WorldWideScience

Sample records for learning theoretic method

  1. Theoretical Foundations of Active Learning

    Science.gov (United States)

    2009-05-01

    I study the informational complexity of active learning in a statistical learning theory framework. Specifically, I derive bounds on the rates of...convergence achievable by active learning , under various noise models and under general conditions on the hypothesis class. I also study the theoretical...advantages of active learning over passive learning, and develop procedures for transforming passive learning algorithms into active learning algorithms

  2. Qualitative methods in theoretical physics

    CERN Document Server

    Maslov, Dmitrii

    2018-01-01

    This book comprises a set of tools which allow researchers and students to arrive at a qualitatively correct answer without undertaking lengthy calculations. In general, Qualitative Methods in Theoretical Physics is about combining approximate mathematical methods with fundamental principles of physics: conservation laws and symmetries. Readers will learn how to simplify problems, how to estimate results, and how to apply symmetry arguments and conduct dimensional analysis. A comprehensive problem set is included. The book will appeal to a wide range of students and researchers.

  3. Machine learning a theoretical approach

    CERN Document Server

    Natarajan, Balas K

    2014-01-01

    This is the first comprehensive introduction to computational learning theory. The author's uniform presentation of fundamental results and their applications offers AI researchers a theoretical perspective on the problems they study. The book presents tools for the analysis of probabilistic models of learning, tools that crisply classify what is and is not efficiently learnable. After a general introduction to Valiant's PAC paradigm and the important notion of the Vapnik-Chervonenkis dimension, the author explores specific topics such as finite automata and neural networks. The presentation

  4. Unorthodox theoretical methods

    Energy Technology Data Exchange (ETDEWEB)

    Nedd, Sean [Iowa State Univ., Ames, IA (United States)

    2012-01-01

    The use of the ReaxFF force field to correlate with NMR mobilities of amine catalytic substituents on a mesoporous silica nanosphere surface is considered. The interfacing of the ReaxFF force field within the Surface Integrated Molecular Orbital/Molecular Mechanics (SIMOMM) method, in order to replicate earlier SIMOMM published data and to compare with the ReaxFF data, is discussed. The development of a new correlation consistent Composite Approach (ccCA) is presented, which incorporates the completely renormalized coupled cluster method with singles, doubles and non-iterative triples corrections towards the determination of heats of formations and reaction pathways which contain biradical species.

  5. An e-Learning Theoretical Framework

    Science.gov (United States)

    Aparicio, Manuela; Bacao, Fernando; Oliveira, Tiago

    2016-01-01

    E-learning systems have witnessed a usage and research increase in the past decade. This article presents the e-learning concepts ecosystem. It summarizes the various scopes on e-learning studies. Here we propose an e-learning theoretical framework. This theory framework is based upon three principal dimensions: users, technology, and services…

  6. Theoretical foundations of learning through simulation.

    Science.gov (United States)

    Zigmont, Jason J; Kappus, Liana J; Sudikoff, Stephanie N

    2011-04-01

    Health care simulation is a powerful educational tool to help facilitate learning for clinicians and change their practice to improve patient outcomes and safety. To promote effective life-long learning through simulation, the educator needs to consider individuals, their experiences, and their environments. Effective education of adults through simulation requires a sound understanding of both adult learning theory and experiential learning. This review article provides a framework for developing and facilitating simulation courses, founded upon empiric and theoretic research in adult and experiential learning. Specifically, this article provides a theoretic foundation for using simulation to change practice to improve patient outcomes and safety. Copyright © 2011 Elsevier Inc. All rights reserved.

  7. Theoretical Foundations of Learning Environments. Second Edition

    Science.gov (United States)

    Jonassen, David, Ed.; Land, Susan, Ed.

    2012-01-01

    "Theoretical Foundations of Learning Environments" provides students, faculty, and instructional designers with a clear, concise introduction to the major pedagogical and psychological theories and their implications for the design of new learning environments for schools, universities, or corporations. Leading experts describe the most…

  8. Theoretical Perspectives of How Digital Natives Learn

    Science.gov (United States)

    Kivunja, Charles

    2014-01-01

    Marck Prensky, an authority on teaching and learning especially with the aid of Information and Communication Technologies, has referred to 21st century children born after 1980 as "Digital Natives". This paper reviews literature of leaders in the field to shed some light on theoretical perspectives of how Digital Natives learn and how…

  9. Strongly Correlated Systems Theoretical Methods

    CERN Document Server

    Avella, Adolfo

    2012-01-01

    The volume presents, for the very first time, an exhaustive collection of those modern theoretical methods specifically tailored for the analysis of Strongly Correlated Systems. Many novel materials, with functional properties emerging from macroscopic quantum behaviors at the frontier of modern research in physics, chemistry and materials science, belong to this class of systems. Any technique is presented in great detail by its own inventor or by one of the world-wide recognized main contributors. The exposition has a clear pedagogical cut and fully reports on the most relevant case study where the specific technique showed to be very successful in describing and enlightening the puzzling physics of a particular strongly correlated system. The book is intended for advanced graduate students and post-docs in the field as textbook and/or main reference, but also for other researchers in the field who appreciates consulting a single, but comprehensive, source or wishes to get acquainted, in a as painless as po...

  10. Effects of lattice parameters on piezoelectric constants in wurtzite materials: A theoretical study using first-principles and statistical-learning methods

    Science.gov (United States)

    Momida, Hiroyoshi; Oguchi, Tamio

    2018-04-01

    Longitudinal piezoelectric constant (e 33) values of wurtzite materials, which are listed in a structure database, are calculated and analyzed by using first-principles and statistical learning methods. It is theoretically shown that wurtzite materials with high e 33 generally have small lattice constant ratios (c/a) almost independent of constituent elements, and approximately expressed as e 33 ∝ c/a - (c/a)0 with ideal lattice constant ratio (c/a)0. This relation also holds for highly-piezoelectric ternary materials such as Sc x Al1- x N. We conducted a search for high-piezoelectric wurtzite materials by identifying materials with smaller c/a values. It is proposed that the piezoelectricity of ZnO can be significantly enhanced by substitutions of Zn with Ca.

  11. Information Theoretic-Learning Auto-Encoder

    OpenAIRE

    Santana, Eder; Emigh, Matthew; Principe, Jose C

    2016-01-01

    We propose Information Theoretic-Learning (ITL) divergence measures for variational regularization of neural networks. We also explore ITL-regularized autoencoders as an alternative to variational autoencoding bayes, adversarial autoencoders and generative adversarial networks for randomly generating sample data without explicitly defining a partition function. This paper also formalizes, generative moment matching networks under the ITL framework.

  12. Organisational Learning: Theoretical Shortcomings and Practical Challenges

    Directory of Open Access Journals (Sweden)

    Jon Aarum Andersen

    2014-05-01

    Full Text Available This paper addresses two problems related to learning and the use of knowledge at work. The first problem is the theoretical shortcomings stemming from the controversy between three different concepts of ‘organisational learning.’ In order to enhance scholarship in this field the notion that organisations - as organisations - can learn need to be rejected for theoretical and empirical reasons. The metaphorical use of ‘organisational learning’ creates only confusion. Learning is a process and knowledge is the outcome of that process. It is argued that learning and knowledge is only related to individuals. Knowledge is thus the individual capability to draw distinctions, within a domain of action, based on an appreciation of context or theory. Consequently, knowledge becomes organisational when it is created, developed and transmitted to other individuals in the organisation. In a strict sense knowledge becomes organisational when employees use it and act based on generalisations due to the rules and procedures found in their organisation. The gravest problem is practical challenges due to the fact that the emphasis on learning, knowledge and competence of the working force do not materialize in the application of the knowledge acquired. It is evident that employees do not use their increased knowledge. However, we do not know why they do not use it. An enormous waste of money is spent on learning and knowledge in organisations which does not yield what is expected. How can managers act in order to enhance the application of increased knowledge possessed by the workforce?

  13. Data, Methods, and Theoretical Implications

    Science.gov (United States)

    Hannagan, Rebecca J.; Schneider, Monica C.; Greenlee, Jill S.

    2012-01-01

    Within the subfields of political psychology and the study of gender, the introduction of new data collection efforts, methodologies, and theoretical approaches are transforming our understandings of these two fields and the places at which they intersect. In this article we present an overview of the research that was presented at a National…

  14. Robust recognition via information theoretic learning

    CERN Document Server

    He, Ran; Yuan, Xiaotong; Wang, Liang

    2014-01-01

    This Springer Brief represents a comprehensive review of information theoretic methods for robust recognition. A variety of information theoretic methods have been proffered in the past decade, in a large variety of computer vision applications; this work brings them together, attempts to impart the theory, optimization and usage of information entropy.The?authors?resort to a new information theoretic concept, correntropy, as a robust measure and apply it to solve robust face recognition and object recognition problems. For computational efficiency,?the brief?introduces the additive and multip

  15. Game-Theoretic Learning in Distributed Control

    KAUST Repository

    Marden, Jason R.

    2018-01-05

    In distributed architecture control problems, there is a collection of interconnected decision-making components that seek to realize desirable collective behaviors through local interactions and by processing local information. Applications range from autonomous vehicles to energy to transportation. One approach to control of such distributed architectures is to view the components as players in a game. In this approach, two design considerations are the components’ incentives and the rules that dictate how components react to the decisions of other components. In game-theoretic language, the incentives are defined through utility functions, and the reaction rules are online learning dynamics. This chapter presents an overview of this approach, covering basic concepts in game theory, special game classes, measures of distributed efficiency, utility design, and online learning rules, all with the interpretation of using game theory as a prescriptive paradigm for distributed control design.

  16. A collection of research reporting, theoretical analysis, and practical applications in science education: Examining qualitative research methods, action research, educator-researcher partnerships, and constructivist learning theory

    Science.gov (United States)

    Hartle, R. Todd

    2007-12-01

    . Understanding how to identify and evaluate constructivist lessons is the first step in promoting and improving constructivism in teaching. Chapter 4 summarizes a theoretically-generated series of practical criteria that define constructivism: (1) Eliciting Prior Knowledge, (2) Creating Cognitive Dissonance, (3) Application of New Knowledge with Feedback, and (4) Reflection on Learning, or Metacognition. These criteria can be used by any practitioner to evaluate the level of constructivism used in a given lesson or activity.

  17. Surface physics theoretical models and experimental methods

    CERN Document Server

    Mamonova, Marina V; Prudnikova, I A

    2016-01-01

    The demands of production, such as thin films in microelectronics, rely on consideration of factors influencing the interaction of dissimilar materials that make contact with their surfaces. Bond formation between surface layers of dissimilar condensed solids-termed adhesion-depends on the nature of the contacting bodies. Thus, it is necessary to determine the characteristics of adhesion interaction of different materials from both applied and fundamental perspectives of surface phenomena. Given the difficulty in obtaining reliable experimental values of the adhesion strength of coatings, the theoretical approach to determining adhesion characteristics becomes more important. Surface Physics: Theoretical Models and Experimental Methods presents straightforward and efficient approaches and methods developed by the authors that enable the calculation of surface and adhesion characteristics for a wide range of materials: metals, alloys, semiconductors, and complex compounds. The authors compare results from the ...

  18. Nanoscale thermal transport: Theoretical method and application

    Science.gov (United States)

    Zeng, Yu-Jia; Liu, Yue-Yang; Zhou, Wu-Xing; Chen, Ke-Qiu

    2018-03-01

    With the size reduction of nanoscale electronic devices, the heat generated by the unit area in integrated circuits will be increasing exponentially, and consequently the thermal management in these devices is a very important issue. In addition, the heat generated by the electronic devices mostly diffuses to the air in the form of waste heat, which makes the thermoelectric energy conversion also an important issue for nowadays. In recent years, the thermal transport properties in nanoscale systems have attracted increasing attention in both experiments and theoretical calculations. In this review, we will discuss various theoretical simulation methods for investigating thermal transport properties and take a glance at several interesting thermal transport phenomena in nanoscale systems. Our emphasizes will lie on the advantage and limitation of calculational method, and the application of nanoscale thermal transport and thermoelectric property. Project supported by the Nation Key Research and Development Program of China (Grant No. 2017YFB0701602) and the National Natural Science Foundation of China (Grant No. 11674092).

  19. Information theoretic learning Renyi's entropy and Kernel perspectives

    CERN Document Server

    Principe, Jose C

    2010-01-01

    This book presents the first cohesive treatment of Information Theoretic Learning (ITL) algorithms to adapt linear or nonlinear learning machines both in supervised or unsupervised paradigms. ITL is a framework where the conventional concepts of second order statistics (covariance, L2 distances, correlation functions) are substituted by scalars and functions with information theoretic underpinnings, respectively entropy, mutual information and correntropy. ITL quantifies the stochastic structure of the data beyond second order statistics for improved performance without using full-blown Bayesi

  20. Learning Physical Domains: Toward a Theoretical Framework.

    Science.gov (United States)

    1986-12-01

    advanced ids o the iaime doinain in containing more information, especially perceptual " ’It. iho lI b1 rwt... tI hat. psychboigists by no means...Acquisitions Dr Kenneth D Forbus 4833 Rugby Avenue University of Illinois Dr Robert Glaser Bethesda, MD 20014 Department of Computer Science Learning

  1. Cognitive culture: theoretical and empirical insights into social learning strategies.

    Science.gov (United States)

    Rendell, Luke; Fogarty, Laurel; Hoppitt, William J E; Morgan, Thomas J H; Webster, Mike M; Laland, Kevin N

    2011-02-01

    Research into social learning (learning from others) has expanded significantly in recent years, not least because of productive interactions between theoretical and empirical approaches. This has been coupled with a new emphasis on learning strategies, which places social learning within a cognitive decision-making framework. Understanding when, how and why individuals learn from others is a significant challenge, but one that is critical to numerous fields in multiple academic disciplines, including the study of social cognition. Copyright © 2010 Elsevier Ltd. All rights reserved.

  2. Model United Nations and Deep Learning: Theoretical and Professional Learning

    Science.gov (United States)

    Engel, Susan; Pallas, Josh; Lambert, Sarah

    2017-01-01

    This article demonstrates that the purposeful subject design, incorporating a Model United Nations (MUN), facilitated deep learning and professional skills attainment in the field of International Relations. Deep learning was promoted in subject design by linking learning objectives to Anderson and Krathwohl's (2001) four levels of knowledge or…

  3. Theoretical Foundation for Advanced Distributed Learning Research

    National Research Council Canada - National Science Library

    Hays, Robert

    2001-01-01

    ... and constrained by system principles. The goal of this paper is to sensitize individuals working in all aspects of ADL systems to the power of a system view and to provide several examples of system methods...

  4. Set-theoretic methods in control

    CERN Document Server

    Blanchini, Franco

    2015-01-01

    The second edition of this monograph describes the set-theoretic approach for the control and analysis of dynamic systems, both from a theoretical and practical standpoint.  This approach is linked to fundamental control problems, such as Lyapunov stability analysis and stabilization, optimal control, control under constraints, persistent disturbance rejection, and uncertain systems analysis and synthesis.  Completely self-contained, this book provides a solid foundation of mathematical techniques and applications, extensive references to the relevant literature, and numerous avenues for further theoretical study. All the material from the first edition has been updated to reflect the most recent developments in the field, and a new chapter on switching systems has been added.  Each chapter contains examples, case studies, and exercises to allow for a better understanding of theoretical concepts by practical application. The mathematical language is kept to the minimum level necessary for the adequate for...

  5. Theoretical frameworks for the learning of geometrical reasoning

    OpenAIRE

    Jones, Keith

    1998-01-01

    With the growth in interest in geometrical ideas it is important to be clear about the nature of geometrical reasoning and how it develops. This paper provides an overview of three theoretical frameworks for the learning of geometrical reasoning: the van Hiele model of thinking in geometry, Fischbein’s theory of figural concepts, and Duval’s cognitive model of geometrical reasoning. Each of these frameworks provides theoretical resources to support research into the development of geometrical...

  6. Theoretical physics 7 quantum mechanics : methods and applications

    CERN Document Server

    Nolting, Wolfgang

    2017-01-01

    This textbook offers a clear and comprehensive introduction to methods and applications in quantum mechanics, one of the core components of undergraduate physics courses. It follows on naturally from the previous volumes in this series, thus developing the understanding of quantized states further on. The first part of the book introduces the quantum theory of angular momentum and approximation methods. More complex themes are covered in the second part of the book, which describes multiple particle systems and scattering theory. Ideally suited to undergraduate students with some grounding in the basics of quantum mechanics, the book is enhanced throughout with learning features such as boxed inserts and chapter summaries, with key mathematical derivations highlighted to aid understanding. The text is supported by numerous worked examples and end of chapter problem sets.  About the Theoretical Physics series Translated from the renowned and highly successful German editions, the eight volumes of this seri...

  7. Theoretical and simulation studies of seeding methods

    Energy Technology Data Exchange (ETDEWEB)

    Pellegrini, Claudio [Univ. of California, Los Angeles, CA (United States)

    2017-12-11

    We report the theoretical and experimental studies done with the support of DOE-Grant DE-SC0009983 to increase an X-ray FEL peak power from the present level of 20 to 40 GW to one or more TW by seeding, undulator tapering and using the new concept of the Double Bunch FEL.

  8. Collaborative Learning: Theoretical Foundations and Applicable Strategies to University

    Science.gov (United States)

    Roselli, Nestor D.

    2016-01-01

    Collaborative learning is a construct that identifies a current strong field, both in face-to-face and virtual education. Firstly, three converging theoretical sources are analyzed: socio-cognitive conflict theory, intersubjectivity theory and distributed cognition theory. Secondly, a model of strategies that can be implemented by teachers to…

  9. Organizational Learning and Product Design Management: Towards a Theoretical Model.

    Science.gov (United States)

    Chiva-Gomez, Ricardo; Camison-Zornoza, Cesar; Lapiedra-Alcami, Rafael

    2003-01-01

    Case studies of four Spanish ceramics companies were used to construct a theoretical model of 14 factors essential to organizational learning. One set of factors is related to the conceptual-analytical phase of the product design process and the other to the creative-technical phase. All factors contributed to efficient product design management…

  10. A review of theoretical perspectives on language learning and acquisition

    Directory of Open Access Journals (Sweden)

    Norbahira Mohamad Nor

    2018-01-01

    Full Text Available This paper reviews three main theoretical perspectives on language learning and acquisition in an attempt to elucidate how people acquire their first language (L1 and learn their second language (L2. Behaviorist, Innatist and Interactionist offer different perspectives on language learning and acquisition which influence the acceptance of how an L2 should be taught and learned. This paper also explicates the relationship between L1 and L2, and elaborates on the similarities and differences between the two. This paper concludes that there is no one solid linguistic theory which can provide the ultimate explanation of L1 acquisition and L2 learning as there are many interrelated factors that influence the success of language acquisition or language learning. The implication is that teachers should base their classroom management practices and pedagogical techniques on several theories rather than a single theory as learners learn and acquire language differently. It is hoped that this paper provides useful insights into the complex process involved in language acquisition and learning, and contributes to the increased awareness of the process among the stakeholders in the field of language education. Keywords: behaviorist, innatist, interactionist, language acquisition, second language learning

  11. Almost Free Modules Set-Theoretic Methods

    CERN Document Server

    Eklof, PC

    1990-01-01

    This is an extended treatment of the set-theoretic techniques which have transformed the study of abelian group and module theory over the last 15 years. Part of the book is new work which does not appear elsewhere in any form. In addition, a large body of material which has appeared previously (in scattered and sometimes inaccessible journal articles) has been extensively reworked and in many cases given new and improved proofs. The set theory required is carefully developed with algebraists in mind, and the independence results are derived from explicitly stated axioms. The book contains exe

  12. Theoretical-methodical Fundamentals of industrial marketing research

    OpenAIRE

    Butenko, N.

    2009-01-01

    The article proves the necessity to research theoretical and methodical fundamentals of industrial marketing and defines main key aspects of relationship management with the customers on industrial market.

  13. Molecular physics. Theoretical principles and experimental methods

    International Nuclear Information System (INIS)

    Demtroeder, W.

    2005-01-01

    This advanced textbook comprehensively explains important principles of diatomic and polyatomic molecules and their spectra in two separate, distinct parts. The first part concentrates on the theoretical aspects of molecular physics, whereas the second part of the book covers experimental techniques, i.e. laser, Fourier, NMR, and ESR spectroscopies, used in the fields of physics, chemistry, biolog, and material science. Appropriate for undergraduate and graduate students in physics and chemistry with a knowledge of atomic physics and familiar with the basics of quantum mechanics. From the contents: - Electronic States of Molecules, - Rotation, Oscillation and Potential Curves of Diatomic Molecules, - The Spectra of Diatomic Molecules, - Molecule Symmetries and Group Theory, - Rotation and Oscillations of Polyatomic Molecules, - Electronic States of Polyatomic Molecules, - The Spectra of Polyatomic Molecules, - Collapse of the Born-Oppenheimer-Approximation, Disturbances in Molecular Spectra, - Molecules in Disturbing Fields, - Van-der-Waals-Molecules and Cluster, - Experimental Techniques in Molecular Physics. (orig.)

  14. Unsupervised active learning based on hierarchical graph-theoretic clustering.

    Science.gov (United States)

    Hu, Weiming; Hu, Wei; Xie, Nianhua; Maybank, Steve

    2009-10-01

    Most existing active learning approaches are supervised. Supervised active learning has the following problems: inefficiency in dealing with the semantic gap between the distribution of samples in the feature space and their labels, lack of ability in selecting new samples that belong to new categories that have not yet appeared in the training samples, and lack of adaptability to changes in the semantic interpretation of sample categories. To tackle these problems, we propose an unsupervised active learning framework based on hierarchical graph-theoretic clustering. In the framework, two promising graph-theoretic clustering algorithms, namely, dominant-set clustering and spectral clustering, are combined in a hierarchical fashion. Our framework has some advantages, such as ease of implementation, flexibility in architecture, and adaptability to changes in the labeling. Evaluations on data sets for network intrusion detection, image classification, and video classification have demonstrated that our active learning framework can effectively reduce the workload of manual classification while maintaining a high accuracy of automatic classification. It is shown that, overall, our framework outperforms the support-vector-machine-based supervised active learning, particularly in terms of dealing much more efficiently with new samples whose categories have not yet appeared in the training samples.

  15. Cooperative Learning as a Democratic Learning Method

    Science.gov (United States)

    Erbil, Deniz Gökçe; Kocabas, Ayfer

    2018-01-01

    In this study, the effects of applying the cooperative learning method on the students' attitude toward democracy in an elementary 3rd-grade life studies course was examined. Over the course of 8 weeks, the cooperative learning method was applied with an experimental group, and traditional methods of teaching life studies in 2009, which was still…

  16. Machine learning methods for planning

    CERN Document Server

    Minton, Steven

    1993-01-01

    Machine Learning Methods for Planning provides information pertinent to learning methods for planning and scheduling. This book covers a wide variety of learning methods and learning architectures, including analogical, case-based, decision-tree, explanation-based, and reinforcement learning.Organized into 15 chapters, this book begins with an overview of planning and scheduling and describes some representative learning systems that have been developed for these tasks. This text then describes a learning apprentice for calendar management. Other chapters consider the problem of temporal credi

  17. Examining Asymmetrical Relationships of Organizational Learning Antecedents: A Theoretical Model

    Directory of Open Access Journals (Sweden)

    Ery Tri Djatmika

    2016-02-01

    Full Text Available Global era is characterized by highly competitive advantage market demand. Responding to the challenge of rapid environmental changes, organizational learning is becoming a strategic way and solution to empower people themselves within the organization in order to create a novelty as valuable positioning source. For research purposes, determining the influential antecedents that affect organizational learning is vital to understand research-based solutions given for practical implications. Accordingly, identification of variables examined by asymmetrical relationships is critical to establish. Possible antecedent variables come from organizational and personal point of views. It is also possible to include a moderating one. A proposed theoretical model of asymmetrical effects of organizational learning and its antecedents is discussed in this article.

  18. A Theoretical Model for Meaning Construction through Constructivist Concept Learning

    DEFF Research Database (Denmark)

    Badie, Farshad

    The central focus of this Ph.D. research is on ‘Logic and Cognition’ and, more specifically, this research covers the quintuple (Logic and Logical Philosophy, Philosophy of Education, Educational Psychology, Cognitive Science, Computer Science). The most significant contributions of this Ph.D. di...... of ‘learning’, ‘mentoring’, and ‘knowledge’ within learning and knowledge acquisition systems. Constructivism as an epistemology and as a model of knowing and, respectively as a theoretical model of learning builds up the central framework of this research........D. dissertation are conceptual, logical, terminological, and semantic analysis of Constructivist Concept Learning (specifically, in the context of humans’ interactions with their environment and with other agents). This dissertation is concerned with the specification of the conceptualisation of the phenomena...

  19. Theoretical and numerical method in aeroacoustics

    Directory of Open Access Journals (Sweden)

    Nicuşor ALEXANDRESCU

    2010-06-01

    Full Text Available The paper deals with the mathematical and numerical modeling of the aerodynamic noisegenerated by the fluid flow interaction with the solid structure of a rotor blade.Our analysis use Lighthill’s acoustic analogy. Lighthill idea was to express the fundamental equationsof motion into a wave equation for acoustic fluctuation with a source term on the right-hand side. Theobtained wave equation is solved numerically by the spatial discretization. The method is applied inthe case of monopole source placed in different points of blade surfaces to find this effect of noisepropagation.

  20. Active Learning Methods

    Science.gov (United States)

    Zayapragassarazan, Z.; Kumar, Santosh

    2012-01-01

    Present generation students are primarily active learners with varied learning experiences and lecture courses may not suit all their learning needs. Effective learning involves providing students with a sense of progress and control over their own learning. This requires creating a situation where learners have a chance to try out or test their…

  1. Qualitative methods in workplace learning

    OpenAIRE

    Fabritius, Hannele

    2015-01-01

    Methods of learning in the workplace will be introduced. The methods are connect to competence development and to the process of conducting development discussions in a dialogical way. The tools developed and applied are a fourfold table, a cycle of work identity, a plan of personal development targets, a learning meeting and a learning map. The methods introduced will aim to better learning at work.

  2. Applied Mathematical Methods in Theoretical Physics

    Science.gov (United States)

    Masujima, Michio

    2005-04-01

    All there is to know about functional analysis, integral equations and calculus of variations in a single volume. This advanced textbook is divided into two parts: The first on integral equations and the second on the calculus of variations. It begins with a short introduction to functional analysis, including a short review of complex analysis, before continuing a systematic discussion of different types of equations, such as Volterra integral equations, singular integral equations of Cauchy type, integral equations of the Fredholm type, with a special emphasis on Wiener-Hopf integral equations and Wiener-Hopf sum equations. After a few remarks on the historical development, the second part starts with an introduction to the calculus of variations and the relationship between integral equations and applications of the calculus of variations. It further covers applications of the calculus of variations developed in the second half of the 20th century in the fields of quantum mechanics, quantum statistical mechanics and quantum field theory. Throughout the book, the author presents over 150 problems and exercises -- many from such branches of physics as quantum mechanics, quantum statistical mechanics, and quantum field theory -- together with outlines of the solutions in each case. Detailed solutions are given, supplementing the materials discussed in the main text, allowing problems to be solved making direct use of the method illustrated. The original references are given for difficult problems. The result is complete coverage of the mathematical tools and techniques used by physicists and applied mathematicians Intended for senior undergraduates and first-year graduates in science and engineering, this is equally useful as a reference and self-study guide.

  3. The theoretical base of e-learning and its role in surgical education.

    Science.gov (United States)

    Evgeniou, Evgenios; Loizou, Peter

    2012-01-01

    The advances in Internet and computer technology offer many solutions that can enhance surgical education and increase the effectiveness of surgical teaching. E-learning plays an important role in surgical education today, with many e-learning projects already available on the Internet. E-learning is based on a mixture of educational theories that derive from behaviorist, cognitivist, and constructivist educational theoretical frameworks. CAN EDUCATIONAL THEORY IMPROVE E-LEARNING?: Conventional educational theory can be applied to improve the quality and effectiveness of e-learning. The theory of "threshold concepts" and educational theories on reflection, motivation, and communities of practice can be applied when designing e-learning material. E-LEARNING IN SURGICAL EDUCATION: E-learning has many advantages but also has weaknesses. Studies have shown that e-learning is an effective teaching method that offers high levels of learner satisfaction. Instead of trying to compare e-learning with traditional methods of teaching, it is better to integrate in e-learning elements of traditional teaching that have been proven to be effective. E-learning can play an important role in surgical education as a blended approach, combined with more traditional methods of teaching, which offer better face-to-interaction with patients and colleagues in different circumstances and hands on practice of practical skills. National provision of e-learning can make evaluation easier. The correct utilization of Internet and computer resources combined with the application of valid conventional educational theory to design e-learning relevant to the various levels of surgical training can be effective in the training of future surgeons. Copyright © 2012 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

  4. Geometrical methods in learning theory

    International Nuclear Information System (INIS)

    Burdet, G.; Combe, Ph.; Nencka, H.

    2001-01-01

    The methods of information theory provide natural approaches to learning algorithms in the case of stochastic formal neural networks. Most of the classical techniques are based on some extremization principle. A geometrical interpretation of the associated algorithms provides a powerful tool for understanding the learning process and its stability and offers a framework for discussing possible new learning rules. An illustration is given using sequential and parallel learning in the Boltzmann machine

  5. Symbolic interactionism as a theoretical perspective for multiple method research.

    Science.gov (United States)

    Benzies, K M; Allen, M N

    2001-02-01

    Qualitative and quantitative research rely on different epistemological assumptions about the nature of knowledge. However, the majority of nurse researchers who use multiple method designs do not address the problem of differing theoretical perspectives. Traditionally, symbolic interactionism has been viewed as one perspective underpinning qualitative research, but it is also the basis for quantitative studies. Rooted in social psychology, symbolic interactionism has a rich intellectual heritage that spans more than a century. Underlying symbolic interactionism is the major assumption that individuals act on the basis of the meaning that things have for them. The purpose of this paper is to present symbolic interactionism as a theoretical perspective for multiple method designs with the aim of expanding the dialogue about new methodologies. Symbolic interactionism can serve as a theoretical perspective for conceptually clear and soundly implemented multiple method research that will expand the understanding of human health behaviour.

  6. Comparative Study on Theoretical and Machine Learning Methods for Acquiring Compressed Liquid Densities of 1,1,1,2,3,3,3-Heptafluoropropane (R227ea via Song and Mason Equation, Support Vector Machine, and Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Hao Li

    2016-01-01

    Full Text Available 1,1,1,2,3,3,3-Heptafluoropropane (R227ea is a good refrigerant that reduces greenhouse effects and ozone depletion. In practical applications, we usually have to know the compressed liquid densities at different temperatures and pressures. However, the measurement requires a series of complex apparatus and operations, wasting too much manpower and resources. To solve these problems, here, Song and Mason equation, support vector machine (SVM, and artificial neural networks (ANNs were used to develop theoretical and machine learning models, respectively, in order to predict the compressed liquid densities of R227ea with only the inputs of temperatures and pressures. Results show that compared with the Song and Mason equation, appropriate machine learning models trained with precise experimental samples have better predicted results, with lower root mean square errors (RMSEs (e.g., the RMSE of the SVM trained with data provided by Fedele et al. [1] is 0.11, while the RMSE of the Song and Mason equation is 196.26. Compared to advanced conventional measurements, knowledge-based machine learning models are proved to be more time-saving and user-friendly.

  7. Collaborative Learning: Theoretical Foundations and Applicable Strategies to University Teaching

    Directory of Open Access Journals (Sweden)

    Nestor D. Roselli

    2016-04-01

    Full Text Available Collaborative learning is a construct that identifies a current strong field, both in face-to-face and virtual education. Firstly, three converging theoretical sources are analyzed: socio-cognitive conflict theory, intersubjectivity theory and distributed cognition theory. Secondly, a model of strategies that can be implemented by teachers to develop socio-cognitive collaboration is presented. This model integrates and systematizes several academic group animation techniques developed within the collaborative learning field. These integrated techniques, within a coherent and unified didactic intention, allow talking more about strategies than independent and dissociated techniques. Each strategy is specifically described, which refers to six areas: encouragement of dialogue, listening to others and reciprocal assessment; collaboration for negotiation and consensus building; activity organization; study and appropriation of bibliographic information; conceptual development; collective writing. These strategies proposed (designed to stimulate the collaboration between 2, 4 and exceptionally, 6 or 8 students are not the only possible strategies, they can be combined with the ones the teacher might suggest. The strict pattern of each strategy is a characteristic of the proposal. The teacher is also encouraged to benchmark the results obtained using each strategy and those obtained using individual or non-collaborative strategies. Finally, conclusions and recommendations for the implementation of these strategies are discussed.

  8. Theoretical methods and models for mechanical properties of soft biomaterials

    Directory of Open Access Journals (Sweden)

    Zhonggang Feng

    2017-06-01

    Full Text Available We review the most commonly used theoretical methods and models for the mechanical properties of soft biomaterials, which include phenomenological hyperelastic and viscoelastic models, structural biphasic and network models, and the structural alteration theory. We emphasize basic concepts and recent developments. In consideration of the current progress and needs of mechanobiology, we introduce methods and models for tackling micromechanical problems and their applications to cell biology. Finally, the challenges and perspectives in this field are discussed.

  9. Advanced Numerical and Theoretical Methods for Photonic Crystals and Metamaterials

    Science.gov (United States)

    Felbacq, Didier

    2016-11-01

    This book provides a set of theoretical and numerical tools useful for the study of wave propagation in metamaterials and photonic crystals. While concentrating on electromagnetic waves, most of the material can be used for acoustic (or quantum) waves. For each presented numerical method, numerical code written in MATLAB® is presented. The codes are limited to 2D problems and can be easily translated in Python or Scilab, and used directly with Octave as well.

  10. Some New Theoretical Issues in Systems Thinking Relevant for Modelling Corporate Learning

    Science.gov (United States)

    Minati, Gianfranco

    2007-01-01

    Purpose: The purpose of this paper is to describe fundamental concepts and theoretical challenges with regard to systems, and to build on these in proposing new theoretical frameworks relevant to learning, for example in so-called learning organizations. Design/methodology/approach: The paper focuses on some crucial fundamental aspects introduced…

  11. Parallelization of the ROOT Machine Learning Methods

    CERN Document Server

    Vakilipourtakalou, Pourya

    2016-01-01

    Today computation is an inseparable part of scientific research. Specially in Particle Physics when there is a classification problem like discrimination of Signals from Backgrounds originating from the collisions of particles. On the other hand, Monte Carlo simulations can be used in order to generate a known data set of Signals and Backgrounds based on theoretical physics. The aim of Machine Learning is to train some algorithms on known data set and then apply these trained algorithms to the unknown data sets. However, the most common framework for data analysis in Particle Physics is ROOT. In order to use Machine Learning methods, a Toolkit for Multivariate Data Analysis (TMVA) has been added to ROOT. The major consideration in this report is the parallelization of some TMVA methods, specially Cross-Validation and BDT.

  12. Acceptance of technology-enhanced learning for a theoretical radiological science course: a randomized controlled trial

    Directory of Open Access Journals (Sweden)

    Nkenke Emeka

    2012-03-01

    Full Text Available Abstract Background Technology-enhanced learning (TEL gives a view to improved education. However, there is a need to clarify how TEL can be used effectively. The study compared students' attitudes and opinions towards a traditional face-to-face course on theoretical radiological science and a TEL course where students could combine face-to-face lectures and e-learning modules at their best convenience. Methods 42 third-year dental students were randomly assigned to the traditional face-to-face group and the TEL group. Both groups completed questionnaires before the beginning and after completion of the course on attitudes and opinions towards a traditional face-to-face lectures and technology-enhanced learning. After completion of the course both groups also filled in the validated German-language TRIL (Trierer Inventar zur Lehrevaluation questionnaire for the evaluation of courses given at universities. Results Both groups had a positive attitude towards e-learning that did not change over time. The TEL group attended significantly less face-to-face lectures than the traditional group. However, both groups stated that face-to-face lectures were the basis for education in a theoretical radiological science course. The members of the TEL group rated e-mail reminders significantly more important when they filled in the questionnaire on attitudes and opinions towards a traditional face-to-face lectures and technology-enhanced learning for the second time after completion of the course. The members of the technology-enhanced learning group were significantly less confident in passing the exam compared to the members of the traditional group. However, examination results did not differ significantly for traditional and the TEL group. Conclusions It seems that technology-enhanced learning in a theoretical radiological science course has the potential to reduce the need for face-to-face lectures. At the same time examination results are not impaired

  13. Acceptance of technology-enhanced learning for a theoretical radiological science course: a randomized controlled trial

    Science.gov (United States)

    2012-01-01

    Background Technology-enhanced learning (TEL) gives a view to improved education. However, there is a need to clarify how TEL can be used effectively. The study compared students' attitudes and opinions towards a traditional face-to-face course on theoretical radiological science and a TEL course where students could combine face-to-face lectures and e-learning modules at their best convenience. Methods 42 third-year dental students were randomly assigned to the traditional face-to-face group and the TEL group. Both groups completed questionnaires before the beginning and after completion of the course on attitudes and opinions towards a traditional face-to-face lectures and technology-enhanced learning. After completion of the course both groups also filled in the validated German-language TRIL (Trierer Inventar zur Lehrevaluation) questionnaire for the evaluation of courses given at universities. Results Both groups had a positive attitude towards e-learning that did not change over time. The TEL group attended significantly less face-to-face lectures than the traditional group. However, both groups stated that face-to-face lectures were the basis for education in a theoretical radiological science course. The members of the TEL group rated e-mail reminders significantly more important when they filled in the questionnaire on attitudes and opinions towards a traditional face-to-face lectures and technology-enhanced learning for the second time after completion of the course. The members of the technology-enhanced learning group were significantly less confident in passing the exam compared to the members of the traditional group. However, examination results did not differ significantly for traditional and the TEL group. Conclusions It seems that technology-enhanced learning in a theoretical radiological science course has the potential to reduce the need for face-to-face lectures. At the same time examination results are not impaired. However, technology

  14. Theoretical Perspectives Underlying the Application of Cooperative Learning in Classrooms

    Science.gov (United States)

    Tran, Van Dat

    2013-01-01

    Cooperative learning has been the centre of worldwide attention because it has been shown to have strong effects on student learning, as well as other positive outcomes. Although the academic, social, affective and psychological outcomes of students taught by cooperative learning are more positive compared with students taught by the traditional…

  15. Reflexive Learning through Visual Methods

    DEFF Research Database (Denmark)

    Frølunde, Lisbeth

    2014-01-01

    What. This chapter concerns how visual methods and visual materials can support visually oriented, collaborative, and creative learning processes in education. The focus is on facilitation (guiding, teaching) with visual methods in learning processes that are designerly or involve design. Visual...... methods are exemplified through two university classroom cases about collaborative idea generation processes. The visual methods and materials in the cases are photo elicitation using photo cards, and modeling with LEGO Serious Play sets. Why. The goal is to encourage the reader, whether student...... or professional, to facilitate with visual methods in a critical, reflective, and experimental way. The chapter offers recommendations for facilitating with visual methods to support playful, emergent designerly processes. The chapter also has a critical, situated perspective. Where. This chapter offers case...

  16. Information-theoretic methods for estimating of complicated probability distributions

    CERN Document Server

    Zong, Zhi

    2006-01-01

    Mixing up various disciplines frequently produces something that are profound and far-reaching. Cybernetics is such an often-quoted example. Mix of information theory, statistics and computing technology proves to be very useful, which leads to the recent development of information-theory based methods for estimating complicated probability distributions. Estimating probability distribution of a random variable is the fundamental task for quite some fields besides statistics, such as reliability, probabilistic risk analysis (PSA), machine learning, pattern recognization, image processing, neur

  17. Theoretical Implementations of Various Mobile Applications Used in English Language Learning

    Science.gov (United States)

    Small, Melissa

    2014-01-01

    This review of the theoretical framework for Mastery Learning Theory and Sense of Community theories is provided in conjunction with a review of the literature for mobile technology in relation to language learning. Although empirical research is minimal for mobile phone technology as an aid for language learning, the empirical research that…

  18. Information-theoretic semi-supervised metric learning via entropy regularization.

    Science.gov (United States)

    Niu, Gang; Dai, Bo; Yamada, Makoto; Sugiyama, Masashi

    2014-08-01

    We propose a general information-theoretic approach to semi-supervised metric learning called SERAPH (SEmi-supervised metRic leArning Paradigm with Hypersparsity) that does not rely on the manifold assumption. Given the probability parameterized by a Mahalanobis distance, we maximize its entropy on labeled data and minimize its entropy on unlabeled data following entropy regularization. For metric learning, entropy regularization improves manifold regularization by considering the dissimilarity information of unlabeled data in the unsupervised part, and hence it allows the supervised and unsupervised parts to be integrated in a natural and meaningful way. Moreover, we regularize SERAPH by trace-norm regularization to encourage low-dimensional projections associated with the distance metric. The nonconvex optimization problem of SERAPH could be solved efficiently and stably by either a gradient projection algorithm or an EM-like iterative algorithm whose M-step is convex. Experiments demonstrate that SERAPH compares favorably with many well-known metric learning methods, and the learned Mahalanobis distance possesses high discriminability even under noisy environments.

  19. A theoretical study on a convergence problem of nodal methods

    Energy Technology Data Exchange (ETDEWEB)

    Shaohong, Z.; Ziyong, L. [Shanghai Jiao Tong Univ., 1954 Hua Shan Road, Shanghai, 200030 (China); Chao, Y. A. [Westinghouse Electric Company, P. O. Box 355, Pittsburgh, PA 15230-0355 (United States)

    2006-07-01

    The effectiveness of modern nodal methods is largely due to its use of the information from the analytical flux solution inside a homogeneous node. As a result, the nodal coupling coefficients depend explicitly or implicitly on the evolving Eigen-value of a problem during its solution iteration process. This poses an inherently non-linear matrix Eigen-value iteration problem. This paper points out analytically that, whenever the half wave length of an evolving node interior analytic solution becomes smaller than the size of that node, this non-linear iteration problem can become inherently unstable and theoretically can always be non-convergent or converge to higher order harmonics. This phenomenon is confirmed, demonstrated and analyzed via the simplest 1-D problem solved by the simplest analytic nodal method, the Analytic Coarse Mesh Finite Difference (ACMFD, [1]) method. (authors)

  20. Theoretical Foundations for Enhancing Social Connectedness in Online Learning Environments

    Science.gov (United States)

    Slagter van Tryon, Patricia J.; Bishop, M. J.

    2009-01-01

    Group social structure provides a comfortable and predictable context for interaction in learning environments. Students in face-to-face learning environments process social information about others in order to assess traits, predict behaviors, and determine qualifications for assuming particular responsibilities within a group. In online learning…

  1. A theoretical design for learning model addressing the networked society

    DEFF Research Database (Denmark)

    Levinsen, Karin; Nielsen, Janni; Sørensen, Birgitte Holm

    2010-01-01

    The transition from the industrial to the networked society produces contradictions that challenges the educational system and force it to adapt to new conditions. In a Danish virtual Master in Information and Communication Technologies and Learning (MIL) these contradictions appear as a field of...... which enables students to develop Networked Society competencies and maintain progression in the learning process also during the online periods. Additionally we suggest that our model contributes to the innovation of a networked society's design for learning....... is continuously decreasing. We teach for deep learning but are confronted by students' cost-benefit strategies when they navigate through the study programme under time pressure. To meet these challenges a Design for Learning Model has been developed. The aim is to provide a scaffold that ensures students......' acquisition of the subject matter within a time limit and at a learning quality that support their deep learning process during a subsequent period of on-line study work. In the process of moving from theory to application the model passes through three stages: 1) Conceptual modelling; 2) Orchestration, and 3...

  2. Decomposition methods for unsupervised learning

    DEFF Research Database (Denmark)

    Mørup, Morten

    2008-01-01

    This thesis presents the application and development of decomposition methods for Unsupervised Learning. It covers topics from classical factor analysis based decomposition and its variants such as Independent Component Analysis, Non-negative Matrix Factorization and Sparse Coding...... methods and clustering problems is derived both in terms of classical point clustering but also in terms of community detection in complex networks. A guiding principle throughout this thesis is the principle of parsimony. Hence, the goal of Unsupervised Learning is here posed as striving for simplicity...... in the decompositions. Thus, it is demonstrated how a wide range of decomposition methods explicitly or implicitly strive to attain this goal. Applications of the derived decompositions are given ranging from multi-media analysis of image and sound data, analysis of biomedical data such as electroencephalography...

  3. Decentralized indirect methods for learning automata games.

    Science.gov (United States)

    Tilak, Omkar; Martin, Ryan; Mukhopadhyay, Snehasis

    2011-10-01

    We discuss the application of indirect learning methods in zero-sum and identical payoff learning automata games. We propose a novel decentralized version of the well-known pursuit learning algorithm. Such a decentralized algorithm has significant computational advantages over its centralized counterpart. The theoretical study of such a decentralized algorithm requires the analysis to be carried out in a nonstationary environment. We use a novel bootstrapping argument to prove the convergence of the algorithm. To our knowledge, this is the first time that such analysis has been carried out for zero-sum and identical payoff games. Extensive simulation studies are reported, which demonstrate the proposed algorithm's fast and accurate convergence in a variety of game scenarios. We also introduce the framework of partial communication in the context of identical payoff games of learning automata. In such games, the automata may not communicate with each other or may communicate selectively. This comprehensive framework has the capability to model both centralized and decentralized games discussed in this paper.

  4. Virtual Reality Rehabilitation from Social Cognitive and Motor Learning Theoretical Perspectives in Stroke Population

    Directory of Open Access Journals (Sweden)

    Bita Imam

    2014-01-01

    Full Text Available Objectives. To identify the virtual reality (VR interventions used for the lower extremity rehabilitation in stroke population and to explain their underlying training mechanisms using Social Cognitive (SCT and Motor Learning (MLT theoretical frameworks. Methods. Medline, Embase, Cinahl, and Cochrane databases were searched up to July 11, 2013. Randomized controlled trials that included a VR intervention for lower extremity rehabilitation in stroke population were included. The Physiotherapy Evidence Database (PEDro scale was used to assess the quality of the included studies. The underlying training mechanisms involved in each VR intervention were explained according to the principles of SCT (vicarious learning, performance accomplishment, and verbal persuasion and MLT (focus of attention, order and predictability of practice, augmented feedback, and feedback fading. Results. Eleven studies were included. PEDro scores varied from 3 to 7/10. All studies but one showed significant improvement in outcomes in favour of the VR group (P<0.05. Ten VR interventions followed the principle of performance accomplishment. All the eleven VR interventions directed subject’s attention externally, whereas nine provided training in an unpredictable and variable fashion. Conclusions. The results of this review suggest that VR applications used for lower extremity rehabilitation in stroke population predominantly mediate learning through providing a task-oriented and graduated learning under a variable and unpredictable practice.

  5. Virtual reality rehabilitation from social cognitive and motor learning theoretical perspectives in stroke population.

    Science.gov (United States)

    Imam, Bita; Jarus, Tal

    2014-01-01

    Objectives. To identify the virtual reality (VR) interventions used for the lower extremity rehabilitation in stroke population and to explain their underlying training mechanisms using Social Cognitive (SCT) and Motor Learning (MLT) theoretical frameworks. Methods. Medline, Embase, Cinahl, and Cochrane databases were searched up to July 11, 2013. Randomized controlled trials that included a VR intervention for lower extremity rehabilitation in stroke population were included. The Physiotherapy Evidence Database (PEDro) scale was used to assess the quality of the included studies. The underlying training mechanisms involved in each VR intervention were explained according to the principles of SCT (vicarious learning, performance accomplishment, and verbal persuasion) and MLT (focus of attention, order and predictability of practice, augmented feedback, and feedback fading). Results. Eleven studies were included. PEDro scores varied from 3 to 7/10. All studies but one showed significant improvement in outcomes in favour of the VR group (P learning through providing a task-oriented and graduated learning under a variable and unpredictable practice.

  6. Experimental and Theoretical Methods in Algebra, Geometry and Topology

    CERN Document Server

    Veys, Willem; Bridging Algebra, Geometry, and Topology

    2014-01-01

    Algebra, geometry and topology cover a variety of different, but intimately related research fields in modern mathematics. This book focuses on specific aspects of this interaction. The present volume contains refereed papers which were presented at the International Conference “Experimental and Theoretical Methods in Algebra, Geometry and Topology”, held in Eforie Nord (near Constanta), Romania, during 20-25 June 2013. The conference was devoted to the 60th anniversary of the distinguished Romanian mathematicians Alexandru Dimca and Ştefan Papadima. The selected papers consist of original research work and a survey paper. They are intended for a large audience, including researchers and graduate students interested in algebraic geometry, combinatorics, topology, hyperplane arrangements and commutative algebra. The papers are written by well-known experts from different fields of mathematics, affiliated to universities from all over the word, they cover a broad range of topics and explore the research f...

  7. Factors Influencing the Use of Learning Management System in Saudi Arabian Higher Education: A Theoretical Framework

    Science.gov (United States)

    Asiri, Mohammed J. Sherbib; Mahmud, Rosnaini bt; Bakar, Kamariah Abu; Ayub, Ahmad Fauzi bin Mohd

    2012-01-01

    The purpose of this paper is to present the theoretical framework underlying a research on factors that influence utilization of the Jusur Learning Management System (Jusur LMS) in Saudi Arabian public universities. Development of the theoretical framework was done based on library research approach. Initially, the existing literature relevant to…

  8. Theoretical studies of potential energy surfaces and computational methods

    Energy Technology Data Exchange (ETDEWEB)

    Shepard, R. [Argonne National Laboratory, IL (United States)

    1993-12-01

    This project involves the development, implementation, and application of theoretical methods for the calculation and characterization of potential energy surfaces involving molecular species that occur in hydrocarbon combustion. These potential energy surfaces require an accurate and balanced treatment of reactants, intermediates, and products. This difficult challenge is met with general multiconfiguration self-consistent-field (MCSCF) and multireference single- and double-excitation configuration interaction (MRSDCI) methods. In contrast to the more common single-reference electronic structure methods, this approach is capable of describing accurately molecular systems that are highly distorted away from their equilibrium geometries, including reactant, fragment, and transition-state geometries, and of describing regions of the potential surface that are associated with electronic wave functions of widely varying nature. The MCSCF reference wave functions are designed to be sufficiently flexible to describe qualitatively the changes in the electronic structure over the broad range of geometries of interest. The necessary mixing of ionic, covalent, and Rydberg contributions, along with the appropriate treatment of the different electron-spin components (e.g. closed shell, high-spin open-shell, low-spin open shell, radical, diradical, etc.) of the wave functions, are treated correctly at this level. Further treatment of electron correlation effects is included using large scale multireference CI wave functions, particularly including the single and double excitations relative to the MCSCF reference space. This leads to the most flexible and accurate large-scale MRSDCI wave functions that have been used to date in global PES studies.

  9. Reasons and Methods to Learn the Management

    Science.gov (United States)

    Li, Hongxin; Ding, Mengchun

    2010-01-01

    Reasons for learning the management include (1) perfecting the knowledge structure, (2) the management is the base of all organizations, (3) one person may be the manager or the managed person, (4) the management is absolutely not simple knowledge, and (5) the learning of the theoretical knowledge of the management can not be replaced by the…

  10. A Theoretical Basis for Adult Learning Facilitation: Review of Selected Articles

    Science.gov (United States)

    Muneja, Mussa S.

    2015-01-01

    The aim of this paper is to synthesize a theoretical basis for adult learning facilitation in order to provide a valuable systematic resource in the field of adult education. The paper has reviewed 6 journal articles with topics ranging from theory of andragogy; the effect of globalization on adult learning; the contribution of Malcolm Knowles;…

  11. Learning for Cosmopolitan Citizenship: Theoretical Debates and Young People's Experiences.

    Science.gov (United States)

    Osler, Audrey; Starkey, Hugh

    2003-01-01

    Interviews with 600 youth aged 10-18, many from immigrant families, explored how they learn about citizenship and define themselves and their communities. They identify strongly with their city or neighborhood but also have multiple identities, a cosmopolitan citizenship that bridges several worlds. Education for cosmopolitan citizenship should…

  12. Optimal Learning in Schools--Theoretical Evidence: Part 4 Metacognition

    Science.gov (United States)

    Crossland, John

    2017-01-01

    Parts 1 and 2 in this four-part series of articles (Crossland, 2016, 2017a) discussed the recent research from neuroscience linked to concepts from cognitive development that brought Piaget's theories into the 21st century and showed the most effective provision towards more optimal learning strategies. Part 2 reviewed Demetriou's latest thinking…

  13. A theoretical framework for measuring the quality of student learning ...

    African Journals Online (AJOL)

    The most important principles of outcomes-based education is that planning, teaching and assessment should focus on helping learners to achieve significant outcomes to high standards. This cannot be achieved without having suitable ways to describe desired learning outcomes and the quality of students' ...

  14. About possibilities using of theoretical calculation methods in radioecology

    International Nuclear Information System (INIS)

    Demoukhamedova, S.D.; Aliev, D.I.; Alieva, I.N.

    2002-01-01

    Full text: Increasing the radiation level into environment is accompanied by accumulation of radioactive compounds into organism and/or their migration into biosphere. Radiotoxins are accumulated into irradiated plants and animals in result of violation of exchanging processes. The are play an important role at the pathogenesis of irradiation. To date, there is well known that even small quantity of the pesticides capable intensified the radiation effect. To understand the mechanism of radiation effect on physiologically active compounds and their complexes, the knowledge of such molecules three-dimensional organization and electron structure is essential. This work is devoted to study the pesticides of carbamate range, i.e. 'sevin' and its derivatives the physiological activity of which has been connected with cholinesterase degradation. Spatial organization and conformational possibilities of the pesticides has been studied using a method of the theoretical conformational analysis on the base of computational program worked out in laboratory of Molecular Biophysics at the Baku State University. Quantum-chemical methods CNDO/2, AM1 and PM3 and complex programs 'LEV' were used in studies of electronic structures of 'sevin' and number of its analogues. Charge distribution on the atoms, optimization of geometrical electrooptic parameters, as well as molecular electrostatic potentials, electron density and nuclear forces were calculated. Visual maps and surface of valence electron density distribution in the given plane and surface of electron-nuclear forces distribution projection were constructed. The geometrical and energetic characteristics, charges on the atoms of investigated pesticides, as well as the maps and relief of the valence electron density distribution on the atoms have been received. According to calculation results, the changing of charge distribution in naphthalene ring is observed. The conclusion was made that the carbonyl group is essential for

  15. 31st International Colloquium in Group Theoretical Methods in Physics

    CERN Document Server

    Gazeau, Jean-Pierre; Faci, Sofiane; Micklitz, Tobias; Scherer, Ricardo; Toppan, Francesco

    2017-01-01

    This proceedings records the 31st International Colloquium on Group Theoretical Methods in Physics (“Group 31”). Plenary-invited articles propose new approaches to the moduli spaces in gauge theories (V. Pestun, 2016 Weyl Prize Awardee), the phenomenology of neutrinos in non-commutative space-time, the use of Hardy spaces in quantum physics, contradictions in the use of statistical methods on complex systems, and alternative models of supersymmetry. This volume’s survey articles broaden the colloquia’s scope out into Majorana neutrino behavior, the dynamics of radiating charges, statistical pattern recognition of amino acids, and a variety of applications of gauge theory, among others. This year’s proceedings further honors Bertram Kostant (2016 Wigner Medalist), as well as S.T. Ali and L. Boyle, for their life-long contributions to the math and physics communities. The aim of the ICGTMP is to provide a forum for physicists, mathematicians, and scientists of related disciplines who develop or apply ...

  16. THEORETICAL PRINCIPLES OF PSYCHOLOGICAL ANALYSIS OF STUDENTS’ GROUP PROJECT ACTIVITY WHILE LEARNING FOREIGN LANGUAGE

    Directory of Open Access Journals (Sweden)

    Viktoriia Kalamazh

    2016-06-01

    Full Text Available In this research the theoretical principles of psychological analysis of group project activity of students in the process of learning foreign language are defined on the basis of subject-activity, socio-psychological and cognitive paradigms. The approaches of different authors to the understanding of the concept of project and in particular group project activity are considered. The difficulties of the theoretical analysis of this specific notion are indicated due to the considerable variety of subjects, types and forms of the pedagogical activity, academic disciplines regarding which the researches are being carried out. Not disclosed aspects of organizing the group project activity of students are being determined, among them is a project group as an autonomous subject of joint activity for the realization students’ project activity while learning a foreign language; forming psychological readiness of teacher and student to use project method; the role of metacognitive aspect in the surrounding, where the project activity is being carried out; group functioning through the project work as a subject of group examination. It has been indicated that the analysis of project activity as an innovative technology must include its assessment as a condition of student’s developing as a subject of learning activity, his personal, socio-psychological, intellectual and professional self-perfection. Three levels of subjectivity in group project activity are being distinguished: teacher; each particular student; and student project group. Interaction between teacher and student is based on subject-subject relations. An organization of a project activity while learning a foreign language is considered as the one in which the student is moving in order to get the manager position and to master the basis of expert knowledge. Hereby, the main stress is on the group role as a subject of group examination, and also on metacognitive character of the

  17. Statistical learning methods: Basics, control and performance

    Energy Technology Data Exchange (ETDEWEB)

    Zimmermann, J. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)]. E-mail: zimmerm@mppmu.mpg.de

    2006-04-01

    The basics of statistical learning are reviewed with a special emphasis on general principles and problems for all different types of learning methods. Different aspects of controlling these methods in a physically adequate way will be discussed. All principles and guidelines will be exercised on examples for statistical learning methods in high energy and astrophysics. These examples prove in addition that statistical learning methods very often lead to a remarkable performance gain compared to the competing classical algorithms.

  18. Statistical learning methods: Basics, control and performance

    International Nuclear Information System (INIS)

    Zimmermann, J.

    2006-01-01

    The basics of statistical learning are reviewed with a special emphasis on general principles and problems for all different types of learning methods. Different aspects of controlling these methods in a physically adequate way will be discussed. All principles and guidelines will be exercised on examples for statistical learning methods in high energy and astrophysics. These examples prove in addition that statistical learning methods very often lead to a remarkable performance gain compared to the competing classical algorithms

  19. Theoretical and experimental investigation of multispectral photoacoustic osteoporosis detection method

    Science.gov (United States)

    Steinberg, Idan; Hershkovich, Hadas Sara; Gannot, Israel; Eyal, Avishay

    2014-03-01

    Osteoporosis is a widespread disorder, which has a catastrophic impact on patients lives and overwhelming related to healthcare costs. Recently, we proposed a multispectral photoacoustic technique for early detection of osteoporosis. Such technique has great advantages over pure ultrasonic or optical methods as it allows the deduction of both bone functionality from the bone absorption spectrum and bone resistance to fracture from the characteristics of the ultrasound propagation. We demonstrated the propagation of multiple acoustic modes in animal bones in-vitro. To further investigate the effects of multiple wavelength excitations and of induced osteoporosis on the PA signal a multispectral photoacoustic system is presented. The experimental investigation is based on measuring the interference of multiple acoustic modes. The performance of the system is evaluated and a simple two mode theoretical model is fitted to the measured phase signals. The results show that such PA technique is accurate and repeatable. Then a multiple wavelength excitation is tested. It is shown that the PA response due to different excitation wavelengths revels that absorption by the different bone constitutes has a profound effect on the mode generation. The PA response is measured in single wavelength before and after induced osteoporosis. Results show that induced osteoporosis alters the measured amplitude and phase in a consistent manner which allows the detection of the onset of osteoporosis. These results suggest that a complete characterization of the bone over a region of both acoustic and optical frequencies might be used as a powerful tool for in-vivo bone evaluation.

  20. Number theoretic methods in cryptography complexity lower bounds

    CERN Document Server

    Shparlinski, Igor

    1999-01-01

    The book introduces new techniques which imply rigorous lower bounds on the complexity of some number theoretic and cryptographic problems. These methods and techniques are based on bounds of character sums and numbers of solutions of some polynomial equations over finite fields and residue rings. It also contains a number of open problems and proposals for further research. We obtain several lower bounds, exponential in terms of logp, on the de­ grees and orders of • polynomials; • algebraic functions; • Boolean functions; • linear recurring sequences; coinciding with values of the discrete logarithm modulo a prime p at suf­ ficiently many points (the number of points can be as small as pI/He). These functions are considered over the residue ring modulo p and over the residue ring modulo an arbitrary divisor d of p - 1. The case of d = 2 is of special interest since it corresponds to the representation of the right­ most bit of the discrete logarithm and defines whether the argument is a quadratic...

  1. Subsampled Hessian Newton Methods for Supervised Learning.

    Science.gov (United States)

    Wang, Chien-Chih; Huang, Chun-Heng; Lin, Chih-Jen

    2015-08-01

    Newton methods can be applied in many supervised learning approaches. However, for large-scale data, the use of the whole Hessian matrix can be time-consuming. Recently, subsampled Newton methods have been proposed to reduce the computational time by using only a subset of data for calculating an approximation of the Hessian matrix. Unfortunately, we find that in some situations, the running speed is worse than the standard Newton method because cheaper but less accurate search directions are used. In this work, we propose some novel techniques to improve the existing subsampled Hessian Newton method. The main idea is to solve a two-dimensional subproblem per iteration to adjust the search direction to better minimize the second-order approximation of the function value. We prove the theoretical convergence of the proposed method. Experiments on logistic regression, linear SVM, maximum entropy, and deep networks indicate that our techniques significantly reduce the running time of the subsampled Hessian Newton method. The resulting algorithm becomes a compelling alternative to the standard Newton method for large-scale data classification.

  2. PROCESS-BASED LEARNING: TOWARDS THEORETICAL AND LECTURE-BASED COURSEWORK IN STUDIO STYLE

    Directory of Open Access Journals (Sweden)

    Hatem Ezzat Nabih

    2010-07-01

    Full Text Available This article presents a process-based learning approach to design education where theoretical coursework is taught in studio-style. Lecture-based coursework is sometimes regarded as lacking in challenge and broadening the gap between theory and practice. Furthermore, lecture-based curricula tend to be detached from the studio and deny students from applying their theoretically gained knowledge. Following the belief that student motivation is increased by establishing a higher level of autonomy in the learning process, I argue for a design education that links theory with applied design work within the studio setting. By synthesizing principles of Constructivist Learning and Problem-Based Learning, PBL students are given greater autonomy by being actively involved in their education. Accordingly, I argue for a studio setting that incorporates learning in studio style by presenting three design applications involving students in investigation and experimentation in order to self-experience the design process.

  3. A Narrative Approach to Both Teaching and Learning About Democracy with Young Children: A Theoretical Exploration

    Directory of Open Access Journals (Sweden)

    maila dinia husni rahim

    2016-03-01

    Full Text Available As adults, we often believe that children are only interested with games and children’s ‘stuff’. However research has shown that children do indeed show a greater interest in the world around them, including about politics, elections, and democracy. If we need to teach children about democracy, what are the best methods of teaching democracy to young children? Narrative is considered as an effective medium to convey messages to children and discuss hard subjects. This paper is a theoretical exploration that looks at the narrative approach to teaching and learning about democracy with young children. The researchers has used a literature review to look at why narratives should be used, what narratives should be used and how to use narratives.

  4. Theoretical Modelling Methods for Thermal Management of Batteries

    Directory of Open Access Journals (Sweden)

    Bahman Shabani

    2015-09-01

    Full Text Available The main challenge associated with renewable energy generation is the intermittency of the renewable source of power. Because of this, back-up generation sources fuelled by fossil fuels are required. In stationary applications whether it is a back-up diesel generator or connection to the grid, these systems are yet to be truly emissions-free. One solution to the problem is the utilisation of electrochemical energy storage systems (ESS to store the excess renewable energy and then reusing this energy when the renewable energy source is insufficient to meet the demand. The performance of an ESS amongst other things is affected by the design, materials used and the operating temperature of the system. The operating temperature is critical since operating an ESS at low ambient temperatures affects its capacity and charge acceptance while operating the ESS at high ambient temperatures affects its lifetime and suggests safety risks. Safety risks are magnified in renewable energy storage applications given the scale of the ESS required to meet the energy demand. This necessity has propelled significant effort to model the thermal behaviour of ESS. Understanding and modelling the thermal behaviour of these systems is a crucial consideration before designing an efficient thermal management system that would operate safely and extend the lifetime of the ESS. This is vital in order to eliminate intermittency and add value to renewable sources of power. This paper concentrates on reviewing theoretical approaches used to simulate the operating temperatures of ESS and the subsequent endeavours of modelling thermal management systems for these systems. The intent of this review is to present some of the different methods of modelling the thermal behaviour of ESS highlighting the advantages and disadvantages of each approach.

  5. Teaching learning methods of an entrepreneurship curriculum

    Directory of Open Access Journals (Sweden)

    KERAMAT ESMI

    2015-10-01

    Full Text Available Introduction: One of the most significant elements of entrepreneurship curriculum design is teaching-learning methods, which plays a key role in studies and researches related to such a curriculum. It is the teaching method, and systematic, organized and logical ways of providing lessons that should be consistent with entrepreneurship goals and contents, and should also be developed according to the learners’ needs. Therefore, the current study aimed to introduce appropriate, modern, and effective methods of teaching entrepreneurship and their validation Methods: This is a mixed method research of a sequential exploratory kind conducted through two stages: a developing teaching methods of entrepreneurship curriculum, and b validating developed framework. Data were collected through “triangulation” (study of documents, investigating theoretical basics and the literature, and semi-structured interviews with key experts. Since the literature on this topic is very rich, and views of the key experts are vast, directed and summative content analysis was used. In the second stage, qualitative credibility of research findings was obtained using qualitative validation criteria (credibility, confirmability, and transferability, and applying various techniques. Moreover, in order to make sure that the qualitative part is reliable, reliability test was used. Moreover, quantitative validation of the developed framework was conducted utilizing exploratory and confirmatory factor analysis methods and Cronbach’s alpha. The data were gathered through distributing a three-aspect questionnaire (direct presentation teaching methods, interactive, and practical-operational aspects with 29 items among 90 curriculum scholars. Target population was selected by means of purposive sampling and representative sample. Results: Results obtained from exploratory factor analysis showed that a three factor structure is an appropriate method for describing elements of

  6. Teaching learning methods of an entrepreneurship curriculum.

    Science.gov (United States)

    Esmi, Keramat; Marzoughi, Rahmatallah; Torkzadeh, Jafar

    2015-10-01

    One of the most significant elements of entrepreneurship curriculum design is teaching-learning methods, which plays a key role in studies and researches related to such a curriculum. It is the teaching method, and systematic, organized and logical ways of providing lessons that should be consistent with entrepreneurship goals and contents, and should also be developed according to the learners' needs. Therefore, the current study aimed to introduce appropriate, modern, and effective methods of teaching entrepreneurship and their validation. This is a mixed method research of a sequential exploratory kind conducted through two stages: a) developing teaching methods of entrepreneurship curriculum, and b) validating developed framework. Data were collected through "triangulation" (study of documents, investigating theoretical basics and the literature, and semi-structured interviews with key experts). Since the literature on this topic is very rich, and views of the key experts are vast, directed and summative content analysis was used. In the second stage, qualitative credibility of research findings was obtained using qualitative validation criteria (credibility, confirmability, and transferability), and applying various techniques. Moreover, in order to make sure that the qualitative part is reliable, reliability test was used. Moreover, quantitative validation of the developed framework was conducted utilizing exploratory and confirmatory factor analysis methods and Cronbach's alpha. The data were gathered through distributing a three-aspect questionnaire (direct presentation teaching methods, interactive, and practical-operational aspects) with 29 items among 90 curriculum scholars. Target population was selected by means of purposive sampling and representative sample. Results obtained from exploratory factor analysis showed that a three factor structure is an appropriate method for describing elements of teaching-learning methods of entrepreneurship curriculum

  7. Proverbs as Theoretical Frameworks for Lifelong Learning in Indigenous African Education

    Science.gov (United States)

    Avoseh, Mejai B. M.

    2013-01-01

    Every aspect of a community's life and values in indigenous Africa provide the theoretical framework for education. The holistic worldview of the traditional system places a strong emphasis on the centrality of the human element and orature in the symmetrical relationship between life and learning. This article focuses on proverbs and the words…

  8. New e-learning method using databases

    Directory of Open Access Journals (Sweden)

    Andreea IONESCU

    2012-10-01

    Full Text Available The objective of this paper is to present a new e-learning method that use databases. The solution could pe implemented for any typeof e-learning system in any domain. The article will purpose a solution to improve the learning process for virtual classes.

  9. Experts in Teams – An experiential learning method

    DEFF Research Database (Denmark)

    Johansen, Steffen Kjær

    2017-01-01

    T becomes a learning method rather than a teaching method. Besides discussing the pedagogical characteristics of EiT, the study also gives a general introduction to EiT as it was taught at SDU fall 2016 as well as a brief review of the basic theory behind experiential learning. As such this study serves...... courses. Most of the practical courses are group work along the lines of project based learning. EiT is in a way both. It is a practical course in as much as our students get hands-on experience with interdisciplinary team work and innovation processes. EiT is a theoretical course in as much as our...... both as an introduction to e.g. new teachers of EiT but also as a starting point for a clarification of the features that makes EiT an experiential learning endeavor....

  10. Numerical Methods Application for Reinforced Concrete Elements-Theoretical Approach for Direct Stiffness Matrix Method

    Directory of Open Access Journals (Sweden)

    Sergiu Ciprian Catinas

    2015-07-01

    Full Text Available A detailed theoretical and practical investigation of the reinforced concrete elements is due to recent techniques and method that are implemented in the construction market. More over a theoretical study is a demand for a better and faster approach nowadays due to rapid development of the calculus technique. The paper above will present a study for implementing in a static calculus the direct stiffness matrix method in order capable to address phenomena related to different stages of loading, rapid change of cross section area and physical properties. The method is a demand due to the fact that in our days the FEM (Finite Element Method is the only alternative to such a calculus and FEM are considered as expensive methods from the time and calculus resources point of view. The main goal in such a method is to create the moment-curvature diagram in the cross section that is analyzed. The paper above will express some of the most important techniques and new ideas as well in order to create the moment curvature graphic in the cross sections considered.

  11. Theoretical framework on selected core issues on conditions for productive learning in networked learning environments

    DEFF Research Database (Denmark)

    Dirckinck-Holmfeld, Lone; Svendsen, Brian Møller; Ponti, Marisa

    The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments.......The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments....

  12. How A Flipped Learning Environment Affects Learning In A Course On Theoretical Computer Science

    DEFF Research Database (Denmark)

    Gnaur, Dorina; Hüttel, Hans

    2014-01-01

    This paper reports initial experiences with flipping the classroom in an undergraduate computer science course as part of an overall attempt to enhance the pedagogical support for student learning. Our findings indicate that, just as the flipped classroom implies, a shift of focus in the learning...... context influences the way students engage with the course and their learning strategies....

  13. The learning technique. Theoretical considerations for planning lessons wit h a strategic learning approach

    Directory of Open Access Journals (Sweden)

    Dania Regueira Martínez

    2014-03-01

    Full Text Available This article presents the learning task considered as the unit of smaller organization level in the teaching-learning process that conditions in its systemic structuring, the learning actions, for the students acquisition of the content, by means of the development of the reflection and the metacognitiv e regulation when they conscious ly or partially plan different types of learning strategies in the ir realization, with the objective to solv e the pedagogic professional problems that are p resented in the disciplines they receive and in its research task during the direction o f the teaching-learning process.

  14. Theoretical prediction method of subcooled flow boiling CHF

    Energy Technology Data Exchange (ETDEWEB)

    Kwon, Young Min; Chang, Soon Heung [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1999-12-31

    A theoretical critical heat flux (CHF ) model, based on lateral bubble coalescence on the heated wall, is proposed to predict the subcooled flow boiling CHF in a uniformly heated vertical tube. The model is based on the concept that a single layer of bubbles contacted to the heated wall prevents a bulk liquid from reaching the wall at near CHF condition. Comparisons between the model predictions and experimental data result in satisfactory agreement within less than 9.73% root-mean-square error by the appropriate choice of the critical void fraction in the bubbly layer. The present model shows comparable performance with the CHF look-up table of Groeneveld et al.. 28 refs., 11 figs., 1 tab. (Author)

  15. Theoretical prediction method of subcooled flow boiling CHF

    Energy Technology Data Exchange (ETDEWEB)

    Kwon, Young Min; Chang, Soon Heung [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

    1998-12-31

    A theoretical critical heat flux (CHF ) model, based on lateral bubble coalescence on the heated wall, is proposed to predict the subcooled flow boiling CHF in a uniformly heated vertical tube. The model is based on the concept that a single layer of bubbles contacted to the heated wall prevents a bulk liquid from reaching the wall at near CHF condition. Comparisons between the model predictions and experimental data result in satisfactory agreement within less than 9.73% root-mean-square error by the appropriate choice of the critical void fraction in the bubbly layer. The present model shows comparable performance with the CHF look-up table of Groeneveld et al.. 28 refs., 11 figs., 1 tab. (Author)

  16. Detecting Network Vulnerabilities Through Graph TheoreticalMethods

    Energy Technology Data Exchange (ETDEWEB)

    Cesarz, Patrick; Pomann, Gina-Maria; Torre, Luis de la; Villarosa, Greta; Flournoy, Tamara; Pinar, Ali; Meza Juan

    2007-09-30

    Identifying vulnerabilities in power networks is an important problem, as even a small number of vulnerable connections can cause billions of dollars in damage to a network. In this paper, we investigate a graph theoretical formulation for identifying vulnerabilities of a network. We first try to find the most critical components in a network by finding an optimal solution for each possible cutsize constraint for the relaxed version of the inhibiting bisection problem, which aims to find loosely coupled subgraphs with significant demand/supply mismatch. Then we investigate finding critical components by finding a flow assignment that minimizes the maximum among flow assignments on all edges. We also report experiments on IEEE 30, IEEE 118, and WSCC 179 benchmark power networks.

  17. Learning Science, Learning about Science, Doing Science: Different Goals Demand Different Learning Methods

    Science.gov (United States)

    Hodson, Derek

    2014-01-01

    This opinion piece paper urges teachers and teacher educators to draw careful distinctions among four basic learning goals: learning science, learning about science, doing science and learning to address socio-scientific issues. In elaboration, the author urges that careful attention is paid to the selection of teaching/learning methods that…

  18. Theoretical studies of densiometric methods using γ-radiation

    International Nuclear Information System (INIS)

    Luebbesmeyer, D.; Wesser, U.

    1975-10-01

    Some conclusions could be drawn from the calculations performed for the practical measuring method to be applied: 1) The incident method for the density measurement of an inhomogenous two-phase flow involves a lot of errors. 2) Should one, due to limited expense, only use two detectors for the measuring chains, then the scattered-beam method is more advantageous than the two-beam method. 3) If three detectors can be used, a greater accuracy can be expected than with the scattered-beam method. 4) The accuracy of all methods increases if a certain homogenity of a part of the flow is allowed. 5) The most favourable energy region is different for scattered-beam and multi-beam processes. Whereas the scattered-beam method can be used to an optimum at energies of about 60 KeV due to the enlarged scattering cross sections at small radiation energies, the energies with multi-beam methods should be more than 100 KeV. 6) If small calibration problems are important, than the multi-beam method is preferable to the scattered-beam method. A good compromise between apparative expenditure and the accuracy to be obtained is the three-beam method with, e.g., 137 Cs as a source. (orig./LH) [de

  19. Methods for control over learning individual trajectory

    Science.gov (United States)

    Mitsel, A. A.; Cherniaeva, N. V.

    2015-09-01

    The article discusses models, methods and algorithms of determining student's optimal individual educational trajectory. A new method of controlling the learning trajectory has been developed as a dynamic model of learning trajectory control, which uses score assessment to construct a sequence of studied subjects.

  20. The Guided Autobiography Method: A Learning Experience

    Science.gov (United States)

    Thornton, James E.

    2008-01-01

    This article discusses the proposition that learning is an unexplored feature of the guided autobiography method and its developmental exchange. Learning, conceptualized and explored as the embedded and embodied processes, is essential in narrative activities of the guided autobiography method leading to psychosocial development and growth in…

  1. Active teaching methods, studying responses and learning

    DEFF Research Database (Denmark)

    Christensen, Hans Peter; Vigild, Martin Etchells; Thomsen, Erik Vilain

    2010-01-01

    Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching. The resulting learning outcome is discussed.......Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching. The resulting learning outcome is discussed....

  2. Praxis and reflexivity for interprofessional education: towards an inclusive theoretical framework for learning.

    Science.gov (United States)

    Hutchings, Maggie; Scammell, Janet; Quinney, Anne

    2013-09-01

    While there is growing evidence of theoretical perspectives adopted in interprofessional education, learning theories tend to foreground the individual, focusing on psycho-social aspects of individual differences and professional identity to the detriment of considering social-structural factors at work in social practices. Conversely socially situated practice is criticised for being context-specific, making it difficult to draw generalisable conclusions for improving interprofessional education. This article builds on a theoretical framework derived from earlier research, drawing on the dynamics of Dewey's experiential learning theory and Archer's critical realist social theory, to make a case for a meta-theoretical framework enabling social-constructivist and situated learning theories to be interlinked and integrated through praxis and reflexivity. Our current analysis is grounded in an interprofessional curriculum initiative mediated by a virtual community peopled by health and social care users. Student perceptions, captured through quantitative and qualitative data, suggest three major disruptive themes, creating opportunities for congruence and disjuncture and generating a model of zones of interlinked praxis associated with professional differences and identity, pedagogic strategies and technology-mediated approaches. This model contributes to a framework for understanding the complexity of interprofessional learning and offers bridges between individual and structural factors for engaging with the enablements and constraints at work in communities of practice and networks for interprofessional education.

  3. Theoretical analysis and experimental study of spray degassing method

    International Nuclear Information System (INIS)

    Wu Ruizhi; Shu Da; Sun Baode; Wang Jun; Li Fei; Chen Haiyan; Lu YanLing

    2005-01-01

    A new hydrogen-removal method of aluminum melt, spray degassing, is presented. The thermodynamic and kinetic analysis of the method are discussed. A comparison between the thermodynamics and kinetics of the spray degassing method and rotary impellor degassing method is made. The thermodynamic analysis shows that the relationship between the final hydrogen content of the aluminum melt and the ratio of purge gas flow rate to melt flow rate is linear. The result of thermodynamic calculation shows that, in spray degassing, when the ratio of G/q is larger than 2.2 x 10 -6 , the final hydrogen content will be less than 0.1 ml/100 g Al. From the kinetic analysis, the degassing effect is affected by both the size of melt droplets and the time that melt droplets move from sprayer to the bottom of the treatment tank. In numerical calculation, the hydrogen in aluminum melt can be degassed to 0.05 ml/100 g Al from 0.2 ml/100 g Al in 0.02 s with the spray degassing method. Finally, the water-model experiments are presented with the spray degassing method and rotary impellor degassing method. Melt experiments are also presented. Both the water-model experiments and the melt experiments show that the degassing effect of the spray degassing method is better than that of the rotary impeller method

  4. Dynamical Systems Method and Applications Theoretical Developments and Numerical Examples

    CERN Document Server

    Ramm, Alexander G

    2012-01-01

    Demonstrates the application of DSM to solve a broad range of operator equations The dynamical systems method (DSM) is a powerful computational method for solving operator equations. With this book as their guide, readers will master the application of DSM to solve a variety of linear and nonlinear problems as well as ill-posed and well-posed problems. The authors offer a clear, step-by-step, systematic development of DSM that enables readers to grasp the method's underlying logic and its numerous applications. Dynamical Systems Method and Applications begins with a general introduction and

  5. Ensemble Machine Learning Methods and Applications

    CERN Document Server

    Ma, Yunqian

    2012-01-01

    It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face detection and are now being applied in areas as diverse as object trackingand bioinformatics.   Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including various contributions from researchers in leading industrial research labs. At once a solid theoretical study and a practical guide, the volume is a windfall for r...

  6. Facilitating behavioral learning and habit change in voice therapy—theoretic premises and practical strategies

    DEFF Research Database (Denmark)

    Iwarsson, Jenny

    2014-01-01

    A typical goal of voice therapy is a behavioral change in the patient’s everyday speech. The SLP’s plan for voice therapy should therefore optimally include strategies for automatization. The aim of the present study was to identify and describe factors that promote behavioral learning and habit...... are described and discussed from a learning theory perspective. Nine factors that seem to be relevant to facilitate behavioral learning and habit change in voice therapy are presented, together with related practical strategies and theoretical underpinnings. These are: 1) Cue-altering; 2) Attention exercises; 3...... change in voice behavior and have the potential to affect patient compliance and thus therapy outcome. Research literature from the areas of motor and behavioral learning, habit formation, and habit change was consulted. Also, specific elements from personal experience of clinical voice therapy...

  7. After Fukushima? On the educational and learning theoretical reflection of nuclear disasters. International perspectives

    International Nuclear Information System (INIS)

    Wigger, Lothar; Buenger, Carsten

    2017-01-01

    The book on the educational and learning theoretical reflection of nuclear disasters as a consequence of Fukushima includes contributions on the following issues: pedagogical approach: children write on Fukushima, description of the reality as pedagogical challenge; lessons learned on the nuclear technology - perspectives and limits of pedagogical evaluation: moral education - Japanese teaching materials, educational challenges at the universities with respect to nuclear technology and technology impact assessment; education and technology - questions concerning the pedagogical responsibility: considerations on the responsibility of scientists, on the discrepancy between technology and education, disempowerment of the public by structural corruption - nuclear disaster and post-democratic tendencies in Japan.

  8. Theoretical method for determining particle distribution functions of classical systems

    International Nuclear Information System (INIS)

    Johnson, E.

    1980-01-01

    An equation which involves the triplet distribution function and the three-particle direct correlation function is obtained. This equation was derived using an analogue of the Ornstein--Zernike equation. The new equation is used to develop a variational method for obtaining the triplet distribution function of uniform one-component atomic fluids from the pair distribution function. The variational method may be used with the first and second equations in the YBG hierarchy to obtain pair and triplet distribution functions. It should be easy to generalize the results to the n-particle distribution function

  9. The influence of leadership in the working environment, teamwork and organisational learning : a theoretical review

    OpenAIRE

    Lacedón Montemayor, Marta

    2016-01-01

    Treball Final de Grau en Administració d'Empreses. Codi: AE1049. Curs: 2015/2016 The objective of this paper is to examine the influence that leadership has on creating a good working environment, on work teams and on organisational learning, through a theoretical revision. For this, concepts are addressed related to leadership such as the leader's profile, the role he represents within an organisation, his functions and skills, which will help us understand the importance of ...

  10. A Theoretical Perspective on the Case Study Method

    Science.gov (United States)

    Çakmak, Zafer; Akgün, Ismail Hakan

    2018-01-01

    Ensuring that students reach the determined goals of the courses at the desired level is one of the primary goals of teaching. In order to achieve this purpose, educators use a variety of teaching strategies and methods, and teaching materials appropriate to the content and the subject of the courses in the teaching process. As a matter of fact,…

  11. Integral methods in science and engineering theoretical and practical aspects

    CERN Document Server

    Constanda, C; Rollins, D

    2006-01-01

    Presents a series of analytic and numerical methods of solution constructed for important problems arising in science and engineering, based on the powerful operation of integration. This volume is meant for researchers and practitioners in applied mathematics, physics, and mechanical and electrical engineering, as well as graduate students.

  12. Theoretical aspects of new options of sublevel caving methods

    Directory of Open Access Journals (Sweden)

    Ladislav Kačmár

    2008-12-01

    Full Text Available The article deals with the proposal of the SMZ Jelšava a.s. exploitation issue. Author refers to possible options of the new methodsaplication, which rises of the theory of gravity flow loose and blasting rocks. With mentioned methods the safety of exploitation couldbe higher, especially in bigger depths.

  13. The Ulam Index: Methods of Theoretical Computer Science Help in Identifying Chemical Substances

    Science.gov (United States)

    Beltran, Adriana; Salvador, James

    1997-01-01

    In this paper, we show how methods developed for solving a theoretical computer problem of graph isomorphism are used in structural chemistry. We also discuss potential applications of these methods to exobiology: the search for life outside Earth.

  14. Nonstationary Hydrological Frequency Analysis: Theoretical Methods and Application Challenges

    Science.gov (United States)

    Xiong, L.

    2014-12-01

    Because of its great implications in the design and operation of hydraulic structures under changing environments (either climate change or anthropogenic changes), nonstationary hydrological frequency analysis has become so important and essential. Two important achievements have been made in methods. Without adhering to the consistency assumption in the traditional hydrological frequency analysis, the time-varying probability distribution of any hydrological variable can be established by linking the distribution parameters to some covariates such as time or physical variables with the help of some powerful tools like the Generalized Additive Model of Location, Scale and Shape (GAMLSS). With the help of copulas, the multivariate nonstationary hydrological frequency analysis has also become feasible. However, applications of the nonstationary hydrological frequency formula to the design and operation of hydraulic structures for coping with the impacts of changing environments in practice is still faced with many challenges. First, the nonstationary hydrological frequency formulae with time as covariate could only be extrapolated for a very short time period beyond the latest observation time, because such kind of formulae is not physically constrained and the extrapolated outcomes could be unrealistic. There are two physically reasonable methods that can be used for changing environments, one is to directly link the quantiles or the distribution parameters to some measureable physical factors, and the other is to use the derived probability distributions based on hydrological processes. However, both methods are with a certain degree of uncertainty. For the design and operation of hydraulic structures under changing environments, it is recommended that design results of both stationary and nonstationary methods be presented together and compared with each other, to help us understand the potential risks of each method.

  15. Theoretical and applied aerodynamics and related numerical methods

    CERN Document Server

    Chattot, J J

    2015-01-01

    This book covers classical and modern aerodynamics, theories and related numerical methods, for senior and first-year graduate engineering students, including: -The classical potential (incompressible) flow theories for low speed aerodynamics of thin airfoils and high and low aspect ratio wings. - The linearized theories for compressible subsonic and supersonic aerodynamics. - The nonlinear transonic small disturbance potential flow theory, including supercritical wing sections, the extended transonic area rule with lift effect, transonic lifting line and swept or oblique wings to minimize wave drag. Unsteady flow is also briefly discussed. Numerical simulations based on relaxation mixed-finite difference methods are presented and explained. - Boundary layer theory for all Mach number regimes and viscous/inviscid interaction procedures used in practical aerodynamics calculations. There are also four chapters covering special topics, including wind turbines and propellers, airplane design, flow analogies and h...

  16. Group theoretical methods and wavelet theory: coorbit theory and applications

    Science.gov (United States)

    Feichtinger, Hans G.

    2013-05-01

    Before the invention of orthogonal wavelet systems by Yves Meyer1 in 1986 Gabor expansions (viewed as discretized inversion of the Short-Time Fourier Transform2 using the overlap and add OLA) and (what is now perceived as) wavelet expansions have been treated more or less at an equal footing. The famous paper on painless expansions by Daubechies, Grossman and Meyer3 is a good example for this situation. The description of atomic decompositions for functions in modulation spaces4 (including the classical Sobolev spaces) given by the author5 was directly modeled according to the corresponding atomic characterizations by Frazier and Jawerth,6, 7 more or less with the idea of replacing the dyadic partitions of unity of the Fourier transform side by uniform partitions of unity (so-called BUPU's, first named as such in the early work on Wiener-type spaces by the author in 19808). Watching the literature in the subsequent two decades one can observe that the interest in wavelets "took over", because it became possible to construct orthonormal wavelet systems with compact support and of any given degree of smoothness,9 while in contrast the Balian-Low theorem is prohibiting the existence of corresponding Gabor orthonormal bases, even in the multi-dimensional case and for general symplectic lattices.10 It is an interesting historical fact that* his construction of band-limited orthonormal wavelets (the Meyer wavelet, see11) grew out of an attempt to prove the impossibility of the existence of such systems, and the final insight was that it was not impossible to have such systems, and in fact quite a variety of orthonormal wavelet system can be constructed as we know by now. Meanwhile it is established wisdom that wavelet theory and time-frequency analysis are two different ways of decomposing signals in orthogonal resp. non-orthogonal ways. The unifying theory, covering both cases, distilling from these two situations the common group theoretical background lead to the

  17. Towards a Theoretical Framework for Understanding PGCE Student Teacher Learning in the Wild Coast Rural Schools' Partnership Project

    Science.gov (United States)

    Pennefather, Jane

    2016-01-01

    This article focuses on a theoretical model that I am developing in order to understand student teacher learning in a rural context and the enabling conditions that can support this learning. The question of whether a supervised teaching practice in a rural context can contribute to the development of student teacher professional learning and…

  18. A Learning Method for Neural Networks Based on a Pseudoinverse Technique

    Directory of Open Access Journals (Sweden)

    Chinmoy Pal

    1996-01-01

    Full Text Available A theoretical formulation of a fast learning method based on a pseudoinverse technique is presented. The efficiency and robustness of the method are verified with the help of an Exclusive OR problem and a dynamic system identification of a linear single degree of freedom mass–spring problem. It is observed that, compared with the conventional backpropagation method, the proposed method has a better convergence rate and a higher degree of learning accuracy with a lower equivalent learning coefficient. It is also found that unlike the steepest descent method, the learning capability of which is dependent on the value of the learning coefficient ν, the proposed pseudoinverse based backpropagation algorithm is comparatively robust with respect to its equivalent variable learning coefficient. A combination of the pseudoinverse method and the steepest descent method is proposed for a faster, more accurate learning capability.

  19. Kernel methods for deep learning

    OpenAIRE

    Cho, Youngmin

    2012-01-01

    We introduce a new family of positive-definite kernels that mimic the computation in large neural networks. We derive the different members of this family by considering neural networks with different activation functions. Using these kernels as building blocks, we also show how to construct other positive-definite kernels by operations such as composition, multiplication, and averaging. We explore the use of these kernels in standard models of supervised learning, such as support vector mach...

  20. Acceptance of technology-enhanced learning for a theoretical radiological science course: a randomized controlled trial.

    Science.gov (United States)

    Nkenke, Emeka; Vairaktaris, Elefterios; Bauersachs, Anne; Eitner, Stephan; Budach, Alexander; Knipfer, Christoph; Stelzle, Florian

    2012-03-30

    Technology-enhanced learning (TEL) gives a view to improved education. However, there is a need to clarify how TEL can be used effectively. The study compared students' attitudes and opinions towards a traditional face-to-face course on theoretical radiological science and a TEL course where students could combine face-to-face lectures and e-learning modules at their best convenience. 42 third-year dental students were randomly assigned to the traditional face-to-face group and the TEL group. Both groups completed questionnaires before the beginning and after completion of the course on attitudes and opinions towards a traditional face-to-face lectures and technology-enhanced learning. After completion of the course both groups also filled in the validated German-language TRIL (Trierer Inventar zur Lehrevaluation) questionnaire for the evaluation of courses given at universities. Both groups had a positive attitude towards e-learning that did not change over time. The TEL group attended significantly less face-to-face lectures than the traditional group. However, both groups stated that face-to-face lectures were the basis for education in a theoretical radiological science course. The members of the TEL group rated e-mail reminders significantly more important when they filled in the questionnaire on attitudes and opinions towards a traditional face-to-face lectures and technology-enhanced learning for the second time after completion of the course. The members of the technology-enhanced learning group were significantly less confident in passing the exam compared to the members of the traditional group. However, examination results did not differ significantly for traditional and the TEL group. It seems that technology-enhanced learning in a theoretical radiological science course has the potential to reduce the need for face-to-face lectures. At the same time examination results are not impaired. However, technology-enhanced learning cannot completely replace

  1. Learning theories and tools for the assessment of core nursing competencies in simulation: A theoretical review.

    Science.gov (United States)

    Lavoie, Patrick; Michaud, Cécile; Bélisle, Marilou; Boyer, Louise; Gosselin, Émilie; Grondin, Myrian; Larue, Caroline; Lavoie, Stéphan; Pepin, Jacinthe

    2018-02-01

    To identify the theories used to explain learning in simulation and to examine how these theories guided the assessment of learning outcomes related to core competencies in undergraduate nursing students. Nurse educators face the challenge of making explicit the outcomes of competency-based education, especially when competencies are conceptualized as holistic and context dependent. Theoretical review. Research papers (N = 182) published between 1999-2015 describing simulation in nursing education. Two members of the research team extracted data from the papers, including theories used to explain how simulation could engender learning and tools used to assess simulation outcomes. Contingency tables were created to examine the associations between theories, outcomes and tools. Some papers (N = 79) did not provide an explicit theory. The 103 remaining papers identified one or more learning or teaching theories; the most frequent were the National League for Nursing/Jeffries Simulation Framework, Kolb's theory of experiential learning and Bandura's social cognitive theory and concept of self-efficacy. Students' perceptions of simulation, knowledge and self-confidence were the most frequently assessed, mainly via scales designed for the study where they were used. Core competencies were mostly assessed with an observational approach. This review highlighted the fact that few studies examined the use of simulation in nursing education through learning theories and via assessment of core competencies. It also identified observational tools used to assess competencies in action, as holistic and context-dependent constructs. © 2017 John Wiley & Sons Ltd.

  2. Information theoretic methods for image processing algorithm optimization

    Science.gov (United States)

    Prokushkin, Sergey F.; Galil, Erez

    2015-01-01

    Modern image processing pipelines (e.g., those used in digital cameras) are full of advanced, highly adaptive filters that often have a large number of tunable parameters (sometimes > 100). This makes the calibration procedure for these filters very complex, and the optimal results barely achievable in the manual calibration; thus an automated approach is a must. We will discuss an information theory based metric for evaluation of algorithm adaptive characteristics ("adaptivity criterion") using noise reduction algorithms as an example. The method allows finding an "orthogonal decomposition" of the filter parameter space into the "filter adaptivity" and "filter strength" directions. This metric can be used as a cost function in automatic filter optimization. Since it is a measure of a physical "information restoration" rather than perceived image quality, it helps to reduce the set of the filter parameters to a smaller subset that is easier for a human operator to tune and achieve a better subjective image quality. With appropriate adjustments, the criterion can be used for assessment of the whole imaging system (sensor plus post-processing).

  3. Activating teaching methods, studying responses and learning

    OpenAIRE

    Christensen, Hans Peter; Vigild, Martin E.; Thomsen, Erik; Szabo, Peter; Horsewell, Andy

    2009-01-01

    Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching. The resulting learning outcome is discussed. Peer Reviewed

  4. Effect of Methods of Learning and Self Regulated Learning toward Outcomes of Learning Social Studies

    Science.gov (United States)

    Tjalla, Awaluddin; Sofiah, Evi

    2015-01-01

    This research aims to reveal the influence of learning methods and self-regulated learning on students learning scores for Social Studies object. The research was done in Islamic Junior High School (MTs Manba'ul Ulum), Batuceper City Tangerang using quasi-experimental method. The research employed simple random technique to 28 students. Data were…

  5. Active learning methods for interactive image retrieval.

    Science.gov (United States)

    Gosselin, Philippe Henri; Cord, Matthieu

    2008-07-01

    Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensions are now being proposed to handle multimedia applications. This paper provides algorithms within a statistical framework to extend active learning for online content-based image retrieval (CBIR). The classification framework is presented with experiments to compare several powerful classification techniques in this information retrieval context. Focusing on interactive methods, active learning strategy is then described. The limitations of this approach for CBIR are emphasized before presenting our new active selection process RETIN. First, as any active method is sensitive to the boundary estimation between classes, the RETIN strategy carries out a boundary correction to make the retrieval process more robust. Second, the criterion of generalization error to optimize the active learning selection is modified to better represent the CBIR objective of database ranking. Third, a batch processing of images is proposed. Our strategy leads to a fast and efficient active learning scheme to retrieve sets of online images (query concept). Experiments on large databases show that the RETIN method performs well in comparison to several other active strategies.

  6. Deep Learning and Bayesian Methods

    Directory of Open Access Journals (Sweden)

    Prosper Harrison B.

    2017-01-01

    Full Text Available A revolution is underway in which deep neural networks are routinely used to solve diffcult problems such as face recognition and natural language understanding. Particle physicists have taken notice and have started to deploy these methods, achieving results that suggest a potentially significant shift in how data might be analyzed in the not too distant future. We discuss a few recent developments in the application of deep neural networks and then indulge in speculation about how such methods might be used to automate certain aspects of data analysis in particle physics. Next, the connection to Bayesian methods is discussed and the paper ends with thoughts on a significant practical issue, namely, how, from a Bayesian perspective, one might optimize the construction of deep neural networks.

  7. Learning styles: The learning methods of air traffic control students

    Science.gov (United States)

    Jackson, Dontae L.

    In the world of aviation, air traffic controllers are an integral part in the overall level of safety that is provided. With a number of controllers reaching retirement age, the Air Traffic Collegiate Training Initiative (AT-CTI) was created to provide a stronger candidate pool. However, AT-CTI Instructors have found that a number of AT-CTI students are unable to memorize types of aircraft effectively. This study focused on the basic learning styles (auditory, visual, and kinesthetic) of students and created a teaching method to try to increase memorization in AT-CTI students. The participants were asked to take a questionnaire to determine their learning style. Upon knowing their learning styles, participants attended two classroom sessions. The participants were given a presentation in the first class, and divided into a control and experimental group for the second class. The control group was given the same presentation from the first classroom session while the experimental group had a group discussion and utilized Middle Tennessee State University's Air Traffic Control simulator to learn the aircraft types. Participants took a quiz and filled out a survey, which tested the new teaching method. An appropriate statistical analysis was applied to determine if there was a significant difference between the control and experimental groups. The results showed that even though the participants felt that the method increased their learning, there was no significant difference between the two groups.

  8. Pragmatics of Contemporary Teaching and Learning Methods

    Directory of Open Access Journals (Sweden)

    Ryszard Józef Panfil

    2013-09-01

    Full Text Available The dynamics of the environment in which educational institutions operate have a significant influence on the basic activity of these institutions, i.e. the process of educating, and particularly teaching and learning methods used during that process: traditional teaching, tutoring, mentoring and coaching. The identity of an educational institution and the appeal of its services depend on how flexible, diverse and adaptable is the educational process it offers as a core element of its services. Such a process is determined by how its pragmatism is displayed in the operational relativism of methods, their applicability, as well as practical dimension of achieved results and values. Based on the above premises, this publication offers a pragmatic-systemic identification of contemporary teaching and learning methods, while taking into account the differences between them and the scope of their compatibility. Secondly, using the case of sport coaches’ education, the author exemplifies the pragmatic theory of perception of contemporary teaching and learning methods.

  9. Exploring the Learning of Language Through Global Dance and Music: a Theoretical Analysis

    OpenAIRE

    Banafi, Norah

    2014-01-01

    This research paper explores theories behind Total Physical Response (T.P.R) methods and psychology by associating them with music in order to examine the role of listening to music and dancing in language learning. This research utilises the five pillars of Zumba (music, dance, the power of now, enjoyment, and relaxing) that may create an environment for motivating language fluency learning and investigates whether these pillars have the potential for making Zumba, a global phenomenon in tea...

  10. e-Learning Business Research Methods

    Science.gov (United States)

    Cowie, Jonathan

    2004-01-01

    This paper outlines the development of a generic Business Research Methods course from a simple name in a box to a full e-Learning web based module. It highlights particular issues surrounding the nature of the discipline and the integration of a large number of cross faculty subject specific research methods courses into a single generic module.…

  11. Facilitating behavioral learning and habit change in voice therapy--theoretic premises and practical strategies.

    Science.gov (United States)

    Iwarsson, Jenny

    2015-12-01

    A typical goal of voice therapy is a behavioral change in the patient's everyday speech. The SLP's plan for voice therapy should therefore optimally include strategies for automatization. The aim of the present study was to identify and describe factors that promote behavioral learning and habit change in voice behavior and have the potential to affect patient compliance and thus therapy outcome. Research literature from the areas of motor and behavioral learning, habit formation, and habit change was consulted. Also, specific elements from personal experience of clinical voice therapy are described and discussed from a learning theory perspective. Nine factors that seem to be relevant to facilitate behavioral learning and habit change in voice therapy are presented, together with related practical strategies and theoretical underpinnings. These are: 1) Cue-altering; 2) Attention exercises; 3) Repetition; 4) Cognitive activation; 5) Negative practice; 6) Inhibition through interruption; 7) Decomposing complex behavior; 8) The 'each time-every time' principle; and 9) Successive implementation of automaticity.

  12. Deep Learning and Bayesian Methods

    OpenAIRE

    Prosper Harrison B.

    2017-01-01

    A revolution is underway in which deep neural networks are routinely used to solve diffcult problems such as face recognition and natural language understanding. Particle physicists have taken notice and have started to deploy these methods, achieving results that suggest a potentially significant shift in how data might be analyzed in the not too distant future. We discuss a few recent developments in the application of deep neural networks and then indulge in speculation about how such meth...

  13. Characterizing Reinforcement Learning Methods through Parameterized Learning Problems

    Science.gov (United States)

    2011-06-03

    extraneous. The agent could potentially adapt these representational aspects by applying methods from feature selection ( Kolter and Ng, 2009; Petrik et al...611–616. AAAI Press. Kolter , J. Z. and Ng, A. Y. (2009). Regularization and feature selection in least-squares temporal difference learning. In A. P

  14. Tracking by Machine Learning Methods

    CERN Document Server

    Jofrehei, Arash

    2015-01-01

    Current track reconstructing methods start with two points and then for each layer loop through all possible hits to find proper hits to add to that track. Another idea would be to use this large number of already reconstructed events and/or simulated data and train a machine on this data to find tracks given hit pixels. Training time could be long but real time tracking is really fast Simulation might not be as realistic as real data but tacking has been done for that with 100 percent efficiency while by using real data we would probably be limited to current efficiency.

  15. Technology-mediated collaborative learning: theoretical contributions based on analysis of educational practice

    Directory of Open Access Journals (Sweden)

    Sonia CASILLAS MARTÍN

    2017-12-01

    Full Text Available Collaborative learning has been a subject of great interest in the context of educational research, giving rise to many studies emphasizing the potential of the collaboration process in student learning, knowledge building, the development of diverse abilities and improved academic performance. Based on a conceptual review and thorough reflection on this topic, this article presents the results of a case study carried out in different schools in the Autonomous Community of Castile y Leon (Spain in an attempt to identify patterns of common action through the implementation of collaborative learning methods mediated by information and communication technologies (ICT. Among the many outcomes of this study, we conclude by highlighting the need to plan collaborative work very carefully, taking advantage of the opportunities offered by ICT as communicative environments where it is possible to construct joint and shared learning

  16. A Scale Development for Teacher Competencies on Cooperative Learning Method

    Science.gov (United States)

    Kocabas, Ayfer; Erbil, Deniz Gokce

    2017-01-01

    Cooperative learning method is a learning method studied both in Turkey and in the world for long years as an active learning method. Although cooperative learning method takes place in training programs, it cannot be implemented completely in the direction of its principles. The results of the researches point out that teachers have problems with…

  17. Improving the interpersonal competences of head nurses through Peplau's theoretical active learning approach.

    Science.gov (United States)

    Suhariyanto; Hariyati, Rr Tutik Sri; Ungsianik, Titin

    2018-02-01

    Effective interpersonal skills are essential for head nurses in governing and managing their work units. Therefore, an active learning strategy could be the key to enhance the interpersonal competences of head nurses. This study aimed to investigate the effects of Peplau's theoretical approach of active learning on the improvement of head nurses' interpersonal skills. This study used a pre-experimental design with one group having pretests and posttests, without control group. A total sample of 25 head nurses from inpatient units of a wellknown private hospital in Jakarta was involved in the study. Data were analyzed using the paired t-test. The results showed a significant increase in head nurses' knowledge following the training to strengthen their interpersonal roles (P=.003). The results also revealed significant increases in the head nurses' skills in playing the roles of leader (P=.006), guardian (P=.014), and teacher/speaker (P=.015). Nonetheless, the results showed no significant increases in the head nurses' skills in playing the roles of counselor (P=.092) and stranger (P=.182). Training in strengthening the interpersonal roles of head nurses significantly increased the head nurses' knowledge and skills. The results of the study suggested the continuation of active learning strategies to improve the interpersonal abilities of head nurses. Furthermore, these strategies could be used to build the abilities of head nurses in other managerial fields. Copyright © 2018 Elsevier España, S.L.U. All rights reserved.

  18. Learning Method, Facilities And Infrastructure, And Learning Resources In Basic Networking For Vocational School

    OpenAIRE

    Pamungkas, Bian Dwi

    2017-01-01

    This study aims to examine the contribution of learning methods on learning output, the contribution of facilities and infrastructure on output learning, the contribution of learning resources on learning output, and the contribution of learning methods, the facilities and infrastructure, and learning resources on learning output. The research design is descriptive causative, using a goal-oriented assessment approach in which the assessment focuses on assessing the achievement of a goal. The ...

  19. Enriching behavioral ecology with reinforcement learning methods.

    Science.gov (United States)

    Frankenhuis, Willem E; Panchanathan, Karthik; Barto, Andrew G

    2018-02-13

    This article focuses on the division of labor between evolution and development in solving sequential, state-dependent decision problems. Currently, behavioral ecologists tend to use dynamic programming methods to study such problems. These methods are successful at predicting animal behavior in a variety of contexts. However, they depend on a distinct set of assumptions. Here, we argue that behavioral ecology will benefit from drawing more than it currently does on a complementary collection of tools, called reinforcement learning methods. These methods allow for the study of behavior in highly complex environments, which conventional dynamic programming methods do not feasibly address. In addition, reinforcement learning methods are well-suited to studying how biological mechanisms solve developmental and learning problems. For instance, we can use them to study simple rules that perform well in complex environments. Or to investigate under what conditions natural selection favors fixed, non-plastic traits (which do not vary across individuals), cue-driven-switch plasticity (innate instructions for adaptive behavioral development based on experience), or developmental selection (the incremental acquisition of adaptive behavior based on experience). If natural selection favors developmental selection, which includes learning from environmental feedback, we can also make predictions about the design of reward systems. Our paper is written in an accessible manner and for a broad audience, though we believe some novel insights can be drawn from our discussion. We hope our paper will help advance the emerging bridge connecting the fields of behavioral ecology and reinforcement learning. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

  20. Theoretical assumptions of Maffesoli's sensitivity and Problem-Based Learning in Nursing Education

    Directory of Open Access Journals (Sweden)

    María-Aurora Rodríguez-Borrego

    2014-06-01

    Full Text Available OBJECTIVE: understand the everyday and the imaginary of Nursing students in their knowledge socialization process through the Problem-Based Learning (PBL strategy.METHOD: Action Research, involving 86 students from the second year of an undergraduate Nursing program in Spain. A Critical Incident Questionnaire and Group interview were used. Thematic/categorical analysis, triangulation of researchers, subjects and techniques.RESULTS: the students signal the need to have a view from within, reinforcing the criticism against the schematic dualism; PBL allows one to learn how to be with the other, with his mechanical and organic solidarity; the feeling together, with its emphasis on learning to work in group and wanting to be close to the person taking care.CONCLUSIONS: The great contradictions the protagonists of the process, that is, the students experience seem to express that group learning is not a form of gaining knowledge, as it makes them lose time to study. The daily, the execution time and the imaginary of how learning should be do not seem to have an intersection point in the use of Problem-Based Learning. The importance of focusing on the daily and the imaginary should be reinforced when we consider nursing education.

  1. Theoretical assumptions of Maffesoli's sensitivity and Problem-Based Learning in Nursing Education1

    Science.gov (United States)

    Rodríguez-Borrego, María-Aurora; Nitschke, Rosane Gonçalves; do Prado, Marta Lenise; Martini, Jussara Gue; Guerra-Martín, María-Dolores; González-Galán, Carmen

    2014-01-01

    Objective understand the everyday and the imaginary of Nursing students in their knowledge socialization process through the Problem-Based Learning (PBL) strategy. Method Action Research, involving 86 students from the second year of an undergraduate Nursing program in Spain. A Critical Incident Questionnaire and Group interview were used. Thematic/categorical analysis, triangulation of researchers, subjects and techniques. Results the students signal the need to have a view from within, reinforcing the criticism against the schematic dualism; PBL allows one to learn how to be with the other, with his mechanical and organic solidarity; the feeling together, with its emphasis on learning to work in group and wanting to be close to the person taking care. Conclusions The great contradictions the protagonists of the process, that is, the students experience seem to express that group learning is not a form of gaining knowledge, as it makes them lose time to study. The daily, the execution time and the imaginary of how learning should be do not seem to have an intersection point in the use of Problem-Based Learning. The importance of focusing on the daily and the imaginary should be reinforced when we consider nursing education. PMID:25029064

  2. 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…

  3. Keystone Method: A Learning Paradigm in Mathematics

    Science.gov (United States)

    Siadat, M. Vali; Musial, Paul M.; Sagher, Yoram

    2008-01-01

    This study reports the effects of an integrated instructional program (the Keystone Method) on the students' performance in mathematics and reading, and tracks students' persistence and retention. The subject of the study was a large group of students in remedial mathematics classes at the college, willing to learn but lacking basic educational…

  4. Students' Ideas on Cooperative Learning Method

    Science.gov (United States)

    Yoruk, Abdulkadir

    2016-01-01

    Aim of this study is to investigate students' ideas on cooperative learning method. For that purpose students who are studying at elementary science education program are distributed into two groups through an experimental design. Factors threaten the internal validity are either eliminated or reduced to minimum value. Data analysis is done…

  5. Suggestology as an Effective Language Learning Method.

    Science.gov (United States)

    MaCoy, Katherine W.

    The methods used and the results obtained by means of the accelerated language learning techniques developed by Georgi Lozanov, Director of the Institute of Suggestology in Bulgaria, are discussed. The following topics are included: (1) discussion of hypermnesia, "super memory," and the reasons foreign languages were chosen for purposes…

  6. Theoretical Coalescence: A Method to Develop Qualitative Theory: The Example of Enduring.

    Science.gov (United States)

    Morse, Janice M

    Qualitative research is frequently context bound, lacks generalizability, and is limited in scope. The purpose of this article was to describe a method, theoretical coalescence, that provides a strategy for analyzing complex, high-level concepts and for developing generalizable theory. Theoretical coalescence is a method of theoretical expansion, inductive inquiry, of theory development, that uses data (rather than themes, categories, and published extracts of data) as the primary source for analysis. Here, using the development of the lay concept of enduring as an example, I explore the scientific development of the concept in multiple settings over many projects and link it within the Praxis Theory of Suffering. As comprehension emerges when conducting theoretical coalescence, it is essential that raw data from various different situations be available for reinterpretation/reanalysis and comparison to identify the essential features of the concept. The concept is then reconstructed, with additional inquiry that builds description, and evidence is conducted and conceptualized to create a more expansive concept and theory. By utilizing apparently diverse data sets from different contexts that are linked by certain characteristics, the essential features of the concept emerge. Such inquiry is divergent and less bound by context yet purposeful, logical, and with significant pragmatic implications for practice in nursing and beyond our discipline. Theoretical coalescence is a means by which qualitative inquiry is broadened to make an impact, to accommodate new theoretical shifts and concepts, and to make qualitative research applied and accessible in new ways.

  7. Theoretical and methodological basis of the comparative historical and legal method development

    Directory of Open Access Journals (Sweden)

    Д. А. Шигаль

    2015-05-01

    Full Text Available Problem setting. Development of any scientific method is always both a question of its structural and functional characteristics and place in the system of scientific methods, and a comment as for practicability of such methodological work. This paper attempts to give a detailed response to the major comments and objections arising in respect of the separation as an independent means of special and scientific knowledge of comparative historical and legal method. Recent research and publications analysis. Analyzing research and publications within the theme of the scientific article, it should be noted that attention to methodological issues of both general and legal science at the time was paid by such prominent foreign and domestic scholars as I. D. Andreev, Yu. Ya. Baskin, O. L. Bygych, M. A. Damirli, V. V. Ivanov, I. D. Koval'chenko, V. F. Kolomyitsev, D. V. Lukyanov, L. A. Luts, J. Maida, B. G. Mogilnytsky, N. M. Onishchenko, N. M. Parkhomenko, O. V. Petryshyn, S. P. Pogrebnyak, V. I. Synaisky, V. M. Syryh, O. F. Skakun, A. O. Tille, D. I. Feldman and others. It should be noted that, despite a large number of scientific papers in this field, the interest of research partnership in the methodology of history of state and law science still unfairly remains very low. Paper objective. The purpose of this scientific paper is theoretical and methodological rationale for the need of separation and development of comparative historical and legal method in the form of answers to more common questions and objections that arise in scientific partnership in this regard. Paper main body. Development of comparative historical and legal means of knowledge is quite justified because it meets the requirements of the scientific method efficiency, which criteria are the speed for achieving this goal, ease of use of one or another way of scientific knowledge, universality of research methods, convenience of techniques that are used and so on. Combining the

  8. Effects of Jigsaw Learning Method on Students’ Self-Efficacy and Motivation to Learn

    OpenAIRE

    Dwi Nur Rachmah

    2017-01-01

    Jigsaw learning as a cooperative learning method, according to the results of some studies, can improve academic skills, social competence, behavior in learning, and motivation to learn. However, in some other studies, there are different findings regarding the effect of jigsaw learning method on self-efficacy. The purpose of this study is to examine the effects of jigsaw learning method on self-efficacy and motivation to learn in psychology students at the Faculty of Medicine, Universitas La...

  9. Color image definition evaluation method based on deep learning method

    Science.gov (United States)

    Liu, Di; Li, YingChun

    2018-01-01

    In order to evaluate different blurring levels of color image and improve the method of image definition evaluation, this paper proposed a method based on the depth learning framework and BP neural network classification model, and presents a non-reference color image clarity evaluation method. Firstly, using VGG16 net as the feature extractor to extract 4,096 dimensions features of the images, then the extracted features and labeled images are employed in BP neural network to train. And finally achieve the color image definition evaluation. The method in this paper are experimented by using images from the CSIQ database. The images are blurred at different levels. There are 4,000 images after the processing. Dividing the 4,000 images into three categories, each category represents a blur level. 300 out of 400 high-dimensional features are trained in VGG16 net and BP neural network, and the rest of 100 samples are tested. The experimental results show that the method can take full advantage of the learning and characterization capability of deep learning. Referring to the current shortcomings of the major existing image clarity evaluation methods, which manually design and extract features. The method in this paper can extract the images features automatically, and has got excellent image quality classification accuracy for the test data set. The accuracy rate is 96%. Moreover, the predicted quality levels of original color images are similar to the perception of the human visual system.

  10. Project Oriented Immersion Learning: Method and Results

    DEFF Research Database (Denmark)

    Icaza, José I.; Heredia, Yolanda; Borch, Ole M.

    2005-01-01

    A pedagogical approach called “project oriented immersion learning” is presented and tested on a graduate online course. The approach combines the Project Oriented Learning method with immersion learning in a virtual enterprise. Students assumed the role of authors hired by a fictitious publishing...... house that develops digital products including e-books, tutorials, web sites and so on. The students defined the problem that their product was to solve; choose the type of product and the content; and built the product following a strict project methodology. A wiki server was used as a platform to hold...

  11. The method of global learning in teaching foreign languages

    Directory of Open Access Journals (Sweden)

    Tatjana Dragovič

    2001-12-01

    Full Text Available The authors describe the method of global learning of foreign languages, which is based on the principles of neurolinguistic programming (NLP. According to this theory, the educator should use the method of the so-called periphery learning, where students learn relaxation techniques and at the same time they »incidentally « or subconsciously learn a foreign language. The method of global learning imitates successful strategies of learning in early childhood and therefore creates a relaxed attitude towards learning. Global learning is also compared with standard methods.

  12. Theoretical Commitment and Implicit Knowledge: Why Anomalies do not Trigger Learning

    Science.gov (United States)

    Ohlsson, Stellan

    A theory consists of a mental model, laws that specify parameters of the model and one or more explanatory schemas. Models represent by being isomorphic to real systems. To explain an event is to reenact its genesis by executing the relevant model in the mind's eye. Schemas capture recurring structural features of explanations. To subscribe to a theory is to be committed to explaining a particular class of events with that theory (and nothing else). Given theoretical commitment, an anomaly, i.e., an event that cannot be explained, is an occasion for theory change, but in the absence of commitment, the response is instead to exclude the anomalous event from the domain of application of the theory. Lay people and children hold their theories implicitly and hence without commitment. These observations imply that the analogy between scientist's theories and children's knowledge is valid, but that the analogy between theory change and learning is not.

  13. Lessons learned: advantages and disadvantages of mixed method research

    DEFF Research Database (Denmark)

    Malina, Mary A.; Nørreklit, Hanne; Selto, Frank H.

    2011-01-01

    on the use and usefulness of a specialized balanced scorecard; and third, to encourage researchers to actually use multiple methods and sources of data to address the very many accounting phenomena that are not fully understood. Design/methodology/approach – This paper is an opinion piece based...... on the authors' experience conducting a series of longitudinal mixed method studies. Findings – The authors suggest that in many studies, using a mixed method approach provides the best opportunity for addressing research questions. Originality/value – This paper provides encouragement to those who may wish......Purpose – The purpose of this paper is first, to discuss the theoretical assumptions, qualities, problems and myopia of the dominating quantitative and qualitative approaches; second, to describe the methodological lessons that the authors learned while conducting a series of longitudinal studies...

  14. SAIL: Summation-bAsed Incremental Learning for Information-Theoretic Text Clustering.

    Science.gov (United States)

    Cao, Jie; Wu, Zhiang; Wu, Junjie; Xiong, Hui

    2013-04-01

    Information-theoretic clustering aims to exploit information-theoretic measures as the clustering criteria. A common practice on this topic is the so-called Info-Kmeans, which performs K-means clustering with KL-divergence as the proximity function. While expert efforts on Info-Kmeans have shown promising results, a remaining challenge is to deal with high-dimensional sparse data such as text corpora. Indeed, it is possible that the centroids contain many zero-value features for high-dimensional text vectors, which leads to infinite KL-divergence values and creates a dilemma in assigning objects to centroids during the iteration process of Info-Kmeans. To meet this challenge, in this paper, we propose a Summation-bAsed Incremental Learning (SAIL) algorithm for Info-Kmeans clustering. Specifically, by using an equivalent objective function, SAIL replaces the computation of KL-divergence by the incremental computation of Shannon entropy. This can avoid the zero-feature dilemma caused by the use of KL-divergence. To improve the clustering quality, we further introduce the variable neighborhood search scheme and propose the V-SAIL algorithm, which is then accelerated by a multithreaded scheme in PV-SAIL. Our experimental results on various real-world text collections have shown that, with SAIL as a booster, the clustering performance of Info-Kmeans can be significantly improved. Also, V-SAIL and PV-SAIL indeed help improve the clustering quality at a lower cost of computation.

  15. Synergy between experimental and theoretical methods in the exploration of homogeneous transition metal catalysis

    DEFF Research Database (Denmark)

    Lupp, Daniel; Christensen, Niels Johan; Fristrup, Peter

    2014-01-01

    n this Perspective, we will focus on the use of both experimental and theoretical methods in the exploration of reaction mechanisms in homogeneous transition metal catalysis. We briefly introduce the use of Hammett studies and kinetic isotope effects (KIE). Both of these techniques can be complem......n this Perspective, we will focus on the use of both experimental and theoretical methods in the exploration of reaction mechanisms in homogeneous transition metal catalysis. We briefly introduce the use of Hammett studies and kinetic isotope effects (KIE). Both of these techniques can...... be complemented by computational chemistry – in particular in cases where interpretation of the experimental results is not straightforward. The good correspondence between experiment and theory is only possible due to recent advances within the applied theoretical framework. We therefore also highlight...

  16. Theoretical investigations of the new Cokriging method for variable-fidelity surrogate modeling

    DEFF Research Database (Denmark)

    Zimmermann, Ralf; Bertram, Anna

    2018-01-01

    Cokriging is a variable-fidelity surrogate modeling technique which emulates a target process based on the spatial correlation of sampled data of different levels of fidelity. In this work, we address two theoretical questions associated with the so-called new Cokriging method for variable fidelity...

  17. Machine Learning Methods for Production Cases Analysis

    Science.gov (United States)

    Mokrova, Nataliya V.; Mokrov, Alexander M.; Safonova, Alexandra V.; Vishnyakov, Igor V.

    2018-03-01

    Approach to analysis of events occurring during the production process were proposed. Described machine learning system is able to solve classification tasks related to production control and hazard identification at an early stage. Descriptors of the internal production network data were used for training and testing of applied models. k-Nearest Neighbors and Random forest methods were used to illustrate and analyze proposed solution. The quality of the developed classifiers was estimated using standard statistical metrics, such as precision, recall and accuracy.

  18. Learning Algorithm of Boltzmann Machine Based on Spatial Monte Carlo Integration Method

    Directory of Open Access Journals (Sweden)

    Muneki Yasuda

    2018-04-01

    Full Text Available The machine learning techniques for Markov random fields are fundamental in various fields involving pattern recognition, image processing, sparse modeling, and earth science, and a Boltzmann machine is one of the most important models in Markov random fields. However, the inference and learning problems in the Boltzmann machine are NP-hard. The investigation of an effective learning algorithm for the Boltzmann machine is one of the most important challenges in the field of statistical machine learning. In this paper, we study Boltzmann machine learning based on the (first-order spatial Monte Carlo integration method, referred to as the 1-SMCI learning method, which was proposed in the author’s previous paper. In the first part of this paper, we compare the method with the maximum pseudo-likelihood estimation (MPLE method using a theoretical and a numerical approaches, and show the 1-SMCI learning method is more effective than the MPLE. In the latter part, we compare the 1-SMCI learning method with other effective methods, ratio matching and minimum probability flow, using a numerical experiment, and show the 1-SMCI learning method outperforms them.

  19. A method for comparison of experimental and theoretical differential neutron spectra in the Zenith reactor

    International Nuclear Information System (INIS)

    Reed, D.L.; Symons, C.R.

    1965-01-01

    A method of calculation is given which assists the analyses of chopper measurements of spectra from ZENITH and enables complex multigroup theoretical calculations of the spectra to be put into a form which may be compared with experiment. In addition the theory of the cut-off function has been extended to give analytical expressions which take into account the effects of sub-collimators, off centre slits and of a rotor made of a material partially transparent to neutrons. The theoretical cut-off function suggested shows good agreement with experiment. (author)

  20. A method for comparison of experimental and theoretical differential neutron spectra in the Zenith reactor

    Energy Technology Data Exchange (ETDEWEB)

    Reed, D L; Symons, C R [General Reactor Physics Division, Atomic Energy Establishment, Winfrith, Dorchester, Dorset (United Kingdom)

    1965-01-15

    A method of calculation is given which assists the analyses of chopper measurements of spectra from ZENITH and enables complex multigroup theoretical calculations of the spectra to be put into a form which may be compared with experiment. In addition the theory of the cut-off function has been extended to give analytical expressions which take into account the effects of sub-collimators, off centre slits and of a rotor made of a material partially transparent to neutrons. The theoretical cut-off function suggested shows good agreement with experiment. (author)

  1. Aligning professional skills and active learning methods: an application for information and communications technology engineering

    Science.gov (United States)

    Llorens, Ariadna; Berbegal-Mirabent, Jasmina; Llinàs-Audet, Xavier

    2017-07-01

    Engineering education is facing new challenges to effectively provide the appropriate skills to future engineering professionals according to market demands. This study proposes a model based on active learning methods, which is expected to facilitate the acquisition of the professional skills most highly valued in the information and communications technology (ICT) market. The theoretical foundations of the study are based on the specific literature on active learning methodologies. The Delphi method is used to establish the fit between learning methods and generic skills required by the ICT sector. An innovative proposition is therefore presented that groups the required skills in relation to the teaching method that best develops them. The qualitative research suggests that a combination of project-based learning and the learning contract is sufficient to ensure a satisfactory skills level for this profile of engineers.

  2. Implementing Collaborative Learning Methods in the Political Science Classroom

    Science.gov (United States)

    Wolfe, Angela

    2012-01-01

    Collaborative learning is one, among other, active learning methods, widely acclaimed in higher education. Consequently, instructors in fields that lack pedagogical training often implement new learning methods such as collaborative learning on the basis of trial and error. Moreover, even though the benefits in academic circles are broadly touted,…

  3. The 8 Learning Events Model: a Pedagogic Conceptual Tool Supporting Diversification of Learning Methods

    NARCIS (Netherlands)

    Verpoorten, Dominique; Poumay, M; Leclercq, D

    2006-01-01

    Please, cite this publication as: Verpoorten, D., Poumay, M., & Leclercq, D. (2006). The 8 Learning Events Model: a Pedagogic Conceptual Tool Supporting Diversification of Learning Methods. Proceedings of International Workshop in Learning Networks for Lifelong Competence Development, TENCompetence

  4. Engineers' Perceptions of Diversity and the Learning Environment at Work: A Mixed Methods Study

    Science.gov (United States)

    Firestone, Brenda L.

    2012-01-01

    The purpose of this dissertation research study was to investigate engineers' perceptions of diversity and the workplace learning environment surrounding diversity education efforts in engineering occupations. The study made use of a mixed methods methodology and was theoretically framed using a critical feminist adult education lens and…

  5. Theoretical reflections on the connection between environmental assessment methods and conflict

    International Nuclear Information System (INIS)

    Persson, Jesper

    2006-01-01

    Today there is a great variety of methods for evaluating the environmental impact of plans, programs and projects. But which of these methods should planners and managers choose? This theoretical article explores the connection between conflicts, communication and rationality in assessment methods. It focuses on the form (rationality) and substance of communication, i.e. what we should communicate about. The outcome supports the view that environmental assessments should be based on value- and interest-focused thinking, following a teleological ethic, when goals, alternatives and compensations are to be developed and impacts evaluated

  6. Methods to determine stratification efficiency of thermal energy storage processes–Review and theoretical comparison

    DEFF Research Database (Denmark)

    Haller, Michel; Cruickshank, Chynthia; Streicher, Wolfgang

    2009-01-01

    This paper reviews different methods that have been proposed to characterize thermal stratification in energy storages from a theoretical point of view. Specifically, this paper focuses on the methods that can be used to determine the ability of a storage to promote and maintain stratification...... during charging, storing and discharging, and represent this ability with a single numerical value in terms of a stratification efficiency for a given experiment or under given boundary conditions. Existing methods for calculating stratification efficiencies have been applied to hypothetical storage...

  7. Statistical learning methods in high-energy and astrophysics analysis

    Energy Technology Data Exchange (ETDEWEB)

    Zimmermann, J. [Forschungszentrum Juelich GmbH, Zentrallabor fuer Elektronik, 52425 Juelich (Germany) and Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)]. E-mail: zimmerm@mppmu.mpg.de; Kiesling, C. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)

    2004-11-21

    We discuss several popular statistical learning methods used in high-energy- and astro-physics analysis. After a short motivation for statistical learning we present the most popular algorithms and discuss several examples from current research in particle- and astro-physics. The statistical learning methods are compared with each other and with standard methods for the respective application.

  8. Statistical learning methods in high-energy and astrophysics analysis

    International Nuclear Information System (INIS)

    Zimmermann, J.; Kiesling, C.

    2004-01-01

    We discuss several popular statistical learning methods used in high-energy- and astro-physics analysis. After a short motivation for statistical learning we present the most popular algorithms and discuss several examples from current research in particle- and astro-physics. The statistical learning methods are compared with each other and with standard methods for the respective application

  9. Game-theoretic methods for functional response and optimal foraging behavior

    Czech Academy of Sciences Publication Activity Database

    Cressman, R.; Křivan, Vlastimil; Brown, J. S.; Garay, J.

    2014-01-01

    Roč. 9, č. 2 (2014), e88773 E-ISSN 1932-6203 Grant - others:Hungarian National Research Fund(HU) K62000; Hungarian National Research Fund(HU) K67961 Institutional support: RVO:60077344 Keywords : game-theoretic methods Subject RIV: EH - Ecology, Behaviour Impact factor: 3.234, year: 2014 http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0088773

  10. Theoretical methods for the calculation of the multiphoton ionisation cross-section of atoms and molecules

    International Nuclear Information System (INIS)

    Moccia, R.

    1991-01-01

    Some of the available theoretical methods to compute the two-photon ionisation cross-section of many-electron systems are reviewed. In particular the problems concerning the computation of (i) reliable approximations for the transition matrix elements and the excitation energies; and (ii) accurate results pertaining to the electronic continuum by the use of L 2 basis functions are considered. (author). 29 refs., 6 figs., 1 tab

  11. Learning phacoemulsification. Results of different teaching methods.

    Directory of Open Access Journals (Sweden)

    Hennig Albrecht

    2004-01-01

    Full Text Available We report the learning curves of three eye surgeons converting from sutureless extracapsular cataract extraction to phacoemulsification using different teaching methods. Posterior capsule rupture (PCR as a per-operative complication and visual outcome of the first 100 operations were analysed. The PCR rate was 4% and 15% in supervised and unsupervised surgery respectively. Likewise, an uncorrected visual acuity of > or = 6/18 on the first postoperative day was seen in 62 (62% of patients and in 22 (22% in supervised and unsupervised surgery respectively.

  12. Influence on Learning of a Collaborative Learning Method Comprising the Jigsaw Method and Problem-based Learning (PBL).

    Science.gov (United States)

    Takeda, Kayoko; Takahashi, Kiyoshi; Masukawa, Hiroyuki; Shimamori, Yoshimitsu

    2017-01-01

    Recently, the practice of active learning has spread, increasingly recognized as an essential component of academic studies. Classes incorporating small group discussion (SGD) are conducted at many universities. At present, assessments of the effectiveness of SGD have mostly involved evaluation by questionnaires conducted by teachers, by peer assessment, and by self-evaluation of students. However, qualitative data, such as open-ended descriptions by students, have not been widely evaluated. As a result, we have been unable to analyze the processes and methods involved in how students acquire knowledge in SGD. In recent years, due to advances in information and communication technology (ICT), text mining has enabled the analysis of qualitative data. We therefore investigated whether the introduction of a learning system comprising the jigsaw method and problem-based learning (PBL) would improve student attitudes toward learning; we did this by text mining analysis of the content of student reports. We found that by applying the jigsaw method before PBL, we were able to improve student attitudes toward learning and increase the depth of their understanding of the area of study as a result of working with others. The use of text mining to analyze qualitative data also allowed us to understand the processes and methods by which students acquired knowledge in SGD and also changes in students' understanding and performance based on improvements to the class. This finding suggests that the use of text mining to analyze qualitative data could enable teachers to evaluate the effectiveness of various methods employed to improve learning.

  13. EXPLANATORY METHODS OF MARKETING DATA ANALYSIS – THEORETICAL AND METHODOLOGICAL CONSIDERATIONS

    Directory of Open Access Journals (Sweden)

    Rozalia GABOR

    2010-01-01

    Full Text Available Explanatory methods of data analysis – also named by some authors supervised learning methods - enable researchers to identify and analyse configurations of relations between two or several variables, most of them with a high accuracy, as there is possibility of testing statistic significance by calculating the confidence level associated with validation of relation concerned across the entire population and not only the surveyed sample. The paper shows some of these methods, respectively: variance analysis, covariance analysis, segmentation and discriminant analysis with the mention - for every method – of applicability area for marketing research.

  14. Eclecticism as the foundation of meta-theoretical, mixed methods and interdisciplinary research in social sciences.

    Science.gov (United States)

    Kroos, Karmo

    2012-03-01

    This article examines the value of "eclecticism" as the foundation of meta-theoretical, mixed methods and interdisciplinary research in social sciences. On the basis of the analysis of the historical background of the concept, it is first suggested that eclecticism-based theoretical scholarship in social sciences could benefit from the more systematic research method that has been developed for synthesizing theoretical works under the name metatheorizing. Second, it is suggested that the mixed methods community could base its research approach on philosophical eclecticism instead of pragmatism because the basic idea of eclecticism is much more in sync with the nature of the combined research tradition. Finally, the Kuhnian frame is used to support the argument for interdisciplinary research and, hence, eclecticism in social sciences (rather than making an argument against multiple paradigms). More particularly, it is suggested that integrating the different (inter)disciplinary traditions and schools into one is not necessarily desirable at all in social sciences because of the complexity and openness of the research field. If it is nevertheless attempted, experience in economics suggests that paradigmatic unification comes at a high price.

  15. COOPERATIVE LEARNING IN DISTANCE LEARNING: A MIXED METHODS STUDY

    Directory of Open Access Journals (Sweden)

    Lori Kupczynski

    2012-07-01

    Full Text Available Distance learning has facilitated innovative means to include Cooperative Learning (CL in virtual settings. This study, conducted at a Hispanic-Serving Institution, compared the effectiveness of online CL strategies in discussion forums with traditional online forums. Quantitative and qualitative data were collected from 56 graduate student participants. Quantitative results revealed no significant difference on student success between CL and Traditional formats. The qualitative data revealed that students in the cooperative learning groups found more learning benefits than the Traditional group. The study will benefit instructors and students in distance learning to improve teaching and learning practices in a virtual classroom.

  16. Machine learning methods for metabolic pathway prediction

    Directory of Open Access Journals (Sweden)

    Karp Peter D

    2010-01-01

    Full Text Available Abstract Background A key challenge in systems biology is the reconstruction of an organism's metabolic network from its genome sequence. One strategy for addressing this problem is to predict which metabolic pathways, from a reference database of known pathways, are present in the organism, based on the annotated genome of the organism. Results To quantitatively validate methods for pathway prediction, we developed a large "gold standard" dataset of 5,610 pathway instances known to be present or absent in curated metabolic pathway databases for six organisms. We defined a collection of 123 pathway features, whose information content we evaluated with respect to the gold standard. Feature data were used as input to an extensive collection of machine learning (ML methods, including naïve Bayes, decision trees, and logistic regression, together with feature selection and ensemble methods. We compared the ML methods to the previous PathoLogic algorithm for pathway prediction using the gold standard dataset. We found that ML-based prediction methods can match the performance of the PathoLogic algorithm. PathoLogic achieved an accuracy of 91% and an F-measure of 0.786. The ML-based prediction methods achieved accuracy as high as 91.2% and F-measure as high as 0.787. The ML-based methods output a probability for each predicted pathway, whereas PathoLogic does not, which provides more information to the user and facilitates filtering of predicted pathways. Conclusions ML methods for pathway prediction perform as well as existing methods, and have qualitative advantages in terms of extensibility, tunability, and explainability. More advanced prediction methods and/or more sophisticated input features may improve the performance of ML methods. However, pathway prediction performance appears to be limited largely by the ability to correctly match enzymes to the reactions they catalyze based on genome annotations.

  17. Machine learning methods for metabolic pathway prediction

    Science.gov (United States)

    2010-01-01

    Background A key challenge in systems biology is the reconstruction of an organism's metabolic network from its genome sequence. One strategy for addressing this problem is to predict which metabolic pathways, from a reference database of known pathways, are present in the organism, based on the annotated genome of the organism. Results To quantitatively validate methods for pathway prediction, we developed a large "gold standard" dataset of 5,610 pathway instances known to be present or absent in curated metabolic pathway databases for six organisms. We defined a collection of 123 pathway features, whose information content we evaluated with respect to the gold standard. Feature data were used as input to an extensive collection of machine learning (ML) methods, including naïve Bayes, decision trees, and logistic regression, together with feature selection and ensemble methods. We compared the ML methods to the previous PathoLogic algorithm for pathway prediction using the gold standard dataset. We found that ML-based prediction methods can match the performance of the PathoLogic algorithm. PathoLogic achieved an accuracy of 91% and an F-measure of 0.786. The ML-based prediction methods achieved accuracy as high as 91.2% and F-measure as high as 0.787. The ML-based methods output a probability for each predicted pathway, whereas PathoLogic does not, which provides more information to the user and facilitates filtering of predicted pathways. Conclusions ML methods for pathway prediction perform as well as existing methods, and have qualitative advantages in terms of extensibility, tunability, and explainability. More advanced prediction methods and/or more sophisticated input features may improve the performance of ML methods. However, pathway prediction performance appears to be limited largely by the ability to correctly match enzymes to the reactions they catalyze based on genome annotations. PMID:20064214

  18. Student Achievement in Basic College Mathematics: Its Relationship to Learning Style and Learning Method

    Science.gov (United States)

    Gunthorpe, Sydney

    2006-01-01

    From the assumption that matching a student's learning style with the learning method best suited for the student, it follows that developing courses that correlate learning method with learning style would be more successful for students. Albuquerque Technical Vocational Institute (TVI) in New Mexico has attempted to provide students with more…

  19. Two Undergraduate Process Modeling Courses Taught Using Inductive Learning Methods

    Science.gov (United States)

    Soroush, Masoud; Weinberger, Charles B.

    2010-01-01

    This manuscript presents a successful application of inductive learning in process modeling. It describes two process modeling courses that use inductive learning methods such as inquiry learning and problem-based learning, among others. The courses include a novel collection of multi-disciplinary complementary process modeling examples. They were…

  20. The Method of High School English Word Learning

    Institute of Scientific and Technical Information of China (English)

    吴博涵

    2016-01-01

    Most Chinese students are not interested in English learning, especially English words. In this paper, I focus on English vocabulary learning, for example, the study of high school students English word learning method, and also introduce several ways to make vocabulary memory becomes more effective. The purpose is to make high school students grasp more English word learning skills.

  1. A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression.

    Science.gov (United States)

    Stock, Michiel; Pahikkala, Tapio; Airola, Antti; De Baets, Bernard; Waegeman, Willem

    2018-06-12

    Many machine learning problems can be formulated as predicting labels for a pair of objects. Problems of that kind are often referred to as pairwise learning, dyadic prediction, or network inference problems. During the past decade, kernel methods have played a dominant role in pairwise learning. They still obtain a state-of-the-art predictive performance, but a theoretical analysis of their behavior has been underexplored in the machine learning literature. In this work we review and unify kernel-based algorithms that are commonly used in different pairwise learning settings, ranging from matrix filtering to zero-shot learning. To this end, we focus on closed-form efficient instantiations of Kronecker kernel ridge regression. We show that independent task kernel ridge regression, two-step kernel ridge regression, and a linear matrix filter arise naturally as a special case of Kronecker kernel ridge regression, implying that all these methods implicitly minimize a squared loss. In addition, we analyze universality, consistency, and spectral filtering properties. Our theoretical results provide valuable insights into assessing the advantages and limitations of existing pairwise learning methods.

  2. Theoretical and numerical investigations into the SPRT method for anomaly detection

    Energy Technology Data Exchange (ETDEWEB)

    Schoonewelle, H.; Hagen, T.H.J.J. van der; Hoogenboom, J.E. [Interuniversitair Reactor Inst., Delft (Netherlands)

    1995-11-01

    The sequential probability ratio test developed by Wald is a powerful method of testing an alternative hypothesis against a null hypothesis. This makes the method applicable for anomaly detection. In this paper the method is used to detect a change of the standard deviation of a Gaussian distributed white noise signal. The false alarm probability, the alarm failure probability and the average time to alarm of the method, which are important parameters for anomaly detection, are determined by simulation and compared with theoretical results. Each of the three parameters is presented in dependence of the other two and the ratio of the standard deviation of the anomalous signal and that of the normal signal. Results show that the method is very well suited for anomaly detection. It can detect for example a 50% change in standard deviation within 1 second with a false alarm and alarm failure rate of less than once per month. (author).

  3. Theoretical and numerical investigations into the SPRT method for anomaly detection

    International Nuclear Information System (INIS)

    Schoonewelle, H.; Hagen, T.H.J.J. van der; Hoogenboom, J.E.

    1995-01-01

    The sequential probability ratio test developed by Wald is a powerful method of testing an alternative hypothesis against a null hypothesis. This makes the method applicable for anomaly detection. In this paper the method is used to detect a change of the standard deviation of a Gaussian distributed white noise signal. The false alarm probability, the alarm failure probability and the average time to alarm of the method, which are important parameters for anomaly detection, are determined by simulation and compared with theoretical results. Each of the three parameters is presented in dependence of the other two and the ratio of the standard deviation of the anomalous signal and that of the normal signal. Results show that the method is very well suited for anomaly detection. It can detect for example a 50% change in standard deviation within 1 second with a false alarm and alarm failure rate of less than once per month. (author)

  4. Medical Students’ View about the Effects of Practical Courses on Learning the General Theoretical Concepts of Basic Medical Sciences

    Directory of Open Access Journals (Sweden)

    Leila Roshangar

    2014-05-01

    Full Text Available Introduction: The basic medical sciences section requires 2.5 years in the medical education curriculum. Practical courses complement theoretical knowledge in this period to improve their appreciation. Despite spending lots of disbursement and time, this period’s efficacy is not clearly known. Methods: One hundred thirty-three General Practitioner (GP students have been included in this descriptive cross-sectional study and were asked by questionnaire about the positive impact of practical courses on learning theoretical knowledge. Data were analyzed by descriptive statistics. Result: The agreement in “Practical Head and Neck Anatomy” was 40.91% ± 29.45, in “Practical Trunk Anatomy” was 63.62% ± 2.32 and in “Practical Anatomy of Extremities” was 56.16% ± 2.57. In “Practical Histology”, agreement was 69.50%±2.19; “Practical Biophysics” was 45.97%±2.25, “Practical Physiology” 61.75%±2.17; “Practical Biochemistry” 36.28%±2.42; “Practical Pathology” 59.80%±2.53; “Practical Immunology” 56.25%±26.40; “Practical Microbiology and Virology” 60.39%±2.27 and “Practical Mycology and Parasitology” 68.2%± 2.16.Conclusion: GP students in Tabriz University of Medical Sciences are not optimistic about the applicability of practical courses of basic medical sciences lessons.

  5. A theoretical global optimization method for vapor-compression refrigeration systems based on entransy theory

    International Nuclear Information System (INIS)

    Xu, Yun-Chao; Chen, Qun

    2013-01-01

    The vapor-compression refrigeration systems have been one of the essential energy conversion systems for humankind and exhausting huge amounts of energy nowadays. Surrounding the energy efficiency promotion of the systems, there are lots of effectual optimization methods but mainly relied on engineering experience and computer simulations rather than theoretical analysis due to the complex and vague physical essence. We attempt to propose a theoretical global optimization method based on in-depth physical analysis for the involved physical processes, i.e. heat transfer analysis for condenser and evaporator, through introducing the entransy theory and thermodynamic analysis for compressor and expansion valve. The integration of heat transfer and thermodynamic analyses forms the overall physical optimization model for the systems to describe the relation between all the unknown parameters and known conditions, which makes theoretical global optimization possible. With the aid of the mathematical conditional extremum solutions, an optimization equation group and the optimal configuration of all the unknown parameters are analytically obtained. Eventually, via the optimization of a typical vapor-compression refrigeration system with various working conditions to minimize the total heat transfer area of heat exchangers, the validity and superior of the newly proposed optimization method is proved. - Highlights: • A global optimization method for vapor-compression systems is proposed. • Integrating heat transfer and thermodynamic analyses forms the optimization model. • A mathematical relation between design parameters and requirements is derived. • Entransy dissipation is introduced into heat transfer analysis. • The validity of the method is proved via optimization of practical cases

  6. Theoretical Methods of Domain Structures in Ultrathin Ferroelectric Films: A Review

    Directory of Open Access Journals (Sweden)

    Jianyi Liu

    2014-09-01

    Full Text Available This review covers methods and recent developments of the theoretical study of domain structures in ultrathin ferroelectric films. The review begins with an introduction to some basic concepts and theories (e.g., polarization and its modern theory, ferroelectric phase transition, domain formation, and finite size effects, etc. that are relevant to the study of domain structures in ultrathin ferroelectric films. Basic techniques and recent progress of a variety of important approaches for domain structure simulation, including first-principles calculation, molecular dynamics, Monte Carlo simulation, effective Hamiltonian approach and phase field modeling, as well as multiscale simulation are then elaborated. For each approach, its important features and relative merits over other approaches for modeling domain structures in ultrathin ferroelectric films are discussed. Finally, we review recent theoretical studies on some important issues of domain structures in ultrathin ferroelectric films, with an emphasis on the effects of interfacial electrostatics, boundary conditions and external loads.

  7. TEACHING AND LEARNING WITH TECHNOLOGY: A THEORETICAL MODEL FOR GOOD EDUCATIONAL PRACTICES WITH ICT

    Directory of Open Access Journals (Sweden)

    Jesús Valverde Berrocoso

    2010-02-01

    Full Text Available This article aims to define a theoretical explanatory framework for the integration of information technologies and communication technologies (ICT in education from the perspective of teacher education. The initial and continuing training of teachers is characterized by a tendency towards "essentialisation" of technology and generation of users who do not usually think about educational uses of technology in their own contexts. Our research on the integration of ICT in the classroom has allowed us to observe the lack of connection between the personal and professional use of teachers of these technological tools, as well as the need for training is geared towards developing skills and knowledge to examine, in a critical manner, the educational implications of these new teaching aids. This article is based on the proposed Koehler & Mishra (2005, 2006, 2007 and 2008 called TPCK (Technological Pedagogical Content Knowledge which is based on the construct of PCK Shulman (1987 to which is added the concept of "Technology" (T to those of "Pedagogy" (P and "Curriculum Content" (C. Connections and dynamic interactions between these three key components leading to different components to be considered in understanding the processes of integration of ICT in schools. Good educational practices with ICT are multidimensional and complex actions that require (1 understand the representation and formulation of concepts and procedures for their understanding through ICT, (2 develop constructivist teaching strategies that use ICT for teaching content curriculum, (3 know the difficulties in learning concepts and how ICT can help overcome them, and (4 knowing the students' prior knowledge and the epistemology of the curriculum to understand how ICT can be used to build on pre-existing knowledge and develop new epistemologies. These skills clearly go beyond the isolation that has an expert in a curriculum (teacher of a discipline, an expert in IT (engineer, or an

  8. Promoting communication, participation, and learning with regard to organic food products: a communication theoretical approach

    Directory of Open Access Journals (Sweden)

    Peter Kastberg

    2015-03-01

    Full Text Available The market for organic foods is growing, however, the proportion of consumers buying organic foods is still considered low. Research shows that a significant barrier to consumers purchasing more organic foods is lack of information. This leads the relevant body of research to call for better communication around organic foods. The same body of research, however, neither questions what good communication surrounding organic foods is, nor what would make it better. Applying the communication theoretical formats of transmission, interaction, and coaction, respectively, onto instances of organic communication activities, I will discuss to what extent each format encourages consumer participation and learning. Transmission, typically in the form of monologuous mass communication, is cost effective. It is also a format that bars a sender, e.g., producer or farmer, from gauging deposits in the consumer, e.g., understanding the message, trusting the sender, etc. Interaction, typically in the form of dialoguous encounters, integrates feedback into communication allowing the sender to appreciate the level of understanding, trust, etc., which the communicative effort has given rise to, albeit at a higher price in terms of money, time, and manpower. In the format of coaction, typically in the form of co-operative endeavors, the deposit is a matter of what is coconstructed by the participants, e.g., understanding, trust, etc. Coaction thus satisfies the organic communicators craving for involving the consumer, and because food is a low-involvement commodity, this is critical. But emancipating the consumer comes at a price. First of all, coactional communication is dependent on highly motivated participants, and second, coactional communication is difficult if not impossible to control. Informed by these insights, I present an in-depth, critical discussion of the promises and pitfalls of how multicriteria assessments may be communicated and coconstructed on a

  9. The equivalence of information-theoretic and likelihood-based methods for neural dimensionality reduction.

    Directory of Open Access Journals (Sweden)

    Ross S Williamson

    2015-04-01

    Full Text Available Stimulus dimensionality-reduction methods in neuroscience seek to identify a low-dimensional space of stimulus features that affect a neuron's probability of spiking. One popular method, known as maximally informative dimensions (MID, uses an information-theoretic quantity known as "single-spike information" to identify this space. Here we examine MID from a model-based perspective. We show that MID is a maximum-likelihood estimator for the parameters of a linear-nonlinear-Poisson (LNP model, and that the empirical single-spike information corresponds to the normalized log-likelihood under a Poisson model. This equivalence implies that MID does not necessarily find maximally informative stimulus dimensions when spiking is not well described as Poisson. We provide several examples to illustrate this shortcoming, and derive a lower bound on the information lost when spiking is Bernoulli in discrete time bins. To overcome this limitation, we introduce model-based dimensionality reduction methods for neurons with non-Poisson firing statistics, and show that they can be framed equivalently in likelihood-based or information-theoretic terms. Finally, we show how to overcome practical limitations on the number of stimulus dimensions that MID can estimate by constraining the form of the non-parametric nonlinearity in an LNP model. We illustrate these methods with simulations and data from primate visual cortex.

  10. Teaching and learning methods in IVET

    DEFF Research Database (Denmark)

    Aarkrog, Vibe

    The cases deals about learner centered learning in a commercial program and a technical program.......The cases deals about learner centered learning in a commercial program and a technical program....

  11. Beyond Assessment: Conducting Theoretically Grounded Research on Service-Learning in Gerontology Courses.

    Science.gov (United States)

    Kruger, Tina M; Pearl, Andrew J

    2016-01-01

    Service-learning is a useful pedagogical tool and high-impact practice, providing multiple benefits. Gerontology (and other) courses frequently include service-learning activities but lack theory-based, intentional research on outcomes. Here, the authors define service-learning and contextualize it in higher education, provide an overview of research and assessment in service-learning and gerontology courses, demonstrate the shortcomings of program evaluations, and offer suggestions for future research to advance and generate theory.

  12. Theoretical analysis of integral neutron transport equation using collision probability method with quadratic flux approach

    International Nuclear Information System (INIS)

    Shafii, Mohammad Ali; Meidianti, Rahma; Wildian,; Fitriyani, Dian; Tongkukut, Seni H. J.; Arkundato, Artoto

    2014-01-01

    Theoretical analysis of integral neutron transport equation using collision probability (CP) method with quadratic flux approach has been carried out. In general, the solution of the neutron transport using the CP method is performed with the flat flux approach. In this research, the CP method is implemented in the cylindrical nuclear fuel cell with the spatial of mesh being conducted into non flat flux approach. It means that the neutron flux at any point in the nuclear fuel cell are considered different each other followed the distribution pattern of quadratic flux. The result is presented here in the form of quadratic flux that is better understanding of the real condition in the cell calculation and as a starting point to be applied in computational calculation

  13. Theoretical analysis of integral neutron transport equation using collision probability method with quadratic flux approach

    Energy Technology Data Exchange (ETDEWEB)

    Shafii, Mohammad Ali, E-mail: mashafii@fmipa.unand.ac.id; Meidianti, Rahma, E-mail: mashafii@fmipa.unand.ac.id; Wildian,, E-mail: mashafii@fmipa.unand.ac.id; Fitriyani, Dian, E-mail: mashafii@fmipa.unand.ac.id [Department of Physics, Andalas University Padang West Sumatera Indonesia (Indonesia); Tongkukut, Seni H. J. [Department of Physics, Sam Ratulangi University Manado North Sulawesi Indonesia (Indonesia); Arkundato, Artoto [Department of Physics, Jember University Jember East Java Indonesia (Indonesia)

    2014-09-30

    Theoretical analysis of integral neutron transport equation using collision probability (CP) method with quadratic flux approach has been carried out. In general, the solution of the neutron transport using the CP method is performed with the flat flux approach. In this research, the CP method is implemented in the cylindrical nuclear fuel cell with the spatial of mesh being conducted into non flat flux approach. It means that the neutron flux at any point in the nuclear fuel cell are considered different each other followed the distribution pattern of quadratic flux. The result is presented here in the form of quadratic flux that is better understanding of the real condition in the cell calculation and as a starting point to be applied in computational calculation.

  14. Theoretically Based Pedagogical Strategies Leading to Deep Learning in Asynchronous Online Gerontology Courses

    Science.gov (United States)

    Majeski, Robin; Stover, Merrily

    2007-01-01

    Online learning has enjoyed increasing popularity in gerontology. This paper presents instructional strategies grounded in Fink's (2003) theory of significant learning designed for the completely asynchronous online gerontology classroom. It links these components with the development of mastery learning goals and provides specific guidelines for…

  15. The Cognitive Perspective on Learning: Its Theoretical Underpinnings and Implications for Classroom Practices

    Science.gov (United States)

    Yilmaz, Kaya

    2011-01-01

    Learning theories are essential for effective teaching in that they shed light on different aspects of the learning process. The spectrum of learning theories can be categorized into three main areas: behaviorism, cognitivism, and constructivism. "Behaviorism" as a teacher-centered instructional framework for a long time dominated educational…

  16. Facilitating organizational development through action learning : Some practical and theoretical considerations

    NARCIS (Netherlands)

    Donnenberg, O.; De Loo, I.G.M.

    2004-01-01

    Action learning programmes are supposed to result in both personal and organizational development. However, organizational development can be negligible because, as the term implies, a connection must be secured between what has been learned by action learning participants and other members of an

  17. When practice precedes theory - A mixed methods evaluation of students' learning experiences in an undergraduate study program in nursing.

    Science.gov (United States)

    Falk, Kristin; Falk, Hanna; Jakobsson Ung, Eva

    2016-01-01

    A key area for consideration is determining how optimal conditions for learning can be created. Higher education in nursing aims to prepare students to develop their capabilities to become independent professionals. The aim of this study was to evaluate the effects of sequencing clinical practice prior to theoretical studies on student's experiences of self-directed learning readiness and students' approach to learning in the second year of a three-year undergraduate study program in nursing. 123 nursing students was included in the study and divided in two groups. In group A (n = 60) clinical practice preceded theoretical studies. In group (n = 63) theoretical studies preceded clinical practice. Learning readiness was measured using the Directed Learning Readiness Scale for Nursing Education (SDLRSNE), and learning process was measured using the revised two-factor version of the Study Process Questionnaire (R-SPQ-2F). Students were also asked to write down their personal reflections throughout the course. By using a mixed method design, the qualitative component focused on the students' personal experiences in relation to the sequencing of theoretical studies and clinical practice. The quantitative component provided information about learning readiness before and after the intervention. Our findings confirm that students are sensitive and adaptable to their learning contexts, and that the sequencing of courses is subordinate to a pedagogical style enhancing students' deep learning approaches, which needs to be incorporated in the development of undergraduate nursing programs. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. An information-theoretic machine learning approach to expression QTL analysis.

    Directory of Open Access Journals (Sweden)

    Tao Huang

    Full Text Available Expression Quantitative Trait Locus (eQTL analysis is a powerful tool to study the biological mechanisms linking the genotype with gene expression. Such analyses can identify genomic locations where genotypic variants influence the expression of genes, both in close proximity to the variant (cis-eQTL, and on other chromosomes (trans-eQTL. Many traditional eQTL methods are based on a linear regression model. In this study, we propose a novel method by which to identify eQTL associations with information theory and machine learning approaches. Mutual Information (MI is used to describe the association between genetic marker and gene expression. MI can detect both linear and non-linear associations. What's more, it can capture the heterogeneity of the population. Advanced feature selection methods, Maximum Relevance Minimum Redundancy (mRMR and Incremental Feature Selection (IFS, were applied to optimize the selection of the affected genes by the genetic marker. When we applied our method to a study of apoE-deficient mice, it was found that the cis-acting eQTLs are stronger than trans-acting eQTLs but there are more trans-acting eQTLs than cis-acting eQTLs. We compared our results (mRMR.eQTL with R/qtl, and MatrixEQTL (modelLINEAR and modelANOVA. In female mice, 67.9% of mRMR.eQTL results can be confirmed by at least two other methods while only 14.4% of R/qtl result can be confirmed by at least two other methods. In male mice, 74.1% of mRMR.eQTL results can be confirmed by at least two other methods while only 18.2% of R/qtl result can be confirmed by at least two other methods. Our methods provide a new way to identify the association between genetic markers and gene expression. Our software is available from supporting information.

  19. When the Mannequin Dies, Creation and Exploration of a Theoretical Framework Using a Mixed Methods Approach.

    Science.gov (United States)

    Tripathy, Shreepada; Miller, Karen H; Berkenbosch, John W; McKinley, Tara F; Boland, Kimberly A; Brown, Seth A; Calhoun, Aaron W

    2016-06-01

    Controversy exists in the simulation community as to the emotional and educational ramifications of mannequin death due to learner action or inaction. No theoretical framework to guide future investigations of learner actions currently exists. The purpose of our study was to generate a model of the learner experience of mannequin death using a mixed methods approach. The study consisted of an initial focus group phase composed of 11 learners who had previously experienced mannequin death due to action or inaction on the part of learners as defined by Leighton (Clin Simul Nurs. 2009;5(2):e59-e62). Transcripts were analyzed using grounded theory to generate a list of relevant themes that were further organized into a theoretical framework. With the use of this framework, a survey was generated and distributed to additional learners who had experienced mannequin death due to action or inaction. Results were analyzed using a mixed methods approach. Forty-one clinicians completed the survey. A correlation was found between the emotional experience of mannequin death and degree of presession anxiety (P framework. Using the previous approach, we created a model of the effect of mannequin death on the educational and psychological state of learners. We offer the final model as a guide to future research regarding the learner experience of mannequin death.

  20. Do students’ styles of learning affect how they adapt to learning methods and to the learning environment?

    OpenAIRE

    Topal, Kenan; Sarıkaya, Özlem; Basturk, Ramazan; Buke, Akile

    2015-01-01

    Objectives: The process of development and evaluation of undergraduate medical education programs should include analysis of learners’ characteristics, needs, and perceptions about learning methods. This study aims to evaluate medical students’ perceptions about problem-based learning methods and to compare these results with their individual learning styles.Materials and Methods: The survey was conducted at Marmara University Medical School where problem-based learning was implemented in the...

  1. Community of practice as a collective way of learning and development of practices and knowledge of the family health strategy: a theoretical study

    Directory of Open Access Journals (Sweden)

    Ana Ecilda Lima Ellery

    2012-06-01

    Full Text Available Objective: Present and discuss the contribution of the concept of Community of Practice (CP, while collective space of learning and development of knowledge and practice in multidisciplinary teams of Family Health Strategy. Methods: Theoretical study through nonsystematic literature reviews the theme of “Communities of Practice” in the work of social researchers Jean Lave and Etienne Wenger, who developed this concept, completed with studies on the same topic from the research in online databases. Results: A CP is characterized by a group of people who forged and got engaged in a common project, sharing a repertoire, which allowed communication between them. Several effects are attributed to the experienceof working together in a CP, such as the socialization of knowledge, the interprofessional collaboration and the development of an environment conducive to reflective practice, which facilitates the conflict mediation. The theory of CP requires a major change in theconception of learning. Unlike theories that consider learning as resulting mainly from the internal process of the person, as the cognitive, the CP’s theory conceives learning through the angle of social participation. The inter-relationship developed by the CP influences the learning process, negotiation of meaning and identity formation, which results from the fact of belonging to the community and from the meaning attributed to the collaborative. Conclusion: The formation of Community of Practice in Family Health Strategy can be adevice to facilitate the construction of interdisciplinary projects, expressed by the integration of knowledge and interprofessional collaboration.

  2. Structural, vibrational and nuclear magnetic resonance investigations of 4-bromoisoquinoline by experimental and theoretical DFT methods.

    Science.gov (United States)

    Arjunan, V; Thillai Govindaraja, S; Jayapraksh, A; Mohan, S

    2013-04-15

    Quantum chemical calculations of energy, structural parameters and vibrational wavenumbers of 4-bromoisoquinoline (4BIQ) were carried out by using B3LYP method using 6-311++G(**), cc-pVTZ and LANL2DZ basis sets. The optimised geometrical parameters obtained by DFT calculations are in good agreement with electron diffraction data. Interpretations of the experimental FTIR and FT-Raman spectra have been reported with the aid of the theoretical wavenumbers. The differences between the observed and scaled wavenumber values of most of the fundamentals are very small. The thermodynamic parameters have also been computed. Electronic properties of the molecule were discussed through the molecular electrostatic potential surface, HOMO-LUMO energy gap and NBO analysis. To provide precise assignments of (1)H and (13)CNMR spectra, isotropic shielding and chemical shifts were calculated with the Gauge-Invariant Atomic Orbital (GIAO) method. Copyright © 2013 Elsevier B.V. All rights reserved.

  3. Using a fuzzy comprehensive evaluation method to determine product usability: A proposed theoretical framework.

    Science.gov (United States)

    Zhou, Ronggang; Chan, Alan H S

    2017-01-01

    In order to compare existing usability data to ideal goals or to that for other products, usability practitioners have tried to develop a framework for deriving an integrated metric. However, most current usability methods with this aim rely heavily on human judgment about the various attributes of a product, but often fail to take into account of the inherent uncertainties in these judgments in the evaluation process. This paper presents a universal method of usability evaluation by combining the analytic hierarchical process (AHP) and the fuzzy evaluation method. By integrating multiple sources of uncertain information during product usability evaluation, the method proposed here aims to derive an index that is structured hierarchically in terms of the three usability components of effectiveness, efficiency, and user satisfaction of a product. With consideration of the theoretical basis of fuzzy evaluation, a two-layer comprehensive evaluation index was first constructed. After the membership functions were determined by an expert panel, the evaluation appraisals were computed by using the fuzzy comprehensive evaluation technique model to characterize fuzzy human judgments. Then with the use of AHP, the weights of usability components were elicited from these experts. Compared to traditional usability evaluation methods, the major strength of the fuzzy method is that it captures the fuzziness and uncertainties in human judgments and provides an integrated framework that combines the vague judgments from multiple stages of a product evaluation process.

  4. Can learning style predict student satisfaction with different instruction methods and academic achievement in medical education?

    Science.gov (United States)

    Gurpinar, Erol; Alimoglu, Mustafa Kemal; Mamakli, Sumer; Aktekin, Mehmet

    2010-12-01

    The curriculum of our medical school has a hybrid structure including both traditional training (lectures) and problem-based learning (PBL) applications. The purpose of this study was to determine the learning styles of our medical students and investigate the relation of learning styles with each of satisfaction with different instruction methods and academic achievement in them. This study was carried out with the participation of 170 first-year medical students (the participation rate was 91.4%). The researchers prepared sociodemographic and satisfaction questionnaires to determine the characteristics of the participants and their satisfaction levels with traditional training and PBL. The Kolb learning styles inventory was used to explore the learning styles of the study group. The participants completed all forms at the end of the first year of medical education. Indicators of academic achievement were scores of five theoretical block exams and five PBL exams performed throughout the academic year of 2008-2009. The majority of the participants took part in the "diverging" (n = 84, 47.7%) and "assimilating" (n = 73, 41.5%) groups. Numbers of students in the "converging" and "accommodating" groups were 11 (6.3%) and 8 (4.5%), respectively. In all learning style groups, PBL satisfaction scores were significantly higher than those of traditional training. Exam scores for "PBL and traditional training" did not differ among the four learning styles. In logistic regression analysis, learning style (assimilating) predicted student satisfaction with traditional training and success in theoretical block exams. Nothing predicted PBL satisfaction and success. This is the first study conducted among medical students evaluating the relation of learning style with student satisfaction and academic achievement. More research with larger groups is needed to generalize our results. Some learning styles may relate to satisfaction with and achievement in some instruction methods.

  5. Deep learning versus traditional machine learning methods for aggregated energy demand prediction

    NARCIS (Netherlands)

    Paterakis, N.G.; Mocanu, E.; Gibescu, M.; Stappers, B.; van Alst, W.

    2018-01-01

    In this paper the more advanced, in comparison with traditional machine learning approaches, deep learning methods are explored with the purpose of accurately predicting the aggregated energy consumption. Despite the fact that a wide range of machine learning methods have been applied to

  6. Preparing Students for Flipped or Team-Based Learning Methods

    Science.gov (United States)

    Balan, Peter; Clark, Michele; Restall, Gregory

    2015-01-01

    Purpose: Teaching methods such as Flipped Learning and Team-Based Learning require students to pre-learn course materials before a teaching session, because classroom exercises rely on students using self-gained knowledge. This is the reverse to "traditional" teaching when course materials are presented during a lecture, and students are…

  7. USE OF VIRTUAL LEARNING ENVIRONMENTS: A THEORETICAL MODEL USING DECOMPOSED EXPECTANCY DISCONFIRMATION THEORY

    OpenAIRE

    Pereira, Fernando Antonio de Melo; Ramos, Anatália Saraiva Martins; Andrade, Adrianne Paula Vieira de; Oliveira, Bruna Miyuki Kasuya de

    2015-01-01

    ABSTRACT The present study aims to investigate the determinants of satisfaction and the resulting continuance intention in the e-learning context. The constructs of decomposed expectancy disconfirmation theory (DEDT) are evaluated from the perspective of users of a virtual learning environment (VLE) in relation to expectations and perceived performance. An online survey collected responses from 197 students of a public management distance learning course. Structural equation modeling was oper...

  8. Assessment of two theoretical methods to estimate potentiometric titration curves of peptides: comparison with experiment.

    Science.gov (United States)

    Makowska, Joanna; Bagiñska, Katarzyna; Makowski, Mariusz; Jagielska, Anna; Liwo, Adam; Kasprzykowski, Franciszek; Chmurzyñski, Lech; Scheraga, Harold A

    2006-03-09

    We compared the ability of two theoretical methods of pH-dependent conformational calculations to reproduce experimental potentiometric titration curves of two models of peptides: Ac-K5-NHMe in 95% methanol (MeOH)/5% water mixture and Ac-XX(A)7OO-NH2 (XAO) (where X is diaminobutyric acid, A is alanine, and O is ornithine) in water, methanol (MeOH), and dimethyl sulfoxide (DMSO), respectively. The titration curve of the former was taken from the literature, and the curve of the latter was determined in this work. The first theoretical method involves a conformational search using the electrostatically driven Monte Carlo (EDMC) method with a low-cost energy function (ECEPP/3 plus the SRFOPT surface-solvation model, assumming that all titratable groups are uncharged) and subsequent reevaluation of the free energy at a given pH with the Poisson-Boltzmann equation, considering variable protonation states. In the second procedure, molecular dynamics (MD) simulations are run with the AMBER force field and the generalized Born model of electrostatic solvation, and the protonation states are sampled during constant-pH MD runs. In all three solvents, the first pKa of XAO is strongly downshifted compared to the value for the reference compounds (ethylamine and propylamine, respectively); the water and methanol curves have one, and the DMSO curve has two jumps characteristic of remarkable differences in the dissociation constants of acidic groups. The predicted titration curves of Ac-K5-NHMe are in good agreement with the experimental ones; better agreement is achieved with the MD-based method. The titration curves of XAO in methanol and DMSO, calculated using the MD-based approach, trace the shape of the experimental curves, reproducing the pH jump, while those calculated with the EDMC-based approach and the titration curve in water calculated using the MD-based approach have smooth shapes characteristic of the titration of weak multifunctional acids with small differences

  9. Learning Methods for Dynamic Topic Modeling in Automated Behavior Analysis.

    Science.gov (United States)

    Isupova, Olga; Kuzin, Danil; Mihaylova, Lyudmila

    2017-09-27

    Semisupervised and unsupervised systems provide operators with invaluable support and can tremendously reduce the operators' load. In the light of the necessity to process large volumes of video data and provide autonomous decisions, this paper proposes new learning algorithms for activity analysis in video. The activities and behaviors are described by a dynamic topic model. Two novel learning algorithms based on the expectation maximization approach and variational Bayes inference are proposed. Theoretical derivations of the posterior estimates of model parameters are given. The designed learning algorithms are compared with the Gibbs sampling inference scheme introduced earlier in the literature. A detailed comparison of the learning algorithms is presented on real video data. We also propose an anomaly localization procedure, elegantly embedded in the topic modeling framework. It is shown that the developed learning algorithms can achieve 95% success rate. The proposed framework can be applied to a number of areas, including transportation systems, security, and surveillance.

  10. Theoretical simulation of the dual-heat-flux method in deep body temperature measurements.

    Science.gov (United States)

    Huang, Ming; Chen, Wenxi

    2010-01-01

    Deep body temperature reveals individual physiological states, and is important in patient monitoring and chronobiological studies. An innovative dual-heat-flux method has been shown experimentally to be competitive with the conventional zero-heat-flow method in its performance, in terms of measurement accuracy and step response to changes in the deep temperature. We have utilized a finite element method to model and simulate the dynamic process of a dual-heat-flux probe in deep body temperature measurements to validate the fundamental principles of the dual-heat-flux method theoretically, and to acquire a detailed quantitative description of the thermal profile of the dual-heat-flux probe. The simulation results show that the estimated deep body temperature is influenced by the ambient temperature (linearly, at a maximum rate of 0.03 °C/°C) and the blood perfusion rate. The corresponding depth of the estimated temperature in the skin and subcutaneous tissue layer is consistent when using the dual-heat-flux probe. Insights in improving the performance of the dual-heat-flux method were discussed for further studies of dual-heat-flux probes, taking into account structural and geometric considerations.

  11. Effects of Jigsaw Learning Method on Students’ Self-Efficacy and Motivation to Learn

    Directory of Open Access Journals (Sweden)

    Dwi Nur Rachmah

    2017-12-01

    Full Text Available Jigsaw learning as a cooperative learning method, according to the results of some studies, can improve academic skills, social competence, behavior in learning, and motivation to learn. However, in some other studies, there are different findings regarding the effect of jigsaw learning method on self-efficacy. The purpose of this study is to examine the effects of jigsaw learning method on self-efficacy and motivation to learn in psychology students at the Faculty of Medicine, Universitas Lambung Mangkurat. The method used in the study is the experimental method using one group pre-test and post-test design. The results of the measurements before and after the use of jigsaw learning method were compared using paired samples t-test. The results showed that there is a difference in students’ self-efficacy and motivation to learn before and after subjected to the treatments; therefore, it can be said that jigsaw learning method had significant effects on self-efficacy and motivation to learn. The application of jigsaw learning model in a classroom with large number of students was the discussion of this study.

  12. A Swarm-Based Learning Method Inspired by Social Insects

    Science.gov (United States)

    He, Xiaoxian; Zhu, Yunlong; Hu, Kunyuan; Niu, Ben

    Inspired by cooperative transport behaviors of ants, on the basis of Q-learning, a new learning method, Neighbor-Information-Reference (NIR) learning method, is present in the paper. This is a swarm-based learning method, in which principles of swarm intelligence are strictly complied with. In NIR learning, the i-interval neighbor's information, namely its discounted reward, is referenced when an individual selects the next state, so that it can make the best decision in a computable local neighborhood. In application, different policies of NIR learning are recommended by controlling the parameters according to time-relativity of concrete tasks. NIR learning can remarkably improve individual efficiency, and make swarm more "intelligent".

  13. Theoretical model and experimental verification on the PID tracking method using liquid crystal optical phased array

    Science.gov (United States)

    Wang, Xiangru; Xu, Jianhua; Huang, Ziqiang; Wu, Liang; Zhang, Tianyi; Wu, Shuanghong; Qiu, Qi

    2017-02-01

    Liquid crystal optical phased array (LC-OPA) has been considered with great potential on the non-mechanical laser deflector because it is fabricated using photolithographic patterning technology which has been well advanced by the electronics and display industry. As a vital application of LC-OPA, free space laser communication has demonstrated its merits on communication bandwidth. Before data communication, ATP (acquisition, tracking and pointing) process costs relatively long time to result in a bottle-neck of free space laser communication. Meanwhile, dynamic real time accurate tracking is sensitive to keep a stable communication link. The electro-optic medium liquid crystal with low driving voltage can be used as the laser beam deflector. This paper presents a fast-track method using liquid crystal optical phased array as the beam deflector, CCD as a beacon light detector. PID (Proportion Integration Differentiation) loop algorithm is introduced as the controlling algorithm to generate the corresponding steering angle. To achieve the goal of fast and accurate tracking, theoretical analysis and experimental verification are demonstrated that PID closed-loop system can suppress the attitude random vibration. Meanwhile, theoretical analysis shows that tracking accuracy can be less than 6.5μrad, with a relative agreement with experimental results which is obtained after 10 adjustments that the tracking accuracy is less than12.6μrad.

  14. Arts-based Methods and Organizational Learning

    DEFF Research Database (Denmark)

    This thematic volume explores the relationship between the arts and learning in various educational contexts and across cultures, but with a focus on higher education and organizational learning. Arts-based interventions are at the heart of this volume, which addresses how they are conceived, des...

  15. Microgenetic Learning Analytics Methods: Workshop Report

    Science.gov (United States)

    Aghababyan, Ani; Martin, Taylor; Janisiewicz, Philip; Close, Kevin

    2016-01-01

    Learning analytics is an emerging discipline and, as such, benefits from new tools and methodological approaches. This work reviews and summarizes our workshop on microgenetic data analysis techniques using R, held at the second annual Learning Analytics Summer Institute in Cambridge, Massachusetts, on 30 June 2014. Specifically, this paper…

  16. STRUCTURAL AND METHODICAL MODEL OF INCREASING THE LEVEL OF THEORETICAL TRAINING OF CADETS USING INFORMATION AND COMMUNICATION TECHNOLOGIES

    Directory of Open Access Journals (Sweden)

    Vladislav V. Bulgakov

    2018-03-01

    Full Text Available Features of training in higher educational institutions of system of EMERCOM of Russia demand introduction of the new educational techniques and the technical means directed on intensification of educational process, providing an opportunity of preparation of cadets at any time in the independent mode and improving quality of their theoretical knowledge. The authors have developed a structural and methodological model of increasing the level of theoretical training of cadets using information and communication technologies. The proposed structural and methodological model that includes elements to stimulate and enhance cognitive activity, allows you to generate the trajectory of theoretical training of cadets for the entire period of study at the University, to organize a systematic independent work, objective, current and final control of theoretical knowledge. The structural and methodological model for improving the level of theoretical training consists of three main elements: the base of theoretical questions, functional modules "teacher" and "cadet". The basis of the structural and methodological model of increasing the level of theoretical training of cadets is the base of theoretical issues, developed in all disciplines specialty 20.05.01 – fire safety. The functional module "teacher" allows you to create theoretical questions of various kinds, edit questions and delete them from the database if necessary, as well as create tests and monitor their implementation. The functional module "cadet" provides ample opportunities for theoretical training through independent work, testing for current and final control, the implementation of the game form of training in the form of a duel, as well as for the formation of the results of the cadets in the form of statistics and rankings. Structural and methodical model of increasing the level of theoretical training of cadets is implemented in practice in the form of a multi-level automated system

  17. A Theoretical Analysis of Learning with Graphics--Implications for Computer Graphics Design.

    Science.gov (United States)

    ChanLin, Lih-Juan

    This paper reviews the literature pertinent to learning with graphics. The dual coding theory provides explanation about how graphics are stored and precessed in semantic memory. The level of processing theory suggests how graphics can be employed in learning to encourage deeper processing. In addition to dual coding theory and level of processing…

  18. A theoretical analysis of temporal difference learning in the iterated prisoner's dilemma game.

    Science.gov (United States)

    Masuda, Naoki; Ohtsuki, Hisashi

    2009-11-01

    Direct reciprocity is a chief mechanism of mutual cooperation in social dilemma. Agents cooperate if future interactions with the same opponents are highly likely. Direct reciprocity has been explored mostly by evolutionary game theory based on natural selection. Our daily experience tells, however, that real social agents including humans learn to cooperate based on experience. In this paper, we analyze a reinforcement learning model called temporal difference learning and study its performance in the iterated Prisoner's Dilemma game. Temporal difference learning is unique among a variety of learning models in that it inherently aims at increasing future payoffs, not immediate ones. It also has a neural basis. We analytically and numerically show that learners with only two internal states properly learn to cooperate with retaliatory players and to defect against unconditional cooperators and defectors. Four-state learners are more capable of achieving a high payoff against various opponents. Moreover, we numerically show that four-state learners can learn to establish mutual cooperation for sufficiently small learning rates.

  19. D4.1 Learning analytics: theoretical background, methodology and expected results

    NARCIS (Netherlands)

    Tammets, Kairit; Laanpere, Mart; Eradze, Maka; Brouns, Francis; Padrón-Nápoles, Carmen; De Rosa, Rosanna; Ferrari, Chiara

    2014-01-01

    The purpose of the EMMA project is to showcase excellence in innovative teaching methodologies and learning approaches through the large-scale piloting of MOOCs on different subjects. The main objectives related with the implementation of learning analytics in EMMa project are to: ● develop the

  20. Alienation and Engagement: Development of an Alternative Theoretical Framework for Understanding Student Learning

    Science.gov (United States)

    Case, Jennifer M.

    2008-01-01

    In this paper it is suggested that the themes of alienation and engagement offer a productive alternative perspective for characterising the student experience of learning in higher education, compared to current dominant perspectives such as that offered by approaches to learning and related concepts. A conceptual and historical background of the…

  1. Studying Economic Space: Synthesis of Balance and Game-Theoretic Methods of Modelling

    Directory of Open Access Journals (Sweden)

    Natalia Gennadyevna Zakharchenko

    2015-12-01

    Full Text Available The article introduces questions about development of models used to study economic space. The author proposes the model that combines balance and game-theoretic methods for estimating system effects of economic agents’ interactions in multi-level economic space. The model is applied to research interactions between economic agents that are spatially heterogeneous within the Russian Far East. In the model the economic space of region is considered in a territorial dimension (the first level of decomposing space and also in territorial and product dimensions (the second level of decomposing space. The paper shows the mechanism of system effects formation that exists in the economic space of region. The author estimates system effects, analyses the real allocation of these effects between economic agents and identifies three types of local industrial markets: with zero, positive and negative system effects

  2. Group theoretical methods in physics. [Tuebingen, July 18-22, 1977

    Energy Technology Data Exchange (ETDEWEB)

    Kramer, P; Rieckers, A

    1978-01-01

    This volume comprises the proceedings of the 6th International Colloquium on Group Theoretical Methods in Physics, held at Tuebingen in July 1977. Invited papers were presented on the following topics: supersymmetry and graded Lie algebras; concepts of order and disorder arising from molecular physics; symplectic structures and many-body physics; symmetry breaking in statistical mechanics and field theory; automata and systems as examples of applied (semi-) group theory; renormalization group; and gauge theories. Summaries are given of the contributed papers, which can be grouped as follows: supersymmetry, symmetry in particles and relativistic physics; symmetry in molecular and solid state physics; broken symmetry and phase transitions; structure of groups and dynamical systems; representations of groups and Lie algebras; and general symmetries, quantization. Those individual papers in scope for the TIC data base are being entered from ATOMINDEX tapes. (RWR)

  3. Valence and lowest Rydberg electronic states of phenol investigated by synchrotron radiation and theoretical methods

    Energy Technology Data Exchange (ETDEWEB)

    Limão-Vieira, P., E-mail: plimaovieira@fct.unl.pt; Ferreira da Silva, F.; Lange, E. [Laboratório de Colisões Atómicas e Moleculares, CEFITEC, Departamento de Física, Faculdade de Ciências e Tecnologia, Universidade NOVA de Lisboa, 2829-516 Caparica (Portugal); Duflot, D. [Univ. Lille, UMR 8523–Physique des Lasers Atomes et Molécules, F-59000 Lille (France); CNRS, UMR 8523, F-59000 Lille (France); Jones, N. C.; Hoffmann, S. V. [ISA, Department of Physics and Astronomy, Aarhus University, Ny Munkegade 120, DK-8000 Aarhus C (Denmark); Śmiałek, M. A. [Department of Control and Power Engineering, Faculty of Ocean Engineering and Ship Technology, Gdańsk University of Technology, Gabriela Narutowicza 11/12, 80-233 Gdańsk (Poland); Department of Physical Sciences, The Open University, Walton Hall, MK7 6AA Milton Keynes (United Kingdom); Jones, D. B. [School of Chemical and Physical Sciences, Flinders University, GPO Box 2100, Adelaide, SA 5001 (Australia); Brunger, M. J. [School of Chemical and Physical Sciences, Flinders University, GPO Box 2100, Adelaide, SA 5001 (Australia); Institute of Mathematical Sciences, University of Malaya, 50603 Kuala Lumpur (Malaysia)

    2016-07-21

    We present the experimental high-resolution vacuum ultraviolet (VUV) photoabsorption spectra of phenol covering for the first time the full 4.3–10.8 eV energy-range, with absolute cross sections determined. Theoretical calculations on the vertical excitation energies and oscillator strengths were performed using time-dependent density functional theory and the equation-of-motion coupled cluster method restricted to single and double excitations level. These have been used in the assignment of valence and Rydberg transitions of the phenol molecule. The VUV spectrum reveals several new features not previously reported in the literature, with particular reference to the 6.401 eV transition, which is here assigned to the 3sσ/σ{sup ∗}(OH)←3π(3a″) transition. The measured absolute photoabsorption cross sections have been used to calculate the photolysis lifetime of phenol in the earth’s atmosphere (0–50 km).

  4. Group-theoretical method in the many-beam theory of electron diffraction

    International Nuclear Information System (INIS)

    Kogiso, Motokazu; Takahashi, Hidewo.

    1977-01-01

    A group-theoretical method is developed for the many-beam dynamical theory of the symmetric Laue case. When the incident wave is directed so that the Laue point lies on a symmetric position in the reciprocal lattice, the dispersion matrix in the fundamental equation can be reduced to a block diagonal form. The transformation matrix is composed of column vectors belonging to irreducible representations of the group of the incident wave vector. Without performing reduction, the reduced form of the dispersion matrix is determined from characters of representations. Practical application is made to the case of symmorphic crystals, where general reduced forms and all solvable examples are given in terms of some geometrical factors of reciprocal lattice arrangements. (auth.)

  5. Work Process Oriented Learning via Mobile Devices – Theoretical Basics and Examples for a (New Didactical Approach

    Directory of Open Access Journals (Sweden)

    Georg Spöttl

    2012-04-01

    Full Text Available Two problems can be identified which counteract the need for further training: On the one hand the clientele of skilled workers is not necessarily keen on further training. On the other hand the time and cost pressure within the sector does not offer any room for time-consuming further training measures far away from the workplace. This is why the project “Virtual Learning on the building site – (Vila-b” was realized in cooperation with the project partners of the University of Bremen (Working group »Digital Media« of the Centre for Information Technology as well as from the economy (Arbeitskreis ökologischer Holzbau e. V. and Claus Holm, pm|c. The project team has tested a concept which facilitated learning adapted to the occupational reality and supported by the advantages of digital media. The central didactical elements for the development of this further training course are the contextual and methodological orientation to real work processes as well as the use of digital mobile media which facilitate learning directly at the workplace. The present article starts with a description of the theoretical basics for learning within the work process and discusses the didactical elements which are necessary for work process oriented learning with digital and mobile media.

  6. Question presentation methods for paired-associate learning

    NARCIS (Netherlands)

    Engel, F.L.; Geerings, M.P.W.

    1988-01-01

    Four different methods of question presentation, in interactive computeraided learning of Dutch-English word pairs are evaluated experimentally. These methods are: 1) the 'open-question method', 2) the 'multiple-choice method', 3) the 'sequential method' and 4) the 'true/ false method'. When

  7. Theoretical validation of potential habitability via analytical and boosted tree methods: An optimistic study on recently discovered exoplanets

    Science.gov (United States)

    Saha, S.; Basak, S.; Safonova, M.; Bora, K.; Agrawal, S.; Sarkar, P.; Murthy, J.

    2018-04-01

    Seven Earth-sized planets, known as the TRAPPIST-1 system, was discovered with great fanfare in the last week of February 2017. Three of these planets are in the habitable zone of their star, making them potentially habitable planets (PHPs) a mere 40 light years away. The discovery of the closest potentially habitable planet to us just a year before - Proxima b and a realization that Earth-type planets in circumstellar habitable zones are a common occurrence provides the impetus to the existing pursuit for life outside the Solar System. The search for life has two goals essentially: looking for planets with Earth-like conditions (Earth similarity) and looking for the possibility of life in some form (habitability). An index was recently developed, the Cobb-Douglas Habitability Score (CDHS), based on Cobb-Douglas habitability production function (CD-HPF), which computes the habitability score by using measured and estimated planetary parameters. As an initial set, radius, density, escape velocity and surface temperature of a planet were used. The proposed metric, with exponents accounting for metric elasticity, is endowed with analytical properties that ensure global optima and can be scaled to accommodate a finite number of input parameters. We show here that the model is elastic, and the conditions on elasticity to ensure global maxima can scale as the number of predictor parameters increase. K-NN (K-Nearest Neighbor) classification algorithm, embellished with probabilistic herding and thresholding restriction, utilizes CDHS scores and labels exoplanets into appropriate classes via feature-learning methods yielding granular clusters of habitability. The algorithm works on top of a decision-theoretical model using the power of convex optimization and machine learning. The goal is to characterize the recently discovered exoplanets into an "Earth League" and several other classes based on their CDHS values. A second approach, based on a novel feature-learning and

  8. Efficient model learning methods for actor-critic control.

    Science.gov (United States)

    Grondman, Ivo; Vaandrager, Maarten; Buşoniu, Lucian; Babuska, Robert; Schuitema, Erik

    2012-06-01

    We propose two new actor-critic algorithms for reinforcement learning. Both algorithms use local linear regression (LLR) to learn approximations of the functions involved. A crucial feature of the algorithms is that they also learn a process model, and this, in combination with LLR, provides an efficient policy update for faster learning. The first algorithm uses a novel model-based update rule for the actor parameters. The second algorithm does not use an explicit actor but learns a reference model which represents a desired behavior, from which desired control actions can be calculated using the inverse of the learned process model. The two novel methods and a standard actor-critic algorithm are applied to the pendulum swing-up problem, in which the novel methods achieve faster learning than the standard algorithm.

  9. Decomposition of overlapping protein complexes: A graph theoretical method for analyzing static and dynamic protein associations

    Directory of Open Access Journals (Sweden)

    Guimarães Katia S

    2006-04-01

    Full Text Available Abstract Background Most cellular processes are carried out by multi-protein complexes, groups of proteins that bind together to perform a specific task. Some proteins form stable complexes, while other proteins form transient associations and are part of several complexes at different stages of a cellular process. A better understanding of this higher-order organization of proteins into overlapping complexes is an important step towards unveiling functional and evolutionary mechanisms behind biological networks. Results We propose a new method for identifying and representing overlapping protein complexes (or larger units called functional groups within a protein interaction network. We develop a graph-theoretical framework that enables automatic construction of such representation. We illustrate the effectiveness of our method by applying it to TNFα/NF-κB and pheromone signaling pathways. Conclusion The proposed representation helps in understanding the transitions between functional groups and allows for tracking a protein's path through a cascade of functional groups. Therefore, depending on the nature of the network, our representation is capable of elucidating temporal relations between functional groups. Our results show that the proposed method opens a new avenue for the analysis of protein interaction networks.

  10. Adaptive e-learning methods and IMS Learning Design. An integrated approach

    NARCIS (Netherlands)

    Burgos, Daniel; Specht, Marcus

    2006-01-01

    Please, cite this publication as: Burgos, D., & Specht, M. (2006). Adaptive e-learning methods and IMS Learning Design. In Kinshuk, R. Koper, P. Kommers, P. Kirschner, D. G. Sampson & W. Didderen (Eds.), Proceedings of the 6th IEEE International Conference on Advanced Learning Technologies (pp.

  11. Geometrical Modification of Learning Vector Quantization Method for Solving Classification Problems

    Directory of Open Access Journals (Sweden)

    Korhan GÜNEL

    2016-09-01

    Full Text Available In this paper, a geometrical scheme is presented to show how to overcome an encountered problem arising from the use of generalized delta learning rule within competitive learning model. It is introduced a theoretical methodology for describing the quantization of data via rotating prototype vectors on hyper-spheres.The proposed learning algorithm is tested and verified on different multidimensional datasets including a binary class dataset and two multiclass datasets from the UCI repository, and a multiclass dataset constructed by us. The proposed method is compared with some baseline learning vector quantization variants in literature for all domains. Large number of experiments verify the performance of our proposed algorithm with acceptable accuracy and macro f1 scores.

  12. Spatial memory: Theoretical basis and comparative review on experimental methods in rodents.

    Science.gov (United States)

    Paul, Carrillo-Mora; Magda, Giordano; Abel, Santamaría

    2009-11-05

    The assessment of learning and memory in animal models has been widely employed in scientific research for a long time. Among these models, those representing diseases with primary processes of affected memory - such as amnesia, dementia, brain aging, etc. - studies dealing with the toxic effects of specific drugs, and other exploring neurodevelopment, trauma, epilepsy and neuropsychiatric disorders, are often called on to employ these tools. There is a diversity of experimental methods assessing animal learning and memory skills. Overall, mazes are the devices mostly used today to test memory in rodents; there are several types of them, but their real usefulness, advantages and applications remain to be fully established and depend on the particular variant selected by the experimenter. The aims of the present article are first, to briefly review the accumulated knowledge in regard to spatial memory tasks; second, to bring the reader information on the different types of rodent mazes available to test spatial memory; and third, to elucidate the usefulness and limitations of each of these devices.

  13. ISSLS prize winner: integrating theoretical and experimental methods for functional tissue engineering of the annulus fibrosus.

    Science.gov (United States)

    Nerurkar, Nandan L; Mauck, Robert L; Elliott, Dawn M

    2008-12-01

    Integrating theoretical and experimental approaches for annulus fibrosus (AF) functional tissue engineering. Apply a hyperelastic constitutive model to characterize the evolution of engineered AF via scalar model parameters. Validate the model and predict the response of engineered constructs to physiologic loading scenarios. There is need for a tissue engineered replacement for degenerate AF. When evaluating engineered replacements for load-bearing tissues, it is necessary to evaluate mechanical function with respect to the native tissue, including nonlinearity and anisotropy. Aligned nanofibrous poly-epsilon-caprolactone scaffolds with prescribed fiber angles were seeded with bovine AF cells and analyzed over 8 weeks, using experimental (mechanical testing, biochemistry, histology) and theoretical methods (a hyperelastic fiber-reinforced constitutive model). The linear region modulus for phi = 0 degrees constructs increased by approximately 25 MPa, and for phi = 90 degrees by approximately 2 MPa from 1 day to 8 weeks in culture. Infiltration and proliferation of AF cells into the scaffold and abundant deposition of s-GAG and aligned collagen was observed. The constitutive model had excellent fits to experimental data to yield matrix and fiber parameters that increased with time in culture. Correlations were observed between biochemical measures and model parameters. The model was successfully validated and used to simulate time-varying responses of engineered AF under shear and biaxial loading. AF cells seeded on nanofibrous scaffolds elaborated an organized, anisotropic AF-like extracellular matrix, resulting in improved mechanical properties. A hyperelastic fiber-reinforced constitutive model characterized the functional evolution of engineered AF constructs, and was used to simulate physiologically relevant loading configurations. Model predictions demonstrated that fibers resist shear even when the shearing direction does not coincide with the fiber direction

  14. Unpacking Teacher-Researcher Collaboration with Three Theoretical Frameworks: A Case of Expansive Learning Activity?

    Science.gov (United States)

    Gade, Sharada

    2015-01-01

    Long association with a mathematics teacher at a Grade 4-6 school in Sweden, is basis for reporting a case of teacher-researcher collaboration. Three theoretical frameworks used to study its development over time are relational knowing, relational agency and cogenerative dialogue. While relational knowing uses narrative perspectives to explore the…

  15. Variation Theory: A Theory of Learning and a Useful Theoretical Framework for Chemical Education Research

    Science.gov (United States)

    Bussey, Thomas J.; Orgill, MaryKay; Crippen, Kent J.

    2013-01-01

    Instructors are constantly baffled by the fact that two students who are sitting in the same class, who have access to the same materials, can come to understand a particular chemistry concept differently. Variation theory offers a theoretical framework from which to explore possible variations in experience and the resulting differences in…

  16. An Innovative Teaching Method To Promote Active Learning: Team-Based Learning

    Science.gov (United States)

    Balasubramanian, R.

    2007-12-01

    Traditional teaching practice based on the textbook-whiteboard- lecture-homework-test paradigm is not very effective in helping students with diverse academic backgrounds achieve higher-order critical thinking skills such as analysis, synthesis, and evaluation. Consequently, there is a critical need for developing a new pedagogical approach to create a collaborative and interactive learning environment in which students with complementary academic backgrounds and learning skills can work together to enhance their learning outcomes. In this presentation, I will discuss an innovative teaching method ('Team-Based Learning (TBL)") which I recently developed at National University of Singapore to promote active learning among students in the environmental engineering program with learning abilities. I implemented this new educational activity in a graduate course. Student feedback indicates that this pedagogical approach is appealing to most students, and promotes active & interactive learning in class. Data will be presented to show that the innovative teaching method has contributed to improved student learning and achievement.

  17. Deep kernel learning method for SAR image target recognition

    Science.gov (United States)

    Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

    2017-10-01

    With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

  18. An investigation on characterizing dense coal-water slurry with ultrasound: theoretical and experimental method

    Energy Technology Data Exchange (ETDEWEB)

    Xue, M.H.; Su, M.X.; Dong, L.L.; Shang, Z.T.; Cai, X.S. [Shanghai University of Science & Technology, Shanghai (China)

    2010-07-01

    Particle size distribution and concentration in particulate two-phase flow are important parameters in a wide variety of industrial areas. For the purpose of online characterization in dense coal-water slurries, ultrasonic methods have many advantages such as avoiding dilution, the capability for being used in real time, and noninvasive testing, while light-based techniques are not capable of providing information because optical methods often require the slurry to be diluted. In this article, the modified Urick equation including temperature modification, which can be used to determine the concentration by means of the measurement of ultrasonic velocity in a coal-water slurry, is evaluated on the basis of theoretical analysis and experimental study. A combination of the coupled-phase model and the Bouguer-Lambert-Beer law is employed in this work, and the attenuation spectrum is measured within the frequency region from 3 to 12 MHz. Particle size distributions of the coal-water slurry at different volume fractions are obtained with the optimum regularization technique. Therefore, the ultrasonic technique presented in this work brings the possibility of using ultrasound for online measurements of dense slurries.

  19. TiO2 synthesized by microwave assisted solvothermal method: Experimental and theoretical evaluation

    International Nuclear Information System (INIS)

    Moura, K.F.; Maul, J.; Albuquerque, A.R.; Casali, G.P.; Longo, E.; Keyson, D.; Souza, A.G.; Sambrano, J.R.; Santos, I.M.G.

    2014-01-01

    In this study, a microwave assisted solvothermal method was used to synthesize TiO 2 with anatase structure. The synthesis was done using Ti (IV) isopropoxide and ethanol without templates or alkalinizing agents. Changes in structural features were observed with increasing time of synthesis and evaluated using periodic quantum chemical calculations. The anatase phase was obtained after only 1 min of reaction besides a small amount of brookite phase. Experimental Raman spectra are in accordance with the theoretical one. Micrometric spheres constituted by nanometric particles were obtained for synthesis from 1 to 30 min, while spheres and sticks were observed after 60 min. - Graphical abstract: FE-SEM images of anatase obtained with different periods of synthesis associated with the order–disorder degree. Display Omitted - Highlights: • Anatase microspheres were obtained by the microwave assisted hydrothermal method. • Only ethanol and titanium isopropoxide were used as precursors during the synthesis. • Raman spectra and XRD patterns were compared with quantum chemical calculations. • Time of synthesis increased the short-range disorder in one direction and decreased in another

  20. A Review on Different Virtual Learning Methods in Pharmacy Education

    Directory of Open Access Journals (Sweden)

    Amin Noori

    2015-10-01

    Full Text Available Virtual learning is a type of electronic learning system based on the web. It models traditional in- person learning by providing virtual access to classes, tests, homework, feedbacks and etc. Students and teachers can interact through chat rooms or other virtual environments. Web 2.0 services are usually used for this method. Internet audio-visual tools, multimedia systems, a disco CD-ROMs, videotapes, animation, video conferencing, and interactive phones can all be used to deliver data to the students. E-learning can occur in or out of the classroom. It is time saving with lower costs compared to traditional methods. It can be self-paced, it is suitable for distance learning and it is flexible. It is a great learning style for continuing education and students can independently solve their problems but it has its disadvantages too. Thereby, blended learning (combination of conventional and virtual education is being used worldwide and has improved knowledge, skills and confidence of pharmacy students.The aim of this study is to review, discuss and introduce different methods of virtual learning for pharmacy students.Google scholar, Pubmed and Scupus databases were searched for topics related to virtual, electronic and blended learning and different styles like computer simulators, virtual practice environment technology, virtual mentor, virtual patient, 3D simulators, etc. are discussed in this article.Our review on different studies on these areas shows that the students are highly satisfied withvirtual and blended types of learning.

  1. Beyond the SCS-CN method: A theoretical framework for spatially lumped rainfall-runoff response

    Science.gov (United States)

    Bartlett, M. S.; Parolari, A. J.; McDonnell, J. J.; Porporato, A.

    2016-06-01

    Since its introduction in 1954, the Soil Conservation Service curve number (SCS-CN) method has become the standard tool, in practice, for estimating an event-based rainfall-runoff response. However, because of its empirical origins, the SCS-CN method is restricted to certain geographic regions and land use types. Moreover, it does not describe the spatial variability of runoff. To move beyond these limitations, we present a new theoretical framework for spatially lumped, event-based rainfall-runoff modeling. In this framework, we describe the spatially lumped runoff model as a point description of runoff that is upscaled to a watershed area based on probability distributions that are representative of watershed heterogeneities. The framework accommodates different runoff concepts and distributions of heterogeneities, and in doing so, it provides an implicit spatial description of runoff variability. Heterogeneity in storage capacity and soil moisture are the basis for upscaling a point runoff response and linking ecohydrological processes to runoff modeling. For the framework, we consider two different runoff responses for fractions of the watershed area: "prethreshold" and "threshold-excess" runoff. These occur before and after infiltration exceeds a storage capacity threshold. Our application of the framework results in a new model (called SCS-CNx) that extends the SCS-CN method with the prethreshold and threshold-excess runoff mechanisms and an implicit spatial description of runoff. We show proof of concept in four forested watersheds and further that the resulting model may better represent geographic regions and site types that previously have been beyond the scope of the traditional SCS-CN method.

  2. A Comparison between the Effect of Cooperative Learning Teaching Method and Lecture Teaching Method on Students' Learning and Satisfaction Level

    Science.gov (United States)

    Mohammadjani, Farzad; Tonkaboni, Forouzan

    2015-01-01

    The aim of the present research is to investigate a comparison between the effect of cooperative learning teaching method and lecture teaching method on students' learning and satisfaction level. The research population consisted of all the fourth grade elementary school students of educational district 4 in Shiraz. The statistical population…

  3. BRIEF INTRODUCTION TO THEORETICAL INTENTION OF "NEEDLING METHOD FOR TRANQUILLIZATION AND CALMING THE MIND" FOR TREATMENT OF INSOMNIA

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    A set of scientific theories and an effective acupuncture therapy for insomnia about "the needling method for tranquillization and calming the mind" are gradually formed through many years' theoretical and clinical studies. In this paper, the theoretical intention about "the needling method for tranquillization and calming the mind" for treatment of insomnia are briefly introduced mainly from the cause of disease,pathogenesis, therapeutic method and characteristics of composition of a prescription, etc. in order to provide a new train of thoughts and a new method for working out scientific and standard prescriptions in the treatment of insomnia.

  4. Unsupervised process monitoring and fault diagnosis with machine learning methods

    CERN Document Server

    Aldrich, Chris

    2013-01-01

    This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel methods to multiple kernel learning for feature extraction from data, and the incremental training of multilayer perceptrons to construct deep architectures for enhanced data

  5. What roles do errors serve in motor skill learning? An examination of two theoretical predictions.

    Science.gov (United States)

    Sanli, Elizabeth A; Lee, Timothy D

    2014-01-01

    Easy-to-difficult and difficult-to-easy progressions of task difficulty during skill acquisition were examined in 2 experiments that assessed retention, dual-task, and transfer tests of learning. Findings of the first experiment suggest that an easy-to difficult progression did not consistently induce implicit learning processes and was not consistently beneficial to performance under a secondary-task load. The findings of experiment two did not support the predictions made based on schema theory and only partially supported predictions based on reinvestment theory. The authors interpret these findings to suggest that the timing of error in relation to the difficulty of the task (functional task difficulty) plays a role in the transfer of learning to novel versions of a task.

  6. Application of machine learning methods in bioinformatics

    Science.gov (United States)

    Yang, Haoyu; An, Zheng; Zhou, Haotian; Hou, Yawen

    2018-05-01

    Faced with the development of bioinformatics, high-throughput genomic technology have enabled biology to enter the era of big data. [1] Bioinformatics is an interdisciplinary, including the acquisition, management, analysis, interpretation and application of biological information, etc. It derives from the Human Genome Project. The field of machine learning, which aims to develop computer algorithms that improve with experience, holds promise to enable computers to assist humans in the analysis of large, complex data sets.[2]. This paper analyzes and compares various algorithms of machine learning and their applications in bioinformatics.

  7. Theoretical and practical considerations for the development of online international collaborative learning for dental hygiene students.

    Science.gov (United States)

    Gussy, M G; Knevel, R J M; Sigurdson, V; Karlberg, G

    2006-08-01

    Globalization and concurrent development in computer and communication technology has increased interest in collaborative online teaching and learning for students in higher education institutions. Many institutions and teachers have introduced computer-supported programmes in areas including dental hygiene. The potential for the use of this technology is exciting; however, its introduction should be careful and considered. We suggest that educators wanting to introduce computer-supported programmes make explicit their pedagogical principles and then select technologies that support and exploit these principles. This paper describes this process as it was applied to the development of an international web-based collaborative learning programme for dental hygiene students.

  8. Are students' impressions of improved learning through active learning methods reflected by improved test scores?

    Science.gov (United States)

    Everly, Marcee C

    2013-02-01

    To report the transformation from lecture to more active learning methods in a maternity nursing course and to evaluate whether student perception of improved learning through active-learning methods is supported by improved test scores. The process of transforming a course into an active-learning model of teaching is described. A voluntary mid-semester survey for student acceptance of the new teaching method was conducted. Course examination results, from both a standardized exam and a cumulative final exam, among students who received lecture in the classroom and students who had active learning activities in the classroom were compared. Active learning activities were very acceptable to students. The majority of students reported learning more from having active-learning activities in the classroom rather than lecture-only and this belief was supported by improved test scores. Students who had active learning activities in the classroom scored significantly higher on a standardized assessment test than students who received lecture only. The findings support the use of student reflection to evaluate the effectiveness of active-learning methods and help validate the use of student reflection of improved learning in other research projects. Copyright © 2011 Elsevier Ltd. All rights reserved.

  9. Theoretical study of the electronic structure of f-element complexes by quantum chemical methods

    International Nuclear Information System (INIS)

    Vetere, V.

    2002-09-01

    This thesis is related to comparative studies of the chemical properties of molecular complexes containing lanthanide or actinide trivalent cations, in the context of the nuclear waste disposal. More precisely, our aim was a quantum chemical analysis of the metal-ligand bonding in such species. Various theoretical approaches were compared, for the inclusion of correlation (density functional theory, multiconfigurational methods) and of relativistic effects (relativistic scalar and 2-component Hamiltonians, relativistic pseudopotentials). The performance of these methods were checked by comparing computed structural properties to published experimental data, on small model systems: lanthanide and actinide tri-halides and on X 3 M-L species (X=F, Cl; M=La, Nd, U; L = NH 3 , acetonitrile, CO). We have thus shown the good performance of density functionals combined with a quasi-relativistic method, as well as of gradient-corrected functionals associated with relativistic pseudopotentials. In contrast, functionals including some part of exact exchange are less reliable to reproduce experimental trends, and we have given a possible explanation for this result . Then, a detailed analysis of the bonding has allowed us to interpret the discrepancies observed in the structural properties of uranium and lanthanides complexes, based on a covalent contribution to the bonding, in the case of uranium(III), which does not exist in the lanthanide(III) homologues. Finally, we have examined more sizeable systems, closer to experimental species, to analyse the influence of the coordination number, of the counter-ions and of the oxidation state of uranium, on the metal-ligand bonding. (author)

  10. A Critical Review of the Use of Wenger's Community of Practice (CoP) Theoretical Framework in Online and Blended Learning Research, 2000-2014

    Science.gov (United States)

    Smith, Sedef Uzuner; Hayes, Suzanne; Shea, Peter

    2017-01-01

    After presenting a brief overview of the key elements that underpin Etienne Wenger's communities of practice (CoP) theoretical framework, one of the most widely cited and influential conceptions of social learning, this paper reviews extant empirical work grounded in this framework to investigate online/blended learning in higher education and in…

  11. Optimal Learning in Schools--Theoretical Evidence: Part 2 Updating Piaget

    Science.gov (United States)

    Crossland, John

    2017-01-01

    Part 1 in this four-part series of articles discussed Piaget's theories of learning and development (Crossland, 2016). Part 2 explores how post-Piagetian researchers have addressed criticisms of Piaget's theories by linking recent evidence including that from neuroscience. The outcomes show that good teachers make a difference by implementing…

  12. Puberty and Sexuality Education Using a Learning and Teaching Theoretical Framework

    Science.gov (United States)

    Collier-Harris, Christine A.; Goldman, Juliette D. G.

    2017-01-01

    All children need timely puberty and sexuality education. The task falls to schools because they have the learning and teaching processes, competency programmes, opportunities, and resources for age-appropriate cognitive, knowledge, and skills development in children and adolescents. Quality sexuality education guidance documents have been…

  13. Optimal Learning in Schools--Theoretical Evidence: Part 3 Individual Differences

    Science.gov (United States)

    Crossland, John

    2017-01-01

    Parts 1 and 2 in this four-part series of articles (Crossland, 2016, 2017) discussed the recent research from neuroscience linked to concepts from cognitive development that brought Piaget's theories into the 21st century and showed the most effective provision towards more optimal learning strategies. Then the discussion moved onto Demetriou's…

  14. Problem Based Learning to enhance students’ reflexivity; theoretical framework and experimental design

    NARCIS (Netherlands)

    Fortuin, K.P.J.; Koppen, van C.S.A.

    2013-01-01

    A crucial skill for scientists involved in sustainability issues is the ability to reflect on knowledge and knowledge production in research projects with high levels of interaction between scientists and other stakeholders. Little is known about adequate teaching and learning strategies that allow

  15. Modeling as a Technique for Promoting Classroom Learning and Prosocial Behavior. Theoretical Paper No. 39.

    Science.gov (United States)

    Frayer, Dorothy A.; Klausmeier, Herbert J.

    Research has shown that a behavior may be acquired through observing and imitating a model. A behavior which has already been acquired may be inhibited, disinhibited, or elicited by observing and imitating. A definition of imitation is given, and the effects of imitation on learning and performance are summarized. Research on factors which affect…

  16. A Practical Guide, with Theoretical Underpinnings, for Creating Effective Virtual Reality Learning Environments

    Science.gov (United States)

    O'Connor, Eileen A.; Domingo, Jelia

    2017-01-01

    With the advent of open source virtual environments, the associated cost reductions, and the more flexible options, avatar-based virtual reality environments are within reach of educators. By using and repurposing readily available virtual environments, instructors can bring engaging, community-building, and immersive learning opportunities to…

  17. Exploratory Theoretical Tests of the Instructor Humor-Student Learning Link

    Science.gov (United States)

    Bolkan, San; Goodboy, Alan K.

    2015-01-01

    Instructors' use of humor is generally a positive influence on student outcomes. However, examinations of humor have found that specific types of messages may not impact, or may even reverse, its positive effect. Instructional humor processing theory (IHPT) has been used to explain how humor impacts student learning. The current study sought to…

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

    Directory of Open Access Journals (Sweden)

    Susana Correnti

    2016-01-01

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

  19. Improved machine learning method for analysis of gas phase chemistry of peptides

    Directory of Open Access Journals (Sweden)

    Ahn Natalie

    2008-12-01

    Full Text Available Abstract Background Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS of peptides from complex digests with theoretically derived spectra from a database of protein sequences. Improved discrimination is achieved with theoretical spectra that are based on simulating gas phase chemistry of the peptides, but the limited understanding of those processes affects the accuracy of predictions from theoretical spectra. Results We employed a robust data mining strategy using new feature annotation functions of MAE software, which revealed under-prediction of the frequency of occurrence in fragmentation of the second peptide bond. We applied methods of exploratory data analysis to pre-process the information in the MS/MS spectra, including data normalization and attribute selection, to reduce the attributes to a smaller, less correlated set for machine learning studies. We then compared our rule building machine learning program, DataSqueezer, with commonly used association rules and decision tree algorithms. All used machine learning algorithms produced similar results that were consistent with expected properties for a second gas phase mechanism at the second peptide bond. Conclusion The results provide compelling evidence that we have identified underlying chemical properties in the data that suggest the existence of an additional gas phase mechanism for the second peptide bond. Thus, the methods described in this study provide a valuable approach for analyses of this kind in the future.

  20. Games and Diabetes: A Review Investigating Theoretical Frameworks, Evaluation Methodologies, and Opportunities for Design Grounded in Learning Theories.

    Science.gov (United States)

    Lazem, Shaimaa; Webster, Mary; Holmes, Wayne; Wolf, Motje

    2015-09-02

    Here we review 18 articles that describe the design and evaluation of 1 or more games for diabetes from technical, methodological, and theoretical perspectives. We undertook searches covering the period 2010 to May 2015 in the ACM, IEEE, Journal of Medical Internet Research, Studies in Health Technology and Informatics, and Google Scholar online databases using the keywords "children," "computer games," "diabetes," "games," "type 1," and "type 2" in various Boolean combinations. The review sets out to establish, for future research, an understanding of the current landscape of digital games designed for children with diabetes. We briefly explored the use and impact of well-established learning theories in such games. The most frequently mentioned theoretical frameworks were social cognitive theory and social constructivism. Due to the limitations of the reported evaluation methodologies, little evidence was found to support the strong promise of games for diabetes. Furthermore, we could not establish a relation between design features and the game outcomes. We argue that an in-depth discussion about the extent to which learning theories could and should be manifested in the design decisions is required. © 2015 Diabetes Technology Society.

  1. Theoretical prediction of hysteretic rubber friction in ball on plate configuration by finite element method

    Directory of Open Access Journals (Sweden)

    2009-11-01

    Full Text Available This paper has investigated theoretically the influence of sliding speed and temperature on the hysteretic friction in case of a smooth, reciprocating steel ball sliding on smooth rubber plate by finite element method (FEM. Generalized Maxwell-models combined with Mooney-Rivlin model have been used to describe the material behaviour of the ethylenepropylene-diene-monomer (EPDM rubber studied. Additionally, the effect of the technique applied at the parameter identification of the material model and the number of Maxwell elements on the coefficient of friction (COF was also investigated. Finally, the open parameter of the Greenwood-Tabor analytical model has been determined from a fit to the FE results. By fitting, as usual, the Maxwell-model to the storage modulus master curve the predicted COF, in a broad frequency range, will be underestimated even in case of 40-term Maxwell-model. To obtain more accurate numerical prediction or to provide an upper limit for the hysteretic friction, in the interesting frequency range, the Maxwell parameters should be determined, as proposed, from a fit to the measured loss factor master curve. This conclusion can be generalized for all the FE simulations where the hysteresis plays an important role.

  2. THEORETICAL AND METHODICAL APPROACHES TO THE FORMATION AND EVALUATION OF THE QUALITY OF TOURIST SERVICES

    Directory of Open Access Journals (Sweden)

    Nataliya Vasylykha

    2017-12-01

    Full Text Available The study, the results of which are described in the article, is devoted to analysing and substantiating approaches to the assessment and quality assurance of tourism services, which form their competitiveness, namely factors and indicators of quality. After all, the integration and globalization of the world society determine the development of tourism as a catalyst for these global processes, and world practice has proved that tourism can be an effective way to solve many socio-economic problems. The subject of the study is the peculiarities of assessing the quality of tourist services. Methodology. The methodological basis of the work is a system of general scientific and special scientific methods, mainly, in the process of research, there are used such methods as system-analytical and dialectical methods – for the theoretical generalization of the investigated material; structural and logical method – in systematizing factors and indicators of the quality of tourist services. The purpose of the article is a theoretical justification of approaches to the quality of tourist services and optimization of their quality assessment. In the research, approaches to the interpretation of the concept of quality are presented and analysed, features of services in general and tourism in particular are concentrated, and it is suggested to group and classify factors and indicators of their quality. The interpretation of the notion of quality is ambiguous, both in Ukrainian and in foreign literary sources, and depends on the point of view on this notion. In our opinion, the most thorough definition characterizes the quality of products and services as a complex feature that determines their suitability to the needs of the consumer. Taking into account the specificity of the term “service”, peculiarities determining the approaches to their evaluation are studied, such a service can be considered a product dominated by intangible elements and also

  3. An Analytical framework of social learning facilitated by participatory methods

    NARCIS (Netherlands)

    Scholz, G.; Dewulf, A.; Pahl-Wostl, C.

    2014-01-01

    Social learning among different stakeholders is often a goal in problem solving contexts such as environmental management. Participatory methods (e.g., group model-building and role playing games) are frequently assumed to stimulate social learning. Yet understanding if and why this assumption is

  4. Blended learning – integrating E-learning with traditional learning methods in teaching basic medical science

    OpenAIRE

    J.G. Bagi; N.K. Hashilkar

    2014-01-01

    Background: Blended learning includes an integration of face to face classroom learning with technology enhanced online material. It provides the convenience, speed and cost effectiveness of e-learning with the personal touch of traditional learning. Objective: The objective of the present study was to assess the effectiveness of a combination of e-learning module and traditional teaching (Blended learning) as compared to traditional teaching alone to teach acid base homeostasis to Phase I MB...

  5. Learning Methods for Radial Basis Functions Networks

    Czech Academy of Sciences Publication Activity Database

    Neruda, Roman; Kudová, Petra

    2005-01-01

    Roč. 21, - (2005), s. 1131-1142 ISSN 0167-739X R&D Projects: GA ČR GP201/03/P163; GA ČR GA201/02/0428 Institutional research plan: CEZ:AV0Z10300504 Keywords : radial basis function networks * hybrid supervised learning * genetic algorithms * benchmarking Subject RIV: BA - General Mathematics Impact factor: 0.555, year: 2005

  6. Machine Learning Methods to Predict Diabetes Complications.

    Science.gov (United States)

    Dagliati, Arianna; Marini, Simone; Sacchi, Lucia; Cogni, Giulia; Teliti, Marsida; Tibollo, Valentina; De Cata, Pasquale; Chiovato, Luca; Bellazzi, Riccardo

    2018-03-01

    One of the areas where Artificial Intelligence is having more impact is machine learning, which develops algorithms able to learn patterns and decision rules from data. Machine learning algorithms have been embedded into data mining pipelines, which can combine them with classical statistical strategies, to extract knowledge from data. Within the EU-funded MOSAIC project, a data mining pipeline has been used to derive a set of predictive models of type 2 diabetes mellitus (T2DM) complications based on electronic health record data of nearly one thousand patients. Such pipeline comprises clinical center profiling, predictive model targeting, predictive model construction and model validation. After having dealt with missing data by means of random forest (RF) and having applied suitable strategies to handle class imbalance, we have used Logistic Regression with stepwise feature selection to predict the onset of retinopathy, neuropathy, or nephropathy, at different time scenarios, at 3, 5, and 7 years from the first visit at the Hospital Center for Diabetes (not from the diagnosis). Considered variables are gender, age, time from diagnosis, body mass index (BMI), glycated hemoglobin (HbA1c), hypertension, and smoking habit. Final models, tailored in accordance with the complications, provided an accuracy up to 0.838. Different variables were selected for each complication and time scenario, leading to specialized models easy to translate to the clinical practice.

  7. Theoretical and Practical Studies on a Possible Genetic Method for Tsetse Fly Control

    Energy Technology Data Exchange (ETDEWEB)

    Curtis, C. F. [Tsetse Research Laboratory, School of Veterinary Science, University Of Bristol, Langford, Bristol (United Kingdom); Hill, W. G. [Institute of Animal Genetics, Edinburgh (United Kingdom)

    1968-06-15

    Chromosome translocations may be useful in pest control because they are a common type of mutation in a variety of organisms and, frequently, the heterozygote is semi-sterile and the homo- zygote folly fertile. It might be possible to induce such a translocation in a pest species, to breed from a selected ancestral pair of translocation homozygotes a large number of the homozygotes and to release these into a wild population. This would cause the production of heterozygotes in the wild population and hence would reduce the fertility of the population. This reduction would persist for a number of generations. Calculations, based on simplified assumptions, showed that this method of fertility reduction might be more economical than the use of sterilized males. In the present paper a theoretical comparison is made of the translocation and sterilized-male methods for the control of tsetse flies (Glossina sp.). A computer model has been set up which simulates, as far as possible, the known facts about birth, mating and death in a wild tsetse population. The predicted effects of releases of sterilized males and of translocation homozygotes are described and the modifications which would be caused by density-dependent mortality, migration and reduced viability of the translocation genotypes and sterilized males are indicated. It is concluded that to eradicate a well isolated wild population the numbers of translocation homozygotes required might well be considerably less than the number of sterilized males required for the same task. However, immigration into the population would greatly reduce the efficiency of the translocation method. The progress so far in attempting to produce a suitable translocation in Glossina austeni is described. Males have been treated with 5-7 krad of gamma radiation and a number of semi-sterile individuals have been selected from among their progeny. The semi-sterility is inherited and, by analogy with the results in other organisms, is

  8. PREFACE: XXXth International Colloquium on Group Theoretical Methods in Physics (ICGTMP) (Group30)

    Science.gov (United States)

    Brackx, Fred; De Schepper, Hennie; Van der Jeugt, Joris

    2015-04-01

    The XXXth International Colloquium on Group Theoretical Methods in Physics (ICGTMP), also known as the Group30 conference, took place in Ghent (Belgium) from Monday 14 to Friday 18 July 2014. The conference was organised by Ghent University (Department of Applied Mathematics, Computer Science and Statistics, and Department of Mathematical Analysis). The website http://www.group30.ugent.be is still available. The ICGTMP is one of the traditional conference series covering the most important topics of symmetry which are relevant to the interplay of present-day mathematics and physics. More than 40 years ago a group of enthusiasts, headed by H. Bacry of Marseille and A. Janner of Nijmegen, initiated a series of annual meetings with the aim to provide a common forum for scientists interested in group theoretical methods. At that time most of the participants belonged to two important communities: on the one hand solid state specialists, elementary particle theorists and phenomenologists, and on the other mathematicians eager to apply newly-discovered group and algebraic structures. The conference series has become a meeting point for scientists working at modelling physical phenomena through mathematical and numerical methods based on geometry and symmetry. It is considered as the oldest one among the conference series devoted to geometry and physics. It has been further broadened and diversified due to the successful applications of geometric and algebraic methods in life sciences and other areas. The first four meetings took place alternatively in Marseille and Nijmegen. Soon after, the conference acquired an international standing, especially following the 1975 colloquium in Nijmegen and the 1976 colloquium in Montreal. Since then it has been organized in many places around the world. It has become a bi-annual colloquium since 1990, the year it was organized in Moscow. This was the first time the colloquium took place in Belgium. There were 246 registered

  9. Learning in Non-Stationary Environments Methods and Applications

    CERN Document Server

    Lughofer, Edwin

    2012-01-01

    Recent decades have seen rapid advances in automatization processes, supported by modern machines and computers. The result is significant increases in system complexity and state changes, information sources, the need for faster data handling and the integration of environmental influences. Intelligent systems, equipped with a taxonomy of data-driven system identification and machine learning algorithms, can handle these problems partially. Conventional learning algorithms in a batch off-line setting fail whenever dynamic changes of the process appear due to non-stationary environments and external influences.   Learning in Non-Stationary Environments: Methods and Applications offers a wide-ranging, comprehensive review of recent developments and important methodologies in the field. The coverage focuses on dynamic learning in unsupervised problems, dynamic learning in supervised classification and dynamic learning in supervised regression problems. A later section is dedicated to applications in which dyna...

  10. Comparative Analysis of Kernel Methods for Statistical Shape Learning

    National Research Council Canada - National Science Library

    Rathi, Yogesh; Dambreville, Samuel; Tannenbaum, Allen

    2006-01-01

    .... In this work, we perform a comparative analysis of shape learning techniques such as linear PCA, kernel PCA, locally linear embedding and propose a new method, kernelized locally linear embedding...

  11. Implementing Adaptive Educational Methods with IMS Learning Design

    NARCIS (Netherlands)

    Specht, Marcus; Burgos, Daniel

    2006-01-01

    Please, cite this publication as: Specht, M. & Burgos, D. (2006). Implementing Adaptive Educational Methods with IMS Learning Design. Proceedings of Adaptive Hypermedia. June, Dublin, Ireland. Retrieved June 30th, 2006, from http://dspace.learningnetworks.org

  12. Implementation of Active Learning Method in Unit Operations II Subject

    OpenAIRE

    Ma'mun, Sholeh

    2018-01-01

    ABSTRACT: Active Learning Method which requires students to take an active role in the process of learning in the classroom has been applied in Department of Chemical Engineering, Faculty of Industrial Technology, Islamic University of Indonesia for Unit Operations II subject in the Even Semester of Academic Year 2015/2016. The purpose of implementation of the learning method is to assist students in achieving competencies associated with the Unit Operations II subject and to help in creating...

  13. Studying depression using imaging and machine learning methods

    Directory of Open Access Journals (Sweden)

    Meenal J. Patel

    2016-01-01

    Full Text Available Depression is a complex clinical entity that can pose challenges for clinicians regarding both accurate diagnosis and effective timely treatment. These challenges have prompted the development of multiple machine learning methods to help improve the management of this disease. These methods utilize anatomical and physiological data acquired from neuroimaging to create models that can identify depressed patients vs. non-depressed patients and predict treatment outcomes. This article (1 presents a background on depression, imaging, and machine learning methodologies; (2 reviews methodologies of past studies that have used imaging and machine learning to study depression; and (3 suggests directions for future depression-related studies.

  14. Studying depression using imaging and machine learning methods.

    Science.gov (United States)

    Patel, Meenal J; Khalaf, Alexander; Aizenstein, Howard J

    2016-01-01

    Depression is a complex clinical entity that can pose challenges for clinicians regarding both accurate diagnosis and effective timely treatment. These challenges have prompted the development of multiple machine learning methods to help improve the management of this disease. These methods utilize anatomical and physiological data acquired from neuroimaging to create models that can identify depressed patients vs. non-depressed patients and predict treatment outcomes. This article (1) presents a background on depression, imaging, and machine learning methodologies; (2) reviews methodologies of past studies that have used imaging and machine learning to study depression; and (3) suggests directions for future depression-related studies.

  15. Medical Students’ View about the Effects of Practical Courses on Learning the General Theoretical Concepts of Basic Medical Sciences

    OpenAIRE

    Leila Roshangar; Fariba Salek Ranjbarzadeh; Reza Piri; Mahdi Karimi Shoar; Leila Rasi Marzabadi

    2014-01-01

    Introduction: The basic medical sciences section requires 2.5 years in the medical education curriculum. Practical courses complement theoretical knowledge in this period to improve their appreciation. Despite spending lots of disbursement and time, this period’s efficacy is not clearly known. Methods: One hundred thirty-three General Practitioner (GP) students have been included in this descriptive cross-sectional study and were asked by questionnaire about the positive impact of practical c...

  16. A Hebbian learning rule gives rise to mirror neurons and links them to control theoretic inverse models

    Directory of Open Access Journals (Sweden)

    Alexander eHanuschkin

    2013-06-01

    Full Text Available Mirror neurons are neurons whose responses to the observation of a motor act resemble responses measured during production of that act. Computationally, mirror neurons have been viewed as evidence for the existence of internal inverse models. Such models, rooted within control theory, map desired sensory targets onto the motor commands required to generate those targets. To jointly explore both the formation of mirrored responses and their functional contribution to inverse models, we develop a correlation-based theory of interactions between a sensory and a motor area. We show that a simple eligibility-weighted Hebbian learning rule, operating within a sensorimotor loop during motor explorations and stabilized by heterosynaptic competition, naturally gives rise to mirror neurons as well as control theoretic inverse models encoded in the synaptic weights from sensory to motor neurons. Crucially, we find that the correlational structure or stereotypy of the neural code underlying motor explorations determines the nature of the learned inverse model: Random motor codes lead to causal inverses that map sensory activity patterns to their motor causes; such inverses are maximally useful, they allow for imitating arbitrary sensory target sequences. By contrast, stereotyped motor codes lead to less useful predictive inverses that map sensory activity to future motor actions.Our theory generalizes previous work on inverse models by showing that such models can be learned in a simple Hebbian framework without the need for error signals or backpropagation, and it makes new conceptual connections between the causal nature of inverse models, the statistical structure of motor variability, and the time-lag between sensory and motor responses of mirror neurons. Applied to bird song learning, our theory can account for puzzling aspects of the song system, including necessity of sensorimotor gating and selectivity of auditory responses to bird’s own song

  17. A Hebbian learning rule gives rise to mirror neurons and links them to control theoretic inverse models.

    Science.gov (United States)

    Hanuschkin, A; Ganguli, S; Hahnloser, R H R

    2013-01-01

    Mirror neurons are neurons whose responses to the observation of a motor act resemble responses measured during production of that act. Computationally, mirror neurons have been viewed as evidence for the existence of internal inverse models. Such models, rooted within control theory, map-desired sensory targets onto the motor commands required to generate those targets. To jointly explore both the formation of mirrored responses and their functional contribution to inverse models, we develop a correlation-based theory of interactions between a sensory and a motor area. We show that a simple eligibility-weighted Hebbian learning rule, operating within a sensorimotor loop during motor explorations and stabilized by heterosynaptic competition, naturally gives rise to mirror neurons as well as control theoretic inverse models encoded in the synaptic weights from sensory to motor neurons. Crucially, we find that the correlational structure or stereotypy of the neural code underlying motor explorations determines the nature of the learned inverse model: random motor codes lead to causal inverses that map sensory activity patterns to their motor causes; such inverses are maximally useful, by allowing the imitation of arbitrary sensory target sequences. By contrast, stereotyped motor codes lead to less useful predictive inverses that map sensory activity to future motor actions. Our theory generalizes previous work on inverse models by showing that such models can be learned in a simple Hebbian framework without the need for error signals or backpropagation, and it makes new conceptual connections between the causal nature of inverse models, the statistical structure of motor variability, and the time-lag between sensory and motor responses of mirror neurons. Applied to bird song learning, our theory can account for puzzling aspects of the song system, including necessity of sensorimotor gating and selectivity of auditory responses to bird's own song (BOS) stimuli.

  18. Maintenance and methods of forming theoretical knowledge and methodical and practical abilities in area of physical culture for students, future specialists on social work

    Directory of Open Access Journals (Sweden)

    Leyfa A.V.

    2009-12-01

    Full Text Available The value of theoretical knowledge, methodical, practical studies, skills in forming physical activity of students is rotined. The level of mastering of components of physical activity is closely associate with the basic blocks of professional preparation of students and their future professional activity. Theoretical knowledge on discipline the «Physical culture» assist the certain affecting depth and breadth of mastering of knowledge of professional preparation.

  19. Active teaching methods, studying responses and learning

    DEFF Research Database (Denmark)

    Christensen, Hans Peter; Vigild, Martin Etchells; Thomsen, Erik Vilain

    Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching.......Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching....

  20. Developing a Blended Learning-Based Method for Problem-Solving in Capability Learning

    Science.gov (United States)

    Dwiyogo, Wasis D.

    2018-01-01

    The main objectives of the study were to develop and investigate the implementation of blended learning based method for problem-solving. Three experts were involved in the study and all three had stated that the model was ready to be applied in the classroom. The implementation of the blended learning-based design for problem-solving was…

  1. SMALL GROUP LEARNING METHODS AND THEIR EFFECT ON LEARNERS’ RELATIONSHIPS

    Directory of Open Access Journals (Sweden)

    Radka Borůvková

    2016-04-01

    Full Text Available Building relationships in the classroom is an essential part of any teacher's career. Having healthy teacher-to-learner and learner-to-learner relationships is an effective way to help prevent pedagogical failure, social conflict and quarrelsome behavior. Many strategies are available that can be used to achieve good long-lasting relationships in the classroom setting. Successful teachers’ pedagogical work in the classroom requires detailed knowledge of learners’ relationships. Good understanding of the relationships is necessary, especially in the case of teenagers’ class. This sensitive period of adolescence demands attention of all teachers who should deal with the problems of their learners. Special care should be focused on children that are out of their classmates’ interest (so called isolated learners or isolates in such class and on possibilities to integrate them into the class. Natural idea how to do it is that of using some modern non-traditional teaching/learning methods, especially the methods based on work in small groups involving learners’ cooperation. Small group education (especially problem-based learning, project-based learning, cooperative learning, collaborative learning or inquire-based learning as one of these methods involves a high degree of interaction. The effectiveness of learning groups is determined by the extent to which the interaction enables members to clarify their own understanding, build upon each other's contributions, sift out meanings, ask and answer questions. An influence of this kind of methods (especially cooperative learning (CL on learners’ relationships was a subject of the further described research. Within the small group education, students work with their classmates to solve complex and authentic problems that help develop content knowledge as well as problem-solving, reasoning, communication, and self-assessment skills. The aim of the research was to answer the question: Can the

  2. Think Pair Share (TPS as Method to Improve Student’s Learning Motivation and Learning Achievement

    Directory of Open Access Journals (Sweden)

    Hetika Hetika

    2018-03-01

    Full Text Available This research aims to find out the application of Think Pair Share (TPS learning method in improving learning motivation and learning achievement in the subject of Introduction to Accounting I of the Accounting Study Program students of Politeknik Harapan Bersama. The Method of data collection in this study used observation method, test method, and documentation method. The research instruments used observation sheet, questionnaire and test question. This research used Class Action Research Design which is an action implementation oriented research, with the aim of improving quality or problem solving in a group by carefully and observing the success rate due to the action. The method of analysis used descriptive qualitative and quantitative analysis method. The results showed that the application of Think Pair Share Learning (TPS Method can improve the Learning Motivation and Achievement. Before the implementation of the action, the obtained score is 67% then in the first cycle increases to 72%, and in the second cycle increasws to 80%. In addition, based on questionnaires distributed to students, it also increases the score of Accounting Learning Motivation where the score in the first cycle of 76% increases to 79%. In addition, in the first cycle, the score of pre test and post test of the students has increased from 68.86 to 76.71 while in the second cycle the score of pre test and post test of students has increased from 79.86 to 84.86.

  3. Theoretical Background for Predicting the Properties of Petroleum Fluids via Group Contribution Methods

    Czech Academy of Sciences Publication Activity Database

    Bogdanić, Grozdana; Pavlíček, Jan; Wichterle, Ivan

    2012-01-01

    Roč. 42, SI (2012), s. 1873-1878 E-ISSN 1877-7058. [International Congress of Chemical and Process Engineering CHISA 2012 and 15th Conference PRES 2012 /20./. Prague, 25.08.2012-29.08.2012] Institutional support: RVO:67985858 Keywords : petroleum fluids * prediction * physico-chemical properties Subject RIV: CF - Physical ; Theoretical Chemistry

  4. Transactors, Transformers and Beyond. A Multi-Method Development of a Theoretical Typology of Leadership.

    Science.gov (United States)

    Pearce, Craig L.; Sims, Henry P., Jr.; Cox, Jonathan F.; Ball, Gail; Schnell, Eugene; Smith, Ken A.; Trevino, Linda

    2003-01-01

    To extend the transactional-transformational model of leadership, four theoretical behavioral types of leadership were developed based on literature review and data from studies of executive behavior (n=253) and subordinate attitudes (n=208). Confirmatory factor analysis of a third data set (n=702) support the existence of four leadership types:…

  5. Theoretical vs. empirical discriminability: the application of ROC methods to eyewitness identification.

    Science.gov (United States)

    Wixted, John T; Mickes, Laura

    2018-01-01

    Receiver operating characteristic (ROC) analysis was introduced to the field of eyewitness identification 5 years ago. Since that time, it has been both influential and controversial, and the debate has raised an issue about measuring discriminability that is rarely considered. The issue concerns the distinction between empirical discriminability (measured by area under the ROC curve) vs. underlying/theoretical discriminability (measured by d' or variants of it). Under most circumstances, the two measures will agree about a difference between two conditions in terms of discriminability. However, it is possible for them to disagree, and that fact can lead to confusion about which condition actually yields higher discriminability. For example, if the two conditions have implications for real-world practice (e.g., a comparison of competing lineup formats), should a policymaker rely on the area-under-the-curve measure or the theory-based measure? Here, we illustrate the fact that a given empirical ROC yields as many underlying discriminability measures as there are theories that one is willing to take seriously. No matter which theory is correct, for practical purposes, the singular area-under-the-curve measure best identifies the diagnostically superior procedure. For that reason, area under the ROC curve informs policy in a way that underlying theoretical discriminability never can. At the same time, theoretical measures of discriminability are equally important, but for a different reason. Without an adequate theoretical understanding of the relevant task, the field will be in no position to enhance empirical discriminability.

  6. A decision-theoretic approach to collaboration: Principal description methods and efficient heuristic approximations

    NARCIS (Netherlands)

    Oliehoek, F.A.; Visser, A.; Babuška, R.; Groen, F.C.A

    2010-01-01

    This chapter gives an overview of the state of the art in decision-theoretic models to describe cooperation between multiple agents in a dynamic environment. Making (near-) optimal decisions in such settings gets harder when the number of agents grows or the uncertainty about the environment

  7. Deep learning methods for protein torsion angle prediction.

    Science.gov (United States)

    Li, Haiou; Hou, Jie; Adhikari, Badri; Lyu, Qiang; Cheng, Jianlin

    2017-09-18

    Deep learning is one of the most powerful machine learning methods that has achieved the state-of-the-art performance in many domains. Since deep learning was introduced to the field of bioinformatics in 2012, it has achieved success in a number of areas such as protein residue-residue contact prediction, secondary structure prediction, and fold recognition. In this work, we developed deep learning methods to improve the prediction of torsion (dihedral) angles of proteins. We design four different deep learning architectures to predict protein torsion angles. The architectures including deep neural network (DNN) and deep restricted Boltzmann machine (DRBN), deep recurrent neural network (DRNN) and deep recurrent restricted Boltzmann machine (DReRBM) since the protein torsion angle prediction is a sequence related problem. In addition to existing protein features, two new features (predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments) are used as input to each of the four deep learning architectures to predict phi and psi angles of protein backbone. The mean absolute error (MAE) of phi and psi angles predicted by DRNN, DReRBM, DRBM and DNN is about 20-21° and 29-30° on an independent dataset. The MAE of phi angle is comparable to the existing methods, but the MAE of psi angle is 29°, 2° lower than the existing methods. On the latest CASP12 targets, our methods also achieved the performance better than or comparable to a state-of-the art method. Our experiment demonstrates that deep learning is a valuable method for predicting protein torsion angles. The deep recurrent network architecture performs slightly better than deep feed-forward architecture, and the predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments are useful features for improving prediction accuracy.

  8. In silico machine learning methods in drug development.

    Science.gov (United States)

    Dobchev, Dimitar A; Pillai, Girinath G; Karelson, Mati

    2014-01-01

    Machine learning (ML) computational methods for predicting compounds with pharmacological activity, specific pharmacodynamic and ADMET (absorption, distribution, metabolism, excretion and toxicity) properties are being increasingly applied in drug discovery and evaluation. Recently, machine learning techniques such as artificial neural networks, support vector machines and genetic programming have been explored for predicting inhibitors, antagonists, blockers, agonists, activators and substrates of proteins related to specific therapeutic targets. These methods are particularly useful for screening compound libraries of diverse chemical structures, "noisy" and high-dimensional data to complement QSAR methods, and in cases of unavailable receptor 3D structure to complement structure-based methods. A variety of studies have demonstrated the potential of machine-learning methods for predicting compounds as potential drug candidates. The present review is intended to give an overview of the strategies and current progress in using machine learning methods for drug design and the potential of the respective model development tools. We also regard a number of applications of the machine learning algorithms based on common classes of diseases.

  9. TEACHING METHODS IN MBA AND LIFELONG LEARNING PROGRAMMES FOR MANAGERS

    Directory of Open Access Journals (Sweden)

    Jarošová, Eva

    2017-09-01

    Full Text Available Teaching methods in MBA and Lifelong Learning Programmes (LLP for managers should be topically relevant in terms of content as well as the teaching methods used. In terms of the content, the integral part of MBA and Lifelong Learning Programmes for managers should be the development of participants’ leadership competencies and their understanding of current leadership concepts. The teaching methods in educational programmes for managers as adult learners should correspond to the strategy of learner-centred teaching that focuses on the participants’ learning process and their active involvement in class. The focus on the participants’ learning process also raises questions about whether the programme’s participants perceive the teaching methods used as useful and relevant for their development as leaders. The paper presents the results of the analysis of the responses to these questions in a sample of 54 Czech participants in the MBA programme and of lifelong learning programmes at the University of Economics, Prague. The data was acquired based on written or electronically submitted questionnaires. The data was analysed in relation to the usefulness of the teaching methods for understanding the concepts of leadership, leadership skills development as well as respondents’ personal growth. The results show that the respondents most valued the methods that enabled them to get feedback, activated them throughout the programme and got them involved in discussions with others in class. Implications for managerial education practices are discussed.

  10. FLIPPED CLASSROOM LEARNING METHOD TO IMPROVE CARING AND LEARNING OUTCOME IN FIRST YEAR NURSING STUDENT

    Directory of Open Access Journals (Sweden)

    Ni Putu Wulan Purnama Sari

    2017-08-01

    Full Text Available Background and Purpose: Caring is the essence of nursing profession. Stimulation of caring attitude should start early. Effective teaching methods needed to foster caring attitude and improve learning achievement. This study aimed to explain the effect of applying flipped classroom learning method for improving caring attitude and learning achievement of new student nurses at nursing institutions in Surabaya. Method: This is a pre-experimental study using the one group pretest posttest and posttest only design. Population was all new student nurses on nursing institutions in Surabaya. Inclusion criteria: female, 18-21 years old, majoring in nursing on their own volition and being first choice during students selection process, status were active in the even semester of 2015/2016 academic year. Sample size was 67 selected by total sampling. Variables: 1 independent: application of flipped classroom learning method; 2 dependent: caring attitude, learning achievement. Instruments: teaching plan, assignment descriptions, presence list, assignment assessment rubrics, study materials, questionnaires of caring attitude. Data analysis: paired and one sample t test. Ethical clearance was available. Results: Most respondents were 20 years old (44.8%, graduated from high school in Surabaya (38.8%, living with parents (68.7% in their homes (64.2%. All data were normally distributed. Flipped classroom learning method could improve caring attitude by 4.13%. Flipped classroom learning method was proved to be effective for improving caring attitude (p=0.021 and learning achievement (p=0.000. Conclusion and Recommendation: Flipped classroom was effective for improving caring attitude and learning achievement of new student nurse. It is recommended to use mix-method and larger sample for further study.

  11. Science Learning Cycle Method to Enhance the Conceptual Understanding and the Learning Independence on Physics Learning

    Science.gov (United States)

    Sulisworo, Dwi; Sutadi, Novitasari

    2017-01-01

    There have been many studies related to the implementation of cooperative learning. However, there are still many problems in school related to the learning outcomes on science lesson, especially in physics. The aim of this study is to observe the application of science learning cycle (SLC) model on improving scientific literacy for secondary…

  12. Finding protein sites using machine learning methods

    Directory of Open Access Journals (Sweden)

    Jaime Leonardo Bobadilla Molina

    2003-07-01

    Full Text Available The increasing amount of protein three-dimensional (3D structures determined by x-ray and NMR technologies as well as structures predicted by computational methods results in the need for automated methods to provide inital annotations. We have developed a new method for recognizing sites in three-dimensional protein structures. Our method is based on a previosly reported algorithm for creating descriptions of protein microenviroments using physical and chemical properties at multiple levels of detail. The recognition method takes three inputs: 1. A set of control nonsites that share some structural or functional role. 2. A set of control nonsites that lack this role. 3. A single query site. A support vector machine classifier is built using feature vectors where each component represents a property in a given volume. Validation against an independent test set shows that this recognition approach has high sensitivity and specificity. We also describe the results of scanning four calcium binding proteins (with the calcium removed using a three dimensional grid of probe points at 1.25 angstrom spacing. The system finds the sites in the proteins giving points at or near the blinding sites. Our results show that property based descriptions along with support vector machines can be used for recognizing protein sites in unannotated structures.

  13. Approximation methods for efficient learning of Bayesian networks

    CERN Document Server

    Riggelsen, C

    2008-01-01

    This publication offers and investigates efficient Monte Carlo simulation methods in order to realize a Bayesian approach to approximate learning of Bayesian networks from both complete and incomplete data. For large amounts of incomplete data when Monte Carlo methods are inefficient, approximations are implemented, such that learning remains feasible, albeit non-Bayesian. The topics discussed are: basic concepts about probabilities, graph theory and conditional independence; Bayesian network learning from data; Monte Carlo simulation techniques; and, the concept of incomplete data. In order to provide a coherent treatment of matters, thereby helping the reader to gain a thorough understanding of the whole concept of learning Bayesian networks from (in)complete data, this publication combines in a clarifying way all the issues presented in the papers with previously unpublished work.

  14. Research on demand-oriented Business English learning method

    Directory of Open Access Journals (Sweden)

    Zhou Yuan

    2016-01-01

    Full Text Available Business English is integrated with visual-audio-oral English, which focuses on the application for English listening and speaking skills in common business occasions, and acquire business knowledge and improve skills through English. This paper analyzes the Business English Visual-audio-oral Course, and learning situation of higher vocational students’ learning objectives, interests, vocabulary, listening and speaking, and focuses on the research of effective methods to guide the higher vocational students to learn Business English Visual-audio-oral Course, master Business English knowledge, and improve communicative competence of Business English.

  15. The evaluation of reflective learning from the nursing student's point of view: A mixed method approach.

    Science.gov (United States)

    Fernández-Peña, Rosario; Fuentes-Pumarola, Concepció; Malagón-Aguilera, M Carme; Bonmatí-Tomàs, Anna; Bosch-Farré, Cristina; Ballester-Ferrando, David

    2016-09-01

    Adapting university programmes to European Higher Education Area criteria has required substantial changes in curricula and teaching methodologies. Reflective learning (RL) has attracted growing interest and occupies an important place in the scientific literature on theoretical and methodological aspects of university instruction. However, fewer studies have focused on evaluating the RL methodology from the point of view of nursing students. To assess nursing students' perceptions of the usefulness and challenges of RL methodology. Mixed method design, using a cross-sectional questionnaire and focus group discussion. The research was conducted via self-reported reflective learning questionnaire complemented by focus group discussion. Students provided a positive overall evaluation of RL, highlighting the method's capacity to help them better understand themselves, engage in self-reflection about the learning process, optimize their strengths and discover additional training needs, along with searching for continuous improvement. Nonetheless, RL does not help them as much to plan their learning or identify areas of weakness or needed improvement in knowledge, skills and attitudes. Among the difficulties or challenges, students reported low motivation and lack of familiarity with this type of learning, along with concerns about the privacy of their reflective journals and about the grading criteria. In general, students evaluated RL positively. The results suggest areas of needed improvement related to unfamiliarity with the methodology, ethical aspects of developing a reflective journal and the need for clear evaluation criteria. Copyright © 2016 Elsevier Ltd. All rights reserved.

  16. [Which learning methods are expected for ultrasound training? Blended learning on trial].

    Science.gov (United States)

    Röhrig, S; Hempel, D; Stenger, T; Armbruster, W; Seibel, A; Walcher, F; Breitkreutz, R

    2014-10-01

    Current teaching methods in graduate and postgraduate training often include frontal presentations. Especially in ultrasound education not only knowledge but also sensomotory and visual skills need to be taught. This requires new learning methods. This study examined which types of teaching methods are preferred by participants in ultrasound training courses before, during and after the course by analyzing a blended learning concept. It also investigated how much time trainees are willing to spend on such activities. A survey was conducted at the end of a certified ultrasound training course. Participants were asked to complete a questionnaire based on a visual analogue scale (VAS) in which three categories were defined: category (1) vote for acceptance with a two thirds majority (VAS 67-100%), category (2) simple acceptance (50-67%) and category (3) rejection (learning program with interactive elements, short presentations (less than 20 min), incorporating interaction with the audience, hands-on sessions in small groups, an alternation between presentations and hands-on-sessions, live demonstrations and quizzes. For post-course learning, interactive and media-assisted approaches were preferred, such as e-learning, films of the presentations and the possibility to stay in contact with instructors in order to discuss the results. Participants also voted for maintaining a logbook for documentation of results. The results of this study indicate the need for interactive learning concepts and blended learning activities. Directors of ultrasound courses may consider these aspects and are encouraged to develop sustainable learning pathways.

  17. Research on demand-oriented Business English learning method

    OpenAIRE

    Zhou Yuan

    2016-01-01

    Business English is integrated with visual-audio-oral English, which focuses on the application for English listening and speaking skills in common business occasions, and acquire business knowledge and improve skills through English. This paper analyzes the Business English Visual-audio-oral Course, and learning situation of higher vocational students’ learning objectives, interests, vocabulary, listening and speaking, and focuses on the research of effective methods to guide the higher voca...

  18. Future Competencies and Learning Methods in Engineering Education

    DEFF Research Database (Denmark)

    Kolmos, Anette

    2002-01-01

    What are the competencies for tommorow´s enginnering education and the implications of these regarding the choice of teaching content and learning methods? The paper analyses two trends: the traditional and the techo-science approach. These two trends are based on technological innovation...... and change processes and impact on educational content and methods....

  19. Empowering and Engaging Students in Learning Research Methods

    Science.gov (United States)

    Liu, Shuang; Breit, Rhonda

    2013-01-01

    The capacity to conduct research is essential for university graduates to survive and thrive in their future career. However, research methods courses have often been considered by students as "abstract", "uninteresting", and "hard". Thus, motivating students to engage in the process of learning research methods has become a crucial challenge for…

  20. Radiochemical methods. Analytical chemistry by open learning

    Energy Technology Data Exchange (ETDEWEB)

    Geary, W.J.; James, A.M. (ed.)

    1986-01-01

    This book presents the analytical uses of radioactive isotopes within the context of radiochemistry as a whole. It is designed for scientists with relatively little background knowledge of the subject. Thus the initial emphasis is on developing the basic concepts of radioactive decay, particularly as they affect the potential usage of radioisotopes. Discussion of the properties of various types of radiation, and of factors such as half-life, is related to practical considerations such as counting and preparation methods, and handling/disposal problems. Practical aspects are then considered in more detail, and the various radioanalytical methods are outlined with particular reference to their applicability. The approach is 'user friendly' and the use of self assessment questions allows the reader to test his/her understanding of individual sections easily. For those who wish to develop their knowledge further, a reading list is provided.

  1. Uncertain Photometric Redshifts with Deep Learning Methods

    Science.gov (United States)

    D'Isanto, A.

    2017-06-01

    The need for accurate photometric redshifts estimation is a topic that has fundamental importance in Astronomy, due to the necessity of efficiently obtaining redshift information without the need of spectroscopic analysis. We propose a method for determining accurate multi-modal photo-z probability density functions (PDFs) using Mixture Density Networks (MDN) and Deep Convolutional Networks (DCN). A comparison with a Random Forest (RF) is performed.

  2. Monte Carlo methods for preference learning

    DEFF Research Database (Denmark)

    Viappiani, P.

    2012-01-01

    Utility elicitation is an important component of many applications, such as decision support systems and recommender systems. Such systems query the users about their preferences and give recommendations based on the system’s belief about the utility function. Critical to these applications is th...... is the acquisition of prior distribution about the utility parameters and the possibility of real time Bayesian inference. In this paper we consider Monte Carlo methods for these problems....

  3. Game-theoretic learning and distributed optimization in memoryless multi-agent systems

    CERN Document Server

    Tatarenko, Tatiana

    2017-01-01

    This book presents new efficient methods for optimization in realistic large-scale, multi-agent systems. These methods do not require the agents to have the full information about the system, but instead allow them to make their local decisions based only on the local information, possibly obtained during scommunication with their local neighbors. The book, primarily aimed at researchers in optimization and control, considers three different information settings in multi-agent systems: oracle-based, communication-based, and payoff-based. For each of these information types, an efficient optimization algorithm is developed, which leads the system to an optimal state. The optimization problems are set without such restrictive assumptions as convexity of the objective functions, complicated communication topologies, closed-form expressions for costs and utilities, and finiteness of the system’s state space. .

  4. The Influence of Background Music on Learning in the Light of Different Theoretical Perspectives and the Role of Working Memory Capacity

    OpenAIRE

    Lehmann, Janina A. M.; Seufert, Tina

    2017-01-01

    This study investigates how background music influences learning with respect to three different theoretical approaches. Both the Mozart effect as well as the arousal-mood-hypothesis indicate that background music can potentially benefit learning outcomes. While the Mozart effect assumes a direct influence of background music on cognitive abilities, the arousal-mood-hypothesis assumes a mediation effect over arousal and mood. However, the seductive detail effect indicates that seductive detai...

  5. Choosing Learning Methods Suitable for Teaching and Learning in Computer Science

    Science.gov (United States)

    Taylor, Estelle; Breed, Marnus; Hauman, Ilette; Homann, Armando

    2013-01-01

    Our aim is to determine which teaching methods students in Computer Science and Information Systems prefer. There are in total 5 different paradigms (behaviorism, cognitivism, constructivism, design-based and humanism) with 32 models between them. Each model is unique and states different learning methods. Recommendations are made on methods that…

  6. Implementation of 2D Discrete Wavelet Transform by Number Theoretic Transform and 2D Overlap-Save Method

    Directory of Open Access Journals (Sweden)

    Lina Yang

    2014-01-01

    Full Text Available To reduce the computation complexity of wavelet transform, this paper presents a novel approach to be implemented. It consists of two key techniques: (1 fast number theoretic transform(FNTT In the FNTT, linear convolution is replaced by the circular one. It can speed up the computation of 2D discrete wavelet transform. (2 In two-dimensional overlap-save method directly calculating the FNTT to the whole input sequence may meet two difficulties; namely, a big modulo obstructs the effective implementation of the FNTT and a long input sequence slows the computation of the FNTT down. To fight with such deficiencies, a new technique which is referred to as 2D overlap-save method is developed. Experiments have been conducted. The fast number theoretic transform and 2D overlap-method have been used to implement the dyadic wavelet transform and applied to contour extraction in pattern recognition.

  7. Primary exploration of the application of case based learning method in clinical probation teaching of the integrated curriculum of hematology

    Institute of Scientific and Technical Information of China (English)

    Zi-zhen XU; Ye-fei WANG; Yan WANG; Shu CHENG; Yi-qun HU; Lei DING

    2015-01-01

    Objective To explore the application and the effect of the case based learning(CBL)method in clinical probation teaching of the integrated curriculum of hematology among eight-year-program medical students.Methods The CBL method was applied to the experimental group,and the traditional approach for the control group.After the lecture,a questionnaire survey was conducted to evaluate the teaching effect in the two groups.Results The CBL method efficiently increased the students’interest in learning and autonomous learning ability,enhanced their ability to solve clinical problems with basic theoretic knowledge and cultivated their clinical thinking ability.Conclusion The CBL method can improve the quality of clinical probation teaching of the integrated curriculum of hematology among eight-year-program medical students.

  8. Machine Learning Methods for Attack Detection in the Smart Grid.

    Science.gov (United States)

    Ozay, Mete; Esnaola, Inaki; Yarman Vural, Fatos Tunay; Kulkarni, Sanjeev R; Poor, H Vincent

    2016-08-01

    Attack detection problems in the smart grid are posed as statistical learning problems for different attack scenarios in which the measurements are observed in batch or online settings. In this approach, machine learning algorithms are used to classify measurements as being either secure or attacked. An attack detection framework is provided to exploit any available prior knowledge about the system and surmount constraints arising from the sparse structure of the problem in the proposed approach. Well-known batch and online learning algorithms (supervised and semisupervised) are employed with decision- and feature-level fusion to model the attack detection problem. The relationships between statistical and geometric properties of attack vectors employed in the attack scenarios and learning algorithms are analyzed to detect unobservable attacks using statistical learning methods. The proposed algorithms are examined on various IEEE test systems. Experimental analyses show that machine learning algorithms can detect attacks with performances higher than attack detection algorithms that employ state vector estimation methods in the proposed attack detection framework.

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

    Directory of Open Access Journals (Sweden)

    Wei Xue

    2016-08-01

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

  10. The Open Method of Co-ordination and the Analysis of Mutual Learning Processes of the European Employment Strategy

    DEFF Research Database (Denmark)

    Nedergaard, Peter

    2005-01-01

    The purpose of this paper is to address two normative and interlinked methodological and theoretical questions concerning the Open Method of Coordination (OMC): First, what is the most appropriate approach to learning in the analyses of the processes of the European Employment Strategy (EES......)? Second, how should mutual learning processes be diffused among the Member States in order to be efficient? In answering these two questions the paper draws on a social constructivist approach to learning thereby contributing to the debate about learning in the political science literature. At the same...... time, based on the literature and participatory observations, it is concluded that the learning effects of the EES are probably somewhat larger than what is normally suggested, but that successful diffusion still depends on a variety of contextual factors. At the end of the paper a path for empirical...

  11. The theoretical study of full spectrum analysis method for airborne gamma-ray spectrometric data

    International Nuclear Information System (INIS)

    Ni Weichong

    2011-01-01

    Spectra of airborne gamma-ray spectrometry was found to be the synthesis of spectral components of radioelement sources by analyzing the constitution of radioactive sources for airborne gamma-ray spectrometric survey and establishing the models of gamma-ray measurement. The mathematical equation for analysising airborne gamma-ray full spectrometric data can be expressed into matrix and related expansions were developed for the mineral resources exploration, environmental radiation measurement, nuclear emergency monitoring, and so on. Theoretical study showed that the atmospheric radon could be directly computed by airborne gamma-ray spectrometric data with full spectrum analysis without the use of the accessional upward-looking detectors. (authors)

  12. Current and future prospects for the application of systematic theoretical methods to the study of problems in physical oceanography

    Energy Technology Data Exchange (ETDEWEB)

    Constantin, A., E-mail: adrian.constantin@kcl.ac.uk [Department of Mathematics, King' s College London, Strand, London WC2R 2LS (United Kingdom); Faculty of Mathematics, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Vienna (Austria); Johnson, R.S., E-mail: r.s.johnson@ncl.ac.uk [School of Mathematics & Statistics, Newcastle University, Newcastle upon Tyne NE1 7RU (United Kingdom)

    2016-09-07

    Highlights: • Systematic theoretical methods in studies of equatorial ocean dynamics. • Linear wave-current interactions in stratified flows. • Exact solutions – Kelvin waves, azimuthal non-uniform currents. • Three-dimensional nonlinear currents. • Hamiltonian formulation for the governing equations and for structure-preserving/enhancing approximations. - Abstract: This essay is a commentary on the pivotal role of systematic theoretical methods in physical oceanography. At some level, there will always be a conflict between theory and experiment/data collection: Which is pre-eminent? Which should come first? This issue appears to be particularly marked in physical oceanography, to the extreme detriment of the development of the subject. It is our contention that the classical theory of fluids, coupled with methods from the theory of differential equations, can play a significant role in carrying the subject, and our understanding, forward. We outline the philosophy behind a systematic theoretical approach, highlighting some aspects of equatorial ocean dynamics where these methods have already been successful, paving the way for much more in the future and leading, we expect, to the better understanding of this and many other types of ocean flow. We believe that the ideas described here promise to reveal a rich and beautiful dynamical structure.

  13. Bayesian methods for addressing long-standing problems in associative learning: The case of PREE.

    Science.gov (United States)

    Blanco, Fernando; Moris, Joaquín

    2017-07-20

    Most associative models typically assume that learning can be understood as a gradual change in associative strength that captures the situation into one single parameter, or representational state. We will call this view single-state learning. However, there is ample evidence showing that under many circumstances different relationships that share features can be learned independently, and animals can quickly switch between expressing one or another. We will call this multiple-state learning. Theoretically, it is understudied because it needs a different data analysis approach from those usually employed. In this paper, we present a Bayesian model of the Partial Reinforcement Extinction Effect (PREE) that can test the predictions of the multiple-state view. This implies estimating the moment of change in the responses (from the acquisition to the extinction performance), both at the individual and at the group levels. We used this model to analyze data from a PREE experiment with three levels of reinforcement during acquisition (100%, 75% and 50%). We found differences in the estimated moment of switch between states during extinction, so that it was delayed after leaner partial reinforcement schedules. The finding is compatible with the multiple-state view. It is the first time, to our knowledge, that the predictions from the multiple-state view are tested directly. The paper also aims to show the benefits that Bayesian methods can bring to the associative learning field.

  14. Cooperative Learning in Elementary Schools

    Science.gov (United States)

    Slavin, Robert E.

    2015-01-01

    Cooperative learning refers to instructional methods in which students work in small groups to help each other learn. Although cooperative learning methods are used for different age groups, they are particularly popular in elementary (primary) schools. This article discusses methods and theoretical perspectives on cooperative learning for the…

  15. Collaborative and situated learning on the web ? how can teacher education theoretically and practically respond to changing demands and roles of teachers?

    DEFF Research Database (Denmark)

    Petersen, Karen Bjerg

    2006-01-01

    Etienne Wenger. The work by Jean Lave from 1988 (Lave, 1988) based on anthropological field studies in Brazil and Liberia as well as later works by Lave & Wenger (Lave and Wenger, 1991; Chaiklin and Lave, 1993; Wenger, 1998; Wenger, McDermott, R. and W. Snyder, 2002) on situated learning and social...... and scaffolded learning (Wood, Bruner & Ross, 1976; Bruner, 1985; Bruner 1996; Kaye, 1992; Meyer, 1993; Sorensen, 1999) and ?learning in communities of practice? have deeply inspired and to a certain degree become a sort of theoretical and practical framework in Denmark with respect to development of web based...

  16. The Influence of Background Music on Learning in the Light of Different Theoretical Perspectives and the Role of Working Memory Capacity.

    Science.gov (United States)

    Lehmann, Janina A M; Seufert, Tina

    2017-01-01

    This study investigates how background music influences learning with respect to three different theoretical approaches. Both the Mozart effect as well as the arousal-mood-hypothesis indicate that background music can potentially benefit learning outcomes. While the Mozart effect assumes a direct influence of background music on cognitive abilities, the arousal-mood-hypothesis assumes a mediation effect over arousal and mood. However, the seductive detail effect indicates that seductive details such as background music worsen learning. Moreover, as working memory capacity has a crucial influence on learning with seductive details, we also included the learner's working memory capacity as a factor in our study. We tested 81 college students using a between-subject design with half of the sample listening to two pop songs while learning a visual text and the other half learning in silence. We included working memory capacity in the design as a continuous organism variable. Arousal and mood scores before and after learning were collected as potential mediating variables. To measure learning outcomes we tested recall and comprehension. We did not find a mediation effect between background music and arousal or mood on learning outcomes. In addition, for recall performance there were no main effects of background music or working memory capacity, nor an interaction effect of these factors. However, when considering comprehension we did find an interaction between background music and working memory capacity: the higher the learners' working memory capacity, the better they learned with background music. This is in line with the seductive detail assumption.

  17. Comparison of information-theoretic to statistical methods for gene-gene interactions in the presence of genetic heterogeneity

    Directory of Open Access Journals (Sweden)

    Sucheston Lara

    2010-09-01

    Full Text Available Abstract Background Multifactorial diseases such as cancer and cardiovascular diseases are caused by the complex interplay between genes and environment. The detection of these interactions remains challenging due to computational limitations. Information theoretic approaches use computationally efficient directed search strategies and thus provide a feasible solution to this problem. However, the power of information theoretic methods for interaction analysis has not been systematically evaluated. In this work, we compare power and Type I error of an information-theoretic approach to existing interaction analysis methods. Methods The k-way interaction information (KWII metric for identifying variable combinations involved in gene-gene interactions (GGI was assessed using several simulated data sets under models of genetic heterogeneity driven by susceptibility increasing loci with varying allele frequency, penetrance values and heritability. The power and proportion of false positives of the KWII was compared to multifactor dimensionality reduction (MDR, restricted partitioning method (RPM and logistic regression. Results The power of the KWII was considerably greater than MDR on all six simulation models examined. For a given disease prevalence at high values of heritability, the power of both RPM and KWII was greater than 95%. For models with low heritability and/or genetic heterogeneity, the power of the KWII was consistently greater than RPM; the improvements in power for the KWII over RPM ranged from 4.7% to 14.2% at for α = 0.001 in the three models at the lowest heritability values examined. KWII performed similar to logistic regression. Conclusions Information theoretic models are flexible and have excellent power to detect GGI under a variety of conditions that characterize complex diseases.

  18. Development of methods for theoretical analysis of nuclear reactors (Phase II), I-V, Part IV, Fuel depletion

    International Nuclear Information System (INIS)

    Pop-Jordanov, J.

    1962-10-01

    This report includes the analysis of plutonium isotopes from U 238 depletion chain. Two theoretical approaches for solving the depletion of fuel are shown. One results in the system of differential equations that can be solved only by using electronic calculators and the second, Machinari-Goto method enables obtaining analytical equations for approximative values of particular nuclei. In addition, differential equations are given for different approximation levels in calculating Pu 239 , as well as relations between the released energy and irradiation [sr

  19. Information-seeking behavior during residency is associated with quality of theoretical learning, academic career achievements, and evidence-based medical practice: a strobe-compliant article.

    Science.gov (United States)

    Oussalah, Abderrahim; Fournier, Jean-Paul; Guéant, Jean-Louis; Braun, Marc

    2015-02-01

    Data regarding knowledge acquisition during residency training are sparse. Predictors of theoretical learning quality, academic career achievements and evidence-based medical practice during residency are unknown. We performed a cross-sectional study on residents and attending physicians across several residency programs in 2 French faculties of medicine. We comprehensively evaluated the information-seeking behavior (I-SB) during residency using a standardized questionnaire and looked for independent predictors of theoretical learning quality, academic career achievements, and evidence-based medical practice among I-SB components using multivariate logistic regression analysis. Between February 2013 and May 2013, 338 fellows and attending physicians were included in the study. Textbooks and international medical journals were reported to be used on a regular basis by 24% and 57% of the respondents, respectively. Among the respondents, 47% refer systematically (4.4%) or frequently (42.6%) to published guidelines from scientific societies upon their publication. The median self-reported theoretical learning quality score was 5/10 (interquartile range, 3-6; range, 1-10). A high theoretical learning quality score (upper quartile) was independently and strongly associated with the following I-SB components: systematic reading of clinical guidelines upon their publication (odds ratio [OR], 5.55; 95% confidence interval [CI], 1.77-17.44); having access to a library that offers the leading textbooks of the specialty in the medical department (OR, 2.45, 95% CI, 1.33-4.52); knowledge of the specialty leading textbooks (OR, 2.12; 95% CI, 1.09-4.10); and PubMed search skill score ≥5/10 (OR, 1.94; 95% CI, 1.01-3.73). Research Master (M2) and/or PhD thesis enrolment were independently and strongly associated with the following predictors: PubMed search skill score ≥5/10 (OR, 4.10; 95% CI, 1.46-11.53); knowledge of the leading medical journals of the specialty (OR, 3.33; 95

  20. Information-seeking Behavior During Residency Is Associated With Quality of Theoretical Learning, Academic Career Achievements, and Evidence-based Medical Practice

    Science.gov (United States)

    Oussalah, Abderrahim; Fournier, Jean-Paul; Guéant, Jean-Louis; Braun, Marc

    2015-01-01

    Abstract Data regarding knowledge acquisition during residency training are sparse. Predictors of theoretical learning quality, academic career achievements and evidence-based medical practice during residency are unknown. We performed a cross-sectional study on residents and attending physicians across several residency programs in 2 French faculties of medicine. We comprehensively evaluated the information-seeking behavior (I-SB) during residency using a standardized questionnaire and looked for independent predictors of theoretical learning quality, academic career achievements, and evidence-based medical practice among I-SB components using multivariate logistic regression analysis. Between February 2013 and May 2013, 338 fellows and attending physicians were included in the study. Textbooks and international medical journals were reported to be used on a regular basis by 24% and 57% of the respondents, respectively. Among the respondents, 47% refer systematically (4.4%) or frequently (42.6%) to published guidelines from scientific societies upon their publication. The median self-reported theoretical learning quality score was 5/10 (interquartile range, 3–6; range, 1–10). A high theoretical learning quality score (upper quartile) was independently and strongly associated with the following I-SB components: systematic reading of clinical guidelines upon their publication (odds ratio [OR], 5.55; 95% confidence interval [CI], 1.77–17.44); having access to a library that offers the leading textbooks of the specialty in the medical department (OR, 2.45, 95% CI, 1.33–4.52); knowledge of the specialty leading textbooks (OR, 2.12; 95% CI, 1.09–4.10); and PubMed search skill score ≥5/10 (OR, 1.94; 95% CI, 1.01–3.73). Research Master (M2) and/or PhD thesis enrolment were independently and strongly associated with the following predictors: PubMed search skill score ≥5/10 (OR, 4.10; 95% CI, 1.46–11.53); knowledge of the leading medical journals of the

  1. "Mastery Learning" Como Metodo Psicoeducativo para Ninos con Problemas Especificos de Aprendizaje. ("Mastery Learning" as a Psychoeducational Method for Children with Specific Learning Problems.)

    Science.gov (United States)

    Coya, Liliam de Barbosa; Perez-Coffie, Jorge

    1982-01-01

    "Mastery Learning" was compared with the "conventional" method of teaching reading skills to Puerto Rican children with specific learning disabilities. The "Mastery Learning" group showed significant gains in the cognitive and affective domains. Results suggested Mastery Learning is a more effective method of teaching…

  2. A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    JongHyup Lee

    2016-08-01

    Full Text Available For practical deployment of wireless sensor networks (WSN, WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections.

  3. A game-theoretic method for cross-layer stochastic resilient control design in CPS

    Science.gov (United States)

    Shen, Jiajun; Feng, Dongqin

    2018-03-01

    In this paper, the cross-layer security problem of cyber-physical system (CPS) is investigated from the game-theoretic perspective. Physical dynamics of plant is captured by stochastic differential game with cyber-physical influence being considered. The sufficient and necessary condition for the existence of state-feedback equilibrium strategies is given. The attack-defence cyber interactions are formulated by a Stackelberg game intertwined with stochastic differential game in physical layer. The condition such that the Stackelberg equilibrium being unique and the corresponding analytical solutions are both provided. An algorithm is proposed for obtaining hierarchical security strategy by solving coupled games, which ensures the operational normalcy and cyber security of CPS subject to uncertain disturbance and unexpected cyberattacks. Simulation results are given to show the effectiveness and performance of the proposed algorithm.

  4. A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks

    Science.gov (United States)

    Lee, JongHyup; Pak, Dohyun

    2016-01-01

    For practical deployment of wireless sensor networks (WSN), WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections. PMID:27589743

  5. Theoretical treatment of molecular photoionization based on the R-matrix method

    International Nuclear Information System (INIS)

    Tashiro, Motomichi

    2012-01-01

    The R-matrix method was implemented to treat molecular photoionization problem based on the UK R-matrix codes. This method was formulated to treat photoionization process long before, however, its application has been mostly limited to photoionization of atoms. Application of the method to valence photoionization as well as inner-shell photoionization process will be presented.

  6. Designing Of Lectures through Systemic Approach to Teaching and Learning, a Model for (SATL) MethodologyConcepts play a vital role in enabling chemist to deliver. The recently developing concept based teaching methods are likely to play a pivotal role towards the efforts for promoting understanding of chemical concepts and assimilation of vital theoretical foundations of chemistry. A. F. M. Fahmy and J. J. Lagowski are the leading figures in a worldwide derive towards concept building of young generation through this novel mode of teaching and learning. However, their efforts, till recently have been mostly organic chemistry specific. Nevertheless, SALTC teaching methods are equally applicable to various other disciplines in chemistry. SATLC methodology can also be thus used to overcome the problems faced by students in understanding the efficacy of any chemical entity for a specific and desired chemical action. This presentation outlines possible applications of SATLC technique to the concepts related to a number of aspects of Physical Chemistry that are to be put together in one unit for facilitating a chemical compound’s application in any chemical change desired by any researcher.

    OpenAIRE

    *M. Nazir; I. I. Naqvi

    2012-01-01

    Concepts play a vital role in enabling chemist to deliver. The recently developing concept based teaching methods are likely to play a pivotal role towards the efforts for promoting understanding of chemical concepts and assimilation of vital theoretical foundations of chemistry. A. F. M. Fahmy and J. J. Lagowski are the leading figures in a worldwide derive towards concept building of young generation through this novel mode of teaching and learning. However, their efforts, till recently hav...

  7. Electron transfer driven decomposition of adenine and selected analogs as probed by experimental and theoretical methods

    Science.gov (United States)

    Cunha, T.; Mendes, M.; Ferreira da Silva, F.; Eden, S.; García, G.; Bacchus-Montabonel, M.-C.; Limão-Vieira, P.

    2018-04-01

    We report on a combined experimental and theoretical study of electron-transfer-induced decomposition of adenine (Ad) and a selection of analog molecules in collisions with potassium (K) atoms. Time-of-flight negative ion mass spectra have been obtained in a wide collision energy range (6-68 eV in the centre-of-mass frame), providing a comprehensive investigation of the fragmentation patterns of purine (Pu), adenine (Ad), 9-methyl adenine (9-mAd), 6-dimethyl adenine (6-dimAd), and 2-D adenine (2-DAd). Following our recent communication about selective hydrogen loss from the transient negative ions (TNIs) produced in these collisions [T. Cunha et al., J. Chem. Phys. 148, 021101 (2018)], this work focuses on the production of smaller fragment anions. In the low-energy part of the present range, several dissociation channels that are accessible in free electron attachment experiments are absent from the present mass spectra, notably NH2 loss from adenine and 9-methyl adenine. This can be understood in terms of a relatively long transit time of the K+ cation in the vicinity of the TNI tending to enhance the likelihood of intramolecular electron transfer. In this case, the excess energy can be redistributed through the available degrees of freedom inhibiting fragmentation pathways. Ab initio theoretical calculations were performed for 9-methyl adenine (9-mAd) and adenine (Ad) in the presence of a potassium atom and provided a strong basis for the assignment of the lowest unoccupied molecular orbitals accessed in the collision process.

  8. Comparisons and Analyses of Gifted Students' Characteristics and Learning Methods

    Science.gov (United States)

    Lu, Jiamei; Li, Daqi; Stevens, Carla; Ye, Renmin

    2017-01-01

    Using PISA 2009, an international education database, this study compares gifted and talented (GT) students in three groups with normal (non-GT) students by examining student characteristics, reading, schooling, learning methods, and use of strategies for understanding and memorizing. Results indicate that the GT and non-GT gender distributions…

  9. Identification of alternative method of teaching and learning the ...

    African Journals Online (AJOL)

    This study examines alternative method of teaching and learning of the concept of diffusion. An improvised U-shape glass tube called ionic mobility tube was used to observed and measure the rate of movement of divalent metal ions in an aqueous medium in the absence of an electric current. The study revealed that the ...

  10. Kernel Methods for Machine Learning with Life Science Applications

    DEFF Research Database (Denmark)

    Abrahamsen, Trine Julie

    Kernel methods refer to a family of widely used nonlinear algorithms for machine learning tasks like classification, regression, and feature extraction. By exploiting the so-called kernel trick straightforward extensions of classical linear algorithms are enabled as long as the data only appear a...

  11. Research on Language Learning Strategies: Methods, Findings, and Instructional Issues.

    Science.gov (United States)

    Oxford, Rebecca; Crookall, David

    1989-01-01

    Surveys research on formal and informal second-language learning strategies, covering the effectiveness of research methods involving making lists, interviews and thinking aloud, note-taking, diaries, surveys, and training. Suggestions for future and improved research are presented. (131 references) (CB)

  12. Second-Order Learning Methods for a Multilayer Perceptron

    International Nuclear Information System (INIS)

    Ivanov, V.V.; Purehvdorzh, B.; Puzynin, I.V.

    1994-01-01

    First- and second-order learning methods for feed-forward multilayer neural networks are studied. Newton-type and quasi-Newton algorithms are considered and compared with commonly used back-propagation algorithm. It is shown that, although second-order algorithms require enhanced computer facilities, they provide better convergence and simplicity in usage. 13 refs., 2 figs., 2 tabs

  13. Educational integrating projects as a method of interactive learning

    Directory of Open Access Journals (Sweden)

    Иван Николаевич Куринин

    2013-12-01

    Full Text Available The article describes a method of interactive learning based on educational integrating projects. Some examples of content of such projects for the disciplines related to the study of information and Internet technologies and their application in management are presented.

  14. Learning by Designing Interview Methods in Special Education

    DEFF Research Database (Denmark)

    Jönsson, Lise Høgh

    2017-01-01

    , and people with learning disabilities worked together to develop five new visual and digital methods for interviewing in special education. Thereby not only enhancing the students’ competences, knowledge and proficiency in innovation and research, but also proposing a new teaching paradigm for university...

  15. Arabic Supervised Learning Method Using N-Gram

    Science.gov (United States)

    Sanan, Majed; Rammal, Mahmoud; Zreik, Khaldoun

    2008-01-01

    Purpose: Recently, classification of Arabic documents is a real problem for juridical centers. In this case, some of the Lebanese official journal documents are classified, and the center has to classify new documents based on these documents. This paper aims to study and explain the useful application of supervised learning method on Arabic texts…

  16. A Simulator to Enhance Teaching and Learning of Mining Methods ...

    African Journals Online (AJOL)

    Audio visual education that incorporates devices and materials which involve sight, sound, or both has become a sine qua non in recent times in the teaching and learning process. An automated physical model of mining methods aided with video instructions was designed and constructed by harnessing locally available ...

  17. The Keyimage Method of Learning Sound-Symbol Correspondences: A Case Study of Learning Written Khmer

    Directory of Open Access Journals (Sweden)

    Elizabeth Lavolette

    2009-01-01

    Full Text Available I documented my strategies for learning sound-symbol correspondences during a Khmer course. I used a mnemonic strategy that I call the keyimage method. In this method, a character evokes an image (the keyimage, which evokes the corresponding sound. For example, the keyimage for the character 2 could be a swan with its head tucked in. This evokes the sound "kaw" that a swan makes, which sounds similar to the Khmer sound corresponding to 2. The method has some similarities to the keyword method. Considering the results of keyword studies, I hypothesize that the keyimage method is more effective than rote learning and that peer-generated keyimages are more effective than researcher- or teacher-generated keyimages, which are more effective than learner-generated ones. In Dr. Andrew Cohen's plenary presentation at the Hawaii TESOL 2007 conference, he mentioned that more case studies are needed on learning strategies (LSs. One reason to study LSs is that what learners do with input to produce output is unclear, and knowing what strategies learners use may help us understand that process (Dornyei, 2005, p. 170. Hopefully, we can use that knowledge to improve language learning, perhaps by teaching learners to use the strategies that we find. With that in mind, I have examined the LSs that I used in studying Khmer as a foreign language, focusing on learning the syllabic alphabet.

  18. A Fast Optimization Method for General Binary Code Learning.

    Science.gov (United States)

    Shen, Fumin; Zhou, Xiang; Yang, Yang; Song, Jingkuan; Shen, Heng; Tao, Dacheng

    2016-09-22

    Hashing or binary code learning has been recognized to accomplish efficient near neighbor search, and has thus attracted broad interests in recent retrieval, vision and learning studies. One main challenge of learning to hash arises from the involvement of discrete variables in binary code optimization. While the widely-used continuous relaxation may achieve high learning efficiency, the pursued codes are typically less effective due to accumulated quantization error. In this work, we propose a novel binary code optimization method, dubbed Discrete Proximal Linearized Minimization (DPLM), which directly handles the discrete constraints during the learning process. Specifically, the discrete (thus nonsmooth nonconvex) problem is reformulated as minimizing the sum of a smooth loss term with a nonsmooth indicator function. The obtained problem is then efficiently solved by an iterative procedure with each iteration admitting an analytical discrete solution, which is thus shown to converge very fast. In addition, the proposed method supports a large family of empirical loss functions, which is particularly instantiated in this work by both a supervised and an unsupervised hashing losses, together with the bits uncorrelation and balance constraints. In particular, the proposed DPLM with a supervised `2 loss encodes the whole NUS-WIDE database into 64-bit binary codes within 10 seconds on a standard desktop computer. The proposed approach is extensively evaluated on several large-scale datasets and the generated binary codes are shown to achieve very promising results on both retrieval and classification tasks.

  19. Method to predict process signals to learn for SVM

    International Nuclear Information System (INIS)

    Minowa, Hirotsugu; Gofuku, Akio

    2013-01-01

    Study of diagnostic system using machine learning to reduce the incidents of the plant is in advance because an accident causes large damage about human, economic and social loss. There is a problem that 2 performances between a classification performance and generalization performance on the machine diagnostic machine is exclusive. However, multi agent diagnostic system makes it possible to use a diagnostic machine specialized either performance by multi diagnostic machines can be used. We propose method to select optimized variables to improve classification performance. The method can also be used for other supervised learning machine but Support Vector Machine. This paper reports that our method and result of evaluation experiment applied our method to output 40% of Monju. (author)

  20. Studying depression using imaging and machine learning methods

    OpenAIRE

    Patel, Meenal J.; Khalaf, Alexander; Aizenstein, Howard J.

    2015-01-01

    Depression is a complex clinical entity that can pose challenges for clinicians regarding both accurate diagnosis and effective timely treatment. These challenges have prompted the development of multiple machine learning methods to help improve the management of this disease. These methods utilize anatomical and physiological data acquired from neuroimaging to create models that can identify depressed patients vs. non-depressed patients and predict treatment outcomes. This article (1) presen...

  1. E-learning as new method of medical education.

    Science.gov (United States)

    Masic, Izet

    2008-01-01

    NONE DECLARED Distance learning refers to use of technologies based on health care delivered on distance and covers areas such as electronic health, tele-health (e-health), telematics, telemedicine, tele-education, etc. For the need of e-health, telemedicine, tele-education and distance learning there are various technologies and communication systems from standard telephone lines to the system of transmission digitalized signals with modem, optical fiber, satellite links, wireless technologies, etc. Tele-education represents health education on distance, using Information Communication Technologies (ICT), as well as continuous education of a health system beneficiaries and use of electronic libraries, data bases or electronic data with data bases of knowledge. Distance learning (E-learning) as a part of tele-education has gained popularity in the past decade; however, its use is highly variable among medical schools and appears to be more common in basic medical science courses than in clinical education. Distance learning does not preclude traditional learning processes; frequently it is used in conjunction with in-person classroom or professional training procedures and practices. Tele-education has mostly been used in biomedical education as a blended learning method, which combines tele-education technology with traditional instructor-led training, where, for example, a lecture or demonstration is supplemented by an online tutorial. Distance learning is used for self-education, tests, services and for examinations in medicine i.e. in terms of self-education and individual examination services. The possibility of working in the exercise mode with image files and questions is an attractive way of self education. Automated tracking and reporting of learners' activities lessen faculty administrative burden. Moreover, e-learning can be designed to include outcomes assessment to determine whether learning has occurred. This review article evaluates the current

  2. Frank Gilbreth and health care delivery method study driven learning.

    Science.gov (United States)

    Towill, Denis R

    2009-01-01

    The purpose of this article is to look at method study, as devised by the Gilbreths at the beginning of the twentieth century, which found early application in hospital quality assurance and surgical "best practice". It has since become a core activity in all modern methods, as applied to healthcare delivery improvement programmes. The article traces the origin of what is now currently and variously called "business process re-engineering", "business process improvement" and "lean healthcare" etc., by different management gurus back to the century-old pioneering work of Frank Gilbreth. The outcome is a consistent framework involving "width", "length" and "depth" dimensions within which healthcare delivery systems can be analysed, designed and successfully implemented to achieve better and more consistent performance. Healthcare method (saving time plus saving motion) study is best practised as co-joint action learning activity "owned" by all "players" involved in the re-engineering process. However, although process mapping is a key step forward, in itself it is no guarantee of effective re-engineering. It is not even the beginning of the end of the change challenge, although it should be the end of the beginning. What is needed is innovative exploitation of method study within a healthcare organisational learning culture accelerated via the Gilbreth Knowledge Flywheel. It is shown that effective healthcare delivery pipeline improvement is anchored into a team approach involving all "players" in the system especially physicians. A comprehensive process study, constructive dialogue, proper and highly professional re-engineering plus managed implementation are essential components. Experience suggests "learning" is thereby achieved via "natural groups" actively involved in healthcare processes. The article provides a proven method for exploiting Gilbreths' outputs and their many successors in enabling more productive evidence-based healthcare delivery as summarised

  3. Non-Gaussian Methods for Causal Structure Learning.

    Science.gov (United States)

    Shimizu, Shohei

    2018-05-22

    Causal structure learning is one of the most exciting new topics in the fields of machine learning and statistics. In many empirical sciences including prevention science, the causal mechanisms underlying various phenomena need to be studied. Nevertheless, in many cases, classical methods for causal structure learning are not capable of estimating the causal structure of variables. This is because it explicitly or implicitly assumes Gaussianity of data and typically utilizes only the covariance structure. In many applications, however, non-Gaussian data are often obtained, which means that more information may be contained in the data distribution than the covariance matrix is capable of containing. Thus, many new methods have recently been proposed for using the non-Gaussian structure of data and inferring the causal structure of variables. This paper introduces prevention scientists to such causal structure learning methods, particularly those based on the linear, non-Gaussian, acyclic model known as LiNGAM. These non-Gaussian data analysis tools can fully estimate the underlying causal structures of variables under assumptions even in the presence of unobserved common causes. This feature is in contrast to other approaches. A simulated example is also provided.

  4. Theoretical study of electron transfer mechanism in biological systems with a QM (MRSCI+DFT)/MM method

    Energy Technology Data Exchange (ETDEWEB)

    Takada, Toshikazu [Research Program for Computational Science, RIKEN 2-1, Hirosawa, Wako, Saitama 351-0198 (Japan)

    2007-07-15

    The goal of this project is to understand the charge separation mechanisms in biological systems using the molecular orbital theories. Specially, the charge separation in the photosynthetic reaction center is focused on, since the efficiency in use of the solar energy is extraordinary and the reason for it is still kept unknown. Here, a QM/MM theoretical scheme is employed to take the effects of the surrounding proteins onto the pigments into account. To describe such excited electronic structures, a unified theory by MRSCI and DFT is newly invented. For atoms in the MM space, a new sampling method has also been created, based on the statistical physics. By using these theoretical framework, the excited and positively charged states of the special pair, that is, chlorophyll dimmer are planning to be calculated this year.

  5. Theoretical study of electron transfer mechanism in biological systems with a QM (MRSCI+DFT)/MM method

    International Nuclear Information System (INIS)

    Takada, Toshikazu

    2007-01-01

    The goal of this project is to understand the charge separation mechanisms in biological systems using the molecular orbital theories. Specially, the charge separation in the photosynthetic reaction center is focused on, since the efficiency in use of the solar energy is extraordinary and the reason for it is still kept unknown. Here, a QM/MM theoretical scheme is employed to take the effects of the surrounding proteins onto the pigments into account. To describe such excited electronic structures, a unified theory by MRSCI and DFT is newly invented. For atoms in the MM space, a new sampling method has also been created, based on the statistical physics. By using these theoretical framework, the excited and positively charged states of the special pair, that is, chlorophyll dimmer are planning to be calculated this year

  6. Unified Theoretical Frame of a Joint Transmitter-Receiver Reduced Dimensional STAP Method for an Airborne MIMO Radar

    Directory of Open Access Journals (Sweden)

    Guo Yiduo

    2016-10-01

    Full Text Available The unified theoretical frame of a joint transmitter-receiver reduced dimensional Space-Time Adaptive Processing (STAP method is studied for an airborne Multiple-Input Multiple-Output (MIMO radar. First, based on the transmitted waveform diverse characteristics of the transmitted waveform of the airborne MIMO radar, a uniform theoretical frame structure for the reduced dimensional joint adaptive STAP is constructed. Based on it, three reduced dimensional STAP fixed structures are established. Finally, three reduced rank STAP algorithms, which are suitable for a MIMO system, are presented corresponding to the three reduced dimensional STAP fixed structures. The simulations indicate that the joint adaptive algorithms have preferable clutter suppression and anti-interference performance.

  7. Does Macaulay Duration Provide The Most Cost-Effective Immunization Method – A Theoretical Approach

    Directory of Open Access Journals (Sweden)

    Zaremba Leszek

    2017-02-01

    Full Text Available In the following, we offer a theoretical approach that attempts to explain (Comments 1-3 why and when the Macaulay duration concept happens to be a good approximation of a bond’s price sensitivity. We are concerned with the basic immunization problem with a single liability to be discharged at a future time q. Our idea is to divide the class K of all shifts a(t of a term structure of interest rates s(t into many classes and then to find a sufficient and necessary condition a given bond portfolio, dependent on a class of shifts, must satisfy to secure immunization at time q against all shifts a(t from that class. For this purpose, we introduce the notions of dedicated duration and dedicated convexity. For each class of shifts, we show how to choose from a bond market under consideration a portfolio with maximal dedicated convexity among all immunizing portfolios. We demonstrate that the portfolio yields the maximal unanticipated rate of return and appears to be uniquely determined as a barbell strategy (portfolio built up with 2 zero-coupon bearing bonds with maximal and respective minimal dedicated durations. Finally, an open problem addressed to researchers performing empirical studies is formulated.

  8. Quantitative fluorescence lifetime spectroscopy in turbid media: comparison of theoretical, experimental and computational methods

    International Nuclear Information System (INIS)

    Vishwanath, Karthik; Mycek, Mary-Ann; Pogue, Brian

    2002-01-01

    A Monte Carlo model developed to simulate time-resolved fluorescence propagation in a semi-infinite turbid medium was validated against previously reported theoretical and computational results. Model simulations were compared to experimental measurements of fluorescence spectra and lifetimes on tissue-simulating phantoms for single and dual fibre-optic probe geometries. Experiments and simulations using a single probe revealed that scattering-induced artefacts appeared in fluorescence emission spectra, while fluorescence lifetimes were unchanged. Although fluorescence lifetime measurements are generally more robust to scattering artefacts than are measurements of fluorescence spectra, in the dual-probe geometry scattering-induced changes in apparent lifetime were predicted both from diffusion theory and via Monte Carlo simulation, as well as measured experimentally. In all cases, the recovered apparent lifetime increased with increasing scattering and increasing source-detector separation. Diffusion theory consistently underestimated the magnitude of these increases in apparent lifetime (predicting a maximum increase of ∼15%), while Monte Carlo simulations and experiment were closely matched (showing increases as large as 30%). These results indicate that quantitative simulations of time-resolved fluorescence propagation in turbid media will be important for accurate recovery of fluorophore lifetimes in biological spectroscopy and imaging applications. (author)

  9. Illumination of interior spaces by bended hollow light guides: Application of the theoretical light propagation method

    Energy Technology Data Exchange (ETDEWEB)

    Darula, Stanislav; Kocifaj, Miroslav; Kittler, Richard [ICA, Slovak Academy of Sciences, Bratislava (Slovakia); Kundracik, Frantisek [Department of Experimental Physics, FMPI, Comenius University, Bratislava (Slovakia)

    2010-12-15

    To ensure comfort and healthy conditions in interior spaces the thermal, acoustics and daylight factors of the environment have to be considered in the building design. Due to effective energy performance in buildings the new technology and applications also in daylight engineering are sought such as tubular light guides. These allow the transport of natural light into the building core reducing energy consumption. A lot of installations with various geometrical and optical properties can be applied in real buildings. The simplest set of tubular light guide consists of a transparent cupola, direct tube with high reflected inner surface and a ceiling cover or diffuser redistributing light into the interior. Such vertical tubular guide is often used on flat roofs. When the roof construction is inclined a bend in the light guide system has to be installed. In this case the cupola is set on the sloped roof which collects sunlight and skylight from the seen part of the sky hemisphere as well as that reflected from the ground and opposite facades. In comparison with the vertical tube some additional light losses and distortions of the propagated light have to be expected in bended tubular light guides. Recently the theoretical model of light propagation was already published and its applications are presented in this study solving illuminance distributions on the ceiling cover interface and further illuminance distribution on the working plane in the interior. (author)

  10. Theoretical Study of Palladium Membrane Reactor Performance During Propane Dehydrogenation Using CFD Method

    Directory of Open Access Journals (Sweden)

    Kamran Ghasemzadeh

    2017-04-01

    Full Text Available This study presents a 2D-axisymmetric computational fluid dynamic (CFD model to investigate the performance Pd membrane reactor (MR during propane dehydrogenation process for hydrogen production. The proposed CFD model provided the local information of temperature and component concentration for the driving force analysis. After investigation of mesh independency of CFD model, the validation of CFD model results was carried out by other modeling data and a good agreement between CFD model results and theoretical data was achieved. Indeed, in the present model, a tubular reactor with length of 150 mm was considered, in which the Pt-Sn-K/Al2O3 as catalyst were filled in reaction zone. Hence, the effects of the important operating parameter (reaction temperature on the performances of membrane reactor (MR were studied in terms of propane conversion and hydrogen yield. The CFD results showed that the suggested MR system during propane dehydrogenation reaction presents higher performance with respect to once obtained in the conventional reactor (CR. In particular, by applying Pd membrane, was found that propane conversion can be increased from 41% to 49%. Moreover, the highest value of propane conversion (X = 91% was reached in case of Pd-Ag MR. It was also established that the feed flow rate of the MR is to be the one of the most important factors defining efficiency of the propane dehydrogenation process.

  11. Theoretical investigation of dielectric corona pre-ionization TEA nitrogen laser based on transmission line method

    Science.gov (United States)

    Bahrampour, Alireza; Fallah, Robabeh; Ganjovi, Alireza A.; Bahrampour, Abolfazl

    2007-07-01

    This paper models the dielectric corona pre-ionization, capacitor transfer type of flat-plane transmission line traveling wave transverse excited atmospheric pressure nitrogen laser by a non-linear lumped RLC electric circuit. The flat-plane transmission line and the pre-ionizer dielectric are modeled by a lumped linear RLC and time-dependent non-linear RC circuit, respectively. The main discharge region is considered as a time-dependent non-linear RLC circuit where its resistance value is also depends on the radiated pre-ionization ultra violet (UV) intensity. The UV radiation is radiated by the resistance due to the surface plasma on the pre-ionizer dielectric. The theoretical predictions are in a very good agreement with the experimental observations. The electric circuit equations (including the ionization rate equations), the equations of laser levels population densities and propagation equation of laser intensities, are solved numerically. As a result, the effects of pre-ionizer dielectric parameters on the electrical behavior and output laser intensity are obtained.

  12. Aggregative Learning Method and Its Application for Communication Quality Evaluation

    Science.gov (United States)

    Akhmetov, Dauren F.; Kotaki, Minoru

    2007-12-01

    In this paper, so-called Aggregative Learning Method (ALM) is proposed to improve and simplify the learning and classification abilities of different data processing systems. It provides a universal basis for design and analysis of mathematical models of wide class. A procedure was elaborated for time series model reconstruction and analysis for linear and nonlinear cases. Data approximation accuracy (during learning phase) and data classification quality (during recall phase) are estimated from introduced statistic parameters. The validity and efficiency of the proposed approach have been demonstrated through its application for monitoring of wireless communication quality, namely, for Fixed Wireless Access (FWA) system. Low memory and computation resources were shown to be needed for the procedure realization, especially for data classification (recall) stage. Characterized with high computational efficiency and simple decision making procedure, the derived approaches can be useful for simple and reliable real-time surveillance and control system design.

  13. Learning and retention of quantum concepts with different teaching methods

    Science.gov (United States)

    Deslauriers, Louis; Wieman, Carl

    2011-06-01

    We measured mastery and retention of conceptual understanding of quantum mechanics in a modern physics course. This was studied for two equivalent cohorts of students taught with different pedagogical approaches using the Quantum Mechanics Conceptual Survey. We measured the impact of pedagogical approach both on the original conceptual learning and on long-term retention. The cohort of students who had a very highly rated traditional lecturer scored 19% lower than the equivalent cohort that was taught using interactive engagement methods. However, the amount of retention was very high for both cohorts, showing only a few percent decrease in scores when retested 6 and 18 months after completion of the course and with no exposure to the material in the interim period. This high level of retention is in striking contrast to the retention measured for more factual learning from university courses and argues for the value of emphasizing conceptual learning.

  14. Sunspot drawings handwritten character recognition method based on deep learning

    Science.gov (United States)

    Zheng, Sheng; Zeng, Xiangyun; Lin, Ganghua; Zhao, Cui; Feng, Yongli; Tao, Jinping; Zhu, Daoyuan; Xiong, Li

    2016-05-01

    High accuracy scanned sunspot drawings handwritten characters recognition is an issue of critical importance to analyze sunspots movement and store them in the database. This paper presents a robust deep learning method for scanned sunspot drawings handwritten characters recognition. The convolution neural network (CNN) is one algorithm of deep learning which is truly successful in training of multi-layer network structure. CNN is used to train recognition model of handwritten character images which are extracted from the original sunspot drawings. We demonstrate the advantages of the proposed method on sunspot drawings provided by Chinese Academy Yunnan Observatory and obtain the daily full-disc sunspot numbers and sunspot areas from the sunspot drawings. The experimental results show that the proposed method achieves a high recognition accurate rate.

  15. A diagram retrieval method with multi-label learning

    Science.gov (United States)

    Fu, Songping; Lu, Xiaoqing; Liu, Lu; Qu, Jingwei; Tang, Zhi

    2015-01-01

    In recent years, the retrieval of plane geometry figures (PGFs) has attracted increasing attention in the fields of mathematics education and computer science. However, the high cost of matching complex PGF features leads to the low efficiency of most retrieval systems. This paper proposes an indirect classification method based on multi-label learning, which improves retrieval efficiency by reducing the scope of compare operation from the whole database to small candidate groups. Label correlations among PGFs are taken into account for the multi-label classification task. The primitive feature selection for multi-label learning and the feature description of visual geometric elements are conducted individually to match similar PGFs. The experiment results show the competitive performance of the proposed method compared with existing PGF retrieval methods in terms of both time consumption and retrieval quality.

  16. Learning Method and Its Influence on Nutrition Study Results Throwing the Ball

    Science.gov (United States)

    Samsudin; Nugraha, Bayu

    2015-01-01

    This study aimed to know the difference between playing and learning methods of exploratory learning methods to learning outcomes throwing the ball. In addition, this study also aimed to determine the effect of nutritional status of these two learning methods mentioned above. This research was conducted at SDN Cipinang Besar Selatan 16 Pagi East…

  17. Advanced Steel Microstructural Classification by Deep Learning Methods.

    Science.gov (United States)

    Azimi, Seyed Majid; Britz, Dominik; Engstler, Michael; Fritz, Mario; Mücklich, Frank

    2018-02-01

    The inner structure of a material is called microstructure. It stores the genesis of a material and determines all its physical and chemical properties. While microstructural characterization is widely spread and well known, the microstructural classification is mostly done manually by human experts, which gives rise to uncertainties due to subjectivity. Since the microstructure could be a combination of different phases or constituents with complex substructures its automatic classification is very challenging and only a few prior studies exist. Prior works focused on designed and engineered features by experts and classified microstructures separately from the feature extraction step. Recently, Deep Learning methods have shown strong performance in vision applications by learning the features from data together with the classification step. In this work, we propose a Deep Learning method for microstructural classification in the examples of certain microstructural constituents of low carbon steel. This novel method employs pixel-wise segmentation via Fully Convolutional Neural Network (FCNN) accompanied by a max-voting scheme. Our system achieves 93.94% classification accuracy, drastically outperforming the state-of-the-art method of 48.89% accuracy. Beyond the strong performance of our method, this line of research offers a more robust and first of all objective way for the difficult task of steel quality appreciation.

  18. Hybrid Method for Mobile learning Cooperative: Study of Timor Leste

    Science.gov (United States)

    da Costa Tavares, Ofelia Cizela; Suyoto; Pranowo

    2018-02-01

    In the modern world today the decision support system is very useful to help in solving a problem, so this study discusses the learning process of savings and loan cooperatives in Timor Leste. The purpose of the observation is that the people of Timor Leste are still in the process of learning the use DSS for good saving and loan cooperative process. Based on existing research on the Timor Leste community on credit cooperatives, a mobile application will be built that will help the cooperative learning process in East Timorese society. The methods used for decision making are AHP (Analytical Hierarchy Process) and SAW (simple additive Weighting) method to see the result of each criterion and the weight of the value. The result of this research is mobile leaning cooperative in decision support system by using SAW and AHP method. Originality Value: Changed the two methods of mobile application development using AHP and SAW methods to help the decision support system process of a savings and credit cooperative in Timor Leste.

  19. Hybrid Method for Mobile learning Cooperative: Study of Timor Leste

    Directory of Open Access Journals (Sweden)

    da Costa Tavares Ofelia Cizela

    2018-01-01

    Full Text Available In the modern world today the decision support system is very useful to help in solving a problem, so this study discusses the learning process of savings and loan cooperatives in Timor Leste. The purpose of the observation is that the people of Timor Leste are still in the process of learning the use DSS for good saving and loan cooperative process. Based on existing research on the Timor Leste community on credit cooperatives, a mobile application will be built that will help the cooperative learning process in East Timorese society. The methods used for decision making are AHP (Analytical Hierarchy Process and SAW (simple additive Weighting method to see the result of each criterion and the weight of the value. The result of this research is mobile leaning cooperative in decision support system by using SAW and AHP method. Originality Value: Changed the two methods of mobile application development using AHP and SAW methods to help the decision support system process of a savings and credit cooperative in Timor Leste.

  20. Theoretical study on new bias factor methods to effectively use critical experiments for improvement of prediction accuracy of neutronic characteristics

    International Nuclear Information System (INIS)

    Kugo, Teruhiko; Mori, Takamasa; Takeda, Toshikazu

    2007-01-01

    Extended bias factor methods are proposed with two new concepts, the LC method and the PE method, in order to effectively use critical experiments and to enhance the applicability of the bias factor method for the improvement of the prediction accuracy of neutronic characteristics of a target core. Both methods utilize a number of critical experimental results and produce a semifictitious experimental value with them. The LC and PE methods define the semifictitious experimental values by a linear combination of experimental values and the product of exponentiated experimental values, respectively, and the corresponding semifictitious calculation values by those of calculation values. A bias factor is defined by the ratio of the semifictitious experimental value to the semifictitious calculation value in both methods. We formulate how to determine weights for the LC method and exponents for the PE method in order to minimize the variance of the design prediction value obtained by multiplying the design calculation value by the bias factor. From a theoretical comparison of these new methods with the conventional method which utilizes a single experimental result and the generalized bias factor method which was previously proposed to utilize a number of experimental results, it is concluded that the PE method is the most useful method for improving the prediction accuracy. The main advantages of the PE method are summarized as follows. The prediction accuracy is necessarily improved compared with the design calculation value even when experimental results include large experimental errors. This is a special feature that the other methods do not have. The prediction accuracy is most effectively improved by utilizing all the experimental results. From these facts, it can be said that the PE method effectively utilizes all the experimental results and has a possibility to make a full-scale-mockup experiment unnecessary with the use of existing and future benchmark

  1. Machine learning methods without tears: a primer for ecologists.

    Science.gov (United States)

    Olden, Julian D; Lawler, Joshua J; Poff, N LeRoy

    2008-06-01

    Machine learning methods, a family of statistical techniques with origins in the field of artificial intelligence, are recognized as holding great promise for the advancement of understanding and prediction about ecological phenomena. These modeling techniques are flexible enough to handle complex problems with multiple interacting elements and typically outcompete traditional approaches (e.g., generalized linear models), making them ideal for modeling ecological systems. Despite their inherent advantages, a review of the literature reveals only a modest use of these approaches in ecology as compared to other disciplines. One potential explanation for this lack of interest is that machine learning techniques do not fall neatly into the class of statistical modeling approaches with which most ecologists are familiar. In this paper, we provide an introduction to three machine learning approaches that can be broadly used by ecologists: classification and regression trees, artificial neural networks, and evolutionary computation. For each approach, we provide a brief background to the methodology, give examples of its application in ecology, describe model development and implementation, discuss strengths and weaknesses, explore the availability of statistical software, and provide an illustrative example. Although the ecological application of machine learning approaches has increased, there remains considerable skepticism with respect to the role of these techniques in ecology. Our review encourages a greater understanding of machin learning approaches and promotes their future application and utilization, while also providing a basis from which ecologists can make informed decisions about whether to select or avoid these approaches in their future modeling endeavors.

  2. Theoretical study of the F2 molecule using the variational cellular method

    International Nuclear Information System (INIS)

    Lima, M.A.P.; Leite, J.R.; Fazzio, A.

    1981-02-01

    Variational Cellular Method calculations for F 2 have been carried out at several internuclear distances. The ground and excited state potential curves are presented. The overall agreement between the VCM results and ab initio calculations is fairly good. (Author) [pt

  3. Performance analysis of demodulation with diversity -- A combinatorial approach I: Symmetric function theoretical methods

    Directory of Open Access Journals (Sweden)

    Jean-Louis Dornstetter

    2002-12-01

    Full Text Available This paper is devoted to the presentation of a combinatorial approach, based on the theory of symmetric functions, for analyzing the performance of a family of demodulation methods used in mobile telecommunications.

  4. Performance analysis of demodulation with diversity -- A combinatorial approach I: Symmetric function theoretical methods

    OpenAIRE

    Jean-Louis Dornstetter; Daniel Krob; Jean-Yves Thibon; Ekaterina A. Vassilieva

    2002-01-01

    This paper is devoted to the presentation of a combinatorial approach, based on the theory of symmetric functions, for analyzing the performance of a family of demodulation methods used in mobile telecommunications.

  5. The design and testing of a caring teaching model based on the theoretical framework of caring in the Chinese Context: a mixed-method study.

    Science.gov (United States)

    Guo, Yujie; Shen, Jie; Ye, Xuchun; Chen, Huali; Jiang, Anli

    2013-08-01

    This paper aims to report the design and test the effectiveness of an innovative caring teaching model based on the theoretical framework of caring in the Chinese context. Since the 1970's, caring has been a core value in nursing education. In a previous study, a theoretical framework of caring in the Chinese context is explored employing a grounded theory study, considered beneficial for caring education. A caring teaching model was designed theoretically and a one group pre- and post-test quasi-experimental study was administered to test its effectiveness. From Oct, 2009 to Jul, 2010, a cohort of grade-2 undergraduate nursing students (n=64) in a Chinese medical school was recruited to participate in the study. Data were gathered through quantitative and qualitative methods to evaluate the effectiveness of the caring teaching model. The caring teaching model created an esthetic situation and experiential learning style for teaching caring that was integrated within the curricula. Quantitative data from the quasi-experimental study showed that the post-test scores of each item were higher than those on the pre-test (p<0.01). Thematic analysis of 1220 narratives from students' caring journals and reports of participant class observation revealed two main thematic categories, which reflected, from the students' points of view, the development of student caring character and the impact that the caring teaching model had on this regard. The model could be used as an integrated approach to teach caring in nursing curricula. It would also be beneficial for nursing administrators in cultivating caring nurse practitioners. Copyright © 2012 Elsevier Ltd. All rights reserved.

  6. Theoretical study of fiber Raman amplifiers by broadband pumps through moment method

    International Nuclear Information System (INIS)

    Teimorpour, M. H.; Pourmoghadas, A.; Rahimi, L.; Farman, F.; Bahrampour, A.

    2007-01-01

    The governing equations of Raman optical fiber amplifier with broadband pumps in the steady state are a system of Uncountable Nonlinear Ordinary Differential Equations. In this paper, the Moment Method is used to reduce the uncountable system of Nonlinear Ordinary Differential Equations to a system of finite number of Nonlinear Ordinary Differential Equations. This system of equations is solved numerically. It is shown that the Moment Method is a precise and fast technique for analysis of optical fiber Raman Amplifier with broadband pumps.

  7. Constructing the principles: Method and metaphysics in the progress of theoretical physics

    Science.gov (United States)

    Glass, Lawrence C.

    This thesis presents a new framework for the philosophy of physics focused on methodological differences found in the practice of modern theoretical physics. The starting point for this investigation is the longstanding debate over scientific realism. Some philosophers have argued that it is the aim of science to produce an accurate description of the world including explanations for observable phenomena. These scientific realists hold that our best confirmed theories are approximately true and that the entities they propose actually populate the world, whether or not they have been observed. Others have argued that science achieves only frameworks for the prediction and manipulation of observable phenomena. These anti-realists argue that truth is a misleading concept when applied to empirical knowledge. Instead, focus should be on the empirical adequacy of scientific theories. This thesis argues that the fundamental distinction at issue, a division between true scientific theories and ones which are empirically adequate, is best explored in terms of methodological differences. In analogy with the realism debate, there are at least two methodological strategies. Rather than focusing on scientific theories as wholes, this thesis takes as units of analysis physical principles which are systematic empirical generalizations. The first possible strategy, the conservative, takes the assumption that the empirical adequacy of a theory in one domain serves as good evidence for such adequacy in other domains. This then motivates the application of the principle to new domains. The second strategy, the innovative, assumes that empirical adequacy in one domain does not justify the expectation of adequacy in other domains. New principles are offered as explanations in the new domain. The final part of the thesis is the application of this framework to two examples. On the first, Lorentz's use of the aether is reconstructed in terms of the conservative strategy with respect to

  8. Theoretical Proof and Empirical Confirmation of a Continuous Labeling Method Using Naturally 13C-Depleted Carbon Dioxide

    Institute of Scientific and Technical Information of China (English)

    Weixin Cheng; Feike A. Dijkstra

    2007-01-01

    Continuous isotope labeling and tracing is often needed to study the transformation, movement, and allocation of carbon in plant-soil systems. However, existing labeling methods have numerous limitations. The present study introduces a new continuous labeling method using naturally 13C-depleted CO2. We theoretically proved that a stable level of 13C-CO2 abundance In a labeling chamber can be maintained by controlling the rate of CO2-free air injection and the rate of ambient airflow with coupling of automatic control of CO2 concentration using a CO2 analyzer. The theoretical results were tested and confirmed in a 54 day experiment in a plant growth chamber. This new continuous labeling method avoids the use of radioactive 14C or expensive 13C-enriched CO2 required by existing methods and therefore eliminates issues of radiation safety or unaffordable isotope cost, as well as creating new opportunities for short- or long-term labeling experiments under a controlled environment.

  9. Probability estimation with machine learning methods for dichotomous and multicategory outcome: theory.

    Science.gov (United States)

    Kruppa, Jochen; Liu, Yufeng; Biau, Gérard; Kohler, Michael; König, Inke R; Malley, James D; Ziegler, Andreas

    2014-07-01

    Probability estimation for binary and multicategory outcome using logistic and multinomial logistic regression has a long-standing tradition in biostatistics. However, biases may occur if the model is misspecified. In contrast, outcome probabilities for individuals can be estimated consistently with machine learning approaches, including k-nearest neighbors (k-NN), bagged nearest neighbors (b-NN), random forests (RF), and support vector machines (SVM). Because machine learning methods are rarely used by applied biostatisticians, the primary goal of this paper is to explain the concept of probability estimation with these methods and to summarize recent theoretical findings. Probability estimation in k-NN, b-NN, and RF can be embedded into the class of nonparametric regression learning machines; therefore, we start with the construction of nonparametric regression estimates and review results on consistency and rates of convergence. In SVMs, outcome probabilities for individuals are estimated consistently by repeatedly solving classification problems. For SVMs we review classification problem and then dichotomous probability estimation. Next we extend the algorithms for estimating probabilities using k-NN, b-NN, and RF to multicategory outcomes and discuss approaches for the multicategory probability estimation problem using SVM. In simulation studies for dichotomous and multicategory dependent variables we demonstrate the general validity of the machine learning methods and compare it with logistic regression. However, each method fails in at least one simulation scenario. We conclude with a discussion of the failures and give recommendations for selecting and tuning the methods. Applications to real data and example code are provided in a companion article (doi:10.1002/bimj.201300077). © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Stroke Health and Risk Education (SHARE): design, methods, and theoretical basis.

    Science.gov (United States)

    Brown, Devin L; Conley, Kathleen M; Resnicow, Kenneth; Murphy, Jillian; Sánchez, Brisa N; Cowdery, Joan E; Sais, Emma; Lisabeth, Lynda D; Skolarus, Lesli E; Zahuranec, Darin B; Williams, Geoffrey C; Morgenstern, Lewis B

    2012-07-01

    Stroke is a disease with tremendous individual, family, and societal impact across all race/ethnic groups. Mexican Americans, the largest subgroup of Hispanic Americans, are at even higher risk of stroke than European Americans. To test the effectiveness of a culturally sensitive, church-based, multi-component, motivational enhancement intervention for Mexican Americans and European Americans in reducing stroke risk factors. Participants enroll in family or friendship pairs, from the same Catholic church in the Corpus Christi Texas area, and are encouraged to change diet and physical activity behaviors and provide support for behavior change to their partners. Churches are randomized to either the intervention or control group. Goal enrollment for each of the 10 participating churches is 40 participant pairs. The intervention consists of self-help materials (including a motivational short film, cookbook/healthy eating guide, physical activity guide with pedometer, and photonovella), five motivational interviewing calls, two tailored newsletters, parish health promotion activities and environmental changes, and a peer support workshop where participants learn to provide autonomy supportive counseling to their partner. SHARE's three primary outcomes are self-reported sodium intake, fruit and vegetable intake, and level of physical activity. Participants complete questionnaires and have measurements at baseline, six months, and twelve months. Persistence testing is performed at 18 months in the intervention group. The trial is registered with clinicaltrials.gov (NCT01378780). Copyright © 2012 Elsevier Inc. All rights reserved.

  11. The Effect of Using Cooperative Learning Method on Tenth Grade Students' Learning Achievement and Attitude towards Biology

    Science.gov (United States)

    Rabgay, Tshewang

    2018-01-01

    The study investigated the effect of using cooperative learning method on tenth grade students' learning achievement in biology and their attitude towards the subject in a Higher Secondary School in Bhutan. The study used a mixed method approach. The quantitative component included an experimental design where cooperative learning was the…

  12. Introduction of active learning method in learning physiology by MBBS students.

    Science.gov (United States)

    Gilkar, Suhail Ahmad; Lone, Shabiruddin; Lone, Riyaz Ahmad

    2016-01-01

    Active learning has received considerable attention over the past several years, often presented or perceived as a radical change from traditional instruction methods. Current research on learning indicates that using a variety of teaching strategies in the classroom increases student participation and learning. To introduce active learning methodology, i.e., "jigsaw technique" in undergraduate medical education and assess the student and faculty response to it. This study was carried out in the Department of Physiology in a Medical College of North India. A topic was chosen and taught using one of the active learning methods (ALMs), i.e., jigsaw technique. An instrument (questionnaire) was developed in English through an extensive review of literature and was properly validated. The students were asked to give their response on a five-point Likert scale. The feedback was kept anonymous. Faculty also provided their feedback in a separately provided feedback proforma. The data were collected, compiled, and analyzed. Of 150 students of MBBS-first year batch 2014, 142 participated in this study along with 14 faculty members of the Physiology Department. The majority of the students (>90%) did welcome the introduction of ALM and strongly recommended the use of such methods in teaching many more topics in future. 100% faculty members were of the opinion that many more topics shall be taken up using ALMs. This study establishes the fact that both the medical students and faculty want a change from the traditional way of passive, teacher-centric learning, to the more active teaching-learning techniques.

  13. Data Mining and Machine Learning Methods for Dementia Research.

    Science.gov (United States)

    Li, Rui

    2018-01-01

    Patient data in clinical research often includes large amounts of structured information, such as neuroimaging data, neuropsychological test results, and demographic variables. Given the various sources of information, we can develop computerized methods that can be a great help to clinicians to discover hidden patterns in the data. The computerized methods often employ data mining and machine learning algorithms, lending themselves as the computer-aided diagnosis (CAD) tool that assists clinicians in making diagnostic decisions. In this chapter, we review state-of-the-art methods used in dementia research, and briefly introduce some recently proposed algorithms subsequently.

  14. A Pharmacy Preregistration Course Using Online Teaching and Learning Methods

    Science.gov (United States)

    McDowell, Jenny; Marriott, Jennifer L.; Calandra, Angela; Duncan, Gregory

    2009-01-01

    Objective To design and evaluate a preregistration course utilizing asynchronous online learning as the primary distance education delivery method. Design Online course components including tutorials, quizzes, and moderated small-group asynchronous case-based discussions were implemented. Online delivery was supplemented with self-directed and face-to-face learning. Assessment Pharmacy graduates who had completed the course in 2004 and 2005 were surveyed. The majority felt they had benefited from all components of the course, and that online delivery provided benefits including increased peer support, shared learning, and immediate feedback on performance. A majority of the first cohort reported that the workload associated with asynchronous online discussions was too great. The course was altered in 2005 to reduce the online component. Participant satisfaction improved, and most felt that the balance of online to face-to-face delivery was appropriate. Conclusion A new pharmacy preregistration course was successfully implemented. Online teaching and learning was well accepted and appeared to deliver benefits over traditional distance education methods once workload issues were addressed. PMID:19777092

  15. Impact of statistical learning methods on the predictive power of multivariate normal tissue complication probability models

    NARCIS (Netherlands)

    Xu, Cheng-Jian; van der Schaaf, Arjen; Schilstra, Cornelis; Langendijk, Johannes A.; van t Veld, Aart A.

    2012-01-01

    PURPOSE: To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. METHODS AND MATERIALS: In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator

  16. Theoretical methods for determination of core parameters in uranium-plutonium lattices

    International Nuclear Information System (INIS)

    Pop-Jordanov, J.; Bosevski, T.; Matausek, M.; Stefanovic, D.; Strugar, P.

    1972-01-01

    The prediction of plutonium production in power reactors depends essentially on how the change of neutron energy spectra in a reactor cell during burn-up is determined. In the epithermal region, where the build-up of plutonium occurs, the slowing down effects are particularly important, whereas, on the other hand, the thermal neutron spectrum is strongly influenced by the low-lying plutonium resonances. For accurate analysis, multi-group numerical methods are required, which, applied to burn-up prediction, are extremely laborious and time consuming even for large computers. This paper contains a comprehensive review of the methods of core parameter determination in the uranium-plutonium lattices developed in Yugoslavia during the last few years. Faced with the problem of using small computers, the authors had to find new approaches combining physical evidence and mathematical elegance. The main feature of these approaches is the tendency to proceed with analytical treatment as far as possible and then to include suitable numerical improvements. With this philosophy, which is generally overlooked when using large computers, fast and reasonably accurate methods were developed. The methods include original means for adequate treatment of neutron spectra and cell geometry effects,especially suitable for U-Pu systems. In particular, procedures based on the energy dependent boundary conditions, the discrete energy representation, the improved collision probabilities and the Green function slowing down solutions were developed and applied. Results obtained with these methods are presented and compared with those of the experiments and those obtained with other methods. (author)

  17. Theoretical methods for determination of core parameters in uranium-plutonium lattices

    Energy Technology Data Exchange (ETDEWEB)

    Pop-Jordanov, J.; Bosevski, T.; Matausek, M.; Stefanovic, D.; Strugar, P. [Institut za Nuklearne Nauke Boris Kidric, Belgrade (Yugoslavia)

    1972-07-01

    The prediction of plutonium production in power reactors depends essentially on how the change of neutron energy spectra in a reactor cell during burn-up is determined. In the epithermal region, where the build-up of plutonium occurs, the slowing down effects are particularly important, whereas, on the other hand, the thermal neutron spectrum is strongly influenced by the low-lying plutonium resonances. For accurate analysis, multi-group numerical methods are required, which, applied to burn-up prediction, are extremely laborious and time consuming even for large computers. This paper contains a comprehensive review of the methods of core parameter determination in the uranium-plutonium lattices developed in Yugoslavia during the last few years. Faced with the problem of using small computers, the authors had to find new approaches combining physical evidence and mathematical elegance. The main feature of these approaches is the tendency to proceed with analytical treatment as far as possible and then to include suitable numerical improvements. With this philosophy, which is generally overlooked when using large computers, fast and reasonably accurate methods were developed. The methods include original means for adequate treatment of neutron spectra and cell geometry effects,especially suitable for U-Pu systems. In particular, procedures based on the energy dependent boundary conditions, the discrete energy representation, the improved collision probabilities and the Green function slowing down solutions were developed and applied. Results obtained with these methods are presented and compared with those of the experiments and those obtained with other methods. (author)

  18. The Army Method Revisited: The Historical and Theoretical Backgrounds of the Military Intensive Language Programs.

    Science.gov (United States)

    Bayuk, Milla; Bayuk, Barry S.

    A program currently in use by the military that gives instruction in the so-called "sensitive" languages is based on the "Army Method" which was initiated in military language programs during World War II. Attention to the sensitive language program initiated a review of the programs, especially those conducted by the military intelligence schools…

  19. Measuring subjective meaning structures by the laddering method: Theoretical considerations and methodological problems

    DEFF Research Database (Denmark)

    Grunert, Klaus G.; Grunert, Suzanne C.

    1995-01-01

    Starting from a general model of measuring cognitive structures for predicting consumer behaviour, we discuss laddering as a possible method to obtain estimates of consumption-relevant cognitive structures which will have predictive validity. Four criteria for valid measurement are derived and ap...

  20. Theoretical Significance in Q Methodology: A Qualitative Approach to a Mixed Method

    Science.gov (United States)

    Ramlo, Susan

    2015-01-01

    Q methodology (Q) has offered researchers a unique scientific measure of subjectivity since William Stephenson's first article in 1935. Q's focus on subjectivity includes self-referential meaning and interpretation. Q is most often identified with its technique (Q-sort) and its method (factor analysis to group people); yet, it consists of a…

  1. Systems identification: a theoretical method applied to tracer kinetics in aquatic microcosms

    International Nuclear Information System (INIS)

    Halfon, E.; Georgia Univ., Athens

    1974-01-01

    A mathematical model of radionuclide kinetics in a laboratory microcosm was built and the transfer parameters estimated by multiple regression and system identification techniques. Insight into the functioning of the system was obtained from analysis of the model. Methods employed have allowed movements of radioisotopes not directly observable in the experimental systems to be distinguished. Results are generalized to whole ecosystems

  2. The Learners’ Attitudes towards Using Different Learning Methods in E-Learning Portal Environment

    Directory of Open Access Journals (Sweden)

    Issham Ismail

    2011-09-01

    Full Text Available This study investigates the learners’ preference of academic, collaborative and social interaction towards interaction methods in e-learning portal. Academic interaction consists of interaction between learners and online learning resources such as online reading, online explanation, online examination and also online question answering. Collaborative interaction occurs when learners interact among themselves using online group discussion. Social interaction happens when learners and instructors participate in the session either via online text chatting or voice chatting. The study employed qualitative methodology where data were collected through questionnaire that was administered to 933 distance education students from Bachelor of Management, Bachelor of Science, Bachelor of Social Science and Bachelor of Art. The survey responses were tabulated in a 5-point Likert scale and analyzed using the Statistical Package for Social Science (SPSS Version 12.0 based on frequency and percentage distribution. The result of the study suggest that among three types of interaction, most of the student prefer academic interaction for their learning supports in e-learning portal compared to collaborative and social interaction. They wish to interact with learning content rather than interact with people. They prefer to read and learn from the resources rather than sharing knowledge among themselves and instructors via collaborative and social interaction.

  3. Realization of Chinese word segmentation based on deep learning method

    Science.gov (United States)

    Wang, Xuefei; Wang, Mingjiang; Zhang, Qiquan

    2017-08-01

    In recent years, with the rapid development of deep learning, it has been widely used in the field of natural language processing. In this paper, I use the method of deep learning to achieve Chinese word segmentation, with large-scale corpus, eliminating the need to construct additional manual characteristics. In the process of Chinese word segmentation, the first step is to deal with the corpus, use word2vec to get word embedding of the corpus, each character is 50. After the word is embedded, the word embedding feature is fed to the bidirectional LSTM, add a linear layer to the hidden layer of the output, and then add a CRF to get the model implemented in this paper. Experimental results show that the method used in the 2014 People's Daily corpus to achieve a satisfactory accuracy.

  4. A Photometric Machine-Learning Method to Infer Stellar Metallicity

    Science.gov (United States)

    Miller, Adam A.

    2015-01-01

    Following its formation, a star's metal content is one of the few factors that can significantly alter its evolution. Measurements of stellar metallicity ([Fe/H]) typically require a spectrum, but spectroscopic surveys are limited to a few x 10(exp 6) targets; photometric surveys, on the other hand, have detected > 10(exp 9) stars. I present a new machine-learning method to predict [Fe/H] from photometric colors measured by the Sloan Digital Sky Survey (SDSS). The training set consists of approx. 120,000 stars with SDSS photometry and reliable [Fe/H] measurements from the SEGUE Stellar Parameters Pipeline (SSPP). For bright stars (g' learning method is similar to the scatter in [Fe/H] measurements from low-resolution spectra..

  5. A Photometric Machine-Learning Method to Infer Stellar Metallicity

    Science.gov (United States)

    Miller, Adam A.

    2015-01-01

    Following its formation, a star's metal content is one of the few factors that can significantly alter its evolution. Measurements of stellar metallicity ([Fe/H]) typically require a spectrum, but spectroscopic surveys are limited to a few x 10(exp 6) targets; photometric surveys, on the other hand, have detected > 10(exp 9) stars. I present a new machine-learning method to predict [Fe/H] from photometric colors measured by the Sloan Digital Sky Survey (SDSS). The training set consists of approx. 120,000 stars with SDSS photometry and reliable [Fe/H] measurements from the SEGUE Stellar Parameters Pipeline (SSPP). For bright stars (g' machine-learning method is similar to the scatter in [Fe/H] measurements from low-resolution spectra..

  6. Theoretical study (ab initio and DFT methods on acidic dissociation constant of xylenol orange in aqueous solution

    Directory of Open Access Journals (Sweden)

    F. Kiani

    2017-07-01

    Full Text Available Analytical measurement of materials requires exact knowledge of their acid dissociation constant (pKa values. In recent years, quantum mechanical calculations have been extensively used to study of acidities in the aqueous solutions and the results were compared with the experimental values. In this study, a theoretical study was carried out on xylenol orange (in water solution by ab initio method. We calculated the pKa values of xylenol orange in water, using high-level ab initio (PM3, DFT (HF, B3LYP/6-31+G(d and SCRF methods. The experimental determination of these values (pKa,s is a challenge because xylenol orange has a low solubility in water. We considered several ionization reactions and equilibriums in water that constitute the indispensable theoretical basis to calculate the pKa values of xylenol orange. The results show that the calculated pKa values have a comparable agreement with the experimentally determined pKa values. Therefore, this method can be used to predict such properties for indicators, drugs and other important molecules.

  7. Comparing three experiential learning methods and their effect on medical students' attitudes to learning communication skills.

    Science.gov (United States)

    Koponen, Jonna; Pyörälä, Eeva; Isotalus, Pekka

    2012-01-01

    Despite numerous studies exploring medical students' attitudes to communication skills learning (CSL), there are apparently no studies comparing different experiential learning methods and their influence on students' attitudes. We compared medical students' attitudes to learning communication skills before and after a communication course in the data as a whole, by gender and when divided into three groups using different methods. Second-year medical students (n = 129) were randomly assigned to three groups. In group A (n = 42) the theatre in education method, in group B (n = 44) simulated patients and in group C (n = 43) role-play were used. The data were gathered before and after the course using Communication Skills Attitude Scale. Students' positive attitudes to learning communication skills (PAS; positive attitude scale) increased significantly and their negative attitudes (NAS; negative attitude scale) decreased significantly between the beginning and end of the course. Female students had more positive attitudes than the male students. There were no significant differences in the three groups in the mean scores for PAS or NAS measured before or after the course. The use of experiential methods and integrating communication skills training with visits to health centres may help medical students to appreciate the importance of CSL.

  8. Theoretical and methodical peculiarities of training of student's female on a soccer

    Directory of Open Access Journals (Sweden)

    Galuza S.S.

    2012-09-01

    Full Text Available Generals are considered on planning and leadthrough of employments football with students. The anatomic physiological features of activity of womanish organism are generalized. Directions of increase of health of students are considered. It is set that in Ukrainian higher educational establishments from 70 to 90 % certain rejections have all of students in a state of health. The necessity of increase of indexes of health is marked on the basis of forming of proof motivation to regular employments by physical exercises and use of the proper effective methods. Most perspective and optimum is the use of such methods in extracurricular time. It is rotined that the use of positive complex influence of employments on the different systems of organism improves the bodily condition of students football.

  9. Theoretical studies on CH+ ion molecule using configuration interaction method and its spectroscopic properties

    International Nuclear Information System (INIS)

    Machado, F.B.C.

    1985-01-01

    The use of the configuration (CI) method for the calculation of very accurate potential energy curves and dipole moment functions, and then their use in the comprehension of spectroscopic properties of diatomic molecules is presented. The spectroscopic properties of CH + and CD + such as: vibrational levels, spectroscopic constants, averaged dipole moments for all vibrational levels, radiative transition probabilities for emission and absorption, and radiative lifetimes are verificated. (M.J.C.) [pt

  10. What is new in the study of differential equations by group theoretical methods

    International Nuclear Information System (INIS)

    Winternitz, P.

    1986-11-01

    Several recent developments have made the application of group theory to the solving of differential equations more powerful than it used to be. The ones discussed here are: 1. The advent of symbol manipulating computer languages that greatly simplify the construction of the symmetry group of an equation 2. Methods of finding all subgroups of a given Lie symmetry group 3. The theory of infinite dimensional Lie algebras 4. The combination of group theory and singularity analysis

  11. Housing Value Forecasting Based on Machine Learning Methods

    OpenAIRE

    Mu, Jingyi; Wu, Fang; Zhang, Aihua

    2014-01-01

    In the era of big data, many urgent issues to tackle in all walks of life all can be solved via big data technique. Compared with the Internet, economy, industry, and aerospace fields, the application of big data in the area of architecture is relatively few. In this paper, on the basis of the actual data, the values of Boston suburb houses are forecast by several machine learning methods. According to the predictions, the government and developers can make decisions about whether developing...

  12. 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

  13. A critical assessment of theoretical methods for finding reaction pathways and transition states of surface processes

    International Nuclear Information System (INIS)

    Klimes, JirI; Michaelides, Angelos; Bowler, David R

    2010-01-01

    The performance of a variety of techniques for locating transition states on potential energy surfaces is evaluated within the density functional theory framework. Diffusion of a water molecule across NaCl(001) and HCl bond breaking on the same surface are treated as general test cases; the former is an example of a low barrier diffusion process and the latter an example of a relatively high barrier covalent bond rupture event. The methods considered include the nudged elastic band (NEB), Dewar, Healy and Stewart (DHS), dimer, constrained optimization (CO), activation-relaxation technique (ART) and one-side growing string (OGS) as well as novel combinations of the DHS with growing string (DHS + GS) and DHS plus climbing image (CI-DHS). A key conclusion to come from this study is that the NEB method is relatively fast, especially when just a single (climbing) image is used. Indeed, using more images represents an unnecessary computational burden for our set of processes. The dimer method exhibits variable performance; being poor for the water diffusion processes, which have small activation energies, but much more efficient for the HCl bond breaking process which has a higher barrier. When only a poor initial guess of the transition state geometry is available, the CI-DHS scheme is one of the most efficient techniques considered. And as a means to quickly establish an approximate minimum energy pathway the DHS + GS scheme offers some potential.

  14. Experimental and Theoretical Structural Investigation of AuPt Nanoparticles Synthesized Using a Direct Electrochemical Method.

    Science.gov (United States)

    Lapp, Aliya S; Duan, Zhiyao; Marcella, Nicholas; Luo, Long; Genc, Arda; Ringnalda, Jan; Frenkel, Anatoly I; Henkelman, Graeme; Crooks, Richard M

    2018-05-11

    In this report, we examine the structure of bimetallic nanomaterials prepared by an electrochemical approach known as hydride-terminated (HT) electrodeposition. It has been shown previously that this method can lead to deposition of a single Pt monolayer on bulk-phase Au surfaces. Specifically, under appropriate electrochemical conditions and using a solution containing PtCl 4 2- , a monolayer of Pt atoms electrodeposits onto bulk-phase Au immediately followed by a monolayer of H atoms. The H atom capping layer prevents deposition of Pt multilayers. We applied this method to ∼1.6 nm Au nanoparticles (AuNPs) immobilized on an inert electrode surface. In contrast to the well-defined, segregated Au/Pt structure of the bulk-phase surface, we observe that HT electrodeposition leads to the formation of AuPt quasi-random alloy NPs rather than the core@shell structure anticipated from earlier reports relating to deposition onto bulk phases. The results provide a good example of how the phase behavior of macro materials does not always translate to the nano world. A key component of this study was the structure determination of the AuPt NPs, which required a combination of electrochemical methods, electron microscopy, X-ray absorption spectroscopy, and theory (DFT and MD).

  15. A diffusion-theoretical method to calculate the neutron flux distribution in multisphere configurations

    International Nuclear Information System (INIS)

    Schuerrer, F.

    1980-01-01

    For characterizing heterogene configurations of pebble-bed reactors the fine structure of the flux distribution as well as the determination of the macroscopic neutronphysical quantities are of interest. When calculating system parameters of Wigner-Seitz-cells the usual codes for neutron spectra calculation always neglect the modulation of the neutron flux by the influence of neighbouring spheres. To judge the error arising from that procedure it is necessary to determinate the flux distribution in the surrounding of a spherical fuel element. In the present paper an approximation method to calculate the flux distribution in the two-sphere model is developed. This method is based on the exactly solvable problem of the flux determination of a point source of neutrons in an infinite medium, which contains a spherical perturbation zone eccentric to the point source. An iteration method allows by superposing secondary fields and alternately satisfying the conditions of continuity on the surface of each of the two fuel elements to advance to continually improving approximations. (orig.) 891 RW/orig. 892 CKA [de

  16. Impact source identification in finite isotropic plates using a time-reversal method: theoretical study

    International Nuclear Information System (INIS)

    Chen, Chunlin; Yuan, Fuh-Gwo

    2010-01-01

    This paper aims to identify impact sources on plate-like structures based on the synthetic time-reversal (T-R) concept using an array of sensors. The impact source characteristics, namely, impact location and impact loading time history, are reconstructed using the invariance of time-reversal concept, reciprocal theory, and signal processing algorithms. Numerical verification for two finite isotropic plates under low and high velocity impacts is performed to demonstrate the versatility of the synthetic T-R method for impact source identification. The results show that the impact location and time history of the impact force with various shapes and frequency bands can be readily obtained with only four sensors distributed around the impact location. The effects of time duration and the inaccuracy in the estimated impact location on the accuracy of the time history of the impact force using the T-R method are investigated. Since the T-R technique retraces all the multi-paths of reflected waves from the geometrical boundaries back to the impact location, it is well suited for quantifying the impact characteristics for complex structures. In addition, this method is robust against noise and it is suggested that a small number of sensors is sufficient to quantify the impact source characteristics through simple computation; thus it holds promise for the development of passive structural health monitoring (SHM) systems for impact monitoring in near real-time

  17. After Fukushima? On the educational and learning theoretical reflection of nuclear disasters. International perspectives; Nach Fukushima? Zur erziehungs- und bildungstheoretischen Reflexion atomarer Katastrophen. Internationale Perspektiven

    Energy Technology Data Exchange (ETDEWEB)

    Wigger, Lothar; Buenger, Carsten (eds.) [Technische Univ. Dortmund (Germany). Bereich Allgemeine Erziehungswissenschaft; Platzer, Barbara [Technische Univ. Dortmund (Germany)

    2017-08-01

    The book on the educational and learning theoretical reflection of nuclear disasters as a consequence of Fukushima includes contributions on the following issues: pedagogical approach: children write on Fukushima, description of the reality as pedagogical challenge; lessons learned on the nuclear technology - perspectives and limits of pedagogical evaluation: moral education - Japanese teaching materials, educational challenges at the universities with respect to nuclear technology and technology impact assessment; education and technology - questions concerning the pedagogical responsibility: considerations on the responsibility of scientists, on the discrepancy between technology and education, disempowerment of the public by structural corruption - nuclear disaster and post-democratic tendencies in Japan.

  18. A Doctoral Seminar in Qualitative Research Methods: Lessons Learned

    Directory of Open Access Journals (Sweden)

    Suzanne Franco

    2016-09-01

    Full Text Available New qualitative research methods continue to emerge in response to factors such as renewed interest in mixed methods, better understanding of the importance of a researcher’s philosophical stance, as well as the increased use of technology in data collection and analysis, to name a few. As a result, those facilitating research methods courses must revisit content and instructional strategies in order to prepare well-informed researchers. Approaches range from paradigm to pragmatic emphasis. This descriptive case study of a doctoral seminar for novice qualitative researchers describes the intricacies of the syllabus of a pragmatic approach in a constructivist/social constructionist learning environment. The purpose was to document the delivery and faculty/student interactions and reactions. Noteworthy were the contradictions and frustrations in the delivery as well as in student experiences. In the end, student input led to seminal learning experiences. The confirmation of the effectiveness of a constructivist/social constructivist learning environment is applicable to higher education pedagogy in general.

  19. Deep Learning Methods for Underwater Target Feature Extraction and Recognition

    Directory of Open Access Journals (Sweden)

    Gang Hu

    2018-01-01

    Full Text Available The classification and recognition technology of underwater acoustic signal were always an important research content in the field of underwater acoustic signal processing. Currently, wavelet transform, Hilbert-Huang transform, and Mel frequency cepstral coefficients are used as a method of underwater acoustic signal feature extraction. In this paper, a method for feature extraction and identification of underwater noise data based on CNN and ELM is proposed. An automatic feature extraction method of underwater acoustic signals is proposed using depth convolution network. An underwater target recognition classifier is based on extreme learning machine. Although convolution neural networks can execute both feature extraction and classification, their function mainly relies on a full connection layer, which is trained by gradient descent-based; the generalization ability is limited and suboptimal, so an extreme learning machine (ELM was used in classification stage. Firstly, CNN learns deep and robust features, followed by the removing of the fully connected layers. Then ELM fed with the CNN features is used as the classifier to conduct an excellent classification. Experiments on the actual data set of civil ships obtained 93.04% recognition rate; compared to the traditional Mel frequency cepstral coefficients and Hilbert-Huang feature, recognition rate greatly improved.

  20. THE THEORETICAL AND METHODICAL APPROACH TO AN ASSESSMENT OF A LEVEL OF DEVELOPMENT OF THE ENTERPRISE IN CONDITIONS OF GLOBALIZATION

    Directory of Open Access Journals (Sweden)

    Tatiana Shved

    2016-11-01

    Full Text Available The subject of this article is theoretical, methodical and practical aspects of enterprise development in conditions of globalization. The purpose of this research is to provide theoretical and methodical approach to an assessment of a level of development of the enterprise, which is based on the relationship between the factors and influence, illustrating the effect of the internal and external environment of enterprises functioning, and indicates the level of development of the enterprise. Methodology. Theoretical basis of the study was the examination and rethinking of the main achievements of world and domestic science on the development of enterprises. To achieve the objectives of the research following methods were used: systemic and structural analysis for the formation of methodical approaches to the selection of the factors, influencing the development of enterprises; abstract and logical – for the formulation of conclusions and proposals; the method of valuation and expert assessments to the implementation of the proposed theoretical and methodical approach to an assessment of a level of development of the enterprise in conditions of globalization. Results of the research is the proposed theoretical and methodical to an assessment of a level of development of the enterprise in conditions of globalization, which is associated with the idea of development of the enterprise as a system with inputs–factors, influencing on the development , and outputs – indicators of the level of enterprise development within these factors. So, the chosen factors – resources, financial-economic activity, innovation and investment activities, competition, government influence, and foreign trade. Indicators that express these factors, are capital productivity, labour productivity, material efficiency within the first factor; the profitability of the activity, the coefficient of current assets, the total liquidity coefficient, financial stability

  1. Development of a nursing education program for improving Chinese undergraduates' self-directed learning: A mixed-method study.

    Science.gov (United States)

    Tao, Ying; Li, Liping; Xu, Qunyan; Jiang, Anli

    2015-11-01

    This paper demonstrates the establishment of an extra-curricular education program in Chinese context and evaluates its effectiveness on undergraduate nursing students' self-directed learning. Zimmerman's self-directed learning model was used as the theoretical framework for the development of an education program. Mixed-method was applied in this research study. 165 undergraduate students from a nursing college were divided into experimental group (n=32) and control group (n=133). Pre- and post-tests were implemented to evaluate the effectiveness of this education program using the self-directed learning scale of nursing undergraduates. Qualitative interview was undertaken within participants from the experimental group to obtain their insights into the influence of this program. Both quantitative and qualitative analyses showed that the program contributed to nursing students' self-directed learning ability. In the experimental group, the post-test score showed an increase compared with pretest score (plearning activities and influence on learning environment. It can be found in the qualitative analysis that learners benefited from this program. The education program contributes to the improvement of nursing undergraduates' self-directed learning. Various pedagogic methods could be applied for self-directed learning. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Oxygen termination of homoepitaxial diamond surface by ozone and chemical methods: An experimental and theoretical perspective

    Science.gov (United States)

    Navas, Javier; Araujo, Daniel; Piñero, José Carlos; Sánchez-Coronilla, Antonio; Blanco, Eduardo; Villar, Pilar; Alcántara, Rodrigo; Montserrat, Josep; Florentin, Matthieu; Eon, David; Pernot, Julien

    2018-03-01

    Phenomena related with the diamond surface of both power electronic and biosensor devices govern their global behaviour. In particular H- or O-terminations lead to wide variations in their characteristics. To study the origins of such aspects in greater depth, different methods to achieve oxygen terminated diamond were investigated following a multi-technique approach. DFT calculations were then performed to understand the different configurations between the C and O atoms. Three methods for O-terminating the diamond surface were performed: two physical methods with ozone at different pressures, and an acid chemical treatment. X-ray photoelectron spectroscopy, spectroscopic ellipsometry, HRTEM, and EELS were used to characterize the oxygenated surface. Periodic-DFT calculations were undertaken to understand the effect of the different ways in which the oxygen atoms are bonded to carbon atoms on the diamond surface. XPS results showed the presence of hydroxyl or ether groups, composed of simple Csbnd O bonds, and the acid treatment resulted in the highest amount of O on the diamond surface. In turn, ellipsometry showed that the different treatments led to the surface having different optical properties, such as a greater refraction index and extinction coefficient in the case of the sample subjected to acid treatment. TEM analysis showed that applying temperature treatment improved the distribution of the oxygen atoms at the interface and that this generates a thinner amount of oxygen at each position and higher interfacial coverage. Finally, DFT calculations showed both an increase in the number of preferential electron transport pathways when π bonds and ether groups appear in the system, and also the presence of states in the middle of the band gap when there are π bonds, Cdbnd C or Cdbnd O.

  3. Application of machine learning methods for traffic signs recognition

    Science.gov (United States)

    Filatov, D. V.; Ignatev, K. V.; Deviatkin, A. V.; Serykh, E. V.

    2018-02-01

    This paper focuses on solving a relevant and pressing safety issue on intercity roads. Two approaches were considered for solving the problem of traffic signs recognition; the approaches involved neural networks to analyze images obtained from a camera in the real-time mode. The first approach is based on a sequential image processing. At the initial stage, with the help of color filters and morphological operations (dilatation and erosion), the area containing the traffic sign is located on the image, then the selected and scaled fragment of the image is analyzed using a feedforward neural network to determine the meaning of the found traffic sign. Learning of the neural network in this approach is carried out using a backpropagation method. The second approach involves convolution neural networks at both stages, i.e. when searching and selecting the area of the image containing the traffic sign, and when determining its meaning. Learning of the neural network in the second approach is carried out using the intersection over union function and a loss function. For neural networks to learn and the proposed algorithms to be tested, a series of videos from a dash cam were used that were shot under various weather and illumination conditions. As a result, the proposed approaches for traffic signs recognition were analyzed and compared by key indicators such as recognition rate percentage and the complexity of neural networks’ learning process.

  4. Kernel methods for interpretable machine learning of order parameters

    Science.gov (United States)

    Ponte, Pedro; Melko, Roger G.

    2017-11-01

    Machine learning is capable of discriminating phases of matter, and finding associated phase transitions, directly from large data sets of raw state configurations. In the context of condensed matter physics, most progress in the field of supervised learning has come from employing neural networks as classifiers. Although very powerful, such algorithms suffer from a lack of interpretability, which is usually desired in scientific applications in order to associate learned features with physical phenomena. In this paper, we explore support vector machines (SVMs), which are a class of supervised kernel methods that provide interpretable decision functions. We find that SVMs can learn the mathematical form of physical discriminators, such as order parameters and Hamiltonian constraints, for a set of two-dimensional spin models: the ferromagnetic Ising model, a conserved-order-parameter Ising model, and the Ising gauge theory. The ability of SVMs to provide interpretable classification highlights their potential for automating feature detection in both synthetic and experimental data sets for condensed matter and other many-body systems.

  5. Machine Learning and Data Mining Methods in Diabetes Research.

    Science.gov (United States)

    Kavakiotis, Ioannis; Tsave, Olga; Salifoglou, Athanasios; Maglaveras, Nicos; Vlahavas, Ioannis; Chouvarda, Ioanna

    2017-01-01

    The remarkable advances in biotechnology and health sciences have led to a significant production of data, such as high throughput genetic data and clinical information, generated from large Electronic Health Records (EHRs). To this end, application of machine learning and data mining methods in biosciences is presently, more than ever before, vital and indispensable in efforts to transform intelligently all available information into valuable knowledge. Diabetes mellitus (DM) is defined as a group of metabolic disorders exerting significant pressure on human health worldwide. Extensive research in all aspects of diabetes (diagnosis, etiopathophysiology, therapy, etc.) has led to the generation of huge amounts of data. The aim of the present study is to conduct a systematic review of the applications of machine learning, data mining techniques and tools in the field of diabetes research with respect to a) Prediction and Diagnosis, b) Diabetic Complications, c) Genetic Background and Environment, and e) Health Care and Management with the first category appearing to be the most popular. A wide range of machine learning algorithms were employed. In general, 85% of those used were characterized by supervised learning approaches and 15% by unsupervised ones, and more specifically, association rules. Support vector machines (SVM) arise as the most successful and widely used algorithm. Concerning the type of data, clinical datasets were mainly used. The title applications in the selected articles project the usefulness of extracting valuable knowledge leading to new hypotheses targeting deeper understanding and further investigation in DM.

  6. Identification of Dynamic Flow Stress Curves Using the Virtual Fields Methods: Theoretical Feasibility Analysis

    Science.gov (United States)

    Leem, Dohyun; Kim, Jin-Hwan; Barlat, Frédéric; Song, Jung Han; Lee, Myoung-Gyu

    2018-03-01

    An inverse approach based on the virtual fields method (VFM) is presented to identify the material hardening parameters under dynamic deformation. This dynamic-VFM (D-VFM) method does not require load information for the parameter identification. Instead, it utilizes acceleration fields in a specimen's gage region. To investigate the feasibility of the proposed inverse approach for dynamic deformation, the virtual experiments using dynamic finite element simulations were conducted. The simulation could provide all the necessary data for the identification such as displacement, strain, and acceleration fields. The accuracy of the identification results was evaluated by changing several parameters such as specimen geometry, velocity, and traction boundary conditions. The analysis clearly shows that the D-VFM which utilizes acceleration fields can be a good alternative to the conventional identification procedure that uses load information. Also, it was found that proper deformation conditions are required for generating sufficient acceleration fields during dynamic deformation to enhance the identification accuracy with the D-VFM.

  7. Theoretical methods for creep and stress relaxation studies of SSC coil

    International Nuclear Information System (INIS)

    McAdams, J.; Markley, F.

    1992-04-01

    Extrapolation of laboratory measurements of SSC coil properties to the actual construction of SSC magnets requires mathematical models of the experimental data. A variety of models were used to approximate the data collected from creep and stress relaxation experiments performed on Kapton film and SSC coil samples. The coefficients for these mathematical models were found by performing a least-squares fit via the program MINUIT. Once the semiempirical expressions for the creep data were found, they were converted to expressions for stress relaxation using an approximate I pn of the Laplace integral relating the two processes. The data sets from creep experiments were also converted directly to stress relaxation data by numeric integration. Both of these methods allow comparison of data from two different methods of measuring viscoelastic properties. Three companion papers presented at this conference will present: Stress relaxation in SSC 50mm dipole coil. Measurement of the elastic modulus of Kapton perpendicular to the plane of the film at room and cryogenic temperatures. Temperature dependence of the viscoelastic properties of SSC coil insulation (Kapton)

  8. Method of experimental and theoretical modeling for multiple pressure tube rupture for RBMK reactor

    International Nuclear Information System (INIS)

    Medvedeva, N.Y.; Goldstein, R.V.; Burrows, J.A.

    2001-01-01

    The rupture of single RBMK reactor channels has occurred at a number of stations with a variety of initiating events. It is assumed in RBMK Safety Cases that the force of the escaping fluid will not cause neighbouring channels to break. This assumption has not been justified. A chain reaction of tube breaks could over-pressurise the reactor cavity leading to catastrophic failure of the containment. To validate the claims of the RBMK Safety Cases the Electrogorsk Research and Engineering Centre, in participation with experts from the Institute of Mechanics of RAS, has developed the method of interacting multiscale physical and mathematical modelling for coupled thermophysical, hydrogasodynamic processes and deformation and break processes causing and (or) accompanying potential failures, design and beyond the design RBMK reactor accidents. To realise the method the set of rigs, physical and mathematical models and specialized computer codes are under creation. This article sets out an experimental philosophy and programme for achieving this objective to solve the problem of credibility or non-credibility for multiple fuel channel rupture in RBMK.(author)

  9. A cross-benchmark comparison of 87 learning to rank methods

    NARCIS (Netherlands)

    Tax, N.; Bockting, S.; Hiemstra, D.

    2015-01-01

    Learning to rank is an increasingly important scientific field that comprises the use of machine learning for the ranking task. New learning to rank methods are generally evaluated on benchmark test collections. However, comparison of learning to rank methods based on evaluation results is hindered

  10. Characteristics and Consequences of Adult Learning Methods and Strategies. Practical Evaluation Reports, Volume 2, Number 1

    Science.gov (United States)

    Trivette, Carol M.; Dunst, Carl J.; Hamby, Deborah W.; O'Herin, Chainey E.

    2009-01-01

    The effectiveness of four adult learning methods (accelerated learning, coaching, guided design, and just-in-time training) constituted the focus of this research synthesis. Findings reported in "How People Learn" (Bransford et al., 2000) were used to operationally define six adult learning method characteristics, and to code and analyze…

  11. Introducing the Collaborative E-Learning Design Method (CoED)

    DEFF Research Database (Denmark)

    Ryberg, Thomas; Buus, Lillian; Nyvang, Tom

    2015-01-01

    In this chapter, a specific learning design method is introduced and explained, namely the Collaborative E-learning Design method (CoED), which has been developed through various projects in “e-Learning Lab – Centre for User Driven Innovation, Learning and Design” (Nyvang & Georgsen, 2007). We br...

  12. Actively Teaching Research Methods with a Process Oriented Guided Inquiry Learning Approach

    Science.gov (United States)

    Mullins, Mary H.

    2017-01-01

    Active learning approaches have shown to improve student learning outcomes and improve the experience of students in the classroom. This article compares a Process Oriented Guided Inquiry Learning style approach to a more traditional teaching method in an undergraduate research methods course. Moving from a more traditional learning environment to…

  13. Development and implementation of theoretical methods for the description of electronically core-excited states

    Energy Technology Data Exchange (ETDEWEB)

    Wenzel, Jan

    2016-03-23

    My PhD project mainly consists of two important parts. One was to enhance and develop variants of the core-valence-separation-algebraic-diagrammatic-construction (CVS-ADC) method and implement all approaches efficiently in the adcman program, which is part of the Q-chem program package. Secondly, I benchmarked these implementations and simulated X-ray absorption spectra of small- and medium-sized molecules from different fields. In this thesis, I present my implementations, as well as the results and applications obtained with the CVS-ADC methods and give a general introduction into quantum chemical methods. At first, I implemented the CVS-ADC approach up to the extended second in an efficient way. The program is able to deal with systems up to 500 basis functions in an adequate computational time, which allows for accurate calculations of medium-sized closed-shell molecules, e.g. acenaphthenequinone (ANQ). Afterwards, the CVS-ADC implementation was extended for the first time to deal with open-shell systems, i.e. ions and radicals, which implies a treatment of unrestricted wave functions and spin-orbitals. The resulting method is denoted as CVS-UADC(2)-x. For the first time, I applied the CVS approximation to the the third order ADC scheme, derived the working equations, and implemented the CVS-ADC(3) method in adcman. As the last step, I applied the CVS formalism for the first time to the ISR approach to enable calculations of core-excited state properties and densities. To benchmark all restricted and unrestricted CVS-ADC/CVS-ISR methods up to third order in perturbation theory, I chose a set of small molecules, e.g. carbon monoxide (CO). The calculated values of core-excitation energies, transition moments and static dipole moments are compared with experimental data or other approaches, thereby estimating complete basis set (CBS) limits. Furthermore, a comprehensive study of different basis sets is performed. In combination with the CBS limit of the aug

  14. The theoretical study of passive and active optical devices via planewave based transfer (scattering) matrix method and other approaches

    Energy Technology Data Exchange (ETDEWEB)

    Zhuo, Ye [Iowa State Univ., Ames, IA (United States)

    2011-01-01

    In this thesis, we theoretically study the electromagnetic wave propagation in several passive and active optical components and devices including 2-D photonic crystals, straight and curved waveguides, organic light emitting diodes (OLEDs), and etc. Several optical designs are also presented like organic photovoltaic (OPV) cells and solar concentrators. The first part of the thesis focuses on theoretical investigation. First, the plane-wave-based transfer (scattering) matrix method (TMM) is briefly described with a short review of photonic crystals and other numerical methods to study them (Chapter 1 and 2). Next TMM, the numerical method itself is investigated in details and developed in advance to deal with more complex optical systems. In chapter 3, TMM is extended in curvilinear coordinates to study curved nanoribbon waveguides. The problem of a curved structure is transformed into an equivalent one of a straight structure with spatially dependent tensors of dielectric constant and magnetic permeability. In chapter 4, a new set of localized basis orbitals are introduced to locally represent electromagnetic field in photonic crystals as alternative to planewave basis. The second part of the thesis focuses on the design of optical devices. First, two examples of TMM applications are given. The first example is the design of metal grating structures as replacements of ITO to enhance the optical absorption in OPV cells (chapter 6). The second one is the design of the same structure as above to enhance the light extraction of OLEDs (chapter 7). Next, two design examples by ray tracing method are given, including applying a microlens array to enhance the light extraction of OLEDs (chapter 5) and an all-angle wide-wavelength design of solar concentrator (chapter 8). In summary, this dissertation has extended TMM which makes it capable of treating complex optical systems. Several optical designs by TMM and ray tracing method are also given as a full complement of this

  15. The Influence of Background Music on Learning in the Light of Different Theoretical Perspectives and the Role of Working Memory Capacity

    Directory of Open Access Journals (Sweden)

    Janina A. M. Lehmann

    2017-10-01

    Full Text Available This study investigates how background music influences learning with respect to three different theoretical approaches. Both the Mozart effect as well as the arousal-mood-hypothesis indicate that background music can potentially benefit learning outcomes. While the Mozart effect assumes a direct influence of background music on cognitive abilities, the arousal-mood-hypothesis assumes a mediation effect over arousal and mood. However, the seductive detail effect indicates that seductive details such as background music worsen learning. Moreover, as working memory capacity has a crucial influence on learning with seductive details, we also included the learner’s working memory capacity as a factor in our study. We tested 81 college students using a between-subject design with half of the sample listening to two pop songs while learning a visual text and the other half learning in silence. We included working memory capacity in the design as a continuous organism variable. Arousal and mood scores before and after learning were collected as potential mediating variables. To measure learning outcomes we tested recall and comprehension. We did not find a mediation effect between background music and arousal or mood on learning outcomes. In addition, for recall performance there were no main effects of background music or working memory capacity, nor an interaction effect of these factors. However, when considering comprehension we did find an interaction between background music and working memory capacity: the higher the learners’ working memory capacity, the better they learned with background music. This is in line with the seductive detail assumption.

  16. Effect of Chemistry Triangle Oriented Learning Media on Cooperative, Individual and Conventional Method on Chemistry Learning Result

    Science.gov (United States)

    Latisma D, L.; Kurniawan, W.; Seprima, S.; Nirbayani, E. S.; Ellizar, E.; Hardeli, H.

    2018-04-01

    The purpose of this study was to see which method are well used with the Chemistry Triangle-oriented learning media. This quasi experimental research involves first grade of senior high school students in six schools namely each two SMA N in Solok city, in Pasaman and two SMKN in Pariaman. The sampling technique was done by Cluster Random Sampling. Data were collected by test and analyzed by one-way anova and Kruskall Wallish test. The results showed that the high school students in Solok learning taught by cooperative method is better than the results of student learning taught by conventional and Individual methods, both for students who have high initial ability and low-ability. Research in SMK showed that the overall student learning outcomes taught by conventional method is better than the student learning outcomes taught by cooperative and individual methods. Student learning outcomes that have high initial ability taught by individual method is better than student learning outcomes that are taught by cooperative method and for students who have low initial ability, there is no difference in student learning outcomes taught by cooperative, individual and conventional methods. Learning in high school in Pasaman showed no significant difference in learning outcomes of the three methods undertaken.

  17. Finite element methods for engineering sciences. Theoretical approach and problem solving techniques

    Energy Technology Data Exchange (ETDEWEB)

    Chaskalovic, J. [Ariel University Center of Samaria (Israel); Pierre and Marie Curie (Paris VI) Univ., 75 (France). Inst. Jean le Rond d' Alembert

    2008-07-01

    This self-tutorial offers a concise yet thorough grounding in the mathematics necessary for successfully applying FEMs to practical problems in science and engineering. The unique approach first summarizes and outlines the finite-element mathematics in general and then, in the second and major part, formulates problem examples that clearly demonstrate the techniques of functional analysis via numerous and diverse exercises. The solutions of the problems are given directly afterwards. Using this approach, the author motivates and encourages the reader to actively acquire the knowledge of finite- element methods instead of passively absorbing the material, as in most standard textbooks. The enlarged English-language edition, based on the original French, also contains a chapter on the approximation steps derived from the description of nature with differential equations and then applied to the specific model to be used. Furthermore, an introduction to tensor calculus using distribution theory offers further insight for readers with different mathematical backgrounds. (orig.)

  18. Theoretical treatment of photodissociation of water by time-dependent quantum mechanical methods

    International Nuclear Information System (INIS)

    Weide, K.

    1993-01-01

    An algorithm for wavepacket propagation, based on Kosloff's method of expansion of the time evolution operator in terms of Chebychev polynomials, and some details of its implementation are described. With the programs developed, quantum-mechanical calculations for up to three independent molecular coordinates are possible and feasible and therefore photodissociation of non-rotating triatomic molecules can be treated exactly. The angular degree of freedom here is handled by expansion in terms of free diatomic rotor states. The time-dependent wave packet picture is compared with the more traditional view of stationary wave functions, and both are used to interpret computational results where appropriate. Two-dimensional calculations have been performed to explain several experimental observations about water photodissociation. All calculations are based on ab initio potential energy surfaces, and it is explained in each case why it is reasonable to neglect the third degree of freedom. Many experimental results are reproduced quantitatively. (orig.) [de

  19. Field-theoretic methods in strongly-coupled models of general gauge mediation

    International Nuclear Information System (INIS)

    Fortin, Jean-François; Stergiou, Andreas

    2013-01-01

    An often-exploited feature of the operator product expansion (OPE) is that it incorporates a splitting of ultraviolet and infrared physics. In this paper we use this feature of the OPE to perform simple, approximate computations of soft masses in gauge-mediated supersymmetry breaking. The approximation amounts to truncating the OPEs for hidden-sector current–current operator products. Our method yields visible-sector superpartner spectra in terms of vacuum expectation values of a few hidden-sector IR elementary fields. We manage to obtain reasonable approximations to soft masses, even when the hidden sector is strongly coupled. We demonstrate our techniques in several examples, including a new framework where supersymmetry breaking arises both from a hidden sector and dynamically. Our results suggest that strongly-coupled models of supersymmetry breaking are naturally split

  20. Field-theoretic Methods in Strongly-Coupled Models of General Gauge Mediation

    CERN Document Server

    Fortin, Jean-Francois

    2013-01-01

    An often-exploited feature of the operator product expansion (OPE) is that it incorporates a splitting of ultraviolet and infrared physics. In this paper we use this feature of the OPE to perform simple, approximate computations of soft masses in gauge-mediated supersymmetry breaking. The approximation amounts to truncating the OPEs for hidden-sector current-current operator products. Our method yields visible-sector superpartner spectra in terms of vacuum expectation values of a few hidden-sector IR elementary fields. We manage to obtain reasonable approximations to soft masses, even when the hidden sector is strongly coupled. We demonstrate our techniques in several examples, including a new framework where supersymmetry-breaking arises both from a hidden sector and dynamically.

  1. The Theoretical and Methodical Foundations of Formation and Development of the Managerial Knowledge of Enterprise

    Directory of Open Access Journals (Sweden)

    Denysiuk Olga V.

    2017-05-01

    Full Text Available The article defines the relationship between the concepts of «managerial competency» and «managerial knowledge of enterprise». By generalizing the conceptual provisions, a typology of the enterprise’s competencies has been developed. In order to clarify the contents of the concept of managerial competency, the classification attributes of the managerial knowledge of enterprise have been allocated. The need to use management standards (management of business processes, staff, quality, projects, and production in the processes of formation and development of the managerial competencies of the enterprise has been substantiated. The composition of the methodical support of formation and development of the managerial competencies of enterprise have been provided.

  2. INVESTIGATIONS OF THE FLOW INTO A STORAGE TANK BY MEANS OF ADVANCED EXPERIMENTAL AND THEORETICAL METHODS

    DEFF Research Database (Denmark)

    Jordan, Ulrike; Shah, Louise Jivan; Furbo, Simon

    2003-01-01

    that the luminescence intensity depends on the water temperature, the temperature fields in the tank can be visualized and also be recorded with a camera. The measurements were compared with calculations of the flow and temperature fields carried out with the Computational Fluid Dynamics (CFD) tool Fluent. In future...... is to study the influence of the inlet device geometry and of the operating conditions (the flow rate, draw-off volume, and temperatures) on the thermal stratification in the tank. Measurements of the flow and temperature fields were carried out with two visualization techniques: - To visualize the flow field...... a method called Particle Image Velocimetry (PIV) was applied. Particles with a size of 1 to 10 mm were seeded in the water and then illuminated by a laser within a narrow plane. In order to measure the three velocity components of the flow within the plane, the particle displacements between laser pulses...

  3. Theoretical comparison of performance using transfer functions for reactivity meters based on inverse kinetic method and simple feedback method

    International Nuclear Information System (INIS)

    Shimazu, Yoichiro; Tashiro, Shoichi; Tojo, Masayuki

    2017-01-01

    The performance of two digital reactivity meters, one based on the conventional inverse kinetic method and the other one based on simple feedback theory, are compared analytically using their respective transfer functions. The latter one is proposed by one of the authors. It has been shown that the performance of the two reactivity meters become almost identical when proper system parameters are selected for each reactivity meter. A new correlation between the system parameters of the two reactivity meters is found. With this correlation, filter designers can easily determine the system parameters for the respective reactivity meters to obtain identical performance. (author)

  4. Measuring the surgical 'learning curve': methods, variables and competency.

    Science.gov (United States)

    Khan, Nuzhath; Abboudi, Hamid; Khan, Mohammed Shamim; Dasgupta, Prokar; Ahmed, Kamran

    2014-03-01

    To describe how learning curves are measured and what procedural variables are used to establish a 'learning curve' (LC). To assess whether LCs are a valuable measure of competency. A review of the surgical literature pertaining to LCs was conducted using the Medline and OVID databases. Variables should be fully defined and when possible, patient-specific variables should be used. Trainee's prior experience and level of supervision should be quantified; the case mix and complexity should ideally be constant. Logistic regression may be used to control for confounding variables. Ideally, a learning plateau should reach a predefined/expert-derived competency level, which should be fully defined. When the group splitting method is used, smaller cohorts should be used in order to narrow the range of the LC. Simulation technology and competence-based objective assessments may be used in training and assessment in LC studies. Measuring the surgical LC has potential benefits for patient safety and surgical education. However, standardisation in the methods and variables used to measure LCs is required. Confounding variables, such as participant's prior experience, case mix, difficulty of procedures and level of supervision, should be controlled. Competency and expert performance should be fully defined. © 2013 The Authors. BJU International © 2013 BJU International.

  5. Stacking interactions between carbohydrate and protein quantified by combination of theoretical and experimental methods.

    Directory of Open Access Journals (Sweden)

    Michaela Wimmerová

    Full Text Available Carbohydrate-receptor interactions are an integral part of biological events. They play an important role in many cellular processes, such as cell-cell adhesion, cell differentiation and in-cell signaling. Carbohydrates can interact with a receptor by using several types of intermolecular interactions. One of the most important is the interaction of a carbohydrate's apolar part with aromatic amino acid residues, known as dispersion interaction or CH/π interaction. In the study presented here, we attempted for the first time to quantify how the CH/π interaction contributes to a more general carbohydrate-protein interaction. We used a combined experimental approach, creating single and double point mutants with high level computational methods, and applied both to Ralstonia solanacearum (RSL lectin complexes with α-L-Me-fucoside. Experimentally measured binding affinities were compared with computed carbohydrate-aromatic amino acid residue interaction energies. Experimental binding affinities for the RSL wild type, phenylalanine and alanine mutants were -8.5, -7.1 and -4.1 kcal x mol(-1, respectively. These affinities agree with the computed dispersion interaction energy between carbohydrate and aromatic amino acid residues for RSL wild type and phenylalanine, with values -8.8, -7.9 kcal x mol(-1, excluding the alanine mutant where the interaction energy was -0.9 kcal x mol(-1. Molecular dynamics simulations show that discrepancy can be caused by creation of a new hydrogen bond between the α-L-Me-fucoside and RSL. Observed results suggest that in this and similar cases the carbohydrate-receptor interaction can be driven mainly by a dispersion interaction.

  6. Application of unsupervised learning methods in high energy physics

    Energy Technology Data Exchange (ETDEWEB)

    Koevesarki, Peter; Nuncio Quiroz, Adriana Elizabeth; Brock, Ian C. [Physikalisches Institut, Universitaet Bonn, Bonn (Germany)

    2011-07-01

    High energy physics is a home for a variety of multivariate techniques, mainly due to the fundamentally probabilistic behaviour of nature. These methods generally require training based on some theory, in order to discriminate a known signal from a background. Nevertheless, new physics can show itself in ways that previously no one thought about, and in these cases conventional methods give little or no help. A possible way to discriminate between known processes (like vector bosons or top-quark production) or look for new physics is using unsupervised machine learning to extract the features of the data. A technique was developed, based on the combination of neural networks and the method of principal curves, to find a parametrisation of the non-linear correlations of the data. The feasibility of the method is shown on ATLAS data.

  7. Cross analysis of knowledge and learning methods followed by French residents in cardiology.

    Science.gov (United States)

    Menet, Aymeric; Assez, Nathalie; Lacroix, Dominique

    2015-01-01

    No scientific assessment of the theoretical teaching of cardiology in France is available. To analyse the impact of the available teaching modalities on the theoretical knowledge of French residents in cardiology. Electronic questionnaires were returned by 283 residents. In the first part, an inventory of the teaching/learning methods was taken, using 21 questions (Yes/No format). The second part was a knowledge test, comprising 15 multiple-choice questions, exploring the core curriculum. Of the 21 variables tested, four emerged as independent predictors of the score obtained in the knowledge test: access to self-assessment (P=0.0093); access to teaching methods other than lectures (P=0.036); systematic discussion about clinical decisions (P=0.013); and the opportunity to prepare and give lectures (P=0.039). The fifth variable was seniority in residency (P=0.0003). Each item of the knowledge test was analysed independently: the score was higher when teaching the item was driven by reading guidelines and was lower if the item had not been covered by the programme (Pcardiology by involving students in the training, by using teaching methods other than lectures and by facilitating access to self-assessment. The use of digital tools may be a particularly effective approach. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

  8. Comparison of Machine Learning Methods for the Arterial Hypertension Diagnostics

    Directory of Open Access Journals (Sweden)

    Vladimir S. Kublanov

    2017-01-01

    Full Text Available The paper presents results of machine learning approach accuracy applied analysis of cardiac activity. The study evaluates the diagnostics possibilities of the arterial hypertension by means of the short-term heart rate variability signals. Two groups were studied: 30 relatively healthy volunteers and 40 patients suffering from the arterial hypertension of II-III degree. The following machine learning approaches were studied: linear and quadratic discriminant analysis, k-nearest neighbors, support vector machine with radial basis, decision trees, and naive Bayes classifier. Moreover, in the study, different methods of feature extraction are analyzed: statistical, spectral, wavelet, and multifractal. All in all, 53 features were investigated. Investigation results show that discriminant analysis achieves the highest classification accuracy. The suggested approach of noncorrelated feature set search achieved higher results than data set based on the principal components.

  9. Theoretical and Experimental Studies of Dissimilar Secondary Metallurgy Methods for Improving Steel Cleanliness

    Science.gov (United States)

    Pitts-Baggett, April

    Due to a continual increasing industry demand for clean steels, a multi-depth sampling approach was developed to gain a more detailed depiction of the reactions occurring in the ladle throughout the Ladle Metallurgy Furnace (LMF) processing. This sampling technique allows for the ability for samples to be reached at depths, which have not been able to be captured before, of approximately 1.5 m below the slag layer. These samples were also taken in conjunction with samples taken just under the slag layer as well as in between those samples. Additional samples were also taken during the processing including multi-point slag sampling. The heats were divided in to five key processing steps: Start of heat (S), after Alloying (A), after desulfurization/start of pre-Rinse (R), prior to Ca treatment (C), and End of heat (E). Sampling sets were collected to compare the effects of silicon, desulfurization rates, slag emulsification, slag evolution and inclusion evolution. By gaining the ability to gather multiple depths, it was determined that the slag emulsification has the ability to follow the flow pattern of the ladle deeper into the ladle than previously seen in literature. Inclusion evolution has been shown by numerous researchers; however, this study showed differences in the inclusion grouping and distribution at the different depths of the ladle through Automated Feature Analysis (AFA). Also, the inclusion path was seen to change depending on both the silicon content and the sulfur content of the steel. This method was applied to develop a desulfurization model at Nucor Steel Tuscaloosa, Inc. (NSTI). In addition to a desulfurization model, a calcium (Ca) model was also developed. The Ca model was applied to target a finished inclusion region based on the conditions up to the wire treatment. These conditions included time, silicon content, and sulfur concentration. Due to the inability of this model to handle every process variable, a new procedure was created to

  10. Assessment of Student Performance in a PSI College Physics Course Using Ausubel's Learning Theory as a Theoretical Framework for Content Organization.

    Science.gov (United States)

    Moriera, M. A.

    1979-01-01

    David Ausubel's learning theory was used as a framework for the content organization of an experimental Personalized System of Instruction (PSI) course in physics. Evaluation suggests that the combination of PSI as a method of instruction and Ausubel's theory for organization might result in better learning outcomes. (Author/JMD)

  11. An Efficient Ensemble Learning Method for Gene Microarray Classification

    Directory of Open Access Journals (Sweden)

    Alireza Osareh

    2013-01-01

    Full Text Available The gene microarray analysis and classification have demonstrated an effective way for the effective diagnosis of diseases and cancers. However, it has been also revealed that the basic classification techniques have intrinsic drawbacks in achieving accurate gene classification and cancer diagnosis. On the other hand, classifier ensembles have received increasing attention in various applications. Here, we address the gene classification issue using RotBoost ensemble methodology. This method is a combination of Rotation Forest and AdaBoost techniques which in turn preserve both desirable features of an ensemble architecture, that is, accuracy and diversity. To select a concise subset of informative genes, 5 different feature selection algorithms are considered. To assess the efficiency of the RotBoost, other nonensemble/ensemble techniques including Decision Trees, Support Vector Machines, Rotation Forest, AdaBoost, and Bagging are also deployed. Experimental results have revealed that the combination of the fast correlation-based feature selection method with ICA-based RotBoost ensemble is highly effective for gene classification. In fact, the proposed method can create ensemble classifiers which outperform not only the classifiers produced by the conventional machine learning but also the classifiers generated by two widely used conventional ensemble learning methods, that is, Bagging and AdaBoost.

  12. Theoretical Frameworks, Methods, and Procedures for Conducting Phenomenological Studies in Educational Settings

    Directory of Open Access Journals (Sweden)

    Pelin Yüksel

    2015-01-01

    Full Text Available The main purposes of phenomenological research are to seek reality from individuals’ narratives of their experiences and feelings, and to produce in-depth descriptions of the phenomenon. Phenomenological research studies in educational settings generally embody lived experience, perception, and feelings of participants about a phenomenon. This study aims to provide a general framework for researchers who are interested in phenomenological studies especially in educational setting. Additionally, the study provides a guide for researchers on how to conduct a phenomenological research and how to collect and analyze phenomenal data. The first part of the paper explains the underpinnings of the research methodology consisting of methodological framework and key phenomenological concepts. The second part provides guidance for a phenomenological research in education settings, focusing particularly on phenomenological data collection procedure and phenomenological data analysis methods.Keywords: Phenomenology, phenomenological inquiry, phenomenological data analysis Eğitim Ortamlarında Fenomenal Çalışmaları Yürütmek İçin Teorik Çerçeveler, Yöntemler ve ProsedürlerÖzFenomenolojik araştırmaların temel amacı, bireyin deneyimlerinden ve duygularından yola çıkarak belli bir fenomenan üzerinde yaptığı anlatılarında gerçeği aramak ve bu fenomenana yönelik derinlemesine açıklamalar üretmektir. Eğitim ortamlarında fenomenolojik araştırmalar genellikle araştırmaya katılanların belli bir fenomenan hakkında yaşantıları, deneyimleri, algıları ve duyguları somutlaştırmak için kullanılır. Bu çalışma, özellikle eğitim ortamlarında fenomenolojik çalışmalarla ilgilenen araştırmacılar için genel bir çerçeve sunmayı amaçlamaktadır. Ayrıca, çalışmada fenomenolojik araştırmalar için veri toplamak ve bu fenomenal verileri analiz yapmak için araştırmacılara yön gösterici bir k

  13. Theoretical study of the dependence of single impurity Anderson model on various parameters within distributional exact diagonalization method

    Science.gov (United States)

    Syaina, L. P.; Majidi, M. A.

    2018-04-01

    Single impurity Anderson model describes a system consisting of non-interacting conduction electrons coupled with a localized orbital having strongly interacting electrons at a particular site. This model has been proven successful to explain the phenomenon of metal-insulator transition through Anderson localization. Despite the well-understood behaviors of the model, little has been explored theoretically on how the model properties gradually evolve as functions of hybridization parameter, interaction energy, impurity concentration, and temperature. Here, we propose to do a theoretical study on those aspects of a single impurity Anderson model using the distributional exact diagonalization method. We solve the model Hamiltonian by randomly generating sampling distribution of some conducting electron energy levels with various number of occupying electrons. The resulting eigenvalues and eigenstates are then used to define the local single-particle Green function for each sampled electron energy distribution using Lehmann representation. Later, we extract the corresponding self-energy of each distribution, then average over all the distributions and construct the local Green function of the system to calculate the density of states. We repeat this procedure for various values of those controllable parameters, and discuss our results in connection with the criteria of the occurrence of metal-insulator transition in this system.

  14. Experimental and theoretical analysis of the rate of solvent equilibration in the hanging drop method of protein crystal growth

    Science.gov (United States)

    Fowlis, William W.; Delucas, Lawrence J.; Twigg, Pamela J.; Howard, Sandra B.; Meehan, Edward J.

    1988-01-01

    The principles of the hanging-drop method of crystal growth are discussed, and the rate of water evaporation in a water droplet (containing protein, buffer, and a precipitating agent) suspended above a well containing a double concentration of precipitating agent is investigated theoretically. It is shown that, on earth, the rate of evaporation may be determined from diffusion theory and the colligative properties of solutions. The parameters affecting the rate of evaporation include the temperature, the vapor pressure of water, the ionization constant of the salt, the volume of the drop, the contact angle between the droplet and the coverslip, the number of moles of salt in the droplet, the number of moles of water and salt in the well, the molar volumes of water and salt, the distance from the droplet to the well, and the coefficient of diffusion of water vapor through air. To test the theoretical equations, hanging-drop experiments were conducted using various reagent concentrations in 25-microliter droplets and measuring the evaporation times at 4 C and 25 C. The results showed good agreement with the theory.

  15. IP-MLI: An Independency of Learning Materials from Platforms in a Mobile Learning using Intelligent Method

    Directory of Open Access Journals (Sweden)

    Mohammed Abdallh Otair

    2006-06-01

    Full Text Available Attempting to deliver a monolithic mobile learning system is too inflexible in view of the heterogeneous mixture of hardware and services available and the desirability of facility blended approaches to learning delivery, and how to build learning materials to run on all platforms[1]. This paper proposes a framework of mobile learning system using an intelligent method (IP-MLI . A fuzzy matching method is used to find suitable learning material design. It will provide a best matching for each specific platform type for each learner. The main contribution of the proposed method is to use software layer to insulate learning materials from device-specific features. Consequently, many versions of learning materials can be designed to work on many platform types.

  16. Machine learning methods can replace 3D profile method in classification of amyloidogenic hexapeptides

    Directory of Open Access Journals (Sweden)

    Stanislawski Jerzy

    2013-01-01

    Full Text Available Abstract Background Amyloids are proteins capable of forming fibrils. Many of them underlie serious diseases, like Alzheimer disease. The number of amyloid-associated diseases is constantly increasing. Recent studies indicate that amyloidogenic properties can be associated with short segments of aminoacids, which transform the structure when exposed. A few hundreds of such peptides have been experimentally found. Experimental testing of all possible aminoacid combinations is currently not feasible. Instead, they can be predicted by computational methods. 3D profile is a physicochemical-based method that has generated the most numerous dataset - ZipperDB. However, it is computationally very demanding. Here, we show that dataset generation can be accelerated. Two methods to increase the classification efficiency of amyloidogenic candidates are presented and tested: simplified 3D profile generation and machine learning methods. Results We generated a new dataset of hexapeptides, using more economical 3D profile algorithm, which showed very good classification overlap with ZipperDB (93.5%. The new part of our dataset contains 1779 segments, with 204 classified as amyloidogenic. The dataset of 6-residue sequences with their binary classification, based on the energy of the segment, was applied for training machine learning methods. A separate set of sequences from ZipperDB was used as a test set. The most effective methods were Alternating Decision Tree and Multilayer Perceptron. Both methods obtained area under ROC curve of 0.96, accuracy 91%, true positive rate ca. 78%, and true negative rate 95%. A few other machine learning methods also achieved a good performance. The computational time was reduced from 18-20 CPU-hours (full 3D profile to 0.5 CPU-hours (simplified 3D profile to seconds (machine learning. Conclusions We showed that the simplified profile generation method does not introduce an error with regard to the original method, while

  17. Machine learning methods can replace 3D profile method in classification of amyloidogenic hexapeptides.

    Science.gov (United States)

    Stanislawski, Jerzy; Kotulska, Malgorzata; Unold, Olgierd

    2013-01-17

    Amyloids are proteins capable of forming fibrils. Many of them underlie serious diseases, like Alzheimer disease. The number of amyloid-associated diseases is constantly increasing. Recent studies indicate that amyloidogenic properties can be associated with short segments of aminoacids, which transform the structure when exposed. A few hundreds of such peptides have been experimentally found. Experimental testing of all possible aminoacid combinations is currently not feasible. Instead, they can be predicted by computational methods. 3D profile is a physicochemical-based method that has generated the most numerous dataset - ZipperDB. However, it is computationally very demanding. Here, we show that dataset generation can be accelerated. Two methods to increase the classification efficiency of amyloidogenic candidates are presented and tested: simplified 3D profile generation and machine learning methods. We generated a new dataset of hexapeptides, using more economical 3D profile algorithm, which showed very good classification overlap with ZipperDB (93.5%). The new part of our dataset contains 1779 segments, with 204 classified as amyloidogenic. The dataset of 6-residue sequences with their binary classification, based on the energy of the segment, was applied for training machine learning methods. A separate set of sequences from ZipperDB was used as a test set. The most effective methods were Alternating Decision Tree and Multilayer Perceptron. Both methods obtained area under ROC curve of 0.96, accuracy 91%, true positive rate ca. 78%, and true negative rate 95%. A few other machine learning methods also achieved a good performance. The computational time was reduced from 18-20 CPU-hours (full 3D profile) to 0.5 CPU-hours (simplified 3D profile) to seconds (machine learning). We showed that the simplified profile generation method does not introduce an error with regard to the original method, while increasing the computational efficiency. Our new dataset

  18. Improving Nursing Students' Learning Outcomes in Fundamentals of Nursing Course through Combination of Traditional and e-Learning Methods.

    Science.gov (United States)

    Sheikhaboumasoudi, Rouhollah; Bagheri, Maryam; Hosseini, Sayed Abbas; Ashouri, Elaheh; Elahi, Nasrin

    2018-01-01

    Fundamentals of nursing course are prerequisite to providing comprehensive nursing care. Despite development of technology on nursing education, effectiveness of using e-learning methods in fundamentals of nursing course is unclear in clinical skills laboratory for nursing students. The aim of this study was to compare the effect of blended learning (combining e-learning with traditional learning methods) with traditional learning alone on nursing students' scores. A two-group post-test experimental study was administered from February 2014 to February 2015. Two groups of nursing students who were taking the fundamentals of nursing course in Iran were compared. Sixty nursing students were selected as control group (just traditional learning methods) and experimental group (combining e-learning with traditional learning methods) for two consecutive semesters. Both groups participated in Objective Structured Clinical Examination (OSCE) and were evaluated in the same way using a prepared checklist and questionnaire of satisfaction. Statistical analysis was conducted through SPSS software version 16. Findings of this study reflected that mean of midterm (t = 2.00, p = 0.04) and final score (t = 2.50, p = 0.01) of the intervention group (combining e-learning with traditional learning methods) were significantly higher than the control group (traditional learning methods). The satisfaction of male students in intervention group was higher than in females (t = 2.60, p = 0.01). Based on the findings, this study suggests that the use of combining traditional learning methods with e-learning methods such as applying educational website and interactive online resources for fundamentals of nursing course instruction can be an effective supplement for improving nursing students' clinical skills.

  19. Theoretical Physics 1. Theoretical Mechanics

    International Nuclear Information System (INIS)

    Dreizler, Reiner M.; Luedde, Cora S.

    2010-01-01

    After an introduction to basic concepts of mechanics more advanced topics build the major part of this book. Interspersed is a discussion of selected problems of motion. This is followed by a concise treatment of the Lagrangian and the Hamiltonian formulation of mechanics, as well as a brief excursion on chaotic motion. The last chapter deals with applications of the Lagrangian formulation to specific systems (coupled oscillators, rotating coordinate systems, rigid bodies). The level of this textbook is advanced undergraduate. The authors combine teaching experience of more than 40 years in all fields of Theoretical Physics and related mathematical disciplines and thorough knowledge in creating advanced eLearning content. The text is accompanied by an extensive collection of online material, in which the possibilities of the electronic medium are fully exploited, e.g. in the form of applets, 2D- and 3D-animations. (orig.)

  20. Theoretical Physics 1. Theoretical Mechanics

    Energy Technology Data Exchange (ETDEWEB)

    Dreizler, Reiner M.; Luedde, Cora S. [Frankfurt Univ. (Germany). Inst. fuer Theoretische Physik

    2010-07-01

    After an introduction to basic concepts of mechanics more advanced topics build the major part of this book. Interspersed is a discussion of selected problems of motion. This is followed by a concise treatment of the Lagrangian and the Hamiltonian formulation of mechanics, as well as a brief excursion on chaotic motion. The last chapter deals with applications of the Lagrangian formulation to specific systems (coupled oscillators, rotating coordinate systems, rigid bodies). The level of this textbook is advanced undergraduate. The authors combine teaching experience of more than 40 years in all fields of Theoretical Physics and related mathematical disciplines and thorough knowledge in creating advanced eLearning content. The text is accompanied by an extensive collection of online material, in which the possibilities of the electronic medium are fully exploited, e.g. in the form of applets, 2D- and 3D-animations. (orig.)

  1. Best practices for learning physiology: combining classroom and online methods.

    Science.gov (United States)

    Anderson, Lisa C; Krichbaum, Kathleen E

    2017-09-01

    Physiology is a requisite course for many professional allied health programs and is a foundational science for learning pathophysiology, health assessment, and pharmacology. Given the demand for online learning in the health sciences, it is important to evaluate the efficacy of online and in-class teaching methods, especially as they are combined to form hybrid courses. The purpose of this study was to compare two hybrid physiology sections in which one section was offered mostly in-class (85% in-class), and the other section was offered mostly online (85% online). The two sections in 2 yr ( year 1 and year 2 ) were compared in terms of knowledge of physiology measured in exam scores and pretest-posttest improvement, and in measures of student satisfaction with teaching. In year 1 , there were some differences on individual exam scores between the two sections, but no significant differences in mean exam scores or in pretest-posttest improvements. However, in terms of student satisfaction, the mostly in-class students in year 1 rated the instructor significantly higher than did the mostly online students. Comparisons between in-class and online students in the year 2 cohort yielded data that showed that mean exam scores were not statistically different, but pre-post changes were significantly greater in the mostly online section; student satisfaction among mostly online students also improved significantly. Education researchers must investigate effective combinations of in-class and online methods for student learning outcomes, while maintaining the flexibility and convenience that online methods provide. Copyright © 2017 the American Physiological Society.

  2. MACHINE LEARNING METHODS IN DIGITAL AGRICULTURE: ALGORITHMS AND CASES

    Directory of Open Access Journals (Sweden)

    Aleksandr Vasilyevich Koshkarov

    2018-05-01

    Full Text Available Ensuring food security is a major challenge in many countries. With a growing global population, the issues of improving the efficiency of agriculture have become most relevant. Farmers are looking for new ways to increase yields, and governments of different countries are developing new programs to support agriculture. This contributes to a more active implementation of digital technologies in agriculture, helping farmers to make better decisions, increase yields and take care of the environment. The central point is the collection and analysis of data. In the industry of agriculture, data can be collected from different sources and may contain useful patterns that identify potential problems or opportunities. Data should be analyzed using machine learning algorithms to extract useful insights. Such methods of precision farming allow the farmer to monitor individual parts of the field, optimize the consumption of water and chemicals, and identify problems quickly. Purpose: to make an overview of the machine learning algorithms used for data analysis in agriculture. Methodology: an overview of the relevant literature; a survey of farmers. Results: relevant algorithms of machine learning for the analysis of data in agriculture at various levels were identified: soil analysis (soil assessment, soil classification, soil fertility predictions, weather forecast (simulation of climate change, temperature and precipitation prediction, and analysis of vegetation (weed identification, vegetation classification, plant disease identification, crop forecasting. Practical implications: agriculture, crop production.

  3. Estimating building energy consumption using extreme learning machine method

    International Nuclear Information System (INIS)

    Naji, Sareh; Keivani, Afram; Shamshirband, Shahaboddin; Alengaram, U. Johnson; Jumaat, Mohd Zamin; Mansor, Zulkefli; Lee, Malrey

    2016-01-01

    The current energy requirements of buildings comprise a large percentage of the total energy consumed around the world. The demand of energy, as well as the construction materials used in buildings, are becoming increasingly problematic for the earth's sustainable future, and thus have led to alarming concern. The energy efficiency of buildings can be improved, and in order to do so, their operational energy usage should be estimated early in the design phase, so that buildings are as sustainable as possible. An early energy estimate can greatly help architects and engineers create sustainable structures. This study proposes a novel method to estimate building energy consumption based on the ELM (Extreme Learning Machine) method. This method is applied to building material thicknesses and their thermal insulation capability (K-value). For this purpose up to 180 simulations are carried out for different material thicknesses and insulation properties, using the EnergyPlus software application. The estimation and prediction obtained by the ELM model are compared with GP (genetic programming) and ANNs (artificial neural network) models for accuracy. The simulation results indicate that an improvement in predictive accuracy is achievable with the ELM approach in comparison with GP and ANN. - Highlights: • Buildings consume huge amounts of energy for operation. • Envelope materials and insulation influence building energy consumption. • Extreme learning machine is used to estimate energy usage of a sample building. • The key effective factors in this study are insulation thickness and K-value.

  4. Evaluation Methods on Usability of M-Learning Environments

    Directory of Open Access Journals (Sweden)

    Teresa Magal-Royo

    2007-10-01

    Full Text Available Nowadays there are different evaluation methods focused in the assessment of the usability of telematic methods. The assessment of 3rd generation web environments evaluates the effectiveness and usability of application with regard to the user needs. Wireless usability and, specifically in mobile phones, is concentrated in the validation of the features and tools management using conventional interactive environments. There is not a specific and suitable criterion to evaluate created environments and m-learning platforms, where the restricted and sequential representation is a fundamental aspect to be considered.The present paper exposes the importance of the conventional usability methods to verify both: the employed contents in wireless formats, and the possible interfaces from the conception phases, to the validations of the platform with such characteristics.The development of usability adapted inspection could be complemented with the Remote’s techniques of usability testing, which are being carried out these days in the mobile devices field and which pointed out the need to apply common criteria in the validation of non-located learning scenarios.

  5. A Preliminary Survey of the Preferred Learning Methods for Interpretation Students

    Science.gov (United States)

    Heinz, Michael

    2013-01-01

    There are many different methods that individuals use to learn languages like reading books or writing essays. Not all methods are equally successful for second language learners but nor do all successful learners of a second language show identical preferences for learning methods. Additionally, at the highest level of language learning various…

  6. Characterizing Engineering Learners' Preferences for Active and Passive Learning Methods

    Science.gov (United States)

    Magana, Alejandra J.; Vieira, Camilo; Boutin, Mireille

    2018-01-01

    This paper studies electrical engineering learners' preferences for learning methods with various degrees of activity. Less active learning methods such as homework and peer reviews are investigated, as well as a newly introduced very active (constructive) learning method called "slectures," and some others. The results suggest that…

  7. Comparisons of likelihood and machine learning methods of individual classification

    Science.gov (United States)

    Guinand, B.; Topchy, A.; Page, K.S.; Burnham-Curtis, M. K.; Punch, W.F.; Scribner, K.T.

    2002-01-01

    Classification methods used in machine learning (e.g., artificial neural networks, decision trees, and k-nearest neighbor clustering) are rarely used with population genetic data. We compare different nonparametric machine learning techniques with parametric likelihood estimations commonly employed in population genetics for purposes of assigning individuals to their population of origin (“assignment tests”). Classifier accuracy was compared across simulated data sets representing different levels of population differentiation (low and high FST), number of loci surveyed (5 and 10), and allelic diversity (average of three or eight alleles per locus). Empirical data for the lake trout (Salvelinus namaycush) exhibiting levels of population differentiation comparable to those used in simulations were examined to further evaluate and compare classification methods. Classification error rates associated with artificial neural networks and likelihood estimators were lower for simulated data sets compared to k-nearest neighbor and decision tree classifiers over the entire range of parameters considered. Artificial neural networks only marginally outperformed the likelihood method for simulated data (0–2.8% lower error rates). The relative performance of each machine learning classifier improved relative likelihood estimators for empirical data sets, suggesting an ability to “learn” and utilize properties of empirical genotypic arrays intrinsic to each population. Likelihood-based estimation methods provide a more accessible option for reliable assignment of individuals to the population of origin due to the intricacies in development and evaluation of artificial neural networks. In recent years, characterization of highly polymorphic molecular markers such as mini- and microsatellites and development of novel methods of analysis have enabled researchers to extend investigations of ecological and evolutionary processes below the population level to the level of

  8. Advanced methods in NDE using machine learning approaches

    Science.gov (United States)

    Wunderlich, Christian; Tschöpe, Constanze; Duckhorn, Frank

    2018-04-01

    Machine learning (ML) methods and algorithms have been applied recently with great success in quality control and predictive maintenance. Its goal to build new and/or leverage existing algorithms to learn from training data and give accurate predictions, or to find patterns, particularly with new and unseen similar data, fits perfectly to Non-Destructive Evaluation. The advantages of ML in NDE are obvious in such tasks as pattern recognition in acoustic signals or automated processing of images from X-ray, Ultrasonics or optical methods. Fraunhofer IKTS is using machine learning algorithms in acoustic signal analysis. The approach had been applied to such a variety of tasks in quality assessment. The principal approach is based on acoustic signal processing with a primary and secondary analysis step followed by a cognitive system to create model data. Already in the second analysis steps unsupervised learning algorithms as principal component analysis are used to simplify data structures. In the cognitive part of the software further unsupervised and supervised learning algorithms will be trained. Later the sensor signals from unknown samples can be recognized and classified automatically by the algorithms trained before. Recently the IKTS team was able to transfer the software for signal processing and pattern recognition to a small printed circuit board (PCB). Still, algorithms will be trained on an ordinary PC; however, trained algorithms run on the Digital Signal Processor and the FPGA chip. The identical approach will be used for pattern recognition in image analysis of OCT pictures. Some key requirements have to be fulfilled, however. A sufficiently large set of training data, a high signal-to-noise ratio, and an optimized and exact fixation of components are required. The automated testing can be done subsequently by the machine. By integrating the test data of many components along the value chain further optimization including lifetime and durability

  9. Critical learning episodes in the evolution of Brazilian business start-ups: a theoretical and analytical tool

    NARCIS (Netherlands)

    A.A. Corradi (Ariane Agnes)

    2013-01-01

    textabstractThis study investigates critical learning episodes as landmarks in the evolution of business start-ups. A framework that combines individual learning processes with the Penrosian resource-based theory of the firm, and the concepts of search and routines from evolutionary economics

  10. The experimental field work as practical learning method

    Directory of Open Access Journals (Sweden)

    Nicolás Fernández Losa

    2014-11-01

    Full Text Available This paper describes a teaching experience about experimental field work as practical learning method implemented in the subject of Organizational Behaviour. With this teaching experience we pretend to change the practical training, as well as in its evaluation process, in order to favour the development of transversal skills of students. For this purpose, the use of a practice plan, tackled through an experimental field work and carried out with the collaboration of a business organization within a work team (as organic unity of learning, arises as an alternative to the traditional method of practical teachings and allows the approach of business reality into the classroom, as well as actively promote the use of transversal skills. In particular, we develop the experience in three phases. Initially, the students, after forming a working group and define a field work project, should get the collaboration of a nearby business organization in which to obtain data on one or more functional areas of organizational behaviour. Subsequently, students carry out the field work with the realization of the scheduled visits and elaboration of a memory to establish a diagnosis of the strategy followed by the company in these functional areas in order to propose and justify alternative actions that improve existing ones. Finally, teachers assess the different field work memories and their public presentations according to evaluation rubrics, which try to objectify and unify to the maximum the evaluation criteria and serve to guide the learning process of students. The results of implementation of this teaching experience, measured through a Likert questionnaire, are very satisfactory for students.

  11. Application of blended learning in teaching statistical methods

    Directory of Open Access Journals (Sweden)

    Barbara Dębska

    2012-12-01

    Full Text Available The paper presents the application of a hybrid method (blended learning - linking traditional education with on-line education to teach selected problems of mathematical statistics. This includes the teaching of the application of mathematical statistics to evaluate laboratory experimental results. An on-line statistics course was developed to form an integral part of the module ‘methods of statistical evaluation of experimental results’. The course complies with the principles outlined in the Polish National Framework of Qualifications with respect to the scope of knowledge, skills and competencies that students should have acquired at course completion. The paper presents the structure of the course and the educational content provided through multimedia lessons made accessible on the Moodle platform. Following courses which used the traditional method of teaching and courses which used the hybrid method of teaching, students test results were compared and discussed to evaluate the effectiveness of the hybrid method of teaching when compared to the effectiveness of the traditional method of teaching.

  12. The Open Method of Co-ordination and the Analysis of Mutual Learning Processes of the European Employment Strategy

    DEFF Research Database (Denmark)

    Nedergaard, Peter

    The purpose of this paper is solely to address two interlinked methodological and theoretical questions concerning the Open Method of Coordination (OMC), using the European Employment Strategy as a case: First, what is the most appropriate approach to learning in the analyses of the processes...... of the European Employment Strategy (EES)? Second, how is mutual learning processes diffused among the Member States? In answering these two questions the paper draws on a social constructivist approach to learning thereby contributing to the debate about learning in the political science literature. At the same...... time, based on this concept of learning, it is concluded that the learning effects of the EES are probably somewhat larger than what is normally suggested, but that successful diffusion still depends on a variety of contextual factors....

  13. Methods of Efficient Study Habits and Physics Learning

    Science.gov (United States)

    Zettili, Nouredine

    2010-02-01

    We want to discuss the methods of efficient study habits and how they can be used by students to help them improve learning physics. In particular, we deal with the most efficient techniques needed to help students improve their study skills. We focus on topics such as the skills of how to develop long term memory, how to improve concentration power, how to take class notes, how to prepare for and take exams, how to study scientific subjects such as physics. We argue that the students who conscientiously use the methods of efficient study habits achieve higher results than those students who do not; moreover, a student equipped with the proper study skills will spend much less time to learn a subject than a student who has no good study habits. The underlying issue here is not the quantity of time allocated to the study efforts by the students, but the efficiency and quality of actions so that the student can function at peak efficiency. These ideas were developed as part of Project IMPACTSEED (IMproving Physics And Chemistry Teaching in SEcondary Education), an outreach grant funded by the Alabama Commission on Higher Education. This project is motivated by a major pressing local need: A large number of high school physics teachers teach out of field. )

  14. A Photometric Machine-Learning Method to Infer Stellar Metallicity

    Science.gov (United States)

    Miller, Adam A.

    2015-01-01

    Following its formation, a star's metal content is one of the few factors that can significantly alter its evolution. Measurements of stellar metallicity ([Fe/H]) typically require a spectrum, but spectroscopic surveys are limited to a few x 10(exp 6) targets; photometric surveys, on the other hand, have detected > 10(exp 9) stars. I present a new machine-learning method to predict [Fe/H] from photometric colors measured by the Sloan Digital Sky Survey (SDSS). The training set consists of approx. 120,000 stars with SDSS photometry and reliable [Fe/H] measurements from the SEGUE Stellar Parameters Pipeline (SSPP). For bright stars (g' < or = 18 mag), with 4500 K < or = Teff < or = 7000 K, corresponding to those with the most reliable SSPP estimates, I find that the model predicts [Fe/H] values with a root-mean-squared-error (RMSE) of approx.0.27 dex. The RMSE from this machine-learning method is similar to the scatter in [Fe/H] measurements from low-resolution spectra..

  15. Multiple instance learning tracking method with local sparse representation

    KAUST Repository

    Xie, Chengjun

    2013-10-01

    When objects undergo large pose change, illumination variation or partial occlusion, most existed visual tracking algorithms tend to drift away from targets and even fail in tracking them. To address this issue, in this study, the authors propose an online algorithm by combining multiple instance learning (MIL) and local sparse representation for tracking an object in a video system. The key idea in our method is to model the appearance of an object by local sparse codes that can be formed as training data for the MIL framework. First, local image patches of a target object are represented as sparse codes with an overcomplete dictionary, where the adaptive representation can be helpful in overcoming partial occlusion in object tracking. Then MIL learns the sparse codes by a classifier to discriminate the target from the background. Finally, results from the trained classifier are input into a particle filter framework to sequentially estimate the target state over time in visual tracking. In addition, to decrease the visual drift because of the accumulative errors when updating the dictionary and classifier, a two-step object tracking method combining a static MIL classifier with a dynamical MIL classifier is proposed. Experiments on some publicly available benchmarks of video sequences show that our proposed tracker is more robust and effective than others. © The Institution of Engineering and Technology 2013.

  16. Using M-learning as a Means to Promote Self-direction and Engagement in Apprenticeship Theoretical Lessons

    Directory of Open Access Journals (Sweden)

    Alan O'Donnell

    2014-06-01

    Full Text Available An exploratory case study was carried out to investigate if the use of mobile phones as a tool for learning could address concerns over the current learning of the carpentry and joinery apprentices in the Dublin Institute of Technology. The concerns are regarding a lack of learner self-direction and engagement with the learning content. A high level of mobile phone usage was apparent among the apprentice cohort. It was decided to take advantage of the potential learning opportunity offered by mobile technologies to promote the learning and engagement of the apprentices. Towards this goal, a compatible resource was developed, hosting presentations, course content, videos and questions. This study explored the views of the learners in the carpentry and joinery trade apprenticeship and their attitudes towards developing an m-learning resource. The aim of the research was to explore if this m-learning resource encouraged self-direction and engagement. Further objectives of this study were to establish a start point for further research projects and resource development.

  17. Exploring Instructional Strategies and Learning Theoretical Foundations of eHealth and mHealth Education Interventions.

    Science.gov (United States)

    Tamim, Suha R; Grant, Michael M

    2016-05-19

    This qualitative study aimed at exploring how health professionals use theories and models from the field of education to create ehealth and mhealth education interventions in an effort to provide insights for future research and practice on the development and implementation of health promotion initiatives. A purposeful sample of 12 participants was selected, using criterion and snowballing sampling strategies. Data were collected and analyzed from semistructured interviews, planning materials, and artifacts. The findings revealed that none of the participants used a specific learning theory or an instructional model in their interventions. However, based on participants' description, three themes emerged: (1) connections to behaviorist approaches to learning, (2) connections to cognitivist approaches to learning, and (3) connections to constructivist approaches to learning. Suggested implications for practice are (1) the design of a guidebook on the interplay of learning theories, instructional models, and health education and (2) the establishment of communities of practice. Further research can (1) investigate how learning theories and models intertwine with health behavior theories and models, (2) evaluate how the different instructional strategies presented in this study affect learning outcomes and health behavior change processes, and (3) investigate factors behind the instructional strategies choices made by health professionals. © 2016 Society for Public Health Education.

  18. Deep Learning Methods for Improved Decoding of Linear Codes

    Science.gov (United States)

    Nachmani, Eliya; Marciano, Elad; Lugosch, Loren; Gross, Warren J.; Burshtein, David; Be'ery, Yair

    2018-02-01

    The problem of low complexity, close to optimal, channel decoding of linear codes with short to moderate block length is considered. It is shown that deep learning methods can be used to improve a standard belief propagation decoder, despite the large example space. Similar improvements are obtained for the min-sum algorithm. It is also shown that tying the parameters of the decoders across iterations, so as to form a recurrent neural network architecture, can be implemented with comparable results. The advantage is that significantly less parameters are required. We also introduce a recurrent neural decoder architecture based on the method of successive relaxation. Improvements over standard belief propagation are also observed on sparser Tanner graph representations of the codes. Furthermore, we demonstrate that the neural belief propagation decoder can be used to improve the performance, or alternatively reduce the computational complexity, of a close to optimal decoder of short BCH codes.

  19. Machine learning methods for clinical forms analysis in mental health.

    Science.gov (United States)

    Strauss, John; Peguero, Arturo Martinez; Hirst, Graeme

    2013-01-01

    In preparation for a clinical information system implementation, the Centre for Addiction and Mental Health (CAMH) Clinical Information Transformation project completed multiple preparation steps. An automated process was desired to supplement the onerous task of manual analysis of clinical forms. We used natural language processing (NLP) and machine learning (ML) methods for a series of 266 separate clinical forms. For the investigation, documents were represented by feature vectors. We used four ML algorithms for our examination of the forms: cluster analysis, k-nearest neigh-bours (kNN), decision trees and support vector machines (SVM). Parameters for each algorithm were optimized. SVM had the best performance with a precision of 64.6%. Though we did not find any method sufficiently accurate for practical use, to our knowledge this approach to forms has not been used previously in mental health.

  20. Statistical learning modeling method for space debris photometric measurement

    Science.gov (United States)

    Sun, Wenjing; Sun, Jinqiu; Zhang, Yanning; Li, Haisen

    2016-03-01

    Photometric measurement is an important way to identify the space debris, but the present methods of photometric measurement have many constraints on star image and need complex image processing. Aiming at the problems, a statistical learning modeling method for space debris photometric measurement is proposed based on the global consistency of the star image, and the statistical information of star images is used to eliminate the measurement noises. First, the known stars on the star image are divided into training stars and testing stars. Then, the training stars are selected as the least squares fitting parameters to construct the photometric measurement model, and the testing stars are used to calculate the measurement accuracy of the photometric measurement model. Experimental results show that, the accuracy of the proposed photometric measurement model is about 0.1 magnitudes.

  1. A Learning-Based Steganalytic Method against LSB Matching Steganography

    Directory of Open Access Journals (Sweden)

    Z. Xia

    2011-04-01

    Full Text Available This paper considers the detection of spatial domain least significant bit (LSB matching steganography in gray images. Natural images hold some inherent properties, such as histogram, dependence between neighboring pixels, and dependence among pixels that are not adjacent to each other. These properties are likely to be disturbed by LSB matching. Firstly, histogram will become smoother after LSB matching. Secondly, the two kinds of dependence will be weakened by the message embedding. Accordingly, three features, which are respectively based on image histogram, neighborhood degree histogram and run-length histogram, are extracted at first. Then, support vector machine is utilized to learn and discriminate the difference of features between cover and stego images. Experimental results prove that the proposed method possesses reliable detection ability and outperforms the two previous state-of-the-art methods. Further more, the conclusions are drawn by analyzing the individual performance of three features and their fused feature.

  2. Relabeling exchange method (REM) for learning in neural networks

    Science.gov (United States)

    Wu, Wen; Mammone, Richard J.

    1994-02-01

    The supervised training of neural networks require the use of output labels which are usually arbitrarily assigned. In this paper it is shown that there is a significant difference in the rms error of learning when `optimal' label assignment schemes are used. We have investigated two efficient random search algorithms to solve the relabeling problem: the simulated annealing and the genetic algorithm. However, we found them to be computationally expensive. Therefore we shall introduce a new heuristic algorithm called the Relabeling Exchange Method (REM) which is computationally more attractive and produces optimal performance. REM has been used to organize the optimal structure for multi-layered perceptrons and neural tree networks. The method is a general one and can be implemented as a modification to standard training algorithms. The motivation of the new relabeling strategy is based on the present interpretation of dyslexia as an encoding problem.

  3. Automatic Detection of Acromegaly From Facial Photographs Using Machine Learning Methods.

    Science.gov (United States)

    Kong, Xiangyi; Gong, Shun; Su, Lijuan; Howard, Newton; Kong, Yanguo

    2018-01-01

    Automatic early detection of acromegaly is theoretically possible from facial photographs, which can lessen the prevalence and increase the cure probability. In this study, several popular machine learning algorithms were used to train a retrospective development dataset consisting of 527 acromegaly patients and 596 normal subjects. We firstly used OpenCV to detect the face bounding rectangle box, and then cropped and resized it to the same pixel dimensions. From the detected faces, locations of facial landmarks which were the potential clinical indicators were extracted. Frontalization was then adopted to synthesize frontal facing views to improve the performance. Several popular machine learning methods including LM, KNN, SVM, RT, CNN, and EM were used to automatically identify acromegaly from the detected facial photographs, extracted facial landmarks, and synthesized frontal faces. The trained models were evaluated using a separate dataset, of which half were diagnosed as acromegaly by growth hormone suppression test. The best result of our proposed methods showed a PPV of 96%, a NPV of 95%, a sensitivity of 96% and a specificity of 96%. Artificial intelligence can automatically early detect acromegaly with a high sensitivity and specificity. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  4. Incorporating Meaningful Gamification in a Blended Learning Research Methods Class: Examining Student Learning, Engagement, and Affective Outcomes

    Science.gov (United States)

    Tan, Meng; Hew, Khe Foon

    2016-01-01

    In this study, we investigated how the use of meaningful gamification affects student learning, engagement, and affective outcomes in a short, 3-day blended learning research methods class using a combination of experimental and qualitative research methods. Twenty-two postgraduates were randomly split into two groups taught by the same…

  5. Prediction of Student Dropout in E-Learning Program Through the Use of Machine Learning Method

    Directory of Open Access Journals (Sweden)

    Mingjie Tan

    2015-02-01

    Full Text Available The high rate of dropout is a serious problem in E-learning program. Thus it has received extensive concern from the education administrators and researchers. Predicting the potential dropout students is a workable solution to prevent dropout. Based on the analysis of related literature, this study selected student’s personal characteristic and academic performance as input attributions. Prediction models were developed using Artificial Neural Network (ANN, Decision Tree (DT and Bayesian Networks (BNs. A large sample of 62375 students was utilized in the procedures of model training and testing. The results of each model were presented in confusion matrix, and analyzed by calculating the rates of accuracy, precision, recall, and F-measure. The results suggested all of the three machine learning methods were effective in student dropout prediction, and DT presented a better performance. Finally, some suggestions were made for considerable future research.

  6. A Simple Deep Learning Method for Neuronal Spike Sorting

    Science.gov (United States)

    Yang, Kai; Wu, Haifeng; Zeng, Yu

    2017-10-01

    Spike sorting is one of key technique to understand brain activity. With the development of modern electrophysiology technology, some recent multi-electrode technologies have been able to record the activity of thousands of neuronal spikes simultaneously. The spike sorting in this case will increase the computational complexity of conventional sorting algorithms. In this paper, we will focus spike sorting on how to reduce the complexity, and introduce a deep learning algorithm, principal component analysis network (PCANet) to spike sorting. The introduced method starts from a conventional model and establish a Toeplitz matrix. Through the column vectors in the matrix, we trains a PCANet, where some eigenvalue vectors of spikes could be extracted. Finally, support vector machine (SVM) is used to sort spikes. In experiments, we choose two groups of simulated data from public databases availably and compare this introduced method with conventional methods. The results indicate that the introduced method indeed has lower complexity with the same sorting errors as the conventional methods.

  7. PYRAMID METHOD OF DISTANCE LEARNING IN HIGER EDUCATION

    Directory of Open Access Journals (Sweden)

    Дмитрий Васильевич Сенашенко

    2017-12-01

    Full Text Available The article deals with modern methods of distance learning in the corporate sector. On the specifics of the application of the described methods is their classification and be subject to review their specific differences based on the features and applications of these techniques given the characteristics of the organization of teaching in higher education, a conclusion about their preferred sides, which can be used in distance education. Later in the article, taking into account the above factors, it is proposed an innovative method of formation of educational programs. In view of the similarity of the rendered appearance of the pyramids, this technique proposed name “pyramid”. Offered by the authors, this technique is best synthesis of the best features of the previously described in the article for the online teaching methods. In the future, we are given a detailed description and conducted a preliminary analysis of the applicability of this technique to the training process in the Russian Federation. The analysis describes the eight alleged authors of distance education problems of high school that this method can help to solve.

  8. Prediction of stress- and strain-based forming limits of automotive thin sheets by numerical, theoretical and experimental methods

    Science.gov (United States)

    Béres, Gábor; Weltsch, Zoltán; Lukács, Zsolt; Tisza, Miklós

    2018-05-01

    Forming limit is a complex concept of limit values related to the onset of local necking in the sheet metal. In cold sheet metal forming, major and minor limit strains are influenced by the sheet thickness, strain path (deformation history) as well as material parameters and microstructure. Forming Limit Curves are plotted in ɛ1 - ɛ2 coordinate system providing the classic strain-based Forming Limit Diagram (FLD). Using the appropriate constitutive model, the limit strains can be changed into the stress-based Forming Limit Diagram (SFLD), irrespective of the strain path. This study is about the effect of the hardening model parameters on defining of limit stress values during Nakazima tests for automotive dual phase (DP) steels. Five limit strain pairs were specified experimentally with the loading of five different sheet geometries, which performed different strain-paths from pure shear (-2ɛ2=ɛ1) up to biaxial stretching (ɛ2=ɛ1). The former works of Hill, Levy-Tyne and Keeler-Brazier made possible some kind of theoretical strain determination, too. This was followed by the stress calculation based on the experimental and theoretical strain data. Since the n exponent in the Nádai expression is varying with the strain at some DP steels, we applied the least-squares method to fit other hardening model parameters (Ludwik, Voce, Hockett-Sherby) to calculate the stress fields belonging to each limit strains. The results showed that each model parameters could produce some discrepancies between the limit stress states in the range of higher equivalent strains than uniaxial stretching. The calculated hardening models were imported to FE code to extend and validate the results by numerical simulations.

  9. Learning Specific Content in Technology Education: Learning Study as a Collaborative Method in Swedish Preschool Class Using Hands-On Material

    Science.gov (United States)

    Kilbrink, Nina; Bjurulf, Veronica; Blomberg, Ingela; Heidkamp, Anja; Hollsten, Ann-Christin

    2014-01-01

    This article describes the process of a learning study conducted in technology education in a Swedish preschool class. The learning study method used in this study is a collaborative method, where researchers and teachers work together as a team concerning teaching and learning about a specific learning object. The object of learning in this study…

  10. English Language Learning in the Malaysian School Setting: Where Can We Find 10,000 Hours? A Theoretical Perspective

    Directory of Open Access Journals (Sweden)

    George Iber

    2016-08-01

    Full Text Available In these days of standardized assessments in education  that seek to measure the rate of learning in all subject matters, the question is seldom asked, “Just how long does it take to become proficient?” No matter the subject, we all agree that some amount of practice is necessary for basic proficiency and that more will be needed to really master a skill or subject area.  But how much is difficult to say because different individuals come to the task with different levels of motivation and opportunity to learn.  In the case of learning a second or foreign language different theories predict that a two to five year “structured exposure” is needed for either a basic communication or an academic level of proficiency (Cummins, 1980 respectively. This paper proposes that the range can be described in terms of hours. Based on the concept from Outliers by Gladwell (2008, this paper proposes that 10,000 hours is the target “time-on-task” required for academic proficiency in second language learning.  The implications for school language study is readily apparent. If we want academically proficient second language speakers, those individuals will need to have access to the target language in numbers vastly greater than school can provide in its standard curriculum. Keywords:  Second language learning, curriculum development, foreign language learning, time-on-task, international education, exchange programs, English as a foreign language 1. Introduction

  11. A direct vulnerable atherosclerotic plaque elasticity reconstruction method based on an original material-finite element formulation: theoretical framework

    Science.gov (United States)

    Bouvier, Adeline; Deleaval, Flavien; Doyley, Marvin M.; Yazdani, Saami K.; Finet, Gérard; Le Floc'h, Simon; Cloutier, Guy; Pettigrew, Roderic I.; Ohayon, Jacques

    2013-12-01

    The peak cap stress (PCS) amplitude is recognized as a biomechanical predictor of vulnerable plaque (VP) rupture. However, quantifying PCS in vivo remains a challenge since the stress depends on the plaque mechanical properties. In response, an iterative material finite element (FE) elasticity reconstruction method using strain measurements has been implemented for the solution of these inverse problems. Although this approach could resolve the mechanical characterization of VPs, it suffers from major limitations since (i) it is not adapted to characterize VPs exhibiting high material discontinuities between inclusions, and (ii) does not permit real time elasticity reconstruction for clinical use. The present theoretical study was therefore designed to develop a direct material-FE algorithm for elasticity reconstruction problems which accounts for material heterogeneities. We originally modified and adapted the extended FE method (Xfem), used mainly in crack analysis, to model material heterogeneities. This new algorithm was successfully applied to six coronary lesions of patients imaged in vivo with intravascular ultrasound. The results demonstrated that the mean relative absolute errors of the reconstructed Young's moduli obtained for the arterial wall, fibrosis, necrotic core, and calcified regions of the VPs decreased from 95.3±15.56%, 98.85±72.42%, 103.29±111.86% and 95.3±10.49%, respectively, to values smaller than 2.6 × 10-8±5.7 × 10-8% (i.e. close to the exact solutions) when including modified-Xfem method into our direct elasticity reconstruction method.

  12. Internet-based versus traditional teaching and learning methods.

    Science.gov (United States)

    Guarino, Salvatore; Leopardi, Eleonora; Sorrenti, Salvatore; De Antoni, Enrico; Catania, Antonio; Alagaratnam, Swethan

    2014-10-01

    The rapid and dramatic incursion of the Internet and social networks in everyday life has revolutionised the methods of exchanging data. Web 2.0 represents the evolution of the Internet as we know it. Internet users are no longer passive receivers, and actively participate in the delivery of information. Medical education cannot evade this process. Increasingly, students are using tablets and smartphones to instantly retrieve medical information on the web or are exchanging materials on their Facebook pages. Medical educators cannot ignore this continuing revolution, and therefore the traditional academic schedules and didactic schemes should be questioned. Analysing opinions collected from medical students regarding old and new teaching methods and tools has become mandatory, with a view towards renovating the process of medical education. A cross-sectional online survey was created with Google® docs and administrated to all students of our medical school. Students were asked to express their opinion on their favourite teaching methods, learning tools, Internet websites and Internet delivery devices. Data analysis was performed using spss. The online survey was completed by 368 students. Although textbooks remain a cornerstone for training, students also identified Internet websites, multimedia non-online material, such as the Encyclopaedia on CD-ROM, and other non-online computer resources as being useful. The Internet represented an important aid to support students' learning needs, but textbooks are still their resource of choice. Among the websites noted, Google and Wikipedia significantly surpassed the peer-reviewed medical databases, and access to the Internet was primarily through personal computers in preference to other Internet access devices, such as mobile phones and tablet computers. Increasingly, students are using tablets and smartphones to instantly retrieve medical information. © 2014 John Wiley & Sons Ltd.

  13. The Keyword Method of Foreign Vocabulary Learning: An Investigation of Its Generalizability. Working Paper No. 270.

    Science.gov (United States)

    Pressley, Michael; And Others

    In five experiments, college-age students of differing foreign language-learning abilities were asked to learn Latin word translations to determine the effectiveness of the keyword method of foreign language vocabulary learning. The Latin words were the types for which it has been argued that the keyword method effects would be maximized (the…

  14. Towards a Theoretical Construct for Modelling Smallholders’ Forestland-Use Decisions: What Can We Learn from Agriculture and Forest Economics?

    Directory of Open Access Journals (Sweden)

    Kahlil Baker

    2017-09-01

    Full Text Available Academic research on smallholders’ forestland-use decisions is regularly addressed in different streams of literature using different theoretical constructs that are independently incomplete. In this article, we propose a theoretical construct for modelling smallholders’ forestland-use decisions intended to serve in the guidance and operationalization of future models for quantitative analysis. Our construct is inspired by the sub-disciplines of forestry and agricultural economics with a crosscutting theme of how transaction costs drive separability between consumption and production decisions. Our results help explain why exogenous variables proposed in the existing literature are insufficient at explaining smallholders’ forestland-use decisions, and provide theoretical context for endogenizing characteristics of the household, farm and landscape. Smallholders’ forestland-use decisions are best understood in an agricultural context of competing uses for household assets and interdependent consumption and production decisions. Forest production strategies range from natural regeneration to intensive management of the forest resource to co-jointly produce market and non-market values. Due to transaction costs, decision prices are best represented by their shadow as opposed to market prices. Shadow prices are shaped by endogenous smallholder-specific preferences for leisure, non-market values, time, risk, and uncertainty. Our proposed construct is intended to provide a theoretical basis to assist modellers in the selection of variables for quantitative analysis.

  15. Statistical and Machine Learning forecasting methods: Concerns and ways forward.

    Science.gov (United States)

    Makridakis, Spyros; Spiliotis, Evangelos; Assimakopoulos, Vassilios

    2018-01-01

    Machine Learning (ML) methods have been proposed in the academic literature as alternatives to statistical ones for time series forecasting. Yet, scant evidence is available about their relative performance in terms of accuracy and computational requirements. The purpose of this paper is to evaluate such performance across multiple forecasting horizons using a large subset of 1045 monthly time series used in the M3 Competition. After comparing the post-sample accuracy of popular ML methods with that of eight traditional statistical ones, we found that the former are dominated across both accuracy measures used and for all forecasting horizons examined. Moreover, we observed that their computational requirements are considerably greater than those of statistical methods. The paper discusses the results, explains why the accuracy of ML models is below that of statistical ones and proposes some possible ways forward. The empirical results found in our research stress the need for objective and unbiased ways to test the performance of forecasting methods that can be achieved through sizable and open competitions allowing meaningful comparisons and definite conclusions.

  16. Statistical and Machine Learning forecasting methods: Concerns and ways forward

    Science.gov (United States)

    Makridakis, Spyros; Assimakopoulos, Vassilios

    2018-01-01

    Machine Learning (ML) methods have been proposed in the academic literature as alternatives to statistical ones for time series forecasting. Yet, scant evidence is available about their relative performance in terms of accuracy and computational requirements. The purpose of this paper is to evaluate such performance across multiple forecasting horizons using a large subset of 1045 monthly time series used in the M3 Competition. After comparing the post-sample accuracy of popular ML methods with that of eight traditional statistical ones, we found that the former are dominated across both accuracy measures used and for all forecasting horizons examined. Moreover, we observed that their computational requirements are considerably greater than those of statistical methods. The paper discusses the results, explains why the accuracy of ML models is below that of statistical ones and proposes some possible ways forward. The empirical results found in our research stress the need for objective and unbiased ways to test the performance of forecasting methods that can be achieved through sizable and open competitions allowing meaningful comparisons and definite conclusions. PMID:29584784

  17. Learning the scientific method using GloFish.

    Science.gov (United States)

    Vick, Brianna M; Pollak, Adrianna; Welsh, Cynthia; Liang, Jennifer O

    2012-12-01

    Here we describe projects that used GloFish, brightly colored, fluorescent, transgenic zebrafish, in experiments that enabled students to carry out all steps in the scientific method. In the first project, students in an undergraduate genetics laboratory course successfully tested hypotheses about the relationships between GloFish phenotypes and genotypes using PCR, fluorescence microscopy, and test crosses. In the second and third projects, students doing independent research carried out hypothesis-driven experiments that also developed new GloFish projects for future genetics laboratory students. Brianna Vick, an undergraduate student, identified causes of the different shades of color found in orange GloFish. Adrianna Pollak, as part of a high school science fair project, characterized the fluorescence emission patterns of all of the commercially available colors of GloFish (red, orange, yellow, green, blue, and purple). The genetics laboratory students carrying out the first project found that learning new techniques and applying their knowledge of genetics were valuable. However, assessments of their learning suggest that this project was not challenging to many of the students. Thus, the independent projects will be valuable as bases to widen the scope and range of difficulty of experiments available to future genetics laboratory students.

  18. Machine Learning-Empowered Biometric Methods for Biomedicine Applications

    Directory of Open Access Journals (Sweden)

    Qingxue Zhang

    2017-07-01

    Full Text Available Nowadays, pervasive computing technologies are paving a promising way for advanced smart health applications. However, a key impediment faced by wide deployment of these assistive smart devices, is the increasing privacy and security issue, such as how to protect access to sensitive patient data in the health record. Focusing on this challenge, biometrics are attracting intense attention in terms of effective user identification to enable confidential health applications. In this paper, we take special interest in two bio-potential-based biometric modalities, electrocardiogram (ECG and electroencephalogram (EEG, considering that they are both unique to individuals, and more reliable than token (identity card and knowledge-based (username/password methods. After extracting effective features in multiple domains from ECG/EEG signals, several advanced machine learning algorithms are introduced to perform the user identification task, including Neural Network, K-nearest Neighbor, Bagging, Random Forest and AdaBoost. Experimental results on two public ECG and EEG datasets show that ECG is a more robust biometric modality compared to EEG, leveraging a higher signal to noise ratio and also more distinguishable morphological patterns. Among different machine learning classifiers, the random forest greatly outperforms the others and owns an identification rate as high as 98%. This study is expected to demonstrate that properly selected biometric empowered by an effective machine learner owns a great potential, to enable confidential biomedicine applications in the era of smart digital health.

  19. E-learning support for Economic-mathematical methods

    Directory of Open Access Journals (Sweden)

    Pavel Kolman

    2009-01-01

    Full Text Available Article is describing process of creating and using of e-learning program for graphical solution of li­near programming problems that is used in the Economic mathematical methods course on Faculty of Business and Economics, MZLU. The program was created within FRVŠ 788/2008 grant and is intended for practicing of graphical solution of LP problems and allows better understanding of the li­near programming problems. In the article is on one hand described the way, how does the program work, it means how were the algorithms implemented, and on the other hand there is described way of use of that program. The program is constructed for working with integer and rational numbers. At the end of the article are shown basic statistics of programs use of students in the present form and the part-time form of study. It is mainly the number of programs downloads and comparison to another programs and students opinion on the e-learning support.

  20. Theories and models about learning in connected and ubiquitous environments. Bases for a new theoretical model from a critical vision of “connectivism”

    Directory of Open Access Journals (Sweden)

    Miguel ZAPATA-ROS

    2015-04-01

    Full Text Available This paper aims at setting the bases for the construction of a theoretical model of learning and of elaboration of knowledge, within connected learning environments. The starting point is a critical view of connectivism, and a premise: the study and recognition of existing theories, since their scope is still under development as regards their potentialities and affordances when applied in social, ubiquitous environments. The paper also includes reflections and a hypothesis on the causes that underlie in the origin of connectivism in its actual stage of development in the Information and Knowledge Society, in order to use the obtained conclusions as the bases of a new model, at a later phase.

  1. Comparison of Machine Learning methods for incipient motion in gravel bed rivers

    Science.gov (United States)

    Valyrakis, Manousos

    2013-04-01

    Soil erosion and sediment transport of natural gravel bed streams are important processes which affect both the morphology as well as the ecology of earth's surface. For gravel bed rivers at near incipient flow conditions, particle entrainment dynamics are highly intermittent. This contribution reviews the use of modern Machine Learning (ML) methods implemented for short term prediction of entrainment instances of individual grains exposed in fully developed near boundary turbulent flows. Results obtained by network architectures of variable complexity based on two different ML methods namely the Artificial Neural Network (ANN) and the Adaptive Neuro-Fuzzy Inference System (ANFIS) are compared in terms of different error and performance indices, computational efficiency and complexity as well as predictive accuracy and forecast ability. Different model architectures are trained and tested with experimental time series obtained from mobile particle flume experiments. The experimental setup consists of a Laser Doppler Velocimeter (LDV) and a laser optics system, which acquire data for the instantaneous flow and particle response respectively, synchronously. The first is used to record the flow velocity components directly upstream of the test particle, while the later tracks the particle's displacements. The lengthy experimental data sets (millions of data points) are split into the training and validation subsets used to perform the corresponding learning and testing of the models. It is demonstrated that the ANFIS hybrid model, which is based on neural learning and fuzzy inference principles, better predicts the critical flow conditions above which sediment transport is initiated. In addition, it is illustrated that empirical knowledge can be extracted, validating the theoretical assumption that particle ejections occur due to energetic turbulent flow events. Such a tool may find application in management and regulation of stream flows downstream of dams for stream

  2. Geocoding location expressions in Twitter messages: A preference learning method

    Directory of Open Access Journals (Sweden)

    Wei Zhang

    2014-12-01

    Full Text Available Resolving location expressions in text to the correct physical location, also known as geocoding or grounding, is complicated by the fact that so many places around the world share the same name. Correct resolution is made even more difficult when there is little context to determine which place is intended, as in a 140-character Twitter message, or when location cues from different sources conflict, as may be the case among different metadata fields of a Twitter message. We used supervised machine learning to weigh the different fields of the Twitter message and the features of a world gazetteer to create a model that will prefer the correct gazetteer candidate to resolve the extracted expression. We evaluated our model using the F1 measure and compared it to similar algorithms. Our method achieved results higher than state-of-the-art competitors.

  3. Employing Machine-Learning Methods to Study Young Stellar Objects

    Science.gov (United States)

    Moore, Nicholas

    2018-01-01

    Vast amounts of data exist in the astronomical data archives, and yet a large number of sources remain unclassified. We developed a multi-wavelength pipeline to classify infrared sources. The pipeline uses supervised machine learning methods to classify objects into the appropriate categories. The program is fed data that is already classified to train it, and is then applied to unknown catalogues. The primary use for such a pipeline is the rapid classification and cataloging of data that would take a much longer time to classify otherwise. While our primary goal is to study young stellar objects (YSOs), the applications extend beyond the scope of this project. We present preliminary results from our analysis and discuss future applications.

  4. New Learning Methods for Marine Oil Spill Response Training

    Directory of Open Access Journals (Sweden)

    Justiina Halonen

    2017-06-01

    Full Text Available In Finland the Regional Fire and Rescue Services (RFRS are responsible for near shore oil spill response and shoreline cleanup operations. In addition, they assist in other types of maritime incidents, such as search and rescue operations and fire-fighting on board. These statutory assignments require the RFRS to have capability to act both on land and at sea. As maritime incidents occur infrequently, little routine has been established. In order to improve their performance in maritime operations, the RFRS are participating in a new oil spill training programme to be launched by South-Eastern Finland University of Applied Sciences. This training programme aims to utilize new educational methods; e-learning and simulator based training. In addition to fully exploiting the existing navigational bridge simulator, radio communication simulator and crisis management simulator, an entirely new simulator is developed. This simulator is designed to model the oil recovery process; recovery method, rate and volume in various conditions with different oil types. New simulator enables creation of a comprehensive training programme covering training tasks from a distress call to the completion of an oil spill response operation. Structure of the training programme, as well as the training objectives, are based on the findings from competence and education surveys conducted in spring 2016. In these results, a need for vessel maneuvering and navigation exercises together with actual response measures training were emphasized. Also additional training for maritime radio communication, GMDSS-emergency protocols and collaboration with maritime authorities were seemed important. This paper describes new approach to the maritime operations training designed for rescue authorities, a way of learning by doing, without mobilising the vessels at sea.

  5. BEBP: An Poisoning Method Against Machine Learning Based IDSs

    OpenAIRE

    Li, Pan; Liu, Qiang; Zhao, Wentao; Wang, Dongxu; Wang, Siqi

    2018-01-01

    In big data era, machine learning is one of fundamental techniques in intrusion detection systems (IDSs). However, practical IDSs generally update their decision module by feeding new data then retraining learning models in a periodical way. Hence, some attacks that comprise the data for training or testing classifiers significantly challenge the detecting capability of machine learning-based IDSs. Poisoning attack, which is one of the most recognized security threats towards machine learning...

  6. A Semantic Reasoning Method Towards Ontological Model for Automated Learning Analysis

    OpenAIRE

    Okoye, Kingsley; Tawil, Abdel-Rahman; Naeem, Usman; Lamine, Elyes

    2015-01-01

    Semantic reasoning can help solve the problem of regulating the evolving and static measures of knowledge at theoretical and technological levels. The technique has been proven to enhance the capability of process models by making inferences, retaining and applying what they have learned as well as discovery of new processes. The work in this paper propose a semantic rule-based approach directed towards discovering learners interaction patterns within a learning knowledge base, and then respo...

  7. Extremely Randomized Machine Learning Methods for Compound Activity Prediction

    Directory of Open Access Journals (Sweden)

    Wojciech M. Czarnecki

    2015-11-01

    Full Text Available Speed, a relatively low requirement for computational resources and high effectiveness of the evaluation of the bioactivity of compounds have caused a rapid growth of interest in the application of machine learning methods to virtual screening tasks. However, due to the growth of the amount of data also in cheminformatics and related fields, the aim of research has shifted not only towards the development of algorithms of high predictive power but also towards the simplification of previously existing methods to obtain results more quickly. In the study, we tested two approaches belonging to the group of so-called ‘extremely randomized methods’—Extreme Entropy Machine and Extremely Randomized Trees—for their ability to properly identify compounds that have activity towards particular protein targets. These methods were compared with their ‘non-extreme’ competitors, i.e., Support Vector Machine and Random Forest. The extreme approaches were not only found out to improve the efficiency of the classification of bioactive compounds, but they were also proved to be less computationally complex, requiring fewer steps to perform an optimization procedure.

  8. Housing Value Forecasting Based on Machine Learning Methods

    Directory of Open Access Journals (Sweden)

    Jingyi Mu

    2014-01-01

    Full Text Available In the era of big data, many urgent issues to tackle in all walks of life all can be solved via big data technique. Compared with the Internet, economy, industry, and aerospace fields, the application of big data in the area of architecture is relatively few. In this paper, on the basis of the actual data, the values of Boston suburb houses are forecast by several machine learning methods. According to the predictions, the government and developers can make decisions about whether developing the real estate on corresponding regions or not. In this paper, support vector machine (SVM, least squares support vector machine (LSSVM, and partial least squares (PLS methods are used to forecast the home values. And these algorithms are compared according to the predicted results. Experiment shows that although the data set exists serious nonlinearity, the experiment result also show SVM and LSSVM methods are superior to PLS on dealing with the problem of nonlinearity. The global optimal solution can be found and best forecasting effect can be achieved by SVM because of solving a quadratic programming problem. In this paper, the different computation efficiencies of the algorithms are compared according to the computing times of relevant algorithms.

  9. Nurse practitioner preferences for distance education methods related to learning style, course content, and achievement.

    Science.gov (United States)

    Andrusyszyn, M A; Cragg, C E; Humbert, J

    2001-04-01

    The relationships among multiple distance delivery methods, preferred learning style, content, and achievement was sought for primary care nurse practitioner students. A researcher-designed questionnaire was completed by 86 (71%) participants, while 6 engaged in follow-up interviews. The results of the study included: participants preferred learning by "considering the big picture"; "setting own learning plans"; and "focusing on concrete examples." Several positive associations were found: learning on own with learning by reading, and setting own learning plans; small group with learning through discussion; large group with learning new things through hearing and with having learning plans set by others. The most preferred method was print-based material and the least preferred method was audio tape. The most suited method for content included video teleconferencing for counseling, political action, and transcultural issues; and video tape for physical assessment. Convenience, self-direction, and timing of learning were more important than delivery method or learning style. Preferred order of learning was reading, discussing, observing, doing, and reflecting. Recommended considerations when designing distance courses include a mix of delivery methods, specific content, outcomes, learner characteristics, and state of technology.

  10. Photocatalytical Properties and Theoretical Analysis of N, Cd-Codoped TiO2 Synthesized by Thermal Decomposition Method

    Directory of Open Access Journals (Sweden)

    Hongtao Gao

    2012-01-01

    Full Text Available N, Cd-codoped TiO2 have been synthesized by thermal decomposition method. The products were characterized by X-ray diffraction (XRD, scanning electron microscope (SEM, UV-visible diffuse reflectance spectra (DRS, X-ray photoelectron spectroscopy (XPS, and Brunauer-Emmett-Teller (BET specific surface area analysis, respectively. The products represented good performance in photocatalytic degradation of methyl orange. The effect of the incorporation of N and Cd on electronic structure and optical properties of TiO2 was studied by first-principle calculations on the basis of density functional theory (DFT. The impurity states, introduced by N 2p or Cd 5d, lied between the valence band and the conduction band. Due to dopants, the band gap of N, Cd-codoped TiO2 became narrow. The electronic transition from the valence band to conduction band became easy, which could account for the observed photocatalytic performance of N, Cd-codoped TiO2. The theoretical analysis might provide a probable reference for the experimentally element-doped TiO2 synthesis.

  11. Archaeological culture and medieval ethnic community: theoretical and methodical problems of correlation (the case of medieval Bulgaria

    Directory of Open Access Journals (Sweden)

    Izmaylov Iskander L.

    2014-09-01

    Full Text Available Problems related to archaeological culture and ethnos comparison in the case of medieval Bulgaria are discussed in the article. According to the author, in recent years it has become evident that the traditional concept and methodology of the study of the Bulgars’ ethnogenesis and ethnic history are in contradiction with the facts accumulated. The methods of “archaeological ethno-genetics”, which dictated solving problems of ethnogenesis of the ancient population belonging to an archaeological culture in direct correlation with ethnicity, are currently being criticized. According to modern ideas about ethnos and ethnicity, ethnicity is based upon identity with a complex hierarchical nature. Contemporary methodology requires proceeding with the integrated study of the problems of ethnogenesis on the basis of archaeology and ethnology. This kind of analysis is based upon the study of the medieval Bulgar mentality as a source of information on key aspects of ethno-political ideas. The analysis of authentic historical sources, historiographical tradition elements and folklore materials makes it possible to reconstruct the basic ideas that were significant for an ethnic group. The archaeological culture of the population of Bulgaria is characterized by two clearly distinguished and interconnected elements – the common Muslim culture and that of the elite military “druzhina” (squad. These elements directly characterize the Bulgar ethno-political community. These theoretical conclusions and empirical research concerning the case of the medieval Bulgars’ ethnogenesis attest to the productivity of ethnological synthesis techniques on an interdisciplinary basis.

  12. Computerization of Hungarian reforestation manual with machine learning methods

    Science.gov (United States)

    Czimber, Kornél; Gálos, Borbála; Mátyás, Csaba; Bidló, András; Gribovszki, Zoltán

    2017-04-01

    Hungarian forests are highly sensitive to the changing climate, especially to the available precipitation amount. Over the past two decades several drought damages were observed for tree species which are in the lower xeric limit of their distribution. From year to year these affected forest stands become more difficult to reforest with the same native species because these are not able to adapt to the increasing probability of droughts. The climate related parameter set of the Hungarian forest stand database needs updates. Air humidity that was formerly used to define the forest climate zones is not measured anymore and its value based on climate model outputs is highly uncertain. The aim was to develop a novel computerized and objective method to describe the species-specific climate conditions that is essential for survival, growth and optimal production of the forest ecosystems. The method is expected to project the species spatial distribution until 2100 on the basis of regional climate model simulations. Until now, Hungarian forest managers have been using a carefully edited spreadsheet for reforestation purposes. Applying binding regulations this spreadsheet prescribes the stand-forming and admixed tree species and their expected growth rate for each forest site types. We are going to present a new machine learning based method to replace the former spreadsheet. We took into great consideration of various methods, such as maximum likelihood, Bayesian networks, Fuzzy logic. The method calculates distributions, setups classification, which can be validated and modified by experts if necessary. Projected climate change conditions makes necessary to include into this system an additional climate zone that does not exist in our region now, as well as new options for potential tree species. In addition to or instead of the existing ones, the influence of further limiting parameters (climatic extremes, soil water retention) are also investigated. Results will be

  13. Fast learning method for convolutional neural networks using extreme learning machine and its application to lane detection.

    Science.gov (United States)

    Kim, Jihun; Kim, Jonghong; Jang, Gil-Jin; Lee, Minho

    2017-03-01

    Deep learning has received significant attention recently as a promising solution to many problems in the area of artificial intelligence. Among several deep learning architectures, convolutional neural networks (CNNs) demonstrate superior performance when compared to other machine learning methods in the applications of object detection and recognition. We use a CNN for image enhancement and the detection of driving lanes on motorways. In general, the process of lane detection consists of edge extraction and line detection. A CNN can be used to enhance the input images before lane detection by excluding noise and obstacles that are irrelevant to the edge detection result. However, training conventional CNNs requires considerable computation and a big dataset. Therefore, we suggest a new learning algorithm for CNNs using an extreme learning machine (ELM). The ELM is a fast learning method used to calculate network weights between output and hidden layers in a single iteration and thus, can dramatically reduce learning time while producing accurate results with minimal training data. A conventional ELM can be applied to networks with a single hidden layer; as such, we propose a stacked ELM architecture in the CNN framework. Further, we modify the backpropagation algorithm to find the targets of hidden layers and effectively learn network weights while maintaining performance. Experimental results confirm that the proposed method is effective in reducing learning time and improving performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

  14. A Theoretical Analysis of the Performance of Learning Disabled Students on the Woodcock-Johnson Psycho-Educational Battery.

    Science.gov (United States)

    Shinn, Mark; And Others

    Two studies were conducted to (1) analyze the subtest characteristics of the Woodcock-Johnson Psycho-Educational Battery, and (2) apply those results to an analysis of 50 fourth grade learning disabled (LD) students' performance on the Battery. Analyses indicated that the poorer performance of LD students on the Woodcock-Johnson Tests of Cognitive…

  15. E-learning in engineering education: a theoretical and empirical study of the Algerian higher education institution

    Science.gov (United States)

    Benchicou, Soraya; Aichouni, Mohamed; Nehari, Driss

    2010-06-01

    Technology-mediated education or e-learning is growing globally both in scale and delivery capacity due to the large diffusion of the ubiquitous information and communication technologies (ICT) in general and the web technologies in particular. This statement has not yet been fully supported by research, especially in developing countries such as Algeria. The purpose of this paper was to identify directions for addressing the needs of academics in higher education institutions in Algeria in order to adopt the e-learning approach as a strategy to improve quality of education. The paper will report results of an empirical study that measures the readiness of the Algerian higher education institutions towards the implementation of ICT in the educational process and the attitudes of faculty members towards the application of the e-learning approach in engineering education. Three main objectives were targeted, namely: (a) to provide an initial evaluation of faculty members' attitudes and perceptions towards web-based education; (b) reporting on their perceived requirements for implementing e-learning in university courses; (c) providing an initial input for a collaborative process of developing an institutional strategy for e-learning. Statistical analysis of the survey results indicates that the Algerian higher education institution, which adopted the Licence - Master and Doctorate educational system, is facing a big challenge to take advantage of emerging technological innovations and the advent of e-learning to further develop its teaching programmes and to enhance the quality of education in engineering fields. The successful implementation of this modern approach is shown to depend largely on a set of critical success factors that would include: 1. The extent to which the institution will adopt a formal and official e-learning strategy. 2. The extent to which faculty members will adhere and adopt this strategy and develop ownership of the various measures in the

  16. Theoretical Mathematics

    Science.gov (United States)

    Stöltzner, Michael

    Answering to the double-faced influence of string theory on mathematical practice and rigour, the mathematical physicists Arthur Jaffe and Frank Quinn have contemplated the idea that there exists a `theoretical' mathematics (alongside `theoretical' physics) whose basic structures and results still require independent corroboration by mathematical proof. In this paper, I shall take the Jaffe-Quinn debate mainly as a problem of mathematical ontology and analyse it against the backdrop of two philosophical views that are appreciative towards informal mathematical development and conjectural results: Lakatos's methodology of proofs and refutations and John von Neumann's opportunistic reading of Hilbert's axiomatic method. The comparison of both approaches shows that mitigating Lakatos's falsificationism makes his insights about mathematical quasi-ontology more relevant to 20th century mathematics in which new structures are introduced by axiomatisation and not necessarily motivated by informal ancestors. The final section discusses the consequences of string theorists' claim to finality for the theory's mathematical make-up. I argue that ontological reductionism as advocated by particle physicists and the quest for mathematically deeper axioms do not necessarily lead to identical results.

  17. Understanding the Effects of Time on Collaborative Learning Processes in Problem Based Learning: A Mixed Methods Study

    Science.gov (United States)

    Hommes, J.; Van den Bossche, P.; de Grave, W.; Bos, G.; Schuwirth, L.; Scherpbier, A.

    2014-01-01

    Little is known how time influences collaborative learning groups in medical education. Therefore a thorough exploration of the development of learning processes over time was undertaken in an undergraduate PBL curriculum over 18 months. A mixed-methods triangulation design was used. First, the quantitative study measured how various learning…

  18. Project-Based Learning Using Discussion and Lesson-Learned Methods via Social Media Model for Enhancing Problem Solving Skills

    Science.gov (United States)

    Jewpanich, Chaiwat; Piriyasurawong, Pallop

    2015-01-01

    This research aims to 1) develop the project-based learning using discussion and lesson-learned methods via social media model (PBL-DLL SoMe Model) used for enhancing problem solving skills of undergraduate in education student, and 2) evaluate the PBL-DLL SoMe Model used for enhancing problem solving skills of undergraduate in education student.…

  19. Theoretical Mechanics Theoretical Physics 1

    CERN Document Server

    Dreizler, Reiner M

    2011-01-01

    After an introduction to basic concepts of mechanics more advanced topics build the major part of this book. Interspersed is a discussion of selected problems of motion. This is followed by a concise treatment of the Lagrangian and the Hamiltonian formulation of mechanics, as well as a brief excursion on chaotic motion. The last chapter deals with applications of the Lagrangian formulation to specific systems (coupled oscillators, rotating coordinate systems, rigid bodies). The level of this textbook is advanced undergraduate. The authors combine teaching experience of more than 40 years in all fields of Theoretical Physics and related mathematical disciplines and thorough knowledge in creating advanced eLearning content. The text is accompanied by an extensive collection of online material, in which the possibilities of the electronic medium are fully exploited, e.g. in the form of applets, 2D- and 3D-animations. - A collection of 74 problems with detailed step-by-step guidance towards the solutions. - A col...

  20. Cross-organism learning method to discover new gene functionalities.

    Science.gov (United States)

    Domeniconi, Giacomo; Masseroli, Marco; Moro, Gianluca; Pinoli, Pietro

    2016-04-01

    Knowledge of gene and protein functions is paramount for the understanding of physiological and pathological biological processes, as well as in the development of new drugs and therapies. Analyses for biomedical knowledge discovery greatly benefit from the availability of gene and protein functional feature descriptions expressed through controlled terminologies and ontologies, i.e., of gene and protein biomedical controlled annotations. In the last years, several databases of such annotations have become available; yet, these valuable annotations are incomplete, include errors and only some of them represent highly reliable human curated information. Computational techniques able to reliably predict new gene or protein annotations with an associated likelihood value are thus paramount. Here, we propose a novel cross-organisms learning approach to reliably predict new functionalities for the genes of an organism based on the known controlled annotations of the genes of another, evolutionarily related and better studied, organism. We leverage a new representation of the annotation discovery problem and a random perturbation of the available controlled annotations to allow the application of supervised algorithms to predict with good accuracy unknown gene annotations. Taking advantage of the numerous gene annotations available for a well-studied organism, our cross-organisms learning method creates and trains better prediction models, which can then be applied to predict new gene annotations of a target organism. We tested and compared our method with the equivalent single organism approach on different gene annotation datasets of five evolutionarily related organisms (Homo sapiens, Mus musculus, Bos taurus, Gallus gallus and Dictyostelium discoideum). Results show both the usefulness of the perturbation method of available annotations for better prediction model training and a great improvement of the cross-organism models with respect to the single-organism ones