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1

Tunaoglu, Doruk. "Implementation Of A Closed-loop Action Generation System On A Humanoid Robot Through Learning By Demonstration." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/12612477/index.pdf.

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In this thesis the action learning and generation problem on a humanoid robot is studied. Our aim is to realize action learning, generation and recognition in one system and our inspiration source is the mirror neuron hypothesis which suggests that action learning, generation and recognition share the same neural circuitry. Dynamic Movement Primitives, an efficient action learning and generation approach, are modified in order to fulfill this aim. The system we developed (1) can learn from multiple demonstrations, (2) can generalize to different conditions, (3) generates actions in a closed-loop and online fashion and (4) can be used for online action recognition. These claims are supported by experiments and the applicability of the developed system in real world is demonstrated through implementing it on a humanoid robot.
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Du, Plessis Linda Alida. "'n Onderrigmodel vir die aanwending van tegnologie by die implementering van aksieleer in die vak inligtingstelsels / Linda Alida du Plessis." Thesis, Potchefstroom University for Christian Higher Education, 2002. http://hdl.handle.net/10394/9095.

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In this study, the integration of technology in education and the application of action learning as a teaching strategy, are investigated through a literature study and with empirical research. The purpose is to develop a teaching model wherein technology can be effectively incorporated for the offering of the subject Information Systems (IS). The study also focuses on the nature and scope of the subject Information Systems, as well as the status concerning the subject Information Systems at Technikons in South Africa. Knowledge regarding technology quickly becomes obsolete and therefore IS-learners should have the means and skills to keep abreast of advances in technology. IS-learners not only need subject oriented knowledge, but also personal skills that are known as critical cross field outcomes in the new educational paradigm. The establishment of the National Qualification framework, led to an academic initiative that is based on transparent national standards and clear descriptions of learning outcomes. For higher education institutions in South Africa the implication was that all curricula of subjects, including Information Systems, had to be rewritten in terms of outcomes. Specialisation is essential for the Information System qualification, as it became apparent that information system applications and demands from industry are becoming specialised. In 1999 the IS-qualification was adjusted to provide for specialisation areas at Technikons in South Africa. Action learning integrates the theories and characteristics of several disciplines, amongst others, education, psychology, systems thinking, political science, ethics, anthropology and sociology. During the process of action learning, knowledge must be constructed by asking questions, processing information and applying the newly acquired knowledge. Links must be established between new knowledge and pre-knowledge. Action learning attempts to integrate the elements of knowledge, insight and practice, and states that there can be no learning without action and that no purposeful action can take place without learning, while the solving of a problem influences both the problem and the person that acts on the problem. Action learning satisfies all the requirements needed to address the knowledge, values, skills and behaviour that IS-learners should adhere to. Action learning stimulates the development of cognitive skills that are essential for the training ofiS-learners. The different types of information systems that are found in organisations are not isolated systems, but rather integrated systems that collaborate in order to support a business function. IS-learners should not only understand the development, but also the integration and implementation of these systems. From this it becomes apparent that action learning is a suitable teaching strategy for IS-learners. The classification of educational technology as well as a framework for the implementation thereof, is discussed in the study. According to the literature study and from results obtained from the empirical research, a teaching model is proposed that consists of the following three components: • Determinants that influence the teaching and learning scenario. These determinants include the National Qualification framework industry; technology infrastructure; institutional policy and outcomes based education. • The didactic triangle, in which the distinct roles of the learners (that can act as facilitators during action learning) and educators are discussed, as well as the outcomes for the subject Information Systems. • Action learning and the utilisation of technology as the teaching strategy within the proposed model. The proposed action learning and technology teaching model promotes a learner-centred approach and focuses on learning outcomes, rather than learning contents. The proposed model empowers learners as well as educators and makes provision for the use of technology within the financial constraints of institutions.
Thesis (Ph.D. (Education))--Potchefstroom University for Christian Higher Education, 2003
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Deprez, Stefan Gert Marie. "Towards monitoring that makes sense : action research design of a planning, learning and accountability system for a sustainable agriculture programme in Eastern Indonesia." Thesis, Rhodes University, 2011. http://hdl.handle.net/10962/d1003686.

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This study is an account of an action research process to develop a planning, learning and accountability (PLA) system for the sustainable agriculture chain development programme of VECO (Vredeseilanden Country Office) Indonesia. Many monitoring and evaluation (M&E) processes in development programmes are largely carried out to provide information for funding agencies, to meet external accountability requirements and for symbolic protection. This study generates insights into an integrated, learning-oriented monitoring practice which fosters reflective practice, provides feedback to programme stakeholders about performance, progress and results achieved, facilitates improved accountability, and generates information and knowledge useful for the programme stakeholders to take decisions for improved action. It is argued that M&E systems have the potential, if developed well, to serve as a framework or ‘carrier’ for organisational and institutional learning – an essential requirement to respond to the complex nature of development processes. Outcome mapping is presented as a possible approach to be used as the basis for such a M&E system. This study was underpinned by a socially critical orientation to development (programmes) and by an action research method to guide the PLA system design process. The design process was organized around seven steps - which in themselves were a result of the action research process – including specific steps to ensure a learning-oriented M&E system. Based on the agreed purposes and intended uses of the monitoring and learning process, the resulting PLA system is focused around the organizational spaces and rhythms of VECO Indonesia which are central to sharing, debate, learning and decision-making. In this way, the PLA system becomes integral to the thinking and doing of the organization. It is built on the premise that monitoring does not end with gathering data; it also needs to include a process of understanding and deciding how data can best be used and analysed to strengthen concerted action and facilitate decision-making. It highlights the importance of sense-making – interpreting information to make it usable for action. Furthermore, it incorporates an approach to assess and consciously plan for the creation of the necessary organisational conditions to implement and maintain a learning-oriented M&E system. The study is completed by critical reflection on the relevance of VECO’s new PLA system for planning, learning and accountability, combined with the use of a future scenario technique to generate recommendations and identify critical future directions. Further exploration of ‘intelligent’ information-seeking methods and processes is called for; and a practice which moves beyond intra-organisational monitoring – focusing on VECO’s own monitoring needs – towards a monitoring process that facilitates change based on the viewpoints of, and in collaboration with local actors, i.e., institutional monitoring and learning, is recommended. VECO is encouraged to continue developing a mindset and practice whereby the programme team and partners have the ability to leave the safe zone of pre-determined outcomes and actions, and to make sense of the world as they engage in action.
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Smaill, Christopher Raymond. "Online Assessment System with Integrated Study (OASIS) to enhance the learning of Electrical Engineering students: an action research study." Curtin University of Technology, Science and Mathematics Education Centre, 2006. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=16885.

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World-wide, there has been a large increase in tertiary student numbers, not entirely matched by funding increases. Consequently, instructors are faced with large, diverse classes, and find themselves struggling to provide adequate assessment and prompt feedback, two quantities critical in an effective learning environment. Personal computers and the Internet can help solve this problem. The aim of this study was to develop, implement and validate a Web-based software package that, through providing practice and assessment opportunities, improved student learning and reduced marking and related mundane aspects of instructor workload. At the start of the study, such a package already existed in prototype form: OASIS (Online Assessment System with Integrated Study). As the study progressed, this software package was first fully rewritten and then repeatedly modified. OASIS delivers individualised tasks, marks student responses, supplies prompt feedback, and logs student activity. Staff can deliver sets of practice questions and assessments to students: assessments may involve different questions for different students, not just numerically different versions of the same questions. Given my role as teacher, the traditional research ideal of observing without affecting the research environment was both impossible and unconscionable. In particular, since preliminary evidence suggested that OASIS did enhance student learning, I could not adopt a ‘two groups’ approach to the research, with one group using OASIS while the other did not. Instead, an action research methodology was seen as most appropriate for my double role of teacher and researcher.
This methodology enabled me, in the light of my findings, to continuously modify the learning environment and enhance student learning. The action research proceeded through a spiral of one-semester cycles of planning, acting, observing and reflecting. To maximize rigour, the research ran through eight cycles over four years and involved considerable triangulation. OASIS itself collected much quantitative data. Further data were collected via interview, survey, email and informal discussion from three groups: current students, postgraduates and academics. My colleagues provided alternative perceptions and interpretations, as did Physics Department academics who were using OASIS, and an external academic who interviewed academics and investigated the implementation of OASIS. Perhaps surprisingly, academics had generally adopted OASIS to promote student learning rather than to decrease their own workloads. In some cases workloads were reduced; however, where OASIS assessments augmented rather than replaced existing traditional assessments, workloads actually went up slightly. All instructors who used OASIS reported enhanced student learning and wished to continue using it. Student surveys, interviews, focus-group discussions and informal feedback showed that students found the software easy to use and considered that it helped them improve their skills and understanding. OASIS questions were preferred over textbook questions. Students commonly requested OASIS to be available in more of their areas of study. In general students wanted hints or model answers though some argued against their provision.
The majority of students were enthusiastic about the use of OASIS for practice, and activity logs revealed that they did use OASIS extensively. These logs also revealed the motivating power of assessments: typically half the online practice activity took place in the last 36 hours prior to assessments. Interviews provided further interesting insights into the ways different students approached their studies and assessments. However, students did voice concerns about the validity of OASIS assignments, noting their peers could rely on the efforts of others to score highly in these. A number of steps were carried out in an attempt to defuse these concerns, including: disabling OASIS practice during assignments, basing assignments on previously unseen questions, and providing different assignment questions to different students. While this study has achieved the goal of developing, implementing and validating OASIS, many future opportunities exist. OASIS may be used in schools as well as universities. Non-numerical questions, where answers may be somewhere between right and wrong, are possible. OASIS can also be used to deliver concept inventories to students to support research into concept acquisition and retention.
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Lee, Yiu Man. "A sociotechnical system approach for enhancing the dynamic capabilities of an organisation : a participatory action research in the manufacturing industry in mainland China /." access full-text access abstract and table of contents, 2009. http://libweb.cityu.edu.hk/cgi-bin/ezdb/thesis.pl?engd-meem-b23750959f.pdf.

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Thesis (Eng.D.)--City University of Hong Kong, 2009.
"Submitted to Department of Manufacturing Engineering and Engineering Management in partial fulfillment of the requirements for the degree of Engineering Doctorate." Includes bibliographical references (leaves 150-170)
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6

Cao, Wen. "Exploring an action research process of multimodal learning system design for online learners of English language education in a Chinese university." Thesis, University of Nottingham, 2010. http://eprints.nottingham.ac.uk/11850/.

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This thesis is my professional autobiography that records an action research process of three full cycles ranging from 2004 to 2006. I follow a narrative style and a first person perspective to present this process in loyalty to the action research nature and my research reality. I work at an online institute (the Institute) of a Chinese university and I am responsible for course design and development of degree-bearing courses in English language education via online delivery to learners nationwide. My job is contextualized in a situation in China where online course design and development booms in practice, yet it lacks theoretical guidelines, quality research with responsive approaches and staff with professional identity and practice. I started my research in 2004 with a mono-commitment -- a real-situation task of adapting the courseware of an "orientation” module of a post-diploma BA course in English language education. I worked alone as both a researcher and a practitioner, only to find that the task involved more than just courseware design - it dealt with subject matter in that online course design and development was a process as well as a product that aimed at the construction of a learning system (the "What" issue); it also dealt with a methodological issue of selecting a research approach that could accommodate my research need and situation (the "How" issue). I started my second research cycle in 2005 with dual commitments – the exploration of instructional design as a subject matter guideline and action research as a responsive research methodology. I led a team of 3 tutor-researchers and 15 learner-researchers through a process of "plan -- act -- analyze and reflect” during the design, development, implementation and evaluation phases of the "orientation" module. Two issues emerged from this research cycle. One was that there existed four major tensions between instructional design and the learners' reality: time design, media selection, support design in relation to interaction and group learning, and assessment design. The other was that action research could be applied as an effective approach to professional development. I conducted my third research cycle in 2006 with tri-commitments – professional development (the "Who" issue) of 12 new staff at the Institute in addition to a further exploration of instructional design (the "What" issue) and action research (the "How" issue). This research cycle revealed that the interventional strategies worked to some extent, but some issues persisted and new issues emerged. Among them, the tensions between instructional design and the learners' reality, and the multi-faceted context of the research were repeatedly recognized. The three research cycles have informed my further research to establish a paradigmatic and practical framework that can integrate the "What", the "How" and the "Who" issues. This framework is termed multimodal learning system design that adopts a design, learning, multimodal and ecological view to guide a cyclical process that involves a community of practice in inquiry and reflection as well as all the major stakeholders (e.g. designers, tutors, administrators and learners) and a product that creates a learning system. This framework is valued for its responsiveness to sustainable improvements and changes in the online education field full of innovation and challenges in theory, research and professionalism.
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Kalinga, Ellen. "Development of an Interactive e-Learning Management System (e-LMS) for Tanzanian Secondary Schools." Licentiate thesis, Karlskrona : Blekinge Institute of Technology, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-00404.

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e-learning, as defined to be the use of information and communications technology (ICT) for supporting the educational processes, has motivated Tanzania to apply ICT in its education system. Tanzania secondary schools in rural areas are geographically and socially isolated. Rural Tanzania secondary schools face a number of problems including ways in getting learning materials, as well as inadequacy in qualified teachers. The impact of these problems is poor performance in National Examinations. This poor performance however is highly noted in science and mathematics subjects. The problem in getting learning materials can be reduced by employing ICT in secondary school education system. This research develops an interactive e-learning management system (e-LMS) to be used by Tanzanian secondary schools. The research is aiming to support teaching and learning functions by allowing creation and storage of learning materials, making them available, easily accessed and sharable among students from different secondary schools in Tanzania in a more organized way. Tanzania has only one curriculum for all secondary schools registered under the Ministry of Education and Vocational Training (MoEVT). During development stage it will not be easy to involve all scattered Tanzanian secondary schools. The research is focusing to two selected pilot schools; Kibaha secondary school and Wali-ul-Asr girls’ seminary in Kibaha town, Pwani region. Features of the e-LMS will represent the standard form of any other secondary school registered by the MoEVT. The complete implementation of the e-LMS to these selected pilot schools will later be extended to all other secondary schools in Tanzania. The development uses Object-Oriented System Analysis and Design (OOSAD) approach along with the power of modeling as it has been emphasized by Model Driven Architecture (MDA). Unified Modeling Language (UML) is mainly used in both cases. To create an interoperable system, UML is integrated with extensible markup language (XML) during model transformation from e-LMS Platform Independent Model (PIM) to e-LMS Platform Specific Model (PSM). Development will make use of open source software. For context specific development, participatory action research methodology is adopted and the inputs are well presented in developing e-LMS. Customization of open source learning management system (LMS) platforms is employed to help generate a timely solution to e-LMS development. Finally, this thesis also considers the need for replication and mirroring of the database for the purpose of making learning materials highly available to end-users.
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Chatzistratidi, Fotini. "Wikis in High Schools: an example of using Wikis for the Project course in Greek High Schools." Thesis, Linnéuniversitetet, Institutionen för informatik (IK), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-47352.

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The use of ITs in education has created new opportunities for learning and has introduced new ways for knowledge acquisition. Web 2.0 technology presents a variety of tools that can support learning procedure in all levels of Education. Wikis constitute one of the most widespread tools that support cooperation and Project-based learning. This study examines the possibility of a wider use of Wikis for the “Project”, a course that has been taught in Greek High Schools for the last four years. Recently the Greek Ministry of Education attempted to make a shift from traditional learning methods to modern teaching ways that use ITs in all level of education. “Project” course constitutes a pilot course for this attempt and follows new innovating ways of learning. The course has an interdisciplinary character and aims to exploit the benefits of the Project-based learning and to enhance students to cooperation and interaction. The research explores the way that Wikis could support the basic aims of the course and the circumstances under which learners and teachers could be motivated for this use. This qualitative study was conducted in the 1st Lyceum of Eleusis, “Aristoteleio”, and followed the Action-oriented Research approach. The research included interviews with five teachers and a focus group of students. The main outcomes showed that important changes in the Greek Educational system should be done in order for this use to be enhanced.
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Byadarhaly, Kiran. "A Neuro-dynamical model of Synergistic Motor Control." University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1384426521.

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Dam, Hai Huong Information Technology &amp Electrical Engineering Australian Defence Force Academy UNSW. "A scalable evolutionary learning classifier system for knowledge discovery in stream data mining." Awarded by:University of New South Wales - Australian Defence Force Academy, 2008. http://handle.unsw.edu.au/1959.4/38865.

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Data mining (DM) is the process of finding patterns and relationships in databases. The breakthrough in computer technologies triggered a massive growth in data collected and maintained by organisations. In many applications, these data arrive continuously in large volumes as a sequence of instances known as a data stream. Mining these data is known as stream data mining. Due to the large amount of data arriving in a data stream, each record is normally expected to be processed only once. Moreover, this process can be carried out on different sites in the organisation simultaneously making the problem distributed in nature. Distributed stream data mining poses many challenges to the data mining community including scalability and coping with changes in the underlying concept over time. In this thesis, the author hypothesizes that learning classifier systems (LCSs) - a class of classification algorithms - have the potential to work efficiently in distributed stream data mining. LCSs are an incremental learner, and being evolutionary based they are inherently adaptive. However, they suffer from two main drawbacks that hinder their use as fast data mining algorithms. First, they require a large population size, which slows down the processing of arriving instances. Second, they require a large number of parameter settings, some of them are very sensitive to the nature of the learning problem. As a result, it becomes difficult to choose a right setup for totally unknown problems. The aim of this thesis is to attack these two problems in LCS, with a specific focus on UCS - a supervised evolutionary learning classifier system. UCS is chosen as it has been tested extensively on classification tasks and it is the supervised version of XCS, a state of the art LCS. In this thesis, the architectural design for a distributed stream data mining system will be first introduced. The problems that UCS should face in a distributed data stream task are confirmed through a large number of experiments with UCS and the proposed architectural design. To overcome the problem of large population sizes, the idea of using a Neural Network to represent the action in UCS is proposed. This new system - called NLCS { was validated experimentally using a small fixed population size and has shown a large reduction in the population size needed to learn the underlying concept in the data. An adaptive version of NLCS called ANCS is then introduced. The adaptive version dynamically controls the population size of NLCS. A comprehensive analysis of the behaviour of ANCS revealed interesting patterns in the behaviour of the parameters, which motivated an ensemble version of the algorithm with 9 nodes, each using a different parameter setting. In total they cover all patterns of behaviour noticed in the system. A voting gate is used for the ensemble. The resultant ensemble does not require any parameter setting, and showed better performance on all datasets tested. The thesis concludes with testing the ANCS system in the architectural design for distributed environments proposed earlier. The contributions of the thesis are: (1) reducing the UCS population size by an order of magnitude using a neural representation; (2) introducing a mechanism for adapting the population size; (3) proposing an ensemble method that does not require parameter setting; and primarily (4) showing that the proposed LCS can work efficiently for distributed stream data mining tasks.
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Ramos, Gabriel de Oliveira. "Regret minimisation and system-efficiency in route choice." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2018. http://hdl.handle.net/10183/178665.

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Aprendizagem por reforço multiagente (do inglês, MARL) é uma tarefa desafiadora em que agentes buscam, concorrentemente, uma política capaz de maximizar sua utilidade. Aprender neste tipo de cenário é difícil porque os agentes devem se adaptar uns aos outros, tornando o objetivo um alvo em movimento. Consequentemente, não existem garantias de convergência para problemas de MARL em geral. Esta tese explora um problema em particular, denominado escolha de rotas (onde motoristas egoístas deve escolher rotas que minimizem seus custos de viagem), em busca de garantias de convergência. Em particular, esta tese busca garantir a convergência de algoritmos de MARL para o equilíbrio dos usuários (onde nenhum motorista consegue melhorar seu desempenho mudando de rota) e para o ótimo do sistema (onde o tempo médio de viagem é mínimo). O principal objetivo desta tese é mostrar que, no contexto de escolha de rotas, é possível garantir a convergência de algoritmos de MARL sob certas condições. Primeiramente, introduzimos uma algoritmo de aprendizagem por reforço baseado em minimização de arrependimento, o qual provamos ser capaz de convergir para o equilíbrio dos usuários Nosso algoritmo estima o arrependimento associado com as ações dos agentes e usa tal informação como sinal de reforço dos agentes. Além do mais, estabelecemos um limite superior no arrependimento dos agentes. Em seguida, estendemos o referido algoritmo para lidar com informações não-locais, fornecidas por um serviço de navegação. Ao usar tais informações, os agentes são capazes de estimar melhor o arrependimento de suas ações, o que melhora seu desempenho. Finalmente, de modo a mitigar os efeitos do egoísmo dos agentes, propomos ainda um método genérico de pedágios baseados em custos marginais, onde os agentes são cobrados proporcionalmente ao custo imposto por eles aos demais. Neste sentido, apresentamos ainda um algoritmo de aprendizagem por reforço baseado em pedágios que, provamos, converge para o ótimo do sistema e é mais justo que outros existentes na literatura.
Multiagent reinforcement learning (MARL) is a challenging task, where self-interested agents concurrently learn a policy that maximise their utilities. Learning here is difficult because agents must adapt to each other, which makes their objective a moving target. As a side effect, no convergence guarantees exist for the general MARL setting. This thesis exploits a particular MARL problem, namely route choice (where selfish drivers aim at choosing routes that minimise their travel costs), to deliver convergence guarantees. We are particularly interested in guaranteeing convergence to two fundamental solution concepts: the user equilibrium (UE, when no agent benefits from unilaterally changing its route) and the system optimum (SO, when average travel time is minimum). The main goal of this thesis is to show that, in the context of route choice, MARL can be guaranteed to converge to the UE as well as to the SO upon certain conditions. Firstly, we introduce a regret-minimising Q-learning algorithm, which we prove that converges to the UE. Our algorithm works by estimating the regret associated with agents’ actions and using such information as reinforcement signal for updating the corresponding Q-values. We also establish a bound on the agents’ regret. We then extend this algorithm to deal with non-local information provided by a navigation service. Using such information, agents can improve their regrets estimates, thus performing empirically better. Finally, in order to mitigate the effects of selfishness, we also present a generalised marginal-cost tolling scheme in which drivers are charged proportional to the cost imposed on others. We then devise a toll-based Q-learning algorithm, which we prove that converges to the SO and that is fairer than existing tolling schemes.
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Barroy, Willy. "L’hybridation du dispositif de formation d’Airbus Helicopters face aux technologies immersives : des enjeux d’apprentissage individuel et organisationnel." Thesis, Toulon, 2018. http://www.theses.fr/2018TOUL0002.

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L’objet de cette recherche porte sur l’évolution des dispositifs de formation avec l’introduction de technologies de réalité virtuelle dans des contextes industrialisés. Cette thèse Cifre s’appuie sur une intégration au sein du département « training » d’Airbus Helicopters. La démarche de recherche-action mise en œuvre permet d’observer et de participer à l’élaboration d’une technologie immersive pour la formation de pilotes. Cet outil est mis en situation avec des clients en formation et plusieurs démonstrations sont faites auprès d’acteurs de différents métiers. Nous mettons en avant des configurations hybrides dans le sens ou les situations de formation révèlent des aspects de la pratique et de la théorie telles qu’elles sont pensées dans la « langue de l’organisation ». Nous montrons alors que la mise en œuvre de telles technologies pourrait remettre en question les modèles rationalisés dans l’organisation. Ces éléments nous permettent d’envisager qu’une « approche par l’hybridation des dispositifs » amène l’organisation à interroger à chaque étape du projet ses propres modèles (objets structurés de partage d’information, organigramme, compétences et métiers des acteurs). C’est alors une remise en question en « profondeur » du projet de l’organisation apprenante qui est rendue possible, à partir de l’expérience des sujets
The purpose of this research is to better understand how training devices evolve, with the introduction of virtual reality technology, in industrialized training situations. This work I based on an immersion in the "training" department of Airbus Helicopters. The research-action approach allows us to observe and participate in the emergence of a technology of reality for pilot’s training. The tool is put in situation with customers as part of their training and several demonstrations are made to actors of different trades around the training. We identify hybrid configurations in the sense that training situations are both practical and at the same time theoretical in the language of the organization. Then we show that the implementation of these technologies requires to rethink a traditional rationalization. These elements allow to suggest an "approach by the hybridization of systems" gives the organization the ability to reconsider its own project (structured objects of information, organization chart, skills and trades of actors). It is a depth questioning of the learning organization that is possible, from the experience of subjects
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Le, roy Dimitri. "L’interdisciplinarité scolaire en question : analyse de l’activité de l’enseignant et des perceptions des élèves en Éducation Physique et Sportive." Thesis, Rennes 2, 2020. http://www.bu.univ-rennes2.fr/system/files/theses/2020theseLeRoyD.pdf.

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L’objectif de cette thèse est d’analyser, avec une double visée épistémique et transformative, l’activité d’enseignants d’EPS dans des dispositifs interdisciplinaires — leurs actions, focalisations, préoccupations et connaissances typiques — au prisme de la perception des élèves. Ce travail s’inscrit dans le cadre théorique et méthodologique du cours d’action (Theureau, 2004, 2006). Trois dispositifs interdisciplinaires ont été étudiés : un premier, à la croisée de l’EPS, de la technologie et des mathématiques, finalisé par la création d’applications Androïd © ; un second, entre l’EPS et le français au sein duquel les élèves vivent et communiquent sur différents types d’émotions vécues dans des activités de pleine nature et un troisième dans lequel les élèves créent un tutoriel en anglais sur un programme de renforcement musculaire de leur choix. À partir de l’analyse des différentes données recueillies (leçons d’EPS, entretiens d’autoconfrontation et notes ethnographiques), les résultats mettent en évidence (1) les actions, focalisations, préoccupations et connaissances typiques des enseignants lors des moments transversaux (2) les formes, fonctions et finalités éducatives des croisements disciplinaires mis en œuvre par les enseignants (3) les temporalités de moments transversaux à l’échelle de la leçon et de la séquence d’enseignement et (4) les corrélations et divergences existantes entre les finalités éducatives envisagés par les enseignants d’EPS et leur perception par les élèves. Ces résultats sont discutés au regard des connaissances déjà présentes sur cette thématique dans la littérature scientifique ; mais également selon une visée transformative afin que les enseignants et futurs enseignants souhaitant s’engager dans des dispositifs transversaux puissent trouver des pistes de propositions pour gagner en efficacité dans leurs pratiques quotidiennes
The aim of this thesis is to analyze, with both an epistemic and transformative goal, the PE teachers’ activity in interdisciplinary devices — their actions, focus, preoccupations and typical knowledge — versus students’ perceptions of it. This work is conducted within the theoretical and methodological framework of the course of action (Theureau, 2004, 2006). Three interdisciplinary devices have been studied : the first, at the junction of PE, Technology and Mathematics, finalized by the creation of Android © applications ; the second, alternates between PE and French literature in which students live and communicate on different kinds of emotions experienced in open-air physical and sports activities, and the third in which students create an English tutorial on a muscle building strengthening exercises of their choice. From the analysis of the various data collected (PE lessons, self-confrontation interviews and ethnographic notes), results highlight (1) teachers’ actions, focus, preoccupations and typical knowledge during transversal moments; (2) cross-curricularism’s forms, functions and educational finalities carried out by teachers; (3) temporalities of the transversal moments on the scale of lesson and teaching sequence; and (4) correlations and divergences between the intended educational finalities of the PE teacher and the students’ perceptions. These results are discussed in view of the knowledge already exists about this thematic in the scientific literature; but also in a transformative aim, so that teachers and future teachers wishing to engage in transversal devices can find clues to become more efficient in their daily practices
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Lorek, Maria. "Pôles de croissance et reconversion des territoires industriels dans une nouvelle économie de marché : Étude appliquée au cas de l'économie de Gdansk (Pologne)." Thesis, Littoral, 2013. http://www.theses.fr/2013DUNK0503.

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Depuis la libéralisation économique, les pôles de croissance construits sous la tutelle de l’État ont connu des transformations institutionnelles et organisationnelles majeures dans les pays centralement planifiés. Les nouvelles formes d’organisation industrielle, qui sont à l’origine de ces transformations, donnent la priorité aux logiques territoriales. Les économies locales, sous-estimées pendant l’économie centralement planifiée, sont devenues des espaces prioritaires d’application de la politique économique. Dans ce contexte, les travaux sur les districts industriels, les milieux innovateurs, les clusters retrouvent un regain d’intérêt. En revanche, la question de la reconversion des pôles de croissance par la libéralisation économique demeure nettement peu explorée en termes d’impact sur le développement de l’innovation dans les ex-pays centralement planifiés. L’impact de la libéralisation économique des pays centralement planifiés se manifeste par les nouvelles pratiques de coopération, du partage et des actions collectives s’inscrivent dans le cadre de la « nouvelle » économie de marché. La convergence des intérêts publics et privés qui en découlent et l’émergence de l’apprentissage collectif jouent un rôle essentiel pour le développement de l’innovation. Les études théoriques sur les pôles de croissance ne prennent pas en considération ces transformations, elles restent concentrées sur le rôle des industries motrices qui sont capables d’entraîner les autres composantes du système productif grâce à leur dimension ou à la productivité. Pourtant, la réalité économique approuve que les pôles de croissance se soient transformés en appuyant sur l’articulation entre les différents acteurs de proximité, des ressources spécifiques locales, des rapports développés sur le marché et hors marché et la mise en place de l’innovation. Pour décrire les capacités innovantes des acteurs locaux, nous proposons un concept du système d’innovation territorialisé. À partir de cette analyse découle l’intérêt de cibler l’étude sur un pôle de croissance en particulier. L’histoire économique, la mise en place de la nouvelle politique économique locale (après 1989), les choix des autorités locales, la croissance notable bien qu’émergente du secteur de haute technologie et l’absence d’étude antérieure sur cette question sont autant de facteurs qui font de la région de Gdansk un cas intéressant pour analyser dans quelle mesure la libéralisation économique a été une incitation au développement de l’innovation sur son territoire. À cet effet, nous analysons le potentiel de l’innovation de la région de Gdansk qui se forge au cours de l’instauration de l’économie de marché en Pologne, d’abord à travers une analyse statistique de l’économie de Gdansk depuis la fin de la Seconde Guerre mondiale pour donner un aperçu sur l’ensemble des conditions initiales. Puis, à travers l’étude des données des enquêtes réalisées par le bureau statistique national (GUS) que nous mobilisons pour compléter notre analyse et présenter le potentiel de l’innovation de la région de Gdansk. À l’issue de l’analyse empirique découle que la libéralisation a contribué au développement de l’innovation dans la région de Gdansk en favorisant d’abord, l’accumulation des actifs secondaires, ensuite, l’amélioration de son potentiel scientifique et technique et afin d’encourager l’émergence des entreprises innovantes. Ces dernières sont issues d’un processus de destruction créatrice qui a permis le renouveau du tissu productif local. L’ensemble des résultats permet d’approuver que la région de Gdansk au cours de sa reconversion a subi des changements institutionnels, économiques et sociaux qui l’ont transformé en système d’innovation territorialisé. Ce système est le résultat de l’articulation entre l’action des autorités locales et les activités des acteurs privés susceptibles d’innover
Since economic liberalization, growth poles constructed under the State’s supervision have seen major institutional and organizational changes in the centrally planned economies. New forms of industrial organization that are responsible for these changes, gives priority to the territorial logic. The local economy which was underestimated during the centrally planned economies has become a main area for the application of the economic policy. In this context, scientific studies on industrial districts, innovative milieus, clusters, have won a new revival. However, the question of the conversion of growth poles through economic liberalization remains substantially unexplored in terms of the impact on the development of innovation in the former centrally planned countries. The impact of economic liberalization in the centrally planned countries is manifested by the new practices of cooperation, sharing and collective actions in the context of the "new" market economy. The resulting convergence and emergence of collective learning public and private interests play an essential role in the development of innovation. Theoretical studies on growth poles do not take into account these changes; they only focus on the role of the main industries that are able to lead the rest of the components of the production system due to their size or productivity. However, the economic reality that supports growth poles have become based on the relationship between the different actors of proximity, specific local resources, relationships developed within and outside market and implementation of innovation. To describe the innovative capacity of local actors we propose a concept of regionalized innovation system. From this analysis comes the interest of the study focus on a singular growth pole in particular. Its economic history, the establishment of new local economic policy (after1989), the choice of local authorities, the significant growth (still emergent though) of high-tech sector and the absence of previous research on this issue, are as many factors that make the Gdansk region an interesting case study of how economic liberalization has been an incentive for the development of innovation in its territory. For this purpose, we analyze the potential of innovation in the area of Gdansk that is forged during the introduction of the market economy in Poland. First, we proceed through a statistical analysis of the economy of Gdansk since the end of the Second World War to give an overview of the set of initial conditions taken in this context. Then, we study the data issued from the surveys conducted by the National Statistical Office (GUS) in order to complete our analysis and present the potential for innovation in the area of Gdansk. The empirical analysis shows that liberalization has contributed to the development of innovation in the Gdansk region: first, by promoting the accumulation of secondary assets and second, by improving its scientific and technical potential and encouraging the emergence of innovative companies. These are derived from a process of creative destruction that has led to the revival of local production. The overall results reveal that the conversion of the Gdansk region has been associated to sustained institutional, economic and social changes that have transformed into a regionalized innovation system. This system is the result of a joint action between the local authorities and the activities of private actors likely to innovate. With this transformation the Gdansk region is still one of the poles of growth of the Polish economy based not only on its industrial potential inherited from the past but also on its potential of innovation mainly related to the development of activities of higher added value
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15

Pereira, Marcel pierre. "Tandem présentiel-distance : articulation difficile, enjeux et perspectives de mutations de l’enseignement et de l’apprentissage au Cap-Vert." Thesis, Clermont-Ferrand 2, 2014. http://www.theses.fr/2014CLF20013/document.

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Cette recherche s’inscrit dans le domaine des technologies de l’information et de la communication pour l’enseignement (Tice) et a pour objet d’étudier l’articulation du présentiel et de la distance dans le contexte capverdien. Elle vise la compréhension de cette modalité d’apprentissage hybride. Un dispositif permettant aux étudiants d’échanger et de collaborer autour de tâches collaboratives a été mis en place.Le cadre théorique fait référence au socioconstructivisme, à la communication médiée par ordinateur (CMO) et à l’écrit comme fondement de base pour cette recherche. Celle-ci a une visée compréhensive et praxéologique, l’objectif général et à terme étant d’apporter des éclairages permettant d’appréhender plus facilement les Tice en vue de les intégrer efficacement dans des formations en français autorisant l’usage des outils technologiques. La démarche que nous avons adoptée est axée sur une approche ethnométhodologique. Les données obtenues ont été analysées quantitativement et qualitativement puis, elles ont été croisées selon le principe de la triangulation (Van Der Maren, 1997).Cette recherche propose quelques éléments de réponse. L’usage des outils technologiques facilite les échanges entre les étudiants, leur permet de co-construire leur apprentissage, autorise des rétroactions sur les formes linguistiques. Elle facilite l’encadrement et l’accompagnement des étudiants. Les conditions technologiques et techniques sont également importantes
This research is in the field of information technology and communication for teaching (ITC) and aims at studying the joint-face and distance in the Cape Verdean context. It is in order to understand this form of blended learning that a device allowing students to share and collaborate around collaborative tasks has been established.The theoretical framework refers to social constructivism, communication mediated by computer (CMC) and written as basic foundation for this search. It has a comprehensive and praxeological reference, the overall objective is to provide insights for easier understanding of the ITC to effectively integrate the use of technological tools in training in teaching French. The approach we have adopted is based on an ethnomethodological approach. The data obtained were analyzed quantitatively and qualitatively, then they were crossed according to the principle of triangulation (Van Der Maren, 1997).This research provides some answers. The use of technological tools facilitates exchanges between students, allowing them to co- construct their learning, and enables feedback on linguistic forms. It also facilitates management and support to students. Technological and technical conditions are also important
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Andrianirina, Hoby. "Analyses des usages d'un dispositif hybride d’apprentissage du français et éléments pour un appui à la conception de dispositifs en contexte malgache." Thesis, Clermont-Ferrand 2, 2011. http://www.theses.fr/2011CLF20019/document.

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La recherche se situe au carrefour de la didactique des langues-cultures et de l’ALAO (Apprentissage des Langues Assistée par Ordinateur) via des dispositifs hybrides. Elle porte sur les usages des dispositifs médiatisés d’apprentissage de la langue étrangère par des apprenants non-spécialistes. Le postulat de départ est qu’une recherche sur les usages constitue un moyen pour les concepteurs d’appréhender les manières dont les apprenants s’approprient ces dispositifs. L’hypothèse émise est qu’il y a un décalage entre les usages attendus par les enseignants et les usages réels des apprenants et qu’il est pertinent, d’un point de vue didactique, de travailler sur ces décalages afin, d'une part, que les enseignants concepteurs puissent modifier les modèles d’usages en amont de la mise en œuvre du dispositif d’apprentissage et d'autre part, puissent réagir de manière plus adéquate pendant l’utilisation du dispositif par les apprenants. Cette hypothèse conduit à formuler deux questions de recherche principales. Premièrement, quels usages font les apprenants de langues étrangères des dispositifs hybrides ? Et deuxièmement, sur quels éléments des usages les concepteurs peuvent-ils s’appuyer pour la conception ou pour l’actualisation du dispositif ?La recherche est une recherche-action de type expérimental. Elle s’effectue sur deux terrains particuliers : un terrain en contexte français qui constitue le terrain d’analyse et un terrain en contexte malgache qui est le terrain de conception et d’expérimentation. Ces deux terrains présentent des points communs : public-cible constitué d’étudiants non-spécialistes de la langue et spécialistes d’autres disciplines, inscrit en première année de formation, apprentissage de la langue-cible s’effectuant à distance via une plateforme. Deux formes de données de recherche sont exploitées de ces deux terrains : des données invoquées (traces laissées par les apprenants sur la plateforme), suscitées (des questionnaires en direction des apprenants et des entretiens semi-directifs auprès des enseignants-concepteurs afin de cerner les usages prescrits). Les résultats attendus sont de trois types. Sur le plan herméneutique, la recherche permet de caractériser les usages des apprenants selon leurs modes d’interprétation et d’appropriation du dispositif. Sur le plan praxéologique, elle constitue un appui à la conception de dispositifs hybrides, par le biais de recommandations soulignant le rôle de la scénarisation, l’importance de l’articulation d’un côté, des outils mis à disposition des apprenants avec les tâches proposées et de l’autre côté, du présentiel et du distantiel dansl'hybridation. Enfin, elle participe à la promotion, à la diffusion et à l’apprentissage de la langue française en direction des étudiants malgachophones
This research work is situated at the crossroads of the didactics of Languages and Cultures and CALL (Computer-Assisted Language Learning) via blended learning courseware systems. It focuses on the learners’ usage of computer-mediated learning environments for foreign languages. The premise is that research on usage constitutes a means for course designers to apprehend the ways learners adapt to these tools. Our hypothesis is that there is a discrepancy between the usage prescribed by the teachers and the real usage made by the learners. We believe that it is therefore relevant, from a didactic perspective, to work on these discrepancies so that teacher-designers can improve their practices of these learning systems by adapting their usage models ahead of the implementation of the course setup and by reacting in a more appropriate way during the time the learners are using the tools. This hypothesis raises two main research questions. On the one hand, what use do foreign language learners make of blended learning systems? And, on the other hand, what particular information on usage will help courseware designers in the design or update of their system?The research can be described as experimental action research. This is performed in two research fields: a French context, which is the analytical field and a Malagasy context, which is the field of design and experimentation. These two fields share some common points: a target group of non-specialist language students and specialists of other disciplines enrolled in the first year of their courses and the learning of the target language taking place on a distancelearning platform. Two forms of research data are utilised in both of these fields: invoked data (learners’ traces left on the platform) and raised data (questionnaires completed by the learners and semi-guided interviews of teacher-designers in order to better understand the prescribed uses). The results are of three kinds. At the hermeneutic level, the research enables learners’ usage to be characterised according to their ways of interpreting and adapting to the system. At the praxeological level, it supports the design of courseware systems by giving advice which underlines the role of scenario design and the importance of the strategic use of the tools available to the learner for the tasks proposed. Finally, it helps promote and disseminate the French language to Malagasy students
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Husseini, Orabi Ahmed. "Multi-Modal Technology for User Interface Analysis including Mental State Detection and Eye Tracking Analysis." Thesis, Université d'Ottawa / University of Ottawa, 2017. http://hdl.handle.net/10393/36451.

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We present a set of easy-to-use methods and tools to analyze human attention, behaviour, and physiological responses. A potential application of our work is evaluating user interfaces being used in a natural manner. Our approach is designed to be scalable and to work remotely on regular personal computers using expensive and noninvasive equipment. The data sources our tool processes are nonintrusive, and captured from video; i.e. eye tracking, and facial expressions. For video data retrieval, we use a basic webcam. We investigate combinations of observation modalities to detect and extract affective and mental states. Our tool provides a pipeline-based approach that 1) collects observational, data 2) incorporates and synchronizes the signal modality mentioned above, 3) detects users' affective and mental state, 4) records user interaction with applications and pinpoints the parts of the screen users are looking at, 5) analyzes and visualizes results. We describe the design, implementation, and validation of a novel multimodal signal fusion engine, Deep Temporal Credence Network (DTCN). The engine uses Deep Neural Networks to provide 1) a generative and probabilistic inference model, and 2) to handle multimodal data such that its performance does not degrade due to the absence of some modalities. We report on the recognition accuracy of basic emotions for each modality. Then, we evaluate our engine in terms of effectiveness of recognizing basic six emotions and six mental states, which are agreeing, concentrating, disagreeing, interested, thinking, and unsure. Our principal contributions include the implementation of a 1) multimodal signal fusion engine, 2) real time recognition of affective and primary mental states from nonintrusive and inexpensive modality, 3) novel mental state-based visualization techniques, 3D heatmaps, 3D scanpaths, and widget heatmaps that find parts of the user interface where users are perhaps unsure, annoyed, frustrated, or satisfied.
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18

Grönland, Axel, and Möllerstedt Viktor Eriksson. "Robust Reinforcement Learning in Continuous Action/State Space." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-293879.

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In this project we aim to apply Robust Reinforce-ment Learning algorithms, presented by Doya and Morimoto [1],[2], to control problems. Specifically, we train an agent to balancea pendulum in the unstable equilibrium, which is the invertedstate.We investigate the performance of controllers based on twodifferent function approximators. One is quadratic, and the othermakes use of a Radial Basis Function neural network. To achieverobustness we will make use of an approach similar toH∞control, which amounts to introducing an adversary in the controlsystem.By changing the mass of the pendulum after training, we aimedto show as in [2] that the supposedly robust controllers couldhandle this disruption better than its non-robust counterparts.This was not the case. We also added a random disturber signalafter training and performed similar tests, but we were againunable to show robustness.
I detta projekt applicerar vi Robust Rein- forcement Learning (RRL) algoritmer, framtagna av Doya och Morimoto [1], [2], på reglerproblem. Målet var att träna en agent att balansera en pendel i det instabila jämviktsläget; det inverterade tillståndet. Vi undersökte prestandan hos regulatorer baserade på två value function approximators. Den ena är kvadratisk och den andra en Radial Basis Function neuralt nätverk. För att skapa robusthet så använder vi en metod som är ekvivalent med H∞ - reglering, som innebär att man introducerar en motståndare i reglersystemet. Genom att ändra pendelns massa efter träning, hoppas vi att som i [2] kunna visa att den förment robusta regulatorn klarar av denna störning bättre än sin icke-robusta mostvarighet. Detta var inte fallet. Vi lade även till en slumpmässig störsignal efter träning och utförde liknande tester, men lyckades inte visa robusthet i detta fall heller.
Kandidatexjobb i elektroteknik 2020, KTH, Stockholm
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19

Barry, Alwyn. "XCS performance and population structure in multi-step environments." Thesis, Queen's University Belfast, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326357.

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20

Windridge, David, Michael Felsberg, and Affan Shaukat. "A Framework for Hierarchical Perception–Action Learning Utilizing Fuzzy Reasoning." Linköpings universitet, Datorseende, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-85688.

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Perception-action (P-A) learning is an approach to cognitive system building that seeks to reduce the complexity associated with conventional environment-representation/action-planning approaches. Instead, actions are directly mapped onto the perceptual transitions that they bring about, eliminating the need for intermediate representation and significantly reducing training requirements. We here set out a very general learning framework for cognitive systems in which online learning of the P-A mapping may be conducted within a symbolic processing context, so that complex contextual reasoning can influence the P-A mapping. In utilizing a variational calculus approach to define a suitable objective function, the P-A mapping can be treated as an online learning problem via gradient descent using partial derivatives. Our central theoretical result is to demonstrate top-down modulation of low-level perceptual confidences via the Jacobian of the higher levels of a subsumptive P-A hierarchy. Thus, the separation of the Jacobian as a multiplying factor between levels within the objective function naturally enables the integration of abstract symbolic manipulation in the form of fuzzy deductive logic into the P-A mapping learning. We experimentally demonstrate that the resulting framework achieves significantly better accuracy than using P-A learning without top-down modulation. We also demonstrate that it permits novel forms of context-dependent multilevel P-A mapping, applying the mechanism in the context of an intelligent driver assistance system.
DIPLECS
GARNICS
CUAS
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21

Sanga, Camilius. "A technique for the evaluation of free and open source e-learning systems." Thesis, University of the Western Cape, 2010. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_6242_1306494254.

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Evaluating software is a universal and complex problem. The question is: how should software be selected and adopted, or rather, which of the software packages is the most suitable for a specific environment? Extensive research on the evaluation of software has been done, but only a few researchers have considered evaluation of e-learning systems based on three software quality characteristics (i.e. usability, maintainability and deployability) for implementation in third world countries. In this thesis, it will be considered how to use a mixed research methods for the evaluation of free and open source e-learning systems in a developing country. The scope of this investigation is the evaluation of two free and open source e-learning systems at the Open University of Tanzania using 33 stakeholders (some with more and others with less computer expertise).

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Frost, Geoff P. "Stochastic optimisation of vehicle suspension control systems via learning automata." Thesis, Loughborough University, 1998. https://dspace.lboro.ac.uk/2134/11660.

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This thesis considers the optimisation of vehicle suspension systems via a reinforcement learning technique The aim is to assess the potential of learning automata to learn 'optimum' control of suspension systems, which contain some active element under electronic control, without recourse to system models. Control optimisation tasks on full-active and senu-active suspension systems are used for the feasibility assessment and subsequent development of the learning automata technique. The quarter-vehicle simulation model, with ideal full-active suspension actuation, provides a well-known environment for initial studies applying classical discrete learning automata to learn the controller gains of a linear state-feedback controller. Learning automata are shown to be capable of acquiring near optimal controllers without any explicit knowledge of the suspension environment. However, the methodology has to be developed to allow safe on-line application. A moderator is introduced to prevent excessive suspension deviations as a result of possible unstable control actions applied during learning. A hardware trial is successfully implemented on a test vehicle fitted with semi-active suspension, excited by a hydraulic road simulation rig. During these initial studies some inherent weaknesses of the discrete automata are noted A discrete action set provides insufficient coverage of a continuous controller space so optima may be overlooked. Subsequent methods to increase the resolution of search lead to a forced convergence and hence an increased likelihood of local optima location. Th1s motivates the development of a new formulation of learning automaton, the CARLA, which exhibits a continuous action space and a reinforcement generalisation. The new method is compared w1th discrete automata on vanous stochastic function optimisatwn case stui1es, demonstrating that the new functionality of CARLA overcomes many of the identified shortcomings of discrete automata. Furthermore, CARLA shows a potential capability to learn in non-stationary environments. Repeatmg the earlier suspension tasks with CARLA applied, including an on-line hardware study, further demonstrates a performance gain over discrete automata Finally, a complex multi-goal learning task is considered A dynamic roll-control strategy is formulated based on the senu-active suspension hardware of the test vehicle. The CARLA is applied to the free parameters of this strategy and is seen to successfully synthesise improved roll-control over passive suspension.
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Thomas, Sean C. "UNDERSTANDING THE NEUROPHYSIOLOGICAL REPRESENTATION PATTERNS OF NON-VERIFIABLE MENTAL ACTION VERBS: AN ERP INVESTIGATION." Thesis, Laurentian University of Sudbury, 2014. https://zone.biblio.laurentian.ca/dspace/handle/10219/2161.

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Imaging has revealed that brain activation of verbs with verifiable products (‘throw, kick’) activate language areas as well as the motor cortex responsible for the performance of the action described. An exploratory comparison of eye related verbs with no verifiable products (‘observe’) to mouth related verbs with verifiable products (‘shout’) has revealed a similar activation pattern. Thus in order to further study mental action verbs with no verifiable products, the present two-part study used words that were suitable across two modalities (e.g. you can ‘perceive’ both through vision and audition) and compare them to themselves under differing contexts of auditory and visual verbs so as to eliminate any word characteristics differences, as well as explored the two modalities directly. The primary purpose was to delineate whether associative learning or the mirror systems theory might better account for the acquisition of this unique subclass of verbs. Results suggest that Mirror systems theory more likely accounts for the observed cognitive processing differences between the two verbs. Keywords: Verbs, language, Event-related potentials, abstract, associative learning theory, mirror systems theory.
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Szijarto, Barbara. "Mediating Social Change: Building Adaptive Learning Systems through Developmental Evaluation." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39159.

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Complex social problems are at the forefront of our awareness. We are witnessing intensifying political, social and environmental challenges and waning confidence in our ability to engineer solutions. We are also seeing a proliferation of large scale, multi-agency interventions that seek change at the level of systems, and through which actors pursue adaptive learning as a means to develop effective solutions. Proponents assert that the prediction and control on which conventional program design and evaluation are based are not available under complex conditions. They propose instead that learning through experience in a program’s own context can create more responsive, impactful and sustainable interventions. These ideas offer a potentially transformative opportunity. However, they need to be complemented with a better understanding of implementation - the ‘ways of doing things’ that bring them to life. This study focused on developmental evaluation as an example of an adaptive learning (AL) approach for the development of innovative social interventions. The study was informed by ‘sensemaking’ theories and research in organizational learning, knowledge mobilization and program evaluation. Through an exploratory lens and a mixed methods design, this study sheds light on the role of specialized intermediaries in an AL process; how the role is performed in practice; and what this implies for adaptive learning in the domain of social interventions. The study documents how an intermediary can help actors navigate recognized challenges of developing interventions under complex and dynamic conditions. The findings have implications for how an AL process is understood and implemented. They provide an empirical contribution to an emerging field of study on the design of AL systems, to support future research and real-world practice as AL approaches become mainstream.
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Roodt, June. "An exploration of learning by women in the clothing and textile industry within the context of the National Skills Development Strategy." Thesis, University of the Western Cape, 2008. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_1385_1259738338.

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This study explored the learning experiences of black working class women in the context of the National Skills Development Strategy. The research focused firstly, on how the National Skills Development Strategy facilitated women's learning and secondly, what has helped and hindered their learning and how their learning experiences related to the literature on women's learning.

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Liu, Hairong. "Student modeling in e-learning environments /." free to MU campus, to others for purchase, 2004. http://wwwlib.umi.com/cr/mo/fullcit?p1420936.

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DI, NUZZO CHIARA. "L'apprendimento motorio in persone sane e Parkinsoniane: L'effetto combinato dell'esperienza multimodale e di neurostimolazione." Doctoral thesis, Università Cattolica del Sacro Cuore, 2015. http://hdl.handle.net/10280/6211.

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L'obiettivo principale del lavoro è stato di valutare il ruolo della neurostimolazione e della multimodalità (intesa come la presentazione visiva di un modello che esegue un movimento assieme a una musica sincrona) nell’apprendimento motorio, indagando sia gli effetti sugli adulti sani sia su pazienti affetti da Morbo di Parkinson (MP). Per raggiungere tale obiettivo, sono state condotte tre ricerche sperimentali e longitudinali, utilizzando diversi strumenti, come tDCS, biofeedback e KinectTM. Partendo da una sistematica revisione della letteratura nel campo della riabilitazione neuromotoria, sono state identificate tre forme di trattamento che sembrano efficaci contro i sintomi motori del MP. Tuttavia, pur riconoscendo la loro efficacia, non sono mai stati combinati nella pratica riabilitativa: l’Action Observation Learning (basato sulla teoria del sistema dei neuroni specchio), la neurostimolazione anodica non-invasiva sulla zona motoria primaria e l'uso della musica. I risultati dimostrano un chiaro sostegno della multimodalità e della neuro stimolazione nella fase di encoding e un loro supporto nel migliorare le funzioni motorie, anche a distanza di un mese. Questo lavoro offre nuove indicazioni per lo sviluppo di approcci innovativi ed efficaci nel campo dell’apprendimento motorio.
The main objective was to assess the role of neurostimulation and multimodality (namely the presentation of a visual model together with a synchronized musical track) in motor learning, by considering both healthy adults and Parkinsonian patients (PD). In order to achieve this goal, three experimental and longitudinal studies were carried out, using different tools such as tDCS, biofeedback and KinectTM. Starting with a systematic review, three innovative approaches which seem to be effective in treating the motor symptoms of PD, were identified. However, while recognizing the effectiveness of these three promising approaches, they have never been combined: Action Observation Learning (based on the theory of mirror neuron system), the non-invasive anodal neurostimulation on the primary motor area and the use of music. The results showed a clear support of multimodality and neurostimulation during the encoding phase and in improving motor functions, even after one month. This work provides new suggestions for innovative and effective treatments in motor learning field.
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Beaugnon, Anaël. "Expert-in-the-loop supervised learning for computer security detection systems." Thesis, Paris Sciences et Lettres (ComUE), 2018. http://www.theses.fr/2018PSLEE049/document.

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L’objectif de cette thèse est de faciliter l’utilisation de l’apprentissage supervisé dans les systèmes de détection pour renforcer la détection. Dans ce but, nous considérons toute la chaîne de traitement de l’apprentissage supervisé (annotation, extraction d’attributs, apprentissage, et évaluation) en impliquant les experts en sécurité. Tout d’abord, nous donnons des conseils méthodologiques pour les aider à construire des modèles de détection supervisés qui répondent à leurs contraintes opérationnelles. De plus, nous concevons et nous implémentons DIADEM, un outil de visualisation interactif qui aide les experts en sécurité à appliquer la méthodologie présentée. DIADEM s’occupe des rouages de l’apprentissage supervisé pour laisser les experts en sécurité se concentrer principalement sur la détection. Par ailleurs, nous proposons une solution pour réduire le coût des projets d’annotations en sécurité informatique. Nous concevons et implémentons un système d’apprentissage actif complet, ILAB, adapté aux besoins des experts en sécurité. Nos expériences utilisateur montrent qu’ils peuvent annoter un jeu de données avec une charge de travail réduite grâce à ILAB. Enfin, nous considérons la génération automatique d’attributs pour faciliter l’utilisation de l’apprentissage supervisé dans les systèmes de détection. Nous définissons les contraintes que de telles méthodes doivent remplir pour être utilisées dans le cadre de la détection de menaces. Nous comparons trois méthodes de l’état de l’art en suivant ces critères, et nous mettons en avant des pistes de recherche pour mieux adapter ces techniques aux besoins des experts en sécurité
The overall objective of this thesis is to foster the deployment of supervised learning in detection systems to strengthen detection. To that end, we consider the whole machine learning pipeline (data annotation, feature extraction, training, and evaluation) with security experts as its core since it is crucial to pursue real-world impact. First, we provide methodological guidance to help security experts build supervised detection models that suit their operational constraints. Moreover, we design and implement DIADEM, an interactive visualization tool that helps security experts apply the methodology set out. DIADEM deals with the machine learning machinery to let security experts focus mainly on detection. Besides, we propose a solution to effectively reduce the labeling cost in computer security annotation projects. We design and implement an end-to-end active learning system, ILAB, tailored to security experts needs. Our user experiments on a real-world annotation project demonstrate that they can annotate a dataset with a low workload thanks to ILAB. Finally, we consider automatic feature generation as a means to ease, and thus foster, the use of machine learning in detection systems. We define the constraints that such methods should meet to be effective in building detection models. We compare three state-of-the-art methods based on these criteria, and we point out some avenues of research to better tailor automatic feature generation to computer security experts needs
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Uppströmer, Viktor, and Henning Råberg. "Detecting Lateral Movement in Microsoft Active Directory Log Files : A supervised machine learning approach." Thesis, Blekinge Tekniska Högskola, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-18337.

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Cyberattacker utgör ett stort hot för dagens företag och organisationer, med engenomsnittlig kostnad för ett intrång på ca 3,86 miljoner USD. För att minimera kostnaden av ett intrång är det viktigt att detektera intrånget i ett så tidigt stadium som möjligt. Avancerande långvariga hot (APT) är en sofistikerad cyberattack som har en lång närvaro i offrets nätverk. Efter attackerarens första intrång kommer fokuset av attacken skifta till att få kontroll över så många enheter som möjligt på nätverket. Detta steg kallas för lateral rörelse och är ett av de mest kritiska stegen i en APT. Syftet med denna uppsats är att undersöka hur och hur väl lateral rörelse kan upptäckas med hjälp av en maskininlärningsmetod. I undersökningen jämförs och utvärderas fem maskininlärningsalgoritmer med upprepad korsvalidering följt av statistisk testning för att bestämma vilken av algoritmerna som är bäst. Undersökningen konkluderar även vilka attributer i det undersökta datasetet som är väsentliga för att detektera laterala rörelser. Datasetet kommer från en Active Directory domänkontrollant där datasetets attributer är skapade av korrelerade loggar med hjälp av datornamn, IP-adress och användarnamn. Datasetet består av en syntetisk, samt, en verklig del vilket skapar ett semi-syntetiskt dataset som innehåller ett multiklass klassifierings problem. Experimentet konkluderar att all fem algoritmer klassificerar rätt med en pricksäkerhet (accuracy) på 0.998. Algoritmen RF presterar med den högsta f-measure (0.88) samt recall (0.858), SVM är bäst gällande precision (0.972) och DT har denlägsta inlärningstiden (1237ms). Baserat på resultaten indikerar undersökningenatt algoritmerna RF, SVM och DT presterar bäst i olika scenarier. Till exempel kan SVM användas om en låg mängd falsk positiva larm är viktigt. Om en balanserad prestation av de olika prestanda mätningarna är viktigast ska RF användas. Undersökningen konkluderar även att en stor mängd utav de undersökta attributerna av datasetet kan bortses i framtida experiment, då det inte påverkade prestandan på någon av algoritmerna.
Cyber attacks raise a high threat for companies and organisations worldwide. With the cost of a data breach reaching $3.86million on average, the demand is high fora rapid solution to detect cyber attacks as early as possible. Advanced persistent threats (APT) are sophisticated cyber attacks which have long persistence inside the network. During an APT, the attacker will spread its foothold over the network. This stage, which is one of the most critical steps in an APT, is called lateral movement. The purpose of the thesis is to investigate lateral movement detection with a machine learning approach. Five machine learning algorithms are compared using repeated cross-validation followed statistical testing to determine the best performing algorithm and feature importance. Features used for learning the classifiers are extracted from Active Directory log entries that relate to each other, with a similar workstation, IP, or account name. These features are the basis of a semi-synthetic dataset, which consists of a multiclass classification problem. The experiment concludes that all five algorithms perform with an accuracy of 0.998. RF displays the highest f1-score (0.88) and recall (0.858), SVM performs the best with the performance metric precision (0.972), and DT has the lowest computational cost (1237ms). Based on these results, the thesis concludes that the algorithms RF, SVM, and DT perform best in different scenarios. For instance, SVM should be used if a low amount of false positives is favoured. If the general and balanced performance of multiple metrics is preferred, then RF will perform best. The results also conclude that a significant amount of the examined features can be disregarded in future experiments, as they do not impact the performance of either classifier.
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Wingkvist, Anna. "The Quest for Equilibrium : Towards an Understanding of Scalability and Sustainability for Mobile Learning." Licentiate thesis, Växjö University, School of Mathematics and Systems Engineering, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:vxu:diva-2504.

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The research presented in this thesis investigates the concept of sustainability in relation to mobile learning initiatives. Sustainability is seen as a key concept for mobile learning to gain acceptance. In linking sustainability to scalability, a term used to describe how well something can grow to suit an increasing complexity, a representation of this process is provided. In this thesis, this process is called ``the quest for equilibrium.''

A study was conducted of an actual mobile learning initiative that involved introducing podcasts as a supplement to traditional lectures in higher education. In following this initiative, thorough data gathering was conducted, utilizing the process of iterative cycles that characterizes the action research approach. In accordance, a literature survey was conducted, whereby leading publications in mobile learning were classified and analyzed according to the following criteria: Reflections, Frameworks, Scalability, and Sustainability.

As the mobile learning system evolved from idea to an actual empirical study, trying to understand this process became important. The insights gained during this research were used to develop a conceptual model that is based on the notion that the two concepts of Scalability and Sustainability can be linked to each other.

This conceptual model is presented describing how a mobile learning system evolves, from Idea, to Experiment, to Project, to Release. Further, each of the stages in this evolution is described by using four areas of concern: Technology, Learning, Social, and Organization.

Using the experience from a specific mobile learning initiative to define a conceptual model that then is used to describe the same initiative, was a way to bring together practice, theory, and research, thus provide reliable evidence for the model itself.

The conceptual model can serve as a thinking tool for mobile learning practitioners, to help address the complexity involved when undertaking new efforts and initiatives in this field.

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Åhman, Sebastian, and Jonny Nguyen. "Students' Perception on Using Student Response Systems in Flipped Classroom in Higher Education : A Case Study at Linnaeus University in south of Sweden." Thesis, Linnéuniversitetet, Institutionen för informatik (IK), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-98173.

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The technological improvements and a generation with increased interest in using technology to aid in their learning. Cause a need for a change in the educational approaches or already established methodologies. The modern educational approach hints a move from the traditional passive learning approach, where the students are passive listeners, into an active learning approach, where the students access the information beforehand. Therefore, classroom time is used to elaborate on complex subjects through an active discussion during the lectures. Student Response Systems (SRS) aims to integrate technological tools with the educational environment, thereby improving the students' participation and engagement. The purpose of this thesis is to study the factors influencing the students' engagement when using SRS in a flipped classroom environment. Furthermore, to what extend can the SRS facilitate the students' active participation in the discussion within an educational context. The research is performed at Linnaeus University in a course at a Master level course. A pre-study was conducted, consisting of observing the course later to form the interview question from the acquired knowledge. Afterward, interviews were conducted with 7 of the participating students. The results of the study might provide additional knowledge for the teachers to decide upon an approach to implement the use of SRS with the flipped classroom approach.
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Sagayam, Arul Thileeban. "LIDS: An Extended LSTM Based Web Intrusion Detection System With Active and Distributed Learning." Thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/103471.

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Intrusion detection systems are an integral part of web application security. As Internet use continues to increase, the demand for fast, accurate intrusion detection systems has grown. Various IDSs like Snort, Zeek, Solarwinds SEM, and Sleuth9, detect malicious intent based on existing patterns of attack. While these systems are widely deployed, there are limitations with their approach, and anomaly-based IDSs that classify baseline behavior and trigger on deviations were developed to address their shortcomings. Existing anomaly-based IDSs have limitations that are typical of any machine learning system, including high false-positive rates, a lack of clear infrastructure for deployment, the requirement for data to be centralized, and an inability to add modules tailored to specific organizational threats. To address these shortcomings, our work proposes a system that is distributed in nature, can actively learn and uses experts to improve accuracy. Our results indicate that the integrated system can operate independently as a holistic system while maintaining an accuracy of 99.03%, a false positive rate of 0.5%, and speed of processing 160,000 packets per second for an average system.
Master of Science
Intrusion detection systems are an integral part of web application security. The task of an intrusion detection system is to identify attacks on web applications. As Internet use continues to increase, the demand for fast, accurate intrusion detection systems has grown. Various IDSs like Snort, Zeek, Solarwinds SEM, and Sleuth9, detect malicious intent based on existing attack patterns. While these systems are widely deployed, there are limitations with their approach, and anomaly-based IDSs that learn a system's baseline behavior and trigger on deviations were developed to address their shortcomings. Existing anomaly-based IDSs have limitations that are typical of any machine learning system, including high false-positive rates, a lack of clear infrastructure for deployment, the requirement for data to be centralized, and an inability to add modules tailored to specific organizational threats. To address these shortcomings, our work proposes a system that is distributed in nature, can actively learn and uses experts to improve accuracy. Our results indicate that the integrated system can operate independently as a holistic system while maintaining an accuracy of 99.03%, a false positive rate of 0.5%, and speed of processing 160,000 packets per second for an average system.
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Clark, Kristen Radsliff. "Charting transformative practice critical multiliteracies via informal learning design /." Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2007. http://wwwlib.umi.com/cr/ucsd/fullcit?p3259635.

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Thesis (Ph. D.)--University of California, San Diego, 2007.
Title from first page of PDF file (viewed June 11, 2007). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 187-195).
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Jung, Yusun. "A Dialogic Action Perspective on Open Collective Inquiry in Online Forums." Case Western Reserve University School of Graduate Studies / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=case1327699379.

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35

Andersson, Marcus. "Complexity and problem solving : A tale of two systems." Thesis, Umeå universitet, Institutionen för psykologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-150937.

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The purpose of this thesis is to investigate if increasing complexity for a problem makes a difference for a learning system with dual parts. The dual parts of the learning system are modelled after the Actor and Critic parts from the Actor-Critic algorithm, using the reinforcement learning framework. The results conclude that not any difference can be found in the relative performance in the Actor and Critic parts when increasing the complexity of a problem. These results could depend on technical difficulties in comparing the environments and the algorithms. The difference in complexity would then be non-uniform in an unknowable way and uncertain to use as comparison. If on the other hand the change of complexity is uniform, this could point to the fact that there is an actual difference in how each of the actor and critic handles different types of complexity. Further studies with a controlled increase in complexity are needed to establish which of the scenarios is most likely to be true. In the discussion an idea is presented of using the Actor-Critic framework as a model to understand the success rate of psychological treatments better.
Syftet med den här uppsatsen är att undersöka om en ökande komplexitet på ett problem, innebär en skillnad för ett lärande system med två samverkande. De två samverkande delarna som används är från “Actor” och “Critic”, som kommer ifrån algoritmen “Actor-Critic”. som implementeras med hjälp av ramverket “Reinforcement learning”. Resultaten bekräftar att det inte verkar vara någon skillnad i relativ effektivitet mellan “Actor” och “Critic” när komplexiteten ändras mellan två problem. Detta kan bero på tekniska svårigheter att jämföra miljöerna i experimentet och algoritmerna som används. Om det finns problem med jämförelserna skulle skillnaden i komplexitet vara icke-uniform på ett obestämbart sätt, och att kunna göra jämförelser blir därför svårt. Däremot om skillnaden i komplexitet är uniform, skulle det kunna tyda på det kanske finns en skillnad i hur “Actor” och “Critic” hanterar olika typer av komplexitet. Vidare studier med kontrollerade ökningar för komplexiteten är nödvändiga för att fastställa hur “Actor-Crtic” algoritmen samverkar med skillnader i komplexitet. I diskussionen presenteras iden att använda Actor-Critic modellen för att förstå metoder för psykologiska behandlingar bättre.
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Stephanos, Dembe. "Machine Learning Approaches to Dribble Hand-off Action Classification with SportVU NBA Player Coordinate Data." Digital Commons @ East Tennessee State University, 2021. https://dc.etsu.edu/etd/3908.

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Recently, strategies of National Basketball Association teams have evolved with the skillsets of players and the emergence of advanced analytics. One of the most effective actions in dynamic offensive strategies in basketball is the dribble hand-off (DHO). This thesis proposes an architecture for a classification pipeline for detecting DHOs in an accurate and automated manner. This pipeline consists of a combination of player tracking data and event labels, a rule set to identify candidate actions, manually reviewing game recordings to label the candidates, and embedding player trajectories into hexbin cell paths before passing the completed training set to the classification models. This resulting training set is examined using the information gain from extracted and engineered features and the effectiveness of various machine learning algorithms. Finally, we provide a comprehensive accuracy evaluation of the classification models to compare various machine learning algorithms and highlight their subtle differences in this problem domain.
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Weekley, Paul. "Improving Sahelian food security through facilitating action learning networks : a case study among the Fulbe Jelgobe of Northern Burkina Faso /." [Richmond, N.S.W.} : Faculty of Environmental Management and Agriculture, University of Western Sydney, Hawkesbury, 1999. http://library.uws.edu.au/adt-NUWS/public/adt-NUWS20030508.110110/index.html.

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Alabdulrahman, Rabaa. "Towards Personalized Recommendation Systems: Domain-Driven Machine Learning Techniques and Frameworks." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/41012.

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Recommendation systems have been widely utilized in e-commerce settings to aid users through their shopping experiences. The principal advantage of these systems is their ability to narrow down the purchase options in addition to marketing items to customers. However, a number of challenges remain, notably those related to obtaining a clearer understanding of users, their profiles, and their preferences in terms of purchased items. Specifically, recommender systems based on collaborative filtering recommend items that have been rated by other users with preferences similar to those of the targeted users. Intuitively, the more information and ratings collected about the user, the more accurate are the recommendations such systems suggest. In a typical recommender systems database, the data are sparse. Sparsity occurs when the number of ratings obtained by the users is much lower than the number required to build a prediction model. This usually occurs because of the users’ reluctance to share their reviews, either due to privacy issues or an unwillingness to make the extra effort. Grey-sheep users pose another challenge. These are users who shared their reviews and ratings yet disagree with the majority in the systems. The current state-of-the-art typically treats these users as outliers and removes them from the system. Our goal is to determine whether keeping these users in the system may benefit learning. Thirdly, cold-start problems refer to the scenario whereby a new item or user enters the system and is another area of active research. In this case, the system will have no information about the new user or item, making it problematic to find a correlation with others in the system. This thesis addresses the three above-mentioned research challenges through the development of machine learning methods for use within the recommendation system setting. First, we focus on the label and data sparsity though the development of the Hybrid Cluster analysis and Classification learning (HCC-Learn) framework, combining supervised and unsupervised learning methods. We show that combining classification algorithms such as k-nearest neighbors and ensembles based on feature subspaces with cluster analysis algorithms such as expectation maximization, hierarchical clustering, canopy, k-means, and cascade k-means methods, generally produces high-quality results when applied to benchmark datasets. That is, cluster analysis clearly benefits the learning process, leading to high predictive accuracies for existing users. Second, to address the cold-start problem, we present the Popular Users Personalized Predictions (PUPP-DA) framework. This framework combines cluster analysis and active learning, or so-called user-in-the-loop, to assign new customers to the most appropriate groups in our framework. Based on our findings from the HCC-Learn framework, we employ the expectation maximization soft clustering technique to create our user segmentations in the PUPP-DA framework, and we further incorporate Convolutional Neural Networks into our design. Our results show the benefits of user segmentation based on soft clustering and the use of active learning to improve predictions for new users. Furthermore, our findings show that focusing on frequent or popular users clearly improves classification accuracy. In addition, we demonstrate that deep learning outperforms machine learning techniques, notably resulting in more accurate predictions for individual users. Thirdly, we address the grey-sheep problem in our Grey-sheep One-class Recommendations (GSOR) framework. The existence of grey-sheep users in the system results in a class imbalance whereby the majority of users will belong to one class and a small portion (grey-sheep users) will fall into the minority class. In this framework, we use one-class classification to provide a class structure for the training examples. As a pre-assessment stage, we assess the characteristics of grey-sheep users and study their impact on model accuracy. Next, as mentioned above, we utilize one-class learning, whereby we focus on the majority class to first learn the decision boundary in order to generate prediction lists for the grey-sheep (minority class). Our results indicate that including grey-sheep users in the training step, as opposed to treating them as outliers and removing them prior to learning, has a positive impact on the general predictive accuracy.
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Sörsäter, Michael. "Active Learning for Road Segmentation using Convolutional Neural Networks." Thesis, Linköpings universitet, Datorseende, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-152286.

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In recent years, development of Convolutional Neural Networks has enabled high performing semantic segmentation models. Generally, these deep learning based segmentation methods require a large amount of annotated data. Acquiring such annotated data for semantic segmentation is a tedious and expensive task. Within machine learning, active learning involves in the selection of new data in order to limit the usage of annotated data. In active learning, the model is trained for several iterations and additional samples are selected that the model is uncertain of. The model is then retrained on additional samples and the process is repeated again. In this thesis, an active learning framework has been applied to road segmentation which is semantic segmentation of objects related to road scenes. The uncertainty in the samples is estimated with Monte Carlo dropout. In Monte Carlo dropout, several dropout masks are applied to the model and the variance is captured, working as an estimate of the model’s uncertainty. Other metrics to rank the uncertainty evaluated in this work are: a baseline method that selects samples randomly, the entropy in the default predictions and three additional variations/extensions of Monte Carlo dropout. Both the active learning framework and uncertainty estimation are implemented in the thesis. Monte Carlo dropout performs slightly better than the baseline in 3 out of 4 metrics. Entropy outperforms all other implemented methods in all metrics. The three additional methods do not perform better than Monte Carlo dropout. An analysis of what kind of uncertainty Monte Carlo dropout capture is performed together with a comparison of the samples selected by baseline and Monte Carlo dropout. Future development and possible improvements are also discussed.
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Pozo, Manuel. "Towards Accurate and Scalable Recommender Systems." Thesis, Paris, CNAM, 2016. http://www.theses.fr/2016CNAM1061/document.

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Les systèmes de recommandation visent à présélectionner et présenter en premier les informations susceptibles d'intéresser les utilisateurs. Ceci a suscité l'attention du commerce électronique, où l'historique des achats des utilisateurs sont analysés pour prédire leurs intérêts futurs et pouvoir personnaliser les offres ou produits (appelés aussi items) qui leur sont proposés. Dans ce cadre, les systèmes de recommandation exploitent les préférences des utilisateurs et les caractéristiques des produits et des utilisateurs pour prédire leurs préférences pour des futurs items. Bien qu'ils aient démontré leur précision, ces systèmes font toujours face à de grands défis tant pour le monde académique que pour l'industrie : ces techniques traitent un grand volume de données qui exige une parallélisation des traitements, les données peuvent être également très hétérogènes, et les systèmes de recommandation souffrent du démarrage à froid, situation dans laquelle le système n'a pas (ou pas assez) d'informations sur (les nouveaux) utilisateurs/items pour proposer des recommandations précises. La technique de factorisation matricielle a démontré une précision dans les prédictions et une simplicité de passage à l'échelle. Cependant, cette approche a deux inconvénients : la complexité d'intégrer des données hétérogènes externes (telles que les caractéristiques des items) et le démarrage à froid pour un nouvel utilisateur. Cette thèse a pour objectif de proposer un système offrant une précision dans les recommandations, un passage à l'échelle pour traiter des données volumineuses, et permettant d'intégrer des données variées sans remettre en question l'indépendance du système par rapport au domaine d'application. De plus, le système doit faire face au démarrage à froid utilisateurs car il est important de fidéliser et satisfaire les nouveaux utilisateurs. Cette thèse présente quatre contributions au domaine des systèmes de recommandation: (1) nous proposons une implémentation d'un algorithme de recommandation de factorisation matricielle parallélisable pour assurer un meilleur passage à l'échelle, (2) nous améliorons la précision des recommandations en prenant en compte l'intérêt implicite des utilisateurs dans les attributs des items, (3) nous proposons une représentation compacte des caractéristiques des utilisateurs/items basée sur les filtres de bloom permettant de réduire la quantité de mémoire utile, (4) nous faisons face au démarrage à froid d'un nouvel utilisateur en utilisant des techniques d'apprentissage actif. La phase d'expérimentation utilise le jeu de données MovieLens et la base de données IMDb publiquement disponibles, ce qui permet d'effectuer des comparaisons avec des techniques existantes dans l'état de l'art. Ces expérimentations ont démontré la précision et l'efficacité de nos approches
Recommender Systems aim at pre-selecting and presenting first the information in which users may be interested. This has raised the attention of the e-commerce, where the interests of users are analysed in order to predict future interests and to personalize the offers (a.k.a. items). Recommender systems exploit the current preferences of users and the features of items/users in order to predict their future preference in items.Although they demonstrate accuracy in many domains, these systems still face great challenges for both academia and industry: they require distributed techniques to deal with a huge volume of data, they aim to exploit very heterogeneous data, and they suffer from cold-start, situation in which the system has not (enough) information about (new) users/items to provide accurate recommendations. Among popular techniques, Matrix Factorization has demonstrated high accurate predictions and scalability to parallelize the analysis among multiple machines. However, it has two main drawbacks: (1) difficulty of integrating external heterogeneous data such as items' features, and (2) the cold-start issue. The objective of this thesis is to answer to many challenges in the field of recommender systems: (1) recommendation techniques deal with complex analysis and a huge volume of data; in order to alleviate the time consumption of analysis, these techniques need to parallelize the process among multiple machines, (2) collaborative filtering techniques do not naturally take into account the items' descriptions in the recommendation, although this information may help to perform more accurate recommendations, (3) users' and items' descriptions in very large dataset contexts can become large and memory-consuming; this makes data analysis more complex, and (4) the new user cold-start is particularly important to perform new users' recommendations and to assure new users fidelity. Our contributions to this area are given by four aspects: (1) we improve the distribution of a matrix factorization recommendation algorithm in order to achieve better scalability, (2) we enhance recommendations performed by matrix factorization by studying the implicit interest of the users in the attributes of the items, (3) we propose an accurate and low-space binary vector based on Bloom Filters for representing users/items through a high quantity of features in low memory-consumption, and (4) we cope with the new user cold-start in collaborative filtering by using active learning techniques. The experimentation phase uses the publicly available MovieLens dataset and IMDb database, what allows to perform fair comparisons to the state of the art. Our contributions demonstrate their performance in terms of accuracy and efficiency
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41

Roberts, Kathleen. "The Meaning Making That Leads to Social Entrepreneurial Action." Antioch University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=antioch1323395903.

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42

Babb, Jeffry. "TOWARDS A REFLECTIVE-AGILE LEARNING MODEL AND METHOD IN THE CASE OF SMALL-SHOP SOFTWARE DEVELOPMENT: EVIDENCE FROM AN ACTION RESEARCH STUDY." VCU Scholars Compass, 2009. http://scholarscompass.vcu.edu/etd/1763.

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The ascension and use of agile and lightweight software development methods have challenged extant software design and development paradigms; this is especially notable in the case of small-team and small-shop software development. In this dissertation, a Reflective-Agile Learning Method and Methodology (RALMM) for small-shop software development, is proposed to enhance communication and learning in the use of agile methods. The purpose of the inquiry in this dissertation pertains to: the nature of the professional practice of small team software development; the implications of the epistemology of Reflective Practice has for the professional practice of small-team software development; and whether the introduction of Reflective Practice to an extant agile methodology improves process, productivity and professional confidence for a small development team. This dissertation uses Dialogical Action Research (Mårtensson and Lee 2004), or Dialogical AR, a qualitative and interpretive research approach, to iteratively develop and refine the Reflective-Agile Learning Model and Method (RALMM). The proposed model and method also considers Hazzan and Tomayko’s (2002, 2004, and 2005) synthesis of Schön’s (1983, 1987) Reflective Practice and Extreme Programming (XP). RALMM is shaped by Argyris and Schön’s theories of practice (1974) and Organizational Learning (1978, 1996) and Schön’s ancillary work on generative metaphor (1979) and frames (Schön et al. 1994). The RALMM artifact was developed in a Dialogical AR Partnership using Lee’s (2007) framework for synthesizing design science and action research. The development and use of RALMM facilitated theorizing on the role of Reflective Practice in the successful use of agile methods. To assist in interpretation and analysis, the data collected during Dialogical AR cycles are analyzed using Strauss and Corbin’s (1998) Grounded Theory as a mode of analysis to guide in the coding and analysis of qualitative evidence from the research. As a result of this research, RALMM improved the practitioners’ processes and productivity. Furthermore, RALMM helped to establish, formalize and reinforce a team learning system for the continued development of the practitioners’ professional repertoire. Additionally, the iterative development of RALMM provides a basis for theorizing on Reflective Practice as an epistemology, paradigm, metaphor and frame of reference for the professional practice of small-shop software development.
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43

Olsson, CJ. "Imaging imagining actions." Doctoral thesis, Umeå : Section for Physiology, Department of Integrative Medical Biology, Umeå University, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1910.

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44

Nagaraj, Varun. "Emergent Learning in Digital Product Teams." Case Western Reserve University School of Graduate Studies / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case1553980113426569.

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45

Rasolzadeh, Babak. "Visual Attention in Active Vision Systems : Attending, Classifying and Manipulating Objects." Doctoral thesis, KTH, Datorseende och robotik, CVAP, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-53484.

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This thesis has presented a computational model for the combination of bottom-up and top-down attentional mechanisms. Furthermore, the use for this model has been demonstrated in a variety of applications of machine and robotic vision. We have observed that an attentional mechanism is imperative in any active vision system, machine as well as biological, since it not only reduces the amount of information that needs to be further processed (for say recognition, action), but also by only processing the attended image regions, such tasks become more robust to large amounts of clutter and noise in the visual field. Using various feature channels such as color, orientation, texture, depth and symmetry, as input, the presented model is able with a pre-trained artificial neural network to modulate a saliency map for a particular top-down goal, e.g. visual search for a target object. More specifically it dynamically combines the unmodulated bottom-up saliency with the modulated top-down saliency, by means of a biologically and psychophysically motivated temporal differential equation. This way the system is for instance able to detect important bottom-up cues, even while in visual search mode (top-down) for a particular object. All the computational steps for yielding the final attentional map, that ranks regions in images according to their importance for the system, are shown to be biologically plausible. It has also been demonstrated that the presented attentional model facilitates tasks other than visual search. For instance, using the covert attentional peaks that the model returns, we can improve scene understanding and segmentation through clustering or scattering of the 2D/3D components of the scene, depending on the configuration of these attentional peaks and their relations to other attributes of the scene. More specifically this is performed by means of entropy optimization of the scence under varying cluster-configurations, i.e. different groupings of the various components of the scene. Qualitative experiments demonstrated the use of this attentional model on a robotic humanoid platform and in a real-time manner control the overt attention of the robot by specifying the saccadic movements of the robot head. These experiments also exposed another highly important aspect of the model; its temporal variability, as opposed to many other attentional (saliency) models that exclusively deal with static images. Here the dynamic aspects of the attentional mechanism proved to allow for a temporally varying trade-off between top-down and bottom-up influences depending on changes in the environment of the robot. The thesis has also lay forward systematic and quantitative large scale experiments on the actual benefits and uses of this kind of attentional model. To this end a simulated 2D environment was implemented, where the system could not “see” the entire environment and needed to perform overt shifts of attention (a simulated saccade) in order to perfom a visual search task for a pre-defined sought object. This allowed for a simple and rapid substitution of the core attentional-model of the system with comparative computational models designed by other researchers. Nine such contending models were tested and compared with the presented model, in a quantitative manner. Given certain asumptions these experiments showed that the attentional model presented in this work outperforms the other models in simple visualsearch tasks.
QC 20111228
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46

Almejalli, Khaled A. "Intelligent Real-Time Decision Support Systems for Road Traffic Management. Multi-agent based Fuzzy Neural Networks with a GA learning approach in managing control actions of road traffic centres." Thesis, University of Bradford, 2010. http://hdl.handle.net/10454/4264.

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The selection of the most appropriate traffic control actions to solve non-recurrent traffic congestion is a complex task which requires significant expert knowledge and experience. In this thesis we develop and investigate the application of an intelligent traffic control decision support system for road traffic management to assist the human operator to identify the most suitable control actions in order to deal with non-recurrent and non-predictable traffic congestion in a real-time situation. Our intelligent system employs a Fuzzy Neural Networks (FNN) Tool that combines the capabilities of fuzzy reasoning in measuring imprecise and dynamic factors and the capabilities of neural networks in terms of learning processes. In this work we present an effective learning approach with regard to the FNN-Tool, which consists of three stages: initializing the membership functions of both input and output variables by determining their centres and widths using self-organizing algorithms; employing an evolutionary Genetic Algorithm (GA) based learning method to identify the fuzzy rules; tune the derived structure and parameters using the back-propagation learning algorithm. We evaluate experimentally the performance and the prediction capability of this three-stage learning approach using well-known benchmark examples. Experimental results demonstrate the ability of the learning approach to identify all relevant fuzzy rules from the training data. A comparative analysis shows that the proposed learning approach has a higher degree of predictive capability than existing models. We also address the scalability issue of our intelligent traffic control decision support system by using a multi-agent based approach. The large network is divided into sub-networks, each of which has its own associated agent. Finally, our intelligent traffic control decision support system is applied to a number of road traffic case studies using the traffic network in Riyadh, in Saudi Arabia. The results obtained are promising and show that our intelligent traffic control decision support system can provide an effective support for real-time traffic control.
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Szilagyi, Ioan. "Technologies sémantiques pour un système actif d’apprentissage." Thesis, Besançon, 2014. http://www.theses.fr/2014BESA1008/document.

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Les méthodes d’apprentissage évoluent et aux modèles classiques d’enseignement viennent s’ajouter de nouveaux paradigmes, dont les systèmes d’information et de communication, notamment le Web, sont une partie essentielle. Afin améliorer la capacité de traitement de l’information de ces systèmes, le Web sémantique définit un modèle de description de ressources (Resource Description Framework – RDF), ainsi qu’un langage pour la définition d’ontologies (Web Ontology Language – OWL). Partant des concepts, des méthodes, des théories d’apprentissage, en suivant une approche systémique, nous avons utilisé les technologies du Web sémantique pour réaliser une plateforme d’apprentissage capable d’enrichir et de personnaliser l’expérience de l’apprenant. Les résultats de nos travaux sont concrétisés dans la proposition d’un prototype pour un Système Actif et Sémantique d’Apprentissage (SASA). Suite à l’identification et la modélisation des entités participant à l’apprentissage, nous avons construit six ontologies, englobant les caractéristiques de ces entités. Elles sont les suivantes : (1) ontologie de l’apprenant, (2) ontologie de l’objet pédagogique, (3) ontologie de l’objectif d’apprentissage, (4) ontologie de l’objet d’évaluation, (5) ontologie de l’objet d’annotation et (6) ontologie du cadre d’enseignement. L’intégration des règles au niveau des ontologies déclarées, cumulée avec les capacités de raisonnement des moteurs d’inférences incorporés au niveau du noyau sémantique du SASA, permettent l’adaptation du contenu d’apprentissage aux particularités des apprenants. L’utilisation des technologies sémantiques facilite l’identification des ressources d’apprentissage existant sur le Web ainsi que l’interprétation et l’agrégation de ces ressources dans le cadre du SASA
Learning methods keep evolving and new paradigms are added to traditional teaching models where the information and communication systems, particularly the Web, are an essential part. In order to improve the processing capacity of information systems, the Semantic Web defines a model for describing resources (Resource Description Framework - RDF), and a language for defining ontologies (Web Ontology Language – OWL). Based on concepts, methods, learning theories, and following a systemic approach, we have used Semantic Web technologies in order to provide a learning system that is able to enrich and personalize the experience of the learner. As a result of our work we are proposing a prototype for an Active Semantic Learning System (SASA). Following the identification and modeling of entities involved in the learning process, we created the following six ontologies that summarize the characteristics of these entities: (1) learner ontology, (2) learning object ontology, (3) learning objective ontology, (4) evaluation object ontology, (5) annotation object ontology and (6) learning framework ontology. Integrating certain rules in the declared ontologies combined with reasoning capacities of the inference engines embedded in the kernel of the SASA, allow the adaptation of learning content to the characteristics of learners. The use of semantic technologies facilitates the identification of existing learning resources on the web as well as the interpretation and aggregation of these resources within the context of SASA
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48

Peniak, Martin. "GPU computing for cognitive robotics." Thesis, University of Plymouth, 2014. http://hdl.handle.net/10026.1/3052.

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This thesis presents the first investigation of the impact of GPU computing on cognitive robotics by providing a series of novel experiments in the area of action and language acquisition in humanoid robots and computer vision. Cognitive robotics is concerned with endowing robots with high-level cognitive capabilities to enable the achievement of complex goals in complex environments. Reaching the ultimate goal of developing cognitive robots will require tremendous amounts of computational power, which was until recently provided mostly by standard CPU processors. CPU cores are optimised for serial code execution at the expense of parallel execution, which renders them relatively inefficient when it comes to high-performance computing applications. The ever-increasing market demand for high-performance, real-time 3D graphics has evolved the GPU into a highly parallel, multithreaded, many-core processor extraordinary computational power and very high memory bandwidth. These vast computational resources of modern GPUs can now be used by the most of the cognitive robotics models as they tend to be inherently parallel. Various interesting and insightful cognitive models were developed and addressed important scientific questions concerning action-language acquisition and computer vision. While they have provided us with important scientific insights, their complexity and application has not improved much over the last years. The experimental tasks as well as the scale of these models are often minimised to avoid excessive training times that grow exponentially with the number of neurons and the training data. This impedes further progress and development of complex neurocontrollers that would be able to take the cognitive robotics research a step closer to reaching the ultimate goal of creating intelligent machines. This thesis presents several cases where the application of the GPU computing on cognitive robotics algorithms resulted in the development of large-scale neurocontrollers of previously unseen complexity enabling the conducting of the novel experiments described herein.
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49

Ajiboye, Shola. "Designing the Framework of Entrepreneurial Relationship Management (ERM) for Strategic Actions and Effective Decision-Making." Case Western Reserve University School of Graduate Studies / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case155429869587576.

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50

Janmohammadi, Siamak. "Classifying Pairwise Object Interactions: A Trajectory Analytics Approach." Thesis, University of North Texas, 2015. https://digital.library.unt.edu/ark:/67531/metadc801901/.

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We have a huge amount of video data from extensively available surveillance cameras and increasingly growing technology to record the motion of a moving object in the form of trajectory data. With proliferation of location-enabled devices and ongoing growth in smartphone penetration as well as advancements in exploiting image processing techniques, tracking moving objects is more flawlessly achievable. In this work, we explore some domain-independent qualitative and quantitative features in raw trajectory (spatio-temporal) data in videos captured by a fixed single wide-angle view camera sensor in outdoor areas. We study the efficacy of those features in classifying four basic high level actions by employing two supervised learning algorithms and show how each of the features affect the learning algorithms’ overall accuracy as a single factor or confounded with others.
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