body of elements formulated to provide an approach to evidence-based learning sustained by Learning Objects and web based technology Due to the demands for continuous improvement in the delivery of healthcare and in the continuous endeavour to improve the quality of life, there is a continuous need for practitioner's to update their knowledge by accomplishing accredited courses. The rapid advances in medical science has mea...

  5. Project- Based Learning and Problem-Based Learning: Are They Effective to Improve Student's Thinking Skills?

    OpenAIRE

    Anazifa, R. D; Djukri, D

    2017-01-01

    The study aims at finding (1) the effect of project-based learning and problem-based learning on student's creativity and critical thinking and (2) the difference effect of project-based learning and problem-based learning on student's creativity and critical thinking. This study is quasi experiment using non-equivalent control-group design. Research population of this study was all classes in eleventh grade of mathematics and natural science program of SMA N 1 Temanggung. The participants we...

  6. Comparing Learning Outcomes of Video-Based E-Learning with Face-to-Face Lectures of Agricultural Engineering Courses in Korean Agricultural High Schools

    Science.gov (United States)

    Park, Sung Youl; Kim, Soo-Wook; Cha, Seung-Bong; Nam, Min-Woo

    2014-01-01

    This study investigated the effectiveness of e-learning by comparing the learning outcomes in conventional face-to-face lectures and e-learning methods. Two video-based e-learning contents were developed based on the rapid prototyping model and loaded onto the learning management system (LMS), which was available at http://www.greenehrd.com.…

  7. Simulation and case-based learning

    DEFF Research Database (Denmark)

    Ørngreen, Rikke; Guralnick, David

    2008-01-01

    Abstract- This paper has its origin in the authors' reflection on years of practical experiences combined with literature readings in our preparation for a workshop on learn-by-doing simulation and case-based learning to be held at the ICELW 2008 conference (the International Conference on E-Learning...... in the Workplace). The purpose of this paper is to describe the two online learning methodologies and to raise questions for future discussion. In the workshop, the organizers and participants work with and discuss differences and similarities within the two pedagogical methodologies, focusing on how...... they are applied in workplace related and e-learning contexts. In addition to the organizers, a small number of invited presenters will attend, giving demonstrations of their work within learn-by-doing simulation and cases-based learning, but still leaving ample of time for discussion among all participants....

  8. PERANCANGAN WEB BASED LEARNING SEBAGAI MEDIA PEMBELAJARAN BERBASIS ICT

    Directory of Open Access Journals (Sweden)

    Ricky Firmansyah

    2016-09-01

    Full Text Available ABSTRACT The media is very important component of communication process. The effectiveness of media is very influential on extent to which a communication role will be accepted by the audience with fast and precise, or vice versa. E-Learning is present as ICT based learning media that allows students and teachers interact in different places. Web Based Learning (WBL is used as one part of the E-Learning. This study focuses on designing web-based ICT as a learning medium that is used for students and teacher interaction media that equipped with learning material in content form that will be delivered. Students can learn about learning materials that submitted by teachers through the website anytime and anywhere as long as internet access is available, including taking a test in accordance with the time specified by the teacher. Waterfall method is used as a system development method implemented using the server-side web programming scripting like PHP MySQL. After using the system, questionnaire survey conducted on students and teachers. The results from this study is 71% of the number of students who complete the survey claimed that the system is easy and fun to use and 68% of the number of teachers who complete the survey claimed that this system is very assist with their work, especially in managing test scores. Keywords: design, e-learni

  9. Learning and the Instructional System

    Science.gov (United States)

    Kozma, Robert B.

    1977-01-01

    Faculty members can use information about six components of the learning situation to increase student learning. The nature, function, and interrelationships of the following elements are described: instructor, content, medium, student, evaluation, environment, and implementation. (Editor/LBH)

  10. The Development of a Robot-Based Learning Companion: A User-Centered Design Approach

    Science.gov (United States)

    Hsieh, Yi-Zeng; Su, Mu-Chun; Chen, Sherry Y.; Chen, Gow-Dong

    2015-01-01

    A computer-vision-based method is widely employed to support the development of a variety of applications. In this vein, this study uses a computer-vision-based method to develop a playful learning system, which is a robot-based learning companion named RobotTell. Unlike existing playful learning systems, a user-centered design (UCD) approach is…

  11. E-learning systems intelligent techniques for personalization

    CERN Document Server

    Klašnja-Milićević, Aleksandra; Ivanović, Mirjana; Budimac, Zoran; Jain, Lakhmi C

    2017-01-01

    This monograph provides a comprehensive research review of intelligent techniques for personalisation of e-learning systems. Special emphasis is given to intelligent tutoring systems as a particular class of e-learning systems, which support and improve the learning and teaching of domain-specific knowledge. A new approach to perform effective personalization based on Semantic web technologies achieved in a tutoring system is presented. This approach incorporates a recommender system based on collaborative tagging techniques that adapts to the interests and level of students' knowledge. These innovations are important contributions of this monograph. Theoretical models and techniques are illustrated on a real personalised tutoring system for teaching Java programming language. The monograph is directed to, students and researchers interested in the e-learning and personalization techniques. .

  12. Towards a Pattern Language for Learning Management Systems

    NARCIS (Netherlands)

    Avgeriou, Paris; Papasalouros, Andreas; Retalis, Symeon; Skordalakis, Manolis

    2003-01-01

    Learning Management Systems are sophisticated web-based applications that are being engineered today in increasing numbers by numerous institutions and companies that want to get involved in e-learning either for providing services to third parties, or for educating and training their own people.

  13. Energy and carbon emissions analysis and prediction of complex petrochemical systems based on an improved extreme learning machine integrated interpretative structural model

    International Nuclear Information System (INIS)

    Han, Yongming; Zhu, Qunxiong; Geng, Zhiqiang; Xu, Yuan

    2017-01-01

    Highlights: • The ELM integrated ISM (ISM-ELM) method is proposed. • The proposed method is more efficient and accurate than the ELM through the UCI data set. • Energy and carbon emissions analysis and prediction of petrochemical industries based ISM-ELM is obtained. • The proposed method is valid in improving energy efficiency and reducing carbon emissions of ethylene plants. - Abstract: Energy saving and carbon emissions reduction of the petrochemical industry are affected by many factors. Thus, it is difficult to analyze and optimize the energy of complex petrochemical systems accurately. This paper proposes an energy and carbon emissions analysis and prediction approach based on an improved extreme learning machine (ELM) integrated interpretative structural model (ISM) (ISM-ELM). ISM based the partial correlation coefficient is utilized to analyze key parameters that affect the energy and carbon emissions of the complex petrochemical system, and can denoise and reduce dimensions of data to decrease the training time and errors of the ELM prediction model. Meanwhile, in terms of the model accuracy and the training time, the robustness and effectiveness of the ISM-ELM model are better than the ELM through standard data sets from the University of California Irvine (UCI) repository. Moreover, a multi-inputs and single-output (MISO) model of energy and carbon emissions of complex ethylene systems is established based on the ISM-ELM. Finally, detailed analyses and simulations using the real ethylene plant data demonstrate the effectiveness of the ISM-ELM and can guide the improvement direction of energy saving and carbon emissions reduction in complex petrochemical systems.

  14. Problem-Based Learning Approaches in Meteorology

    Science.gov (United States)

    Charlton-Perez, Andrew James

    2013-01-01

    Problem-Based Learning, despite recent controversies about its effectiveness, is used extensively as a teaching method throughout higher education. In meteorology, there has been little attempt to incorporate Problem-Based Learning techniques into the curriculum. Motivated by a desire to enhance the reflective engagement of students within a…

  15. Personalised learning object based on multi-agent model and learners’ learning styles

    Directory of Open Access Journals (Sweden)

    Noppamas Pukkhem

    2011-09-01

    Full Text Available A multi-agent model is proposed in which learning styles and a word analysis technique to create a learning object recommendation system are used. On the basis of a learning style-based design, a concept map combination model is proposed to filter out unsuitable learning concepts from a given course. Our learner model classifies learners into eight styles and implements compatible computational methods consisting of three recommendations: i non-personalised, ii preferred feature-based, and iii neighbour-based collaborative filtering. The analysis of preference error (PE was performed by comparing the actual preferred learning object with the predicted one. In our experiments, the feature-based recommendation algorithm has the fewest PE.

  16. Learning outcomes between Socioscientific Issues-Based Learning and Conventional Learning Activities

    OpenAIRE

    Piyaluk Wongsri; Prasart Nuangchalerm

    2010-01-01

    Problem statement: Socioscientific issues-based learning activity is essential for scientific reasoning skills and it could be used for analyzing problems be applied to each situation for more successful and suitable. The purposes of this research aimed to compare learning achievement, analytical thinking and moral reasoning of seventh grade students who were organized between socioscientific issues-based learning and conventional learning activities. Approach: The samples used in research we...

  17. ADMultiImg: a novel missing modality transfer learning based CAD system for diagnosis of MCI due to AD using incomplete multi-modality imaging data

    Science.gov (United States)

    Liu, Xiaonan; Chen, Kewei; Wu, Teresa; Weidman, David; Lure, Fleming; Li, Jing

    2018-02-01

    Alzheimer's Disease (AD) is the most common cause of dementia and currently has no cure. Treatments targeting early stages of AD such as Mild Cognitive Impairment (MCI) may be most effective to deaccelerate AD, thus attracting increasing attention. However, MCI has substantial heterogeneity in that it can be caused by various underlying conditions, not only AD. To detect MCI due to AD, NIA-AA published updated consensus criteria in 2011, in which the use of multi-modality images was highlighted as one of the most promising methods. It is of great interest to develop a CAD system based on automatic, quantitative analysis of multi-modality images and machine learning algorithms to help physicians more adequately diagnose MCI due to AD. The challenge, however, is that multi-modality images are not universally available for many patients due to cost, access, safety, and lack of consent. We developed a novel Missing Modality Transfer Learning (MMTL) algorithm capable of utilizing whatever imaging modalities are available for an MCI patient to diagnose the patient's likelihood of MCI due to AD. Furthermore, we integrated MMTL with radiomics steps including image processing, feature extraction, and feature screening, and a post-processing for uncertainty quantification (UQ), and developed a CAD system called "ADMultiImg" to assist clinical diagnosis of MCI due to AD using multi-modality images together with patient demographic and genetic information. Tested on ADNI date, our system can generate a diagnosis with high accuracy even for patients with only partially available image modalities (AUC=0.94), and therefore may have broad clinical utility.

  18. Adaptive Hypermedia Systems for E-Learning

    Directory of Open Access Journals (Sweden)

    Aammou Souhaib

    2010-11-01

    Full Text Available The domain of traditional hypermedia is revolutionized by the arrival of the concept of adaptation. Currently the domain of Adaptive Hypermedia Systems (AHS is constantly growing. A major goal of current research is to provide a personalized educational experience that meets the needs specific to each learner (knowledge level, goals, motivation etc.... In this article we have studied the possibility of implementing traditional features of adaptive hypermedia in an open environment, and discussed the standards for describing learning objects and architectural models based on the use of ontologies as a prerequisite for such an adaptation.

  19. Assessing E-Learning System in Higher Education Institutes: Evidence from Structural Equation Modelling

    Science.gov (United States)

    Ali, Muhammad; Raza, Syed Ali; Qazi, Wasim; Puah, Chin-Hong

    2018-01-01

    Purpose: This study aims to examine university students' acceptance of e-learning systems in Pakistan. A Web-based learning system is a new form of utilizing technological features. Although, developed countries have initiated and established the concept for e-learning, developing countries require empirical support to implement e-learning.…

  20. What is the future of work based learning in VET?

    DEFF Research Database (Denmark)

    Jørgensen, Christian Helms

    not to pursue an academic career. Countries with strong apprenticeship systems tend to have less youth unemployment and a smoother transition to the labour market than others. Furthermore, from a learning perspective, the outcomes of work-based training and informal learning are enhanced when they are combined...... that question the future role and organisation of work-based training in VET. The purpose of this paper is to examine these challenges based on a review of research on European VET systems and analyses of the Danish dual system of VET. In the end of the paper, some innovative solutions to these challenges...