WorldWideScience

Sample records for learning complex systems

  1. Conceptualizing Debates in Learning and Educational Research: Toward a Complex Systems Conceptual Framework of Learning

    Science.gov (United States)

    Jacobson, Michael J.; Kapur, Manu; Reimann, Peter

    2016-01-01

    This article proposes a conceptual framework of learning based on perspectives and methodologies being employed in the study of complex physical and social systems to inform educational research. We argue that the contexts in which learning occurs are complex systems with elements or agents at different levels--including neuronal, cognitive,…

  2. Patients with Parkinson's disease learn to control complex systems-an indication for intact implicit cognitive skill learning.

    Science.gov (United States)

    Witt, Karsten; Daniels, Christine; Daniel, Victoria; Schmitt-Eliassen, Julia; Volkmann, Jens; Deuschl, Günther

    2006-01-01

    Implicit memory and learning mechanisms are composed of multiple processes and systems. Previous studies demonstrated a basal ganglia involvement in purely cognitive tasks that form stimulus response habits by reinforcement learning such as implicit classification learning. We will test the basal ganglia influence on two cognitive implicit tasks previously described by Berry and Broadbent, the sugar production task and the personal interaction task. Furthermore, we will investigate the relationship between certain aspects of an executive dysfunction and implicit learning. To this end, we have tested 22 Parkinsonian patients and 22 age-matched controls on two implicit cognitive tasks, in which participants learned to control a complex system. They interacted with the system by choosing an input value and obtaining an output that was related in a complex manner to the input. The objective was to reach and maintain a specific target value across trials (dynamic system learning). The two tasks followed the same underlying complex rule but had different surface appearances. Subsequently, participants performed an executive test battery including the Stroop test, verbal fluency and the Wisconsin card sorting test (WCST). The results demonstrate intact implicit learning in patients, despite an executive dysfunction in the Parkinsonian group. They lead to the conclusion that the basal ganglia system affected in Parkinson's disease does not contribute to the implicit acquisition of a new cognitive skill. Furthermore, the Parkinsonian patients were able to reach a specific goal in an implicit learning context despite impaired goal directed behaviour in the WCST, a classic test of executive functions. These results demonstrate a functional independence of implicit cognitive skill learning and certain aspects of executive functions.

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

    Science.gov (United States)

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

    2008-01-01

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

  4. Active Learning for Directed Exploration of Complex Systems

    Science.gov (United States)

    Burl, Michael C.; Wang, Esther

    2009-01-01

    Physics-based simulation codes are widely used in science and engineering to model complex systems that would be infeasible to study otherwise. Such codes provide the highest-fidelity representation of system behavior, but are often so slow to run that insight into the system is limited. For example, conducting an exhaustive sweep over a d-dimensional input parameter space with k-steps along each dimension requires k(sup d) simulation trials (translating into k(sup d) CPU-days for one of our current simulations). An alternative is directed exploration in which the next simulation trials are cleverly chosen at each step. Given the results of previous trials, supervised learning techniques (SVM, KDE, GP) are applied to build up simplified predictive models of system behavior. These models are then used within an active learning framework to identify the most valuable trials to run next. Several active learning strategies are examined including a recently-proposed information-theoretic approach. Performance is evaluated on a set of thirteen synthetic oracles, which serve as surrogates for the more expensive simulations and enable the experiments to be replicated by other researchers.

  5. Clinical quality needs complex adaptive systems and machine learning.

    Science.gov (United States)

    Marsland, Stephen; Buchan, Iain

    2004-01-01

    The vast increase in clinical data has the potential to bring about large improvements in clinical quality and other aspects of healthcare delivery. However, such benefits do not come without cost. The analysis of such large datasets, particularly where the data may have to be merged from several sources and may be noisy and incomplete, is a challenging task. Furthermore, the introduction of clinical changes is a cyclical task, meaning that the processes under examination operate in an environment that is not static. We suggest that traditional methods of analysis are unsuitable for the task, and identify complexity theory and machine learning as areas that have the potential to facilitate the examination of clinical quality. By its nature the field of complex adaptive systems deals with environments that change because of the interactions that have occurred in the past. We draw parallels between health informatics and bioinformatics, which has already started to successfully use machine learning methods.

  6. Joined up Thinking? Evaluating the Use of Concept-Mapping to Develop Complex System Learning

    Science.gov (United States)

    Stewart, Martyn

    2012-01-01

    In the physical and natural sciences, the complexity of natural systems and their interactions is becoming better understood. With increased emphasis on learning about complex systems, students will be encountering concepts that are dynamic, ill-structured and interconnected. Concept-mapping is a method considered particularly valuable for…

  7. Are Agile and Lean Manufacturing Systems Employing Sustainability, Complexity and Organizational Learning?

    Science.gov (United States)

    Flumerfelt, Shannon; Siriban-Manalang, Anna Bella; Kahlen, Franz-Josef

    2012-01-01

    Purpose: This paper aims to peruse theories and practices of agile and lean manufacturing systems to determine whether they employ sustainability, complexity and organizational learning. Design/methodology/approach: The critical review of the comparative operational similarities and difference of the two systems was conducted while the new views…

  8. Machine learning and complex-network for personalized and systems biomedicine

    KAUST Repository

    Cannistraci, Carlo Vittorio

    2016-01-27

    The talk will begin with an introduction on using machine learning to discover hidden information and unexpected patterns in large biomedical datasets. Then, recent results on the use of complex network theory in biomedicine and neuroscience will be discussed. In particular, metagenomics and metabolomics data, approaches for drug-target repositioning, functional/structural MR connectomes and gut-brain axis data will be presented. The conclusion will outline the novel and exciting perspectives offered by the translation of these methods from systems biology to systems medicine.

  9. Learning from Evidence in a Complex World

    Science.gov (United States)

    Sterman, John D.

    2006-01-01

    Policies to promote public health and welfare often fail or worsen the problems they are intended to solve. Evidence-based learning should prevent such policy resistance, but learning in complex systems is often weak and slow. Complexity hinders our ability to discover the delayed and distal impacts of interventions, generating unintended “side effects.” Yet learning often fails even when strong evidence is available: common mental models lead to erroneous but self-confirming inferences, allowing harmful beliefs and behaviors to persist and undermining implementation of beneficial policies. Here I show how systems thinking and simulation modeling can help expand the boundaries of our mental models, enhance our ability to generate and learn from evidence, and catalyze effective change in public health and beyond. PMID:16449579

  10. Complexity Theory and CALL Curriculum in Foreign Language Learning

    Directory of Open Access Journals (Sweden)

    Hassan Soleimani

    2014-05-01

    Full Text Available Complexity theory literally indicates the complexity of a system, behavior, or a process. Its connotative meaning, while, implies dynamism, openness, sensitivity to initial conditions and feedback, and adaptation properties of a system. Regarding English as a Foreign/ Second Language (EFL/ESL this theory emphasizes on the complexity of the process of teaching and learning, including all the properties of a complex system. The purpose of the current study is to discuss the role of CALL as a modern technology in simplifying the process of teaching and learning a new language while integrating into the complexity theory. Nonetheless, the findings obtained from reviewing previously conducted studies in this field confirmed the usefulness of CALL curriculum in EFL/ESL contexts. These findings can also provide pedagogical implications for employing computer as an effective teaching and learning tool.

  11. QUALITY ASSURANCE IN RWANDAN HIGHER LEARNING EDUCATION: IS THE SYSTEM ADAPTIVE OR COMPLEX?

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    Nathan Kanuma Taremwa

    2014-01-01

    Full Text Available Developing knowledge infrastructure by massive investments in education and training are taken as a benchmark in facilitating the acceleration and possible increases in skills, capacities and competences of Rwandan people has become apriority issue in the recent years. This notion is relevant to vision 2020 where human resource development and building of a knowledge based economy are fundamental pillars. In the past years, several policy reforms have taken place in education sector. However, the overarching question is if such reforms are becoming adaptive or complex and if such reforms will not compromise the quality of education in higher learning education in Rwanda? The main objective of the study was to investigate the impact of changes in Higher Learning Institutions on the quality of education in Rwanda. This research had three hypotheses, namely; there is an impact of changes in Higher Learning Institutions on quality of education in Rwanda; the current complexity in Rwandan education system is affecting the quality of education in HLIs; Tailoring education system to the regional reforms and implementation strategies is affecting the quality of education in Rwanda. This study was carried out in 10 higher learning institutions (5 public, 5 private and 2 Ministry of Education directorates (HEC and REB. Key informants were the senior management/head of institutions, experienced academic staff, and students. The parameters considered included; the learning methods, assessment styles, workloads, language of instruction, merging of public HLIs, curriculum, and the transformation of some private higher learning institutions into company forms. Main research instruments were questionnaires and interview guides. Both qualitative and quantitative research was collected. Analyses were done using SPSS and excel packages. Major findings indicate that the system is still in transition with indicative gaps. Ample time would therefore be necessary for

  12. Integrating Emotion and Cognition in Successful Service Learning: A Complex System Approach (Invited)

    Science.gov (United States)

    Raia, F.

    2010-12-01

    Service-learning (S-L) has evolved as valuable pedagogic concept during the last two decades, based on the hypothesis that learning can best be accomplished when placed in the context of real-life social settings, e.g. schools, production, research, healthcare etc. What students learn in the academic course/context must be elaborated in the context of the S-L experience. In return for the authentic learning experience, the learner provides the service-provider with a "free" service. This reciprocality makes service-learning an appealing concept. Because of its attractive "win-win" design, the field of service-learning is continuously expanding. At a major public university CCNY with a very diverse student population, we were interested in developing and participating in S-L experience in the field of Earth System Science. We designed an upper level undergraduate course - Environmental Soil Science for Urban Sustainability - specifically targeted to students of Earth Science, Engineering, Economics and, Political Sciences to support environmental entrepreneurship. Specifically, we integrated S-L activities in the exploration of soil studies and urban agriculture. Students worked together in small groups both in class and for their S-L experience (30 hours) with urban garden and agriculture organizations. Students were required to apply the content learned in the academic course providing soil testing and soil evaluation to the partners, generate reports through a series of homework assignments and journal entries connecting three major components: Community Service, Personal Experience and Course Content. Our experience with this course shows the following results: S-L must be considered a complex system characterized by the continually changing interactions among the above mentioned three major components and three social and academic diverse groups of people involved: Students, Service-Providers and Academic Instructors. Because experience alone does not produce

  13. Environmental Factors Affecting Computer Assisted Language Learning Success: A Complex Dynamic Systems Conceptual Model

    Science.gov (United States)

    Marek, Michael W.; Wu, Wen-Chi Vivian

    2014-01-01

    This conceptual, interdisciplinary inquiry explores Complex Dynamic Systems as the concept relates to the internal and external environmental factors affecting computer assisted language learning (CALL). Based on the results obtained by de Rosnay ["World Futures: The Journal of General Evolution", 67(4/5), 304-315 (2011)], who observed…

  14. Preparing new nurses with complexity science and problem-based learning.

    Science.gov (United States)

    Hodges, Helen F

    2011-01-01

    Successful nurses function effectively with adaptability, improvability, and interconnectedness, and can see emerging and unpredictable complex problems. Preparing new nurses for complexity requires a significant change in prevalent but dated nursing education models for rising graduates. The science of complexity coupled with problem-based learning and peer review contributes a feasible framework for a constructivist learning environment to examine real-time systems data; explore uncertainty, inherent patterns, and ambiguity; and develop skills for unstructured problem solving. This article describes a pilot study of a problem-based learning strategy guided by principles of complexity science in a community clinical nursing course. Thirty-five senior nursing students participated during a 3-year period. Assessments included peer review, a final project paper, reflection, and a satisfaction survey. Results were higher than expected levels of student satisfaction, increased breadth and analysis of complex data, acknowledgment of community as complex adaptive systems, and overall higher level thinking skills than in previous years. 2011, SLACK Incorporated.

  15. Complexity Thinking in PE: Game-Centred Approaches, Games as Complex Adaptive Systems, and Ecological Values

    Science.gov (United States)

    Storey, Brian; Butler, Joy

    2013-01-01

    Background: This article draws on the literature relating to game-centred approaches (GCAs), such as Teaching Games for Understanding, and dynamical systems views of motor learning to demonstrate a convergence of ideas around games as complex adaptive learning systems. This convergence is organized under the title "complexity thinking"…

  16. The emergence of learning-teaching trajectories in education: a complex dynamic systems approach.

    Science.gov (United States)

    Steenbeek, Henderien; van Geert, Paul

    2013-04-01

    In this article we shall focus on learning-teaching trajectories ='successful' as well as 'unsuccessful' ones - as emergent and dynamic phenomena resulting from the interactions in the entire educational context, in particular the interaction between students and teachers viewed as processes of intertwining self-, other- and co-regulation. The article provides a review of the educational research literature on action regulation in learning and teaching, and interprets this literature in light of the theory of complex dynamic systems. Based on this reinterpretation of the literature, two dynamic models are proposed, one focusing on the short-term dynamics of learning-teaching interactions as they take place in classrooms, the other focusing on the long-term dynamics of interactions in a network of variables encompassing concerns, evaluations, actions and action effects (such as learning) students and teachers. The aim of presenting these models is to demonstrate, first, the possibility of transforming existing educational theory into dynamic models and, second, to provide some suggestions as to how such models can be used to further educational theory and practice.

  17. Adaptive Landmark-Based Navigation System Using Learning Techniques

    DEFF Research Database (Denmark)

    Zeidan, Bassel; Dasgupta, Sakyasingha; Wörgötter, Florentin

    2014-01-01

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

  18. Complexity in practice: understanding primary care as a complex adaptive system

    Directory of Open Access Journals (Sweden)

    Beverley Ellis

    2010-06-01

    Conclusions The results are real-world exemplars of the emergent properties of complex adaptive systems. Improving clinical governance in primary care requires both complex social interactions and underpinning informatics. The socio-technical lessons learned from this research should inform future management approaches.

  19. Supervised Learning with Complex-valued Neural Networks

    CERN Document Server

    Suresh, Sundaram; Savitha, Ramasamy

    2013-01-01

    Recent advancements in the field of telecommunications, medical imaging and signal processing deal with signals that are inherently time varying, nonlinear and complex-valued. The time varying, nonlinear characteristics of these signals can be effectively analyzed using artificial neural networks.  Furthermore, to efficiently preserve the physical characteristics of these complex-valued signals, it is important to develop complex-valued neural networks and derive their learning algorithms to represent these signals at every step of the learning process. This monograph comprises a collection of new supervised learning algorithms along with novel architectures for complex-valued neural networks. The concepts of meta-cognition equipped with a self-regulated learning have been known to be the best human learning strategy. In this monograph, the principles of meta-cognition have been introduced for complex-valued neural networks in both the batch and sequential learning modes. For applications where the computati...

  20. Learning to manage complexity through simulation: students' challenges and possible strategies.

    Science.gov (United States)

    Gormley, Gerard J; Fenwick, Tara

    2016-06-01

    Many have called for medical students to learn how to manage complexity in healthcare. This study examines the nuances of students' challenges in coping with a complex simulation learning activity, using concepts from complexity theory, and suggests strategies to help them better understand and manage complexity.Wearing video glasses, participants took part in a simulation ward-based exercise that incorporated characteristics of complexity. Video footage was used to elicit interviews, which were transcribed. Using complexity theory as a theoretical lens, an iterative approach was taken to identify the challenges that participants faced and possible coping strategies using both interview transcripts and video footage.Students' challenges in coping with clinical complexity included being: a) unprepared for 'diving in', b) caught in an escalating system, c) captured by the patient, and d) unable to assert boundaries of acceptable practice.Many characteristics of complexity can be recreated in a ward-based simulation learning activity, affording learners an embodied and immersive experience of these complexity challenges. Possible strategies for managing complexity themes include: a) taking time to size up the system, b) attuning to what emerges, c) reducing complexity, d) boundary practices, and e) working with uncertainty. This study signals pedagogical opportunities for recognizing and dealing with complexity.

  1. Automatic Emergence Detection in Complex Systems

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    Eugene Santos

    2017-01-01

    Full Text Available Complex systems consist of multiple interacting subsystems, whose nonlinear interactions can result in unanticipated (emergent system events. Extant systems analysis approaches fail to detect such emergent properties, since they analyze each subsystem separately and arrive at decisions typically through linear aggregations of individual analysis results. In this paper, we propose a quantitative definition of emergence for complex systems. We also propose a framework to detect emergent properties given observations of its subsystems. This framework, based on a probabilistic graphical model called Bayesian Knowledge Bases (BKBs, learns individual subsystem dynamics from data, probabilistically and structurally fuses said dynamics into a single complex system dynamics, and detects emergent properties. Fusion is the central element of our approach to account for situations when a common variable may have different probabilistic distributions in different subsystems. We evaluate our detection performance against a baseline approach (Bayesian Network ensemble on synthetic testbeds from UCI datasets. To do so, we also introduce a method to simulate and a metric to measure discrepancies that occur with shared/common variables. Experiments demonstrate that our framework outperforms the baseline. In addition, we demonstrate that this framework has uniform polynomial time complexity across all three learning, fusion, and reasoning procedures.

  2. Automated design of complex dynamic systems.

    Directory of Open Access Journals (Sweden)

    Michiel Hermans

    Full Text Available Several fields of study are concerned with uniting the concept of computation with that of the design of physical systems. For example, a recent trend in robotics is to design robots in such a way that they require a minimal control effort. Another example is found in the domain of photonics, where recent efforts try to benefit directly from the complex nonlinear dynamics to achieve more efficient signal processing. The underlying goal of these and similar research efforts is to internalize a large part of the necessary computations within the physical system itself by exploiting its inherent non-linear dynamics. This, however, often requires the optimization of large numbers of system parameters, related to both the system's structure as well as its material properties. In addition, many of these parameters are subject to fabrication variability or to variations through time. In this paper we apply a machine learning algorithm to optimize physical dynamic systems. We show that such algorithms, which are normally applied on abstract computational entities, can be extended to the field of differential equations and used to optimize an associated set of parameters which determine their behavior. We show that machine learning training methodologies are highly useful in designing robust systems, and we provide a set of both simple and complex examples using models of physical dynamical systems. Interestingly, the derived optimization method is intimately related to direct collocation a method known in the field of optimal control. Our work suggests that the application domains of both machine learning and optimal control have a largely unexplored overlapping area which envelopes a novel design methodology of smart and highly complex physical systems.

  3. Unified Computational Intelligence for Complex Systems

    CERN Document Server

    Seiffertt, John

    2010-01-01

    Computational intelligence encompasses a wide variety of techniques that allow computation to learn, to adapt, and to seek. That is, they may be designed to learn information without explicit programming regarding the nature of the content to be retained, they may be imbued with the functionality to adapt to maintain their course within a complex and unpredictably changing environment, and they may help us seek out truths about our own dynamics and lives through their inclusion in complex system modeling. These capabilities place our ability to compute in a category apart from our ability to e

  4. Complexity of Economical Systems

    Directory of Open Access Journals (Sweden)

    G. P. Pavlos

    2015-01-01

    Full Text Available In this study new theoretical concepts are described concerning the interpretation of economical complex dynamics. In addition a summary of an extended algorithm of nonlinear time series analysis is provided which is applied not only in economical time series but also in other physical complex systems (e.g. [22, 24]. In general, Economy is a vast and complicated set of arrangements and actions wherein agents—consumers, firms, banks, investors, government agencies—buy and sell, speculate, trade, oversee, bring products into being, offer services, invest in companies, strategize, explore, forecast, compete, learn, innovate, and adapt. As a result the economic and financial variables such as foreign exchange rates, gross domestic product, interest rates, production, stock market prices and unemployment exhibit large-amplitude and aperiodic fluctuations evident in complex systems. Thus, the Economics can be considered as spatially distributed non-equilibrium complex system, for which new theoretical concepts, such as Tsallis non extensive statistical mechanics and strange dynamics, percolation, nonGaussian, multifractal and multiscale dynamics related to fractional Langevin equations can be used for modeling and understanding of the economical complexity locally or globally.

  5. Strategies and Rubrics for Teaching Complex Systems Theory to Novices (Invited)

    Science.gov (United States)

    Fichter, L. S.

    2010-12-01

    Bifurcation. Self-similarity. Fractal. Sensitive dependent. Agents. Self-organized criticality. Avalanche behavior. Power laws. Strange attractors. Emergence. The language of complexity is fundamentally different from the language of equilibrium. If students do not know these phenomena, and what they tell us about the pulse of dynamic systems, complex systems will be opaque. A complex system is a group of agents. (individual interacting units, like birds in a flock, sand grains in a ripple, or individual friction units along a fault zone), existing far from equilibrium, interacting through positive and negative feedbacks, following simple rules, forming interdependent, dynamic, evolutionary networks. Complex systems produce behaviors that cannot be predicted deductively from knowledge of the behaviors of the individual components themselves; they must be experienced. What complexity theory demonstrates is that, by following simple rules, all the agents end up coordinating their behavior—self organizing—so that what emerges is not chaos, but meaningful patterns. How can we introduce Freshman, non-science, general education students to complex systems theories, in 3 to 5 classes; in a way they really get it, and can use the principles to understand real systems? Complex systems theories are not a series of unconnected or disconnected equations or models; they are developed as narratives that makes sense of how all the pieces and properties are interrelated. The principles of complex systems must be taught as deliberately and systematically as the equilibrium principles normally taught; as, say, the systematic training from pre-algebra and geometry to algebra. We have developed a sequence of logically connected narratives (strategies and rubrics) that introduce complex systems principles using models that can be simulated in a computer, in class, in real time. The learning progression has a series of 12 models (e.g. logistic system, bifurcation diagrams, genetic

  6. System complexity and (im)possible sound changes

    NARCIS (Netherlands)

    Seinhorst, K.T.

    2016-01-01

    In the acquisition of phonological patterns, learners tend to considerably reduce the complexity of their input. This learning bias may also constrain the set of possible sound changes, which might be expected to contain only those changes that do not increase the complexity of the system. However,

  7. The Meaning of System: Towards a Complexity Orientation in Systems Thinking

    DEFF Research Database (Denmark)

    Leleur, Steen

    2017-01-01

    when used to complex real-world problems. As regards systems practice it is found that selective use and combination of five presented research approaches (functionalist, interpretive, emancipatory, postmodern and complexity) which function as different but complementing ‘epistemic lenses’ in a process...... described as constructive circularity, may strengthen the exploration and learning efforts in systems-based intervention.......This article reviews the generic meaning of ‘system’ and complements more conventional system notions with a system perception based on recent complexity theory. With system as the core concept of systems theory, its actual meaning is not just of theoretical interest but is highly relevant also...

  8. Fostering Complexity Thinking in Action Research for Change in Social-Ecological Systems

    Directory of Open Access Journals (Sweden)

    Kevin H. Rogers

    2013-06-01

    Full Text Available Complexity thinking is increasingly being embraced by a wide range of academics and professionals as imperative for dealing with today's pressing social-ecological challenges. In this context, action researchers partner directly with stakeholders (communities, governance institutions, and work resource managers, etc. to embed a complexity frame of reference for decision making. In doing so, both researchers and stakeholders must strive to internalize not only "intellectual complexity" (knowing but also "lived complexity" (being and practicing. Four common conceptualizations of learning (explicit/tacit knowledge framework; unlearning selective exposure; conscious/competence learning matrix; and model of learning loops are integrated to provide a new framework that describes how learning takes place in complex systems. Deep reflection leading to transformational learning is required to foster the changes in mindset and behaviors needed to adopt a complexity frame of reference. We then present three broad frames of mind (openness, situational awareness, and a healthy respect for the restraint/action paradox, which each encompass a set of habits of mind, to create a useful framework that allows one to unlearn reductionist habits while adopting and embedding those more conducive to working in complex systems. Habits of mind provide useful heuristic tools to guide researchers and stakeholders through processes of participative planning and adaptive decision making in complex social-ecological systems.

  9. Toward A Dual-Learning Systems Model of Speech Category Learning

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    Bharath eChandrasekaran

    2014-07-01

    Full Text Available More than two decades of work in vision posits the existence of dual-learning systems of category learning. The reflective system uses working memory to develop and test rules for classifying in an explicit fashion, while the reflexive system operates by implicitly associating perception with actions that lead to reinforcement. Dual-learning systems models hypothesize that in learning natural categories, learners initially use the reflective system and, with practice, transfer control to the reflexive system. The role of reflective and reflexive systems in auditory category learning and more specifically in speech category learning has not been systematically examined. In this article we describe a neurobiologically-constrained dual-learning systems theoretical framework that is currently being developed in speech category learning and review recent applications of this framework. Using behavioral and computational modeling approaches, we provide evidence that speech category learning is predominantly mediated by the reflexive learning system. In one application, we explore the effects of normal aging on non-speech and speech category learning. We find an age related deficit in reflective-optimal but not reflexive-optimal auditory category learning. Prominently, we find a large age-related deficit in speech learning. The computational modeling suggests that older adults are less likely to transition from simple, reflective, uni-dimensional rules to more complex, reflexive, multi-dimensional rules. In a second application we summarize a recent study examining auditory category learning in individuals with elevated depressive symptoms. We find a deficit in reflective-optimal and an enhancement in reflexive-optimal auditory category learning. Interestingly, individuals with elevated depressive symptoms also show an advantage in learning speech categories. We end with a brief summary and description of a number of future directions.

  10. Revisiting the Blended Learning Literature: Using a Complex Adaptive Systems Framework

    Science.gov (United States)

    Wang, Yuping; Han, Xibin; Yang, Juan

    2015-01-01

    This research has two aims: (1) to bridge a gap in blended learning research--the lack of a systems approach to the understanding of blended learning research and practice, and (2) to promote a more comprehensive understanding of what has been achieved and what needs to be achieved in blended learning research and practice. To achieve these aims,…

  11. Does supporting multiple student strategies lead to greater learning and motivation? Investigating a source of complexity in the architecture of intelligent tutoring systems

    NARCIS (Netherlands)

    Waalkens, Maaike; Aleven, Vincent; Taatgen, Niels

    Intelligent tutoring systems (ITS) support students in learning a complex problem-solving skill. One feature that makes an ITS architecturally complex, and hard to build, is support for strategy freedom, that is, the ability to let students pursue multiple solution strategies within a given problem.

  12. Investing in Youth Work: Learning from Complexity

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    Kari Denissen Cunnien

    2017-04-01

    Full Text Available This article proposes key elements for a system of support for youth workers to develop their professional skills and capabilities by using a human development approach.  The article argues that narrowed and bureaucratic approaches to professional development can ignore the complex dynamics of human development that support engaged learning and continuous growth and improvement.  The author suggests a more dynamic system where professional development in grounded by practice; employs reflection, mentorship and coaching; and supports healthy organizational culture to foster high quality youth work.

  13. Complexity and Control: Towards a Rigorous Behavioral Theory of Complex Dynamical Systems

    Science.gov (United States)

    Ivancevic, Vladimir G.; Reid, Darryn J.

    We introduce our motive for writing this book on complexity and control with a popular "complexity myth," which seems to be quite wide spread among chaos and complexity theory fashionistas: quote>Low-dimensional systems usually exhibit complex behaviours (which we know fromMay's studies of the Logisticmap), while high-dimensional systems usually exhibit simple behaviours (which we know from synchronisation studies of the Kuramoto model)...quote> We admit that this naive view on complex (e.g., human) systems versus simple (e.g., physical) systems might seem compelling to various technocratic managers and politicians; indeed, the idea makes for appealing sound-bites. However, it is enough to see both in the equations and computer simulations of pendula of various degree - (i) a single pendulum, (ii) a double pendulum, and (iii) a triple pendulum - that this popular myth is plain nonsense. The only thing that we can learn from it is what every tyrant already knows: by using force as a strong means of control, it is possible to effectively synchronise even hundreds of millions of people, at least for a while.

  14. Exploring the application of an evolutionary educational complex systems framework to teaching and learning about issues in the science and technology classroom

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    Yoon, Susan Anne

    Understanding the world through a complex systems lens has recently garnered a great deal of interest in many knowledge disciplines. In the educational arena, interactional studies, through their focus on understanding patterns of system behaviour including the dynamical processes and trajectories of learning, lend support for investigating how a complex systems approach can inform educational research. This study uses previously existing literature and tools for complex systems applications and seeks to extend this research base by exploring learning outcomes of a complex systems framework when applied to curriculum and instruction. It is argued that by applying the evolutionary dynamics of variation, interaction and selection, complexity may be harnessed to achieve growth in both the social and cognitive systems of the classroom. Furthermore, if the goal of education, i.e., the social system under investigation, is to teach for understanding, conceptual knowledge of the kind described in Popper's (1972; 1976) World 3, needs to evolve. Both the study of memetic processes and knowledge building pioneered by Bereiter (cf. Bereiter, 2002) draw on the World 3 notion of ideas existing as conceptual artifacts that can be investigated as products outside of the individual mind providing an educational lens from which to proceed. The curricular topic addressed is the development of an ethical understanding of the scientific and technological issues of genetic engineering. 11 grade 8 students are studied as they proceed through 40 hours of curricular instruction based on the complex systems evolutionary framework. Results demonstrate growth in both complex systems thinking and content knowledge of the topic of genetic engineering. Several memetic processes are hypothesized to have influenced how and why ideas change. Categorized by factors influencing either reflective or non-reflective selection, these processes appear to have exerted differential effects on students

  15. Modeling Complex Systems

    International Nuclear Information System (INIS)

    Schreckenberg, M

    2004-01-01

    This book by Nino Boccara presents a compilation of model systems commonly termed as 'complex'. It starts with a definition of the systems under consideration and how to build up a model to describe the complex dynamics. The subsequent chapters are devoted to various categories of mean-field type models (differential and recurrence equations, chaos) and of agent-based models (cellular automata, networks and power-law distributions). Each chapter is supplemented by a number of exercises and their solutions. The table of contents looks a little arbitrary but the author took the most prominent model systems investigated over the years (and up until now there has been no unified theory covering the various aspects of complex dynamics). The model systems are explained by looking at a number of applications in various fields. The book is written as a textbook for interested students as well as serving as a comprehensive reference for experts. It is an ideal source for topics to be presented in a lecture on dynamics of complex systems. This is the first book on this 'wide' topic and I have long awaited such a book (in fact I planned to write it myself but this is much better than I could ever have written it!). Only section 6 on cellular automata is a little too limited to the author's point of view and one would have expected more about the famous Domany-Kinzel model (and more accurate citation!). In my opinion this is one of the best textbooks published during the last decade and even experts can learn a lot from it. Hopefully there will be an actualization after, say, five years since this field is growing so quickly. The price is too high for students but this, unfortunately, is the normal case today. Nevertheless I think it will be a great success! (book review)

  16. A new generative complexity science of learning for a complex pedagogy

    NARCIS (Netherlands)

    Jörg, T.

    2007-01-01

    Proposal for the SIG Chaos and Complexity Theories at AERA 2007 Title: A New Generative Complexity Science of Learning for a Complex Pedagogy Ton Jörg IVLOS Institute of Education University of Utrecht The Netherlands A.G.D.Jorg@ivlos.uu.nl Introduction My paper focuses on the link between thinking

  17. Assessment for Complex Learning Resources: Development and Validation of an Integrated Model

    Directory of Open Access Journals (Sweden)

    Gudrun Wesiak

    2013-01-01

    Full Text Available Today’s e-learning systems meet the challenge to provide interactive, personalized environments that support self-regulated learning as well as social collaboration and simulation. At the same time assessment procedures have to be adapted to the new learning environments by moving from isolated summative assessments to integrated assessment forms. Therefore, learning experiences enriched with complex didactic resources - such as virtualized collaborations and serious games - have emerged. In this extension of [1] an integrated model for e-assessment (IMA is outlined, which incorporates complex learning resources and assessment forms as main components for the development of an enriched learning experience. For a validation the IMA was presented to a group of experts from the fields of cognitive science, pedagogy, and e-learning. The findings from the validation lead to several refinements of the model, which mainly concern the component forms of assessment and the integration of social aspects. Both aspects are accounted for in the revised model, the former by providing a detailed sub-model for assessment forms.

  18. Informed Systems: Enabling Collaborative Evidence Based Organizational Learning

    Directory of Open Access Journals (Sweden)

    Mary M. Somerville

    2015-12-01

    theoretical approach. Results – Over time and with practice, as co-workers design and enact information-focused and evidence based learning experiences, they learn the way to decision-making and action-taking. Increasingly more complex experiences of information exchange, sense making, and knowledge creation, well supported by workplace communication systems and professional practices, further dialogue and reflection and thereby enrich analysis and interpretation of complexities and interdependencies. Conclusions - Research projects and evaluation studies conducted since 2003 demonstrate the transformative potential of the holistic Informed Systems approach to creating robust workplace learning environments. Leaders are responsible for design of workplace environments supportive of well contextualized, information-rich conversations. Co-workers revisit both the nature of organizational information and the purpose of organizational work. As colleagues better understand the complexities of the organization and its situation, they learn to diagnose problems and identify consequences, guided by Informed Systems models. Systemic activity and process models activate collaborative evidence based information processes within enabling conditions for thought leadership and workplace learning that recognize learning is social. Enabling communication systems and professional practices therefore intentionally catalyze and support collegial inquiry to co-create information experiences and organizational knowledge through evidence based practice to enliven capacity, inform decisions, produce improvements, and sustain relationships. The Informed Systems approach is thereby a contribution to professional practice and workplace renewal through evidence based decision-making and action-taking in contemporary organizations.

  19. Reinforcement learning agents providing advice in complex video games

    Science.gov (United States)

    Taylor, Matthew E.; Carboni, Nicholas; Fachantidis, Anestis; Vlahavas, Ioannis; Torrey, Lisa

    2014-01-01

    This article introduces a teacher-student framework for reinforcement learning, synthesising and extending material that appeared in conference proceedings [Torrey, L., & Taylor, M. E. (2013)]. Teaching on a budget: Agents advising agents in reinforcement learning. {Proceedings of the international conference on autonomous agents and multiagent systems}] and in a non-archival workshop paper [Carboni, N., &Taylor, M. E. (2013, May)]. Preliminary results for 1 vs. 1 tactics in StarCraft. {Proceedings of the adaptive and learning agents workshop (at AAMAS-13)}]. In this framework, a teacher agent instructs a student agent by suggesting actions the student should take as it learns. However, the teacher may only give such advice a limited number of times. We present several novel algorithms that teachers can use to budget their advice effectively, and we evaluate them in two complex video games: StarCraft and Pac-Man. Our results show that the same amount of advice, given at different moments, can have different effects on student learning, and that teachers can significantly affect student learning even when students use different learning methods and state representations.

  20. Collectives and the design of complex systems

    CERN Document Server

    Wolpert, David

    2004-01-01

    Increasingly powerful computers are making possible distributed systems comprised of many adaptive and self-motivated computational agents. Such systems, when distinguished by system-level performance criteria, are known as "collectives." Collectives and the Design of Complex Systems lays the foundation for a science of collectives and describes how to design them for optimal performance. An introductory survey chapter is followed by descriptions of information-processing problems that can only be solved by the joint actions of large communities of computers, each running its own complex, decentralized machine-learning algorithm. Subsequent chapters analyze the dynamics and structures of collectives, as well as address economic, model-free, and control-theory approaches to designing complex systems. The work assumes a modest understanding of basic statistics and calculus. Topics and Features: Introduces the burgeoning science of collectives and its practical applications in a single useful volume Combines ap...

  1. Using Ontologies for the E-learning System in Healthcare Human Resources Management

    Directory of Open Access Journals (Sweden)

    Lidia BAJENARU

    2015-01-01

    Full Text Available This paper provides a model for the use of ontology in e-learning systems for structuring educational content in the domain of healthcare human resources management (HHRM in Romania. In this respect we propose an effective method to improve the learning system by providing personalized learning paths created using ontology and advanced educational strategies to provide a personalized learning content for the medical staff. Personalization of e-learning process for the chosen target group will be achieved by setting up learning path for each user according to his profile. This will become possible using: domain ontology, learning objects, modeling student knowledge. Developing an ontology-based system for competence management allows complex interactions, providing intelligent interfacing. This is a new approach for the healthcare system managers in permanent training based on e-learning technologies and specific ontologies in a complex area that needs urgent modernization and efficiency to meet the public health economic, social and political context of Romania.

  2. Abstraction in artificial intelligence and complex systems

    CERN Document Server

    Saitta, Lorenza

    2013-01-01

    Abstraction is a fundamental mechanism underlying both human and artificial perception, representation of knowledge, reasoning and learning. This mechanism plays a crucial role in many disciplines, notably Computer Programming, Natural and Artificial Vision, Complex Systems, Artificial Intelligence and Machine Learning, Art, and Cognitive Sciences. This book first provides the reader with an overview of the notions of abstraction proposed in various disciplines by comparing both commonalities and differences.  After discussing the characterizing properties of abstraction, a formal model, the K

  3. Creating a Framework for Improving the Learnability of a Complex System

    Directory of Open Access Journals (Sweden)

    Minttu Linja-aho

    2006-01-01

    Full Text Available When designing complex systems, it is crucial but challenging to make them easy to learn. In this paper, a framework for improving the learnability of a complex system is presented. A classification of factors affecting the learnability of a building modeling system as well as guidelines that refine the factors into practical ways of action are introduced. The factors and guidelines include issues related to the user interface, conformity of the system to user’s expectations, and training. The classification is based on empirical research during which learnability was assessed with several methods. The methodology and the classification of learnability factors can be used as references when analyzing and improving the learnability of other systems. System developers and training providers can utilize these guidelines when striving to make systems easier to learn.

  4. Adaptive learning and complex dynamics

    International Nuclear Information System (INIS)

    Gomes, Orlando

    2009-01-01

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

  5. Systems for Teaching Complex Texts: A Proof-of-Concept Investigation

    Science.gov (United States)

    Fisher, Douglas; Frey, Nancy

    2016-01-01

    In this article we investigate the systems that need to be in place for students to learn from increasingly complex texts. Our concept, drawn from past research, includes clear learning targets, teacher modeling, collaborative conversations, close reading, small group reading, and wide reading. Using a "proof of concept" model, we follow…

  6. VBOT: Motivating computational and complex systems fluencies with constructionist virtual/physical robotics

    Science.gov (United States)

    Berland, Matthew W.

    As scientists use the tools of computational and complex systems theory to broaden science perspectives (e.g., Bar-Yam, 1997; Holland, 1995; Wolfram, 2002), so can middle-school students broaden their perspectives using appropriate tools. The goals of this dissertation project are to build, study, evaluate, and compare activities designed to foster both computational and complex systems fluencies through collaborative constructionist virtual and physical robotics. In these activities, each student builds an agent (e.g., a robot-bird) that must interact with fellow students' agents to generate a complex aggregate (e.g., a flock of robot-birds) in a participatory simulation environment (Wilensky & Stroup, 1999a). In a participatory simulation, students collaborate by acting in a common space, teaching each other, and discussing content with one another. As a result, the students improve both their computational fluency and their complex systems fluency, where fluency is defined as the ability to both consume and produce relevant content (DiSessa, 2000). To date, several systems have been designed to foster computational and complex systems fluencies through computer programming and collaborative play (e.g., Hancock, 2003; Wilensky & Stroup, 1999b); this study suggests that, by supporting the relevant fluencies through collaborative play, they become mutually reinforcing. In this work, I will present both the design of the VBOT virtual/physical constructionist robotics learning environment and a comparative study of student interaction with the virtual and physical environments across four middle-school classrooms, focusing on the contrast in systems perspectives differently afforded by the two environments. In particular, I found that while performance gains were similar overall, the physical environment supported agent perspectives on aggregate behavior, and the virtual environment supported aggregate perspectives on agent behavior. The primary research questions

  7. Promoting evaluation capacity building in a complex adaptive system.

    Science.gov (United States)

    Lawrenz, Frances; Kollmann, Elizabeth Kunz; King, Jean A; Bequette, Marjorie; Pattison, Scott; Nelson, Amy Grack; Cohn, Sarah; Cardiel, Christopher L B; Iacovelli, Stephanie; Eliou, Gayra Ostgaard; Goss, Juli; Causey, Lauren; Sinkey, Anne; Beyer, Marta; Francisco, Melanie

    2018-04-10

    This study provides results from an NSF funded, four year, case study about evaluation capacity building in a complex adaptive system, the Nanoscale Informal Science Education Network (NISE Net). The results of the Complex Adaptive Systems as a Model for Network Evaluations (CASNET) project indicate that complex adaptive system concepts help to explain evaluation capacity building in a network. The NISE Network was found to be a complex learning system that was supportive of evaluation capacity building through feedback loops that provided for information sharing and interaction. Participants in the system had different levels of and sources of evaluation knowledge. To be successful at building capacity, the system needed to have a balance between both centralized and decentralized control, coherence, redundancy, and diversity. Embeddedness of individuals within the system also provided support and moved the capacity of the system forward. Finally, success depended on attention being paid to the control of resources. Implications of these findings are discussed. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Stefan Hesse

    2012-02-01

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

  9. Managing Contextual Complexity in an Experiential Learning Course: A Dynamic Systems Approach through the Identification of Turning Points in Students' Emotional Trajectories

    Directory of Open Access Journals (Sweden)

    Gloria Nogueiras

    2017-05-01

    Full Text Available This study adopts a dynamic systems approach to investigate how individuals successfully manage contextual complexity. To that end, we tracked individuals' emotional trajectories during a challenging training course, seeking qualitative changes–turning points—and we tested their relationship with the perceived complexity of the training. The research context was a 5-day higher education course based on process-oriented experiential learning, and the sample consisted of 17 students. The students used a five-point Likert scale to rate the intensity of 16 emotions and the complexity of the training on 8 measurement points. Monte Carlo permutation tests enabled to identify 30 turning points in the 272 emotional trajectories analyzed (17 students * 16 emotions each. 83% of the turning points indicated a change of pattern in the emotional trajectories that consisted of: (a increasingly intense positive emotions or (b decreasingly intense negative emotions. These turning points also coincided with particularly complex periods in the training as perceived by the participants (p = 0.003, and p = 0.001 respectively. The relationship between positively-trended turning points in the students' emotional trajectories and the complexity of the training may be interpreted as evidence of a successful management of the cognitive conflict arising from the clash between the students' prior ways of meaning-making and the challenging demands of the training. One of the strengths of this study is that it provides a relatively simple procedure for identifying turning points in developmental trajectories, which can be applied to various longitudinal experiences that are very common in educational and developmental contexts. Additionally, the findings contribute to sustaining that the assumption that complex contextual demands lead unfailingly to individuals' learning is incomplete. Instead, it is how individuals manage complexity which may or may not lead to

  10. Applications of learning based systems at AREVA group

    International Nuclear Information System (INIS)

    Jeanmart, F.; Leclerc, C.

    2006-01-01

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

  11. Achieving Complex Learning Outcomes through Adoption of a Pedagogical Perspective: A Model for Computer Technology Delivered Instruction

    Science.gov (United States)

    Bellard, Breshanica

    2018-01-01

    Professionals responsible for the delivery of education and training using technology systems and platforms can facilitate complex learning through application of relevant strategies, principles and theories that support how learners learn and that support how curriculum should be designed in a technology based learning environment. Technological…

  12. Engineering education as a complex system

    Science.gov (United States)

    Gattie, David K.; Kellam, Nadia N.; Schramski, John R.; Walther, Joachim

    2011-12-01

    This paper presents a theoretical basis for cultivating engineering education as a complex system that will prepare students to think critically and make decisions with regard to poorly understood, ill-structured issues. Integral to this theoretical basis is a solution space construct developed and presented as a benchmark for evaluating problem-solving orientations that emerge within students' thinking as they progress through an engineering curriculum. It is proposed that the traditional engineering education model, while analytically rigorous, is characterised by properties that, although necessary, are insufficient for preparing students to address complex issues of the twenty-first century. A Synthesis and Design Studio model for engineering education is proposed, which maintains the necessary rigor of analysis within a uniquely complex yet sufficiently structured learning environment.

  13. SOCIAL COMPLEXITY AND LEARNING FORAGING TASKS IN BEES

    Directory of Open Access Journals (Sweden)

    AMAYA-MÁRQUEZ MARISOL

    2008-12-01

    Full Text Available Social complexity and models concerning central place foraging were tested with respect to learning predictions using the social honey bee (Apis mellifera and solitary blue orchard bee (Osmia lignaria when given foraging problems. Both species were presented the same foraging problems, where 1 only reward molarity varied between flower morphs, and 2 only reward volume varied between flower morphs. Experiments utilized blue vs. white flower patches to standardize rewards in each experimental situation. Although honey bees learned faster than blue orchard bees when given a molarity difference reward problem, there was no significant difference in learning rate when presented a volume difference reward problem. Further, the rate at which blue orchard bees learned the volume difference problem was not significantly different from that with which honey bees learned about reward molarity differences. The results do not support the predictions of the social complexity theory, but do support those of the central place model

  14. Low Complexity Sparse Bayesian Learning for Channel Estimation Using Generalized Mean Field

    DEFF Research Database (Denmark)

    Pedersen, Niels Lovmand; Manchón, Carles Navarro; Fleury, Bernard Henri

    2014-01-01

    We derive low complexity versions of a wide range of algorithms for sparse Bayesian learning (SBL) in underdetermined linear systems. The proposed algorithms are obtained by applying the generalized mean field (GMF) inference framework to a generic SBL probabilistic model. In the GMF framework, we...

  15. Bounds on the sample complexity for private learning and private data release

    Energy Technology Data Exchange (ETDEWEB)

    Kasiviswanathan, Shiva [Los Alamos National Laboratory; Beime, Amos [BEN-GURION UNIV.; Nissim, Kobbi [BEN-GURION UNIV.

    2009-01-01

    Learning is a task that generalizes many of the analyses that are applied to collections of data, and in particular, collections of sensitive individual information. Hence, it is natural to ask what can be learned while preserving individual privacy. [Kasiviswanathan, Lee, Nissim, Raskhodnikova, and Smith; FOCS 2008] initiated such a discussion. They formalized the notion of private learning, as a combination of PAC learning and differential privacy, and investigated what concept classes can be learned privately. Somewhat surprisingly, they showed that, ignoring time complexity, every PAC learning task could be performed privately with polynomially many samples, and in many natural cases this could even be done in polynomial time. While these results seem to equate non-private and private learning, there is still a significant gap: the sample complexity of (non-private) PAC learning is crisply characterized in terms of the VC-dimension of the concept class, whereas this relationship is lost in the constructions of private learners, which exhibit, generally, a higher sample complexity. Looking into this gap, we examine several private learning tasks and give tight bounds on their sample complexity. In particular, we show strong separations between sample complexities of proper and improper private learners (such separation does not exist for non-private learners), and between sample complexities of efficient and inefficient proper private learners. Our results show that VC-dimension is not the right measure for characterizing the sample complexity of proper private learning. We also examine the task of private data release (as initiated by [Blum, Ligett, and Roth; STOC 2008]), and give new lower bounds on the sample complexity. Our results show that the logarithmic dependence on size of the instance space is essential for private data release.

  16. Eliciting design patterns for e-learning systems

    Science.gov (United States)

    Retalis, Symeon; Georgiakakis, Petros; Dimitriadis, Yannis

    2006-06-01

    Design pattern creation, especially in the e-learning domain, is a highly complex process that has not been sufficiently studied and formalized. In this paper, we propose a systematic pattern development cycle, whose most important aspects focus on reverse engineering of existing systems in order to elicit features that are cross-validated through the use of appropriate, authentic scenarios. However, an iterative pattern process is proposed that takes advantage of multiple data sources, thus emphasizing a holistic view of the teaching learning processes. The proposed schema of pattern mining has been extensively validated for Asynchronous Network Supported Collaborative Learning (ANSCL) systems, as well as for other types of tools in a variety of scenarios, with promising results.

  17. Complexity control in statistical learning

    Indian Academy of Sciences (India)

    Then we describe how the method of regularization is used to control complexity in learning. We discuss two examples of regularization, one in which the function space used is finite dimensional, and another in which it is a reproducing kernel Hilbert space. Our exposition follows the formulation of Cucker and Smale.

  18. Implications of complex adaptive systems theory for interpreting research about health care organizations.

    Science.gov (United States)

    Jordon, Michelle; Lanham, Holly Jordan; Anderson, Ruth A; McDaniel, Reuben R

    2010-02-01

    Data about health care organizations (HCOs) are not useful until they are interpreted. Such interpretations are influenced by the theoretical lenses used by the researcher. Our purpose was to suggest the usefulness of theories of complex adaptive systems (CASs) in guiding research interpretation. Specifically, we addressed two questions: (1) What are the implications for interpreting research observations in HCOs of the fact that we are observing relationships among diverse agents? (2) What are the implications for interpreting research observations in HCOs of the fact that we are observing relationships among agents that learn? We defined diversity and learning and the implications of the non-linear relationships among agents from a CAS perspective. We then identified some common analytical practices that were problematic and may lead to conceptual and methodological errors. Then we described strategies for interpreting the results of research observations. We suggest that the task of interpreting research observations of HCOs could be improved if researchers take into account that the systems they study are CASs with non-linear relationships among diverse, learning agents. Our analysis points out how interpretation of research results might be shaped by the fact that HCOs are CASs. We described how learning is, in fact, the result of interactions among diverse agents and that learning can, by itself, reduce or increase agent diversity. We encouraged researchers to be persistent in their attempts to reason about complex systems and learn to attend not only to structures, but also to processes and functions of complex systems.

  19. Complex Dynamic Systems View on Conceptual Change: How a Picture of Students' Intuitive Conceptions Accrue from Dynamically Robust Task Dependent Learning Outcomes

    Science.gov (United States)

    Koponen, Ismo T.; Kokkonen, Tommi; Nousiainen, Maiji

    2017-01-01

    We discuss here conceptual change and the formation of robust learning outcomes from the viewpoint of complex dynamic systems (CDS). The CDS view considers students' conceptions as context dependent and multifaceted structures which depend on the context of their application. In the CDS view the conceptual patterns (i.e. intuitive conceptions…

  20. Study of Environmental Data Complexity using Extreme Learning Machine

    Science.gov (United States)

    Leuenberger, Michael; Kanevski, Mikhail

    2017-04-01

    The main goals of environmental data science using machine learning algorithm deal, in a broad sense, around the calibration, the prediction and the visualization of hidden relationship between input and output variables. In order to optimize the models and to understand the phenomenon under study, the characterization of the complexity (at different levels) should be taken into account. Therefore, the identification of the linear or non-linear behavior between input and output variables adds valuable information for the knowledge of the phenomenon complexity. The present research highlights and investigates the different issues that can occur when identifying the complexity (linear/non-linear) of environmental data using machine learning algorithm. In particular, the main attention is paid to the description of a self-consistent methodology for the use of Extreme Learning Machines (ELM, Huang et al., 2006), which recently gained a great popularity. By applying two ELM models (with linear and non-linear activation functions) and by comparing their efficiency, quantification of the linearity can be evaluated. The considered approach is accompanied by simulated and real high dimensional and multivariate data case studies. In conclusion, the current challenges and future development in complexity quantification using environmental data mining are discussed. References - Huang, G.-B., Zhu, Q.-Y., Siew, C.-K., 2006. Extreme learning machine: theory and applications. Neurocomputing 70 (1-3), 489-501. - Kanevski, M., Pozdnoukhov, A., Timonin, V., 2009. Machine Learning for Spatial Environmental Data. EPFL Press; Lausanne, Switzerland, p.392. - Leuenberger, M., Kanevski, M., 2015. Extreme Learning Machines for spatial environmental data. Computers and Geosciences 85, 64-73.

  1. Learning Latent Structure in Complex Networks

    DEFF Research Database (Denmark)

    Mørup, Morten; Hansen, Lars Kai

    such as the Modularity, it has recently been shown that latent structure in complex networks is learnable by Bayesian generative link distribution models (Airoldi et al., 2008, Hofman and Wiggins, 2008). In this paper we propose a new generative model that allows representation of latent community structure......Latent structure in complex networks, e.g., in the form of community structure, can help understand network dynamics, identify heterogeneities in network properties, and predict ‘missing’ links. While most community detection algorithms are based on optimizing heuristic clustering objectives...... as in the previous Bayesian approaches and in addition allows learning of node specific link properties similar to that in the modularity objective. We employ a new relaxation method for efficient inference in these generative models that allows us to learn the behavior of very large networks. We compare the link...

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

    Science.gov (United States)

    Chan, Tak-Wai

    1996-01-01

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

  3. Network affordances through online learning: Increasing use and complexity.

    OpenAIRE

    Hajhashemi, Karim; Anderson, Neil; Jackson, Cliff; Caltabiano, Nerina

    2013-01-01

    Computers, mobile devices and the Internet have enabled a learning environment described as online learning or a variety of other terms such as e-learning. Researchers believe that online learning has become more complex due to learners' sharing and acquiring knowledge at a variety of remote locations, in a variety of modalities. However, advances in technology and the integration of ICT with teaching and learning settings have quickened the growth of online learning and importantly have chan...

  4. The complexity of patient safety reporting systems in UK dentistry.

    Science.gov (United States)

    Renton, T; Master, S

    2016-10-21

    Since the 'Francis Report', UK regulation focusing on patient safety has significantly changed. Healthcare workers are increasingly involved in NHS England patient safety initiatives aimed at improving reporting and learning from patient safety incidents (PSIs). Unfortunately, dentistry remains 'isolated' from these main events and continues to have a poor record for reporting and learning from PSIs and other events, thus limiting improvement of patient safety in dentistry. The reasons for this situation are complex.This paper provides a review of the complexities of the existing systems and procedures in relation to patient safety in dentistry. It highlights the conflicting advice which is available and which further complicates an overly burdensome process. Recommendations are made to address these problems with systems and procedures supporting patient safety development in dentistry.

  5. Etoile Project : Social Intelligent ICT-System for very large scale education in complex systems

    Science.gov (United States)

    Bourgine, P.; Johnson, J.

    2009-04-01

    The project will devise new theory and implement new ICT-based methods of delivering high-quality low-cost postgraduate education to many thousands of people in a scalable way, with the cost of each extra student being negligible (Socially Intelligent Resource Mining system to gather large volumes of high quality educational resources from the internet; new methods to deconstruct these to produce a semantically tagged Learning Object Database; a Living Course Ecology to support the creation and maintenance of evolving course materials; systems to deliver courses; and a ‘socially intelligent assessment system'. The system will be tested on one to ten thousand postgraduate students in Europe working towards the Complex System Society's title of European PhD in Complex Systems. Étoile will have a very high impact both scientifically and socially by (i) the provision of new scalable ICT-based methods for providing very low cost scientific education, (ii) the creation of new mathematical and statistical theory for the multiscale dynamics of complex systems, (iii) the provision of a working example of adaptation and emergence in complex socio-technical systems, and (iv) making a major educational contribution to European complex systems science and its applications.

  6. Complexity explained

    CERN Document Server

    Erdi, Peter

    2008-01-01

    This book explains why complex systems research is important in understanding the structure, function and dynamics of complex natural and social phenomena. Readers will learn the basic concepts and methods of complex system research.

  7. Complexity, Training Paradigm Design, and the Contribution of Memory Subsystems to Grammar Learning

    Science.gov (United States)

    Ettlinger, Marc; Wong, Patrick C. M.

    2016-01-01

    Although there is variability in nonnative grammar learning outcomes, the contributions of training paradigm design and memory subsystems are not well understood. To examine this, we presented learners with an artificial grammar that formed words via simple and complex morphophonological rules. Across three experiments, we manipulated training paradigm design and measured subjects' declarative, procedural, and working memory subsystems. Experiment 1 demonstrated that passive, exposure-based training boosted learning of both simple and complex grammatical rules, relative to no training. Additionally, procedural memory correlated with simple rule learning, whereas declarative memory correlated with complex rule learning. Experiment 2 showed that presenting corrective feedback during the test phase did not improve learning. Experiment 3 revealed that structuring the order of training so that subjects are first exposed to the simple rule and then the complex improved learning. The cumulative findings shed light on the contributions of grammatical complexity, training paradigm design, and domain-general memory subsystems in determining grammar learning success. PMID:27391085

  8. Complexity, Training Paradigm Design, and the Contribution of Memory Subsystems to Grammar Learning.

    Science.gov (United States)

    Antoniou, Mark; Ettlinger, Marc; Wong, Patrick C M

    2016-01-01

    Although there is variability in nonnative grammar learning outcomes, the contributions of training paradigm design and memory subsystems are not well understood. To examine this, we presented learners with an artificial grammar that formed words via simple and complex morphophonological rules. Across three experiments, we manipulated training paradigm design and measured subjects' declarative, procedural, and working memory subsystems. Experiment 1 demonstrated that passive, exposure-based training boosted learning of both simple and complex grammatical rules, relative to no training. Additionally, procedural memory correlated with simple rule learning, whereas declarative memory correlated with complex rule learning. Experiment 2 showed that presenting corrective feedback during the test phase did not improve learning. Experiment 3 revealed that structuring the order of training so that subjects are first exposed to the simple rule and then the complex improved learning. The cumulative findings shed light on the contributions of grammatical complexity, training paradigm design, and domain-general memory subsystems in determining grammar learning success.

  9. Complexity, Training Paradigm Design, and the Contribution of Memory Subsystems to Grammar Learning.

    Directory of Open Access Journals (Sweden)

    Mark Antoniou

    Full Text Available Although there is variability in nonnative grammar learning outcomes, the contributions of training paradigm design and memory subsystems are not well understood. To examine this, we presented learners with an artificial grammar that formed words via simple and complex morphophonological rules. Across three experiments, we manipulated training paradigm design and measured subjects' declarative, procedural, and working memory subsystems. Experiment 1 demonstrated that passive, exposure-based training boosted learning of both simple and complex grammatical rules, relative to no training. Additionally, procedural memory correlated with simple rule learning, whereas declarative memory correlated with complex rule learning. Experiment 2 showed that presenting corrective feedback during the test phase did not improve learning. Experiment 3 revealed that structuring the order of training so that subjects are first exposed to the simple rule and then the complex improved learning. The cumulative findings shed light on the contributions of grammatical complexity, training paradigm design, and domain-general memory subsystems in determining grammar learning success.

  10. Situated learning theory: adding rate and complexity effects via Kauffman's NK model.

    Science.gov (United States)

    Yuan, Yu; McKelvey, Bill

    2004-01-01

    For many firms, producing information, knowledge, and enhancing learning capability have become the primary basis of competitive advantage. A review of organizational learning theory identifies two approaches: (1) those that treat symbolic information processing as fundamental to learning, and (2) those that view the situated nature of cognition as fundamental. After noting that the former is inadequate because it focuses primarily on behavioral and cognitive aspects of individual learning, this paper argues the importance of studying learning as interactions among people in the context of their environment. It contributes to organizational learning in three ways. First, it argues that situated learning theory is to be preferred over traditional behavioral and cognitive learning theories, because it treats organizations as complex adaptive systems rather than mere information processors. Second, it adds rate and nonlinear learning effects. Third, following model-centered epistemology, it uses an agent-based computational model, in particular a "humanized" version of Kauffman's NK model, to study the situated nature of learning. Using simulation results, we test eight hypotheses extending situated learning theory in new directions. The paper ends with a discussion of possible extensions of the current study to better address key issues in situated learning.

  11. Does formal complexity reflect cognitive complexity? Investigating aspects of the Chomsky Hierarchy in an artificial language learning study.

    Science.gov (United States)

    Öttl, Birgit; Jäger, Gerhard; Kaup, Barbara

    2015-01-01

    This study investigated whether formal complexity, as described by the Chomsky Hierarchy, corresponds to cognitive complexity during language learning. According to the Chomsky Hierarchy, nested dependencies (context-free) are less complex than cross-serial dependencies (mildly context-sensitive). In two artificial grammar learning (AGL) experiments participants were presented with a language containing either nested or cross-serial dependencies. A learning effect for both types of dependencies could be observed, but no difference between dependency types emerged. These behavioral findings do not seem to reflect complexity differences as described in the Chomsky Hierarchy. This study extends previous findings in demonstrating learning effects for nested and cross-serial dependencies with more natural stimulus materials in a classical AGL paradigm after only one hour of exposure. The current findings can be taken as a starting point for further exploring the degree to which the Chomsky Hierarchy reflects cognitive processes.

  12. Simulation-Based Learning Environments to Teach Complexity: The Missing Link in Teaching Sustainable Public Management

    Directory of Open Access Journals (Sweden)

    Michael Deegan

    2014-05-01

    Full Text Available While public-sector management problems are steeped in positivistic and socially constructed complexity, public management education in the management of complexity lags behind that of business schools, particularly in the application of simulation-based learning. This paper describes a Simulation-Based Learning Environment for public management education that includes a coupled case study and System Dynamics simulation surrounding flood protection, a domain where stewardship decisions regarding public infrastructure and investment have direct and indirect effects on businesses and the public. The Pointe Claire case and CoastalProtectSIM simulation provide a platform for policy experimentation under conditions of exogenous uncertainty (weather and climate change as well as endogenous effects generated by structure. We discuss the model in some detail, and present teaching materials developed to date to support the use of our work in public administration curricula. Our experience with this case demonstrates the potential of this approach to motivate sustainable learning about complexity in public management settings and enhance learners’ competency to deal with complex dynamic problems.

  13. Designing for Discovery Learning of Complexity Principles of Congestion by Driving Together in the TrafficJams Simulation

    Science.gov (United States)

    Levy, Sharona T.; Peleg, Ran; Ofeck, Eyal; Tabor, Naamit; Dubovi, Ilana; Bluestein, Shiri; Ben-Zur, Hadar

    2018-01-01

    We propose and evaluate a framework supporting collaborative discovery learning of complex systems. The framework blends five design principles: (1) individual action: amidst (2) social interactions; challenged with (3) multiple tasks; set in (4) a constrained interactive learning environment that draws attention to (5) highlighted target…

  14. How Do Students Regulate their Learning of Complex Systems with Hypermedia?.

    Science.gov (United States)

    Azevedo, Roger; Seibert, Diane; Guthrie, John T.; Cromley, Jennifer G.; Wang, Huei-yu; Tron, Myriam

    This study examined the role of different goal-setting instructional interventions in facilitating students' shift to more sophisticated mental models of the circulatory system as indicated by both performance and process data. Researchers adopted the information processing model of self-regulated learning of P. Winne and colleagues (1998, 2001)…

  15. NHL and RCGA Based Multi-Relational Fuzzy Cognitive Map Modeling for Complex Systems

    Directory of Open Access Journals (Sweden)

    Zhen Peng

    2015-11-01

    Full Text Available In order to model multi-dimensions and multi-granularities oriented complex systems, this paper firstly proposes a kind of multi-relational Fuzzy Cognitive Map (FCM to simulate the multi-relational system and its auto construct algorithm integrating Nonlinear Hebbian Learning (NHL and Real Code Genetic Algorithm (RCGA. The multi-relational FCM fits to model the complex system with multi-dimensions and multi-granularities. The auto construct algorithm can learn the multi-relational FCM from multi-relational data resources to eliminate human intervention. The Multi-Relational Data Mining (MRDM algorithm integrates multi-instance oriented NHL and RCGA of FCM. NHL is extended to mine the causal relationships between coarse-granularity concept and its fined-granularity concepts driven by multi-instances in the multi-relational system. RCGA is used to establish high-quality high-level FCM driven by data. The multi-relational FCM and the integrating algorithm have been applied in complex system of Mutagenesis. The experiment demonstrates not only that they get better classification accuracy, but it also shows the causal relationships among the concepts of the system.

  16. Effect of reinforcement learning on coordination of multiangent systems

    Science.gov (United States)

    Bukkapatnam, Satish T. S.; Gao, Greg

    2000-12-01

    For effective coordination of distributed environments involving multiagent systems, learning ability of each agent in the environment plays a crucial role. In this paper, we develop a simple group learning method based on reinforcement, and study its effect on coordination through application to a supply chain procurement scenario involving a computer manufacturer. Here, all parties are represented by self-interested, autonomous agents, each capable of performing specific simple tasks. They negotiate with each other to perform complex tasks and thus coordinate supply chain procurement. Reinforcement learning is intended to enable each agent to reach a best negotiable price within a shortest possible time. Our simulations of the application scenario under different learning strategies reveals the positive effects of reinforcement learning on an agent's as well as the system's performance.

  17. Multiple systems for motor skill learning.

    Science.gov (United States)

    Clark, Dav; Ivry, Richard B

    2010-07-01

    Motor learning is a ubiquitous feature of human competence. This review focuses on two particular classes of model tasks for studying skill acquisition. The serial reaction time (SRT) task is used to probe how people learn sequences of actions, while adaptation in the context of visuomotor or force field perturbations serves to illustrate how preexisting movements are recalibrated in novel environments. These tasks highlight important issues regarding the representational changes that occur during the course of motor learning. One important theme is that distinct mechanisms vary in their information processing costs during learning and performance. Fast learning processes may require few trials to produce large changes in performance but impose demands on cognitive resources. Slower processes are limited in their ability to integrate complex information but minimally demanding in terms of attention or processing resources. The representations derived from fast systems may be accessible to conscious processing and provide a relatively greater measure of flexibility, while the representations derived from slower systems are more inflexible and automatic in their behavior. In exploring these issues, we focus on how multiple neural systems may interact and compete during the acquisition and consolidation of new behaviors. Copyright © 2010 John Wiley & Sons, Ltd. This article is categorized under: Psychology > Motor Skill and Performance. Copyright © 2010 John Wiley & Sons, Ltd.

  18. Feature economy vs. logical complexity in phonological pattern learning

    NARCIS (Netherlands)

    Seinhorst, K.T.

    Complexity has been linked to ease of learning. This article explores the roles of two measures of complexity – feature economy and logical complexity – in the acquisition of sets of signs, taken from a small sign language that serves as an analogue of plosive inventories in spoken language. In a

  19. Improvement of Inquiry in a Complex Technology-Enhanced Learning Environment

    NARCIS (Netherlands)

    Pedaste, Margus; Kori, Külli; Maeots, Mario; de Jong, Anthonius J.M.; Riopel, Martin; Smyrnaiou, Zacharoula

    2016-01-01

    Inquiry learning is an effective approach in science education. Complex technology-enhanced learning environments are needed to apply inquiry worldwide to support knowledge gain and improvement of inquiry skills. In our study, we applied an ecology mission in the SCY-Lab learning environment and

  20. A deep learning approach for fetal QRS complex detection.

    Science.gov (United States)

    Zhong, Wei; Liao, Lijuan; Guo, Xuemei; Wang, Guoli

    2018-04-20

    Non-invasive foetal electrocardiography (NI-FECG) has the potential to provide more additional clinical information for detecting and diagnosing fetal diseases. We propose and demonstrate a deep learning approach for fetal QRS complex detection from raw NI-FECG signals by using a convolutional neural network (CNN) model. The main objective is to investigate whether reliable fetal QRS complex detection performance can still be obtained from features of single-channel NI-FECG signals, without canceling maternal ECG (MECG) signals. A deep learning method is proposed for recognizing fetal QRS complexes. Firstly, we collect data from set-a of the PhysioNet/computing in Cardiology Challenge database. The sample entropy method is used for signal quality assessment. Part of the bad quality signals is excluded in the further analysis. Secondly, in the proposed method, the features of raw NI-FECG signals are normalized before they are fed to a CNN classifier to perform fetal QRS complex detection. We use precision, recall, F-measure and accuracy as the evaluation metrics to assess the performance of fetal QRS complex detection. The proposed deep learning method can achieve relatively high precision (75.33%), recall (80.54%), and F-measure scores (77.85%) compared with three other well-known pattern classification methods, namely KNN, naive Bayes and SVM. the proposed deep learning method can attain reliable fetal QRS complex detection performance from the raw NI-FECG signals without canceling MECG signals. In addition, the influence of different activation functions and signal quality assessment on classification performance are evaluated, and results show that Relu outperforms the Sigmoid and Tanh on this particular task, and better classification performance is obtained with the signal quality assessment step in this study.

  1. Evolutionary and adaptive learning in complex markets: a brief summary

    Science.gov (United States)

    Hommes, Cars H.

    2007-06-01

    We briefly review some work on expectations and learning in complex markets, using the familiar demand-supply cobweb model. We discuss and combine two different approaches on learning. According to the adaptive learning approach, agents behave as econometricians using time series observations to form expectations, and update the parameters as more observations become available. This approach has become popular in macro. The second approach has an evolutionary flavor and is sometimes referred to as reinforcement learning. Agents employ different forecasting strategies and evaluate these strategies based upon a fitness measure, e.g. past realized profits. In this framework, boundedly rational agents switch between different, but fixed behavioral rules. This approach has become popular in finance. We combine evolutionary and adaptive learning to model complex markets and discuss whether this theory can match empirical facts and forecasting behavior in laboratory experiments with human subjects.

  2. Embracing Big Data in Complex Educational Systems: The Learning Analytics Imperative and the Policy Challenge

    Science.gov (United States)

    Macfadyen, Leah P.; Dawson, Shane; Pardo, Abelardo; Gaševic, Dragan

    2014-01-01

    In the new era of big educational data, learning analytics (LA) offer the possibility of implementing real-time assessment and feedback systems and processes at scale that are focused on improvement of learning, development of self-regulated learning skills, and student success. However, to realize this promise, the necessary shifts in the…

  3. Machine learning paradigms applications in recommender systems

    CERN Document Server

    Lampropoulos, Aristomenis S

    2015-01-01

    This timely book presents Applications in Recommender Systems which are making recommendations using machine learning algorithms trained via examples of content the user likes or dislikes. Recommender systems built on the assumption of availability of both positive and negative examples do not perform well when negative examples are rare. It is exactly this problem that the authors address in the monograph at hand. Specifically, the books approach is based on one-class classification methodologies that have been appearing in recent machine learning research. The blending of recommender systems and one-class classification provides a new very fertile field for research, innovation and development with potential applications in “big data” as well as “sparse data” problems. The book will be useful to researchers, practitioners and graduate students dealing with problems of extensive and complex data. It is intended for both the expert/researcher in the fields of Pattern Recognition, Machine Learning and ...

  4. The effect of multiple external representations (MERs) worksheets toward complex system reasoning achievement

    Science.gov (United States)

    Sumarno; Ibrahim, M.; Supardi, Z. A. I.

    2018-03-01

    The application of a systems approach to assessing biological systems provides hope for a coherent understanding of cell dynamics patterns and their relationship to plant life. This action required the reasoning about complex systems. In other sides, there were a lot of researchers who provided the proof about the instructional successions. They involved the multiple external representations which improved the biological learning. The researcher conducted an investigation using one shoot case study design which involved 30 students in proving that the MERs worksheets could affect the student's achievement of reasoning about complex system. The data had been collected based on test of reasoning about complex system and student's identification result who worked through MERs. The result showed that only partially students could achieve reasoning about system complex, but their MERs skill could support their reasoning ability of complex system. This study could bring a new hope to develop the MERs worksheet as a tool to facilitate the reasoning about complex system.

  5. Student Learning of Complex Earth Systems: Conceptual Frameworks of Earth Systems and Instructional Design

    Science.gov (United States)

    Scherer, Hannah H.; Holder, Lauren; Herbert, Bruce

    2017-01-01

    Engaging students in authentic problem solving concerning environmental issues in near-surface complex Earth systems involves both developing student conceptualization of Earth as a system and applying that scientific knowledge using techniques that model those used by professionals. In this first paper of a two-part series, we review the state of…

  6. Force and complexity of tongue task training influences behavioral measures of motor learning

    DEFF Research Database (Denmark)

    Kothari, Mohit; Svensson, Peter; Huo, Xueliang

    2012-01-01

    Relearning of motor skills is important in neurorehabilitation. We investigated the improvement of training success during simple tongue protrusion (two force levels) and a more complex tongue-training paradigm using the Tongue Drive System (TDS). We also compared subject-based reports of fun, pain...... training influences behavioral aspects of tongue motor learning....

  7. Interorganizational learning systems

    DEFF Research Database (Denmark)

    Hjalager, Anne-Mette

    1999-01-01

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

  8. Introduction to Focus Issue: Complex network perspectives on flow systems.

    Science.gov (United States)

    Donner, Reik V; Hernández-García, Emilio; Ser-Giacomi, Enrico

    2017-03-01

    During the last few years, complex network approaches have demonstrated their great potentials as versatile tools for exploring the structural as well as dynamical properties of dynamical systems from a variety of different fields. Among others, recent successful examples include (i) functional (correlation) network approaches to infer hidden statistical interrelationships between macroscopic regions of the human brain or the Earth's climate system, (ii) Lagrangian flow networks allowing to trace dynamically relevant fluid-flow structures in atmosphere, ocean or, more general, the phase space of complex systems, and (iii) time series networks unveiling fundamental organization principles of dynamical systems. In this spirit, complex network approaches have proven useful for data-driven learning of dynamical processes (like those acting within and between sub-components of the Earth's climate system) that are hidden to other analysis techniques. This Focus Issue presents a collection of contributions addressing the description of flows and associated transport processes from the network point of view and its relationship to other approaches which deal with fluid transport and mixing and/or use complex network techniques.

  9. Mixed-complexity artificial grammar learning in humans and macaque monkeys: evaluating learning strategies.

    Science.gov (United States)

    Wilson, Benjamin; Smith, Kenny; Petkov, Christopher I

    2015-03-01

    Artificial grammars (AG) can be used to generate rule-based sequences of stimuli. Some of these can be used to investigate sequence-processing computations in non-human animals that might be related to, but not unique to, human language. Previous AG learning studies in non-human animals have used different AGs to separately test for specific sequence-processing abilities. However, given that natural language and certain animal communication systems (in particular, song) have multiple levels of complexity, mixed-complexity AGs are needed to simultaneously evaluate sensitivity to the different features of the AG. Here, we tested humans and Rhesus macaques using a mixed-complexity auditory AG, containing both adjacent (local) and non-adjacent (longer-distance) relationships. Following exposure to exemplary sequences generated by the AG, humans and macaques were individually tested with sequences that were either consistent with the AG or violated specific adjacent or non-adjacent relationships. We observed a considerable level of cross-species correspondence in the sensitivity of both humans and macaques to the adjacent AG relationships and to the statistical properties of the sequences. We found no significant sensitivity to the non-adjacent AG relationships in the macaques. A subset of humans was sensitive to this non-adjacent relationship, revealing interesting between- and within-species differences in AG learning strategies. The results suggest that humans and macaques are largely comparably sensitive to the adjacent AG relationships and their statistical properties. However, in the presence of multiple cues to grammaticality, the non-adjacent relationships are less salient to the macaques and many of the humans. © 2015 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

  10. Brain signal complexity rises with repetition suppression in visual learning.

    Science.gov (United States)

    Lafontaine, Marc Philippe; Lacourse, Karine; Lina, Jean-Marc; McIntosh, Anthony R; Gosselin, Frédéric; Théoret, Hugo; Lippé, Sarah

    2016-06-21

    Neuronal activity associated with visual processing of an unfamiliar face gradually diminishes when it is viewed repeatedly. This process, known as repetition suppression (RS), is involved in the acquisition of familiarity. Current models suggest that RS results from interactions between visual information processing areas located in the occipito-temporal cortex and higher order areas, such as the dorsolateral prefrontal cortex (DLPFC). Brain signal complexity, which reflects information dynamics of cortical networks, has been shown to increase as unfamiliar faces become familiar. However, the complementarity of RS and increases in brain signal complexity have yet to be demonstrated within the same measurements. We hypothesized that RS and brain signal complexity increase occur simultaneously during learning of unfamiliar faces. Further, we expected alteration of DLPFC function by transcranial direct current stimulation (tDCS) to modulate RS and brain signal complexity over the occipito-temporal cortex. Participants underwent three tDCS conditions in random order: right anodal/left cathodal, right cathodal/left anodal and sham. Following tDCS, participants learned unfamiliar faces, while an electroencephalogram (EEG) was recorded. Results revealed RS over occipito-temporal electrode sites during learning, reflected by a decrease in signal energy, a measure of amplitude. Simultaneously, as signal energy decreased, brain signal complexity, as estimated with multiscale entropy (MSE), increased. In addition, prefrontal tDCS modulated brain signal complexity over the right occipito-temporal cortex during the first presentation of faces. These results suggest that although RS may reflect a brain mechanism essential to learning, complementary processes reflected by increases in brain signal complexity, may be instrumental in the acquisition of novel visual information. Such processes likely involve long-range coordinated activity between prefrontal and lower order visual

  11. Learning Visual Representations for Perception-Action Systems

    DEFF Research Database (Denmark)

    Piater, Justus; Jodogne, Sebastien; Detry, Renaud

    2011-01-01

    and RLJC, our second method learns structural object models for robust object detection and pose estimation by probabilistic inference. To these models, the method associates grasp experiences autonomously learned by trial and error. These experiences form a nonparametric representation of grasp success......We discuss vision as a sensory modality for systems that effect actions in response to perceptions. While the internal representations informed by vision may be arbitrarily complex, we argue that in many cases it is advantageous to link them rather directly to action via learned mappings....... These arguments are illustrated by two examples of our own work. First, our RLVC algorithm performs reinforcement learning directly on the visual input space. To make this very large space manageable, RLVC interleaves the reinforcement learner with a supervised classification algorithm that seeks to split...

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

    Science.gov (United States)

    Hurst, Jacob; Bull, Larry

    2006-01-01

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

  13. Prototypes and matrix relevance learning in complex fourier space

    NARCIS (Netherlands)

    Straat, M.; Kaden, M.; Gay, M.; Villmann, T.; Lampe, Alexander; Seiffert, U.; Biehl, M.; Melchert, F.

    2017-01-01

    In this contribution, we consider the classification of time-series and similar functional data which can be represented in complex Fourier coefficient space. We apply versions of Learning Vector Quantization (LVQ) which are suitable for complex-valued data, based on the so-called Wirtinger

  14. Action observation versus motor imagery in learning a complex motor task: a short review of literature and a kinematics study.

    Science.gov (United States)

    Gatti, R; Tettamanti, A; Gough, P M; Riboldi, E; Marinoni, L; Buccino, G

    2013-04-12

    Both motor imagery and action observation have been shown to play a role in learning or re-learning complex motor tasks. According to a well accepted view they share a common neurophysiological basis in the mirror neuron system. Neurons within this system discharge when individuals perform a specific action and when they look at another individual performing the same or a motorically related action. In the present paper, after a short review of literature on the role of action observation and motor imagery in motor learning, we report the results of a kinematics study where we directly compared motor imagery and action observation in learning a novel complex motor task. This involved movement of the right hand and foot in the same angular direction (in-phase movement), while at the same time moving the left hand and foot in an opposite angular direction (anti-phase movement), all at a frequency of 1Hz. Motor learning was assessed through kinematics recording of wrists and ankles. The results showed that action observation is better than motor imagery as a strategy for learning a novel complex motor task, at least in the fast early phase of motor learning. We forward that these results may have important implications in educational activities, sport training and neurorehabilitation. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  15. Citizen Data Science for Social Good in Complex Systems

    OpenAIRE

    Soumya Banerjee

    2018-01-01

    The confluence of massive amounts of openly available data, sophisticated machine learning algorithms and an enlightened citizenry willing to engage in data science presents novel opportunities for crowd sourced data science for social good. In this submission, I present vignettes of data science projects that I have been involved in and which have impact in various spheres of life and on social good. Complex systems are all around us: from social networks to transportation systems, cities, e...

  16. Variable complexity online sequential extreme learning machine, with applications to streamflow prediction

    Science.gov (United States)

    Lima, Aranildo R.; Hsieh, William W.; Cannon, Alex J.

    2017-12-01

    In situations where new data arrive continually, online learning algorithms are computationally much less costly than batch learning ones in maintaining the model up-to-date. The extreme learning machine (ELM), a single hidden layer artificial neural network with random weights in the hidden layer, is solved by linear least squares, and has an online learning version, the online sequential ELM (OSELM). As more data become available during online learning, information on the longer time scale becomes available, so ideally the model complexity should be allowed to change, but the number of hidden nodes (HN) remains fixed in OSELM. A variable complexity VC-OSELM algorithm is proposed to dynamically add or remove HN in the OSELM, allowing the model complexity to vary automatically as online learning proceeds. The performance of VC-OSELM was compared with OSELM in daily streamflow predictions at two hydrological stations in British Columbia, Canada, with VC-OSELM significantly outperforming OSELM in mean absolute error, root mean squared error and Nash-Sutcliffe efficiency at both stations.

  17. Variability in Second Language Learning: The Roles of Individual Differences, Learning Conditions, and Linguistic Complexity

    Science.gov (United States)

    Tagarelli, Kaitlyn M.; Ruiz, Simón; Vega, José Luis Moreno; Rebuschat, Patrick

    2016-01-01

    Second language learning outcomes are highly variable, due to a variety of factors, including individual differences, exposure conditions, and linguistic complexity. However, exactly how these factors interact to influence language learning is unknown. This article examines the relationship between these three variables in language learners.…

  18. A Concise Introduction to the Statistical Physics of Complex Systems

    CERN Document Server

    Bertin, Eric

    2012-01-01

    This concise primer (based on lectures given at summer schools on complex systems and on a masters degree course in complex systems modeling) will provide graduate students and newcomers to the field with the basic knowledge of the concepts and methods of statistical physics and its potential for application to interdisciplinary topics.  Indeed, in recent years, statistical physics has begun to attract the interest of a broad community of researchers in the field of complex system sciences, ranging from biology to the social sciences, economics and computer science. More generally, a growing number of graduate students and researchers feel the need to learn some basic concepts and questions originating in other disciplines without necessarily having to master all of the corresponding technicalities and jargon. Generally speaking, the goals of statistical physics may be summarized as follows: on the one hand to study systems composed of a large number of interacting ‘entities’, and on the other to predict...

  19. Assessing Complexity in Learning Outcomes--A Comparison between the SOLO Taxonomy and the Model of Hierarchical Complexity

    Science.gov (United States)

    Stålne, Kristian; Kjellström, Sofia; Utriainen, Jukka

    2016-01-01

    An important aspect of higher education is to educate students who can manage complex relationships and solve complex problems. Teachers need to be able to evaluate course content with regard to complexity, as well as evaluate students' ability to assimilate complex content and express it in the form of a learning outcome. One model for evaluating…

  20. Gradient descent learning algorithm overview: a general dynamical systems perspective.

    Science.gov (United States)

    Baldi, P

    1995-01-01

    Gives a unified treatment of gradient descent learning algorithms for neural networks using a general framework of dynamical systems. This general approach organizes and simplifies all the known algorithms and results which have been originally derived for different problems (fixed point/trajectory learning), for different models (discrete/continuous), for different architectures (forward/recurrent), and using different techniques (backpropagation, variational calculus, adjoint methods, etc.). The general approach can also be applied to derive new algorithms. The author then briefly examines some of the complexity issues and limitations intrinsic to gradient descent learning. Throughout the paper, the author focuses on the problem of trajectory learning.

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

    DEFF Research Database (Denmark)

    Dalsgaard, Christian

    2006-01-01

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

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

    Science.gov (United States)

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

    2012-02-01

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

  3. Task complexity, student perceptions of vocabulary learning in EFL, and task performance.

    Science.gov (United States)

    Wu, Xiaoli; Lowyck, Joost; Sercu, Lies; Elen, Jan

    2013-03-01

    The study deepened our understanding of how students' self-efficacy beliefs contribute to the context of teaching English as a foreign language in the framework of cognitive mediational paradigm at a fine-tuned task-specific level. The aim was to examine the relationship among task complexity, self-efficacy beliefs, domain-related prior knowledge, learning strategy use, and task performance as they were applied to English vocabulary learning from reading tasks. Participants were 120 second-year university students (mean age 21) from a Chinese university. This experiment had two conditions (simple/complex). A vocabulary level test was first conducted to measure participants' prior knowledge of English vocabulary. Participants were then randomly assigned to one of the learning tasks. Participants were administered task booklets together with the self-efficacy scales, measures of learning strategy use, and post-tests. Data obtained were submitted to multivariate analysis of variance (MANOVA) and path analysis. Results from the MANOVA model showed a significant effect of vocabulary level on self-efficacy beliefs, learning strategy use, and task performance. Task complexity showed no significant effect; however, an interaction effect between vocabulary level and task complexity emerged. Results from the path analysis showed self-efficacy beliefs had an indirect effect on performance. Our results highlighted the mediating role of self-efficacy beliefs and learning strategy use. Our findings indicate that students' prior knowledge plays a crucial role on both self-efficacy beliefs and task performance, and the predictive power of self-efficacy on task performance may lie in its association with learning strategy use. © 2011 The British Psychological Society.

  4. New designing of E-Learning systems with using network learning

    OpenAIRE

    Malayeri, Amin Daneshmand; Abdollahi, Jalal

    2010-01-01

    One of the most applied learning in virtual spaces is using E-Learning systems. Some E-Learning methodologies has been introduced, but the main subject is the most positive feedback from E-Learning systems. In this paper, we introduce a new methodology of E-Learning systems entitle "Network Learning" with review of another aspects of E-Learning systems. Also, we present benefits and advantages of using these systems in educating and fast learning programs. Network Learning can be programmable...

  5. Predicting protein complexes using a supervised learning method combined with local structural information.

    Science.gov (United States)

    Dong, Yadong; Sun, Yongqi; Qin, Chao

    2018-01-01

    The existing protein complex detection methods can be broadly divided into two categories: unsupervised and supervised learning methods. Most of the unsupervised learning methods assume that protein complexes are in dense regions of protein-protein interaction (PPI) networks even though many true complexes are not dense subgraphs. Supervised learning methods utilize the informative properties of known complexes; they often extract features from existing complexes and then use the features to train a classification model. The trained model is used to guide the search process for new complexes. However, insufficient extracted features, noise in the PPI data and the incompleteness of complex data make the classification model imprecise. Consequently, the classification model is not sufficient for guiding the detection of complexes. Therefore, we propose a new robust score function that combines the classification model with local structural information. Based on the score function, we provide a search method that works both forwards and backwards. The results from experiments on six benchmark PPI datasets and three protein complex datasets show that our approach can achieve better performance compared with the state-of-the-art supervised, semi-supervised and unsupervised methods for protein complex detection, occasionally significantly outperforming such methods.

  6. Energy and carbon emissions analysis and prediction of complex petrochemical systems based on an improved extreme learning machine integrated interpretative structural model

    International Nuclear Information System (INIS)

    Han, Yongming; Zhu, Qunxiong; Geng, Zhiqiang; Xu, Yuan

    2017-01-01

    Highlights: • The ELM integrated ISM (ISM-ELM) method is proposed. • The proposed method is more efficient and accurate than the ELM through the UCI data set. • Energy and carbon emissions analysis and prediction of petrochemical industries based ISM-ELM is obtained. • The proposed method is valid in improving energy efficiency and reducing carbon emissions of ethylene plants. - Abstract: Energy saving and carbon emissions reduction of the petrochemical industry are affected by many factors. Thus, it is difficult to analyze and optimize the energy of complex petrochemical systems accurately. This paper proposes an energy and carbon emissions analysis and prediction approach based on an improved extreme learning machine (ELM) integrated interpretative structural model (ISM) (ISM-ELM). ISM based the partial correlation coefficient is utilized to analyze key parameters that affect the energy and carbon emissions of the complex petrochemical system, and can denoise and reduce dimensions of data to decrease the training time and errors of the ELM prediction model. Meanwhile, in terms of the model accuracy and the training time, the robustness and effectiveness of the ISM-ELM model are better than the ELM through standard data sets from the University of California Irvine (UCI) repository. Moreover, a multi-inputs and single-output (MISO) model of energy and carbon emissions of complex ethylene systems is established based on the ISM-ELM. Finally, detailed analyses and simulations using the real ethylene plant data demonstrate the effectiveness of the ISM-ELM and can guide the improvement direction of energy saving and carbon emissions reduction in complex petrochemical systems.

  7. Formative assessment in an online learning environment to support flexible on-the-job learning in complex professional domains

    NARCIS (Netherlands)

    Tamara van Gog; Desirée Joosten-ten Brinke; F. J. Prins; Dominique Sluijsmans

    2010-01-01

    This article describes a blueprint for an online learning environment that is based on prominent instructional design and assessment theories for supporting learning in complex domains. The core of this environment consists of formative assessment tasks (i.e., assessment for learning) that center on

  8. Learning from simple ebooks, online cases or classroom teaching when acquiring complex knowledge. A randomized controlled trial in respiratory physiology and pulmonology.

    Science.gov (United States)

    Worm, Bjarne Skjødt

    2013-01-01

    E-learning is developing fast because of the rapid increased use of smartphones, tablets and portable computers. We might not think of it as e-learning, but today many new e-books are in fact very complex electronic teaching platforms. It is generally accepted that e-learning is as effective as classroom teaching methods, but little is known about its value in relaying contents of different levels of complexity to students. We set out to investigate e-learning effects on simple recall and complex problem-solving compared to classroom teaching. 63 nurses specializing in anesthesiology were evenly randomized into three groups. They were given internet-based knowledge tests before and after attending a teaching module about respiratory physiology and pulmonology. The three groups was either an e-learning group with eBook teaching material, an e-learning group with case-based teaching or a group with face-to-face case-based classroom teaching. After the module the students were required to answer a post-test. Time spent and the number of logged into the system was also measured. For simple recall, all methods were equally effective. For problem-solving, the eCase group achieved a comparable knowledge level to classroom teaching, while textbook learning was inferior to both (p<0.01). The textbook group also spent the least amount of time on acquiring knowledge (33 minutes, p<0.001), while the eCase group spent significantly more time on the subject (53 minutes, p<0.001) and logged into the system significantly more (2.8 vs 1.6, p<0.001). E-learning based cases are an effective tool for teaching complex knowledge and problem-solving ability, but future studies using higher-level e-learning are encouraged.Simple recall skills, however, do not require any particular learning method.

  9. Learning from simple ebooks, online cases or classroom teaching when acquiring complex knowledge. A randomized controlled trial in respiratory physiology and pulmonology.

    Directory of Open Access Journals (Sweden)

    Bjarne Skjødt Worm

    Full Text Available BACKGROUND AND AIMS: E-learning is developing fast because of the rapid increased use of smartphones, tablets and portable computers. We might not think of it as e-learning, but today many new e-books are in fact very complex electronic teaching platforms. It is generally accepted that e-learning is as effective as classroom teaching methods, but little is known about its value in relaying contents of different levels of complexity to students. We set out to investigate e-learning effects on simple recall and complex problem-solving compared to classroom teaching. METHODS: 63 nurses specializing in anesthesiology were evenly randomized into three groups. They were given internet-based knowledge tests before and after attending a teaching module about respiratory physiology and pulmonology. The three groups was either an e-learning group with eBook teaching material, an e-learning group with case-based teaching or a group with face-to-face case-based classroom teaching. After the module the students were required to answer a post-test. Time spent and the number of logged into the system was also measured. RESULTS: For simple recall, all methods were equally effective. For problem-solving, the eCase group achieved a comparable knowledge level to classroom teaching, while textbook learning was inferior to both (p<0.01. The textbook group also spent the least amount of time on acquiring knowledge (33 minutes, p<0.001, while the eCase group spent significantly more time on the subject (53 minutes, p<0.001 and logged into the system significantly more (2.8 vs 1.6, p<0.001. CONCLUSIONS: E-learning based cases are an effective tool for teaching complex knowledge and problem-solving ability, but future studies using higher-level e-learning are encouraged.Simple recall skills, however, do not require any particular learning method.

  10. Representational scripting for carrying out complex learning tasks

    NARCIS (Netherlands)

    Slof, B.

    2011-01-01

    Learning to solve complex problems is important because in our rapidly changing modern society and work environments knowing the answer is often not possible. Although educators and instructional designers acknowledge the benefits of problem solving, they also realize that learners need good

  11. Complex scenes and situations visualization in hierarchical learning algorithm with dynamic 3D NeoAxis engine

    Science.gov (United States)

    Graham, James; Ternovskiy, Igor V.

    2013-06-01

    We applied a two stage unsupervised hierarchical learning system to model complex dynamic surveillance and cyber space monitoring systems using a non-commercial version of the NeoAxis visualization software. The hierarchical scene learning and recognition approach is based on hierarchical expectation maximization, and was linked to a 3D graphics engine for validation of learning and classification results and understanding the human - autonomous system relationship. Scene recognition is performed by taking synthetically generated data and feeding it to a dynamic logic algorithm. The algorithm performs hierarchical recognition of the scene by first examining the features of the objects to determine which objects are present, and then determines the scene based on the objects present. This paper presents a framework within which low level data linked to higher-level visualization can provide support to a human operator and be evaluated in a detailed and systematic way.

  12. The Usefulness and Ease of Use of a Mobile Simulation Application for Learning of ERP Systems

    Directory of Open Access Journals (Sweden)

    Brenda Scholtz

    2017-10-01

    Full Text Available The hands-on use of complex, industrial Enterprise Resource Planning (ERP systems in educational contexts can be costly and complex. Tools that simulate the hands-on use of an ERP system have been proposed as alternatives. Research into the perceived usefulness (PU and perceived ease of use (PEOU of these simulation tools in an m-learning environment is limited. As part of this study, an m-learning simulation application (SYSPRO Latte was designed based on experiential learning theory and on a previously proposed theoretical framework for m-learning. The application simulates the hands-on experience of an ERP system. The purpose of this paper is to analyse the results of a study of 49 students who used SYSPRO Latte and completed a questionnaire on its PEOU and PU. The results revealed that students perceived SYSPRO Latte to be easy to use and useful, and verified other studies identifying a correlation between PEOU and PU. The study also confirmed the benefits of simulation-based learning and m-learning particularly for content presentation. The importance of considering design principles for m-learning applications was highlighted. This study is part of a larger, comprehensive research project that aims at improving learning of ERP systems in higher education.

  13. Supervised Learning for Dynamical System Learning.

    Science.gov (United States)

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

    2015-01-01

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

  14. Technological learning in bioenergy systems

    International Nuclear Information System (INIS)

    Junginger, Martin; Visser, Erika de; Hjort-Gregersen, Kurt; Koornneef, Joris; Raven, Rob; Faaij, Andre; Turkenburg, Wim

    2006-01-01

    The main goal of this article is to determine whether cost reductions in different bioenergy systems can be quantified using the experience curve approach, and how specific issues (arising from the complexity of biomass energy systems) can be addressed. This is pursued by case studies on biofuelled combined heat and power (CHP) plants in Sweden, global development of fluidized bed boilers and Danish biogas plants. As secondary goal, the aim is to identify learning mechanisms behind technology development and cost reduction for the biomass energy systems investigated. The case studies reveal large difficulties to devise empirical experience curves for investment costs of biomass-fuelled power plants. To some extent, this is due to lack of (detailed) data. The main reason, however, are varying plant costs due to differences in scale, fuel type, plant layout, region etc. For fluidized bed boiler plants built on a global level, progress ratios (PRs) for the price of entire plants lies approximately between 90-93% (which is typical for large plant-like technologies). The costs for the boiler section alone was found to decline much faster. The experience curve approach delivers better results, when the production costs of the final energy carrier are analyzed. Electricity from biofuelled CHP-plants yields PRs of 91-92%, i.e. an 8-9% reduction of electricity production costs with each cumulative doubling of electricity production. The experience curve for biogas production displays a PR of 85% from 1984 to the beginning of 1990, and then levels to approximately 100% until 2002. For technologies developed on a local level (e.g. biogas plants), learning-by-using and learning-by-interacting are important learning mechanism, while for CHP plants utilizing fluidized bed boilers, upscaling is probably one of the main mechanisms behind cost reductions

  15. Learning Content Management Systems

    Directory of Open Access Journals (Sweden)

    Tache JURUBESCU

    2008-01-01

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

  16. Multiscale Support Vector Learning With Projection Operator Wavelet Kernel for Nonlinear Dynamical System Identification.

    Science.gov (United States)

    Lu, Zhao; Sun, Jing; Butts, Kenneth

    2016-02-03

    A giant leap has been made in the past couple of decades with the introduction of kernel-based learning as a mainstay for designing effective nonlinear computational learning algorithms. In view of the geometric interpretation of conditional expectation and the ubiquity of multiscale characteristics in highly complex nonlinear dynamic systems [1]-[3], this paper presents a new orthogonal projection operator wavelet kernel, aiming at developing an efficient computational learning approach for nonlinear dynamical system identification. In the framework of multiresolution analysis, the proposed projection operator wavelet kernel can fulfill the multiscale, multidimensional learning to estimate complex dependencies. The special advantage of the projection operator wavelet kernel developed in this paper lies in the fact that it has a closed-form expression, which greatly facilitates its application in kernel learning. To the best of our knowledge, it is the first closed-form orthogonal projection wavelet kernel reported in the literature. It provides a link between grid-based wavelets and mesh-free kernel-based methods. Simulation studies for identifying the parallel models of two benchmark nonlinear dynamical systems confirm its superiority in model accuracy and sparsity.

  17. System Thinking Scales and Learning Environment of Family Planning Field Workers in East Java, Indonesia

    Science.gov (United States)

    Listyawardani, Dwi; Hariastuti, Iswari

    2016-01-01

    Systems thinking is needed due to the growing complexity of the problems faced family planning field workers in the external environment that is constantly changing. System thinking ability could not be separated from efforts to develop learning for the workers, both learning at the individual, group, or organization level. The design of the study…

  18. Leadership within Emergent Events in Complex Systems: Micro-Enactments and the Mechanisms of Organisational Learning and Change

    Science.gov (United States)

    Hazy, James K.; Silberstang, Joyce

    2009-01-01

    One tradition within the complexity paradigm considers organisations as complex adaptive systems in which autonomous individuals interact, often in complex ways with difficult to predict, non-linear outcomes. Building upon this tradition, and more specifically following the complex systems leadership theory approach, we describe the ways in which…

  19. Structure, Behavior, Function as a Framework For Teaching and Learning about Complexity In Ecosystems: Lessons from Middle School Classrooms (Invited)

    Science.gov (United States)

    Hmelo-Silver, C.; Gray, S.; Jordan, R.

    2010-12-01

    Complex systems surround us, and as Sabelli (2006) has argued, understanding complex systems is a critical component of science literacy. Understanding natural and designed systems are also prominent in the new draft science standards (NRC, 2010) and therefore of growing importance in the science classroom. Our work has focused on promoting an understanding of one complex natural system, aquatic ecosystems, which given current events, is fast becoming a requisite for informed decision-making as citizens (Jordan et al. 2008). Learners have difficulty understanding many concepts related to complex natural systems (e.g., Hmelo-Silver, Marathe, & Liu, 2007; Jordan, Gray, Liu, Demeter, & Hmelo-Silver, 2009). Studies of how students think about complex ecological systems (e.g; Hmelo-Silver, Marathe, & Liu, 2007; Hogan, 2000, Hogan & Fisherkeller, 1996: Covitt & Gunkel, 2008) have revealed difficulties in thinking beyond linear flow, single causality, and visible structure. Helping students to learn about ecosystems is a complex task that requires providing opportunities for students to not only engage directly with ecosystems but also with resources that provide relevant background knowledge and opportunities for learners to make their thinking visible. Both tasks can be difficult given the large spatial and temporal scales on which ecosystems operate. Additionally, visible components interact with often invisible components which can obscure ecosystem processes for students. Working in the context of aquatic ecosystems, we sought to provide learners with representations and simulations that make salient the relationship between system components. In particular, we provided learners with opportunities to experience both the micro-level and macro-level phenomena that are key to understanding ecosystems (Hmelo-Silver, Liu, Gray, & Jordan, submitted; Liu & Hmelo-Silver, 2008; Jacobson & Wilensky, 2006). To accomplish this, we needed to help learners make connections across

  20. SCScore: Synthetic Complexity Learned from a Reaction Corpus.

    Science.gov (United States)

    Coley, Connor W; Rogers, Luke; Green, William H; Jensen, Klavs F

    2018-02-26

    Several definitions of molecular complexity exist to facilitate prioritization of lead compounds, to identify diversity-inducing and complexifying reactions, and to guide retrosynthetic searches. In this work, we focus on synthetic complexity and reformalize its definition to correlate with the expected number of reaction steps required to produce a target molecule, with implicit knowledge about what compounds are reasonable starting materials. We train a neural network model on 12 million reactions from the Reaxys database to impose a pairwise inequality constraint enforcing the premise of this definition: that on average, the products of published chemical reactions should be more synthetically complex than their corresponding reactants. The learned metric (SCScore) exhibits highly desirable nonlinear behavior, particularly in recognizing increases in synthetic complexity throughout a number of linear synthetic routes.

  1. Systemic Analysis of the Cultural Production of a Virtual Learning Community

    Directory of Open Access Journals (Sweden)

    Germán Alejandro Miranda Díaz

    2013-04-01

    Full Text Available This paper describes a systemic analysis from the standpoint of activity theory of the cultural emergence of a virtual learning community as a complex system. Three levels of analysis were employed: data mining, visualization of complex systems and analysis of discursive interactions, with the aim of understanding the emerging phenomena of online learning and in order to have the necessary elements to assist in planning the formation of virtual communities in formal settings. This was carried out using six years of activity from 3,324 people from different documentary sources: 9,871,531 CMS records; 1,371,907 from LMS; 67,828 IRC statements; and 27,798 online forum comments. In the process, we observed how action aimed at socialization and discussion of its object evolve into historical-cultural milestones such as the culture of merit as opposed to certification, the division of labor and the process of transition from free software to free culture.

  2. Targeted learning in data science causal inference for complex longitudinal studies

    CERN Document Server

    van der Laan, Mark J

    2018-01-01

    This textbook for graduate students in statistics, data science, and public health deals with the practical challenges that come with big, complex, and dynamic data. It presents a scientific roadmap to translate real-world data science applications into formal statistical estimation problems by using the general template of targeted maximum likelihood estimators. These targeted machine learning algorithms estimate quantities of interest while still providing valid inference. Targeted learning methods within data science area critical component for solving scientific problems in the modern age. The techniques can answer complex questions including optimal rules for assigning treatment based on longitudinal data with time-dependent confounding, as well as other estimands in dependent data structures, such as networks. Included in Targeted Learning in Data Science are demonstrations with soft ware packages and real data sets that present a case that targeted learning is crucial for the next generatio...

  3. Generalized Combination Complex Synchronization for Fractional-Order Chaotic Complex Systems

    Directory of Open Access Journals (Sweden)

    Cuimei Jiang

    2015-07-01

    Full Text Available Based on two fractional-order chaotic complex drive systems and one fractional-order chaotic complex response system with different dimensions, we propose generalized combination complex synchronization. In this new synchronization scheme, there are two complex scaling matrices that are non-square matrices. On the basis of the stability theory of fractional-order linear systems, we design a general controller via active control. Additionally, by virtue of two complex scaling matrices, generalized combination complex synchronization between fractional-order chaotic complex systems and real systems is investigated. Finally, three typical examples are given to demonstrate the effectiveness and feasibility of the schemes.

  4. Fast social-like learning of complex behaviors based on motor motifs

    Science.gov (United States)

    Calvo Tapia, Carlos; Tyukin, Ivan Y.; Makarov, Valeri A.

    2018-05-01

    Social learning is widely observed in many species. Less experienced agents copy successful behaviors exhibited by more experienced individuals. Nevertheless, the dynamical mechanisms behind this process remain largely unknown. Here we assume that a complex behavior can be decomposed into a sequence of n motor motifs. Then a neural network capable of activating motor motifs in a given sequence can drive an agent. To account for (n -1 )! possible sequences of motifs in a neural network, we employ the winnerless competition approach. We then consider a teacher-learner situation: one agent exhibits a complex movement, while another one aims at mimicking the teacher's behavior. Despite the huge variety of possible motif sequences we show that the learner, equipped with the provided learning model, can rewire "on the fly" its synaptic couplings in no more than (n -1 ) learning cycles and converge exponentially to the durations of the teacher's motifs. We validate the learning model on mobile robots. Experimental results show that the learner is indeed capable of copying the teacher's behavior composed of six motor motifs in a few learning cycles. The reported mechanism of learning is general and can be used for replicating different functions, including, for example, sound patterns or speech.

  5. Implementation of a school-based social and emotional learning intervention: understanding diffusion processes within complex systems.

    Science.gov (United States)

    Evans, Rhiannon; Murphy, Simon; Scourfield, Jonathan

    2015-07-01

    Sporadic and inconsistent implementation remains a significant challenge for social and emotional learning (SEL) interventions. This may be partly explained by the dearth of flexible, causative models that capture the multifarious determinants of implementation practices within complex systems. This paper draws upon Rogers (2003) Diffusion of Innovations Theory to explain the adoption, implementation and discontinuance of a SEL intervention. A pragmatic, formative process evaluation was conducted in alignment with phase 1 of the UK Medical Research Council's framework for Developing and Evaluating Complex Interventions. Employing case-study methodology, qualitative data were generated with four socio-economically and academically contrasting secondary schools in Wales implementing the Student Assistance Programme. Semi-structured interviews were conducted with 15 programme stakeholders. Data suggested that variation in implementation activity could be largely attributed to four key intervention reinvention points, which contributed to the transformation of the programme as it interacted with contextual features and individual needs. These reinvention points comprise the following: intervention training, which captures the process through which adopters acquire knowledge about a programme and delivery expertise; intervention assessment, which reflects adopters' evaluation of an intervention in relation to contextual needs; intervention clarification, which comprises the cascading of knowledge through an organisation in order to secure support in delivery; and intervention responsibility, which refers to the process of assigning accountability for sustainable delivery. Taken together, these points identify opportunities to predict and intervene with potential implementation problems. Further research would benefit from exploring additional reinvention activity.

  6. Optimizing the number of steps in learning tasks for complex skills.

    Science.gov (United States)

    Nadolski, Rob J; Kirschner, Paul A; van Merriënboer, Jeroen J G

    2005-06-01

    Carrying out whole tasks is often too difficult for novice learners attempting to acquire complex skills. The common solution is to split up the tasks into a number of smaller steps. The number of steps must be optimized for efficient and effective learning. The aim of the study is to investigate the relation between the number of steps provided to learners and the quality of their learning of complex skills. It is hypothesized that students receiving an optimized number of steps will learn better than those receiving either the whole task in only one step or those receiving a large number of steps. Participants were 35 sophomore law students studying at Dutch universities, mean age=22.8 years (SD=3.5), 63% were female. Participants were randomly assigned to 1 of 3 computer-delivered versions of a multimedia programme on how to prepare and carry out a law plea. The versions differed only in the number of learning steps provided. Videotaped plea-performance results were determined, various related learning measures were acquired and all computer actions were logged and analyzed. Participants exposed to an intermediate (i.e. optimized) number of steps outperformed all others on the compulsory learning task. No differences in performance on a transfer task were found. A high number of steps proved to be less efficient for carrying out the learning task. An intermediate number of steps is the most effective, proving that the number of steps can be optimized for improving learning.

  7. Designing Computer-Supported Complex Systems Curricula for the Next Generation Science Standards in High School Science Classrooms

    Directory of Open Access Journals (Sweden)

    Susan A. Yoon

    2016-12-01

    Full Text Available We present a curriculum and instruction framework for computer-supported teaching and learning about complex systems in high school science classrooms. This work responds to a need in K-12 science education research and practice for the articulation of design features for classroom instruction that can address the Next Generation Science Standards (NGSS recently launched in the USA. We outline the features of the framework, including curricular relevance, cognitively rich pedagogies, computational tools for teaching and learning, and the development of content expertise, and provide examples of how the framework is translated into practice. We follow this up with evidence from a preliminary study conducted with 10 teachers and 361 students, aimed at understanding the extent to which students learned from the activities. Results demonstrated gains in students’ complex systems understanding and biology content knowledge. In interviews, students identified influences of various aspects of the curriculum and instruction framework on their learning.

  8. Pattern-recognition software detecting the onset of failures in complex systems

    International Nuclear Information System (INIS)

    Mott, J.; King, R.

    1987-01-01

    A very general mathematical framework for embodying learned data from a complex system and combining it with a current observation to estimate the true current state of the system has been implemented using nearly universal pattern-recognition algorithms and applied to surveillance of the EBR-II power plant. In this application the methodology can provide signal validation and replacement of faulty signals on a near-real-time basis for hundreds of plant parameters. The mathematical framework, the pattern-recognition algorithms, examples of the learning and estimating process, and plant operating decisions made using this methodology are discussed. The entire methodology has been reduced to a set of FORTRAN subroutines which are small, fast, robust and executable on a personal computer with a serial link to the system's data acquisition computer, or on the data acquisition computer itself

  9. Design and Use of a Learning Object for Finding Complex Polynomial Roots

    Science.gov (United States)

    Benitez, Julio; Gimenez, Marcos H.; Hueso, Jose L.; Martinez, Eulalia; Riera, Jaime

    2013-01-01

    Complex numbers are essential in many fields of engineering, but students often fail to have a natural insight of them. We present a learning object for the study of complex polynomials that graphically shows that any complex polynomials has a root and, furthermore, is useful to find the approximate roots of a complex polynomial. Moreover, we…

  10. ARCHITECTURES FOR DISTRIBUTED AND COMPLEX M-LEARNING SYSTEMS: Applying Intelligent Technologies.

    Directory of Open Access Journals (Sweden)

    Ozlem OZAN,

    2010-04-01

    Full Text Available Today mobile technologies have become an integral part of the learning activities. With mobile technologies ―Any time, anywhere, any device‖ promise of e-learning is going to become actually applicable and mobile technologies are going to provide opportunities to be ―always on‖ and connected for twenty-first century learners and to get information on demand with ―just enough, just in time, and just for me‖ approach (Yamamoto, Ozan, & Demiray, 2010. Mobile technology includes both hardware and networking applications; hence both of them are necessary for the existence of m-Learning. Today one of the big challenges of mobile learning is technical issues. This book provides case studies and solution about technical applications of mobile learning.The book's broader audience is anyone who is interested in mobile learning systems‘ architecture. Beside this, it gives valuable information for mobile learning designers.The book is edited by The book is edited by Angel Juan , Thanasis Daradoumis, Fatos Xhafa and Santi Caballé. Angel A. Juan is an associate professor of simulation and data analysis in the computer sciences department at the Open University of Catalonia (Spain.Thanasis Daradoumis is an associate professor

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

    Science.gov (United States)

    Kim, Dong Won; Yao, Jingtao

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

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

    Science.gov (United States)

    Chen, C. M.

    2008-01-01

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

  13. Machine learning systems

    Energy Technology Data Exchange (ETDEWEB)

    Forsyth, R

    1984-05-01

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

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

    Science.gov (United States)

    Qudrat-Ullah, Hassan

    2010-01-01

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

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

    Directory of Open Access Journals (Sweden)

    von Müller, Lutz

    2013-11-01

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

  16. Recommender Systems for Learning

    CERN Document Server

    Manouselis, Nikos; Verbert, Katrien; Duval, Erik

    2013-01-01

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

  17. Coupling Visualization, Simulation, and Deep Learning for Ensemble Steering of Complex Energy Models: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Potter, Kristin C [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Brunhart-Lupo, Nicholas J [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Bush, Brian W [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Gruchalla, Kenny M [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Bugbee, Bruce [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Krishnan, Venkat K [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-10-09

    We have developed a framework for the exploration, design, and planning of energy systems that combines interactive visualization with machine-learning based approximations of simulations through a general purpose dataflow API. Our system provides a visual inter- face allowing users to explore an ensemble of energy simulations representing a subset of the complex input parameter space, and spawn new simulations to 'fill in' input regions corresponding to new enegery system scenarios. Unfortunately, many energy simula- tions are far too slow to provide interactive responses. To support interactive feedback, we are developing reduced-form models via machine learning techniques, which provide statistically sound esti- mates of the full simulations at a fraction of the computational cost and which are used as proxies for the full-form models. Fast com- putation and an agile dataflow enhance the engagement with energy simulations, and allow researchers to better allocate computational resources to capture informative relationships within the system and provide a low-cost method for validating and quality-checking large-scale modeling efforts.

  18. Information system analysis of an e-learning system used for dental restorations simulation.

    Science.gov (United States)

    Bogdan, Crenguţa M; Popovici, Dorin M

    2012-09-01

    The goal of using virtual and augmented reality technologies in therapeutic interventions simulation, in the fixed prosthodontics (VirDenT) project, is to increase the quality of the educational process in dental faculties, by assisting students in learning how to prepare teeth for all-ceramic restorations. Its main component is an e-learning virtual reality-based software system that will be used for the developing skills in grinding teeth, needed in all-ceramic restorations. The complexity of the domain problem that the software system dealt with made the analysis of the information system supported by VirDenT necessary. The analysis contains the following activities: identification and classification of the system stakeholders, description of the business processes, formulation of the business rules, and modelling of business objects. During this stage, we constructed the context diagram, the business use case diagram, the activity diagrams and the class diagram of the domain model. These models are useful for the further development of the software system that implements the VirDenT information system. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  19. Complex Adaptive Systems of Systems (CASOS) engineering environment.

    Energy Technology Data Exchange (ETDEWEB)

    Detry, Richard Joseph; Linebarger, John Michael; Finley, Patrick D.; Maffitt, S. Louise; Glass, Robert John, Jr.; Beyeler, Walter Eugene; Ames, Arlo Leroy

    2012-02-01

    Complex Adaptive Systems of Systems, or CASoS, are vastly complex physical-socio-technical systems which we must understand to design a secure future for the nation. The Phoenix initiative implements CASoS Engineering principles combining the bottom up Complex Systems and Complex Adaptive Systems view with the top down Systems Engineering and System-of-Systems view. CASoS Engineering theory and practice must be conducted together to develop a discipline that is grounded in reality, extends our understanding of how CASoS behave and allows us to better control the outcomes. The pull of applications (real world problems) is critical to this effort, as is the articulation of a CASoS Engineering Framework that grounds an engineering approach in the theory of complex adaptive systems of systems. Successful application of the CASoS Engineering Framework requires modeling, simulation and analysis (MS and A) capabilities and the cultivation of a CASoS Engineering Community of Practice through knowledge sharing and facilitation. The CASoS Engineering Environment, itself a complex adaptive system of systems, constitutes the two platforms that provide these capabilities.

  20. Zebrafish and relational memory: Could a simple fish be useful for the analysis of biological mechanisms of complex vertebrate learning?

    Science.gov (United States)

    Gerlai, Robert

    2017-08-01

    Analysis of the zebrafish allows one to combine two distinct scientific approaches, comparative ethology and neurobehavioral genetics. Furthermore, this species arguably represents an optimal compromise between system complexity and practical simplicity. This mini-review focuses on a complex form of learning, relational learning and memory, in zebrafish. It argues that zebrafish are capable of this type of learning, and it attempts to show how this species may be useful in the analysis of the mechanisms and the evolution of this complex brain function. The review is not intended to be comprehensive. It is a short opinion piece that reflects the author's own biases, and it draws some of its examples from the work coming from his own laboratory. Nevertheless, it is written in the hope that it will persuade those who have not utilized zebrafish and who may be interested in opening their research horizon to this relatively novel but powerful vertebrate research tool. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Interaction and Technological Resources to Support Learning of Complex Numbers

    Directory of Open Access Journals (Sweden)

    Cassiano Scott Puhl

    2016-02-01

    Full Text Available This article presents a didactic proposal, a workshop for the introduction of the study of complex numbers. Unlike recurrent practices, the workshop began developing the geometric shape of the complex number, implicitly, through vectors. Eliminating student formal vision and algebraic, enriching the teaching practice. The main objective of the strategy was to build the concept of imaginary unit without causing a feeling of strangeness or insignificance of number. The theory of David Ausubel, meaningful learning, the workshop was based on a strategy developed to analyze the subsumers of students and develop a learning by subject. Combined with dynamic and interactive activities in the workshop, there is the use of a learning object (http://matematicacomplexa.meximas.com/. An environment created and basing on the theory of meaningful learning, making students reflect and interact in developed applications sometimes being challenged and other testing hypotheses and, above all, building knowledge. This proposal provided a rich environment for exchange of information between participants and deepening of ideas and concepts that served as subsumers. The result of the experience was very positive, as evidenced by the comments and data submitted by the participants, thus demonstrating that the objectives of this didactic proposal have been achieved.

  2. Power, autonomy, utopia new approaches toward complex systems

    CERN Document Server

    1986-01-01

    The "world" is becoming more and more intractable. We have learned to discern "systems" in it, we have developed a highly sophisticated math­ ematical apparatus to "model'" them, large computer simulation programs handle thousands of equations with zillions of parameters. But how ade­ quate are these efforts? Part One of this volume is a discussion containing some proposals for eliminating the constraints we encounter when approaching complex systems with our models: Is it possible, at all, to design a political or econom­ ic system without considering killing, torture, and oppression? Can we adequately model the present state of affairs while ignoring their often symbolic and paradoxical nature? Is it possible to explain teleological concepts such as "means" and "ends" in terms of basically 17th century Newtonian mechanics? Can we really make appropriate use of the vast a­ mount of systems concepts without exploring their relations, without de­ veloping a "system of systems concepts"? And why do more th...

  3. Everyday complexities and sociomaterialities of learning, technology, affects and effects

    DEFF Research Database (Denmark)

    Hansbøl, Mikala

    design with particular intended educational purposes (e.g. educational technology and technology education), the everyday complexities and sociomaterialities of learning and technology intermingles with how students/professionals become affected by digital technology and hence also which matters......This paper starts out with the challenge of establishing and researching relationships between educational design, digital technology and professional learning. The paper is empirical and takes point of departure in case examples from two development projects with a focus on professional education....... Both projects focus on new waysto build relationships between digital technologies, professional education and learning. Each project takes a different take on how to approach and position digital technology and it’s relationships with the educational programs and students’ learning. Project Wellfare...

  4. Modeling learning technology systems as business systems

    NARCIS (Netherlands)

    Avgeriou, Paris; Retalis, Symeon; Papaspyrou, Nikolaos

    2003-01-01

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

  5. Nonlinear Dynamics, Chaotic and Complex Systems

    Science.gov (United States)

    Infeld, E.; Zelazny, R.; Galkowski, A.

    2011-04-01

    Part I. Dynamic Systems Bifurcation Theory and Chaos: 1. Chaos in random dynamical systems V. M. Gunldach; 2. Controlling chaos using embedded unstable periodic orbits: the problem of optimal periodic orbits B. R. Hunt and E. Ott; 3. Chaotic tracer dynamics in open hydrodynamical flows G. Karolyi, A. Pentek, T. Tel and Z. Toroczkai; 4. Homoclinic chaos L. P. Shilnikov; Part II. Spatially Extended Systems: 5. Hydrodynamics of relativistic probability flows I. Bialynicki-Birula; 6. Waves in ionic reaction-diffusion-migration systems P. Hasal, V. Nevoral, I. Schreiber, H. Sevcikova, D. Snita, and M. Marek; 7. Anomalous scaling in turbulence: a field theoretical approach V. Lvov and I. Procaccia; 8. Abelian sandpile cellular automata M. Markosova; 9. Transport in an incompletely chaotic magnetic field F. Spineanu; Part III. Dynamical Chaos Quantum Physics and Foundations Of Statistical Mechanics: 10. Non-equilibrium statistical mechanics and ergodic theory L. A. Bunimovich; 11. Pseudochaos in statistical physics B. Chirikov; 12. Foundations of non-equilibrium statistical mechanics J. P. Dougherty; 13. Thermomechanical particle simulations W. G. Hoover, H. A. Posch, C. H. Dellago, O. Kum, C. G. Hoover, A. J. De Groot and B. L. Holian; 14. Quantum dynamics on a Markov background and irreversibility B. Pavlov; 15. Time chaos and the laws of nature I. Prigogine and D. J. Driebe; 16. Evolutionary Q and cognitive systems: dynamic entropies and predictability of evolutionary processes W. Ebeling; 17. Spatiotemporal chaos information processing in neural networks H. Szu; 18. Phase transitions and learning in neural networks C. Van den Broeck; 19. Synthesis of chaos A. Vanecek and S. Celikovsky; 20. Computational complexity of continuous problems H. Wozniakowski; Part IV. Complex Systems As An Interface Between Natural Sciences and Environmental Social and Economic Sciences: 21. Stochastic differential geometry in finance studies V. G. Makhankov; Part V. Conference Banquet

  6. Multimodal versus Unimodal Instructions in a Complex Learning Context.

    NARCIS (Netherlands)

    Gellevij, M.R.M.; van der Meij, Hans; de Jong, Anthonius J.M.; Pieters, Julius Marie

    2002-01-01

    Multimodal instruction with text and pictures was compared with unimodal, text-only instruction. More specifically, 44 students used a visual or a textual manual to learn a complex software application. During 2 103–116-min training sessions, cognitive load, and time and ability to recover from

  7. Multimodal versus Unimodal Instruction in a Complex Learning Context.

    Science.gov (United States)

    Gellevij, Mark; van der Meij, Hans; de Jong, Ton; Pieters, Jules

    2002-01-01

    Compared multimodal instruction with text and pictures with unimodal text-only instruction as 44 college students used a visual or textual manual to learn a complex software application. Results initially support dual coding theory and indicate that multimodal instruction led to better performance than unimodal instruction. (SLD)

  8. Community Learning Campus: It Takes a Simple Message to Build a Complex Project

    Science.gov (United States)

    Pearson, George

    2012-01-01

    Education Canada asked Tom Thompson, president of Olds College and a prime mover behind the Community Learning Campus (CLC): What were the lessons learned from this unusually ambitious education project? Thompson mentions six lessons he learned from this complex project which include: (1) Dream big, build small, act now; (2) Keep a low profile at…

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

    Directory of Open Access Journals (Sweden)

    Ali Alharbi

    2014-06-01

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

  10. Modeling Complex Systems

    CERN Document Server

    Boccara, Nino

    2010-01-01

    Modeling Complex Systems, 2nd Edition, explores the process of modeling complex systems, providing examples from such diverse fields as ecology, epidemiology, sociology, seismology, and economics. It illustrates how models of complex systems are built and provides indispensable mathematical tools for studying their dynamics. This vital introductory text is useful for advanced undergraduate students in various scientific disciplines, and serves as an important reference book for graduate students and young researchers. This enhanced second edition includes: . -recent research results and bibliographic references -extra footnotes which provide biographical information on cited scientists who have made significant contributions to the field -new and improved worked-out examples to aid a student’s comprehension of the content -exercises to challenge the reader and complement the material Nino Boccara is also the author of Essentials of Mathematica: With Applications to Mathematics and Physics (Springer, 2007).

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

    Science.gov (United States)

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

    1988-01-01

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

  12. What Learning Systems do Intelligent Agents Need? Complementary Learning Systems Theory Updated.

    Science.gov (United States)

    Kumaran, Dharshan; Hassabis, Demis; McClelland, James L

    2016-07-01

    We update complementary learning systems (CLS) theory, which holds that intelligent agents must possess two learning systems, instantiated in mammalians in neocortex and hippocampus. The first gradually acquires structured knowledge representations while the second quickly learns the specifics of individual experiences. We broaden the role of replay of hippocampal memories in the theory, noting that replay allows goal-dependent weighting of experience statistics. We also address recent challenges to the theory and extend it by showing that recurrent activation of hippocampal traces can support some forms of generalization and that neocortical learning can be rapid for information that is consistent with known structure. Finally, we note the relevance of the theory to the design of artificial intelligent agents, highlighting connections between neuroscience and machine learning. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Extending Life Concepts to Complex Systems

    Directory of Open Access Journals (Sweden)

    Jean Le Fur

    2013-01-01

    Full Text Available There is still no consensus definition of complex systems. This article explores, as a heuristic approach, the possibility of using notions associated with life as transversal concepts for defining complex systems. This approach is developed within a general classification of systems, with complex systems considered as a general ‘living things’ category and living organisms as a specialised class within this category. Concepts associated with life are first explored in the context of complex systems: birth, death and lifetime, adaptation, ontogeny and growth, reproduction. Thereafter, a refutation approach is used to test the proposed classification against a set of diverse systems, including a reference case, edge cases and immaterial complex systems. The summary of this analysis is then used to generate a definition of complex systems, based on the proposal, and within the background of cybernetics, complex adaptive systems and biology. Using notions such as ‘birth’ or ‘lifespan’ as transversal concepts may be of heuristic value for the generic characterization of complex systems, opening up new lines of research for improving their definition.

  14. Critical Points in Distance Learning System

    Directory of Open Access Journals (Sweden)

    Airina Savickaitė

    2013-08-01

    Full Text Available Purpose – This article presents the results of distance learning system analysis, i.e. the critical elements of the distance learning system. The critical points of distance learning are a part of distance education online environment interactivity/community process model. The most important is the fact that the critical point is associated with distance learning participants. Design/methodology/approach – Comparative review of articles and analysis of distance learning module. Findings – A modern man is a lifelong learner and distance learning is a way to be a modern person. The focus on a learner and feedback is the most important thing of learning distance system. Also, attention should be paid to the lecture-appropriate knowledge and ability to convey information. Distance system adaptation is the way to improve the learner’s learning outcomes. Research limitations/implications – Different learning disciplines and learning methods may have different critical points. Practical implications – The information of analysis could be important for both lecturers and students, who studies distance education systems. There are familiar critical points which may deteriorate the quality of learning. Originality/value – The study sought to develop remote systems for applications in order to improve the quality of knowledge. Keywords: distance learning, process model, critical points. Research type: review of literature and general overview.

  15. Students' explanations in complex learning of disciplinary programming

    Science.gov (United States)

    Vieira, Camilo

    Computational Science and Engineering (CSE) has been denominated as the third pillar of science and as a set of important skills to solve the problems of a global society. Along with the theoretical and the experimental approaches, computation offers a third alternative to solve complex problems that require processing large amounts of data, or representing complex phenomena that are not easy to experiment with. Despite the relevance of CSE, current professionals and scientists are not well prepared to take advantage of this set of tools and methods. Computation is usually taught in an isolated way from engineering disciplines, and therefore, engineers do not know how to exploit CSE affordances. This dissertation intends to introduce computational tools and methods contextualized within the Materials Science and Engineering curriculum. Considering that learning how to program is a complex task, the dissertation explores effective pedagogical practices that can support student disciplinary and computational learning. Two case studies will be evaluated to identify the characteristics of effective worked examples in the context of CSE. Specifically, this dissertation explores students explanations of these worked examples in two engineering courses with different levels of transparency: a programming course in materials science and engineering glass box and a thermodynamics course involving computational representations black box. Results from this study suggest that students benefit in different ways from writing in-code comments. These benefits include but are not limited to: connecting xv individual lines of code to the overall problem, getting familiar with the syntax, learning effective algorithm design strategies, and connecting computation with their discipline. Students in the glass box context generate higher quality explanations than students in the black box context. These explanations are related to students prior experiences. Specifically, students with

  16. Influence of learning strategy on response time during complex value-based learning and choice.

    Directory of Open Access Journals (Sweden)

    Shiva Farashahi

    Full Text Available Measurements of response time (RT have long been used to infer neural processes underlying various cognitive functions such as working memory, attention, and decision making. However, it is currently unknown if RT is also informative about various stages of value-based choice, particularly how reward values are constructed. To investigate these questions, we analyzed the pattern of RT during a set of multi-dimensional learning and decision-making tasks that can prompt subjects to adopt different learning strategies. In our experiments, subjects could use reward feedback to directly learn reward values associated with possible choice options (object-based learning. Alternatively, they could learn reward values of options' features (e.g. color, shape and combine these values to estimate reward values for individual options (feature-based learning. We found that RT was slower when the difference between subjects' estimates of reward probabilities for the two alternative objects on a given trial was smaller. Moreover, RT was overall faster when the preceding trial was rewarded or when the previously selected object was present. These effects, however, were mediated by an interaction between these factors such that subjects were faster when the previously selected object was present rather than absent but only after unrewarded trials. Finally, RT reflected the learning strategy (i.e. object-based or feature-based approach adopted by the subject on a trial-by-trial basis, indicating an overall faster construction of reward value and/or value comparison during object-based learning. Altogether, these results demonstrate that the pattern of RT can be informative about how reward values are learned and constructed during complex value-based learning and decision making.

  17. Criteria for the Development of Complex Teaching-Learning Environments.

    Science.gov (United States)

    Achtenhagen, Frank

    2001-01-01

    Relates aspects of the didactic tradition, especially the German didactic tradition, to the theory and practice of instructional design. Focuses on processes that are necessary to the modeling of reality and describes the design and development of a virtual enterprise as a complex teaching-learning environment in a German business school.…

  18. Complex Systems: An Introduction

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 14; Issue 9. Complex Systems: An Introduction - Anthropic Principle, Terrestrial Complexity, Complex Materials. V K Wadhawan. General Article Volume 14 Issue 9 September 2009 pp 894-906 ...

  19. Probing Interactions in Complex Molecular Systems through Ordered Assembly

    International Nuclear Information System (INIS)

    De Yoreo, J.J.; Bartelt, M.C.; Orme, C.A.; Villacampa, A.; Weeks, B.L.; Miller, A.E.

    2002-01-01

    Emerging from the machinery of epitaxial science and chemical synthesis, is a growing emphasis on development of self-organized systems of complex molecular species. The nature of self-organization in these systems spans the continuum from simple crystallization of large molecules such as dendrimers and proteins, to assembly into large organized networks of nanometer-scale structures such as quantum dots or nanoparticles. In truth, self-organization in complex molecular systems has always been a central feature of many scientific disciplines including fields as diverse as structural biology, polymer science and geochemistry. But over the past decade, changes in those fields have often been marked by the degree to which researchers are using molecular-scale approaches to understand the hierarchy of structures and processes driven by this ordered assembly. At the same time, physical scientists have begun to use their knowledge of simple atomic and molecular systems to fabricate synthetic self-organized systems. This increasing activity in the field of self-organization is testament to the success of the physical and chemical sciences in building a detailed understanding of crystallization and epitaxy in simple atomic and molecular systems, one that is soundly rooted in thermodynamics and chemical kinetics. One of the fundamental challenges of chemistry and materials science in the coming decades is to develop a similarly well-founded physical understanding of assembly processes in complex molecular systems. Over the past five years, we have successfully used in situ atomic force microscopy (AFM) to investigate the physical controls on single crystal epitaxy from solutions for a wide range of molecular species. More recently, we have combined this method with grazing incidence X-ray diffraction and kinetic Monte Carlo modeling in order to relate morphology to surface atomic structure and processes. The purpose of this proposal was to extend this approach to assemblies

  20. Complex Systems and Dependability

    CERN Document Server

    Zamojski, Wojciech; Sugier, Jaroslaw

    2012-01-01

    Typical contemporary complex system is a multifaceted amalgamation of technical, information, organization, software and human (users, administrators and management) resources. Complexity of such a system comes not only from its involved technical and organizational structure but mainly from complexity of information processes that must be implemented in the operational environment (data processing, monitoring, management, etc.). In such case traditional methods of reliability analysis focused mainly on technical level are usually insufficient in performance evaluation and more innovative meth

  1. Communities of Practice and Social Learning Systems: the Career of a Concept

    Science.gov (United States)

    Wenger, Etienne

    The concept of community of practice was not born in the systems theory tradition. It has its roots in attempts to develop accounts of the social nature of human learning inspired by anthropology and social theory (Lave, 1988; Bourdieu, 1977; Giddens, 1984; Foucault, 1980; Vygotsky, 1978). But the concept of community of practice is well aligned with the perspective of systems traditions. A community of practice itself can be viewed as a simple social system. And a complex social system can be viewed as constituted by interrelated communities of practice. In this essay I first explore the systemic nature of the concept at these two levels. Then I use this foundation to look at the applications of the concept, some of its main critiques, and its potential for developing a social discipline of learning.

  2. LDA merging and splitting with applications to multiagent cooperative learning and system alteration.

    Science.gov (United States)

    Pang, Shaoning; Ban, Tao; Kadobayashi, Youki; Kasabov, Nikola K

    2012-04-01

    To adapt linear discriminant analysis (LDA) to real-world applications, there is a pressing need to equip it with an incremental learning ability to integrate knowledge presented by one-pass data streams, a functionality to join multiple LDA models to make the knowledge sharing between independent learning agents more efficient, and a forgetting functionality to avoid reconstruction of the overall discriminant eigenspace caused by some irregular changes. To this end, we introduce two adaptive LDA learning methods: LDA merging and LDA splitting. These provide the benefits of ability of online learning with one-pass data streams, retained class separability identical to the batch learning method, high efficiency for knowledge sharing due to condensed knowledge representation by the eigenspace model, and more preferable time and storage costs than traditional approaches under common application conditions. These properties are validated by experiments on a benchmark face image data set. By a case study on the application of the proposed method to multiagent cooperative learning and system alternation of a face recognition system, we further clarified the adaptability of the proposed methods to complex dynamic learning tasks.

  3. Effect of Error Augmentation on Brain Activation and Motor Learning of a Complex Locomotor Task

    Directory of Open Access Journals (Sweden)

    Laura Marchal-Crespo

    2017-09-01

    Full Text Available Up to date, the functional gains obtained after robot-aided gait rehabilitation training are limited. Error augmenting strategies have a great potential to enhance motor learning of simple motor tasks. However, little is known about the effect of these error modulating strategies on complex tasks, such as relearning to walk after a neurologic accident. Additionally, neuroimaging evaluation of brain regions involved in learning processes could provide valuable information on behavioral outcomes. We investigated the effect of robotic training strategies that augment errors—error amplification and random force disturbance—and training without perturbations on brain activation and motor learning of a complex locomotor task. Thirty-four healthy subjects performed the experiment with a robotic stepper (MARCOS in a 1.5 T MR scanner. The task consisted in tracking a Lissajous figure presented on a display by coordinating the legs in a gait-like movement pattern. Behavioral results showed that training without perturbations enhanced motor learning in initially less skilled subjects, while error amplification benefited better-skilled subjects. Training with error amplification, however, hampered transfer of learning. Randomly disturbing forces induced learning and promoted transfer in all subjects, probably because the unexpected forces increased subjects' attention. Functional MRI revealed main effects of training strategy and skill level during training. A main effect of training strategy was seen in brain regions typically associated with motor control and learning, such as, the basal ganglia, cerebellum, intraparietal sulcus, and angular gyrus. Especially, random disturbance and no perturbation lead to stronger brain activation in similar brain regions than error amplification. Skill-level related effects were observed in the IPS, in parts of the superior parietal lobe (SPL, i.e., precuneus, and temporal cortex. These neuroimaging findings

  4. Encyclopedia of Complexity and Systems Science

    CERN Document Server

    Meyers, Robert A

    2009-01-01

    Encyclopedia of Complexity and Systems Science provides an authoritative single source for understanding and applying the concepts of complexity theory together with the tools and measures for analyzing complex systems in all fields of science and engineering. The science and tools of complexity and systems science include theories of self-organization, complex systems, synergetics, dynamical systems, turbulence, catastrophes, instabilities, nonlinearity, stochastic processes, chaos, neural networks, cellular automata, adaptive systems, and genetic algorithms. Examples of near-term problems and major unknowns that can be approached through complexity and systems science include: The structure, history and future of the universe; the biological basis of consciousness; the integration of genomics, proteomics and bioinformatics as systems biology; human longevity limits; the limits of computing; sustainability of life on earth; predictability, dynamics and extent of earthquakes, hurricanes, tsunamis, and other n...

  5. Multiscale asymmetric orthogonal wavelet kernel for linear programming support vector learning and nonlinear dynamic systems identification.

    Science.gov (United States)

    Lu, Zhao; Sun, Jing; Butts, Kenneth

    2014-05-01

    Support vector regression for approximating nonlinear dynamic systems is more delicate than the approximation of indicator functions in support vector classification, particularly for systems that involve multitudes of time scales in their sampled data. The kernel used for support vector learning determines the class of functions from which a support vector machine can draw its solution, and the choice of kernel significantly influences the performance of a support vector machine. In this paper, to bridge the gap between wavelet multiresolution analysis and kernel learning, the closed-form orthogonal wavelet is exploited to construct new multiscale asymmetric orthogonal wavelet kernels for linear programming support vector learning. The closed-form multiscale orthogonal wavelet kernel provides a systematic framework to implement multiscale kernel learning via dyadic dilations and also enables us to represent complex nonlinear dynamics effectively. To demonstrate the superiority of the proposed multiscale wavelet kernel in identifying complex nonlinear dynamic systems, two case studies are presented that aim at building parallel models on benchmark datasets. The development of parallel models that address the long-term/mid-term prediction issue is more intricate and challenging than the identification of series-parallel models where only one-step ahead prediction is required. Simulation results illustrate the effectiveness of the proposed multiscale kernel learning.

  6. Optimal Control of Complex Systems Based on Improved Dual Heuristic Dynamic Programming Algorithm

    Directory of Open Access Journals (Sweden)

    Hui Li

    2017-01-01

    Full Text Available When applied to solving the data modeling and optimal control problems of complex systems, the dual heuristic dynamic programming (DHP technique, which is based on the BP neural network algorithm (BP-DHP, has difficulty in prediction accuracy, slow convergence speed, poor stability, and so forth. In this paper, a dual DHP technique based on Extreme Learning Machine (ELM algorithm (ELM-DHP was proposed. Through constructing three kinds of network structures, the paper gives the detailed realization process of the DHP technique in the ELM. The controller designed upon the ELM-DHP algorithm controlled a molecular distillation system with complex features, such as multivariability, strong coupling, and nonlinearity. Finally, the effectiveness of the algorithm is verified by the simulation that compares DHP and HDP algorithms based on ELM and BP neural network. The algorithm can also be applied to solve the data modeling and optimal control problems of similar complex systems.

  7. Adaptive generalized combination complex synchronization of uncertain real and complex nonlinear systems

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Shi-bing, E-mail: wang-shibing@dlut.edu.cn, E-mail: wangxy@dlut.edu.cn [School of Computer and Information Engineering, Fuyang Normal University, Fuyang 236041 (China); Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China); Wang, Xing-yuan, E-mail: wang-shibing@dlut.edu.cn, E-mail: wangxy@dlut.edu.cn [Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China); Wang, Xiu-you [School of Computer and Information Engineering, Fuyang Normal University, Fuyang 236041 (China); Zhou, Yu-fei [College of Electrical Engineering and Automation, Anhui University, Hefei 230601 (China)

    2016-04-15

    With comprehensive consideration of generalized synchronization, combination synchronization and adaptive control, this paper investigates a novel adaptive generalized combination complex synchronization (AGCCS) scheme for different real and complex nonlinear systems with unknown parameters. On the basis of Lyapunov stability theory and adaptive control, an AGCCS controller and parameter update laws are derived to achieve synchronization and parameter identification of two real drive systems and a complex response system, as well as two complex drive systems and a real response system. Two simulation examples, namely, ACGCS for chaotic real Lorenz and Chen systems driving a hyperchaotic complexsystem, and hyperchaotic complex Lorenz and Chen systems driving a real chaotic Lü system, are presented to verify the feasibility and effectiveness of the proposed scheme.

  8. Synthesis for the Interdisciplinary Environmental Sciences: Integrating Systems Approaches and Service Learning

    Science.gov (United States)

    Simon, Gregory L.; Wee, Bryan Shao-Chang; Chin, Anne; Tindle, Amy Depierre; Guth, Dan; Mason, Hillary

    2013-01-01

    As our understanding of complex environmental issues increases, institutions of higher education are evolving to develop new learning models that emphasize synthesis across disciplines, concepts, data, and methodologies. To this end, we argue for the implementation of environmental science education at the intersection of systems theory and…

  9. Management of complex dynamical systems

    Science.gov (United States)

    MacKay, R. S.

    2018-02-01

    Complex dynamical systems are systems with many interdependent components which evolve in time. One might wish to control their trajectories, but a more practical alternative is to control just their statistical behaviour. In many contexts this would be both sufficient and a more realistic goal, e.g. climate and socio-economic systems. I refer to it as ‘management’ of complex dynamical systems. In this paper, some mathematics for management of complex dynamical systems is developed in the weakly dependent regime, and questions are posed for the strongly dependent regime.

  10. Self-organization scenario acting as physical basis of intelligent complex systems created in laboratory

    International Nuclear Information System (INIS)

    Lozneanu, Erzilia; Sanduloviciu, Mircea

    2006-01-01

    The recognition of limits in the tendency to miniaturize the so-called self-organizing devices inspired scientists to seek inspiration from living organisms that operate with functional elements that employ thermal energy exploiting quantum phenomena. Here we show how such operations are performed by a complex space charge configuration emerged by self-organization in plasma. Endowed with a special kind of memory, the complexity is able to ensure its survival in a metastable state performing the operations 'learned' during its emergence by self-organization. Possessing memory, the complexity works as an intelligent system able to evolve under suitable environmental conditions

  11. Web-Based Learning Support System

    Science.gov (United States)

    Fan, Lisa

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

  12. Virtual educational complex of the course “Methods of design of experiments” in distance learning environment of Moodle

    Directory of Open Access Journals (Sweden)

    E. V. Guseva

    2016-01-01

    Full Text Available Currently the information technologies have penetrated to all spheres of human activity, including education. The main objective of the article is to show the advantages of the developed complex and to familiarize with its structure too. The article presents the arguments that the use of the distance learning tools has a significant impact on Russian education. This approach provides the conditions for the development of innovative teaching methods. The approach describes the capabilities offered by the virtual education center of distance learning Moodle too. It is attractive not only openness but because it contains a large set of libraries, classes and functions in the programming language PHP too, which makes it a convenient tool for developing various online information systems. It is shown that the effectiveness of distance learning depends on the organization of educational material. The basic modules of the course were underlined. This section provides a comprehensive understanding of material. For the verification and control of students knowledge the testing system was developed. In addition, the training package has been developed which contains the information, helping to assess the level of students knowledge. The testing system includes a list of tests divided into sections and consists of a set of questions of different complexity. The questions are stored in the single database (“The bank of questions” and can be reused in one or more courses or sections. After passing the correct answers to the test questions can be available for the student. In addition, this module includes tools for grading by the teacher. The article concludes that the virtual educational complex enables to teach students, has a friendly interface that stimulate the students to continue the work and its successful completion.

  13. Control of complex systems

    CERN Document Server

    Albertos, Pedro; Blanke, Mogens; Isidori, Alberto; Schaufelberger, Walter; Sanz, Ricardo

    2001-01-01

    The world of artificial systems is reaching complexity levels that es­ cape human understanding. Surface traffic, electricity distribution, air­ planes, mobile communications, etc. , are examples that demonstrate that we are running into problems that are beyond classical scientific or engi­ neering knowledge. There is an ongoing world-wide effort to understand these systems and develop models that can capture its behavior. The reason for this work is clear, if our lack of understanding deepens, we will lose our capability to control these systems and make they behave as we want. Researchers from many different fields are trying to understand and develop theories for complex man-made systems. This book presents re­ search from the perspective of control and systems theory. The book has grown out of activities in the research program Control of Complex Systems (COSY). The program has been sponsored by the Eu­ ropean Science Foundation (ESF) which for 25 years has been one of the leading players in stimula...

  14. Learning by Preparing to Teach: Fostering Self-Regulatory Processes and Achievement during Complex Mathematics Problem Solving

    Science.gov (United States)

    Muis, Krista R.; Psaradellis, Cynthia; Chevrier, Marianne; Di Leo, Ivana; Lajoie, Susanne P.

    2016-01-01

    We developed an intervention based on the learning by teaching paradigm to foster self-regulatory processes and better learning outcomes during complex mathematics problem solving in a technology-rich learning environment. Seventy-eight elementary students were randomly assigned to 1 of 2 conditions: learning by preparing to teach, or learning for…

  15. Synchronization in node of complex networks consist of complex chaotic system

    Energy Technology Data Exchange (ETDEWEB)

    Wei, Qiang, E-mail: qiangweibeihua@163.com [Beihua University computer and technology College, BeiHua University, Jilin, 132021, Jilin (China); Digital Images Processing Institute of Beihua University, BeiHua University, Jilin, 132011, Jilin (China); Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, 116024 (China); Xie, Cheng-jun [Beihua University computer and technology College, BeiHua University, Jilin, 132021, Jilin (China); Digital Images Processing Institute of Beihua University, BeiHua University, Jilin, 132011, Jilin (China); Liu, Hong-jun [School of Information Engineering, Weifang Vocational College, Weifang, 261041 (China); Li, Yan-hui [The Library, Weifang Vocational College, Weifang, 261041 (China)

    2014-07-15

    A new synchronization method is investigated for node of complex networks consists of complex chaotic system. When complex networks realize synchronization, different component of complex state variable synchronize up to different scaling complex function by a designed complex feedback controller. This paper change synchronization scaling function from real field to complex field for synchronization in node of complex networks with complex chaotic system. Synchronization in constant delay and time-varying coupling delay complex networks are investigated, respectively. Numerical simulations are provided to show the effectiveness of the proposed method.

  16. The importance of cultivating a preference for complexity in veterinarians for effective lifelong learning.

    Science.gov (United States)

    Dale, Vicki H M; Pierce, Stephanie E; May, Stephen A

    2010-01-01

    Much attention has been paid to the link between students' approaches to study and the quality of their learning. Less attention has been paid to the lifelong learner. We conceptualized a tripartite relationship between three measures of learning preference: conceptions of knowledge (construction and use vs. intake), need for cognition (high vs. low), and approach to study (deep vs. surface) and hypothesized that an individual's profile on these three measures-reconceptualized as a preference for complexity versus simplicity-would affect their attitude toward continuing professional development (CPD). A questionnaire was mailed to 2,000 randomly selected, home-practicing UK veterinarians to quantify their learning preferences, motivation to engage in CPD, and perception of barriers to participation and to assess the relationships between these constructs. Analysis of 775 responses (a 38.8% response rate) confirmed our tripartite model of learning and showed that a preference for complexity was negatively correlated with barriers and positively correlated with intrinsic, social, and extrinsic motivating factors, suggesting that all play a role in the continuing education of this group of professionals. A preference for simplicity was negatively correlated with social motivation and positively correlated with barriers. This study demonstrates that approach not only affects the quality of learning but crucially affects motivation to engage in CPD and perception of barriers to lifelong learning. This should emphasize to veterinary educators the importance of fostering a preference for complexity from an early age, both in terms of its immediate benefits (better understanding) and longer-term benefits (continued engagement with learning).

  17. Trans-algorithmic nature of learning in biological systems.

    Science.gov (United States)

    Shimansky, Yury P

    2018-05-02

    Learning ability is a vitally important, distinctive property of biological systems, which provides dynamic stability in non-stationary environments. Although several different types of learning have been successfully modeled using a universal computer, in general, learning cannot be described by an algorithm. In other words, algorithmic approach to describing the functioning of biological systems is not sufficient for adequate grasping of what is life. Since biosystems are parts of the physical world, one might hope that adding some physical mechanisms and principles to the concept of algorithm could provide extra possibilities for describing learning in its full generality. However, a straightforward approach to that through the so-called physical hypercomputation so far has not been successful. Here an alternative approach is proposed. Biosystems are described as achieving enumeration of possible physical compositions though random incremental modifications inflicted on them by active operating resources (AORs) in the environment. Biosystems learn through algorithmic regulation of the intensity of the above modifications according to a specific optimality criterion. From the perspective of external observers, biosystems move in the space of different algorithms driven by random modifications imposed by the environmental AORs. A particular algorithm is only a snapshot of that motion, while the motion itself is essentially trans-algorithmic. In this conceptual framework, death of unfit members of a population, for example, is viewed as a trans-algorithmic modification made in the population as a biosystem by environmental AORs. Numerous examples of AOR utilization in biosystems of different complexity, from viruses to multicellular organisms, are provided.

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

    Institute of Scientific and Technical Information of China (English)

    PIAOSonghao; HONGBingrong; CHUHaitao

    2004-01-01

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

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

    CERN Document Server

    Choi, Kwonhue

    2016-01-01

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

  20. Improving Literacy Skills in Students with Complex Communication Needs Who Use Augmentative/Alternative Communication Systems

    Science.gov (United States)

    Bailey, Rita L.; Angell, Maureen E.; Stoner, Julia B.

    2011-01-01

    A structured intervention package including direct, scaffolded, instructional lessons was implemented using an error correction learning system and a picture book-based phonological and phonemic awareness activity for four participants with complex communication needs, ranging from 12 to 15 years, in a junior high school setting. Although…

  1. Multi-agent and complex systems

    CERN Document Server

    Ren, Fenghui; Fujita, Katsuhide; Zhang, Minjie; Ito, Takayuki

    2017-01-01

    This book provides a description of advanced multi-agent and artificial intelligence technologies for the modeling and simulation of complex systems, as well as an overview of the latest scientific efforts in this field. A complex system features a large number of interacting components, whose aggregate activities are nonlinear and self-organized. A multi-agent system is a group or society of agents which interact with others cooperatively and/or competitively in order to reach their individual or common goals. Multi-agent systems are suitable for modeling and simulation of complex systems, which is difficult to accomplish using traditional computational approaches.

  2. European Conference on Complex Systems 2012

    CERN Document Server

    Kirkilionis, Markus; Nicolis, Gregoire

    2013-01-01

    The European Conference on Complex Systems, held under the patronage of the Complex Systems Society, is an annual event that has become the leading European conference devoted to complexity science. ECCS'12, its ninth edition, took place in Brussels, during the first week of September 2012. It gathered about 650 scholars representing a wide range of topics relating to complex systems research, with emphasis on interdisciplinary approaches. More specifically, the following tracks were covered:  1. Foundations of Complex Systems 2. Complexity, Information and Computation 3. Prediction, Policy and Planning, Environment 4. Biological Complexity 5. Interacting Populations, Collective Behavior 6. Social Systems, Economics and Finance This book contains a selection of the contributions presented at the conference and its satellite meetings. Its contents reflect the extent, diversity and richness of research areas in the field, both fundamental and applied.  

  3. OWL model of multi-agent Smart-system of distance learning for people with vision disabilities

    Directory of Open Access Journals (Sweden)

    Galina A. Samigulina

    2017-01-01

    Full Text Available The aim of the study is to develop an ontological model of multiagent smart-system of distance learning for visually impaired people based on Java Agent Development Framework for obtaining high-quality engineering education in laboratories of join use on modern equipment.Materials and methods of research. In developing multi-agent smart-system of distance learning, using various agents based on cognitive, ontological, statistical and intellectual methods is important. It is more convenient to implement this task in the form of software using multi-agent approach and Java Agent Development Framework. The main advantages of the platform are stability of operation, clear interface, simplicity of creating agents and extensive user database. In multi-agent systems, the solution is obtained automatically as result of interaction of many independent, purposeful agents. Each agent can perform certain tasks and pursue specified goals. Intellectual multi-agent systems and practical applications in distance learning based on them are considered.Results. The structural diagram of functioning of smart system distance learning for visually impaired people using various agents based on the system approach and the multi-agent platform Java Agent Development Framework is developed. The complex approach of distance learning of visually impaired people for obtaining highquality engineering education in laboratories of joint use on modern equipment is offered.The ontological model of multi-agent smart-system with a detailed description of the functions of following agents is created: personal, manager, ontological, cognitive, statistical, intellectual, shared laboratory agent, health agent, assistant to the agent and state agent. These agents execute their individual functions and provide a quality environment for learning.Conclusion. Thus, the proposed smart-system of distance learning for visually impaired people can significantly improve effectiveness and

  4. Understanding the Online Informal Learning of English as a Complex Dynamic System: An Emic Approach

    Science.gov (United States)

    Sockett, Geoffrey

    2013-01-01

    Research into the online informal learning of English has already shown it to be a widespread phenomenon involving a range of comprehension and production activities such as viewing original version television series, listening to music on demand and social networking with other English users. Dynamic systems theory provides a suitable framework…

  5. Envisioning engineering education and practice in the coming intelligence convergence era — a complex adaptive systems approach

    Science.gov (United States)

    Noor, Ahmed K.

    2013-12-01

    Some of the recent attempts for improving and transforming engineering education are reviewed. The attempts aim at providing the entry level engineers with the skills needed to address the challenges of future large-scale complex systems and projects. Some of the frontier sectors and future challenges for engineers are outlined. The major characteristics of the coming intelligence convergence era (the post-information age) are identified. These include the prevalence of smart devices and environments, the widespread applications of anticipatory computing and predictive / prescriptive analytics, as well as a symbiotic relationship between humans and machines. Devices and machines will be able to learn from, and with, humans in a natural collaborative way. The recent game changers in learnscapes (learning paradigms, technologies, platforms, spaces, and environments) that can significantly impact engineering education in the coming era are identified. Among these are open educational resources, knowledge-rich classrooms, immersive interactive 3D learning, augmented reality, reverse instruction / flipped classroom, gamification, robots in the classroom, and adaptive personalized learning. Significant transformative changes in, and mass customization of, learning are envisioned to emerge from the synergistic combination of the game changers and other technologies. The realization of the aforementioned vision requires the development of a new multidisciplinary framework of emergent engineering for relating innovation, complexity and cybernetics, within the future learning environments. The framework can be used to treat engineering education as a complex adaptive system, with dynamically interacting and communicating components (instructors, individual, small, and large groups of learners). The emergent behavior resulting from the interactions can produce progressively better, and continuously improving, learning environment. As a first step towards the realization of

  6. Recommendation System for Adaptive Learning.

    Science.gov (United States)

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

    2018-01-01

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

  7. Learning and inference using complex generative models in a spatial localization task.

    Science.gov (United States)

    Bejjanki, Vikranth R; Knill, David C; Aslin, Richard N

    2016-01-01

    A large body of research has established that, under relatively simple task conditions, human observers integrate uncertain sensory information with learned prior knowledge in an approximately Bayes-optimal manner. However, in many natural tasks, observers must perform this sensory-plus-prior integration when the underlying generative model of the environment consists of multiple causes. Here we ask if the Bayes-optimal integration seen with simple tasks also applies to such natural tasks when the generative model is more complex, or whether observers rely instead on a less efficient set of heuristics that approximate ideal performance. Participants localized a "hidden" target whose position on a touch screen was sampled from a location-contingent bimodal generative model with different variances around each mode. Over repeated exposure to this task, participants learned the a priori locations of the target (i.e., the bimodal generative model), and integrated this learned knowledge with uncertain sensory information on a trial-by-trial basis in a manner consistent with the predictions of Bayes-optimal behavior. In particular, participants rapidly learned the locations of the two modes of the generative model, but the relative variances of the modes were learned much more slowly. Taken together, our results suggest that human performance in a more complex localization task, which requires the integration of sensory information with learned knowledge of a bimodal generative model, is consistent with the predictions of Bayes-optimal behavior, but involves a much longer time-course than in simpler tasks.

  8. Reduction of Subjective and Objective System Complexity

    Science.gov (United States)

    Watson, Michael D.

    2015-01-01

    Occam's razor is often used in science to define the minimum criteria to establish a physical or philosophical idea or relationship. Albert Einstein is attributed the saying "everything should be made as simple as possible, but not simpler". These heuristic ideas are based on a belief that there is a minimum state or set of states for a given system or phenomena. In looking at system complexity, these heuristics point us to an idea that complexity can be reduced to a minimum. How then, do we approach a reduction in complexity? Complexity has been described as a subjective concept and an objective measure of a system. Subjective complexity is based on human cognitive comprehension of the functions and inter relationships of a system. Subjective complexity is defined by the ability to fully comprehend the system. Simplifying complexity, in a subjective sense, is thus gaining a deeper understanding of the system. As Apple's Jonathon Ive has stated," It's not just minimalism or the absence of clutter. It involves digging through the depth of complexity. To be truly simple, you have to go really deep". Simplicity is not the absence of complexity but a deeper understanding of complexity. Subjective complexity, based on this human comprehension, cannot then be discerned from the sociological concept of ignorance. The inability to comprehend a system can be either a lack of knowledge, an inability to understand the intricacies of a system, or both. Reduction in this sense is based purely on a cognitive ability to understand the system and no system then may be truly complex. From this view, education and experience seem to be the keys to reduction or eliminating complexity. Objective complexity, is the measure of the systems functions and interrelationships which exist independent of human comprehension. Jonathon Ive's statement does not say that complexity is removed, only that the complexity is understood. From this standpoint, reduction of complexity can be approached

  9. The Neural Feedback Response to Error As a Teaching Signal for the Motor Learning System

    Science.gov (United States)

    Shadmehr, Reza

    2016-01-01

    When we experience an error during a movement, we update our motor commands to partially correct for this error on the next trial. How does experience of error produce the improvement in the subsequent motor commands? During the course of an erroneous reaching movement, proprioceptive and visual sensory pathways not only sense the error, but also engage feedback mechanisms, resulting in corrective motor responses that continue until the hand arrives at its goal. One possibility is that this feedback response is co-opted by the learning system and used as a template to improve performance on the next attempt. Here we used electromyography (EMG) to compare neural correlates of learning and feedback to test the hypothesis that the feedback response to error acts as a template for learning. We designed a task in which mixtures of error-clamp and force-field perturbation trials were used to deconstruct EMG time courses into error-feedback and learning components. We observed that the error-feedback response was composed of excitation of some muscles, and inhibition of others, producing a complex activation/deactivation pattern during the reach. Despite this complexity, across muscles the learning response was consistently a scaled version of the error-feedback response, but shifted 125 ms earlier in time. Across people, individuals who produced a greater feedback response to error, also learned more from error. This suggests that the feedback response to error serves as a teaching signal for the brain. Individuals who learn faster have a better teacher in their feedback control system. SIGNIFICANCE STATEMENT Our sensory organs transduce errors in behavior. To improve performance, we must generate better motor commands. How does the nervous system transform an error in sensory coordinates into better motor commands in muscle coordinates? Here we show that when an error occurs during a movement, the reflexes transform the sensory representation of error into motor

  10. Enhancing Teacher Utilization of Complex Instructional Systems.

    Science.gov (United States)

    Shore, Ann; Daniel, Dan

    This paper describes a research and development effort by Jostens Learning Corporation that resulted in the Renaissance Information Management System (RIMS), an information-management user interface for an integrated learning system that is designed to overcome two major obstacles to the use of computer systems by classroom teachers--limited…

  11. Emergent learning and learning ecologies in Web 2.0

    OpenAIRE

    Williams, Roy; Karousou, Regina; Mackness, J.

    2011-01-01

    This paper describes emergent learning and situates it within learning networks and systems and the broader learning ecology of Web 2.0. It describes the nature of emergence and emergent learning and the conditions that enable emergent, self-organised learning to occur and to flourish. Specifically, it explores whether emergent learning can be validated and self-correcting and whether it is possible to link or integrate emergent and prescribed learning. It draws on complexity theory, commu...

  12. Increase of Organization in Complex Systems

    OpenAIRE

    Georgiev, Georgi Yordanov; Daly, Michael; Gombos, Erin; Vinod, Amrit; Hoonjan, Gajinder

    2013-01-01

    Measures of complexity and entropy have not converged to a single quantitative description of levels of organization of complex systems. The need for such a measure is increasingly necessary in all disciplines studying complex systems. To address this problem, starting from the most fundamental principle in Physics, here a new measure for quantity of organization and rate of self-organization in complex systems based on the principle of least (stationary) action is applied to a model system -...

  13. The Pedagogy of Complex Work Support Systems: Infrastructuring Practices and the Production of Critical Awareness in Risk Auditing

    Science.gov (United States)

    Mathisen, Arve; Nerland, Monika

    2012-01-01

    This paper employs a socio-technical perspective to explore the role of complex work support systems in organising knowledge and providing opportunities for learning in professional work. Drawing on concepts from infrastructure studies, such systems are seen as work infrastructures which connect information, knowledge, standards and work…

  14. Anti-synchronization between different chaotic complex systems

    International Nuclear Information System (INIS)

    Liu Ping; Liu Shutang

    2011-01-01

    Many studies on the anti-synchronization of nonlinear real dynamic systems have been carried out, whereas the anti-synchronization of chaotic complex systems has not been studied extensively. In this work, the anti-synchronization between a new chaotic complex system and a complex Lorenz system and that between a new chaotic complex system and a complex Lue system were separately investigated by active control and nonlinear control methods, and explicit expressions were derived for the controllers that are used to achieve the anti-synchronization of chaotic complex systems. These expressions were tested numerically and excellent agreement was found. Concerning the new chaotic complex system, we discuss its dynamical properties including dissipation, chaotic behavior, fixed points, and their stability and invariance.

  15. The Effect of Contextualized Conversational Feedback in a Complex Open-Ended Learning Environment

    Science.gov (United States)

    Segedy, James R.; Kinnebrew, John S.; Biswas, Gautam

    2013-01-01

    Betty's Brain is an open-ended learning environment in which students learn about science topics by teaching a virtual agent named Betty through the construction of a visual causal map that represents the relevant science phenomena. The task is complex, and success requires the use of metacognitive strategies that support knowledge acquisition,…

  16. ENGINEERING OF UNIVERSITY INTELLIGENT LEARNING SYSTEMS

    Directory of Open Access Journals (Sweden)

    Vasiliy M. Trembach

    2016-01-01

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

  17. Computer-assisted learning and simulation systems in dentistry--a challenge to society.

    Science.gov (United States)

    Welk, A; Splieth, Ch; Wierinck, E; Gilpatrick, R O; Meyer, G

    2006-07-01

    Computer technology is increasingly used in practical training at universities. However, in spite of their potential, computer-assisted learning (CAL) and computer-assisted simulation (CAS) systems still appear to be underutilized in dental education. Advantages, challenges, problems, and solutions of computer-assisted learning and simulation in dentistry are discussed by means of MEDLINE, open Internet platform searches, and key results of a study among German dental schools. The advantages of computer-assisted learning are seen for example in self-paced and self-directed learning and increased motivation. It is useful for both objective theoretical and practical tests and for training students to handle complex cases. CAL can lead to more structured learning and can support training in evidence-based decision-making. The reasons for the still relatively rare implementation of CAL/CAS systems in dental education include an inability to finance, lack of studies of CAL/CAS, and too much effort required to integrate CAL/CAS systems into the curriculum. To overcome the reasons for the relative low degree of computer technology use, we should strive for multicenter research and development projects monitored by the appropriate national and international scientific societies, so that the potential of computer technology can be fully realized in graduate, postgraduate, and continuing dental education.

  18. Establishment of a Learning Management System

    International Nuclear Information System (INIS)

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

    2006-01-01

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

  19. Transformative Learning: Patterns of Psychophysiologic Response and Technology-Enabled Learning and Intervention Systems

    Science.gov (United States)

    2008-09-01

    Psychophysiologic Response and Technology -Enabled Learning and Intervention Systems PRINCIPAL INVESTIGATOR: Leigh W. Jerome, Ph.D...NUMBER Transformative Learning : Patterns of Psychophysiologic Response and Technology - Enabled Learning and Intervention Systems 5b. GRANT NUMBER...project entitled “Transformative Learning : Patterns of Psychophysiologic Response in Technology Enabled Learning and Intervention Systems.” The

  20. Authoring Systems Delivering Reusable Learning Objects

    Directory of Open Access Journals (Sweden)

    George Nicola Sammour

    2009-10-01

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

  1. Complexity in Dynamical Systems

    Science.gov (United States)

    Moore, Cristopher David

    The study of chaos has shown us that deterministic systems can have a kind of unpredictability, based on a limited knowledge of their initial conditions; after a finite time, the motion appears essentially random. This observation has inspired a general interest in the subject of unpredictability, and more generally, complexity; how can we characterize how "complex" a dynamical system is?. In this thesis, we attempt to answer this question with a paradigm of complexity that comes from computer science, we extract sets of symbol sequences, or languages, from a dynamical system using standard methods of symbolic dynamics; we then ask what kinds of grammars or automata are needed a generate these languages. This places them in the Chomsky heirarchy, which in turn tells us something about how subtle and complex the dynamical system's behavior is. This gives us insight into the question of unpredictability, since these automata can also be thought of as computers attempting to predict the system. In the culmination of the thesis, we find a class of smooth, two-dimensional maps which are equivalent to the highest class in the Chomsky heirarchy, the turning machine; they are capable of universal computation. Therefore, these systems possess a kind of unpredictability qualitatively different from the usual "chaos": even if the initial conditions are known exactly, questions about the system's long-term dynamics are undecidable. No algorithm exists to answer them. Although this kind of unpredictability has been discussed in the context of distributed, many-degree-of -freedom systems (for instance, cellular automata) we believe this is the first example of such phenomena in a smooth, finite-degree-of-freedom system.

  2. Neuronal avalanches and learning

    Energy Technology Data Exchange (ETDEWEB)

    Arcangelis, Lucilla de, E-mail: dearcangelis@na.infn.it [Department of Information Engineering and CNISM, Second University of Naples, 81031 Aversa (Italy)

    2011-05-01

    Networks of living neurons represent one of the most fascinating systems of biology. If the physical and chemical mechanisms at the basis of the functioning of a single neuron are quite well understood, the collective behaviour of a system of many neurons is an extremely intriguing subject. Crucial ingredient of this complex behaviour is the plasticity property of the network, namely the capacity to adapt and evolve depending on the level of activity. This plastic ability is believed, nowadays, to be at the basis of learning and memory in real brains. Spontaneous neuronal activity has recently shown features in common to other complex systems. Experimental data have, in fact, shown that electrical information propagates in a cortex slice via an avalanche mode. These avalanches are characterized by a power law distribution for the size and duration, features found in other problems in the context of the physics of complex systems and successful models have been developed to describe their behaviour. In this contribution we discuss a statistical mechanical model for the complex activity in a neuronal network. The model implements the main physiological properties of living neurons and is able to reproduce recent experimental results. Then, we discuss the learning abilities of this neuronal network. Learning occurs via plastic adaptation of synaptic strengths by a non-uniform negative feedback mechanism. The system is able to learn all the tested rules, in particular the exclusive OR (XOR) and a random rule with three inputs. The learning dynamics exhibits universal features as function of the strength of plastic adaptation. Any rule could be learned provided that the plastic adaptation is sufficiently slow.

  3. Neuronal avalanches and learning

    International Nuclear Information System (INIS)

    Arcangelis, Lucilla de

    2011-01-01

    Networks of living neurons represent one of the most fascinating systems of biology. If the physical and chemical mechanisms at the basis of the functioning of a single neuron are quite well understood, the collective behaviour of a system of many neurons is an extremely intriguing subject. Crucial ingredient of this complex behaviour is the plasticity property of the network, namely the capacity to adapt and evolve depending on the level of activity. This plastic ability is believed, nowadays, to be at the basis of learning and memory in real brains. Spontaneous neuronal activity has recently shown features in common to other complex systems. Experimental data have, in fact, shown that electrical information propagates in a cortex slice via an avalanche mode. These avalanches are characterized by a power law distribution for the size and duration, features found in other problems in the context of the physics of complex systems and successful models have been developed to describe their behaviour. In this contribution we discuss a statistical mechanical model for the complex activity in a neuronal network. The model implements the main physiological properties of living neurons and is able to reproduce recent experimental results. Then, we discuss the learning abilities of this neuronal network. Learning occurs via plastic adaptation of synaptic strengths by a non-uniform negative feedback mechanism. The system is able to learn all the tested rules, in particular the exclusive OR (XOR) and a random rule with three inputs. The learning dynamics exhibits universal features as function of the strength of plastic adaptation. Any rule could be learned provided that the plastic adaptation is sufficiently slow.

  4. Complex logistics audit system

    Directory of Open Access Journals (Sweden)

    Zuzana Marková

    2010-02-01

    Full Text Available Complex logistics audit system is a tool for realization of logistical audit in the company. The current methods for logistics auditare based on “ad hok” analysis of logisticsl system. This paper describes system for complex logistics audit. It is a global diagnosticsof logistics processes and functions of enterprise. The goal of logistics audit is to provide comparative documentation for managementabout state of logistics in company and to show the potential of logistics changes in order to achieve more effective companyperformance.

  5. CLASSIFICATION OF LEARNING MANAGEMENT SYSTEMS

    Directory of Open Access Journals (Sweden)

    Yu. B. Popova

    2016-01-01

    Full Text Available Using of information technologies and, in particular, learning management systems, increases opportunities of teachers and students in reaching their goals in education. Such systems provide learning content, help organize and monitor training, collect progress statistics and take into account the individual characteristics of each user. Currently, there is a huge inventory of both paid and free systems are physically located both on college servers and in the cloud, offering different features sets of different licensing scheme and the cost. This creates the problem of choosing the best system. This problem is partly due to the lack of comprehensive classification of such systems. Analysis of more than 30 of the most common now automated learning management systems has shown that a classification of such systems should be carried out according to certain criteria, under which the same type of system can be considered. As classification features offered by the author are: cost, functionality, modularity, keeping the customer’s requirements, the integration of content, the physical location of a system, adaptability training. Considering the learning management system within these classifications and taking into account the current trends of their development, it is possible to identify the main requirements to them: functionality, reliability, ease of use, low cost, support for SCORM standard or Tin Can API, modularity and adaptability. According to the requirements at the Software Department of FITR BNTU under the guidance of the author since 2009 take place the development, the use and continuous improvement of their own learning management system.

  6. Measuring Complexity of SAP Systems

    Directory of Open Access Journals (Sweden)

    Ilja Holub

    2016-10-01

    Full Text Available The paper discusses the reasons of complexity rise in ERP system SAP R/3. It proposes a method for measuring complexity of SAP. Based on this method, the computer program in ABAP for measuring complexity of particular SAP implementation is proposed as a tool for keeping ERP complexity under control. The main principle of the measurement method is counting the number of items or relations in the system. The proposed computer program is based on counting of records in organization tables in SAP.

  7. European Conference on Complex Systems

    CERN Document Server

    Pellegrini, Francesco; Caldarelli, Guido; Merelli, Emanuela

    2016-01-01

    This work contains a stringent selection of extended contributions presented at the meeting of 2014 and its satellite meetings, reflecting scope, diversity and richness of research areas in the field, both fundamental and applied. The ECCS meeting, held under the patronage of the Complex Systems Society, is an annual event that has become the leading European conference devoted to complexity science. It offers cutting edge research and unique opportunities to study novel scientific approaches in a multitude of application areas. ECCS'14, its eleventh occurrence, took place in Lucca, Italy. It gathered some 650 scholars representing a wide range of topics relating to complex systems research, with emphasis on interdisciplinary approaches. The editors are among the best specialists in the area. The book is of great interest to scientists, researchers and graduate students in complexity, complex systems and networks.

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

    Science.gov (United States)

    Mihai, Gabroveanu

    2015-09-01

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

  9. Third International Conference on Complex Systems

    CERN Document Server

    Minai, Ali A; Unifying Themes in Complex Systems

    2006-01-01

    In recent years, scientists have applied the principles of complex systems science to increasingly diverse fields. The results have been nothing short of remarkable: their novel approaches have provided answers to long-standing questions in biology, ecology, physics, engineering, computer science, economics, psychology and sociology. The Third International Conference on Complex Systems attracted over 400 researchers from around the world. The conference aimed to encourage cross-fertilization between the many disciplines represented and to deepen our understanding of the properties common to all complex systems. This volume contains over 35 papers selected from those presented at the conference on topics including: self-organization in biology, ecological systems, language, economic modeling, ecological systems, artificial life, robotics, and complexity and art. ALI MINAI is an Affiliate of the New England Complex Systems Institute and an Associate Professor in the Department of Electrical and Computer Engine...

  10. USING A MULTI CRITERIA DECISION MAKING APPROACH FOR OPEN AND DISTANCE LEARNING SYSTEM SELECTION

    OpenAIRE

    KAMIŞLI ÖZTÜRK, Zehra

    2015-01-01

    Today, there's a wide variety of open and distance learning (ODL) systems around the world. Herein, for lifelong learning how to select an ODL program becomes a critic question for a learner who wants to extent abilities on his/her career path. This is a complex decision problem with interdependent criteria. The Analytic Network Process (ANP) is a multicriteria decision making methodology  that  reflects  these  interdependencies.  Within &...

  11. Sixth International Conference on Complex Systems

    CERN Document Server

    Minai, Ali; Bar-Yam, Yaneer; Unifying Themes in Complex Systems

    2008-01-01

    The International Conference on Complex Systems (ICCS) creates a unique atmosphere for scientists of all fields, engineers, physicians, executives, and a host of other professionals to explore the common themes and applications of complex systems science. In June 2006, 500 participants convened in Boston for the sixth ICCS, exploring an array of topics, including networks, systems biology, evolution and ecology, nonlinear dynamics and pattern formation, as well as neural, psychological, psycho-social, socio-economic, and global systems. This volume selects 77 papers from over 300 presented at the conference. With this new volume, Unifying Themes in Complex Systems continues to build common ground between the wide-ranging domains of complex systems science.

  12. A framework for exploring integrated learning systems for the governance and management of public protected areas.

    Science.gov (United States)

    Nkhata, Bimo Abraham; Breen, Charles

    2010-02-01

    This article discusses how the concept of integrated learning systems provides a useful means of exploring the functional linkages between the governance and management of public protected areas. It presents a conceptual framework of an integrated learning system that explicitly incorporates learning processes in governance and management subsystems. The framework is premised on the assumption that an understanding of an integrated learning system is essential if we are to successfully promote learning across multiple scales as a fundamental component of adaptability in the governance and management of protected areas. The framework is used to illustrate real-world situations that reflect the nature and substance of the linkages between governance and management. Drawing on lessons from North America and Africa, the article demonstrates that the establishment and maintenance of an integrated learning system take place in a complex context which links elements of governance learning and management learning subsystems. The degree to which the two subsystems are coupled influences the performance of an integrated learning system and ultimately adaptability. Such performance is largely determined by how integrated learning processes allow for the systematic testing of societal assumptions (beliefs, values, and public interest) to enable society and protected area agencies to adapt and learn in the face of social and ecological change. It is argued that an integrated perspective provides a potentially useful framework for explaining and improving shared understanding around which the concept of adaptability is structured and implemented.

  13. Student Modelling in Adaptive E-Learning Systems

    Directory of Open Access Journals (Sweden)

    Clemens Bechter

    2011-09-01

    Full Text Available Most e-Learning systems provide web-based learning so that students can access the same online courses via the Internet without adaptation, based on each student's profile and behavior. In an e-Learning system, one size does not fit all. Therefore, it is a challenge to make e-Learning systems that are suitably “adaptive”. The aim of adaptive e-Learning is to provide the students the appropriate content at the right time, means that the system is able to determine the knowledge level, keep track of usage, and arrange content automatically for each student for the best learning result. This study presents a proposed system which includes major adaptive features based on a student model. The proposed system is able to initialize the student model for determining the knowledge level of a student when the student registers for the course. After a student starts learning the lessons and doing many activities, the system can track information of the student until he/she takes a test. The student’s knowledge level, based on the test scores, is updated into the system for use in the adaptation process, which combines the student model with the domain model in order to deliver suitable course contents to the students. In this study, the proposed adaptive e-Learning system is implemented on an “Introduction to Java Programming Language” course, using LearnSquare software. After the system was tested, the results showed positive feedback towards the proposed system, especially in its adaptive capability.

  14. Philosophy of complex systems

    CERN Document Server

    2011-01-01

    The domain of nonlinear dynamical systems and its mathematical underpinnings has been developing exponentially for a century, the last 35 years seeing an outpouring of new ideas and applications and a concomitant confluence with ideas of complex systems and their applications from irreversible thermodynamics. A few examples are in meteorology, ecological dynamics, and social and economic dynamics. These new ideas have profound implications for our understanding and practice in domains involving complexity, predictability and determinism, equilibrium, control, planning, individuality, responsibility and so on. Our intention is to draw together in this volume, we believe for the first time, a comprehensive picture of the manifold philosophically interesting impacts of recent developments in understanding nonlinear systems and the unique aspects of their complexity. The book will focus specifically on the philosophical concepts, principles, judgments and problems distinctly raised by work in the domain of comple...

  15. Large-scale Complex IT Systems

    OpenAIRE

    Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard

    2011-01-01

    This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that identifies the major challen...

  16. Large-scale complex IT systems

    OpenAIRE

    Sommerville, Ian; Cliff, Dave; Calinescu, Radu; Keen, Justin; Kelly, Tim; Kwiatkowska, Marta; McDermid, John; Paige, Richard

    2012-01-01

    12 pages, 2 figures This paper explores the issues around the construction of large-scale complex systems which are built as 'systems of systems' and suggests that there are fundamental reasons, derived from the inherent complexity in these systems, why our current software engineering methods and techniques cannot be scaled up to cope with the engineering challenges of constructing such systems. It then goes on to propose a research and education agenda for software engineering that ident...

  17. Thrive or overload? The effect of task complexity on novices' simulation-based learning.

    Science.gov (United States)

    Haji, Faizal A; Cheung, Jeffrey J H; Woods, Nicole; Regehr, Glenn; de Ribaupierre, Sandrine; Dubrowski, Adam

    2016-09-01

    Fidelity is widely viewed as an important element of simulation instructional design based on its purported relationship with transfer of learning. However, higher levels of fidelity may increase task complexity to a point at which novices' cognitive resources become overloaded. In this experiment, we investigate the effects of variations in task complexity on novices' cognitive load and learning during simulation-based procedural skills training. Thirty-eight medical students were randomly assigned to simulation training on a simple or complex lumbar puncture (LP) task. Participants completed four practice trials on this task (skill acquisition). After 10 days of rest, all participants completed one additional trial on their assigned task (retention) and one trial on a 'very complex' simulation designed to be similar to the complex task (transfer). We assessed LP performance and cognitive load on each trial using multiple measures. In both groups, LP performance improved significantly during skill acquisition (p ≤ 0.047, f = 0.29-0.96) and was maintained at retention. The simple task group demonstrated superior performance compared with the complex task group throughout these phases (p ≤ 0.002, d = 1.13-2.31). Cognitive load declined significantly in the simple task group (p Education.

  18. 5th International Conference on Complex Systems

    CERN Document Server

    Braha, Dan; Bar-Yam, Yaneer

    2011-01-01

    The International Conference on Complex Systems (ICCS) creates a unique atmosphere for scientists of all fields, engineers, physicians, executives, and a host of other professionals to explore common themes and applications of complex system science. With this new volume, Unifying Themes in Complex Systems continues to build common ground between the wide-ranging domains of complex system science.

  19. 7th International Conference on Complex Systems

    CERN Document Server

    Braha, Dan; Bar-Yam, Yaneer

    2012-01-01

    The International Conference on Complex Systems (ICCS) creates a unique atmosphere for scientists of all fields, engineers, physicians, executives, and a host of other professionals to explore common themes and applications of complex system science. With this new volume, Unifying Themes in Complex Systems continues to build common ground between the wide-ranging domains of complex system science.

  20. Micro Learning: A Modernized Education System

    Directory of Open Access Journals (Sweden)

    Omer Jomah

    2016-03-01

    Full Text Available Learning is an understanding of how the human brain is wired to learning rather than to an approach or a system. It is one of the best and most frequent approaches for the 21st century learners. Micro learning is more interesting due to its way of teaching and learning the content in a small, very specific burst. Here the learners decide what and when to learn. Content, time, curriculum, form, process, mediality, and learning type are the dimensions of micro learning. Our paper will discuss about micro learning and about the micro-content management system. The study will reflect the views of different users, and will analyze the collected data. Finally, it will be concluded with its pros and cons. 

  1. Learning To Live with Complexity.

    Science.gov (United States)

    Dosa, Marta

    Neither the design of information systems and networks nor the delivery of library services can claim true user centricity without an understanding of the multifaceted psychological environment of users and potential users. The complexity of the political process, social problems, challenges to scientific inquiry, entrepreneurship, and…

  2. The information system of learning quality control in higher education institutions: achievements and problems of European universities

    Directory of Open Access Journals (Sweden)

    Orekhova Elena

    2016-01-01

    Full Text Available The article deals with the main trends in the development of the system of learning quality control connected with the European integration of higher education and the democratization of education. The authors analyze the state of information systems of learning quality control existing in European higher education and identify their strong and weak points. The authors show that in the learning process universities actively use innovative analytic methods as well as modern means of collecting, storing and transferring information that ensure the successful management of such a complex object as the university of the 21st century.

  3. Effects of cerebellar nuclear inactivation on the learning of a complex forelimb movement in cats.

    Science.gov (United States)

    Wang, J J; Shimansky, Y; Bracha, V; Bloedel, J R

    1998-05-01

    lateral cerebellum are not required either for learning this type of complex voluntary movement or for retaining the capacity to perform the task once it is learned. Nevertheless, when the cerebellum becomes available for executing a task learned in the absence of this structure, reacquisition of the behavior usually is necessary. It is hypothesized that the relearning observed after acquisition during muscimol inactivation reflects the tendency of the system to incorporate the cerebellum into the interactions responsible for the learning and performance of a motor sequence that is optimal for executing the task.

  4. Learned parametrized dynamic movement primitives with shared synergies for controlling robotic and musculoskeletal systems

    Directory of Open Access Journals (Sweden)

    Elmar eRückert

    2013-10-01

    Full Text Available A salient feature of human motor skill learning is the ability to exploitsimilarities across related tasks.In biological motor control, it has been hypothesized that muscle synergies,coherent activations of groups of muscles, allow for exploiting shared knowledge.Recent studies have shown that a rich set of complex motor skills can be generated bya combination of a small number of muscle synergies.In robotics, dynamic movement primitives are commonlyused for motor skill learning. This machine learning approach implements a stable attractor systemthat facilitates learning and it can be used in high-dimensional continuous spaces. However, it does not allow for reusing shared knowledge, i.e. for each task an individual set of parameters has to be learned.We propose a novel movement primitive representationthat employs parametrized basis functions, which combines the benefits of muscle synergiesand dynamic movement primitives. For each task asuperposition of synergies modulates a stable attractor system.This approach leads to a compact representation of multiple motor skills andat the same time enables efficient learning in high-dimensional continuous systems.The movement representation supports discrete and rhythmic movements andin particular includes the dynamic movement primitive approach as a special case.We demonstrate the feasibility of the movement representation in three multi-task learning simulated scenarios.First, the characteristics of the proposed representation are illustrated in a point-mass task.Second, in complex humanoid walking experiments,multiple walking patterns with different step heights are learned robustly and efficiently.Finally, in a multi-directional reaching task simulated with a musculoskeletal modelof the human arm, we show how the proposed movement primitives can be used tolearn appropriate muscle excitation patterns and to generalize effectively to new reaching skills.

  5. Learning Management Systems and Comparison of Open Source Learning Management Systems and Proprietary Learning Management Systems

    Directory of Open Access Journals (Sweden)

    Yücel Yılmaz

    2016-04-01

    Full Text Available The concept of learning has been increasingly gaining importance for individuals, businesses and communities in the age of information. On the other hand, developments in information and communication technologies take effect in the field of learning activities. With these technologies, barriers of time and space against the learning activities largely disappear and these technologies make it easier to carry out these activities more effectively. There remain a lot of questions regarding selection of learning management system (LMS to be used for the management of e-learning processes by all organizations conducing educational practices including universities, companies, non-profit organizations, etc. The main questions are as follows: Shall we choose open source LMS or commercial LMS? Can the selected LMS meet existing needs and future potential needs for the organization? What are the possibilities of technical support in the management of LMS? What kind of problems may be experienced in the use of LMS and how can these problems be solved? How much effective can officials in the organization be in the management of LMS? In this study, primarily e-learning and the concept of LMS will be discussed, and in the next section, as for answers to these questions, open source LMSs and centrally developed LMSs will be examined and their advantages and disadvantages relative to each other will be discussed.

  6. Learning about Complex Multi-Stakeholder Issues: Assessing the Visual Problem Appraisal

    NARCIS (Netherlands)

    Witteveen, L.M.; Put, M.; Leeuwis, C.

    2010-01-01

    This paper presents an evaluation of the visual problem appraisal (VPA) learning environment in higher education. The VPA has been designed for the training of competences that are required in complex stakeholder settings in relation to sustainability issues. The design of VPA incorporates a

  7. Reliability of large and complex systems

    CERN Document Server

    Kolowrocki, Krzysztof

    2014-01-01

    Reliability of Large and Complex Systems, previously titled Reliability of Large Systems, is an innovative guide to the current state and reliability of large and complex systems. In addition to revised and updated content on the complexity and safety of large and complex mechanisms, this new edition looks at the reliability of nanosystems, a key research topic in nanotechnology science. The author discusses the importance of safety investigation of critical infrastructures that have aged or have been exposed to varying operational conditions. This reference provides an asympt

  8. Resolving the Problem of Intelligent Learning Content in Learning Management Systems

    Science.gov (United States)

    Rey-Lopez, Marta; Brusilovsky, Peter; Meccawy, Maram; Diaz-Redondo, Rebeca; Fernandez-Vilas, Ana; Ashman, Helen

    2008-01-01

    Current e-learning standardization initiatives have put much effort into easing interoperability between systems and the reusability of contents. For this to be possible, one of the most relevant areas is the definition of a run-time environment, which allows Learning Management Systems to launch, track and communicate with learning objects.…

  9. Evaluating Usability of E-Learning Systems in Universities

    OpenAIRE

    Nicholas Kipkurui Kiget; Professor G. Wanyembi; Anselemo Ikoha Peters

    2014-01-01

    The use of e-learning systems has increased significantly in the recent times. E-learning systems are supplementing teaching and learning in universities globally. Kenyan universities have adopted e-learning technologies as means for delivering course content. However despite adoption of these systems, there are considerable challenges facing the usability of the systems. Lecturers and students have different perceptions in regard to the usability of e-learning systems. The aim of this study ...

  10. Geographical National Condition and Complex System

    Directory of Open Access Journals (Sweden)

    WANG Jiayao

    2016-01-01

    Full Text Available The significance of studying the complex system of geographical national conditions lies in rationally expressing the complex relationships of the “resources-environment-ecology-economy-society” system. Aiming to the problems faced by the statistical analysis of geographical national conditions, including the disunity of research contents, the inconsistency of range, the uncertainty of goals, etc.the present paper conducted a range of discussions from the perspectives of concept, theory and method, and designed some solutions based on the complex system theory and coordination degree analysis methods.By analyzing the concepts of geographical national conditions, geographical national conditions survey and geographical national conditions statistical analysis, as well as investigating the relationships between theirs, the statistical contents and the analytical range of geographical national conditions are clarified and defined. This investigation also clarifies the goals of the statistical analysis by analyzing the basic characteristics of the geographical national conditions and the complex system, and the consistency between the analysis of the degree of coordination and statistical analyses. It outlines their goals, proposes a concept for the complex system of geographical national conditions, and it describes the concept. The complex system theory provides new theoretical guidance for the statistical analysis of geographical national conditions. The degree of coordination offers new approaches on how to undertake the analysis based on the measurement method and decision-making analysis scheme upon which the complex system of geographical national conditions is based. It analyzes the overall trend via the degree of coordination of the complex system on a macro level, and it determines the direction of remediation on a micro level based on the degree of coordination among various subsystems and of single systems. These results establish

  11. Learning to Learn: towards a Relational and Transformational Model of Learning for Improved Integrated Care Delivery

    Directory of Open Access Journals (Sweden)

    John Diamond

    2013-06-01

    Full Text Available Health and social care systems are implementing fundamental changes to organizational structures and work practices in an effort to achieve integrated care. While some integration initiatives have produced positive outcomes, many have not. We reframe the concept of integration as a learning process fueled by knowledge exchange across diverse professional and organizational communities. We thus focus on the cognitive and social dynamics of learning in complex adaptive systems, and on learning behaviours and conditions that foster collective learning and improved collaboration. We suggest that the capacity to learn how to learn shapes the extent to which diverse professional groups effectively exchange knowledge and self-organize for integrated care delivery.

  12. Learning to live with complexity.

    Science.gov (United States)

    Sargut, Gökçe; McGrath, Rita Gunther

    2011-09-01

    Business life has always featured the unpredictable, the surprising, and the unexpected. But in today's hyperconnected world, complexity is the norm. Systems that used to be separate are now intertwined and interdependent, and knowing the starting conditions is no guide to predicting outcomes; too many continuously changing interactive elements are in play. Managers looking to navigate these difficulties need to adopt new approaches. They should drop outmoded forecasting tools-for example, ones that rely on averages, which are often less important than outliers. Instead, they should use models that simulate the behavior of the system. They should also make sure that their data include a good amount of future-oriented information. Risk mitigation is crucial as well. Managers should minimize the need to rely on predictions-for instance, they can give users a say in product design. They can decouple elements in a system and build in redundancy to minimize the consequences of a partial system failure, and turn to outside partners to extend their own company's capabilities. They can complement hard analysis with "soft" methods such as storytelling to make potentially important future possibilities more real. And they can make trade-offs that keep early failures small and provide the diversity of thought needed in a nimble organization faced with complexity on virtually every front.

  13. Teaching and Learning about Complex Systems in K-12 Science Education: A Review of Empirical Studies 1995-2015

    Science.gov (United States)

    Yoon, Susan A.; Goh, Sao-Ee; Park, Miyoung

    2018-01-01

    The study of complex systems has been highlighted in recent science education policy in the United States and has been the subject of important real-world scientific investigation. Because of this, research on complex systems in K-12 science education has shown a marked increase over the past two decades. In this systematic review, we analyzed 75…

  14. Feedback Design Patterns for Math Online Learning Systems

    Science.gov (United States)

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

    2017-01-01

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

  15. Reframing the challenges to integrated care: a complex-adaptive systems perspective

    Directory of Open Access Journals (Sweden)

    Peter Tsasis

    2012-09-01

    Full Text Available Introduction: Despite over two decades of international experience and research on health systems integration, integrated care has not developed widely. We hypothesized that part of the problem may lie in how we conceptualize the integration process and the complex systems within which integrated care is enacted. This study aims to contribute to discourse regarding the relevance and utility of a complex-adaptive systems (CAS perspective on integrated care.Methods: In the Canadian province of Ontario, government mandated the development of fourteen Local Health Integration Networks in 2006. Against the backdrop of these efforts to integrate care, we collected focus group data from a diverse sample of healthcare professionals in the Greater Toronto Area using convenience and snowball sampling. A semi-structured interview guide was used to elicit participant views and experiences of health systems integration. We use a CAS framework to describe and analyze the data, and to assess the theoretical fit of a CAS perspective with the dominant themes in participant responses.Results: Our findings indicate that integration is challenged by system complexity, weak ties and poor alignment among professionals and organizations, a lack of funding incentives to support collaborative work, and a bureaucratic environment based on a command and control approach to management. Using a CAS framework, we identified several characteristics of CAS in our data, including diverse, interdependent and semi-autonomous actors; embedded co-evolutionary systems; emergent behaviours and non-linearity; and self-organizing capacity. Discussion and Conclusion: One possible explanation for the lack of systems change towards integration is that we have failed to treat the healthcare system as complex-adaptive. The data suggest that future integration initiatives must be anchored in a CAS perspective, and focus on building the system's capacity to self-organize. We conclude that

  16. Reframing the challenges to integrated care: a complex-adaptive systems perspective

    Directory of Open Access Journals (Sweden)

    Peter Tsasis

    2012-09-01

    Full Text Available Introduction: Despite over two decades of international experience and research on health systems integration, integrated care has not developed widely. We hypothesized that part of the problem may lie in how we conceptualize the integration process and the complex systems within which integrated care is enacted. This study aims to contribute to discourse regarding the relevance and utility of a complex-adaptive systems (CAS perspective on integrated care. Methods: In the Canadian province of Ontario, government mandated the development of fourteen Local Health Integration Networks in 2006. Against the backdrop of these efforts to integrate care, we collected focus group data from a diverse sample of healthcare professionals in the Greater Toronto Area using convenience and snowball sampling. A semi-structured interview guide was used to elicit participant views and experiences of health systems integration. We use a CAS framework to describe and analyze the data, and to assess the theoretical fit of a CAS perspective with the dominant themes in participant responses. Results: Our findings indicate that integration is challenged by system complexity, weak ties and poor alignment among professionals and organizations, a lack of funding incentives to support collaborative work, and a bureaucratic environment based on a command and control approach to management. Using a CAS framework, we identified several characteristics of CAS in our data, including diverse, interdependent and semi-autonomous actors; embedded co-evolutionary systems; emergent behaviours and non-linearity; and self-organizing capacity.  Discussion and Conclusion: One possible explanation for the lack of systems change towards integration is that we have failed to treat the healthcare system as complex-adaptive. The data suggest that future integration initiatives must be anchored in a CAS perspective, and focus on building the system's capacity to self-organize. We conclude that

  17. Capturing the complexity: Content, type, and amount of instruction and quality of the classroom learning environment synergistically predict third graders' vocabulary and reading comprehension outcomes.

    Science.gov (United States)

    Connor, Carol McDonald; Spencer, Mercedes; Day, Stephanie L; Giuliani, Sarah; Ingebrand, Sarah W; McLean, Leigh; Morrison, Frederick J

    2014-08-01

    We examined classrooms as complex systems that affect students' literacy learning through interacting effects of content and amount of time individual students spent in literacy instruction along with the global quality of the classroom-learning environment. We observed 27 third grade classrooms serving 315 target students using two different observation systems. The first assessed instruction at a more micro-level; specifically, the amount of time individual students spent in literacy instruction defined by the type of instruction, role of the teacher, and content. The second assessed the quality of the classroom-learning environment at a more macro level focusing on classroom organization, teacher responsiveness, and support for vocabulary and language. Results revealed that both global quality of the classroom learning environment and time individual students spent in specific types of literacy instruction covering specific content interacted to predict students' comprehension and vocabulary gains whereas neither system alone did. These findings support a dynamic systems model of how individual children learn in the context of classroom literacy instruction and the classroom-learning environment, which can help to improve observations systems, advance research, elevate teacher evaluation and professional development, and enhance student achievement.

  18. Capturing the complexity: Content, type, and amount of instruction and quality of the classroom learning environment synergistically predict third graders’ vocabulary and reading comprehension outcomes

    Science.gov (United States)

    Connor, Carol McDonald; Spencer, Mercedes; Day, Stephanie L.; Giuliani, Sarah; Ingebrand, Sarah W.; McLean, Leigh; Morrison, Frederick J.

    2014-01-01

    We examined classrooms as complex systems that affect students’ literacy learning through interacting effects of content and amount of time individual students spent in literacy instruction along with the global quality of the classroom-learning environment. We observed 27 third grade classrooms serving 315 target students using two different observation systems. The first assessed instruction at a more micro-level; specifically, the amount of time individual students spent in literacy instruction defined by the type of instruction, role of the teacher, and content. The second assessed the quality of the classroom-learning environment at a more macro level focusing on classroom organization, teacher responsiveness, and support for vocabulary and language. Results revealed that both global quality of the classroom learning environment and time individual students spent in specific types of literacy instruction covering specific content interacted to predict students’ comprehension and vocabulary gains whereas neither system alone did. These findings support a dynamic systems model of how individual children learn in the context of classroom literacy instruction and the classroom-learning environment, which can help to improve observations systems, advance research, elevate teacher evaluation and professional development, and enhance student achievement. PMID:25400293

  19. Facilitating the Evaluation of Complexity in the Public Sector: Learning from the NHS in Scotland

    Science.gov (United States)

    Connolly, John; Reid, Garth; Mooney, Allan

    2015-01-01

    It is necessary for public managers to be able to evaluate programmes in the context of complexity. This article offers key learning and reflections based on the experience of facilitating the evaluation of complexity with a range of public sector partners in Scotland. There have been several articles that consider evaluating complexity and…

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

    International Nuclear Information System (INIS)

    Kapur, A

    2015-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2015-06-15

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

  2. Fourth International Conference on Complex Systems

    CERN Document Server

    Minai, Ali A; Unifying Themes in Complex Systems IV

    2008-01-01

    In June of 2002, over 500 professors, students and researchers met in Boston, Massachusetts for the Fourth International Conference on Complex Systems. The attendees represented a remarkably diverse collection of fields: biology, ecology, physics, engineering, computer science, economics, psychology and sociology, The goal of the conference was to encourage cross-fertilization between the many disciplines represented and to deepen understanding of the properties common to all complex systems. This volume contains 43 papers selected from the more than 200 presented at the conference. Topics include: cellular automata, neurology, evolution, computer science, network dynamics, and urban planning. About NECSI: For over 10 years, The New England Complex Systems Institute (NECSI) has been instrumental in the development of complex systems science and its applications. NECSI conducts research, education, knowledge dissemination, and community development around the world for the promotion of the study of complex sys...

  3. Preparing Information Systems Graduates for a Complex Society: Aligning IS Curricula with Liberal Education Learning Outcomes

    Science.gov (United States)

    Pratt, Jean A.; Keys, Anthony; Wirkus, Tyrrell

    2014-01-01

    The purpose of this paper is to encourage Information Systems (IS) faculty to intentionally revise their curriculum to address (and assess) higher-order learning skills which are demanded by industry and society and are representative of a liberal arts based education. We substantiated the need for this proposed curriculum revision by first…

  4. Indirect learning control for nonlinear dynamical systems

    Science.gov (United States)

    Ryu, Yeong Soon; Longman, Richard W.

    1993-01-01

    In a previous paper, learning control algorithms were developed based on adaptive control ideas for linear time variant systems. The learning control methods were shown to have certain advantages over their adaptive control counterparts, such as the ability to produce zero tracking error in time varying systems, and the ability to eliminate repetitive disturbances. In recent years, certain adaptive control algorithms have been developed for multi-body dynamic systems such as robots, with global guaranteed convergence to zero tracking error for the nonlinear system euations. In this paper we study the relationship between such adaptive control methods designed for this specific class of nonlinear systems, and the learning control problem for such systems, seeking to converge to zero tracking error in following a specific command repeatedly, starting from the same initial conditions each time. The extension of these methods from the adaptive control problem to the learning control problem is seen to be trivial. The advantages and disadvantages of using learning control based on such adaptive control concepts for nonlinear systems, and the use of other currently available learning control algorithms are discussed.

  5. Task Complexity Modulates Sleep-Related Offline Learning in Sequential Motor Skills

    Directory of Open Access Journals (Sweden)

    Klaus Blischke

    2017-07-01

    Full Text Available Recently, a number of authors have advocated the introduction of gross motor tasks into research on sleep-related motor offline learning. Such tasks are often designed to be more complex than traditional key-pressing tasks. However, until now, little effort has been undertaken to scrutinize the role of task complexity in any systematic way. Therefore, the effect of task complexity on the consolidation of gross motor sequence memory was examined by our group in a series of three experiments. Criterion tasks always required participants to produce unrestrained arm movement sequences by successively fitting a small peg into target holes on a pegboard. The sequences always followed a certain spatial pattern in the horizontal plane. The targets were visualized prior to each transport movement on a computer screen. The tasks differed with respect to sequence length and structural complexity. In each experiment, half of the participants initially learned the task in the morning and were retested 12 h later following a wake retention interval. The other half of the subjects underwent practice in the evening and was retested 12 h later following a night of sleep. The dependent variables were the error rate and total sequence execution time (inverse to the sequence execution speed. Performance generally improved during acquisition. The error rate was always low and remained stable during retention. The sequence execution time significantly decreased again following sleep but not after waking when the sequence length was long and structural complexity was high. However, sleep-related offline improvements were absent when the sequence length was short or when subjects performed a highly regular movement pattern. It is assumed that the occurrence of sleep-related offline performance improvements in sequential motor tasks is associated with a sufficient amount of motor task complexity.

  6. SOFTWARE COMPLEX FOR CREATION AND ACCUMULATION OF MODERN LEARNING MATERIALS

    Directory of Open Access Journals (Sweden)

    V. V. Polinovskyi

    2010-08-01

    Full Text Available The article analyzes weaknesses of existing tools for lecture materials creation and suggests new complex with modular architecture, which supports different types of lecture materials, templates, interactive elements, includes lecture material database with searching, sorting, and grouping capabilities and can be used for creating lectures courses for distance learning, as well as for interactive lectures for full-time courses.

  7. Learning with Generalization Capability by Kernel Methods of Bounded Complexity

    Czech Academy of Sciences Publication Activity Database

    Kůrková, Věra; Sanguineti, M.

    2005-01-01

    Roč. 21, č. 3 (2005), s. 350-367 ISSN 0885-064X R&D Projects: GA AV ČR 1ET100300419 Institutional research plan: CEZ:AV0Z10300504 Keywords : supervised learning * generalization * model complexity * kernel methods * minimization of regularized empirical errors * upper bounds on rates of approximate optimization Subject RIV: BA - General Mathematics Impact factor: 1.186, year: 2005

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

    Science.gov (United States)

    Yu, Peter Paul

    2015-03-01

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

  9. An Intelligent System for Determining Learning Style

    Science.gov (United States)

    Ozdemir, Ali; Alaybeyoglu, Aysegul; Mulayim, Naciye; Uysal, Muhammed

    2018-01-01

    In this study, an intelligent system which determines learning style of the students is developed to increase success in effective and easy learning. The importance of the proposed software system is to determine convenience degree of the student's learning style. Personal information form and Dunn Learning Style Preference Survey are used to…

  10. Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics.

    Science.gov (United States)

    Yang, Qian; Sing-Long, Carlos A; Reed, Evan J

    2017-08-01

    We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.

  11. Learning Markov models for stationary system behaviors

    DEFF Research Database (Denmark)

    Chen, Yingke; Mao, Hua; Jaeger, Manfred

    2012-01-01

    to a single long observation sequence, and in these situations existing automatic learning methods cannot be applied. In this paper, we adapt algorithms for learning variable order Markov chains from a single observation sequence of a target system, so that stationary system properties can be verified using......Establishing an accurate model for formal verification of an existing hardware or software system is often a manual process that is both time consuming and resource demanding. In order to ease the model construction phase, methods have recently been proposed for automatically learning accurate...... the learned model. Experiments demonstrate that system properties (formulated as stationary probabilities of LTL formulas) can be reliably identified using the learned model....

  12. An Orchestrating Evaluation of Complex Educational Technologies: a Case Study of a CSCL System

    Directory of Open Access Journals (Sweden)

    Luis P. Prieto

    2014-06-01

    Full Text Available As digital technologies permeate every aspect of our lives, the complexity of the educational settings, and of the technological support we use within them, unceasingly rises. This increased complexity, along with the need for educational practitioners to apply such technologies within multi-constraint authentic settings, has given rise to the notion of technology-enhanced learning practice as “orchestration of learning”. However, at the same time, the complexity involved in evaluating the benefits of such educational technologies has also increased, prompting questions about the way evaluators can cope with the different places, technologies, informants and issues involved in their evaluation activity. By proposing the notion of “orchestrating evaluation”, this paper tries to reconcile the often disparate “front office accounts” of research publications and the “shop floor practice” of evaluation of educational technology, through the case study of evaluating a system to help teachers in coordinating computer-supported collaborative learning (CSCL scenarios. We reuse an internationally-evaluated conceptual framework of “orchestration aspects” (design, management, adaptation, pragmatism, etc. to structure the case‟s narrative, showing how the original evaluation questions and methods were modulated in the face of the multiple (authentic evaluation setting constraints.

  13. A novel multi-agent decentralized win or learn fast policy hill-climbing with eligibility trace algorithm for smart generation control of interconnected complex power grids

    International Nuclear Information System (INIS)

    Xi, Lei; Yu, Tao; Yang, Bo; Zhang, Xiaoshun

    2015-01-01

    Highlights: • Proposing a decentralized smart generation control scheme for the automatic generation control coordination. • A novel multi-agent learning algorithm is developed to resolve stochastic control problems in power systems. • A variable learning rate are introduced base on the framework of stochastic games. • A simulation platform is developed to test the performance of different algorithms. - Abstract: This paper proposes a multi-agent smart generation control scheme for the automatic generation control coordination in interconnected complex power systems. A novel multi-agent decentralized win or learn fast policy hill-climbing with eligibility trace algorithm is developed, which can effectively identify the optimal average policies via a variable learning rate under various operation conditions. Based on control performance standards, the proposed approach is implemented in a flexible multi-agent stochastic dynamic game-based smart generation control simulation platform. Based on the mixed strategy and average policy, it is highly adaptive in stochastic non-Markov environments and large time-delay systems, which can fulfill automatic generation control coordination in interconnected complex power systems in the presence of increasing penetration of decentralized renewable energy. Two case studies on both a two-area load–frequency control power system and the China Southern Power Grid model have been done. Simulation results verify that multi-agent smart generation control scheme based on the proposed approach can obtain optimal average policies thus improve the closed-loop system performances, and can achieve a fast convergence rate with significant robustness compared with other methods

  14. Optimizing the number of steps in learning tasks for complex skills.

    NARCIS (Netherlands)

    Nadolski, Rob; Kirschner, Paul A.; Van Merriënboer, Jeroen

    2007-01-01

    Background. Carrying out whole tasks is often too difficult for novice learners attempting to acquire complex skills. The common solution is to split up the tasks into a number of smaller steps. The number of steps must be optimised for efficient and effective learning. Aim. The aim of the study is

  15. Constructivist learning theories and complex learning environments

    NARCIS (Netherlands)

    R-J. Simons; Dr. S. Bolhuis

    2004-01-01

    Learning theories broadly characterised as constructivist, agree on the importance to learning of the environment, but differ on what exactly it is that constitutes this importance. Accordingly, they also differ on the educational consequences to be drawn from the theoretical perspective. Cognitive

  16. VIRTUAL LABORATORY IN DISTANCE LEARNING SYSTEM

    Directory of Open Access Journals (Sweden)

    Е. Kozlovsky

    2011-11-01

    Full Text Available Questions of designing and a choice of technologies of creation of virtual laboratory for the distance learning system are considered. Distance learning system «Kherson Virtual University» is used as illustration.

  17. Estimating the complexity of 3D structural models using machine learning methods

    Science.gov (United States)

    Mejía-Herrera, Pablo; Kakurina, Maria; Royer, Jean-Jacques

    2016-04-01

    Quantifying the complexity of 3D geological structural models can play a major role in natural resources exploration surveys, for predicting environmental hazards or for forecasting fossil resources. This paper proposes a structural complexity index which can be used to help in defining the degree of effort necessary to build a 3D model for a given degree of confidence, and also to identify locations where addition efforts are required to meet a given acceptable risk of uncertainty. In this work, it is considered that the structural complexity index can be estimated using machine learning methods on raw geo-data. More precisely, the metrics for measuring the complexity can be approximated as the difficulty degree associated to the prediction of the geological objects distribution calculated based on partial information on the actual structural distribution of materials. The proposed methodology is tested on a set of 3D synthetic structural models for which the degree of effort during their building is assessed using various parameters (such as number of faults, number of part in a surface object, number of borders, ...), the rank of geological elements contained in each model, and, finally, their level of deformation (folding and faulting). The results show how the estimated complexity in a 3D model can be approximated by the quantity of partial data necessaries to simulated at a given precision the actual 3D model without error using machine learning algorithms.

  18. Innovation in user-centered skills and performance improvement for sustainable complex service systems.

    Science.gov (United States)

    Karwowski, Waldemar; Ahram, Tareq Z

    2012-01-01

    In order to leverage individual and organizational learning and to remain competitive in current turbulent markets it is important for employees, managers, planners and leaders to perform at high levels over time. Employee competence and skills are extremely important matters in view of the general shortage of talent and the mobility of employees with talent. Two factors emerged to have the greatest impact on the competitiveness of complex service systems: improving managerial and employee's knowledge attainment for skills, and improving the training and development of the workforce. This paper introduces the knowledge-based user-centered service design approach for sustainable skill and performance improvement in education, design and modeling of the next generation of complex service systems. The rest of the paper cover topics in human factors and sustainable business process modeling for the service industry, and illustrates the user-centered service system development cycle with the integration of systems engineering concepts in service systems. A roadmap for designing service systems of the future is discussed. The framework introduced in this paper is based on key user-centered design principles and systems engineering applications to support service competitiveness.

  19. Physical approach to complex systems

    Science.gov (United States)

    Kwapień, Jarosław; Drożdż, Stanisław

    2012-06-01

    Typically, complex systems are natural or social systems which consist of a large number of nonlinearly interacting elements. These systems are open, they interchange information or mass with environment and constantly modify their internal structure and patterns of activity in the process of self-organization. As a result, they are flexible and easily adapt to variable external conditions. However, the most striking property of such systems is the existence of emergent phenomena which cannot be simply derived or predicted solely from the knowledge of the systems’ structure and the interactions among their individual elements. This property points to the holistic approaches which require giving parallel descriptions of the same system on different levels of its organization. There is strong evidence-consolidated also in the present review-that different, even apparently disparate complex systems can have astonishingly similar characteristics both in their structure and in their behaviour. One can thus expect the existence of some common, universal laws that govern their properties. Physics methodology proves helpful in addressing many of the related issues. In this review, we advocate some of the computational methods which in our opinion are especially fruitful in extracting information on selected-but at the same time most representative-complex systems like human brain, financial markets and natural language, from the time series representing the observables associated with these systems. The properties we focus on comprise the collective effects and their coexistence with noise, long-range interactions, the interplay between determinism and flexibility in evolution, scale invariance, criticality, multifractality and hierarchical structure. The methods described either originate from “hard” physics-like the random matrix theory-and then were transmitted to other fields of science via the field of complex systems research, or they originated elsewhere but

  20. Identification of Complex Dynamical Systems with Neural Networks (2/2)

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    The identification and analysis of high dimensional nonlinear systems is obviously a challenging task. Neural networks have been proven to be universal approximators but this still leaves the identification task a hard one. To do it efficiently, we have to violate some of the rules of classical regression theory. Furthermore we should focus on the interpretation of the resulting model to overcome its black box character. First, we will discuss function approximation with 3 layer feedforward neural networks up to new developments in deep neural networks and deep learning. These nets are not only of interest in connection with image analysis but are a center point of the current artificial intelligence developments. Second, we will focus on the analysis of complex dynamical system in the form of state space models realized as recurrent neural networks. After the introduction of small open dynamical systems we will study dynamical systems on manifolds. Here manifold and dynamics have to be identified in parall...

  1. Identification of Complex Dynamical Systems with Neural Networks (1/2)

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    The identification and analysis of high dimensional nonlinear systems is obviously a challenging task. Neural networks have been proven to be universal approximators but this still leaves the identification task a hard one. To do it efficiently, we have to violate some of the rules of classical regression theory. Furthermore we should focus on the interpretation of the resulting model to overcome its black box character. First, we will discuss function approximation with 3 layer feedforward neural networks up to new developments in deep neural networks and deep learning. These nets are not only of interest in connection with image analysis but are a center point of the current artificial intelligence developments. Second, we will focus on the analysis of complex dynamical system in the form of state space models realized as recurrent neural networks. After the introduction of small open dynamical systems we will study dynamical systems on manifolds. Here manifold and dynamics have to be identified in parall...

  2. Statistical mechanics of complex neural systems and high dimensional data

    International Nuclear Information System (INIS)

    Advani, Madhu; Lahiri, Subhaneil; Ganguli, Surya

    2013-01-01

    Recent experimental advances in neuroscience have opened new vistas into the immense complexity of neuronal networks. This proliferation of data challenges us on two parallel fronts. First, how can we form adequate theoretical frameworks for understanding how dynamical network processes cooperate across widely disparate spatiotemporal scales to solve important computational problems? Second, how can we extract meaningful models of neuronal systems from high dimensional datasets? To aid in these challenges, we give a pedagogical review of a collection of ideas and theoretical methods arising at the intersection of statistical physics, computer science and neurobiology. We introduce the interrelated replica and cavity methods, which originated in statistical physics as powerful ways to quantitatively analyze large highly heterogeneous systems of many interacting degrees of freedom. We also introduce the closely related notion of message passing in graphical models, which originated in computer science as a distributed algorithm capable of solving large inference and optimization problems involving many coupled variables. We then show how both the statistical physics and computer science perspectives can be applied in a wide diversity of contexts to problems arising in theoretical neuroscience and data analysis. Along the way we discuss spin glasses, learning theory, illusions of structure in noise, random matrices, dimensionality reduction and compressed sensing, all within the unified formalism of the replica method. Moreover, we review recent conceptual connections between message passing in graphical models, and neural computation and learning. Overall, these ideas illustrate how statistical physics and computer science might provide a lens through which we can uncover emergent computational functions buried deep within the dynamical complexities of neuronal networks. (paper)

  3. Teach Them How They Learn: Learning Styles and Information Systems Education

    Science.gov (United States)

    Cegielski, Casey G.; Hazen, Benjamin T.; Rainer, R. Kelly

    2011-01-01

    The rich, interdisciplinary tradition of learning styles is markedly absent in information systems-related research. The current study applies the framework of learning styles to a common educational component of many of today's information systems curricula--object-oriented systems development--in an effort to answer the question as to whether…

  4. Machine Learning

    Energy Technology Data Exchange (ETDEWEB)

    Chikkagoudar, Satish; Chatterjee, Samrat; Thomas, Dennis G.; Carroll, Thomas E.; Muller, George

    2017-04-21

    The absence of a robust and unified theory of cyber dynamics presents challenges and opportunities for using machine learning based data-driven approaches to further the understanding of the behavior of such complex systems. Analysts can also use machine learning approaches to gain operational insights. In order to be operationally beneficial, cybersecurity machine learning based models need to have the ability to: (1) represent a real-world system, (2) infer system properties, and (3) learn and adapt based on expert knowledge and observations. Probabilistic models and Probabilistic graphical models provide these necessary properties and are further explored in this chapter. Bayesian Networks and Hidden Markov Models are introduced as an example of a widely used data driven classification/modeling strategy.

  5. Examining Motivation in Online Distance Learning Environments: Complex, Multifaceted, and Situation-Dependent

    Directory of Open Access Journals (Sweden)

    Maggie Hartnett

    2011-10-01

    Full Text Available Existing research into motivation in online environments has tended to use one of two approaches. The first adopts a trait-like model that views motivation as a relatively stable, personal characteristic of the learner. Research from this perspective has contributed to the notion that online learners are, on the whole, intrinsically motivated. The alternative view concentrates on the design of online learning environments to encourage optimal learner motivation. Neither approach acknowledges a contemporary view of motivation that emphasises the situated, mutually constitutive relationship of the learner and the learning environment. Using self-determination theory (SDT as a framework, this paper explores the motivation to learn of preservice teachers in two online distance-learning contexts. In this study, learners were found to be not primarily intrinsically motivated. Instead, student motivation was found to be complex, multifaceted, and sensitive to situational conditions.

  6. Intelligent data analysis for e-learning enhancing security and trustworthiness in online learning systems

    CERN Document Server

    Miguel, Jorge; Xhafa, Fatos

    2016-01-01

    Intelligent Data Analysis for e-Learning: Enhancing Security and Trustworthiness in Online Learning Systems addresses information security within e-Learning based on trustworthiness assessment and prediction. Over the past decade, many learning management systems have appeared in the education market. Security in these systems is essential for protecting against unfair and dishonest conduct-most notably cheating-however, e-Learning services are often designed and implemented without considering security requirements. This book provides functional approaches of trustworthiness analysis, modeling, assessment, and prediction for stronger security and support in online learning, highlighting the security deficiencies found in most online collaborative learning systems. The book explores trustworthiness methodologies based on collective intelligence than can overcome these deficiencies. It examines trustworthiness analysis that utilizes the large amounts of data-learning activities generate. In addition, as proc...

  7. What Is a Complex Innovation System?

    Science.gov (United States)

    Katz, J. Sylvan

    2016-01-01

    Innovation systems are sometimes referred to as complex systems, something that is intuitively understood but poorly defined. A complex system dynamically evolves in non-linear ways giving it unique properties that distinguish it from other systems. In particular, a common signature of complex systems is scale-invariant emergent properties. A scale-invariant property can be identified because it is solely described by a power law function, f(x) = kxα, where the exponent, α, is a measure of scale-invariance. The focus of this paper is to describe and illustrate that innovation systems have properties of a complex adaptive system. In particular scale-invariant emergent properties indicative of their complex nature that can be quantified and used to inform public policy. The global research system is an example of an innovation system. Peer-reviewed publications containing knowledge are a characteristic output. Citations or references to these articles are an indirect measure of the impact the knowledge has on the research community. Peer-reviewed papers indexed in Scopus and in the Web of Science were used as data sources to produce measures of sizes and impact. These measures are used to illustrate how scale-invariant properties can be identified and quantified. It is demonstrated that the distribution of impact has a reasonable likelihood of being scale-invariant with scaling exponents that tended toward a value of less than 3.0 with the passage of time and decreasing group sizes. Scale-invariant correlations are shown between the evolution of impact and size with time and between field impact and sizes at points in time. The recursive or self-similar nature of scale-invariance suggests that any smaller innovation system within the global research system is likely to be complex with scale-invariant properties too. PMID:27258040

  8. What Is a Complex Innovation System?

    Directory of Open Access Journals (Sweden)

    J Sylvan Katz

    Full Text Available Innovation systems are sometimes referred to as complex systems, something that is intuitively understood but poorly defined. A complex system dynamically evolves in non-linear ways giving it unique properties that distinguish it from other systems. In particular, a common signature of complex systems is scale-invariant emergent properties. A scale-invariant property can be identified because it is solely described by a power law function, f(x = kxα, where the exponent, α, is a measure of scale-invariance. The focus of this paper is to describe and illustrate that innovation systems have properties of a complex adaptive system. In particular scale-invariant emergent properties indicative of their complex nature that can be quantified and used to inform public policy. The global research system is an example of an innovation system. Peer-reviewed publications containing knowledge are a characteristic output. Citations or references to these articles are an indirect measure of the impact the knowledge has on the research community. Peer-reviewed papers indexed in Scopus and in the Web of Science were used as data sources to produce measures of sizes and impact. These measures are used to illustrate how scale-invariant properties can be identified and quantified. It is demonstrated that the distribution of impact has a reasonable likelihood of being scale-invariant with scaling exponents that tended toward a value of less than 3.0 with the passage of time and decreasing group sizes. Scale-invariant correlations are shown between the evolution of impact and size with time and between field impact and sizes at points in time. The recursive or self-similar nature of scale-invariance suggests that any smaller innovation system within the global research system is likely to be complex with scale-invariant properties too.

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

    Science.gov (United States)

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

    2015-01-01

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

  10. Metric Learning Method Aided Data-Driven Design of Fault Detection Systems

    Directory of Open Access Journals (Sweden)

    Guoyang Yan

    2014-01-01

    Full Text Available Fault detection is fundamental to many industrial applications. With the development of system complexity, the number of sensors is increasing, which makes traditional fault detection methods lose efficiency. Metric learning is an efficient way to build the relationship between feature vectors with the categories of instances. In this paper, we firstly propose a metric learning-based fault detection framework in fault detection. Meanwhile, a novel feature extraction method based on wavelet transform is used to obtain the feature vector from detection signals. Experiments on Tennessee Eastman (TE chemical process datasets demonstrate that the proposed method has a better performance when comparing with existing methods, for example, principal component analysis (PCA and fisher discriminate analysis (FDA.

  11. Synchronization and emergence in complex systems

    Indian Academy of Sciences (India)

    ... complex systems. Fatihcan M Atay. Synchronization, Coupled Systems and Networks Volume 77 Issue 5 November 2011 pp 855-863 ... We show how novel behaviour can emerge in complex systems at the global level through synchronization of the activities of their constituent units. Two mechanisms are suggested for ...

  12. Infinite Particle Systems: Complex Systems III

    Directory of Open Access Journals (Sweden)

    Editorial Board

    2008-06-01

    Full Text Available In the years 2002-2005, a group of German and Polish mathematicians worked under a DFG research project No 436 POL 113/98/0-1 entitled "Methods of stochastic analysis in the theory of collective phenomena: Gibbs states and statistical hydrodynamics". The results of their study were summarized at the German-Polish conference, which took place in Poland in October 2005. The venue of the conference was Kazimierz Dolny upon Vistula - a lovely town and a popular place for various cultural, scientific, and even political events of an international significance. The conference was also attended by scientists from France, Italy, Portugal, UK, Ukraine, and USA, which predetermined its international character. Since that time, the conference, entitled "Infinite Particle Systems: Complex Systems" has become an annual international event, attended by leading scientists from Germany, Poland and many other countries. The present volume of the "Condensed Matter Physics" contains proceedings of the conference "Infinite Particle Systems: Complex Systems III", which took place in June 2007.

  13. Training complex judgment: The effects of critical thinking and complex judgment

    NARCIS (Netherlands)

    Helsdingen, Anne; Van Gog, Tamara; Van Merriënboer, Jeroen

    2010-01-01

    Helsdingen, A. S., Van Gog, T., & Van Merrienboer, J. J. G. (2009). Training complex judgment: The effects of critical thinking and contextual interference. Paper presented at the International Center for Learning, Education and Performance Systems (ICLEPS). Talahassee, Florida: Florida State

  14. Using an adaptive expertise lens to understand the quality of teachers' classroom implementation of computer-supported complex systems curricula in high school science

    Science.gov (United States)

    Yoon, Susan A.; Koehler-Yom, Jessica; Anderson, Emma; Lin, Joyce; Klopfer, Eric

    2015-05-01

    Background: This exploratory study is part of a larger-scale research project aimed at building theoretical and practical knowledge of complex systems in students and teachers with the goal of improving high school biology learning through professional development and a classroom intervention. Purpose: We propose a model of adaptive expertise to better understand teachers' classroom practices as they attempt to navigate myriad variables in the implementation of biology units that include working with computer simulations, and learning about and teaching through complex systems ideas. Sample: Research participants were three high school biology teachers, two females and one male, ranging in teaching experience from six to 16 years. Their teaching contexts also ranged in student achievement from 14-47% advanced science proficiency. Design and methods: We used a holistic multiple case study methodology and collected data during the 2011-2012 school year. Data sources include classroom observations, teacher and student surveys, and interviews. Data analyses and trustworthiness measures were conducted through qualitative mining of data sources and triangulation of findings. Results: We illustrate the characteristics of adaptive expertise of more or less successful teaching and learning when implementing complex systems curricula. We also demonstrate differences between case study teachers in terms of particular variables associated with adaptive expertise. Conclusions: This research contributes to scholarship on practices and professional development needed to better support teachers to teach through a complex systems pedagogical and curricular approach.

  15. From System Complexity to Emergent Properties

    CERN Document Server

    Aziz-Alaoui, M. A

    2009-01-01

    Emergence and complexity refer to the appearance of higher-level properties and behaviours of a system that obviously comes from the collective dynamics of that system's components. These properties are not directly deductable from the lower-level motion of that system. Emergent properties are properties of the "whole'' that are not possessed by any of the individual parts making up that whole. Such phenomena exist in various domains and can be described, using complexity concepts and thematic knowledges. This book highlights complexity modelling through dynamical or behavioral systems. The pluridisciplinary purposes, developped along the chapters, are enable to design links between a wide-range of fundamental and applicative Sciences. Developing such links - instead of focusing on specific and narrow researches - is characteristic of the Science of Complexity that we try to promote by this contribution.

  16. Complex Systems Design & Management : Proceedings of the Third International Conference on Complex Systems Design & Management

    CERN Document Server

    Caseau, Yves; Krob, Daniel; Rauzy, Antoine

    2013-01-01

    This book contains all refereed papers that were accepted to the third edition of the « Complex Systems Design & Management » (CSD&M 2012) international conference that took place in Paris (France) from December 12-14, 2012. (Website: http://www.csdm2012.csdm.fr)  These proceedings cover the most recent trends in the emerging field of complex systems sciences & practices from an industrial and academic perspective, including the main industrial domains (transport, defense & security, electronics, energy & environment, e-services), scientific & technical topics (systems fundamentals, systems architecture& engineering, systems metrics & quality, systemic  tools) and system types (transportation systems, embedded systems, software & information systems, systems of systems, artificial ecosystems). The CSD&M 2012 conference is organized under the guidance of the CESAMES non-profit organization (http://www.cesames.net).

  17. E-learning systems intelligent techniques for personalization

    CERN Document Server

    Klašnja-Milićević, Aleksandra; Ivanović, Mirjana; Budimac, Zoran; Jain, Lakhmi C

    2017-01-01

    This monograph provides a comprehensive research review of intelligent techniques for personalisation of e-learning systems. Special emphasis is given to intelligent tutoring systems as a particular class of e-learning systems, which support and improve the learning and teaching of domain-specific knowledge. A new approach to perform effective personalization based on Semantic web technologies achieved in a tutoring system is presented. This approach incorporates a recommender system based on collaborative tagging techniques that adapts to the interests and level of students' knowledge. These innovations are important contributions of this monograph. Theoretical models and techniques are illustrated on a real personalised tutoring system for teaching Java programming language. The monograph is directed to, students and researchers interested in the e-learning and personalization techniques. .

  18. An Intrinsic Value System for Developing Multiple Invariant Representations with Incremental Slowness Learning

    Directory of Open Access Journals (Sweden)

    Matthew David Luciw

    2013-05-01

    Full Text Available Curiosity Driven Modular Incremental Slow Feature Analysis (CD-MISFA;~cite{cdmisfa} is a recently introduced model of intrinsically-motivated invariance learning, which shows how curiosity enables the orderly formation of multiple stable sensory representations, through which the agent can simplify its complex sensory input. Here, we first discuss the computational properties of the CD-MISFA model itself, followed by a discussion of neurophysiological analogs fulfilling similar functional roles. CD-MISFA combines 1. unsupervised representation learning through the slowness principle, 2. generation of an intrinsic reward signal through the learning progress of the developing features, and 3. balancing of exploration and exploitation in order to maximize learning progress and quickly learn multiple feature sets for perceptual simplification. Experimental results on synthetic observations and on the iCub robot show that the intrinsic value system is an essential component to representation learning, further, the model explores such that the representations are typically learned in order from least to most costly, as predicted by the theory of Artificial Curiosity.

  19. Complexity in physics and technology

    CERN Document Server

    Garrido, Manuel S

    1992-01-01

    A system is loosely defined as complex if it is composed of a large number of elements, interacting with each other, and the emergent global dynamics is qualitatively different from the dynamics of each one of the parts. The global dynamics may be either ordered or chaotic and among the most interesting emergent global properties are those of learning and adaptation.Complex systems, in the above sense, appear in many fields ranging from physics and technology to life and social sciences. Research in complex systems involves therefore a wide range of topics, studied in seemingly disparate field

  20. A systemic framework for managing e-learning adoption in campus universities: individual strategies in context

    Directory of Open Access Journals (Sweden)

    Carol Russell

    2009-12-01

    Full Text Available There are hopes that new learning technologies will help to transform university learning and teaching into a more engaging experience for twenty-first-century students. But since 2000 the changes in campus university teaching have been more limited than expected. I have drawn on ideas from organisational change management research to investigate why this is happening in one particular campus university context. My study examines the strategies of individual lecturers for adopting e-learning within their disciplinary, departmental and university work environments to develop a conceptual framework for analysing university learning and teaching as a complex adaptive system. This conceptual framework links the processes through which university teaching changes, the resulting forms of learning activity and the learning technologies used – all within the organisational context of the university. The framework suggests that systemic transformation of a university's learning and teaching requires coordinated change across activities that have traditionally been managed separately in campus universities. Without such coordination, established ways of organising learning and teaching will reassert themselves, as support staff and lecturers seek to optimise their own work locally. The conceptual framework could inform strategies for realising the full benefits of new learning technologies in other campus universities.

  1. Assisted Learning Systems in e-Education

    Directory of Open Access Journals (Sweden)

    Gabriel ZAMFIR

    2014-01-01

    Full Text Available Human society, analyzed as a learning environment, presumes different languages in order to know, to understand or to develop it. This statement results as a default application of the cog-nitive domain in the educational scientific research, and it highlights a key feature: each essen-tial discovery was available for the entire language compatible society. E-Society is constructed as an application of E-Science in social services, and it is going to reveal a learning system for each application of the information technology developed for a compatible society. This article is proposed as a conceptual one focused on scientific research and the interrelationship be-tween the building blocks of research, defined as an engine for any designed learning system applied in the cognitive domain. In this approach, educational research become a learning sys-tem in e-Education. The purpose of this analysis is to configure the teacher assisted learning system and to expose its main principles which could be integrated in standard assisted instruc-tion applications, available in e-Classroom, supporting the design of specific didactic activities.

  2. The Meaning of System: Towards a Complexity Orientation in Systems Thinking

    DEFF Research Database (Denmark)

    Leleur, Steen

    2014-01-01

    for systems practice. It is argued that complexity theory and thinking with reference to Luhmann a.o. ought to be recognised and paid attention to by the systems community. Overall, it is found that a complexity orientation may contribute to extend and enrich the explanatory power of current systems theory......This article reviews the generic meaning of ‘system’ and complements more conventional system notions with a system perception based on recent complexity theory. With system as the core concept of systems theory, its actual meaning is not just of theoretical interest but is highly relevant also...... when used to complex real-world problems. As regards systems practice it is found that selective use and combination of five presented research approaches (functionalist, interpretive, emancipatory, postmodern and complexity) which function as different but complementing ‘epistemic lenses’ in a process...

  3. Genetic learning in rule-based and neural systems

    Science.gov (United States)

    Smith, Robert E.

    1993-01-01

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

  4. Personalized E- learning System Based on Intelligent Agent

    Science.gov (United States)

    Duo, Sun; Ying, Zhou Cai

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

  5. Sandpile model for relaxation in complex systems

    International Nuclear Information System (INIS)

    Vazquez, A.; Sotolongo-Costa, O.; Brouers, F.

    1997-10-01

    The relaxation in complex systems is, in general, nonexponential. After an initial rapid decay the system relaxes slowly following a long time tail. In the present paper a sandpile moderation of the relaxation in complex systems is analysed. Complexity is introduced by a process of avalanches in the Bethe lattice and a feedback mechanism which leads to slower decay with increasing time. In this way, some features of relaxation in complex systems: long time tails relaxation, aging, and fractal distribution of characteristic times, are obtained by simple computer simulations. (author)

  6. University Learning Systems for Participative Courses.

    Science.gov (United States)

    Billingham, Carol J.; Harper, William W.

    1980-01-01

    Describes the instructional development of a course for advanced finance students on the use of data files and/or databases for solving complex finance problems. Areas covered include course goals and the design. The course class schedule and sample learning assessment assignments are provided. (JD)

  7. A Simple and Effective Remedial Learning System with a Fuzzy Expert System

    Science.gov (United States)

    Lin, C.-C.; Guo, K.-H.; Lin, Y.-C.

    2016-01-01

    This study aims at implementing a simple and effective remedial learning system. Based on fuzzy inference, a remedial learning material selection system is proposed for a digital logic course. Two learning concepts of the course have been used in the proposed system: number systems and combinational logic. We conducted an experiment to validate…

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

    Science.gov (United States)

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

    2011-12-01

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

  9. Embracing uncertainty, managing complexity: applying complexity thinking principles to transformation efforts in healthcare systems.

    Science.gov (United States)

    Khan, Sobia; Vandermorris, Ashley; Shepherd, John; Begun, James W; Lanham, Holly Jordan; Uhl-Bien, Mary; Berta, Whitney

    2018-03-21

    Complexity thinking is increasingly being embraced in healthcare, which is often described as a complex adaptive system (CAS). Applying CAS to healthcare as an explanatory model for understanding the nature of the system, and to stimulate changes and transformations within the system, is valuable. A seminar series on systems and complexity thinking hosted at the University of Toronto in 2016 offered a number of insights on applications of CAS perspectives to healthcare that we explore here. We synthesized topics from this series into a set of six insights on how complexity thinking fosters a deeper understanding of accepted ideas in healthcare, applications of CAS to actors within the system, and paradoxes in applications of complexity thinking that may require further debate: 1) a complexity lens helps us better understand the nebulous term "context"; 2) concepts of CAS may be applied differently when actors are cognizant of the system in which they operate; 3) actor responses to uncertainty within a CAS is a mechanism for emergent and intentional adaptation; 4) acknowledging complexity supports patient-centred intersectional approaches to patient care; 5) complexity perspectives can support ways that leaders manage change (and transformation) in healthcare; and 6) complexity demands different ways of implementing ideas and assessing the system. To enhance our exploration of key insights, we augmented the knowledge gleaned from the series with key articles on complexity in the literature. Ultimately, complexity thinking acknowledges the "messiness" that we seek to control in healthcare and encourages us to embrace it. This means seeing challenges as opportunities for adaptation, stimulating innovative solutions to ensure positive adaptation, leveraging the social system to enable ideas to emerge and spread across the system, and even more important, acknowledging that these adaptive actions are part of system behaviour just as much as periods of stability are. By

  10. Systems Approach to Tourism: A Methodology for Defining Complex Tourism System

    Directory of Open Access Journals (Sweden)

    Jere Jakulin Tadeja

    2017-08-01

    Full Text Available Background and Purpose: The complexity of the tourism system, as well as modelling in a frame of system dynamics, will be discussed in this paper. The phaenomenon of tourism, which possesses the typical properties of global and local organisations, will be presented as an open complex system with all its elements, and an optimal methodology to explain the relations among them. The approach we want to present is due to its transparency an excellent tool for searching systems solutions and serves also as a strategic decision-making assessment. We will present systems complexity and develop three models of a complex tourism system: the first one will present tourism as an open complex system with its elements, which operate inside of a tourism market area. The elements of this system present subsystems, which relations and interdependencies will be explained with two models: causal-loop diagram and a simulation model in frame of systems dynamics.

  11. Impact of pedagogical approaches on cognitive complexity and motivation to learn: Comparing nursing and engineering undergraduate students.

    Science.gov (United States)

    McComb, Sara A; Kirkpatrick, Jane M

    2016-01-01

    The changing higher education landscape is prompting nurses to rethink educational strategies. Looking beyond traditional professional boundaries may be beneficial. We compare nursing to engineering because engineering has similar accreditation outcome goals and different pedagogical approaches. We compare students' cognitive complexity and motivation to learn to identify opportunities to share pedagogical approaches between nursing and engineering. Cross-sectional data were collected from 1,167 freshmen through super senior students. Comparisons were made across years and between majors. Overall nursing and engineering students advance in cognitive complexity while maintaining motivation for learning. Sophomores reported the lowest scores on many dimensions indicating that their experiences need review. The strong influence of the National Council Licensure Examination on nursing students may drive their classroom preferences. Increased intrinsic motivation, coupled with decreased extrinsic motivation, suggests that we are graduating burgeoning life-long learners equipped to maintain currency. The disciplines' strategies for incorporating real-world learning opportunities differ, yet the students similarly advance in cognitive complexity and maintain motivation to learn. Lessons can be exchanged across professional boundaries. Copyright © 2016 Elsevier Inc. All rights reserved.

  12. Metasynthetic computing and engineering of complex systems

    CERN Document Server

    Cao, Longbing

    2015-01-01

    Provides a comprehensive overview and introduction to the concepts, methodologies, analysis, design and applications of metasynthetic computing and engineering. The author: Presents an overview of complex systems, especially open complex giant systems such as the Internet, complex behavioural and social problems, and actionable knowledge discovery and delivery in the big data era. Discusses ubiquitous intelligence in complex systems, including human intelligence, domain intelligence, social intelligence, network intelligence, data intelligence and machine intelligence, and their synergy thro

  13. Complexity: Outline of the NWO strategic theme Dynamics of complex systems

    NARCIS (Netherlands)

    Burgers, G.; Doelman, A.; Frenken, K.; Hogeweg, P.; Hommes, C.; van der Maas, H.; Mulder, B.; Stam, K.; van Steen, M.; Zandee, L.

    2008-01-01

    Dynamics of complex systems is one of the program 5 themes in the NWO (Netherlands Organisation for Scientific Research) strategy for the years 2007-2011. The ambition of the current proposal is to initiate integrated activities in the field of complex systems within the Netherlands, to provide

  14. Complexity : outline of the NWO strategic theme dynamics of complex systems

    NARCIS (Netherlands)

    Burgers, G.; Doelman, A.; Frenken, K.; Hogeweg, P.; Hommes, C.; Maas, van der H.; Mulder, B.; Stam, K.; Steen, van M.; Zandee, L.

    2008-01-01

    Dynamics of complex systems is one of the program 5 themes in the NWO (Netherlands Organisation for Scientific Research) strategy for the years 2007-2011. The ambition of the current proposal is to initiate integrated activities in the field of complex systems within the Netherlands, to provide

  15. Learning from simple ebooks, online cases or classroom teaching when acquiring complex knowledge. A randomized controlled trial in respiratory physiology and pulmonology

    DEFF Research Database (Denmark)

    Worm, Bjarne Skjødt

    2013-01-01

    E-learning is developing fast because of the rapid increased use of smartphones, tablets and portable computers. We might not think of it as e-learning, but today many new e-books are in fact very complex electronic teaching platforms. It is generally accepted that e-learning is as effective...... as classroom teaching methods, but little is known about its value in relaying contents of different levels of complexity to students. We set out to investigate e-learning effects on simple recall and complex problem-solving compared to classroom teaching....

  16. Imbalanced learning foundations, algorithms, and applications

    CERN Document Server

    He, Haibo

    2013-01-01

    The first book of its kind to review the current status and future direction of the exciting new branch of machine learning/data mining called imbalanced learning Imbalanced learning focuses on how an intelligent system can learn when it is provided with imbalanced data. Solving imbalanced learning problems is critical in numerous data-intensive networked systems, including surveillance, security, Internet, finance, biomedical, defense, and more. Due to the inherent complex characteristics of imbalanced data sets, learning from such data requires new understandings, principles,

  17. Recommender Systems in Technology Enhanced Learning

    NARCIS (Netherlands)

    Manouselis, Nikos; Drachsler, Hendrik; Verbert, Katrien; Santos, Olga

    2010-01-01

    Manouselis, N., Drachsler, H., Verbert, K., & Santos, C. S. (Eds.) (2010). Recommender System in Technology Enhanced Learning. Elsevier Procedia Computer Science: Volume 1, Issue 2. Proceedings of the 1st Workshop on Recommender Systems for Technology Enhanced Learning (RecSysTEL). September, 29-30,

  18. Reconceptualizing Learning as a Dynamical System.

    Science.gov (United States)

    Ennis, Catherine D.

    1992-01-01

    Dynamical systems theory can increase our understanding of the constantly evolving learning process. Current research using experimental and interpretive paradigms focuses on describing the attractors and constraints stabilizing the educational process. Dynamical systems theory focuses attention on critical junctures in the learning process as…

  19. Complex systems fractionality, time-delay and synchronization

    CERN Document Server

    Sun, Jian-Qiao

    2012-01-01

    "Complex Systems: Fractionality, Time-delay and Synchronization" covers the most recent developments and advances in the theory and application of complex systems in these areas. Each chapter was written by scientists highly active in the field of complex systems. The book discusses a new treatise on fractional dynamics and control, as well as the new methods for differential delay systems and control. Lastly, a theoretical framework for the complexity and synchronization of complex system is presented. The book is intended for researchers in the field of nonlinear dynamics in mathematics, physics and engineering. It can also serve as a reference book for graduate students in physics, applied mathematics and engineering. Dr. Albert C.J. Luo is a Professor at Southern Illinois University Edwardsville, USA. Dr. Jian-Qiao Sun is a Professor at the University of California, Merced, USA.

  20. Framework for Designing Context-Aware Learning Systems

    Science.gov (United States)

    Tortorella, Richard A. W.; Kinshuk; Chen, Nian-Shing

    2018-01-01

    Today people learn in many diverse locations and contexts, beyond the confines of classical brick and mortar classrooms. This trend is ever increasing, progressing hand-in-hand with the progress of technology. Context-aware learning systems are systems which adapt to the learner's context, providing tailored learning for a particular learning…

  1. Understanding valve program complexity in a refurbishment environment - learning from the past

    International Nuclear Information System (INIS)

    Roth, H.E.

    2012-01-01

    The complexity of Valve Program development, planning, execution and management in a refurbishment environment is an enormous undertaking requiring the proper coordination and integration of many moving parts. As such, lack of attention and understanding of this complexity has led to significant cost and schedule overruns in past refurbishment projects in the province. OPEX indicates the challenges in completing valve scope during refurbishments are related but not limited to; lack of detailed condition assessments, improper scope development, insignificant strategic approach to work task planning, scheduling and procurement, absence of contingency planning for common ‘as found’ conditions during execution, lack of proper training requirements, etc. In addition, past contracting strategies to employ numerous companies in collaboration to complete such a complex and specialized program, has resulted in further complications surrounding the management and integration of multiple quality programs and internal company processes. Finally, the aftermath of such fragmented projects results in an absolute closeout nightmare, often times taking years to locate, sift through and re-integrate pertinent information back into customer systems. Valve Program complexity cannot be understood by just anyone, only those that have lived through a refurbishment project and experienced the challenges mentioned above have the knowledge, skill, and ability to appreciate how to tactically apply past learning to realize future improvements. Furthermore, effective contractor-customer collaboration is crucial; true and in-depth knowledge and understanding of the customer quality programs, engineering and work management processes, configuration management requirements, and most importantly the imperative significance of nuclear safety, are all essential components to ensure overall alignment and program success. (author)

  2. Understanding valve program complexity in a refurbishment environment - learning from the past

    Energy Technology Data Exchange (ETDEWEB)

    Roth, H.E. [Babcock & Wilcox Canada Ltd., Cambridge, Ontario (Canada)

    2012-07-01

    The complexity of Valve Program development, planning, execution and management in a refurbishment environment is an enormous undertaking requiring the proper coordination and integration of many moving parts. As such, lack of attention and understanding of this complexity has led to significant cost and schedule overruns in past refurbishment projects in the province. OPEX indicates the challenges in completing valve scope during refurbishments are related but not limited to; lack of detailed condition assessments, improper scope development, insignificant strategic approach to work task planning, scheduling and procurement, absence of contingency planning for common ‘as found’ conditions during execution, lack of proper training requirements, etc. In addition, past contracting strategies to employ numerous companies in collaboration to complete such a complex and specialized program, has resulted in further complications surrounding the management and integration of multiple quality programs and internal company processes. Finally, the aftermath of such fragmented projects results in an absolute closeout nightmare, often times taking years to locate, sift through and re-integrate pertinent information back into customer systems. Valve Program complexity cannot be understood by just anyone, only those that have lived through a refurbishment project and experienced the challenges mentioned above have the knowledge, skill, and ability to appreciate how to tactically apply past learning to realize future improvements. Furthermore, effective contractor-customer collaboration is crucial; true and in-depth knowledge and understanding of the customer quality programs, engineering and work management processes, configuration management requirements, and most importantly the imperative significance of nuclear safety, are all essential components to ensure overall alignment and program success. (author)

  3. Mining sensor data from complex systems

    NARCIS (Netherlands)

    Vespier, Ugo

    2015-01-01

    Today, virtually everything, from natural phenomena to complex artificial and physical systems, can be measured and the resulting information collected, stored and analyzed in order to gain new insight. This thesis shows how complex systems often exhibit diverse behavior at different temporal

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

    Directory of Open Access Journals (Sweden)

    Sanja Bauk

    2014-01-01

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

  5. Instructional Control of Cognitive Load in the Design of Complex Learning Environments

    NARCIS (Netherlands)

    Kester, Liesbeth; Paas, Fred; Van Merriënboer, Jeroen

    2010-01-01

    Kester, L., Paas, F., & Van Merriënboer, J. J. G. (2010). Instructional control of cognitive load in the design of complex learning environments. In J. L. Plass, R. Moreno, & Roland Brünken (Eds.), Cognitive Load Theory (pp. 109-130). New York: Cambridge University Press.

  6. Digital case-based learning system in school.

    Science.gov (United States)

    Gu, Peipei; Guo, Jiayang

    2017-01-01

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

  7. Digital case-based learning system in school.

    Directory of Open Access Journals (Sweden)

    Peipei Gu

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

  8. Broad Learning System: An Effective and Efficient Incremental Learning System Without the Need for Deep Architecture.

    Science.gov (United States)

    Chen, C L Philip; Liu, Zhulin

    2018-01-01

    Broad Learning System (BLS) that aims to offer an alternative way of learning in deep structure is proposed in this paper. Deep structure and learning suffer from a time-consuming training process because of a large number of connecting parameters in filters and layers. Moreover, it encounters a complete retraining process if the structure is not sufficient to model the system. The BLS is established in the form of a flat network, where the original inputs are transferred and placed as "mapped features" in feature nodes and the structure is expanded in wide sense in the "enhancement nodes." The incremental learning algorithms are developed for fast remodeling in broad expansion without a retraining process if the network deems to be expanded. Two incremental learning algorithms are given for both the increment of the feature nodes (or filters in deep structure) and the increment of the enhancement nodes. The designed model and algorithms are very versatile for selecting a model rapidly. In addition, another incremental learning is developed for a system that has been modeled encounters a new incoming input. Specifically, the system can be remodeled in an incremental way without the entire retraining from the beginning. Satisfactory result for model reduction using singular value decomposition is conducted to simplify the final structure. Compared with existing deep neural networks, experimental results on the Modified National Institute of Standards and Technology database and NYU NORB object recognition dataset benchmark data demonstrate the effectiveness of the proposed BLS.

  9. Towards an evaluation framework for complex social systems

    Science.gov (United States)

    McDonald, Diane M.; Kay, Nigel

    While there is growing realisation that the world in which we live in is highly complex with multiple interdependencies and irreducibly open to outside influence, how to make these 'systems' more manageable is still a significant outstanding issue. As (2004) suggests, applying the theoretical principles of Complex Systems may help solve complex problems in this complex world. While Bar-Yam provides examples of forward-thinking organisations which have begun to see the relevance of complex systems principles, for many organisations the language and concepts of complexity science such as self-organisation and unpredictability while they make theoretical sense offer no practical or acceptable method of implementation to those more familiar with definitive facts and classical hierarchical, deterministic approaches to control. Complexity Science explains why designed systems or interventions may not function as anticipated in differing environments, without providing a silver bullet which enables control or engineering of the system to ensure the desired results. One familiar process which might, if implemented with complex systems in mind, provide the basis of an accessible and understandable framework that enables policy makers and practitioners to better design and manage complex socio-technical systems is that of evaluation.

  10. Adaptive e-learning system using ontology

    OpenAIRE

    Yarandi, Maryam; Tawil, Abdel-Rahman; Jahankhani, Hossein

    2011-01-01

    This paper proposes an innovative ontological approach to design a personalised e-learning system which creates a tailored workflow for individual learner. Moreover, the learning content and sequencing logic is separated into content model and pedagogical model to increase the reusability and flexibility of the system.

  11. Community detection in complex networks using deep auto-encoded extreme learning machine

    Science.gov (United States)

    Wang, Feifan; Zhang, Baihai; Chai, Senchun; Xia, Yuanqing

    2018-06-01

    Community detection has long been a fascinating topic in complex networks since the community structure usually unveils valuable information of interest. The prevalence and evolution of deep learning and neural networks have been pushing forward the advancement in various research fields and also provide us numerous useful and off the shelf techniques. In this paper, we put the cascaded stacked autoencoders and the unsupervised extreme learning machine (ELM) together in a two-level embedding process and propose a novel community detection algorithm. Extensive comparison experiments in circumstances of both synthetic and real-world networks manifest the advantages of the proposed algorithm. On one hand, it outperforms the k-means clustering in terms of the accuracy and stability thus benefiting from the determinate dimensions of the ELM block and the integration of sparsity restrictions. On the other hand, it endures smaller complexity than the spectral clustering method on account of the shrinkage in time spent on the eigenvalue decomposition procedure.

  12. Component-Based Approach in Learning Management System Development

    Science.gov (United States)

    Zaitseva, Larisa; Bule, Jekaterina; Makarov, Sergey

    2013-01-01

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

  13. Learning Science in a Virtual Reality Application: The Impacts of Animated-Virtual Actors' Visual Complexity

    Science.gov (United States)

    Kartiko, Iwan; Kavakli, Manolya; Cheng, Ken

    2010-01-01

    As the technology in computer graphics advances, Animated-Virtual Actors (AVAs) in Virtual Reality (VR) applications become increasingly rich and complex. Cognitive Theory of Multimedia Learning (CTML) suggests that complex visual materials could hinder novice learners from attending to the lesson properly. On the other hand, previous studies have…

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

    Directory of Open Access Journals (Sweden)

    Omar Abou Khaled

    2000-01-01

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

  15. An earned presence: studying the effect of multi-task improvisation systems on cognitive and learning capacity

    Science.gov (United States)

    Hansen, Pil; Oxoby, Robert J.

    2017-01-01

    In this article, we articulate preliminary insights from two pilot studies. These studies contribute to an ongoing process of developing empirical, cross-disciplinary measures to understand the cognitive and learning effects of complex artistic practices - effects that we situate between theory of embodied concepts and conceptually calibrated physical attention and action. The stage of this process that we report on here was led by the cognitive performance studies scholar and dramaturge, Pil Hansen, and undertaken in collaboration with the experimental psychologist, Vina Goghari, and the behavioural economist, Robert Oxoby, assisted by four research assistants from Drama, Music, and Psychology at the University of Calgary. Our team set out to test the following hypothesis: Active participation in performance generating systems has a positive effect on advanced student performers' working memory capacity, executive functions, and learning. Our results have implications, in particular, for understandings of embodied learning in the educational sector, however a perhaps more significant contribution is a better understanding of the measures and constructs needed to arrive at a more complex, yet operational concept of embodied learning and forward the experimental study of relationships between performing arts practices, cognition, and learning.

  16. A System for Complex Robotic Welding

    DEFF Research Database (Denmark)

    Madsen, Ole; Sørensen, Carsten Bro; Olsen, Birger

    2002-01-01

    This paper presents the architecture of a system for robotic welding of complex tasks. The system integrates off-line programming, control of redundant robots, collision-free motion planning and sensor-based control. An implementation for pipe structure welding made at Odense Steel Shipyard Ltd......., Denmark, demonstrates the system can be used for automatic welding of complex products in one-of-a-kind production....

  17. Analysis and control of complex dynamical systems robust bifurcation, dynamic attractors, and network complexity

    CERN Document Server

    Imura, Jun-ichi; Ueta, Tetsushi

    2015-01-01

    This book is the first to report on theoretical breakthroughs on control of complex dynamical systems developed by collaborative researchers in the two fields of dynamical systems theory and control theory. As well, its basic point of view is of three kinds of complexity: bifurcation phenomena subject to model uncertainty, complex behavior including periodic/quasi-periodic orbits as well as chaotic orbits, and network complexity emerging from dynamical interactions between subsystems. Analysis and Control of Complex Dynamical Systems offers a valuable resource for mathematicians, physicists, and biophysicists, as well as for researchers in nonlinear science and control engineering, allowing them to develop a better fundamental understanding of the analysis and control synthesis of such complex systems.

  18. Emergent Learning and Learning Ecologies in Web 2.0

    Directory of Open Access Journals (Sweden)

    Roy Williams

    2011-03-01

    Full Text Available This paper describes emergent learning and situates it within learning networks and systems and the broader learning ecology of Web 2.0. It describes the nature of emergence and emergent learning and the conditions that enable emergent, self-organised learning to occur and to flourish. Specifically, it explores whether emergent learning can be validated and self-correcting and whether it is possible to link or integrate emergent and prescribed learning. It draws on complexity theory, communities of practice, and the notion of connectivism to develop some of the foundations for an analytic framework, for enabling and managing emergent learning and networks in which agents and systems co-evolve. It then examines specific cases of learning to test and further develop the analytic framework.The paper argues that although social networking media increase the potential range and scope for emergent learning exponentially, considerable effort is required to ensure an effective balance between openness and constraint. It is possible to manage the relationship between prescriptive and emergent learning, both of which need to be part of an integrated learning ecology.

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

    Directory of Open Access Journals (Sweden)

    Xu Ling

    2016-01-01

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

  20. Modeling Power Systems as Complex Adaptive Systems

    Energy Technology Data Exchange (ETDEWEB)

    Chassin, David P.; Malard, Joel M.; Posse, Christian; Gangopadhyaya, Asim; Lu, Ning; Katipamula, Srinivas; Mallow, J V.

    2004-12-30

    Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.

  1. E-Learning Systems, Environments and Approaches

    OpenAIRE

    Isaias, P.; Spector, J.M.; Ifenthaler, D.; Sampson, D.G.

    2015-01-01

    The volume consists of twenty-five chapters selected from among peer-reviewed papers presented at the CELDA (Cognition and Exploratory Learning in the Digital Age) 2013 Conference held in Fort Worth, Texas, USA, in October 2013 and also from world class scholars in e-learning systems, environments and approaches. The following sub-topics are included: Exploratory Learning Technologies (Part I), e-Learning social web design (Part II), Learner communities through e-Learning implementations (Par...

  2. Intelligent fractions learning system: implementation

    CSIR Research Space (South Africa)

    Smith, Andrew C

    2011-05-01

    Full Text Available Conference Proceedings Paul Cunningham and Miriam Cunningham (Eds) IIMC International Information Management Corporation, 2011 ISBN: 978-1-905824-24-3 An Intelligent Fractions Learning System: Implementation Andrew Cyrus SMITH1, Teemu H. LAINE2 1CSIR... to fractions. Our aim with the current research project is to extend the existing UFractions learning system to incorporate automatic data capturing. ?Intelligent UFractions? allows a teacher to remotely monitor the children?s progress during...

  3. The amygdala complex: multiple roles in associative learning and attention.

    OpenAIRE

    Gallagher, M; Holland, P C

    1994-01-01

    Although certain neurophysiological functions of the amygdala complex in learning seem well established, the purpose of this review is to propose that an additional conceptualization of amygdala function is now needed. The research we review provides evidence that a subsystem within the amygdala provides a coordinated regulation of attentional processes. An important aspect of this additional neuropsychology of the amygdala is that it may aid in understanding the importance of connections bet...

  4. Modelling methodology for engineering of complex sociotechnical systems

    CSIR Research Space (South Africa)

    Oosthuizen, R

    2014-10-01

    Full Text Available Different systems engineering techniques and approaches are applied to design and develop complex sociotechnical systems for complex problems. In a complex sociotechnical system cognitive and social humans use information technology to make sense...

  5. Stephen Jay Kline on systems, or physics, complex systems, and the gap between.

    Energy Technology Data Exchange (ETDEWEB)

    Campbell, Philip LaRoche

    2011-06-01

    At the end of his life, Stephen Jay Kline, longtime professor of mechanical engineering at Stanford University, completed a book on how to address complex systems. The title of the book is 'Conceptual Foundations of Multi-Disciplinary Thinking' (1995), but the topic of the book is systems. Kline first establishes certain limits that are characteristic of our conscious minds. Kline then establishes a complexity measure for systems and uses that complexity measure to develop a hierarchy of systems. Kline then argues that our minds, due to their characteristic limitations, are unable to model the complex systems in that hierarchy. Computers are of no help to us here. Our attempts at modeling these complex systems are based on the way we successfully model some simple systems, in particular, 'inert, naturally-occurring' objects and processes, such as what is the focus of physics. But complex systems overwhelm such attempts. As a result, the best we can do in working with these complex systems is to use a heuristic, what Kline calls the 'Guideline for Complex Systems.' Kline documents the problems that have developed due to 'oversimple' system models and from the inappropriate application of a system model from one domain to another. One prominent such problem is the Procrustean attempt to make the disciplines that deal with complex systems be 'physics-like.' Physics deals with simple systems, not complex ones, using Kline's complexity measure. The models that physics has developed are inappropriate for complex systems. Kline documents a number of the wasteful and dangerous fallacies of this type.

  6. An E-learning System based on Affective Computing

    Science.gov (United States)

    Duo, Sun; Song, Lu Xue

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

  7. Successfully carrying out complex learning-tasks through guiding teams' qualitative and quantitative reasoning

    NARCIS (Netherlands)

    Slof, B.; Erkens, G.; Kirschner, P. A.; Janssen, J.; Jaspers, J. G. M.

    This study investigated whether and how scripting learners' use of representational tools in a computer supported collaborative learning (CSCL)-environment fostered their collaborative performance on a complex business-economics task. Scripting the problem-solving process sequenced and made its

  8. Sonification and haptic feedback in addition to visual feedback enhances complex motor task learning.

    Science.gov (United States)

    Sigrist, Roland; Rauter, Georg; Marchal-Crespo, Laura; Riener, Robert; Wolf, Peter

    2015-03-01

    Concurrent augmented feedback has been shown to be less effective for learning simple motor tasks than for complex tasks. However, as mostly artificial tasks have been investigated, transfer of results to tasks in sports and rehabilitation remains unknown. Therefore, in this study, the effect of different concurrent feedback was evaluated in trunk-arm rowing. It was then investigated whether multimodal audiovisual and visuohaptic feedback are more effective for learning than visual feedback only. Naïve subjects (N = 24) trained in three groups on a highly realistic virtual reality-based rowing simulator. In the visual feedback group, the subject's oar was superimposed to the target oar, which continuously became more transparent when the deviation between the oars decreased. Moreover, a trace of the subject's trajectory emerged if deviations exceeded a threshold. The audiovisual feedback group trained with oar movement sonification in addition to visual feedback to facilitate learning of the velocity profile. In the visuohaptic group, the oar movement was inhibited by path deviation-dependent braking forces to enhance learning of spatial aspects. All groups significantly decreased the spatial error (tendency in visual group) and velocity error from baseline to the retention tests. Audiovisual feedback fostered learning of the velocity profile significantly more than visuohaptic feedback. The study revealed that well-designed concurrent feedback fosters complex task learning, especially if the advantages of different modalities are exploited. Further studies should analyze the impact of within-feedback design parameters and the transferability of the results to other tasks in sports and rehabilitation.

  9. Complex engineering systems science meets technology

    CERN Document Server

    Minai, Ali A; Bar-Yam, Yaneer

    2006-01-01

    Every time that we take money out of an ATM, surf the internet or simply turn on a light switch, we enjoy the benefits of complex engineered systems. Systems like power grids and global communication networks are so ubiquitous in our daily lives that we usually take them for granted, only noticing them when they break down. But how do such amazing technologies and infrastructures come to be what they are? How are these systems designed? How do distributed networks work? How are they made to respond rapidly in 'real time'? And as the demands that we place on these systems become increasingly complex, are traditional systems-engineering practices still relevant? This volume examines the difficulties that arise in creating highly complex engineered systems and new approaches that are being adopted. Topics addressed range from the formal representation and classification of distributed networked systems to revolutionary engineering practices inspired by biological evolution. By bringing together the latest resear...

  10. Moving towards Virtual Learning Clouds from Traditional Learning: Higher Educational Systems in India

    Directory of Open Access Journals (Sweden)

    Vasanthi Muniasamy

    2014-10-01

    Full Text Available E-Learning has become an increasingly popular learning approach in higher Education institutions due to the rapid growth of Communication and Information Technology (CIT. In recent years, it has been integrated in many university programs and it is one of the new learning trends. But in many Indian Universities did not implement this novel technology in their Educational Systems. E-Learning is not intended to replace the traditional classroom setting, but to provide new opportunities and new virtual environment for interaction and communication between the students and teacher. E-Learning through Cloud is now becoming an interesting and very useful revolutionary technology in the field of education. E-Learning system usually requires huge amount of hardware and software resources. Due to the cost, many universities in India do not want to implement the E-Learning technology in their Educational system and they cannot afford such investments. Cloud Virtual Learning is the only solution for this problem. This paper presents the benefits of using cloud technology in E-Learning system, working mode, Services, Models. And also we discuss the cloud computing educational environment and how higher education may take advantage of clouds not only in terms of cost but also in terms of Security, flexibility, portability, efficiency and reliability. And also we present some educational clouds introduced by popular cloud providers.

  11. Linear System Control Using Stochastic Learning Automata

    Science.gov (United States)

    Ziyad, Nigel; Cox, E. Lucien; Chouikha, Mohamed F.

    1998-01-01

    This paper explains the use of a Stochastic Learning Automata (SLA) to control switching between three systems to produce the desired output response. The SLA learns the optimal choice of the damping ratio for each system to achieve a desired result. We show that the SLA can learn these states for the control of an unknown system with the proper choice of the error criteria. The results of using a single automaton are compared to using multiple automata.

  12. Controlling Uncertainty Decision Making and Learning in Complex Worlds

    CERN Document Server

    Osman, Magda

    2010-01-01

    Controlling Uncertainty: Decision Making and Learning in Complex Worlds reviews and discusses the most current research relating to the ways we can control the uncertain world around us.: Features reviews and discussions of the most current research in a number of fields relevant to controlling uncertainty, such as psychology, neuroscience, computer science and engineering; Presents a new framework that is designed to integrate a variety of disparate fields of research; Represents the first book of its kind to provide a general overview of work related to understanding control

  13. Modeling student's learning styles in web 2.0 learning systems

    Directory of Open Access Journals (Sweden)

    Ramon Cabada Zatarain Cabada, M. L. Barron Estrada, L. Zepeda Sanchez, Guillermo Sandoval, J.M. Osorio Velazquez, J.E. Urias Barrientos

    2009-12-01

    Full Text Available The identification of the best learning style in an Intelligent Tutoring System must be considered essential as part of thesuccess in the teaching process. In many implementations of automatic classifiers finding the right student learning styler e p r e s e n t s t h e h a r d e s t a s s i g n m e n t . T h e r e a s o n i s t h a t m o s t o f t h e t e c h n i q u e s w o r k u s i n g e x p e r t g r o u p s o r a s e t o fquestionnaires which define how the learning styles are assigned to students. This paper presents a novel approach forautomatic learning styles classification using a Kohonen network. The approach is used by an author tool for buildingIntelligent Tutoring Systems running under a Web 2.0 collaborative learning platform. The tutoring systems together withthe neural network can also be exported to mobile devices. We present different results to the approach working under theauthor tool.

  14. ComplexContact: a web server for inter-protein contact prediction using deep learning

    KAUST Repository

    Zeng, Hong; Wang, Sheng; Zhou, Tianming; Zhao, Feifeng; Li, Xiufeng; Wu, Qing; Xu, Jinbo

    2018-01-01

    ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

  15. ComplexContact: a web server for inter-protein contact prediction using deep learning

    KAUST Repository

    Zeng, Hong

    2018-05-20

    ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

  16. ComplexContact: a web server for inter-protein contact prediction using deep learning.

    Science.gov (United States)

    Zeng, Hong; Wang, Sheng; Zhou, Tianming; Zhao, Feifeng; Li, Xiufeng; Wu, Qing; Xu, Jinbo

    2018-05-22

    ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.

  17. Decentralized control of complex systems

    CERN Document Server

    Siljak, Dragoslav D

    2011-01-01

    Complex systems require fast control action in response to local input, and perturbations dictate the use of decentralized information and control structures. This much-cited reference book explores the approaches to synthesizing control laws under decentralized information structure constraints.Starting with a graph-theoretic framework for structural modeling of complex systems, the text presents results related to robust stabilization via decentralized state feedback. Subsequent chapters explore optimization, output feedback, the manipulative power of graphs, overlapping decompositions and t

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

    Science.gov (United States)

    Jeong, Hwa-Young; Yi, Gangman

    2014-01-01

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

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

    Science.gov (United States)

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

    2011-01-01

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

  20. Early motor learning changes in upper-limb dynamics and shoulder complex loading during handrim wheelchair propulsion.

    Science.gov (United States)

    Vegter, Riemer J K; Hartog, Johanneke; de Groot, Sonja; Lamoth, Claudine J; Bekker, Michel J; van der Scheer, Jan W; van der Woude, Lucas H V; Veeger, Dirkjan H E J

    2015-03-10

    To propel in an energy-efficient manner, handrim wheelchair users must learn to control the bimanually applied forces onto the rims, preserving both speed and direction of locomotion. Previous studies have found an increase in mechanical efficiency due to motor learning associated with changes in propulsion technique, but it is unclear in what way the propulsion technique impacts the load on the shoulder complex. The purpose of this study was to evaluate mechanical efficiency, propulsion technique and load on the shoulder complex during the initial stage of motor learning. 15 naive able-bodied participants received 12-minutes uninstructed wheelchair practice on a motor driven treadmill, consisting of three 4-minute blocks separated by two minutes rest. Practice was performed at a fixed belt speed (v = 1.1 m/s) and constant low-intensity power output (0.2 W/kg). Energy consumption, kinematics and kinetics of propulsion technique were continuously measured. The Delft Shoulder Model was used to calculate net joint moments, muscle activity and glenohumeral reaction force. With practice mechanical efficiency increased and propulsion technique changed, reflected by a reduced push frequency and increased work per push, performed over a larger contact angle, with more tangentially applied force and reduced power losses before and after each push. Contrary to our expectations, the above mentioned propulsion technique changes were found together with an increased load on the shoulder complex reflected by higher net moments, a higher total muscle power and higher peak and mean glenohumeral reaction forces. It appears that the early stages of motor learning in handrim wheelchair propulsion are indeed associated with improved technique and efficiency due to optimization of the kinematics and dynamics of the upper extremity. This process goes at the cost of an increased muscular effort and mechanical loading of the shoulder complex. This seems to be associated with an

  1. Learning in tele-autonomous systems using Soar

    Science.gov (United States)

    Laird, John E.; Yager, Eric S.; Tuck, Christopher M.; Hucka, Michael

    1989-01-01

    Robo-Soar is a high-level robot arm control system implemented in Soar. Robo-Soar learns to perform simple block manipulation tasks using advice from a human. Following learning, the system is able to perform similar tasks without external guidance. It can also learn to correct its knowledge, using its own problem solving in addition to outside guidance. Robo-Soar corrects its knowledge by accepting advice about relevance of features in its domain, using a unique integration of analytic and empirical learning techniques.

  2. Student Learning of Complex Earth Systems: A Model to Guide Development of Student Expertise in Problem-Solving

    Science.gov (United States)

    Holder, Lauren N.; Scherer, Hannah H.; Herbert, Bruce E.

    2017-01-01

    Engaging students in problem-solving concerning environmental issues in near-surface complex Earth systems involves developing student conceptualization of the Earth as a system and applying that scientific knowledge to the problems using practices that model those used by professionals. In this article, we review geoscience education research…

  3. Visualizing complex (hydrological) systems with correlation matrices

    Science.gov (United States)

    Haas, J. C.

    2016-12-01

    When trying to understand or visualize the connections of different aspects of a complex system, this often requires deeper understanding to start with, or - in the case of geo data - complicated GIS software. To our knowledge, correlation matrices have rarely been used in hydrology (e.g. Stoll et al., 2011; van Loon and Laaha, 2015), yet they do provide an interesting option for data visualization and analysis. We present a simple, python based way - using a river catchment as an example - to visualize correlations and similarities in an easy and colorful way. We apply existing and easy to use python packages from various disciplines not necessarily linked to the Earth sciences and can thus quickly show how different aquifers work or react, and identify outliers, enabling this system to also be used for quality control of large datasets. Going beyond earlier work, we add a temporal and spatial element, enabling us to visualize how a system reacts to local phenomena such as for example a river, or changes over time, by visualizing the passing of time in an animated movie. References: van Loon, A.F., Laaha, G.: Hydrological drought severity explained by climate and catchment characteristics, Journal of Hydrology 526, 3-14, 2015, Drought processes, modeling, and mitigation Stoll, S., Hendricks Franssen, H. J., Barthel, R., Kinzelbach, W.: What can we learn from long-term groundwater data to improve climate change impact studies?, Hydrology and Earth System Sciences 15(12), 3861-3875, 2011

  4. Assessing Complex Learning Objectives through Analytics

    Science.gov (United States)

    Horodyskyj, L.; Mead, C.; Buxner, S.; Semken, S. C.; Anbar, A. D.

    2016-12-01

    A significant obstacle to improving the quality of education is the lack of easy-to-use assessments of higher-order thinking. Most existing assessments focus on recall and understanding questions, which demonstrate lower-order thinking. Traditionally, higher-order thinking is assessed with practical tests and written responses, which are time-consuming to analyze and are not easily scalable. Computer-based learning environments offer the possibility of assessing such learning outcomes based on analysis of students' actions within an adaptive learning environment. Our fully online introductory science course, Habitable Worlds, uses an intelligent tutoring system that collects and responds to a range of behavioral data, including actions within the keystone project. This central project is a summative, game-like experience in which students synthesize and apply what they have learned throughout the course to identify and characterize a habitable planet from among hundreds of stars. Student performance is graded based on completion and accuracy, but two additional properties can be utilized to gauge higher-order thinking: (1) how efficient a student is with the virtual currency within the project and (2) how many of the optional milestones a student reached. In the project, students can use the currency to check their work and "unlock" convenience features. High-achieving students spend close to the minimum amount required to reach these goals, indicating a high-level of concept mastery and efficient methodology. Average students spend more, indicating effort, but lower mastery. Low-achieving students were more likely to spend very little, which indicates low effort. Differences on these metrics were statistically significant between all three of these populations. We interpret this as evidence that high-achieving students develop and apply efficient problem-solving skills as compared to lower-achieving student who use more brute-force approaches.

  5. Conveying the Complex: Updating U.S. Joint Systems Analysis Doctrine with Complexity Theory

    Science.gov (United States)

    2013-12-10

    and useful to as broad 59See Peter Checkland and John Poulter, Learning for Action: A Short Definitive Account of Soft Systems Methodology and Its...Unstoppable Power of Leaderless Organizations. New York: Penguin Group, 2006. Checkland , Peter and Poulter, John. Learning for Action: A Short Definitive

  6. A computational approach to achieve situational awareness from limited observations of a complex system

    Science.gov (United States)

    Sherwin, Jason

    human activities. Nevertheless, since it is not constrained by computational details, the study of situational awareness provides a unique opportunity to approach complex tasks of operation from an analytical perspective. In other words, with SA, we get to see how humans observe, recognize and react to complex systems on which they exert some control. Reconciling this perspective on complexity with complex systems research, it might be possible to further our understanding of complex phenomena if we can probe the anatomical mechanisms by which we, as humans, do it naturally. At this unique intersection of two disciplines, a hybrid approach is needed. So in this work, we propose just such an approach. In particular, this research proposes a computational approach to the situational awareness (SA) of complex systems. Here we propose to implement certain aspects of situational awareness via a biologically-inspired machine-learning technique called Hierarchical Temporal Memory (HTM). In doing so, we will use either simulated or actual data to create and to test computational implementations of situational awareness. This will be tested in two example contexts, one being more complex than the other. The ultimate goal of this research is to demonstrate a possible approach to analyzing and understanding complex systems. By using HTM and carefully developing techniques to analyze the SA formed from data, it is believed that this goal can be obtained.

  7. Coping with complexity: machine learning optimization of cell-free protein synthesis.

    Science.gov (United States)

    Caschera, Filippo; Bedau, Mark A; Buchanan, Andrew; Cawse, James; de Lucrezia, Davide; Gazzola, Gianluca; Hanczyc, Martin M; Packard, Norman H

    2011-09-01

    Biological systems contain complex metabolic pathways with many nonlinearities and synergies that make them difficult to predict from first principles. Protein synthesis is a canonical example of such a pathway. Here we show how cell-free protein synthesis may be improved through a series of iterated high-throughput experiments guided by a machine-learning algorithm implementing a form of evolutionary design of experiments (Evo-DoE). The algorithm predicts fruitful experiments from statistical models of the previous experimental results, combined with stochastic exploration of the experimental space. The desired experimental response, or evolutionary fitness, was defined as the yield of the target product, and new experimental conditions were discovered to have ∼ 350% greater yield than the standard. An analysis of the best experimental conditions discovered indicates that there are two distinct classes of kinetics, thus showing how our evolutionary design of experiments is capable of significant innovation, as well as gradual improvement. Copyright © 2011 Wiley Periodicals, Inc.

  8. Balancing exploration and exploitation in learning to rank online

    NARCIS (Netherlands)

    Hofmann, K.; Whiteson, S.; de Rijke, M.

    2011-01-01

    As retrieval systems become more complex, learning to rank approaches are being developed to automatically tune their parameters. Using online learning to rank approaches, retrieval systems can learn directly from implicit feedback, while they are running. In such an online setting, algorithms need

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

    Science.gov (United States)

    Rahmaniar; Putri, Maharani

    2018-03-01

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

  10. Self-Efficacy, Task Complexity and Task Performance: Exploring Interactions in Two Versions of Vocabulary Learning Tasks

    Science.gov (United States)

    Wu, Xiaoli; Lowyck, Joost; Sercu, Lies; Elen, Jan

    2012-01-01

    The present study aimed for better understanding of the interactions between task complexity and students' self-efficacy beliefs and students' use of learning strategies, and finally their interacting effects on task performance. This investigation was carried out in the context of Chinese students learning English as a foreign language in a…

  11. Seeking a potential system in managing organizational knowledge flow towards enhancing individual learning and intellectual capital

    Directory of Open Access Journals (Sweden)

    Intan Soraya Rosdi

    2013-12-01

    Full Text Available The knowledge-based economy of today heralds an era where the business environment is characterized by complex and ever-changing conditions, driven by rapid technological advancements. With knowledge regarded as the main competitive resource, continuous learning becomes critical to firms as they try to keep up with the latest technology and business practices. Moreover, knowledge resides within individual employees, and the challenge is to ensure that knowledge is acquired, applied, and shared to benefit the firm. The situation becomes more complex when it is established that there exists different human capital in firms at any one time, differentiated based on the types of knowledge they contribute to the firm. Further, scant literature exists on the relationship dynamics between the different human capital groups and their influences on individual learning. This paper aims to propose a potential system to manage interaction between the different human capital groups within firms, and its link to enhancing different types of individual learning and intellectual capital.

  12. Gender, Complexity, and Science for All: Systemizing and Its Impact on Motivation to Learn Science for Different Science Subjects

    Science.gov (United States)

    Zeyer, Albert

    2018-01-01

    The present study is based on a large cross-cultural study, which showed that a systemizing cognition type has a high impact on motivation to learn science, while the impact of gender is only indirect thorough systemizing. The present study uses the same structural equation model as in the cross-cultural study and separately tests it for physics,…

  13. A Studi on High Plant Systems Course with Active Learning in Higher Education Through Outdoor Learning to Increase Student Learning Activities

    OpenAIRE

    Nur Rokhimah Hanik, Anwari Adi Nugroho

    2015-01-01

    Biology learning especially high plant system courses needs to be applied to active learning centered on the student (Active Learning In Higher Education) to enhance the students' learning activities so that the quality of learning for the better. Outdoor Learning is one of the active learning invites students to learn outside of the classroom by exploring the surrounding environment. This research aims to improve the students' learning activities in the course of high plant systems through t...

  14. Task complexity as a driver for collaborative learning efficiency: The collective working-memory effect

    NARCIS (Netherlands)

    Kirschner, Femke; Paas, Fred; Kirschner, Paul A.

    2010-01-01

    Kirschner, F., Paas, F., & Kirschner, P. A. (2011). Task complexity as a driver for collaborative learning efficiency: The collective working-memory effect. Applied Cognitive Psychology, 25, 615–624. doi: 10.1002/acp.1730.

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

    Directory of Open Access Journals (Sweden)

    Hwa-Young Jeong

    2014-01-01

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

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

    OpenAIRE

    Wernhuar Tarng; Weichian Tsai

    2010-01-01

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

  17. Organizational Learning in Health Care Organizations

    Directory of Open Access Journals (Sweden)

    Savithiri Ratnapalan

    2014-02-01

    Full Text Available The process of collective education in an organization that has the capacity to impact an organization’s operations, performance and outcomes is called organizational learning. In health care organizations, patient care is provided through one or more visible and invisible teams. These teams are composed of experts and novices from diverse backgrounds working together to provide coordinated care. The number of teams involved in providing care and the possibility of breakdowns in communication and coordinated care increases in direct proportion to sophisticated technology and treatment strategies of complex disease processes. Safe patient care is facilitated by individual professional learning; inter-professional team learning and system based organizational learning, which encompass modified context specific learning by multiple teams and team members in a health care organization. Organizational learning in health care systems is central to managing the learning requirements in complex interconnected dynamic systems where all have to know common background knowledge along with shared meta-knowledge of roles and responsibilities to execute their assigned functions, communicate and transfer the flow of pertinent information and collectively provide safe patient care. Organizational learning in health care is not a onetime intervention, but a continuing organizational phenomenon that occurs through formal and informal learning which has reciprocal association with organizational change. As such, organizational changes elicit organizational learning and organizational learning implements new knowledge and practices to create organizational changes.

  18. Building flexibility and managing complexity in community mental health: lessons learned in a large urban centre.

    Science.gov (United States)

    Stergiopoulos, Vicky; Saab, Dima; Francombe Pridham, Kate; Aery, Anjana; Nakhost, Arash

    2018-01-24

    Across many jurisdictions, adults with complex mental health and social needs face challenges accessing appropriate supports due to system fragmentation and strict eligibility criteria of existing services. To support this underserviced population, Toronto's local health authority launched two novel community mental health models in 2014, inspired by Flexible Assertive Community Team principles. This study explores service user and provider perspectives on the acceptability of these services, and lessons learned during early implementation. We purposively sampled 49 stakeholders (staff, physicians, service users, health systems stakeholders) and conducted 17 semi-structured qualitative interviews and 5 focus groups between October 23, 2014 and March 2, 2015, exploring stakeholder perspectives on the newly launched team based models, as well as activities and strategies employed to support early implementation. Interviews and focus groups were audio recorded, transcribed verbatim and analyzed using thematic analysis. Findings revealed wide-ranging endorsement for the two team-based models' success in engaging the target population of adults with complex service needs. Implementation strengths included the broad recognition of existing service gaps, the use of interdisciplinary teams and experienced service providers, broad partnerships and collaboration among various service sectors, training and team building activities. Emerging challenges included lack of complementary support services such as suitable housing, organizational contexts reluctant to embrace change and risk associated with complexity, as well as limited service provider and organizational capacity to deliver evidence-based interventions. Findings identified implementation drivers at the practitioner, program, and system levels, specific to the implementation of community mental health interventions for adults with complex health and social needs. These can inform future efforts to address the health

  19. A Cognition-based View of Decision Processes in Complex Social-Ecological Systems

    Directory of Open Access Journals (Sweden)

    Kathi K. Beratan

    2007-06-01

    Full Text Available This synthesis paper is intended to provide an overview of individual and collective decision-making processes that might serve as a theoretical foundation for a complexity-based approach to environmental policy design and natural resource management planning. Human activities are the primary drivers of change in the Earth's biosphere today, so efforts to shift the trajectory of social-ecological systems must focus on changes in individual and collective human behavior. Recent advances in understanding the biological basis of thought and memory offer insights of use in designing management and planning processes. The human brain has evolved ways of dealing with complexity and uncertainty, and is particularly attuned to social information. Changes in an individual's schemas, reflecting changes in the patterns of neural connections that are activated by particular stimuli, occur primarily through nonconsious processes in response to experiential learning during repeated exposure to novel situations, ideas, and relationships. Discourse is an important mechanism for schema modification, and thus for behavior change. Through discourse, groups of people construct a shared story - a collective model - that is useful for predicting likely outcomes of actions and events. In effect, good stories are models that filter and organize distributed knowledge about complex situations and relationships in ways that are readily absorbed by human cognitive processes. The importance of discourse supports the view that collaborative approaches are needed to effectively deal with environmental problems and natural resource management challenges. Methods derived from the field of mediation and dispute resolution can help us take advantage of the distinctly human ability to deal with complexity and uncertainty. This cognitive view of decision making supports fundamental elements of resilience management and adaptive co-management, including fostering social learning

  20. The immune system, adaptation, and machine learning

    Science.gov (United States)

    Farmer, J. Doyne; Packard, Norman H.; Perelson, Alan S.

    1986-10-01

    The immune system is capable of learning, memory, and pattern recognition. By employing genetic operators on a time scale fast enough to observe experimentally, the immune system is able to recognize novel shapes without preprogramming. Here we describe a dynamical model for the immune system that is based on the network hypothesis of Jerne, and is simple enough to simulate on a computer. This model has a strong similarity to an approach to learning and artificial intelligence introduced by Holland, called the classifier system. We demonstrate that simple versions of the classifier system can be cast as a nonlinear dynamical system, and explore the analogy between the immune and classifier systems in detail. Through this comparison we hope to gain insight into the way they perform specific tasks, and to suggest new approaches that might be of value in learning systems.

  1. When complexity science meets implementation science: a theoretical and empirical analysis of systems change.

    Science.gov (United States)

    Braithwaite, Jeffrey; Churruca, Kate; Long, Janet C; Ellis, Louise A; Herkes, Jessica

    2018-04-30

    Implementation science has a core aim - to get evidence into practice. Early in the evidence-based medicine movement, this task was construed in linear terms, wherein the knowledge pipeline moved from evidence created in the laboratory through to clinical trials and, finally, via new tests, drugs, equipment, or procedures, into clinical practice. We now know that this straight-line thinking was naïve at best, and little more than an idealization, with multiple fractures appearing in the pipeline. The knowledge pipeline derives from a mechanistic and linear approach to science, which, while delivering huge advances in medicine over the last two centuries, is limited in its application to complex social systems such as healthcare. Instead, complexity science, a theoretical approach to understanding interconnections among agents and how they give rise to emergent, dynamic, systems-level behaviors, represents an increasingly useful conceptual framework for change. Herein, we discuss what implementation science can learn from complexity science, and tease out some of the properties of healthcare systems that enable or constrain the goals we have for better, more effective, more evidence-based care. Two Australian examples, one largely top-down, predicated on applying new standards across the country, and the other largely bottom-up, adopting medical emergency teams in over 200 hospitals, provide empirical support for a complexity-informed approach to implementation. The key lessons are that change can be stimulated in many ways, but a triggering mechanism is needed, such as legislation or widespread stakeholder agreement; that feedback loops are crucial to continue change momentum; that extended sweeps of time are involved, typically much longer than believed at the outset; and that taking a systems-informed, complexity approach, having regard for existing networks and socio-technical characteristics, is beneficial. Construing healthcare as a complex adaptive system

  2. Learning to Control Advanced Life Support Systems

    Science.gov (United States)

    Subramanian, Devika

    2004-01-01

    Advanced life support systems have many interacting processes and limited resources. Controlling and optimizing advanced life support systems presents unique challenges. In particular, advanced life support systems are nonlinear coupled dynamical systems and it is difficult for humans to take all interactions into account to design an effective control strategy. In this project. we developed several reinforcement learning controllers that actively explore the space of possible control strategies, guided by rewards from a user specified long term objective function. We evaluated these controllers using a discrete event simulation of an advanced life support system. This simulation, called BioSim, designed by Nasa scientists David Kortenkamp and Scott Bell has multiple, interacting life support modules including crew, food production, air revitalization, water recovery, solid waste incineration and power. They are implemented in a consumer/producer relationship in which certain modules produce resources that are consumed by other modules. Stores hold resources between modules. Control of this simulation is via adjusting flows of resources between modules and into/out of stores. We developed adaptive algorithms that control the flow of resources in BioSim. Our learning algorithms discovered several ingenious strategies for maximizing mission length by controlling the air and water recycling systems as well as crop planting schedules. By exploiting non-linearities in the overall system dynamics, the learned controllers easily out- performed controllers written by human experts. In sum, we accomplished three goals. We (1) developed foundations for learning models of coupled dynamical systems by active exploration of the state space, (2) developed and tested algorithms that learn to efficiently control air and water recycling processes as well as crop scheduling in Biosim, and (3) developed an understanding of the role machine learning in designing control systems for

  3. Complex Physical, Biophysical and Econophysical Systems

    Science.gov (United States)

    Dewar, Robert L.; Detering, Frank

    1. Introduction to complex and econophysics systems: a navigation map / T. Aste and T. Di Matteo -- 2. An introduction to fractional diffusion / B. I. Henry, T.A.M. Langlands and P. Straka -- 3. Space plasmas and fusion plasmas as complex systems / R. O. Dendy -- 4. Bayesian data analysis / M. S. Wheatland -- 5. Inverse problems and complexity in earth system science / I. G. Enting -- 6. Applied fluid chaos: designing advection with periodically reoriented flows for micro to geophysical mixing and transport enhancement / G. Metcalfe -- 7. Approaches to modelling the dynamical activity of brain function based on the electroencephalogram / D. T. J. Liley and F. Frascoli -- 8. Jaynes' maximum entropy principle, Riemannian metrics and generalised least action bound / R. K. Niven and B. Andresen -- 9. Complexity, post-genomic biology and gene expression programs / R. B. H. Williams and O. J.-H. Luo -- 10. Tutorials on agent-based modelling with NetLogo and network analysis with Pajek / M. J. Berryman and S. D. Angus.

  4. Understanding Student Cognition about Complex Earth System Processes Related to Climate Change

    Science.gov (United States)

    McNeal, K. S.; Libarkin, J.; Ledley, T. S.; Dutta, S.; Templeton, M. C.; Geroux, J.; Blakeney, G. A.

    2011-12-01

    The Earth's climate system includes complex behavior and interconnections with other Earth spheres that present challenges to student learning. To better understand these unique challenges, we have conducted experiments with high-school and introductory level college students to determine how information pertaining to the connections between the Earth's atmospheric system and the other Earth spheres (e.g., hydrosphere and cryosphere) are processed. Specifically, we include psychomotor tests (e.g., eye-tracking) and open-ended questionnaires in this research study, where participants were provided scientific images of the Earth (e.g., global precipitation and ocean and atmospheric currents), eye-tracked, and asked to provide causal or relational explanations about the viewed images. In addition, the students engaged in on-line modules (http://serc.carleton.edu/eslabs/climate/index.html) focused on Earth system science as training activities to address potential cognitive barriers. The developed modules included interactive media, hands-on lessons, links to outside resources, and formative assessment questions to promote a supportive and data-rich learning environment. Student eye movements were tracked during engagement with the materials to determine the role of perception and attention on understanding. Students also completed a conceptual questionnaire pre-post to determine if these on-line curriculum materials assisted in their development of connections between Earth's atmospheric system and the other Earth systems. The pre-post results of students' thinking about climate change concepts, as well as eye-tracking results, will be presented.

  5. A heuristic method for simulating open-data of arbitrary complexity that can be used to compare and evaluate machine learning methods.

    Science.gov (United States)

    Moore, Jason H; Shestov, Maksim; Schmitt, Peter; Olson, Randal S

    2018-01-01

    A central challenge of developing and evaluating artificial intelligence and machine learning methods for regression and classification is access to data that illuminates the strengths and weaknesses of different methods. Open data plays an important role in this process by making it easy for computational researchers to easily access real data for this purpose. Genomics has in some examples taken a leading role in the open data effort starting with DNA microarrays. While real data from experimental and observational studies is necessary for developing computational methods it is not sufficient. This is because it is not possible to know what the ground truth is in real data. This must be accompanied by simulated data where that balance between signal and noise is known and can be directly evaluated. Unfortunately, there is a lack of methods and software for simulating data with the kind of complexity found in real biological and biomedical systems. We present here the Heuristic Identification of Biological Architectures for simulating Complex Hierarchical Interactions (HIBACHI) method and prototype software for simulating complex biological and biomedical data. Further, we introduce new methods for developing simulation models that generate data that specifically allows discrimination between different machine learning methods.

  6. Active Learning of Markov Decision Processes for System Verification

    DEFF Research Database (Denmark)

    Chen, Yingke; Nielsen, Thomas Dyhre

    2012-01-01

    deterministic Markov decision processes from data by actively guiding the selection of input actions. The algorithm is empirically analyzed by learning system models of slot machines, and it is demonstrated that the proposed active learning procedure can significantly reduce the amount of data required...... demanding process, and this shortcoming has motivated the development of algorithms for automatically learning system models from observed system behaviors. Recently, algorithms have been proposed for learning Markov decision process representations of reactive systems based on alternating sequences...... of input/output observations. While alleviating the problem of manually constructing a system model, the collection/generation of observed system behaviors can also prove demanding. Consequently we seek to minimize the amount of data required. In this paper we propose an algorithm for learning...

  7. Design of an eLearning System for Accreditation of Non-formal Learning

    OpenAIRE

    Kovatcheva , Eugenia; Nikolov , Roumen

    2008-01-01

    This paper deals with issues related to the non-formal learning in vocational education, and the role of ICT for providing appropriate accreditation model in such education. The presented conclusions are based on the Leonardo da Vinci project LeoSPAN. The paper emphasises on the development of a model and a prototype of an adaptive eLearning system that ensures the pre-defined learner outcomes. One of the advantages of the eLearning system is the flexibility for people who upgrade and improve...

  8. Learning management system and e-learning tools: an experience of medical students' usage and expectations.

    Science.gov (United States)

    Back, David A; Behringer, Florian; Haberstroh, Nicole; Ehlers, Jan P; Sostmann, Kai; Peters, Harm

    2016-08-20

    To investigate medical students´ utilization of and problems with a learning management system and its e-learning tools as well as their expectations on future developments. A single-center online survey has been carried out to investigate medical students´ (n = 505) usage and perception concerning the learning management system Blackboard, and provided e-learning tools. Data were collected with a standardized questionnaire consisting of 70 items and analyzed by quantitative and qualitative methods. The participants valued lecture notes (73.7%) and Wikipedia (74%) as their most important online sources for knowledge acquisition. Missing integration of e-learning into teaching was seen as the major pitfall (58.7%). The learning management system was mostly used for study information (68.3%), preparation of exams (63.3%) and lessons (54.5%). Clarity (98.3%), teaching-related contexts (92.5%) and easy use of e-learning offers (92.5%) were rated highest. Interactivity was most important in free-text comments (n = 123). It is desired that contents of a learning management system support an efficient learning. Interactivity of tools and their conceptual integration into face-to-face teaching are important for students. The learning management system was especially important for organizational purposes and the provision of learning materials. Teachers should be aware that free online sources such as Wikipedia enjoy a high approval as source of knowledge acquisition. This study provides an empirical basis for medical schools and teachers to improve their offerings in the field of digital learning for their students.

  9. System Quality Characteristics for Selecting Mobile Learning Applications

    Directory of Open Access Journals (Sweden)

    Mohamed SARRAB

    2015-10-01

    Full Text Available The majority of M-learning (Mobile learning applications available today are developed for the formal learning and education environment. These applications are characterized by the improvement in the interaction between learners and instructors to provide high interaction and flexibility to the learning process. M-learning is gaining increased recognition and adoption by different organizations. With the high number of M-learning applications available today, making the right decision about which, application to choose can be quite challenging. To date there is no complete and well defined set of system characteristics for such M-learning applications. This paper presents system quality characteristics for selecting M-learning applications based on the result of a systematic review conducted in this domain.

  10. Successfully Carrying out Complex Learning-Tasks through Guiding Teams' Qualitative and Quantitative Reasoning

    Science.gov (United States)

    Slof, B.; Erkens, G.; Kirschner, P. A.; Janssen, J.; Jaspers, J. G. M.

    2012-01-01

    This study investigated whether and how scripting learners' use of representational tools in a computer supported collaborative learning (CSCL)-environment fostered their collaborative performance on a complex business-economics task. Scripting the problem-solving process sequenced and made its phase-related part-task demands explicit, namely…

  11. Panorama of Recommender Systems to Support Learning

    NARCIS (Netherlands)

    Drachsler, Hendrik; Verbert, Katrien; Santos, Olga C.; Manouselis, Nikos

    2015-01-01

    This chapter presents an analysis of recommender systems in TechnologyEnhanced Learning along their 15 years existence (2000-2014). All recommender systems considered for the review aim to support educational stakeholders by personalising the learning process. In this meta-review 82 recommender

  12. The Role of Celestial Compass Information in Cataglyphis Ants during Learning Walks and for Neuroplasticity in the Central Complex and Mushroom Bodies.

    Science.gov (United States)

    Grob, Robin; Fleischmann, Pauline N; Grübel, Kornelia; Wehner, Rüdiger; Rössler, Wolfgang

    2017-01-01

    Central place foragers are faced with the challenge to learn the position of their nest entrance in its surroundings, in order to find their way back home every time they go out to search for food. To acquire navigational information at the beginning of their foraging career, Cataglyphis noda performs learning walks during the transition from interior worker to forager. These small loops around the nest entrance are repeatedly interrupted by strikingly accurate back turns during which the ants stop and precisely gaze back to the nest entrance-presumably to learn the landmark panorama of the nest surroundings. However, as at this point the complete navigational toolkit is not yet available, the ants are in need of a reference system for the compass component of the path integrator to align their nest entrance-directed gazes. In order to find this directional reference system, we systematically manipulated the skylight information received by ants during learning walks in their natural habitat, as it has been previously suggested that the celestial compass, as part of the path integrator, might provide such a reference system. High-speed video analyses of distinct learning walk elements revealed that even exclusion from the skylight polarization pattern, UV-light spectrum and the position of the sun did not alter the accuracy of the look back to the nest behavior. We therefore conclude that C. noda uses a different reference system to initially align their gaze directions. However, a comparison of neuroanatomical changes in the central complex and the mushroom bodies before and after learning walks revealed that exposure to UV light together with a naturally changing polarization pattern was essential to induce neuroplasticity in these high-order sensory integration centers of the ant brain. This suggests a crucial role of celestial information, in particular a changing polarization pattern, in initially calibrating the celestial compass system.

  13. The Role of Celestial Compass Information in Cataglyphis Ants during Learning Walks and for Neuroplasticity in the Central Complex and Mushroom Bodies

    Directory of Open Access Journals (Sweden)

    Robin Grob

    2017-11-01

    Full Text Available Central place foragers are faced with the challenge to learn the position of their nest entrance in its surroundings, in order to find their way back home every time they go out to search for food. To acquire navigational information at the beginning of their foraging career, Cataglyphis noda performs learning walks during the transition from interior worker to forager. These small loops around the nest entrance are repeatedly interrupted by strikingly accurate back turns during which the ants stop and precisely gaze back to the nest entrance—presumably to learn the landmark panorama of the nest surroundings. However, as at this point the complete navigational toolkit is not yet available, the ants are in need of a reference system for the compass component of the path integrator to align their nest entrance-directed gazes. In order to find this directional reference system, we systematically manipulated the skylight information received by ants during learning walks in their natural habitat, as it has been previously suggested that the celestial compass, as part of the path integrator, might provide such a reference system. High-speed video analyses of distinct learning walk elements revealed that even exclusion from the skylight polarization pattern, UV-light spectrum and the position of the sun did not alter the accuracy of the look back to the nest behavior. We therefore conclude that C. noda uses a different reference system to initially align their gaze directions. However, a comparison of neuroanatomical changes in the central complex and the mushroom bodies before and after learning walks revealed that exposure to UV light together with a naturally changing polarization pattern was essential to induce neuroplasticity in these high-order sensory integration centers of the ant brain. This suggests a crucial role of celestial information, in particular a changing polarization pattern, in initially calibrating the celestial compass system.

  14. USE OF FACIAL EMOTION RECOGNITION IN E-LEARNING SYSTEMS

    Directory of Open Access Journals (Sweden)

    Uğur Ayvaz

    2017-09-01

    Full Text Available Since the personal computer usage and internet bandwidth are increasing, e-learning systems are also widely spreading. Although e-learning has some advantages in terms of information accessibility, time and place flexibility compared to the formal learning, it does not provide enough face-to-face interactivity between an educator and learners. In this study, we are proposing a hybrid information system, which is combining computer vision and machine learning technologies for visual and interactive e-learning systems. The proposed information system detects emotional states of the learners and gives feedback to an educator about their instant and weighted emotional states based on facial expressions. In this way, the educator will be aware of the general emotional state of the virtual classroom and the system will create a formal learning-like interactive environment. Herein, several classification algorithms were applied to learn instant emotional state and the best accuracy rates were obtained using kNN and SVM algorithms.

  15. The organization of an autonomous learning system

    Science.gov (United States)

    Kanerva, Pentti

    1988-01-01

    The organization of systems that learn from experience is examined, human beings and animals being prime examples of such systems. How is their information processing organized. They build an internal model of the world and base their actions on the model. The model is dynamic and predictive, and it includes the systems' own actions and their effects. In modeling such systems, a large pattern of features represents a moment of the system's experience. Some of the features are provided by the system's senses, some control the system's motors, and the rest have no immediate external significance. A sequence of such patterns then represents the system's experience over time. By storing such sequences appropriately in memory, the system builds a world model based on experience. In addition to the essential function of memory, fundamental roles are played by a sensory system that makes raw information about the world suitable for memory storage and by a motor system that affects the world. The relation of sensory and motor systems to the memory is discussed, together with how favorable actions can be learned and unfavorable actions can be avoided. Results in classical learning theory are explained in terms of the model, more advanced forms of learning are discussed, and the relevance of the model to the frame problem of robotics is examined.

  16. A PEDAGOGICAL CRITICAL REVIEW OF ONLINE LEARNING SYSTEM

    Directory of Open Access Journals (Sweden)

    Dwi SULISWORO

    2016-08-01

    Full Text Available E-learning which have various shapes such as blog, classroom learning which is facilitated the World Wide Web; a mix of online instruction and meeting the class known as additional models or hybrid; or the full online experience, where all assessment and instruction is done electronically. Object relationship of learning and constructivist educational philosophy and confirmed that online learning has the orientation which is basically a constructivist ideology, where the combination of some of the knowledge is an inquiry-oriented activities and authentic and also promote the progress of the construction of new knowledge. Description of the online learning system in theory and practice can be illustrated in a few examples that have been found in the research that has been done and found new discoveries obtained in the study, but not everything can be done because of several factors. Please note that the components in the online learning system can serve as a learning system which is very strong influence on learning in the class. The objective of this research is to a pedagogical critical review of online learning system in theory and practice that can be applied by teachers in the teaching process in the classroom. The results obtained in this study were teachers and students need extra effort to make online classes and virtual. Further research is needed on appropriate strategies in order to determine the next result is more useful. There some advices for any studies that discuss online learning system are done in certain areas, namely the use of electricity and other disciplines such as social and humanities.

  17. Managing Schools as Complex Adaptive Systems: A Strategic Perspective

    Science.gov (United States)

    Fidan, Tuncer; Balci, Ali

    2017-01-01

    This conceptual study examines the analogies between schools and complex adaptive systems and identifies strategies used to manage schools as complex adaptive systems. Complex adaptive systems approach, introduced by the complexity theory, requires school administrators to develop new skills and strategies to realize their agendas in an…

  18. Online reinforcement learning control for aerospace systems

    NARCIS (Netherlands)

    Zhou, Y.

    2018-01-01

    Reinforcement Learning (RL) methods are relatively new in the field of aerospace guidance, navigation, and control. This dissertation aims to exploit RL methods to improve the autonomy and online learning of aerospace systems with respect to the a priori unknown system and environment, dynamical

  19. LBS Mobile Learning System Based on Android Platform

    Directory of Open Access Journals (Sweden)

    Zhang Ya-Li

    2017-01-01

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

  20. Panorama of recommender systems to support learning

    OpenAIRE

    Drachsler, Hendrik; Verbert, Katrien; Santos, Olga; Manouselis, Nikos

    2015-01-01

    This chapter presents an analysis of recommender systems in Technology-Enhanced Learning along their 15 years existence (2000-2014). All recommender systems considered for the review aim to support educational stakeholders by personalising the learning process. In this meta-review 82 recommender systems from 35 different countries have been investigated and categorised according to a given classification framework. The reviewed systems have been classified into 7 clusters according to their c...

  1. Complexity in electronic negotiation support systems.

    Science.gov (United States)

    Griessmair, Michele; Strunk, Guido; Vetschera, Rudolf; Koeszegi, Sabine T

    2011-10-01

    It is generally acknowledged that the medium influences the way we communicate and negotiation research directs considerable attention to the impact of different electronic communication modes on the negotiation process and outcomes. Complexity theories offer models and methods that allow the investigation of how pattern and temporal sequences unfold over time in negotiation interactions. By focusing on the dynamic and interactive quality of negotiations as well as the information, choice, and uncertainty contained in the negotiation process, the complexity perspective addresses several issues of central interest in classical negotiation research. In the present study we compare the complexity of the negotiation communication process among synchronous and asynchronous negotiations (IM vs. e-mail) as well as an electronic negotiation support system including a decision support system (DSS). For this purpose, transcripts of 145 negotiations have been coded and analyzed with the Shannon entropy and the grammar complexity. Our results show that negotiating asynchronically via e-mail as well as including a DSS significantly reduces the complexity of the negotiation process. Furthermore, a reduction of the complexity increases the probability of reaching an agreement.

  2. Reinforcement and Systemic Machine Learning for Decision Making

    CERN Document Server

    Kulkarni, Parag

    2012-01-01

    Reinforcement and Systemic Machine Learning for Decision Making There are always difficulties in making machines that learn from experience. Complete information is not always available-or it becomes available in bits and pieces over a period of time. With respect to systemic learning, there is a need to understand the impact of decisions and actions on a system over that period of time. This book takes a holistic approach to addressing that need and presents a new paradigm-creating new learning applications and, ultimately, more intelligent machines. The first book of its kind in this new an

  3. Cultural impacts on e-learning systems' success

    OpenAIRE

    Aparicio, M.; Bação, F.; Oliveira, T.

    2016-01-01

    WOS:000383295100007 (Nº de Acesso Web of Science) E-learning systems are enablers in the learning process, strengthening their importance as part of the educational strategy. Understanding the determinants of e-learning success is crucial for defining instructional strategies. Several authors have studied e-learning implementation and adoption, and various studies have addressed e-learning success from different perspectives. However, none of these studies have verified whether students' c...

  4. Speak Clearly, If You Speak at All; Carve Every Word Before You Let It Fall: Problems of Ambiguous Terminology in eLearning System Development

    Directory of Open Access Journals (Sweden)

    Damian Gordon

    2014-06-01

    Full Text Available This paper addresses issues associated with the development of eLearning software systems. The development of software systems in general is a highly complex process, and a number of methodologies and models have been developed to help address some of these complexities. Generally the first stage in most development processes is the gathering of requirements which involves elicitation from end-users. This process is made more complex by problems associated with ambiguous terminology. Types of ambiguous terminology include homonymous, polysemous and inaccurate terms. This range of ambiguous terminology can cause significant misunderstandings in the requirements gathering process, which in turn can lead to software systems that do not meet the requirements of the end-users. This research seeks to explore some of the more common terms that can be ambiguously interpreted in the development of eLearning systems, and suggests software engineering approaches to help alleviate the potentially erroneous outcomes of these ambiguities.

  5. Harnessing the Power of Learning Management Systems: An E-Learning Approach for Professional Development.

    Science.gov (United States)

    White, Meagan; Shellenbarger, Teresa

    E-learning provides an alternative approach to traditional professional development activities. A learning management system may help nursing professional development practitioners deliver content more efficiently and effectively; however, careful consideration is needed during planning and implementation. This article provides essential information in the selection and use of a learning management system for professional development.

  6. Kaiser Permanente's performance improvement system, Part 4: Creating a learning organization.

    Science.gov (United States)

    Schilling, Lisa; Dearing, James W; Staley, Paul; Harvey, Patti; Fahey, Linda; Kuruppu, Francesca

    2011-12-01

    In 2006, recognizing variations in performance in quality, safety, service, and efficiency, Kaiser Permanente leaders initiated the development of a performance improvement (PI) system. Kaiser Permanente has implemented a strategy for creating the systemic capacity for continuous improvement that characterizes a learning organization. Six "building blocks" were identified to enable Kaiser Permanente to make the transition to becoming a learning organization: real-time sharing of meaningful performance data; formal training in problem-solving methodology; workforce engagement and informal knowledge sharing; leadership structures, beliefs, and behaviors; internal and external benchmarking; and technical knowledge sharing. Putting each building block into place required multiple complex strategies combining top-down and bottom-up approaches. Although the strategies have largely been successful, challenges remain. The demand for real-time meaningful performance data can conflict with prioritized changes to health information systems. It is an ongoing challenge to teach PI, change management, innovation, and project management to all managers and staff without consuming too much training time. Challenges with workforce engagement include low initial use of tools intended to disseminate information through virtual social networking. Uptake of knowledge-sharing technologies is still primarily by innovators and early adopters. Leaders adopt new behaviors at varying speeds and have a range of abilities to foster an environment that is psychologically safe and stimulates inquiry. A learning organization has the capability to improve, and it develops structures and processes that facilitate the acquisition and sharing of knowledge.

  7. Learning in Artificial Neural Systems

    Science.gov (United States)

    Matheus, Christopher J.; Hohensee, William E.

    1987-01-01

    This paper presents an overview and analysis of learning in Artificial Neural Systems (ANS's). It begins with a general introduction to neural networks and connectionist approaches to information processing. The basis for learning in ANS's is then described, and compared with classical Machine learning. While similar in some ways, ANS learning deviates from tradition in its dependence on the modification of individual weights to bring about changes in a knowledge representation distributed across connections in a network. This unique form of learning is analyzed from two aspects: the selection of an appropriate network architecture for representing the problem, and the choice of a suitable learning rule capable of reproducing the desired function within the given network. The various network architectures are classified, and then identified with explicit restrictions on the types of functions they are capable of representing. The learning rules, i.e., algorithms that specify how the network weights are modified, are similarly taxonomized, and where possible, the limitations inherent to specific classes of rules are outlined.

  8. MITT writer and MITT writer advanced development: Developing authoring and training systems for complex technical domains

    Science.gov (United States)

    Wiederholt, Bradley J.; Browning, Elica J.; Norton, Jeffrey E.; Johnson, William B.

    1991-01-01

    MITT Writer is a software system for developing computer based training for complex technical domains. A training system produced by MITT Writer allows a student to learn and practice troubleshooting and diagnostic skills. The MITT (Microcomputer Intelligence for Technical Training) architecture is a reasonable approach to simulation based diagnostic training. MITT delivers training on available computing equipment, delivers challenging training and simulation scenarios, and has economical development and maintenance costs. A 15 month effort was undertaken in which the MITT Writer system was developed. A workshop was also conducted to train instructors in how to use MITT Writer. Earlier versions were used to develop an Intelligent Tutoring System for troubleshooting the Minuteman Missile Message Processing System.

  9. Knowledge acquisition and interface design for learning on demand systems

    Science.gov (United States)

    Nelson, Wayne A.

    1993-01-01

    The rapid changes in our world precipitated by technology have created new problems and new challenges for education and training. A knowledge 'explosion' is occurring as our society moves toward a service oriented economy that relies on information as the major resource. Complex computer systems are beginning to dominate the workplace, causing alarming growth and change in many fields. The rapidly changing nature of the workplace, especially in fields related to information technology, requires that our knowledge be updated constantly. This characteristic of modern society poses seemingly unsolvable instructional problems involving coverage and obsolescence. The sheer amount of information to be learned is rapidly increasing, while at the same time some information becomes obsolete in light of new information. Education, therefore, must become a lifelong process that features learning of new material and skills as needed in relation to the job to be done. Because of the problems cited above, the current model of learning in advance may no longer be feasible in our high-technology world. In many cases, learning in advance is impossible because there are simply too many things to learn. In addition, learning in advance can be time consuming, and often results in decontextualized knowledge that does not readily transfer to the work environment. The large and growing discrepancy between the amount of potentially relevant knowledge available and the amount a person can know and remember makes learning on demand an important alternative to current instructional practices. Learning on demand takes place whenever an individual must learn something new in order to perform a task or make a decision. Learning on demand is a promising approach for addressing the problems of coverage and obsolescence because learning is contextualized and integrated into the task environment rather than being relegated to a separate phase that precedes work. Learning on demand allows learners

  10. Advances in complex societal, environmental and engineered systems

    CERN Document Server

    Essaaidi, Mohammad

    2017-01-01

    This book addresses recent technological progress that has led to an increased complexity in many natural and artificial systems. The resulting complexity research due to the emergence of new properties and spatio-temporal interactions among a large number of system elements - and between the system and its environment - is the primary focus of this text. This volume is divided into three parts: Part one focuses on societal and ecological systems, Part two deals with approaches for understanding, modeling, predicting and mastering socio-technical systems, and Part three includes real-life examples. Each chapter has its own special features; it is a self-contained contribution of distinguished experts working on different fields of science and technology relevant to the study of complex systems. Advances in Complex Systems of Contemporary Reality: Societal, Environmental and Engineered Systems will provide postgraduate students, researchers and managers with qualitative and quantitative methods for handling th...

  11. Promoting system-level learning from project-level lessons

    Energy Technology Data Exchange (ETDEWEB)

    Jong, Amos A. de, E-mail: amosdejong@gmail.com [Innovation Management, Utrecht (Netherlands); Runhaar, Hens A.C., E-mail: h.a.c.runhaar@uu.nl [Section of Environmental Governance, Utrecht University, Utrecht (Netherlands); Runhaar, Piety R., E-mail: piety.runhaar@wur.nl [Organisational Psychology and Human Resource Development, University of Twente, Enschede (Netherlands); Kolhoff, Arend J., E-mail: Akolhoff@eia.nl [The Netherlands Commission for Environmental Assessment, Utrecht (Netherlands); Driessen, Peter P.J., E-mail: p.driessen@geo.uu.nl [Department of Innovation and Environment Sciences, Utrecht University, Utrecht (Netherlands)

    2012-02-15

    A growing number of low and middle income nations (LMCs) have adopted some sort of system for environmental impact assessment (EIA). However, generally many of these EIA systems are characterised by a low performance in terms of timely information dissemination, monitoring and enforcement after licencing. Donor actors (such as the World Bank) have attempted to contribute to a higher performance of EIA systems in LMCs by intervening at two levels: the project level (e.g. by providing scoping advice or EIS quality review) and the system level (e.g. by advising on EIA legislation or by capacity building). The aims of these interventions are environmental protection in concrete cases and enforcing the institutionalisation of environmental protection, respectively. Learning by actors involved is an important condition for realising these aims. A relatively underexplored form of learning concerns learning at EIA system-level via project level donor interventions. This 'indirect' learning potentially results in system changes that better fit the specific context(s) and hence contribute to higher performances. Our exploratory research in Ghana and the Maldives shows that thus far, 'indirect' learning only occurs incidentally and that donors play a modest role in promoting it. Barriers to indirect learning are related to the institutional context rather than to individual characteristics. Moreover, 'indirect' learning seems to flourish best in large projects where donors achieved a position of influence that they can use to evoke reflection upon system malfunctions. In order to enhance learning at all levels donors should thereby present the outcomes of the intervention elaborately (i.e. discuss the outcomes with a large audience), include practical suggestions about post-EIS activities such as monitoring procedures and enforcement options and stimulate the use of their advisory reports to generate organisational memory and ensure a better

  12. Promoting system-level learning from project-level lessons

    International Nuclear Information System (INIS)

    Jong, Amos A. de; Runhaar, Hens A.C.; Runhaar, Piety R.; Kolhoff, Arend J.; Driessen, Peter P.J.

    2012-01-01

    A growing number of low and middle income nations (LMCs) have adopted some sort of system for environmental impact assessment (EIA). However, generally many of these EIA systems are characterised by a low performance in terms of timely information dissemination, monitoring and enforcement after licencing. Donor actors (such as the World Bank) have attempted to contribute to a higher performance of EIA systems in LMCs by intervening at two levels: the project level (e.g. by providing scoping advice or EIS quality review) and the system level (e.g. by advising on EIA legislation or by capacity building). The aims of these interventions are environmental protection in concrete cases and enforcing the institutionalisation of environmental protection, respectively. Learning by actors involved is an important condition for realising these aims. A relatively underexplored form of learning concerns learning at EIA system-level via project level donor interventions. This ‘indirect’ learning potentially results in system changes that better fit the specific context(s) and hence contribute to higher performances. Our exploratory research in Ghana and the Maldives shows that thus far, ‘indirect’ learning only occurs incidentally and that donors play a modest role in promoting it. Barriers to indirect learning are related to the institutional context rather than to individual characteristics. Moreover, ‘indirect’ learning seems to flourish best in large projects where donors achieved a position of influence that they can use to evoke reflection upon system malfunctions. In order to enhance learning at all levels donors should thereby present the outcomes of the intervention elaborately (i.e. discuss the outcomes with a large audience), include practical suggestions about post-EIS activities such as monitoring procedures and enforcement options and stimulate the use of their advisory reports to generate organisational memory and ensure a better information

  13. Understanding complex urban systems multidisciplinary approaches to modeling

    CERN Document Server

    Gurr, Jens; Schmidt, J

    2014-01-01

    Understanding Complex Urban Systems takes as its point of departure the insight that the challenges of global urbanization and the complexity of urban systems cannot be understood – let alone ‘managed’ – by sectoral and disciplinary approaches alone. But while there has recently been significant progress in broadening and refining the methodologies for the quantitative modeling of complex urban systems, in deepening the theoretical understanding of cities as complex systems, or in illuminating the implications for urban planning, there is still a lack of well-founded conceptual thinking on the methodological foundations and the strategies of modeling urban complexity across the disciplines. Bringing together experts from the fields of urban and spatial planning, ecology, urban geography, real estate analysis, organizational cybernetics, stochastic optimization, and literary studies, as well as specialists in various systems approaches and in transdisciplinary methodologies of urban analysis, the volum...

  14. Observation-Driven Configuration of Complex Software Systems

    Science.gov (United States)

    Sage, Aled

    2010-06-01

    The ever-increasing complexity of software systems makes them hard to comprehend, predict and tune due to emergent properties and non-deterministic behaviour. Complexity arises from the size of software systems and the wide variety of possible operating environments: the increasing choice of platforms and communication policies leads to ever more complex performance characteristics. In addition, software systems exhibit different behaviour under different workloads. Many software systems are designed to be configurable so that policies can be chosen to meet the needs of various stakeholders. For complex software systems it can be difficult to accurately predict the effects of a change and to know which configuration is most appropriate. This thesis demonstrates that it is useful to run automated experiments that measure a selection of system configurations. Experiments can find configurations that meet the stakeholders' needs, find interesting behavioural characteristics, and help produce predictive models of the system's behaviour. The design and use of ACT (Automated Configuration Tool) for running such experiments is described, in combination a number of search strategies for deciding on the configurations to measure. Design Of Experiments (DOE) is discussed, with emphasis on Taguchi Methods. These statistical methods have been used extensively in manufacturing, but have not previously been used for configuring software systems. The novel contribution here is an industrial case study, applying the combination of ACT and Taguchi Methods to DC-Directory, a product from Data Connection Ltd (DCL). The case study investigated the applicability of Taguchi Methods for configuring complex software systems. Taguchi Methods were found to be useful for modelling and configuring DC- Directory, making them a valuable addition to the techniques available to system administrators and developers.

  15. Computer-aided auscultation learning system for nursing technique instruction.

    Science.gov (United States)

    Hou, Chun-Ju; Chen, Yen-Ting; Hu, Ling-Chen; Chuang, Chih-Chieh; Chiu, Yu-Hsien; Tsai, Ming-Shih

    2008-01-01

    Pulmonary auscultation is a physical assessment skill learned by nursing students for examining the respiratory system. Generally, a sound simulator equipped mannequin is used to group teach auscultation techniques via classroom demonstration. However, nursing students cannot readily duplicate this learning environment for self-study. The advancement of electronic and digital signal processing technologies facilitates simulating this learning environment. This study aims to develop a computer-aided auscultation learning system for assisting teachers and nursing students in auscultation teaching and learning. This system provides teachers with signal recording and processing of lung sounds and immediate playback of lung sounds for students. A graphical user interface allows teachers to control the measuring device, draw lung sound waveforms, highlight lung sound segments of interest, and include descriptive text. Effects on learning lung sound auscultation were evaluated for verifying the feasibility of the system. Fifteen nursing students voluntarily participated in the repeated experiment. The results of a paired t test showed that auscultative abilities of the students were significantly improved by using the computer-aided auscultation learning system.

  16. Design tools for complex dynamic security systems.

    Energy Technology Data Exchange (ETDEWEB)

    Byrne, Raymond Harry; Rigdon, James Brian; Rohrer, Brandon Robinson; Laguna, Glenn A.; Robinett, Rush D. III (.; ); Groom, Kenneth Neal; Wilson, David Gerald; Bickerstaff, Robert J.; Harrington, John J.

    2007-01-01

    The development of tools for complex dynamic security systems is not a straight forward engineering task but, rather, a scientific task where discovery of new scientific principles and math is necessary. For years, scientists have observed complex behavior but have had difficulty understanding it. Prominent examples include: insect colony organization, the stock market, molecular interactions, fractals, and emergent behavior. Engineering such systems will be an even greater challenge. This report explores four tools for engineered complex dynamic security systems: Partially Observable Markov Decision Process, Percolation Theory, Graph Theory, and Exergy/Entropy Theory. Additionally, enabling hardware technology for next generation security systems are described: a 100 node wireless sensor network, unmanned ground vehicle and unmanned aerial vehicle.

  17. Towards a lessons learned system for critical software

    International Nuclear Information System (INIS)

    Andrade, J.; Ares, J.; Garcia, R.; Pazos, J.; Rodriguez, S.; Rodriguez-Paton, A.; Silva, A.

    2007-01-01

    Failure can be a major driver for the advance of any engineering discipline and Software Engineering is no exception. But failures are useful only if lessons are learned from them. In this article we aim to make a strong defence of, and set the requirements for, lessons learned systems for safety-critical software. We also present a prototype lessons learned system that includes many of the features discussed here. We emphasize that, apart from individual organizations, lessons learned systems should target industrial sectors and even the Software Engineering community. We would like to encourage the Software Engineering community to use this kind of systems as another tool in the toolbox, which complements or enhances other approaches like, for example, standards and checklists

  18. Towards a lessons learned system for critical software

    Energy Technology Data Exchange (ETDEWEB)

    Andrade, J. [University of A Coruna. Campus de Elvina, s/n. 15071, A Coruna (Spain)]. E-mail: jag@udc.es; Ares, J. [University of A Coruna. Campus de Elvina, s/n. 15071, A Coruna (Spain)]. E-mail: juanar@udc.es; Garcia, R. [University of A Coruna. Campus de Elvina, s/n. 15071, A Coruna (Spain)]. E-mail: rafael@udc.es; Pazos, J. [Technical University of Madrid. Campus de Montegancedo, s/n. 28660, Boadilla del Monte, Madrid (Spain)]. E-mail: jpazos@fi.upm.es; Rodriguez, S. [University of A Coruna. Campus de Elvina, s/n. 15071, A Coruna (Spain)]. E-mail: santi@udc.es; Rodriguez-Paton, A. [Technical University of Madrid. Campus de Montegancedo, s/n. 28660, Boadilla del Monte, Madrid (Spain)]. E-mail: arpaton@fi.upm.es; Silva, A. [Technical University of Madrid. Campus de Montegancedo, s/n. 28660, Boadilla del Monte, Madrid (Spain)]. E-mail: asilva@fi.upm.es

    2007-07-15

    Failure can be a major driver for the advance of any engineering discipline and Software Engineering is no exception. But failures are useful only if lessons are learned from them. In this article we aim to make a strong defence of, and set the requirements for, lessons learned systems for safety-critical software. We also present a prototype lessons learned system that includes many of the features discussed here. We emphasize that, apart from individual organizations, lessons learned systems should target industrial sectors and even the Software Engineering community. We would like to encourage the Software Engineering community to use this kind of systems as another tool in the toolbox, which complements or enhances other approaches like, for example, standards and checklists.

  19. Methodology for Measuring the Complexity of Enterprise Information Systems

    Directory of Open Access Journals (Sweden)

    Ilja Holub

    2016-07-01

    Full Text Available The complexity of enterprise information systems is currently a challenge faced not only by IT professionals and project managers, but also by the users of such systems. Current methodologies and frameworks used to design and implement information systems do not specifically deal with the issue of their complexity and, apart from few exceptions, do not at all attempt to simplify the complexity. This article presents the author's own methodology for managing complexity, which can be used to complement any other methodology and which helps limit the growth of complexity. It introduces its own definition and metric of complexity, which it defines as the sum of entities of the individual UML models of the given system, which are selected according to the MMDIS methodology so as to consistently describe all relevant content dimensions of the system. The main objective is to propose a methodology to manage information system complexity and to verify it in practice on a real-life SAP implementation project.

  20. Risk Modeling of Interdependent Complex Systems of Systems: Theory and Practice.

    Science.gov (United States)

    Haimes, Yacov Y

    2018-01-01

    The emergence of the complexity characterizing our systems of systems (SoS) requires a reevaluation of the way we model, assess, manage, communicate, and analyze the risk thereto. Current models for risk analysis of emergent complex SoS are insufficient because too often they rely on the same risk functions and models used for single systems. These models commonly fail to incorporate the complexity derived from the networks of interdependencies and interconnectedness (I-I) characterizing SoS. There is a need to reevaluate currently practiced risk analysis to respond to this reality by examining, and thus comprehending, what makes emergent SoS complex. The key to evaluating the risk to SoS lies in understanding the genesis of characterizing I-I of systems manifested through shared states and other essential entities within and among the systems that constitute SoS. The term "essential entities" includes shared decisions, resources, functions, policies, decisionmakers, stakeholders, organizational setups, and others. This undertaking can be accomplished by building on state-space theory, which is fundamental to systems engineering and process control. This article presents a theoretical and analytical framework for modeling the risk to SoS with two case studies performed with the MITRE Corporation and demonstrates the pivotal contributions made by shared states and other essential entities to modeling and analysis of the risk to complex SoS. A third case study highlights the multifarious representations of SoS, which require harmonizing the risk analysis process currently applied to single systems when applied to complex SoS. © 2017 Society for Risk Analysis.

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

    Directory of Open Access Journals (Sweden)

    Diego Martín

    2018-01-01

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

  2. 3D Game-Based Learning System for Improving Learning Achievement in Software Engineering Curriculum

    Science.gov (United States)

    Su,Chung-Ho; Cheng, Ching-Hsue

    2013-01-01

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

  3. Learning to Support Learning Together: An Experience with the Soft Systems Methodology

    Science.gov (United States)

    Sanchez, Adolfo; Mejia, Andres

    2008-01-01

    An action research approach called soft systems methodology (SSM) was used to foster organisational learning in a school regarding the role of the learning support department within the school and its relation with the normal teaching-learning activities. From an initial situation of lack of coordination as well as mutual misunderstanding and…

  4. The sleeping brain as a complex system.

    Science.gov (United States)

    Olbrich, Eckehard; Achermann, Peter; Wennekers, Thomas

    2011-10-13

    'Complexity science' is a rapidly developing research direction with applications in a multitude of fields that study complex systems consisting of a number of nonlinear elements with interesting dynamics and mutual interactions. This Theme Issue 'The complexity of sleep' aims at fostering the application of complexity science to sleep research, because the brain in its different sleep stages adopts different global states that express distinct activity patterns in large and complex networks of neural circuits. This introduction discusses the contributions collected in the present Theme Issue. We highlight the potential and challenges of a complex systems approach to develop an understanding of the brain in general and the sleeping brain in particular. Basically, we focus on two topics: the complex networks approach to understand the changes in the functional connectivity of the brain during sleep, and the complex dynamics of sleep, including sleep regulation. We hope that this Theme Issue will stimulate and intensify the interdisciplinary communication to advance our understanding of the complex dynamics of the brain that underlies sleep and consciousness.

  5. Leadership Perspectives on Operationalizing the Learning Health Care System in an Integrated Delivery System.

    Science.gov (United States)

    Psek, Wayne; Davis, F Daniel; Gerrity, Gloria; Stametz, Rebecca; Bailey-Davis, Lisa; Henninger, Debra; Sellers, Dorothy; Darer, Jonathan

    2016-01-01

    Healthcare leaders need operational strategies that support organizational learning for continued improvement and value generation. The learning health system (LHS) model may provide leaders with such strategies; however, little is known about leaders' perspectives on the value and application of system-wide operationalization of the LHS model. The objective of this project was to solicit and analyze senior health system leaders' perspectives on the LHS and learning activities in an integrated delivery system. A series of interviews were conducted with 41 system leaders from a broad range of clinical and administrative areas across an integrated delivery system. Leaders' responses were categorized into themes. Ten major themes emerged from our conversations with leaders. While leaders generally expressed support for the concept of the LHS and enhanced system-wide learning, their concerns and suggestions for operationalization where strongly aligned with their functional area and strategic goals. Our findings suggests that leaders tend to adopt a very pragmatic approach to learning. Leaders expressed a dichotomy between the operational imperative to execute operational objectives efficiently and the need for rigorous evaluation. Alignment of learning activities with system-wide strategic and operational priorities is important to gain leadership support and resources. Practical approaches to addressing opportunities and challenges identified in the themes are discussed. Continuous learning is an ongoing, multi-disciplinary function of a health care delivery system. Findings from this and other research may be used to inform and prioritize system-wide learning objectives and strategies which support reliable, high value care delivery.

  6. Status Checking System of Home Appliances using machine learning

    Directory of Open Access Journals (Sweden)

    Yoon Chi-Yurl

    2017-01-01

    Full Text Available This paper describes status checking system of home appliances based on machine learning, which can be applied to existing household appliances without networking function. Designed status checking system consists of sensor modules, a wireless communication module, cloud server, android application and a machine learning algorithm. The developed system applied to washing machine analyses and judges the four-kinds of appliance’s status such as staying, washing, rinsing and spin-drying. The measurements of sensor and transmission of sensing data are operated on an Arduino board and the data are transmitted to cloud server in real time. The collected data are parsed by an Android application and injected into the machine learning algorithm for learning the status of the appliances. The machine learning algorithm compares the stored learning data with collected real-time data from the appliances. Our results are expected to contribute as a base technology to design an automatic control system based on machine learning technology for household appliances in real-time.

  7. PERSO: Towards an Adaptive e-Learning System

    Science.gov (United States)

    Chorfi, Henda; Jemni, Mohamed

    2004-01-01

    In today's information technology society, members are increasingly required to be up to date on new technologies, particularly for computers, regardless of their background social situation. In this context, our aim is to design and develop an adaptive hypermedia e-learning system, called PERSO (PERSOnalizing e-learning system), where learners…

  8. Divulging Personal Information within Learning Analytics Systems

    Science.gov (United States)

    Ifenthaler, Dirk; Schumacher, Clara

    2015-01-01

    The purpose of this study was to investigate if students are prepared to release any personal data in order to inform learning analytics systems. Besides the well-documented benefits of learning analytics, serious concerns and challenges are associated with the application of these data driven systems. Most notably, empirical evidence regarding…

  9. Third International Conference on Complex Systems

    CERN Document Server

    Minai, Ali A; Unifying Themes in Complex Systems

    2006-01-01

    In recent years, scientists have applied the principles of complex systems science to increasingly diverse fields. The results have been nothing short of remarkable: their novel approaches have provided answers to long-standing questions in biology, ecology, physics, engineering, computer science, economics, psychology and sociology. The Third International Conference on Complex Systems attracted over 400 researchers from around the world. The conference aimed to encourage cross-fertilization between the many disciplines represented and to deepen our understanding of the properties common to all complex systems. This volume contains selected transcripts from presentations given at the conference. Speakers include: Chris Adami, Kenneth Arrow, Michel Baranger, Dan Braha, Timothy Buchman, Michael Caramanis, Kathleen Carley, Greg Chaitin, David Clark, Jack Cohen, Jim Collins, George Cowan, Clay Easterly, Steven Eppinger, Irving Epstein, Dan Frey, Ary Goldberger, Helen Harte, Leroy Hood, Don Ingber, Atlee Jackson,...

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

    Directory of Open Access Journals (Sweden)

    A. A. Salama

    2015-03-01

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

  11. Cross-Disciplinary Collaboration and Learning

    Directory of Open Access Journals (Sweden)

    Deana D. Pennington

    2008-12-01

    Full Text Available Complex environmental problem solving depends on cross-disciplinary collaboration among scientists. Collaborative research must be preceded by an exploratory phase of collective thinking that creates shared conceptual frameworks. Collective thinking, in a cross-disciplinary setting, depends on the facility with which collaborators are able to learn and understand each others' perspectives. This paper applies three perspectives on learning to the problem of enabling cross-disciplinary collaboration: Maslow's hierarchy of needs, constructivism, and organizational learning. Application of learning frameworks to collaboration provides insights regarding receptive environments for collaboration, and processes that facilitate cross-disciplinary interactions. These environments and interactions need time to develop and require a long phase of idea generation preceding any focused research effort. The findings highlight that collaboration is itself a complex system of people, scientific theory, and tools that must be intentionally managed. Effective management of the system requires leaders who are facilitators and are capable of orchestrating effective environments and interactions.

  12. A Memristor-Based Hyperchaotic ComplexSystem and Its Adaptive Complex Generalized Synchronization

    Directory of Open Access Journals (Sweden)

    Shibing Wang

    2016-02-01

    Full Text Available This paper introduces a new memristor-based hyperchaotic complexsystem (MHCLS and investigates its adaptive complex generalized synchronization (ACGS. Firstly, the complex system is constructed based on a memristor-based hyperchaotic real Lü system, and its properties are analyzed theoretically. Secondly, its dynamical behaviors, including hyperchaos, chaos, transient phenomena, as well as periodic behaviors, are explored numerically by means of bifurcation diagrams, Lyapunov exponents, phase portraits, and time history diagrams. Thirdly, an adaptive controller and a parameter estimator are proposed to realize complex generalized synchronization and parameter identification of two identical MHCLSs with unknown parameters based on Lyapunov stability theory. Finally, the numerical simulation results of ACGS and its applications to secure communication are presented to verify the feasibility and effectiveness of the proposed method.

  13. The Role of Corticostriatal Systems in Speech Category Learning.

    Science.gov (United States)

    Yi, Han-Gyol; Maddox, W Todd; Mumford, Jeanette A; Chandrasekaran, Bharath

    2016-04-01

    One of the most difficult category learning problems for humans is learning nonnative speech categories. While feedback-based category training can enhance speech learning, the mechanisms underlying these benefits are unclear. In this functional magnetic resonance imaging study, we investigated neural and computational mechanisms underlying feedback-dependent speech category learning in adults. Positive feedback activated a large corticostriatal network including the dorsolateral prefrontal cortex, inferior parietal lobule, middle temporal gyrus, caudate, putamen, and the ventral striatum. Successful learning was contingent upon the activity of domain-general category learning systems: the fast-learning reflective system, involving the dorsolateral prefrontal cortex that develops and tests explicit rules based on the feedback content, and the slow-learning reflexive system, involving the putamen in which the stimuli are implicitly associated with category responses based on the reward value in feedback. Computational modeling of response strategies revealed significant use of reflective strategies early in training and greater use of reflexive strategies later in training. Reflexive strategy use was associated with increased activation in the putamen. Our results demonstrate a critical role for the reflexive corticostriatal learning system as a function of response strategy and proficiency during speech category learning. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  14. Environmental influences on neural systems of relational complexity

    Directory of Open Access Journals (Sweden)

    Layne eKalbfleisch

    2013-09-01

    Full Text Available Constructivist learning theory contends that we construct knowledge by experience and that environmental context influences learning. To explore this principle, we examined the cognitive process relational complexity (RC, defined as the number of visual dimensions considered during problem solving on a matrix reasoning task and a well-documented measure of mature reasoning capacity. We sought to determine how the visual environment influences RC by examining the influence of color and visual contrast on RC in a neuroimaging task. To specify the contributions of sensory demand and relational integration to reasoning, our participants performed a non-verbal matrix task comprised of color, no-color line, or black-white visual contrast conditions parametrically varied by complexity (relations 0, 1, 2. The use of matrix reasoning is ecologically valid for its psychometric relevance and for its potential to link the processing of psychophysically specific visual properties with various levels of relational complexity during reasoning. The role of these elements is important because matrix tests assess intellectual aptitude based on these seemingly context-less exercises. This experiment is a first step toward examining the psychophysical underpinnings of performance on these types of problems. The importance of this is increased in light of recent evidence that intelligence can be linked to visual discrimination. We submit three main findings. First, color and black-white visual contrast add demand at a basic sensory level, but contributions from color and from black-white visual contrast are dissociable in cortex such that color engages a reasoning heuristic and black-white visual contrast engages a sensory heuristic. Second, color supports contextual sense-making by boosting salience resulting in faster problem solving. Lastly, when visual complexity reaches 2-relations, color and visual contrast relinquish salience to other dimensions of problem

  15. Embedded interruptions and task complexity influence schema-related cognitive load progression in an abstract learning task.

    Science.gov (United States)

    Wirzberger, Maria; Esmaeili Bijarsari, Shirin; Rey, Günter Daniel

    2017-09-01

    Cognitive processes related to schema acquisition comprise an essential source of demands in learning situations. Since the related amount of cognitive load is supposed to change over time, plausible temporal models of load progression based on different theoretical backgrounds are inspected in this study. A total of 116 student participants completed a basal symbol sequence learning task, which provided insights into underlying cognitive dynamics. Two levels of task complexity were determined by the amount of elements within the symbol sequence. In addition, interruptions due to an embedded secondary task occurred at five predefined stages over the task. Within the resulting 2x5-factorial mixed between-within design, the continuous monitoring of efficiency in learning performance enabled assumptions on relevant resource investment. From the obtained results, a nonlinear change of learning efficiency over time seems most plausible in terms of cognitive load progression. Moreover, different effects of the induced interruptions show up in conditions of task complexity, which indicate the activation of distinct cognitive mechanisms related to structural aspects of the task. Findings are discussed in the light of evidence from research on memory and information processing. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Evaluating a learning management system for blended learning in Greek higher education.

    Science.gov (United States)

    Kabassi, Katerina; Dragonas, Ioannis; Ntouzevits, Alexandra; Pomonis, Tzanetos; Papastathopoulos, Giorgos; Vozaitis, Yiannis

    2016-01-01

    This paper focuses on the usage of a learning management system in an educational institution for higher education in Greece. More specifically, the paper examines the literature on the use of different learning management systems for blended learning in higher education in Greek Universities and Technological Educational Institutions and reviews the advantages and disadvantages. Moreover, the paper describes the usage of the Open eClass platform in a Technological Educational Institution, TEI of Ionian Islands, and the effort to improve the educational material by organizing it and adding video-lectures. The platform has been evaluated by the students of the TEI of Ionian Islands based on six dimensions: namely student, teacher, course, technology, system design, and environmental dimension. The results of this evaluation revealed that Open eClass has been successfully used for blended learning in the TEI of Ionian Islands. Despite the instructors' initial worries about students' lack of participation in their courses if their educational material was made available online and especially in video lectures; blended learning did not reduce physical presence of the students in the classroom. Instead it was only used as a supplementary tool that helps students to study further, watch missed lectures, etc.

  17. Citizen Data Science for Social Good in Complex Systems: Case Studies and Vignettes from Recent Projects

    OpenAIRE

    Banerjee, Soumya

    2017-01-01

    The confluence of massive amounts of openly available data, sophisticated machine learning algorithms and an enlightened citizenry willing to engage in data science presents novel opportunities for crowd sourced data science for social good. In this submission, I present vignettes of data science projects that I have been involved in and which have impact in various spheres of life and on social good. Complex systems are all around us: from social networks to transportation sys...

  18. Discrimination of Rock Fracture and Blast Events Based on Signal Complexity and Machine Learning

    Directory of Open Access Journals (Sweden)

    Zilong Zhou

    2018-01-01

    Full Text Available The automatic discrimination of rock fracture and blast events is complex and challenging due to the similar waveform characteristics. To solve this problem, a new method based on the signal complexity analysis and machine learning has been proposed in this paper. First, the permutation entropy values of signals at different scale factors are calculated to reflect complexity of signals and constructed into a feature vector set. Secondly, based on the feature vector set, back-propagation neural network (BPNN as a means of machine learning is applied to establish a discriminator for rock fracture and blast events. Then to evaluate the classification performances of the new method, the classifying accuracies of support vector machine (SVM, naive Bayes classifier, and the new method are compared, and the receiver operating characteristic (ROC curves are also analyzed. The results show the new method obtains the best classification performances. In addition, the influence of different scale factor q and number of training samples n on discrimination results is discussed. It is found that the classifying accuracy of the new method reaches the highest value when q = 8–15 or 8–20 and n=140.

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

    Directory of Open Access Journals (Sweden)

    Amirkhanpour, Monaliz

    2011-01-01

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

  20. Multidimensional Learner Model In Intelligent Learning System

    Science.gov (United States)

    Deliyska, B.; Rozeva, A.

    2009-11-01

    The learner model in an intelligent learning system (ILS) has to ensure the personalization (individualization) and the adaptability of e-learning in an online learner-centered environment. ILS is a distributed e-learning system whose modules can be independent and located in different nodes (servers) on the Web. This kind of e-learning is achieved through the resources of the Semantic Web and is designed and developed around a course, group of courses or specialty. An essential part of ILS is learner model database which contains structured data about learner profile and temporal status in the learning process of one or more courses. In the paper a learner model position in ILS is considered and a relational database is designed from learner's domain ontology. Multidimensional modeling agent for the source database is designed and resultant learner data cube is presented. Agent's modules are proposed with corresponding algorithms and procedures. Multidimensional (OLAP) analysis guidelines on the resultant learner module for designing dynamic learning strategy have been highlighted.

  1. Self-Disclosure and Adults with Learning Disabilities: Practical Ideas about a Complex Process

    Science.gov (United States)

    Gerber, Paul J.; Price, Lynda A.

    2008-01-01

    Self-disclosure for adults with learning disabilities is very complex after the beyond-school years. The issues of invisibility, risk/benefit, and the multiple contexts of adult functioning create many challenges in the process of disclosure. Moreover, self-disclosure, one element of the larger issue of self-determination, is viewed as an entry…

  2. Research on cultivating medical students' self-learning ability using teaching system integrated with learning analysis technology.

    Science.gov (United States)

    Luo, Hong; Wu, Cheng; He, Qian; Wang, Shi-Yong; Ma, Xiu-Qiang; Wang, Ri; Li, Bing; He, Jia

    2015-01-01

    Along with the advancement of information technology and the era of big data education, using learning process data to provide strategic decision-making in cultivating and improving medical students' self-learning ability has become a trend in educational research. Educator Abuwen Toffler said once, the illiterates in the future may not be the people not able to read and write, but not capable to know how to learn. Serving as educational institutions cultivating medical students' learning ability, colleges and universities should not only instruct specific professional knowledge and skills, but also develop medical students' self-learning ability. In this research, we built a teaching system which can help to restore medical students' self-learning processes and analyze their learning outcomes and behaviors. To evaluate the effectiveness of the system in supporting medical students' self-learning, an experiment was conducted in 116 medical students from two grades. The results indicated that problems in self-learning process through this system was consistent with problems raised from traditional classroom teaching. Moreover, the experimental group (using this system) acted better than control group (using traditional classroom teaching) to some extent. Thus, this system can not only help medical students to develop their self-learning ability, but also enhances the ability of teachers to target medical students' questions quickly, improving the efficiency of answering questions in class.

  3. Fuzzy self-learning control for magnetic servo system

    Science.gov (United States)

    Tarn, J. H.; Kuo, L. T.; Juang, K. Y.; Lin, C. E.

    1994-01-01

    It is known that an effective control system is the key condition for successful implementation of high-performance magnetic servo systems. Major issues to design such control systems are nonlinearity; unmodeled dynamics, such as secondary effects for copper resistance, stray fields, and saturation; and that disturbance rejection for the load effect reacts directly on the servo system without transmission elements. One typical approach to design control systems under these conditions is a special type of nonlinear feedback called gain scheduling. It accommodates linear regulators whose parameters are changed as a function of operating conditions in a preprogrammed way. In this paper, an on-line learning fuzzy control strategy is proposed. To inherit the wealth of linear control design, the relations between linear feedback and fuzzy logic controllers have been established. The exercise of engineering axioms of linear control design is thus transformed into tuning of appropriate fuzzy parameters. Furthermore, fuzzy logic control brings the domain of candidate control laws from linear into nonlinear, and brings new prospects into design of the local controllers. On the other hand, a self-learning scheme is utilized to automatically tune the fuzzy rule base. It is based on network learning infrastructure; statistical approximation to assign credit; animal learning method to update the reinforcement map with a fast learning rate; and temporal difference predictive scheme to optimize the control laws. Different from supervised and statistical unsupervised learning schemes, the proposed method learns on-line from past experience and information from the process and forms a rule base of an FLC system from randomly assigned initial control rules.

  4. Assessing the Value of E-Learning Systems

    Science.gov (United States)

    Levy, Yair

    2006-01-01

    "Assessing the Value of E-Learning Systems" provides an extensive literature review pulling theories from the field of information systems, psychology and cognitive sciences, distance and online learning, as well as marketing and decision sciences. This book provides empirical evidence for the power of measuring value in the context of e-learning…

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

    Energy Technology Data Exchange (ETDEWEB)

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

    1995-06-01

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

  6. A presentation system for just-in-time learning in radiology.

    Science.gov (United States)

    Kahn, Charles E; Santos, Amadeu; Thao, Cheng; Rock, Jayson J; Nagy, Paul G; Ehlers, Kevin C

    2007-03-01

    There is growing interest in bringing medical educational materials to the point of care. We sought to develop a system for just-in-time learning in radiology. A database of 34 learning modules was derived from previously published journal articles. Learning objectives were specified for each module, and multiple-choice test items were created. A web-based system-called TEMPO-was developed to allow radiologists to select and view the learning modules. Web services were used to exchange clinical context information between TEMPO and the simulated radiology work station. Preliminary evaluation was conducted using the System Usability Scale (SUS) questionnaire. TEMPO identified learning modules that were relevant to the age, sex, imaging modality, and body part or organ system of the patient being viewed by the radiologist on the simulated clinical work station. Users expressed a high degree of satisfaction with the system's design and user interface. TEMPO enables just-in-time learning in radiology, and can be extended to create a fully functional learning management system for point-of-care learning in radiology.

  7. Adaptive polymeric system for Hebbian type learning

    OpenAIRE

    2011-01-01

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

  8. Adaptive E-learning System in Secondary Education

    Directory of Open Access Journals (Sweden)

    Sofija Tosheva

    2012-02-01

    Full Text Available In this paper we describe an adaptive web application E-school, where students can adjust some features according to their preferences and learning style. This e-learning environment enables monitoring students progress, total time students have spent in the system, their activity on the forums, the overall achievements in lessons learned, tests performed and solutions to given projects. Personalized assistance that teacher provides in a traditional classroom is not easy to implement. Students have regular contact with teachers using e-mail tools and conversation, so teacher get mentoring role for each student. The results of exploitation of the e-learning system show positive impact in acquiring the material and improvement of student’s achievements.

  9. Intelligent e-Learning Systems: An Educational Paradigm Shift

    Directory of Open Access Journals (Sweden)

    Suman Bhattacharya

    2016-12-01

    Full Text Available Learning is the long process of transforming information as well as experience into knowledge, skills, attitude and behaviors. To make up the wide gap between the demand of increasing higher education and comparatively limited resources, more and more educational institutes are looking into instructional technology. Use of online resources not only reduces the cost of education but also meet the needs of society. Intelligent e-learning has become one of the important channels to reach out to students exceeding geographic boundaries. Besides this, the characteristics of e-learning have complicated the process of education, and have brought challenges to both instructors and students. This paper will focus on the discussion of different discipline of intelligent e-learning like scaffolding based e-learning, personalized e-learning, confidence based e-learning, intelligent tutoring system, etc. to illuminate the educational paradigm shift in intelligent e-learning system.

  10. Simulation of noisy dynamical system by Deep Learning

    Science.gov (United States)

    Yeo, Kyongmin

    2017-11-01

    Deep learning has attracted huge attention due to its powerful representation capability. However, most of the studies on deep learning have been focused on visual analytics or language modeling and the capability of the deep learning in modeling dynamical systems is not well understood. In this study, we use a recurrent neural network to model noisy nonlinear dynamical systems. In particular, we use a long short-term memory (LSTM) network, which constructs internal nonlinear dynamics systems. We propose a cross-entropy loss with spatial ridge regularization to learn a non-stationary conditional probability distribution from a noisy nonlinear dynamical system. A Monte Carlo procedure to perform time-marching simulations by using the LSTM is presented. The behavior of the LSTM is studied by using noisy, forced Van der Pol oscillator and Ikeda equation.

  11. Courseware Development with Animated Pedagogical Agents in Learning System to Improve Learning Motivation

    Science.gov (United States)

    Chin, Kai-Yi; Hong, Zeng-Wei; Huang, Yueh-Min; Shen, Wei-Wei; Lin, Jim-Min

    2016-01-01

    The addition of animated pedagogical agents (APAs) in computer-assisted learning (CAL) systems could successfully enhance students' learning motivation and engagement in learning activities. Conventionally, the APA incorporated multimedia materials are constructed through the cooperation of teachers and software programmers. However, the thinking…

  12. Learning with incomplete information in the committee machine.

    Science.gov (United States)

    Bergmann, Urs M; Kühn, Reimer; Stamatescu, Ion-Olimpiu

    2009-12-01

    We study the problem of learning with incomplete information in a student-teacher setup for the committee machine. The learning algorithm combines unsupervised Hebbian learning of a series of associations with a delayed reinforcement step, in which the set of previously learnt associations is partly and indiscriminately unlearnt, to an extent that depends on the success rate of the student on these previously learnt associations. The relevant learning parameter lambda represents the strength of Hebbian learning. A coarse-grained analysis of the system yields a set of differential equations for overlaps of student and teacher weight vectors, whose solutions provide a complete description of the learning behavior. It reveals complicated dynamics showing that perfect generalization can be obtained if the learning parameter exceeds a threshold lambda ( c ), and if the initial value of the overlap between student and teacher weights is non-zero. In case of convergence, the generalization error exhibits a power law decay as a function of the number of examples used in training, with an exponent that depends on the parameter lambda. An investigation of the system flow in a subspace with broken permutation symmetry between hidden units reveals a bifurcation point lambda* above which perfect generalization does not depend on initial conditions. Finally, we demonstrate that cases of a complexity mismatch between student and teacher are optimally resolved in the sense that an over-complex student can emulate a less complex teacher rule, while an under-complex student reaches a state which realizes the minimal generalization error compatible with the complexity mismatch.

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

    Science.gov (United States)

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

    2012-09-01

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

  14. Organisational simplification and secondary complexity in health services for adults with learning disabilities.

    Science.gov (United States)

    Heyman, Bob; Swain, John; Gillman, Maureen

    2004-01-01

    This paper explores the role of complexity and simplification in the delivery of health care for adults with learning disabilities, drawing upon qualitative data obtained in a study carried out in NE England. It is argued that the requirement to manage complex health needs with limited resources causes service providers to simplify, standardise and routinise care. Simplified service models may work well enough for the majority of clients, but can impede recognition of the needs of those whose characteristics are not congruent with an adopted model. The data were analysed in relation to the core category, identified through thematic analysis, of secondary complexity arising from organisational simplification. Organisational simplification generates secondary complexity when operational routines designed to make health complexity manageable cannot accommodate the needs of non-standard service users. Associated themes, namely the social context of services, power and control, communication skills, expertise and service inclusiveness and evaluation are explored in relation to the core category. The concept of secondary complexity resulting from organisational simplification may partly explain seemingly irrational health service provider behaviour.

  15. Patterns for Designing Learning Management Systems

    NARCIS (Netherlands)

    Avgeriou, Paris; Retalis, Symeon; Papasalouros, Andreas

    2003-01-01

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

  16. Synchronization coupled systems to complex networks

    CERN Document Server

    Boccaletti, Stefano; del Genio, Charo I; Amann, Andreas

    2018-01-01

    A modern introduction to synchronization phenomena, this text presents recent discoveries and the current state of research in the field, from low-dimensional systems to complex networks. The book describes some of the main mechanisms of collective behaviour in dynamical systems, including simple coupled systems, chaotic systems, and systems of infinite-dimension. After introducing the reader to the basic concepts of nonlinear dynamics, the book explores the main synchronized states of coupled systems and describes the influence of noise and the occurrence of synchronous motion in multistable and spatially-extended systems. Finally, the authors discuss the underlying principles of collective dynamics on complex networks, providing an understanding of how networked systems are able to function as a whole in order to process information, perform coordinated tasks, and respond collectively to external perturbations. The demonstrations, numerous illustrations and application examples will help advanced graduate s...

  17. Confluence and convergence: team effectiveness in complex systems.

    Science.gov (United States)

    Porter-OʼGrady, Tim

    2015-01-01

    Complex adaptive systems require nursing leadership to rethink organizational work and the viability and effectiveness of teams. Much of emergent thinking about complexity and systems and organizations alter the understanding of the nature and function of teamwork and the configuration and leadership of team effort. Reflecting on basic concepts of complexity and their application to team formation, dynamics, and outcomes lays an important foundation for effectively guiding the strategic activity of systems through the focused tactical action of teams. Basic principles of complexity, their impact on teams, and the fundamental elements of team effectiveness are explored.

  18. Which Recommender System Can Best Fit Social Learning Platforms?

    NARCIS (Netherlands)

    Fazeli, Soude; Loni, Babak; Drachsler, Hendrik; Sloep, Peter

    2014-01-01

    This study aims to develop a recommender system for social learning platforms that combine traditional learning management systems with commercial social networks like Facebook. We therefore take into account social interactions of users to make recommendations on learning resources. We propose to

  19. Prototype learning and dissociable categorization systems in Alzheimer's disease.

    Science.gov (United States)

    Heindel, William C; Festa, Elena K; Ott, Brian R; Landy, Kelly M; Salmon, David P

    2013-08-01

    Recent neuroimaging studies suggest that prototype learning may be mediated by at least two dissociable memory systems depending on the mode of acquisition, with A/Not-A prototype learning dependent upon a perceptual representation system located within posterior visual cortex and A/B prototype learning dependent upon a declarative memory system associated with medial temporal and frontal regions. The degree to which patients with Alzheimer's disease (AD) can acquire new categorical information may therefore critically depend upon the mode of acquisition. The present study examined A/Not-A and A/B prototype learning in AD patients using procedures that allowed direct comparison of learning across tasks. Despite impaired explicit recall of category features in all tasks, patients showed differential patterns of category acquisition across tasks. First, AD patients demonstrated impaired prototype induction along with intact exemplar classification under incidental A/Not-A conditions, suggesting that the loss of functional connectivity within visual cortical areas disrupted the integration processes supporting prototype induction within the perceptual representation system. Second, AD patients demonstrated intact prototype induction but impaired exemplar classification during A/B learning under observational conditions, suggesting that this form of prototype learning is dependent on a declarative memory system that is disrupted in AD. Third, the surprisingly intact classification of both prototypes and exemplars during A/B learning under trial-and-error feedback conditions suggests that AD patients shifted control from their deficient declarative memory system to a feedback-dependent procedural memory system when training conditions allowed. Taken together, these findings serve to not only increase our understanding of category learning in AD, but to also provide new insights into the ways in which different memory systems interact to support the acquisition of

  20. Nursing students learning the pharmacology of diabetes mellitus with complexity-based computerized models: A quasi-experimental study.

    Science.gov (United States)

    Dubovi, Ilana; Dagan, Efrat; Sader Mazbar, Ola; Nassar, Laila; Levy, Sharona T

    2018-02-01

    Pharmacology is a crucial component of medications administration in nursing, yet nursing students generally find it difficult and self-rate their pharmacology skills as low. To evaluate nursing students learning pharmacology with the Pharmacology Inter-Leaved Learning-Cells environment, a novel approach to modeling biochemical interactions using a multiscale, computer-based model with a complexity perspective based on a small set of entities and simple rules. This environment represents molecules, organelles and cells to enhance the understanding of cellular processes, and combines these cells at a higher scale to obtain whole-body interactions. Sophomore nursing students who learned the pharmacology of diabetes mellitus with the Pharmacology Inter-Leaved Learning-Cells environment (experimental group; n=94) or via a lecture-based curriculum (comparison group; n=54). A quasi-experimental pre- and post-test design was conducted. The Pharmacology-Diabetes-Mellitus questionnaire and the course's final exam were used to evaluate students' knowledge of the pharmacology of diabetes mellitus. Conceptual learning was significantly higher for the experimental than for the comparison group for the course final exam scores (unpaired t=-3.8, pLearning with complexity-based computerized models is highly effective and enhances the understanding of moving between micro and macro levels of the biochemical phenomena, this is then related to better understanding of medication actions. Moreover, the Pharmacology Inter-Leaved Learning-Cells approach provides a more general reasoning scheme for biochemical processes, which enhances pharmacology learning beyond the specific topic learned. The present study implies that deeper understanding of pharmacology will support nursing students' clinical decisions and empower their proficiency in medications administration. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Complex systems relationships between control, communications and computing

    CERN Document Server

    2016-01-01

    This book gives a wide-ranging description of the many facets of complex dynamic networks and systems within an infrastructure provided by integrated control and supervision: envisioning, design, experimental exploration, and implementation. The theoretical contributions and the case studies presented can reach control goals beyond those of stabilization and output regulation or even of adaptive control. Reporting on work of the Control of Complex Systems (COSY) research program, Complex Systems follows from and expands upon an earlier collection: Control of Complex Systems by introducing novel theoretical techniques for hard-to-control networks and systems. The major common feature of all the superficially diverse contributions encompassed by this book is that of spotting and exploiting possible areas of mutual reinforcement between control, computing and communications. These help readers to achieve not only robust stable plant system operation but also properties such as collective adaptivity, integrity an...

  2. Semiotics of constructed complex systems

    Energy Technology Data Exchange (ETDEWEB)

    Landauer, C.; Bellman, K.L.

    1996-12-31

    The scope of this paper is limited to software and other constructed complex systems mediated or integrated by software. Our research program studies foundational issues that we believe will help us develop a theoretically sound approach to constructing complex systems. There have really been only two theoretical approaches that have helped us understand and develop computational systems: mathematics and linguistics. We show how semiotics can also play a role, whether we think of it as part of these other theories or as subsuming one or both of them. We describe our notion of {open_quotes}computational semiotics{close_quotes}, which we define to be the study of computational methods of dealing with symbols, show how such a theory might be formed, and describe what we might get from it in terms of more interesting use of symbols by computing systems. This research was supported in part by the Federal Highway Administration`s Office of Advanced Research and by the Advanced Research Projects Agency`s Software and Intelligent Systems Technology Office.

  3. SYSTEM APPROACH TO THE BLENDED LEARNING

    Directory of Open Access Journals (Sweden)

    Vladimir Kukharenko

    2015-10-01

    Full Text Available Currently, much attention is paid to the development of learning sour cream – a combination of traditional and distance (30-70% of training. Such training is sometimes called hybrid and referred to disruptive technologies. Purpose – to show that the use of systemic campaign in blended learning provides a high quality of education, and the technology can be devastating. The subject of the study – blended learning, object of study – Mixed learning process. The analysis results show that the combined training increases the motivation of students, qualification of teachers, personalized learning process. At the same time there are no reliable methods of assessing the quality of education and training standards. It is important that blended learning strategy to support the institutional goals and had an effective organizational model for support.

  4. DIDACTIC ENGINEERING: DESIGNING NEW GENERATION LEARNING SYSTEMS

    Directory of Open Access Journals (Sweden)

    Nail K. Nuriyev

    2016-09-01

    Full Text Available Introduction: the article deals with the organisation of training activities in the man-made environment. Didactic engineering is seen as a methodology within which problems of didactics are solved with application of pedagogical, psychological, engineering methods. It is obvious that in order to implement the training of future engineers in a competence-based format (according to educational standard a new type of teaching system is needed, with new capacities (properties. These systems should set each student towards the development of professionally significant (key abilities, taking into account his/her psychological characteristics; ensure training on the verge of permissible difficulties (developing training, and thereby achieve rapid development of key skills, through his/her zone of “immediate development”; to diagnose the quality of possession of a competence in the academic sense. For the objectivity and reliability of assessment of the level and depth of learned knowledge it is necessary to generate this evaluation in a metric format. As a result, we created a didactic system, which combines all the listed properties and the properties of classical systems. This allowed us to construct a new generation of didactic systems. Materials and Methods: the research is based on a systematic analysis of the activity of an engineer; on models of “zones of immediate development” by L. S. Vygotsky; on “developmental education” by L. N. Zankova; on the use of pedagogical and psychological patterns as well as taxonomic methods, didactic engineering, theory of probability and mathematical statistics. Results: constructed is a model for training engineers in the metric format of competence, which envisages a rapid development of students project and constructive abilit ies based on their knowledge learned. Discussion and Conclusions: the parameters defining the probability of engineer’s success have been described; the taxonomic scale

  5. Complex energy system management using optimization techniques

    Energy Technology Data Exchange (ETDEWEB)

    Bridgeman, Stuart; Hurdowar-Castro, Diana; Allen, Rick; Olason, Tryggvi; Welt, Francois

    2010-09-15

    Modern energy systems are often very complex with respect to the mix of generation sources, energy storage, transmission, and avenues to market. Historically, power was provided by government organizations to load centers, and pricing was provided in a regulatory manner. In recent years, this process has been displaced by the independent system operator (ISO). This complexity makes the operation of these systems very difficult, since the components of the system are interdependent. Consequently, computer-based large-scale simulation and optimization methods like Decision Support Systems are now being used. This paper discusses the application of a DSS to operations and planning systems.

  6. Complex systems and networks dynamics, controls and applications

    CERN Document Server

    Yu, Xinghuo; Chen, Guanrong; Yu, Wenwu

    2016-01-01

    This elementary book provides some state-of-the-art research results on broad disciplinary sciences on complex networks. It presents an in-depth study with detailed description of dynamics, controls and applications of complex networks. The contents of this book can be summarized as follows. First, the dynamics of complex networks, for example, the cluster dynamic analysis by using kernel spectral methods, community detection algorithms in bipartite networks, epidemiological modeling with demographics and epidemic spreading on multi-layer networks, are studied. Second, the controls of complex networks are investigated including topics like distributed finite-time cooperative control of multi-agent systems by applying homogenous-degree and Lyapunov methods, composite finite-time containment control for disturbed second-order multi-agent systems, fractional-order observer design of multi-agent systems, chaos control and anticontrol of complex systems via Parrondos game and many more. Third, the applications of ...

  7. Could a Mobile-Assisted Learning System Support Flipped Classrooms for Classical Chinese Learning?

    Science.gov (United States)

    Wang, Y.-H.

    2016-01-01

    In this study, the researcher aimed to develop a mobile-assisted learning system and to investigate whether it could promote teenage learners' classical Chinese learning through the flipped classroom approach. The researcher first proposed the structure of the Cross-device Mobile-Assisted Classical Chinese (CMACC) system according to the pilot…

  8. Examining the Potential of Web-Based Multimedia to Support Complex Fine Motor Skill Learning: An Empirical Study

    Science.gov (United States)

    Papastergiou, Marina; Pollatou, Elisana; Theofylaktou, Ioannis; Karadimou, Konstantina

    2014-01-01

    Research on the utilization of the Web for complex fine motor skill learning that involves whole body movements is still scarce. The aim of this study was to evaluate the impact of the introduction of a multimedia web-based learning environment, which was targeted at a rhythmic gymnastics routine consisting of eight fine motor skills, into an…

  9. IMPROVING CAUSE DETECTION SYSTEMS WITH ACTIVE LEARNING

    Data.gov (United States)

    National Aeronautics and Space Administration — IMPROVING CAUSE DETECTION SYSTEMS WITH ACTIVE LEARNING ISAAC PERSING AND VINCENT NG Abstract. Active learning has been successfully applied to many natural language...

  10. LONS: Learning Object Negotiation System

    Science.gov (United States)

    García, Antonio; García, Eva; de-Marcos, Luis; Martínez, José-Javier; Gutiérrez, José-María; Gutiérrez, José-Antonio; Barchino, Roberto; Otón, Salvador; Hilera, José-Ramón

    This system comes up as a result of the increase of e-learning systems. It manages all relevant modules in this context, such as the association of digital rights with the contents (courses), management and payment processing on rights. There are three blocks:

  11. Maze learning by a hybrid brain-computer system.

    Science.gov (United States)

    Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

    2016-09-13

    The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

  12. Maze learning by a hybrid brain-computer system

    Science.gov (United States)

    Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

    2016-09-01

    The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

  13. [Multi-course web-learning system for supporting students of medical technology].

    Science.gov (United States)

    Honma, Satoru; Wakamatsu, Hidetoshi; Kurihara, Yuriko; Yoshida, Shoko; Sakai, Nobue

    2013-05-01

    Web-Learning system was developed to support the self-learning for national qualification examination and medical engineering practice by students. The results from small tests in various situations suggest that the unit-learning systems are more effective, especially for the early stage of their self learning. In addition, the answers of some questionnaire suggest that the students' motivation has a certain relation with the number of the questions in the system. That is, the less number of the questions, the easier they are worked out with a higher learning motivation by students. Thus, the system was extended to enable students to study various subjects and/or units by themselves. The system enables them to have learning effects more easily by the exercise during lectures. The effectiveness of the system was investigated on medical associated subjects installed in the system. The concerning questions of Medical engineering and Pathological histology are adequately divided into several groups, of which sixteen Web-Learning subsystems were well composed for their practical application. Our concerning various unit-learning systems were confirmed much useful for most students comparing with the case of the overall Web-Learning system.

  14. Building machine learning systems with Python

    CERN Document Server

    Richert, Willi

    2013-01-01

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

  15. Repetitive learning control of continuous chaotic systems

    International Nuclear Information System (INIS)

    Chen Maoyin; Shang Yun; Zhou Donghua

    2004-01-01

    Combining a shift method and the repetitive learning strategy, a repetitive learning controller is proposed to stabilize unstable periodic orbits (UPOs) within chaotic attractors in the sense of least mean square. If nonlinear parts in chaotic systems satisfy Lipschitz condition, the proposed controller can be simplified into a simple proportional repetitive learning controller

  16. Expert Students in Social Learning Management Systems

    Science.gov (United States)

    Avogadro, Paolo; Calegari, Silvia; Dominoni, Matteo Alessandro

    2016-01-01

    Purpose: A social learning management system (social LMS) is a tool which favors social interactions and allows scholastic institutions to supervise and guide the learning process. The inclusion of the social feature to a "normal" LMS leads to the creation of educational social networks (EduSN), where the students interact and learn. The…

  17. Intensitas Perilaku Pengguna E-learning System dengan Model Utaut

    OpenAIRE

    Sari, Fatma; Purnamasari, Susan Dian

    2013-01-01

    This study aims to determine behavioral intention in the use of e-learning system using models UTAUT. The phenomenon underlying the research is: It is not yet optimal use of e-learning by students information systems in the learning process, not yet optimal socialization of the existence of e-learning, so that is not maximized and yet utilization measurability of the impact of using e-learning for lecturers.This study is limited in its scope: analysis of the influence of performance expectanc...

  18. DESIGNING MOTIVATIONAL LEARNING SYSTEMS IN DISTANCE EDUCATION

    Directory of Open Access Journals (Sweden)

    Jale BALABAN-SALI

    2008-07-01

    Full Text Available ABSTRACT The designing of instruction, when considered as a process, is the determination of instructional requirements of the learner and development of functional learning systems in order to meet these requirements. In fact, as a consequence of studies on the development of effective learning systems some instructional design theories have emerged. Among these theories the motivational design theory points out that instructional processes are required to be configured with the strategies which increases the attention, relevance, confidence and satisfaction of the students for an instructional design which ensures the continuity of learning motivation. The studies indicate that the systems which are developed on the basis of mentioned strategies raise the attention of the student during instruction, develop a relevance to the students’ requirements, create a positive expectation for success and help having a satisfaction by reinforcing success. In this article, the empirical studies related with this subject and the suggestions for presenting more effective motivational instructional designs in distance learning are summarized.

  19. An Architecture for Online Laboratory E-Learning System

    Science.gov (United States)

    Duan, Bing; Hosseini, Habib Mir M.; Ling, Keck Voon; Gay, Robert Kheng Leng

    2006-01-01

    Internet-based learning systems, or e-learning, are widely available in institutes, universities, and industrial companies, hosting regular or continuous education programs. The dream of teaching and learning from anywhere and at anytime becomes a reality due to the construction of e-learning infrastructure. Traditional teaching materials and…

  20. Classroom-oriented research from a complex systems perspective

    Directory of Open Access Journals (Sweden)

    Diane Larsen-Freeman

    2016-09-01

    Full Text Available Bringing a complex systems perspective to bear on classroom-oriented research challenges researchers to think differently, seeing the classroom ecology as one dynamic system nested in a hierarchy of such systems at different levels of scale, all of which are spatially and temporally situated. This article begins with an introduction to complex dynamic systems theory, in which challenges to traditional ways of conducting classroom research are interwoven. It concludes with suggestions for research methods that are more consistent with the theory. Research does not become easier when approached from a complex systems perspective, but it has the virtue of reflecting the way the world works.

  1. Complex and adaptive dynamical systems a primer

    CERN Document Server

    Gros, Claudius

    2013-01-01

    Complex system theory is rapidly developing and gaining importance, providing tools and concepts central to our modern understanding of emergent phenomena. This primer offers an introduction to this area together with detailed coverage of the mathematics involved. All calculations are presented step by step and are straightforward to follow. This new third edition comes with new material, figures and exercises. Network theory, dynamical systems and information theory, the core of modern complex system sciences, are developed in the first three chapters, covering basic concepts and phenomena like small-world networks, bifurcation theory and information entropy. Further chapters use a modular approach to address the most important concepts in complex system sciences, with the emergence and self-organization playing a central role. Prominent examples are self-organized criticality in adaptive systems, life at the edge of chaos, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase...

  2. Energy Flows in Low-Entropy Complex Systems

    Directory of Open Access Journals (Sweden)

    Eric J. Chaisson

    2015-12-01

    Full Text Available Nature’s many complex systems—physical, biological, and cultural—are islands of low-entropy order within increasingly disordered seas of surrounding, high-entropy chaos. Energy is a principal facilitator of the rising complexity of all such systems in the expanding Universe, including galaxies, stars, planets, life, society, and machines. A large amount of empirical evidence—relating neither entropy nor information, rather energy—suggests that an underlying simplicity guides the emergence and growth of complexity among many known, highly varied systems in the 14-billion-year-old Universe, from big bang to humankind. Energy flows are as centrally important to life and society as they are to stars and galaxies. In particular, the quantity energy rate density—the rate of energy flow per unit mass—can be used to explicate in a consistent, uniform, and unifying way a huge collection of diverse complex systems observed throughout Nature. Operationally, those systems able to utilize optimal amounts of energy tend to survive and those that cannot are non-randomly eliminated.

  3. Signs, Systems and Complexity of Transmedia Storytelling

    Directory of Open Access Journals (Sweden)

    Renira Rampazzo Gambarato

    2012-12-01

    Full Text Available This article addresses key concepts such as sign, system and complexity in order to approach transmedia storytelling and better understand its intricate nature. The theoretical framework chosen to investigate transmedia storytelling meanders is Semiotics by Charles Sanders Peirce (1839-1914 and General Systems Theory by Mario Bunge (1919-. The complexity of transmedia storytelling is not simply the one of the signs of the works included in a transmedia franchise. It also includes the complexity of the dispositions of users/consumers/players as interpreters of semiotic elements (e.g. characters, themes, environments, events and outcomes presented by transmedia products. It extends further to the complexity of social, cultural, economical and political constructs. The German transmedia narrative The Ultimate SuperHero-Blog by Stefan Gieren and Sofia’s Diary, a Portuguese multiplatform production by BeActive, are presented as examples of closed and open system transmedia storytelling respectively.

  4. Language Networks as Complex Systems

    Science.gov (United States)

    Lee, Max Kueiming; Ou, Sheue-Jen

    2008-01-01

    Starting in the late eighties, with a growing discontent with analytical methods in science and the growing power of computers, researchers began to study complex systems such as living organisms, evolution of genes, biological systems, brain neural networks, epidemics, ecology, economy, social networks, etc. In the early nineties, the research…

  5. Visual artificial grammar learning by rhesus macaques (Macaca mulatta): exploring the role of grammar complexity and sequence length.

    Science.gov (United States)

    Heimbauer, Lisa A; Conway, Christopher M; Christiansen, Morten H; Beran, Michael J; Owren, Michael J

    2018-03-01

    Humans and nonhuman primates can learn about the organization of stimuli in the environment using implicit sequential pattern learning capabilities. However, most previous artificial grammar learning studies with nonhuman primates have involved relatively simple grammars and short input sequences. The goal in the current experiments was to assess the learning capabilities of monkeys on an artificial grammar-learning task that was more complex than most others previously used with nonhumans. Three experiments were conducted using a joystick-based, symmetrical-response serial reaction time task in which two monkeys were exposed to grammar-generated sequences at sequence lengths of four in Experiment 1, six in Experiment 2, and eight in Experiment 3. Over time, the monkeys came to respond faster to the sequences generated from the artificial grammar compared to random versions. In a subsequent generalization phase, subjects generalized their knowledge to novel sequences, responding significantly faster to novel instances of sequences produced using the familiar grammar compared to those constructed using an unfamiliar grammar. These results reveal that rhesus monkeys can learn and generalize the statistical structure inherent in an artificial grammar that is as complex as some used with humans, for sequences up to eight items long. These findings are discussed in relation to whether or not rhesus macaques and other primate species possess implicit sequence learning abilities that are similar to those that humans draw upon to learn natural language grammar.

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

    Directory of Open Access Journals (Sweden)

    Francesco Colace

    2014-03-01

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

  7. Catastrophic failure in complex socio-technical systems

    International Nuclear Information System (INIS)

    Weir, D.

    2004-01-01

    This paper reviews the sequences leading to catastrophic failures in complex socio-technical systems. It traces some of the elements of an analytic framework to that proposed by Beer in Decision and Control, first published in 1966, and argues that these ideas are centrally relevant to a topic on which research interest has developed subsequently, the study of crises, catastrophes and disasters in complex socio-technical systems in high technology sectors. But while the system perspective is central, it is not by itself entirely adequate. The problems discussed cannot be discussed simply in terms of system parameters like variety, redundancy and complexity. Much empirical research supports the view that these systems typically operate in degraded mode. The degradations may be primarily initiated within the social components of the socio-technical system. Such variables as hierarchical position, actors' motivations and intentions are relevant to explain the ways in which communication systems typically operate to filter out messages from lower participants and to ignore the 'soft signals' issuing from small-scale and intermittent malfunctions. (author)

  8. Membrane tethering complexes in the endosomal system

    Directory of Open Access Journals (Sweden)

    Anne eSpang

    2016-05-01

    Full Text Available Vesicles that are generated by endocytic events at the plasma membrane are destined to early endosomes. A prerequisite for proper fusion is the tethering of two membrane entities. Tethering of vesicles to early endosomes is mediated by the CORVET complex, while fusion of late endosomes with lysosomes depends on the HOPS complex. Recycling through the TGN and to the plasma membrane is facilitated by the GARP and EARP complexes, respectively. However, there are other tethering functions in the endosomal system as there are multiple pathways through which proteins can be delivered from endosomes to either the TGN or the plasma membrane. Furthermore, complexes that may be part of novel tethering complexes have been recently identified. Thus it is likely that more tethering factors exist. In this review, I will provide an overview of different tethering complexes of the endosomal system and discuss how they may provide specificity in membrane traffic.

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

    Directory of Open Access Journals (Sweden)

    Mihyang Bang

    2014-06-01

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

  10. A Design Research Study of a Curriculum and Diagnostic Assessment System for a Learning Trajectory on Equipartitioning

    Science.gov (United States)

    Confrey, Jere; Maloney, Alan

    2015-01-01

    Design research studies provide significant opportunities to study new innovations and approaches and how they affect the forms of learning in complex classroom ecologies. This paper reports on a two-week long design research study with twelve 2nd through 4th graders using curricular materials and a tablet-based diagnostic assessment system, both…

  11. Managing Complexity

    DEFF Research Database (Denmark)

    Maylath, Bruce; Vandepitte, Sonia; Minacori, Patricia

    2013-01-01

    and into French. The complexity of the undertaking proved to be a central element in the students' learning, as the collaboration closely resembles the complexity of international documentation workplaces of language service providers. © Association of Teachers of Technical Writing.......This article discusses the largest and most complex international learning-by-doing project to date- a project involving translation from Danish and Dutch into English and editing into American English alongside a project involving writing, usability testing, and translation from English into Dutch...

  12. Active learning machine learns to create new quantum experiments.

    Science.gov (United States)

    Melnikov, Alexey A; Poulsen Nautrup, Hendrik; Krenn, Mario; Dunjko, Vedran; Tiersch, Markus; Zeilinger, Anton; Briegel, Hans J

    2018-02-06

    How useful can machine learning be in a quantum laboratory? Here we raise the question of the potential of intelligent machines in the context of scientific research. A major motivation for the present work is the unknown reachability of various entanglement classes in quantum experiments. We investigate this question by using the projective simulation model, a physics-oriented approach to artificial intelligence. In our approach, the projective simulation system is challenged to design complex photonic quantum experiments that produce high-dimensional entangled multiphoton states, which are of high interest in modern quantum experiments. The artificial intelligence system learns to create a variety of entangled states and improves the efficiency of their realization. In the process, the system autonomously (re)discovers experimental techniques which are only now becoming standard in modern quantum optical experiments-a trait which was not explicitly demanded from the system but emerged through the process of learning. Such features highlight the possibility that machines could have a significantly more creative role in future research.

  13. It helps to untangle really complicated situations: 'AS IF' supervision for working with complexity

    OpenAIRE

    Haydon-Laurelut, Mark; Millett, E.; Bissmire, D.; Doswell, S.; Heneage, C.

    2012-01-01

    Working effectively with people with learning disabilities may well involve negotiating complex systems of relationships. Negotiating a network - particularly in the context of risk, anxiety, and conflict - is a common task for clinical psychologists and systemic psychotherapists in Community Learning Disability Teams (CLDT's). In this paper we describe our use of the 'AS IF' consultation exercise (Anderson, 1987) as a tool for addressing complexity and stuck-ness. We have employed 'AS IF' in...

  14. Learning of spatio-temporal codes in a coupled oscillator system.

    Science.gov (United States)

    Orosz, Gábor; Ashwin, Peter; Townley, Stuart

    2009-07-01

    In this paper, we consider a learning strategy that allows one to transmit information between two coupled phase oscillator systems (called teaching and learning systems) via frequency adaptation. The dynamics of these systems can be modeled with reference to a number of partially synchronized cluster states and transitions between them. Forcing the teaching system by steady but spatially nonhomogeneous inputs produces cyclic sequences of transitions between the cluster states, that is, information about inputs is encoded via a "winnerless competition" process into spatio-temporal codes. The large variety of codes can be learned by the learning system that adapts its frequencies to those of the teaching system. We visualize the dynamics using "weighted order parameters (WOPs)" that are analogous to "local field potentials" in neural systems. Since spatio-temporal coding is a mechanism that appears in olfactory systems, the developed learning rules may help to extract information from these neural ensembles.

  15. Managing Complex Dynamical Systems

    Science.gov (United States)

    Cox, John C.; Webster, Robert L.; Curry, Jeanie A.; Hammond, Kevin L.

    2011-01-01

    Management commonly engages in a variety of research designed to provide insight into the motivation and relationships of individuals, departments, organizations, etc. This paper demonstrates how the application of concepts associated with the analysis of complex systems applied to such data sets can yield enhanced insights for managerial action.

  16. Workshop on Nonlinear Phenomena in Complex Systems

    CERN Document Server

    1989-01-01

    This book contains a thorough treatment of neural networks, cellular-automata and synergetics, in an attempt to provide three different approaches to nonlinear phenomena in complex systems. These topics are of major interest to physicists active in the fields of statistical mechanics and dynamical systems. They have been developed with a high degree of sophistication and include the refinements necessary to work with the complexity of real systems as well as the more recent research developments in these areas.

  17. Seizure Classification From EEG Signals Using Transfer Learning, Semi-Supervised Learning and TSK Fuzzy System.

    Science.gov (United States)

    Jiang, Yizhang; Wu, Dongrui; Deng, Zhaohong; Qian, Pengjiang; Wang, Jun; Wang, Guanjin; Chung, Fu-Lai; Choi, Kup-Sze; Wang, Shitong

    2017-12-01

    Recognition of epileptic seizures from offline EEG signals is very important in clinical diagnosis of epilepsy. Compared with manual labeling of EEG signals by doctors, machine learning approaches can be faster and more consistent. However, the classification accuracy is usually not satisfactory for two main reasons: the distributions of the data used for training and testing may be different, and the amount of training data may not be enough. In addition, most machine learning approaches generate black-box models that are difficult to interpret. In this paper, we integrate transductive transfer learning, semi-supervised learning and TSK fuzzy system to tackle these three problems. More specifically, we use transfer learning to reduce the discrepancy in data distribution between the training and testing data, employ semi-supervised learning to use the unlabeled testing data to remedy the shortage of training data, and adopt TSK fuzzy system to increase model interpretability. Two learning algorithms are proposed to train the system. Our experimental results show that the proposed approaches can achieve better performance than many state-of-the-art seizure classification algorithms.

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

    Science.gov (United States)

    Wu, Ting-Ting

    2014-10-01

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

  19. On synchronisation of a class of complex chaotic systems with complex unknown parameters via integral sliding mode control

    Science.gov (United States)

    Tirandaz, Hamed; Karami-Mollaee, Ali

    2018-06-01

    Chaotic systems demonstrate complex behaviour in their state variables and their parameters, which generate some challenges and consequences. This paper presents a new synchronisation scheme based on integral sliding mode control (ISMC) method on a class of complex chaotic systems with complex unknown parameters. Synchronisation between corresponding states of a class of complex chaotic systems and also convergence of the errors of the system parameters to zero point are studied. The designed feedback control vector and complex unknown parameter vector are analytically achieved based on the Lyapunov stability theory. Moreover, the effectiveness of the proposed methodology is verified by synchronisation of the Chen complex system and the Lorenz complex systems as the leader and the follower chaotic systems, respectively. In conclusion, some numerical simulations related to the synchronisation methodology is given to illustrate the effectiveness of the theoretical discussions.

  20. Complex and Adaptive Dynamical Systems A Primer

    CERN Document Server

    Gros, Claudius

    2011-01-01

    We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...

  1. Complex and adaptive dynamical systems a primer

    CERN Document Server

    Gros, Claudius

    2007-01-01

    We are living in an ever more complex world, an epoch where human actions can accordingly acquire far-reaching potentialities. Complex and adaptive dynamical systems are ubiquitous in the world surrounding us and require us to adapt to new realities and the way of dealing with them. This primer has been developed with the aim of conveying a wide range of "commons-sense" knowledge in the field of quantitative complex system science at an introductory level, providing an entry point to this both fascinating and vitally important subject. The approach is modular and phenomenology driven. Examples of emerging phenomena of generic importance treated in this book are: -- The small world phenomenon in social and scale-free networks. -- Phase transitions and self-organized criticality in adaptive systems. -- Life at the edge of chaos and coevolutionary avalanches resulting from the unfolding of all living. -- The concept of living dynamical systems and emotional diffusive control within cognitive system theory. Techn...

  2. Synchronization in Complex Networks of Nonlinear Dynamical Systems

    CERN Document Server

    Wu, Chai Wah

    2007-01-01

    This book brings together two emerging research areas: synchronization in coupled nonlinear systems and complex networks, and study conditions under which a complex network of dynamical systems synchronizes. While there are many texts that study synchronization in chaotic systems or properties of complex networks, there are few texts that consider the intersection of these two very active and interdisciplinary research areas. The main theme of this book is that synchronization conditions can be related to graph theoretical properties of the underlying coupling topology. The book introduces ide

  3. Large-scale computing techniques for complex system simulations

    CERN Document Server

    Dubitzky, Werner; Schott, Bernard

    2012-01-01

    Complex systems modeling and simulation approaches are being adopted in a growing number of sectors, including finance, economics, biology, astronomy, and many more. Technologies ranging from distributed computing to specialized hardware are explored and developed to address the computational requirements arising in complex systems simulations. The aim of this book is to present a representative overview of contemporary large-scale computing technologies in the context of complex systems simulations applications. The intention is to identify new research directions in this field and

  4. Collective Machine Learning: Team Learning and Classification in Multi-Agent Systems

    Science.gov (United States)

    Gifford, Christopher M.

    2009-01-01

    This dissertation focuses on the collaboration of multiple heterogeneous, intelligent agents (hardware or software) which collaborate to learn a task and are capable of sharing knowledge. The concept of collaborative learning in multi-agent and multi-robot systems is largely under studied, and represents an area where further research is needed to…

  5. Vibrations and stability of complex beam systems

    CERN Document Server

    Stojanović, Vladimir

    2015-01-01

     This book reports on solved problems concerning vibrations and stability of complex beam systems. The complexity of a system is considered from two points of view: the complexity originating from the nature of the structure, in the case of two or more elastically connected beams; and the complexity derived from the dynamic behavior of the system, in the case of a damaged single beam, resulting from the harm done to its simple structure. Furthermore, the book describes the analytical derivation of equations of two or more elastically connected beams, using four different theories (Euler, Rayleigh, Timoshenko and Reddy-Bickford). It also reports on a new, improved p-version of the finite element method for geometrically nonlinear vibrations. The new method provides more accurate approximations of solutions, while also allowing us to analyze geometrically nonlinear vibrations. The book describes the appearance of longitudinal vibrations of damaged clamped-clamped beams as a result of discontinuity (damage). It...

  6. Reliability assessment of complex electromechanical systems under epistemic uncertainty

    International Nuclear Information System (INIS)

    Mi, Jinhua; Li, Yan-Feng; Yang, Yuan-Jian; Peng, Weiwen; Huang, Hong-Zhong

    2016-01-01

    The appearance of macro-engineering and mega-project have led to the increasing complexity of modern electromechanical systems (EMSs). The complexity of the system structure and failure mechanism makes it more difficult for reliability assessment of these systems. Uncertainty, dynamic and nonlinearity characteristics always exist in engineering systems due to the complexity introduced by the changing environments, lack of data and random interference. This paper presents a comprehensive study on the reliability assessment of complex systems. In view of the dynamic characteristics within the system, it makes use of the advantages of the dynamic fault tree (DFT) for characterizing system behaviors. The lifetime of system units can be expressed as bounded closed intervals by incorporating field failures, test data and design expertize. Then the coefficient of variation (COV) method is employed to estimate the parameters of life distributions. An extended probability-box (P-Box) is proposed to convey the present of epistemic uncertainty induced by the incomplete information about the data. By mapping the DFT into an equivalent Bayesian network (BN), relevant reliability parameters and indexes have been calculated. Furthermore, the Monte Carlo (MC) simulation method is utilized to compute the DFT model with consideration of system replacement policy. The results show that this integrated approach is more flexible and effective for assessing the reliability of complex dynamic systems. - Highlights: • A comprehensive study on the reliability assessment of complex system is presented. • An extended probability-box is proposed to convey the present of epistemic uncertainty. • The dynamic fault tree model is built. • Bayesian network and Monte Carlo simulation methods are used. • The reliability assessment of a complex electromechanical system is performed.

  7. E-Learning System for Learning Virtual Circuit Making with a Microcontroller and Programming to Control a Robot

    Science.gov (United States)

    Takemura, Atsushi

    2015-01-01

    This paper proposes a novel e-Learning system for learning electronic circuit making and programming a microcontroller to control a robot. The proposed e-Learning system comprises a virtual-circuit-making function for the construction of circuits with a versatile, Arduino microcontroller and an educational system that can simulate behaviors of…

  8. Systems control with generalized probabilistic fuzzy-reinforcement learning

    NARCIS (Netherlands)

    Hinojosa, J.; Nefti, S.; Kaymak, U.

    2011-01-01

    Reinforcement learning (RL) is a valuable learning method when the systems require a selection of control actions whose consequences emerge over long periods for which input-output data are not available. In most combinations of fuzzy systems and RL, the environment is considered to be

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

    Science.gov (United States)

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

    2017-01-01

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

  10. Data integration, systems approach and multilevel description of complex biosystems

    International Nuclear Information System (INIS)

    Hernández-Lemus, Enrique

    2013-01-01

    Recent years have witnessed the development of new quantitative approaches and theoretical tenets in the biological sciences. The advent of high throughput experiments in genomics, proteomics and electrophysiology (to cite just a few examples) have provided the researchers with unprecedented amounts of data to be analyzed. Large datasets, however can not provide the means to achieve a complete understanding of the underlying biological phenomena, unless they are supplied with a solid theoretical framework and with proper analytical tools. It is now widely accepted that by using and extending some of the paradigmatic principles of what has been called complex systems theory, some degree of advance in this direction can be attained. We will be presenting ways in which by using data integration techniques (linear, non-linear, combinatorial, graphical), multidimensional-multilevel descriptions (multifractal modeling, dimensionality reduction, computational learning), as well as an approach based in systems theory (interaction maps, probabilistic graphical models, non-equilibrium physics) have allowed us to better understand some problems in the interface of Statistical Physics and Computational Biology

  11. Using virtual humans and computer animations to learn complex motor skills: a case study in karate

    Directory of Open Access Journals (Sweden)

    Spanlang Bernhard

    2011-12-01

    Full Text Available Learning motor skills is a complex task involving a lot of cognitive issues. One of the main issues consists in retrieving the relevant information from the learning environment. In a traditional learning situation, a teacher gives oral explanations and performs actions to provide the learner with visual examples. Using virtual reality (VR as a tool for learning motor tasks is promising. However, it raises questions about the type of information this kind of environments can offer. In this paper, we propose to analyze the impact of virtual humans on the perception of the learners. As a case study, we propose to apply this research problem to karate gestures. The results of this study show no significant difference on the after training performance of learners confronted to three different learning environments (traditional group, video and VR.

  12. A new decision sciences for complex systems.

    Science.gov (United States)

    Lempert, Robert J

    2002-05-14

    Models of complex systems can capture much useful information but can be difficult to apply to real-world decision-making because the type of information they contain is often inconsistent with that required for traditional decision analysis. New approaches, which use inductive reasoning over large ensembles of computational experiments, now make possible systematic comparison of alternative policy options using models of complex systems. This article describes Computer-Assisted Reasoning, an approach to decision-making under conditions of deep uncertainty that is ideally suited to applying complex systems to policy analysis. The article demonstrates the approach on the policy problem of global climate change, with a particular focus on the role of technology policies in a robust, adaptive strategy for greenhouse gas abatement.

  13. Slowness and sparseness have diverging effects on complex cell learning.

    Directory of Open Access Journals (Sweden)

    Jörn-Philipp Lies

    2014-03-01

    Full Text Available Following earlier studies which showed that a sparse coding principle may explain the receptive field properties of complex cells in primary visual cortex, it has been concluded that the same properties may be equally derived from a slowness principle. In contrast to this claim, we here show that slowness and sparsity drive the representations towards substantially different receptive field properties. To do so, we present complete sets of basis functions learned with slow subspace analysis (SSA in case of natural movies as well as translations, rotations, and scalings of natural images. SSA directly parallels independent subspace analysis (ISA with the only difference that SSA maximizes slowness instead of sparsity. We find a large discrepancy between the filter shapes learned with SSA and ISA. We argue that SSA can be understood as a generalization of the Fourier transform where the power spectrum corresponds to the maximally slow subspace energies in SSA. Finally, we investigate the trade-off between slowness and sparseness when combined in one objective function.

  14. Implementation of standards within eLearning information systems

    Directory of Open Access Journals (Sweden)

    Roman Malo

    2007-01-01

    Full Text Available Nowadays, eLearning standards' support within eLearning systems is much discussed problem. In this problem domain especially the reference model SCORM must be considered. This de-facto standard is a package of common standards and specifications used for the standardization of eLearning activities as eLearning content preparation, using e-course, communication etc. Implementation of standards itself is a process with great difficulty and time requests. Interesting and considerable approach to this problem is dividing all the process into several standalone and isolated steps focused on the individual segments of standards. This concept, in the paper described as 4-tier model of eLearning standards’ implementation, principally based upon the SCORM model enables sequential implementation of support for standards of eLearning metadata, eLearning content and also communication and navigation in e-courses. This possibility leads to portability and independence of result e-content. Discuss concept is a framework for standardization within eLearning subsystem of University Information System at Mendel University in Brno.

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

    OpenAIRE

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

    2008-01-01

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

  16. e-Learning Management System (eLMS) -

    Data.gov (United States)

    Department of Transportation — DOT's electronic Learning Management System (eLMS) is a state-of-the-art web-based system that meets the needs of training administrators, learners, and managers and...

  17. Atomic switch networks as complex adaptive systems

    Science.gov (United States)

    Scharnhorst, Kelsey S.; Carbajal, Juan P.; Aguilera, Renato C.; Sandouk, Eric J.; Aono, Masakazu; Stieg, Adam Z.; Gimzewski, James K.

    2018-03-01

    Complexity is an increasingly crucial aspect of societal, environmental and biological phenomena. Using a dense unorganized network of synthetic synapses it is shown that a complex adaptive system can be physically created on a microchip built especially for complex problems. These neuro-inspired atomic switch networks (ASNs) are a dynamic system with inherent and distributed memory, recurrent pathways, and up to a billion interacting elements. We demonstrate key parameters describing self-organized behavior such as non-linearity, power law dynamics, and multistate switching regimes. Device dynamics are then investigated using a feedback loop which provides control over current and voltage power-law behavior. Wide ranging prospective applications include understanding and eventually predicting future events that display complex emergent behavior in the critical regime.

  18. The Impacts of System and Human Factors on Online Learning Systems Use and Learner Satisfaction

    Science.gov (United States)

    Alshare, Khaled A.; Freeze, Ronald D.; Lane, Peggy L.; Wen, H. Joseph

    2011-01-01

    Success in an online learning environment is tied to both human and system factors. This study illuminates the unique contributions of human factors (comfort with online learning, self-management of learning, and perceived Web self-efficacy) to online learning system success, which is measured in terms of usage and satisfaction. The research model…

  19. Using mLearning and MOOCs to Understand Chaos, Emergence, and Complexity in Education

    Science.gov (United States)

    deWaard, Inge; Abajian, Sean; Gallagher, Michael Sean; Hogue, Rebecca; Keskin, Nilgun; Koutropoulos, Apostolos; Rodriguez, Osvaldo C.

    2011-01-01

    In this paper, we look at how the massive open online course (MOOC) format developed by connectivist researchers and enthusiasts can help analyze the complexity, emergence, and chaos at work in the field of education today. We do this through the prism of a MobiMOOC, a six-week course focusing on mLearning that ran from April to May 2011. MobiMOOC…

  20. Systems thinking and complexity: considerations for health promoting schools.

    Science.gov (United States)

    Rosas, Scott R

    2017-04-01

    The health promoting schools concept reflects a comprehensive and integrated philosophy to improving student and personnel health and well-being. Conceptualized as a configuration of interacting, interdependent parts connected through a web of relationships that form a whole greater than the sum of its parts, school health promotion initiatives often target several levels (e.g. individual, professional, procedural and policy) simultaneously. Health promoting initiatives, such as those operationalized under the whole school approach, include several interconnected components that are coordinated to improve health outcomes in complex settings. These complex systems interventions are embedded in intricate arrangements of physical, biological, ecological, social, political and organizational relationships. Systems thinking and characteristics of complex adaptive systems are introduced in this article to provide a perspective that emphasizes the patterns of inter-relationships associated with the nonlinear, dynamic and adaptive nature of complex hierarchical systems. Four systems thinking areas: knowledge, networks, models and organizing are explored as a means to further manage the complex nature of the development and sustainability of health promoting schools. Applying systems thinking and insights about complex adaptive systems can illuminate how to address challenges found in settings with both complicated (i.e. multi-level and multisite) and complex aspects (i.e. synergistic processes and emergent outcomes). © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.