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. 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.

  3. 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.

  4. 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…

  5. 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…

  6. 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…

  7. 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.

  8. 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…

  9. 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.

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

    Directory of Open Access Journals (Sweden)

    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

  11. 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…

  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. 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.

  14. 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,…

  15. 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…

  16. 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)…

  17. 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…

  18. 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…

  19. 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.

  20. Using Deep Learning to Predict Complex Systems: A Case Study in Wind Farm Generation

    Directory of Open Access Journals (Sweden)

    J. M. Torres

    2018-01-01

    Full Text Available Making every component of an electrical system work in unison is being made more challenging by the increasing number of renewable energies used, the electrical output of which is difficult to determine beforehand. In Spain, the daily electricity market opens with a 12-hour lead time, where the supply and demand expected for the following 24 hours are presented. When estimating the generation, energy sources like nuclear are highly stable, while peaking power plants can be run as necessary. Renewable energies, however, which should eventually replace peakers insofar as possible, are reliant on meteorological conditions. In this paper we propose using different deep-learning techniques and architectures to solve the problem of predicting wind generation in order to participate in the daily market, by making predictions 12 and 36 hours in advance. We develop and compare various estimators based on feedforward, convolutional, and recurrent neural networks. These estimators were trained and validated with data from a wind farm located on the island of Tenerife. We show that the best candidates for each type are more precise than the reference estimator and the polynomial regression currently used at the wind farm. We also conduct a sensitivity analysis to determine which estimator type is most robust to perturbations. An analysis of our findings shows that the most accurate and robust estimators are those based on feedforward neural networks with a SELU activation function and convolutional neural networks.

  1. 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

  2. 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.

  3. 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)

  4. 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

  5. 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.

  6. 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.

  7. 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 ...

  8. 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…

  9. Facilitating Learning and Physical Change in Complex Systems through Employee Involvement

    DEFF Research Database (Denmark)

    Bjerrum, Eva; Dahl, Susanne

    In a Danish workplace an experiment with mobile seating was carried out. Instead of implementing a certain concept designed by the management team the process was facilitated as a user involvement process based on Stacey´s theory of complex responsive processes. Here providing alternative picture...... of the organisation challenged the discursive practice of the organisation and engaged employees in a process where they challenged each other’s accepted understandings of the organisation and of their work....

  10. 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.

  11. Portfolio of automated trading systems: complexity and learning set size issues.

    Science.gov (United States)

    Raudys, Sarunas

    2013-03-01

    In this paper, we consider using profit/loss histories of multiple automated trading systems (ATSs) as N input variables in portfolio management. By means of multivariate statistical analysis and simulation studies, we analyze the influences of sample size (L) and input dimensionality on the accuracy of determining the portfolio weights. We find that degradation in portfolio performance due to inexact estimation of N means and N(N - 1)/2 correlations is proportional to N/L; however, estimation of N variances does not worsen the result. To reduce unhelpful sample size/dimensionality effects, we perform a clustering of N time series and split them into a small number of blocks. Each block is composed of mutually correlated ATSs. It generates an expert trading agent based on a nontrainable 1/N portfolio rule. To increase the diversity of the expert agents, we use training sets of different lengths for clustering. In the output of the portfolio management system, the regularized mean-variance framework-based fusion agent is developed in each walk-forward step of an out-of-sample portfolio validation experiment. Experiments with the real financial data (2003-2012) confirm the effectiveness of the suggested approach.

  12. 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…

  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. 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

  15. 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…

  16. 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,…

  17. 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....

  18. Investing in Youth Work: Learning from Complexity

    Directory of Open Access Journals (Sweden)

    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.

  19. 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.

  20. 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…

  1. 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

  2. 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.

  3. 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

  4. 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).

  5. 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...

  6. 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.

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

    Science.gov (United States)

    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

  8. 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.

  9. 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...

  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. Complexity control in statistical learning

    Indian Academy of Sciences (India)

    complexity of the class of models from which we are to choose our model. In this ... As is explained in §2, we use the concept of covering numbers to quantify the complexity of a class of ..... called structural risk minimization (SRM). Vapnik ...

  12. Complex adaptive systems ecology

    DEFF Research Database (Denmark)

    Sommerlund, Julie

    2003-01-01

    In the following, I will analyze two articles called Complex Adaptive Systems EcologyI & II (Molin & Molin, 1997 & 2000). The CASE-articles are some of the more quirkyarticles that have come out of the Molecular Microbial Ecology Group - a groupwhere I am currently making observational studies....... They are the result of acooperation between Søren Molin, professor in the group, and his brother, JanMolin, professor at Department of Organization and Industrial Sociology atCopenhagen Business School. The cooperation arises from the recognition that bothmicrobial ecology and sociology/organization theory works...

  13. Forecasting in Complex Systems

    Science.gov (United States)

    Rundle, J. B.; Holliday, J. R.; Graves, W. R.; Turcotte, D. L.; Donnellan, A.

    2014-12-01

    Complex nonlinear systems are typically characterized by many degrees of freedom, as well as interactions between the elements. Interesting examples can be found in the areas of earthquakes and finance. In these two systems, fat tails play an important role in the statistical dynamics. For earthquake systems, the Gutenberg-Richter magnitude-frequency is applicable, whereas for daily returns for the securities in the financial markets are known to be characterized by leptokurtotic statistics in which the tails are power law. Very large fluctuations are present in both systems. In earthquake systems, one has the example of great earthquakes such as the M9.1, March 11, 2011 Tohoku event. In financial systems, one has the example of the market crash of October 19, 1987. Both were largely unexpected events that severely impacted the earth and financial systems systemically. Other examples include the M9.3 Andaman earthquake of December 26, 2004, and the Great Recession which began with the fall of Lehman Brothers investment bank on September 12, 2013. Forecasting the occurrence of these damaging events has great societal importance. In recent years, national funding agencies in a variety of countries have emphasized the importance of societal relevance in research, and in particular, the goal of improved forecasting technology. Previous work has shown that both earthquakes and financial crashes can be described by a common Landau-Ginzburg-type free energy model. These metastable systems are characterized by fat tail statistics near the classical spinodal. Correlations in these systems can grow and recede, but do not imply causation, a common source of misunderstanding. In both systems, a common set of techniques can be used to compute the probabilities of future earthquakes or crashes. In this talk, we describe the basic phenomenology of these systems and emphasize their similarities and differences. We also consider the problem of forecast validation and verification

  14. Leadership Learning for Complex Organizations

    Science.gov (United States)

    Ng, F. S. David

    2015-01-01

    Many school leadership programs are set and delivered in specific modules or workshops in order to achieve a pre-determined set of competencies, knowledge, and skills. In addition, these programs are driven by the faculty member and the prescribed content. As Singapore schools become more complex in the roles and responsibilities to educate the…

  15. Learning from Nature - Mapping of Complex Hydrological and Geomorphological Process Systems for More Realistic Modelling of Hazard-related Maps

    Science.gov (United States)

    Chifflard, Peter; Tilch, Nils

    2010-05-01

    Introduction Hydrological or geomorphological processes in nature are often very diverse and complex. This is partly due to the regional characteristics which vary over time and space, as well as changeable process-initiating and -controlling factors. Despite being aware of this complexity, such aspects are usually neglected in the modelling of hazard-related maps due to several reasons. But particularly when it comes to creating more realistic maps, this would be an essential component to consider. The first important step towards solving this problem would be to collect data relating to regional conditions which vary over time and geographical location, along with indicators of complex processes. Data should be acquired promptly during and after events, and subsequently digitally combined and analysed. Study area In June 2009, considerable damage occurred in the residential area of Klingfurth (Lower Austria) as a result of great pre-event wetness and repeatedly heavy rainfall, leading to flooding, debris flow deposit and gravitational mass movement. One of the causes is the fact that the meso-scale watershed (16 km²) of the Klingfurth stream is characterised by adverse geological and hydrological conditions. Additionally, the river system network with its discharge concentration within the residential zone contributes considerably to flooding, particularly during excessive rainfall across the entire region, as the flood peaks from different parts of the catchment area are superposed. First results of mapping Hydro(geo)logical surveys across the entire catchment area have shown that - over 600 gravitational mass movements of various type and stage have occurred. 516 of those have acted as a bed load source, while 325 mass movements had not reached the final stage yet and could thus supply bed load in the future. It should be noted that large mass movements in the initial or intermediate stage were predominately found in clayey-silty areas and weathered material

  16. 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.

  17. 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"…

  18. 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.

  19. 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

  20. 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.

  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. 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.

  3. 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.

  4. 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...

  5. 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.

  6. 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

  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. Automatic Emergence Detection in Complex Systems

    Directory of Open Access Journals (Sweden)

    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.

  9. Anomaly Detection for Complex Systems

    Data.gov (United States)

    National Aeronautics and Space Administration — In performance maintenance in large, complex systems, sensor information from sub-components tends to be readily available, and can be used to make predictions about...

  10. 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

  11. 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.

  12. 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.

  13. 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...

  14. 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…

  15. 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.

  16. Addressing complex design problems through inductive learning

    OpenAIRE

    Hanna, S.

    2012-01-01

    Optimisation and related techniques are well suited to clearly defined problems involving systems that can be accurately simulated, but not to tasks in which the phenomena in question are highly complex or the problem ill-defined. These latter are typical of architecture and particularly creative design tasks, which therefore currently lack viable computational tools. It is argued that as design teams and construction projects of unprecedented scale are increasingly frequent, this is just whe...

  17. 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.

  18. 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.

  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. 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

  1. 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.

  2. 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

  3. Combinations of complex dynamical systems

    CERN Document Server

    Pilgrim, Kevin M

    2003-01-01

    This work is a research-level monograph whose goal is to develop a general combination, decomposition, and structure theory for branched coverings of the two-sphere to itself, regarded as the combinatorial and topological objects which arise in the classification of certain holomorphic dynamical systems on the Riemann sphere. It is intended for researchers interested in the classification of those complex one-dimensional dynamical systems which are in some loose sense tame. The program is motivated by the dictionary between the theories of iterated rational maps and Kleinian groups.

  4. 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.

  5. 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,

  6. 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.

  7. 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.

  8. Computational models of complex systems

    CERN Document Server

    Dabbaghian, Vahid

    2014-01-01

    Computational and mathematical models provide us with the opportunities to investigate the complexities of real world problems. They allow us to apply our best analytical methods to define problems in a clearly mathematical manner and exhaustively test our solutions before committing expensive resources. This is made possible by assuming parameter(s) in a bounded environment, allowing for controllable experimentation, not always possible in live scenarios. For example, simulation of computational models allows the testing of theories in a manner that is both fundamentally deductive and experimental in nature. The main ingredients for such research ideas come from multiple disciplines and the importance of interdisciplinary research is well recognized by the scientific community. This book provides a window to the novel endeavours of the research communities to present their works by highlighting the value of computational modelling as a research tool when investigating complex systems. We hope that the reader...

  9. Advancing the application of systems thinking in health: sustainability evaluation as learning and sense-making in a complex urban health system in Northern Bangladesh.

    Science.gov (United States)

    Sarriot, Eric G; Kouletio, Michelle; Jahan, Dr Shamim; Rasul, Izaz; Musha, Akm

    2014-08-26

    Starting in 1999, Concern Worldwide Inc. (Concern) worked with two Bangladeshi municipal health departments to support delivery of maternal and child health preventive services. A mid-term evaluation identified sustainability challenges. Concern relied on systems thinking implicitly to re-prioritize sustainability, but stakeholders also required a method, an explicit set of processes, to guide their decisions and choices during and after the project. Concern chose the Sustainability Framework method to generate creative thinking from stakeholders, create a common vision, and monitor progress. The Framework is based on participatory and iterative steps: defining (mapping) the local system and articulating a long-term vision, describing scenarios for achieving the vision, defining the elements of the model, and selecting corresponding indicators, setting and executing an assessment plan,, and repeated stakeholder engagement in analysis and decisions . Formal assessments took place up to 5 years post-project (2009). Strategic choices for the project were guided by articulating a collective vision for sustainable health, mapping the system of actors required to effect and sustain change, and defining different components of analysis. Municipal authorities oriented health teams toward equity-oriented service delivery efforts, strengthening of the functionality of Ward Health Committees, resource leveraging between municipalities and the Ministry of Health, and mitigation of contextual risks. Regular reference to a vision (and set of metrics (population health, organizational and community capacity) mitigated political factors. Key structures and processes were maintained following elections and political changes. Post-project achievements included the maintenance or improvement 5 years post-project (2009) in 9 of the 11 health indicator gains realized during the project (1999-2004). Some elements of performance and capacity weakened, but reductions in the equity gap

  10. 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

  11. Optimal quantum sample complexity of learning algorithms

    NARCIS (Netherlands)

    Arunachalam, S.; de Wolf, R.

    2017-01-01

    In learning theory, the VC dimension of a concept class C is the most common way to measure its "richness." A fundamental result says that the number of examples needed to learn an unknown target concept c 2 C under an unknown distribution D, is tightly determined by the VC dimension d of the

  12. 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.

  13. Interdisciplinary Symposium on Complex Systems

    CERN Document Server

    Zelinka, Ivan; Rössler, Otto

    2014-01-01

    The book you hold in your hands is the outcome of the "ISCS 2013: Interdisciplinary Symposium on Complex Systems" held at the historical capital of Bohemia as a continuation of our series of symposia in the science of complex systems. Prague, one of the most beautiful European cities, has its own beautiful genius loci. Here, a great number of important discoveries were made and many important scientists spent fruitful and creative years to leave unforgettable traces. The perhaps most significant period was the time of Rudolf II who was a great supporter of the art and the science and attracted a great number of prominent minds to Prague. This trend would continue. Tycho Brahe, Niels Henrik Abel, Johannes Kepler, Bernard Bolzano, August Cauchy Christian Doppler, Ernst Mach, Albert Einstein and many others followed developing fundamental mathematical and physical theories or expanding them. Thus in the beginning of the 17th century, Kepler formulated here the first two of his three laws of planetary motion on ...

  14. 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

  15. 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

  16. Adaptive Landmark-Based Navigation System Using Learning Techniques

    DEFF Research Database (Denmark)

    Zeidan, Bassel; Dasgupta, Sakyasingha; Wörgötter, Florentin

    2014-01-01

    The goal-directed navigational ability of animals is an essential prerequisite for them to survive. They can learn to navigate to a distal goal in a complex environment. During this long-distance navigation, they exploit environmental features, like landmarks, to guide them towards their goal. 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...

  17. 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.

  18. Multilevel Complex Networks and Systems

    Science.gov (United States)

    Caldarelli, Guido

    2014-03-01

    Network theory has been a powerful tool to model isolated complex systems. However, the classical approach does not take into account the interactions often present among different systems. Hence, the scientific community is nowadays concentrating the efforts on the foundations of new mathematical tools for understanding what happens when multiple networks interact. The case of economic and financial networks represents a paramount example of multilevel networks. In the case of trade, trade among countries the different levels can be described by the different granularity of the trading relations. Indeed, we have now data from the scale of consumers to that of the country level. In the case of financial institutions, we have a variety of levels at the same scale. For example one bank can appear in the interbank networks, ownership network and cds networks in which the same institution can take place. In both cases the systemically important vertices need to be determined by different procedures of centrality definition and community detection. In this talk I will present some specific cases of study related to these topics and present the regularities found. Acknowledged support from EU FET Project ``Multiplex'' 317532.

  19. 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…

  20. Early Language Learning: Complexity and Mixed Methods

    Science.gov (United States)

    Enever, Janet, Ed.; Lindgren, Eva, Ed.

    2017-01-01

    This is the first collection of research studies to explore the potential for mixed methods to shed light on foreign or second language learning by young learners in instructed contexts. It brings together recent studies undertaken in Cameroon, China, Croatia, Ethiopia, France, Germany, Italy, Kenya, Mexico, Slovenia, Spain, Sweden, Tanzania and…

  1. 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 -...

  2. Lessons Learned from Crowdsourcing Complex Engineering Tasks.

    Science.gov (United States)

    Staffelbach, Matthew; Sempolinski, Peter; Kijewski-Correa, Tracy; Thain, Douglas; Wei, Daniel; Kareem, Ahsan; Madey, Gregory

    2015-01-01

    Crowdsourcing is the practice of obtaining needed ideas, services, or content by requesting contributions from a large group of people. Amazon Mechanical Turk is a web marketplace for crowdsourcing microtasks, such as answering surveys and image tagging. We explored the limits of crowdsourcing by using Mechanical Turk for a more complicated task: analysis and creation of wind simulations. Our investigation examined the feasibility of using crowdsourcing for complex, highly technical tasks. This was done to determine if the benefits of crowdsourcing could be harnessed to accurately and effectively contribute to solving complex real world engineering problems. Of course, untrained crowds cannot be used as a mere substitute for trained expertise. Rather, we sought to understand how crowd workers can be used as a large pool of labor for a preliminary analysis of complex data. We compared the skill of the anonymous crowd workers from Amazon Mechanical Turk with that of civil engineering graduate students, making a first pass at analyzing wind simulation data. For the first phase, we posted analysis questions to Amazon crowd workers and to two groups of civil engineering graduate students. A second phase of our experiment instructed crowd workers and students to create simulations on our Virtual Wind Tunnel website to solve a more complex task. With a sufficiently comprehensive tutorial and compensation similar to typical crowd-sourcing wages, we were able to enlist crowd workers to effectively complete longer, more complex tasks with competence comparable to that of graduate students with more comprehensive, expert-level knowledge. Furthermore, more complex tasks require increased communication with the workers. As tasks become more complex, the employment relationship begins to become more akin to outsourcing than crowdsourcing. Through this investigation, we were able to stretch and explore the limits of crowdsourcing as a tool for solving complex problems.

  3. 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.

  4. 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

  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. 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.

  7. 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

  8. 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.

  9. 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…

  10. 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

  11. 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

  12. 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 ...

  13. 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

  14. 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...

  15. 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.

  16. Quantum mechanics in complex systems

    Science.gov (United States)

    Hoehn, Ross Douglas

    This document should be considered in its separation; there are three distinct topics contained within and three distinct chapters within the body of works. In a similar fashion, this abstract should be considered in three parts. Firstly, we explored the existence of multiply-charged atomic ions by having developed a new set of dimensional scaling equations as well as a series of relativistic augmentations to the standard dimensional scaling procedure and to the self-consistent field calculations. Secondly, we propose a novel method of predicting drug efficacy in hopes to facilitate the discovery of new small molecule therapeutics by modeling the agonist-protein system as being similar to the process of Inelastic Electron Tunneling Spectroscopy. Finally, we facilitate the instruction in basic quantum mechanical topics through the use of quantum games; this method of approach allows for the generation of exercises with the intent of conveying the fundamental concepts within a first year quantum mechanics classroom. Furthermore, no to be mentioned within the body of the text, yet presented in appendix form, certain works modeling the proliferation of cells types within the confines of man-made lattices for the purpose of facilitating artificial vascular transplants. In Chapter 2, we present a theoretical framework which describes multiply-charged atomic ions, their stability within super-intense laser fields, also lay corrections to the systems due to relativistic effects. Dimensional scaling calculations with relativistic corrections for systems: H, H-, H 2-, He, He-, He2-, He3- within super-intense laser fields were completed. Also completed were three-dimensional self consistent field calculations to verify the dimensionally scaled quantities. With the aforementioned methods the system's ability to stably bind 'additional' electrons through the development of multiple isolated regions of high potential energy leading to nodes of high electron density is shown

  17. 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.  

  18. 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...

  19. Systemic Resilience of Complex Urban Systems

    Directory of Open Access Journals (Sweden)

    Serge Salat

    2012-07-01

    Full Text Available Two key paradigms emerge out of the variety of urban forms: certain cities resemble trees, others leaves. The structural difference between a tree and a leaf is huge: one is open, the other closed. Trees are entirely disconnected on a given scale: even if two twigs are spatially close, if they do not belong to the same branch, to go from one to the other implies moving down and then up all the hierarchy of branches.  Leaves on the contrary are entirely connected on intermediary scales. The veins of a leaf are disconnected on the two larger scales but entirely connected on the two or three following intermediary scales before presenting tiny tree-like structures on the finest capillary scales. Deltas are leaves not trees. Neither galaxies nor whirlpools are trees. We will see in this paper that historical cities, like leaves, deltas, galaxies, lungs, brains and vein systems are all fractal structures, multiply connected and complex on all scales. These structures display the same degree of complexity and connectivity, regardless of the magnification scale on which we observe them. We say that these structures are scale free. Mathematical fractal forms are often generated recursively by applying again and again the same generator to an initiator. The iteration creates an arborescence. But scale free structure is not synonymous with a recursive tree-like structure. The fractal structure of the leaf is much more complex than that of the tree by its multiconnectivity on three or more intermediary levels. In contrast, trees in the virgin forest, even when they seem to be entangled, horizontal, and rhizomic, have branches that are not interconnected to form a lattice. As we will see, the history of urban planning has evolved from leaf-like to tree-like patterns, with a consequent loss of efficiency and resilience. Indeed, in a closed foliar path structure, the formation of cycles enables internal complexification and flow fluctuations due to the

  20. 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…

  1. 1989 lectures in complex systems

    International Nuclear Information System (INIS)

    Jen, E.

    1990-01-01

    This report contains papers on the following topics: Lectures on a Theory of Computation and Complexity over the Reals; Algorithmic Information Content, Church-Turing Thesis, Physical Entroph, and Maxwell's Demon; Physical Measures of Complexity; An Introduction to Chaos and Prediction; Hamiltonian Chaos in Nonlinear Polarized Optical Beam; Chemical Oscillators and Nonlinear Chemical Dynamics; Isotropic Navier-Stokes Turbulence. I. Qualitative Features and Basic Equations; Isotropic Navier-Stokes Turbulence. II. Statistical Approximation Methods; Lattice Gases; Data-Parallel Computation and the Connection Machine; Preimages and Forecasting for Cellular Automata; Lattice-Gas Models for Multiphase Flows and Magnetohydrodynamics; Probabilistic Cellular Automata: Some Statistical Mechanical Considerations; Complexity Due to Disorder and Frustration; Self-Organization by Simulated Evolution; Theoretical Immunology; Morphogenesis by Cell Intercalation; and Theoretical Physics Meets Experimental Neurobiology

  2. 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 ...

  3. 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)

  4. 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.

  5. 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...

  6. 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...

  7. 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...

  8. Learning about knowledge: A complex network approach

    International Nuclear Information System (INIS)

    Fontoura Costa, Luciano da

    2006-01-01

    An approach to modeling knowledge acquisition in terms of walks along complex networks is described. Each subset of knowledge is represented as a node, and relations between such knowledge are expressed as edges. Two types of edges are considered, corresponding to free and conditional transitions. The latter case implies that a node can only be reached after visiting previously a set of nodes (the required conditions). The process of knowledge acquisition can then be simulated by considering the number of nodes visited as a single agent moves along the network, starting from its lowest layer. It is shown that hierarchical networks--i.e., networks composed of successive interconnected layers--are related to compositions of the prerequisite relationships between the nodes. In order to avoid deadlocks--i.e., unreachable nodes--the subnetwork in each layer is assumed to be a connected component. Several configurations of such hierarchical knowledge networks are simulated and the performance of the moving agent quantified in terms of the percentage of visited nodes after each movement. The Barabasi-Albert and random models are considered for the layer and interconnecting subnetworks. Although all subnetworks in each realization have the same number of nodes, several interconnectivities, defined by the average node degree of the interconnection networks, have been considered. Two visiting strategies are investigated: random choice among the existing edges and preferential choice to so far untracked edges. A series of interesting results are obtained, including the identification of a series of plateaus of knowledge stagnation in the case of the preferential movement strategy in the presence of conditional edges

  9. 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.

  10. 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.

  11. Models of complex attitude systems

    DEFF Research Database (Denmark)

    Sørensen, Bjarne Taulo

    search algorithms and structural equation models. The results suggest that evaluative judgments of the importance of production system attributes are generated in a schematic manner, driven by personal value orientations. The effect of personal value orientations was strong and largely unmediated...... that evaluative affect propagates through the system in such a way that the system becomes evaluatively consistent and operates as a schema for the generation of evaluative judgments. In the empirical part of the paper, the causal structure of an attitude system from which people derive their evaluations of pork......Existing research on public attitudes towards agricultural production systems is largely descriptive, abstracting from the processes through which members of the general public generate their evaluations of such systems. The present paper adopts a systems perspective on such evaluations...

  12. 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.…

  13. 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

  14. 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)

  15. 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.

  16. 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

  17. 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

  18. 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...

  19. 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.

  20. 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

  1. 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...

  2. 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.…

  3. 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.

  4. 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.

  5. 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:

  6. 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

  7. 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...

  8. 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.

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

    Directory of Open Access Journals (Sweden)

    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. 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.

  11. Interval stability for complex systems

    Science.gov (United States)

    Klinshov, Vladimir V.; Kirillov, Sergey; Kurths, Jürgen; Nekorkin, Vladimir I.

    2018-04-01

    Stability of dynamical systems against strong perturbations is an important problem of nonlinear dynamics relevant to many applications in various areas. Here, we develop a novel concept of interval stability, referring to the behavior of the perturbed system during a finite time interval. Based on this concept, we suggest new measures of stability, namely interval basin stability (IBS) and interval stability threshold (IST). IBS characterizes the likelihood that the perturbed system returns to the stable regime (attractor) in a given time. IST provides the minimal magnitude of the perturbation capable to disrupt the stable regime for a given interval of time. The suggested measures provide important information about the system susceptibility to external perturbations which may be useful for practical applications. Moreover, from a theoretical viewpoint the interval stability measures are shown to bridge the gap between linear and asymptotic stability. We also suggest numerical algorithms for quantification of the interval stability characteristics and demonstrate their potential for several dynamical systems of various nature, such as power grids and neural networks.

  12. 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...

  13. Systems Biology and Health Systems Complexity in;

    NARCIS (Netherlands)

    Donald Combs, C.; Barham, S.R.; Sloot, P.M.A.

    2016-01-01

    Systems biology addresses interactions in biological systems at different scales of biological organization, from the molecular to the cellular, organ, organism, societal, and ecosystem levels. This chapter expands on the concept of systems biology, explores its implications for individual patients

  14. 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...

  15. 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.

  16. Quantum transport in complex system

    International Nuclear Information System (INIS)

    Kusnezov, D.; Bulgac, A.; DoDang, G.

    1998-01-01

    We derive the influence function and the effective dynamics of a quantum systems coupled to a chaotic environment, using very general parametric and banded random matrices to describe the quantum properties of a chaotic bath. We find that only in certain limits the thermalization can result from the environment. We study the general transport problems including escape, fusion and tunneling (fission). (author)

  17. Lectures in Complex Systems (1991)

    Science.gov (United States)

    1992-08-05

    of Development and Aging of the Nervous System, edited by J. M. Lauder , 217-225. New York: Plenum Press, 1990. 88. Keller, E. F. A Feeling for the...not every player wins an infinite amount of money just because the expected winning is infinite. The perception of this paradox in the 1700s was to cast

  18. Complex System Governance for Acquisition

    Science.gov (United States)

    2016-04-30

    are not the privilege, or curse, of any particular field or sector (energy, utilities, healthcare, transportation , commerce, defense, security...2005; Whitney et al., 2015) and Management Cybernetics ( Beer , 1972, 1979, 1985) and the field has been built upon their philosophical, theoretical, and...et al., 2015), while Management Cybernetics has been identified as the science of effective (system) organization ( Beer , 1972). Following from the

  19. 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.

  20. 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....

  1. 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.

  2. 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...

  3. 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.

  4. Dynamics of complex quantum systems

    CERN Document Server

    Akulin, Vladimir M

    2014-01-01

    This book gathers together a range of similar problems that can be encountered in different fields of modern quantum physics and that have common features with regard to multilevel quantum systems. The main motivation was to examine from a uniform standpoint various models and approaches that have been developed in atomic, molecular, condensed matter, chemical, laser and nuclear physics in various contexts. The book should help senior-level undergraduate, graduate students and researchers putting particular problems in these fields into a broader scientific context and thereby taking advantage of well-established techniques used in adjacent fields. This second edition has been expanded to include substantial new material (e.g. new sections on Dynamic Localization and on Euclidean Random Matrices and new chapters on Entanglement, Open Quantum Systems, and Coherence Protection). It is based on the author’s lectures at the Moscow Institute of Physics and Technology, at the CNRS Aimé Cotton Laboratory, and on ...

  5. Bilinear effect in complex systems

    Science.gov (United States)

    Lam, Lui; Bellavia, David C.; Han, Xiao-Pu; Alston Liu, Chih-Hui; Shu, Chang-Qing; Wei, Zhengjin; Zhou, Tao; Zhu, Jichen

    2010-09-01

    The distribution of the lifetime of Chinese dynasties (as well as that of the British Isles and Japan) in a linear Zipf plot is found to consist of two straight lines intersecting at a transition point. This two-section piecewise-linear distribution is different from the power law or the stretched exponent distribution, and is called the Bilinear Effect for short. With assumptions mimicking the organization of ancient Chinese regimes, a 3-layer network model is constructed. Numerical results of this model show the bilinear effect, providing a plausible explanation of the historical data. The bilinear effect in two other social systems is presented, indicating that such a piecewise-linear effect is widespread in social systems.

  6. Thermodynamic modeling of complex systems

    DEFF Research Database (Denmark)

    Liang, Xiaodong

    after an oil spill. Engineering thermodynamics could be applied in the state-of-the-art sonar products through advanced artificial technology, if the speed of sound, solubility and density of oil-seawater systems could be satisfactorily modelled. The addition of methanol or glycols into unprocessed well...... is successfully applied to model the phase behaviour of water, chemical and hydrocarbon (oil) containing systems with newly developed pure component parameters for water and chemicals and characterization procedures for petroleum fluids. The performance of the PCSAFT EOS on liquid-liquid equilibria of water...... with hydrocarbons has been under debate for some vii years. An interactive step-wise procedure is proposed to fit the model parameters for small associating fluids by taking the liquid-liquid equilibrium data into account. It is still far away from a simple task to apply PC-SAFT in routine PVT simulations and phase...

  7. Agile Integration of Complex Systems

    Science.gov (United States)

    2010-04-28

    intervention in using SOA can be reduced Page 5 SOA in DoD DoD has mandated that all systems support the Network - Centric Environment and SOA is fundamental to...it and dropping it on an orchestrate icon (slide 22) Di i lifi d d d i l Page 13 scovery s mp e an ma e v sua SOAF Messaging Service Transport

  8. 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...

  9. 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....

  10. 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.

  11. Complex motions and chaos in nonlinear systems

    CERN Document Server

    Machado, José; Zhang, Jiazhong

    2016-01-01

    This book brings together 10 chapters on a new stream of research examining complex phenomena in nonlinear systems—including engineering, physics, and social science. Complex Motions and Chaos in Nonlinear Systems provides readers a particular vantage of the nature and nonlinear phenomena in nonlinear dynamics that can develop the corresponding mathematical theory and apply nonlinear design to practical engineering as well as the study of other complex phenomena including those investigated within social science.

  12. 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.

  13. 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...

  14. The Self as a Complex Dynamic System

    Science.gov (United States)

    Mercer, Sarah

    2011-01-01

    This article explores the potential offered by complexity theories for understanding language learners' sense of self and attempts to show how the self might usefully be conceived of as a complex dynamic system. Rather than presenting empirical findings, the article discusses existent research on the self and aims at outlining a conceptual…

  15. Strategies of complexity leadership in governance systems

    NARCIS (Netherlands)

    Nooteboom, S.G.; Termeer, C.J.A.M.

    2013-01-01

    In complex governance systems, innovations may emerge, not controlled by a single leader, but enabled by many. We discuss how these leaders are embedded in networks and which strategies they use. The theoretical framework is based on Complexity Leadership Theory. We conducted participatory

  16. 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.

  17. 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)

  18. 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

  19. 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...

  20. 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

  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. 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.

  3. Coordination Approaches for Complex Software Systems

    NARCIS (Netherlands)

    Bosse, T.; Hoogendoorn, M.; Treur, J.

    2006-01-01

    This document presents the results of a collaboration between the Vrije Universiteit Amsterdam, Department of Artificial Intelligence and Force Vision to investigate coordination approaches for complex software systems. The project was funded by Force Vision.

  4. 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…

  5. Platform strategy for complex products and systems

    NARCIS (Netherlands)

    Alblas, A.A.

    2011-01-01

    The thesis of Alex Alblas presents a design reuse strategy for firms producing complex products and systems (CoPS). Examples of CoPS include industrial machinery, oil-rigs, electrical power distribution systems, integrated mail processing systems and printing press machinery. CoPS firms are

  6. Distributed redundancy and robustness in complex systems

    KAUST Repository

    Randles, Martin; Lamb, David J.; Odat, Enas M.; Taleb-Bendiab, Azzelarabe

    2011-01-01

    that emerges in complex biological and natural systems. However, in order to promote an evolutionary approach, through emergent self-organisation, it is necessary to specify the systems in an 'open-ended' manner where not all states of the system are prescribed

  7. A new decision sciences for complex systems

    OpenAIRE

    Lempert, Robert J.

    2002-01-01

    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...

  8. Project risk management in complex petrochemical system

    Directory of Open Access Journals (Sweden)

    Kirin Snežana

    2012-01-01

    Full Text Available Investigation of risk in complex industrial systems, as well as evaluation of main factors influencing decision making and implementation process using large petrochemical company as an example, has proved the importance of successful project risk management. This is even more emphasized when analyzing systems with complex structure, i.e. with several organizational units. It has been shown that successful risk management requires modern methods, based on adequate application of statistical analysis methods.

  9. 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.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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...

  16. 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.

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. Discontinuity and complexity in nonlinear physical systems

    CERN Document Server

    Baleanu, Dumitru; Luo, Albert

    2014-01-01

    This unique book explores recent developments in experimental research in this broad field, organized in four distinct sections. Part I introduces the reader to the fractional dynamics and Lie group analysis for nonlinear partial differential equations. Part II covers chaos and complexity in nonlinear Hamiltonian systems, important to understand the resonance interactions in nonlinear dynamical systems, such as Tsunami waves and wildfire propagations; as well as Lev flights in chaotic trajectories, dynamical system synchronization and DNA information complexity analysis. Part III examines chaos and periodic motions in discontinuous dynamical systems, extensively present in a range of systems, including piecewise linear systems, vibro-impact systems and drilling systems in engineering. And in Part IV, engineering and financial nonlinearity are discussed. The mechanism of shock wave with saddle-node bifurcation and rotating disk stability will be presented, and the financial nonlinear models will be discussed....

  2. 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.

  3. 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.

  4. 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.

  5. 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…

  6. 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…

  7. Modeling complex work systems - method meets reality

    NARCIS (Netherlands)

    van der Veer, Gerrit C.; Hoeve, Machteld; Lenting, Bert

    1996-01-01

    Modeling an existing task situation is often a first phase in the (re)design of information systems. For complex systems design, this model should consider both the people and the organization involved, the work, and situational aspects. Groupware Task Analysis (GTA) as part of a method for the

  8. 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.

  9. 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.

  10. Radwaste treatment complex. DRAWMACS planned maintenance system

    International Nuclear Information System (INIS)

    Keel, A.J.

    1992-07-01

    This document describes the operation of the Planned Maintenance System for the Radwaste Treatment Complex. The Planned Maintenance System forms part of the Decommissioning and Radwaste Management Computer System (DRAWMACS). Further detailed information about the data structure of the system is contained in Database Design for the DRAWMACS Planned Maintenance System (AEA-D and R-0285, 2nd issue, 25th February 1992). Information for other components of DRAWMACS is contained in Basic User Guide for the Radwaste Treatment Plant Computer System (AEA-D and R-0019, July 1990). (author)

  11. The self as a complex dynamic system

    Directory of Open Access Journals (Sweden)

    Sarah Mercer

    2011-04-01

    Full Text Available This article explores the potential offered by complexity theories for understanding language learners’ sense of self and attempts to show how the self might usefully be conceived of as a complex dynamic system. Rather than presenting empirical findings, the article discusses existent research on the self and aims at outlining a conceptual perspective that may inform future studies into the self and possibly other individual learner differences. The article concludes by critically considering the merits of a complexity perspective but also reflecting on the challenges it poses for research.

  12. Distributed redundancy and robustness in complex systems

    KAUST Repository

    Randles, Martin

    2011-03-01

    The uptake and increasing prevalence of Web 2.0 applications, promoting new large-scale and complex systems such as Cloud computing and the emerging Internet of Services/Things, requires tools and techniques to analyse and model methods to ensure the robustness of these new systems. This paper reports on assessing and improving complex system resilience using distributed redundancy, termed degeneracy in biological systems, to endow large-scale complicated computer systems with the same robustness that emerges in complex biological and natural systems. However, in order to promote an evolutionary approach, through emergent self-organisation, it is necessary to specify the systems in an \\'open-ended\\' manner where not all states of the system are prescribed at design-time. In particular an observer system is used to select robust topologies, within system components, based on a measurement of the first non-zero Eigen value in the Laplacian spectrum of the components\\' network graphs; also known as the algebraic connectivity. It is shown, through experimentation on a simulation, that increasing the average algebraic connectivity across the components, in a network, leads to an increase in the variety of individual components termed distributed redundancy; the capacity for structurally distinct components to perform an identical function in a particular context. The results are applied to a specific application where active clustering of like services is used to aid load balancing in a highly distributed network. Using the described procedure is shown to improve performance and distribute redundancy. © 2010 Elsevier Inc.

  13. Athletes and sports teams as complex adaptive system: A review of implications for learning design. [Atletas y equipos deportivos como sistemas adaptativos complejos: Una revision de las Implicaciones para el diseño del aprendizaje].

    Directory of Open Access Journals (Sweden)

    Keith Davids

    2015-01-01

    Full Text Available Ecological dynamics is a systems-oriented theoretical framework which conceptualises sport performers as complex adaptive systems. It seeks to understand the adaptive relations that emerge during coordination of interactions between each performer and a specific performance environment. This approach has identified the individual-environment relationship as the relevant scale of analysis for explaining how processes of perception, cognition and action underpin expert performance in sport. This theoretical overview elucidates key ideas from previous work identifying functional characteristics of complex adaptive systems, such as co-adaptation, emergent coordination tendencies and capacity to utilise affordances, which underlie performance and learning in team and individual sports. The review of research focuses on how key principles of ecological dynamics inform our understanding of learning and transfer, and their impact on practice task design in sport development programmes. To support this analysis, data from research on performance of elite and developmental athletes in individual and team sports are presented to highlight important principles of learning design from an ecological dynamics perspective. Resumen La dinámica ecológica es un marco teórico orientado a los sistemas que conceptualiza a los athletas como sistemas complejos adaptativos. Con el objeto de comprender las relaciones adaptativas que surgen durante la coordinación de las interacciones entre cada uno de los athletas y un medio/ambiente de actuación específico. Este enfoque ha identificado la relación individuo-ambiente como la escala de análisis relevante para explicar cómo los procesos de la percepción, la cognición y la acción respaldan el rendimiento de expertos en el deporte. Este documento de posición teórica aclara características funcionales esenciales de los sistemas adaptativos complejos, tales como co-adaptación, tendencias emergentes de

  14. 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.

  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. 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.

  17. 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,...

  18. 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

  19. 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.

  20. 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.

  1. Learning Management Systems on Blended Learning Courses

    DEFF Research Database (Denmark)

    Kuran, Mehmet Şükrü; Pedersen, Jens Myrup; Elsner, Raphael

    2017-01-01

    LMSes, Moodle, Blackboard Learn, Canvas, and Stud.IP with respect to these. We explain how these features were utilized to increase the efficiency, tractability, and quality of experience of the course. We found that an LMS with advanced features such as progress tracking, modular course support...

  2. System crash as dynamics of complex networks.

    Science.gov (United States)

    Yu, Yi; Xiao, Gaoxi; Zhou, Jie; Wang, Yubo; Wang, Zhen; Kurths, Jürgen; Schellnhuber, Hans Joachim

    2016-10-18

    Complex systems, from animal herds to human nations, sometimes crash drastically. Although the growth and evolution of systems have been extensively studied, our understanding of how systems crash is still limited. It remains rather puzzling why some systems, appearing to be doomed to fail, manage to survive for a long time whereas some other systems, which seem to be too big or too strong to fail, crash rapidly. In this contribution, we propose a network-based system dynamics model, where individual actions based on the local information accessible in their respective system structures may lead to the "peculiar" dynamics of system crash mentioned above. Extensive simulations are carried out on synthetic and real-life networks, which further reveal the interesting system evolution leading to the final crash. Applications and possible extensions of the proposed model are discussed.

  3. Understanding Complex Construction Systems Through Modularity

    DEFF Research Database (Denmark)

    Jensen, Tor Clarke; Bekdik, Baris; Thuesen, Christian

    2014-01-01

    This paper develops a framework for understanding complexity in construction projects by combining theories of complexity management and modularization. The framework incorporates three dimensions of product, process, and organizational modularity with the case of gypsum wall elements. The analysis...... system, rather than a modular, although the industry forces modular organizational structures. This creates a high complexity degree caused by the non-alignment of building parts and organizations and the frequent swapping of modules....... finds that the main driver of complexity is the fragmentation of the design and production, which causes the production modules to construct and install new product types and variants for each project as the designers are swapped for every project. The many interfaces are characteristics of an integral...

  4. 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.

  5. E-Learning Systems, Environments and Approaches

    OpenAIRE

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

    2015-01-01

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

  6. 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.

  7. Extraction of quantifiable information from complex systems

    CERN Document Server

    Dahmen, Wolfgang; Griebel, Michael; Hackbusch, Wolfgang; Ritter, Klaus; Schneider, Reinhold; Schwab, Christoph; Yserentant, Harry

    2014-01-01

    In April 2007, the  Deutsche Forschungsgemeinschaft (DFG) approved the  Priority Program 1324 “Mathematical Methods for Extracting Quantifiable Information from Complex Systems.” This volume presents a comprehensive overview of the most important results obtained over the course of the program.   Mathematical models of complex systems provide the foundation for further technological developments in science, engineering and computational finance.  Motivated by the trend toward steadily increasing computer power, ever more realistic models have been developed in recent years. These models have also become increasingly complex, and their numerical treatment poses serious challenges.   Recent developments in mathematics suggest that, in the long run, much more powerful numerical solution strategies could be derived if the interconnections between the different fields of research were systematically exploited at a conceptual level. Accordingly, a deeper understanding of the mathematical foundations as w...

  8. Complex and adaptive dynamical systems a primer

    CERN Document Server

    Gros, Claudius

    2015-01-01

    This primer offers readers an introduction to the central concepts that form our modern understanding of complex and emergent behavior, together with detailed coverage of accompanying mathematical methods. All calculations are presented step by step and are easy to follow. This new fourth edition has been fully reorganized and includes new chapters, figures and exercises. The core aspects of modern complex system sciences are presented in the first chapters, covering network theory, dynamical systems, bifurcation and catastrophe theory, chaos and adaptive processes, together with the principle of self-organization in reaction-diffusion systems and social animals. Modern information theoretical principles are treated in further chapters, together with the concept of self-organized criticality, gene regulation networks, hypercycles and coevolutionary avalanches, synchronization phenomena, absorbing phase transitions and the cognitive system approach to the brain. Technical course prerequisites are the standard ...

  9. Morphogenetic Engineering Toward Programmable Complex Systems

    CERN Document Server

    Sayama, Hiroki; Michel, Olivier

    2012-01-01

    Generally, spontaneous pattern formation phenomena are random and repetitive, whereas elaborate devices are the deterministic product of human design. Yet, biological organisms and collective insect constructions are exceptional examples of complex systems that are both self-organized and architectural.   This book is the first initiative of its kind toward establishing a new field of research, Morphogenetic Engineering, to explore the modeling and implementation of “self-architecturing” systems. Particular emphasis is placed on the programmability and computational abilities of self-organization, properties that are often underappreciated in complex systems science—while, conversely, the benefits of self-organization are often underappreciated in engineering methodologies.   Altogether, the aim of this work is to provide a framework for and examples of a larger class of “self-architecturing” systems, while addressing fundamental questions such as   > How do biological organisms carry out morphog...

  10. Managing interoperability and complexity in health systems.

    Science.gov (United States)

    Bouamrane, M-M; Tao, C; Sarkar, I N

    2015-01-01

    In recent years, we have witnessed substantial progress in the use of clinical informatics systems to support clinicians during episodes of care, manage specialised domain knowledge, perform complex clinical data analysis and improve the management of health organisations' resources. However, the vision of fully integrated health information eco-systems, which provide relevant information and useful knowledge at the point-of-care, remains elusive. This journal Focus Theme reviews some of the enduring challenges of interoperability and complexity in clinical informatics systems. Furthermore, a range of approaches are proposed in order to address, harness and resolve some of the many remaining issues towards a greater integration of health information systems and extraction of useful or new knowledge from heterogeneous electronic data repositories.

  11. On complex adaptive systems and terrorism

    International Nuclear Information System (INIS)

    Ahmed, E.; Elgazzar, A.S.; Hegazi, A.S.

    2005-01-01

    Complex adaptive systems (CAS) are ubiquitous in nature. They are basic in social sciences. An overview of CAS is given with emphasize on the occurrence of bad side effects to seemingly 'wise' decisions. Hence application to terrorism is given. Some conclusions on how to deal with this phenomena are proposed

  12. Complex systems modeling by cellular automata

    NARCIS (Netherlands)

    Kroc, J.; Sloot, P.M.A.; Rabuñal Dopico, J.R.; Dorado de la Calle, J.; Pazos Sierra, A.

    2009-01-01

    In recent years, the notion of complex systems proved to be a very useful concept to define, describe, and study various natural phenomena observed in a vast number of scientific disciplines. Examples of scientific disciplines that highly benefit from this concept range from physics, mathematics,

  13. Engineering Education as a Complex System

    Science.gov (United States)

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

    2011-01-01

    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…

  14. Designing complex systems - a structured activity

    NARCIS (Netherlands)

    van der Veer, Gerrit C.; van Vliet, Johannes C.; Lenting, Bert; Olson, Gary M.; Schuon, Sue

    1995-01-01

    This paper concerns the development of complex systems from the point of view of design as a structure of activities, related both to the clients and the users. Several modeling approaches will be adopted for different aspects of design, and several views on design will be integrated. The proposed

  15. 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...

  16. Ensemble annealing of complex physical systems

    OpenAIRE

    Habeck, Michael

    2015-01-01

    Algorithms for simulating complex physical systems or solving difficult optimization problems often resort to an annealing process. Rather than simulating the system at the temperature of interest, an annealing algorithm starts at a temperature that is high enough to ensure ergodicity and gradually decreases it until the destination temperature is reached. This idea is used in popular algorithms such as parallel tempering and simulated annealing. A general problem with annealing methods is th...

  17. 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...

  18. Dependency visualization for complex system understanding

    Energy Technology Data Exchange (ETDEWEB)

    Smart, J. Allison Cory [Univ. of California, Davis, CA (United States)

    1994-09-01

    With the volume of software in production use dramatically increasing, the importance of software maintenance has become strikingly apparent. Techniques now sought and developed for reverse engineering and design extraction and recovery. At present, numerous commercial products and research tools exist which are capable of visualizing a variety of programming languages and software constructs. The list of new tools and services continues to grow rapidly. Although the scope of the existing commercial and academic product set is quite broad, these tools still share a common underlying problem. The ability of each tool to visually organize object representations is increasingly impaired as the number of components and component dependencies within systems increases. Regardless of how objects are defined, complex ``spaghetti`` networks result in nearly all large system cases. While this problem is immediately apparent in modem systems analysis involving large software implementations, it is not new. As will be discussed in Chapter 2, related problems involving the theory of graphs were identified long ago. This important theoretical foundation provides a useful vehicle for representing and analyzing complex system structures. While the utility of directed graph based concepts in software tool design has been demonstrated in literature, these tools still lack the capabilities necessary for large system comprehension. This foundation must therefore be expanded with new organizational and visualization constructs necessary to meet this challenge. This dissertation addresses this need by constructing a conceptual model and a set of methods for interactively exploring, organizing, and understanding the structure of complex software systems.

  19. Multidimensional approach to complex system resilience analysis

    International Nuclear Information System (INIS)

    Gama Dessavre, Dante; Ramirez-Marquez, Jose E.; Barker, Kash

    2016-01-01

    Recent works have attempted to formally define a general metric for quantifying resilience for complex systems as a relationship of performance of the systems against time. The technical content in the proposed work introduces a new model that allows, for the first time, to compare the system resilience among systems (or different modifications to a system), by introducing a new dimension to system resilience models, called stress, to mimic the definition of resilience in material science. The applicability and usefulness of the model is shown with a new heat map visualization proposed in this work, and it is applied to a simulated network resilience case to exemplify its potential benefits. - Highlights: • We analyzed two of the main current metrics of resilience. • We create a new model that relates events with the effects they have. • We develop a novel heat map visualization to compare system resilience. • We showed the model and visualization usefulness in a simulated case.

  20. 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.

  1. 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.

  2. 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.

  3. A Multifaceted Mathematical Approach for Complex Systems

    Energy Technology Data Exchange (ETDEWEB)

    Alexander, F.; Anitescu, M.; Bell, J.; Brown, D.; Ferris, M.; Luskin, M.; Mehrotra, S.; Moser, B.; Pinar, A.; Tartakovsky, A.; Willcox, K.; Wright, S.; Zavala, V.

    2012-03-07

    Applied mathematics has an important role to play in developing the tools needed for the analysis, simulation, and optimization of complex problems. These efforts require the development of the mathematical foundations for scientific discovery, engineering design, and risk analysis based on a sound integrated approach for the understanding of complex systems. However, maximizing the impact of applied mathematics on these challenges requires a novel perspective on approaching the mathematical enterprise. Previous reports that have surveyed the DOE's research needs in applied mathematics have played a key role in defining research directions with the community. Although these reports have had significant impact, accurately assessing current research needs requires an evaluation of today's challenges against the backdrop of recent advances in applied mathematics and computing. To address these needs, the DOE Applied Mathematics Program sponsored a Workshop for Mathematics for the Analysis, Simulation and Optimization of Complex Systems on September 13-14, 2011. The workshop had approximately 50 participants from both the national labs and academia. The goal of the workshop was to identify new research areas in applied mathematics that will complement and enhance the existing DOE ASCR Applied Mathematics Program efforts that are needed to address problems associated with complex systems. This report describes recommendations from the workshop and subsequent analysis of the workshop findings by the organizing committee.

  4. Transition Manifolds of Complex Metastable Systems

    Science.gov (United States)

    Bittracher, Andreas; Koltai, Péter; Klus, Stefan; Banisch, Ralf; Dellnitz, Michael; Schütte, Christof

    2018-04-01

    We consider complex dynamical systems showing metastable behavior, but no local separation of fast and slow time scales. The article raises the question of whether such systems exhibit a low-dimensional manifold supporting its effective dynamics. For answering this question, we aim at finding nonlinear coordinates, called reaction coordinates, such that the projection of the dynamics onto these coordinates preserves the dominant time scales of the dynamics. We show that, based on a specific reducibility property, the existence of good low-dimensional reaction coordinates preserving the dominant time scales is guaranteed. Based on this theoretical framework, we develop and test a novel numerical approach for computing good reaction coordinates. The proposed algorithmic approach is fully local and thus not prone to the curse of dimension with respect to the state space of the dynamics. Hence, it is a promising method for data-based model reduction of complex dynamical systems such as molecular dynamics.

  5. Structured analysis and modeling of complex systems

    Science.gov (United States)

    Strome, David R.; Dalrymple, Mathieu A.

    1992-01-01

    The Aircrew Evaluation Sustained Operations Performance (AESOP) facility at Brooks AFB, Texas, combines the realism of an operational environment with the control of a research laboratory. In recent studies we collected extensive data from the Airborne Warning and Control Systems (AWACS) Weapons Directors subjected to high and low workload Defensive Counter Air Scenarios. A critical and complex task in this environment involves committing a friendly fighter against a hostile fighter. Structured Analysis and Design techniques and computer modeling systems were applied to this task as tools for analyzing subject performance and workload. This technology is being transferred to the Man-Systems Division of NASA Johnson Space Center for application to complex mission related tasks, such as manipulating the Shuttle grappler arm.

  6. 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…

  7. 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.

  8. 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

  9. Dependability problems of complex information systems

    CERN Document Server

    Zamojski, Wojciech

    2014-01-01

    This monograph presents original research results on selected problems of dependability in contemporary Complex Information Systems (CIS). The ten chapters are concentrated around the following three aspects: methods for modelling of the system and its components, tasks ? or in more generic and more adequate interpretation, functionalities ? accomplished by the system and conditions for their correct realization in the dynamic operational environment. While the main focus is on theoretical advances and roadmaps for implementations of new technologies, a?much needed forum for sharing of the bes

  10. 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.

  11. 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).

  12. Controlling Complex Systems and Developing Dynamic Technology

    Science.gov (United States)

    Avizienis, Audrius Victor

    In complex systems, control and understanding become intertwined. Following Ilya Prigogine, we define complex systems as having control parameters which mediate transitions between distinct modes of dynamical behavior. From this perspective, determining the nature of control parameters and demonstrating the associated dynamical phase transitions are practically equivalent and fundamental to engaging with complexity. In the first part of this work, a control parameter is determined for a non-equilibrium electrochemical system by studying a transition in the morphology of structures produced by an electroless deposition reaction. Specifically, changing the size of copper posts used as the substrate for growing metallic silver structures by the reduction of Ag+ from solution under diffusion-limited reaction conditions causes a dynamical phase transition in the crystal growth process. For Cu posts with edge lengths on the order of one micron, local forces promoting anisotropic growth predominate, and the reaction produces interconnected networks of Ag nanowires. As the post size is increased above 10 microns, the local interfacial growth reaction dynamics couple with the macroscopic diffusion field, leading to spatially propagating instabilities in the electrochemical potential which induce periodic branching during crystal growth, producing dendritic deposits. This result is interesting both as an example of control and understanding in a complex system, and as a useful combination of top-down lithography with bottom-up electrochemical self-assembly. The second part of this work focuses on the technological development of devices fabricated using this non-equilibrium electrochemical process, towards a goal of integrating a complex network as a dynamic functional component in a neuromorphic computing device. Self-assembled networks of silver nanowires were reacted with sulfur to produce interfacial "atomic switches": silver-silver sulfide junctions, which exhibit

  13. 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.

  14. 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.

  15. Morphodynamics: Ergodic theory of complex systems

    International Nuclear Information System (INIS)

    Fivaz, R.

    1993-01-01

    Morphodynamics is a general theory of stationary complex systems, such as living systems, or mental and social systems; it is based on the thermodynamics of physical systems and built on the same lines. By means of the ergodic hypothesis, thermodynamics is known to connect the particle dynamics to the emergence of order parameters in the equations of state. In the same way, morphodynamics connects order parameters to the emergence of higher level variables; through recurrent applications of the ergodic hypothesis, a hierarchy of equations of state is established which describes a series of successive levels of organization. The equations support a cognitivist interpretation that leads to general principles of evolution; the principles determine the spontaneous and irreversible complexification of systems living in their natural environment. 19 refs

  16. Communication and control for networked complex systems

    CERN Document Server

    Peng, Chen; Han, Qing-Long

    2015-01-01

    This book reports on the latest advances in the study of Networked Control Systems (NCSs). It highlights novel research concepts on NCSs; the analysis and synthesis of NCSs with special attention to their networked character; self- and event-triggered communication schemes for conserving limited network resources; and communication and control co-design for improving the efficiency of NCSs. The book will be of interest to university researchers, control and network engineers, and graduate students in the control engineering, communication and network sciences interested in learning the core principles, methods, algorithms and applications of NCSs.

  17. Relaxation and Diffusion in Complex Systems

    CERN Document Server

    Ngai, K L

    2011-01-01

    Relaxation and Diffusion in Complex Systems comprehensively presents a variety of experimental evidences of universal relaxation and diffusion properties in complex materials and systems. The materials discussed include liquids, glasses, colloids, polymers, rubbers, plastic crystals and aqueous mixtures, as well as carbohydrates, biomolecules, bioprotectants and pharmaceuticals. Due to the abundance of experimental data, emphasis is placed on glass-formers and the glass transition problem, a still unsolved problem in condensed matter physics and chemistry. The evidence for universal properties of relaxation and diffusion dynamics suggests that a fundamental physical law is at work. The origin of the universal properties is traced to the many-body effects of the interaction, rigorous theory of which does not exist at the present time. However, using solutions of simplified models as guides, key quantities have been identified and predictions of the universal properties generated. These predictions from Ngai’...

  18. Symmetry analysis in parametrisation of complex systems

    International Nuclear Information System (INIS)

    Sikora, W; Malinowski, J

    2010-01-01

    The symmetry analysis method based on the theory of group representations is used for description of complex systems and their behavior in this work. The first trial of using the symmetry analysis in modeling of behavior of complex social system is presented. The evacuation of large building scenarios are discussed as transition from chaotic to ordered states, described as movements of individuals according to fields of displacements, calculated correspondingly to given scenario. The symmetry of the evacuation space is taken into account in calculation of displacements field - the displacements related to every point of this space are presented in the coordinate frame in the best way adapted to given symmetry space group, which is the set of basic vectors of irreducible representation of given symmetry group. The results got with using the symmetry consideration are compared with corresponding results calculated under assumption of shortest way to exits (Voronoi assumption).

  19. Symmetry analysis in parametrisation of complex systems

    Energy Technology Data Exchange (ETDEWEB)

    Sikora, W; Malinowski, J, E-mail: sikora@novell.ftj.agh.edu.p [Faculty of Physics and Applied Computer Science, AGH - University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow (Poland)

    2010-03-01

    The symmetry analysis method based on the theory of group representations is used for description of complex systems and their behavior in this work. The first trial of using the symmetry analysis in modeling of behavior of complex social system is presented. The evacuation of large building scenarios are discussed as transition from chaotic to ordered states, described as movements of individuals according to fields of displacements, calculated correspondingly to given scenario. The symmetry of the evacuation space is taken into account in calculation of displacements field - the displacements related to every point of this space are presented in the coordinate frame in the best way adapted to given symmetry space group, which is the set of basic vectors of irreducible representation of given symmetry group. The results got with using the symmetry consideration are compared with corresponding results calculated under assumption of shortest way to exits (Voronoi assumption).

  20. 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

  1. 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…

  2. Analysis of complex systems using neural networks

    International Nuclear Information System (INIS)

    Uhrig, R.E.

    1992-01-01

    The application of neural networks, alone or in conjunction with other advanced technologies (expert systems, fuzzy logic, and/or genetic algorithms), to some of the problems of complex engineering systems has the potential to enhance the safety, reliability, and operability of these systems. Typically, the measured variables from the systems are analog variables that must be sampled and normalized to expected peak values before they are introduced into neural networks. Often data must be processed to put it into a form more acceptable to the neural network (e.g., a fast Fourier transformation of the time-series data to produce a spectral plot of the data). Specific applications described include: (1) Diagnostics: State of the Plant (2) Hybrid System for Transient Identification, (3) Sensor Validation, (4) Plant-Wide Monitoring, (5) Monitoring of Performance and Efficiency, and (6) Analysis of Vibrations. Although specific examples described deal with nuclear power plants or their subsystems, the techniques described can be applied to a wide variety of complex engineering systems

  3. Verification and Examination Management of Complex Systems

    Directory of Open Access Journals (Sweden)

    Stian Ruud

    2014-10-01

    Full Text Available As ship systems become more complex, with an increasing number of safety-critical functions, many interconnected subsystems, tight integration to other systems, and a large amount of potential failure modes, several industry parties have identified the need for improved methods for managing the verification and examination efforts of such complex systems. Such needs are even more prominent now that the marine and offshore industries are targeting more activities and operations in the Arctic environment. In this paper, a set of requirements and a method for verification and examination management are proposed for allocating examination efforts to selected subsystems. The method is based on a definition of a verification risk function for a given system topology and given requirements. The marginal verification risks for the subsystems may then be evaluated, so that examination efforts for the subsystem can be allocated. Two cases of requirements and systems are used to demonstrate the proposed method. The method establishes a systematic relationship between the verification loss, the logic system topology, verification method performance, examination stop criterion, the required examination effort, and a proposed sequence of examinations to reach the examination stop criterion.

  4. 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

  5. FRAM Modelling Complex Socio-technical Systems

    CERN Document Server

    Hollnagel, Erik

    2012-01-01

    There has not yet been a comprehensive method that goes behind 'human error' and beyond the failure concept, and various complicated accidents have accentuated the need for it. The Functional Resonance Analysis Method (FRAM) fulfils that need. This book presents a detailed and tested method that can be used to model how complex and dynamic socio-technical systems work, and understand both why things sometimes go wrong but also why they normally succeed.

  6. Complex Systems and Self-organization Modelling

    CERN Document Server

    Bertelle, Cyrille; Kadri-Dahmani, Hakima

    2009-01-01

    The concern of this book is the use of emergent computing and self-organization modelling within various applications of complex systems. The authors focus their attention both on the innovative concepts and implementations in order to model self-organizations, but also on the relevant applicative domains in which they can be used efficiently. This book is the outcome of a workshop meeting within ESM 2006 (Eurosis), held in Toulouse, France in October 2006.

  7. 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.

  8. 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. 

  9. 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.

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. Complex Engineered Systems: A New Paradigm

    Science.gov (United States)

    Mina, Ali A.; Braha, Dan; Bar-Yam, Yaneer

    Human history is often seen as an inexorable march towards greater complexity — in ideas, artifacts, social, political and economic systems, technology, and in the structure of life itself. While we do not have detailed knowledge of ancient times, it is reasonable to conclude that the average resident of New York City today faces a world of much greater complexity than the average denizen of Carthage or Tikal. A careful consideration of this change, however, suggests that most of it has occurred recently, and has been driven primarily by the emergence of technology as a force in human life. In the 4000 years separating the Indus Valley Civilization from 18th century Europe, human transportation evolved from the bullock cart to the hansom, and the methods of communication used by George Washington did not differ significantly from those used by Alexander or Rameses. The world has moved radically towards greater complexity in the last two centuries. We have moved from buggies and letter couriers to airplanes and the Internet — an increase in capacity, and through its diversity also in complexity, orders of magnitude greater than that accumulated through the rest of human history. In addition to creating iconic artifacts — the airplane, the car, the computer, the television, etc. — this change has had a profound effect on the scope of experience by creating massive, connected and multiultra- level systems — traffic networks, power grids, markets, multinational corporations — that defy analytical understanding and seem to have a life of their own. This is where complexity truly enters our lives.

  15. 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.

  16. Life: An Introduction to Complex Systems Biology

    CERN Document Server

    Kaneko, Kunihiko

    2006-01-01

    What is life? Has molecular biology given us a satisfactory answer to this question? And if not, why, and how to carry on from there? This book examines life not from the reductionist point of view, but rather asks the question: what are the universal properties of living systems and how can one construct from there a phenomenological theory of life that leads naturally to complex processes such as reproductive cellular systems, evolution and differentiation? The presentation has been deliberately kept fairly non-technical so as to address a broad spectrum of students and researchers from the natural sciences and informatics.

  17. Chaos from simple models to complex systems

    CERN Document Server

    Cencini, Massimo; Vulpiani, Angelo

    2010-01-01

    Chaos: from simple models to complex systems aims to guide science and engineering students through chaos and nonlinear dynamics from classical examples to the most recent fields of research. The first part, intended for undergraduate and graduate students, is a gentle and self-contained introduction to the concepts and main tools for the characterization of deterministic chaotic systems, with emphasis to statistical approaches. The second part can be used as a reference by researchers as it focuses on more advanced topics including the characterization of chaos with tools of information theor

  18. 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.

  19. Learning and the Instructional System

    Science.gov (United States)

    Kozma, Robert B.

    1977-01-01

    Faculty members can use information about six components of the learning situation to increase student learning. The nature, function, and interrelationships of the following elements are described: instructor, content, medium, student, evaluation, environment, and implementation. (Editor/LBH)

  20. Reliability Standards of Complex Engineering Systems

    Science.gov (United States)

    Galperin, E. M.; Zayko, V. A.; Gorshkalev, P. A.

    2017-11-01

    Production and manufacture play an important role in today’s modern society. Industrial production is nowadays characterized by increased and complex communications between its parts. The problem of preventing accidents in a large industrial enterprise becomes especially relevant. In these circumstances, the reliability of enterprise functioning is of particular importance. Potential damage caused by an accident at such enterprise may lead to substantial material losses and, in some cases, can even cause a loss of human lives. That is why industrial enterprise functioning reliability is immensely important. In terms of their reliability, industrial facilities (objects) are divided into simple and complex. Simple objects are characterized by only two conditions: operable and non-operable. A complex object exists in more than two conditions. The main characteristic here is the stability of its operation. This paper develops the reliability indicator combining the set theory methodology and a state space method. Both are widely used to analyze dynamically developing probability processes. The research also introduces a set of reliability indicators for complex technical systems.

  1. 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.

  2. 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.

  3. Lighting characteristics of complex fenestration systems

    Energy Technology Data Exchange (ETDEWEB)

    Laouadi, A. [National Research Council of Canada, Ottawa, ON (Canada). Inst. for Research in Construction; Parekh, A. [Natural Resources Canada, Ottawa, ON (Canada). CANMET Energy Technology Centre, Sustainable Buildings and Community Group

    2006-07-01

    Innovations in window technologies have been motivated by the need for energy conservation in buildings. Shading devices and windows with complex glazings such as smart glazings, translucent and transparent insulation, and patterned glass are among the newly developed products. Although complex fenestration systems (CFS) have superior energy performance, a potential glare problem can have a significant effect on the indoor environment as experienced by occupants. A good view and glare-free environment are important for the commercialization of fenestration products. This study addressed the development of new lighting quality indices for the outdoor view, indoor view and window luminance. It was noted that the outdoor view gives a feeling of connection to the outside, an indoor view affects the feelings of privacy, while window luminance indicates the potential risk of discomfort glare. The study applied the new lighting quality indices on a typical complex fenestration system consisting of a double clear window combined with different types of an interior perforated shading screen with opaque and translucent materials. According to simulation results, the light-coloured screen has a significant impact on the outdoor view and window's luminance, and depends largely on the sky conditions. Under clear sky conditions, the luminance of a window with a translucent screen can increase by up to 80 per cent compared to overcast sky conditions. This study aspires to have these indices be part of a fenestration product ratings for indoor environment quality. 19 refs., 1 tab., 3 figs.

  4. Propagating wave correlations in complex systems

    International Nuclear Information System (INIS)

    Creagh, Stephen C; Gradoni, Gabriele; Hartmann, Timo; Tanner, Gregor

    2017-01-01

    We describe a novel approach for computing wave correlation functions inside finite spatial domains driven by complex and statistical sources. By exploiting semiclassical approximations, we provide explicit algorithms to calculate the local mean of these correlation functions in terms of the underlying classical dynamics. By defining appropriate ensemble averages, we show that fluctuations about the mean can be characterised in terms of classical correlations. We give in particular an explicit expression relating fluctuations of diagonal contributions to those of the full wave correlation function. The methods have a wide range of applications both in quantum mechanics and for classical wave problems such as in vibro-acoustics and electromagnetism. We apply the methods here to simple quantum systems, so-called quantum maps, which model the behaviour of generic problems on Poincaré sections. Although low-dimensional, these models exhibit a chaotic classical limit and share common characteristics with wave propagation in complex structures. (paper)

  5. Community characterization of heterogeneous complex systems

    International Nuclear Information System (INIS)

    Tumminello, Michele; Miccichè, Salvatore; Lillo, Fabrizio; Mantegna, Rosario N; Varho, Jan; Piilo, Jyrki

    2011-01-01

    We introduce an analytical statistical method for characterizing the communities detected in heterogeneous complex systems. By proposing a suitable null hypothesis, our method makes use of the hypergeometric distribution to assess the probability that a given property is over-expressed in the elements of a community with respect to all the elements of the investigated set. We apply our method to two specific complex networks, namely a network of world movies and a network of physics preprints. The characterization of the elements and of the communities is done in terms of languages and countries for the movie network and of journals and subject categories for papers. We find that our method is able to characterize clearly the communities identified. Moreover our method works well both for large and for small communities

  6. Complex harmonic modal analysis of rotor systems

    International Nuclear Information System (INIS)

    Han, Dong Ju

    2015-01-01

    Complex harmonic analysis for rotor systems has been proposed from the strict complex modal analysis based upon Floquet theory. In this process the harmonic balance method is adopted, effectively associated with conventional eigenvalue analysis. Also, the harmonic coefficients equivalent to dFRFs in harmonic mode has been derived in practice. The modes are classified from identifying the modal characteristics, and the adaptation of harmonic balance method has been proven by comparing the results of the stability analyses from Floque theory and the eigen analysis. The modal features of each critical speed are depicted in quantitatively and qualitatively by showing that the strengths of each component of the harmonic coefficients are estimated from the order of magnitude analysis according to their harmonic patterns. This effectiveness has been verified by comparing with the numerical solutions

  7. Simulating Complex Systems by Cellular Automata

    CERN Document Server

    Kroc, Jiri; Hoekstra, Alfons G

    2010-01-01

    Deeply rooted in fundamental research in Mathematics and Computer Science, Cellular Automata (CA) are recognized as an intuitive modeling paradigm for Complex Systems. Already very basic CA, with extremely simple micro dynamics such as the Game of Life, show an almost endless display of complex emergent behavior. Conversely, CA can also be designed to produce a desired emergent behavior, using either theoretical methodologies or evolutionary techniques. Meanwhile, beyond the original realm of applications - Physics, Computer Science, and Mathematics – CA have also become work horses in very different disciplines such as epidemiology, immunology, sociology, and finance. In this context of fast and impressive progress, spurred further by the enormous attraction these topics have on students, this book emerges as a welcome overview of the field for its practitioners, as well as a good starting point for detailed study on the graduate and post-graduate level. The book contains three parts, two major parts on th...

  8. Supervisory control for a complex robotic system

    International Nuclear Information System (INIS)

    Miller, D.J.

    1988-01-01

    The Robotic Radiation Survey and Analysis System investigates the use of advanced robotic technology for performing remote radiation surveys on nuclear waste shipping casks. Robotic systems have the potential for reducing personnel exposure to radiation and providing fast reliable throughput at future repository sites. A primary technology issue is the integrated control of distributed specialized hardware through a modular supervisory software system. Automated programming of robot trajectories based upon mathematical models of the cask and robot coupled with sensory feedback enables flexible operation of a commercial gantry robot with the reliability needed to perform autonomous operations in a hazardous environment. Complexity is managed using structured software engineering techniques resulting in the generation of reusable command primitives which contribute to a software parts catalog for a generalized robot programming language

  9. Simulating Complex Window Systems using BSDF Data

    Energy Technology Data Exchange (ETDEWEB)

    Konstantoglou, Maria; Jonsson, Jacob; Lee, Eleanor

    2009-06-22

    Nowadays, virtual models are commonly used to evaluate the performance of conventional window systems. Complex fenestration systems can be difficult to simulate accurately not only because of their geometry but also because of their optical properties that scatter light in an unpredictable manner. Bi-directional Scattering Distribution Functions (BSDF) have recently been developed based on a mixture of measurements and modelling to characterize the optics of such systems. This paper describes the workflow needed to create then use these BSDF datasets in the Radiance lighting simulation software. Limited comparisons are made between visualizations produced using the standard ray-tracing method, the BSDF method, and that taken in a full-scale outdoor mockup.

  10. Nanostructured, complex hydride systems for hydrogen generation

    Directory of Open Access Journals (Sweden)

    Robert A. Varin

    2015-02-01

    Full Text Available Complex hydride systems for hydrogen (H2 generation for supplying fuel cells are being reviewed. In the first group, the hydride systems that are capable of generating H2 through a mechanical dehydrogenation phenomenon at the ambient temperature are discussed. There are few quite diverse systems in this group such as lithium alanate (LiAlH4 with the following additives: nanoiron (n-Fe, lithium amide (LiNH2 (a hydride/hydride system and manganese chloride MnCl2 (a hydride/halide system. Another hydride/hydride system consists of lithium amide (LiNH2 and magnesium hydride (MgH2, and finally, there is a LiBH4-FeCl2 (hydride/halide system. These hydride systems are capable of releasing from ~4 to 7 wt.% H2 at the ambient temperature during a reasonably short duration of ball milling. The second group encompasses systems that generate H2 at slightly elevated temperature (up to 100 °C. In this group lithium alanate (LiAlH4 ball milled with the nano-Fe and nano-TiN/TiC/ZrC additives is a prominent system that can relatively quickly generate up to 7 wt.% H2 at 100 °C. The other hydride is manganese borohydride (Mn(BH42 obtained by mechano-chemical activation synthesis (MCAS. In a ball milled (2LiBH4 + MnCl2 nanocomposite, Mn(BH42 co-existing with LiCl can desorb ~4.5 wt.% H2 at 100 °C within a reasonable duration of dehydrogenation. Practical application aspects of hydride systems for H2 generation/storage are also briefly discussed.

  11. Automated Diagnosis and Control of Complex Systems

    Science.gov (United States)

    Kurien, James; Plaunt, Christian; Cannon, Howard; Shirley, Mark; Taylor, Will; Nayak, P.; Hudson, Benoit; Bachmann, Andrew; Brownston, Lee; Hayden, Sandra; hide

    2007-01-01

    Livingstone2 is a reusable, artificial intelligence (AI) software system designed to assist spacecraft, life support systems, chemical plants, or other complex systems by operating with minimal human supervision, even in the face of hardware failures or unexpected events. The software diagnoses the current state of the spacecraft or other system, and recommends commands or repair actions that will allow the system to continue operation. Livingstone2 is an enhancement of the Livingstone diagnosis system that was flight-tested onboard the Deep Space One spacecraft in 1999. This version tracks multiple diagnostic hypotheses, rather than just a single hypothesis as in the previous version. It is also able to revise diagnostic decisions made in the past when additional observations become available. In such cases, Livingstone might arrive at an incorrect hypothesis. Re-architecting and re-implementing the system in C++ has increased performance. Usability has been improved by creating a set of development tools that is closely integrated with the Livingstone2 engine. In addition to the core diagnosis engine, Livingstone2 includes a compiler that translates diagnostic models written in a Java-like language into Livingstone2's language, and a broad set of graphical tools for model development.

  12. Modular interdependency in complex dynamical systems.

    Science.gov (United States)

    Watson, Richard A; Pollack, Jordan B

    2005-01-01

    Herbert A. Simon's characterization of modularity in dynamical systems describes subsystems as having dynamics that are approximately independent of those of other subsystems (in the short term). This fits with the general intuition that modules must, by definition, be approximately independent. In the evolution of complex systems, such modularity may enable subsystems to be modified and adapted independently of other subsystems, whereas in a nonmodular system, modifications to one part of the system may result in deleterious side effects elsewhere in the system. But this notion of modularity and its effect on evolvability is not well quantified and is rather simplistic. In particular, modularity need not imply that intermodule dependences are weak or unimportant. In dynamical systems this is acknowledged by Simon's suggestion that, in the long term, the dynamical behaviors of subsystems do interact with one another, albeit in an "aggregate" manner--but this kind of intermodule interaction is omitted in models of modularity for evolvability. In this brief discussion we seek to unify notions of modularity in dynamical systems with notions of how modularity affects evolvability. This leads to a quantifiable measure of modularity and a different understanding of its effect on evolvability.

  13. Overcoming complexities: Damage detection using dictionary learning framework

    Science.gov (United States)

    Alguri, K. Supreet; Melville, Joseph; Deemer, Chris; Harley, Joel B.

    2018-04-01

    For in situ damage detection, guided wave structural health monitoring systems have been widely researched due to their ability to evaluate large areas and their ability detect many types of damage. These systems often evaluate structural health by recording initial baseline measurements from a pristine (i.e., undamaged) test structure and then comparing later measurements with that baseline. Yet, it is not always feasible to have a pristine baseline. As an alternative, substituting the baseline with data from a surrogate (nearly identical and pristine) structure is a logical option. While effective in some circumstance, surrogate data is often still a poor substitute for pristine baseline measurements due to minor differences between the structures. To overcome this challenge, we present a dictionary learning framework to adapt surrogate baseline data to better represent an undamaged test structure. We compare the performance of our framework with two other surrogate-based damage detection strategies: (1) using raw surrogate data for comparison and (2) using sparse wavenumber analysis, a precursor to our framework for improving the surrogate data. We apply our framework to guided wave data from two 108 mm by 108 mm aluminum plates. With 20 measurements, we show that our dictionary learning framework achieves a 98% accuracy, raw surrogate data achieves a 92% accuracy, and sparse wavenumber analysis achieves a 57% accuracy.

  14. On sampling and modeling complex systems

    International Nuclear Information System (INIS)

    Marsili, Matteo; Mastromatteo, Iacopo; Roudi, Yasser

    2013-01-01

    The study of complex systems is limited by the fact that only a few variables are accessible for modeling and sampling, which are not necessarily the most relevant ones to explain the system behavior. In addition, empirical data typically undersample the space of possible states. We study a generic framework where a complex system is seen as a system of many interacting degrees of freedom, which are known only in part, that optimize a given function. We show that the underlying distribution with respect to the known variables has the Boltzmann form, with a temperature that depends on the number of unknown variables. In particular, when the influence of the unknown degrees of freedom on the known variables is not too irregular, the temperature decreases as the number of variables increases. This suggests that models can be predictable only when the number of relevant variables is less than a critical threshold. Concerning sampling, we argue that the information that a sample contains on the behavior of the system is quantified by the entropy of the frequency with which different states occur. This allows us to characterize the properties of maximally informative samples: within a simple approximation, the most informative frequency size distributions have power law behavior and Zipf’s law emerges at the crossover between the under sampled regime and the regime where the sample contains enough statistics to make inferences on the behavior of the system. These ideas are illustrated in some applications, showing that they can be used to identify relevant variables or to select the most informative representations of data, e.g. in data clustering. (paper)

  15. 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

  16. 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,

  17. 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

  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. 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…

  20. 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

  1. 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.

  2. Metaheuristics progress in complex systems optimization

    CERN Document Server

    Doerner, Karl F; Greistorfer, Peter; Gutjahr, Walter; Hartl, Richard F; Reimann, Marc

    2007-01-01

    The aim of ""Metaheuristics: Progress in Complex Systems Optimization"" is to provide several different kinds of information: a delineation of general metaheuristics methods, a number of state-of-the-art articles from a variety of well-known classical application areas as well as an outlook to modern computational methods in promising new areas. Therefore, this book may equally serve as a textbook in graduate courses for students, as a reference book for people interested in engineering or social sciences, and as a collection of new and promising avenues for researchers working in this field.

  3. Complex Fluids in Energy Dissipating Systems

    Directory of Open Access Journals (Sweden)

    Francisco J. Galindo-Rosales

    2016-07-01

    Full Text Available The development of engineered systems for energy dissipation (or absorption during impacts or vibrations is an increasing need in our society, mainly for human protection applications, but also for ensuring the right performance of different sort of devices, facilities or installations. In the last decade, new energy dissipating composites based on the use of certain complex fluids have flourished, due to their non-linear relationship between stress and strain rate depending on the flow/field configuration. This manuscript intends to review the different approaches reported in the literature, analyses the fundamental physics behind them and assess their pros and cons from the perspective of their practical applications.

  4. 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.

  5. Statistical Physics of Complex Substitutive Systems

    Science.gov (United States)

    Jin, Qing

    Diffusion processes are central to human interactions. Despite extensive studies that span multiple disciplines, our knowledge is limited to spreading processes in non-substitutive systems. Yet, a considerable number of ideas, products, and behaviors spread by substitution; to adopt a new one, agents must give up an existing one. This captures the spread of scientific constructs--forcing scientists to choose, for example, a deterministic or probabilistic worldview, as well as the adoption of durable items, such as mobile phones, cars, or homes. In this dissertation, I develop a statistical physics framework to describe, quantify, and understand substitutive systems. By empirically exploring three collected high-resolution datasets pertaining to such systems, I build a mechanistic model describing substitutions, which not only analytically predicts the universal macroscopic phenomenon discovered in the collected datasets, but also accurately captures the trajectories of individual items in a complex substitutive system, demonstrating a high degree of regularity and universality in substitutive systems. I also discuss the origins and insights of the parameters in the substitution model and possible generalization form of the mathematical framework. The systematical study of substitutive systems presented in this dissertation could potentially guide the understanding and prediction of all spreading phenomena driven by substitutions, from electric cars to scientific paradigms, and from renewable energy to new healthy habits.

  6. 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…

  7. Recommender Systems in Technology Enhanced Learning

    NARCIS (Netherlands)

    Manouselis, Nikos; Drachsler, Hendrik; Vuorikari, Riina; Hummel, Hans; Koper, Rob

    2010-01-01

    Manouselis, N., Drachsler, H., Vuorikari, R., Hummel, H. G. K., & Koper, R. (2011). Recommender Systems in Technology Enhanced Learning. In P. B. Kantor, F. Ricci, L. Rokach, & B. Shapira (Eds.), Recommender Systems Handbook (pp. 387-415). Berlin: Springer.

  8. 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...

  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. 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

  11. 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.

  12. 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.

  13. Theories and simulations of complex social systems

    CERN Document Server

    Mago, Vijay

    2014-01-01

    Research into social systems is challenging due to their complex nature. Traditional methods of analysis are often difficult to apply effectively as theories evolve over time. This can be due to a lack of appropriate data, or too much uncertainty. It can also be the result of problems which are not yet understood well enough in the general sense so that they can be classified, and an appropriate solution quickly identified. Simulation is one tool that deals well with these challenges, fits in well with the deductive process, and is useful for testing theory. This field is still relatively new, and much of the work is necessarily innovative, although it builds upon a rich and varied foundation. There are a number of existing modelling paradigms being applied to complex social systems research. Additionally, new methods and measures are being devised through the process of conducting research. We expect that readers will enjoy the collection of high quality research works from new and accomplished researchers. ...

  14. Electromagnetic driving units for complex microrobotic systems

    Science.gov (United States)

    Michel, Frank; Ehrfeld, Wolfgang; Berg, Udo; Degen, Reinhard; Schmitz, Felix

    1998-10-01

    Electromagnetic actuators play an important role in macroscopic robotic systems. In combination with motion transformers, like reducing gear units, angular gears or spindle-screw drives, electromagnetic motors in large product lines ensure the rotational or linear motion of robot driving units and grippers while electromagnets drive valves or part conveyors. In this paper micro actuators and miniaturized motion transformers are introduced which allow a similar development in microrobotics. An electromagnetic motor and a planetary gear box, both with a diameter of 1.9 mm, are already commercially available from the cooperation partner of IMM, the company Dr. Fritz Faulhaber GmbH in Schonaich, Germany. In addition, a motor with a diameter of 2.4 mm is in development. The motors successfully drive an angular gear and a belt drive. A linear stage with a motion range of 7 mm and an overall size as small as 5 X 3.5 X 24 mm3 has been realized involving the motor, a stationary spur gear with zero backlash and a spindle-screw drive. By the use of these commercially available elements complex microrobots can be built up cost-efficiently and rapidly. Furthermore, a batch process has been developed to produce the coils of micro actuator arrays using lithographic techniques with SU-8 resin. In applying these components, the modular construction of complex microrobotic systems becomes feasible.

  15. 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.

  16. Intrinsic Uncertainties in Modeling Complex Systems.

    Energy Technology Data Exchange (ETDEWEB)

    Cooper, Curtis S; Bramson, Aaron L.; Ames, Arlo L.

    2014-09-01

    Models are built to understand and predict the behaviors of both natural and artificial systems. Because it is always necessary to abstract away aspects of any non-trivial system being modeled, we know models can potentially leave out important, even critical elements. This reality of the modeling enterprise forces us to consider the prospective impacts of those effects completely left out of a model - either intentionally or unconsidered. Insensitivity to new structure is an indication of diminishing returns. In this work, we represent a hypothetical unknown effect on a validated model as a finite perturba- tion whose amplitude is constrained within a control region. We find robustly that without further constraints, no meaningful bounds can be placed on the amplitude of a perturbation outside of the control region. Thus, forecasting into unsampled regions is a very risky proposition. We also present inherent difficulties with proper time discretization of models and representing in- herently discrete quantities. We point out potentially worrisome uncertainties, arising from math- ematical formulation alone, which modelers can inadvertently introduce into models of complex systems. Acknowledgements This work has been funded under early-career LDRD project #170979, entitled "Quantify- ing Confidence in Complex Systems Models Having Structural Uncertainties", which ran from 04/2013 to 09/2014. We wish to express our gratitude to the many researchers at Sandia who con- tributed ideas to this work, as well as feedback on the manuscript. In particular, we would like to mention George Barr, Alexander Outkin, Walt Beyeler, Eric Vugrin, and Laura Swiler for provid- ing invaluable advice and guidance through the course of the project. We would also like to thank Steven Kleban, Amanda Gonzales, Trevor Manzanares, and Sarah Burwell for their assistance in managing project tasks and resources.

  17. 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.

  18. 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....

  19. 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…

  20. 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

  1. Optimal control of complex atomic quantum systems.

    Science.gov (United States)

    van Frank, S; Bonneau, M; Schmiedmayer, J; Hild, S; Gross, C; Cheneau, M; Bloch, I; Pichler, T; Negretti, A; Calarco, T; Montangero, S

    2016-10-11

    Quantum technologies will ultimately require manipulating many-body quantum systems with high precision. Cold atom experiments represent a stepping stone in that direction: a high degree of control has been achieved on systems of increasing complexity. However, this control is still sub-optimal. In many scenarios, achieving a fast transformation is crucial to fight against decoherence and imperfection effects. Optimal control theory is believed to be the ideal candidate to bridge the gap between early stage proof-of-principle demonstrations and experimental protocols suitable for practical applications. Indeed, it can engineer protocols at the quantum speed limit - the fastest achievable timescale of the transformation. Here, we demonstrate such potential by computing theoretically and verifying experimentally the optimal transformations in two very different interacting systems: the coherent manipulation of motional states of an atomic Bose-Einstein condensate and the crossing of a quantum phase transition in small systems of cold atoms in optical lattices. We also show that such processes are robust with respect to perturbations, including temperature and atom number fluctuations.

  2. Control of multidimensional systems on complex network

    Science.gov (United States)

    Bagnoli, Franco; Battistelli, Giorgio; Chisci, Luigi; Fanelli, Duccio

    2017-01-01

    Multidimensional systems coupled via complex networks are widespread in nature and thus frequently invoked for a large plethora of interesting applications. From ecology to physics, individual entities in mutual interactions are grouped in families, homogeneous in kind. These latter interact selectively, through a sequence of self-consistently regulated steps, whose deeply rooted architecture is stored in the assigned matrix of connections. The asymptotic equilibrium eventually attained by the system, and its associated stability, can be assessed by employing standard nonlinear dynamics tools. For many practical applications, it is however important to externally drive the system towards a desired equilibrium, which is resilient, hence stable, to external perturbations. To this end we here consider a system made up of N interacting populations which evolve according to general rate equations, bearing attributes of universality. One species is added to the pool of interacting families and used as a dynamical controller to induce novel stable equilibria. Use can be made of the root locus method to shape the needed control, in terms of intrinsic reactivity and adopted protocol of injection. The proposed method is tested on both synthetic and real data, thus enabling to demonstrate its robustness and versatility. PMID:28892493

  3. Empirical and theoretical analysis of complex systems

    Science.gov (United States)

    Zhao, Guannan

    This thesis is an interdisciplinary work under the heading of complexity science which focuses on an arguably common "hard" problem across physics, finance and biology [1], to quantify and mimic the macroscopic "emergent phenomenon" in large-scale systems consisting of many interacting "particles" governed by microscopic rules. In contrast to traditional statistical physics, we are interested in systems whose dynamics are subject to feedback, evolution, adaption, openness, etc. Global financial markets, like the stock market and currency market, are ideal candidate systems for such a complexity study: there exists a vast amount of accurate data, which is the aggregate output of many autonomous agents continuously competing with each other. We started by examining the ultrafast "mini flash crash (MFC)" events in the US stock market. An abrupt system-wide composition transition from a mixed human machine phase to a new all-machine phase is uncovered, and a novel theory developed to explain this observation. Then in the study of FX market, we found an unexpected variation in the synchronicity of price changes in different market subsections as a function of the overall trading activity. Several survival models have been tested in analyzing the distribution of waiting times to the next price change. In the region of long waiting-times, the distribution for each currency pair exhibits a power law with exponent in the vicinity of 3.5. By contrast, for short waiting times only, the market activity can be mimicked by the fluctuations emerging from a finite resource competition model containing multiple agents with limited rationality (so called El Farol Model). Switching to the biomedical domain, we present a minimal mathematical model built around a co-evolving resource network and cell population, yielding good agreement with primary tumors in mice experiment and with clinical metastasis data. In the quest to understand contagion phenomena in systems where social group

  4. Complex biological and bio-inspired systems

    Energy Technology Data Exchange (ETDEWEB)

    Ecke, Robert E [Los Alamos National Laboratory

    2009-01-01

    The understanding and characterization ofthe fundamental processes of the function of biological systems underpins many of the important challenges facing American society, from the pathology of infectious disease and the efficacy ofvaccines, to the development of materials that mimic biological functionality and deliver exceptional and novel structural and dynamic properties. These problems are fundamentally complex, involving many interacting components and poorly understood bio-chemical kinetics. We use the basic science of statistical physics, kinetic theory, cellular bio-chemistry, soft-matter physics, and information science to develop cell level models and explore the use ofbiomimetic materials. This project seeks to determine how cell level processes, such as response to mechanical stresses, chemical constituents and related gradients, and other cell signaling mechanisms, integrate and combine to create a functioning organism. The research focuses on the basic physical processes that take place at different levels ofthe biological organism: the basic role of molecular and chemical interactions are investigated, the dynamics of the DNA-molecule and its phylogenetic role are examined and the regulatory networks of complex biochemical processes are modeled. These efforts may lead to early warning algorithms ofpathogen outbreaks, new bio-sensors to detect hazards from pathomic viruses to chemical contaminants. Other potential applications include the development of efficient bio-fuel alternative-energy processes and the exploration ofnovel materials for energy usages. Finally, we use the notion of 'coarse-graining,' which is a method for averaging over less important degrees of freedom to develop computational models to predict cell function and systems-level response to disease, chemical stress, or biological pathomic agents. This project supports Energy Security, Threat Reduction, and the missions of the DOE Office of Science through its efforts to

  5. 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 ...

  6. 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

  7. Optimal sensor configuration for complex systems

    DEFF Research Database (Denmark)

    Sadegh, Payman; Spall, J. C.

    1998-01-01

    . The procedure for sensor configuration is based on the simultaneous perturbation stochastic approximation (SPSA) algorithm. SPSA avoids the need for detailed modeling of the sensor response by simply relying on the observed responses obtained by limited experimentation with test sensor configurations. We......The paper considers the problem of sensor configuration for complex systems with the aim of maximizing the useful information about certain quantities of interest. Our approach involves: 1) definition of an appropriate optimality criterion or performance measure; and 2) description of an efficient...... and practical algorithm for achieving the optimality objective. The criterion for optimal sensor configuration is based on maximizing the overall sensor response while minimizing the correlation among the sensor outputs, so as to minimize the redundant information being provided by the multiple sensors...

  8. Optimal sensor configuration for complex systems

    DEFF Research Database (Denmark)

    Sadegh, Payman; Spall, J. C.

    1998-01-01

    configuration is based on maximizing the overall sensor response while minimizing the correlation among the sensor outputs. The procedure for sensor configuration is based on simultaneous perturbation stochastic approximation (SPSA). SPSA avoids the need for detailed modeling of the sensor response by simply......Considers the problem of sensor configuration for complex systems. Our approach involves definition of an appropriate optimality criterion or performance measure, and description of an efficient and practical algorithm for achieving the optimality objective. The criterion for optimal sensor...... relying on observed responses as obtained by limited experimentation with test sensor configurations. We illustrate the approach with the optimal placement of acoustic sensors for signal detection in structures. This includes both a computer simulation study for an aluminum plate, and real...

  9. Exergy Analysis of Complex Ship Energy Systems

    Directory of Open Access Journals (Sweden)

    Pierre Marty

    2016-04-01

    Full Text Available With multiple primary and secondary energy converters (diesel engines, steam turbines, waste heat recovery (WHR and oil-fired boilers, etc. and extensive energy networks (steam, cooling water, exhaust gases, etc., ships may be considered as complex energy systems. Understanding and optimizing such systems requires advanced holistic energy modeling. This modeling can be done in two ways: The simpler approach focuses on energy flows, and has already been tested, approved and presented; a new, more complicated approach, focusing on energy quality, i.e., exergy, is presented in this paper. Exergy analysis has rarely been applied to ships, and, as a general rule, the shipping industry is not familiar with this tool. This paper tries to fill this gap. We start by giving a short reminder of what exergy is and describe the principles of exergy modeling to explain what kind of results should be expected from such an analysis. We then apply these principles to the analysis of a large two-stroke diesel engine with its cooling and exhaust systems. Simulation results are then presented along with the exergy analysis. Finally, we propose solutions for energy and exergy saving which could be applied to marine engines and ships in general.

  10. 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…

  11. 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.

  12. Process Systems Engineering Education: Learning by Research

    Science.gov (United States)

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

    2009-01-01

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

  13. Learning and Organizational Effectiveness: A Systems Perspective

    Science.gov (United States)

    Andreadis, Nicholas

    2009-01-01

    The challenge for leaders today is to create and develop the capability of their organization. Leaders must perceive and manage their organization as a dynamic, open system where learning is the core competence underlying innovation, growth, and sustainability. Creating a culture of learning is the first work of leadership. This article presents a…

  14. A Distributed Intelligent E-Learning System

    Science.gov (United States)

    Kristensen, Terje

    2016-01-01

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

  15. 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

  16. 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.

  17. 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)

  18. 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.

  19. 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.

  20. 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...

  1. Circadian modulation of complex learning in diurnal and nocturnal Aplysia

    OpenAIRE

    Lyons, Lisa C.; Rawashdeh, Oliver; Katzoff, Ayelet; Susswein, Abraham J.; Eskin, Arnold

    2005-01-01

    Understanding modulation of memory, as well as the mechanisms underlying memory formation, has become a key issue in neuroscience research. Previously, we found that the formation of long-term, but not short-term, memory for a nonassociative form of learning, sensitization, was modulated by the circadian clock in the diurnal Aplysia californica. To define the scope of circadian modulation of memory, we examined an associative operant learning paradigm, learning that food is inedible (LFI). Si...

  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. 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.

  4. System dynamics in complex psychiatric treatment organizations.

    Science.gov (United States)

    Rosenheck, R

    1988-05-01

    One of the major challenges facing contemporary psychiatry is the coordination of diverse services through organizational integration. With increasing frequency, psychiatric treatment takes place in complex treatment systems composed of multiple inpatient and outpatient programs. Particularly in public health care systems serving the chronically ill, contemporary practice demands a broad spectrum of programs, often geographically dispersed, that include crisis intervention teams, day treatment programs, substance abuse units, social rehabilitation programs and halfway houses (Bachrach 1983; Turner and TenHoor 1978). Individualized treatment planning often requires that a particular patient participate in two or more specialized programs either simultaneously or in a specified sequence. As a consequence of this specialization, treatment fragmentation has emerged as a significant clinical problem, and continuity of care has been highlighted as a valuable but elusive ingredient of optimal treatment. This paper will describe the dynamic interactions that result when several such programs are united under a common organizational roof. Using a large VA Psychiatry Service as an example, I will outline the hierarchical structure characteristic of such an organization, as well as the persistent pulls toward both integration and fragmentation that influence its operation.

  5. Indirect learning control for nonlinear dynamical systems

    Science.gov (United States)

    Ryu, Yeong Soon; Longman, Richard W.

    1993-01-01

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

  6. systemic approach to teaching and learning chemistry

    African Journals Online (AJOL)

    unesco

    2National Core Group in Chemistry, H.E.J Research Institute of Chemistry,. University of ... innovative way of teaching and learning through systemic approach (SATL) has been .... available to do useful work in a thermodynamic process.

  7. Metric for Calculation of System Complexity based on its Connections

    Directory of Open Access Journals (Sweden)

    João Ricardo Braga de Paiva

    2017-02-01

    Full Text Available This paper proposes a methodology based on system connections to calculate its complexity. Two study cases are proposed: the dining Chinese philosophers’ problem and the distribution center. Both studies are modeled using the theory of Discrete Event Systems and simulations in different contexts were performed in order to measure their complexities. The obtained results present i the static complexity as a limiting factor for the dynamic complexity, ii the lowest cost in terms of complexity for each unit of measure of the system performance and iii the output sensitivity to the input parameters. The associated complexity and performance measures aggregate knowledge about the system.

  8. 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…

  9. 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

  10. 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.

  11. 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…

  12. 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)

  13. 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...

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

    Science.gov (United States)

    Deegan, Robin

    2015-01-01

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

  15. A Holistic Approach to Scoring in Complex Mobile Learning Scenarios

    Science.gov (United States)

    Gebbe, Marcel; Teine, Matthias; Beutner, Marc

    2016-01-01

    Interactive dialogues are key elements for designing authentic and motivating learning situations, and in combination with learning analysis they provide educators and users with the opportunity to track information related to professional competences, but mind-sets as well. This paper offers exemplary insights into the project NetEnquiry that is…

  16. 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…

  17. 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.

  18. 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.

  19. Integrated Programme Control Systems: Lessons Learned

    Energy Technology Data Exchange (ETDEWEB)

    Brown, C. W. [Babcock International Group PLC (formerly UKAEA Ltd) B21 Forss, Thurso, Caithness, Scotland (United Kingdom)

    2013-08-15

    Dounreay was the UK's centre of fast reactor research and development from 1955 until 1994 and is now Scotland's largest nuclear clean up and demolition project. After four decades of research, Dounreay is now a site of construction, demolition and waste management, designed to return the site to as near as practicable to its original condition. Dounreay has a turnover in the region of Pounds 150 million a year and employs approximately 900 people. It subcontracts work to 50 or so companies in the supply chain and this provides employment for a similar number of people. The plan for decommissioning the site anticipates all redundant buildings will be cleared in the short term. The target date to achieve interim end state by 2039 is being reviewed in light of Government funding constraints, and will be subject to change through the NDA led site management competition. In the longer term, controls will be put in place on the use of contaminated land until 2300. In supporting the planning, management and organisational aspects for this complex decommissioning programme an integrated programme controls system has been developed and deployed. This consists of a combination of commercial and bespoke tools integrated to support all aspects of programme management, namely scope, schedule, cost, estimating and risk in order to provide baseline and performance management data based upon the application of earned value management principles. Through system evolution and lessons learned, the main benefits of this approach are management data consistency, rapid communication of live information, and increased granularity of data providing summary and detailed reports which identify performance trends that lead to corrective actions. The challenges of such approach are effective use of the information to realise positive changes, balancing the annual system support and development costs against the business needs, and maximising system performance. (author)

  20. Systems Thinking, Lean Production and Action Learning

    Science.gov (United States)

    Seddon, John; Caulkin, Simon

    2007-01-01

    Systems thinking underpins "lean" management and is best understood through action-learning as the ideas are counter-intuitive. The Toyota Production System is just that--a system; the failure to appreciate that starting-place and the advocacy of "tools" leads many to fail to grasp what is, without doubt, a significant…

  1. 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.

  2. 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.

  3. System for circular and complex tomography

    International Nuclear Information System (INIS)

    Hellstrom, M.J.

    1979-01-01

    This invention discloses a system for conducting circular as well as complex tomographic procedures utilizing apparatus which has no mechanical linkage between the X-ray source and the X-ray receptor. The path of travel of the X-ray source both circularly and linearly is sensed by electromagnetic radiation and more particularly by light radiation which is generated by a laser. The linear travel is sensed by means of reflected laser radiation directed to the X-ray source and fed to an interferometer. The circular travel, on the other hand, is sensed by means of a laser gyroscope also receiving light radiation from a laser. Optical energy sensing means is thus used to generate command signals which are coupled to respective drive motors which act to rotate and when desirable, translate the X-ray receptor so that its motion follows the motion, both orbital and linear, of the X-ray source for performing any desired type of tomographic procedure

  4. Modeling Complex Chemical Systems: Problems and Solutions

    Science.gov (United States)

    van Dijk, Jan

    2016-09-01

    Non-equilibrium plasmas in complex gas mixtures are at the heart of numerous contemporary technologies. They typically contain dozens to hundreds of species, involved in hundreds to thousands of reactions. Chemists and physicists have always been interested in what are now called chemical reduction techniques (CRT's). The idea of such CRT's is that they reduce the number of species that need to be considered explicitly without compromising the validity of the model. This is usually achieved on the basis of an analysis of the reaction time scales of the system under study, which identifies species that are in partial equilibrium after a given time span. The first such CRT that has been widely used in plasma physics was developed in the 1960's and resulted in the concept of effective ionization and recombination rates. It was later generalized to systems in which multiple levels are effected by transport. In recent years there has been a renewed interest in tools for chemical reduction and reaction pathway analysis. An example of the latter is the PumpKin tool. Another trend is that techniques that have previously been developed in other fields of science are adapted as to be able to handle the plasma state of matter. Examples are the Intrinsic Low Dimension Manifold (ILDM) method and its derivatives, which originate from combustion engineering, and the general-purpose Principle Component Analysis (PCA) technique. In this contribution we will provide an overview of the most common reduction techniques, then critically assess the pros and cons of the methods that have gained most popularity in recent years. Examples will be provided for plasmas in argon and carbon dioxide.

  5. 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.

  6. 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…

  7. Cosmic Ray Neutron Sensing in Complex Systems

    Science.gov (United States)

    Piussi, L. M.; Tomelleri, E.; Tonon, G.; Bertoldi, G.; Mejia Aguilar, A.; Monsorno, R.; Zebisch, M.

    2017-12-01

    Soil moisture is a key variable in environmental monitoring and modelling: being located at the soil-atmosphere boundary, it is a driving force for water, energy and carbon fluxes. Nevertheless its importance, soil moisture observations lack of long time-series at high acquisition frequency in spatial meso-scale resolutions: traditional measurements deliver either long time series with high measurement frequency at spatial point scale or large scale and low frequency acquisitions. The Cosmic Ray Neutron Sensing (CRNS) technique fills this gap because it supplies information from a footprint of 240m of diameter and 15 to 83 cm of depth at a temporal resolution varying between 15 minutes and 24 hours. In addition, being a passive sensing technique, it is non-invasive. For these reasons, CRNS is gaining more and more attention from the scientific community. Nevertheless, the application of this technique in complex systems is still an open issue: where different Hydrogen pools are present and where their distributions vary appreciably with space and time, the traditional calibration method shows some limits. In order to obtain a better understanding of the data and to compare them with remote sensing products and spatially distributed traditional measurements (i.e. Wireless Sensors Network), the complexity of the surrounding environment has to be taken into account. In the current work we assessed the effects of spatial-temporal variability of soil moisture within the footprint, in a steep, heterogeneous mountain grassland area. Measurement were performed with a Cosmic Ray Neutron Probe (CRNP) and a mobile Wireless Sensors Network. We performed an in-deep sensitivity analysis of the effects of varying distributions of soil moisture on the calibration of the CRNP and our preliminary results show how the footprint shape varies depending on these dynamics. The results are then compared with remote sensing data (Sentinel 1 and 2). The current work is an assessment of

  8. 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

  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. Lie and Noether symmetries of systems of complex ordinary ...

    Indian Academy of Sciences (India)

    2014-07-02

    Jul 2, 2014 ... Abstract. The Lie and Noether point symmetry analyses of a kth-order system of m complex ordi- nary differential equations (ODEs) with m dependent variables are performed. The decomposition of complex symmetries of the given system of complex ODEs yields Lie- and Noether-like opera- tors.

  11. 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.

  12. 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

  13. 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.

  14. The Joint Lessons Learned System and Interoperability

    Science.gov (United States)

    1989-06-02

    Learned: 1988-1989 As mentioned in the introduction to this chaoter, the Organizacion of the JcinC Chiefs cf Staff .OJCS) ueren significant transformatioi...Organization and Functions Manual . Washington, D.C.: HQDA, Office of the Deputy Chief 0f Staff for Operations and Plans, June 1984. ’..S. Army. Concept...U.S. Department of Defense. Joint Universal Lessons Learned System (JULLS) User’s Manual . Orlando, Florida: University of Central Florida, Institute

  15. 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…

  16. Integrated Visualisation and Description of Complex Systems

    National Research Council Canada - National Science Library

    Goodburn, D

    1999-01-01

    ... on system topographies and feature overlays. System information from the domain's information space is filtered and integrated into a Composite Systems Model that provides a basis for consistency and integration between all system views...

  17. Learning in Complex Environments: The Effects of Background Speech on Early Word Learning

    Science.gov (United States)

    McMillan, Brianna T. M.; Saffran, Jenny R.

    2016-01-01

    Although most studies of language learning take place in quiet laboratory settings, everyday language learning occurs under noisy conditions. The current research investigated the effects of background speech on word learning. Both younger (22- to 24-month-olds; n = 40) and older (28- to 30-month-olds; n = 40) toddlers successfully learned novel…

  18. Chaotic systems in complex phase space

    Indian Academy of Sciences (India)

    figure 1, a qualitative change in the complex behaviour is quite evident in ..... [19] S Fishman, Quantum Localization in Quantum Chaos, Proc. of the International ... of the 44th Scottish Universities Summer School in Physics, Stirling, August ...

  19. Studies of complexity in fluid systems

    Energy Technology Data Exchange (ETDEWEB)

    Nagel, Sidney R.

    2000-06-12

    This is the final report of Grant DE-FG02-92ER25119, ''Studies of Complexity in Fluids'', we have investigated turbulence, flow in granular materials, singularities in evolution of fluid surfaces and selective withdrawal fluid flows. We have studied numerical methods for dealing with complex phenomena, and done simulations on the formation of river networks. We have also studied contact-line deposition that occurs in a drying drop.

  20. Membrane Tethering Complexes in the Endosomal System

    OpenAIRE

    Spang, Anne

    2016-01-01

    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 class C core vacuole/endosome tethering (CORVET) complex, while fusion of late endosomes with lysosomes depends on the homotypic fusion and vacuole protein sorting (HOPS) complex. Recycling through the trans-Golgi network (TGN) and to the plasma membrane is...

  1. How Instructional Systems Will Manage Learning

    Science.gov (United States)

    Flanagan, John C.

    1970-01-01

    Discusses trends toward the systems approach in education including the development of effective instructional systems in government and industry; the introduction of teaching machines, programed learning, and computer- assisted instruction; and the increase in both the amount and sophistication of educational research and development. (JF)

  2. An Architecture for Open Learning Management Systems

    NARCIS (Netherlands)

    Avgeriou, Paris; Retalis, Simos; Skordalakis, Manolis

    2003-01-01

    There exists an urgent demand on defining architectures for Learning Management Systems, so that high-level frameworks for understanding these systems can be discovered, and quality attributes like portability, interoperability, reusability and modifiability can be achieved. In this paper we propose

  3. 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.

  4. 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

  5. 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,…

  6. 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…

  7. Transitioning from learning healthcare systems to learning health care communities.

    Science.gov (United States)

    Mullins, C Daniel; Wingate, La'Marcus T; Edwards, Hillary A; Tofade, Toyin; Wutoh, Anthony

    2018-02-26

    The learning healthcare system (LHS) model framework has three core, foundational components. These include an infrastructure for health-related data capture, care improvement targets and a supportive policy environment. Despite progress in advancing and implementing LHS approaches, low levels of participation from patients and the public have hampered the transformational potential of the LHS model. An enhanced vision of a community-engaged LHS redesign would focus on the provision of health care from the patient and community perspective to complement the healthcare system as the entity that provides the environment for care. Addressing the LHS framework implementation challenges and utilizing community levers are requisite components of a learning health care community model, version two of the LHS archetype.

  8. 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

  9. 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.

  10. Multistage Spectral Relaxation Method for Solving the Hyperchaotic Complex Systems

    Directory of Open Access Journals (Sweden)

    Hassan Saberi Nik

    2014-01-01

    Full Text Available We present a pseudospectral method application for solving the hyperchaotic complex systems. The proposed method, called the multistage spectral relaxation method (MSRM is based on a technique of extending Gauss-Seidel type relaxation ideas to systems of nonlinear differential equations and using the Chebyshev pseudospectral methods to solve the resulting system on a sequence of multiple intervals. In this new application, the MSRM is used to solve famous hyperchaotic complex systems such as hyperchaotic complex Lorenz system and the complex permanent magnet synchronous motor. We compare this approach to the Runge-Kutta based ode45 solver to show that the MSRM gives accurate results.

  11. Applications of Nonlinear Dynamics Model and Design of Complex Systems

    CERN Document Server

    In, Visarath; Palacios, Antonio

    2009-01-01

    This edited book is aimed at interdisciplinary, device-oriented, applications of nonlinear science theory and methods in complex systems. In particular, applications directed to nonlinear phenomena with space and time characteristics. Examples include: complex networks of magnetic sensor systems, coupled nano-mechanical oscillators, nano-detectors, microscale devices, stochastic resonance in multi-dimensional chaotic systems, biosensors, and stochastic signal quantization. "applications of nonlinear dynamics: model and design of complex systems" brings together the work of scientists and engineers that are applying ideas and methods from nonlinear dynamics to design and fabricate complex systems.

  12. Establishing a methodology to develop complex sociotechnical systems

    CSIR Research Space (South Africa)

    Oosthuizen, R

    2013-02-01

    Full Text Available Many modern management systems, such as military command and control, tend to be large and highly interconnected sociotechnical systems operating in a complex environment. Successful development, assessment and implementation of these systems...

  13. 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 ...

  14. 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.

  15. 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.

  16. Satlc model lesson for teaching and learning complex ...

    African Journals Online (AJOL)

    Environmental chemistry is one of the disciplines of Science. For the goal of the deep learning of the subject, it is indispensable to present perception and models of chemical behaviour explicitly. This can be accomplished by giving careful consideration to the development of concepts such that newer approaches are given ...

  17. Implications of Complexity and Chaos Theories for Organizations that Learn

    Science.gov (United States)

    Smith, Peter A. C.

    2003-01-01

    In 1996 Hubert Saint-Onge and Smith published an article ("The evolutionary organization: avoiding a Titanic fate", in The Learning Organization, Vol. 3 No. 4), based on their experience at the Canadian Imperial Bank of Commerce (CIBC). It was established at CIBC that change could be successfully facilitated through blended application…

  18. 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.

  19. 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

  20. 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

  1. 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

  2. Smart modeling and simulation for complex systems practice and theory

    CERN Document Server

    Ren, Fenghui; Zhang, Minjie; Ito, Takayuki; Tang, Xijin

    2015-01-01

    This book aims to provide a description of these new Artificial Intelligence technologies and approaches to the modeling and simulation of complex systems, as well as an overview of the latest scientific efforts in this field such as the platforms and/or the software tools for smart modeling and simulating complex systems. These tasks are difficult to accomplish using traditional computational approaches due to the complex relationships of components and distributed features of resources, as well as the dynamic work environments. In order to effectively model the complex systems, intelligent technologies such as multi-agent systems and smart grids are employed to model and simulate the complex systems in the areas of ecosystem, social and economic organization, web-based grid service, transportation systems, power systems and evacuation systems.

  3. Integration of the immune system: a complex adaptive supersystem

    Science.gov (United States)

    Crisman, Mark V.

    2001-10-01

    Immunity to pathogenic organisms is a complex process involving interacting factors within the immune system including circulating cells, tissues and soluble chemical mediators. Both the efficiency and adaptive responses of the immune system in a dynamic, often hostile, environment are essential for maintaining our health and homeostasis. This paper will present a brief review of one of nature's most elegant, complex adaptive systems.

  4. Complex network synchronization of chaotic systems with delay coupling

    International Nuclear Information System (INIS)

    Theesar, S. Jeeva Sathya; Ratnavelu, K.

    2014-01-01

    The study of complex networks enables us to understand the collective behavior of the interconnected elements and provides vast real time applications from biology to laser dynamics. In this paper, synchronization of complex network of chaotic systems has been studied. Every identical node in the complex network is assumed to be in Lur’e system form. In particular, delayed coupling has been assumed along with identical sector bounded nonlinear systems which are interconnected over network topology

  5. 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…

  6. A complex systems methodology to transition management

    NARCIS (Netherlands)

    Alkemade, F.; Frenken, K.; Hekkert, M.P.; Schwoon, M.

    2009-01-01

    There is a general sense of urgency that major technological transitions are required for sustainable development. Such transitions are best perceived as involving multiple transition steps along a transition path. Due to the path dependent and irreversible nature of innovation in complex

  7. Outcomes-Based Authentic Learning, Portfolio Assessment, and a Systems Approach to ‘Complex Problem-Solving’: Related Pillars for Enhancing the Innovative Role of PBL in Future Higher Education

    Directory of Open Access Journals (Sweden)

    Cameron Richards

    2015-06-01

    Full Text Available The challenge of better reconciling individual and collective aspects of innovative problem-solving can be productively addressed to enhance the role of PBL as a key focus of the creative process in future higher education. This should involve ‘active learning’ approaches supported by related processes of teaching, assessment and curriculum. As Biggs & Tan (2011 have suggested, an integrated or systemic approach is needed for the most effective practice of outcomes-based education also especially relevant for addressing relatively simple as well as more complex problems. Such a model will be discussed in relation to the practical example of a Masters subject conceived with interdisciplinary implications, applications, and transferability: ‘sustainable policy studies in science, technology and innovation’. Different modes of PBL might be encouraged in terms of the authentic kinds of ‘complex problem-solving’ issues and challenges which increasingly confront an interdependent and changing world. PBL can be further optimized when projects or cases also involve contexts and examples of research and inquiry. However, perhaps the most crucial pillar is a model of portfolio assessment for linking and encouraging as well as distinguishing individual contributions to collaborative projects and activities.

  8. 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…

  9. 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.

  10. Adaptive control for a class of nonlinear complex dynamical systems with uncertain complex parameters and perturbations.

    Directory of Open Access Journals (Sweden)

    Jian Liu

    Full Text Available In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic systems (CVCSs in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.

  11. Adaptive control for a class of nonlinear complex dynamical systems with uncertain complex parameters and perturbations.

    Science.gov (United States)

    Liu, Jian; Liu, Kexin; Liu, Shutang

    2017-01-01

    In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.

  12. 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

  13. Classical and quantum mechanics of complex Hamiltonian systems ...

    Indian Academy of Sciences (India)

    Vol. 73, No. 2. — journal of. August 2009 physics pp. 287–297. Classical and quantum mechanics of complex. Hamiltonian systems: An extended complex phase space ... 1Department of Physics, Ramjas College (University Enclave), University of Delhi,. Delhi 110 ... 1.1 Motivation behind the study of complex Hamiltonians.

  14. From Hamiltonian chaos to complex systems a nonlinear physics approach

    CERN Document Server

    Leonetti, Marc

    2013-01-01

    From Hamiltonian Chaos to Complex Systems: A Nonlinear Physics Approach collects contributions on recent developments in non-linear dynamics and statistical physics with an emphasis on complex systems. This book provides a wide range of state-of-the-art research in these fields. The unifying aspect of this book is a demonstration of how similar tools coming from dynamical systems, nonlinear physics, and statistical dynamics can lead to a large panorama of  research in various fields of physics and beyond, most notably with the perspective of application in complex systems. This book also: Illustrates the broad research influence of tools coming from dynamical systems, nonlinear physics, and statistical dynamics Adopts a pedagogic approach to facilitate understanding by non-specialists and students Presents applications in complex systems Includes 150 illustrations From Hamiltonian Chaos to Complex Systems: A Nonlinear Physics Approach is an ideal book for graduate students and researchers working in applied...

  15. Exploring Complex Engineering Learning Over Time with Epistemic Network Analysis

    OpenAIRE

    Svarovsky, Gina Navoa

    2011-01-01

    Recently, K-12 engineering education has received increased attention as a pathway to building stronger foundations in math andscience and introducing young people to the profession. However, the National Academy of Engineering found that many K-12engineering programs focus heavily on engineering design and science and math learning while minimizing the development ofengineering habits of mind. This narrowly-focused engineering activity can leave young people – and in particular, girls – with...

  16. Complexity, flow, and antifragile healthcare systems: implications for nurse executives.

    Science.gov (United States)

    Clancy, Thomas R

    2015-04-01

    As systems evolve over time, their natural tendency is to become increasingly more complex. Studies in the field of complex systems have generated new perspectives on the application of management strategies in health systems. Much of this research appears as a natural extension of the cross-disciplinary field of systems theory. In this article, I further discuss the concept of fragility, its impact on system behavior, and ways to reduce it.

  17. Multimodal Learning Analytics and Education Data Mining: Using Computational Technologies to Measure Complex Learning Tasks

    Science.gov (United States)

    Blikstein, Paulo; Worsley, Marcelo

    2016-01-01

    New high-frequency multimodal data collection technologies and machine learning analysis techniques could offer new insights into learning, especially when students have the opportunity to generate unique, personalized artifacts, such as computer programs, robots, and solutions engineering challenges. To date most of the work on learning analytics…

  18. 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…

  19. Oxalate complexation in dissolved carbide systems

    International Nuclear Information System (INIS)

    Choppin, G.R.; Bokelund, H.; Valkiers, S.

    1983-01-01

    It has been shown that the oxalic acid produced in the dissolution of mixed uranium, plutonium carbides in nitric acid can account for the problems of incomplete uranium and plutonium extraction on the Purex process. Moreover, it was demonstrated that other identified products such as benzene polycarboxylic acids are either too insoluble or insufficiently complexing to be of concern. The stability constants for oxalate complexing of UO 2 +2 and Pu +4 ions (as UO 2 (C 2 O 4 ), Pu(C 2 O 4 ) 2+ and Pu(C 2 O 4 ) 2 , respectively) were measured in nitrate solutions of 4.0 molar ionic strength (0-4 M HNO 3 ) by extraction of these species with TBP. (orig.)

  20. 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...

  1. Challenges in the analysis of complex systems: introduction and overview

    Science.gov (United States)

    Hastings, Harold M.; Davidsen, Jörn; Leung, Henry

    2017-12-01

    One of the main challenges of modern physics is to provide a systematic understanding of systems far from equilibrium exhibiting emergent behavior. Prominent examples of such complex systems include, but are not limited to the cardiac electrical system, the brain, the power grid, social systems, material failure and earthquakes, and the climate system. Due to the technological advances over the last decade, the amount of observations and data available to characterize complex systems and their dynamics, as well as the capability to process that data, has increased substantially. The present issue discusses a cross section of the current research on complex systems, with a focus on novel experimental and data-driven approaches to complex systems that provide the necessary platform to model the behavior of such systems.

  2. An Instructional and Collaborative Learning System with Content Recommendation

    Science.gov (United States)

    Zheng, Xiang-wei; Ma, Hong-wei; Li, Yan

    2013-01-01

    With the rapid development of Internet, e-learning has become a new teaching and learning mode. However, lots of e-learning systems deployed on Internet are just electronic learning materials with very limited interactivity and diagnostic capability. This paper presents an integrated e-learning environment named iCLSR. Firstly, iCLSR provides an…

  3. Learning through the taste system

    Directory of Open Access Journals (Sweden)

    Thomas R. Scott

    2011-11-01

    Full Text Available Taste is the final arbiter of which chemicals from the environment will be admitted to the body. The action of swallowing a substance leads to a physiological consequence of which the taste system should be informed. Accordingly, taste neurons in the central nervous system are closely allied with those that receive input from the viscera so as to monitor the impact of a recently ingested substance. There is behavioral, anatomical, electrophysiological, gene expression, and neurochemical evidence that the consequences of ingestion influence subsequent food selection through development of either a conditioned taste aversion (if illness ensues or a conditioned taste preference (if satiety. This ongoing communication between taste and the viscera permits the animal to tailor its taste system to its individual needs over a lifetime.

  4. Information Systems in University Learning

    Directory of Open Access Journals (Sweden)

    Gheorghe SABAU

    2010-01-01

    Full Text Available The authors of this article are going to bring into light the significance, the place and the role of information systems in the university education process. At the same time they define the objectives and the target group of the subject named Economic Information Systems and state the competence gained by students by studying this subject. Special attention is given to the curriculum to be taught to students and to a suggestive enumeration of a series of economic applications that can be themes for laboratory practice and for students’ dissertation (graduation thesis.

  5. 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

  6. 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.

  7. satlc model lesson for teaching and learning complex environmental ...

    African Journals Online (AJOL)

    IICBA01

    Greenhouse-gas-induced temperature increase is one of the main reasons of ... The relation between altitude and density is a fairly complex exponential that has been ... in to ocean by which water becomes acidic also when water is heated it ...

  8. Toward a Learning Science for Complex Crowdsourcing Tasks

    Science.gov (United States)

    Doroudi, Shayan; Kamar, Ece; Brunskill, Emma; Horvitz, Eric

    2016-01-01

    We explore how crowdworkers can be trained to tackle complex crowdsourcing tasks. We are particularly interested in training novice workers to perform well on solving tasks in situations where the space of strategies is large and workers need to discover and try different strategies to be successful. In a first experiment, we perform a comparison…

  9. Play, learn, explore: grasping complexity through gaming and ...

    African Journals Online (AJOL)

    Increased demand for agricultural products, the aspirations of rural communities and a growing recognition of planetary boundaries outline the complex trade-offs resource users are facing on a daily basis. Management problems typically involve multiple stakeholders with diverse and often conflicting worldviews, needs ...

  10. Cueing Complex Animations: Does Direction of Attention Foster Learning Processes?

    Science.gov (United States)

    Lowe, Richard; Boucheix, Jean-Michel

    2011-01-01

    The time course of learners' processing of a complex animation was studied using a dynamic diagram of a piano mechanism. Over successive repetitions of the material, two forms of cueing (standard colour cueing and anti-cueing) were administered either before or during the animated segment of the presentation. An uncued group and two other control…

  11. 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.

  12. SUPERCOMPUTER SIMULATION OF CRITICAL PHENOMENA IN COMPLEX SOCIAL SYSTEMS

    Directory of Open Access Journals (Sweden)

    Petrus M.A. Sloot

    2014-09-01

    Full Text Available The paper describes a problem of computer simulation of critical phenomena in complex social systems on a petascale computing systems in frames of complex networks approach. The three-layer system of nested models of complex networks is proposed including aggregated analytical model to identify critical phenomena, detailed model of individualized network dynamics and model to adjust a topological structure of a complex network. The scalable parallel algorithm covering all layers of complex networks simulation is proposed. Performance of the algorithm is studied on different supercomputing systems. The issues of software and information infrastructure of complex networks simulation are discussed including organization of distributed calculations, crawling the data in social networks and results visualization. The applications of developed methods and technologies are considered including simulation of criminal networks disruption, fast rumors spreading in social networks, evolution of financial networks and epidemics spreading.

  13. Implementing the learning health care system.

    NARCIS (Netherlands)

    Verheij, R.; Barten, D.J.; Hek, K.; Nielen, M.; Prins, M.; Zwaanswijk, M.; Bakker, D. de

    2014-01-01

    Background: As computerisation of primary care facilities is rapidly increasing, a wealth of data is created in routinely recorded electronic health records (EHRs). This data can be used to create a true learning health care system, in which routinely available data are processed and analysed in

  14. Distance Learning Delivery Systems: Instructional Options.

    Science.gov (United States)

    Steele, Ray L.

    1993-01-01

    Discusses the availability of satellite and cable programing to provide distance education opportunities in school districts. Various delivery systems are described, including telephones with speakers, personal computers, and satellite dishes; and a sidebar provides a directory of distance learning opportunities, including telecommunications…

  15. 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.

  16. 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.

  17. 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.

  18. Statistical analysis of complex systems with nonclassical invariant measures

    KAUST Repository

    Fratalocchi, Andrea

    2011-01-01

    I investigate the problem of finding a statistical description of a complex many-body system whose invariant measure cannot be constructed stemming from classical thermodynamics ensembles. By taking solitons as a reference system and by employing a

  19. 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...

  20. Size and complexity in model financial systems

    Science.gov (United States)

    Arinaminpathy, Nimalan; Kapadia, Sujit; May, Robert M.

    2012-01-01

    The global financial crisis has precipitated an increasing appreciation of the need for a systemic perspective toward financial stability. For example: What role do large banks play in systemic risk? How should capital adequacy standards recognize this role? How is stability shaped by concentration and diversification in the financial system? We explore these questions using a deliberately simplified, dynamic model of a banking system that combines three different channels for direct transmission of contagion from one bank to another: liquidity hoarding, asset price contagion, and the propagation of defaults via counterparty credit risk. Importantly, we also introduce a mechanism for capturing how swings in “confidence” in the system may contribute to instability. Our results highlight that the importance of relatively large, well-connected banks in system stability scales more than proportionately with their size: the impact of their collapse arises not only from their connectivity, but also from their effect on confidence in the system. Imposing tougher capital requirements on larger banks than smaller ones can thus enhance the resilience of the system. Moreover, these effects are more pronounced in more concentrated systems, and continue to apply, even when allowing for potential diversification benefits that may be realized by larger banks. We discuss some tentative implications for policy, as well as conceptual analogies in ecosystem stability and in the control of infectious diseases. PMID:23091020

  1. Narrowing the gap between network models and real complex systems

    OpenAIRE

    Viamontes Esquivel, Alcides

    2014-01-01

    Simple network models that focus only on graph topology or, at best, basic interactions are often insufficient to capture all the aspects of a dynamic complex system. In this thesis, I explore those limitations, and some concrete methods of resolving them. I argue that, in order to succeed at interpreting and influencing complex systems, we need to take into account  slightly more complex parts, interactions and information flows in our models.This thesis supports that affirmation with five a...

  2. Leadership Behaviors of Management for Complex Adaptive Systems

    Science.gov (United States)

    2010-04-01

    Leadership Behaviors of Management for Complex Adaptive Systems Systems and Software Technology Conference April 2010 Dr. Suzette S. Johnson...2010 2. REPORT TYPE 3. DATES COVERED 00-00-2010 to 00-00-2010 4. TITLE AND SUBTITLE Leadership Behaviors of Management for Complex Adaptive...as they evolve – Control is dispersed and decentralized – Simple rules and governance used to direct behavior • Complexity Leadership Theory – Built on

  3. Learning System Center App Controller

    CERN Document Server

    Naeem, Nasir

    2015-01-01

    This book is intended for IT professionals working with Hyper-V, Azure cloud, VMM, and private cloud technologies who are looking for a quick way to get up and running with System Center 2012 R2 App Controller. To get the most out of this book, you should be familiar with Microsoft Hyper-V technology. Knowledge of Virtual Machine Manager is helpful but not mandatory.

  4. Learning to teach secondary mathematics using an online learning system

    Science.gov (United States)

    Cavanagh, Michael; Mitchelmore, Michael

    2011-12-01

    We report the results of a classroom study of three secondary mathematics teachers who had no prior experience teaching with technology as they began to use an online mathematics learning system in their lessons. We gave the teachers only basic instruction on how to operate the system and then observed them intensively over four school terms as they taught using it. We documented changes in the teachers' Pedagogical Technology Knowledge and subsequently classified their various roles as technology bystanders, adopters, adaptors and innovators. Results show that all teachers made some progress toward using the system in more sophisticated ways, but the improvements were not uniform across the teachers. We suggest possible reasons to explain the variation and discuss some implications for teacher professional development.

  5. Complex Systems: Science for the 21st Century

    Energy Technology Data Exchange (ETDEWEB)

    Shank, Charles V. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Awschalom, David [Univ. of California, Santa Barbara, CA (United States); Bawendi, Moungi [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Frechet, Jean [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Murphy, Donald [Lucent Technologies (United States); Stupp, Sam [Northwestern Univ., Evanston, IL (United States); Wolynes, Peter [Univ. of Illinois, Urbana, IL (United States)

    1999-03-06

    The workshop was designed to help define new scientific directions related to complex systems in order to create new understanding about the nano world and complicated, multicomponent structures. Five emerging themes regarding complexity were covered: Collective Phenomena; Materials by Design; Functional Systems; Nature's Mastery; and New Tools.

  6. Application of Complex Adaptive Systems in Portfolio Management

    Science.gov (United States)

    Su, Zheyuan

    2017-01-01

    Simulation-based methods are becoming a promising research tool in financial markets. A general Complex Adaptive System can be tailored to different application scenarios. Based on the current research, we built two models that would benefit portfolio management by utilizing Complex Adaptive Systems (CAS) in Agent-based Modeling (ABM) approach.…

  7. Common cause failure analysis methodology for complex systems

    International Nuclear Information System (INIS)

    Wagner, D.P.; Cate, C.L.; Fussell, J.B.

    1977-01-01

    Common cause failure analysis, also called common mode failure analysis, is an integral part of a complex system reliability analysis. This paper extends existing methods of computer aided common cause failure analysis by allowing analysis of the complex systems often encountered in practice. The methods presented here aid in identifying potential common cause failures and also address quantitative common cause failure analysis

  8. Diagnostics of the vibrations of complex rotor systems

    Science.gov (United States)

    Yugraytis, I. Y.; Ragulskis, K. M.; Ionushas, R. A.; Karuzhene, I. P.

    1973-01-01

    The parameters of the imbalance of a complex rotor system, having n parallel rotors and having six degrees of freedom, can be determined from the parameters of the vibrations of two appropriate degrees of freedom. This considerably simplifies diagnostics of the vibrations of complex rotor systems.

  9. Complex, Dynamic Systems: A New Transdisciplinary Theme for Applied Linguistics?

    Science.gov (United States)

    Larsen-Freeman, Diane

    2012-01-01

    In this plenary address, I suggest that Complexity Theory has the potential to contribute a transdisciplinary theme to applied linguistics. Transdisciplinary themes supersede disciplines and spur new kinds of creative activity (Halliday 2001 [1990]). Investigating complex systems requires researchers to pay attention to system dynamics. Since…

  10. What is complex in the complex world? Niklas Luhmann and the theory of social systems

    Directory of Open Access Journals (Sweden)

    Clarissa Eckert Baeta Neves

    Full Text Available This paper discusses Niklas Luhmann's understanding of complexity, its function in the theory and the different ways of its use. It starts with the paradigmatic change that occurred in the field of general Science, with the rupture of the Newtonian model. In the 20th century, the paradigm of order, symmetry, regularity, regulation of the intellect to things, collapses.Based on new formulations of Physics, Chemistry, etc., a new universe is built on bases radically opposed to those of modern Science.Chaos, the procedural irreversibility, indeterminism, the observer and the complexity are rehabilitated.This new conceptual context served as substratum to Niklas Luhmann's theoretical reflection.With his Theory of Social Systems, he proposes the reduction of the world's complexity.Social systems have the function of reducing complexity because of their difference in relation to the environment.On the other hand, the reduction of complexity also creates its own complexity. Luhmann defines complexity as the moment when it is not possible anymore for each element to relate at any moment with all the others. Complexity forces the selection, what means contingency and risk. Luhmann expands the concept of complexity when he introduces the figure of the observer and the distinction of complexity as a unit of a multiplicity. He also deals with the limit of relations in connection, the time factor, the self-reference of operations and the representation of complexity in the form of sense. To conclude, the paper discusses the complexity in the system of science, the way it reduces internal and external complexity, in accordance in its own operative basis.

  11. Principles of e-learning systems engineering

    CERN Document Server

    Gilbert, Lester

    2008-01-01

    The book integrates the principles of software engineering with the principles of educational theory, and applies them to the problems of e-learning development, thus establishing the discipline of E-learning systems engineering. For the first time, these principles are collected and organised into the coherent framework that this book provides. Both newcomers to and established practitioners in the field are provided with integrated and grounded advice on theory and practice. The book presents strong practical and theoretical frameworks for the design and development of technology-based mater

  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. 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…

  14. 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...

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. Nonlinear and Complex Dynamics in Real Systems

    OpenAIRE

    William Barnett; Apostolos Serletis; Demitre Serletis

    2005-01-01

    This paper was produced for the El-Naschie Symposium on Nonlinear Dynamics in Shanghai in December 2005. In this paper we provide a review of the literature with respect to fluctuations in real systems and chaos. In doing so, we contrast the order and organization hypothesis of real systems with nonlinear chaotic dynamics and discuss some techniques used in distinguishing between stochastic and deterministic behavior. Moreover, we look at the issue of where and when the ideas of chaos could p...

  1. Optimal interdependence enhances robustness of complex systems

    OpenAIRE

    Singh, R. K.; Sinha, Sitabhra

    2017-01-01

    While interdependent systems have usually been associated with increased fragility, we show that strengthening the interdependence between dynamical processes on different networks can make them more robust. By coupling the dynamics of networks that in isolation exhibit catastrophic collapse with extinction of nodal activity, we demonstrate system-wide persistence of activity for an optimal range of interdependence between the networks. This is related to the appearance of attractors of the g...

  2. Top event prevention in complex systems

    International Nuclear Information System (INIS)

    Youngblood, R.W.; Worrell, R.B.

    1995-01-01

    A key step in formulating a regulatory basis for licensing complex and potentially hazardous facilities is identification of a collection of design elements that is necessary and sufficient to achieve the desired level of protection of the public, the workers, and the environment. Here, such a collection of design elements will be called a ''prevention set.'' At the design stage, identifying a prevention set helps to determine what elements to include in the final design. Separately, a prevention-set argument could be used to limit the scope of regulatory oversight to a subset of design elements. This step can be taken during initial review of a design, or later as part of an effort to justify relief from regulatory requirements that are burdensome but provide little risk reduction. This paper presents a systematic approach to the problem of optimally choosing a prevention set

  3. 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)

  4. 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)

  5. On the sample complexity of learning for networks of spiking neurons with nonlinear synaptic interactions.

    Science.gov (United States)

    Schmitt, Michael

    2004-09-01

    We study networks of spiking neurons that use the timing of pulses to encode information. Nonlinear interactions model the spatial groupings of synapses on the neural dendrites and describe the computations performed at local branches. Within a theoretical framework of learning we analyze the question of how many training examples these networks must receive to be able to generalize well. Bounds for this sample complexity of learning can be obtained in terms of a combinatorial parameter known as the pseudodimension. This dimension characterizes the computational richness of a neural network and is given in terms of the number of network parameters. Two types of feedforward architectures are considered: constant-depth networks and networks of unconstrained depth. We derive asymptotically tight bounds for each of these network types. Constant depth networks are shown to have an almost linear pseudodimension, whereas the pseudodimension of general networks is quadratic. Networks of spiking neurons that use temporal coding are becoming increasingly more important in practical tasks such as computer vision, speech recognition, and motor control. The question of how well these networks generalize from a given set of training examples is a central issue for their successful application as adaptive systems. The results show that, although coding and computation in these networks is quite different and in many cases more powerful, their generalization capabilities are at least as good as those of traditional neural network models.

  6. Task complexity and maximal isometric strength gains through motor learning

    Science.gov (United States)

    McGuire, Jessica; Green, Lara A.; Gabriel, David A.

    2014-01-01

    Abstract This study compared the effects of a simple versus complex contraction pattern on the acquisition, retention, and transfer of maximal isometric strength gains and reductions in force variability. A control group (N = 12) performed simple isometric contractions of the wrist flexors. An experimental group (N = 12) performed complex proprioceptive neuromuscular facilitation (PNF) contractions consisting of maximal isometric wrist extension immediately reversing force direction to wrist flexion within a single trial. Ten contractions were completed on three consecutive days with a retention and transfer test 2‐weeks later. For the retention test, the groups performed their assigned contraction pattern followed by a transfer test that consisted of the other contraction pattern for a cross‐over design. Both groups exhibited comparable increases in strength (20.2%, P < 0.01) and reductions in mean torque variability (26.2%, P < 0.01), which were retained and transferred. There was a decrease in the coactivation ratio (antagonist/agonist muscle activity) for both groups, which was retained and transferred (35.2%, P < 0.01). The experimental group exhibited a linear decrease in variability of the torque‐ and sEMG‐time curves, indicating transfer to the simple contraction pattern (P < 0.01). The control group underwent a decrease in variability of the torque‐ and sEMG‐time curves from the first day of training to retention, but participants returned to baseline levels during the transfer condition (P < 0.01). However, the difference between torque RMS error versus the variability in torque‐ and sEMG‐time curves suggests the demands of the complex task were transferred, but could not be achieved in a reproducible way. PMID:25428951

  7. 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 ...

  8. 5th International Conference on Complex Systems Design & Management

    CERN Document Server

    Krob, Daniel; Morel, Gérard; Roussel, Jean-Claude

    2015-01-01

    This book contains all refereed papers that were accepted to the fifth edition of the « Complex Systems Design & Management » (CSD&M 2014) international conference which took place in Paris (France) on the November 12-14, 2014. 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 (aeronautic & aerospace, transportation & systems, defense & security, electronics & robotics, energy & environment, health & welfare services, software & 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 2014 conference is organized under the guidance of the CESAMES non-profit organization, addres...

  9. 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...

  10. Grasping the Dynamic Complexity of Team Learning: An Integrative Model for Effective Team Learning in Organisations

    Science.gov (United States)

    Decuyper, Stefan; Dochy, Filip; Van den Bossche, Piet

    2010-01-01

    In this article we present an integrative model of team learning. Literature shows that effective team learning requires the establishment of a dialogical space amongst team members, in which communicative behaviours such as "sharing", "co-construction" and "constructive conflict" are balanced. However, finding this balance is not enough.…

  11. Employees' and Managers' Accounts of Interactive Workplace Learning: A Grounded Theory of "Complex Integrative Learning"

    Science.gov (United States)

    Armson, Genevieve; Whiteley, Alma

    2010-01-01

    Purpose: The purpose of this paper is to investigate employees' and managers' accounts of interactive learning and what might encourage or inhibit emergent learning. Design/methodology/approach: The approach taken was a constructivist/social constructivist ontology, interpretive epistemology and qualitative methodology, using grounded theory…

  12. Hybrid Techniques for Optimizing Complex Systems

    Science.gov (United States)

    2009-12-01

    relay placement problem, we modeled the network as a mechanical system with springs and a viscous damper ⎯a widely used approach for solving optimization...fundamental mathematical tools in many branches of physics such as fluid and solid mechanics, and general relativity [108]. More recently, several

  13. Dynamical systems examples of complex behaviour

    CERN Document Server

    Jost, Jürgen

    2005-01-01

    Our aim is to introduce, explain, and discuss the fundamental problems, ideas, concepts, results, and methods of the theory of dynamical systems and to show how they can be used in speci?c examples. We do not intend to give a comprehensive overview of the present state of research in the theory of dynamical systems, nor a detailed historical account of its development. We try to explain the important results, often neglecting technical re?nements 1 and, usually, we do not provide proofs. One of the basic questions in studying dynamical systems, i.e. systems that evolve in time, is the construction of invariants that allow us to classify qualitative types of dynamical evolution, to distinguish between qualitatively di?erent dynamics, and to studytransitions between di?erent types. Itis also important to ?nd out when a certain dynamic behavior is stable under small perturbations, as well as to understand the various scenarios of instability. Finally, an essential aspect of a dynamic evolution is the transformat...

  14. A system for learning statistical motion patterns.

    Science.gov (United States)

    Hu, Weiming; Xiao, Xuejuan; Fu, Zhouyu; Xie, Dan; Tan, Tieniu; Maybank, Steve

    2006-09-01

    Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy K-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction.

  15. An Alternative Front End Analysis Strategy for Complex Systems

    Science.gov (United States)

    2014-12-01

    missile ( ABM ) system . Patriot is employed in the field through a battalion echelon organizational structure. The line battery is the basic building...Research Report 1981 An Alternative Front End Analysis Strategy for Complex Systems M. Glenn Cobb U.S. Army Research Institute...NUMBER W5J9CQ11D0003 An Alternative Front End Analysis Strategy for Complex Systems 5b. PROGRAM ELEMENT NUMBER 633007 6

  16. Some overdetermined systems of complex partial differential equations

    International Nuclear Information System (INIS)

    Le Hung Son.

    1990-01-01

    In this paper we extend some properties of analytic functions on several complex variables to solutions of overdetermined systems of complex partial differential equations. It is proved that many global properties of analytic functions are true for solutions of the Vekua system in special cases. The relation between analytic functions and solutions of quasi-linear systems is discussed in the paper. (author). 8 refs

  17. Mathematical Models to Determine Stable Behavior of Complex Systems

    Science.gov (United States)

    Sumin, V. I.; Dushkin, A. V.; Smolentseva, T. E.

    2018-05-01

    The paper analyzes a possibility to predict functioning of a complex dynamic system with a significant amount of circulating information and a large number of random factors impacting its functioning. Functioning of the complex dynamic system is described as a chaotic state, self-organized criticality and bifurcation. This problem may be resolved by modeling such systems as dynamic ones, without applying stochastic models and taking into account strange attractors.

  18. 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.

  19. 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.

  20. Synchronizing and controlling hyperchaos in complex Lorentz-Haken systems

    Energy Technology Data Exchange (ETDEWEB)

    Jinqing, Fang [Academia Sinica, Beijing, BJ (China). Inst. of Atomic Energy

    1995-03-01

    Synchronizing hyperchaos is realized by the drive-response relationship in the complex Lorentz-Haken system and its higher-order cascading systems for the first time. Controlling hyperchaos is achieved by the intermittent proportional feedback to all of the drive (master) system variables. The complex Lorentz-Haken system describes the detuned single-mode laser and is taken as a typical example of hyperchaotic synchronization to clarify our ideas and results. The ideas and concepts could be extended to some nonlinear dynamical systems and have prospects for potential applications, for example. to laser, electronics, plasma, cryptography, communication, chemical and biological systems and so on. (8 figs., 2 tabs.).

  1. Synchronizing and controlling hyperchaos in complex Lorentz-Haken systems

    International Nuclear Information System (INIS)

    Fang Jinqing

    1995-03-01

    Synchronizing hyperchaos is realized by the drive-response relationship in the complex Lorentz-Haken system and its higher-order cascading systems for the first time. Controlling hyperchaos is achieved by the intermittent proportional feedback to all of the drive (master) system variables. The complex Lorentz-Haken system describes the detuned single-mode laser and is taken as a typical example of hyperchaotic synchronization to clarify our ideas and results. The ideas and concepts could be extended to some nonlinear dynamical systems and have prospects for potential applications, for example. to laser, electronics, plasma, cryptography, communication, chemical and biological systems and so on. (8 figs., 2 tabs.)

  2. Fourth International Conference on Complex Systems Design & Management

    CERN Document Server

    Boulanger, Frédéric; Krob, Daniel; Marchal, Clotilde

    2014-01-01

    This book contains all refereed papers that were accepted to the fourth edition of the « Complex Systems Design & Management » (CSD&M 2013) international conference which took place in Paris (France) from December 4-6, 2013. 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 2013 conference is organized under the guidance of the CESAMES non-profit organization

  3. 7th International Conference on Complex Systems Design & Management

    CERN Document Server

    Goubault, Eric; Krob, Daniel; Stephan, François

    2017-01-01

    This book contains all refereed papers that were accepted to the seventh edition of the international conference « Complex Systems Design & Management Paris» (CSD&M Paris 2016) which took place in Paris (France) on the December 13-14, 2016 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 (aeronautic & aerospace, defense & security, electronics & robotics, energy & environment, healthcare & welfare services, software & e-services, transportation), scientific & technical topics (systems fundamentals, systems architecture & engineering, systems metrics & quality, system is modeling tools) and system types (artificial ecosystems, embedded systems, software & information systems, systems of systems, transportation systems). The CSD&M Paris 2016 conference is organized under the guidance of the CESAMES non-profit orga...

  4. 6th International Conference on Complex Systems Design & Management

    CERN Document Server

    Bocquet, Jean-Claude; Bonjour, Eric; Krob, Daniel

    2016-01-01

    This book contains all refereed papers that were accepted to the sixth edition of the « Complex Systems Design & Management Paris » (CSD&M Paris 2015) international conference which took place in Paris (France) on November 23-25, 2015. 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 (aeronautics & aerospace, defense & security, electronics & robotics, energy & environment, health & welfare, software & e-services, transportation), scientific & technical topics (systems fundamentals, systems architecture & engineering, systems metrics & quality, systems modeling tools) and systems types (artificial ecosystems, embedded systems, software & information systems, systems of systems, transportation systems). The CSD&M Paris 2015 conference is organized under the guidance of the CESAMES non-profit organization, address...

  5. Theoretical optical spectroscopy of complex systems

    International Nuclear Information System (INIS)

    Conte, A. Mosca; Violante, C.; Missori, M.; Bechstedt, F.; Teodonio, L.; Ippoliti, E.; Carloni, P.; Guidoni, L.; Pulci, O.

    2013-01-01

    Highlights: ► We review some theoretical condensed matter ab initio spectroscopic computational techniques. ► We show several applications ranging from 0 to 3 dimensional systems. ► For each system studied, we show which kind of information it is possible to obtain by performing these calculations. -- Abstract: We review here some of the most reliable and efficient computational theoretical ab initio techniques for the prediction of optical and electronic spectroscopic properties and show some important applications to molecules, surfaces, and solids. We investigate the role of the solvent in the optical absorption spectrum of indole molecule. We study the excited-state properties of a photo-active minimal model molecule for the retinal of rhodopsin, responsible for vision mechanism in animals. We then show a study about spectroscopic properties of Si(1 1 1) surface. Finally we simulate a bulk system: paper, that is mainly made of cellulose, a pseudo-crystalline material representing 40% of annual biomass production in the Earth

  6. Theoretical optical spectroscopy of complex systems

    Energy Technology Data Exchange (ETDEWEB)

    Conte, A. Mosca, E-mail: adriano.mosca.conte@roma2.infn.it [MIFP, NAST, ETSF,CNR INFM-SMC, Universitá di Roma Tor Vergata, Via della Ricerca Scientifica 1, Roma (Italy); Violante, C., E-mail: claudia.violante@roma2.infn.it [MIFP, NAST, ETSF,CNR INFM-SMC, Universitá di Roma Tor Vergata, Via della Ricerca Scientifica 1, Roma (Italy); Missori, M., E-mail: mauro.missori@isc.cnr.it [Istituto dei Sistemi Complessi, Consiglio Nazionale delle Ricerche, Via Salaria Km 29.300, 00016 Monterotondo Scalo (Rome) (Italy); Bechstedt, F., E-mail: bech@ifto.physik.uni-jena.de [Institut fur Festkorpertheorie und -optik, Friedrich-Schiller-Universitat, Max-Wien-Platz 1, 07743 Jena (Germany); Teodonio, L. [MIFP, NAST, ETSF,CNR INFM-SMC, Universitá di Roma Tor Vergata, Via della Ricerca Scientifica 1, Roma (Italy); Istituto centrale per il restauro e la conservazione del patrimonio archivistico e librario (IC-RCPAL), Italian Minister for Cultural Heritage, Via Milano 76, 00184 Rome (Italy); Ippoliti, E.; Carloni, P. [German Research School for Simulation Sciences, Julich (Germany); Guidoni, L., E-mail: leonardo.guidoni@univaq.it [Università degli Studi di L’Aquila, Dipartimento di Chimica e Materiali, Via Campo di Pile, 67100 L’Aquila (Italy); Pulci, O., E-mail: olivia.pulci@roma2.infn.it [MIFP, NAST, ETSF,CNR INFM-SMC, Universitá di Roma Tor Vergata, Via della Ricerca Scientifica 1, Roma (Italy)

    2013-08-15

    Highlights: ► We review some theoretical condensed matter ab initio spectroscopic computational techniques. ► We show several applications ranging from 0 to 3 dimensional systems. ► For each system studied, we show which kind of information it is possible to obtain by performing these calculations. -- Abstract: We review here some of the most reliable and efficient computational theoretical ab initio techniques for the prediction of optical and electronic spectroscopic properties and show some important applications to molecules, surfaces, and solids. We investigate the role of the solvent in the optical absorption spectrum of indole molecule. We study the excited-state properties of a photo-active minimal model molecule for the retinal of rhodopsin, responsible for vision mechanism in animals. We then show a study about spectroscopic properties of Si(1 1 1) surface. Finally we simulate a bulk system: paper, that is mainly made of cellulose, a pseudo-crystalline material representing 40% of annual biomass production in the Earth.

  7. Critical care nursing: Embedded complex systems.

    Science.gov (United States)

    Trinier, Ruth; Liske, Lori; Nenadovic, Vera

    2016-01-01

    Variability in parameters such as heart rate, respiratory rate and blood pressure defines healthy physiology and the ability of the person to adequately respond to stressors. Critically ill patients have lost this variability and require highly specialized nursing care to support life and monitor changes in condition. The critical care environment is a dynamic system through which information flows. The critical care unit is typically designed as a tree structure with generally one attending physician and multiple nurses and allied health care professionals. Information flow through the system allows for identification of deteriorating patient status and timely interventionfor rescue from further deleterious effects. Nurses provide the majority of direct patient care in the critical care setting in 2:1, 1:1 or 1:2 nurse-to-patient ratios. The bedside nurse-critically ill patient relationship represents the primary, real-time feedback loop of information exchange, monitoring and treatment. Variables that enhance information flow through this loop and support timely nursing intervention can improve patient outcomes, while barriers can lead to errors and adverse events. Examining patient information flow in the critical care environment from a dynamic systems perspective provides insights into how nurses deliver effective patient care and prevent adverse events.

  8. Computer aided operation of complex systems

    International Nuclear Information System (INIS)

    Goodstein, L.P.

    1985-09-01

    Advanced technology is having the effect that industrial systems are becoming more highly automated and do not rely on human intervention for the control of normally planned and/or predicted situations. Thus the importance of the operator has shifted from being a manual controller to becoming more of a systems manager and supervisory controller. At the same time, the use of advanced information technology in the control room and its potential impact on human-machine capabilities places additional demands on the designer. This report deals with work carried out to describe the plant-operator relationship in order to systematize the design and evaluation of suitable information systems in the control room. This design process starts with the control requirements from the plant and transforms them into corresponding sets of decision-making tasks with appropriate allocation of responsibilities between computer and operator. To further effectivize this cooperation, appropriate information display and accession are identified. The conceptual work has been supported by experimental studies on a small-scale simulator. (author)

  9. Integrated Modeling of Complex Optomechanical Systems

    Science.gov (United States)

    Andersen, Torben; Enmark, Anita

    2011-09-01

    Mathematical modeling and performance simulation are playing an increasing role in large, high-technology projects. There are two reasons; first, projects are now larger than they were before, and the high cost calls for detailed performance prediction before construction. Second, in particular for space-related designs, it is often difficult to test systems under realistic conditions beforehand, and mathematical modeling is then needed to verify in advance that a system will work as planned. Computers have become much more powerful, permitting calculations that were not possible before. At the same time mathematical tools have been further developed and found acceptance in the community. Particular progress has been made in the fields of structural mechanics, optics and control engineering, where new methods have gained importance over the last few decades. Also, methods for combining optical, structural and control system models into global models have found widespread use. Such combined models are usually called integrated models and were the subject of this symposium. The objective was to bring together people working in the fields of groundbased optical telescopes, ground-based radio telescopes, and space telescopes. We succeeded in doing so and had 39 interesting presentations and many fruitful discussions during coffee and lunch breaks and social arrangements. We are grateful that so many top ranked specialists found their way to Kiruna and we believe that these proceedings will prove valuable during much future work.

  10. Tailoring Enterprise Systems Engineering Policy for Project Scale and Complexity

    Science.gov (United States)

    Cox, Renee I.; Thomas, L. Dale

    2014-01-01

    Space systems are characterized by varying degrees of scale and complexity. Accordingly, cost-effective implementation of systems engineering also varies depending on scale and complexity. Recognizing that systems engineering and integration happen everywhere and at all levels of a given system and that the life cycle is an integrated process necessary to mature a design, the National Aeronautic and Space Administration's (NASA's) Marshall Space Flight Center (MSFC) has developed a suite of customized implementation approaches based on project scale and complexity. While it may be argued that a top-level system engineering process is common to and indeed desirable across an enterprise for all space systems, implementation of that top-level process and the associated products developed as a result differ from system to system. The implementation approaches used for developing a scientific instrument necessarily differ from those used for a space station. .

  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. 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

  13. 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.

  14. 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

  15. 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

  16. Complex fluids in biological systems experiment, theory, and computation

    CERN Document Server

    2015-01-01

    This book serves as an introduction to the continuum mechanics and mathematical modeling of complex fluids in living systems. The form and function of living systems are intimately tied to the nature of surrounding fluid environments, which commonly exhibit nonlinear and history dependent responses to forces and displacements. With ever-increasing capabilities in the visualization and manipulation of biological systems, research on the fundamental phenomena, models, measurements, and analysis of complex fluids has taken a number of exciting directions. In this book, many of the world’s foremost experts explore key topics such as: Macro- and micro-rheological techniques for measuring the material properties of complex biofluids and the subtleties of data interpretation Experimental observations and rheology of complex biological materials, including mucus, cell membranes, the cytoskeleton, and blood The motility of microorganisms in complex fluids and the dynamics of active suspensions Challenges and solut...

  17. 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.

  18. Extensible Adaptive System for STEM Learning

    Science.gov (United States)

    2013-07-16

    Copyright 2013 Raytheon BBN Technologies Corp. All Rights Reserved ONR STEM Grand Challenge Extensible Adaptive System for STEM Learning ...Contract # N00014-12-C-0535 Raytheon BBN Technologies Corp. (BBN) Reference # 14217 In partial fulfillment of contract deliverable item # A001...Quarterly Progress Report #2 April 7, 2013 –July 6, 2013 Submitted July 16, 2013 BBN Technical POC: John Makhoul Raytheon BBN Technologies

  19. Outcomes-Based Authentic Learning, Portfolio Assessment, and a Systems Approach to "Complex Problem-Solving": Related Pillars for Enhancing the Innovative Role of PBL in Future Higher Education

    Science.gov (United States)

    Richards, Cameron

    2015-01-01

    The challenge of better reconciling individual and collective aspects of innovative problem-solving can be productively addressed to enhance the role of PBL as a key focus of the creative process in future higher education. This should involve "active learning" approaches supported by related processes of teaching, assessment and…

  20. Learning Preference Models for Autonomous Mobile Robots in Complex Domains

    Science.gov (United States)

    2010-12-01

    templates,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 167–172, 2009. 128, 153 [254] J. Z. Kolter , P. Abbeel, and A. Y...92] Knepper, R. A. [246] Koller, D. [234] Kolter , J. Z. [254] Konolige, K. [148] Koutsougeras, C. [32] Krotkov, E. [96, 123, 178] Kuffner, J. [252