WorldWideScience

Sample records for adaptive reuse learning

  1. 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…

  2. Learning for design reuse

    DEFF Research Database (Denmark)

    Duffy, Alex; Duffy, Sandra M.

    1996-01-01

    Over the past decade "design assistance", that is, where the computer is viewed as an Intelligent Design Assistant (IDA), has emerged in knowledge based design support and has formed the basic research strategy for the CAD Cantre, University of Strathclyde, since the mid-1980s. Within...... this philosophy, an IDA would act as a colleague to a designer, providing guidance, learning from past experiences, carrying out semi- and fully-automated tasks, explaining its reasoning and in essence complementing the designer's own natural skills, and thus leaving the ultimate decision-making, control......, and responsibility with the designer.The ability to learn and evolve has been recognized as one of the key components of an IDA for it to fully support the designer's activities. Consequently, we have been directing our research effort on two main fronts, formalizing our understanding and developing models...

  3. Learning for design reuse

    DEFF Research Database (Denmark)

    Duffy, Alex; Duffy, Sandra M.

    1996-01-01

    Over the past decade "design assistance", that is, where the computer is viewed as an Intelligent Design Assistant (IDA), has emerged in knowledge based design support and has formed the basic research strategy for the CAD Cantre, University of Strathclyde, since the mid-1980s. Within this philos......Over the past decade "design assistance", that is, where the computer is viewed as an Intelligent Design Assistant (IDA), has emerged in knowledge based design support and has formed the basic research strategy for the CAD Cantre, University of Strathclyde, since the mid-1980s. Within...... this philosophy, an IDA would act as a colleague to a designer, providing guidance, learning from past experiences, carrying out semi- and fully-automated tasks, explaining its reasoning and in essence complementing the designer's own natural skills, and thus leaving the ultimate decision-making, control...

  4. Quantifying the Reuse of Learning Objects

    Science.gov (United States)

    Elliott, Kristine; Sweeney, Kevin

    2008-01-01

    This paper reports the findings of one case study from a larger project, which aims to quantify the claimed efficiencies of reusing learning objects to develop e-learning resources. The case study describes how an online inquiry project "Diabetes: A waste of energy" was developed by searching for, evaluating, modifying and then…

  5. Creating by Reusing Learning Design Solutions

    NARCIS (Netherlands)

    Hernández-Leo, Davinia; Harrer, Andreas; Dodero, Juan Manuel; Asensio-Pérez, Juan; Burgos, Daniel

    2006-01-01

    Hernández-Leo, D., Harrer, A., Dodero, J. M., Asension-Pérez, J. I., & Burgos, D. (2006). Creating by reusing Learning Design solutions. Proceedings of 8th Simposo Internacional de Informática Educativa, León, Spain: IEEE Technical Committee on Learning Technology. Retrieved October 3rd, 2006, from

  6. Reuse of Digital Learning Resources in Collaborative Learning Environments

    OpenAIRE

    2006-01-01

    PhD thesis; With background in the proliferation of Information- and Communication Technologies (ICTs) in educational institutions, there is a growing interest in deploying ICT that complies with specifications and standards for learning technologies in these institutions. A key to obtaining the benefits of cost-efficiency and quality that motivate this interest is reuse of digital learning resources. Despite the significant efforts being made in design and deployment of learning technology s...

  7. A Workflow for Learning Objects Lifecycle and Reuse: Towards Evaluating Cost Effective Reuse

    Science.gov (United States)

    Sampson, Demetrios G.; Zervas, Panagiotis

    2011-01-01

    Over the last decade Learning Objects (LOs) have gained a lot of attention as a common format for developing and sharing digital educational content in the field of technology-enhanced learning. The main advantage of LOs is considered to be their potential for component-based reuse in different learning settings supporting different learning…

  8. Strategies for Reuse of Learning Objects: Context Dimensions

    Science.gov (United States)

    Strijker, Allard; Collis, Betty

    2006-01-01

    Based on research in ten projects in a university, corporate learning, and military context, a set of dimensions is found that can help decision makers to develop strategies for reuse (Strijker, 2004). This article describes how these dimensions and their relation with human and technical aspects can be used in a reuse strategy. The dimensions can…

  9. Conservation and adaptive reuse of industrial heritage in Shanghai

    Institute of Scientific and Technical Information of China (English)

    ZHANG Song

    2007-01-01

    This paper takes a retrospective review of the evolution of the conservation of industrial heritage in urban Shanghai since the 1990s within the context of the international industrial heritage conservation movement,with the emphasis on the construction of preservation systems,technical regulation compilation and conservation practice.Active conservation and adaptive reuse is the focus within the framework of the conservation of the architectural characteristics of industrial buildings and the townscape of industrial districts.

  10. Variance Analysis and Adaptive Sampling for Indirect Light Path Reuse

    Institute of Scientific and Technical Information of China (English)

    Hao Qin; Xin Sun; Jun Yan; Qi-Ming Hou; Zhong Ren; Kun Zhou

    2016-01-01

    In this paper, we study the estimation variance of a set of global illumination algorithms based on indirect light path reuse. These algorithms usually contain two passes — in the first pass, a small number of indirect light samples are generated and evaluated, and they are then reused by a large number of reconstruction samples in the second pass. Our analysis shows that the covariance of the reconstruction samples dominates the estimation variance under high reconstruction rates and increasing the reconstruction rate cannot effectively reduce the covariance. We also find that the covariance represents to what degree the indirect light samples are reused during reconstruction. This analysis motivates us to design a heuristic approximating the covariance as well as an adaptive sampling scheme based on this heuristic to reduce the rendering variance. We validate our analysis and adaptive sampling scheme in the indirect light field reconstruction algorithm and the axis-aligned filtering algorithm for indirect lighting. Experiments are in accordance with our analysis and show that rendering artifacts can be greatly reduced at a similar computational cost.

  11. Reuse of Learning Objects in Context: Technical and Human Aspects.

    NARCIS (Netherlands)

    Strijker, A.

    2004-01-01

    This dissertation focuses on the application of learning technology standards for learning objects and the differences in reuse in university, corporate, and military contexts. This is addressed from two different perspectives: the technology involving learning objects and the human aspects that

  12. Technology and human issues in reusing learning objects

    NARCIS (Netherlands)

    Collis, Betty; Strijker, Allard

    2004-01-01

    Reusing learning objects is as old as retelling a story or making use of libraries and textbooks, and in electronic form has received an enormous new impetus because of the World Wide Web and Web technologies. Are we at the brink of changing the "shape and form of learning, ... of being able to trul

  13. Technology and Human Issues in Reusing Learning Objects.

    NARCIS (Netherlands)

    Collis, Betty; Strijker, Allard

    2004-01-01

    Reusing learning objects is as old as retelling a story or making use of libraries and textbooks, and in electronic form has received an enormous new impetus because of the World Wide Web and Web technologies. Are we at the brink of changing the "shape and form of learning, ... of being able to trul

  14. The Language of Flexible Reuse; Reuse, Portability and Interoperability of Learning Content or Why an Educational Modelling Language

    NARCIS (Netherlands)

    Sloep, Peter

    2003-01-01

    Sloep, P.B. (2004). Reuse, Portability and Interoperability of Learning Content: Or Why an Educational Modelling Language. In R. McGreal, (Ed.), Online Education Using Learning Objects (pp. 128-137). London: Routledge/Falmer.

  15. Personalized Adaptive Learning

    NARCIS (Netherlands)

    Kravcik, Milos; Specht, Marcus; Naeve, Ambjorn

    2009-01-01

    Kravcik, M., Specht, M., & Naeve, A. (2008). Personalized Adaptive Learning. Presentation of PROLEARN WP1 Personalized Adaptive Learning at the final review meeting. February, 27, 2008, Hannover, Germany.

  16. Adaptive Re-Use Principles in Historic Hotel Buildings in Melaka And George Town

    Directory of Open Access Journals (Sweden)

    Ab Wahab Lilawati

    2016-01-01

    Full Text Available Adaptive re-use of historic buildings is a process of changing the original function of the historic buildings to another function that can optimise the use of existing historic buildings. The selection of appropriate new function is an important factor in determining the success of adaptive re-use of historic buildings. However, adaptive re-use work done on historic buildings on the World Heritage Site is not an easy task due to rules and principles outlined by local and international charters that must be abide by. This research is conducted to gather the true picture of applied adaptive re-use principles that has been done on heritage hotels available in Melaka and George Town World Heritage Sites. This research is started with an inventory that led to the discovery of 35 hotels which applied the principle of adaptive re-use of historic buildings. Based on this finding, 4 historic hotels from adaptive re-use applications have been selected as the case studies. Results of the case studies carried out show that the level of conservation of heritage hotel is moderate and measures of control should be taken to ensure the privileges of heritage hotel. As a result of this research, a number of suggestions are made to ensure that adaptive re-use work done in the future will be conducted as optimum as possible according to the adaptive re-use and conservation principles.

  17. Reusing open data for learning database design through project development

    Directory of Open Access Journals (Sweden)

    Jose-Norberto MAZÓN

    2015-12-01

    Full Text Available This paper describes a novel methodology based on reusing open data for applying project-based learning in a Database Design subject of a university degree. This methodology is applied to the ARA (Alto Rendimiento Académico or High Academic Performance group taught in the degree in Computer Engineering at the University of Alicante (Spain during 2012/2013, 2013/2014, and 2014/2015. Openness philosophy implies that huge amount of data is available to students in tabular format, ready for reusing. In our teaching experience, students propose an original scenario where different open data can be reused to a specific goal. Then, it is proposed to design a database in order to manage this data in the envisioned scenario. Open data in the subject helps in instilling a creative and entrepreneur attitude in students, as well as encourages autonomous and lifelong learning. Surveys made to students at the end of each year shown that reusing open data within project-based learning methodologies makes more motivated students since they are using real data.

  18. Adaptive learning in moodle: three practical cases

    Directory of Open Access Journals (Sweden)

    Dolores LERÍS LÓPEZ

    2015-12-01

    Full Text Available One of the most important challenges that the education will have to face is the need to adapt the learning process to the student’s characteristics. Nowadays it is still noticed the weak technological support and the few personalised learning practices. Two main types of e-learning platforms have been developed for last years: Learning Management Systems (LMS and Adaptive Educational Hypermedia Systems. Both lines of development are converging so that the new versions of the LMS incorporate adaptive capacities that are allowing to design individualized or differentiated instruction. In this paper the adaptive functionalities available in Moodle are checked. It is explained how to implement three adaptive instructional designs in Moodle. Moreover, it is checked their effectiveness, in terms of the learning achieved by the student, and their efficiency, by reusing materials of previous learning experiences.

  19. A meta level to LAG for adaptation language re-use

    OpenAIRE

    Hendrix, Maurice; Cristea, Alexandra I.

    2008-01-01

    Recently, a growing body of research targets authoring of content and adaptation strategies for adaptive systems. The driving force behind it is semantics-based reuse: the same adaptation strategy can be used for various domains, and vice versa. E.g., a Java course can be taught via a strategy differentiating between beginner and advanced users, or between visual versus verbal users. Whilst using an Adaptation Language (LAG) to express reusable adaptation strategies, we noticed, however, that...

  20. Guidelines for Supporting Re-Use of Existing Digital Learning Materials and Methods in Higher Education

    Science.gov (United States)

    Schoonenboom, Judith; Sligte, Henk; Kliphuis, Eja

    2009-01-01

    The literature on the re-use of learning materials has largely focused on the development of materials. This paper explores how re-use can be stimulated after learning materials have been developed and made available. We searched for and developed guidelines that support staff and/or management most frequently adopt in cases of (un)successful…

  1. Guidelines for Supporting Re-Use of Existing Digital Learning Materials and Methods in Higher Education

    Science.gov (United States)

    Schoonenboom, Judith; Sligte, Henk; Kliphuis, Eja

    2009-01-01

    The literature on the re-use of learning materials has largely focused on the development of materials. This paper explores how re-use can be stimulated after learning materials have been developed and made available. We searched for and developed guidelines that support staff and/or management most frequently adopt in cases of (un)successful…

  2. Adaptive Learning Management System

    Directory of Open Access Journals (Sweden)

    Violeta Moisa

    2013-06-01

    Full Text Available This article is an introduction to a new model for an adaptive Learning Management System. It presents the current e-learning standards and describes the elements that can be used to create the system: the sequencing control modes, sequencing rules, navigation controls, learning records and learning record stores. The model is based on artificial intelligent algorithms that analyze the data captured for each user and creates an adaptive navigation path through the learning content of the system, allowing each user to experience the content in different ways

  3. Transdisciplinary Pedagogical Templates and Their Potential for Adaptive Reuse

    Science.gov (United States)

    Dobozy, Eva; Dalziel, James

    2016-01-01

    This article explores the use and usefulness of carefully designed transdisciplinary pedagogical templates (TPTs) aligned to different learning theories. The TPTs are based on the Learning Design Framework outlined in the Larnaca Declaration (Dalziel et al. in this collection). The generation of pedagogical plans or templates is not new. However,…

  4. The adaptive reuse of historic city centres. Bologna and Lisbon: solutions for urban regeneration

    Directory of Open Access Journals (Sweden)

    Andrea Boeri

    2016-11-01

    Full Text Available The European historic city centres are currently experiencing innovative approaches for rehabilitation of urban spaces afflicted by social and physical decay. The revitalization challenges are a consequence of the integration of contemporary technologies and solutions to achieve new requirements and of the impacts of socio-economic dynamics. Understanding and boosting the drivers connected to the cultural potential of the historic city centres can play an important role in adaptive re-use. This paper focuses on the synergy between cultural heritage and urban development, cultural heritage preservation and local economic growth, proposing adaptive reuse design practices applied in historic city centre, through the adoption of a multi-criteria methodology for heritage-led regeneration.

  5. Adaptive reuse in the healthcare industry: repurposing abandoned buildings to serve medical missions.

    Science.gov (United States)

    Elrod, James K; Fortenberry, John L

    2017-07-11

    Adaptive reuse-the practice of identifying, acquiring, renovating, and placing back into service a building or similar structure for a purpose different than that for which it was originally designed-offers great potential for addressing the spatial expansion needs of healthcare establishments in a unique and mutually beneficial manner. This repurposing approach, however, has received very little attention in the health sciences literature, diminishing the opportunities of those serving in hospitals, medical clinics, and related care providing institutions to acquire an understanding of the practice. The delivery of healthcare services primarily is site based, requiring physical space for physicians, nurses, administrators, and others to carry out the many duties associated with the provision of medical care and attention. But this space often represents a significant expenditure, consuming financial resources which otherwise could be directed toward patient care. Economies on this front are possible through adaptive reuse, permitting more resources to be directed toward mission fulfillment activities. This article directs attention toward adaptive reuse by profiling Willis-Knighton Health System's associated experiences and implementation strategies. Among other things, opportunities and obstacles are discussed, detailed cases are presented, and an operational framework is provided, permitting healthcare providers to understand and make use of this novel practice for addressing spatial expansion needs more affordably. Since space considerations exist throughout the lives of healthcare establishments, providers must ensure an awareness of methods for productively attending to these requirements. Evidenced by Willis-Knighton Health System's associated experiences and outcomes, adaptive reuse presents an option for more economically addressing spatial requirements, fostering opportunities to expand the delivery of health and medical services.

  6. Advanced Technology for the Re-use of Learning Objects in a Course Management System

    NARCIS (Netherlands)

    Strijker, A.; Collis, B.A.

    2005-01-01

    The creation, labelling, use, and re-use of learning objects is an important area of development involving learning technology. In the higher education context, instructors typically use a course management system (CMS) to organize and manage their own learning objects. The needs and practices of in

  7. Adaptive manifold learning.

    Science.gov (United States)

    Zhang, Zhenyue; Wang, Jing; Zha, Hongyuan

    2012-02-01

    Manifold learning algorithms seek to find a low-dimensional parameterization of high-dimensional data. They heavily rely on the notion of what can be considered as local, how accurately the manifold can be approximated locally, and, last but not least, how the local structures can be patched together to produce the global parameterization. In this paper, we develop algorithms that address two key issues in manifold learning: 1) the adaptive selection of the local neighborhood sizes when imposing a connectivity structure on the given set of high-dimensional data points and 2) the adaptive bias reduction in the local low-dimensional embedding by accounting for the variations in the curvature of the manifold as well as its interplay with the sampling density of the data set. We demonstrate the effectiveness of our methods for improving the performance of manifold learning algorithms using both synthetic and real-world data sets.

  8. Sharing and Adaptation of Educational Documents in E-Learning

    Directory of Open Access Journals (Sweden)

    Chekry Abderrahman

    2012-03-01

    Full Text Available Few documents can be reused among the huge number of the educational documents on the web. The exponential increase of these documents makes it almost impossible to search for relevant documents. In addition to this, e-learning is designed for public users who have different levels of knowledge and varied skills so they should be given a content that sees to their needs. This work is about adapting the content of learning with learners preferences, and give the teachers the ability to reuse a given content.

  9. Shared Learning: Feminist Student Research on Household Reuse Behavior

    Science.gov (United States)

    Medley, Kimberly E.; Zhou, Ying; Condon, Darcy

    2006-01-01

    This paper describes collaborative student research on waste management that first compiled home interviews with women professors in Oxford, Ohio, USA, and Beijing, China, on household reuse for a graduate thesis and then communicated the findings in a handbook for undergraduate students. The women participants described diverse household reuse…

  10. Reuse as Heuristic: From Transmission to Nurture in Learning Activity Design

    Science.gov (United States)

    Sweet, John; Ellaway, Rachel

    2010-01-01

    In recent years a combination of ever more flexible and sophisticated Web technologies and an explosion in the quantity of online content has sparked learning technologists around the world to pursue the promise of the "reusable learning object" or RLO with the idea that RLOs could be reused in different educational contexts, thereby…

  11. Investigation on Adaptive Re-use of Heritage Building in George Town, Penang

    Directory of Open Access Journals (Sweden)

    Marhamah Abdul Hadi

    2013-09-01

    Full Text Available Adaptive re-use of heritage buildings in George Town has gained attention from their owners. Their owners either private owners or government, want to adapt their respective buildings to new usage for instance to become a gallery, museum, restaurant, boutique hotel and many more. Every heritage building that is being adapted to paper main objective is to identify the changes made in terms of structure, space and material when adapting the heritage buildings to a new usage specifically into a gallery. Two heritage buildings are chosen as case studies for this paper which are Rumah Teh Bunga and Fort Cornwallis; both buildings located in Penang, Malaysia. The changes made to these two buildings were analyzed using the guidelines provided which are Guideline for Conservation areas and Heritage Buildings and National Heritage Acts 2005. Both buildings will be analyzed using National Heritage Acts, while only Fort Cornwallis will be analyzed using Guideline for Conservation areas and Heritage Buildings. Adaptation of these two heritage buildings requires changes in structure, space and material. The changes in Rumah Teh Bunga focuses more on materials and space while changes in Fort Cornwallis emphasize more to space and addition of other structures. Analysis on the changes are made by using the guideline provided, most of the changes made to both of these heritage buildings comply the rules and regulations stated in the guideline. It was found from the data that some of the reasons on why the owner change Rumah Teh Bunga to gallery are because of its complicated procedure that involves in privatization of this building to other owner and the need to promote the heritage significance of this building to the public. As for Fort Cornwallis, the adaptation is more on strengthening its value as a fort and becoming a tourist attraction.

  12. Blogs: Learning through Using and Reusing Authentic Materials

    Science.gov (United States)

    Coppens, Julian; Rico, Mercedes; Agudo, J. Enrique

    2012-01-01

    Language learning and acquisition requires exposure to a language whether in a formal or informal learning environment as well as opportunities to produce the target language in a meaningful context. Therefore, it is unsurprising that the development of tools and web-based applications that allow written, audio, visual, and audio-visual material…

  13. ADAPTIVE REUSE FOR NEW SOCIAL AND MUNICIPAL FUNCTIONS AS AN ACCEPTABLE APPROACH FOR CONSERVATION OF INDUSTRIAL HERITAGE ARCHITECTURE IN THE CZECH REPUBLIC

    Directory of Open Access Journals (Sweden)

    Oleg Fetisov

    2016-04-01

    Full Text Available The present paper deals with a problem of conservation and adaptive reuse of industrial heritage architecture. The relevance and topicality of the problem of adaptive reuse of industrial heritage architecture for new social and municipal functions as the conservation concept are defined. New insights on the typology of industrial architecture are reviewed (e. g. global changes in all European industry, new concepts and technologies in manufacturing, new features of industrial architecture and their construction and typology, first results of industrialization and changes in the typology of industrial architecture in post-industrial period. General goals and tasks of conservation in context of adaptive reuse of industrial heritage architecture are defined (e. g. historical, architectural and artistic, technical. Adaptive reuse as an acceptable approach for conservation and new use is proposed and reviewed. Moreover, the logical model of adaptive reuse of industrial heritage architecture as an acceptable approach for new use has been developed. Consequently, three general methods for the conservation of industrial heritage architecture by the adaptive reuse approach are developed: historical, architectural and artistic, technical. Relevant functional methods' concepts (social concepts are defined and classified. General beneficial effect of the adaptive reuse approach is given. On the basis of analysis results of experience in adaptive reuse of industrial architecture with new social functions general conclusions are developed.

  14. E-learning Materials Development: Applying and Implementing Software Reuse Principles and Granularity Levels in the Small

    OpenAIRE

    Nabil Arman,

    2010-01-01

    E-learning materials development is typically acknowledged as an expensive, complicated, and lengthy process, often producing materials that are of low quality and difficult to adaptand maintain. It has always been a challenge to identify proper e-learning materials that can be reused at a reasonable cost and effort. In this paper, software engineering reuse principlesare applied to e-learning materials development process. These principles are then applied and implemented in a prototype that...

  15. E-learning Materials Development: Applying and Implementing Software Reuse Principles and Granularity Levels in the Small

    Directory of Open Access Journals (Sweden)

    Nabil Arman

    2010-06-01

    Full Text Available E-learning materials development is typically acknowledged as an expensive, complicated, and lengthy process, often producing materials that are of low quality and difficult to adaptand maintain. It has always been a challenge to identify proper e-learning materials that can be reused at a reasonable cost and effort. In this paper, software engineering reuse principlesare applied to e-learning materials development process. These principles are then applied and implemented in a prototype that is integrated with an open-source course management systems. The reuse of existing e-learning materials is beneficial in improving developers of elearning materials productivity. E-learning material reuse is performed, in this research, based on construct’s granularity rather than on unified constructs of one size.

  16. Conservation and adaptive-reuse of historical industrial building in China in the post-industrial era

    Institute of Scientific and Technical Information of China (English)

    WANG Jianguo; JIANG Nan

    2007-01-01

    The conservation and adaptive-rense of historical industrial building is one of the most important issues to be solved in today's urban development and construction in China.In this paper,the necessity and academic meaning of the conservation and adaptive-reuse of historical industrial building were discussed by reviewing its development rend both at home and abroad,and the basic contents of the implementation of the conservation and adaptive-reuse of historical industrial building in China with specific cases provided were analyzed.It is the central task for China to put forward the restructuring and design methods,assessment principles and relevant core technical specifications based on the empirical researches on the historical industrial building and site.

  17. Adaptive representations for reinforcement learning

    NARCIS (Netherlands)

    Whiteson, S.

    2010-01-01

    This book presents new algorithms for reinforcement learning, a form of machine learning in which an autonomous agent seeks a control policy for a sequential decision task. Since current methods typically rely on manually designed solution representations, agents that automatically adapt their own r

  18. Load-adaptive frequency reuse scheme for inter-cell interference coordination in relay networks

    Institute of Scientific and Technical Information of China (English)

    CHEN Mu-qiong; JI Hong; LI Xi

    2010-01-01

    Cellular relay networks adopting orthogonal frequency division multiple(OFDM)technology has been widely accepted for next generation wireless communication due to its advantage in enlarging coverage scale as well as improving data rate.In order to improve the performance of user equipments(UEs)near the cell edge,especially to avoid the interference from inter-cell and intra cell,an enhanced soft frequency reuse scheme is adopted in this paper to assure inter-cell interference coordination(ICIC).Compared with traditional frequency allocation work,the proposed scheme is interference-aware and load-adaptive,which dynamically assigns available frequency among UES under certain schedule method in variable traffic load condition and mitigates interference using information provided by interference indicator.It can improve signal-to-interference plus noise ratio(SINR)of the UE in each sub channel thus enable the system achieve better throughput and blocking probability performance.Simulation results prove that the proposed scheme may achieve desirable performance on throughput,blocking probability and spectral utilization in the sector under different traffic load compared with other schemes.

  19. Adaptive Object Re-Ranking Mechanism for Ubiquitous Learning Environment

    Directory of Open Access Journals (Sweden)

    Neil Y. Yen

    2011-04-01

    Full Text Available Ubiquitous Learning (U-Learning, as an emerging learning paradigm, makes it possible for learners to carry out the learning activities at any places and at anytime. With the advantages of the devices, learners can obtain a variety of supplementary materials from the Internet. In the scope of distance learning, LOR (Learning Object Repository stands for managing and sharing of learning related materials (known as learning objects. However, some challenges may raise while performing these activities. For instance, a huge amount of learning objects may appear while learners utilize the search service provided by LOR. Learners have to spend time on collecting relevant resources for specific purposes. This situation may discourage the reusability of learning objects especially in a ubiquitous environment. In this paper, based on systematic re-examination of reuse scenarios, an adaptive mechanism, as a resource discovery and search middleware, was proposed to assist learners in obtaining possible objects under ubiquitous environment. Achievement of the proposed mechanism can produce search results adaptive to specific situations in order of similarity degree based on the mixed information. We try to filter out some irrelevant results by using the past usage history, current geographical information and input query, so as to enhance the efficiency of learning objects retrieval in a ubiquitous environment. As a pilot test, Apple iPhone was utilized to be the major client testbed.

  20. Adaptive learning and complex dynamics

    Energy Technology Data Exchange (ETDEWEB)

    Gomes, Orlando [Escola Superior de Comunicacao Social, Instituto Politecnico de Lisboa, Unidade de Investigacao em Desenvolvimento Empresarial Economics Research Center - UNIDE/ISCTE - ERC, Campus de Benfica do IPL, 1549-014 Lisbon (Portugal)], E-mail: ogomes@escs.ipl.pt

    2009-10-30

    In this paper, we explore the dynamic properties of a group of simple deterministic difference equation systems in which the conventional perfect foresight assumption gives place to a mechanism of adaptive learning. These systems have a common feature: under perfect foresight (or rational expectations) they all possess a unique fixed point steady state. This long-term outcome is obtained also under learning if the quality underlying the learning process is high. Otherwise, when the degree of inefficiency of the learning process is relatively strong, nonlinear dynamics (periodic and a-periodic cycles) arise. The specific properties of each one of the proposed systems is explored both in terms of local and global dynamics. One macroeconomic model is used to illustrate how the formation of expectations through learning may eventually lead to awkward long-term outcomes.

  1. Adaptively Ubiquitous Learning in Campus Math Path

    Science.gov (United States)

    Shih, Shu-Chuan; Kuo, Bor-Chen; Liu, Yu-Lung

    2012-01-01

    The purposes of this study are to develop and evaluate the instructional model and learning system which integrate ubiquitous learning, computerized adaptive diagnostic testing system and campus math path learning. The researcher first creates a ubiquitous learning environment which is called "adaptive U-learning math path system". This…

  2. Perceptual learning in sensorimotor adaptation.

    Science.gov (United States)

    Darainy, Mohammad; Vahdat, Shahabeddin; Ostry, David J

    2013-11-01

    Motor learning often involves situations in which the somatosensory targets of movement are, at least initially, poorly defined, as for example, in learning to speak or learning the feel of a proper tennis serve. Under these conditions, motor skill acquisition presumably requires perceptual as well as motor learning. That is, it engages both the progressive shaping of sensory targets and associated changes in motor performance. In the present study, we test the idea that perceptual learning alters somatosensory function and in so doing produces changes to human motor performance and sensorimotor adaptation. Subjects in these experiments undergo perceptual training in which a robotic device passively moves the subject's arm on one of a set of fan-shaped trajectories. Subjects are required to indicate whether the robot moved the limb to the right or the left and feedback is provided. Over the course of training both the perceptual boundary and acuity are altered. The perceptual learning is observed to improve both the rate and extent of learning in a subsequent sensorimotor adaptation task and the benefits persist for at least 24 h. The improvement in the present studies varies systematically with changes in perceptual acuity and is obtained regardless of whether the perceptual boundary shift serves to systematically increase or decrease error on subsequent movements. The beneficial effects of perceptual training are found to be substantially dependent on reinforced decision-making in the sensory domain. Passive-movement training on its own is less able to alter subsequent learning in the motor system. Overall, this study suggests perceptual learning plays an integral role in motor learning.

  3. Software Technology for Adaptable, Reliable System (STARS) Program. Reuse Library Process Model.

    Science.gov (United States)

    The Process Model described in this document is part of the Guidebook requirements for the STARS Reuse Library described in Subtask IS40.3 of the S...Increment Task Proposal for STARS. The objective of a Process Model is to formally characterize the various processes that take place in the context of

  4. Adaptive Bases for Reinforcement Learning

    CERN Document Server

    Di Castro, Dotan

    2010-01-01

    We consider the problem of reinforcement learning using function approximation, where the approximating basis can change dynamically while interacting with the environment. A motivation for such an approach is maximizing the value function fitness to the problem faced. Three errors are considered: approximation square error, Bellman residual, and projected Bellman residual. Algorithms under the actor-critic framework are presented, and shown to converge. The advantage of such an adaptive basis is demonstrated in simulations.

  5. Adaptive Bases for Reinforcement Learning

    OpenAIRE

    Di Castro, Dotan; Mannor, Shie

    2010-01-01

    We consider the problem of reinforcement learning using function approximation, where the approximating basis can change dynamically while interacting with the environment. A motivation for such an approach is maximizing the value function fitness to the problem faced. Three errors are considered: approximation square error, Bellman residual, and projected Bellman residual. Algorithms under the actor-critic framework are presented, and shown to converge. The advantage of such an adaptive basi...

  6. Water quality-scarcity relationships in irrigated agriculture: Health risks and adaptation strategies associated with indirect wastewater reuse

    Science.gov (United States)

    Thebo, A.

    2016-12-01

    Urban wastewater provides a reliable, nutrient rich source of irrigation water for downstream agricultural producers. However, globally, less than ten percent of collected wastewater receives any form of treatment, resulting in the widespread indirect reuse of untreated, diluted wastewater from surface water sources. This research explores these links between water scarcity, anthropogenic drivers of water quality, and adaptation strategies farmer's employ through a case study in Dharwad, a mid-sized South Indian city. This study took an interdisciplinary approach, incorporating survey based research with geospatial analysis, and molecular methods (for waterborne pathogen detection) to develop a systems level understanding of the drivers, health risks, and adaptation strategies associated with the indirect reuse of wastewater in irrigated agriculture. In Dharwad, farmers with better access to wastewater reported growing more water-intensive, but higher value vegetable crops. While farmers further downstream tended to grow more staple crops. This study evaluated levels of culturable E. coli and diarrheagenic E. coli pathotype gene targets to assess contamination in irrigation water, soil, and on produce from farms. Irrigation water source was a major factor affecting the concentrations of culturable E. coli detected in soil samples and on greens. However, even when irrigation water was not contaminated (all borewell water samples) some culturable E. coli were present at low concentrations in soil and on produce samples, suggesting additional sources of contamination on farms. Maximum temperatures within the previous week showed a significant positive association with concentrations of E. coli on wastewater irrigated produce. This presentation will focus on discussing the ways in which urban wastewater management, climate, irrigation practices and cultivation patterns all come together to define the risks and benefits posed via the indirect reuse of wastewater.

  7. Learning Correlations between Linguistic Indicators and Semantic Constraints Reuse of Context-Dependent Descriptions of Entities

    CERN Document Server

    Radev, D R

    1998-01-01

    This paper presents the results of a study on the semantic constraints imposed on lexical choice by certain contextual indicators. We show how such indicators are computed and how correlations between them and the choice of a noun phrase description of a named entity can be automatically established using supervised learning. Based on this correlation, we have developed a technique for automatic lexical choice of descriptions of entities in text generation. We discuss the underlying relationship between the pragmatics of choosing an appropriate description that serves a specific purpose in the automatically generated text and the semantics of the description itself. We present our work in the framework of the more general concept of reuse of linguistic structures that are automatically extracted from large corpora. We present a formal evaluation of our approach and we conclude with some thoughts on potential applications of our method.

  8. Fire Risk Assessment of Adaptive Re-Use of Historic Shop Houses for Sleeping Accommodations in Malaysia

    Directory of Open Access Journals (Sweden)

    Mydin M.A.O.

    2014-01-01

    Full Text Available Heritage buildings were generally constructed without regard for fire risks or the requirements for fire protection, as are obligatory in new constructions. When a heritage building undergoes a change to its original function, improvements to the building’s fire safety are necessary to meet the needs of possible increases in occupancy loads and to account for fire risks related to the new usage. This research focuses on fire safety risks, fire protection and safety systems as well as the rules and regulations that an adaptive reuse heritage shop house is bound to when transitioning to a sleeping accommodation, which, in this case, means becoming a hotel. In this research, six heritage shop houses were chosen as case studies. The objectives of this research were to evaluate current fire emergency plans as well as to identify and assess possible fire hazards created by adaptive reuse of heritage shop houses to sleeping accommodations in Penang through a series of observations and interviews. The results of the research show that most of the buildings were provided with inadequate fire safety systems.

  9. Integrative learning for practicing adaptive resource management

    Directory of Open Access Journals (Sweden)

    Craig A. McLoughlin

    2015-03-01

    Full Text Available Adaptive resource management is a learning-by-doing approach to natural resource management. Its effective practice involves the activation, completion, and regeneration of the "adaptive management cycle" while working toward achieving a flexible set of collaboratively identified objectives. This iterative process requires application of single-, double-, and triple-loop learning, to strategically modify inputs, outputs, assumptions, and hypotheses linked to improving policies, management strategies, and actions, along with transforming governance. Obtaining an appropriate balance between these three modes of learning has been difficult to achieve in practice and building capacity in this area can be achieved through an emphasis on reflexive learning, by employing adaptive feedback systems. A heuristic reflexive learning framework for adaptive resource management is presented in this manuscript. It is built on the conceptual pillars of the following: stakeholder driven adaptive feedback systems; strategic adaptive management (SAM; and hierarchy theory. The SAM Reflexive Learning Framework (SRLF emphasizes the types, roles, and transfer of information within a reflexive learning context. Its adaptive feedback systems enhance the facilitation of single-, double-, and triple-loop learning. Focus on the reflexive learning process is further fostered by streamlining objectives within and across all governance levels; incorporating multiple interlinked adaptive management cycles; having learning as an ongoing, nested process; recognizing when and where to employ the three-modes of learning; distinguishing initiating conditions for this learning; and contemplating practitioner mandates for this learning across governance levels. The SRLF is a key enabler for implementing the "adaptive management cycle," and thereby translating the theory of adaptive resource management into practice. It promotes the heuristics of adaptive management within a cohesive

  10. Effect of adaptive learning style scenarios on learning achievements

    NARCIS (Netherlands)

    Bozhilov, Danail; Stefanov, Krassen; Stoyanov, Slavi

    2009-01-01

    Bozhilov, D., Stefanov, K., & Stoyanov, S. (2009). Effect of adaptive learning style scenarios on learning achievements [Special issue]. International Journal of Continuing Engineering Education and Lifelong Learning (IJCEELL), 19(4/5/6), 381-398.

  11. Adaptive Units of Learning and Educational Videogames

    Science.gov (United States)

    Moreno-Ger, Pablo; Thomas, Pilar Sancho; Martinez-Ortiz, Ivan; Sierra, Jose Luis; Fernandez-Manjon, Baltasar

    2007-01-01

    In this paper, we propose three different ways of using IMS Learning Design to support online adaptive learning modules that include educational videogames. The first approach relies on IMS LD to support adaptation procedures where the educational games are considered as Learning Objects. These games can be included instead of traditional content…

  12. Learning Words through Computer-Adaptive Tool

    DEFF Research Database (Denmark)

    Zhang, Chun

    2005-01-01

    the category of L2 lexical learning in computer-adaptive learning environment. The reason to adopt computer-adaptive tool in WPG is based on the following premises: 1. Lexical learning is incremental in nature. 2. Learning can be measured precisely with tests (objectivist epistemology). In the course of WPG...... construction, I stress the design of a test theory, namely, a learning algorithm. The learning algorithm is designed under such principles that users experience both 'elaborative rehearsal’ (aspects in receptive and productive learning) and 'expanding rehearsal, (memory-based learning and repetitive act...

  13. Template Approach for Adaptive Learning Strategies

    NARCIS (Netherlands)

    Abbing, Jana; Koidl, Kevin

    2006-01-01

    Please, cite this publication as: Abbing, J. & Koidl, K. (2006). Template Approach for Adaptive Learning Strategies. Proceedings of Adaptive Hypermedia. June, Dublin, Ireland. Retrieved June 30th, 2006, from http://dspace.learningnetworks.org

  14. ACO in e-Learning: Towards an adaptive learning path

    Directory of Open Access Journals (Sweden)

    Pushpa. M

    2012-03-01

    Full Text Available Today we are in an era where drastic advancements in networking and information technology are in action. The learning process has also taken these advancements, as a result of which e-learning came to thescene. Personalization in e-learning will improve the performance of the system. Recent researches are concentrating on providing adaptability to the learning management systems, depending upon the varying user needs and contexts. Adaptability can be provided at different levels .Providing an adaptive learning path according to the context of the learners’ is an important issue. An optimal adaptive learning path will help the learners in reducing the cognitive overload and disorientation, and thereby improving the efficiency of the Learning Management System (LMS. Ant Colony Optimization (ACO is a widely accepted technique since it provides an adaptive learning path to the learners. Meta-heuristic which is used in intelligent tutoring systems provides the learning path in an adaptive way. The most interesting feature of ACO is its adaptation and robustness in an environment where the learning materials and learners are changing frequently. In this paper we can have a look through the existing ACO approaches towards providing an adaptive learning path and an introduction towards an enhanced attribute ant for making the e-learning system more adaptive.

  15. Bayesian policy reuse

    CSIR Research Space (South Africa)

    Rosman, Benjamin

    2016-02-01

    Full Text Available to the label of any given instance, it can choose to act through a process of policy reuse from a library in contrast to policy learning. In policy reuse, the agent has prior experience from the class of tasks in the form of a library of policies that were...

  16. Adaptive Learning Systems: Beyond Teaching Machines

    Science.gov (United States)

    Kara, Nuri; Sevim, Nese

    2013-01-01

    Since 1950s, teaching machines have changed a lot. Today, we have different ideas about how people learn, what instructor should do to help students during their learning process. We have adaptive learning technologies that can create much more student oriented learning environments. The purpose of this article is to present these changes and its…

  17. Adaptive designs for learning based on MOOCs

    DEFF Research Database (Denmark)

    Gynther, Karsten

    2016-01-01

    Informed by research in MOOCs and adaptive learning systems the project has developed a design framework which can guide the development of SPOCs (Small Private Online Courses), adapted to experienced school teachers' different learning needs. In 2020 it will be a requirement that, Danish school...

  18. Integrating Learning Styles into Adaptive E-Learning System

    Science.gov (United States)

    Truong, Huong May

    2015-01-01

    This paper provides an overview and update on my PhD research project which focuses on integrating learning styles into adaptive e-learning system. The project, firstly, aims to develop a system to classify students' learning styles through their online learning behaviour. This will be followed by a study on the complex relationship between…

  19. Adaptively Learning the Crowd Kernel

    CERN Document Server

    Tamuz, Omer; Belongie, Serge; Shamir, Ohad; Kalai, Adam Tauman

    2011-01-01

    We introduce an algorithm that, given n objects, learns a similarity matrix over all n^2 pairs, from crowdsourced data alone. The algorithm samples responses to adaptively chosen triplet-based relative-similarity queries. Each query has the form "is object 'a' more similar to 'b' or to 'c'?" and is chosen to be maximally informative given the preceding responses. The output is an embedding of the objects into Euclidean space (like MDS); we refer to this as the "crowd kernel." The runtime (empirically observed to be linear) and cost (about $0.15 per object) of the algorithm are small enough to permit its application to databases of thousands of objects. The distance matrix provided by the algorithm allows for the development of an intuitive and powerful sequential, interactive search algorithm which we demonstrate for a variety of visual stimuli. We present quantitative results that demonstrate the benefit in cost and time of our approach compared to a nonadaptive approach. We also show the ability of our appr...

  20. A Machine Learning Based Framework for Adaptive Mobile Learning

    Science.gov (United States)

    Al-Hmouz, Ahmed; Shen, Jun; Yan, Jun

    Advances in wireless technology and handheld devices have created significant interest in mobile learning (m-learning) in recent years. Students nowadays are able to learn anywhere and at any time. Mobile learning environments must also cater for different user preferences and various devices with limited capability, where not all of the information is relevant and critical to each learning environment. To address this issue, this paper presents a framework that depicts the process of adapting learning content to satisfy individual learner characteristics by taking into consideration his/her learning style. We use a machine learning based algorithm for acquiring, representing, storing, reasoning and updating each learner acquired profile.

  1. Adaptive designs for learning based on MOOCs

    DEFF Research Database (Denmark)

    Gynther, Karsten

    2016-01-01

    teachers have a bachelor degree in the subjects they teach. More than 10,000 teachers need professional development and municipalities ask for an adaptive teacher development program with personalized learning. The project's research question is the study and development of design principles that can guide......Informed by research in MOOCs and adaptive learning systems the project has developed a design framework which can guide the development of SPOCs (Small Private Online Courses), adapted to experienced school teachers' different learning needs. In 2020 it will be a requirement that, Danish school...... the development of adaptive designs for learning on the basis of MOOCs as an overall design framework. The project is methodologically inspired by Design Based Research....

  2. Sharing Knowledge in Adaptive Learning Systems

    NARCIS (Netherlands)

    Kravcik, Milos; Gasevic, Dragan

    2006-01-01

    Please, cite this publication as: Kravcik, M. & Gasevic, D. (2006). Sharing Knowledge in Adaptive Learning Systems. Proceedings of ICALT2006. July, Kerkrade, The Netherlands: IEEE. Retrieved July 30th, 2006, from http://dspace.learningnetworks.org

  3. Representing adaptive eLearning strategies in IMS Learning Design

    NARCIS (Netherlands)

    Burgos, Daniel; Tattersall, Colin; Koper, Rob

    2006-01-01

    Burgos, D., Tattersall, C., & Koper, E. J. R. (2006). Representing adaptive eLearning strategies in IMS Learning Design. In R. Koper & K. Stefanov (Eds.), Proceedings of the International Workshop in Learning Networks for Lifelong Competence Development (pp. 54-60). March, 30-31, 2006, Sofia, Bulgar

  4. ADAPTIVE E-LEARNING AND ITS EVALUATION

    Directory of Open Access Journals (Sweden)

    KOSTOLÁNYOVÁ, Katerina

    2012-12-01

    Full Text Available This paper introduces a complex plan for a complete system of individualized electronic instruction. The core of the system is a computer program to control teaching, the so called “virtual teacher”. The virtual teacher automatically adapts to individual student’s characteristics and their learning style. It adapts to static as well as to dynamic characteristics of the student. To manage all this it needs a database of various styles and forms of teaching as well as a sufficient amount of information about the learning style, type of memory and other characteristics of the student. The information about these characteristics, the structure of data storage and its use by the virtual teacher are also part of this paper. We also outline a methodology of adaptive study materials. We define basic rules and forms to create adaptive study materials. This adaptive e-learning system was pilot tested in learning of more than 50 students. These students filled in a learning style questionnaire at the beginning of the study and they had the option to fill in an adaptive evaluation questionnaire at the end of the study. Results of these questionnaires were analyzed. Several conclusions were concluded from this analysis to alter the methodology of adaptive study materials.

  5. Teacher Adaptation to Personalized Learning Spaces

    Science.gov (United States)

    Deed, Craig; Lesko, Thomas M.; Lovejoy, Valerie

    2014-01-01

    Personalized learning spaces are emerging in schools as a critical reaction to "industrial-era" school models. As the form and function of schools and pedagogy change, this places pressure on teachers to adapt their conventional practice. This paper addresses the question of how teachers can adapt their classroom practice to create…

  6. Adaptive Educational Software by Applying Reinforcement Learning

    Science.gov (United States)

    Bennane, Abdellah

    2013-01-01

    The introduction of the intelligence in teaching software is the object of this paper. In software elaboration process, one uses some learning techniques in order to adapt the teaching software to characteristics of student. Generally, one uses the artificial intelligence techniques like reinforcement learning, Bayesian network in order to adapt…

  7. Different Futures of Adaptive Collaborative Learning Support

    Science.gov (United States)

    Rummel, Nikol; Walker, Erin; Aleven, Vincent

    2016-01-01

    In this position paper we contrast a Dystopian view of the future of adaptive collaborative learning support (ACLS) with a Utopian scenario that--due to better-designed technology, grounded in research--avoids the pitfalls of the Dystopian version and paints a positive picture of the practice of computer-supported collaborative learning 25 years…

  8. Different Futures of Adaptive Collaborative Learning Support

    Science.gov (United States)

    Rummel, Nikol; Walker, Erin; Aleven, Vincent

    2016-01-01

    In this position paper we contrast a Dystopian view of the future of adaptive collaborative learning support (ACLS) with a Utopian scenario that--due to better-designed technology, grounded in research--avoids the pitfalls of the Dystopian version and paints a positive picture of the practice of computer-supported collaborative learning 25 years…

  9. Animal social learning: associations and adaptations.

    Science.gov (United States)

    Reader, Simon M

    2016-01-01

    Social learning, learning from others, is a powerful process known to impact the success and survival of humans and non-human animals alike. Yet we understand little about the neurocognitive and other processes that underpin social learning. Social learning has often been assumed to involve specialized, derived cognitive processes that evolve and develop independently from other processes. However, this assumption is increasingly questioned, and evidence from a variety of organisms demonstrates that current, recent, and early life experience all predict the reliance on social information and thus can potentially explain variation in social learning as a result of experiential effects rather than evolved differences. General associative learning processes, rather than adaptive specializations, may underpin much social learning, as well as social learning strategies. Uncovering these distinctions is important to a variety of fields, for example by widening current views of the possible breadth and adaptive flexibility of social learning. Nonetheless, just like adaptationist evolutionary explanations, associationist explanations for social learning cannot be assumed, and empirical work is required to uncover the mechanisms involved and their impact on the efficacy of social learning. This work is being done, but more is needed. Current evidence suggests that much social learning may be based on 'ordinary' processes but with extraordinary consequences.

  10. Sharing and Reuse in OER: Experiences Gained from Open Reusable Learning Objects in Health

    Science.gov (United States)

    Windle, Richard J.; Wharrad, Heather; McCormick, Damion; Laverty, Helen; Taylor, Michael

    2010-01-01

    The open educational resource (OER) movement has the potential to have a truly transformative effect on higher education, but in order to do so it must move into the mainstream and facilitate widespread participation in the sharing or creating of resources and in their reuse. To help in this process, experience can be gained from projects and…

  11. Active Transfer Learning with Zero-Shot Priors: Reusing Past Datasets for Future Tasks

    NARCIS (Netherlands)

    Gavves, E.; Mensink, T.; Tommasi, T.; Snoek, C.G.M.; Tuytelaars, T.

    2015-01-01

    How can we reuse existing knowledge, in the form of available datasets, when solving a new and apparently unrelated target task from a set of unlabeled data? In this work we make a first contribution to answer this question in the context of image classification. We frame this quest as an active

  12. Simultaneous sensorimotor adaptation and sequence learning.

    Science.gov (United States)

    Overduin, Simon A; Richardson, Andrew G; Bizzi, Emilio; Press, Daniel Z

    2008-01-01

    Sensorimotor adaptation and sequence learning have often been treated as distinct forms of motor learning. But frequently the motor system must acquire both types of experience simultaneously. Here, we investigated the interaction of these two forms of motor learning by having subjects adapt to predictable forces imposed by a robotic manipulandum while simultaneously reaching to an implicit sequence of targets. We show that adaptation to novel dynamics and learning of a sequence of movements can occur simultaneously and without significant interference or facilitation. When both conditions were presented simultaneously to subjects, their trajectory error and reaction time decreased to the same extent as those of subjects who experienced the force field or sequence independently.

  13. Adaptations to a Learning Resource

    Science.gov (United States)

    Libbrecht, Paul

    2015-01-01

    Learning resources have been created to represent digital units of exchangeable materials that teachers and learners can pull from in order to support the learning processes. They resource themselves. Leveraging the web, one can often find these resources. But what characteristics do they need in order to be easily exchangeable? Although several…

  14. Flexible Ubiquitous Learning Management System Adapted to Learning Context

    Science.gov (United States)

    Jeong, Ji-Seong; Kim, Mihye; Park, Chan; Yoo, Jae-Soo; Yoo, Kwan-Hee

    This paper proposes a u-learning management system (ULMS) appropriate to the ubiquitous learning environment, with emphasis on the significance of context awareness and adaptation in learning. The proposed system supports the basic functions of an e-learning management system and incorporates a number of tools and additional features to provide a more customized learning service. The proposed system automatically corresponds to various forms of user terminal without modifying the existing system. The functions, formats, and course learning activities of the system are dynamically and adaptively constructed at runtime according to user terminals, course types, pedagogical goals as well as student characteristics and learning context. A prototype for university use has been implemented to demonstrate and evaluate the proposed approach. We regard the proposed ULMS as an ideal u-learning system because it can not only lead students into continuous and mobile 'anytime, anywhere' learning using any kind of terminal, but can also foster enhanced self-directed learning through the establishment of an adaptive learning environment.

  15. Mechanism for Learning Object retrieval supporting adaptivity

    CERN Document Server

    Chawla, Sonal

    2010-01-01

    In today’s world designing adaptable course material requires new technical knowledge which involves a need for a uniform protocol that allows organizing resources with emphasis on quality and Learning. This can be achieved by bundling the resources in a known and prescribed fashion called Learning objects. Learning Objects are composed of two aspects namely “Learning “ and “Object”. The Learning aspect of Learning objects refers to Education. Since Education is a process so the primary aim of learning objects tends to be facilitating acquisition, assessment and conversion of content into Learning objects while fostering the assimilation of these Learning objects into learning modules and instruction. The Object part of Learning objects relates to the Digital Electronic format of the resources i.e. to say that it deals with the physical resource that forms the Learning objects. The objects in LOs are analogous to objects used in object-oriented modeling (OOM). The analogy helps visual...

  16. The Effect of Adaptive Learning Style Scenarios on Learning Achievements

    NARCIS (Netherlands)

    Bozhilov, Danail; Stefanov, Krassen; Stoyanov, Slavi

    2009-01-01

    Bozhilov, D., Stefanov, K., & Stoyanov, S. (2008). The Effect of Adaptive Learning Style Scenarios on Learning Achievements. In R. Koper, K. Stefanov & D. Dicheva (Eds.), Proceedings of the 5th International TENCompetence Open Workshop "Stimulating Personal Development and Knowledge Sharing" (pp.

  17. Adaptive Learning Objects Sequencing for Competence-Based Learning

    NARCIS (Netherlands)

    Karampiperis, Pythagoras; Demetrios, Sampson

    2006-01-01

    Lifelong learning refers to the activities people perform throughout their life to improve their competence in a particular field. Although adaptive educational hypermedia systems (AEHS) bare the potential to provide personalized learning experiences based on individual’s knowledge, skills, and comp

  18. Fractal Adaptive Web Service for Mobile Learning

    Directory of Open Access Journals (Sweden)

    Ichraf Tirellil

    2006-06-01

    Full Text Available This paper describes our proposition for adaptive web services which is based on configurable, re-usable adaptive/personalized services. To realize our ideas, we have developed an approach for designing, implementing and maintaining personal service. This approach enables the user to accomplish an activity with a set of services answering to his preferences, his profiles and to a personalized context. In this paper, we describe the principle of our approach that we call fractal adaptation approach, and we discuss the implementation of personalization services in the context of mobile and collaborative scenario of learning. We have realized a platform in this context -a platform for mobile and collaborative learning- based on fractal adaptable web services. The platform is tested with a population of students and tutors, in order to release the gaps and the advantages of the approach suggested.

  19. Learning from adaptive neural network output feedback control of a unicycle-type mobile robot.

    Science.gov (United States)

    Zeng, Wei; Wang, Qinghui; Liu, Fenglin; Wang, Ying

    2016-03-01

    This paper studies learning from adaptive neural network (NN) output feedback control of nonholonomic unicycle-type mobile robots. The major difficulties are caused by the unknown robot system dynamics and the unmeasurable states. To overcome these difficulties, a new adaptive control scheme is proposed including designing a new adaptive NN output feedback controller and two high-gain observers. It is shown that the stability of the closed-loop robot system and the convergence of tracking errors are guaranteed. The unknown robot system dynamics can be approximated by radial basis function NNs. When repeating same or similar control tasks, the learned knowledge can be recalled and reused to achieve guaranteed stability and better control performance, thereby avoiding the tremendous repeated training process of NNs. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  20. Adapting Active Learning in Ethiopia

    Science.gov (United States)

    Casale, Carolyn Frances

    2010-01-01

    Ethiopia is a developing country that has invested extensively in expanding its educational opportunities. In this expansion, there has been a drastic restructuring of its system of preparing teachers and teacher educators. Often, improving teacher quality is dependent on professional development that diversifies pedagogy (active learning). This…

  1. Learning adaptive metric for robust visual tracking.

    Science.gov (United States)

    Jiang, Nan; Liu, Wenyu; Wu, Ying

    2011-08-01

    Matching the visual appearances of the target over consecutive image frames is the most critical issue in video-based object tracking. Choosing an appropriate distance metric for matching determines its accuracy and robustness, and thus significantly influences the tracking performance. Most existing tracking methods employ fixed pre-specified distance metrics. However, this simple treatment is problematic and limited in practice, because a pre-specified metric does not likely to guarantee the closest match to be the true target of interest. This paper presents a new tracking approach that incorporates adaptive metric learning into the framework of visual object tracking. Collecting a set of supervised training samples on-the-fly in the observed video, this new approach automatically learns the optimal distance metric for more accurate matching. The design of the learned metric ensures that the closest match is very likely to be the true target of interest based on the supervised training. Such a learned metric is discriminative and adaptive. This paper substantializes this new approach in a solid case study of adaptive-metric differential tracking, and obtains a closed-form analytical solution to motion estimation and visual tracking. Moreover, this paper extends the basic linear distance metric learning method to a more powerful nonlinear kernel metric learning method. Extensive experiments validate the effectiveness of the proposed approach, and demonstrate the improved performance of the proposed new tracking method.

  2. Making Mistakes: Emotional Adaptation and Classroom Learning

    Science.gov (United States)

    McCaslin, Mary; Vriesema, Christine C.; Burggraf, Susan

    2016-01-01

    Background: We studied how students in Grades 4-6 participate in and emotionally adapt to the give-and-take of learning in classrooms, particularly when making mistakes. Our approach is consistent with researchers who (a) include cognitive appraisals in the study of emotional experiences, (b) consider how personal concerns might mediate…

  3. Adapting Cooperative Learning in Tertiary ELT

    Science.gov (United States)

    Ning, Huiping

    2011-01-01

    An updated guideline for tertiary ELT in China has shifted the emphasis to the development of learners' ability to communicate in English. Using group work and getting learners actively involved in the actual use of English are highlighted more than before. This article focuses on adapting cooperative learning methods for ELT with tertiary…

  4. Persuasion, Learning and Context Adaptation

    DEFF Research Database (Denmark)

    Gram-Hansen, Sandra Burri; Ryberg, Thomas

    2013-01-01

    This paper further develops the notion of distinguishing between Persuasive Technology and Persuasive Design, and considering Persuasive Design a meta-perspective which may be applied to more established design traditions as an ethics and context-oriented perspective. The paper addresses...... a challenge often met when aiming to apply persuasive design principles to more established design fields, namely that the unique claim of persuasive design and the relevance of taking it into consideration is unclear. Furthermore, this paper aims to extend the argumentation and exemplify how this new...... understanding of Persuasive Design may potentially facilitate the more established field of technology enhanced learning....

  5. Electroencephalographic identifiers of motor adaptation learning

    Science.gov (United States)

    Özdenizci, Ozan; Yalçın, Mustafa; Erdoğan, Ahmetcan; Patoğlu, Volkan; Grosse-Wentrup, Moritz; Çetin, Müjdat

    2017-08-01

    Objective. Recent brain-computer interface (BCI) assisted stroke rehabilitation protocols tend to focus on sensorimotor activity of the brain. Relying on evidence claiming that a variety of brain rhythms beyond sensorimotor areas are related to the extent of motor deficits, we propose to identify neural correlates of motor learning beyond sensorimotor areas spatially and spectrally for further use in novel BCI-assisted neurorehabilitation settings. Approach. Electroencephalographic (EEG) data were recorded from healthy subjects participating in a physical force-field adaptation task involving reaching movements through a robotic handle. EEG activity recorded during rest prior to the experiment and during pre-trial movement preparation was used as features to predict motor adaptation learning performance across subjects. Main results. Subjects learned to perform straight movements under the force-field at different adaptation rates. Both resting-state and pre-trial EEG features were predictive of individual adaptation rates with relevance of a broad network of beta activity. Beyond sensorimotor regions, a parieto-occipital cortical component observed across subjects was involved strongly in predictions and a fronto-parietal cortical component showed significant decrease in pre-trial beta-powers for users with higher adaptation rates and increase in pre-trial beta-powers for users with lower adaptation rates. Significance. Including sensorimotor areas, a large-scale network of beta activity is presented as predictive of motor learning. Strength of resting-state parieto-occipital beta activity or pre-trial fronto-parietal beta activity can be considered in BCI-assisted stroke rehabilitation protocols with neurofeedback training or volitional control of neural activity for brain-robot interfaces to induce plasticity.

  6. Adaptive Educational Software by Applying Reinforcement Learning

    Directory of Open Access Journals (Sweden)

    Abdellah BENNANE

    2013-04-01

    Full Text Available The introduction of the intelligence in teaching software is the object of this paper. In software elaboration process, one uses some learning techniques in order to adapt the teaching software to characteristics of student. Generally, one uses the artificial intelligence techniques like reinforcement learning, Bayesian network in order to adapt the system to the environment internal and external conditions, and allow this system to interact efficiently with its potentials user. The intention is to automate and manage the pedagogical process of tutoring system, in particular the selection of the content and manner of pedagogic situations. Researchers create a pedagogic learning agent that simplifies the manual logic and supports progress and the management of the teaching process (tutor-learner through natural interactions.

  7. Finding and Reusing Learning Materials with Multimedia Similarity Search and Social Networks

    Science.gov (United States)

    Little, Suzanne; Ferguson, Rebecca; Ruger, Stefan

    2012-01-01

    The authors describe how content-based multimedia search technologies can be used to help learners find new materials and learning pathways by identifying semantic relationships between educational resources in a social learning network. This helps users--both learners and educators--to explore and find material to support their learning aims.…

  8. Finding and Reusing Learning Materials with Multimedia Similarity Search and Social Networks

    Science.gov (United States)

    Little, Suzanne; Ferguson, Rebecca; Ruger, Stefan

    2012-01-01

    The authors describe how content-based multimedia search technologies can be used to help learners find new materials and learning pathways by identifying semantic relationships between educational resources in a social learning network. This helps users--both learners and educators--to explore and find material to support their learning aims.…

  9. Intelligent robots that adapt, learn, and predict

    Science.gov (United States)

    Hall, E. L.; Liao, X.; Ghaffari, M.; Alhaj Ali, S. M.

    2005-10-01

    The purpose of this paper is to describe the concept and architecture for an intelligent robot system that can adapt, learn and predict the future. This evolutionary approach to the design of intelligent robots is the result of several years of study on the design of intelligent machines that could adapt using computer vision or other sensory inputs, learn using artificial neural networks or genetic algorithms, exhibit semiotic closure with a creative controller and perceive present situations by interpretation of visual and voice commands. This information processing would then permit the robot to predict the future and plan its actions accordingly. In this paper we show that the capability to adapt, and learn naturally leads to the ability to predict the future state of the environment which is just another form of semiotic closure. That is, predicting a future state without knowledge of the future is similar to making a present action without knowledge of the present state. The theory will be illustrated by considering the situation of guiding a mobile robot through an unstructured environment for a rescue operation. The significance of this work is in providing a greater understanding of the applications of learning to mobile robots.

  10. Model Driven Architecture (MDA: Integration and Model Reuse for Open Source eLearning Platforms

    Directory of Open Access Journals (Sweden)

    Blasius Lofi Dewanto

    2005-02-01

    Full Text Available Open Source (OS community offers numerous eLearning platforms of both types: Learning Management Systems (LMS and Learning Content Systems (LCS. General purpose OS intermediaries such as SourceForge, ObjectWeb, Apache or specialized intermediaries like CampusSource reduce the cost to locate such eLearning platforms. Still, it is impossible to directly compare the functionalities of those OS software products without performing detailed testing on each product. Some articles available from eLearning Wikipedia show comparisons between eLearning platforms which can help, but at the end they barely serve as documentation which are becoming out of date quickly (1. The absence of integration activities between OS eLearning platforms - which are sometimes quite similar in terms of functionalities and implementation technologies - is sometimes critical since most of the OS projects possess small financial and human resources. This paper shows a possible solution for these barriers of OS eLearning platforms. We propose the Model Driven Architecture (MDA concept to capture functionalities and to identify similarities between available OS eLearning platforms. This contribution evolved from a fruitful discussion at the 2nd CampusSource Developer Conference at the University of Muenster (27th August 2004.Die Open Source-Community bietet zahlreiche eLearning-Plattformen an: Learning Management-Systeme (LMS sowie Learning Content-Systeme (LCS. Allgemeine Open-Source-Mediatoren, wie SourceForge, ObjectWeb, Apache und der eLearning-spezifische Mediator CampusSource ermöglichen eine einfache Suche nach eLearning-Softwareprodukten. Ein Vergleich unterschiedlicher Plattformen in Bezug auf ihre Funktionalitäten ist jedoch aufwändig. Beiträge aus der “eLearning Wikipedia” können kaum als Entscheidungsgrundlage genutzt werden, da sie schnell veraltet sind (1. Zudem fehlen derzeit Aktivitäten zur Integration von Open Source-eLearning-Plattformen, die oft

  11. Adaptive Learning in Extensive Form Games and Sequential Equilibrium

    DEFF Research Database (Denmark)

    Groes, Ebbe; Jacobsen, Hans Jørgen; Sloth, Birgitte

    1999-01-01

    This paper studies adaptive learning in extensive form games and provides conditions for convergence points of adaptive learning to be sequential equilibria. Precisely, we present a set of conditions on learning sequences such that an assessment is a sequential equilibrium if and only...... if there is a learning sequence fulfilling the conditions, which leads to the assessment...

  12. Reuse, Repurposing and Learning Design--Lessons from the DART Project

    Science.gov (United States)

    Bond, Stephen T.; Ingram, Caroline; Ryan, Steve

    2008-01-01

    Digital Anthropological Resources for Teaching (DART) is a major project examining ways in which the use of online learning activities and repositories can enhance the teaching of anthropology and, by extension, other disciplines. This paper reports on one strand of DART activity, the development of customisable learning activities that can be…

  13. Social influences on adaptive criterion learning.

    Science.gov (United States)

    Cassidy, Brittany S; Dubé, Chad; Gutchess, Angela H

    2015-07-01

    People adaptively shift decision criteria when given biased feedback encouraging specific types of errors. Given that work on this topic has been conducted in nonsocial contexts, we extended the literature by examining adaptive criterion learning in both social and nonsocial contexts. Specifically, we compared potential differences in criterion shifting given performance feedback from social sources varying in reliability and from a nonsocial source. Participants became lax when given false positive feedback for false alarms, and became conservative when given false positive feedback for misses, replicating prior work. In terms of a social influence on adaptive criterion learning, people became more lax in response style over time if feedback was provided by a nonsocial source or by a social source meant to be perceived as unreliable and low-achieving. In contrast, people adopted a more conservative response style over time if performance feedback came from a high-achieving and reliable source. Awareness that a reliable and high-achieving person had not provided their feedback reduced the tendency to become more conservative, relative to those unaware of the source manipulation. Because teaching and learning often occur in a social context, these findings may have important implications for many scenarios in which people fine-tune their behaviors, given cues from others.

  14. Yet Another Adaptive Learning Management System Based on Felder and Silverman's Learning Styles and Mashup

    Science.gov (United States)

    Chang, Yi-Hsing; Chen, Yen-Yi; Chen, Nian-Shing; Lu, You-Te; Fang, Rong-Jyue

    2016-01-01

    This study designs and implements an adaptive learning management system based on Felder and Silverman's Learning Style Model and the Mashup technology. In this system, Felder and Silverman's Learning Style model is used to assess students' learning styles, in order to provide adaptive learning to leverage learners' learning preferences.…

  15. Yet Another Adaptive Learning Management System Based on Felder and Silverman's Learning Styles and Mashup

    Science.gov (United States)

    Chang, Yi-Hsing; Chen, Yen-Yi; Chen, Nian-Shing; Lu, You-Te; Fang, Rong-Jyue

    2016-01-01

    This study designs and implements an adaptive learning management system based on Felder and Silverman's Learning Style Model and the Mashup technology. In this system, Felder and Silverman's Learning Style model is used to assess students' learning styles, in order to provide adaptive learning to leverage learners' learning preferences.…

  16. Age Effects in Adaptive Criterion Learning.

    Science.gov (United States)

    Cassidy, Brittany S; Gutchess, Angela H

    2016-11-01

    Although prior work has examined age-related changes to criterion placement and flexibility, no study tested these constructs through a paradigm that employs adaptive feedback to encourage specific criterion changes. The goal of this study was to assess age differences in how young and older adults adapt and shift criteria in recognition memory decisions based on trial-by-trial feedback. Young and older adults completed an adaptive criterion learning paradigm. Over 3 study/test cycles, a biased feedback technique at test encouraged more liberal or strict responding by false-positive feedback toward false alarms or misses. Older adults were more conservative than young, even when feedback first encouraged a liberal response bias, and older adults adaptively placed criteria in response to biased feedback, much like young adults. After first being encouraged to respond conservatively, older adults shifted criteria less than young when feedback encouraged more lenient responding. These findings evidence labile adaptive criteria placement and criteria shifting with age. However, age-related tendencies toward conservative response biases may limit the extent to which criteria can be shifted in a lenient direction. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  17. Wastewater reuse

    Directory of Open Access Journals (Sweden)

    Milan R. Radosavljević

    2013-12-01

    Full Text Available Water scarcity and water pollution are some of the crucial issues that must be addressed within local and global perspectives. One of the ways to reduce the impact of water scarcity  and to minimizine water pollution is to expand water and wastewater reuse. The local conditions including regulations, institutions, financial mechanisms, availability of local technology and stakeholder participation have a great influence on the decisions for wastewater reuse. The increasing awareness of food safety and the influence of the countries which import food are influencing policy makers and agriculturists to improve the standards of wastewater reuse in agriculture. The environmental awareness of consumers has been putting pressure on the producers (industries to opt for environmentally sound technologies including those which conserve water and reduce the level of pollution. It may be observed that we have to move forwards to implement strategies and plans for wastewater reuse. However, their success and sustainability will depend on political will, public awareness and active support from national and international agencies to create favorable    environment for the promotion of environmentally sustainable technologies. Wastewater treatment has a long history, especially in agriculture, but also in industry and households. Poor quality of wastewater can pose a significant risk to the health of farmers and users of agricultural products. The World Health Organization (WHO is working on a project for the reuse of wastewater in agriculture. To reduce effects of human activities to the minimum, it is necessary to provide such technical and technological solutions that would on the one hand ensure complying with  the existing regulations and legislation, and on the other hand provide economically viable systems as seen through investments and operating costs. The use of wastewater The practice of using wastewater varies from country to country. Its

  18. Development of Adaptive Kanji Learning System for Mobile Phone

    Science.gov (United States)

    Li, Mengmeng; Ogata, Hiroaki; Hou, Bin; Hashimoto, Satoshi; Liu, Yuqin; Uosaki, Noriko; Yano, Yoneo

    2010-01-01

    This paper describes an adaptive learning system based on mobile phone email to support the study of Japanese Kanji. In this study, the main emphasis is on using the adaptive learning to resolve one common problem of the mobile-based email or SMS language learning systems. To achieve this goal, the authors main efforts focus on three aspects:…

  19. How Language Supports Adaptive Teaching through a Responsive Learning Culture

    Science.gov (United States)

    Johnston, Peter; Dozier, Cheryl; Smit, Julie

    2016-01-01

    For students to learn optimally, teachers must design classrooms that are responsive to the full range of student development. The teacher must be adaptive, but so must each student and the learning culture itself. In other words, adaptive teaching means constructing a responsive learning culture that accommodates and even capitalizes on diversity…

  20. How Language Supports Adaptive Teaching through a Responsive Learning Culture

    Science.gov (United States)

    Johnston, Peter; Dozier, Cheryl; Smit, Julie

    2016-01-01

    For students to learn optimally, teachers must design classrooms that are responsive to the full range of student development. The teacher must be adaptive, but so must each student and the learning culture itself. In other words, adaptive teaching means constructing a responsive learning culture that accommodates and even capitalizes on diversity…

  1. Learning from adaptive neural dynamic surface control of strict-feedback systems.

    Science.gov (United States)

    Wang, Min; Wang, Cong

    2015-06-01

    Learning plays an essential role in autonomous control systems. However, how to achieve learning in the nonstationary environment for nonlinear systems is a challenging problem. In this paper, we present learning method for a class of n th-order strict-feedback systems by adaptive dynamic surface control (DSC) technology, which achieves the human-like ability of learning by doing and doing with learned knowledge. To achieve the learning, this paper first proposes stable adaptive DSC with auxiliary first-order filters, which ensures the boundedness of all the signals in the closed-loop system and the convergence of tracking errors in a finite time. With the help of DSC, the derivative of the filter output variable is used as the neural network (NN) input instead of traditional intermediate variables. As a result, the proposed adaptive DSC method reduces greatly the dimension of NN inputs, especially for high-order systems. After the stable DSC design, we decompose the stable closed-loop system into a series of linear time-varying perturbed subsystems. Using a recursive design, the recurrent property of NN input variables is easily verified since the complexity is overcome using DSC. Subsequently, the partial persistent excitation condition of the radial basis function NN is satisfied. By combining a state transformation, accurate approximations of the closed-loop system dynamics are recursively achieved in a local region along recurrent orbits. Then, the learning control method using the learned knowledge is proposed to achieve the closed-loop stability and the improved control performance. Simulation studies are performed to demonstrate the proposed scheme can not only reuse the learned knowledge to achieve the better control performance with the faster tracking convergence rate and the smaller tracking error but also greatly alleviate the computational burden because of reducing the number and complexity of NN input variables.

  2. Towards Adaptive Open Learning Environments: Evaluating the Precision of Identifying Learning Styles by Tracking Learners' Behaviours

    Science.gov (United States)

    Fasihuddin, Heba; Skinner, Geoff; Athauda, Rukshan

    2017-01-01

    Open learning represents a new form of online learning where courses are provided freely online for large numbers of learners. MOOCs are examples of this form of learning. The authors see an opportunity for personalising open learning environments by adapting to learners' learning styles and providing adaptive support to meet individual learner…

  3. Learning in Adaptive Management: Insights from Published Practice

    Directory of Open Access Journals (Sweden)

    Christo Fabricius

    2014-03-01

    Full Text Available Adaptive management is often advocated as a solution to understanding and managing complexity in social-ecological systems. Given the centrality of learning in adaptive management, it remains unclear how learning in adaptive management is understood to occur, who learns, what they learn about, and how they learn. We conducted a systematic review using the Thomson Reuters Web of Science, and searched specifically for examples of the practical implementation of adaptive management between 2011 and 2013, i.e., excluding articles that suggested frameworks, models, or recommendations for future action. This provided a subset of 22 papers that were analyzed using five elements: the aims of adaptive management as stated in each paper; the reported achievements of adaptive management; what was learned; who learned; and how they learned. Our results indicate that, although most published adaptive management initiatives aimed at improvements in biological conservation or ecosystem management, scholars of adaptive management tend to report on learning more about governance and about learning, than about ecosystems or biological conservation. Whereas almost all the papers (91% listed improvements in biological conservation and ecosystem management as aims, 59% reported these as achievements. Whereas only 27% listed improved governance as an aim, 73% mentioned this as an achievement. Conservation scientists and academics reporting on adaptive management tend to learn among themselves, and very seldom (18% with external stakeholders. Adaptive ecosystem management is dominated by direct assessment and single-loop learning aimed at improving existing practices (86%, with about 50% engaged in double-loop learning and a similar number in deutero-learning (learning about learning. Some adaptive managers (36% combined double-and single-loop learning and the majority of these (6/8 reported on conservation achievements. A possible explanation for these findings is

  4. Adaptive Learning Environments: A Requirements Analysis in Business Settings

    Directory of Open Access Journals (Sweden)

    Kai Michael Höver

    2009-08-01

    Full Text Available The design and development of an adaptive learning system (ALS should be guided by a thorough analysis of users’ expectations and needs. A requirements analysis has been carried out by means of scenario-based semi-structured interviews in order to investigate the personalization and adaptation preferences of different stakeholder groups in business settings. Results show that an ALS has a decided advantage over a non-adaptive learning system by offering individual treatment of learners. The adaptation of content and learning activities to learner knowledge and learning goal, particularly determined by the job role, is perceived to be most relevant.

  5. INFORMATION TECHNOLOGIES AS A TOOL OF ADAPTIVE LEARNING OF ADULTS

    Directory of Open Access Journals (Sweden)

    Olena I. Ohiienko

    2011-02-01

    Full Text Available In the article necessity of adaptive learning of adults in conditions of information societies is proved; the essence of adaptive learning of adults is investigated; its functions and main principles (a principle of social and personal development, a principle of cultural-historical and valuable development, a principle of individual advancement, a principle of the competence approach are defined and proved; the essence of adaptive learning technologies of adults is defined; the value of information technologies as a tool of adaptive learning of adults which provides conditions for personal growth, social and professional competence development is proved.

  6. The Adaptation of Mobile Learning System Based on Business Rules

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    <正>In the mobile learning system,it is important to adapt to mobile devices.Most of mobile learning systems are not quickly suitable for mobile devices.In order to provide adaptive mobile services,the approach for adaptation is proposed in this paper.Firstly,context of mobile devices and its influence on mobile learning system are analized and business rules based on these analysis are presented.Then,using the approach,the mobile learning system is constructed.The example implies this approach can adapt the mobile service to the mobile devices flexibly.

  7. Perceptual learning reconfigures the effects of visual adaptation.

    Science.gov (United States)

    McGovern, David P; Roach, Neil W; Webb, Ben S

    2012-09-26

    Our sensory experiences over a range of different timescales shape our perception of the environment. Two particularly striking short-term forms of plasticity with manifestly different time courses and perceptual consequences are those caused by visual adaptation and perceptual learning. Although conventionally treated as distinct forms of experience-dependent plasticity, their neural mechanisms and perceptual consequences have become increasingly blurred, raising the possibility that they might interact. To optimize our chances of finding a functionally meaningful interaction between learning and adaptation, we examined in humans the perceptual consequences of learning a fine discrimination task while adapting the neurons that carry most information for performing this task. Learning improved discriminative accuracy to a level that ultimately surpassed that in an unadapted state. This remarkable improvement came at a price: adapting directions that before learning had little effect elevated discrimination thresholds afterward. The improvements in discriminative accuracy grew quickly and surpassed unadapted levels within the first few training sessions, whereas the deterioration in discriminative accuracy had a different time course. This learned reconfiguration of adapted discriminative accuracy occurred without a concomitant change to the characteristic perceptual biases induced by adaptation, suggesting that the system was still in an adapted state. Our results point to a functionally meaningful push-pull interaction between learning and adaptation in which a gain in sensitivity in one adapted state is balanced by a loss of sensitivity in other adapted states.

  8. A Framework to Formulate Adaptivity for Adaptive e-Learning System Using User Response Theory

    Directory of Open Access Journals (Sweden)

    Maria Dominic

    2015-01-01

    Full Text Available These days different e-learning architecture provide different kinds of e-learning experiences due to “one size fits for all” concept. This is no way better than the traditional learning and does not exploit the technological advances. Thus the e-learning system began to evolve to adaptable e-learning systems which adapts or personalizes the learning experience of the learners. Systems infer the characteristics of the learners and identify the preferences of the learners and automatically generate personalized learning path and customize learning contents to the individuals needs. This process is known as adaptation and systems which adapt are known are adaptive systems. So the main objective of this research was to provide an adaptive e-learning system framework which personalizes the learning experience in an efficient way. In this paper a framework for adaptive e-learning system using user response theory is proposed to meet the research objectives identified in section 1.D.

  9. Lessons learned at West Valley during facility decontamination for re-use (1982--1988)

    Energy Technology Data Exchange (ETDEWEB)

    Tundo, D.; Gessner, R.F.; Lawrence, R.E.

    1988-11-01

    The primary mission of the West Valley Demonstration Project (WVDP) is to solidify a large volume of high-level liquid waste (2.3 million liters -- 600,000 gallons) produced during reprocessing plant operations and stored in underground tanks. This is to be accomplished through the maximum use of existing facilities. This required a significant effort to remove existing equipment and to decontaminate areas for installation of liquid and cement processing systems in a safe environment while maintaining exposure to workers as low as reasonably achievable. The reprocessing plant occupied a building of about 33,000 m/sup 2/ (350,000 ft/sup 2/). When the WVDP was initiated, approximately 6 percent of the plant area was in a non-contaminated condition where personnel could function without protective clothing or radiological controls. From 1982 to 1988, an additional 64 percent of the plant was cleaned up and much of this converted to low- and high-level waste processing areas. The high-level liquid and resulting low-level liquids are now being treated in these areas using an Integrated Radwaste Treatment System (IRTS). The Project has now focused attention on installation, qualification and operation of a vitrification system which will convert the remaining high-level waste into borosilicate glass logs. The stabilized waste will be sent to a Federal Repository for long-term storage. From 1982 to 1988, about 70 technical reports were dealing with specific tasks and cleanup efforts. This report provides an overview of the decontamination and decommissioning work done in that period. The report emphasizes lessons learned during that effort. Significant advances were made in: remote and contact decontamination technology; personnel protection and training; planning and procedures; and radiological controls. 62 refs., 35 figs., 5 tabs.

  10. Adaptive graph construction for Isomap manifold learning

    Science.gov (United States)

    Tran, Loc; Zheng, Zezhong; Zhou, Guoqing; Li, Jiang

    2015-03-01

    Isomap is a classical manifold learning approach that preserves geodesic distance of nonlinear data sets. One of the main drawbacks of this method is that it is susceptible to leaking, where a shortcut appears between normally separated portions of a manifold. We propose an adaptive graph construction approach that is based upon the sparsity property of the l1 norm. The l1 enhanced graph construction method replaces k-nearest neighbors in the classical approach. The proposed algorithm is first tested on the data sets from the UCI data base repository which showed that the proposed approach performs better than the classical approach. Next, the proposed approach is applied to two image data sets and achieved improved performances over standard Isomap.

  11. M-Learning: Implications in Learning Domain Specificities, Adaptive Learning, Feedback, Augmented Reality, and the Future of Online Learning

    Science.gov (United States)

    Squires, David R.

    2014-01-01

    The aim of this paper is to examine the potential and effectiveness of m-learning in the field of Education and Learning domains. The purpose of this research is to illustrate how mobile technology can and is affecting novel change in instruction, from m-learning and the link to adaptive learning, to the uninitiated learner and capacities of…

  12. Teacher-Led Design of an Adaptive Learning Environment

    Science.gov (United States)

    Mavroudi, Anna; Hadzilacos, Thanasis; Kalles, Dimitris; Gregoriades, Andreas

    2016-01-01

    This paper discusses a requirements engineering process that exemplifies teacher-led design in the case of an envisioned system for adaptive learning. Such a design poses various challenges and still remains an open research issue in the field of adaptive learning. Starting from a scenario-based elicitation method, the whole process was highly…

  13. Adaptive Web-Based Instruction for Enhancing Learning Ability

    OpenAIRE

    Techataweewan, Wawta

    2010-01-01

    International audience; Web technology in an instructional environment is primarily dedicated to distributing course materials to supplement traditional classroom learning. It also uses designed intelligence to adapt to learners' specific needs. The main purposes of this study were to construct and determine the efficiency of adaptive web-based instruction for LIS students. The web-based content was designed to adapt to three levels of learning ability: high, moderate and low. The system auto...

  14. Development of Adaptive Mobile Learning (AML on Information System Courses

    Directory of Open Access Journals (Sweden)

    I Made Agus Wirawan

    2015-12-01

    Full Text Available In general, the learning process is done conventionally, where the learning process is done face to face between teachers with learners in the classroom. Teachers have a very important role in determining the quantity and quality of the implementation study. Therefore, teachers must think and plan carefully to improve learning opportunities for learners and improve the quality of teaching. Along with the development of mobile technology and communication is rapidly increasing, enabling the learning process is not only done in the classroom, but can be done anywhere and anytime. Based on the analysis of the results of observations in the class conducted by a researcher and as a teacher in the learning courses of Information Systems, found some obstacles encountered during the learning process This research is to develop an Adaptive Mobile Learning on Information Systems courses. The method used in this research is the development of research methods (research and development, which selected the design development using System Development Life Cycle model. Adaptive Mobile Learning will be validated and tested through three phases of testing are: (1 Product technical test as a software. (2 Testing of the product as a medium of learning, through expert review by a media expert, (3 Field test to evaluate the response of the students that learned Adaptive Mobile Learning. The results show that Adaptive Mobile Learning software is can present the material in the course of Information Systems. Media Adaptive Mobile Learning can be used as an alternative medium (supplement of learning Information Systems courses. The response of students to the development and use of software for Adaptive Mobile Learning Information Systems courses is likely to very positive, which is at 67.7% very positive and 32.3% is positive.

  15. Adaptation of courses for trans-European tele-learning

    NARCIS (Netherlands)

    Collis, B.; Parisi, D.; Ligorio, B.

    1996-01-01

    This paper addresses the problems of adapting instructional courses for trans-European tele-learning and for enlarging the range of students and learning modalities in distance learning. Building on previous work on the portability of educational software, the paper examines various dimensions of ad

  16. Adaptation of courses for trans-European tele-learning

    NARCIS (Netherlands)

    Collis, Betty; Parisi, D.; Ligorio, B.

    1996-01-01

    This paper addresses the problems of adapting instructional courses for trans-European tele-learning and for enlarging the range of students and learning modalities in distance learning. Building on previous work on the portability of educational software, the paper examines various dimensions of ad

  17. Adaptive Device Context Based Mobile Learning Systems

    Science.gov (United States)

    Pu, Haitao; Lin, Jinjiao; Song, Yanwei; Liu, Fasheng

    2011-01-01

    Mobile learning is e-learning delivered through mobile computing devices, which represents the next stage of computer-aided, multi-media based learning. Therefore, mobile learning is transforming the way of traditional education. However, as most current e-learning systems and their contents are not suitable for mobile devices, an approach for…

  18. Adaptive Device Context Based Mobile Learning Systems

    Science.gov (United States)

    Pu, Haitao; Lin, Jinjiao; Song, Yanwei; Liu, Fasheng

    2011-01-01

    Mobile learning is e-learning delivered through mobile computing devices, which represents the next stage of computer-aided, multi-media based learning. Therefore, mobile learning is transforming the way of traditional education. However, as most current e-learning systems and their contents are not suitable for mobile devices, an approach for…

  19. 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.

  20. How to Represent Adaptation in e-Learning with IMS Learning Design

    Science.gov (United States)

    Burgos, Daniel; Tattersall, Colin; Koper, Rob

    2007-01-01

    Adaptation in e-learning has been an important research topic for the last few decades in computer-based education. In adaptivity the behaviour of the user triggers some actions in the system that guides the learning process. In adaptability, the user makes changes and takes decisions. Progressing from computer-based training and adaptive…

  1. 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.…

  2. 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.…

  3. Urban regeneration in the context of climate change, on the example of adaptive re-use of the military complex in the Bela Crkva

    Directory of Open Access Journals (Sweden)

    Manić Božidar

    2015-01-01

    Full Text Available The challenges of sustainable development and climate change open up the new possibilities in understanding the importance, principles and methodologies of urban renewal. The paper discusses the problem of abandoned buildings and complexes and their possible reuse in the context of climate change and sustainability at an example of the study of repurposing the military barracks complex in Bela Crkva conducted in the Institute of Architecture and Urban & Spatial Planning of Serbia in 2012. The conceptual solution of the variant 2, based on the idea of climate-aware and socially responsible design, has been embedded into the basic program scheme of the new complex, which includes the establishment of a university campus, construction of experimental social housing, cultural and artistic facilities, as well as urban agriculture, including the use of alternative energy sources and respecting the principles of energy efficiency. The problems of the abandonment of military buildings and complexes, as well as the recommendations for their adaptation, taking into account the past experience and the current environmental problems, are pointed out in the concluding remarks.

  4. Adjusting Felder-Silverman learning styles model for application in adaptive e-learning

    OpenAIRE

    Mihailović Đorđe; Despotović-Zrakić Marijana; Bogdanović Zorica; Barać Dušan; Vujin Vladimir

    2012-01-01

    This paper presents an approach for adjusting Felder-Silverman learning styles model for application in development of adaptive e-learning systems. Main goal of the paper is to improve the existing e-learning courses by developing a method for adaptation based on learning styles. The proposed method includes analysis of data related to students characteristics and applying the concept of personalization in creating e-learning courses. The research has been conducted at Faculty of organi...

  5. Diminished neural adaptation during implicit learning in autism.

    Science.gov (United States)

    Schipul, Sarah E; Just, Marcel Adam

    2016-01-15

    Neuroimaging studies have shown evidence of disrupted neural adaptation during learning in individuals with autism spectrum disorder (ASD) in several types of tasks, potentially stemming from frontal-posterior cortical underconnectivity (Schipul et al., 2012). The aim of the current study was to examine neural adaptations in an implicit learning task that entails participation of frontal and posterior regions. Sixteen high-functioning adults with ASD and sixteen neurotypical control participants were trained on and performed an implicit dot pattern prototype learning task in a functional magnetic resonance imaging (fMRI) session. During the preliminary exposure to the type of implicit prototype learning task later to be used in the scanner, the ASD participants took longer than the neurotypical group to learn the task, demonstrating altered implicit learning in ASD. After equating task structure learning, the two groups' brain activation differed during their learning of a new prototype in the subsequent scanning session. The main findings indicated that neural adaptations in a distributed task network were reduced in the ASD group, relative to the neurotypical group, and were related to ASD symptom severity. Functional connectivity was reduced and did not change as much during learning for the ASD group, and was related to ASD symptom severity. These findings suggest that individuals with ASD show altered neural adaptations during learning, as seen in both activation and functional connectivity measures. This finding suggests why many real-world implicit learning situations may pose special challenges for ASD.

  6. A Competency-Based Guided-Learning Algorithm Applied on Adaptively Guiding E-Learning

    Science.gov (United States)

    Hsu, Wei-Chih; Li, Cheng-Hsiu

    2015-01-01

    This paper presents a new algorithm called competency-based guided-learning algorithm (CBGLA), which can be applied on adaptively guiding e-learning. Computational process analysis and mathematical derivation of competency-based learning (CBL) were used to develop the CBGLA. The proposed algorithm could generate an effective adaptively guiding…

  7. INTUITEL and the Hypercube Model - Developing Adaptive Learning Environments

    Directory of Open Access Journals (Sweden)

    Kevin Fuchs

    2016-06-01

    Full Text Available In this paper we introduce an approach for the creation of adaptive learning environments that give human-like recommendations to a learner in the form of a virtual tutor. We use ontologies defining pedagogical, didactic and learner-specific data describing a learner's progress, learning history, capabilities and the learner's current state within the learning environment. Learning recommendations are based on a reasoning process on these ontologies and can be provided in real-time. The ontologies may describe learning content from any domain of knowledge. Furthermore, we describe an approach to store learning histories as spatio-temporal trajectories and to correlate them with influencing didactic factors. We show how such analysis of spatiotemporal data can be used for learning analytics to improve future adaptive learning environments.

  8. Learning and complexity in genetic auto-adaptive systems

    CERN Document Server

    Adami, C

    1994-01-01

    We describe and investigate the learning capablities displayed by a population of self-replicating segments of computer-code subject to random mutation: the tierra environment. We find that learning is achieved through phase transitions that adapt the population to whichever environment it encounters, with a learning rate characterized by the environmental variables. Our results suggest that most effective learning is achieved close to the edge of chaos.

  9. Anticipatory Learning for Climate Change Adaptation and Resilience

    Directory of Open Access Journals (Sweden)

    Petra Tschakert

    2010-06-01

    Full Text Available This paper is a methodological contribution to emerging debates on the role of learning, particularly forward-looking (anticipatory learning, as a key element for adaptation and resilience in the context of climate change. First, we describe two major challenges: understanding adaptation as a process and recognizing the inadequacy of existing learning tools, with a specific focus on high poverty contexts and complex livelihood-vulnerability risks. Then, the article examines learning processes from a dynamic systems perspective, comparing theoretical aspects and conceptual advances in resilience thinking and action research/learning (AR/AL. Particular attention is paid to learning loops (cycles, critical reflection, spaces for learning, and power. Finally, we outline a methodological framework to facilitate iterative learning processes and adaptive decision making in practice. We stress memory, monitoring of key drivers of change, scenario planning, and measuring anticipatory capacity as crucial ingredients. Our aim is to identify opportunities and obstacles for forward-looking learning processes at the intersection of climatic uncertainty and development challenges in Africa, with the overarching objective to enhance adaptation and resilient livelihood pathways, rather than learning by shock.

  10. Creating adaptive environment for e-learning courses

    Directory of Open Access Journals (Sweden)

    Bozidar Radenkovic

    2009-06-01

    Full Text Available In this paper we provide an approach to creating adaptive environment for e-learning courses. In the context of e-education, successful adaptation has to be performed upon learners’ characteristics. Currently, modeling and discovering users’ needs, goals, knowledge preferences and motivations is one of the most challenging tasks in e-learning systems that deal with large volumes of information. Primary goal of the research is to perform personalizing of distance education system, according to students’ learning styles. Main steps and requirements in applying business intelligence techniques in process of personalization are identified. In addition, we propose generic model and architecture of an adaptive e-learning system by describing the structure of an adaptive course and exemplify correlations among e-learning course content and different learning styles. Moreover, research that dealt with application of data mining technique in a real e-learning system was carried out. We performed adaptation of our e-learning courses using the results from the research.

  11. Adaptive Data Stream Management System Using Learning Automata

    CERN Document Server

    Mohammadi, Shirin; Abdi, Fatemeh; Haghjoo, Mostafa S

    2011-01-01

    In many modern applications, data are received as infinite, rapid, unpredictable and time- variant data elements that are known as data streams. Systems which are able to process data streams with such properties are called Data Stream Management Systems (DSMS). Due to the unpredictable and time- variant properties of data streams as well as system, adaptivity of the DSMS is a major requirement for each DSMS. Accordingly, determining parameters which are effective on the most important performance metric of a DSMS (i.e., response time) and analysing them will affect on designing an adaptive DSMS. In this paper, effective parameters on response time of DSMS are studied and analysed and a solution is proposed for DSMSs' adaptivity. The proposed adaptive DSMS architecture includes a learning unit that frequently evaluates system to adjust the optimal value for each of tuneable effective. Learning Automata is used as the learning mechanism of the learning unit to adjust the value of tuneable effective parameters....

  12. Adaptive functioning in children with epilepsy and learning problems.

    Science.gov (United States)

    Buelow, Janice M; Perkins, Susan M; Johnson, Cynthia S; Byars, Anna W; Fastenau, Philip S; Dunn, David W; Austin, Joan K

    2012-10-01

    In the study we describe adaptive functioning in children with epilepsy whose primary caregivers identified them as having learning problems. This was a cross-sectional study of 50 children with epilepsy and learning problems. Caregivers supplied information regarding the child's adaptive functioning and behavior problems. Children rated their self-concept and completed a battery of neuropsychological tests. Mean estimated IQ (PPVT-III) in the participant children was 72.8 (SD = 18.3). On average, children scored 2 standard deviations below the norm on the Vineland Adaptive Behavior Scale-II and this was true even for children with epilepsy who had estimated IQ in the normal range. In conclusion, children with epilepsy and learning problems had relatively low adaptive functioning scores and substantial neuropsychological and mental health problems. In epilepsy, adaptive behavior screening can be very informative and guide further evaluation and intervention, even in those children whose IQ is in the normal range.

  13. Creating Adaptive Environment for e-Learning Courses

    OpenAIRE

    Bozidar Radenkovic; Marijana Despotovic; Zorica Bogdanovic; Dusan Barac

    2009-01-01

    In this paper we provide an approach to creating adaptive environment for e-learning courses. In the context of e-education, successful adaptation has to be performed upon learners’ characteristics. Currently, modeling and discovering users’ needs, goals, knowledge preferences and motivations is one of the most challenging tasks in e-learning systems that deal with large volumes of information. Primary goal of the research is to perform personalizing of distance education ...

  14. THE RETHINKING OF THE CONSERVATION AND ADAPTIVE REUSE OF HISTORIC INDUSTRIAL BUILDINGS FROM APOCALYPSE OF BRITAIN%从英国对旧工业建筑的保护利用谈中国旧工业的保护

    Institute of Scientific and Technical Information of China (English)

    苏夏

    2012-01-01

    The sustainable reuse of historic industrial buildings hasn' t been a brand new topic. Since the day when these buildings were completed, the ways of use and reuse are keeping on changing. But this kind of reuse is also based on the industrial process while the reuse based on the conservation and non-industrial purposes hasn' t begun until 1950s. In the field of conservation and adaptive reuse of industrial buildings, west Europe is no-doubt ahead of others in the world. From the apocalypse of the reuse of industrial building heritages in Britain and some relevant cases in Germany and France, and by the contract of that in Britain and in China, the situation and the patterns of conservation and adaptive reuse of industrial buildings in China were discussed.%旧工业建筑的可持续性再利用已不是一个新的话题,几乎从这类建筑建成之日起就伴随着其最初使用目的的不断改变。但这种不断改变使用目的的再利用行为实际上还是一种在其本身使用功能范围内的变动,而真正意义上的对旧工业建筑的再利用,则是近50年左右的事情。在这方面,西欧各国毫无疑问是走在世界前列的。以英国旧工业建筑保护与再利用经验为重点,辅以德、法等国在这方面的成果案例,就西欧对旧工业建筑改造利用方面的宝贵经验进行介绍,旨在为我国现阶段旧工业建筑的保护和再利用提供有益的启示和帮助。

  15. Implementation of an Adaptive Learning System Using a Bayesian Network

    Science.gov (United States)

    Yasuda, Keiji; Kawashima, Hiroyuki; Hata, Yoko; Kimura, Hiroaki

    2015-01-01

    An adaptive learning system is proposed that incorporates a Bayesian network to efficiently gauge learners' understanding at the course-unit level. Also, learners receive content that is adapted to their measured level of understanding. The system works on an iPad via the Edmodo platform. A field experiment using the system in an elementary school…

  16. Integrating Adaptive Games in Student-Centered Virtual Learning Environments

    Science.gov (United States)

    del Blanco, Angel; Torrente, Javier; Moreno-Ger, Pablo; Fernandez-Manjon, Baltasar

    2010-01-01

    The increasing adoption of e-Learning technology is facing new challenges, such as how to produce student-centered systems that can be adapted to each student's needs. In this context, educational video games are proposed as an ideal medium to facilitate adaptation and tracking of students' performance for assessment purposes, but integrating the…

  17. A Learning Style Perspective to Investigate the Necessity of Developing Adaptive Learning Systems

    Science.gov (United States)

    Hwang, Gwo-Jen; Sung, Han-Yu; Hung, Chun-Ming; Huang, Iwen

    2013-01-01

    Learning styles are considered to be one of the factors that need to be taken into account in developing adaptive learning systems. However, few studies have been conducted to investigate if students have the ability to choose the best-fit e-learning systems or content presentation styles for themselves in terms of learning style perspective. In…

  18. A Game-Based Adaptive Unit of Learning with IMS Learning Design and

    NARCIS (Netherlands)

    Moreno-Ger, Pablo; Burgos, Daniel; Sierra, José Luis; Manjón, Baltasar Fernández

    2008-01-01

    Moreno-Ger, P., Burgos, D., Sierra, J. L., & Manjón, B. F. (2007). A Game-Based Adaptive Unit of Learning with IMS Learning Design and . In E. Duval, R. Klamma & M. Wolpers, Creating New Learning Experience on a Global Scale, Second European Conference on Technology Enhanced Learning, E

  19. Adaptive strategies for cumulative cultural learning.

    Science.gov (United States)

    Ehn, Micael; Laland, Kevin

    2012-05-21

    The demographic and ecological success of our species is frequently attributed to our capacity for cumulative culture. However, it is not yet known how humans combine social and asocial learning to generate effective strategies for learning in a cumulative cultural context. Here we explore how cumulative culture influences the relative merits of various pure and conditional learning strategies, including pure asocial and social learning, critical social learning, conditional social learning and individual refiner strategies. We replicate the Rogers' paradox in the cumulative setting. However, our analysis suggests that strategies that resolved Rogers' paradox in a non-cumulative setting may not necessarily evolve in a cumulative setting, thus different strategies will optimize cumulative and non-cumulative cultural learning.

  20. Instructional Design and Adaptation Issues in Distance Learning Via Satellite.

    Science.gov (United States)

    Thach, Liz

    1995-01-01

    Discusses a qualitative research study conducted in a distance-learning environment using satellite delivery. Describes changes in instructional design and adaptation issues which faculty and professionals involved in satellite-delivery learning situations used to be successful. (Author/AEF)

  1. Design Framework for an Adaptive MOOC Enhanced by Blended Learning

    DEFF Research Database (Denmark)

    Gynther, Karsten

    2016-01-01

    The research project has developed a design framework for an adaptive MOOC that complements the MOOC format with blended learning. The design framework consists of a design model and a series of learning design principles which can be used to design in-service courses for teacher professional...

  2. Design Framework for an Adaptive MOOC Enhanced by Blended Learning

    DEFF Research Database (Denmark)

    Gynther, Karsten

    2016-01-01

    The research project has developed a design framework for an adaptive MOOC that complements the MOOC format with blended learning. The design framework consists of a design model and a series of learning design principles which can be used to design in-service courses for teacher professional...

  3. Using Learning Design to Support Design and Runtime Adaptation

    NARCIS (Netherlands)

    Van Rosmalen, Peter; Boticario, Jesús

    2005-01-01

    Van Rosmalen, P. & Boticario, J. (2005). Using Learning Design to Support Design and Runtime Adaptation. In: Koper, R. & Tattersall, C., Learning Design: A Handbook on Modelling and Delivering Networked Education and Training (pp. 291-301). Berlin-Heidelberg: Springer Verlag.

  4. Solving Local Minima Problem in Back Propagation Algorithm Using Adaptive Gain, Adaptive Momentum and Adaptive Learning Rate on Classification Problems

    Science.gov (United States)

    Hamid, Norhamreeza Abdul; Nawi, Nazri Mohd; Ghazali, Rozaida; Salleh, Mohd Najib Mohd

    This paper presents a new method to improve back propagation algorithm from getting stuck with local minima problem and slow convergence speeds which caused by neuron saturation in the hidden layer. In this proposed algorithm, each training pattern has its own activation functions of neurons in the hidden layer that are adjusted by the adaptation of gain parameters together with adaptive momentum and learning rate value during the learning process. The efficiency of the proposed algorithm is compared with the conventional back propagation gradient descent and the current working back propagation gradient descent with adaptive gain by means of simulation on three benchmark problems namely iris, glass and thyroid.

  5. Learner Profile Management for Collaborative Adaptive eLearning Application

    DEFF Research Database (Denmark)

    Alrifai, Mohammad; Dolog, Peter; Nejdl, Wolfgang

    2006-01-01

    adaptive hypermedia systems. Existing Web Service standards, however, only provide very basic features and leave out many important issues like transactional management. In this paper we propose a mechanism for enabling consistency maintenance of Learner Profiles shared between collaborating adaptive......Adaptive Learning Systems would perform better if they would be able to exchange as many relevant fragments of information about the learner as possible. The use of Web Services standards is recently gaining the attention of many researches as a promising solution for the problem of interfacing...... learning systems....

  6. Learner Profile Management for Collaborative Adaptive eLearning Application

    DEFF Research Database (Denmark)

    Alrifai, Mohammad; Dolog, Peter; Nejdl, Wolfgang

    2006-01-01

    Adaptive Learning Systems would perform better if they would be able to exchange as many relevant fragments of information about the learner as possible. The use of Web Services standards is recently gaining the attention of many researches as a promising solution for the problem of interfacing...... adaptive hypermedia systems. Existing Web Service standards, however, only provide very basic features and leave out many important issues like transactional management. In this paper we propose a mechanism for enabling consistency maintenance of Learner Profiles shared between collaborating adaptive...... learning systems....

  7. 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.

  8. Conformal prediction for reliable machine learning theory, adaptations and applications

    CERN Document Server

    Balasubramanian, Vineeth; Vovk, Vladimir

    2014-01-01

    The conformal predictions framework is a recent development in machine learning that can associate a reliable measure of confidence with a prediction in any real-world pattern recognition application, including risk-sensitive applications such as medical diagnosis, face recognition, and financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory of the framework, demonstrates how to apply it to real-world problems, and presents several adaptations, including active learning, change detection, and anomaly detecti

  9. Towards an Adaptive competency-based learning System using assessment

    Directory of Open Access Journals (Sweden)

    Noureddine El Faddouli

    2011-01-01

    Full Text Available E-learning is not restricted to publishing online content. The challenge is to apply pedagogical models using new information and communication technologies in order to adjust the learning process. This adaptation will take place by proposing an adaptive learning system. There are several e-learning environment adaptation approaches such as adaptive hypermedia and semantic web. In our proposed system, we focus on evaluation that has not been, up till now, given its real value in the e-learning environment. The purpose is to implement an adaptive learning system for individualized pedagogical paths through a personalized diagnosis of learners' performances. This proposed system relies mainly on assessment and the competency-based approach as a framework. To achieve this goal, we adopt an enhanced cycle of formative assessment while adhering to a service-oriented architecture. The system will be implemented as an activity in a pedagogical scenario defined responding to the learner's needs, while aligning with norms and standards.

  10. Temporal Learning Analytics for Adaptive Assessment

    Science.gov (United States)

    Papamitsiou, Zacharoula; Economides, Anastasios A.

    2014-01-01

    Accurate and early predictions of student performance could significantly affect interventions during teaching and assessment, which gradually could lead to improved learning outcomes. In our research, we seek to identify and formalize temporal parameters as predictors of performance ("temporal learning analytics" or TLA) and examine…

  11. Adaptive Java Optimisation using machine learning techniques

    OpenAIRE

    Long, Shun

    2004-01-01

    There is a continuing demand for higher performance, particularly in the area of scientific and engineering computation. In order to achieve high performance in the context of frequent hardware upgrading, software must be adaptable for portable performance. What is required is an optimising compiler that evolves and adapts itself to environmental change without sacrificing performance. Java has emerged as a dominant programming language widely used in a variety of application areas. Howeve...

  12. 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.

  13. Adaptive segmentation of digital mammograms through reinforcement learning

    Institute of Scientific and Technical Information of China (English)

    LIU Xin-yue; FANG Xiao-xuan; HUANG Lian-qing

    2005-01-01

    An approach based on reinfocement learning for the automated segmentation is presented. The approach consists of two modules:segmentation module and learning module. The segmentation module uses the region-growing algorithm combined with the smooth filtering and the morphological filtering to segment mammograms. The learning module uses the segmentation output as the feedback to learn to select the optimal parameter settings of the segmentation algorithm according to the image properties using reinforcement learning techniques. The approach can adapt itself to various kinds of mammograms through training and therefore obviates the tedious and error-prone tuning of parameter settings manually. Quantitative test results show that the approach is accurate for several kinds of mammograms. Compared to previously proposed approaches,the approach is more adaptable to different mammograms.

  14. Limits of Software Reuse

    NARCIS (Netherlands)

    Holenderski, L.

    2006-01-01

    Software reuse is considered one of the main techniques to increasesoftware productivity. We present two simple mathematical argumentsthat show some theoretical limits of reuse. It turns out that the increase of productivity due to internal reuse is at most linear, farfrom the needed exponential gr

  15. Achieving Adaptability through Inquiry Based Learning

    Science.gov (United States)

    2010-06-01

    knowledge. IBL is based on a different conception of learning, one traceable back to John Dewey (1910) and Jean Piaget (1972; von Glasersfeld, 1995) and...Dewey, 1910; Duffy 2009; Piaget , 1972; Schank, Fano, Bell, and Jona, 1993). If the learners are focused on figuring out what the instructor wants...errors or the inability to fully make sense of a situation provides the basis for learning ( Piaget , 1973; Schank, et al, 1993). Thus the errors

  16. Learning & retention in adaptive serious games.

    Science.gov (United States)

    Bergeron, Bryan P

    2008-01-01

    Serious games are being actively explored as supplements to and, in some cases, replacement for traditional didactic lectures and computer-based instruction in venues ranging from medicine to the military. As part of an intelligent tutoring system (ITS) for nuclear event first responders, we designed and evaluated two serious games that were integrated with adaptive multimedia content. Results reveal that there was no decay in score six weeks following game-based training, which contrasts with results expected with traditional training. This study suggests that adaptive serious games may help integrate didactic content presented though conventional means.

  17. Authoring Game-Based Adaptive Units of Learning with IMS Learning Design and

    OpenAIRE

    Burgos, Daniel; Moreno-Ger, Pablo; Sierra, José Luis; Fernández Manjón, Baltasar; Koper, Rob

    2007-01-01

    Burgos, D., Moreno-Ger, P., Sierra, J. L., Fernández Manjón, B., & Kooper, R. (2007). Authoring Game-Based Adaptive Units of Learning with IMS Learning Design and . International Journal of Learning Technology, 3(3), 252-268.

  18. Authoring Game-Based Adaptive Units of Learning with IMS Learning Design and

    NARCIS (Netherlands)

    Burgos, Daniel; Moreno-Ger, Pablo; Sierra, José Luis; Fernández Manjón, Baltasar; Koper, Rob

    2007-01-01

    Burgos, D., Moreno-Ger, P., Sierra, J. L., Fernández Manjón, B., & Kooper, R. (2007). Authoring Game-Based Adaptive Units of Learning with IMS Learning Design and . International Journal of Learning Technology, 3(3), 252-268.

  19. Aligning Instruction to Individual Learning Needs in Adaptive Hypertext Learning Environments

    NARCIS (Netherlands)

    Bezdan, Eniko; Kester, Liesbeth; Kirschner, Paul A.

    2011-01-01

    Bezdan, E., Kester, L., & Kirschner, P. A. (2011, 31 August). Aligning Instruction to Individual Learning Needs in Adaptive Hypertext Learning Environments. Presentation at the 14th Biennial Conference of the European Association for Research on Learning and Instruction, Exeter, United Kingdom.

  20. Conflict Adaptation by Means of Associative Learning

    Science.gov (United States)

    Braem, Senne; Verguts, Tom; Notebaert, Wim

    2011-01-01

    Cognitive control is responsible for adapting information processing in order to carry out tasks more efficiently. Contrasting global versus local control accounts, it has recently been proposed that control operates in an associative fashion, that is, by binding stimulus-response associations after detection of conflict (Verguts & Notebaert,…

  1. 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.

  2. Human hyolaryngeal movements show adaptive motor learning during swallowing.

    Science.gov (United States)

    Humbert, Ianessa A; Christopherson, Heather; Lokhande, Akshay; German, Rebecca; Gonzalez-Fernandez, Marlis; Celnik, Pablo

    2013-06-01

    The hyoid bone and larynx elevate to protect the airway during swallowing. However, it is unknown whether hyolaryngeal movements during swallowing can adjust and adapt to predict the presence of a persistent perturbation in a feed-forward manner (adaptive motor learning). We investigated adaptive motor learning in nine healthy adults. Electrical stimulation was administered to the anterior neck to reduce hyolaryngeal elevation, requiring more strength to swallow during the perturbation period of this study. We assessed peak hyoid bone and laryngeal movements using videofluoroscopy across thirty-five 5-ml water swallows. Evidence of adaptive motor learning of hyolaryngeal movements was found when (1) participants showed systematic gradual increases in elevation against the force of electrical stimulation and (2) hyolaryngeal elevation overshot the baseline (preperturbation) range of motion, showing behavioral aftereffects, when the perturbation was unexpectedly removed. Hyolaryngeal kinematics demonstrates adaptive, error-reducing movements in the presence of changing and unexpected demands. This is significant because individuals with dysphagia often aspirate due to disordered hyolaryngeal movements. Thus, if rapid motor learning is accessible during swallowing in healthy adults, patients may be taught to predict the presence of perturbations and reduce errors in swallowing before they occur.

  3. Online Adaptation of Game AI with Evolutionary Learning

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Since the beginning of computer games era,artificial intelligence (AI) has been a standard feature of games. The current emphasis in computer game AI is improving the quality of opponent AI. Our research question reads: How can unsupervised online learning be incorporated in Computer Role Playing Game (CRPG) to improve the strategy of the opponent AI? Our goal is to use online evolutionary learning to design strategies that can defeat the opponent. So we apply a novel technique called dynamic scripting that realizes online adaptation of scripted opponent AI and report on experiments performed in a simulated CRPG to assess the adaptive performance obtained with the technique.

  4. Organisational learning and self-adaptation in dynamic disaster environments.

    Science.gov (United States)

    Corbacioglu, Sitki; Kapucu, Naim

    2006-06-01

    This paper examines the problems associated with inter-organisational learning and adaptation in the dynamic environments that characterise disasters. The research uses both qualitative and quantitative methods to investigate whether organisational learning took place during and in the time in between five disaster response operations in Turkey. The availability of information and its exchange and distribution within and among organisational actors determine whether self-adaptation happens in the course of a disaster response operation. Organisational flexibility supported by an appropriate information infrastructure creates conditions conducive to essential interaction and permits the flow of information. The study found that no significant organisational learning occurred within Turkish disaster management following the earthquakes in Erzincan (1992), Dinar (1995) and Ceyhan (1998). By contrast, the 'symmetry-breaking' Marmara earthquake of 1999 initiated a 'double loop' learning process that led to change in the organisational, technical and cultural aspects of Turkish disaster management, as revealed by the Duzce earthquake response operations.

  5. Enhancing Student Adaption to a Case Based Learning Environment

    DEFF Research Database (Denmark)

    Jensen, Lars Peter

    2010-01-01

    ) in groups. It appeared to be difficult for the students to adapt to two different PBL approaches at the same time, and with the project being the most popular the learning outcome of the case studies was not satisfactory after the first semester, but improved on the following semesters. In 2009......) was designed to help the students adapt to the case model. It deals with subjects like learning theory and learning styles, communication and problem solving, organisation and management of cases and a lot of experience and best praxis exchange. The subjects are presented in a combination of short lectures......INTRODUCTION Since Aalborg University (AAU) was started it has been using an educational model, where Problem Based Learning is the turning point. Each semester the students on the Engineering Educations form groups of 3-6 persons, which uses half of the study time within the semester to solve...

  6. Modelling Adaptive Learning Behaviours for Consensus Formation in Human Societies

    Science.gov (United States)

    Yu, Chao; Tan, Guozhen; Lv, Hongtao; Wang, Zhen; Meng, Jun; Hao, Jianye; Ren, Fenghui

    2016-06-01

    Learning is an important capability of humans and plays a vital role in human society for forming beliefs and opinions. In this paper, we investigate how learning affects the dynamics of opinion formation in social networks. A novel learning model is proposed, in which agents can dynamically adapt their learning behaviours in order to facilitate the formation of consensus among them, and thus establish a consistent social norm in the whole population more efficiently. In the model, agents adapt their opinions through trail-and-error interactions with others. By exploiting historical interaction experience, a guiding opinion, which is considered to be the most successful opinion in the neighbourhood, can be generated based on the principle of evolutionary game theory. Then, depending on the consistency between its own opinion and the guiding opinion, a focal agent can realize whether its opinion complies with the social norm (i.e., the majority opinion that has been adopted) in the population, and adapt its behaviours accordingly. The highlight of the model lies in that it captures the essential features of people’s adaptive learning behaviours during the evolution and formation of opinions. Experimental results show that the proposed model can facilitate the formation of consensus among agents, and some critical factors such as size of opinion space and network topology can have significant influences on opinion dynamics.

  7. Auditory-perceptual learning improves speech motor adaptation in children.

    Science.gov (United States)

    Shiller, Douglas M; Rochon, Marie-Lyne

    2014-08-01

    Auditory feedback plays an important role in children's speech development by providing the child with information about speech outcomes that is used to learn and fine-tune speech motor plans. The use of auditory feedback in speech motor learning has been extensively studied in adults by examining oral motor responses to manipulations of auditory feedback during speech production. Children are also capable of adapting speech motor patterns to perceived changes in auditory feedback; however, it is not known whether their capacity for motor learning is limited by immature auditory-perceptual abilities. Here, the link between speech perceptual ability and the capacity for motor learning was explored in two groups of 5- to 7-year-old children who underwent a period of auditory perceptual training followed by tests of speech motor adaptation to altered auditory feedback. One group received perceptual training on a speech acoustic property relevant to the motor task while a control group received perceptual training on an irrelevant speech contrast. Learned perceptual improvements led to an enhancement in speech motor adaptation (proportional to the perceptual change) only for the experimental group. The results indicate that children's ability to perceive relevant speech acoustic properties has a direct influence on their capacity for sensory-based speech motor adaptation.

  8. Biomimetic molecular design tools that learn, evolve, and adapt

    Science.gov (United States)

    2017-01-01

    A dominant hallmark of living systems is their ability to adapt to changes in the environment by learning and evolving. Nature does this so superbly that intensive research efforts are now attempting to mimic biological processes. Initially this biomimicry involved developing synthetic methods to generate complex bioactive natural products. Recent work is attempting to understand how molecular machines operate so their principles can be copied, and learning how to employ biomimetic evolution and learning methods to solve complex problems in science, medicine and engineering. Automation, robotics, artificial intelligence, and evolutionary algorithms are now converging to generate what might broadly be called in silico-based adaptive evolution of materials. These methods are being applied to organic chemistry to systematize reactions, create synthesis robots to carry out unit operations, and to devise closed loop flow self-optimizing chemical synthesis systems. Most scientific innovations and technologies pass through the well-known “S curve”, with slow beginning, an almost exponential growth in capability, and a stable applications period. Adaptive, evolving, machine learning-based molecular design and optimization methods are approaching the period of very rapid growth and their impact is already being described as potentially disruptive. This paper describes new developments in biomimetic adaptive, evolving, learning computational molecular design methods and their potential impacts in chemistry, engineering, and medicine. PMID:28694872

  9. Soft systems thinking and social learning for adaptive management.

    Science.gov (United States)

    Cundill, G; Cumming, G S; Biggs, D; Fabricius, C

    2012-02-01

    The success of adaptive management in conservation has been questioned and the objective-based management paradigm on which it is based has been heavily criticized. Soft systems thinking and social-learning theory expose errors in the assumption that complex systems can be dispassionately managed by objective observers and highlight the fact that conservation is a social process in which objectives are contested and learning is context dependent. We used these insights to rethink adaptive management in a way that focuses on the social processes involved in management and decision making. Our approach to adaptive management is based on the following assumptions: action toward a common goal is an emergent property of complex social relationships; the introduction of new knowledge, alternative values, and new ways of understanding the world can become a stimulating force for learning, creativity, and change; learning is contextual and is fundamentally about practice; and defining the goal to be addressed is continuous and in principle never ends. We believe five key activities are crucial to defining the goal that is to be addressed in an adaptive-management context and to determining the objectives that are desirable and feasible to the participants: situate the problem in its social and ecological context; raise awareness about alternative views of a problem and encourage enquiry and deconstruction of frames of reference; undertake collaborative actions; and reflect on learning. ©2011 Society for Conservation Biology.

  10. Learning styles, personalisation and adaptable e-learning

    OpenAIRE

    Peter, Sophie A.; Bacon, Elizabeth; Dastbaz, Mohammad

    2009-01-01

    Common Learning Management Systems (for example Moodle [1] and Blackboard [2]) are limited in the amount of personalisation that they can offer the learner. They are used widely and do offer a number of tools for instructors to enable them to create and manage courses, however, they do not allow for the learner to have a unique personalised learning experience. The e-Learning platform iLearn offers personalisation for the learner in a number of ways and one way is to offer the specific learni...

  11. Fuzzy adaptive learning control network with sigmoid membership function

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    To get simpler operation in modified fuzzy adaptive learning control network (FALCON) in some engineering application, sigmoid nonlinear function is employed as a substitute of traditional Gaussian membership function. For making the modified FALCON learning more efficient and stable, a simulated annealing (SA) learning coefficient is introduced into learning algorithm. At first, the basic concepts and main advantages of FALCON were briefly reviewed. Subsequently, the topological structure and nodes operation were illustrated; the gradient-descent learning algorithm with SA learning coefficient was derived;and the distinctions between the archetype and the modification were analyzed. Eventually, the significance and worthiness of the modified FALCON were validated by its application to probability prediction of anode effect in aluminium electrolysis cells.

  12. Revisiting the Didactic Triangle in the Case of an Adaptive Learning System

    Directory of Open Access Journals (Sweden)

    Yassine Zaoui Seghroucheni

    2014-10-01

    Full Text Available In this paper we revisit the classical approach of the didactic triangle designed for the classical learning situation (face to face and adapt it to the situation of an adaptive learning system, we discuss also the different components involved in this didactic triangle and how they interact and influence the learning process in an adaptive learning system.

  13. A Proposal of Adaptive PID Controller Based on Reinforcement Learning

    Institute of Scientific and Technical Information of China (English)

    WANG Xue-song; CHENG Yu-hu; SUN Wei

    2007-01-01

    Aimed at the lack of self-tuning PID parameters in conventional PID controllers, the structure and learning algorithm of an adaptive PID controller based on reinforcement learning were proposed. Actor-Critic learning was used to tune PID parameters in an adaptive way by taking advantage of the model-free and on-line learning properties of reinforcement learning effectively. In order to reduce the demand of storage space and to improve the learning efficiency,a single RBF neural network was used to approximate the policy function of Actor and the value function of Critic simultaneously. The inputs of RBF network are the system error, as well as the first and the second-order differences of error. The Actor can realize the mapping from the system state to PID parameters, while the Critic evaluates the outputs of the Actor and produces TD error. Based on TD error performance index and gradient descent method, the updating rules of RBF kernel function and network weights were given. Simulation results show that the proposed controller is efficient for complex nonlinear systems and it is perfectly adaptable and strongly robust, which is better than that of a conventional PID controller.

  14. A Game-Based Adaptive Unit of Learning with IMS Learning Design and

    OpenAIRE

    Moreno-Ger, Pablo; Burgos, Daniel; Sierra, José Luis; Manjón, Baltasar Fernández

    2008-01-01

    Moreno-Ger, P., Burgos, D., Sierra, J. L., & Manjón, B. F. (2007). A Game-Based Adaptive Unit of Learning with IMS Learning Design and . In E. Duval, R. Klamma & M. Wolpers, Creating New Learning Experience on a Global Scale, Second European Conference on Technology Enhanced Learning, EC-TEL 2007 (pp. 247-261). September, 2007, Crete, Greece: Lecture Notes in Computer Science 4753 (Springer)

  15. Motor learning cannot explain stuttering adaptation.

    Science.gov (United States)

    Venkatagiri, Horabail S; Nataraja, Nuggehalli P; Deepthi, M

    2013-08-01

    When persons who stutter (PWS) read a text repeatedly, there is a progressive reduction in stutter frequency over the course of three to five readings. Recently, this phenomenon has been attributed by some researchers to motor learning-the acquisition of relatively permanent motor skills that facilitate fluency through practice in producing words. The current study tested this explanation. 23 PWS read prose passages five times in succession. The number of 'new' and 'old' stutters during repeated readings (words stuttered in the current reading but spoken fluently in the previous reading and words stuttered also in the previous reading) were analyzed. If motor learning facilitated fluency during repeated readings in PWS, words read fluently in a reading should not be stuttered in a later reading in significant numbers. Contrary to this prediction, there was no statistical difference in the number of new words stuttered across five readings. A plausible alternative explanation, which requires further study to verify, is offered.

  16. SaGe Framework - Mapping of SARSA to Adaptive e-Learning using Learning Styles

    Directory of Open Access Journals (Sweden)

    Balasubramanian Velusamy

    2013-04-01

    Full Text Available This paper proposes a mathematical framework – the SaGe framework, which maps the adaptive nature of the e-learning environment to the reinforcement learning approach. An adaptive elearning system works in a similar fashion to an intelligent agent that assesses the various interactions of the user with the system, learns from these interactions and uses this knowledge base to select the best possible action to earn the maximum reward. This is the same methodology of reinforcement learning. The adaptive nature of the e-learning environment is provided by the assessment of the individual differences in the learning styles of the students. In our approach we chose the learning styles provided by the dimensions of the Felder-Silverman Learning Style Model (FSLSM and the SARSA algorithm for thereinforcement learning. Mapping of the reinforcement SARSA algorithm to an adaptive e-learning system is asserted by the time-based update of the Q-values of the SARSA algorithm.

  17. Mispronunciation Detection for Language Learning and Speech Recognition Adaptation

    Science.gov (United States)

    Ge, Zhenhao

    2013-01-01

    The areas of "mispronunciation detection" (or "accent detection" more specifically) within the speech recognition community are receiving increased attention now. Two application areas, namely language learning and speech recognition adaptation, are largely driving this research interest and are the focal points of this work.…

  18. Adaptivity in Educational Systems for Language Learning: A Review

    Science.gov (United States)

    Slavuj, Vanja; Meštrovic, Ana; Kovacic, Božidar

    2017-01-01

    Adaptive and intelligent instructional systems are used to deal with the issue of learning personalisation in contexts where human instructors are not immediately available, so their role is transferred entirely or in part onto the computer. Even though such systems are mostly developed for well-defined domains that have a rather straightforward…

  19. Adaptive Knowledge Management of Project-Based Learning

    Science.gov (United States)

    Tilchin, Oleg; Kittany, Mohamed

    2016-01-01

    The goal of an approach to Adaptive Knowledge Management (AKM) of project-based learning (PBL) is to intensify subject study through guiding, inducing, and facilitating development knowledge, accountability skills, and collaborative skills of students. Knowledge development is attained by knowledge acquisition, knowledge sharing, and knowledge…

  20. Mispronunciation Detection for Language Learning and Speech Recognition Adaptation

    Science.gov (United States)

    Ge, Zhenhao

    2013-01-01

    The areas of "mispronunciation detection" (or "accent detection" more specifically) within the speech recognition community are receiving increased attention now. Two application areas, namely language learning and speech recognition adaptation, are largely driving this research interest and are the focal points of this work.…

  1. Heterogeneous Users in MOOC and their Adaptive Learning Needs

    Directory of Open Access Journals (Sweden)

    María Luisa SEIN-ECHALUCE LACLETA

    2017-02-01

    Full Text Available Many research works point out the overcrowding and the heterogeneity of participant’s profiles in Massive Open Online Courses (MOOC as the main causes of their low completion rate. On the other hand, the methodologies of personalization of the learning, along next to the technologies of the information, that allows to realize techniques of adaptativity, appear in international reports as an effective way to improve the learning. This paper explores the participante’ perception of their adaptive needs in this tupe of course, as well as their relationship with different aspects of the participants, such as: profiles (gender, age, geographical location and academic level, previous experience and knowledge about the topic of the MOOC and motivation to enroll the MOOC. The study is carried out through a survey completes by the participants in the MOOC Campus of Educational Innovation. We conclude that the age or gender of the participants does not significantly influence their need for adaptive techniques in a MOOC. However, living in a Latin American country, working as a manager or enrolling in a MOOC with a specific motivation, are some of the factors that influence in the desire for adaptive techniques in a MOOC. The obtained results will contribute to improve the adaptive designs of the MOOC and will be easily transferable to any online training course, in blended or virtual learning.

  2. ADOPEL: ADAPTIVE DATA COLLECTION PROTOCOL USING REINFORCEMENT LEARNING FOR VANETS

    Directory of Open Access Journals (Sweden)

    Ahmed Soua

    2014-01-01

    Full Text Available Efficient propagation of information over a vehicular wireless network has usually remained the focus of the research community. Although, scanty contributions have been made in the field of vehicular data collection and more especially in applying learning techniques to such a very changing networking scheme. These smart learning approaches excel in making the collecting operation more reactive to nodes mobility and topology changes compared to traditional techniques where a simple adaptation of MANETs propositions was carried out. To grasp the efficiency opportunities offered by these learning techniques, an Adaptive Data collection Protocol using reinforcement Learning (ADOPEL is proposed for VANETs. The proposal is based on a distributed learning algorithm on which a reward function is defined. This latter takes into account the delay and the number of aggregatable packets. The Q-learning technique offers to vehicles the opportunity to optimize their interactions with the very dynamic environment through their experience in the network. Compared to non-learning schemes, our proposal confirms its efficiency and achieves a good tradeoff between delay and collection ratio.

  3. Adaptive Neural Network Nonparametric Identifier With Normalized Learning Laws.

    Science.gov (United States)

    Chairez, Isaac

    2016-04-05

    This paper addresses the design of a normalized convergent learning law for neural networks (NNs) with continuous dynamics. The NN is used here to obtain a nonparametric model for uncertain systems described by a set of ordinary differential equations. The source of uncertainties is the presence of some external perturbations and poor knowledge of the nonlinear function describing the system dynamics. A new adaptive algorithm based on normalized algorithms was used to adjust the weights of the NN. The adaptive algorithm was derived by means of a nonstandard logarithmic Lyapunov function (LLF). Two identifiers were designed using two variations of LLFs leading to a normalized learning law for the first identifier and a variable gain normalized learning law. In the case of the second identifier, the inclusion of normalized learning laws yields to reduce the size of the convergence region obtained as solution of the practical stability analysis. On the other hand, the velocity of convergence for the learning laws depends on the norm of errors in inverse form. This fact avoids the peaking transient behavior in the time evolution of weights that accelerates the convergence of identification error. A numerical example demonstrates the improvements achieved by the algorithm introduced in this paper compared with classical schemes with no-normalized continuous learning methods. A comparison of the identification performance achieved by the no-normalized identifier and the ones developed in this paper shows the benefits of the learning law proposed in this paper.

  4. Operating boundaries of full-scale advanced water reuse treatment plants: many lessons learned from pilot plant experience.

    Science.gov (United States)

    Bele, C; Kumar, Y; Walker, T; Poussade, Y; Zavlanos, V

    2010-01-01

    Three Advanced Water Treatment Plants (AWTP) have recently been built in South East Queensland as part of the Western Corridor Recycled Water Project (WCRWP) producing Purified Recycled Water from secondary treated waste water for the purpose of indirect potable reuse. At Luggage Point, a demonstration plant was primarily operated by the design team for design verification. The investigation program was then extended so that the operating team could investigate possible process optimisation, and operation flexibility. Extending the demonstration plant investigation program enabled monitoring of the long term performance of the microfiltration and reverse osmosis membranes, which did not appear to foul even after more than a year of operation. The investigation primarily identified several ways to optimise the process. It highlighted areas of risk for treated water quality, such as total nitrogen. Ample and rapid swings of salinity from 850 to 3,000 mg/l-TDS were predicted to affect the RO process day-to-day operation and monitoring. Most of the setpoints used for monitoring under HACCP were determined during the pilot plant trials.

  5. Reinforcement learning for adaptive dialogue systems

    CERN Document Server

    Rieser, Verena

    2011-01-01

    The past decade has seen a revolution in the field of spoken dialogue systems. As in other areas of Computer Science and Artificial Intelligence, data-driven methods are now being used to drive new methodologies for system development and evaluation. This book is a unique contribution to that ongoing change. A new methodology for developing spoken dialogue systems is described in detail. The journey starts and ends with human behaviour in interaction, and explores methods for learning from the data, for building simulation environments for training and testing systems, and for evaluating the r

  6. Intelligent and Adaptive Educational-Learning Systems Achievements and Trends

    CERN Document Server

    2013-01-01

    The Smart Innovation, Systems and Technologies book series encompasses the topics of knowledge, intelligence, innovation and sustainability. The aim of the series is to make available a platform for the publication of books on all aspects of single and multi-disciplinary research on these themes in order to make the latest results available in a readily-accessible form.  This book is devoted to the “Intelligent and Adaptive Educational-Learning Systems”. It privileges works that highlight key achievements and outline trends to inspire future research.  After a rigorous revision process twenty manuscripts were accepted and organized into four parts as follows: ·     Modeling: The first part embraces five chapters oriented to: 1) shape the affective behavior; 2) depict the adaptive learning curriculum; 3) predict learning achievements; 4) mine learner models to outcome optimized and adaptive e-learning objects; 5) classify learning preferences of learners. ·     Content: The second part encompas...

  7. Managing Change toward Adaptive Water Management through Social Learning

    Directory of Open Access Journals (Sweden)

    Claudia Pahl-Wostl

    2007-12-01

    Full Text Available The management of water resources is currently undergoing a paradigm shift toward a more integrated and participatory management style. This paper highlights the need to fully take into account the complexity of the systems to be managed and to give more attention to uncertainties. Achieving this requires adaptive management approaches that can more generally be defined as systematic strategies for improving management policies and practices by learning from the outcomes of previous management actions. This paper describes how the principles of adaptive water management might improve the conceptual and methodological base for sustainable and integrated water management in an uncertain and complex world. Critical debate is structured around four questions: (1 What types of uncertainty need to be taken into account in water management? (2 How does adaptive management account for uncertainty? (3 What are the characteristics of adaptive management regimes? (4 What is the role of social learning in managing change? Major transformation processes are needed because, in many cases, the structural requirements, e.g., adaptive institutions and a flexible technical infrastructure, for adaptive management are not available. In conclusion, we itemize a number of research needs and summarize practical recommendations based on the current state of knowledge.

  8. Greywater Treatment and Reuse

    Directory of Open Access Journals (Sweden)

    Gökhan Ekrem ÜSTÜN

    2015-07-01

    Full Text Available The aim of this study, to examine grey water treatment and reuse. For this aim, previous literature studies been research on and interpreted. Project began with study of physical, chemical and biological characteristics of the gray water. At the second part; grey water treatment and reuse were examined. At the third part; the technologies used for the methods treatment of gray water were explained. Then from costs and previous studies about grey water reuse were mentioned.

  9. Wastewater reuse. What can be learned from the Israel experience; Reutilizacion de aguas residuales. Que se puede aprender de la experiencia israeli

    Energy Technology Data Exchange (ETDEWEB)

    Juanico, M.

    2007-07-01

    In Israel, wastewater is defined as an integral part of the water resources of the country and massive water reuse has been performed for almost four decades. Today, reuse achieves 75% of the produced wastewater. The present paper analyzes the historical development of wastewater reuse in Israel, addressing main events, regulations, coexistence of projects of different sizes and characteristics, institutional organization, the contractual relationship between the urban and rural sectors, nutrients recycling, quality of the treated wastewater and the problem of salination of soils and aquifers. The paper gives an holistic and impartial description of the controversial issues that are presently discussed in the country regarding wastewater reuse. (Author) 42 refs.

  10. Adjusting Felder-Silverman learning styles model for application in adaptive e-learning

    Directory of Open Access Journals (Sweden)

    Mihailović Đorđe

    2012-01-01

    Full Text Available This paper presents an approach for adjusting Felder-Silverman learning styles model for application in development of adaptive e-learning systems. Main goal of the paper is to improve the existing e-learning courses by developing a method for adaptation based on learning styles. The proposed method includes analysis of data related to students characteristics and applying the concept of personalization in creating e-learning courses. The research has been conducted at Faculty of organizational sciences, University of Belgrade, during winter semester of 2009/10, on sample of 318 students. The students from the experimental group were divided in three clusters, based on data about their styles identified using adjusted Felder-Silverman questionnaire. Data about learning styles collected during the research were used to determine typical groups of students and then to classify students into these groups. The classification was performed using data mining techniques. Adaptation of the e-learning courses was implemented according to results of data analysis. Evaluation showed that there was statistically significant difference in the results of students who attended the course adapted by using the described method, in comparison with results of students who attended course that was not adapted.

  11. Cross-Lingual Adaptation using Structural Correspondence Learning

    CERN Document Server

    Prettenhofer, Peter

    2010-01-01

    Cross-lingual adaptation, a special case of domain adaptation, refers to the transfer of classification knowledge between two languages. In this article we describe an extension of Structural Correspondence Learning (SCL), a recently proposed algorithm for domain adaptation, for cross-lingual adaptation. The proposed method uses unlabeled documents from both languages, along with a word translation oracle, to induce cross-lingual feature correspondences. From these correspondences a cross-lingual representation is created that enables the transfer of classification knowledge from the source to the target language. The main advantages of this approach over other approaches are its resource efficiency and task specificity. We conduct experiments in the area of cross-language topic and sentiment classification involving English as source language and German, French, and Japanese as target languages. The results show a significant improvement of the proposed method over a machine translation baseline, reducing th...

  12. Relevance of learning analytics to measure and support students' learning in adaptive educational technologies

    NARCIS (Netherlands)

    Bannert, M.; Molenaar, I.; Azevedo, R.; Järvelä, S.; Gasevic, D.

    2017-01-01

    In this poster, we describe the aim and current activities of the EARLI-Centre for Innovative Research (E-CIR) "Measuring and Supporting Student's Self-Regulated Learning in Adaptive Educational Technologies" which is funded by the European Association for Research on Learning and Instruction

  13. Relevance of learning analytics to measure and support students' learning in adaptive educational technologies

    NARCIS (Netherlands)

    Bannert, M.; Molenaar, I.; Azevedo, R.; Järvelä, S.; Gasevic, D.

    2017-01-01

    In this poster, we describe the aim and current activities of the EARLI-Centre for Innovative Research (E-CIR) "Measuring and Supporting Student's Self-Regulated Learning in Adaptive Educational Technologies" which is funded by the European Association for Research on Learning and Instruction (EARLI

  14. Adaptive Web-Assisted Learning System for Students with Specific Learning Disabilities: A Needs Analysis Study

    Science.gov (United States)

    Polat, Elif; Adiguzel, Tufan; Akgun, Ozcan Erkan

    2012-01-01

    Because there is, currently, no education system for primary school students in grades 1-3 who have specific learning disabilities in Turkey and because such students do not receive sufficient support from face-to-face counseling, a needs analysis was conducted in order to prepare an adaptive, web-assisted learning system according to variables…

  15. Developing and Evaluating an Adaptive Business English Self-Learning System for EFL Vocabulary Learning

    OpenAIRE

    Yen-Hui Wang

    2014-01-01

    This paper developed an adaptive Business English self-learning system for EFL vocabulary learning. The components of word reoccurrence and learner engagement have been built into the system where the amount of unknown word reexposure in various customized texts increases and vocabulary enhancement tasks are added to promote learner engagement with wanted words. To evaluate the system effectiveness on EFL vocabulary learning, the experimental group read system-screened texts with immediate an...

  16. Building Adaptive Game-Based Learning Resources: The Integration of IMS Learning Design and

    Science.gov (United States)

    Burgos, Daniel; Moreno-Ger, Pablo; Sierra, Jose Luis; Fernandez-Manjon, Baltasar; Specht, Marcus; Koper, Rob

    2008-01-01

    IMS Learning Design (IMS-LD) is a specification to create units of learning (UoLs), which express a certain pedagogical model or strategy (e.g., adaptive learning with games). However, the authoring process of a UoL remains difficult because of the lack of high-level authoring tools for IMS-LD, even more so when the focus is on specific topics,…

  17. Learning Unknown Structure in CRFs via Adaptive Gradient Projection Method

    Directory of Open Access Journals (Sweden)

    Wei Xue

    2016-08-01

    Full Text Available We study the problem of fitting probabilistic graphical models to the given data when the structure is not known. More specifically, we focus on learning unknown structure in conditional random fields, especially learning both the structure and parameters of a conditional random field model simultaneously. To do this, we first formulate the learning problem as a convex minimization problem by adding an l_2-regularization to the node parameters and a group l_1-regularization to the edge parameters, and then a gradient-based projection method is proposed to solve it which combines an adaptive stepsize selection strategy with a nonmonotone line search. Extensive simulation experiments are presented to show the performance of our approach in solving unknown structure learning problems.

  18. On the nature of cultural transmission networks: evidence from Fijian villages for adaptive learning biases

    OpenAIRE

    Henrich, Joseph; Broesch, James

    2011-01-01

    Unlike other animals, humans are heavily dependent on cumulative bodies of culturally learned information. Selective processes operating on this socially learned information can produce complex, functionally integrated, behavioural repertoires—cultural adaptations. To understand such non-genetic adaptations, evolutionary theorists propose that (i) natural selection has favoured the emergence of psychological biases for learning from those individuals most likely to possess adaptive informatio...

  19. Learning and Adaptive Hybrid Systems for Nonlinear Control

    Science.gov (United States)

    1991-05-01

    6 2.1.1 Single Layer Networks 8 Perceptrons 8 Samuel’s Checker Player 10 ADALINE and MADALINE 12 2.1.2 Multilayer Networks 13 Hebbian Learning 13...was Widrow’s ADALINE and MADALINE [Wid89]. He developed a type of adaptive filter which is still in widespread use today in such items as high speed...time step, and used it for pattern recognition. This "Adaptive Linear Neuron" ( ADALINE ) [Wid89] was then built in actual hardware, where weights were

  20. Water Reclamation and Reuse.

    Science.gov (United States)

    Smith, Daniel W.

    1978-01-01

    Presents a literature review of water reclamation and reuse. This review covers: (1) water resources planning; (2) agriculture and irrigation; (3) ground recharge; (4) industrial reuse; (5) health considerations; and (6) technology developments. A list of 217 references is also presented. (HM)

  1. Learning to speciate: The biased learning of mate preferences promotes adaptive radiation.

    Science.gov (United States)

    Gilman, R Tucker; Kozak, Genevieve M

    2015-11-01

    Bursts of rapid repeated speciation called adaptive radiations have generated much of Earth's biodiversity and fascinated biologists since Darwin, but we still do not know why some lineages radiate and others do not. Understanding what causes assortative mating to evolve rapidly and repeatedly in the same lineage is key to understanding adaptive radiation. Many species that have undergone adaptive radiations exhibit mate preference learning, where individuals acquire mate preferences by observing the phenotypes of other members of their populations. Mate preference learning can be biased if individuals also learn phenotypes to avoid in mates, and shift their preferences away from these avoided phenotypes. We used individual-based computational simulations to study whether biased and unbiased mate preference learning promotes ecological speciation and adaptive radiation. We found that ecological speciation can be rapid and repeated when mate preferences are biased, but is inhibited when mate preferences are learned without bias. Our results suggest that biased mate preference learning may play an important role in generating animal biodiversity through adaptive radiation. © 2015 The Author(s). Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.

  2. Learning Styles as Predictors of Fieldwork Performance and Learning Adaptability of Graduate Nontraditional Occupational Therapy Students.

    Science.gov (United States)

    Landa-Gonzalez, Belkis; Velis, Evelio; Greg, Katherine

    2015-01-01

    Assessing the learning styles of nontraditional graduate students and their adaptation to the fieldwork context is important for the achievement of educational success. A non-experimental mixed-methods design examining learning styles, fieldwork performance, and adaptation to the clinical setting in a sample of 84 graduate nontraditional occupational therapy students. Kolb's Learning Style Inventory and the Fieldwork Performance Evaluation were the outcome measures. Select participants completed a 1-hr interview and reflection on their fieldwork. The Accommodating style was favored (n=37, 44%) with a strong preference for the active experimentation phase of learning (n=38, 45%). MANOVA tests confirmed a significant relationship of learning styles (F(7,71)=2.62, p=0.018) and phases of learning (F(21,198.7)=2.10, plearning approach and used limited diversity of methods to adapt to the fieldwork setting. Recognizing learning styles and adjusting the approach to the learning conditions have relevance for maximizing outcomes. Educators in allied health fields may consider designing instructional activities that advance students' awareness of their preferences and support the use of diverse approaches for success in various learning contexts.

  3. Applying perceptual and adaptive learning techniques for teaching introductory histopathology

    Directory of Open Access Journals (Sweden)

    Sally Krasne

    2013-01-01

    Full Text Available Background: Medical students are expected to master the ability to interpret histopathologic images, a difficult and time-consuming process. A major problem is the issue of transferring information learned from one example of a particular pathology to a new example. Recent advances in cognitive science have identified new approaches to address this problem. Methods: We adapted a new approach for enhancing pattern recognition of basic pathologic processes in skin histopathology images that utilizes perceptual learning techniques, allowing learners to see relevant structure in novel cases along with adaptive learning algorithms that space and sequence different categories (e.g. diagnoses that appear during a learning session based on each learner′s accuracy and response time (RT. We developed a perceptual and adaptive learning module (PALM that utilized 261 unique images of cell injury, inflammation, neoplasia, or normal histology at low and high magnification. Accuracy and RT were tracked and integrated into a "Score" that reflected students rapid recognition of the pathologies and pre- and post-tests were given to assess the effectiveness. Results: Accuracy, RT and Scores significantly improved from the pre- to post-test with Scores showing much greater improvement than accuracy alone. Delayed post-tests with previously unseen cases, given after 6-7 weeks, showed a decline in accuracy relative to the post-test for 1 st -year students, but not significantly so for 2 nd -year students. However, the delayed post-test scores maintained a significant and large improvement relative to those of the pre-test for both 1 st and 2 nd year students suggesting good retention of pattern recognition. Student evaluations were very favorable. Conclusion: A web-based learning module based on the principles of cognitive science showed an evidence for improved recognition of histopathology patterns by medical students.

  4. Adaptive distance metric learning for diffusion tensor image segmentation.

    Science.gov (United States)

    Kong, Youyong; Wang, Defeng; Shi, Lin; Hui, Steve C N; Chu, Winnie C W

    2014-01-01

    High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework.

  5. Adaptive distance metric learning for diffusion tensor image segmentation.

    Directory of Open Access Journals (Sweden)

    Youyong Kong

    Full Text Available High quality segmentation of diffusion tensor images (DTI is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework.

  6. Hierarchical Participation Constraints for Adaptive Learning and Coordination

    DEFF Research Database (Denmark)

    Yi, Sangyoon; Stieglitz, Nils; Knudsen, Thorbjørn

    From the knowledge-based view of competence, firms exist as an institution where knowledge accumulation and knowledge application are facilitated by organizing principles that markets cannot provide. While scholars perceive that these two interdependent knowledge processes could be influenced...... by formal aspects of organizations, the underlying mechanisms still need to be unpacked. As such an organizing principle, we suggest in this study that hierarchical participation constraints promote both adaptive learning at the individual level and dynamic coordination at the organization level...

  7. Designing a Semantic Bliki System to Support Different Types of Knowledge and Adaptive Learning

    Science.gov (United States)

    Huang, Shiu-Li; Yang, Chia-Wei

    2009-01-01

    Though blogs and wikis have been used to support knowledge management and e-learning, existing blogs and wikis cannot support different types of knowledge and adaptive learning. A case in point, types of knowledge vary greatly in category and viewpoints. Additionally, adaptive learning is crucial to improving one's learning performance. This study…

  8. A Context-Adaptive Teacher Training Model in a Ubiquitous Learning Environment

    Science.gov (United States)

    Chen, Min; Chiang, Feng Kuang; Jiang, Ya Na; Yu, Sheng Quan

    2017-01-01

    In view of the discrepancies in teacher training and teaching practice, this paper put forward a context-adaptive teacher training model in a ubiquitous learning (u-learning) environment. The innovative model provides teachers of different subjects with adaptive and personalized learning content in a u-learning environment, implements intra- and…

  9. A Context-Adaptive Teacher Training Model in a Ubiquitous Learning Environment

    Science.gov (United States)

    Chen, Min; Chiang, Feng Kuang; Jiang, Ya Na; Yu, Sheng Quan

    2017-01-01

    In view of the discrepancies in teacher training and teaching practice, this paper put forward a context-adaptive teacher training model in a ubiquitous learning (u-learning) environment. The innovative model provides teachers of different subjects with adaptive and personalized learning content in a u-learning environment, implements intra- and…

  10. Adaptation Criteria for the Personalised Delivery of Learning Materials: A Multi-Stage Empirical Investigation

    Science.gov (United States)

    Thalmann, Stefan

    2014-01-01

    Personalised e-Learning represents a major step-change from the one-size-fits-all approach of traditional learning platforms to a more customised and interactive provision of learning materials. Adaptive learning can support the learning process by tailoring learning materials to individual needs. However, this requires the initial preparation of…

  11. An adaptive online learning framework for practical breast cancer diagnosis

    Science.gov (United States)

    Chu, Tianshu; Wang, Jie; Chen, Jiayu

    2016-03-01

    This paper presents an adaptive online learning (OL) framework for supporting clinical breast cancer (BC) diagnosis. Unlike traditional data mining, which trains a particular model from a fixed set of medical data, our framework offers robust OL models that can be updated adaptively according to new data sequences and newly discovered features. As a result, our framework can naturally learn to perform BC diagnosis using experts' opinions on sequential patient cases with cumulative clinical measurements. The framework integrates both supervised learning (SL) models for BC risk assessment and reinforcement learning (RL) models for decision-making of clinical measurements. In other words, online SL and RL interact with one another, and under a doctor's supervision, push the patient's diagnosis further. Furthermore, our framework can quickly update relevant model parameters based on current diagnosis information during the training process. Additionally, it can build flexible fitted models by integrating different model structures and plugging in the corresponding parameters during the prediction (or decision-making) process. Even when the feature space is extended, it can initialize the corresponding parameters and extend the existing model structure without loss of the cumulative knowledge. We evaluate the OL framework on real datasets from BCSC and WBC, and demonstrate that our SL models achieve accurate BC risk assessment from sequential data and incremental features. We also verify that the well-trained RL models provide promising measurement suggestions.

  12. Distributed reinforcement learning for adaptive and robust network intrusion response

    Science.gov (United States)

    Malialis, Kleanthis; Devlin, Sam; Kudenko, Daniel

    2015-07-01

    Distributed denial of service (DDoS) attacks constitute a rapidly evolving threat in the current Internet. Multiagent Router Throttling is a novel approach to defend against DDoS attacks where multiple reinforcement learning agents are installed on a set of routers and learn to rate-limit or throttle traffic towards a victim server. The focus of this paper is on online learning and scalability. We propose an approach that incorporates task decomposition, team rewards and a form of reward shaping called difference rewards. One of the novel characteristics of the proposed system is that it provides a decentralised coordinated response to the DDoS problem, thus being resilient to DDoS attacks themselves. The proposed system learns remarkably fast, thus being suitable for online learning. Furthermore, its scalability is successfully demonstrated in experiments involving 1000 learning agents. We compare our approach against a baseline and a popular state-of-the-art throttling technique from the network security literature and show that the proposed approach is more effective, adaptive to sophisticated attack rate dynamics and robust to agent failures.

  13. Masters of adaptation: learning in late life adjustments.

    Science.gov (United States)

    Roberson, Donald N

    2005-01-01

    The purpose of this research is to understand the relationship between human development in older adults and personal learning. Personal or self-directed learning (SDL) refers to a style of learning where the individual directs, controls, and evaluates what is learned. It may occur with formal classes, but most often takes place in non-formal situations. This study employed a descriptive qualitative design incorporating in-depth, semistructured interviews for data collection. The sample of 10 purposefully selected older adults from a rural area reflected diversity in gender, race, education, and employment. Data analysis was guided by the constant comparative method. The primary late life adjustments of these older adults were in response to having extra time, changes in family, and social and physical loss. This research also indicated that late life adjustments are a primary incentive for self-directed learning. The results of this study indicated that older adults become masters of adaptation through the use of self-directed learning activities.

  14. Psychosocial and Adaptive Deficits Associated With Learning Disability Subtypes.

    Science.gov (United States)

    Backenson, Erica M; Holland, Sara C; Kubas, Hanna A; Fitzer, Kim R; Wilcox, Gabrielle; Carmichael, Jessica A; Fraccaro, Rebecca L; Smith, Amanda D; Macoun, Sarah J; Harrison, Gina L; Hale, James B

    2015-01-01

    Children with specific learning disabilities (SLD) have deficits in the basic psychological processes that interfere with learning and academic achievement, and for some SLD subtypes, these deficits can also lead to emotional and/or behavior problems. This study examined psychosocial functioning in 123 students, aged 6 to 11, who underwent comprehensive evaluations for learning and/or behavior problems in two Pacific Northwest school districts. Using concordance-discordance model (C-DM) processing strengths and weaknesses SLD identification criteria, results revealed working memory SLD (n = 20), processing speed SLD (n = 30), executive SLD (n = 32), and no disability groups (n = 41). Of the SLD subtypes, repeated measures MANOVA results revealed the processing speed SLD subtype exhibited the greatest psychosocial and adaptive impairment according to teacher behavior ratings. Findings suggest processing speed deficits may be behind the cognitive and psychosocial disturbances found in what has been termed "nonverbal" SLD. Limitations, implications, and future research needs are addressed.

  15. Solar adaptive optics: specificities, lessons learned, and open alternatives

    Science.gov (United States)

    Montilla, I.; Marino, J.; Asensio Ramos, A.; Collados, M.; Montoya, L.; Tallon, M.

    2016-07-01

    the Strehl and the Point Spread Function used in night time adaptive optics but not really suitable to the solar systems, and new control strategies more complex than the ones used in nowadays solar Multi Conjugate Adaptive Optics systems. In this paper we summarize the lessons learned with past and current solar adaptive optics systems and focus on the discussion on the new alternatives to solve present open issues limiting their performance.

  16. Development of an Adaptive Learning System with Multiple Perspectives based on Students' Learning Styles and Cognitive Styles

    Science.gov (United States)

    Yang, Tzu-Chi; Hwang, Gwo-Jen; Yang, Stephen Jen-Hwa

    2013-01-01

    In this study, an adaptive learning system is developed by taking multiple dimensions of personalized features into account. A personalized presentation module is proposed for developing adaptive learning systems based on the field dependent/independent cognitive style model and the eight dimensions of Felder-Silverman's learning style. An…

  17. Reuse rate of treated wastewater in water reuse system

    Institute of Scientific and Technical Information of China (English)

    FAN Yao-bo; YANG Wen-bo; LI Gang; WU Lin-lin; WEI Yuan-song

    2005-01-01

    A water quality model for water reuse was made by mathematics induction. The relationship among the reuse rate of treated wastewater(R), pollutant concentration of reused water( Cs ), pollutant concentration of influent( C0 ), removal efficiency of pollutant in wastewater(E), and the standard of reuse water were discussed in this study. According to the experiment result of a toilet wastewater treatment and reuse with membrane bioreactors, R would be set at less than 40%, on which all the concerned parameters could meet with the reuse water standards. To raise R of reuse water in the toilet, an important way was to improve color removal of the wastewater.

  18. Reduce, reuse and recycle

    CSIR Research Space (South Africa)

    Afrika, M

    2010-10-01

    Full Text Available The adoption of the internationally accepted waste management hierarchy (Sakai et al, 1996) into South African policy has changed the focus from “end of pipe” waste management towards waste minimisation (reuse, recycling and cleaner production...

  19. Reuse and Restoration

    OpenAIRE

    Brand, Peter

    2010-01-01

    Like members of all pre-modern societies, ancient Egyptians practiced various forms of recycling. The reuse of building materials by rulers is attested throughout Egyptian history and was motivated by ideological and economic concerns. Reuse of masonry from the dilapidated monuments of royal predecessors may have given legitimacy to newer constructions, but in some cases, economic considerations or even antipathy towards an earlier ruler were the decisive factors. Private individuals also mad...

  20. Water Reuse: Using Reclaimed Water For Irrigation

    OpenAIRE

    Haering, Kathryn C.; Evanylo, Gregory K.; Benham, Brian Leslie, 1960-; Goatley, Michael

    2009-01-01

    Describes water reuse and reclaimed water, explains how reclaimed water is produced, options for water reuse, water reuse regulations, and agronomic concerns with water reuse, and provides several case studies of water reuse.

  1. Efficient retrieval of landscape Hessian: forced optimal covariance adaptive learning.

    Science.gov (United States)

    Shir, Ofer M; Roslund, Jonathan; Whitley, Darrell; Rabitz, Herschel

    2014-06-01

    Knowledge of the Hessian matrix at the landscape optimum of a controlled physical observable offers valuable information about the system robustness to control noise. The Hessian can also assist in physical landscape characterization, which is of particular interest in quantum system control experiments. The recently developed landscape theoretical analysis motivated the compilation of an automated method to learn the Hessian matrix about the global optimum without derivative measurements from noisy data. The current study introduces the forced optimal covariance adaptive learning (FOCAL) technique for this purpose. FOCAL relies on the covariance matrix adaptation evolution strategy (CMA-ES) that exploits covariance information amongst the control variables by means of principal component analysis. The FOCAL technique is designed to operate with experimental optimization, generally involving continuous high-dimensional search landscapes (≳30) with large Hessian condition numbers (≳10^{4}). This paper introduces the theoretical foundations of the inverse relationship between the covariance learned by the evolution strategy and the actual Hessian matrix of the landscape. FOCAL is presented and demonstrated to retrieve the Hessian matrix with high fidelity on both model landscapes and quantum control experiments, which are observed to possess nonseparable, nonquadratic search landscapes. The recovered Hessian forms were corroborated by physical knowledge of the systems. The implications of FOCAL extend beyond the investigated studies to potentially cover other physically motivated multivariate landscapes.

  2. Classification of multiple sclerosis lesions using adaptive dictionary learning.

    Science.gov (United States)

    Deshpande, Hrishikesh; Maurel, Pierre; Barillot, Christian

    2015-12-01

    This paper presents a sparse representation and an adaptive dictionary learning based method for automated classification of multiple sclerosis (MS) lesions in magnetic resonance (MR) images. Manual delineation of MS lesions is a time-consuming task, requiring neuroradiology experts to analyze huge volume of MR data. This, in addition to the high intra- and inter-observer variability necessitates the requirement of automated MS lesion classification methods. Among many image representation models and classification methods that can be used for such purpose, we investigate the use of sparse modeling. In the recent years, sparse representation has evolved as a tool in modeling data using a few basis elements of an over-complete dictionary and has found applications in many image processing tasks including classification. We propose a supervised classification approach by learning dictionaries specific to the lesions and individual healthy brain tissues, which include white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF). The size of the dictionaries learned for each class plays a major role in data representation but it is an even more crucial element in the case of competitive classification. Our approach adapts the size of the dictionary for each class, depending on the complexity of the underlying data. The algorithm is validated using 52 multi-sequence MR images acquired from 13 MS patients. The results demonstrate the effectiveness of our approach in MS lesion classification.

  3. Context-aware adaptive and personalized mobile learning delivery supported by UoLmP

    Directory of Open Access Journals (Sweden)

    Sergio Gómez

    2014-01-01

    Full Text Available Over the last decade, several research initiatives have investigated the potentials of the educational paradigm shift from the traditional one-size-fits-all teaching approaches to adaptive and personalized learning. On the other hand, mobile devices are recognized as an emerging technology to facilitate teaching and learning strategies that exploit individual learners’ context. This has led to an increased interest on context-aware adaptive and personalized mobile learning systems aiming to provide learning experiences delivered via mobile devices and tailored to learner’s personal characteristics and situation. To this end, in this paper we present a context-aware adaptive and personalized mobile learning system, namely the Units of Learning mobile Player (UoLmP, which aims to support semi-automatic adaptation of learning activities, that is: (a adaptations to the interconnection of the learning activities (namely, the learning flow and (b adaptations to the educational resources, tools and services that support the learning activities. Initial evaluation results from the use of UoLmP provide evidence that UoLmP can successfully adapt the learning flow of an educational scenario and the delivery of educational resources, tools and services that support the learning activities. Finally, these adaptations can facilitate students to complete successfully the learning activities of an educational scenario.

  4. The effect of adaptive performance support system on learning achievements of students

    NARCIS (Netherlands)

    Kommers, Piet; Stoyanov, Slavi; Mileva, Nevena; Martinez Mediano, Catalina

    2008-01-01

    The study compares the effectiveness of two performance support systems, adaptive and non-adaptive, on learning achievements of engineering students. In addition, the research design controls for a possible effect of learning style. The analysis reveals that students working with an adaptive perform

  5. Towards Motivation-Based Adaptation of Difficulty in E-Learning Programs

    Science.gov (United States)

    Endler, Anke; Rey, Gunter Daniel; Butz, Martin V.

    2012-01-01

    The objective of this study was to investigate if an e-learning environment may use measurements of the user's current motivation to adapt the level of task difficulty for more effective learning. In the reported study, motivation-based adaptation was applied randomly to collect a wide range of data for different adaptations in a variety of…

  6. The effect of adaptive performance support system on learning achievements of students

    NARCIS (Netherlands)

    Kommers, Petrus A.M.; Stoyanov, S.; Stoyanov, Slavi; Mileva, Nevena; Martinez Mediano, Catalina

    2008-01-01

    The study compares the effectiveness of two performance support systems, adaptive and non-adaptive, on learning achievements of engineering students. In addition, the research design controls for a possible effect of learning style. The analysis reveals that students working with an adaptive

  7. Dynamic Learner Profiling and Automatic Learner Classification for Adaptive E-Learning Environment

    Science.gov (United States)

    Premlatha, K. R.; Dharani, B.; Geetha, T. V.

    2016-01-01

    E-learning allows learners individually to learn "anywhere, anytime" and offers immediate access to specific information. However, learners have different behaviors, learning styles, attitudes, and aptitudes, which affect their learning process, and therefore learning environments need to adapt according to these differences, so as to…

  8. Adaptive Sampling for Learning Gaussian Processes Using Mobile Sensor Networks

    Directory of Open Access Journals (Sweden)

    Yunfei Xu

    2011-03-01

    Full Text Available This paper presents a novel class of self-organizing sensing agents that adaptively learn an anisotropic, spatio-temporal Gaussian process using noisy measurements and move in order to improve the quality of the estimated covariance function. This approach is based on a class of anisotropic covariance functions of Gaussian processes introduced to model a broad range of spatio-temporal physical phenomena. The covariance function is assumed to be unknown a priori. Hence, it is estimated by the maximum a posteriori probability (MAP estimator. The prediction of the field of interest is then obtained based on the MAP estimate of the covariance function. An optimal sampling strategy is proposed to minimize the information-theoretic cost function of the Fisher Information Matrix. Simulation results demonstrate the effectiveness and the adaptability of the proposed scheme.

  9. Adaptive learning systems: Supporting navigation with customized suggestions

    Directory of Open Access Journals (Sweden)

    Sibel Somyürek

    2014-01-01

    Full Text Available The aim of this study was to share the results from an experimental research which investigate the effects of link annotations in an educational hypermedia on students’ navigation. This study was conducted through a post-test only control group design with 67 undergraduate students. The voluntary research participants were randomly assigned into the experimental and control group. The required data were collected through an academic achievement test, the Motivated Strategies for Learning Questionnaire, the Non-Linear Media Disorientation Assessment Tool, a questionnaire about users’ opinions and user logs. The findings showed that the perceived disorientation scores and revisitation rates were significantly lower for the learners who studied in the adaptive environment than those in the non-adaptive environment. It was observed that students’ non-sequential navigation in experimental group increased significantly and they followed the system's advices. 

  10. Improving Voluntary Environmental Management Programs: Facilitating Learning and Adaptation

    Science.gov (United States)

    Genskow, Kenneth D.; Wood, Danielle M.

    2011-05-01

    Environmental planners and managers face unique challenges understanding and documenting the effectiveness of programs that rely on voluntary actions by private landowners. Programs, such as those aimed at reducing nonpoint source pollution or improving habitat, intend to reach those goals by persuading landowners to adopt behaviors and management practices consistent with environmental restoration and protection. Our purpose with this paper is to identify barriers for improving voluntary environmental management programs and ways to overcome them. We first draw upon insights regarding data, learning, and adaptation from the adaptive management and performance management literatures, describing three key issues: overcoming information constraints, structural limitations, and organizational culture. Although these lessons are applicable to a variety of voluntary environmental management programs, we then present the issues in the context of on-going research for nonpoint source water quality pollution. We end the discussion by highlighting important elements for advancing voluntary program efforts.

  11. An adaptive learning rate GMM for background extraction

    Institute of Scientific and Technical Information of China (English)

    SHENG Zun-bing; CUI Xian-yu

    2008-01-01

    The rapidness and stability of background extraction from image sequences are incompatible, that is, when a conventionalCraussian mixture models (GMM)is used to rebuild the background, if the background regions of the scene are changed, theextracted background becomes bad until the transition is over. A novel adaptive method is presented to adjust the learningrate of GMM in a Hilbert space. The background extraction is treated as a process of approaching to a certain point in theHilbert space, so the real-time learning rate can be obtained by calculating the distance between the two adjacent extractedbackground images, and a judgment method of the stability of background is got too. Compared with conventional GMM,the method has both high rapidness and good stability at the same time, and it can adjust the learning rate online. Theexperiment shows that it is better than conventional GMM, especially in the transition process of background extraction.

  12. The influence of student characteristics on the use of adaptive e-learning material

    NARCIS (Netherlands)

    van Seters, J. R.; Ossevoort, M. A.; Tramper, J.; Goedhart, M. J.

    2012-01-01

    Adaptive e-learning materials can help teachers to educate heterogeneous student groups. This study provides empirical data about the way academic students differ in their learning when using adaptive e-learning materials. Ninety-four students participated in the study. We determined characteristics

  13. The influence of student characteristics on the use of adaptive e-learning material

    NARCIS (Netherlands)

    van Seters, J. R.; Ossevoort, M. A.; Tramper, J.; Goedhart, M. J.

    2012-01-01

    Adaptive e-learning materials can help teachers to educate heterogeneous student groups. This study provides empirical data about the way academic students differ in their learning when using adaptive e-learning materials. Ninety-four students participated in the study. We determined characteristics

  14. Linking Immersive Virtual Field Trips with an Adaptive Learning Platform

    Science.gov (United States)

    Bruce, G.; Taylor, W.; Anbar, A. D.; Semken, S. C.; Buxner, S.; Mead, C.; El-Moujaber, E.; Summons, R. E.; Oliver, C.

    2016-12-01

    The use of virtual environments in science education has been constrained by the difficulty of guiding a learner's actions within the those environments. In this work, we demonstrate how advances in education software technology allow educators to create interactive learning experiences that respond and adapt intelligently to learner input within the virtual environment. This innovative technology provides a far greater capacity for delivering authentic inquiry-driven educational experiences in unique settings from around the world. Our immersive virtual field trips (iVFT) bring students virtually to geologically significant but inaccessible environments, where they learn through authentic practices of scientific inquiry. In one recent example, students explore the fossil beds in Nilpena, South Australia to learn about the Ediacaran fauna. Students interactively engage in 360° recreations of the environment, uncover the nature of the historical ecosystem by identifying fossils with a dichotomous key, explore actual fossil beds in high resolution imagery, and reconstruct what an ecosystem might have looked like millions of years ago in an interactive simulation. With the new capacity to connect actions within the iVFT to an intelligent tutoring system, these learning experiences can be tracked, guided, and tailored individually to the immediate actions of the student. This new capacity also has great potential for learning designers to take a data-driven approach to lesson improvement and for education researchers to study learning in virtual environments. Thus, we expect iVFT will be fertile ground for novel research. Such iVFT are currently in use in several introductory classes offered online at Arizona State University in anthropology, introductory biology, and astrobiology, reaching thousands of students to date. Drawing from these experiences, we are designing a curriculum for historical geology that will be built around iVFT-based exploration of Earth

  15. Issues in Developing Adaptive Learning Management Systems for Higher Education Institutions

    NARCIS (Netherlands)

    Boticario, Jesús; Santos, Olga

    2006-01-01

    Please, cite this publication as: Boticario, J. & Santos, O. (2006). Issues in Developing Adaptive Learning Management Systems for Higher Education Institutions. Proceedings of Adaptive Hypermedia. June, Dublin, Ireland. Retrieved June 30th, 2006, from http://dspace.learningnetworks.org

  16. Reinforcement Learning Based Novel Adaptive Learning Framework for Smart Grid Prediction

    Directory of Open Access Journals (Sweden)

    Tian Li

    2017-01-01

    Full Text Available Smart grid is a potential infrastructure to supply electricity demand for end users in a safe and reliable manner. With the rapid increase of the share of renewable energy and controllable loads in smart grid, the operation uncertainty of smart grid has increased briskly during recent years. The forecast is responsible for the safety and economic operation of the smart grid. However, most existing forecast methods cannot account for the smart grid due to the disabilities to adapt to the varying operational conditions. In this paper, reinforcement learning is firstly exploited to develop an online learning framework for the smart grid. With the capability of multitime scale resolution, wavelet neural network has been adopted in the online learning framework to yield reinforcement learning and wavelet neural network (RLWNN based adaptive learning scheme. The simulations on two typical prediction problems in smart grid, including wind power prediction and load forecast, validate the effectiveness and the scalability of the proposed RLWNN based learning framework and algorithm.

  17. 参数化模型的局部自动适应重用方法%An Automatic Adaptation Reuse Method for the Subparts of Parametric Solid Models

    Institute of Scientific and Technical Information of China (English)

    潘万彬; 高曙明; 陈翔

    2016-01-01

    Adaptation plays a fundamental role in subpart reuse based part design and is usually human de-pendent. In common design works, designers often replace a simple subpart (possessing the design require-ments of shape and location information) in the current design model with an existing reusable subpart hav-ing a similar shape as the simple subpart but more complex. To enable the reusable subpart to smartly adapt itself to the design requirements implied by the simple subpart, a novel automatic adaptation reuse method for subparts is proposed. First, to determine the corresponding faces between the two subparts as their rele-vant elements, a seed face filter method is adopted. Second, to explicitly represent the parametric shape di-mensions and location information of a subpart, a 3D dimension constraint graph with location information is adopted. Finally, based on the corresponding face and the 3D dimension constraint graph, the reusable subpart automatically and accurately adapts its shape and location information to those of the simple subpart through dimension transferring and constraint transferring respectively. The experimental results show that the proposed method is effective for subpart reuse based part design.%在基于局部重用的零件设计中, 设计人员会选择较复杂的可重用局部区域来替换当前零件模型中与其形状相似的简单局部, 期间一般必须进行适应性修改且往往离不开人工交互. 为了使得可重用局部区域能自动满足简单局部区域所蕴含的设计需求, 提出一种局部自动适应方法. 首先基于种子面过滤来确定两局部区域之间的对应面,并以此作为它们的关联元素; 其次采用带定位信息的三维尺寸约束图来显式地表示参数化的局部形状尺寸和定位信息; 最后基于对应面和带定位信息的三维尺寸约束图, 通过尺寸传递和约束传递分别将简单局部区域的形状和定位信息自动、准确地

  18. Adapting online learning for Canada's Northern public health workforce

    Directory of Open Access Journals (Sweden)

    Marnie Bell

    2013-08-01

    Full Text Available Background . Canada's North is a diverse, sparsely populated land, where inequalities and public health issues are evident, particularly for Aboriginal people. The Northern public health workforce is a unique mix of professional and paraprofessional workers. Few have formal public health education. From 2009 to 2012, the Public Health Agency of Canada (PHAC collaborated with a Northern Advisory Group to develop and implement a strategy to strengthen public health capacity in Canada's 3 northern territories. Access to relevant, effective continuing education was identified as a key issue. Challenges include diverse educational and cultural backgrounds of public health workers, geographical isolation and variable technological infrastructure across the north. Methods . PHAC's Skills Online program offers Internet-based continuing education modules for public health professionals. In partnership with the Northern Advisory Group, PHAC conducted 3 pilots between 2008 and 2012 to assess the appropriateness of the Skills Online program for Northern/Aboriginal public health workers. Module content and delivery modalities were adapted for the pilots. Adaptations included adding Inuit and Northern public health examples and using video and teleconference discussions to augment the online self-study component. Results . Findings from the pilots were informative and similar to those from previous Skills Online pilots with learners in developing countries. Online learning is effective in bridging the geographical barriers in remote locations. Incorporating content on Northern and Aboriginal health issues facilitates engagement in learning. Employer support facilitates the recruitment and retention of learners in an online program. Facilitator assets included experience as a public health professional from the north, and flexibility to use modified approaches to support and measure knowledge acquisition and application, especially for First Nations, Inuit and

  19. 一种基于多Agent 适配器的构件重用方法(英文)%A component reuse method based on multiagent adapter

    Institute of Scientific and Technical Information of China (English)

    迟忠先; 阿不都·克里木; 高永强; 王忠

    2002-01-01

    首先提出一种构件适应方法--通过为构件外挂适配器--来解决构件重用中的"接口匹配、消息处理、状态监控和环境模拟"等问题. 并采用多Agent适配器来建立一个可适应机制. 然后讨论基于这种多Agent适配器的构件适应技术的体系结构和建模方法. 最后给出该方法的应用实例和相关的工作.%This paper first presents a component adaptation method-assemble, which can solve the problems of interface matching, message handling, state monitoring, environment simulation and adopts multiagent adapter to build a flexible mechanism. Then a component reuse architecture based on this method is discussed. In the final section, related work and summary are given.

  20. SPATIALLY ADAPTIVE SEMI-SUPERVISED LEARNING WITH GAUSSIAN PROCESSES FOR HYPERSPECTRAL DATA ANALYSIS

    Data.gov (United States)

    National Aeronautics and Space Administration — SPATIALLY ADAPTIVE SEMI-SUPERVISED LEARNING WITH GAUSSIAN PROCESSES FOR HYPERSPECTRAL DATA ANALYSIS GOO JUN * AND JOYDEEP GHOSH* Abstract. A semi-supervised learning...

  1. Peers as resources for learning: a situated learning approach to adapted physical activity in rehabilitation.

    Science.gov (United States)

    Standal, Øyvind F; Jespersen, Ejgil

    2008-07-01

    The purpose of this study was to investigate the learning that takes place when people with disabilities interact in a rehabilitation context. Data were generated through in-depth interviews and close observations in a 2 (1/2) week-long rehabilitation program, where the participants learned both wheelchair skills and adapted physical activities. The findings from the qualitative data analysis are discussed in the context of situated learning (Lave & Wenger, 1991; Wenger, 1998). The results indicate that peer learning extends beyond skills and techniques, to include ways for the participants to make sense of their situations as wheelchair users. Also, it was found that the community of practice established between the participants represented a critical corrective to instructions provided by rehabilitation professionals.

  2. Modeling and Simulation of An Adaptive Neuro-Fuzzy Inference System (ANFIS) for Mobile Learning

    Science.gov (United States)

    Al-Hmouz, A.; Shen, Jun; Al-Hmouz, R.; Yan, Jun

    2012-01-01

    With recent advances in mobile learning (m-learning), it is becoming possible for learning activities to occur everywhere. The learner model presented in our earlier work was partitioned into smaller elements in the form of learner profiles, which collectively represent the entire learning process. This paper presents an Adaptive Neuro-Fuzzy…

  3. Modeling and Simulation of An Adaptive Neuro-Fuzzy Inference System (ANFIS) for Mobile Learning

    Science.gov (United States)

    Al-Hmouz, A.; Shen, Jun; Al-Hmouz, R.; Yan, Jun

    2012-01-01

    With recent advances in mobile learning (m-learning), it is becoming possible for learning activities to occur everywhere. The learner model presented in our earlier work was partitioned into smaller elements in the form of learner profiles, which collectively represent the entire learning process. This paper presents an Adaptive Neuro-Fuzzy…

  4. Promoter reuse in prokaryotes

    NARCIS (Netherlands)

    Nijveen, H.; Matus-Garcia, M.; Passel, van M.W.J.

    2012-01-01

    Anecdotal evidence shows promoters being reused separate from their downstream gene, thus providing a mechanism for the efficient and rapid rewiring of a gene’s transcriptional regulation. We have identified over 4000 groups of highly similar promoters using a conservative sequence similarity search

  5. Developing and Evaluating an Adaptive Business English Self-Learning System for EFL Vocabulary Learning

    Directory of Open Access Journals (Sweden)

    Yen-Hui Wang

    2014-01-01

    Full Text Available This paper developed an adaptive Business English self-learning system for EFL vocabulary learning. The components of word reoccurrence and learner engagement have been built into the system where the amount of unknown word reexposure in various customized texts increases and vocabulary enhancement tasks are added to promote learner engagement with wanted words. To evaluate the system effectiveness on EFL vocabulary learning, the experimental group read system-screened texts with immediate and repeated contacts with individuals’ unknown words and performed vocabulary tasks specific to those unknown words, while the control group read online texts without unknown word reoccurrence and vocabulary practice. After one semester, these two groups were measured by one online vocabulary test, and an online user satisfaction investigation was also administered to the experimental group. The study found that the experimental group reading customized texts to reexpose to previously encountered unknown words in different texts along with doing individualized vocabulary exercises performed significantly better in EFL vocabulary learning than the other group. It was also found that the system was appealing for the learners to show positive attitudes toward the use of the system. The study demonstrated that the constructed adaptive Business English self-learning system could effectively promote vocabulary growth.

  6. Aligning the economic modeling of software reuse with reuse practices

    NARCIS (Netherlands)

    Postmus, D.; Meijler, 27696

    2008-01-01

    In contrast to current practices where software reuse is applied recursively and reusable assets are tailored trough parameterization or specialization, existing reuse economic models assume that (i) the cost of reusing a software asset depends on its size and (ii) reusable assets are developed from

  7. Breast image feature learning with adaptive deconvolutional networks

    Science.gov (United States)

    Jamieson, Andrew R.; Drukker, Karen; Giger, Maryellen L.

    2012-03-01

    Feature extraction is a critical component of medical image analysis. Many computer-aided diagnosis approaches employ hand-designed, heuristic lesion extracted features. An alternative approach is to learn features directly from images. In this preliminary study, we explored the use of Adaptive Deconvolutional Networks (ADN) for learning high-level features in diagnostic breast mass lesion images with potential application to computer-aided diagnosis (CADx) and content-based image retrieval (CBIR). ADNs (Zeiler, et. al., 2011), are recently-proposed unsupervised, generative hierarchical models that decompose images via convolution sparse coding and max pooling. We trained the ADNs to learn multiple layers of representation for two breast image data sets on two different modalities (739 full field digital mammography (FFDM) and 2393 ultrasound images). Feature map calculations were accelerated by use of GPUs. Following Zeiler et. al., we applied the Spatial Pyramid Matching (SPM) kernel (Lazebnik, et. al., 2006) on the inferred feature maps and combined this with a linear support vector machine (SVM) classifier for the task of binary classification between cancer and non-cancer breast mass lesions. Non-linear, local structure preserving dimension reduction, Elastic Embedding (Carreira-Perpiñán, 2010), was then used to visualize the SPM kernel output in 2D and qualitatively inspect image relationships learned. Performance was found to be competitive with current CADx schemes that use human-designed features, e.g., achieving a 0.632+ bootstrap AUC (by case) of 0.83 [0.78, 0.89] for an ultrasound image set (1125 cases).

  8. Adaptive categorization of ART networks in robot behavior learning using game-theoretic formulation.

    Science.gov (United States)

    Fung, Wai-keung; Liu, Yun-hui

    2003-12-01

    Adaptive Resonance Theory (ART) networks are employed in robot behavior learning. Two of the difficulties in online robot behavior learning, namely, (1) exponential memory increases with time, (2) difficulty for operators to specify learning tasks accuracy and control learning attention before learning. In order to remedy the aforementioned difficulties, an adaptive categorization mechanism is introduced in ART networks for perceptual and action patterns categorization in this paper. A game-theoretic formulation of adaptive categorization for ART networks is proposed for vigilance parameter adaptation for category size control on the categories formed. The proposed vigilance parameter update rule can help improving categorization performance in the aspect of category number stability and solve the problem of selecting initial vigilance parameter prior to pattern categorization in traditional ART networks. Behavior learning using physical robot is conducted to demonstrate the effectiveness of the proposed adaptive categorization mechanism in ART networks.

  9. Adaptive learning with guaranteed stability for discrete-time recurrent neural networks

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    To avoid unstable learning, a stable adaptive learning algorithm was proposed for discrete-time recurrent neural networks. Unlike the dynamic gradient methods, such as the backpropagation through time and the real time recurrent learning, the weights of the recurrent neural networks were updated online in terms of Lyapunov stability theory in the proposed learning algorithm, so the learning stability was guaranteed. With the inversion of the activation function of the recurrent neural networks, the proposed learning algorithm can be easily implemented for solving varying nonlinear adaptive learning problems and fast convergence of the adaptive learning process can be achieved. Simulation experiments in pattern recognition show that only 5 iterations are needed for the storage of a 15X15 binary image pattern and only 9 iterations are needed for the perfect realization of an analog vector by an equilibrium state with the proposed learning algorithm.

  10. PROBLEM BASED LEARNING: ADAPTING MODEL OF MONITORING AND ASSESSMENT TOWARDS CHANGING TO STUDENT CENTERED LEARNING

    Directory of Open Access Journals (Sweden)

    Alias Masek

    2010-05-01

    Full Text Available Exam oriented system has long time been practiced whether in the school or at higher educational level. It is common to see that students learn to rote memorization as preparation to pass in the examination. As consequences, the graduates’ ability to apply knowledge in the workplace becomes an issue to be debated. This has led to the loud calls for the new authentic learning environment that may increase students’ ability to apply knowledge, skills and at the same time promoting students’ with higher order thinking levels such as problem solving and critical thinking skills. Within this, the need on educational revamp is seem crucial, and this should be done from the grass root levels. Therefore, student centered learning using Problem Based Learning (PBL approach is suggested to be introduced in integrated living skills subject. The model will be designed to focus on monitoring and assessment methods in fostering student continuous development in three domain areas of knowledge, technical and personal skills. Moreover, this method is believed to be able to incorporate lifelong learning and self directed learning skills that helps student to sustain in our educational system. Thus, the study aims to look into the possible ways of adapting PBL monitoring and assessment methods into existing practices in lifelong learning settings in TVET.

  11. A personalized adaptive e-learning approach based on semantic web technology

    Directory of Open Access Journals (Sweden)

    Maryam Yarandi

    2013-12-01

    Full Text Available Recent developments in semantic web technologies heightened the need for online adaptive learning environment. Adaptive learning is an important research topic in the field of web-based systems as there are no fixed learning paths which are appropriate for all learners. However, most studies in this field have only focused on learning styles and habits of learners. Far too little attention has been paid on understanding the ability of learners. Therefore, it is becoming increasingly difficult to ignore adaptation in the field of e-learning systems. Many researchers are adopting semantic web technologies to find new ways for designing adaptive learning systems based on describing knowledge using ontological models. Ontologies have the potential to design content and learner models required to create adaptive e-learning systems based on various characteristics of learners. The aim of this paper is to present an ontology-based approach to develop adaptive e-learning system based on the design of semantic content, learner and domain models to tailor the teaching process for individual learner’s needs. The proposed new adaptive e-learning has the ability to support personalization based on learner’s ability, learning style, preferences and levels of knowledge. In our approach the ontological user profile is updated based on achieved learner’s abilities.

  12. Adaptive Learning in the Tragedy of the Commons

    Directory of Open Access Journals (Sweden)

    Julian Andrés García

    2010-07-01

    Full Text Available The joint utilisation of a commonly owned resource often causes the resource to be overused, this is known as The tragedy of the Commons. This paper analyses the effects of adaptive learning in such kind of situations using genetic programming. In a game theoretical approach, the situation considers not only the strategic interaction among players, but also the dynamics of a changing enviroment linked strongly to the players' actions and payoffs. The results of an analytical game are used to formulate a simulation game for the commons, the a series of computational experiments are conducted, obtaining evolved game strategies that are examined in comparison with those predicted by the analytical model. The obtained results are similar to those predicted by classic game theory, but not always leading to a tragedy.

  13. Learning about stress: neural, endocrine and behavioral adaptations.

    Science.gov (United States)

    McCarty, Richard

    2016-09-01

    In this review, nonassociative learning is advanced as an organizing principle to draw together findings from both sympathetic-adrenal medullary and hypothalamic-pituitary-adrenocortical (HPA) axis responses to chronic intermittent exposure to a variety of stressors. Studies of habituation, facilitation and sensitization of stress effector systems are reviewed and linked to an animal's prior experience with a given stressor, the intensity of the stressor and the appraisal by the animal of its ability to mobilize physiological systems to adapt to the stressor. Brain pathways that regulate physiological and behavioral responses to stress are discussed, especially in light of their regulation of nonassociative processes in chronic intermittent stress. These findings may have special relevance to various psychiatric diseases, including depression and post-traumatic stress disorder (PTSD).

  14. Adaptive sampling for nonlinear dimensionality reduction based on manifold learning

    DEFF Research Database (Denmark)

    Franz, Thomas; Zimmermann, Ralf; Goertz, Stefan

    2017-01-01

    We make use of the non-intrusive dimensionality reduction method Isomap in order to emulate nonlinear parametric flow problems that are governed by the Reynolds-averaged Navier-Stokes equations. Isomap is a manifold learning approach that provides a low-dimensional embedding space...... that is approximately isometric to the manifold that is assumed to be formed by the high-fidelity Navier-Stokes flow solutions under smooth variations of the inflow conditions. The focus of the work at hand is the adaptive construction and refinement of the Isomap emulator: We exploit the non-Euclidean Isomap metric...... to detect and fill up gaps in the sampling in the embedding space. The performance of the proposed manifold filling method will be illustrated by numerical experiments, where we consider nonlinear parameter-dependent steady-state Navier-Stokes flows in the transonic regime....

  15. Blind separation of image sources via adaptive dictionary learning.

    Science.gov (United States)

    Abolghasemi, Vahid; Ferdowsi, Saideh; Sanei, Saeid

    2012-06-01

    Sparsity has been shown to be very useful in source separation of multichannel observations. However, in most cases, the sources of interest are not sparse in their current domain and one needs to sparsify them using a known transform or dictionary. If such a priori about the underlying sparse domain of the sources is not available, then the current algorithms will fail to successfully recover the sources. In this paper, we address this problem and attempt to give a solution via fusing the dictionary learning into the source separation. We first define a cost function based on this idea and propose an extension of the denoising method in the work of Elad and Aharon to minimize it. Due to impracticality of such direct extension, we then propose a feasible approach. In the proposed hierarchical method, a local dictionary is adaptively learned for each source along with separation. This process improves the quality of source separation even in noisy situations. In another part of this paper, we explore the possibility of adding global priors to the proposed method. The results of our experiments are promising and confirm the strength of the proposed approach.

  16. LEARNING REPOSITORY ADAPTABILITY IN AN AGENT-BASED UNIVERSITY ENVIRONMENT

    Directory of Open Access Journals (Sweden)

    Vanco Cabukovski

    2016-06-01

    Full Text Available Automated e-Learning Systems (AeLS are fundamental to contemporary educational concepts worldwide.It has become a standard not only in support to the formal curriculum, but containing social platform capabilities, gamification elements and functionalities fostering communities of experts, also for faster knowledge dissemination. Additionally, AeLSs support internal communications and customizable analytics and methodologies to quickly identify learning performance, which in turn can be used as feedback to implement adaptability in tailoring the content management to meet specific individual needs. The volume of fast growing AeLS content of supplement material and exchanged communication combined with the already huge material archived in the university libraries is enormous and needs sophisticated managing through electronic repositories. Such integration of content management systems (CMS present challenges which can be solved optimally with the use of distributed management implemented through agent-based systems. This paper depicts a successful implementation of an Integrated Intelligent Agent Based UniversityInformation System (IABUIS.

  17. Extreme learning machine and adaptive sparse representation for image classification.

    Science.gov (United States)

    Cao, Jiuwen; Zhang, Kai; Luo, Minxia; Yin, Chun; Lai, Xiaoping

    2016-09-01

    Recent research has shown the speed advantage of extreme learning machine (ELM) and the accuracy advantage of sparse representation classification (SRC) in the area of image classification. Those two methods, however, have their respective drawbacks, e.g., in general, ELM is known to be less robust to noise while SRC is known to be time-consuming. Consequently, ELM and SRC complement each other in computational complexity and classification accuracy. In order to unify such mutual complementarity and thus further enhance the classification performance, we propose an efficient hybrid classifier to exploit the advantages of ELM and SRC in this paper. More precisely, the proposed classifier consists of two stages: first, an ELM network is trained by supervised learning. Second, a discriminative criterion about the reliability of the obtained ELM output is adopted to decide whether the query image can be correctly classified or not. If the output is reliable, the classification will be performed by ELM; otherwise the query image will be fed to SRC. Meanwhile, in the stage of SRC, a sub-dictionary that is adaptive to the query image instead of the entire dictionary is extracted via the ELM output. The computational burden of SRC thus can be reduced. Extensive experiments on handwritten digit classification, landmark recognition and face recognition demonstrate that the proposed hybrid classifier outperforms ELM and SRC in classification accuracy with outstanding computational efficiency. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Swarm Intelligence: New Techniques for Adaptive Systems to Provide Learning Support

    Science.gov (United States)

    Wong, Lung-Hsiang; Looi, Chee-Kit

    2012-01-01

    The notion of a system adapting itself to provide support for learning has always been an important issue of research for technology-enabled learning. One approach to provide adaptivity is to use social navigation approaches and techniques which involve analysing data of what was previously selected by a cluster of users or what worked for…

  19. An Adaptive Approach to Managing Knowledge Development in a Project-Based Learning Environment

    Science.gov (United States)

    Tilchin, Oleg; Kittany, Mohamed

    2016-01-01

    In this paper we propose an adaptive approach to managing the development of students' knowledge in the comprehensive project-based learning (PBL) environment. Subject study is realized by two-stage PBL. It shapes adaptive knowledge management (KM) process and promotes the correct balance between personalized and collaborative learning. The…

  20. Examining the Role of Emotional Intelligence between Organizational Learning and Adaptive Performance in Indian Manufacturing Industries

    Science.gov (United States)

    Pradhan, Rabindra Kumar; Jena, Lalatendu Kesari; Singh, Sanjay Kumar

    2017-01-01

    Purpose: The purpose of this study is to examine the relationship between organisational learning and adaptive performance. Furthermore, the study investigates the moderating role of emotional intelligence in the perspective of organisational learning for addressing adaptive performance of executives employed in manufacturing organisations.…

  1. A Context-Aware Self-Adaptive Fractal Based Generalized Pedagogical Agent Framework for Mobile Learning

    Science.gov (United States)

    Boulehouache, Soufiane; Maamri, Ramdane; Sahnoun, Zaidi

    2015-01-01

    The Pedagogical Agents (PAs) for Mobile Learning (m-learning) must be able not only to adapt the teaching to the learner knowledge level and profile but also to ensure the pedagogical efficiency within unpredictable changing runtime contexts. Therefore, to deal with this issue, this paper proposes a Context-aware Self-Adaptive Fractal Component…

  2. Effectiveness of Adaptive Assessment versus Learner Control in a Multimedia Learning System

    Science.gov (United States)

    Chen, Ching-Huei; Chang, Shu-Wei

    2015-01-01

    The purpose of this study was to explore the effectiveness of adaptive assessment versus learner control in a multimedia learning system designed to help secondary students learn science. Unlike other systems, this paper presents a workflow of adaptive assessment following instructional materials that better align with learners' cognitive…

  3. Recasting Transfer as a Socio-Personal Process of Adaptable Learning

    Science.gov (United States)

    Billett, Stephen

    2013-01-01

    Transfer is usually cast as an educational, rather than learning, problem. Yet, seeking to adapt what individuals know from one circumstance to another is a process more helpfully associated with learning, than a hybrid one called transfer. Adaptability comprises individuals construing what they experience, then aligning and reconciling with what…

  4. Examining the Relationship between Learning Organization Characteristics and Change Adaptation, Innovation, and Organizational Performance

    Science.gov (United States)

    Kontoghiorghes, Constantine; Awbre, Susan M.; Feurig, Pamela L.

    2005-01-01

    The main purpose of this exploratory study was to examine the relationship between certain learning organization characteristics and change adaptation, innovation, and bottom-line organizational performance. The following learning organization characteristics were found to be the strongest predictors of rapid change adaptation, quick product or…

  5. A new learning statistic for adaptive filter based on predicted residuals

    Institute of Scientific and Technical Information of China (English)

    YANG Yuanxi; GAO Weiguang

    2006-01-01

    A key problem for an adaptive filter is to establish a suitable adaptive factor for balancing the contributions of the measurements and the predicted state information from some kinematic models. The reasonable adaptive factor needs a reliable learning statistics to judge the state kinematic model errors. After analyzing the existing two kinds of learning statistics based on the state discrepancy and variance component ratio, a new learning statistic based on predicted residuals is set up, which is different from the exiting learning statistics. The new learning statistic does not need to estimate the kinemetic state parameters before the filtering process, Of course, it does not need necessary measurements to estimate state parameters for all observation epochs. The new learning statistic can be applied together with the learning factor constructed by the state discrepancy. The advantages and shortcomings of the new learning factor are analyzed, and an example is given.

  6. Guidance Manual for Separation of Graywater from Blackwater for Graywater Reuse (WERF Report INFR4SG09a)

    Science.gov (United States)

    Abstract: Increasing efforts in water conservation have prompted home and business owners to learn more about water reuse. One reuse application of interest is separating graywater (all wastewater excluding kitchen and toilet water) from other wastewater to supplement irrigatio...

  7. OPUS One: An Intelligent Adaptive Learning Environment Using Artificial Intelligence Support

    Science.gov (United States)

    Pedrazzoli, Attilio

    2010-06-01

    AI based Tutoring and Learning Path Adaptation are well known concepts in e-Learning scenarios today and increasingly applied in modern learning environments. In order to gain more flexibility and to enhance existing e-learning platforms, the OPUS One LMS Extension package will enable a generic Intelligent Tutored Adaptive Learning Environment, based on a holistic Multidimensional Instructional Design Model (PENTHA ID Model), allowing AI based tutoring and adaptation functionality to existing Web-based e-learning systems. Relying on "real time" adapted profiles, it allows content- / course authors to apply a dynamic course design, supporting tutored, collaborative sessions and activities, as suggested by modern pedagogy. The concept presented combines a personalized level of surveillance, learning activity- and learning path adaptation suggestions to ensure the students learning motivation and learning success. The OPUS One concept allows to implement an advanced tutoring approach combining "expert based" e-tutoring with the more "personal" human tutoring function. It supplies the "Human Tutor" with precise, extended course activity data and "adaptation" suggestions based on predefined subject matter rules. The concept architecture is modular allowing a personalized platform configuration.

  8. Second Graders Learn Animal Adaptations through Form and Function Analogy Object Boxes

    Science.gov (United States)

    Rule, Audrey C.; Baldwin, Samantha; Schell, Robert

    2008-01-01

    This study examined the use of form and function analogy object boxes to teach second graders (n = 21) animal adaptations. The study used a pretest-posttest design to examine animal adaptation content learned through focused analogy activities as compared with reading and Internet searches for information about adaptations of animals followed by…

  9. A Stochastic Approach for Automatic and Dynamic Modeling of Students' Learning Styles in Adaptive Educational Systems

    Science.gov (United States)

    Dorça, Fabiano Azevedo; Lima, Luciano Vieira; Fernandes, Márcia Aparecida; Lopes, Carlos Roberto

    2012-01-01

    Considering learning and how to improve students' performances, an adaptive educational system must know how an individual learns best. In this context, this work presents an innovative approach for student modeling through probabilistic learning styles combination. Experiments have shown that our approach is able to automatically detect and…

  10. The Effects of Reflective Activities on Skill Adaptation in a Work-Related Instrumental Learning Setting

    Science.gov (United States)

    Roessger, Kevin M.

    2014-01-01

    In work-related instrumental learning contexts, the role of reflective activities is unclear. Kolb's experiential learning theory and Mezirow's transformative learning theory predict skill adaptation as an outcome. This prediction was tested by manipulating reflective activities and assessing participants' response and error rates during novel…

  11. A Framework for Adaptive Learning Design in a Web-Conferencing Environment

    Science.gov (United States)

    Bower, Matt

    2016-01-01

    Many recent technologies provide the ability to dynamically adjust the interface depending on the emerging cognitive and collaborative needs of the learning episode. This means that educators can adaptively re-design the learning environment during the lesson, rather than purely relying on preemptive learning design thinking. Based on a…

  12. Context-Adaptive Learning Designs by Using Semantic Web Services

    Science.gov (United States)

    Dietze, Stefan; Gugliotta, Alessio; Domingue, John

    2007-01-01

    IMS Learning Design (IMS-LD) is a promising technology aimed at supporting learning processes. IMS-LD packages contain the learning process metadata as well as the learning resources. However, the allocation of resources--whether data or services--within the learning design is done manually at design-time on the basis of the subjective appraisals…

  13. Adaptive Resonance Theory: how a brain learns to consciously attend, learn, and recognize a changing world.

    Science.gov (United States)

    Grossberg, Stephen

    2013-01-01

    Adaptive Resonance Theory, or ART, is a cognitive and neural theory of how the brain autonomously learns to categorize, recognize, and predict objects and events in a changing world. This article reviews classical and recent developments of ART, and provides a synthesis of concepts, principles, mechanisms, architectures, and the interdisciplinary data bases that they have helped to explain and predict. The review illustrates that ART is currently the most highly developed cognitive and neural theory available, with the broadest explanatory and predictive range. Central to ART's predictive power is its ability to carry out fast, incremental, and stable unsupervised and supervised learning in response to a changing world. ART specifies mechanistic links between processes of consciousness, learning, expectation, attention, resonance, and synchrony during both unsupervised and supervised learning. ART provides functional and mechanistic explanations of such diverse topics as laminar cortical circuitry; invariant object and scenic gist learning and recognition; prototype, surface, and boundary attention; gamma and beta oscillations; learning of entorhinal grid cells and hippocampal place cells; computation of homologous spatial and temporal mechanisms in the entorhinal-hippocampal system; vigilance breakdowns during autism and medial temporal amnesia; cognitive-emotional interactions that focus attention on valued objects in an adaptively timed way; item-order-rank working memories and learned list chunks for the planning and control of sequences of linguistic, spatial, and motor information; conscious speech percepts that are influenced by future context; auditory streaming in noise during source segregation; and speaker normalization. Brain regions that are functionally described include visual and auditory neocortex; specific and nonspecific thalamic nuclei; inferotemporal, parietal, prefrontal, entorhinal, hippocampal, parahippocampal, perirhinal, and motor cortices

  14. A Case Study of Horizontal Reuse in a Project-Driven Organisation

    DEFF Research Database (Denmark)

    Christensen, Henrik Bærbak; Røn, Henrik

    2000-01-01

    This experience paper presents observations, lessons learned, and recommendations based on a case study of reuse. The case study is concerned with the development, maturation, and reuse of a business domain independent software component (horizontal reuse) in a project-driven organisation that has...... little previous experience with systematic software reuse. The main lessons learned are that: (a) even though domain analysis can alleviate reuse mismatch problems one should not underestimate the technical problems that may arise when reusing; (b) a side-effect of reuse is that software engineering...... knowledge is transferred within an organisation; (c) design patterns can be as risky as they can be beneficial; and (d) there is more to architectural mismatch than “merely ” packaging mismatch....

  15. Evolutionary perspectives on learning: conceptual and methodological issues in the study of adaptive specializations.

    Science.gov (United States)

    Krause, Mark A

    2015-07-01

    Inquiry into evolutionary adaptations has flourished since the modern synthesis of evolutionary biology. Comparative methods, genetic techniques, and various experimental and modeling approaches are used to test adaptive hypotheses. In psychology, the concept of adaptation is broadly applied and is central to comparative psychology and cognition. The concept of an adaptive specialization of learning is a proposed account for exceptions to general learning processes, as seen in studies of Pavlovian conditioning of taste aversions, sexual responses, and fear. The evidence generally consists of selective associations forming between biologically relevant conditioned and unconditioned stimuli, with conditioned responses differing in magnitude, persistence, or other measures relative to non-biologically relevant stimuli. Selective associations for biologically relevant stimuli may suggest adaptive specializations of learning, but do not necessarily confirm adaptive hypotheses as conceived of in evolutionary biology. Exceptions to general learning processes do not necessarily default to an adaptive specialization explanation, even if experimental results "make biological sense". This paper examines the degree to which hypotheses of adaptive specializations of learning in sexual and fear response systems have been tested using methodologies developed in evolutionary biology (e.g., comparative methods, quantitative and molecular genetics, survival experiments). A broader aim is to offer perspectives from evolutionary biology for testing adaptive hypotheses in psychological science.

  16. Learning as You Journey: Anishinaabe Perception of Social-ecological Environments and Adaptive Learning

    Directory of Open Access Journals (Sweden)

    Iain Davidson-Hunt

    2003-12-01

    Full Text Available This paper explores the linkages between social-ecological resilience and adaptive learning. We refer to adaptive learning as a method to capture the two-way relationship between people and their social-ecological environment. In this paper, we focus on traditional ecological knowledge. Research was undertaken with the Anishinaabe people of Iskatewizaagegan No. 39 Independent First Nation, in northwestern Ontario, Canada. The research was carried out over two field seasons, with verification workshops following each field season. The methodology was based on site visits and transects determined by the elders as appropriate to answer a specific question, find specific plants, or locate plant communities. During site visits and transect walks, research themes such as plant nomenclature, plant use, habitat descriptions, biogeophysical landscape vocabulary, and place names were discussed. Working with elders allowed us to record a rich set of vocabulary to describe the spatial characteristics of the biogeophysical landscape. However, elders also directed our attention to places they knew through personal experiences and journeys and remembered from stories and collective history. We documented elders' perceptions of the temporal dynamics of the landscape through discussion of disturbance events and cycles. Again, elders drew our attention to the ways in which time was marked by cultural references to seasons and moons. The social memory of landscape dynamics was documented as a combination of biogeophysical structures and processes, along with the stories by which Iskatewizaagegan people wrote their histories upon the land. Adaptive learning for social-ecological resilience, as suggested by this research, requires maintaining the web of relationships of people and places. Such relationships allow social memory to frame creativity, while allowing knowledge to evolve in the face of change. Social memory does not actually evolve directly out of

  17. Information-educational environment with adaptive control of learning process

    Science.gov (United States)

    Modjaev, A. D.; Leonova, N. M.

    2017-01-01

    Recent years, a new scientific branch connected with the activities in social sphere management developing intensively and it is called "Social Cybernetics". In the framework of this scientific branch, theory and methods of management of social sphere are formed. Considerable attention is paid to the management, directly in real time. However, the decision of such management tasks is largely constrained by the lack of or insufficiently deep study of the relevant sections of the theory and methods of management. The article discusses the use of cybernetic principles in solving problems of control in social systems. Applying to educational activities a model of composite interrelated objects representing the behaviour of students at various stages of educational process is introduced. Statistical processing of experimental data obtained during the actual learning process is being done. If you increase the number of features used, additionally taking into account the degree and nature of variability of levels of current progress of students during various types of studies, new properties of students' grouping are discovered. L-clusters were identified, reflecting the behaviour of learners with similar characteristics during lectures. It was established that the characteristics of the clusters contain information about the dynamics of learners' behaviour, allowing them to be used in additional lessons. The ways of solving the problem of adaptive control based on the identified dynamic characteristics of the learners are planned.

  18. ADAPTIVE E-LEARNING TECHNIQUES IN THE DEVELOPMENT OF TEACHING ELECTRONIC PORTFOLIO – A SURVEY

    Directory of Open Access Journals (Sweden)

    DEKSON D.E.,

    2010-09-01

    Full Text Available Emerging technologies of communication and information influence the society, in particular the educational system in new directions. Media based educational systems are becoming more popular today and vast student population rely on this for learning. In the technologically emerging education system, it is necessary to have an e-learning system which can understand the learner’s preferences and make attempts to deliver content accordingly. It has become a challenging task to understand the learning preferences of the learners and adapt a method to offer content to suit the learning styles of the learners. Many educationists and researchers in education have made attempts and conducted research on delivering adaptive content. The learners of today are on the look out for content that would suit them in terms of their taste, understanding level, learning curve, own preferences and their personal traits. Thelearning process would be more efficient if we could satisfy the above needs of the learners. This paper makes a survey of the various means of offering adaptive content in an e-learning environment and explores the possible ways of achieving adaptability in learning systems. We conduct a study on the various models of adaptive contentdelivery system and propose newer methods of delivering adaptive content in an e-learning environment.

  19. An Ontology for Learning Services on the Shop Floor

    Science.gov (United States)

    Ullrich, Carsten

    2016-01-01

    An ontology expresses a common understanding of a domain that serves as a basis of communication between people or systems, and enables knowledge sharing, reuse of domain knowledge, reasoning and thus problem solving. In Technology-Enhanced Learning, especially in Intelligent Tutoring Systems and Adaptive Learning Environments, ontologies serve as…

  20. Service-Learning and Interior Design: A Case Study

    Science.gov (United States)

    Sterling, Mary

    2007-01-01

    The case study approach was used to analyze experiential learning through its three components: knowledge, action, and reflection. Two interior design courses were integrated through a university service-learning project. The restoration/adaptive reuse of a 95-year-old library building was to serve as a prototype for future off-campus…

  1. Service-Learning and Interior Design: A Case Study

    Science.gov (United States)

    Sterling, Mary

    2007-01-01

    The case study approach was used to analyze experiential learning through its three components: knowledge, action, and reflection. Two interior design courses were integrated through a university service-learning project. The restoration/adaptive reuse of a 95-year-old library building was to serve as a prototype for future off-campus…

  2. Toward a Theory of Adaptive Transfer: Expanding Disciplinary Discussions of "Transfer" in Second-Language Writing and Composition Studies

    Science.gov (United States)

    DePalma, Michael-John; Ringer, Jeffrey M.

    2011-01-01

    In this paper, we argue that discussions of transfer in L2 writing and composition studies have focused primarily on the reuse of past learning and thus have not adequately accounted for the adaptation of learned writing knowledge in unfamiliar situations. In an effort to expand disciplinary discussions of transfer in L2 writing and composition…

  3. AN ARCHITECTURAL-MODEL FOR CONTEXT AWARE ADAPTIVE DELIVERY OF LEARNING MATERIAL

    Directory of Open Access Journals (Sweden)

    Kalla. Madhu Sudhana

    2013-11-01

    Full Text Available The web based learning has become more complex to search required learning resources with continuously growing digital learning contents which are entangled with structural and semantic interrelationship. Meanwhile, the rapid development of communication technology lead to heterogeneity of learning devices than it was in the early stage. The context-aware adaptive learning environment has become a promising solution to these searching and presentation problems in educational domain. To solve this context aware learning content delivery problem, we proposed a novel architectural model based on MVC (Model–View–Controller design pattern, that is able to perform personalized adaptive delivery of course content according to learner contextual information such as learning style and characteristics of the learning device using an ontological approach.

  4. Evaluating the Impact of Adaptation to Learning Styles in a Web-Based Educational System

    Science.gov (United States)

    Popescu, Elvira

    Measuring the effect of providing educational experiences individualized to the learning style of the students is an open research issue. This paper aims at presenting a case study of a dedicated adaptive educational system called WELSA. First, the adaptation logic, methods and techniques employed in WELSA are briefly presented. Next, the validity and effectiveness of the system are assessed by means of an empirical evaluation approach, involving two experiments with 64 undergraduate students. The results obtained (in terms of learner behavior, performance, efficiency and satisfaction) are analyzed and discussed. The overall results of the experimental study indicate a positive effect of adaptation to learning styles on the learning process.

  5. Physically distributed learning: adapting and reinterpreting physical environments in the development of fraction concepts.

    Science.gov (United States)

    Martin, Taylor; Schwartz, Daniel L

    2005-07-08

    Five studies examined how interacting with the physical environment can support the development of fraction concepts. Nine- and 10-year-old children worked on fraction problems they could not complete mentally. Experiments 1 and 2 showed that manipulating physical pieces facilitated children's ability to develop an interpretation of fractions. Experiment 3 demonstrated that when children understood a content area well, they used their interpretations to repurpose many environments to support problem solving, whereas when they needed to learn, they were prone to the structure of the environment. Experiments 4 and 5 examined transfer after children had learned by manipulating physical pieces. Children who learned by adapting relatively unstructured environments transferred to new materials better than children who learned with "well-structured" environments that did not require equivalent adaptation. Together, the findings reveal that during physically distributed learning, the opportunity to adapt an environment permits the development of new interpretations that can advance learning.

  6. Masters of Adaptation: Learning in Late Life Adjustments

    Science.gov (United States)

    Roberson, Jr., Donald N.

    2005-01-01

    The purpose of this research is to understand the relationship between human development in older adults and personal learning. Personal or self-directed learning (SDL) refers to a style of learning where the individual directs, controls, and evaluates what is learned. It may occur with formal classes, but most often takes place in non-formal…

  7. Motivating children to learn arithmetic with an adaptive robot game

    NARCIS (Netherlands)

    Janssen, J.B.; Wal, C.C. van der; Neerincx, M.A.; Looije, R.

    2011-01-01

    Based on a ‘learning by playing’ concept, a basic arithmetic learning task was extended with an engaging game to achieve long-term educational interaction for children. Personalization was added to this learning task, to further support the child’s motivation and success in learning. In an experimen

  8. Web Log Pre-processing and Analysis for Generation of Learning Profiles in Adaptive E-learning

    Directory of Open Access Journals (Sweden)

    Radhika M. Pai

    2016-04-01

    Full Text Available Adaptive E-learning Systems (AESs enhance the efficiency of online courses in education by providing personalized contents and user interfaces that changes according to learner’s requirements and usage patterns. This paper presents the approach to generate learning profile of each learner which helps to identify the learning styles and provide Adaptive User Interface which includes adaptive learning components and learning material. The proposed method analyzes the captured web usage data to identify the learning profile of the learners. The learning profiles are identified by an algorithmic approach that is based on the frequency of accessing the materials and the time spent on the various learning components on the portal. The captured log data is pre-processed and converted into standard XML format to generate learners sequence data corresponding to the different sessions and time spent. The learning style model adopted in this approach is Felder-Silverman Learning Style Model (FSLSM. This paper also presents the analysis of learner’s activities, preprocessed XML files and generated sequences.

  9. Web Log Pre-processing and Analysis for Generation of Learning Profiles in Adaptive E-learning

    Directory of Open Access Journals (Sweden)

    Radhika M. Pai

    2016-03-01

    Full Text Available Adaptive E-learning Systems (AESs enhance the efficiency of online courses in education by providing personalized contents and user interfaces that changes according to learner’s requirements and usage patterns. This paper presents the approach to generate learning profile of each learner which helps to identify the learning styles and provide Adaptive User Interface which includes adaptive learning components and learning material. The proposed method analyzes the captured web usage data to identify the learning profile of the learners. The learning profiles are identified by an algorithmic approach that is based on the frequency of accessing the materials and the time spent on the various learning components on the portal. The captured log data is pre-processed and converted into standard XML format to generate learners sequence data corresponding to the different sessions and time spent. The learning style model adopted in this approach is Felder-Silverman Learning Style Model (FSLSM. This paper also presents the analysis of learner’s activities, preprocessed XML files and generated sequences.

  10. Multi-Agent Reinforcement Learning and Adaptive Neural Networks.

    Science.gov (United States)

    2007-11-02

    learning method. The objective was to study the utility of reinforcement learning as an approach to complex decentralized control problems. The major...accomplishment was a detailed study of multi-agent reinforcement learning applied to a large-scale decentralized stochastic control problem. This study...included a very successful demonstration that a multi-agent reinforcement learning system using neural networks could learn high-performance

  11. Design Framework for an Adaptive MOOC Enhanced by Blended Learning: Supplementary Training and Personalized Learning for Teacher Professional Development

    Science.gov (United States)

    Gynther, Karsten

    2016-01-01

    The research project has developed a design framework for an adaptive MOOC that complements the MOOC format with blended learning. The design framework consists of a design model and a series of learning design principles which can be used to design in-service courses for teacher professional development. The framework has been evaluated by…

  12. The use of and obstacles to social learning in climate change adaptation initiatives in South Africa

    Directory of Open Access Journals (Sweden)

    Shakespear Mudombi

    2017-01-01

    Full Text Available Global environmental change will have major impacts on ecosystems and human livelihoods while challenging the adaptive capacity of individuals and communities. Social learning, an ongoing adaptive process of knowledge generation, reflection and synthesis, may enhance people’s awareness about climate change and its impacts, with positive outcomes for their adaptive capacity. The objectives of this study were to assess the prevalence of factors promoting social learning in climate change adaptation initiatives in South Africa. An online survey was used to obtain the views of decision makers in government and non-governmental organisations about the presence of personal factors and organisational factors that promote social learning. Descriptive analysis was used to assess these issues. The findings provide some evidence of social learning in climate change adaptation projects in South Africa, with the majority of respondents indicating that personal social learning indicators were present. Mechanisms for improved conflict resolution were, however, less prevalent. The organisational and governance-related barriers to implementation also presented significant challenges. Some of the main organisational barriers were short timeframes for implementing projects, inadequate financial resources, political interference, shortcomings in governance systems and lack of knowledge and expertise in organisations. There is a need for organisations to promote social learning by ensuring that their organisational environment and governance structures are conducive for their employees to embrace social learning. This will help contribute to the overall success of climate change adaptation initiatives.

  13. Reuse and recycling - reverse logistics opportunities

    Energy Technology Data Exchange (ETDEWEB)

    Kopicki, R.; Berg, M.J.; Legg, L.

    1993-12-31

    This book is intended to serve as a managerial guide for planning and implementing waste reduction programs. It is based on the premise that proactive management of environmental issues is becoming vital to corporate success, and that these issues are creating new roles and opportunities for logistic professionals. Examined in detail are nonhazardous waste reduction activities; reuse and recycling activities; and source reduction. The book is based on in-depth interviews with seventeen firms and several trade associations acknowledged to be leaders in waste reduction efforts. Topics discussed include adapting inbound supply chains to use more recycled goods; minimizing packaging waste; reverse distribution capabilities for taking back products and packaging; and the use of third party services for recycling, reuse, and source reduction activities. Included are two case analyses of progressive firms like E.I. Dupont Nemours and Home Depot and their waste reduction efforts.

  14. ADAPTATION OF TEACHING PROCESS BASED ON A STUDENTS INDIVIDUAL LEARNING NEEDS

    Directory of Open Access Journals (Sweden)

    TAKÁCS, Ondřej

    2011-03-01

    Full Text Available Development of current society requires integration of information technology to every sector, including education. The idea of adaptive teaching in e-learning environment is based on paying attention and giving support to various learning styles. More effective, user friendly thus better quality education can be achieved through such an environment. Learning can be influenced by many factors. In the paper we deal with such factors as student’s personality and qualities – particularly learning style and motivation. In addition we want to prepare study materials and study environment which respects students’ differences. Adaptive e-learning means an automated way of teaching which adapts to different qualities of students which are characteristic for their learning styles. In the last few years we can see a gradual individualization of study not only in distance forms of study but also with full-time study students. Instructional supports, namely those of e-learning, should take this trend into account and adapt the educational processes to individual students’ qualities. The present learning management systems (LMS offers this possibility only to a very limited extent. This paper deals with a design of intelligent virtual tutor behavior, which would adapt its learning ability to both static and dynamically changing student’s qualities. Virtual tutor, in order to manage all that, has to have a sufficiently rich supply of different styles and forms of teaching, with enough information about styles of learning, kinds of memory and other student’s qualities. This paper describes a draft adaptive education model and the results of the first part of the solution – definition of learning styles, pilot testing on students and an outline of further research.

  15. Learning analytics in practice: The effects of adaptive educational technology Snappet on students' arithmetic skills

    NARCIS (Netherlands)

    Molenaar, I.; Knoop-van Campen, C.A.N.

    2016-01-01

    Even though the recent influx of tablets in primary education goes together with the vision that educational technology empowered with learning analytics will revolutionize education, empirical results supporting this claim are scares. Adaptive educational technology Snappet combines extracted and e

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

    Directory of Open Access Journals (Sweden)

    Houda Zouari Ounaies, ,

    2008-01-01

    Full Text Available 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 on the development of an evaluation framework of adaptive web-based learning systems, adaptation method assessment is a fundamental aspect. Currently, measures significantly lack to express the adaptive systems features and need to be explored. Consequently, we propose a three-fold approach. Firstly, specific adaptation measurement criteria are suggested. Secondly, experts and learners assess these criteria and both current learning situation and similar past experiences are considered. Finally, fuzzy group decision making theory is adopted to integrate different perceptions related to the adaptive system.

  17. Adaptive properties of differential learning rates for positive and negative outcomes.

    Science.gov (United States)

    Cazé, Romain D; van der Meer, Matthijs A A

    2013-12-01

    The concept of the reward prediction error-the difference between reward obtained and reward predicted-continues to be a focal point for much theoretical and experimental work in psychology, cognitive science, and neuroscience. Models that rely on reward prediction errors typically assume a single learning rate for positive and negative prediction errors. However, behavioral data indicate that better-than-expected and worse-than-expected outcomes often do not have symmetric impacts on learning and decision-making. Furthermore, distinct circuits within cortico-striatal loops appear to support learning from positive and negative prediction errors, respectively. Such differential learning rates would be expected to lead to biased reward predictions and therefore suboptimal choice performance. Contrary to this intuition, we show that on static "bandit" choice tasks, differential learning rates can be adaptive. This occurs because asymmetric learning enables a better separation of learned reward probabilities. We show analytically how the optimal learning rate asymmetry depends on the reward distribution and implement a biologically plausible algorithm that adapts the balance of positive and negative learning rates from experience. These results suggest specific adaptive advantages for separate, differential learning rates in simple reinforcement learning settings and provide a novel, normative perspective on the interpretation of associated neural data.

  18. Adaptive Tutoring for Self-Regulated Learning: A Tutorial on Tutoring Systems

    Science.gov (United States)

    2014-12-01

    learning (SRL) per the Army Learning Model • ontology • tools • methods • standards • exemplars Adaptive Tutoring Systems • Adaptive • Affordable... Ontology -based Student model in Semantic-oriented Access to the Knowledge in Digital Libraries. In proc. of HUBUSKA Fourth Open Workshop “Semantic Web...support or direct). This team state model is a compound model of the trust states existing between team members. The trust relationships are bi -direction

  19. COOPERATIVE LAND REUSE PROGRAM

    Energy Technology Data Exchange (ETDEWEB)

    Unknown

    1999-07-30

    The objective of this study was to determine what financial return, if any, DOE would realize if they invest solely in removal of the asbestos from these three Hanford steam plants and the associated large bore distribution piping at the site. Once the asbestos was removed the strategy was to bring in companies that specialize in salvage and material re-use and have them remove, at no cost to DOE, the plants and the associated large bore piping. The salvage companies we contacted had said that if they didn't have to remove asbestos, they may be able to realize enough value from these plants to offset their demolition and/or dismantling cost. The results were not what we expected but they do offer DOE some favorable financial alternatives to their present approach. The study concluded that there was very little salvage and/or re-use value remaining in the steam plant material that could be used to offset the demolition and/or dismantling cost. The notable exception to this is the removal of the 24 inch steam piping that runs from 200E to 200W areas (see IDM executive summary under Dismantling cost). It is estimated that the re-use value of the 24-inch piping would more than pay for the dismantling cost of this piping. On a more favorable note, it does appear as though the cost of conventional demolition can be reduced by a factor of 3 to 5 if the asbestos is removed first and the demolition is performed using competitive and commercial practices. Both estimates in this study are similar except that IDM did not include floor slab removal nor remove the same quantity of piping. This is why we are using a range of 3 to 5 as a reduction factor. The IDM estimate (using union labor) for demolition after removal of asbestos was approximately $1.5M versus $10.0M for accomplishing the work using Hanford practices and rates.

  20. The Dynamics of Learning and the Emergence of Distributed Adaption

    Science.gov (United States)

    2006-05-01

    empirical tests of one of our tabula rasa learning algorithms on our experi- mental multiagent robotic platform. We experimented with learning in groups...but within distribution- dependent learning paradigms. 5 9 Information theory[73] and computation theory[74, 75] also played important roles , though...encouraging results on an algorithm for tab- ula rasa learning running on robotic vehicles. These showed that individual robots and 18 22 robot collectives can

  1. A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG) Pattern Recognition

    Science.gov (United States)

    Huang, Qi; Yang, Dapeng; Jiang, Li; Zhang, Huajie; Liu, Hong; Kotani, Kiyoshi

    2017-01-01

    Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC), by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC). We compared PAC performance with incremental support vector classifier (ISVC) and non-adapting SVC (NSVC) in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05) and ISVC (13.38% ± 2.62%, p = 0.001), and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle). PMID:28608824

  2. A Novel Unsupervised Adaptive Learning Method for Long-Term Electromyography (EMG Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Qi Huang

    2017-06-01

    Full Text Available Performance degradation will be caused by a variety of interfering factors for pattern recognition-based myoelectric control methods in the long term. This paper proposes an adaptive learning method with low computational cost to mitigate the effect in unsupervised adaptive learning scenarios. We presents a particle adaptive classifier (PAC, by constructing a particle adaptive learning strategy and universal incremental least square support vector classifier (LS-SVC. We compared PAC performance with incremental support vector classifier (ISVC and non-adapting SVC (NSVC in a long-term pattern recognition task in both unsupervised and supervised adaptive learning scenarios. Retraining time cost and recognition accuracy were compared by validating the classification performance on both simulated and realistic long-term EMG data. The classification results of realistic long-term EMG data showed that the PAC significantly decreased the performance degradation in unsupervised adaptive learning scenarios compared with NSVC (9.03% ± 2.23%, p < 0.05 and ISVC (13.38% ± 2.62%, p = 0.001, and reduced the retraining time cost compared with ISVC (2 ms per updating cycle vs. 50 ms per updating cycle.

  3. Intelligent Adaptation and Personalization Techniques in Computer-Supported Collaborative Learning

    CERN Document Server

    Demetriadis, Stavros; Xhafa, Fatos

    2012-01-01

    Adaptation and personalization have been extensively studied in CSCL research community aiming to design intelligent systems that adaptively support eLearning processes and collaboration. Yet, with the fast development in Internet technologies, especially with the emergence of new data technologies and the mobile technologies, new opportunities and perspectives are opened for advanced adaptive and personalized systems. Adaptation and personalization are posing new research and development challenges to nowadays CSCL systems. In particular, adaptation should be focused in a multi-dimensional way (cognitive, technological, context-aware and personal). Moreover, it should address the particularities of both individual learners and group collaboration. As a consequence, the aim of this book is twofold. On the one hand, it discusses the latest advances and findings in the area of intelligent adaptive and personalized learning systems. On the other hand it analyzes the new implementation perspectives for intelligen...

  4. Application and Adaptation of an Institutional Learning Framework

    Science.gov (United States)

    Foutz, Susan; Emmons, Claire Thoma

    2017-01-01

    The Children's Museum of Indianapolis has used a mission-aligned learning framework for more than a decade. Designed to foster and support adult-child interaction in exhibitions and programs, the central tool of the family learning framework is the Assessment of Learning Families in Exhibits (ALFIE) Inventory. ALFIE is used as a tool to plan for…

  5. What Do Academic Users Really Want from an Adaptive Learning System?

    NARCIS (Netherlands)

    Harrigan, Martin; Kravcik, Milos; Steiner, Christina; Wade, Vincent

    2009-01-01

    Harrigan, M., Kravčík, M., Steiner, Ch., & Wade, V. (2009). What Do Academic Users Really Want from an Adaptive Learning System?. In G.-J. Houben, G. McCalla, F. Pianesi & M. Zancanaro (Eds.), User Modeling, Adaptation, and Personalization. Proceedings of the 17th International Conference, UMAP 2009

  6. 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).…

  7. 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).…

  8. The Fairness of Report Card Grading Adaptations: What Do Students with and without Learning Disabilities Think?

    Science.gov (United States)

    Bursuck, William D.; Munk, Dennis D.; Olson, Mary M.

    1999-01-01

    A study of 15 high school students with learning disabilities and 257 typical students found no grading adaptation was viewed as fair by a majority of students without disabilities. Changing the grading scale and raising grades to reflect improvement were viewed as fair adaptations by the students with disabilities. (CR)

  9. Adapting Learning Activities: a Case Study of IMS LD based Script and Tooling

    NARCIS (Netherlands)

    Miao, Yongwu

    2009-01-01

    Miao, Y. (2009). Adapting Learning Activities: a Case Study of IMS LD based Script and Tooling. Paper presented at workshop "Adapting Activities Modeled by CSCL Scripts" of the 8th International Conference “Computer Supported Collaborative Learning” (CSCL’09). June, 8-13, 2009, Rhodes, Greece.

  10. Adapting Learning Activities: a Case Study of IMS LD based Script and Tooling

    NARCIS (Netherlands)

    Miao, Yongwu

    2009-01-01

    Miao, Y. (2009). Adapting Learning Activities: a Case Study of IMS LD based Script and Tooling. Presentation at workshop "Adapting Activities Modeled by CSCL Scripts" of the 8th International Conference “Computer Supported Collaborative Learning” (CSCL’09). June, 8-13, 2009, Rhodes, Greece.

  11. Performing Verification and Validation in Reuse-Based Software Engineering

    Science.gov (United States)

    Addy, Edward A.

    1999-01-01

    The implementation of reuse-based software engineering not only introduces new activities to the software development process, such as domain analysis and domain modeling, it also impacts other aspects of software engineering. Other areas of software engineering that are affected include Configuration Management, Testing, Quality Control, and Verification and Validation (V&V). Activities in each of these areas must be adapted to address the entire domain or product line rather than a specific application system. This paper discusses changes and enhancements to the V&V process, in order to adapt V&V to reuse-based software engineering.

  12. 不同再生水处理工艺出水水质回用途径适应性分析%Analysis about reuse approach adaptability for effluent quality from different reclaimed water treatment processes

    Institute of Scientific and Technical Information of China (English)

    张庆康; 郝瑞霞; 刘峰; 赵继成; 杨英杰

    2013-01-01

    为分析典型再生水处理工艺出水的回用途径适应性,采用标准指数法评价了4座不同处理工艺的再生水厂出水质量,为再生水处理工艺选择和安全回用提供参考.结果表明,4种再生水处理工艺出水用于市政杂用水时基本是安全的;除反渗透(RO)工艺外,其他工艺出水回用于景观环境用水时都存在氮磷指标超标问题;膜处理工艺的出水可以满足工业用水标准,但是常规絮凝过滤工艺出水用作工业用水应注意氮磷等指标的进一步处理;各种再生水处理工艺出水质量均不能满足地下水回灌用水标准,主要是氨氮和环境激素DBP超标问题,用作地下水回灌用水时存在一定的环境风险.%The treated effluent quality of four different technologies types of reclaimed water treatment plants was evaluated with the standard index method in order to analyze the adaptability of the reuse approaches of treated effluents from typical reclaimed water treatment processes. This study could be a valuable reference to the selection of reclaimed water treatment processes and the security of reuse. The results of the study indicated that the reclaimed water treated by the four types of the treatment processes was basically safe to be used for municipal water usage. However, they all have different problems with meeting the relevant standards on certain kinds of water utilisation. The reclaimed waters treated by the treatment processes, except treated by RO process, all have problems with their nitrogen and phosphorus concentration exceeding the scandalised concentration in the case of being used for landscape purpose. The effluent water treated by membrane process could meet the requirements of the standard on industrial water usage. The reclaimed water treated by conventional floccula-tion filtration process requires further treatment on nitrogen and phosphorus removal. According to the water quality standard for recharging ground

  13. Adaptive Semantic and Social Web-based learning and assessment environment for the STEM

    Science.gov (United States)

    Babaie, Hassan; Atchison, Chris; Sunderraman, Rajshekhar

    2014-05-01

    We are building a cloud- and Semantic Web-based personalized, adaptive learning environment for the STEM fields that integrates and leverages Social Web technologies to allow instructors and authors of learning material to collaborate in semi-automatic development and update of their common domain and task ontologies and building their learning resources. The semi-automatic ontology learning and development minimize issues related to the design and maintenance of domain ontologies by knowledge engineers who do not have any knowledge of the domain. The social web component of the personal adaptive system will allow individual and group learners to interact with each other and discuss their own learning experience and understanding of course material, and resolve issues related to their class assignments. The adaptive system will be capable of representing key knowledge concepts in different ways and difficulty levels based on learners' differences, and lead to different understanding of the same STEM content by different learners. It will adapt specific pedagogical strategies to individual learners based on their characteristics, cognition, and preferences, allow authors to assemble remotely accessed learning material into courses, and provide facilities for instructors to assess (in real time) the perception of students of course material, monitor their progress in the learning process, and generate timely feedback based on their understanding or misconceptions. The system applies a set of ontologies that structure the learning process, with multiple user friendly Web interfaces. These include the learning ontology (models learning objects, educational resources, and learning goal); context ontology (supports adaptive strategy by detecting student situation), domain ontology (structures concepts and context), learner ontology (models student profile, preferences, and behavior), task ontologies, technological ontology (defines devices and places that surround the

  14. Partner Knowledge Awareness in Knowledge Communication: Learning by Adapting to the Partner

    Science.gov (United States)

    Dehler Zufferey, Jessica; Bodemer, Daniel; Buder, Jurgen; Hesse, Friedrich W.

    2011-01-01

    Awareness of the knowledge of learning partners is not always sufficiently available in collaborative learning scenarios. To compensate, the authors propose to provide collaborators with partner knowledge awareness by means of a visualization tool. Partner knowledge awareness can be used to adapt messages toward the partner. This study…

  15. Educational Multimedia Profiling Recommendations for Device-Aware Adaptive Mobile Learning

    Science.gov (United States)

    Moldovan, Arghir-Nicolae; Ghergulescu, Ioana; Muntean, Cristina Hava

    2014-01-01

    Mobile learning is seeing a fast adoption with the increasing availability and affordability of mobile devices such as smartphones and tablets. As the creation and consumption of educational multimedia content on mobile devices is also increasing fast, educators and mobile learning providers are faced with the challenge to adapt multimedia type…

  16. Fast but fleeting: adaptive motor learning processes associated with aging and cognitive decline.

    Science.gov (United States)

    Trewartha, Kevin M; Garcia, Angeles; Wolpert, Daniel M; Flanagan, J Randall

    2014-10-01

    Motor learning has been shown to depend on multiple interacting learning processes. For example, learning to adapt when moving grasped objects with novel dynamics involves a fast process that adapts and decays quickly-and that has been linked to explicit memory-and a slower process that adapts and decays more gradually. Each process is characterized by a learning rate that controls how strongly motor memory is updated based on experienced errors and a retention factor determining the movement-to-movement decay in motor memory. Here we examined whether fast and slow motor learning processes involved in learning novel dynamics differ between younger and older adults. In addition, we investigated how age-related decline in explicit memory performance influences learning and retention parameters. Although the groups adapted equally well, they did so with markedly different underlying processes. Whereas the groups had similar fast processes, they had different slow processes. Specifically, the older adults exhibited decreased retention in their slow process compared with younger adults. Within the older group, who exhibited considerable variation in explicit memory performance, we found that poor explicit memory was associated with reduced retention in the fast process, as well as the slow process. These findings suggest that explicit memory resources are a determining factor in impairments in the both the fast and slow processes for motor learning but that aging effects on the slow process are independent of explicit memory declines.

  17. Towards Increased Relevance: Context-Adapted Models of the Learning Organization

    Science.gov (United States)

    Örtenblad, Anders

    2015-01-01

    Purpose: The purposes of this paper are to take a closer look at the relevance of the idea of the learning organization for organizations in different generalized organizational contexts; to open up for the existence of multiple, context-adapted models of the learning organization; and to suggest a number of such models.…

  18. The Effect of Adaptive Confidence Strategies in Computer-Assisted Instruction on Learning and Learner Confidence

    Science.gov (United States)

    Warren, Richard Daniel

    2012-01-01

    The purpose of this research was to investigate the effects of including adaptive confidence strategies in instructionally sound computer-assisted instruction (CAI) on learning and learner confidence. Seventy-one general educational development (GED) learners recruited from various GED learning centers at community colleges in the southeast United…

  19. Academic Accountability and University Adaptation: The Architecture of an Academic Learning Organization.

    Science.gov (United States)

    Dill, David D.

    1999-01-01

    Discussses various adaptations in organizational structure and governance of academic learning institutions, using case studies of universities that are attempting to improve the quality of teaching and the learning process. Identifies five characteristics typical of such organizations: (1) a culture of evidence; (2) improved coordination of…

  20. The Effect of Adaptive Confidence Strategies in Computer-Assisted Instruction on Learning and Learner Confidence

    Science.gov (United States)

    Warren, Richard Daniel

    2012-01-01

    The purpose of this research was to investigate the effects of including adaptive confidence strategies in instructionally sound computer-assisted instruction (CAI) on learning and learner confidence. Seventy-one general educational development (GED) learners recruited from various GED learning centers at community colleges in the southeast United…

  1. Towards Increased Relevance: Context-Adapted Models of the Learning Organization

    Science.gov (United States)

    Örtenblad, Anders

    2015-01-01

    Purpose: The purposes of this paper are to take a closer look at the relevance of the idea of the learning organization for organizations in different generalized organizational contexts; to open up for the existence of multiple, context-adapted models of the learning organization; and to suggest a number of such models.…

  2. An Online Adaptive Learning Environment for Critical-Thinking-Infused English Literacy Instruction

    Science.gov (United States)

    Yang, Ya-Ting Carolyn; Gamble, Jeffrey Hugh; Hung, Yu-Wan; Lin, Tzu-Yun

    2014-01-01

    Critical thinking (CT) and English literacy are two essential 21st century competencies that are a priority for teaching and learning in an increasingly digital learning environment. Taking advantage of innovations in educational technology, this study empirically investigates the effectiveness of CT-infused adaptive English literacy instruction…

  3. International Students' Culture Learning and Cultural Adaptation in China

    Science.gov (United States)

    An, Ran; Chiang, Shiao-Yun

    2015-01-01

    This article examines international students' cultural adaptation at a major national university in China. A survey was designed to measure international students' adaptation to the Chinese sociocultural and educational environments in terms of five dimensions: (1) cultural empathy, (2) open-mindedness, (3) emotional stability, (4) social…

  4. Construction of a new adaptive wavelet network and its learning algorithm

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    A new adaptive learning algorithm for constructing and training wavelet networks is proposed based on the time-frequency localization properties of wavelet frames and the adaptive projection algorithm. The exponential convergence of the adaptive projection algorithm in finite-dimensional Hilbert spaces is constructively proved, with exponential decay ratios given with high accuracy. The learning algorithm can sufficiently utilize the time-frequency information contained in the training data, iteratively determines the number of the hidden layer nodes and the weights of wavelet networks, and solves the problem of structure optimization of wavelet networks. The algorithm is simple and efficient, as illustrated by examples of signal representation and denoising.

  5. Learning to bridge the gap between adaptive management and organisational culture

    Directory of Open Access Journals (Sweden)

    Richard J. Stirzaker

    2011-05-01

    Full Text Available Adaptive management is the problem-solving approach of choice proposed for complex and multistakeholder environments, which are, at best, only partly predictable. We discuss the implications of this approach as applicable to scientists, who have to overcome certain entrained behaviour patterns in order to participate effectively in an adaptive management process. The challenge does not end there. Scientists and managers soon discover that an adaptive management approach does not only challenge conventional scientific and management behaviour but also clashes with contemporary organisational culture. We explore the shortcomings and requirements of organisations with regard to enabling adaptive management. Our overall conclusion relates to whether organisations are learning-centred or not. Do we continue to filter out unfamiliar information which does not fit our world view and avoid situations where we might fail, or do we use new and challenging situations to reframe the question and prepare ourselves for continued learning? Conservation implications: For an organisation to effectively embrace adaptive management, its mangers and scientists may first have to adapt their own beliefs regarding their respective roles. Instead of seeking certainty for guiding decisions, managers and scientists should acknowledge a degree of uncertainty inherent to complex social and ecological systems and seek to learn from the patterns emerging from every decision and action. The required organisational culture is one of ongoing and purposeful learning with all relevant stakeholders. Such a learning culture is often talked about but rarely practised in the organisational environment.

  6. 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.

  7. 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.

  8. Specialized hybrid learners resolve Rogers' paradox about the adaptive value of social learning.

    Science.gov (United States)

    Kharratzadeh, Milad; Montrey, Marcel; Metz, Alex; Shultz, Thomas R

    2017-02-07

    Culture is considered an evolutionary adaptation that enhances reproductive fitness. A common explanation is that social learning, the learning mechanism underlying cultural transmission, enhances mean fitness by avoiding the costs of individual learning. This explanation was famously contradicted by Rogers (1988), who used a simple mathematical model to show that cheap social learning can invade a population without raising its mean fitness. He concluded that some crucial factor remained unaccounted for, which would reverse this surprising result. Here we extend this model to include a more complex environment and limited resources, where individuals cannot reliably learn everything about the environment on their own. Under such conditions, cheap social learning evolves and enhances mean fitness, via hybrid learners capable of specializing their individual learning. We then show that while spatial or social constraints hinder the evolution of hybrid learners, a novel social learning strategy, complementary copying, can mitigate these effects.

  9. X-Learn: An XML-Based, Multi-agent System for Supporting "User-Device" Adaptive E-learning

    CERN Document Server

    De Meo, P; Terracina, G; Ursino, D

    2009-01-01

    In this paper we present X-Learn, an XML-based, multi-agent system for supporting "user-device" adaptive e-learning. X-Learn is characterized by the following features: (i) it is highly subjective, since it handles quite a rich and detailed user profile that plays a key role during the learning activities; (ii) it is dynamic and flexible, i.e., it is capable of reacting to variations of exigencies and objectives; (iii) it is device-adaptive, since it decides the learning objects to present to the user on the basis of the device she/he is currently exploiting; (iv) it is generic, i.e., it is capable of operating in a large variety of learning contexts; (v) it is XML based, since it exploits many facilities of XML technology for handling and exchanging information connected to e-learning activities. The paper reports also various experimental results as well as a comparison between X-Learn and other related e-learning management systems already presented in the literature.

  10. A neural learning classifier system with self-adaptive constructivism for mobile robot control.

    Science.gov (United States)

    Hurst, Jacob; Bull, Larry

    2006-01-01

    For artificial entities to achieve true autonomy and display complex lifelike behavior, they will need to exploit appropriate adaptable learning algorithms. In this context adaptability implies flexibility guided by the environment at any given time and an open-ended ability to learn appropriate behaviors. This article examines the use of constructivism-inspired mechanisms within a neural learning classifier system architecture that exploits parameter self-adaptation as an approach to realize such behavior. The system uses a rule structure in which each rule is represented by an artificial neural network. It is shown that appropriate internal rule complexity emerges during learning at a rate controlled by the learner and that the structure indicates underlying features of the task. Results are presented in simulated mazes before moving to a mobile robot platform.

  11. Sparsity-based Image Error Concealment via Adaptive Dual Dictionary Learning and Regularization.

    Science.gov (United States)

    Liu, Xianming; Zhai, Deming; Zhou, Jiantao; Wang, Shiqi; Zhao, Debin; Gao, Huijun

    2016-10-31

    In this paper, we propose a novel sparsity-based image error concealment (EC) algorithm through Adaptive Dual dictionary Learning and Regularization (ADLR). We define two feature spaces: the observed space and the latent space, corresponding to the available regions and the missing regions of image under test, respectively. We learn adaptive and complete dictionaries individually for each space, where the training data are collected via an adaptive template matching mechanism. Based on the piecewise stationarity of natural images, a local correlation model is learned to bridge the sparse representations of the aforementioned dual spaces, allowing us to transfer the knowledge of the available regions to the missing regions for EC purpose. Eventually, the EC task is formulated as a unified optimization problem, where the sparsity of both spaces and the learned correlation model are incorporated. Experimental results show that the proposed method outperforms the state-of-the-art techniques in terms of both objective and perceptual metrics.

  12. Software reuse environment user's guide

    Science.gov (United States)

    1988-01-01

    This document describes the services provided by the prototype Software Reuse Environment, which was developed by CTA for NASA Goddard Space Flight Center, Code 520. This is one of three guides delivered by CTA as part of the environment. The other two guides are: Software Generation and Installation Guide; and SEMANTX--Defining the Schema. The Software Generation and Installation Guide describes the software source modules that make up the Reuse Environment, with instructions on how to generate and install an executable system from the source code. SEMANTX--Defining the Schema describes how a reuse database is created. Actually this guide is more general than the reuse database, as it describes how to generate a SEMANTX database. SEMANTX is an off-the-shelf tool that we have used to implement the reuse database. It is a product of Semantyk Systems, Inc. The Software Reuse Environment is built upon SEMANTX as well as on the IDE Structured Analysis Integrated Environment. (IDE is Interactive Development Environments, Inc.) SEMANTX itself is built on top of the Unify Database Management System. To use the Software Reuse Environment you should have the User's Manuals for SEMANTX, for Unify, and for the IDE software. CTA has provided all of these with the environment.

  13. Adapting web-based instruction to residents' knowledge improves learning efficiency: a randomized controlled trial.

    Science.gov (United States)

    Cook, David A; Beckman, Thomas J; Thomas, Kris G; Thompson, Warren G

    2008-07-01

    Increased clinical demands and decreased available time accentuate the need for efficient learning in postgraduate medical training. Adapting Web-based learning (WBL) to learners' prior knowledge may improve efficiency. We hypothesized that time spent learning would be shorter and test scores not adversely affected for residents who used a WBL intervention that adapted to prior knowledge. Randomized, crossover trial. Academic internal medicine residency program continuity clinic. 122 internal medicine residents. Four WBL modules on ambulatory medicine were developed in standard and adaptive formats. The adaptive format allowed learners who correctly answered case-based questions to skip the corresponding content. The measurements were knowledge posttest, time spent on modules, and format preference. One hundred twenty-two residents completed at least 1 module, and 111 completed all 4. Knowledge scores were similar between the adaptive format (mean +/- standard error of the mean, 76.2 +/- 0.9) and standard (77.2 +/- 0.9, 95% confidence interval [CI] for difference -3.0 to 1.0, P = .34). However, time spent was lower for the adaptive format (29.3 minutes [CI 26.0 to 33.0] per module) than for the standard (35.6 [31.6 to 40.3]), an 18% decrease in time (CI 9 to 26%, P = .0003). Seventy-two of 96 respondents (75%) preferred the adaptive format. Adapting WBL to learners' prior knowledge can reduce learning time without adversely affecting knowledge scores, suggesting greater learning efficiency. In an era where reduced duty hours and growing clinical demands on trainees and faculty limit the time available for learning, such efficiencies will be increasingly important. For clinical trial registration, see http://www.clinicaltrials.gov NCT00466453 ( http://www.clinicaltrials.gov/ct/show/NCT00466453?order=1 ).

  14. Complex Mobile Learning That Adapts to Learners' Cognitive Load

    Science.gov (United States)

    Deegan, Robin

    2015-01-01

    Mobile learning is cognitively demanding and frequently the ubiquitous nature of mobile computing means that mobile devices are used in cognitively demanding environments. This paper examines the use of mobile devices from a Learning, Usability and Cognitive Load Theory perspective. It suggests scenarios where these fields interact and presents an…

  15. Learning Beyond the Buzzwords: Developing the Adaptable, Competent CSS Soldier

    Science.gov (United States)

    2007-11-02

    current and past knowledge. Jean Piaget , one of the major influencers of Constructivist theory, proposed that learning occurs through an interaction...schema. Learning results from a balanced tension between these two processes. 25 Piaget believed that intelligence is shaped by experience, and

  16. Psychosocial and Adaptive Deficits Associated with Learning Disability Subtypes

    Science.gov (United States)

    Backenson, Erica M.; Holland, Sara C.; Kubas, Hanna A.; Fitzer, Kim R.; Wilcox, Gabrielle; Carmichael, Jessica A.; Fraccaro, Rebecca L.; Smith, Amanda D.; Macoun, Sarah J.; Harrison, Gina L.; Hale, James B.

    2015-01-01

    Children with specific learning disabilities (SLD) have deficits in the basic psychological processes that interfere with learning and academic achievement, and for some SLD subtypes, these deficits can also lead to emotional and/or behavior problems. This study examined psychosocial functioning in 123 students, aged 6 to 11, who underwent…

  17. Complex Mobile Learning That Adapts to Learners' Cognitive Load

    Science.gov (United States)

    Deegan, Robin

    2015-01-01

    Mobile learning is cognitively demanding and frequently the ubiquitous nature of mobile computing means that mobile devices are used in cognitively demanding environments. This paper examines the use of mobile devices from a Learning, Usability and Cognitive Load Theory perspective. It suggests scenarios where these fields interact and presents an…

  18. Using Ontology to Drive an Adaptive Learning Interface

    Directory of Open Access Journals (Sweden)

    Andrew Crapo

    2004-10-01

    Full Text Available Intelligent, adaptive interfaces are a pre-requisite to elevating computer-based applications to the realm of collaborative decision support in complex, relatively open-ended domains such as logistics and planning. This is because the composition and effective presentation of even the most useful information must be tailored to constantly changing circumstances. Our objective is to not only achieve an adaptive human-machine interface, but to imbue the software with a significant portion of the responsibility for effectively controlling the adaptation, freeing the user from unnecessary distraction and making the human-machine relationship more collaborative in nature. The foundational concepts of interface adaptation are discussed and a specific logistics application is described as an example.

  19. Using Ontology to Drive an Adaptive Learning Interface

    Directory of Open Access Journals (Sweden)

    Andrew Crapo

    2004-10-01

    Full Text Available Intelligent, adaptive interfaces are a pre-requisite to elevating computer-based applications to the realm of collaborative decision support in complex, relatively open-ended domains such as logistics and planning. This is because the composition and effective presentation of even the most useful information must be tailored to constantly changing circumstances. Our objective is to not only achieve an adaptive human-machine interface, but to imbue the software with a significant portion of the responsibility for effectively controlling the adaptation, freeing the user from unnecessary distraction and making the human-machine relationship more collaborative in nature. The foundational concepts of interface adaptation are discussed and a specific logistics application is described as an example.

  20. ADAPTIVE LEARNING OF HIDDEN MARKOV MODELS FOR EMOTIONAL SPEECH

    Directory of Open Access Journals (Sweden)

    A. V. Tkachenia

    2014-01-01

    Full Text Available An on-line unsupervised algorithm for estimating the hidden Markov models (HMM parame-ters is presented. The problem of hidden Markov models adaptation to emotional speech is solved. To increase the reliability of estimated HMM parameters, a mechanism of forgetting and updating is proposed. A functional block diagram of the hidden Markov models adaptation algorithm is also provided with obtained results, which improve the efficiency of emotional speech recognition.

  1. Lessons Learned from the First Decade of Adaptive Management in Comprehensive Everglades Restoration

    Directory of Open Access Journals (Sweden)

    Andrew J. LoSchiavo

    2013-12-01

    Full Text Available Although few successful examples of large-scale adaptive management applications are available to ecosystem restoration scientists and managers, examining where and how the components of an adaptive management program have been successfully implemented yields insight into what approaches have and have not worked. We document five key lessons learned during the decade-long development and implementation of the Comprehensive Everglades Restoration Plan (CERP Collaborative Adaptive Management Program that might be useful to other adaptive management practitioners. First, legislative and regulatory authorities that require the development of an adaptive management program are necessary to maintain funding and support to set up and implement adaptive management. Second, integration of adaptive management activities into existing institutional processes, and development of technical guidance, helps to ensure that adaptive management activities are understood and roles and responsibilities are clearly articulated so that adaptive management activities are implemented successfully. Third, a strong applied science framework is critical for establishing a prerestoration ecosystem reference condition and understanding of how the system works, as well as for providing a conduit for incorporating new scientific information into the decision-making process. Fourth, clear identification of uncertainties that pose risks to meeting restoration goals helps with the development of hypothesis-driven strategies to inform restoration planning and implementation. Tools such as management options matrices can provide a coherent way to link hypotheses to specific monitoring efforts and options to adjust implementation if performance goals are not achieved. Fifth, independent external peer review of an adaptive management program provides important feedback critical to maintaining and improving adaptive management implementation for ecosystem restoration. These lessons

  2. A modified Adaptive Wavelet PID Control Based on Reinforcement Learning for Wind Energy Conversion System Control

    Directory of Open Access Journals (Sweden)

    REZAZADEH, A.

    2010-05-01

    Full Text Available Nonlinear characteristics of wind turbines and electric generators necessitate complicated and nonlinear control of grid connected Wind Energy Conversion Systems (WECS. This paper proposes a modified self-tuning PID control strategy, using reinforcement learning for WECS control. The controller employs Actor-Critic learning in order to tune PID parameters adaptively. These Actor-Critic learning is a special kind of reinforcement learning that uses a single wavelet neural network to approximate the policy function of the Actor and the value function of the Critic simultaneously. These controllers are used to control a typical WECS in noiseless and noisy condition and results are compared with an adaptive Radial Basis Function (RBF PID control based on reinforcement learning and conventional PID control. Practical emulated results prove the capability and the robustness of the suggested controller versus the other PID controllers to control of the WECS. The ability of presented controller is tested by experimental setup.

  3. Adaptive Content and Process Scaffolding: A key to facilitating students’ self-regulated learning with hypermedia

    Directory of Open Access Journals (Sweden)

    Roger Azevedo

    2011-03-01

    Full Text Available In this mixed-method study, we converged product and process data to examine the effectiveness of three human scaffolding conditions in facilitating students’ learning about the circulatory system and the deployment of key self-regulatory processes during a 40-minute hypermedia learning task. Undergraduate students (N = 123 were randomly assigned to one of three scaffolding conditions (adaptive content and process scaffolding [ACPS], adaptive process scaffolding [APS], and no scaffolding [NS] and were trained to use a hypermedia environment to learn about the circulatory system. The product data revealed that the students in the ACPS condition gained significantly more declarative knowledge than did those in the other two comparison conditions. In addition, ACPS was statistically significantly associated with qualitative shifts in the students’ mental models of the topic, whereas the other two conditions were not. The verbal protocol data revealed that students in the ACPS condition utilized only a few regulatory processes, engaged in help-seeking behavior, and relied on the tutor to regulate their learning. By contrast, the verbal protocol data indicated that learners in the APS condition regulated their learning by using several key monitoring activities and learning strategies, while those in the NS condition were less effective at regulating their learning and used fewer key self-regulatory processes during the activity. We propose several design principles for adaptive hypermedia learning environments based on these findings.

  4. Preference learning with evolutionary Multivariate Adaptive Regression Spline model

    DEFF Research Database (Denmark)

    Abou-Zleikha, Mohamed; Shaker, Noor; Christensen, Mads Græsbøll

    2015-01-01

    for human decision making. Learning models from pairwise preference data is however an NP-hard problem. Therefore, constructing models that can effectively learn such data is a challenging task. Models are usually constructed with accuracy being the most important factor. Another vitally important aspect...... that is usually given less attention is expressiveness, i.e. how easy it is to explain the relationship between the model input and output. Most machine learning techniques are focused either on performance or on expressiveness. This paper employ MARS models which have the advantage of being a powerful method...

  5. On the nature of cultural transmission networks: evidence from Fijian villages for adaptive learning biases.

    Science.gov (United States)

    Henrich, Joseph; Broesch, James

    2011-04-12

    Unlike other animals, humans are heavily dependent on cumulative bodies of culturally learned information. Selective processes operating on this socially learned information can produce complex, functionally integrated, behavioural repertoires-cultural adaptations. To understand such non-genetic adaptations, evolutionary theorists propose that (i) natural selection has favoured the emergence of psychological biases for learning from those individuals most likely to possess adaptive information, and (ii) when these psychological learning biases operate in populations, over generations, they can generate cultural adaptations. Many laboratory experiments now provide evidence for these psychological biases. Here, we bridge from the laboratory to the field by examining if and how these biases emerge in a small-scale society. Data from three cultural domains-fishing, growing yams and using medicinal plants-show that Fijian villagers (ages 10 and up) are biased to learn from others perceived as more successful/knowledgeable, both within and across domains (prestige effects). We also find biases for sex and age, as well as proximity effects. These selective and centralized oblique transmission networks set up the conditions for adaptive cultural evolution.

  6. Vocal learning in elephants: neural bases and adaptive context.

    Science.gov (United States)

    Stoeger, Angela S; Manger, Paul

    2014-10-01

    In the last decade clear evidence has accumulated that elephants are capable of vocal production learning. Examples of vocal imitation are documented in African (Loxodonta africana) and Asian (Elephas maximus) elephants, but little is known about the function of vocal learning within the natural communication systems of either species. We are also just starting to identify the neural basis of elephant vocalizations. The African elephant diencephalon and brainstem possess specializations related to aspects of neural information processing in the motor system (affecting the timing and learning of trunk movements) and the auditory and vocalization system. Comparative interdisciplinary (from behavioral to neuroanatomical) studies are strongly warranted to increase our understanding of both vocal learning and vocal behavior in elephants.

  7. ONR STEM Grand Challenge: Extensible Adaptive System for STEM Learning

    Science.gov (United States)

    2013-04-12

    advanced learning systems. These learning systems employ state-of- the-art pedagogical and computation techniques to improve student proficiency in...used by domain experts and system administrators to add and modify knowledge sources used by the SAT Physics EAITS in an ongoing manner without the...developers, subject matter experts, and system administrators . All such users access the system through one of two end user interfaces, which are both

  8. Cerebellar Contributions to Reach Adaptation and Learning Sensory Consequences of Action

    Science.gov (United States)

    Izawa, Jun; Criscimagna-Hemminger, Sarah E.; Shadmehr, Reza

    2012-01-01

    When we use a novel tool, the motor commands may not produce the expected outcome. In healthy individuals, with practice the brain learns to alter the motor commands. This change depends critically on the cerebellum as damage to this structure impairs adaptation. However, it is unclear precisely what the cerebellum contributes to the process of adaptation in human motor learning. Is the cerebellum crucial for learning to associate motor commands with novel sensory consequences, called forward model, or is the cerebellum important for learning to associate sensory goals with novel motor commands, called inverse model? Here, we compared performance of cerebellar patients and healthy controls in a reaching task with a gradual perturbation schedule. This schedule allowed both groups to adapt their motor commands. Following training, we measured two kinds of behavior: in one case people were presented with reach targets near the direction in which they had trained. The resulting generalization patterns of patients and controls were similar, suggesting comparable inverse models. In another case, they reached without a target and reported the location of their hand. In controls the pattern of change in reported hand location was consistent with simulation results of a forward model that had learned to associate motor commands with new sensory consequences. In patients, this change was significantly smaller. Therefore, in our sample of patients we observed that while adaptation of motor commands can take place despite cerebellar damage, cerebellar integrity appears critical for learning to predict visual sensory consequences of motor commands. PMID:22442085

  9. Economic Analysis on Wastewater Reuse

    Institute of Scientific and Technical Information of China (English)

    Yushan WAN; Na LI

    2012-01-01

    Abstract The shortage of water resources social development. Wastewater reuse is an has become a major limiting factor for effective solution to solve water short- ages, which not only has economic benefits, but also has significant social and en- vironmental benefits. The economic evaluation is an important component in the study of wastewater reuse feasibility and the basis for the program optimization and economic feasibility determination.

  10. Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization

    CERN Document Server

    Golovin, Daniel

    2010-01-01

    Solving stochastic optimization problems under partial observability, where we need to adaptively make decisions with uncertain outcomes, is a fundamental but notoriously difficult challenge. In this paper, we introduce the concept of adaptive submodularity, generalizing submodular set functions to adaptive policies. We prove that if a problem satisfies this property, a simple adaptive greedy algorithm is guaranteed to be competitive with the optimal policy. We illustrate the usefulness of the concept by giving several examples of adaptive submodular objectives arising in diverse applications including sensor placement, viral marketing and pool-based active learning. Proving adaptive submodularity for these problems allows us to recover existing results in these applications as special cases and leads to natural generalizations.

  11. Delayed feedback during sensorimotor learning selectively disrupts adaptation but not strategy use.

    Science.gov (United States)

    Brudner, Samuel N; Kethidi, Nikhit; Graeupner, Damaris; Ivry, Richard B; Taylor, Jordan A

    2016-03-01

    In sensorimotor adaptation tasks, feedback delays can cause significant reductions in the rate of learning. This constraint is puzzling given that many skilled behaviors have inherently long delays (e.g., hitting a golf ball). One difference in these task domains is that adaptation is primarily driven by error-based feedback, whereas skilled performance may also rely to a large extent on outcome-based feedback. This difference suggests that error- and outcome-based feedback may engage different learning processes, and these processes may be associated with different temporal constraints. We tested this hypothesis in a visuomotor adaptation task. Error feedback was indicated by the terminal position of a cursor, while outcome feedback was indicated by points. In separate groups of participants, the two feedback signals were presented immediately at the end of the movement, after a delay, or with just the error feedback delayed. Participants learned to counter the rotation in a similar manner regardless of feedback delay. However, the aftereffect, an indicator of implicit motor adaptation, was attenuated with delayed error feedback, consistent with the hypothesis that a different learning process supports performance under delay. We tested this by employing a task that dissociates the contribution of explicit strategies and implicit adaptation. We find that explicit aiming strategies contribute to the majority of the learning curve, regardless of delay; however, implicit learning, measured over the course of learning and by aftereffects, was significantly attenuated with delayed error-based feedback. These experiments offer new insight into the temporal constraints associated with different motor learning processes.

  12. How assessment and reflection relate to more effective learning in adaptive management

    Directory of Open Access Journals (Sweden)

    Harry Biggs

    2011-05-01

    Full Text Available Assessment (an immediate evaluation of significance or performance and reflection (a lengthy, deep consideration should be important components of adaptive management leading to learning. In this paper we use a prototype adaptive cycle and feedback framework, which are related to some aspects of learning theory, to examine the extent to which assessment and reflection were applied in a series of studies and initiatives in the Kruger National Park. In addition to evaluating assessment and reflection, we also considered how the various contributing components of each case were inter-related to provide a holistic view of each initiative.Two other studies in the Kruger National Park, which have examined learning specifically, are also discussed. One of them suggests that in a complex environment, learning necessarily has a dual nature, with each component of seven contrasting pairs of the aspects of learning in partial tension with the other. We use these dualities to further probe assessment, reflection, inter-relatedness and learning in the cases presented. Each contrasting aspect of a ‘learning duality’ turns out to emphasise either assessment or reflection, which reinforces the idea that both are needed to facilitate sufficient learning for successful adaptive management. We hope this analysis can act as a springboard for further study, practice and reflection on these important and often underrated components of adaptive management.Conservation implications: The better understanding of assessment and reflection as being largely separate but complementary actions will assist adaptive management practitioners to give explicit attention to both, and to relate them better to each other.

  13. Online classifier adaptation for cost-sensitive learning

    OpenAIRE

    Zhang, Junlin; Garcia, Jose

    2015-01-01

    In this paper, we propose the problem of online cost-sensitive clas- sifier adaptation and the first algorithm to solve it. We assume we have a base classifier for a cost-sensitive classification problem, but it is trained with respect to a cost setting different to the desired one. Moreover, we also have some training data samples streaming to the algorithm one by one. The prob- lem is to adapt the given base classifier to the desired cost setting using the steaming training samples online. ...

  14. Self-adaptive learning based discrete differential evolution algorithm for solving CJWTA problem

    Institute of Scientific and Technical Information of China (English)

    Yu Xue; Yi Zhuang; Tianquan Ni; Siru Ni; Xuezhi Wen

    2014-01-01

    Cooperative jamming weapon-target assignment (CJWTA) problem is a key issue in electronic countermeasures (ECM). Some symbols which relevant to the CJWTA are defined firstly. Then, a formulation of jamming fitness is presented. Final y, a model of the CJWTA problem is constructed. In order to solve the CJWTA problem efficiently, a self-adaptive learning based discrete differential evolution (SLDDE) algorithm is proposed by introduc-ing a self-adaptive learning mechanism into the traditional discrete differential evolution algorithm. The SLDDE algorithm steers four candidate solution generation strategies simultaneously in the framework of the self-adaptive learning mechanism. Computa-tional simulations are conducted on ten test instances of CJWTA problem. The experimental results demonstrate that the proposed SLDDE algorithm not only can generate better results than only one strategy based discrete differential algorithms, but also outper-forms two algorithms which are proposed recently for the weapon-target assignment problems.

  15. Bosses of adaptative learning of teenagers in Spain and México

    Directory of Open Access Journals (Sweden)

    Martha Leticia Gaeta González

    2010-10-01

    Full Text Available The principal aim of this research is to compare the patterns of adaptive learning among secondary school students in Spain and Mexico. Participants were 209 students: 105 from Spain and 104 from Mexico. The Patterns of Adaptive Learning Scales -individual patterns and classroom goal structure- (MIDGLEY ET AL., 2000 were used. Statistical "t" test was utilized to find out differences based on sex, type of school (public and private and academic year (first and last years of secondary in the mexican and spanish students.The results suggest that there are not significant differences in the patterns of adaptive learning of spanish and mexican students based on sex or school type. However, there are differences in these patterns based on the academic year: mexicans keep them constant while the spaniards modify them. These and other results are discussed in detail in the document.

  16. Adaptation of learning resources based on the MBTI theory of psychological types

    Directory of Open Access Journals (Sweden)

    Amel Behaz

    2012-01-01

    Full Text Available Today, the resources available on the web increases significantly. The motivation for the dissemination of knowledge and their acquisition by learners is central to learning. However, learners show differences between the ways of learning that suits them best. The objective of the work presented in this paper is to study how it is possible to integrate models from cognitive theories and ontologies for the adaptation of educational resources. The goal is to provide the system capabilities to conduct reasoning on descriptions obtained in order to automatically adapt the resources to a learner according to his preferences. We rely on the model MBTI (Myers-Briggs Type Indicator for the consideration of learning styles of learners as a criterion for adaptation.

  17. Collaborative Learning with Multi-Touch Technology: Developing Adaptive Expertise

    Science.gov (United States)

    Mercier, Emma M.; Higgins, Steven E.

    2013-01-01

    Developing fluency and flexibility in mathematics is a key goal of upper primary schooling, however, while fluency can be developed with practice, designing activities that support the development of flexibility is more difficult. Drawing on concepts of adaptive expertise, we developed a task for a multi-touch classroom, NumberNet, that aimed to…

  18. Qualitative adaptive reward learning with success failure maps: applied to humanoid robot walking.

    Science.gov (United States)

    Nassour, John; Hugel, Vincent; Ben Ouezdou, Fethi; Cheng, Gordon

    2013-01-01

    In the human brain, rewards are encoded in a flexible and adaptive way after each novel stimulus. Neurons of the orbitofrontal cortex are the key reward structure of the brain. Neurobiological studies show that the anterior cingulate cortex of the brain is primarily responsible for avoiding repeated mistakes. According to vigilance threshold, which denotes the tolerance to risks, we can differentiate between a learning mechanism that takes risks and one that averts risks. The tolerance to risk plays an important role in such a learning mechanism. Results have shown the differences in learning capacity between risk-taking and risk-avert behaviors. These neurological properties provide promising inspirations for robot learning based on rewards. In this paper, we propose a learning mechanism that is able to learn from negative and positive feedback with reward coding adaptively. It is composed of two phases: evaluation and decision making. In the evaluation phase, we use a Kohonen self-organizing map technique to represent success and failure. Decision making is based on an early warning mechanism that enables avoiding repeating past mistakes. The behavior to risk is modulated in order to gain experiences for success and for failure. Success map is learned with adaptive reward that qualifies the learned task in order to optimize the efficiency. Our approach is presented with an implementation on the NAO humanoid robot, controlled by a bioinspired neural controller based on a central pattern generator. The learning system adapts the oscillation frequency and the motor neuron gain in pitch and roll in order to walk on flat and sloped terrain, and to switch between them.

  19. Adaptive WTA with an analog VLSI neuromorphic learning chip.

    Science.gov (United States)

    Häfliger, Philipp

    2007-03-01

    In this paper, we demonstrate how a particular spike-based learning rule (where exact temporal relations between input and output spikes of a spiking model neuron determine the changes of the synaptic weights) can be tuned to express rate-based classical Hebbian learning behavior (where the average input and output spike rates are sufficient to describe the synaptic changes). This shift in behavior is controlled by the input statistic and by a single time constant. The learning rule has been implemented in a neuromorphic very large scale integration (VLSI) chip as part of a neurally inspired spike signal image processing system. The latter is the result of the European Union research project Convolution AER Vision Architecture for Real-Time (CAVIAR). Since it is implemented as a spike-based learning rule (which is most convenient in the overall spike-based system), even if it is tuned to show rate behavior, no explicit long-term average signals are computed on the chip. We show the rule's rate-based Hebbian learning ability in a classification task in both simulation and chip experiment, first with artificial stimuli and then with sensor input from the CAVIAR system.

  20. Adaptive memory: animacy effects persist in paired-associate learning.

    Science.gov (United States)

    VanArsdall, Joshua E; Nairne, James S; Pandeirada, Josefa N S; Cogdill, Mindi

    2015-01-01

    Recent evidence suggests that animate stimuli are remembered better than matched inanimate stimuli. Two experiments tested whether this animacy effect persists in paired-associate learning of foreign words. Experiment 1 randomly paired Swahili words with matched animate and inanimate English words. Participants were told simply to learn the English "translations" for a later test. Replicating earlier findings using free recall, a strong animacy advantage was found in this cued-recall task. Concerned that the effect might be due to enhanced accessibility of the individual responses (e.g., animates represent a more accessible category), Experiment 2 selected animate and inanimate English words from two more constrained categories (four-legged animals and furniture). Once again, an advantage was found for pairs using animate targets. These results argue against organisational accounts of the animacy effect and potentially have implications for foreign language vocabulary learning.

  1. Adaptive Learning of Uncontrolled Restless Bandits with Logarithmic Regret

    CERN Document Server

    Tekin, Cem

    2011-01-01

    In this paper we consider the problem of learning the optimal policy for the uncontrolled restless bandit problem. In this problem only the state of the selected arm can be observed, the state transitions are independent of control and the transition law is unknown. We propose a learning algorithm which gives logarithmic regret uniformly over time with respect to the optimal finite horizon policy with known transition law under some assumptions on the transition probabilities of the arms and the structure of the optimal stationary policy for the infinite horizon average reward problem.

  2. Study of a MEMS Vibratory Gyroscope Using Adaptive Iterative Learning Control

    OpenAIRE

    Xiaochun Lu; Juntao Fei

    2014-01-01

    This paper proposes a framework, namely adaptive iterative learning control (AILC), which is used in the control of a microelectromechanical system (MEMS) gyroscope, to realize high-precision trajectory tracking control. According to the characteristics of the MEMS gyroscope’s model, the proposed AILC algorithm includes an adaptive law of parametric estimation and an iteration control law, which is updated in the iterative domain without any prior knowledge of MEMS gyroscopes. The convergence...

  3. Malaysia and Singapore's terrorist rehabilitation programs : learning and adapting to terrorist threats

    OpenAIRE

    Khor, Laura

    2013-01-01

    The central question of this thesis examines how Malaya/Malaysia and Singapore learned and adapted successful terrorist disengagement programs and policies; through their unique and non-military rehabilitation programs. The methodology is a comparative case study analysis of Malaysia and Singapore. In order to understand how the countries of Malaya/Malaysia and Singapore adapted a colonial-era counter-insurgency program to disengage Communist Terrorists into a program that now rehabilitates r...

  4. Impact of learning adaptability and time management disposition on study engagement among Chinese baccalaureate nursing students.

    Science.gov (United States)

    Liu, Jing-Ying; Liu, Yan-Hui; Yang, Ji-Peng

    2014-01-01

    The aim of this study was to explore the relationships among study engagement, learning adaptability, and time management disposition in a sample of Chinese baccalaureate nursing students. A convenient sample of 467 baccalaureate nursing students was surveyed in two universities in Tianjin, China. Students completed a questionnaire that included their demographic information, Chinese Utrecht Work Engagement Scale-Student Questionnaire, Learning Adaptability Scale, and Adolescence Time Management Disposition Scale. One-way analysis of variance tests were used to assess the relationship between certain characteristics of baccalaureate nursing students. Pearson correlation was performed to test the correlation among study engagement, learning adaptability, and time management disposition. Hierarchical linear regression analyses were performed to explore the mediating role of time management disposition. The results revealed that study engagement (F = 7.20, P time management disposition (r = 0.741, P Time management disposition had a partially mediating effect on the relationship between study engagement and learning adaptability. The findings implicate that educators should not only promote interventions to increase engagement of baccalaureate nursing students but also focus on development, investment in adaptability, and time management.

  5. Designing and Developing a Novel Hybrid Adaptive Learning Path Recommendation System (ALPRS) for Gamification Mathematics Geometry Course

    Science.gov (United States)

    Su, Chung-Ho

    2017-01-01

    Since recommendation systems possess the advantage of adaptive recommendation, they have gradually been applied to e-learning systems to recommend subsequent learning content for learners. However, problems exist in current learning recommender systems available to students in that they are often general learning content and unable to offer…

  6. Racing to learn: statistical inference and learning in a single spiking neuron with adaptive kernels.

    Science.gov (United States)

    Afshar, Saeed; George, Libin; Tapson, Jonathan; van Schaik, André; Hamilton, Tara J

    2014-01-01

    This paper describes the Synapto-dendritic Kernel Adapting Neuron (SKAN), a simple spiking neuron model that performs statistical inference and unsupervised learning of spatiotemporal spike patterns. SKAN is the first proposed neuron model to investigate the effects of dynamic synapto-dendritic kernels and demonstrate their computational power even at the single neuron scale. The rule-set defining the neuron is simple: there are no complex mathematical operations such as normalization, exponentiation or even multiplication. The functionalities of SKAN emerge from the real-time interaction of simple additive and binary processes. Like a biological neuron, SKAN is robust to signal and parameter noise, and can utilize both in its operations. At the network scale neurons are locked in a race with each other with the fastest neuron to spike effectively "hiding" its learnt pattern from its neighbors. The robustness to noise, high speed, and simple building blocks not only make SKAN an interesting neuron model in computational neuroscience, but also make it ideal for implementation in digital and analog neuromorphic systems which is demonstrated through an implementation in a Field Programmable Gate Array (FPGA). Matlab, Python, and Verilog implementations of SKAN are available at: http://www.uws.edu.au/bioelectronics_neuroscience/bens/reproducible_research.

  7. Interbank network and regulation policies: an analysis through agent-based simulations with adaptive learning

    OpenAIRE

    Barroso, Ricardo Vieira; Lima, Joaquim Ignacio Alves Vasconcellos; Lucchetti, Alexandre Henrique; Cajueiro, Daniel Oliveira

    2016-01-01

    We develop an agent-based model to study the impacts of a broad range of regulation policies over the banking system. It builds on an iterated version of the \\citet{DiamondDybvig1983} framework and resorts to the experience-weighted attraction learning scheme of \\citet{CamererHo1999} to model agents' adaptive learning. Thereby, we can capture not only the direct impacts of regulation policies, but also the ones that take part through shifting agents' adaptive strategies. Our results show that...

  8. Lost in Translation: Adapting a Face-to-Face Course Into an Online Learning Experience.

    Science.gov (United States)

    Kenzig, Melissa J

    2015-09-01

    Online education has grown dramatically over the past decade. Instructors who teach face-to-face courses are being called on to adapt their courses to the online environment. Many instructors do not have sufficient training to be able to effectively move courses to an online format. This commentary discusses the growth of online learning, common challenges faced by instructors adapting courses from face-to-face to online, and best practices for translating face-to-face courses into online learning opportunities. © 2015 Society for Public Health Education.

  9. Adaptation and empirical evaluation of the questionnaire on students’ motivation towards science learning

    Directory of Open Access Journals (Sweden)

    Olić Stanislava

    2016-01-01

    Full Text Available The aim of this study is to verify the psychometric properties of the translation of the questionnaire which is designed for self-assessment of students’ motivation toward science learning, SMTSL. Besides being translated and adapted to Serbian language, the questionnaire was adapted to the specific properties of chemistry as a school subject. The administered questionnaire consisted of 29 items in the five-point Likert scale and contained five subscales which assessed a sense of self-efficacy for learning chemistry, active learning strategies, chemistry learning value, performance goal and achievement goal. The suitability of the theoretical model and psychometric characteristics of the questionnaire were assessed on the sample of 741 grammar school students. The results show that the tested model has good fit indicators. The calculated values of the indicators of reliability and representativeness indicate quite satisfactory psychometric properties of the questionnaire and it can be used in further research.

  10. Modeling the behavioral substrates of associate learning and memory - Adaptive neural models

    Science.gov (United States)

    Lee, Chuen-Chien

    1991-01-01

    Three adaptive single-neuron models based on neural analogies of behavior modification episodes are proposed, which attempt to bridge the gap between psychology and neurophysiology. The proposed models capture the predictive nature of Pavlovian conditioning, which is essential to the theory of adaptive/learning systems. The models learn to anticipate the occurrence of a conditioned response before the presence of a reinforcing stimulus when training is complete. Furthermore, each model can find the most nonredundant and earliest predictor of reinforcement. The behavior of the models accounts for several aspects of basic animal learning phenomena in Pavlovian conditioning beyond previous related models. Computer simulations show how well the models fit empirical data from various animal learning paradigms.

  11. Surprise and Opportunity for Learning in Grand Canyon: the Glen Canyon Dam Adaptive Management Program

    Directory of Open Access Journals (Sweden)

    Theodore S. Melis

    2015-09-01

    Full Text Available With a focus on resources of the Colorado River ecosystem below Glen Canyon Dam, the Glen Canyon Dam Adaptive Management Program has included a variety of experimental policy tests, ranging from manipulation of water releases from the dam to removal of non-native fish within Grand Canyon National Park. None of these field-scale experiments has yet produced unambiguous results in terms of management prescriptions. But there has been adaptive learning, mostly from unanticipated or surprising resource responses relative to predictions from ecosystem modeling. Surprise learning opportunities may often be viewed with dismay by some stakeholders who might not be clear about the purpose of science and modeling in adaptive management. However, the experimental results from the Glen Canyon Dam program actually represent scientific successes in terms of revealing new opportunities for developing better river management policies. A new long-term experimental management planning process for Glen Canyon Dam operations, started in 2011 by the U.S. Department of the Interior, provides an opportunity to refocus management objectives, identify and evaluate key uncertainties about the influence of dam releases, and refine monitoring for learning over the next several decades. Adaptive learning since 1995 is critical input to this long-term planning effort. Embracing uncertainty and surprise outcomes revealed by monitoring and ecosystem modeling will likely continue the advancement of resource objectives below the dam, and may also promote efficient learning in other complex programs.

  12. Dynamic learning from adaptive neural network control of a class of nonaffine nonlinear systems.

    Science.gov (United States)

    Dai, Shi-Lu; Wang, Cong; Wang, Min

    2014-01-01

    This paper studies the problem of learning from adaptive neural network (NN) control of a class of nonaffine nonlinear systems in uncertain dynamic environments. In the control design process, a stable adaptive NN tracking control design technique is proposed for the nonaffine nonlinear systems with a mild assumption by combining a filtered tracking error with the implicit function theorem, input-to-state stability, and the small-gain theorem. The proposed stable control design technique not only overcomes the difficulty in controlling nonaffine nonlinear systems but also relaxes constraint conditions of the considered systems. In the learning process, the partial persistent excitation (PE) condition of radial basis function NNs is satisfied during tracking control to a recurrent reference trajectory. Under the PE condition and an appropriate state transformation, the proposed adaptive NN control is shown to be capable of acquiring knowledge on the implicit desired control input dynamics in the stable control process and of storing the learned knowledge in memory. Subsequently, an NN learning control design technique that effectively exploits the learned knowledge without re-adapting to the controller parameters is proposed to achieve closed-loop stability and improved control performance. Simulation studies are performed to demonstrate the effectiveness of the proposed design techniques.

  13. Cooperative Learning and Adaptive Instruction in a Mathematics Curriculum.

    Science.gov (United States)

    Terwel, Jan; And Others

    1994-01-01

    Maintains that current research suggests that heterogeneous grouping is preferable. Reports on a study of a new mathematics curriculum using 600 students in 6 Dutch schools. Finds that students in heterogeneous classes taught with cooperative-learning techniques achieved more than students in traditional ability-grouped classrooms. (CFR)

  14. OAEditor--A Framework for Editing Adaptive Learning Objects

    Science.gov (United States)

    Pereira, Joao Carlos Rodrigues; Cabral, Lucidio dos Anjos Formiga; Oiveira, Ronei dos Santos; Bezerra, Lucimar Leandro; de Melo, Nisston Moraes Tavares

    2012-01-01

    Distance Learning supported by the WEB is a reality which is growing fast and, like any technological or empirical innovation, it reveals positive and negative aspects. An important aspect is in relation to the monitoring of the activities done by the students since an accurate online assessment of the knowledge acquired is an open and, therefore,…

  15. Primary Motor Cortex Involvement in Initial Learning during Visuomotor Adaptation

    Science.gov (United States)

    Riek, Stephan; Hinder, Mark R.; Carson, Richard G.

    2012-01-01

    Human motor behaviour is continually modified on the basis of errors between desired and actual movement outcomes. It is emerging that the role played by the primary motor cortex (M1) in this process is contingent upon a variety of factors, including the nature of the task being performed, and the stage of learning. Here we used repetitive TMS to…

  16. 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...

  17. Adaptive Iterative Learning Control for High Precision Motion Systems

    NARCIS (Netherlands)

    Rotariu, I.; Steinbuch, M.; Ellenbroek, R.

    2008-01-01

    Iterative learning control (ILC) is a very effective technique to reduce systematic errors that occur in systems that repetitively perform the same motion or operation. However, several characteristics have prevented standard ILC from being widely used for high precision motion systems. Most importa

  18. Multimodal and Adaptive Learning Management: An Iterative Design

    Science.gov (United States)

    Squires, David R.; Orey, Michael A.

    2015-01-01

    The purpose of this study is to measure the outcome of a comprehensive learning management system implemented at a Spinal Cord Injury (SCI) hospital in the Southeast United States. Specifically this SCI hospital has been experiencing an evident volume of patients returning seeking more information about the nature of their injuries. Recognizing…

  19. Daytime sleep has no effect on the time course of motor sequence and visuomotor adaptation learning.

    Science.gov (United States)

    Backhaus, Winifried; Braaß, Hanna; Renné, Thomas; Krüger, Christian; Gerloff, Christian; Hummel, Friedhelm C

    2016-05-01

    Sleep has previously been claimed to be essential for the continued learning processes of declarative information as well as procedural learning. This study was conducted to examine the importance of sleep, especially the effects of midday naps, on motor sequence and visuomotor adaptation learning. Thirty-five (27 females) healthy, young adults aged between 18 and 30years of age participated in the current study. Addressing potential differences in explicit sequence and motor adaptation learning participants were asked to learn both, a nine-element explicit sequence and a motor adaptation task, in a crossover fashion on two consecutive days. Both tasks were performed with their non-dominant left hand. Prior to learning, each participant was randomized to one of three interventions; (1) power nap: 10-20min sleep, (2) long nap: 50-80min sleep or (3) a 45-min wake-condition. Performance of the motor learning task took place prior to and after a midday rest period, as well as after a night of sleep. Both sleep conditions were dominated by Stage N2 sleep with embedded sleep spindles, which have been described to be associated with enhancement of motor performance. Significant performance changes were observed in both tasks across all interventions (sleep and wake) confirming that learning took place. In the present setup, the magnitude of motor learning was not sleep-dependent in young adults - no differences between the intervention groups (short nap, long nap, no nap) could be found. The effect of the following night of sleep was not influenced by the previous midday rest or sleep period. This finding may be related to the selectiveness of the human brain enhancing especially memory being thought of as important in the future. Previous findings on motor learning enhancing effects of sleep, especially of daytime sleep, are challenged.

  20. Adaptive de-noising method based on wavelet and adaptive learning algorithm in on-line PD monitoring

    Institute of Scientific and Technical Information of China (English)

    王立欣; 诸定秋; 蔡惟铮

    2002-01-01

    It is an important step in the online monitoring of partial discharge (PD) to extract PD pulses from various background noises. An adaptive de-noising method is introduced for adaptive noise reduction during detection of PD pulses. This method is based on Wavelet Transform (WT) , and in the wavelet domain the noises decomposed at the levels are reduced by independent thresholds. Instead of the standard hard thresholding function, a new type of hard thresholding function with continuous derivative is employed by this method. For the selection of thresholds, an unsupervised learning algorithm based on gradient in a mean square error (MSE) is present to search for the optimal threshold for noise reduction, and the optimal threshold is selected when the minimum MSE is obtained. With the simulating signals and on-site experimental data processed by this method,it is shown that the background noises such as narrowband noises can be reduced efficiently. Furthermore, it is proved that in comparison with the conventional wavelet de-noising method the adaptive de-noising method has a better performance in keeping the pulses and is more adaptive when suppressing the background noises of PD signals.

  1. Sharing and reusing multimedia multilingual educational resources in medicine.

    Science.gov (United States)

    Zdrahal, Zdenek; Knoth, Petr; Mulholland, Paul; Collins, Trevor

    2013-01-01

    The paper describes the Eurogene portal for sharing and reusing multilingual multimedia educational resources in human genetics. The content is annotated using concepts of two ontologies and a topic hierarchy. The ontology annotation is used to guide search and for calculating semantically similar content. Educational resources can be aggregated into learning packages. The system is in routine use since 2009.

  2. A framework for adaptive e-learning for continuum mechanics and structural analysis

    OpenAIRE

    Mosquera Feijoo, Juan Carlos; Plaza Beltrán, Luis Francisco; González Rodrigo, Beatriz

    2015-01-01

    This paper presents a project for providing the students of Structural Engineering with the flexibility to learn outside classroom schedules. The goal is a framework for adaptive E-learning based on a repository of open educational courseware with a set of basic Structural Engineering concepts and fundamentals. These are paramount for students to expand their technical knowledge and skills in structural analysis and design of tall buildings, arch-type structures as well as bridges. Thus, conc...

  3. Thai nursing students' adaption to problem-based learning: a qualitative study.

    Science.gov (United States)

    Klunklin, Areewan; Subpaiboongid, Pornpun; Keitlertnapha, Pongsri; Viseskul, Nongkran; Turale, Sue

    2011-11-01

    Student-centred forms of learning have gained favour internationally over the last few decades including problem based learning, an approach now incorporated in medicine, nursing and other disciplines' education in many countries. However, it is still new in Thailand and being piloted to try to offset traditional forms of didactic, teacher-centred forms of teaching. In this qualitative study, 25 undergraduate nursing students in northern Thailand were interviewed about their experiences with problem-based learning in a health promotion subject. Content analysis was used to interrogate interview data, which revealed four categories: adapting, seeking assistance, self-development, and thinking process development. Initially participants had mixed emotions of confusion, negativity or boredom in the adaption process, but expressed satisfaction with creativity in learning, group work, and leadership development. They described increased abilities to problem solve and think critically, but struggled to develop questioning behaviours in learning. Socio-culturally in Thai education, students have great respect for teachers, but rarely question or challenge them or their learning. We conclude that problem-based learning has great potential in Thai nursing education, but educators and systems need to systematically prepare appropriate learning environments, their staff and students, to incorporate this within curricula. Copyright © 2011 Elsevier Ltd. All rights reserved.

  4. The Study of Reinforcement Learning for Traffic Self-Adaptive Control under Multiagent Markov Game Environment

    Directory of Open Access Journals (Sweden)

    Lun-Hui Xu

    2013-01-01

    Full Text Available Urban traffic self-adaptive control problem is dynamic and uncertain, so the states of traffic environment are hard to be observed. Efficient agent which controls a single intersection can be discovered automatically via multiagent reinforcement learning. However, in the majority of the previous works on this approach, each agent needed perfect observed information when interacting with the environment and learned individually with less efficient coordination. This study casts traffic self-adaptive control as a multiagent Markov game problem. The design employs traffic signal control agent (TSCA for each signalized intersection that coordinates with neighboring TSCAs. A mathematical model for TSCAs’ interaction is built based on nonzero-sum markov game which has been applied to let TSCAs learn how to cooperate. A multiagent Markov game reinforcement learning approach is constructed on the basis of single-agent Q-learning. This method lets each TSCA learn to update its Q-values under the joint actions and imperfect information. The convergence of the proposed algorithm is analyzed theoretically. The simulation results show that the proposed method is convergent and effective in realistic traffic self-adaptive control setting.

  5. An adaptive online learning approach for Support Vector Regression: Online-SVR-FID

    Science.gov (United States)

    Liu, Jie; Zio, Enrico

    2016-08-01

    Support Vector Regression (SVR) is a popular supervised data-driven approach for building empirical models from available data. Like all data-driven methods, under non-stationary environmental and operational conditions it needs to be provided with adaptive learning capabilities, which might become computationally burdensome with large datasets cumulating dynamically. In this paper, a cost-efficient online adaptive learning approach is proposed for SVR by combining Feature Vector Selection (FVS) and Incremental and Decremental Learning. The proposed approach adaptively modifies the model only when different pattern drifts are detected according to proposed criteria. Two tolerance parameters are introduced in the approach to control the computational complexity, reduce the influence of the intrinsic noise in the data and avoid the overfitting problem of SVR. Comparisons of the prediction results is made with other online learning approaches e.g. NORMA, SOGA, KRLS, Incremental Learning, on several artificial datasets and a real case study concerning time series prediction based on data recorded on a component of a nuclear power generation system. The performance indicators MSE and MARE computed on the test dataset demonstrate the efficiency of the proposed online learning method.

  6. Managing Cognitive Load in Adaptive ICT-Based Learning

    Directory of Open Access Journals (Sweden)

    Slava Kalyuga

    2009-10-01

    Full Text Available The history of technological innovations in education has many examples of failed high expectations. To avoid becoming another one, current multimedia ICT tools need to be designed in accordance with how the human mind works. There are well established characteristics of its architecture that should be taken into account when evaluating, selecting, and using educational technology. This paper starts with a review of the most important features of human cognitive architecture and their implications for ICT-based learning. Expertise reversal effect relates to the interactions between levels of learner prior knowledge and effectiveness of different instructional techniques and procedures. Designs and techniques that are effective with low-knowledge learners can lose their effectiveness and even have negative consequences for more proficient learners. The paper describes recent empirical findings associated with the expertise reversal effect in multimedia and hypermedia learning environments, their interpretation within a cognitive load framework, and implications for the design of learner-tailored multimedia.

  7. Multiple Kernel Learning for adaptive graph regularized nonnegative matrix factorization

    KAUST Repository

    Wang, Jim Jing-Yan

    2012-01-01

    Nonnegative Matrix Factorization (NMF) has been continuously evolving in several areas like pattern recognition and information retrieval methods. It factorizes a matrix into a product of 2 low-rank non-negative matrices that will define parts-based, and linear representation of non-negative data. Recently, Graph regularized NMF (GrNMF) is proposed to find a compact representation, which uncovers the hidden semantics and simultaneously respects the intrinsic geometric structure. In GNMF, an affinity graph is constructed from the original data space to encode the geometrical information. In this paper, we propose a novel idea which engages a Multiple Kernel Learning approach into refining the graph structure that reflects the factorization of the matrix and the new data space. The GrNMF is improved by utilizing the graph refined by the kernel learning, and then a novel kernel learning method is introduced under the GrNMF framework. Our approach shows encouraging results of the proposed algorithm in comparison to the state-of-the-art clustering algorithms like NMF, GrNMF, SVD etc.

  8. Specification, authoring and prototyping of personalised workplace learning solutions

    DEFF Research Database (Denmark)

    Dolog, Peter; Kravcik, Milos; Cristea, Alexandra

    2007-01-01

    The main goal of this document is to survey the existing approaches for the authoring and engineering of personalisation and adaptation in e-learning systems. This document enables the comparison of various methods and techniques, and facilitates their integration or reuse. It offers a cohesive r...

  9. Specification, authoring and prototyping of personalised workplace learning solutions

    DEFF Research Database (Denmark)

    Dolog, Peter; Kravcik, Milos; Cristea, Alexandra;

    2007-01-01

    The main goal of this document is to survey the existing approaches for the authoring and engineering of personalisation and adaptation in e-learning systems. This document enables the comparison of various methods and techniques, and facilitates their integration or reuse. It offers a cohesive...

  10. AN ADAPTIVE ACO-DRIVEN SCHEME FOR LEARNING AIM ORIENTED PERSONALIZED E-LEARNING

    Directory of Open Access Journals (Sweden)

    Sushma Hans

    2014-10-01

    Full Text Available The e-learning paradigm is now a well-established vehicle of modern education. It caters to a wide spectrum of students with diverse backgrounds who enroll with their own learning aims. A core challenge under this scenario is to generate personalized learning paths so that each student can achieve her learning aim most effectively. Prior works used static attributes such as prior knowledge level, learning ability, browsing preferences, learning style etc. to generate personalized learning paths. In this paper, we take an entirely new route by taking into account the continuous improvement of a learner in the light of her own learning aim, to redefine her learning path at each level of the course. We introduce the concept of personalized examination system that systematically evaluates the dynamic learning ability of every student according to her pre-set goals. The proposed intelligent e-learning system uses Ant Colony Optimization to iteratively optimize the forward learning paths. Experimental results reveal that the system is able to tap a student’s improved learning ability to choose more difficult paths that contribute highly towards her own aims. We demonstrate that the overall learning success of weaker students doubles as compared to statically generated paths while there is considerable improvement of 50% in the learning success for average students as well. This clearly indicates that our approach gives realistic benefits to initially weak students who gradually evolve as the course progresses.

  11. Dry reusing and wet reclaiming of used sodium silicate sand

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Based on the characteristics of used sodium silicate sand and the different use requirements for recycled sand, "dry reusing and wet reclaiming of used sodium silicate sand" is considered as the most suitable technique for the used sand. When the recycled sand is used as support sand, the used sand is only reused by dry process including breaking, screening, dust-removal, etc., and it is not necessary that the used sand is reclaimed with strongly rubbing and scraping method, but when the recycled sand is used as facing sand (or single sand), the used sand must be reclaimed by wet method for higher removal rate of the residual binders. The characteristics and the properties of the dry reused sand are compared with the wet reclaimed sand after combining the different use requirements of support sand and facing sand (or single sand), and above the most adaptive scheme has also been validated.

  12. Direct Adaptive Soft Computing Neural Control of a Continuous Bioprocess via Second Order Learning

    Science.gov (United States)

    Baruch, Ieroham; Mariaca-Gaspar, Carlos-Roman; Barrera-Cortes, Josefina

    This paper proposes a new Kalman Filter Recurrent Neural Network (KFRNN) topology and a recursive Levenberg-Marquardt (L-M) second order learning algorithm capable to estimate parameters and states of highly nonlinear bioprocess in a noisy environment. The proposed KFRNN identifier, learned by the Backpropagation and L-M learning algorithm, was incorporated in a direct adaptive neural control scheme. The proposed control scheme was applied for real-time soft computing identification and control of a continuous stirred tank bioreactor model, where fast convergence, noise filtering and low mean squared error of reference tracking were achieved.

  13. Theoretical information reuse and integration

    CERN Document Server

    Rubin, Stuart

    2016-01-01

    Information Reuse and Integration addresses the efficient extension and creation of knowledge through the exploitation of Kolmogorov complexity in the extraction and application of domain symmetry. Knowledge, which seems to be novel, can more often than not be recast as the image of a sequence of transformations, which yield symmetric knowledge. When the size of those transformations and/or the length of that sequence of transforms exceeds the size of the image, then that image is said to be novel or random. It may also be that the new knowledge is random in that no such sequence of transforms, which produces it exists, or is at least known. The nine chapters comprising this volume incorporate symmetry, reuse, and integration as overt operational procedures or as operations built into the formal representations of data and operators employed. Either way, the aforementioned theoretical underpinnings of information reuse and integration are supported.

  14. Quality Assessment of Adaptive Bitrate Videos using Image Metrics and Machine Learning

    DEFF Research Database (Denmark)

    Søgaard, Jacob; Forchhammer, Søren; Brunnström, Kjell

    2015-01-01

    Adaptive bitrate (ABR) streaming is widely used for distribution of videos over the internet. In this work, we investigate how well we can predict the quality of such videos using well-known image metrics, information about the bitrate levels, and a relatively simple machine learning method...

  15. Comparison of Policy Functions from the Optimal Learning and Adaptive Control Frameworks

    NARCIS (Netherlands)

    Kendrick, D.A.; Amman, H.M.|info:eu-repo/dai/nl/070970777

    2008-01-01

    In this paper we turn our attention to comparing the policy function obtained by Beck and Wieland (2002) to the one obtained with adaptive control methods. It is an integral part of the optimal learning method used by Beck and Wieland to obtain a policy function that provides the optimal control as

  16. Comparison of policy functions from optimal learning and adaptive control frameworks

    NARCIS (Netherlands)

    Amman, H.M.; Kendrick, D.A.

    2014-01-01

    In this paper we turn our attention to comparing the policy function obtained by Beck and Wieland (J Econ Dyn Control 26:1359-1377, 2002) to the one obtained with adaptive control methods. It is an integral part of the optimal learning method used by Beck and Wieland to obtain a policy function that

  17. Investigating Purposeful Science Curriculum Adaptation as a Strategy to Improve Teaching and Learning

    Science.gov (United States)

    Debarger, Angela Haydel; Penuel, William R.; Moorthy, Savitha; Beauvineau, Yves; Kennedy, Cathleen A.; Boscardin, Christy Kim

    2017-01-01

    In this paper, we investigate the potential and conditions for using curriculum adaptation to support reform of science teaching and learning. With each wave of reform in science education, curriculum has played a central role and the contemporary wave focused on implementation of the principles and vision of the "Framework for K-12 Science…

  18. Use of Adaptive Study Material in Education in E-Learning Environment

    Science.gov (United States)

    Kostolányová, Katerina; Šarmanová, Jana

    2014-01-01

    Personalised education is a topical matter today and the impact of ICT on education has been covered extensively. The adaptation of education to various types of student is an issue of a vast number of papers presented at diverse conferences. The topic incorporates the fields of information technologies and eLearning, but in no small part also the…

  19. Adaptive and Intelligent Systems for Collaborative Learning Support: A Review of the Field

    Science.gov (United States)

    Magnisalis, I.; Demetriadis, S.; Karakostas, A.

    2011-01-01

    This study critically reviews the recently published scientific literature on the design and impact of adaptive and intelligent systems for collaborative learning support (AICLS) systems. The focus is threefold: 1) analyze critical design issues of AICLS systems and organize them under a unifying classification scheme, 2) present research evidence…

  20. Japanese English Education and Learning: A History of Adapting Foreign Cultures

    Science.gov (United States)

    Shimizu, Minoru

    2010-01-01

    This essay is a history that relates the Japanese tradition of accepting and adapting aspects of foreign culture, especially as it applies to the learning of foreign languages. In particular, the essay describes the history of English education in Japan by investigating its developments after the Meiji era. The author addresses the issues from the…

  1. Promoting Contextual Vocabulary Learning through an Adaptive Computer-Assisted EFL Reading System

    Science.gov (United States)

    Wang, Y.-H.

    2016-01-01

    The study developed an adaptive computer-assisted reading system and investigated its effect on promoting English as a foreign language learner-readers' contextual vocabulary learning performance. Seventy Taiwanese college students were assigned to two reading groups. Participants in the customised reading group read online English texts, each of…

  2. Effects of a Culturally Adapted Social-Emotional Learning Intervention Program on Students' Mental Health

    Science.gov (United States)

    Cramer, Kristine M.; Castro-Olivo, Sara

    2016-01-01

    Student self-reports of resiliency and social-emotional internalizing problems were examined to determine intervention effects of a culturally adapted social and emotional learning (SEL) program. Data were analyzed from 20 culturally and linguistically diverse high school students who participated in a school-based 12-lesson SEL intervention and…

  3. Towards an open framework for adaptive, agent-supported e-learning

    NARCIS (Netherlands)

    Van Rosmalen, Peter; Brouns, Francis; Tattersall, Colin; Vogten, Hubert; Van Bruggen, Jan; Sloep, Peter; Koper, Rob

    2003-01-01

    Refer to: Van Rosmalen, P., Brouns, F., Tattersall, C.,Vogten, H. Van Bruggen, J, Sloep, P., & Koper, E.J.R. (in press). Towards an Open Framework for Adaptive, Agent-supported e-learning. International Journal of Continuing Engineering Education.

  4. Investigating Purposeful Science Curriculum Adaptation as a Strategy to Improve Teaching and Learning

    Science.gov (United States)

    Debarger, Angela Haydel; Penuel, William R.; Moorthy, Savitha; Beauvineau, Yves; Kennedy, Cathleen A.; Boscardin, Christy Kim

    2017-01-01

    In this paper, we investigate the potential and conditions for using curriculum adaptation to support reform of science teaching and learning. With each wave of reform in science education, curriculum has played a central role and the contemporary wave focused on implementation of the principles and vision of the "Framework for K-12 Science…

  5. Bridging Scientific Reasoning and Conceptual Change through Adaptive Web-Based Learning

    Science.gov (United States)

    She, Hsiao-Ching; Liao, Ya-Wen

    2010-01-01

    This study reports an adaptive digital learning project, Scientific Concept Construction and Reconstruction (SCCR), and examines its effects on 108 8th grade students' scientific reasoning and conceptual change through mixed methods. A one-group pre-, post-, and retention quasi-experimental design was used in the study. All students received tests…

  6. Adapting and Evaluating a Tree of Life Group for Women with Learning Disabilities

    Science.gov (United States)

    Randle-Phillips, Cathy; Farquhar, Sarah; Thomas, Sally

    2016-01-01

    Background: This study describes how a specific narrative therapy approach called 'the tree of life' was adapted to run a group for women with learning disabilities. The group consisted of four participants and ran for five consecutive weeks. Materials and Methods: Participants each constructed a tree to represent their lives and presented their…

  7. Co-operative learning and adaptive instruction in a mathematics curriculum

    NARCIS (Netherlands)

    Terwel, J.; Herfs, P.G.P.; Mertens, E.H.M.; Perrenet, J.Chr.

    1994-01-01

    The AGO 12 to 16 Project (the acronym AGO stands for the Dutch equivalent of 'Adaptive Instruction and Co-operative Learning') seeks to develop and evaluate a mathematics curriculum which is suitable for mixed-ability groups in secondary education. The research questions we will address here are, fi

  8. Interacting adaptive processes with different timescales underlie short-term motor learning.

    Directory of Open Access Journals (Sweden)

    Maurice A Smith

    2006-06-01

    Full Text Available Multiple processes may contribute to motor skill acquisition, but it is thought that many of these processes require sleep or the passage of long periods of time ranging from several hours to many days or weeks. Here we demonstrate that within a timescale of minutes, two distinct fast-acting processes drive motor adaptation. One process responds weakly to error but retains information well, whereas the other responds strongly but has poor retention. This two-state learning system makes the surprising prediction of spontaneous recovery (or adaptation rebound if error feedback is clamped at zero following an adaptation-extinction training episode. We used a novel paradigm to experimentally confirm this prediction in human motor learning of reaching, and we show that the interaction between the learning processes in this simple two-state system provides a unifying explanation for several different, apparently unrelated, phenomena in motor adaptation including savings, anterograde interference, spontaneous recovery, and rapid unlearning. Our results suggest that motor adaptation depends on at least two distinct neural systems that have different sensitivity to error and retain information at different rates.

  9. A New Approach to Teaching Biomechanics Through Active, Adaptive, and Experiential Learning.

    Science.gov (United States)

    Singh, Anita

    2017-07-01

    Demand of biomedical engineers continues to rise to meet the needs of healthcare industry. Current training of bioengineers follows the traditional and dominant model of theory-focused curricula. However, the unmet needs of the healthcare industry warrant newer skill sets in these engineers. Translational training strategies such as solving real world problems through active, adaptive, and experiential learning hold promise. In this paper, we report our findings of adding a real-world 4-week problem-based learning unit into a biomechanics capstone course for engineering students. Surveys assessed student perceptions of the activity and learning experience. While students, across three cohorts, felt challenged to solve a real-world problem identified during the simulation lab visit, they felt more confident in utilizing knowledge learned in the biomechanics course and self-directed research. Instructor evaluations indicated that the active and experiential learning approach fostered their technical knowledge and life-long learning skills while exposing them to the components of adaptive learning and innovation.

  10. A Framework for Creating Semantically Adaptive Collaborative E-learning Environments

    Directory of Open Access Journals (Sweden)

    Marija Cubric

    2009-09-01

    Full Text Available In this paper we present a framework that can be used to generate web-based, semantically adaptive, e-learning and computer-assisted assessment (CAA tools for any given knowledge domain, based upon dynamic ontological modeling. We accomplish this by generating “learning ontologies” for a given knowledge domain. The generated learning ontologies are built upon our previous work on a domain “Glossary” ontology and augmented with additional conceptual relations from the WordNet 3.0 lexical database, using Text2Onto, an open source ontology extraction tool. The main novelty of this work is in “on the fly” generation of computer assisted assessments based on the underlying ontology and pre-defined question templates that are founded on the Bloom’s taxonomy of educational objectives. The main deployment scenario for the framework is a web-service providing collaborative e- learning and knowledge management capabilities to various learning communities. The framework can be extended to provide collection and exploitation of the users’ learning behaviour metrics, in order to further adapt the generated e-learning environment to the learners’ needs.

  11. Multiple-pass water reuse

    Energy Technology Data Exchange (ETDEWEB)

    Bhattacharyya, D.; Farthing, S.S.; Cheng, C.S.

    1982-02-01

    Low-pressure membranes have definite advantages for the treatment of metal-processing wastewaters and acid mine water. The membrane processes are evaluated in terms of obtaining maximum water recovery (greater than 90%), proper ultrafiltrate quality, multiple-pass water reuse, and concentrate recycle. Various multi-salt solutions containing heavy metals (including cyanide complexes), and acid mine waters have been extensively investigated with a bench-scale unit, and a computer simulation model has been used to scale-up from the laboratory data. Water reuse models are presented for multiple passes. 9 references, 12 figures, 3 tables. (JMT)

  12. 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.

  13. NETWORKED LEARNING AS A PROCESS OF IDENTIFICATION IN THE INTERSECTION OF COLLABORATIVE KNOWLEDGE BUILDING - FOSTERING CREATIVITY, AWARENESS AND RE-USE OF OER

    DEFF Research Database (Denmark)

    Østergaard, Rina; Sorensen, Elsebeth Korsgaard

    2011-01-01

    Within professional education a recent shift has taken place. Professional education has moved from specialized education and update of professional knowledge, over competence-based education, to, recently, education with goals such as creativity, innovation, entrepreneur- and entrepreneurship...... for negotiation of meaning in learning, and 3) a view of OER as potential resources and triggers of pedagogic/strategic awareness in educational design. The three phenomena are viewed and discussed in relation to societal and political reforms. The claim of the authors is that there is a strong need for a new...

  14. 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.

  15. Cooperative Learning Groups and the Evolution of Human Adaptability : (Another Reason) Why Hermits Are Rare in Tonga and Elsewhere.

    Science.gov (United States)

    Bell, Adrian Viliami; Hernandez, Daniel

    2017-03-01

    Understanding the prevalence of adaptive culture in part requires understanding the dynamics of learning. Here we explore the adaptive value of social learning in groups and how formal social groups function as effective mediums of information exchange. We discuss the education literature on Cooperative Learning Groups (CLGs), which outlines the potential of group learning for enhancing learning outcomes. Four qualities appear essential for CLGs to enhance learning: (1) extended conversations, (2) regular interactions, (3) gathering of experts, and (4) incentives for sharing knowledge. We analyze these four qualities within the context of a small-scale agricultural society using data we collected in 2010 and 2012. Through an analysis of surveys, interviews, and observations in the Tongan islands, we describe the role CLGs likely plays in facilitating individuals' learning of adaptive information. Our analysis of group affiliation, membership, and topics of conversation suggest that the first three CLG qualities reflect conditions for adaptive learning in groups. We utilize ethnographic anecdotes to suggest the fourth quality is also conducive to adaptive group learning. Using an evolutionary model, we further explore the scope for CLGs outside the Tongan socioecological context. Model analysis shows that environmental volatility and migration rates among human groups mediate the scope for CLGs. We call for wider attention to how group structure facilitates learning in informal settings, which may be key to assessing the contribution of groups to the evolution of complex, adaptive culture.

  16. Reinforcement learning for adaptive threshold control of restorative brain-computer interfaces: a Bayesian simulation.

    Science.gov (United States)

    Bauer, Robert; Gharabaghi, Alireza

    2015-01-01

    Restorative brain-computer interfaces (BCI) are increasingly used to provide feedback of neuronal states in a bid to normalize pathological brain activity and achieve behavioral gains. However, patients and healthy subjects alike often show a large variability, or even inability, of brain self-regulation for BCI control, known as BCI illiteracy. Although current co-adaptive algorithms are powerful for assistive BCIs, their inherent class switching clashes with the operant conditioning goal of restorative BCIs. Moreover, due to the treatment rationale, the classifier of restorative BCIs usually has a constrained feature space, thus limiting the possibility of classifier adaptation. In this context, we applied a Bayesian model of neurofeedback and reinforcement learning for different threshold selection strategies to study the impact of threshold adaptation of a linear classifier on optimizing restorative BCIs. For each feedback iteration, we first determined the thresholds that result in minimal action entropy and maximal instructional efficiency. We then used the resulting vector for the simulation of continuous threshold adaptation. We could thus show that threshold adaptation can improve reinforcement learning, particularly in cases of BCI illiteracy. Finally, on the basis of information-theory, we provided an explanation for the achieved benefits of adaptive threshold setting.

  17. Reinforcement learning for adaptive threshold control of restorative brain-computer interfaces: a Bayesian simulation

    Directory of Open Access Journals (Sweden)

    Robert eBauer

    2015-02-01

    Full Text Available Restorative brain-computer interfaces (BCI are increasingly used to provide feedback of neuronal states in a bid to normalize pathological brain activity and achieve behavioral gains. However, patients and healthy subjects alike often show a large variability, or even inability, of brain self-regulation for BCI control, known as BCI illiteracy. Although current co-adaptive algorithms are powerful for assistive BCIs, their inherent class switching clashes with the operant conditioning goal of restorative BCIs. Moreover, due to the treatment rationale, the classifier of restorative BCIs usually has a constrained feature space, thus limiting the possibility of classifier adaptation.In this context, we applied a Bayesian model of neurofeedback and reinforcement learning for different threshold selection strategies to study the impact of threshold adaptation of a linear classifier on optimizing restorative BCIs. For each feedback iteration, we first determined the thresholds that result in minimal action entropy and maximal instructional efficiency. We then used the resulting vector for the simulation of continuous threshold adaptation. We could thus show that threshold adaptation can improve reinforcement learning, particularly in cases of BCI illiteracy. Finally, on the basis of information-theory, we provided an explanation for the achieved benefits of adaptive threshold setting.

  18. Anatomy of Student Models in Adaptive Learning Systems: A Systematic Literature Review of Individual Differences from 2001 to 2013

    Science.gov (United States)

    Nakic, Jelena; Granic, Andrina; Glavinic, Vlado

    2015-01-01

    This study brings an evidence-based review of user individual characteristics employed as sources of adaptation in recent adaptive learning systems. Twenty-two user individual characteristics were explored in a systematically designed search procedure, while 17 of them were identified as sources of adaptation in final selection. The content…

  19. Does Visuomotor Adaptation Proceed in Stages? An Examination of the Learning Model by Chein and Schneider (2012).

    Science.gov (United States)

    Simon, Anja; Bock, Otmar

    2015-01-01

    A new 3-stage model based on neuroimaging evidence is proposed by Chein and Schneider (2012). Each stage is associated with different brain regions, and draws on cognitive abilities: the first stage on creativity, the second on selective attention, and the third on automatic processing. The purpose of the present study was to scrutinize the validity of this model for 1 popular learning paradigm, visuomotor adaptation. Participants completed tests for creativity, selective attention and automated processing before attending in a pointing task with adaptation to a 60° rotation of visual feedback. To examine the relationship between cognitive abilities and motor learning at different times of practice, associations between cognitive and adaptation scores were calculated repeatedly throughout adaptation. The authors found no benefit of high creativity for adaptive performance. High levels of selective attention were positively associated with early adaptation, but hardly with late adaptation and de-adaptation. High levels of automated execution were beneficial for late adaptation, but hardly for early and de-adaptation. From this we conclude that Chein and Schneider's first learning stage is difficult to confirm by research on visuomotor adaptation, and that the other 2 learning stages rather relate to workaround strategies than to actual adaptive recalibration.

  20. Adaptation for a Changing Environment: Developing learning and teaching with information and communication technologies

    Directory of Open Access Journals (Sweden)

    Adrian Kirkwood

    2006-09-01

    Full Text Available This article examines the relationship between the use of information and communication technologies (ICT and learning and teaching, particularly in distance education contexts. We argue that environmental changes (societal, educational, and technological make it necessary to adapt systems and practices that are no longer appropriate. The need to adapt, however, can be perceived as being technology-led and primarily concerned with requiring academic staff to develop their skills in using ICT. We provide a critique of continuing professional development (CPD for using ICT in teaching and learning that does not entail examining the impact of environmental changes upon the assumptions, goals, and strategies which underlie and shape an organisation’s educational practices. In particular, we oppose CPD that concentrates on the individual teacher and their use of ICT. Instead, we contend that professional development should focus upon the scholarship of teaching and learning, and must also reflect the wider organisational context within which ICT is managed and used.

  1. Flexible explicit but rigid implicit learning in a visuomotor adaptation task.

    Science.gov (United States)

    Bond, Krista M; Taylor, Jordan A

    2015-06-01

    There is mounting evidence for the idea that performance in a visuomotor rotation task can be supported by both implicit and explicit forms of learning. The implicit component of learning has been well characterized in previous experiments and is thought to arise from the adaptation of an internal model driven by sensorimotor prediction errors. However, the role of explicit learning is less clear, and previous investigations aimed at characterizing the explicit component have relied on indirect measures such as dual-task manipulations, posttests, and descriptive computational models. To address this problem, we developed a new method for directly assaying explicit learning by having participants verbally report their intended aiming direction on each trial. While our previous research employing this method has demonstrated the possibility of measuring explicit learning over the course of training, it was only tested over a limited scope of manipulations common to visuomotor rotation tasks. In the present study, we sought to better characterize explicit and implicit learning over a wider range of task conditions. We tested how explicit and implicit learning change as a function of the specific visual landmarks used to probe explicit learning, the number of training targets, and the size of the rotation. We found that explicit learning was remarkably flexible, responding appropriately to task demands. In contrast, implicit learning was strikingly rigid, with each task condition producing a similar degree of implicit learning. These results suggest that explicit learning is a fundamental component of motor learning and has been overlooked or conflated in previous visuomotor tasks. Copyright © 2015 the American Physiological Society.

  2. Ontology-Based Adaptive Dynamic e-Learning Map Planning Method for Conceptual Knowledge Learning

    Science.gov (United States)

    Chen, Tsung-Yi; Chu, Hui-Chuan; Chen, Yuh-Min; Su, Kuan-Chun

    2016-01-01

    E-learning improves the shareability and reusability of knowledge, and surpasses the constraints of time and space to achieve remote asynchronous learning. Since the depth of learning content often varies, it is thus often difficult to adjust materials based on the individual levels of learners. Therefore, this study develops an ontology-based…

  3. MRSA model of learning and adaptation: a qualitative study among the general public

    Directory of Open Access Journals (Sweden)

    Rohde Rodney E

    2012-04-01

    Full Text Available Abstract Background More people in the US now die from Methicillin Resistant Staphylococcus aureus (MRSA infections than from HIV/AIDS. Often acquired in healthcare facilities or during healthcare procedures, the extremely high incidence of MRSA infections and the dangerously low levels of literacy regarding antibiotic resistance in the general public are on a collision course. Traditional medical approaches to infection control and the conventional attitude healthcare practitioners adopt toward public education are no longer adequate to avoid this collision. This study helps us understand how people acquire and process new information and then adapt behaviours based on learning. Methods Using constructivist theory, semi-structured face-to-face and phone interviews were conducted to gather pertinent data. This allowed participants to tell their stories so their experiences could deepen our understanding of this crucial health issue. Interview transcripts were analysed using grounded theory and sensitizing concepts. Results Our findings were classified into two main categories, each of which in turn included three subthemes. First, in the category of Learning, we identified how individuals used their Experiences with MRSA, to answer the questions: What was learned? and, How did learning occur? The second category, Adaptation gave us insights into Self-reliance, Reliance on others, and Reflections on the MRSA journey. Conclusions This study underscores the critical importance of educational programs for patients, and improved continuing education for healthcare providers. Five specific results of this study can reduce the vacuum that currently exists between the knowledge and information available to healthcare professionals, and how that information is conveyed to the public. These points include: 1 a common model of MRSA learning and adaptation; 2 the self-directed nature of adult learning; 3 the focus on general MRSA information, care and

  4. Studying citizen science through adaptive management and learning feedbacks as mechanisms for improving conservation.

    Science.gov (United States)

    Jordan, Rebecca; Gray, Steven; Sorensen, Amanda; Newman, Greg; Mellor, David; Newman, Greg; Hmelo-Silver, Cindy; LaDeau, Shannon; Biehler, Dawn; Crall, Alycia

    2016-06-01

    Citizen science has generated a growing interest among scientists and community groups, and citizen science programs have been created specifically for conservation. We examined collaborative science, a highly interactive form of citizen science, which we developed within a theoretically informed framework. In this essay, we focused on 2 aspects of our framework: social learning and adaptive management. Social learning, in contrast to individual-based learning, stresses collaborative and generative insight making and is well-suited for adaptive management. Adaptive-management integrates feedback loops that are informed by what is learned and is guided by iterative decision making. Participants engaged in citizen science are able to add to what they are learning through primary data collection, which can result in the real-time information that is often necessary for conservation. Our work is particularly timely because research publications consistently report a lack of established frameworks and evaluation plans to address the extent of conservation outcomes in citizen science. To illustrate how our framework supports conservation through citizen science, we examined how 2 programs enacted our collaborative science framework. Further, we inspected preliminary conservation outcomes of our case-study programs. These programs, despite their recent implementation, are demonstrating promise with regard to positive conservation outcomes. To date, they are independently earning funds to support research, earning buy-in from local partners to engage in experimentation, and, in the absence of leading scientists, are collecting data to test ideas. We argue that this success is due to citizen scientists being organized around local issues and engaging in iterative, collaborative, and adaptive learning. © 2016 Society for Conservation Biology.

  5. A Case-Study for Life-Long Learning and Adaptation in Cooperative Robot Teams

    Energy Technology Data Exchange (ETDEWEB)

    Parker, L.E.

    1999-09-19

    While considerable progress has been made in recent years toward the development of multi-robot teams, much work remains to be done before these teams are used widely in real-world applications. Two particular needs toward this end are the development of mechanisms that enable robot teams to generate cooperative behaviors on their own, and the development of techniques that allow these teams to autonomously adapt their behavior over time as the environment or the robot team changes. This paper proposes the use of the Cooperative Multi-Robot Observation of Multiple Moving Targets (CMOMMT) application as a rich domain for studying the issues of multi-robot learning and adaptation. After discussing the need for learning and adaptation in multi-robot teams, this paper describes the CMOMMT application and its relevance to multi-robot learning. We discuss the results of the previously- developed, hand-generated algorithm for CMOMMT and the potential for learning that was discovered from the hand-generated approach. We then describe the early work that has been done (by us and others) to generate multi- robot learning techniques for the CMOMMT application, as well as our ongoing research to develop approaches that give performance as good, or better, than the hand-generated approach. The ultimate goal of this research is to develop techniques for multi-robot learning and adaptation in the CMOMMT application domain that will generalize to cooperative robot applications in other domains, thus making the practical use of multi-robot teams in a wide variety of real-world applications much closer to reality.

  6. Learning from history: Adaptive calibration of 'tilting spine' fiber positioners

    CERN Document Server

    Gilbert, James

    2015-01-01

    This paper discusses a new approach for determining the calibration parameters of independently-actuated optical fibers in multi-object astronomical fiber positioning systems. This work comes from the development of a new type of piezoelectric motor intended to enhance the 'tilting spine' fiber positioning technology originally created by the Australian Astronomical Observatory. Testing has shown that the motor's performance can vary depending on the fiber's location within its accessible field, meaning that an individual fiber is difficult calibrate with a one-time routine. Better performance has resulted from constantly updating calibration parameters based on the observed movements of the fiber during normal closed-loop positioning. Over time, location-specific historical data is amassed that can be used to better predict the results of a future fiber movement. This is similar to a technique previously proposed by the Australian Astronomical Observatory, but with the addition of location-specific learning....

  7. Enhancing Student Adaption to a Case Based Learning Environment

    DEFF Research Database (Denmark)

    Jensen, Lars Peter

    2010-01-01

    the portfolios. A comparison with statements and quotes from student’s semester evaluation from the previous years will be made, and it will be investigated if there is a change in how many students pass the exam. CONCLUSION A first glance at the portfolios show a high degree of satisfactory with the case model......INTRODUCTION Since Aalborg University (AAU) was started it has been using an educational model, where Problem Based Learning is the turning point. Each semester the students on the Engineering Educations form groups of 3-6 persons, which uses half of the study time within the semester to solve...... and document a real-world engineering problem. Four years ago a new engineer education: “Medicine with an industrial specialization” started, and for the Medicine part of the education (Bachelor level) it was decided to use a case based PBL model in combination with project work (app. 1/3 of each semester...

  8. Adaptive Parallel Tempering for Stochastic Maximum Likelihood Learning of RBMs

    CERN Document Server

    Desjardins, Guillaume; Bengio, Yoshua

    2010-01-01

    Restricted Boltzmann Machines (RBM) have attracted a lot of attention of late, as one the principle building blocks of deep networks. Training RBMs remains problematic however, because of the intractibility of their partition function. The maximum likelihood gradient requires a very robust sampler which can accurately sample from the model despite the loss of ergodicity often incurred during learning. While using Parallel Tempering in the negative phase of Stochastic Maximum Likelihood (SML-PT) helps address the issue, it imposes a trade-off between computational complexity and high ergodicity, and requires careful hand-tuning of the temperatures. In this paper, we show that this trade-off is unnecessary. The choice of optimal temperatures can be automated by minimizing average return time (a concept first proposed by [Katzgraber et al., 2006]) while chains can be spawned dynamically, as needed, thus minimizing the computational overhead. We show on a synthetic dataset, that this results in better likelihood ...

  9. Advanced and Effective Learning in Context Aware and Adaptive Mobile Learning Scenarios

    Directory of Open Access Journals (Sweden)

    Nagella Uday Bhaskar

    2010-01-01

    Full Text Available The ability to support students/learners to learn on the move at any place and at any time is new task to be addressed by using the mobile devices of the learners. Mobile technology support has given birth to the concept of mobile learning possessing a wide spectrum of applications and new teaching and learning techniques. This paper discusses a study conducted for undergraduate students on the effect of mobile technology usage in a learning process. The results showcased here indicate acceptance of the mobile devices into the learning process with a well appreciated enthusiasm from the learners.

  10. On the Influence of Informed Agents on Learning and Adaptation over Networks

    CERN Document Server

    Tu, Sheng-Yuan

    2012-01-01

    Adaptive networks consist of a collection of agents with adaptation and learning abilities. The agents interact with each other on a local level and diffuse information across the network through their collaborations. In this work, we consider two types of agents: informed agents and uninformed agents. The former receive new data regularly and perform consultation and in-network tasks, while the latter do not collect data and only participate in the consultation tasks. We examine the performance of adaptive networks as a function of the proportion of informed agents and their distribution in space. The results reveal some interesting and surprising trade-offs between convergence rate and mean-square performance. In particular, among other results, it is shown that the performance of adaptive networks does not necessarily improve with a larger proportion of informed agents. Instead, it is established that the larger the proportion of informed agents is, the faster the convergence rate of the network becomes al...

  11. Towards more efficient e-learning, intelligence and adapted teaching material

    Directory of Open Access Journals (Sweden)

    Damir Kalpić

    2010-12-01

    Full Text Available This article presents results of a research project in which we attempted to determine the relationship between efficient E-learning and teaching materials adapted based on students’ structure of intelligence. The project was conducted on approximately 500 students, 23 classes, nine elementary schools, with ten teachers of history, informatics and several licensed psychologists. E-teaching material was prepared for the subject of History for eight-grade students of elementary school. Students were tested for the structure of intelligence, and based on their most prominent component, they were divided into groups, using teaching materials adapted to their most prominent intelligence component. The results have shown that use of the adapted teaching materials achieved 6-12% better results than E-materials not adapted to students’ structure of intelligence.

  12. Preventing KPI Violations in Business Processes based on Decision Tree Learning and Proactive Runtime Adaptation

    Directory of Open Access Journals (Sweden)

    Dimka Karastoyanova

    2012-01-01

    Full Text Available The performance of business processes is measured and monitored in terms of Key Performance Indicators (KPIs. If the monitoring results show that the KPI targets are violated, the underlying reasons have to be identified and the process should be adapted accordingly to address the violations. In this paper we propose an integrated monitoring, prediction and adaptation approach for preventing KPI violations of business process instances. KPIs are monitored continuously while the process is executed. Additionally, based on KPI measurements of historical process instances we use decision tree learning to construct classification models which are then used to predict the KPI value of an instance while it is still running. If a KPI violation is predicted, we identify adaptation requirements and adaptation strategies in order to prevent the violation.

  13. Encouraging Reuse of Design Knowledge

    DEFF Research Database (Denmark)

    Ahmed, Saeema

    2005-01-01

    The long-term aim of this research is to develop a method to index design knowledge that is intuitive to an engineering designer and therefore encourage the reuse of information. Eighteen interviews were carried out to understand how designers described the process of designing a particular...

  14. Reuse in Practice Workshop Summary

    Science.gov (United States)

    1990-04-01

    SIERRA.STANFORD.EDU Preface The following is a transcript of the keynote address for the Reuse in Practice Workshop sponsored by IDA, SEI and SIGADA. The...used were obtained from the Ads Software Repository via a manual search process (an automated search mecanism would have been an enoamous help). We

  15. Older adults learn less, but still reduce metabolic cost, during motor adaptation

    Science.gov (United States)

    Huang, Helen J.

    2013-01-01

    The ability to learn new movements and dynamics is important for maintaining independence with advancing age. Age-related sensorimotor changes and increased muscle coactivation likely alter the trial-and-error-based process of adapting to new movement demands (motor adaptation). Here, we asked, to what extent is motor adaptation to novel dynamics maintained in older adults (≥65 yr)? We hypothesized that older adults would adapt to the novel dynamics less well than young adults. Because older adults often use muscle coactivation, we expected older adults to use greater muscle coactivation during motor adaptation than young adults. Nevertheless, we predicted that older adults would reduce muscle activity and metabolic cost with motor adaptation, similar to young adults. Seated older (n = 11, 73.8 ± 5.6 yr) and young (n = 15, 23.8 ± 4.7 yr) adults made targeted reaching movements while grasping a robotic arm. We measured their metabolic rate continuously via expired gas analysis. A force field was used to add novel dynamics. Older adults had greater movement deviations and compensated for just 65% of the novel dynamics compared with 84% in young adults. As expected, older adults used greater muscle coactivation than young adults. Last, older adults reduced muscle activity with motor adaptation and had consistent reductions in metabolic cost later during motor adaptation, similar to young adults. These results suggest that despite increased muscle coactivation, older adults can adapt to the novel dynamics, albeit less accurately. These results also suggest that reductions in metabolic cost may be a fundamental feature of motor adaptation. PMID:24133222

  16. Water Reuse in Industrial food Processing

    African Journals Online (AJOL)

    subject of responsible care for the environment, water reuse is increasingly regarded as a tool for ... In this paper some hints are given for implementing water reuse in the food processing industry, ... The problem of rational use of industrial.

  17. Frontal theta links prediction errors to behavioral adaptation in reinforcement learning.

    Science.gov (United States)

    Cavanagh, James F; Frank, Michael J; Klein, Theresa J; Allen, John J B

    2010-02-15

    Investigations into action monitoring have consistently detailed a frontocentral voltage deflection in the event-related potential (ERP) following the presentation of negatively valenced feedback, sometimes termed the feedback-related negativity (FRN). The FRN has been proposed to reflect a neural response to prediction errors during reinforcement learning, yet the single-trial relationship between neural activity and the quanta of expectation violation remains untested. Although ERP methods are not well suited to single-trial analyses, the FRN has been associated with theta band oscillatory perturbations in the medial prefrontal cortex. Mediofrontal theta oscillations have been previously associated with expectation violation and behavioral adaptation and are well suited to single-trial analysis. Here, we recorded EEG activity during a probabilistic reinforcement learning task and fit the performance data to an abstract computational model (Q-learning) for calculation of single-trial reward prediction errors. Single-trial theta oscillatory activities following feedback were investigated within the context of expectation (prediction error) and adaptation (subsequent reaction time change). Results indicate that interactive medial and lateral frontal theta activities reflect the degree of negative and positive reward prediction error in the service of behavioral adaptation. These different brain areas use prediction error calculations for different behavioral adaptations, with medial frontal theta reflecting the utilization of prediction errors for reaction time slowing (specifically following errors), but lateral frontal theta reflecting prediction errors leading to working memory-related reaction time speeding for the correct choice.

  18. Towards Individualized Online Learning: The Design and Development of an Adaptive Web Based Learning Environment

    Science.gov (United States)

    Inan, Fethi A.; Flores, Raymond; Ari, Fatih; Arslan-Ari, Ismahan

    2011-01-01

    The purpose of this study was to document the design and development of an adaptive system which individualizes instruction such as content, interfaces, instructional strategies, and resources dependent on two factors, namely student motivation and prior knowledge levels. Combining adaptive hypermedia methods with strategies proposed by…

  19. View-invariant human action recognition via robust locally adaptive multi-view learning

    Institute of Scientific and Technical Information of China (English)

    Jia-geng FENG; Jun XIAO

    2015-01-01

    Human action recognition is currently one of the most active research areas in computer vision. It has been widely used in many applications, such as intelligent surveillance, perceptual interface, and content-based video retrieval. However, some extrinsic factors are barriers for the development of action recognition;e.g., human actions may be observed from arbitrary camera viewpoints in realistic scene. Thus, view-invariant analysis becomes important for action recognition algorithms, and a number of researchers have paid much attention to this issue. In this paper, we present a multi-view learning approach to recognize human actions from different views. As most existing multi-view learning algorithms often suffer from the problem of lacking data adaptiveness in the nearest neighborhood graph construction procedure, a robust locally adaptive multi-view learning algorithm based on learning multiple local L1-graphs is proposed. Moreover, an efficient iterative optimization method is proposed to solve the proposed objective function. Experiments on three public view-invariant action recognition datasets, i.e., ViHASi, IXMAS, and WVU, demonstrate data adaptiveness, effectiveness, and efficiency of our algorithm. More importantly, when the feature dimension is correctly selected (i.e.,>60), the proposed algorithm stably outperforms state-of-the-art counterparts and obtains about 6%improvement in recognition accuracy on the three datasets.

  20. Fluency adaptation in speakers with Parkinson disease: a motor learning perspective.

    Science.gov (United States)

    Whitfield, Jason A; Delong, Catharine; Goberman, Alexander M; Blomgren, Michael

    2017-06-30

    Fluency adaptation is characterised by a reduction in stuttering-like behaviours over successive readings of the same speech material and is an effect that is typically observed in developmental stuttering. Prominent theories suggest that short-term motor learning associated with practice explain, in part, fluency adaptation. The current investigation examined the fluency adaptation effect in a group of speakers with Parkinson disease (PD) who exhibited stuttering-like disfluencies. Individuals with PD (n = 21) and neurologically healthy controls (n = 19) read a passage five times. Per cent syllables stuttered was measured and calculated for each reading passage. Participants in the PD group exhibited significantly more stuttering-like disfluencies than control speakers. Twelve individuals in the PD group exhibited at least three per cent syllable stuttered on at least one reading. Statistical trends revealed that the subgroup of individuals with PD who stuttered exhibited a significant reduction in stuttering moments over the five successive readings. A significant fluency adaptation effect was observed for the group of speakers with PD who exhibited stuttering-like disfluencies. Results of the current study are discussed within the framework of the motor learning hypothesis of fluency adaptation.

  1. Climate and Adaptive Management: What Are We Learning While We're Doing?

    Science.gov (United States)

    Pulwarty, R.; Melis, T.; Shurts, J.; Jain, S.

    2005-12-01

    Learning is of strategic importance in the decades-long process of adapting to climatic change and variability and in accumulating lessons from past and current practices. Even when physical effects can be established with fair confidence there usually exist large uncertainties about biological and ecological effects and even greater uncertainties with respect to social consequences. Much work and experience has shown that long-term environmental problems can seldom be dealt with by single discrete actions or policies but respond only to continuing, sustained efforts at learning, supported by steady public attention and visibility. In many cases, the complications of recorded changes in the spatial and temporal distribution of rainfall, temperature soil moisture, runoff, frequency and magnitudes of droughts and floods have not been explicitly included in response planning. The idea of "adaptive management" has been widely advocated as a bridge between science and policy with a specific focus on ecosystems. We discuss this idea in the context of climatic and other uncertainties but ground the discussion in the implementation of actual adaptive management programs. Adaptive management has three key tenets (1) Policies are experiments that should be designed to produce usable lessons; (2) It should operate on scales compatible with natural processes, recognizing social and economic viability within functioning ecosystems; and: (3) Is realized through effective partnerships among private, local, state, tribal and federal interests. In a watershed setting this can mean balancing hydropower production, habitat management, conservation, endangered species recovery, and cultural resources in order to experiment, learn, incorporate learning, and adapt. Each of these carries its sources of uncertainty. The primary focus is on the experience of the Columbia and Colorado River Basins, the longest running explicit efforts at adaptive management. Experience will also be drawn

  2. Short-Term Load Forecasting Using Adaptive Annealing Learning Algorithm Based Reinforcement Neural Network

    Directory of Open Access Journals (Sweden)

    Cheng-Ming Lee

    2016-11-01

    Full Text Available A reinforcement learning algorithm is proposed to improve the accuracy of short-term load forecasting (STLF in this article. The proposed model integrates radial basis function neural network (RBFNN, support vector regression (SVR, and adaptive annealing learning algorithm (AALA. In the proposed methodology, firstly, the initial structure of RBFNN is determined by using an SVR. Then, an AALA with time-varying learning rates is used to optimize the initial parameters of SVR-RBFNN (AALA-SVR-RBFNN. In order to overcome the stagnation for searching optimal RBFNN, a particle swarm optimization (PSO is applied to simultaneously find promising learning rates in AALA. Finally, the short-term load demands are predicted by using the optimal RBFNN. The performance of the proposed methodology is verified on the actual load dataset from the Taiwan Power Company (TPC. Simulation results reveal that the proposed AALA-SVR-RBFNN can achieve a better load forecasting precision compared to various RBFNNs.

  3. A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

    Directory of Open Access Journals (Sweden)

    James N Ingram

    2011-09-01

    Full Text Available Motor learning has been extensively studied using dynamic (force-field perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar

  4. Extracting patterns of single-trial EEG using an adaptive learning algorithm.

    Science.gov (United States)

    Lin, Chin-Teng; Wang, Yu-Kai; Fang, Chieh-Ning; Yu, Yi-Hsin; King, Jung-Tai

    2015-01-01

    The improvement of brain imaging technique brings about an opportunity for developing and investigating brain-computer interface (BCI) which is a way to interact with computer and environment. The measured brain activities usually constitute the signals of interest and noises. Applying the portable device and removing noise are the benefits to real-world BCI. In this study, one portable electroencephalogram (EEG) system non-invasively acquired brain dynamics through wireless transmission while six subjects participated in the rapid serial visual presentation (RSVP) paradigm. The event-related potential (ERP) was traditionally estimated by ensemble averaging (EA) to increase the signal-to-noise ratio. One adaptive filter of data-reusing radial basis function network (DR-RBFN) was also utilized as the estimator. The results showed that this portable EEG system stably acquired brain activities. Furthermore, the task-related potentials could be clearly explored from the limited samples of EEG data through DR-RBFN. According to the artifact-free data from the portable device, this study demonstrated the potential to move the BCI from laboratory research to real-life application in the near future.

  5. Sparsity-aware tight frame learning with adaptive subspace recognition for multiple fault diagnosis

    Science.gov (United States)

    Zhang, Han; Chen, Xuefeng; Du, Zhaohui; Yang, Boyuan

    2017-09-01

    It is a challenging problem to design excellent dictionaries to sparsely represent diverse fault information and simultaneously discriminate different fault sources. Therefore, this paper describes and analyzes a novel multiple feature recognition framework which incorporates the tight frame learning technique with an adaptive subspace recognition strategy. The proposed framework consists of four stages. Firstly, by introducing the tight frame constraint into the popular dictionary learning model, the proposed tight frame learning model could be formulated as a nonconvex optimization problem which can be solved by alternatively implementing hard thresholding operation and singular value decomposition. Secondly, the noises are effectively eliminated through transform sparse coding techniques. Thirdly, the denoised signal is decoupled into discriminative feature subspaces by each tight frame filter. Finally, in guidance of elaborately designed fault related sensitive indexes, latent fault feature subspaces can be adaptively recognized and multiple faults are diagnosed simultaneously. Extensive numerical experiments are sequently implemented to investigate the sparsifying capability of the learned tight frame as well as its comprehensive denoising performance. Most importantly, the feasibility and superiority of the proposed framework is verified through performing multiple fault diagnosis of motor bearings. Compared with the state-of-the-art fault detection techniques, some important advantages have been observed: firstly, the proposed framework incorporates the physical prior with the data-driven strategy and naturally multiple fault feature with similar oscillation morphology can be adaptively decoupled. Secondly, the tight frame dictionary directly learned from the noisy observation can significantly promote the sparsity of fault features compared to analytical tight frames. Thirdly, a satisfactory complete signal space description property is guaranteed and thus

  6. Generalization patterns for reach adaptation and proprioceptive recalibration differ after visuomotor learning.

    Science.gov (United States)

    Cressman, Erin K; Henriques, Denise Y P

    2015-07-01

    Visuomotor learning results in changes in both motor and sensory systems (Cressman EK, Henriques DY. J Neurophysiol 102: 3505-3518, 2009), such that reaches are adapted and sense of felt hand position recalibrated after reaching with altered visual feedback of the hand. Moreover, visuomotor learning has been shown to generalize such that reach adaptation achieved at a trained target location can influence reaches to novel target directions (Krakauer JW, Pine ZM, Ghilardi MF, Ghez C. J Neurosci 20: 8916-8924, 2000). We looked to determine whether proprioceptive recalibration also generalizes to novel locations. Moreover, we looked to establish the relationship between reach adaptation and changes in sense of felt hand position by determining whether proprioceptive recalibration generalizes to novel targets in a similar manner as reach adaptation. On training trials, subjects reached to a single target with aligned or misaligned cursor-hand feedback, in which the cursor was either rotated or scaled in extent relative to hand movement. After reach training, subjects reached to the training target and novel targets (including targets from a second start position) without visual feedback to assess generalization of reach adaptation. Subjects then performed a proprioceptive estimation task, in which they indicated the position of their hand relative to visual reference markers placed at similar locations as the trained and novel reach targets. Results indicated that shifts in hand position generalized across novel locations, independent of reach adaptation. Thus these distinct sensory and motor generalization patterns suggest that reach adaptation and proprioceptive recalibration arise from independent error signals and that changes in one system cannot guide adjustments in the other.

  7. Integrating dynamic stopping, transfer learning and language models in an adaptive zero-training ERP speller

    Science.gov (United States)

    Kindermans, Pieter-Jan; Tangermann, Michael; Müller, Klaus-Robert; Schrauwen, Benjamin

    2014-06-01

    Objective. Most BCIs have to undergo a calibration session in which data is recorded to train decoders with machine learning. Only recently zero-training methods have become a subject of study. This work proposes a probabilistic framework for BCI applications which exploit event-related potentials (ERPs). For the example of a visual P300 speller we show how the framework harvests the structure suitable to solve the decoding task by (a) transfer learning, (b) unsupervised adaptation, (c) language model and (d) dynamic stopping. Approach. A simulation study compares the proposed probabilistic zero framework (using transfer learning and task structure) to a state-of-the-art supervised model on n = 22 subjects. The individual influence of the involved components (a)-(d) are investigated. Main results. Without any need for a calibration session, the probabilistic zero-training framework with inter-subject transfer learning shows excellent performance—competitive to a state-of-the-art supervised method using calibration. Its decoding quality is carried mainly by the effect of transfer learning in combination with continuous unsupervised adaptation. Significance. A high-performing zero-training BCI is within reach for one of the most popular BCI paradigms: ERP spelling. Recording calibration data for a supervised BCI would require valuable time which is lost for spelling. The time spent on calibration would allow a novel user to spell 29 symbols with our unsupervised approach. It could be of use for various clinical and non-clinical ERP-applications of BCI.

  8. Integrating dynamic stopping, transfer learning and language models in an adaptive zero-training ERP speller.

    Science.gov (United States)

    Kindermans, Pieter-Jan; Tangermann, Michael; Müller, Klaus-Robert; Schrauwen, Benjamin

    2014-06-01

    Most BCIs have to undergo a calibration session in which data is recorded to train decoders with machine learning. Only recently zero-training methods have become a subject of study. This work proposes a probabilistic framework for BCI applications which exploit event-related potentials (ERPs). For the example of a visual P300 speller we show how the framework harvests the structure suitable to solve the decoding task by (a) transfer learning, (b) unsupervised adaptation, (c) language model and (d) dynamic stopping. A simulation study compares the proposed probabilistic zero framework (using transfer learning and task structure) to a state-of-the-art supervised model on n = 22 subjects. The individual influence of the involved components (a)-(d) are investigated. Without any need for a calibration session, the probabilistic zero-training framework with inter-subject transfer learning shows excellent performance--competitive to a state-of-the-art supervised method using calibration. Its decoding quality is carried mainly by the effect of transfer learning in combination with continuous unsupervised adaptation. A high-performing zero-training BCI is within reach for one of the most popular BCI paradigms: ERP spelling. Recording calibration data for a supervised BCI would require valuable time which is lost for spelling. The time spent on calibration would allow a novel user to spell 29 symbols with our unsupervised approach. It could be of use for various clinical and non-clinical ERP-applications of BCI.

  9. Adaptive learning in a compartmental model of visual cortex - how feedback enables stable category learning and refinement

    Directory of Open Access Journals (Sweden)

    Georg eLayher

    2014-12-01

    Full Text Available The categorization of real world objects is often reflected in the similarity of their visual appearances. Such categories of objects do not necessarily form disjunct sets of objects, neither semantically nor visually. The relationship between categories can often be described in terms of a hierarchical structure. For instance, tigers and leopards build two separate mammalian categories, but both belong to the category of felines. In other words, tigers and leopards are subcategories of the category Felidae. In the last decades, the unsupervised learning of categories of visual input stimuli has been addressed by numerous approaches in machine learning as well as in the computational neurosciences. However, the question of what kind of mechanisms might be involved in the process of subcategory learning, or category refinement, remains a topic of active investigation. We propose a recurrent computational network architecture for the unsupervised learning of categorial and subcategorial visual input representations. During learning, the connection strengths of bottom-up weights from input to higher-level category representations are adapted according to the input activity distribution. In a similar manner, top-down weights learn to encode the characteristics of a specific stimulus category. Feedforward and feedback learning in combination realize an associative memory mechanism, enabling the selective top-down propagation of a category's feedback weight distribution. We suggest that the difference between the expected input encoded in the projective field of a category node and the current input pattern controls the amplification of feedforward-driven representations. Large enough differences trigger the recruitment of new representational resources and the establishment of (sub- category representations. We demonstrate the temporal evolution of such learning and show how the approach successully establishes category and subcategory

  10. Minimal-Learning-Parameter Technique Based Adaptive Neural Sliding Mode Control of MEMS Gyroscope

    Directory of Open Access Journals (Sweden)

    Bin Xu

    2017-01-01

    Full Text Available This paper investigates an adaptive neural sliding mode controller for MEMS gyroscopes with minimal-learning-parameter technique. Considering the system uncertainty in dynamics, neural network is employed for approximation. Minimal-learning-parameter technique is constructed to decrease the number of update parameters, and in this way the computation burden is greatly reduced. Sliding mode control is designed to cancel the effect of time-varying disturbance. The closed-loop stability analysis is established via Lyapunov approach. Simulation results are presented to demonstrate the effectiveness of the method.

  11. Organising for Learning - Adaptive and Innovative Learning in Customer-Supplier Relationships

    DEFF Research Database (Denmark)

    Christensen, Poul Rind; Damgaard, Torben; Munksgaard, Kristin B.

    2004-01-01

    Based on studies of supplier associations, the concepts of adaptived and innovative learning in an interoganisational setting are defined and discussed.......Based on studies of supplier associations, the concepts of adaptived and innovative learning in an interoganisational setting are defined and discussed....

  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. 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…

  14. Learning from Learning: the experiences with implementing Adaptive Collaborative Forest Management in Zimbabwe.

    NARCIS (Netherlands)

    Mutimukuru, T.; Almekinders, C.J.M.

    2011-01-01

    Convinced that participatory resource management is the way forward in the conservation of natural resources, despite the increasing criticism of participatory approaches, the Centre for International Forestry Research (CIFOR) initiated a multi-country adaptive collaborative management (ACM)

  15. Monitoring Social Learning Processes in Adaptive Comanagement: Three Case Studies from South Africa

    Directory of Open Access Journals (Sweden)

    Georgina Cundill

    2010-09-01

    Full Text Available Learning provides the basis for fostering transitions toward adaptive comanagement. Understanding the ways in which arenas for collaboration and learning are created, and the outcomes of these processes in different contexts, is therefore crucial. This paper presents the results of an experimental research process that identified a small set of key variables that influence effective collaboration and learning, and tested a methodology for monitoring these in a collaborative way in three case studies in South Africa. The small set of key variables tested in this study was sensitive enough to register change over a period of 18 months. Results suggest that the background conditions necessary for social learning can be externally managed during an initiative, with positive outcomes for collaboration and learning. Monitoring outcomes suggest that for learning to be effective, a balance needs to be sought between maintaining key individuals within the system, preventing rigidity and vulnerability when this is achieved, and encouraging active participation within communities of practice. Effective facilitation by an 'honest broker' is one of the ways in which this can be achieved. The results point to an over simplification in the rhetoric that currently surrounds the learning outcomes of multilevel networks, and challenges the idea that democratic structures are necessarily important for effective natural resource management at the community level.

  16. AN INDUCTIVE, INTERACTIVE AND ADAPTIVE HYBRID PROBLEM-BASED LEARNING METHODOLOGY: APPLICATION TO STATISTICS

    Directory of Open Access Journals (Sweden)

    ADA ZHENG

    2011-10-01

    Full Text Available We have developed an innovative hybrid problem-based learning (PBL methodology. The methodology has the following distinctive features: i Each complex question was decomposed into a set of coherent finer subquestions by following the carefully designed criteria to maintain a delicate balance between guiding the students and inspiring them to think independently. This learning methodology enabled the students to solve the complex questions progressively in an inductive context. ii Facilitated by the utilization of our web-based learning systems, the teacher was able to interact with the students intensively and could allocate more teaching time to provide tailor-made feedback for individual student. The students were actively engaged in the learning activities, stimulated by the intensive interaction. iii The answers submitted by the students could be automatically consolidated in the report of the Moodle system in real-time. The teacher could adjust the teaching schedule and focus of the class to adapt to the learning progress of the students by analysing the automatically generated report and log files of the web-based learning system. As a result, the attendance rate of the students increased from about 50% to more than 90%, and the students’ learning motivation have been significantly enhanced.

  17. Adaptive Boundary Iterative Learning Control for an Euler-Bernoulli Beam System With Input Constraint.

    Science.gov (United States)

    He, Wei; Meng, Tingting; Huang, Deqing; Li, Xuefang

    2017-03-15

    This paper addresses the vibration control and the input constraint for an Euler-Bernoulli beam system under aperiodic distributed disturbance and aperiodic boundary disturbance. Hyperbolic tangent functions and saturation functions are adopted to tackle the input constraint. A restrained adaptive boundary iterative learning control (ABILC) law is proposed based on a time-weighted Lyapunov-Krasovskii-like composite energy function. In order to deal with the uncertainty of a system parameter and reject the external disturbances, three adaptive laws are designed and learned in the iteration domain. All the system states of the closed-loop system are proved to be bounded in each iteration. Along the iteration axis, the displacements asymptotically converge toward zero. Simulation results are provided to illustrate the effectiveness of the proposed ABILC scheme.

  18. Machine-Learning Based Co-adaptive Calibration: A Perspective to Fight BCI Illiteracy

    Science.gov (United States)

    Vidaurre, Carmen; Sannelli, Claudia; Müller, Klaus-Robert; Blankertz, Benjamin

    "BCI illiteracy" is one of the biggest problems and challenges in BCI research. It means that BCI control cannot be achieved by a non-negligible number of subjects (estimated 20% to 25%). There are two main causes for BCI illiteracy in BCI users: either no SMR idle rhythm is observed over motor areas, or this idle rhythm is not attenuated during motor imagery, resulting in a classification performance lower than 70% (criterion level) already for offline calibration data. In a previous work of the same authors, the concept of machine learning based co-adaptive calibration was introduced. This new type of calibration provided substantially improved performance for a variety of users. Here, we use a similar approach and investigate to what extent co-adapting learning enables substantial BCI control for completely novice users and those who suffered from BCI illiteracy before.

  19. Vocal learning beyond imitation: mechanisms of adaptive vocal development in songbirds and human infants.

    Science.gov (United States)

    Tchernichovski, Ofer; Marcus, Gary

    2014-10-01

    Studies of vocal learning in songbirds typically focus on the acquisition of sensory templates for song imitation and on the consequent process of matching song production to templates. However, functional vocal development also requires the capacity to adaptively diverge from sensory templates, and to flexibly assemble vocal units. Examples of adaptive divergence include the corrective imitation of abnormal songs, and the decreased tendency to copy over-abundant syllables. Such frequency-dependent effects might mirror tradeoffs between the assimilation of group identity (culture) while establishing individual and flexibly expressive songs. Intriguingly, although the requirements for vocal plasticity vary across songbirds, and more so between birdsong and language, the capacity to flexibly assemble vocal sounds develops in a similar, stepwise manner across species. Therefore, universal features of vocal learning go well beyond the capacity to imitate. Copyright © 2014 Elsevier Ltd. All rights reserved.

  20. Reinforcement learning and counterfactual reasoning explain adaptive behavior in a changing environment.

    Science.gov (United States)

    Zhang, Yunfeng; Paik, Jaehyon; Pirolli, Peter

    2015-04-01

    Animals routinely adapt to changes in the environment in order to survive. Though reinforcement learning may play a role in such adaptation, it is not clear that it is the only mechanism involved, as it is not well suited to producing rapid, relatively immediate changes in strategies in response to environmental changes. This research proposes that counterfactual reasoning might be an additional mechanism that facilitates change detection. An experiment is conducted in which a task state changes over time and the participants had to detect the changes in order to perform well and gain monetary rewards. A cognitive model is constructed that incorporates reinforcement learning with counterfactual reasoning to help quickly adjust the utility of task strategies in response to changes. The results show that the model can accurately explain human data and that counterfactual reasoning is key to reproducing the various effects observed in this change detection paradigm.

  1. Distributed adaptive fuzzy iterative learning control of coordination problems for higher order multi-agent systems

    Science.gov (United States)

    Li, Jinsha; Li, Junmin

    2016-07-01

    In this paper, the adaptive fuzzy iterative learning control scheme is proposed for coordination problems of Mth order (M ≥ 2) distributed multi-agent systems. Every follower agent has a higher order integrator with unknown nonlinear dynamics and input disturbance. The dynamics of the leader are a higher order nonlinear systems and only available to a portion of the follower agents. With distributed initial state learning, the unified distributed protocols combined time-domain and iteration-domain adaptive laws guarantee that the follower agents track the leader uniformly on [0, T]. Then, the proposed algorithm extends to achieve the formation control. A numerical example and a multiple robotic system are provided to demonstrate the performance of the proposed approach.

  2. Adaptive eLearning modules for cytopathology education: A review and approach.

    Science.gov (United States)

    Samulski, T Danielle; La, Teresa; Wu, Roseann I

    2016-11-01

    Clinical training imposes time and resource constraints on educators and learners, making it difficult to provide and absorb meaningful instruction. Additionally, innovative and personalized education has become an expectation of adult learners. Fortunately, the development of web-based educational tools provides a possible solution to these challenges. Within this review, we introduce the utility of adaptive eLearning platforms in pathology education. In addition to a review of the current literature, we provide the reader with a suggested approach for module creation, as well as a critical assessment of an available platform, based on our experience in creating adaptive eLearning modules for teaching basic concepts in gynecologic cytopathology. Diagn. Cytopathol. 2016;44:944-951. © 2016 Wiley Periodicals, Inc.

  3. PUBLIC DOMAIN PROTECTION. USES AND REUSES OF PUBLIC DOMAIN WORKS

    OpenAIRE

    Monica Adriana LUPAȘCU

    2015-01-01

    This study tries to highlight the necessity of an awareness of the right of access to the public domain, particularly using the example of works whose protection period has expired, as well as the ones which the law considers to be excluded from protection. Such works are used not only by large libraries from around the world, but also by rights holders, via different means of use, including incorporations into original works or adaptations. However, the reuse that follows these uses often on...

  4. Record Management and Design Reuse

    Science.gov (United States)

    Briggs, Hugh C.

    2008-01-01

    Government mandated records management requirements apply to retention and long term archival of a wide variety of records. Part of the attention is on permanent accession and retention by the U.S. National Archives and Records Administration (NARA) but interim requirements for storage by the source agency are included. As government agencies and the Department of Defense move toward implementations, additional goals often include saving design data for reuse. This paper briefly reviews the government records management requirements then investigates candidate meanings of 'reuse' and proposes an enhanced design records retention approach. The recommended strategy that emerges is, for a given program or product family, to invest in rich and readily re-executable preservation of design artifacts for one or two subsequent generations, then downgrade the data in utility through conversions, ultimately reaching the NARA minimum standard for permanent historical-interest archives.

  5. What Can We Learn from a Well-Adapted Enterprise System? A Case Study Approach

    DEFF Research Database (Denmark)

    Svejvig, Per; Jensen, Tina Blegind

    Previous research in IS provides numerous accounts of failure prone enterprise systems (ES) adaptations due to organizational challenges or misalignment between system and business. Contrary to these findings, empirical data from an ES adaptation in a Scandinavian high-tech company, SCANDI, shows...... how the system was highly integrated, accepted by its users, and well-aligned to the work processes. This leads to the research question: Why is the enterprise system so well-adapted in SCANDI and what can we learn from this case study? Building on the structural model of technology to investigate...... of the enterprise system with a long transition process from “match to current business processes” towards “match to standard package”; and 3) The human actors’ enactment of the ES in practice where existing structures are reinforced. We point to the process of customizing and then un-customizing the system as well...

  6. Enhancing learning, innovation, adaptation, and sustainability in health care organizations: the ELIAS performance management framework.

    Science.gov (United States)

    Persaud, D David

    2014-01-01

    The development of sustainable health care organizations that provide high-quality accessible care is a topic of intense interest. This article provides a practical performance management framework that can be utilized to develop sustainable health care organizations. It is a cyclical 5-step process that is premised on accountability, performance management, and learning practices that are the foundation for a continuous process of measurement, disconfirmation, contextualization, implementation, and routinization This results in the enhancement of learning, innovation, adaptation, and sustainability (ELIAS). Important considerations such as recognizing that health care organizations are complex adaptive systems and the presence of a dynamic learning culture are necessary contextual factors that maximize the effectiveness of the proposed framework. Importantly, the ELIAS framework utilizes data that are already being collected by health care organizations for accountability, improvement, evaluation, and strategic purposes. Therefore, the benefit of the framework, when used as outlined, would be to enhance the chances of health care organizations achieving the goals of ongoing adaptation and sustainability, by design, rather than by chance.

  7. A planning quality evaluation tool for prostate adaptive IMRT based on machine learning

    Energy Technology Data Exchange (ETDEWEB)

    Zhu Xiaofeng; Ge Yaorong; Li Taoran; Thongphiew, Danthai; Yin Fangfang; Wu, Q Jackie [Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27708 (United States); Department of Biomedical Engineering, Wake Forest University Health Sciences, Medical Center Boulevard, Winston-Salem, North Carolina 27106 (United States); Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27708 (United States); Department of Radiation Oncology, Brody School of Medicine, East Carolina University, Greenville, North Carolina 27834 (United States); Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina 27708 (United States)

    2011-02-15

    Purpose: To ensure plan quality for adaptive IMRT of the prostate, we developed a quantitative evaluation tool using a machine learning approach. This tool generates dose volume histograms (DVHs) of organs-at-risk (OARs) based on prior plans as a reference, to be compared with the adaptive plan derived from fluence map deformation. Methods: Under the same configuration using seven-field 15 MV photon beams, DVHs of OARs (bladder and rectum) were estimated based on anatomical information of the patient and a model learned from a database of high quality prior plans. In this study, the anatomical information was characterized by the organ volumes and distance-to-target histogram (DTH). The database consists of 198 high quality prostate plans and was validated with 14 cases outside the training pool. Principal component analysis (PCA) was applied to DVHs and DTHs to quantify their salient features. Then, support vector regression (SVR) was implemented to establish the correlation between the features of the DVH and the anatomical information. Results: DVH/DTH curves could be characterized sufficiently just using only two or three truncated principal components, thus, patient anatomical information was quantified with reduced numbers of variables. The evaluation of the model using the test data set demonstrated its accuracy {approx}80% in prediction and effectiveness in improving ART planning quality. Conclusions: An adaptive IMRT plan quality evaluation tool based on machine learning has been developed, which estimates OAR sparing and provides reference in evaluating ART.

  8. Formalisms for reuse and systems integration

    CERN Document Server

    Rubin, Stuart

    2015-01-01

    Reuse and integration are defined as synergistic concepts, where reuse addresses how to minimize redundancy in the creation of components; while, integration focuses on component composition. Integration supports reuse and vice versa. These related concepts support the design of software and systems for maximizing performance while minimizing cost. Knowledge, like data, is subject to reuse; and, each can be interpreted as the other. This means that inherent complexity, a measure of the potential utility of a system, is directly proportional to the extent to which it maximizes reuse and integration. Formal methods can provide an appropriate context for the rigorous handling of these synergistic concepts. Furthermore, formal languages allow for non ambiguous model specification; and, formal verification techniques provide support for insuring the validity of reuse and integration mechanisms.   This edited book includes 12 high quality research papers written by experts in formal aspects of reuse and integratio...

  9. INTERACTIVE DOMAIN ADAPTION FOR THE CLASSIFICATION OF REMOTE SENSING IMAGES USING ACTIVE LEARNING

    Directory of Open Access Journals (Sweden)

    U.Pushpa Lingam

    2015-11-01

    Full Text Available Interactive Domain Adaptation (IDA technique based on active learning for the classification of remote sensing images. Interactive domain adaptation method is used for adapting the supervised classifier trained on a given remote sensing source image to make it suitable for classifying a different but related target image. The two images can be acquired in different locations and at different times. This method iteratively selects the most informative samples of the target image to be labeled and included in the training set and the source image samples are reweighted or removed from the training set on the basis of their disagreement with the target image classification problem. The consistent information available from the source image can be effectively exploited for the classification of the target image and for guiding the selection of new samples to be labeled, whereas the inconsistent information is automatically detected and removed. This approach significantly reduces the number of new labeled samples to be collected from the target image. Experimental results on both a multispectral very high resolution and a hyper spectral data set confirm the effectiveness of the interactive domain adaptation for theclassification of remote sensing using active learning method.

  10. The dynamic interplay among EFL learners’ ambiguity tolerance, adaptability, cultural intelligence, learning approach, and language achievement

    Directory of Open Access Journals (Sweden)

    Shadi Alahdadi

    2017-01-01

    Full Text Available A key objective of education is to prepare individuals to be fully-functioning learners. This entails developing the cognitive, metacognitive, motivational, cultural, and emotional competencies. The present study aimed to examine the interrelationships among adaptability, tolerance of ambiguity, cultural intelligence, learning approach, and language achievement as manifestations of the above competencies within a single model. The participants comprised one hundred eighty BA and MA Iranian university students studying English language teaching and translation. The instruments used in this study consisted of the translated versions of four questionnaires: second language tolerance of ambiguity scale, adaptability taken from emotional intelligence inventory, cultural intelligence (CQ inventory, and the revised study process questionnaire measuring surface and deep learning. The results estimated via structural equation modeling (SEM revealed that the proposed model containing the variables under study had a good fit with the data. It was found that all the variables except adaptability directly influenced language achievement with deep approach having the highest impact and ambiguity tolerance having the lowest influence. In addition, ambiguity tolerance was a positive and significant predictor of deep approach. CQ was found to be under the influence of both ambiguity tolerance and adaptability. The findings were discussed in the light of the yielded results.

  11. L1-norm locally linear representation regularization multi-source adaptation learning.

    Science.gov (United States)

    Tao, Jianwen; Wen, Shiting; Hu, Wenjun

    2015-09-01

    In most supervised domain adaptation learning (DAL) tasks, one has access only to a small number of labeled examples from target domain. Therefore the success of supervised DAL in this "small sample" regime needs the effective utilization of the large amounts of unlabeled data to extract information that is useful for generalization. Toward this end, we here use the geometric intuition of manifold assumption to extend the established frameworks in existing model-based DAL methods for function learning by incorporating additional information about the target geometric structure of the marginal distribution. We would like to ensure that the solution is smooth with respect to both the ambient space and the target marginal distribution. In doing this, we propose a novel L1-norm locally linear representation regularization multi-source adaptation learning framework which exploits the geometry of the probability distribution, which has two techniques. Firstly, an L1-norm locally linear representation method is presented for robust graph construction by replacing the L2-norm reconstruction measure in LLE with L1-norm one, which is termed as L1-LLR for short. Secondly, considering the robust graph regularization, we replace traditional graph Laplacian regularization with our new L1-LLR graph Laplacian regularization and therefore construct new graph-based semi-supervised learning framework with multi-source adaptation constraint, which is coined as L1-MSAL method. Moreover, to deal with the nonlinear learning problem, we also generalize the L1-MSAL method by mapping the input data points from the input space to a high-dimensional reproducing kernel Hilbert space (RKHS) via a nonlinear mapping. Promising experimental results have been obtained on several real-world datasets such as face, visual video and object.

  12. Feature selection and multi-kernel learning for adaptive graph regularized nonnegative matrix factorization

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-09-20

    Nonnegative matrix factorization (NMF), a popular part-based representation technique, does not capture the intrinsic local geometric structure of the data space. Graph regularized NMF (GNMF) was recently proposed to avoid this limitation by regularizing NMF with a nearest neighbor graph constructed from the input data set. However, GNMF has two main bottlenecks. First, using the original feature space directly to construct the graph is not necessarily optimal because of the noisy and irrelevant features and nonlinear distributions of data samples. Second, one possible way to handle the nonlinear distribution of data samples is by kernel embedding. However, it is often difficult to choose the most suitable kernel. To solve these bottlenecks, we propose two novel graph-regularized NMF methods, AGNMFFS and AGNMFMK, by introducing feature selection and multiple-kernel learning to the graph regularized NMF, respectively. Instead of using a fixed graph as in GNMF, the two proposed methods learn the nearest neighbor graph that is adaptive to the selected features and learned multiple kernels, respectively. For each method, we propose a unified objective function to conduct feature selection/multi-kernel learning, NMF and adaptive graph regularization simultaneously. We further develop two iterative algorithms to solve the two optimization problems. Experimental results on two challenging pattern classification tasks demonstrate that the proposed methods significantly outperform state-of-the-art data representation methods.

  13. EEG-Based Emotion Recognition Using Deep Learning Network with Principal Component Based Covariate Shift Adaptation

    Directory of Open Access Journals (Sweden)

    Suwicha Jirayucharoensak

    2014-01-01

    Full Text Available Automatic emotion recognition is one of the most challenging tasks. To detect emotion from nonstationary EEG signals, a sophisticated learning algorithm that can represent high-level abstraction is required. This study proposes the utilization of a deep learning network (DLN to discover unknown feature correlation between input signals that is crucial for the learning task. The DLN is implemented with a stacked autoencoder (SAE using hierarchical feature learning approach. Input features of the network are power spectral densities of 32-channel EEG signals from 32 subjects. To alleviate overfitting problem, principal component analysis (PCA is applied to extract the most important components of initial input features. Furthermore, covariate shift adaptation of the principal components is implemented to minimize the nonstationary effect of EEG signals. Experimental results show that the DLN is capable of classifying three different levels of valence and arousal with accuracy of 49.52% and 46.03%, respectively. Principal component based covariate shift adaptation enhances the respective classification accuracy by 5.55% and 6.53%. Moreover, DLN provides better performance compared to SVM and naive Bayes classifiers.

  14. Adaptive iterative learning control for a class of non-linearly parameterised systems with input saturations

    Science.gov (United States)

    Zhang, Ruikun; Hou, Zhongsheng; Ji, Honghai; Yin, Chenkun

    2016-04-01

    In this paper, an adaptive iterative learning control scheme is proposed for a class of non-linearly parameterised systems with unknown time-varying parameters and input saturations. By incorporating a saturation function, a new iterative learning control mechanism is presented which includes a feedback term and a parameter updating term. Through the use of parameter separation technique, the non-linear parameters are separated from the non-linear function and then a saturated difference updating law is designed in iteration domain by combining the unknown parametric term of the local Lipschitz continuous function and the unknown time-varying gain into an unknown time-varying function. The analysis of convergence is based on a time-weighted Lyapunov-Krasovskii-like composite energy function which consists of time-weighted input, state and parameter estimation information. The proposed learning control mechanism warrants a L2[0, T] convergence of the tracking error sequence along the iteration axis. Simulation results are provided to illustrate the effectiveness of the adaptive iterative learning control scheme.

  15. Coordinated activity of ventral tegmental neurons adapts to appetitive and aversive learning.

    Directory of Open Access Journals (Sweden)

    Yunbok Kim

    Full Text Available Our understanding of how value-related information is encoded in the ventral tegmental area (VTA is based mainly on the responses of individual putative dopamine neurons. In contrast to cortical areas, the nature of coordinated interactions between groups of VTA neurons during motivated behavior is largely unknown. These interactions can strongly affect information processing, highlighting the importance of investigating network level activity. We recorded the activity of multiple single units and local field potentials (LFP in the VTA during a task in which rats learned to associate novel stimuli with different outcomes. We found that coordinated activity of VTA units with either putative dopamine or GABA waveforms was influenced differently by rewarding versus aversive outcomes. Specifically, after learning, stimuli paired with a rewarding outcome increased the correlation in activity levels between unit pairs whereas stimuli paired with an aversive outcome decreased the correlation. Paired single unit responses also became more redundant after learning. These response patterns flexibly tracked the reversal of contingencies, suggesting that learning is associated with changing correlations and enhanced functional connectivity between VTA neurons. Analysis of LFP recorded simultaneously with unit activity showed an increase in the power of theta oscillations when stimuli predicted reward but not an aversive outcome. With learning, a higher proportion of putative GABA units were phase locked to the theta oscillations than putative dopamine units. These patterns also adapted when task contingencies were changed. Taken together, these data demonstrate that VTA neurons organize flexibly as functional networks to support appetitive and aversive learning.

  16. Adoption, adaptation, and abandonment: Appropriation of science education professional development learning

    Science.gov (United States)

    Longhurst, Max L.

    Understanding factors that impact teacher utilization of learning from professional development is critical in order maximize the educational and financial investment in teacher professional learning. This study used a multicase mixed quantitative and qualitative methodology to investigate the factors that influence teacher adoption, adaption, or abandonment of learning from science teacher professional development. The theoretical framework of activity theory was identified as a useful way to investigate the phenomenon of teacher appropriation of pedagogical practices from professional development. This framework has the capacity to account for a multitude of elements in the context of a learning experience. In this study educational appropriation is understood through a continuum of how an educator acquires and implements both practical and conceptual aspects of learning from professional development within localized context. The variability associated with instructional changes made from professional development drives this inquiry to search for better understandings of the appropriation of pedagogical practices. Purposeful sampling was used to identify two participants from a group of eighth-grade science teachers engaged in professional development designed to investigate how cyber-enabled technologies might enhance instruction and learning in integrated science classrooms. The data from this investigation add to the literature of appropriation of instructional practices by connecting eight factors that influence conceptual and practical tools with the development of ownership of pedagogical practices in the appropriation hierarchy. Recommendations are shared with professional development developers, providers, and participants in anticipation that future science teaching experiences might be informed by findings from this study.

  17. Observer-based Adaptive Iterative Learning Control for Nonlinear Systems with Time-varying Delays

    Institute of Scientific and Technical Information of China (English)

    Wei-Sheng Chen; Rui-Hong Li; Jing Li

    2010-01-01

    An observer-based adaptive iterative learning control (AILC) scheme is developed for a class of nonlinear systems with unknown time-varying parameters and unknown time-varying delays. The linear matrix inequality (LMI) method is employed to design the nonlinear observer. The designed controller contains a proportional-integral-derivative (PID) feedback term in time domain. The learning law of unknown constant parameter is differential-difference-type, and the learning law of unknown time-varying parameter is difference-type. It is assumed that the unknown delay-dependent uncertainty is nonlinearly parameterized. By constructing a Lyapunov-Krasovskii-like composite energy function (CEF), we prove the boundedness of all closed-loop signals and the convergence of tracking error. A simulation example is provided to illustrate the effectiveness of the control algorithm proposed in this paper.

  18. Integrating DGSs and GATPs in an Adaptative and Collaborative Blended-Learning Web-Environment

    CERN Document Server

    Santos, Vanda; 10.4204/EPTCS.79.7

    2012-01-01

    The area of geometry with its very strong and appealing visual contents and its also strong and appealing connection between the visual content and its formal specification, is an area where computational tools can enhance, in a significant way, the learning environments. The dynamic geometry software systems (DGSs) can be used to explore the visual contents of geometry. This already mature tools allows an easy construction of geometric figures build from free objects and elementary constructions. The geometric automated theorem provers (GATPs) allows formal deductive reasoning about geometric constructions, extending the reasoning via concrete instances in a given model to formal deductive reasoning in a geometric theory. An adaptative and collaborative blended-learning environment where the DGS and GATP features could be fully explored would be, in our opinion a very rich and challenging learning environment for teachers and students. In this text we will describe the Web Geometry Laboratory a Web environme...

  19. An Adaptive Learning Rate for RBFNN Using Time-Domain Feedback Analysis

    Directory of Open Access Journals (Sweden)

    Syed Saad Azhar Ali

    2014-01-01

    Full Text Available Radial basis function neural networks are used in a variety of applications such as pattern recognition, nonlinear identification, control and time series prediction. In this paper, the learning algorithm of radial basis function neural networks is analyzed in a feedback structure. The robustness of the learning algorithm is discussed in the presence of uncertainties that might be due to noisy perturbations at the input or to modeling mismatch. An intelligent adaptation rule is developed for the learning rate of RBFNN which gives faster convergence via an estimate of error energy while giving guarantee to the l2 stability governed by the upper bounding via small gain theorem. Simulation results are presented to support our theoretical development.

  20. Designing Adaptive-Content trough E-learning on Electromagnetic Concept

    Science.gov (United States)

    Hakim, L.; Setiawan, A.; Sinaga, P.

    2017-02-01

    Teacher competence development is a national education agenda. Although teachers have adequate learning experience, based on UKA (Academic Competence Test) 2013 results, the content mastery of teachers is still low. In order to reach the maximum development of teacher, it is a must to consider the knowledge level of teachers and the difficulty of content given. This study used a questionnaire given to 40 teachers but only 25 teachers who returned the questionnaire. According to the research, 82% of teachers stated that the electromagnetic is a difficult content. There are several factors why electro magnetic content is considered to be difficult by teachers such as it is abstract, uses a lot of mathematical equations, and correlation with other concepts and content material. From these results, adaptive e-learning design for teacher to learn electromagneticis created.

  1. Adaptive and Energy Efficient Walking in a Hexapod Robot under Neuromechanical Control and Sensorimotor Learning

    DEFF Research Database (Denmark)

    Xiong, Xiaofeng; Wörgötter, Florentin; Manoonpong, Poramate

    2016-01-01

    energy efficient walking, compared to other small legged robots. In addition, this paper also shows that the tight combination of neural control with tunable muscle-like functions, guided by sensory feedback and coupled with sensorimotor learning, is a way forward to better understand and solve adaptive......) to generate the proper leg stiffness (i.e., compliance); and 3) to determine joint angles that give rise to particular positions at the endpoints of the legs. To tackle this problem for a robotic application, here we present a neuromechanical controller coupled with sensorimotor learning. The controller...... feedback and for online tuning the VAAMs' stiffness parameters. The control and learning mechanisms enable the hexapod robot advanced mobility sensor driven-walking device (AMOS) to achieve variable compliant walking that accommodates different gaits and surfaces. As a consequence, AMOS can perform more...

  2. Effectiveness Evaluation Tools and Methods for Adaptive Training and Education in Support of the US Army Learning Model: Research Outline

    Science.gov (United States)

    2015-09-01

    Evaluation Tools and Methods for Adaptive Training and Education in Support of the US Army Learning Model: Research Outline by Joan H Johnston, Greg...4. TITLE AND SUBTITLE Effectiveness Evaluation Tools and Methods for Adaptive Training and Education in Support of the US Army Learning Model...provide affordable, tailored SRL training and educational capabilities for the US Army, the US Army Research Laboratory is investigating and developing

  3. ADAPTATIONAL AND LEARNING-PROCESSES DURING HUMAN SPLIT-BELT LOCOMOTION - INTERACTION BETWEEN CENTRAL MECHANISMS AND AFFERENT INPUT

    NARCIS (Netherlands)

    PROKOP, T; BERGER, W; ZIJLSTRA, W; DIETZ, [No Value

    1995-01-01

    Split-belt locomotion (i.e., walking with unequal leg speeds) requires a rapid adaptation of biomechanical parameters and therefore of leg muscle electromyographic (EMG) activity. This adaptational process during the first strides of asymmetric gait as well as learning effects induced by repetition

  4. ADAPTATIONAL AND LEARNING-PROCESSES DURING HUMAN SPLIT-BELT LOCOMOTION - INTERACTION BETWEEN CENTRAL MECHANISMS AND AFFERENT INPUT

    NARCIS (Netherlands)

    PROKOP, T; BERGER, W; ZIJLSTRA, W; DIETZ, [No Value

    1995-01-01

    Split-belt locomotion (i.e., walking with unequal leg speeds) requires a rapid adaptation of biomechanical parameters and therefore of leg muscle electromyographic (EMG) activity. This adaptational process during the first strides of asymmetric gait as well as learning effects induced by repetition

  5. Self-organizing adaptive map: autonomous learning of curves and surfaces from point samples.

    Science.gov (United States)

    Piastra, Marco

    2013-05-01

    Competitive Hebbian Learning (CHL) (Martinetz, 1993) is a simple and elegant method for estimating the topology of a manifold from point samples. The method has been adopted in a number of self-organizing networks described in the literature and has given rise to related studies in the fields of geometry and computational topology. Recent results from these fields have shown that a faithful reconstruction can be obtained using the CHL method only for curves and surfaces. Within these limitations, these findings constitute a basis for defining a CHL-based, growing self-organizing network that produces a faithful reconstruction of an input manifold. The SOAM (Self-Organizing Adaptive Map) algorithm adapts its local structure autonomously in such a way that it can match the features of the manifold being learned. The adaptation process is driven by the defects arising when the network structure is inadequate, which cause a growth in the density of units. Regions of the network undergo a phase transition and change their behavior whenever a simple, local condition of topological regularity is met. The phase transition is eventually completed across the entire structure and the adaptation process terminates. In specific conditions, the structure thus obtained is homeomorphic to the input manifold. During the adaptation process, the network also has the capability to focus on the acquisition of input point samples in critical regions, with a substantial increase in efficiency. The behavior of the network has been assessed experimentally with typical data sets for surface reconstruction, including suboptimal conditions, e.g. with undersampling and noise.

  6. ICT reuse in socio-economic enterprises

    Energy Technology Data Exchange (ETDEWEB)

    Ongondo, F.O., E-mail: f.ongondo@soton.ac.uk [Centre for Environmental Sciences, Faculty of Engineering and the Environment, Lanchester Building, University of Southampton, University Rd., Highfield, Southampton, Hampshire SO17 1BJ (United Kingdom); Williams, I.D. [Centre for Environmental Sciences, Faculty of Engineering and the Environment, Lanchester Building, University of Southampton, University Rd., Highfield, Southampton, Hampshire SO17 1BJ (United Kingdom); Dietrich, J. [Technische Universität Berlin, Centre for Scientific Continuing Education and Cooperation, Cooperation and Consulting for Environmental Questions (kubus) FH10-1, Fraunhoferstraße 33-36, 10587 Berlin (Germany); Carroll, C. [Centre for Environmental Sciences, Faculty of Engineering and the Environment, Lanchester Building, University of Southampton, University Rd., Highfield, Southampton, Hampshire SO17 1BJ (United Kingdom)

    2013-12-15

    Highlights: • We analyse ICT equipment reuse operations of socio-economic enterprises. • Most common ICT products dealt with are computers and related equipment. • In the UK in 2010, ∼143,750 appliances were reused. • Marketing and legislative difficulties are the common hurdles to reuse activities. • Socio-economic enterprises can significantly contribute to resource efficiency. - Abstract: In Europe, socio-economic enterprises such as charities, voluntary organisations and not-for-profit companies are involved in the repair, refurbishment and reuse of various products. This paper characterises and analyses the operations of socio-economic enterprises that are involved in the reuse of Information and Communication Technology (ICT) equipment. Using findings from a survey, the paper specifically analyses the reuse activities of socio-economic enterprises in the UK from which Europe-wide conclusions are drawn. The amount of ICT products handled by the reuse organisations is quantified and potential barriers and opportunities to their operations are analysed. By-products from reuse activities are discussed and recommendations to improve reuse activities are provided. The most common ICT products dealt with by socio-economic enterprises are computers and related equipment. In the UK in 2010, an estimated 143,750 appliances were reused. However, due to limitations in data, it is difficult to compare this number to the amount of new appliances that entered the UK market or the amount of waste electrical and electronic equipment generated in the same period. Difficulties in marketing products and numerous legislative requirements are the most common barriers to reuse operations. Despite various constraints, it is clear that organisations involved in reuse of ICT could contribute significantly to resource efficiency and a circular economy. It is suggested that clustering of their operations into “reuse parks” would enhance both their profile and their

  7. Stimulating Learning through Policy Experimentation: A Multi-Case Analysis of How Design Influences Policy Learning Outcomes in Experiments for Climate Adaptation

    Directory of Open Access Journals (Sweden)

    Belinda McFadgen

    2017-08-01

    Full Text Available Learning from policy experimentation is a promising way to approach the “wicked problem” of climate adaptation, which is characterised by knowledge gaps and contested understandings of future risk. However, although the role of learning in shaping public policy is well understood, and experiments are expected to facilitate learning, little is known about how experiments produce learning, what types of learning, and how they can be designed to enhance learning effects. Using quantitative research methods, we explore how design choices influence the learning experiences of 173 participants in 18 policy experiments conducted in the Netherlands between 1997 and 2016. The experiments are divided into three “ideal types” that are expected to produce different levels and types of learning. The findings show that policy experiments produce cognitive and relational learning effects, but less normative learning, and experiment design influenced three of six measured dimensions of learning, especially the cognitive learning dimensions. This reveals a trade-off between designing for knowledge development and designing for normative or relational changes; choices that experiment designers should make in the context of their adaptation problem. Our findings also show the role leadership plays in building trust.

  8. Adaptive Local Spatiotemporal Features from RGB-D Data for One-Shot Learning Gesture Recognition.

    Science.gov (United States)

    Lin, Jia; Ruan, Xiaogang; Yu, Naigong; Yang, Yee-Hong

    2016-12-17

    Noise and constant empirical motion constraints affect the extraction of distinctive spatiotemporal features from one or a few samples per gesture class. To tackle these problems, an adaptive local spatiotemporal feature (ALSTF) using fused RGB-D data is proposed. First, motion regions of interest (MRoIs) are adaptively extracted using grayscale and depth velocity variance information to greatly reduce the impact of noise. Then, corners are used as keypoints if their depth, and velocities of grayscale and of depth meet several adaptive local constraints in each MRoI. With further filtering of noise, an accurate and sufficient number of keypoints is obtained within the desired moving body parts (MBPs). Finally, four kinds of multiple descriptors are calculated and combined in extended gradient and motion spaces to represent the appearance and motion features of gestures. The experimental results on the ChaLearn gesture, CAD-60 and MSRDailyActivity3D datasets demonstrate that the proposed feature achieves higher performance compared with published state-of-the-art approaches under the one-shot learning setting and comparable accuracy under the leave-one-out cross validation.

  9. Adaptive Local Spatiotemporal Features from RGB-D Data for One-Shot Learning Gesture Recognition

    Directory of Open Access Journals (Sweden)

    Jia Lin

    2016-12-01

    Full Text Available Noise and constant empirical motion constraints affect the extraction of distinctive spatiotemporal features from one or a few samples per gesture class. To tackle these problems, an adaptive local spatiotemporal feature (ALSTF using fused RGB-D data is proposed. First, motion regions of interest (MRoIs are adaptively extracted using grayscale and depth velocity variance information to greatly reduce the impact of noise. Then, corners are used as keypoints if their depth, and velocities of grayscale and of depth meet several adaptive local constraints in each MRoI. With further filtering of noise, an accurate and sufficient number of keypoints is obtained within the desired moving body parts (MBPs. Finally, four kinds of multiple descriptors are calculated and combined in extended gradient and motion spaces to represent the appearance and motion features of gestures. The experimental results on the ChaLearn gesture, CAD-60 and MSRDailyActivity3D datasets demonstrate that the proposed feature achieves higher performance compared with published state-of-the-art approaches under the one-shot learning setting and comparable accuracy under the leave-one-out cross validation.

  10. An adaptive process model of motor learning: insights for the teaching of motor skills.

    Science.gov (United States)

    Tani, Go; Corrêa, Umberto Cesar; Basso, Luciano; Benda, Rodolfo Novellino; Ugrinowitsch, Herbert; Choshi, Koji

    2014-01-01

    This article presents an outline of a non-equilibrium model, in which motor learning is explained as a continuous process of stabilization and adaptation. The article also shows how propositions derived from this model have been tested, and discusses possible practical implications of some supporting evidence to the teaching of motor skills. The stabilization refers to a process of functional stabilization that is achieved through negative feedback mechanisms. Initially, inconsistent and incorrect responses are gradually reduced, leading to a spatial-temporal patterning of the action. The adaptation is one in which new skills are formed from the reorganization of those already acquired through the flexibility of the system, reorganization of the skill structure, or self-organization. In order to provide learners with competency for adaptation, teachers should (a) guide students to learn motor skills taking into account that the stabilization of performance is just a transitory state that must be dismantled to achieve higher levels of complexity; (b) be clear which parts (micro) compose the skills and how they interact in order to form the whole (macro); (c) manipulate the skills in terms of their temporal, spatial, and/or spatiotemporal dimensions; (d) organize practice initially in a constant way, and then in a varied regimen (random) when the motor skills involve requirements of time and force; and, inversely for motor skills with spatial demands; and (e), provide a moderate frequency of feedback.

  11. Magnetic resonance image restoration via dictionary learning under spatially adaptive constraints.

    Science.gov (United States)

    Wang, Shanshan; Xia, Yong; Dong, Pei; Feng, David Dagan; Luo, Jianhua; Huang, Qiu

    2013-01-01

    This paper proposes a spatially adaptive constrained dictionary learning (SAC-DL) algorithm for Rician noise removal in magnitude magnetic resonance (MR) images. This algorithm explores both the strength of dictionary learning to preserve image structures and the robustness of local variance estimation to remove signal-dependent Rician noise. The magnitude image is first separated into a number of partly overlapping image patches. The statistics of each patch are collected and analyzed to obtain a local noise variance. To better adapt to Rician noise, a correction factor is formulated with the local signal-to-noise ratio (SNR). Finally, the trained dictionary is used to denoise each image patch under spatially adaptive constraints. The proposed algorithm has been compared to the popular nonlocal means (NLM) filtering and unbiased NLM (UNLM) algorithm on simulated T1-weighted, T2-weighted and PD-weighted MR images. Our results suggest that the SAC-DL algorithm preserves more image structures while effectively removing the noise than NLM and it is also superior to UNLM at low noise levels.

  12. NEGOTIATING SERVICE LEARNING THROUGH COMMUNITY ENGAGEMENT: ADAPTIVE LEADERSHIP, KNOWLEDGE, DIALOGUE AND POWER

    Directory of Open Access Journals (Sweden)

    Julia Preece

    2016-04-01

    Full Text Available This article builds on two recent publications (Preece 2013; 2013a concerning the application of asset-based community development and adaptive leadership theories when negotiating university service learning placements with community organisations in one South African province. The first publication introduced the concept of ‘adaptive engagement’. The second analysed empirical findings from the first phase of an action research project that endeavoured to take a teamwork approach to service learning placements. This paper reports on the larger, second phase. Different student teams were each tasked with undertaking an activity that had been identified by an NGO as an area of development need. The paper discusses this approach filtering the above-mentioned theories through a Foucauldian lens for analysing power relationships, knowledge and ownership over decision-making. Findings highlight the multi-layered complexity of community engagement, communication and power relations, and the limiting nature of institutional governmentality in terms of student contributions to sustainable community outcomes and university recognition of community-based knowledge. But the findings also demonstrate the potential for contributing to community change and knowledge sharing when an adaptive leadership approach of clarifying competing goals and values is used alongside respect for community assets of experiential, or subjugated, knowledge.

  13. Using concept similarity in cross ontology for adaptive e-Learning systems

    Directory of Open Access Journals (Sweden)

    B. Saleena

    2015-01-01

    Full Text Available e-Learning is one of the most preferred media of learning by the learners. The learners search the web to gather knowledge about a particular topic from the information in the repositories. Retrieval of relevant materials from a domain can be easily implemented if the information is organized and related in some way. Ontologies are a key concept that helps us to relate information for providing the more relevant lessons to the learner. This paper proposes an adaptive e-Learning system, which generates a user specific e-Learning content by comparing the concepts with more than one system using similarity measures. A cross ontology measure is defined, which consists of fuzzy domain ontology as the primary ontology and the domain expert’s ontology as the secondary ontology, for the comparison process. A personalized document is provided to the user with a user profile, which includes the data obtained from the processing of the proposed method under a User score, which is obtained through the user evaluation. The results of the proposed e-Learning system under the designed cross ontology similarity measure show a significant increase in performance and accuracy under different conditions. The assessment of the comparative analysis, showed the difference in performance of our proposed method over other methods. Based on the assessment results it is proved that the proposed approach is effective over other methods.

  14. Self-Adaptive Trust Based ABR Protocol for MANETs Using Q-Learning

    Science.gov (United States)

    Jeyapal, Akilandeswari

    2014-01-01

    Mobile ad hoc networks (MANETs) are a collection of mobile nodes with a dynamic topology. MANETs work under scalable conditions for many applications and pose different security challenges. Due to the nomadic nature of nodes, detecting misbehaviour is a complex problem. Nodes also share routing information among the neighbours in order to find the route to the destination. This requires nodes to trust each other. Thus we can state that trust is a key concept in secure routing mechanisms. A number of cryptographic protection techniques based on trust have been proposed. Q-learning is a recently used technique, to achieve adaptive trust in MANETs. In comparison to other machine learning computational intelligence techniques, Q-learning achieves optimal results. Our work focuses on computing a score using Q-learning to weigh the trust of a particular node over associativity based routing (ABR) protocol. Thus secure and stable route is calculated as a weighted average of the trust value of the nodes in the route and associativity ticks ensure the stability of the route. Simulation results show that Q-learning based trust ABR protocol improves packet delivery ratio by 27% and reduces the route selection time by 40% over ABR protocol without trust calculation. PMID:25254243

  15. Self-adaptive trust based ABR protocol for MANETs using Q-learning.

    Science.gov (United States)

    Kumar, Anitha Vijaya; Jeyapal, Akilandeswari

    2014-01-01

    Mobile ad hoc networks (MANETs) are a collection of mobile nodes with a dynamic topology. MANETs work under scalable conditions for many applications and pose different security challenges. Due to the nomadic nature of nodes, detecting misbehaviour is a complex problem. Nodes also share routing information among the neighbours in order to find the route to the destination. This requires nodes to trust each other. Thus we can state that trust is a key concept in secure routing mechanisms. A number of cryptographic protection techniques based on trust have been proposed. Q-learning is a recently used technique, to achieve adaptive trust in MANETs. In comparison to other machine learning computational intelligence techniques, Q-learning achieves optimal results. Our work focuses on computing a score using Q-learning to weigh the trust of a particular node over associativity based routing (ABR) protocol. Thus secure and stable route is calculated as a weighted average of the trust value of the nodes in the route and associativity ticks ensure the stability of the route. Simulation results show that Q-learning based trust ABR protocol improves packet delivery ratio by 27% and reduces the route selection time by 40% over ABR protocol without trust calculation.

  16. Self-Adaptive Trust Based ABR Protocol for MANETs Using Q-Learning

    Directory of Open Access Journals (Sweden)

    Anitha Vijaya Kumar

    2014-01-01

    Full Text Available Mobile ad hoc networks (MANETs are a collection of mobile nodes with a dynamic topology. MANETs work under scalable conditions for many applications and pose different security challenges. Due to the nomadic nature of nodes, detecting misbehaviour is a complex problem. Nodes also share routing information among the neighbours in order to find the route to the destination. This requires nodes to trust each other. Thus we can state that trust is a key concept in secure routing mechanisms. A number of cryptographic protection techniques based on trust have been proposed. Q-learning is a recently used technique, to achieve adaptive trust in MANETs. In comparison to other machine learning computational intelligence techniques, Q-learning achieves optimal results. Our work focuses on computing a score using Q-learning to weigh the trust of a particular node over associativity based routing (ABR protocol. Thus secure and stable route is calculated as a weighted average of the trust value of the nodes in the route and associativity ticks ensure the stability of the route. Simulation results show that Q-learning based trust ABR protocol improves packet delivery ratio by 27% and reduces the route selection time by 40% over ABR protocol without trust calculation.

  17. The local enhancement conundrum: in search of the adaptive value of a social learning mechanism.

    Science.gov (United States)

    Arbilly, Michal; Laland, Kevin N

    2014-02-01

    Social learning mechanisms are widely thought to vary in their degree of complexity as well as in their prevalence in the natural world. While learning the properties of a stimulus that generalize to similar stimuli at other locations (stimulus enhancement) prima facie appears more useful to an animal than learning about a specific stimulus at a specific location (local enhancement), empirical evidence suggests that the latter is much more widespread in nature. Simulating populations engaged in a producer-scrounger game, we sought to deploy mathematical models to identify the adaptive benefits of reliance on local enhancement and/or stimulus enhancement, and the alternative conditions favoring their evolution. Surprisingly, we found that while stimulus enhancement readily evolves, local enhancement is advantageous only under highly restricted conditions: when generalization of information was made unreliable or when error in social learning was high. Our results generate a conundrum over how seemingly conflicting empirical and theoretical findings can be reconciled. Perhaps the prevalence of local enhancement in nature is due to stimulus enhancement costs independent of the learning task itself (e.g. predation risk), perhaps natural habitats are often characterized by unreliable yet highly rewarding payoffs, or perhaps local enhancement occurs less frequently, and stimulus enhancement more frequently, than widely believed.

  18. The added value of a gaming context and intelligent adaptation for a mobile application for vocabulary learning

    NARCIS (Netherlands)

    Sandberg, J.; Maris, M.; Hoogendoorn, P.

    2014-01-01

    Two groups participated in a study on the added value of a gaming context and intelligent adaptation for a mobile learning application. The control group worked at home for a fortnight with the original Mobile English Learning application (MEL-original) developed in a previous project. The experimen

  19. The Link between Age, Career Goals, and Adaptive Development for Work-Related Learning among Local Government Employees

    Science.gov (United States)

    Tones, Megan; Pillay, Hitendra; Kelly, Kathy

    2011-01-01

    More recently, lifespan development psychology models of adaptive development have been applied to the workforce to investigate ageing worker and lifespan issues. The current study uses the Learning and Development Survey (LDS) to investigate employee selection and engagement of learning and development goals and opportunities and constraints for…

  20. Implementation of an Automated Grading System with an Adaptive Learning Component to Affect Student Feedback and Response Time

    Science.gov (United States)

    Matthews, Kevin; Janicki, Thomas; He, Ling; Patterson, Laurie

    2012-01-01

    This research focuses on the development and implementation of an adaptive learning and grading system with a goal to increase the effectiveness and quality of feedback to students. By utilizing various concepts from established learning theories, the goal of this research is to improve the quantity, quality, and speed of feedback as it pertains…