On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems.

Science.gov (United States)

Albattat, Ali; Gruenwald, Benjamin C; Yucelen, Tansel

2016-08-16

The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems). These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches.

On Event-Triggered Adaptive Architectures for Decentralized and Distributed Control of Large-Scale Modular Systems

Directory of Open Access Journals (Sweden)

Ali Albattat

2016-08-01

Full Text Available The last decade has witnessed an increased interest in physical systems controlled over wireless networks (networked control systems. These systems allow the computation of control signals via processors that are not attached to the physical systems, and the feedback loops are closed over wireless networks. The contribution of this paper is to design and analyze event-triggered decentralized and distributed adaptive control architectures for uncertain networked large-scale modular systems; that is, systems consist of physically-interconnected modules controlled over wireless networks. Specifically, the proposed adaptive architectures guarantee overall system stability while reducing wireless network utilization and achieving a given system performance in the presence of system uncertainties that can result from modeling and degraded modes of operation of the modules and their interconnections between each other. In addition to the theoretical findings including rigorous system stability and the boundedness analysis of the closed-loop dynamical system, as well as the characterization of the effect of user-defined event-triggering thresholds and the design parameters of the proposed adaptive architectures on the overall system performance, an illustrative numerical example is further provided to demonstrate the efficacy of the proposed decentralized and distributed control approaches.

Application of Transfer Matrix Approach to Modeling and Decentralized Control of Lattice-Based Structures

Science.gov (United States)

Cramer, Nick; Swei, Sean Shan-Min; Cheung, Kenny; Teodorescu, Mircea

2015-01-01

This paper presents a modeling and control of aerostructure developed by lattice-based cellular materials/components. The proposed aerostructure concept leverages a building block strategy for lattice-based components which provide great adaptability to varying ight scenarios, the needs of which are essential for in- ight wing shaping control. A decentralized structural control design is proposed that utilizes discrete-time lumped mass transfer matrix method (DT-LM-TMM). The objective is to develop an e ective reduced order model through DT-LM-TMM that can be used to design a decentralized controller for the structural control of a wing. The proposed approach developed in this paper shows that, as far as the performance of overall structural system is concerned, the reduced order model can be as e ective as the full order model in designing an optimal stabilizing controller.

Robust Visual Knowledge Transfer via Extreme Learning Machine Based Domain Adaptation.

Science.gov (United States)

Zhang, Lei; Zhang, David

2016-08-10

We address the problem of visual knowledge adaptation by leveraging labeled patterns from source domain and a very limited number of labeled instances in target domain to learn a robust classifier for visual categorization. This paper proposes a new extreme learning machine based cross-domain network learning framework, that is called Extreme Learning Machine (ELM) based Domain Adaptation (EDA). It allows us to learn a category transformation and an ELM classifier with random projection by minimizing the -norm of the network output weights and the learning error simultaneously. The unlabeled target data, as useful knowledge, is also integrated as a fidelity term to guarantee the stability during cross domain learning. It minimizes the matching error between the learned classifier and a base classifier, such that many existing classifiers can be readily incorporated as base classifiers. The network output weights cannot only be analytically determined, but also transferrable. Additionally, a manifold regularization with Laplacian graph is incorporated, such that it is beneficial to semi-supervised learning. Extensively, we also propose a model of multiple views, referred as MvEDA. Experiments on benchmark visual datasets for video event recognition and object recognition, demonstrate that our EDA methods outperform existing cross-domain learning methods.

ADAPTATION OF TEACHING PROCESS BASED ON A STUDENTS INDIVIDUAL LEARNING NEEDS

Directory of Open Access Journals (Sweden)

TAKÁCS, Ondřej

2011-03-01

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

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

Science.gov (United States)

Babaie, Hassan; Atchison, Chris; Sunderraman, Rajshekhar

2014-05-01

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

Decentralized DC Microgrid Monitoring and Optimization via Primary Control Perturbations

Science.gov (United States)

Angjelichinoski, Marko; Scaglione, Anna; Popovski, Petar; Stefanovic, Cedomir

2018-06-01

We treat the emerging power systems with direct current (DC) MicroGrids, characterized with high penetration of power electronic converters. We rely on the power electronics to propose a decentralized solution for autonomous learning of and adaptation to the operating conditions of the DC Mirogrids; the goal is to eliminate the need to rely on an external communication system for such purpose. The solution works within the primary droop control loops and uses only local bus voltage measurements. Each controller is able to estimate (i) the generation capacities of power sources, (ii) the load demands, and (iii) the conductances of the distribution lines. To define a well-conditioned estimation problem, we employ decentralized strategy where the primary droop controllers temporarily switch between operating points in a coordinated manner, following amplitude-modulated training sequences. We study the use of the estimator in a decentralized solution of the Optimal Economic Dispatch problem. The evaluations confirm the usefulness of the proposed solution for autonomous MicroGrid operation.

Computerized adaptive testing item selection in computerized adaptive learning systems

NARCIS (Netherlands)

Eggen, Theodorus Johannes Hendrikus Maria; Eggen, T.J.H.M.; Veldkamp, B.P.

2012-01-01

Item selection methods traditionally developed for computerized adaptive testing (CAT) are explored for their usefulness in item-based computerized adaptive learning (CAL) systems. While in CAT Fisher information-based selection is optimal, for recovering learning populations in CAL systems item

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

Science.gov (United States)

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

2011-11-01

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

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

Science.gov (United States)

Tilchin, Oleg; Kittany, Mohamed

2016-01-01

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

Decentralized adaptive control of interconnected nonlinear systems with unknown control directions.

Science.gov (United States)

Huang, Jiangshuai; Wang, Qing-Guo

2018-03-01

In this paper, we propose a decentralized adaptive control scheme for a class of interconnected strict-feedback nonlinear systems without a priori knowledge of subsystems' control directions. To address this problem, a novel Nussbaum-type function is proposed and a key theorem is drawn which involves quantifying the interconnections of multiple Nussbaum-type functions of the subsystems with different control directions in a single inequality. Global stability of the closed-loop system and asymptotic stabilization of subsystems' output are proved and a simulation example is given to illustrate the effectiveness of the proposed control scheme. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive Social Learning Based on Crowdsourcing

Science.gov (United States)

Karataev, Evgeny; Zadorozhny, Vladimir

2017-01-01

Many techniques have been developed to enhance learning experience with computer technology. A particularly great influence of technology on learning came with the emergence of the web and adaptive educational hypermedia systems. While the web enables users to interact and collaborate with each other to create, organize, and share knowledge via…

Evaluation framework based on fuzzy measured method in adaptive learning systems

OpenAIRE

Houda Zouari Ounaies, ,; Yassine Jamoussi; Henda Hajjami Ben Ghezala

2008-01-01

Currently, e-learning systems are mainly web-based applications and tackle a wide range of users all over the world. Fitting learners’ needs is considered as a key issue to guaranty the success of these systems. Many researches work on providing adaptive systems. Nevertheless, evaluation of the adaptivity is still in an exploratory phase. Adaptation methods are a basic factor to guaranty an effective adaptation. This issue is referred as meta-adaptation in numerous researches. In our research...

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

Science.gov (United States)

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

1988-01-01

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

SU-D-BRB-05: Quantum Learning for Knowledge-Based Response-Adaptive Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

El Naqa, I; Ten, R [Haken University of Michigan, Ann Arbor, MI (United States)

2016-06-15

Purpose: There is tremendous excitement in radiotherapy about applying data-driven methods to develop personalized clinical decisions for real-time response-based adaptation. However, classical statistical learning methods lack in terms of efficiency and ability to predict outcomes under conditions of uncertainty and incomplete information. Therefore, we are investigating physics-inspired machine learning approaches by utilizing quantum principles for developing a robust framework to dynamically adapt treatments to individual patient’s characteristics and optimize outcomes. Methods: We studied 88 liver SBRT patients with 35 on non-adaptive and 53 on adaptive protocols. Adaptation was based on liver function using a split-course of 3+2 fractions with a month break. The radiotherapy environment was modeled as a Markov decision process (MDP) of baseline and one month into treatment states. The patient environment was modeled by a 5-variable state represented by patient’s clinical and dosimetric covariates. For comparison of classical and quantum learning methods, decision-making to adapt at one month was considered. The MDP objective was defined by the complication-free tumor control (P{sup +}=TCPx(1-NTCP)). A simple regression model represented state-action mapping. Single bit in classical MDP and a qubit of 2-superimposed states in quantum MDP represented the decision actions. Classical decision selection was done using reinforcement Q-learning and quantum searching was performed using Grover’s algorithm, which applies uniform superposition over possible states and yields quadratic speed-up. Results: Classical/quantum MDPs suggested adaptation (probability amplitude ≥0.5) 79% of the time for splitcourses and 100% for continuous-courses. However, the classical MDP had an average adaptation probability of 0.5±0.22 while the quantum algorithm reached 0.76±0.28. In cases where adaptation failed, classical MDP yielded 0.31±0.26 average amplitude while the

Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System

Directory of Open Access Journals (Sweden)

Guofeng Tong

2014-04-01

Full Text Available This paper proposes an adaptive iterative learning control strategy integrated with saturation-based robust control for uncertain robot system in presence of modelling uncertainties, unknown parameter, and external disturbance under alignment condition. An important merit is that it achieves adaptive switching of gain matrix both in conventional PD-type feedforward control and robust adaptive control in the iteration domain simultaneously. The analysis of convergence of proposed control law is based on Lyapunov's direct method under alignment initial condition. Simulation results demonstrate the faster learning rate and better robust performance with proposed algorithm by comparing with other existing robust controllers. The actual experiment on three-DOF robot manipulator shows its better practical effectiveness.

Enhancing Student Adaption to a Case Based Learning Environment

DEFF Research Database (Denmark)

Jensen, Lars Peter

2010-01-01

these at the end of the semester, showing the development of the student in terms of adapting to the learning model. The idea will be explained more closely in the final paper. RESEARCH METHOD The research part of the experiment was carried out as action research, as the teacher of the course in the same time......INTRODUCTION Since Aalborg University (AAU) was started it has been using an educational model, where Problem Based Learning is the turning point. Each semester the students on the Engineering Educations form groups of 3-6 persons, which uses half of the study time within the semester to solve......) in groups. It appeared to be difficult for the students to adapt to two different PBL approaches at the same time, and with the project being the most popular the learning outcome of the case studies was not satisfactory after the first semester, but improved on the following semesters. In 2009...

Decentralized robust control design using LMI

Directory of Open Access Journals (Sweden)

Dušan Krokavec

2008-03-01

Full Text Available The paper deals with application of decentralized controllers for large-scale systems with subsystems interaction and system matrices uncertainties. The desired stability of the whole system is guaranteed while at the same time the tolerable bounds in the uncertainties due to structural changes are maximized. The design approach is based on the linear matrix inequalities (LMI techniques adaptation for stabilizing controller design.

Designing an Adaptive Web-Based Learning System Based on Students' Cognitive Styles Identified Online

Science.gov (United States)

Lo, Jia-Jiunn; Chan, Ya-Chen; Yeh, Shiou-Wen

2012-01-01

This study developed an adaptive web-based learning system focusing on students' cognitive styles. The system is composed of a student model and an adaptation model. It collected students' browsing behaviors to update the student model for unobtrusively identifying student cognitive styles through a multi-layer feed-forward neural network (MLFF).…

Research on calculation of the IOL tilt and decentration based on surface fitting.

Science.gov (United States)

Li, Lin; Wang, Ke; Yan, Yan; Song, Xudong; Liu, Zhicheng

2013-01-01

The tilt and decentration of intraocular lens (IOL) result in defocussing, astigmatism, and wavefront aberration after operation. The objective is to give a method to estimate the tilt and decentration of IOL more accurately. Based on AS-OCT images of twelve eyes from eight cases with subluxation lens after operation, we fitted spherical equation to the data obtained from the images of the anterior and posterior surfaces of the IOL. By the established relationship between IOL tilt (decentration) and the scanned angle, at which a piece of AS-OCT image was taken by the instrument, the IOL tilt and decentration were calculated. IOL tilt angle and decentration of each subject were given. Moreover, the horizontal and vertical tilt was also obtained. Accordingly, the possible errors of IOL tilt and decentration existed in the method employed by AS-OCT instrument. Based on 6-12 pieces of AS-OCT images at different directions, the tilt angle and decentration values were shown, respectively. The method of the surface fitting to the IOL surface can accurately analyze the IOL's location, and six pieces of AS-OCT images at three pairs symmetrical directions are enough to get tilt angle and decentration value of IOL more precisely.

Research on Calculation of the IOL Tilt and Decentration Based on Surface Fitting

Directory of Open Access Journals (Sweden)

Lin Li

2013-01-01

Full Text Available The tilt and decentration of intraocular lens (IOL result in defocussing, astigmatism, and wavefront aberration after operation. The objective is to give a method to estimate the tilt and decentration of IOL more accurately. Based on AS-OCT images of twelve eyes from eight cases with subluxation lens after operation, we fitted spherical equation to the data obtained from the images of the anterior and posterior surfaces of the IOL. By the established relationship between IOL tilt (decentration and the scanned angle, at which a piece of AS-OCT image was taken by the instrument, the IOL tilt and decentration were calculated. IOL tilt angle and decentration of each subject were given. Moreover, the horizontal and vertical tilt was also obtained. Accordingly, the possible errors of IOL tilt and decentration existed in the method employed by AS-OCT instrument. Based on 6–12 pieces of AS-OCT images at different directions, the tilt angle and decentration values were shown, respectively. The method of the surface fitting to the IOL surface can accurately analyze the IOL’s location, and six pieces of AS-OCT images at three pairs symmetrical directions are enough to get tilt angle and decentration value of IOL more precisely.

DECENTRALIZATION OF MUNICIPAL SERVICES – LEARNING BY DOING

Directory of Open Access Journals (Sweden)

Cristina Elena NICOLESCU

2017-05-01

Full Text Available Public services decentralization is a major concern for policy makers when it comes to identifying the optimum model for reorganizing these services, in light of the 3Es of the organizational performance. The field experiences show that this process is different both from one state to another, and depending on the targeted activity sector, out of which the local transport service is distinguished as an ‘institutional orphan’. Taking into account one of the smart-cities’ recognition criteria, the urban mobility, the paper aims at substantiating that, despite the specific incrementalism of the public services decentralization, having a negative impact upon the services’ efficiency, in the case of local transport service, recognizing the right to mobility and the need to ensuring the environment for exercising this right, impels the ‘bureaucratic apparatus’ to accelerate and consolidate the decentralization of this service. Therefore, the paper puts forward a case study on the impact of decentralization upon the local public transport service of Bucharest municipality.

Parameters identification of photovoltaic models using self-adaptive teaching-learning-based optimization

International Nuclear Information System (INIS)

Yu, Kunjie; Chen, Xu; Wang, Xin; Wang, Zhenlei

2017-01-01

Highlights: • SATLBO is proposed to identify the PV model parameters efficiently. • In SATLBO, the learners self-adaptively select different learning phases. • An elite learning is developed in teacher phase to perform local searching. • A diversity learning is proposed in learner phase to maintain population diversity. • SATLBO achieves the first in ranking on overall performance among nine algorithms. - Abstract: Parameters identification of photovoltaic (PV) model based on measured current-voltage characteristic curves plays an important role in the simulation and evaluation of PV systems. To accurately and reliably identify the PV model parameters, a self-adaptive teaching-learning-based optimization (SATLBO) is proposed in this paper. In SATLBO, the learners can self-adaptively select different learning phases based on their knowledge level. The better learners are more likely to choose the learner phase for improving the population diversity, while the worse learners tend to choose the teacher phase to enhance the convergence rate. Thus, learners at different levels focus on different searching abilities to efficiently enhance the performance of algorithm. In addition, to improve the searching ability of different learning phases, an elite learning strategy and a diversity learning method are introduced into the teacher phase and learner phase, respectively. The performance of SATLBO is firstly evaluated on 34 benchmark functions, and experimental results show that SATLBO achieves the first in ranking on the overall performance among nine algorithms. Then, SATLBO is employed to identify parameters of different PV models, i.e., single diode, double diode, and PV module. Experimental results indicate that SATLBO exhibits high accuracy and reliability compared with other parameter extraction methods.

Evaluation Framework Based on Fuzzy Measured Method in Adaptive Learning Systems

Science.gov (United States)

Ounaies, Houda Zouari; Jamoussi, Yassine; Ben Ghezala, Henda Hajjami

2008-01-01

Currently, e-learning systems are mainly web-based applications and tackle a wide range of users all over the world. Fitting learners' needs is considered as a key issue to guaranty the success of these systems. Many researches work on providing adaptive systems. Nevertheless, evaluation of the adaptivity is still in an exploratory phase.…

Recommendation System for Adaptive Learning.

Science.gov (United States)

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

2018-01-01

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

Student Modelling in Adaptive E-Learning Systems

Directory of Open Access Journals (Sweden)

Clemens Bechter

2011-09-01

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

Subsidiarity in Principle: Decentralization of Water Resources Management

Directory of Open Access Journals (Sweden)

Ryan Stoa

2014-05-01

Full Text Available The subsidiarity principle of water resources management suggests that water management and service delivery should take place at the lowest appropriate governance level. The principle is attractive for several reasons, primarily because: 1 the governance level can be reduced to reflect environmental characteristics, such as the hydrological borders of a watershed that would otherwise cross administrative boundaries; 2 decentralization promotes community and stakeholder engagement when decision-making is localized; 3 inefficiencies are reduced by eliminating reliance on central government bureaucracies and budgetary constraints; and 4 laws and institutions can be adapted to reflect localized conditions at a scale where integrated natural resources management and climate change adaptation is more focused. Accordingly, the principle of subsidiarity has been welcomed by many states committed to decentralized governance, integrated water resources management, and/or civic participation. However, applications of decentralization have not been uniform, and in some cases have produced frustrating outcomes for states and water resources. Successful decentralization strategies are heavily dependent on dedicated financial resources and human resource capacity. This article explores the nexus between the principle of subsidiarity and the enabling environment, in the hope of articulating factors likely to contribute to, or detract from, the success of decentralized water resources management. Case studies from Haiti, Rwanda, and the United States’ Florida Water Management Districts provide examples of the varied stages of decentralization.

E-Learning and Personalized Learning Path: A Proposal Based on the Adaptive Educational Hypermedia System

Directory of Open Access Journals (Sweden)

Francesco Colace

2014-03-01

Full Text Available The E-Learning is becoming an effective approach for the improving of quality of learning. Many institutions are adopting this approach both to improve their traditional courses both to increase the potential audience. In the last period great attention is paid in the introduction of methodologies and techniques for the adaptation of learning process to the real needs of students. In this scenario the Adaptive Educational Hypermedia System can be an effective approach. Adaptive hypermedia is a promising area of research at the crossroads of hypermedia and adaptive systems. One of the most important fields where this approach can be applied is just the e-Learning. In this context the adaptive learning resources selection and sequencing is recognized as among one of the most interesting research questions. An Adaptive Educational Hypermedia System is composed by services for the management of the Knowledge Space, the definition of a User Model, the observation of student during his learning period and, as previously said, the adaptation of the learning path according to the real needs of the students. In particular the use of ontologyཿs formalism for the modeling of the ཿknowledge space࿝ related to the course can increase the sharable of learning objects among similar courses or better contextualize their role in the course. This paper addresses the design problem of an Adaptive hypermedia system by the definition of methodologies able to manage each its components, In particular an original user, learning contents, tracking strategies and adaptation model are developed. The proposed Adaptive Educational Hypermedia System has been integrated in an e-Learning platform and an experimental campaign has been conducted. In particular the proposed approach has been introduced in three different blended courses. A comparison with traditional approach has been described and the obtained results seem to be very promising.

A decentralized control scheme for an effective coordination of phasic and tonic control in a snake-like robot

International Nuclear Information System (INIS)

Sato, Takahide; Kano, Takeshi; Ishiguro, Akio

2012-01-01

Autonomous decentralized control has attracted considerable attention because it enables us to understand the adaptive and versatile locomotion of animals and facilitates the construction of truly intelligent artificial agents. Thus far, we have developed a snake-like robot (HAUBOT I) that is driven by a decentralized control scheme based on a discrepancy function, which incorporates phasic control. In this paper, we investigate a decentralized control scheme in which phasic and tonic control are well coordinated, as an extension of our previous study. To verify the validity of the proposed control scheme, we apply it to a snake-like robot (HAUBOT II) that can adjust both the phase relationship between its body segments and the stiffness at each joint. The results indicate that the proposed control scheme enables the robot to exhibit remarkable real-time adaptability over various frictional and inclined terrains. These findings can potentially enable us to gain a deeper insight into the autonomous decentralized control mechanism underlying the adaptive and resilient locomotion of animals.

Learner Characteristic Based Learning Effort Curve Mode: The Core Mechanism on Developing Personalized Adaptive E-Learning Platform

Science.gov (United States)

Hsu, Pi-Shan

2012-01-01

This study aims to develop the core mechanism for realizing the development of personalized adaptive e-learning platform, which is based on the previous learning effort curve research and takes into account the learner characteristics of learning style and self-efficacy. 125 university students from Taiwan are classified into 16 groups according…

Responsiveness and flexibility in a Decentralized Supply Chain

DEFF Research Database (Denmark)

Petersen, Kristian Rasmus; Bilberg, Arne; Hadar, Ronen

Today’s supply chains are not capable of managing the instabilities that is the case in the market. Instead, there is a need to develop supply chains that are capable of adapting to changes. Through a case study of LEGO, the authors suggest a possible solution: a decentralized supply chain serving...... independent and self-sufficient local factories. The decentralized supply chain is provided with materials, parts and pre-assembled elements from local suppliers and supplies the local market in return. Keywords: Decentralize, Responsiveness, Flexibility...

Learning to Adapt. Organisational Adaptation to Climate Change Impacts

International Nuclear Information System (INIS)

Berkhout, F.; Hertin, J.; Gann, D.M.

2006-01-01

Analysis of human adaptation to climate change should be based on realistic models of adaptive behaviour at the level of organisations and individuals. The paper sets out a framework for analysing adaptation to the direct and indirect impacts of climate change in business organisations with new evidence presented from empirical research into adaptation in nine case-study companies. It argues that adaptation to climate change has many similarities with processes of organisational learning. The paper suggests that business organisations face a number of obstacles in learning how to adapt to climate change impacts, especially in relation to the weakness and ambiguity of signals about climate change and the uncertainty about benefits flowing from adaptation measures. Organisations rarely adapt 'autonomously', since their adaptive behaviour is influenced by policy and market conditions, and draws on resources external to the organisation. The paper identifies four adaptation strategies that pattern organisational adaptive behaviour

Towards a (Decentralization-Based Typology of Peer Production

Directory of Open Access Journals (Sweden)

Melanie Dulong de Rosnay

2016-03-01

Full Text Available Online peer-production platforms facilitate the coordination of creative work and services. Generally considered as empowering participatory tools and a source of common good, they can also be, however, alienating instruments of digital labour. This paper proposes a typology of peer-production platforms, based on the centralization/decentralization levels of several of their design features. Between commons-based peer-production and crowdsourced, user-generated content “enclosed” by corporations, a wide range of models combine different social, political, technical and economic arrangements. This combined analysis of the level of (decentralization of platform features provides information on emancipation capabilities in a more granular way than a market-based qualification of platforms, based on the nature of ownership or business models only. The five selected features of the proposed typology are: ownership of means of production, technical architecture/design, social organization/governance of work patterns, ownership of the peer-produced resource, and value of the output.

Towards adaptation in e-learning 2.0

Science.gov (United States)

Cristea, Alexandra I.; Ghali, Fawaz

2011-04-01

This paper presents several essential steps from an overall study on shaping new ways of learning and teaching, by using the synergetic merger of three different fields: Web 2.0, e-learning and adaptation (in particular, personalisation to the learner). These novel teaching and learning ways-the latter focus of this paper-are reflected in and finally adding to various versions of the My Online Teacher 2.0 adaptive system. In particular, this paper focuses on a study of how to more effectively use and combine the recommendation of peers and content adaptation to enhance the learning outcome in e-learning systems based on Web 2.0. In order to better isolate and examine the effects of peer recommendation and adaptive content presentation, we designed experiments inspecting collaboration between individuals based on recommendation of peers who have greater knowledge, and compare this to adaptive content recommendation, as well as to "simple" learning in a system with a minimum of Web 2.0 support. Overall, the results of adding peer recommendation and adaptive content presentation were encouraging, and are further discussed in detail in this paper.

Learning-based adaptive prescribed performance control of postcapture space robot-target combination without inertia identifications

Science.gov (United States)

Wei, Caisheng; Luo, Jianjun; Dai, Honghua; Bian, Zilin; Yuan, Jianping

2018-05-01

In this paper, a novel learning-based adaptive attitude takeover control method is investigated for the postcapture space robot-target combination with guaranteed prescribed performance in the presence of unknown inertial properties and external disturbance. First, a new static prescribed performance controller is developed to guarantee that all the involved attitude tracking errors are uniformly ultimately bounded by quantitatively characterizing the transient and steady-state performance of the combination. Then, a learning-based supplementary adaptive strategy based on adaptive dynamic programming is introduced to improve the tracking performance of static controller in terms of robustness and adaptiveness only utilizing the input/output data of the combination. Compared with the existing works, the prominent advantage is that the unknown inertial properties are not required to identify in the development of learning-based adaptive control law, which dramatically decreases the complexity and difficulty of the relevant controller design. Moreover, the transient and steady-state performance is guaranteed a priori by designer-specialized performance functions without resorting to repeated regulations of the controller parameters. Finally, the three groups of illustrative examples are employed to verify the effectiveness of the proposed control method.

Shorter Decentralized Attribute-Based Encryption via Extended Dual System Groups

Directory of Open Access Journals (Sweden)

Jie Zhang

2017-01-01

Full Text Available Decentralized attribute-based encryption (ABE is a special form of multiauthority ABE systems, in which no central authority and global coordination are required other than creating the common reference parameters. In this paper, we propose a new decentralized ABE in prime-order groups by using extended dual system groups. We formulate some assumptions used to prove the security of our scheme. Our proposed scheme is fully secure under the standard k-Lin assumption in random oracle model and can support any monotone access structures. Compared with existing fully secure decentralized ABE systems, our construction has shorter ciphertexts and secret keys. Moreover, fast decryption is achieved in our system, in which ciphertexts can be decrypted with a constant number of pairings.

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

Science.gov (United States)

Pedrazzoli, Attilio

2010-06-01

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

Mild decentration measured by a Scheimpflug camera and its impact on visual quality following SMILE in the early learning curve.

Science.gov (United States)

Li, Meiyan; Zhao, Jing; Miao, Huamao; Shen, Yang; Sun, Ling; Tian, Mi; Wadium, Elizabeth; Zhou, Xingtao

2014-05-20

To measure decentration following femtosecond laser small incision lenticule extraction (SMILE) for the correction of myopia and myopic astigmatism in the early learning curve, and to investigate its impact on visual quality. A total of 55 consecutive patients (100 eyes) who underwent the SMILE procedure were included. Decentration was measured using a Scheimpflug camera 6 months after surgery. Uncorrected and corrected distance visual acuity (UDVA, CDVA), manifest refraction, and wavefront errors were also measured. Associations between decentration and the preoperative spherical equivalent were analyzed, as well as the associations between decentration and wavefront aberrations. Regarding efficacy and safety, 40 eyes (40%) had an unchanged CDVA; 32 eyes (32%) gained one line; and 11 eyes (11%) gained two lines. Fifteen eyes (15%) lost one line of CDVA, and two eyes (2%) lost two lines. Ninety-nine of the treated eyes (99%) had a postoperative UDVA better than 1.0, and 100 eyes (100%) had a UDVA better than 0.8. The mean decentered displacement was 0.17 ± 0.09 mm. The decentered displacement of all treated eyes (100%) was within 0.50 mm; 70 eyes (70%) were within 0.20 mm; and 90 eyes (90%) were within 0.30 mm. The vertical coma showed the greatest increase in magnitude. The magnitude of horizontal decentration was found to be associated with an induced horizontal coma. This study suggests that, although mild decentration occurred in the early learning curve, good visual outcomes were achieved after the SMILE surgery. Special efforts to minimize induced vertical coma are necessary. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

Adaptive Critic Nonlinear Robust Control: A Survey.

Science.gov (United States)

Wang, Ding; He, Haibo; Liu, Derong

2017-10-01

Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each other when performing intelligent optimization. They are both regarded as promising methods involving important components of evaluation and improvement, at the background of information technology, such as artificial intelligence, big data, and deep learning. Although great progresses have been achieved and surveyed when addressing nonlinear optimal control problems, the research on robustness of ADP-based control strategies under uncertain environment has not been fully summarized. Hence, this survey reviews the recent main results of adaptive-critic-based robust control design of continuous-time nonlinear systems. The ADP-based nonlinear optimal regulation is reviewed, followed by robust stabilization of nonlinear systems with matched uncertainties, guaranteed cost control design of unmatched plants, and decentralized stabilization of interconnected systems. Additionally, further comprehensive discussions are presented, including event-based robust control design, improvement of the critic learning rule, nonlinear H ∞ control design, and several notes on future perspectives. By applying the ADP-based optimal and robust control methods to a practical power system and an overhead crane plant, two typical examples are provided to verify the effectiveness of theoretical results. Overall, this survey is beneficial to promote the development of adaptive critic control methods with robustness guarantee and the construction of higher level intelligent systems.

The cerebellum does more than sensory prediction error-based learning in sensorimotor adaptation tasks.

Science.gov (United States)

Butcher, Peter A; Ivry, Richard B; Kuo, Sheng-Han; Rydz, David; Krakauer, John W; Taylor, Jordan A

2017-09-01

Individuals with damage to the cerebellum perform poorly in sensorimotor adaptation paradigms. This deficit has been attributed to impairment in sensory prediction error-based updating of an internal forward model, a form of implicit learning. These individuals can, however, successfully counter a perturbation when instructed with an explicit aiming strategy. This successful use of an instructed aiming strategy presents a paradox: In adaptation tasks, why do individuals with cerebellar damage not come up with an aiming solution on their own to compensate for their implicit learning deficit? To explore this question, we employed a variant of a visuomotor rotation task in which, before executing a movement on each trial, the participants verbally reported their intended aiming location. Compared with healthy control participants, participants with spinocerebellar ataxia displayed impairments in both implicit learning and aiming. This was observed when the visuomotor rotation was introduced abruptly ( experiment 1 ) or gradually ( experiment 2 ). This dual deficit does not appear to be related to the increased movement variance associated with ataxia: Healthy undergraduates showed little change in implicit learning or aiming when their movement feedback was artificially manipulated to produce similar levels of variability ( experiment 3 ). Taken together the results indicate that a consequence of cerebellar dysfunction is not only impaired sensory prediction error-based learning but also a difficulty in developing and/or maintaining an aiming solution in response to a visuomotor perturbation. We suggest that this dual deficit can be explained by the cerebellum forming part of a network that learns and maintains action-outcome associations across trials. NEW & NOTEWORTHY Individuals with cerebellar pathology are impaired in sensorimotor adaptation. This deficit has been attributed to an impairment in error-based learning, specifically, from a deficit in using sensory

Adaptation Provisioning with Respect to Learning Styles in a Web-Based Educational System: An Experimental Study

Science.gov (United States)

Popescu, E.

2010-01-01

Personalized instruction is seen as a desideratum of today's e-learning systems. The focus of this paper is on those platforms that use learning styles as personalization criterion called learning style-based adaptive educational systems. The paper presents an innovative approach based on an integrative set of learning preferences that alleviates…

Using the decentralized and liberalized electricity market microworld (LEMM) as an educational tool

International Nuclear Information System (INIS)

Pasaoglu, Guezay

2011-01-01

Decentralized and liberalized electricity market involves a great deal of interdisciplinary concepts, including economic, commercial, environmental and technological issues. Consequently, the system is complicated. Accordingly, nowadays introductory courses focusing on the electricity market dynamics have been added to the curriculum at many universities. However, as the electricity market dynamics are complicated, it is not straightforward for students to understand. A teaching tool to assist students to better understand strategic behaviors in the market is thus in high demand. Due to these reasons, Liberalized Electricity Market Microworld (LEMM), incorporating a system dynamics based simulation model, is developed. The LEMM's contribution to the students learning and understanding of the decentralized and liberalized electricity market dynamics have been explored by organizing game sessions with the LEMM for totally 49 students who participated in 'Energy Policy and Planning' course in Bogazici University. The findings obtained from the exploratory study reveal that the students improved their understanding of the liberalized and decentralized electricity market through the game session with the LEMM. In this paper, the general characteristics of the LEMM and the underlying model are presented, the microworlds', particularly the LEMM's potential contribution to learning and teaching is discussed. - Research highlights: → LEMM describes realistically the dynamics of liberalized and decentralized electricity markets. → LEMM is a system dynamics based microworld used as a teaching tool in universities. → The study reveals that student's learning and understanding improves significantly using LEMM. → Future target groups of the LEMM are energy policy makers and decision makers. → To improve the performance of the training, microworld based game sessions should be used.

Adaptive Trajectory Tracking Control using Reinforcement Learning for Quadrotor

Directory of Open Access Journals (Sweden)

Wenjie Lou

2016-02-01

Full Text Available Inaccurate system parameters and unpredicted external disturbances affect the performance of non-linear controllers. In this paper, a new adaptive control algorithm under the reinforcement framework is proposed to stabilize a quadrotor helicopter. Based on a command-filtered non-linear control algorithm, adaptive elements are added and learned by policy-search methods. To predict the inaccurate system parameters, a new kernel-based regression learning method is provided. In addition, Policy learning by Weighting Exploration with the Returns (PoWER and Return Weighted Regression (RWR are utilized to learn the appropriate parameters for adaptive elements in order to cancel the effect of external disturbance. Furthermore, numerical simulations under several conditions are performed, and the ability of adaptive trajectory-tracking control with reinforcement learning are demonstrated.

Adaptive and perceptual learning technologies in medical education and training.

Science.gov (United States)

Kellman, Philip J

2013-10-01

Recent advances in the learning sciences offer remarkable potential to improve medical education and maximize the benefits of emerging medical technologies. This article describes 2 major innovation areas in the learning sciences that apply to simulation and other aspects of medical learning: Perceptual learning (PL) and adaptive learning technologies. PL technology offers, for the first time, systematic, computer-based methods for teaching pattern recognition, structural intuition, transfer, and fluency. Synergistic with PL are new adaptive learning technologies that optimize learning for each individual, embed objective assessment, and implement mastery criteria. The author describes the Adaptive Response-Time-based Sequencing (ARTS) system, which uses each learner's accuracy and speed in interactive learning to guide spacing, sequencing, and mastery. In recent efforts, these new technologies have been applied in medical learning contexts, including adaptive learning modules for initial medical diagnosis and perceptual/adaptive learning modules (PALMs) in dermatology, histology, and radiology. Results of all these efforts indicate the remarkable potential of perceptual and adaptive learning technologies, individually and in combination, to improve learning in a variety of medical domains. Reprint & Copyright © 2013 Association of Military Surgeons of the U.S.

Decentralized Energy from Waste Systems

Directory of Open Access Journals (Sweden)

Blanca Antizar-Ladislao

2010-01-01

Full Text Available In the last five years or so, biofuels have been given notable consideration worldwide as an alternative to fossil fuels, due to their potential to reduce greenhouse gas emissions by partial replacement of oil as a transport fuel. The production of biofuels using a sustainable approach, should consider local production of biofuels, obtained from local feedstocks and adapted to the socio-economical and environmental characteristics of the particular region where they are developed. Thus, decentralized energy from waste systems will exploit local biomass to optimize their production and consumption. Waste streams such as agricultural and wood residues, municipal solid waste, vegetable oils, and algae residues can all be integrated in energy from waste systems. An integral optimization of decentralized energy from waste systems should not be based on the optimization of each single process, but the overall optimization of the whole process. This is by obtaining optimal energy and environmental benefits, as well as collateral beneficial co-products such as soil fertilizers which will result in a higher food crop production and carbon dioxide fixation which will abate climate change.

Decentralized energy from waste systems

International Nuclear Information System (INIS)

Antizar-Ladislao, B.; Turrion-Gomez, J. L.

2010-01-01

In the last five years or so, biofuels have been given notable consideration worldwide as an alternative to fossil fuels, due to their potential to reduce greenhouse gas emissions by partial replacement of oil as a transport fuel. The production of biofuels using a sustainable approach, should consider local production of biofuels, obtained from local feedstocks and adapted to the socio-economical and environmental characteristics of the particular region where they are developed. Thus, decentralized energy from waste systems will exploit local biomass to optimize their production and consumption. Waste streams such as agricultural and wood residues, municipal solid waste, vegetable oils, and algae residues can all be integrated in energy from waste systems. An integral optimization of decentralized energy from waste systems should not be based on the optimization of each single process, but the overall optimization of the whole process. This is by obtaining optimal energy and environmental benefits, as well as collateral beneficial co-products such as soil fertilizers which will result in a higher food crop production and carbon dioxide fixation which will abate climate change. (author)

LEARNING STYLES BASED ADAPTIVE INTELLIGENT TUTORING SYSTEMS: DOCUMENT ANALYSIS OF ARTICLES PUBLISHED BETWEEN 2001. AND 2016.

Directory of Open Access Journals (Sweden)

Amit Kumar

2017-12-01

Full Text Available Actualizing instructional intercessions to suit learner contrasts has gotten extensive consideration. Among these individual contrast factors, the observational confirmation in regards to the academic benefit of learning styles has been addressed, yet the examination on the issue proceeds. Late improvements in web-based executions have driven researchers to re-examine the learning styles in adaptive tutoring frameworks. Adaptivity in intelligent tutoring systems is strongly influenced by the learning style of a learner. This study involved extensive document analysis of adaptive tutoring systems based on learning styles. Seventy-eight studies in literature from 2001 to 2016 were collected and classified under select parameters such as main focus, purpose, research types, methods, types and levels of participants, field/area of application, learner modelling, data gathering tools used and research findings. The current studies reveal that majority of the studies defined a framework or architecture of adaptive intelligent tutoring system (AITS while others focused on impact of AITS on learner satisfaction and academic outcomes. Currents trends, gaps in literature and ications were discussed.

Decentralization in Air Transportation

NARCIS (Netherlands)

Udluft, H.

2017-01-01

In this work,we demonstrate that decentralized control can result in stable, efficient, and robust operations in the Air Transportation System. We implement decentralized control for aircraft taxiing operations and use Agent-Based Modeling and Simulation to analyze the resulting system behavior

Development of a pharmacy resident rotation to expand decentralized clinical pharmacy services.

Science.gov (United States)

Hill, John D; Williams, Jonathan P; Barnes, Julie F; Greenlee, Katie M; Cardiology, Bcps-Aq; Leonard, Mandy C

2017-07-15

The development of a pharmacy resident rotation to expand decentralized clinical pharmacy services is described. In an effort to align with the initiatives proposed within the ASHP Practice Advancement Initiative, the department of pharmacy at Cleveland Clinic, a 1,400-bed academic, tertiary acute care medical center in Cleveland, Ohio, established a goal to provide decentralized clinical pharmacy services for 100% of patient care units within the hospital. Patient care units that previously had no decentralized pharmacy services were evaluated to identify opportunities for expansion. Metrics analyzed included number of medication orders verified per hour, number of pharmacy dosing consultations, and number of patient discharge counseling sessions. A pilot study was conducted to assess the feasibility of this service and potential resident learning opportunities. A learning experience description was drafted, and feedback was solicited regarding the development of educational components utilized throughout the rotation. Pharmacists who were providing services to similar patient populations were identified to serve as preceptors. Staff pharmacists were deployed to previously uncovered patient care units, with pharmacy residents providing decentralized services on previously covered areas. A rotating preceptor schedule was developed based on geographic proximity and clinical expertise. An initial postimplementation assessment of this resident-driven service revealed that pharmacy residents provided a comparable level of pharmacy services to that of staff pharmacists. Feedback collected from nurses, physicians, and pharmacy staff also supported residents' ability to operate sufficiently in this role to optimize patient care. A learning experience developed for pharmacy residents in a large medical center enabled the expansion of decentralized clinical services without requiring additional pharmacist full-time equivalents. Copyright © 2017 by the American Society of

EEG-Based Emotion Recognition Using Deep Learning Network with Principal Component Based Covariate Shift Adaptation

Directory of Open Access Journals (Sweden)

Suwicha Jirayucharoensak

2014-01-01

Full Text Available Automatic emotion recognition is one of the most challenging tasks. To detect emotion from nonstationary EEG signals, a sophisticated learning algorithm that can represent high-level abstraction is required. This study proposes the utilization of a deep learning network (DLN to discover unknown feature correlation between input signals that is crucial for the learning task. The DLN is implemented with a stacked autoencoder (SAE using hierarchical feature learning approach. Input features of the network are power spectral densities of 32-channel EEG signals from 32 subjects. To alleviate overfitting problem, principal component analysis (PCA is applied to extract the most important components of initial input features. Furthermore, covariate shift adaptation of the principal components is implemented to minimize the nonstationary effect of EEG signals. Experimental results show that the DLN is capable of classifying three different levels of valence and arousal with accuracy of 49.52% and 46.03%, respectively. Principal component based covariate shift adaptation enhances the respective classification accuracy by 5.55% and 6.53%. Moreover, DLN provides better performance compared to SVM and naive Bayes classifiers.

Adaptive Learning Rule for Hardware-based Deep Neural Networks Using Electronic Synapse Devices

OpenAIRE

Lim, Suhwan; Bae, Jong-Ho; Eum, Jai-Ho; Lee, Sungtae; Kim, Chul-Heung; Kwon, Dongseok; Park, Byung-Gook; Lee, Jong-Ho

2017-01-01

In this paper, we propose a learning rule based on a back-propagation (BP) algorithm that can be applied to a hardware-based deep neural network (HW-DNN) using electronic devices that exhibit discrete and limited conductance characteristics. This adaptive learning rule, which enables forward, backward propagation, as well as weight updates in hardware, is helpful during the implementation of power-efficient and high-speed deep neural networks. In simulations using a three-layer perceptron net...

(DeCentralization of the Global Informational Ecosystem

Directory of Open Access Journals (Sweden)

Johanna Möller

2017-09-01

Full Text Available Centralization and decentralization are key concepts in debates that focus on the (antidemocratic character of digital societies. Centralization is understood as the control over communication and data flows, and decentralization as giving it (back to users. Communication and media research focuses on centralization put forward by dominant digital media platforms, such as Facebook and Google, and governments. Decentralization is investigated regarding its potential in civil society, i.e., hacktivism, (encryption technologies, and grass-root technology movements. As content-based media companies increasingly engage with technology, they move into the focus of critical media studies. Moreover, as formerly nationally oriented companies now compete with global media platforms, they share several interests with civil society decentralization agents. Based on 26 qualitative interviews with leading media managers, we investigate (decentralization strategies applied by content-oriented media companies. Theoretically, this perspective on media companies as agents of (decentralization expands (decentralization research beyond traditional democratic stakeholders by considering economic actors within the “global informational ecosystem” (Birkinbine, Gómez, & Wasko, 2017. We provide a three-dimensional framework to empirically investigate (decentralization. From critical media studies, we borrow the (decentralization of data and infrastructures, from media business research, the (decentralization of content distribution.

A decentralized receptance-based damage detection strategy for wireless smart sensors

International Nuclear Information System (INIS)

Jang, Shinae; Spencer Jr, Billie F; Sim, Sung-Han

2012-01-01

Various structural health monitoring strategies have been proposed recently that can be implemented in the decentralized computing environment intrinsic to wireless smart sensor networks (WSSN). Many are based on changes in the experimentally determined flexibility matrix for the structure under consideration. However, the flexibility matrix contains only static information; much richer information is available by considering the dynamic flexibility, or receptance, of the structure. Recently, the stochastic dynamic damage locating vector (SDDLV) method was proposed based on changes of dynamic flexibility matrices employing centrally collected output-only measurements. This paper investigates the potential of the SDDLV method for implementation on a network of wireless smart sensors, where a decentralized, hierarchical, in-network processing approach is used to address issues of scalability of the SDDLV algorithm. Two approaches to aggregate results are proposed that provide robust estimates of damage locations. The efficacy of the developed strategy is first verified using wired sensors emulating a wireless sensor network. Subsequently, the decentralized damage detection strategy is implemented on MEMSIC’s Imote2 smart sensor platform and validated experimentally on a laboratory scale truss bridge. (paper)

Adaptive nodes enrich nonlinear cooperative learning beyond traditional adaptation by links.

Science.gov (United States)

Sardi, Shira; Vardi, Roni; Goldental, Amir; Sheinin, Anton; Uzan, Herut; Kanter, Ido

2018-03-23

Physical models typically assume time-independent interactions, whereas neural networks and machine learning incorporate interactions that function as adjustable parameters. Here we demonstrate a new type of abundant cooperative nonlinear dynamics where learning is attributed solely to the nodes, instead of the network links which their number is significantly larger. The nodal, neuronal, fast adaptation follows its relative anisotropic (dendritic) input timings, as indicated experimentally, similarly to the slow learning mechanism currently attributed to the links, synapses. It represents a non-local learning rule, where effectively many incoming links to a node concurrently undergo the same adaptation. The network dynamics is now counterintuitively governed by the weak links, which previously were assumed to be insignificant. This cooperative nonlinear dynamic adaptation presents a self-controlled mechanism to prevent divergence or vanishing of the learning parameters, as opposed to learning by links, and also supports self-oscillations of the effective learning parameters. It hints on a hierarchical computational complexity of nodes, following their number of anisotropic inputs and opens new horizons for advanced deep learning algorithms and artificial intelligence based applications, as well as a new mechanism for enhanced and fast learning by neural networks.

Feedback-linearization and feedback-feedforward decentralized control for multimachine power system

Energy Technology Data Exchange (ETDEWEB)

De Tuglie, Enrico [Dipartimento di Ingegneria dell' Ambiente, e per lo Sviluppo Sostenibile - DIASS, Politecnico di Bari, Viale del Turismo 8, 74100 Taranto (Italy); Iannone, Silvio Marcello; Torelli, Francesco [Dipartimento di Elettrotecnica, ed Elettronica - DEE, Politecnico di Bari, Via Re David 200, 70125 Bari (Italy)

2008-03-15

In this paper a decentralized nonlinear controller for large-scale power systems is investigated. The proposed controller design is based on the input-output feedback linearization methodology. In order to overcome computational difficulties in adopting such methodology, the overall interconnected nonlinear system, given as n-order, is analyzed as a cascade connection of an n{sub 1}-order nonlinear subsystem and an n{sub 2}-order linear subsystem. The controller design is obtained by applying input-output feedback linearization to the nonlinear subsystem and adopting a tracking control scheme, based on feedback-feedforward technique, for the linear subsystem. In the assumed system model, which is characterised by an interconnected structure between generating units, a decentralised adaptive controller is implemented by decentralizing these constraints. The use of a totally decentralised controller implies a system performance decay with respect to performance when the system is equipped with a centralised controller. Fortunately, the robustness of the proposed controller, based on input-output feedback procedure, guarantees good performance in terms of disturbance even when disturbances are caused by decentralization of interconnection constraints. Test results, provided on the IEEE 30 bus test system, demonstrate the effectiveness and practical applicability of proposed methodology. (author)

Statistical Learning Framework with Adaptive Retraining for Condition-Based Maintenance

International Nuclear Information System (INIS)

An, Sang Ha; Chang, Soon Heung; Heo, Gyun Young; Seo, Ho Joon; Kim, Su Young

2009-01-01

As systems become more complex and more critical in our daily lives, the need for the maintenance based on the reliable monitoring and diagnosis has become more apparent. However, in reality, the general opinion has been that 'maintenance is a necessary evil' or 'nothing can be done to improve maintenance costs'. Perhaps these were true statements twenty years ago when many of the diagnostic technologies were not fully developed. The developments of microprocessor or computer based instrumentation that can be used to monitor the operating condition of plant equipment, machinery and systems have provided the means to manage the maintenance operation. They have provided the means to reduce or eliminate unnecessary repairs, prevent catastrophic machine failures and reduce the negative impact of the maintenance operation on the profitability of manufacturing and production plants. Condition-based maintenance (CBM) techniques help determine the condition of in-service equipment in order to predict when maintenance should be performed. Most of the statistical learning techniques are only valid as long as the physics of a system does not change. If any significant change such as the replacement of a component or equipment occurs in the system, the statistical learning model should be re-trained or re-developed to adapt the new system. In this research, authors will propose a statistical learning framework which can be applicable for various CBMs, and the concept of the adaptive retraining technique will be described to support the execution of the framework so that the monitoring system does not need to be re-developed or re-trained even though there are any significant changes in the system or component

Learner Open Modeling in Adaptive Mobile Learning System for Supporting Student to Learn English

Directory of Open Access Journals (Sweden)

Van Cong Pham

2011-10-01

Full Text Available This paper represents a personalized context-aware mobile learning architecture for supporting student to learn English as foreign language in order to prepare for TOEFL test. We consider how to apply open learner modeling techniques to adapt contents for different learners based on context, which includes location, amount of time to learn, the manner as well as learner's knowledge in learning progress. Through negotiation with system, the editable learner model will be updated to support adaptive engine to select adaptive contents meeting learner's demands. Empirical testing results for students who used application prototype indicate that interaction user modeling is helpful in supporting learner to learn adaptive materials.

Decentralized neural control application to robotics

CERN Document Server

Garcia-Hernandez, Ramon; Sanchez, Edgar N; Alanis, Alma y; Ruz-Hernandez, Jose A

2017-01-01

This book provides a decentralized approach for the identification and control of robotics systems. It also presents recent research in decentralized neural control and includes applications to robotics. Decentralized control is free from difficulties due to complexity in design, debugging, data gathering and storage requirements, making it preferable for interconnected systems. Furthermore, as opposed to the centralized approach, it can be implemented with parallel processors. This approach deals with four decentralized control schemes, which are able to identify the robot dynamics. The training of each neural network is performed on-line using an extended Kalman filter (EKF). The first indirect decentralized control scheme applies the discrete-time block control approach, to formulate a nonlinear sliding manifold. The second direct decentralized neural control scheme is based on the backstepping technique, approximated by a high order neural network. The third control scheme applies a decentralized neural i...

A planning quality evaluation tool for prostate adaptive IMRT based on machine learning

International Nuclear Information System (INIS)

Zhu Xiaofeng; Ge Yaorong; Li Taoran; Thongphiew, Danthai; Yin Fangfang; Wu, Q Jackie

2011-01-01

Purpose: To ensure plan quality for adaptive IMRT of the prostate, we developed a quantitative evaluation tool using a machine learning approach. This tool generates dose volume histograms (DVHs) of organs-at-risk (OARs) based on prior plans as a reference, to be compared with the adaptive plan derived from fluence map deformation. Methods: Under the same configuration using seven-field 15 MV photon beams, DVHs of OARs (bladder and rectum) were estimated based on anatomical information of the patient and a model learned from a database of high quality prior plans. In this study, the anatomical information was characterized by the organ volumes and distance-to-target histogram (DTH). The database consists of 198 high quality prostate plans and was validated with 14 cases outside the training pool. Principal component analysis (PCA) was applied to DVHs and DTHs to quantify their salient features. Then, support vector regression (SVR) was implemented to establish the correlation between the features of the DVH and the anatomical information. Results: DVH/DTH curves could be characterized sufficiently just using only two or three truncated principal components, thus, patient anatomical information was quantified with reduced numbers of variables. The evaluation of the model using the test data set demonstrated its accuracy ∼80% in prediction and effectiveness in improving ART planning quality. Conclusions: An adaptive IMRT plan quality evaluation tool based on machine learning has been developed, which estimates OAR sparing and provides reference in evaluating ART.

On the applicability of the decentralized control mechanism extracted from the true slime mold: a robotic case study with a serpentine robot

International Nuclear Information System (INIS)

Sato, Takahide; Kano, Takeshi; Ishiguro, Akio

2011-01-01

A systematic method for an autonomous decentralized control system is still lacking, despite its appealing concept. In order to alleviate this, we focused on the amoeboid locomotion of the true slime mold, and extracted a design scheme for the decentralized control mechanism that leads to adaptive behavior for the entire system, based on the so-called discrepancy function. In this paper, we intensively investigate the universality of this design scheme by applying it to a different type of locomotion based on a 'synthetic approach'. As a first step, we implement this design scheme to the control of a real physical two-dimensional serpentine robot that exhibits slithering locomotion. The experimental results show that the robot exhibits adaptive behavior and responds to the environmental changes; it is also robust against malfunctions of the body segments due to the local sensory feedback control that is based on the discrepancy function. We expect the results to shed new light on the methodology of autonomous decentralized control systems.

Teacher-Led Design of an Adaptive Learning Environment

Science.gov (United States)

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

2016-01-01

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

Representing adaptive and adaptable Units of Learning. How to model personalized eLearning in IMS Learning Design

OpenAIRE

Burgos, Daniel; Tattersall, Colin; Koper, Rob

2006-01-01

Burgos, D., Tattersall, C., & Koper, E. J. R. (2007). Representing adaptive and adaptable Units of Learning. How to model personalized eLearning in IMS Learning Design. In B. Fernández Manjon, J. M. Sanchez Perez, J. A. Gómez Pulido, M. A. Vega Rodriguez & J. Bravo (Eds.), Computers and Education: E-learning - from theory to practice. Germany: Kluwer.

Performance Analysis of the Decentralized Eigendecomposition and ESPRIT Algorithm

Science.gov (United States)

Suleiman, Wassim; Pesavento, Marius; Zoubir, Abdelhak M.

2016-05-01

In this paper, we consider performance analysis of the decentralized power method for the eigendecomposition of the sample covariance matrix based on the averaging consensus protocol. An analytical expression of the second order statistics of the eigenvectors obtained from the decentralized power method which is required for computing the mean square error (MSE) of subspace-based estimators is presented. We show that the decentralized power method is not an asymptotically consistent estimator of the eigenvectors of the true measurement covariance matrix unless the averaging consensus protocol is carried out over an infinitely large number of iterations. Moreover, we introduce the decentralized ESPRIT algorithm which yields fully decentralized direction-of-arrival (DOA) estimates. Based on the performance analysis of the decentralized power method, we derive an analytical expression of the MSE of DOA estimators using the decentralized ESPRIT algorithm. The validity of our asymptotic results is demonstrated by simulations.

Using Data to Understand How to Better Design Adaptive Learning

Science.gov (United States)

Liu, Min; Kang, Jina; Zou, Wenting; Lee, Hyeyeon; Pan, Zilong; Corliss, Stephanie

2017-01-01

There is much enthusiasm in higher education about the benefits of adaptive learning and using big data to investigate learning processes to make data-informed educational decisions. The benefits of adaptive learning to achieve personalized learning are obvious. Yet, there lacks evidence-based research to understand how data such as user behavior…

Neuromodulatory adaptive combination of correlation-based learning in cerebellum and reward-based learning in basal ganglia for goal-directed behavior control.

Science.gov (United States)

Dasgupta, Sakyasingha; Wörgötter, Florentin; Manoonpong, Poramate

2014-01-01

Goal-directed decision making in biological systems is broadly based on associations between conditional and unconditional stimuli. This can be further classified as classical conditioning (correlation-based learning) and operant conditioning (reward-based learning). A number of computational and experimental studies have well established the role of the basal ganglia in reward-based learning, where as the cerebellum plays an important role in developing specific conditioned responses. Although viewed as distinct learning systems, recent animal experiments point toward their complementary role in behavioral learning, and also show the existence of substantial two-way communication between these two brain structures. Based on this notion of co-operative learning, in this paper we hypothesize that the basal ganglia and cerebellar learning systems work in parallel and interact with each other. We envision that such an interaction is influenced by reward modulated heterosynaptic plasticity (RMHP) rule at the thalamus, guiding the overall goal directed behavior. Using a recurrent neural network actor-critic model of the basal ganglia and a feed-forward correlation-based learning model of the cerebellum, we demonstrate that the RMHP rule can effectively balance the outcomes of the two learning systems. This is tested using simulated environments of increasing complexity with a four-wheeled robot in a foraging task in both static and dynamic configurations. Although modeled with a simplified level of biological abstraction, we clearly demonstrate that such a RMHP induced combinatorial learning mechanism, leads to stabler and faster learning of goal-directed behaviors, in comparison to the individual systems. Thus, in this paper we provide a computational model for adaptive combination of the basal ganglia and cerebellum learning systems by way of neuromodulated plasticity for goal-directed decision making in biological and bio-mimetic organisms.

Fractal Adaptive Web Service for Mobile Learning

Directory of Open Access Journals (Sweden)

Ichraf Tirellil

2006-06-01

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

Representing adaptive and adaptable Units of Learning. How to model personalized eLearning in IMS Learning Design

NARCIS (Netherlands)

Burgos, Daniel; Tattersall, Colin; Koper, Rob

2006-01-01

Burgos, D., Tattersall, C., & Koper, E. J. R. (2007). Representing adaptive and adaptable Units of Learning. How to model personalized eLearning in IMS Learning Design. In B. Fernández Manjon, J. M. Sanchez Perez, J. A. Gómez Pulido, M. A. Vega Rodriguez & J. Bravo (Eds.), Computers and Education:

Learning Experiences Reuse Based on an Ontology Modeling to Improve Adaptation in E-Learning Systems

Science.gov (United States)

Hadj M'tir, Riadh; Rumpler, Béatrice; Jeribi, Lobna; Ben Ghezala, Henda

2014-01-01

Current trends in e-Learning focus mainly on personalizing and adapting the learning environment and learning process. Although their increasingly number, theses researches often ignore the concepts of capitalization and reuse of learner experiences which can be exploited later by other learners. Thus, the major challenge of distance learning is…

Coordinating Decentralized Learning and Conflict Resolution across Agent Boundaries

Science.gov (United States)

Cheng, Shanjun

2012-01-01

It is crucial for embedded systems to adapt to the dynamics of open environments. This adaptation process becomes especially challenging in the context of multiagent systems because of scalability, partial information accessibility and complex interaction of agents. It is a challenge for agents to learn good policies, when they need to plan and…

Game-Based Virtual Worlds as Decentralized Virtual Activity Systems

Science.gov (United States)

Scacchi, Walt

There is widespread interest in the development and use of decentralized systems and virtual world environments as possible new places for engaging in collaborative work activities. Similarly, there is widespread interest in stimulating new technological innovations that enable people to come together through social networking, file/media sharing, and networked multi-player computer game play. A decentralized virtual activity system (DVAS) is a networked computer supported work/play system whose elements and social activities can be both virtual and decentralized (Scacchi et al. 2008b). Massively multi-player online games (MMOGs) such as World of Warcraft and online virtual worlds such as Second Life are each popular examples of a DVAS. Furthermore, these systems are beginning to be used for research, deve-lopment, and education activities in different science, technology, and engineering domains (Bainbridge 2007, Bohannon et al. 2009; Rieber 2005; Scacchi and Adams 2007; Shaffer 2006), which are also of interest here. This chapter explores two case studies of DVASs developed at the University of California at Irvine that employ game-based virtual worlds to support collaborative work/play activities in different settings. The settings include those that model and simulate practical or imaginative physical worlds in different domains of science, technology, or engineering through alternative virtual worlds where players/workers engage in different kinds of quests or quest-like workflows (Jakobsson 2006).

Wave field synthesis, adaptive wave field synthesis and ambisonics using decentralized transformed control: Potential applications to sound field reproduction and active noise control

Science.gov (United States)

Gauthier, Philippe-Aubert; Berry, Alain; Woszczyk, Wieslaw

2005-09-01

Sound field reproduction finds applications in listening to prerecorded music or in synthesizing virtual acoustics. The objective is to recreate a sound field in a listening environment. Wave field synthesis (WFS) is a known open-loop technology which assumes that the reproduction environment is anechoic. Classical WFS, therefore, does not perform well in a real reproduction space such as room. Previous work has suggested that it is physically possible to reproduce a progressive wave field in-room situation using active control approaches. In this paper, a formulation of adaptive wave field synthesis (AWFS) introduces practical possibilities for an adaptive sound field reproduction combining WFS and active control (with WFS departure penalization) with a limited number of error sensors. AWFS includes WFS and closed-loop ``Ambisonics'' as limiting cases. This leads to the modification of the multichannel filtered-reference least-mean-square (FXLMS) and the filtered-error LMS (FELMS) adaptive algorithms for AWFS. Decentralization of AWFS for sound field reproduction is introduced on the basis of sources' and sensors' radiation modes. Such decoupling may lead to decentralized control of source strength distributions and may reduce computational burden of the FXLMS and the FELMS algorithms used for AWFS. [Work funded by NSERC, NATEQ, Université de Sherbrooke and VRQ.] Ultrasound/Bioresponse to

Research on Calculation of the IOL Tilt and Decentration Based on Surface Fitting

OpenAIRE

Li, Lin; Wang, Ke; Yan, Yan; Song, Xudong; Liu, Zhicheng

2013-01-01

The tilt and decentration of intraocular lens (IOL) result in defocussing, astigmatism, and wavefront aberration after operation. The objective is to give a method to estimate the tilt and decentration of IOL more accurately. Based on AS-OCT images of twelve eyes from eight cases with subluxation lens after operation, we fitted spherical equation to the data obtained from the images of the anterior and posterior surfaces of the IOL. By the established relationship between IOL tilt (decentrati...

A Decentralized Eigenvalue Computation Method for Spectrum Sensing Based on Average Consensus

Science.gov (United States)

Mohammadi, Jafar; Limmer, Steffen; Stańczak, Sławomir

2016-07-01

This paper considers eigenvalue estimation for the decentralized inference problem for spectrum sensing. We propose a decentralized eigenvalue computation algorithm based on the power method, which is referred to as generalized power method GPM; it is capable of estimating the eigenvalues of a given covariance matrix under certain conditions. Furthermore, we have developed a decentralized implementation of GPM by splitting the iterative operations into local and global computation tasks. The global tasks require data exchange to be performed among the nodes. For this task, we apply an average consensus algorithm to efficiently perform the global computations. As a special case, we consider a structured graph that is a tree with clusters of nodes at its leaves. For an accelerated distributed implementation, we propose to use computation over multiple access channel (CoMAC) as a building block of the algorithm. Numerical simulations are provided to illustrate the performance of the two algorithms.

Model-Based Design of Tree WSNs for Decentralized Detection

Directory of Open Access Journals (Sweden)

Ashraf Tantawy

2015-08-01

Full Text Available The classical decentralized detection problem of finding the optimal decision rules at the sensor and fusion center, as well as variants that introduce physical channel impairments have been studied extensively in the literature. The deployment of WSNs in decentralized detection applications brings new challenges to the field. Protocols for different communication layers have to be co-designed to optimize the detection performance. In this paper, we consider the communication network design problem for a tree WSN. We pursue a system-level approach where a complete model for the system is developed that captures the interactions between different layers, as well as different sensor quality measures. For network optimization, we propose a hierarchical optimization algorithm that lends itself to the tree structure, requiring only local network information. The proposed design approach shows superior performance over several contentionless and contention-based network design approaches.

Integrative learning for practicing adaptive resource management

Directory of Open Access Journals (Sweden)

Craig A. McLoughlin

2015-03-01

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

AN INDUCTIVE, INTERACTIVE AND ADAPTIVE HYBRID PROBLEM-BASED LEARNING METHODOLOGY: APPLICATION TO STATISTICS

Directory of Open Access Journals (Sweden)

ADA ZHENG

2011-10-01

Full Text Available We have developed an innovative hybrid problem-based learning (PBL methodology. The methodology has the following distinctive features: i Each complex question was decomposed into a set of coherent finer subquestions by following the carefully designed criteria to maintain a delicate balance between guiding the students and inspiring them to think independently. This learning methodology enabled the students to solve the complex questions progressively in an inductive context. ii Facilitated by the utilization of our web-based learning systems, the teacher was able to interact with the students intensively and could allocate more teaching time to provide tailor-made feedback for individual student. The students were actively engaged in the learning activities, stimulated by the intensive interaction. iii The answers submitted by the students could be automatically consolidated in the report of the Moodle system in real-time. The teacher could adjust the teaching schedule and focus of the class to adapt to the learning progress of the students by analysing the automatically generated report and log files of the web-based learning system. As a result, the attendance rate of the students increased from about 50% to more than 90%, and the students’ learning motivation have been significantly enhanced.

Distance Constrained Based Adaptive Flocking Control for Multiagent Networks with Time Delay

Directory of Open Access Journals (Sweden)

Qing Zhang

2015-01-01

Full Text Available The flocking control of multiagent system is a new type of decentralized control method, which has aroused great attention. The paper includes a detailed research in terms of distance constrained based adaptive flocking control for multiagent system with time delay. Firstly, the program on the adaptive flocking with time delay of multiagent is proposed. Secondly, a kind of adaptive controllers and updating laws are presented. According to the Lyapunov stability theory, it is proved that the distance between agents can be larger than a constant during the motion evolution. What is more, velocities of each agent come to the same asymptotically. Finally, the analytical results can be verified by a numerical example.

Seeing the light : adapting to climate change with decentralized renewable energy in developing countries

International Nuclear Information System (INIS)

Venema, H.D.; Cisse, M.

2004-01-01

This book presents innovative and sustainable ways to respond to climate change with particular reference to decentralized renewable energy (DRE) projects. It presents the experience of developing DRE projects in five developing countries, Argentina, Bangladesh, Brazil, Senegal and Zimbabwe. The conditions under which these countries can support DRE through the Kyoto Protocol's Clean Development Mechanism were also examined. Some policy recommendations were proposed for more dynamic DRE support for the Kyoto era. The Clean Development Mechanism was examined as a key financial tool for supporting DRE. The Intergovernmental Panel on Climate Change (IPCC) states that the least developed countries are the least equipped with adaptive capacity, and therefore most vulnerable to climate change. The IPCC claims that climate adaptation and sustainable development can be compatible if policies are made to lessen resource pressure, improve environmental risk management and improve the prosperity of the poorest members of society. This book presents a framework for introducing modern energy services through DRE that can stabilize the socio-economics of a developing country. The main implications of rural energy deprivation include deforestation and ecosystem degradation, chronic rural poverty and high vulnerability to the adverse effects of climate change. refs., tabs., figs

Convergent Double Auction Mechanism for a Prosumers’ Decentralized Smart Grid

Directory of Open Access Journals (Sweden)

Tadahiro Taniguchi

2015-10-01

Full Text Available In this paper, we propose a novel automated double auction mechanism called convergent linear function submission-based double-auction (CLFS-DA for a prosumers’ decentralized smart grid. The target decentralized smart grid is a regional electricity network that consists of many prosumers that have a battery and a renewable energy-based generator, such as photovoltaic cells. In the proposed double-auction mechanism, each intelligent software agent representing each prosumer submits linear demand and supply functions to an automated regional electricity market where they are registered. It is proven that the CLFS-DA mechanism is guaranteed to obtain one of the global optimal price profiles in addition to it achieving an exact balance between demand and supply, even through the learning period. The proof of convergence is provided on the basis of the theory of LFS-DA, which gives a clear bridge between a function submission-based double auction and a dual decomposition (DD-based real-time pricing procedure. The performance of the proposed mechanism is demonstrated numerically through a simulation experiment.

A multi-agent decentralized energy management system based on distributed intelligence for the design and control of autonomous polygeneration microgrids

International Nuclear Information System (INIS)

Karavas, Christos-Spyridon; Kyriakarakos, George; Arvanitis, Konstantinos G.; Papadakis, George

2015-01-01

Highlights: • A decentralized energy management system based on multi agent systems theory. • A decentralized energy management system is technically feasible. • A decentralized approach utilizes the devices better than a centralized one. • A decentralized energy management system is economically competitive. - Abstract: The autonomous polygeneration microgrid topology has been developed in order to cover holistically needs in a remote area such as electrical energy, space heating and cooling, potable water through desalination and hydrogen as fuel for transportation. The existence of an advanced energy management system is essential for the operation of an autonomous polygeneration microgrid. So far, energy management systems based on a centralized management and control have been developed for the autonomous polygeneration microgrid topology based on computational intelligence approaches. A decentralized management and control energy management system can have important benefits, when taking into consideration the autonomous character of these microgrids. This paper presents the design and investigation of a decentralized energy management system for the autonomous polygeneration microgrid topology. The decentralized energy management system gives the possibility to control each unit of the microgrid independently. The most important advantage of using a decentralized architecture is that the managed microgrid has much higher chances of partial operation in cases when malfunctions occur at different parts of it, instead of a complete system breakdown. The designed system was based on a multi-agent system and employed Fuzzy Cognitive Maps for its implementation. It was then compared through a case study with an existing centralized energy management system. The technical performance of the decentralized solution performance is on par with the existing centralized one, presenting improvements in financial and operational terms for the implementation and

Fully Decentralized Semi-supervised Learning via Privacy-preserving Matrix Completion.

Science.gov (United States)

Fierimonte, Roberto; Scardapane, Simone; Uncini, Aurelio; Panella, Massimo

2016-08-26

Distributed learning refers to the problem of inferring a function when the training data are distributed among different nodes. While significant work has been done in the contexts of supervised and unsupervised learning, the intermediate case of Semi-supervised learning in the distributed setting has received less attention. In this paper, we propose an algorithm for this class of problems, by extending the framework of manifold regularization. The main component of the proposed algorithm consists of a fully distributed computation of the adjacency matrix of the training patterns. To this end, we propose a novel algorithm for low-rank distributed matrix completion, based on the framework of diffusion adaptation. Overall, the distributed Semi-supervised algorithm is efficient and scalable, and it can preserve privacy by the inclusion of flexible privacy-preserving mechanisms for similarity computation. The experimental results and comparison on a wide range of standard Semi-supervised benchmarks validate our proposal.

An Adaptive Learning Based Network Selection Approach for 5G Dynamic Environments

Directory of Open Access Journals (Sweden)

Xiaohong Li

2018-03-01

Full Text Available Networks will continue to become increasingly heterogeneous as we move toward 5G. Meanwhile, the intelligent programming of the core network makes the available radio resource be more changeable rather than static. In such a dynamic and heterogeneous network environment, how to help terminal users select optimal networks to access is challenging. Prior implementations of network selection are usually applicable for the environment with static radio resources, while they cannot handle the unpredictable dynamics in 5G network environments. To this end, this paper considers both the fluctuation of radio resources and the variation of user demand. We model the access network selection scenario as a multiagent coordination problem, in which a bunch of rationally terminal users compete to maximize their benefits with incomplete information about the environment (no prior knowledge of network resource and other users’ choices. Then, an adaptive learning based strategy is proposed, which enables users to adaptively adjust their selections in response to the gradually or abruptly changing environment. The system is experimentally shown to converge to Nash equilibrium, which also turns out to be both Pareto optimal and socially optimal. Extensive simulation results show that our approach achieves significantly better performance compared with two learning and non-learning based approaches in terms of load balancing, user payoff and the overall bandwidth utilization efficiency. In addition, the system has a good robustness performance under the condition with non-compliant terminal users.

Adaptive Hypermedia Systems for E-Learning

Directory of Open Access Journals (Sweden)

Aammou Souhaib

2010-11-01

Full Text Available The domain of traditional hypermedia is revolutionized by the arrival of the concept of adaptation. Currently the domain of Adaptive Hypermedia Systems (AHS is constantly growing. A major goal of current research is to provide a personalized educational experience that meets the needs specific to each learner (knowledge level, goals, motivation etc.... In this article we have studied the possibility of implementing traditional features of adaptive hypermedia in an open environment, and discussed the standards for describing learning objects and architectural models based on the use of ontologies as a prerequisite for such an adaptation.

Partially Decentralized Control Architectures for Satellite Formations

Science.gov (United States)

Carpenter, J. Russell; Bauer, Frank H.

2002-01-01

In a partially decentralized control architecture, more than one but less than all nodes have supervisory capability. This paper describes an approach to choosing the number of supervisors in such au architecture, based on a reliability vs. cost trade. It also considers the implications of these results for the design of navigation systems for satellite formations that could be controlled with a partially decentralized architecture. Using an assumed cost model, analytic and simulation-based results indicate that it may be cheaper to achieve a given overall system reliability with a partially decentralized architecture containing only a few supervisors, than with either fully decentralized or purely centralized architectures. Nominally, the subset of supervisors may act as centralized estimation and control nodes for corresponding subsets of the remaining subordinate nodes, and act as decentralized estimation and control peers with respect to each other. However, in the context of partially decentralized satellite formation control, the absolute positions and velocities of each spacecraft are unique, so that correlations which make estimates using only local information suboptimal only occur through common biases and process noise. Covariance and monte-carlo analysis of a simplified system show that this lack of correlation may allow simplification of the local estimators while preserving the global optimality of the maneuvers commanded by the supervisors.

Adaptive Management of Communication in the Chamilo System of Distant Learning

OpenAIRE

Yatsenko Roman Nikolaevich; Polevich Olesya V.

2012-01-01

The article considers the communication management within an adaptive system of distance learning. We present two-circuit interaction system of the adaptive system. We consider the implementation of management communication in distance learning system based on the platform Chamilo.

Soft systems thinking and social learning for adaptive management.

Science.gov (United States)

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

2012-02-01

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

Remote handling of decentralized power generation plants; Fernwirken von dezentralen Energieerzeugungsanlagen

Energy Technology Data Exchange (ETDEWEB)

Conrad, Michael [IDS GmbH, Ettlingen (Germany). Geschaeftsbereich Entwicklung-Prozessautomatisierung; Thomas, Ralf [IDS GmbH, Ettlingen (Germany). Bereich Business Development und Marketing

2011-05-15

The incresing number of decentral power generation systems requires new grid solutions, i.e. the so-called smart grids. One important function is the monitoring and control, e.g. of decentral PV, wind power and cogeneration systems. The data interfaces used are highly diverse and as a rule are taken from measuring and automation technology, i.e. they must be adapted to the data models and transmission procedures of remote control and guidance systems. A compact protocol gateway enables standardized control and diagnosis.

Decentralization and the local development state

DEFF Research Database (Denmark)

Emmenegger, Rony Hugo

2016-01-01

This article explores the politics of decentralization and state-peasant encounters in rural Oromiya, Ethiopia. Breaking with a centralized past, the incumbent government of the Ethiopian People's Revolutionary Democratic Front (EPRDF) committed itself to a decentralization policy in the early 1990......s and has since then created a number of new sites for state-citizen interactions. In the context of electoral authoritarianism, however, decentralization has been interpreted as a means for the expansion of the party-state at the grass-roots level. Against this backdrop, this article attempts...... between the 2005 and 2010 elections. Based on ethnographic field research, the empirical case presented discloses that decentralization and state-led development serve the expansion of state power into rural areas, but that state authority is simultaneously constituted and undermined in the course...

INTUITEL and the Hypercube Model - Developing Adaptive Learning Environments

Directory of Open Access Journals (Sweden)

Kevin Fuchs

2016-06-01

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

Creating adaptive environment for e-learning courses

Directory of Open Access Journals (Sweden)

Bozidar Radenkovic

2009-06-01

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

A Decentralized Multi-Agent-Based Approach for Low Voltage Microgrid Restoration

Directory of Open Access Journals (Sweden)

Ebrahim Rokrok

2017-09-01

Full Text Available Although a well-organized power system is less subject to blackouts, the existence of a proper restoration plan is nevertheless still essential. The goal of a restoration plan is to bring the power system back to its normal operating conditions in the shortest time after a blackout occurs and to minimize the impact of the blackout on society. This paper presents a decentralized multi-agent system (MAS-based restoration method for a low voltage (LV microgrid (MG. In the proposed method, the MG local controllers are assigned to the specific agents who interact with each other to achieve a common decision in the restoration procedure. The evaluation of the proposed decentralized technique using a benchmark low-voltage MG network demonstrates the effectiveness of the proposed restoration plan.

Biomimetic molecular design tools that learn, evolve, and adapt

Science.gov (United States)

2017-01-01

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

Biomimetic molecular design tools that learn, evolve, and adapt

Directory of Open Access Journals (Sweden)

David A Winkler

2017-06-01

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

Blockchain Based Decentralized Management of Demand Response Programs in Smart Energy Grids

Science.gov (United States)

Pop, Claudia; Cioara, Tudor; Antal, Marcel; Anghel, Ionut; Salomie, Ioan; Bertoncini, Massimo

2018-01-01

In this paper, we investigate the use of decentralized blockchain mechanisms for delivering transparent, secure, reliable, and timely energy flexibility, under the form of adaptation of energy demand profiles of Distributed Energy Prosumers, to all the stakeholders involved in the flexibility markets (Distribution System Operators primarily, retailers, aggregators, etc.). In our approach, a blockchain based distributed ledger stores in a tamper proof manner the energy prosumption information collected from Internet of Things smart metering devices, while self-enforcing smart contracts programmatically define the expected energy flexibility at the level of each prosumer, the associated rewards or penalties, and the rules for balancing the energy demand with the energy production at grid level. Consensus based validation will be used for demand response programs validation and to activate the appropriate financial settlement for the flexibility providers. The approach was validated using a prototype implemented in an Ethereum platform using energy consumption and production traces of several buildings from literature data sets. The results show that our blockchain based distributed demand side management can be used for matching energy demand and production at smart grid level, the demand response signal being followed with high accuracy, while the amount of energy flexibility needed for convergence is reduced. PMID:29315250

Blockchain Based Decentralized Management of Demand Response Programs in Smart Energy Grids.

Science.gov (United States)

Pop, Claudia; Cioara, Tudor; Antal, Marcel; Anghel, Ionut; Salomie, Ioan; Bertoncini, Massimo

2018-01-09

In this paper, we investigate the use of decentralized blockchain mechanisms for delivering transparent, secure, reliable, and timely energy flexibility, under the form of adaptation of energy demand profiles of Distributed Energy Prosumers, to all the stakeholders involved in the flexibility markets (Distribution System Operators primarily, retailers, aggregators, etc.). In our approach, a blockchain based distributed ledger stores in a tamper proof manner the energy prosumption information collected from Internet of Things smart metering devices, while self-enforcing smart contracts programmatically define the expected energy flexibility at the level of each prosumer, the associated rewards or penalties, and the rules for balancing the energy demand with the energy production at grid level. Consensus based validation will be used for demand response programs validation and to activate the appropriate financial settlement for the flexibility providers. The approach was validated using a prototype implemented in an Ethereum platform using energy consumption and production traces of several buildings from literature data sets. The results show that our blockchain based distributed demand side management can be used for matching energy demand and production at smart grid level, the demand response signal being followed with high accuracy, while the amount of energy flexibility needed for convergence is reduced.

Blockchain Based Decentralized Management of Demand Response Programs in Smart Energy Grids

Directory of Open Access Journals (Sweden)

Claudia Pop

2018-01-01

Full Text Available In this paper, we investigate the use of decentralized blockchain mechanisms for delivering transparent, secure, reliable, and timely energy flexibility, under the form of adaptation of energy demand profiles of Distributed Energy Prosumers, to all the stakeholders involved in the flexibility markets (Distribution System Operators primarily, retailers, aggregators, etc.. In our approach, a blockchain based distributed ledger stores in a tamper proof manner the energy prosumption information collected from Internet of Things smart metering devices, while self-enforcing smart contracts programmatically define the expected energy flexibility at the level of each prosumer, the associated rewards or penalties, and the rules for balancing the energy demand with the energy production at grid level. Consensus based validation will be used for demand response programs validation and to activate the appropriate financial settlement for the flexibility providers. The approach was validated using a prototype implemented in an Ethereum platform using energy consumption and production traces of several buildings from literature data sets. The results show that our blockchain based distributed demand side management can be used for matching energy demand and production at smart grid level, the demand response signal being followed with high accuracy, while the amount of energy flexibility needed for convergence is reduced.

Fully decentralized control of a soft-bodied robot inspired by true slime mold.

Science.gov (United States)

Umedachi, Takuya; Takeda, Koichi; Nakagaki, Toshiyuki; Kobayashi, Ryo; Ishiguro, Akio

2010-03-01

Animals exhibit astoundingly adaptive and supple locomotion under real world constraints. In order to endow robots with similar capabilities, we must implement many degrees of freedom, equivalent to animals, into the robots' bodies. For taming many degrees of freedom, the concept of autonomous decentralized control plays a pivotal role. However a systematic way of designing such autonomous decentralized control system is still missing. Aiming at understanding the principles that underlie animals' locomotion, we have focused on a true slime mold, a primitive living organism, and extracted a design scheme for autonomous decentralized control system. In order to validate this design scheme, this article presents a soft-bodied amoeboid robot inspired by the true slime mold. Significant features of this robot are twofold: (1) the robot has a truly soft and deformable body stemming from real-time tunable springs and protoplasm, the former is used for an outer skin of the body and the latter is to satisfy the law of conservation of mass; and (2) fully decentralized control using coupled oscillators with completely local sensory feedback mechanism is realized by exploiting the long-distance physical interaction between the body parts stemming from the law of conservation of protoplasmic mass. Simulation results show that this robot exhibits highly supple and adaptive locomotion without relying on any hierarchical structure. The results obtained are expected to shed new light on design methodology for autonomous decentralized control system.

ADAPTIVE E-LEARNING AND ITS EVALUATION

Directory of Open Access Journals (Sweden)

KOSTOLÁNYOVÁ, Katerina

2012-12-01

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

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

Directory of Open Access Journals (Sweden)

Radhika M. Pai

2016-03-01

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

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

Directory of Open Access Journals (Sweden)

Radhika M. Pai

2016-04-01

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

Adapting a Technology-Based Implementation Support Tool for Community Mental Health: Challenges and Lessons Learned.

Science.gov (United States)

Livet, Melanie; Fixsen, Amanda

2018-01-01

With mental health services shifting to community-based settings, community mental health (CMH) organizations are under increasing pressure to deliver effective services. Despite availability of evidence-based interventions, there is a gap between effective mental health practices and the care that is routinely delivered. Bridging this gap requires availability of easily tailorable implementation support tools to assist providers in implementing evidence-based intervention with quality, thereby increasing the likelihood of achieving the desired client outcomes. This study documents the process and lessons learned from exploring the feasibility of adapting such a technology-based tool, Centervention, as the example innovation, for use in CMH settings. Mixed-methods data on core features, innovation-provider fit, and organizational capacity were collected from 44 CMH providers. Lessons learned included the need to augment delivery through technology with more personal interactions, the importance of customizing and integrating the tool with existing technologies, and the need to incorporate a number of strategies to assist with adoption and use of Centervention-like tools in CMH contexts. This study adds to the current body of literature on the adaptation process for technology-based tools and provides information that can guide additional innovations for CMH settings.

An adaptive deep Q-learning strategy for handwritten digit recognition.

Science.gov (United States)

Qiao, Junfei; Wang, Gongming; Li, Wenjing; Chen, Min

2018-02-22

Handwritten digits recognition is a challenging problem in recent years. Although many deep learning-based classification algorithms are studied for handwritten digits recognition, the recognition accuracy and running time still need to be further improved. In this paper, an adaptive deep Q-learning strategy is proposed to improve accuracy and shorten running time for handwritten digit recognition. The adaptive deep Q-learning strategy combines the feature-extracting capability of deep learning and the decision-making of reinforcement learning to form an adaptive Q-learning deep belief network (Q-ADBN). First, Q-ADBN extracts the features of original images using an adaptive deep auto-encoder (ADAE), and the extracted features are considered as the current states of Q-learning algorithm. Second, Q-ADBN receives Q-function (reward signal) during recognition of the current states, and the final handwritten digits recognition is implemented by maximizing the Q-function using Q-learning algorithm. Finally, experimental results from the well-known MNIST dataset show that the proposed Q-ADBN has a superiority to other similar methods in terms of accuracy and running time. Copyright © 2018 Elsevier Ltd. All rights reserved.

A New Mobile Learning Adaptation Model

OpenAIRE

Mohamd Hassan Hassan; Jehad Al-Sadi

2009-01-01

This paper introduces a new model for m- Learning context adaptation due to the need of utilizing mobile technology in education. Mobile learning; m-Learning for short; in considered to be one of the hottest topics in the educational community, many researches had been done to conceptualize this new form of learning. We are presenting a promising design for a model to adapt the learning content in mobile learning applications in order to match the learner context, preferences and the educatio...

Intelligent Web-Based Learning System with Personalized Learning Path Guidance

Science.gov (United States)

Chen, C. M.

2008-01-01

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

Policy Implementation Decentralization Government in Indonesia

Directory of Open Access Journals (Sweden)

Kardin M. Simanjuntak

2015-06-01

Full Text Available Decentralization in Indonesia is that reforms not completed and until the current implementation is not maximized or have not been successful. The essence of decentralization is internalising cost and benefit' for the people and how the government closer to the people. That's the most important essence of essence 'decentralization’. However, the implementation of decentralization in Indonesia is still far from the expectations. It is shown that only benefits of decentralization elite and local authorities, decentralization is a neo-liberal octopus, decentralization of public services are lacking in character, decentralization without institutional efficiency, decentralization fosters corruption in the area, and quasi-fiscal decentralization.

Mapping the potential for decentralized energy generation based on RES in Western Balkans

Directory of Open Access Journals (Sweden)

Schneider Daniel R.

2007-01-01

Full Text Available Although the countries of the Western Balkans are mostly electrified, there are still regions which do not have access to the electricity network or where the network capacity is insufficient. For the most part such areas are under special care of the state (i. e. underdeveloped, devastated by war, depopulated, on islands or in mountainous regions. Since the decentralized energy generation covers a broad range of technologies, including many renewable energy technologies that provide small-scale power at sites close to the users, such concept could be of interest for these locations. This paper identifies the areas in Western Balkans where such systems could be applied. Consideration is given to geographical locations as well as possible applications. Wind, hydro, solar photovoltaic, and biomass conversion systems were taken into consideration. Since the renewable energy sources data for Western Balkans region are rather scarce, the intention was to give a survey of the present situation and an estimate of future potential for decentralized energy generation based on renewable energy sources. The decentralized energy generation based on renewable energy sources in Western Balkans will find its niche easier for the users that will produce electricity for their own needs and for the users located in remote rural areas (off-grid applications.

A Decentralized Multivariable Robust Adaptive Voltage and Speed Regulator for Large-Scale Power Systems

Science.gov (United States)

Okou, Francis A.; Akhrif, Ouassima; Dessaint, Louis A.; Bouchard, Derrick

2013-05-01

This papter introduces a decentralized multivariable robust adaptive voltage and frequency regulator to ensure the stability of large-scale interconnnected generators. Interconnection parameters (i.e. load, line and transormer parameters) are assumed to be unknown. The proposed design approach requires the reformulation of conventiaonal power system models into a multivariable model with generator terminal voltages as state variables, and excitation and turbine valve inputs as control signals. This model, while suitable for the application of modern control methods, introduces problems with regards to current design techniques for large-scale systems. Interconnection terms, which are treated as perturbations, do not meet the common matching condition assumption. A new adaptive method for a certain class of large-scale systems is therefore introduces that does not require the matching condition. The proposed controller consists of nonlinear inputs that cancel some nonlinearities of the model. Auxiliary controls with linear and nonlinear components are used to stabilize the system. They compensate unknown parametes of the model by updating both the nonlinear component gains and excitation parameters. The adaptation algorithms involve the sigma-modification approach for auxiliary control gains, and the projection approach for excitation parameters to prevent estimation drift. The computation of the matrix-gain of the controller linear component requires the resolution of an algebraic Riccati equation and helps to solve the perturbation-mismatching problem. A realistic power system is used to assess the proposed controller performance. The results show that both stability and transient performance are considerably improved following a severe contingency.

A Framework for Creating Semantically Adaptive Collaborative E-learning Environments

Directory of Open Access Journals (Sweden)

Marija Cubric

2009-09-01

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

Opposition-Based Adaptive Fireworks Algorithm

OpenAIRE

Chibing Gong

2016-01-01

A fireworks algorithm (FWA) is a recent swarm intelligence algorithm that is inspired by observing fireworks explosions. An adaptive fireworks algorithm (AFWA) proposes additional adaptive amplitudes to improve the performance of the enhanced fireworks algorithm (EFWA). The purpose of this paper is to add opposition-based learning (OBL) to AFWA with the goal of further boosting performance and achieving global optimization. Twelve benchmark functions are tested in use of an opposition-based a...

Towards a Decentralized Magnetic Indoor Positioning System

Science.gov (United States)

Kasmi, Zakaria; Norrdine, Abdelmoumen; Blankenbach, Jörg

2015-01-01

Decentralized magnetic indoor localization is a sophisticated method for processing sampled magnetic data directly on a mobile station (MS), thereby decreasing or even avoiding the need for communication with the base station. In contrast to central-oriented positioning systems, which transmit raw data to a base station, decentralized indoor localization pushes application-level knowledge into the MS. A decentralized position solution has thus a strong feasibility to increase energy efficiency and to prolong the lifetime of the MS. In this article, we present a complete architecture and an implementation for a decentralized positioning system. Furthermore, we introduce a technique for the synchronization of the observed magnetic field on the MS with the artificially-generated magnetic field from the coils. Based on real-time clocks (RTCs) and a preemptive operating system, this method allows a stand-alone control of the coils and a proper assignment of the measured magnetic fields on the MS. A stand-alone control and synchronization of the coils and the MS have an exceptional potential to implement a positioning system without the need for wired or wireless communication and enable a deployment of applications for rescue scenarios, like localization of miners or firefighters. PMID:26690145

Towards a Decentralized Magnetic Indoor Positioning System

Directory of Open Access Journals (Sweden)

Zakaria Kasmi

2015-12-01

Full Text Available Decentralized magnetic indoor localization is a sophisticated method for processing sampled magnetic data directly on a mobile station (MS, thereby decreasing or even avoiding the need for communication with the base station. In contrast to central-oriented positioning systems, which transmit raw data to a base station, decentralized indoor localization pushes application-level knowledge into the MS. A decentralized position solution has thus a strong feasibility to increase energy efficiency and to prolong the lifetime of the MS. In this article, we present a complete architecture and an implementation for a decentralized positioning system. Furthermore, we introduce a technique for the synchronization of the observed magnetic field on the MS with the artificially-generated magnetic field from the coils. Based on real-time clocks (RTCs and a preemptive operating system, this method allows a stand-alone control of the coils and a proper assignment of the measured magnetic fields on the MS. A stand-alone control and synchronization of the coils and the MS have an exceptional potential to implement a positioning system without the need for wired or wireless communication and enable a deployment of applications for rescue scenarios, like localization of miners or firefighters.

COINSTAC: Decentralizing the future of brain imaging analysis [version 1; referees: 2 approved

Directory of Open Access Journals (Sweden)

Jing Ming

2017-08-01

Full Text Available In the era of Big Data, sharing neuroimaging data across multiple sites has become increasingly important. However, researchers who want to engage in centralized, large-scale data sharing and analysis must often contend with problems such as high database cost, long data transfer time, extensive manual effort, and privacy issues for sensitive data. To remove these barriers to enable easier data sharing and analysis, we introduced a new, decentralized, privacy-enabled infrastructure model for brain imaging data called COINSTAC in 2016. We have continued development of COINSTAC since this model was first introduced. One of the challenges with such a model is adapting the required algorithms to function within a decentralized framework. In this paper, we report on how we are solving this problem, along with our progress on several fronts, including additional decentralized algorithms implementation, user interface enhancement, decentralized regression statistic calculation, and complete pipeline specifications.

Governing decentralization in health care under tough budget constraint: what can we learn from the Italian experience?

Science.gov (United States)

Tediosi, Fabrizio; Gabriele, Stefania; Longo, Francesco

2009-05-01

In many European countries, since the World War II, there has been a trend towards decentralization of health policy to lower levels of governments, while more recently there have been re-centralization processes. Whether re-centralization will be the new paradigm of European health policy or not is difficult to say. In the Italian National Health Service (SSN) decentralization raised two related questions that might be interesting for the international debate on decentralization in health care: (a) what sort of regulatory framework and institutional balances are required to govern decentralization in health care in a heterogeneous country under tough budget constraints? (b) how can it be ensured that the most advanced parts of the country remain committed to solidarity, supporting the weakest ones? To address these questions this article describes the recent trends in SSN funding and expenditure, it reviews the strategy adopted by the Italian government for governing the decentralization process and discusses the findings to draw policy conclusions. The main lessons emerging from this experience are that: (1) when the differences in administrative and policy skills, in socio-economic standards and social capital are wide, decentralization may lead to undesirable divergent evolution paths; (2) even in decentralized systems, the role of the Central government can be very important to contain health expenditure; (3) a strong governance of the Central government may help and not hinder the enforcement of decentralization; and (4) supporting the weakest Regions and maintaining inter-regional solidarity is hard but possible. In Italy, despite an increasing role of the Central government in steering the SSN, the pattern of regional decentralization of health sector decision making does not seem at risk. Nevertheless, the Italian case confirms the complexity of decentralization and re-centralization processes that sometimes can be paradoxically reinforcing each other.

ADRES : autonomous decentralized regenerative energy systems

Energy Technology Data Exchange (ETDEWEB)

Brauner, G.; Einfalt, A.; Leitinger, C.; Tiefgraber, D. [Vienna Univ. of Technology (Austria)

2007-07-01

The autonomous decentralized regenerative energy systems (ADRES) research project demonstrates that decentralized network independent microgrids are the target power systems of the future. This paper presented a typical structure of a microgrid, demonstrating that all types of generation available can be integrated, from wind and small hydro to photovoltaic, fuel cell, biomass or biogas operated stirling motors and micro turbines. In grid connected operation the balancing energy and reactive power for voltage control will come from the public grid. If there is no interconnection to a superior grid, it will form an autonomous micro grid. In order to reduce peak power demand and base energy, autonomous microgrid technology requires highly efficient appliances. Otherwise large collector design, high storage and balancing generation capacities would be necessary, which would increase costs. End-use energy efficiency was discussed with reference to demand side management (DSM) strategies that match energy demand with actual supply in order to minimize the storage size needed. This paper also discussed network controls that comprise active and reactive power. Decentralized robust algorithms were investigated with reference to black-start ability and congestion management features. It was concluded that the trend to develop small decentralized grids in parallel to existing large systems will improve security of supply and reduce greenhouse gas emissions. Decentralized grids will also increase energy efficiency because regenerative energy will be used where it is collected in the form of electricity and heat, thus avoiding transport and the extension of transmission lines. Decentralized energy technology is now becoming more economic by efficient and economic mass production of components. Although decentralized energy technology requires energy automation, computer intelligence is becoming increasingly cost efficient. 2 refs., 4 figs.

Decentralized load- and feed-in-management using a market based agent system; Dezentrales Last- und Einspeisemanagement mittels eines marktbasierten Agentensystems

Energy Technology Data Exchange (ETDEWEB)

Linnenberg, T.; Wior, I.; Schreiber, S.; Fay, A. [Helmut-Schmidt-Univ., Hamburg (Germany). Inst. fuer Automatisierungstechnik

2012-07-01

As a result of the increasing amount of decentralized electricity generation classical, centralized control concepts are taken to their limits. At present, two approaches are being followed to deal with these problems: the expansion of the electricity network and the extension of reserve capacities. The ''DEcentralized MArket based POwer control System'' (DEMAPOS) approach presented in this article, illustrates ways to solve these problems by means of a decentralized, market based control. With a focus on easy expandability and the possibility to cooperate with project partners a methodic and comprehensible development process was used along with open standards and free software. The Validation of the approach was carried out simulation based on real world data. (orig.)

Adaptive polymeric system for Hebbian type learning

OpenAIRE

2011-01-01

Abstract We present the experimental realization of an adaptive polymeric system displaying a ?learning behaviour?. The system consists on a statistically organized networks of memristive elements (memory-resitors) based on polyaniline. In a such network the path followed by the current increments its conductivity, a property which makes the system able to mimic Hebbian type learning and have application in hardware neural networks. After discussing the working principle of ...

Preventing KPI Violations in Business Processes based on Decision Tree Learning and Proactive Runtime Adaptation

Directory of Open Access Journals (Sweden)

Dimka Karastoyanova

2012-01-01

Full Text Available The performance of business processes is measured and monitored in terms of Key Performance Indicators (KPIs. If the monitoring results show that the KPI targets are violated, the underlying reasons have to be identified and the process should be adapted accordingly to address the violations. In this paper we propose an integrated monitoring, prediction and adaptation approach for preventing KPI violations of business process instances. KPIs are monitored continuously while the process is executed. Additionally, based on KPI measurements of historical process instances we use decision tree learning to construct classification models which are then used to predict the KPI value of an instance while it is still running. If a KPI violation is predicted, we identify adaptation requirements and adaptation strategies in order to prevent the violation.

Knowledge Representation and Reasoning in Personalized Web-Based e-Learning Applications

DEFF Research Database (Denmark)

Dolog, Peter

2006-01-01

a user inferred from user interactions with the eLeanrning systems is used to adapt o®ered learning resources and guide a learner through them. This keynote gives an overview about knowledge and rules taken into account in current adaptive eLearning prototypes when adapting learning instructions....... Adaptation is usually based on knowledge about learning esources and users. Rules are used for heuristics to match the learning resources with learners and infer adaptation decisions.......Adaptation that is so natural for teaching by humans is a challenging issue for electronic learning tools. Adaptation in classic teaching is based on observations made about students during teaching. Similar idea was employed in user-adapted (personalized) eLearning applications. Knowledge about...

Decentralized Traffic Management: A Synchronization-Based Intersection Control --- Extended Version

OpenAIRE

Tlig , Mohamed; Buffet , Olivier; Simonin , Olivier

2014-01-01

Controlling the vehicle traffic in large networks remains an important challenge in urban environments and transportation systems. Autonomous vehicles are today considered as a promising approach to deal with traffic control. In this paper, we propose a synchronization-based intersection control mechanism to allow the autonomous vehicle-agents to cross without stopping, i.e., in order to avoid congestions (delays) and energy loss. We decentralize the problem by managing the traffic of each in...

Computerized adaptive testing in computer assisted learning?

NARCIS (Netherlands)

Veldkamp, Bernard P.; Matteucci, Mariagiulia; Eggen, Theodorus Johannes Hendrikus Maria; De Wannemacker, Stefan; Clarebout, Geraldine; De Causmaecker, Patrick

2011-01-01

A major goal in computerized learning systems is to optimize learning, while in computerized adaptive tests (CAT) efficient measurement of the proficiency of students is the main focus. There seems to be a common interest to integrate computerized adaptive item selection in learning systems and

Using assistive technology adaptations to include students with learning disabilities in cooperative learning activities.

Science.gov (United States)

Bryant, D P; Bryant, B R

1998-01-01

Cooperative learning (CL) is a common instructional arrangement that is used by classroom teachers to foster academic achievement and social acceptance of students with and without learning disabilities. Cooperative learning is appealing to classroom teachers because it can provide an opportunity for more instruction and feedback by peers than can be provided by teachers to individual students who require extra assistance. Recent studies suggest that students with LD may need adaptations during cooperative learning activities. The use of assistive technology adaptations may be necessary to help some students with LD compensate for their specific learning difficulties so that they can engage more readily in cooperative learning activities. A process for integrating technology adaptations into cooperative learning activities is discussed in terms of three components: selecting adaptations, monitoring the use of the adaptations during cooperative learning activities, and evaluating the adaptations' effectiveness. The article concludes with comments regarding barriers to and support systems for technology integration, technology and effective instructional practices, and the need to consider technology adaptations for students who have learning disabilities.

Supporting Student Learning in Computer Science Education via the Adaptive Learning Environment ALMA

Directory of Open Access Journals (Sweden)

Alexandra Gasparinatou

2015-10-01

Full Text Available This study presents the ALMA environment (Adaptive Learning Models from texts and Activities. ALMA supports the processes of learning and assessment via: (1 texts differing in local and global cohesion for students with low, medium, and high background knowledge; (2 activities corresponding to different levels of comprehension which prompt the student to practically implement different text-reading strategies, with the recommended activity sequence adapted to the student’s learning style; (3 an overall framework for informing, guiding, and supporting students in performing the activities; and; (4 individualized support and guidance according to student specific characteristics. ALMA also, supports students in distance learning or in blended learning in which students are submitted to face-to-face learning supported by computer technology. The adaptive techniques provided via ALMA are: (a adaptive presentation and (b adaptive navigation. Digital learning material, in accordance with the text comprehension model described by Kintsch, was introduced into the ALMA environment. This material can be exploited in either distance or blended learning.

Reinforcement learning design-based adaptive tracking control with less learning parameters for nonlinear discrete-time MIMO systems.

Science.gov (United States)

Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip; Li, Dong-Juan

2015-01-01

Based on the neural network (NN) approximator, an online reinforcement learning algorithm is proposed for a class of affine multiple input and multiple output (MIMO) nonlinear discrete-time systems with unknown functions and disturbances. In the design procedure, two networks are provided where one is an action network to generate an optimal control signal and the other is a critic network to approximate the cost function. An optimal control signal and adaptation laws can be generated based on two NNs. In the previous approaches, the weights of critic and action networks are updated based on the gradient descent rule and the estimations of optimal weight vectors are directly adjusted in the design. Consequently, compared with the existing results, the main contributions of this paper are: 1) only two parameters are needed to be adjusted, and thus the number of the adaptation laws is smaller than the previous results and 2) the updating parameters do not depend on the number of the subsystems for MIMO systems and the tuning rules are replaced by adjusting the norms on optimal weight vectors in both action and critic networks. It is proven that the tracking errors, the adaptation laws, and the control inputs are uniformly bounded using Lyapunov analysis method. The simulation examples are employed to illustrate the effectiveness of the proposed algorithm.

Decentralized Control of Unmanned Aerial Robots for Wireless Airborne Communication Networks

Directory of Open Access Journals (Sweden)

Deok-Jin Lee

2010-09-01

Full Text Available This paper presents a cooperative control strategy for a team of aerial robotic vehicles to establish wireless airborne communication networks between distributed heterogeneous vehicles. Each aerial robot serves as a flying mobile sensor performing a reconfigurable communication relay node which enabls communication networks with static or slow-moving nodes on gorund or ocean. For distributed optimal deployment of the aerial vehicles for communication networks, an adaptive hill-climbing type decentralized control algorithm is developed to seek out local extremum for optimal localization of the vehicles. The sensor networks estabilished by the decentralized cooperative control approach can adopt its configuraiton in response to signal strength as the function of the relative distance between the autonomous aerial robots and distributed sensor nodes in the sensed environment. Simulation studies are conducted to evaluate the effectiveness of the proposed decentralized cooperative control technique for robust communication networks.

Decentralized flight trajectory planning of multiple aircraft

OpenAIRE

Yokoyama, Nobuhiro; 横山　信宏

2008-01-01

Conventional decentralized algorithms for optimal trajectory planning tend to require prohibitive computational time as the number of aircraft increases. To overcome this drawback, this paper proposes a novel decentralized trajectory planning algorithm adopting a constraints decoupling approach for parallel optimization. The constraints decoupling approach is formulated as the path constraints of the real-time trajectory optimization problem based on nonlinear programming. Due to the parallel...

Adaptation of mathematical educational content in e-learning resources

Directory of Open Access Journals (Sweden)

Yuliya V. Vainshtein

2017-01-01

algorithms for the educational content in the adaptive e-learning resource made it possible to implement individual educational paths in the electronic environment. For each student it was formed a personal space of mathematical educational content that “adapts” to its level of mastering the material, which contributed to improving the quality of the educational process in mathematical disciplines.In this paper, the methods of mathematical modeling and logicalgnosiological analysis, the theory of graphs and hypergraphs, system analysis, dynamic processes and systems control theory, complex systems design and imitation modelling methods were used.Approbation of the proposed algorithms for the educational content organization of adaptation in the adaptive electronic learning resource for the discipline “Discrete mathematics” showed the productivity of the proposed approach in the teaching process. The obtained results could be used for adaptive electronic educational resources construction in other educational institutions of higher education.Further development of the proposed approach involves the development of a formal model of the educational content adaptation, including control rules, based on the expert evaluation methods and the fuzzy-set theory.

Macroeconomic aspects of decentralized electricity production

International Nuclear Information System (INIS)

Percebois, J.

1991-01-01

The development of decentralized electricity production should be viewed first and foremost as a means of adapting production resources to meet the needs of the users between 1995 and 1997. Consumer production and cogeneration are not, however, simply stopgap solutions operating on the fringe of electricity production. These methods serve to highlight a problem that has already been raised in the past: the real advantages and disadvantages of centralized systems managed by companies that exercise a virtual monopoly in either the public or private sector

Learning-Based Adaptive Optimal Tracking Control of Strict-Feedback Nonlinear Systems.

Science.gov (United States)

Gao, Weinan; Jiang, Zhong-Ping; Weinan Gao; Zhong-Ping Jiang; Gao, Weinan; Jiang, Zhong-Ping

2018-06-01

This paper proposes a novel data-driven control approach to address the problem of adaptive optimal tracking for a class of nonlinear systems taking the strict-feedback form. Adaptive dynamic programming (ADP) and nonlinear output regulation theories are integrated for the first time to compute an adaptive near-optimal tracker without any a priori knowledge of the system dynamics. Fundamentally different from adaptive optimal stabilization problems, the solution to a Hamilton-Jacobi-Bellman (HJB) equation, not necessarily a positive definite function, cannot be approximated through the existing iterative methods. This paper proposes a novel policy iteration technique for solving positive semidefinite HJB equations with rigorous convergence analysis. A two-phase data-driven learning method is developed and implemented online by ADP. The efficacy of the proposed adaptive optimal tracking control methodology is demonstrated via a Van der Pol oscillator with time-varying exogenous signals.

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

Science.gov (United States)

Bower, Matt

2016-01-01

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

Decentralized Quasi-Newton Methods

Science.gov (United States)

Eisen, Mark; Mokhtari, Aryan; Ribeiro, Alejandro

2017-05-01

We introduce the decentralized Broyden-Fletcher-Goldfarb-Shanno (D-BFGS) method as a variation of the BFGS quasi-Newton method for solving decentralized optimization problems. The D-BFGS method is of interest in problems that are not well conditioned, making first order decentralized methods ineffective, and in which second order information is not readily available, making second order decentralized methods impossible. D-BFGS is a fully distributed algorithm in which nodes approximate curvature information of themselves and their neighbors through the satisfaction of a secant condition. We additionally provide a formulation of the algorithm in asynchronous settings. Convergence of D-BFGS is established formally in both the synchronous and asynchronous settings and strong performance advantages relative to first order methods are shown numerically.

Federalism and Decentralization of Education in Argentina. Unintended Consequences of Decentralization of Expenditures in a Federal Country.

Science.gov (United States)

Falleti, Tulia G.

By analyzing the process of decentralization of education in Argentina, this paper complements the existing literature on decentralization and federalism in two ways: (1) it studies the impact of federal institutions on the origins and evolution of decentralization; and (2) it analyzes a case of decentralization of education that, in a way not…

Anticipatory Learning for Climate Change Adaptation and Resilience

Directory of Open Access Journals (Sweden)

Petra Tschakert

2010-06-01

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

DECENTRALIZATION IN THE SYSTEM OF NATIONAL ECONOMY MANAGEMENT

Directory of Open Access Journals (Sweden)

Stepaniuk Nataliia

2018-03-01

and promote development of human and resource potential, responsibility of the authorities, increase quality provision of state and public services, consolidation of society, solving of economic, environmental, legal, political and other issues. But in general, decentralization plays an important role at the development of democracy and positive changes in society, the transition to institutions based on the initiative and responsibility of the community and the individual.

The Two Edge Knife of Decentralization

Directory of Open Access Journals (Sweden)

Ahmad Khoirul Umam

2011-07-01

Full Text Available A centralistic government model has become a trend in a number of developing countries, in which the ideosycretic aspect becomes pivotal key in the policy making. The situation constitutes authoritarianism, cronyism, and corruption. To break the impasse, the decentralized system is proposed to make people closer to the public policy making. Decentralization is also convinced to be the solution to create a good governance. But a number of facts in the developing countries demonstrates that decentralization indeed has ignite emerges backfires such as decentralized corruption, parochialism, horizontal conflict, local political instability and others. This article elaborates the theoretical framework on decentralization's ouput as the a double-edge knife. In a simple words, the concept of decentralization does not have a permanent relationship with the creation of good governance and development. Without substantive democracy, decentralization is indeed potential to be a destructive political instrument threating the state's future.

Replication of urban innovations - prioritization of strategies for the replication of Dhaka's community-based decentralized composting model.

Science.gov (United States)

Yedla, Sudhakar

2012-01-01

Dhaka's community-based decentralized composting (DCDC) is a successful demonstration of solid waste management by adopting low-cost technology, local resources community participation and partnerships among the various actors involved. This paper attempts to understand the model, necessary conditions, strategies and their priorities to replicate DCDC in the other developing cities of Asia. Thirteen strategies required for its replication are identified and assessed based on various criteria, namely transferability, longevity, economic viability, adaptation and also overall replication. Priority setting by multi-criteria analysis by applying analytic hierarchy process revealed that immediate transferability without long-term and economic viability consideration is not advisable as this would result in unsustainable replication of DCDC. Based on the analysis, measures to ensure the product quality control; partnership among stakeholders (public-private-community); strategies to achieve better involvement of the private sector in solid waste management (entrepreneurship in approach); simple and low-cost technology; and strategies to provide an effective interface among the complementing sectors are identified as important strategies for its replication.

Decentralized Interleaving of Paralleled Dc-Dc Buck Converters: Preprint

Energy Technology Data Exchange (ETDEWEB)

Johnson, Brian B [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Rodriguez, Miguel [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Sinha, Mohit [University of Minnesota; Dhople, Sairaj [University of Minnesota; Poon, Jason [University of California at Berkeley

2017-09-01

We present a decentralized control strategy that yields switch interleaving among parallel connected dc-dc buck converters without communication. The proposed method is based on the digital implementation of the dynamics of a nonlinear oscillator circuit as the controller. Each controller is fully decentralized, i.e., it only requires the locally measured output current to synthesize the pulse width modulation (PWM) carrier waveform. By virtue of the intrinsic electrical coupling between converters, the nonlinear oscillator-based controllers converge to an interleaved state with uniform phase-spacing across PWM carriers. To the knowledge of the authors, this work represents the first fully decentralized strategy for switch interleaving of paralleled dc-dc buck converters.

EFFECT OF FISCAL DECENTRALIZATION ON CAPITAL EXPENDITURE, GROWTH, AND WELFARE

OpenAIRE

Badrudin, Rudy

2013-01-01

This research analyzes the influence of fiscal decentralization on capital expenditure, economic growth, and social welfare of 29 regencies and 6 cities in Central Java Province based on the data of year 2004 to 2008. The method used to analyze the hypotheses is the Partial Least Square. The results showes that fiscal decentralization has no significant effect on capital expenditure; fiscal decentralization has significant effect on economic growth and social welfare; capital expenditure has ...

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

Science.gov (United States)

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

2017-01-01

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

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

Directory of Open Access Journals (Sweden)

Qi Huang

2017-06-01

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

Individual differences in implicit motor learning: task specificity in sensorimotor adaptation and sequence learning.

Science.gov (United States)

Stark-Inbar, Alit; Raza, Meher; Taylor, Jordan A; Ivry, Richard B

2017-01-01

In standard taxonomies, motor skills are typically treated as representative of implicit or procedural memory. We examined two emblematic tasks of implicit motor learning, sensorimotor adaptation and sequence learning, asking whether individual differences in learning are correlated between these tasks, as well as how individual differences within each task are related to different performance variables. As a prerequisite, it was essential to establish the reliability of learning measures for each task. Participants were tested twice on a visuomotor adaptation task and on a sequence learning task, either the serial reaction time task or the alternating reaction time task. Learning was evident in all tasks at the group level and reliable at the individual level in visuomotor adaptation and the alternating reaction time task but not in the serial reaction time task. Performance variability was predictive of learning in both domains, yet the relationship was in the opposite direction for adaptation and sequence learning. For the former, faster learning was associated with lower variability, consistent with models of sensorimotor adaptation in which learning rates are sensitive to noise. For the latter, greater learning was associated with higher variability and slower reaction times, factors that may facilitate the spread of activation required to form predictive, sequential associations. Interestingly, learning measures of the different tasks were not correlated. Together, these results oppose a shared process for implicit learning in sensorimotor adaptation and sequence learning and provide insight into the factors that account for individual differences in learning within each task domain. We investigated individual differences in the ability to implicitly learn motor skills. As a prerequisite, we assessed whether individual differences were reliable across test sessions. We found that two commonly used tasks of implicit learning, visuomotor adaptation and the

An Online Q-learning Based Multi-Agent LFC for a Multi-Area Multi-Source Power System Including Distributed Energy Resources

Directory of Open Access Journals (Sweden)

H. Shayeghi

2017-12-01

Full Text Available This paper presents an online two-stage Q-learning based multi-agent (MA controller for load frequency control (LFC in an interconnected multi-area multi-source power system integrated with distributed energy resources (DERs. The proposed control strategy consists of two stages. The first stage is employed a PID controller which its parameters are designed using sine cosine optimization (SCO algorithm and are fixed. The second one is a reinforcement learning (RL based supplementary controller that has a flexible structure and improves the output of the first stage adaptively based on the system dynamical behavior. Due to the use of RL paradigm integrated with PID controller in this strategy, it is called RL-PID controller. The primary motivation for the integration of RL technique with PID controller is to make the existing local controllers in the industry compatible to reduce the control efforts and system costs. This novel control strategy combines the advantages of the PID controller with adaptive behavior of MA to achieve the desired level of robust performance under different kind of uncertainties caused by stochastically power generation of DERs, plant operational condition changes, and physical nonlinearities of the system. The suggested decentralized controller is composed of the autonomous intelligent agents, who learn the optimal control policy from interaction with the system. These agents update their knowledge about the system dynamics continuously to achieve a good frequency oscillation damping under various severe disturbances without any knowledge of them. It leads to an adaptive control structure to solve LFC problem in the multi-source power system with stochastic DERs. The results of RL-PID controller in comparison to the traditional PID and fuzzy-PID controllers is verified in a multi-area power system integrated with DERs through some performance indices.

Evolutionary and adaptive learning in complex markets: a brief summary

Science.gov (United States)

Hommes, Cars H.

2007-06-01

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

Adaptive learning by extremal dynamics and negative feedback

International Nuclear Information System (INIS)

Bak, Per; Chialvo, Dante R.

2001-01-01

We describe a mechanism for biological learning and adaptation based on two simple principles: (i) Neuronal activity propagates only through the network's strongest synaptic connections (extremal dynamics), and (ii) the strengths of active synapses are reduced if mistakes are made, otherwise no changes occur (negative feedback). The balancing of those two tendencies typically shapes a synaptic landscape with configurations which are barely stable, and therefore highly flexible. This allows for swift adaptation to new situations. Recollection of past successes is achieved by punishing synapses which have once participated in activity associated with successful outputs much less than neurons that have never been successful. Despite its simplicity, the model can readily learn to solve complicated nonlinear tasks, even in the presence of noise. In particular, the learning time for the benchmark parity problem scales algebraically with the problem size N, with an exponent k∼1.4

Online Adaptation and Over-Trial Learning in Macaque Visuomotor Control

Science.gov (United States)

Braun, Daniel A.; Aertsen, Ad; Paz, Rony; Vaadia, Eilon; Rotter, Stefan; Mehring, Carsten

2011-01-01

When faced with unpredictable environments, the human motor system has been shown to develop optimized adaptation strategies that allow for online adaptation during the control process. Such online adaptation is to be contrasted to slower over-trial learning that corresponds to a trial-by-trial update of the movement plan. Here we investigate the interplay of both processes, i.e., online adaptation and over-trial learning, in a visuomotor experiment performed by macaques. We show that simple non-adaptive control schemes fail to perform in this task, but that a previously suggested adaptive optimal feedback control model can explain the observed behavior. We also show that over-trial learning as seen in learning and aftereffect curves can be explained by learning in a radial basis function network. Our results suggest that both the process of over-trial learning and the process of online adaptation are crucial to understand visuomotor learning. PMID:21720526

Adaptive representations for reinforcement learning

NARCIS (Netherlands)

Whiteson, S.

2010-01-01

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

Organizational decentralization in radiology.

Science.gov (United States)

Aas, I H Monrad

2006-01-01

At present, most hospitals have a department of radiology where images are captured and interpreted. Decentralization is the opposite of centralization and means 'away from the centre'. With a Picture Archiving and Communication System (PACS) and broadband communications, transmitting radiology images between sites will be far easier than before. Qualitative interviews of 26 resource persons were performed in Norway. There was a response rate of 90%. Decentralization of radiology interpretations seems less relevant than centralization, but several forms of decentralization have a role to play. The respondents mentioned several advantages, including exploitation of capacity and competence. They also mentioned several disadvantages, including splitting professional communities and reduced contact between radiologists and clinicians. With the new technology decentralization and centralization of image interpretation are important possibilities in organizational change. This will be important for the future of teleradiology.

Opposition-Based Adaptive Fireworks Algorithm

Directory of Open Access Journals (Sweden)

Chibing Gong

2016-07-01

Full Text Available A fireworks algorithm (FWA is a recent swarm intelligence algorithm that is inspired by observing fireworks explosions. An adaptive fireworks algorithm (AFWA proposes additional adaptive amplitudes to improve the performance of the enhanced fireworks algorithm (EFWA. The purpose of this paper is to add opposition-based learning (OBL to AFWA with the goal of further boosting performance and achieving global optimization. Twelve benchmark functions are tested in use of an opposition-based adaptive fireworks algorithm (OAFWA. The final results conclude that OAFWA significantly outperformed EFWA and AFWA in terms of solution accuracy. Additionally, OAFWA was compared with a bat algorithm (BA, differential evolution (DE, self-adapting control parameters in differential evolution (jDE, a firefly algorithm (FA, and a standard particle swarm optimization 2011 (SPSO2011 algorithm. The research results indicate that OAFWA ranks the highest of the six algorithms for both solution accuracy and runtime cost.

The utility of adaptive eLearning in cervical cytopathology education.

Science.gov (United States)

Samulski, T Danielle; Taylor, Laura A; La, Teresa; Mehr, Chelsea R; McGrath, Cindy M; Wu, Roseann I

2018-02-01

Adaptive eLearning allows students to experience a self-paced, individualized curriculum based on prior knowledge and learning ability. The authors investigated the effectiveness of adaptive online modules in teaching cervical cytopathology. eLearning modules were created that covered basic concepts in cervical cytopathology, including artifacts and infections, squamous lesions (SL), and glandular lesions (GL). The modules used student responses to individualize the educational curriculum and provide real-time feedback. Pathology trainees and faculty from the authors' institution were randomized into 2 groups (SL or GL), and identical pre-tests and post-tests were used to compare the efficacy of eLearning modules versus traditional study methods (textbooks and slide sets). User experience was assessed with a Likert scale and free-text responses. Sixteen of 17 participants completed the SL module, and 19 of 19 completed the GL module. Participants in both groups had improved post-test scores for content in the adaptive eLearning module. Users indicated that the module was effective in presenting content and concepts (Likert scale [from 1 to 5], 4.3 of 5.0), was an efficient and convenient way to review the material (Likert scale, 4.4 of 5.0), and was more engaging than lectures and texts (Likert scale, 4.6 of 5.0). Users favored the immediate feedback and interactivity of the module. Limitations included the inability to review prior content and slow upload time for images. Learners demonstrated improvement in their knowledge after the use of adaptive eLearning modules compared with traditional methods. Overall, the modules were viewed positively by participants. Adaptive eLearning modules can provide an engaging and effective adjunct to traditional teaching methods in cervical cytopathology. Cancer Cytopathol 2018;126:129-35. © 2017 American Cancer Society. © 2017 American Cancer Society.

Fixed Point Learning Based Intelligent Traffic Control System

Science.gov (United States)

Zongyao, Wang; Cong, Sui; Cheng, Shao

2017-10-01

Fixed point learning has become an important tool to analyse large scale distributed system such as urban traffic network. This paper presents a fixed point learning based intelligence traffic network control system. The system applies convergence property of fixed point theorem to optimize the traffic flow density. The intelligence traffic control system achieves maximum road resources usage by averaging traffic flow density among the traffic network. The intelligence traffic network control system is built based on decentralized structure and intelligence cooperation. No central control is needed to manage the system. The proposed system is simple, effective and feasible for practical use. The performance of the system is tested via theoretical proof and simulations. The results demonstrate that the system can effectively solve the traffic congestion problem and increase the vehicles average speed. It also proves that the system is flexible, reliable and feasible for practical use.

Decentralized and Modular Electrical Architecture

Science.gov (United States)

Elisabelar, Christian; Lebaratoux, Laurence

2014-08-01

This paper presents the studies made on the definition and design of a decentralized and modular electrical architecture that can be used for power distribution, active thermal control (ATC), standard inputs-outputs electrical interfaces.Traditionally implemented inside central unit like OBC or RTU, these interfaces can be dispatched in the satellite by using MicroRTU.CNES propose a similar approach of MicroRTU. The system is based on a bus called BRIO (Bus Réparti des IO), which is composed, by a power bus and a RS485 digital bus. BRIO architecture is made with several miniature terminals called BTCU (BRIO Terminal Control Unit) distributed in the spacecraft.The challenge was to design and develop the BTCU with very little volume, low consumption and low cost. The standard BTCU models are developed and qualified with a configuration dedicated to ATC, while the first flight model will fly on MICROSCOPE for PYRO actuations and analogue acquisitions. The design of the BTCU is made in order to be easily adaptable for all type of electric interface needs.Extension of this concept is envisaged for power conditioning and distribution unit, and a Modular PCDU based on BRIO concept is proposed.

Decentralized Budgeting: Getting the Most Out of Disbursements of Funds.

Science.gov (United States)

Jefferson, Anne L.

1995-01-01

Decentralizing educational budgets allows the disbursement of funds aimed at maximizing student development. Three strategies for decentralizing budgets are program budgeting, which eliminates line-item budgeting and allows administrators to address questions regarding the relative value of educational programs; zero-based budgeting, which allows…

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

Science.gov (United States)

She, Hsiao-Ching; Liao, Ya-Wen

2010-01-01

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

Water Governance in Chile and Canada: a Comparison of Adaptive Characteristics

Directory of Open Access Journals (Sweden)

Margot A. Hurlbert

2013-12-01

Full Text Available We compare the structures and adaptive capacities of water governance regimes that respond to water scarcity or drought in the South Saskatchewan River Basin (SSRB of western Canada and the Elqui River Basin (EB in Chile. Both regions anticipate climate change that will result in more extreme weather events including increasing droughts. The SSRB and the EB represent two large, regional, dryland water basins with significant irrigated agricultural production but with significantly different governance structures. The Canadian governance situation is characterized as decentralized multilevel governance with assigned water licenses; the Chilean is characterized as centralized governance with privatized water rights. Both countries have action at all levels in relation to water scarcity or drought. This structural comparison is based on studies carried out in each region assessing the adaptive capacity of each region to climate variability in the respective communities and applicable governance institutions through semistructured qualitative interviews. Based on this comparison, conclusions are drawn on the adaptive capacity of the respective water governance regimes based on four dimensions of adaptive governance that include: responsiveness, learning, capacity, including information, leadership, and equity. The result of the assessment allows discussion of the significant differences in terms of ability of distinct governance structures to foster adaptive capacity in the rural sector, highlights the need for a better understanding of the relationship of adaptive governance and good governance, and the need for more conceptual work on the interconnections of the dimensions of adaptive governance.

Adaptive Learning Systems: Beyond Teaching Machines

Science.gov (United States)

Kara, Nuri; Sevim, Nese

2013-01-01

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

Decentralization in Ethiopia

OpenAIRE

Gemechu, Mulugeta Debebbe

2012-01-01

Ethiopia officially launched the District Level Decentralization Program (DLDP) by the year 2002. The program flagged core objectives such as institutionalizing viable development centers at local levels, deepening devolution of power, enhancing the democratization process through broad-based participatory strategy, promoting good governance and improving service delivery. Since the inception of this program two strategic planning terms (one strategic term is five years) have already elapsed ...

Applying perceptual and adaptive learning techniques for teaching introductory histopathology

Directory of Open Access Journals (Sweden)

Sally Krasne

2013-01-01

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

Optical implementations of associative networks with versatile adaptive learning capabilities.

Science.gov (United States)

Fisher, A D; Lippincott, W L; Lee, J N

1987-12-01

Optical associative, parallel-processing architectures are being developed using a multimodule approach, where a number of smaller, adaptive, associative modules are nonlinearly interconnected and cascaded under the guidance of a variety of organizational principles to structure larger architectures for solving specific problems. A number of novel optical implementations with versatile adaptive learning capabilities are presented for the individual associative modules, including holographic configurations and five specific electrooptic configurations. The practical issues involved in real optical architectures are analyzed, and actual laboratory optical implementations of associative modules based on Hebbian and Widrow-Hoff learning rules are discussed, including successful experimental demonstrations of their operation.

Decentralized H∞ Control of Interconnected Systems with Time-varying Delays

Directory of Open Access Journals (Sweden)

Amal Zouhri

2017-01-01

Full Text Available This paper focuses on the problem of delay dependent stability/stabilization of interconnected systems with time-varying delays. The approach is based on a new Lyapunov-Krasovskii functional. A decentralized delay-dependent stability analysis is performed to characterize linear matrix inequalities (LMIs based on the conditions under which every local subsystem of the linear interconnected delay system is asymptotically stable. Then we design a decentralized state-feedback stabilization scheme such that the family of closedloop feedback subsystems enjoys the delay-dependent asymptotic stability for each subsystem. The decentralized feedback gains are determined by convex optimization over LMIs. All the developed results are tested on a representative example and compared with some recent previous ones.

Multiagent cooperation and competition with deep reinforcement learning.

Directory of Open Access Journals (Sweden)

Ardi Tampuu

Full Text Available Evolution of cooperation and competition can appear when multiple adaptive agents share a biological, social, or technological niche. In the present work we study how cooperation and competition emerge between autonomous agents that learn by reinforcement while using only their raw visual input as the state representation. In particular, we extend the Deep Q-Learning framework to multiagent environments to investigate the interaction between two learning agents in the well-known video game Pong. By manipulating the classical rewarding scheme of Pong we show how competitive and collaborative behaviors emerge. We also describe the progression from competitive to collaborative behavior when the incentive to cooperate is increased. Finally we show how learning by playing against another adaptive agent, instead of against a hard-wired algorithm, results in more robust strategies. The present work shows that Deep Q-Networks can become a useful tool for studying decentralized learning of multiagent systems coping with high-dimensional environments.

Multiagent cooperation and competition with deep reinforcement learning

Science.gov (United States)

Kodelja, Dorian; Kuzovkin, Ilya; Korjus, Kristjan; Aru, Juhan; Aru, Jaan; Vicente, Raul

2017-01-01

Evolution of cooperation and competition can appear when multiple adaptive agents share a biological, social, or technological niche. In the present work we study how cooperation and competition emerge between autonomous agents that learn by reinforcement while using only their raw visual input as the state representation. In particular, we extend the Deep Q-Learning framework to multiagent environments to investigate the interaction between two learning agents in the well-known video game Pong. By manipulating the classical rewarding scheme of Pong we show how competitive and collaborative behaviors emerge. We also describe the progression from competitive to collaborative behavior when the incentive to cooperate is increased. Finally we show how learning by playing against another adaptive agent, instead of against a hard-wired algorithm, results in more robust strategies. The present work shows that Deep Q-Networks can become a useful tool for studying decentralized learning of multiagent systems coping with high-dimensional environments. PMID:28380078

Multiagent cooperation and competition with deep reinforcement learning.

Science.gov (United States)

Tampuu, Ardi; Matiisen, Tambet; Kodelja, Dorian; Kuzovkin, Ilya; Korjus, Kristjan; Aru, Juhan; Aru, Jaan; Vicente, Raul

2017-01-01

Evolution of cooperation and competition can appear when multiple adaptive agents share a biological, social, or technological niche. In the present work we study how cooperation and competition emerge between autonomous agents that learn by reinforcement while using only their raw visual input as the state representation. In particular, we extend the Deep Q-Learning framework to multiagent environments to investigate the interaction between two learning agents in the well-known video game Pong. By manipulating the classical rewarding scheme of Pong we show how competitive and collaborative behaviors emerge. We also describe the progression from competitive to collaborative behavior when the incentive to cooperate is increased. Finally we show how learning by playing against another adaptive agent, instead of against a hard-wired algorithm, results in more robust strategies. The present work shows that Deep Q-Networks can become a useful tool for studying decentralized learning of multiagent systems coping with high-dimensional environments.

Learning-Based Adaptive Imputation Methodwith kNN Algorithm for Missing Power Data

Directory of Open Access Journals (Sweden)

Minkyung Kim

2017-10-01

Full Text Available This paper proposes a learning-based adaptive imputation method (LAI for imputing missing power data in an energy system. This method estimates the missing power data by using the pattern that appears in the collected data. Here, in order to capture the patterns from past power data, we newly model a feature vector by using past data and its variations. The proposed LAI then learns the optimal length of the feature vector and the optimal historical length, which are significant hyper parameters of the proposed method, by utilizing intentional missing data. Based on a weighted distance between feature vectors representing a missing situation and past situation, missing power data are estimated by referring to the k most similar past situations in the optimal historical length. We further extend the proposed LAI to alleviate the effect of unexpected variation in power data and refer to this new approach as the extended LAI method (eLAI. The eLAI selects a method between linear interpolation (LI and the proposed LAI to improve accuracy under unexpected variations. Finally, from a simulation under various energy consumption profiles, we verify that the proposed eLAI achieves about a 74% reduction of the average imputation error in an energy system, compared to the existing imputation methods.

Decentralized control of complex systems

CERN Document Server

Siljak, Dragoslav D

2011-01-01

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

Six hospitals describe decentralization, cost containment, and downsizing.

Science.gov (United States)

Lineweaver, L A; Battle, C E; Schilling, R M; Nall, C M

1999-01-01

Decentralization, cost containment, and downsizing continue in full force as healthcare organizations continue to adapt to constant economic change. Hospitals are forced to take a second and third look at how health care is managed in order to survive. Six Northwest Florida hospitals were surveyed in an effort to explore current changes within the healthcare delivery system. This article provides both managers and staff with an overview of recent healthcare changes in an area of the country with implications for staff development.

Adaptive vs. eductive learning : Theory and evidence

NARCIS (Netherlands)

Bao, T.; Duffy, J.

2014-01-01

Adaptive learning and eductive learning are two widely used ways of modeling learning behavior in macroeconomics. Both approaches yield restrictions on model parameters under which agents are able to learn a rational expectation equilibrium (REE) but these restrictions do not always overlap with one

Subsecond Tsunamis and Delays in Decentralized Electronic Systems

Directory of Open Access Journals (Sweden)

Pedro D. Manrique

2017-10-01

Full Text Available Driven by technological advances and economic gain, society’s electronic systems are becoming larger, faster, more decentralized and autonomous, and yet with increasing global reach. A prime example are the networks of financial markets which—in contrast to popular perception—are largely all-electronic and decentralized with no top-down real-time controller. This prototypical system generates complex subsecond dynamics that emerge from a decentralized network comprising heterogeneous hardware and software components, communications links, and a diverse ecology of trading algorithms that operate and compete within this all-electronics environment. Indeed, these same technological and economic drivers are likely to generate a similarly competitive all-electronic ecology in a variety of future cyberphysical domains such as e-commerce, defense and the transportation system, including the likely appearance of large numbers of autonomous vehicles on the streets of many cities. Hence there is an urgent need to deepen our understanding of stability, safety and security across a wide range of ultrafast, large, decentralized all-electronic systems—in short, society will eventually need to understand what extreme behaviors can occur, why, and what might be the impact of both intentional and unintentional system perturbations. Here we set out a framework for addressing this issue, using a generic model of heterogeneous, adaptive, autonomous components where each has a realistic limit on the amount of information and processing power available to it. We focus on the specific impact of delayed information, possibly through an accidental shift in the latency of information transmission, or an intentional attack from the outside. While much remains to be done in terms of developing formal mathematical results for this system, our preliminary results indicate the type of impact that can occur and the structure of a mathematical theory which may

What supervisors want to know about decentralization.

Science.gov (United States)

Boissoneau, R; Belton, P

1991-06-01

Many organizations in various industries have tended to move away from strict centralization, yet some centralization is still vital to top management. With 19 of the 22 executives interviewed favoring or implementing some form of decentralization, it is probable that traditionally centralized organizations will follow the trend and begin to decentralize their organizational structures. The incentives and advantages of decentralization are too attractive to ignore. Decentralization provides responsibility, clear objectives, accountability for results, and more efficient and effective decision making. However, one must remember that decentralization can be overextended and that centralization is still viable in certain functions. Finding the correct balance between control and autonomy is a key to decentralization. Too much control and too much autonomy are the primary reasons for decentralization failures. In today's changing, competitive environment, structures must be continuously redefined, with the goal of finding an optimal balance between centralization and decentralization. Organizations are cautioned not to seek out and install a single philosopher-king to impose unified direction, but to unify leadership goals, participation, style, and control to develop improved methods of making all responsible leaders of one mind about the organization's needs and goals.

E-learning: Web-based education.

Science.gov (United States)

Sajeva, Marco

2006-12-01

This review introduces state-of-the-art Web-based education and shows how the e-learning model can be applied to an anaesthesia department using Open Source solutions, as well as lifelong learning programs, which is happening in several European research projects. The definition of the term e-learning is still a work in progress due to the fact that technologies are evolving every day and it is difficult to improve teaching methodologies or to adapt traditional methods to a new or already existing educational model. The European Community is funding several research projects to define the new common market place for tomorrow's educational system; this is leading to new frontiers like virtual Erasmus inter-exchange programs based on e-learning. The first step when adapting a course to e-learning is to re-define the educational/learning model adopted: cooperative learning and tutoring are the two key concepts. This means that traditional lecture notes, books and exercises are no longer effective; teaching files must use rich multimedia content and have to be developed using the new media. This can lead to several pitfalls that can be avoided with an accurate design phase.

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

Science.gov (United States)

Lee, Chuen-Chien

1991-01-01

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

Decentralizing the Team Station: Simulation before Reality as a Best-Practice Approach.

Science.gov (United States)

Charko, Jackie; Geertsen, Alice; O'Brien, Patrick; Rouse, Wendy; Shahid, Ammarah; Hardenne, Denise

2016-01-01

The purpose of this article is to share the logistical planning requirements and simulation experience of one Canadian hospital as it prepared its staff for the change from a centralized inpatient unit model to the decentralized design planned for its new community hospital. With the commitment and support of senior leadership, project management resources and clinical leads worked collaboratively to design a decentralized prototype in the form of a pod-style environment in the hospital's current setting. Critical success factors included engaging the right stakeholders, providing an opportunity to test new workflows and technology, creating a strong communication plan and building on lessons learned as subsequent pod prototypes are launched.

Impact of Adapted Hypermedia on Undergraduate Students' Learning of Astronomy in an Elearning Environment

Science.gov (United States)

Zuel, Brian

The purpose of this dissertation was to examine the effectiveness of matching learners' optimal learning styles to their overall knowledge retention. The study attempted to determine if learners who are placed in an online learning environment that matches their optimal learning styles will retain the information at a higher rate than those learners who are not in an adapted learning environment. There were 56 participants that took one of two lessons; the first lesson was textual based, had no hypertext, and was not influenced heavily by the coherence principle, while the second lesson was multimedia based utilizing hypermedia guided by the coherence principle. Each participant took Felder and Soloman's (1991, 2000) Index of Learning Styles (ILS) questionnaire and was classified using the Felder-Silverman Learning Style Model (FSLSM; 1998) into four individual categories. Groups were separated using the Visual/Verbal section of the FSLSM with 55% (n = 31) of participants going to the adapted group, and 45% (n =25) of participants going to the non-adapted group. Each participant completed an immediate posttest directly after the lesson and a retention posttest a week later. Several repeated measures MANOVA tests were conducted to measure the significance of differences in the tests between groups and within groups. Repeated measures MANOVA tests were conducted to determine if significance existed between the immediate posttest results and the retention posttest results. Also, participants were asked their perspectives if the lesson type they received was beneficial to their perceived learning of the material. Of the 56 students who took part in this study, 31 students were placed in the adapted group and 25 in the non-adapted group based on outcomes of the ILS and the FLSSM. No significant differences were found between groups taking the multimedia lesson and the textual lesson in the immediate posttest. No significant differences were found between the adapted and

Emergent Semantics Interoperability in Large-Scale Decentralized Information Systems

CERN Document Server

Cudré-Mauroux, Philippe

2008-01-01

Peer-to-peer systems are evolving with new information-system architectures, leading to the idea that the principles of decentralization and self-organization will offer new approaches in informatics, especially for systems that scale with the number of users or for which central authorities do not prevail. This book describes a new way of building global agreements (semantic interoperability) based only on decentralized, self-organizing interactions.

Decentralized portfolio management

OpenAIRE

Coutinho, Paulo; Tabak, Benjamin Miranda

2003-01-01

We use a mean-variance model to analyze the problem of decentralized portfolio management. We find the solution for the optimal portfolio allocation for a head trader operating in n different markets, which is called the optimal centralized portfolio. However, as there are many traders specialized in different markets, the solution to the problem of optimal decentralized allocation should be different from the centralized case. In this paper we derive conditions for the solutions to be equiva...

Deep reinforcement learning for automated radiation adaptation in lung cancer.

Science.gov (United States)

Tseng, Huan-Hsin; Luo, Yi; Cui, Sunan; Chien, Jen-Tzung; Ten Haken, Randall K; Naqa, Issam El

2017-12-01

To investigate deep reinforcement learning (DRL) based on historical treatment plans for developing automated radiation adaptation protocols for nonsmall cell lung cancer (NSCLC) patients that aim to maximize tumor local control at reduced rates of radiation pneumonitis grade 2 (RP2). In a retrospective population of 114 NSCLC patients who received radiotherapy, a three-component neural networks framework was developed for deep reinforcement learning (DRL) of dose fractionation adaptation. Large-scale patient characteristics included clinical, genetic, and imaging radiomics features in addition to tumor and lung dosimetric variables. First, a generative adversarial network (GAN) was employed to learn patient population characteristics necessary for DRL training from a relatively limited sample size. Second, a radiotherapy artificial environment (RAE) was reconstructed by a deep neural network (DNN) utilizing both original and synthetic data (by GAN) to estimate the transition probabilities for adaptation of personalized radiotherapy patients' treatment courses. Third, a deep Q-network (DQN) was applied to the RAE for choosing the optimal dose in a response-adapted treatment setting. This multicomponent reinforcement learning approach was benchmarked against real clinical decisions that were applied in an adaptive dose escalation clinical protocol. In which, 34 patients were treated based on avid PET signal in the tumor and constrained by a 17.2% normal tissue complication probability (NTCP) limit for RP2. The uncomplicated cure probability (P+) was used as a baseline reward function in the DRL. Taking our adaptive dose escalation protocol as a blueprint for the proposed DRL (GAN + RAE + DQN) architecture, we obtained an automated dose adaptation estimate for use at ∼2/3 of the way into the radiotherapy treatment course. By letting the DQN component freely control the estimated adaptive dose per fraction (ranging from 1-5 Gy), the DRL automatically favored dose

Inference in models with adaptive learning

NARCIS (Netherlands)

Chevillon, G.; Massmann, M.; Mavroeidis, S.

2010-01-01

Identification of structural parameters in models with adaptive learning can be weak, causing standard inference procedures to become unreliable. Learning also induces persistent dynamics, and this makes the distribution of estimators and test statistics non-standard. Valid inference can be

How Teaching Science Using Project-Based Learning Strategies Affects the Classroom Learning Environment

Science.gov (United States)

Hugerat, Muhamad

2016-01-01

This study involved 458 ninth-grade students from two different Arab middle schools in Israel. Half of the students learned science using project-based learning strategies and the other half learned using traditional methods (non-project-based). The classes were heterogeneous regarding their achievements in the sciences. The adapted questionnaire…

Wage Dispersion and Decentralization of Wage Bargaining

DEFF Research Database (Denmark)

Dahl, Christian Møller; le Maire, Christian Daniel; Munch, Jakob R.

2013-01-01

This article studies how decentralization of wage bargaining from sector to firm level influences wage levels and wage dispersion. We use detailed panel data covering a period of decentralization in the Danish labor market. The decentralization process provides variation in the individual worker......'s wage-setting system that facilitates identification of the effects of decentralization. We find a wage premium associated with firm-level bargaining relative to sector-level bargaining and that the return to skills is higher under the more decentralized wage-setting systems. Using quantile regression......, we also find that wages are more dispersed under firm-level bargaining compared to more centralized wage-setting systems....

Interactive ontology-based user modelling for personalized learning content management

NARCIS (Netherlands)

Denaux, R.O.; Dimitrova, V.; Aroyo, L.M.; Aroyo, L.; Tasso, C.

2004-01-01

This position paper discusses the need for using interactive ontology-based user modeling to empower on the fly adaptation in learning information systems. We outline several open issues related to adaptive learning content delivery and present an approach to deal with these issues based on the

Decentralization and Governance in Indonesia

NARCIS (Netherlands)

Holzhacker, Ronald; Wittek, Rafael; Woltjer, Johan

2016-01-01

I. Theoretical Reflections on Decentralization and Governance for Sustainable Society 1. Decentralization and Governance for Sustainable Society in Indonesia Ronald Holzhacker, Rafael Wittek and Johan Woltjer 2. Good Governance Contested: Exploring Human Rights and Sustainability as Normative Goals

Adapting to managed care by becoming a learning organization.

Science.gov (United States)

O'Sullivan, M J

1999-03-01

In the tumultuous and chaotic environment of managed health care, hospital-based mental health providers need to change in fundamental ways. The traditional view of mental health organizations is a professional-bureaucratic one where actions and outcomes of planning are thought to be highly predictable. The author proposes an alternative paradigm for viewing mental health provider organizations, one based on learning theory, which accepts that the future is unknowable because of its complexity and the probabilistic nature of the world. Within this perspective, mental health care providers need to become "learning organizations" to successfully adapt to the new and evolving conditions.

Financial decentralization and its impact on local finance system of Ukraine

Directory of Open Access Journals (Sweden)

I. V. Mizina

2016-07-01

Full Text Available The article researches the influence of the process of financial decentralization system on local finance system in Ukraine. Author determined the basic transformations of local finances system as a result of reform measures and ways to adapt to new conditions. The basic characteristics of the changing role of public authorities and local governments, their relationships and relationships in the system, strengthening public participation in decision­making of local importance are revealed. The main requirements of local finances taking into account the impact of fiscal decentralization processes are formulated. They include the formation of an effective and sustainable framework for the mobilization of financial resources within each territorial community; providing sufficient resources for sustainable and dynamic development at the local level; improve management of local finances with the application process and project approaches. An action plan to change the system of local finance Ukraine in the context of fiscal decentralization on a 5­year period is proposed. The action plan envisages normalization of regulatory provisions in the area of local finance, training local government officials, development resources, monitoring and evaluating the effectiveness of the current system of local finance.

Adaptive eLearning modules for cytopathology education: A review and approach.

Science.gov (United States)

Samulski, T Danielle; La, Teresa; Wu, Roseann I

2016-11-01

Clinical training imposes time and resource constraints on educators and learners, making it difficult to provide and absorb meaningful instruction. Additionally, innovative and personalized education has become an expectation of adult learners. Fortunately, the development of web-based educational tools provides a possible solution to these challenges. Within this review, we introduce the utility of adaptive eLearning platforms in pathology education. In addition to a review of the current literature, we provide the reader with a suggested approach for module creation, as well as a critical assessment of an available platform, based on our experience in creating adaptive eLearning modules for teaching basic concepts in gynecologic cytopathology. Diagn. Cytopathol. 2016;44:944-951. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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.

Towards more efficient e-learning, intelligence and adapted teaching material

Directory of Open Access Journals (Sweden)

Damir Kalpić

2010-12-01

Full Text Available This article presents results of a research project in which we attempted to determine the relationship between efficient E-learning and teaching materials adapted based on students’ structure of intelligence. The project was conducted on approximately 500 students, 23 classes, nine elementary schools, with ten teachers of history, informatics and several licensed psychologists. E-teaching material was prepared for the subject of History for eight-grade students of elementary school. Students were tested for the structure of intelligence, and based on their most prominent component, they were divided into groups, using teaching materials adapted to their most prominent intelligence component. The results have shown that use of the adapted teaching materials achieved 6-12% better results than E-materials not adapted to students’ structure of intelligence.

From centralization to decentralization in Chinese higher education

Directory of Open Access Journals (Sweden)

Xiaohong Qian

2004-12-01

Full Text Available Since the late 1970’s, the Chinese government has been gradually changing its traditional policy for providing higher education and has begun to emphasize the comprehensiveness of the universities. Interdisciplinary cooperation and the synergization of resources are being promoted, and institutional autonomy is gradually increasing. Schools and faculties have been restored in universities, and new research institutions, research schools, research centers and the like have been established. From a unitary three-level model— university/department/ teaching and research group—before the reform, the organizational structures of the universities have developed a new organizational structure that is more flexible and more open. This more adaptable structure is intended to meet the developmental demands of modern universities with close links being created between their work and regional economic and social development. China has moved from a very centralized educational system in which the main decisions were taken by the central government to a decentralized educational system. This reform is also taking place within the institutions of higher education, and their internal organizational structure has also become more decentralized.

Affect-Aware Adaptive Tutoring Based on Human-Automation Etiquette Strategies.

Science.gov (United States)

Yang, Euijung; Dorneich, Michael C

2018-06-01

We investigated adapting the interaction style of intelligent tutoring system (ITS) feedback based on human-automation etiquette strategies. Most ITSs adapt the content difficulty level, adapt the feedback timing, or provide extra content when they detect cognitive or affective decrements. Our previous work demonstrated that changing the interaction style via different feedback etiquette strategies has differential effects on students' motivation, confidence, satisfaction, and performance. The best etiquette strategy was also determined by user frustration. Based on these findings, a rule set was developed that systemically selected the proper etiquette strategy to address one of four learning factors (motivation, confidence, satisfaction, and performance) under two different levels of user frustration. We explored whether etiquette strategy selection based on this rule set (systematic) or random changes in etiquette strategy for a given level of frustration affected the four learning factors. Participants solved mathematics problems under different frustration conditions with feedback that adapted dynamic changes in etiquette strategies either systematically or randomly. The results demonstrated that feedback with etiquette strategies chosen systematically via the rule set could selectively target and improve motivation, confidence, satisfaction, and performance more than changing etiquette strategies randomly. The systematic adaptation was effective no matter the level of frustration for the participant. If computer tutors can vary the interaction style to effectively mitigate negative emotions, then ITS designers would have one more mechanism in which to design affect-aware adaptations that provide the proper responses in situations where human emotions affect the ability to learn.

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

Science.gov (United States)

Singh, Anita

2017-07-01

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

Communication network for decentralized remote tele-science during the Spacelab mission IML-2

Science.gov (United States)

Christ, Uwe; Schulz, Klaus-Juergen; Incollingo, Marco

1994-01-01

The ESA communication network for decentralized remote telescience during the Spacelab mission IML-2, called Interconnection Ground Subnetwork (IGS), provided data, voice conferencing, video distribution/conferencing and high rate data services to 5 remote user centers in Europe. The combination of services allowed the experimenters to interact with their experiments as they would normally do from the Payload Operations Control Center (POCC) at MSFC. In addition, to enhance their science results, they were able to make use of reference facilities and computing resources in their home laboratory, which typically are not available in the POCC. Characteristics of the IML-2 communications implementation were the adaptation to the different user needs based on modular service capabilities of IGS and the cost optimization for the connectivity. This was achieved by using a combination of traditional leased lines, satellite based VSAT connectivity and N-ISDN according to the simulation and mission schedule for each remote site. The central management system of IGS allows minimization of staffing and the involvement of communications personnel at the remote sites. The successful operation of IGS for IML-2 as a precursor network for the Columbus Orbital Facility (COF) has proven the concept for communications to support the operation of the COF decentralized scenario.

Improving Flood Plain Management through Adaptive Learning ...

International Development Research Centre (IDRC) Digital Library (Canada)

This project will explore how an adaptive learning approach can improve CBO governance ... for improving resource sustainability and productivity, and facilitate learning and an exchange ... Middlesex University Higher Education Corporation.

A contingency approach to decentralization

NARCIS (Netherlands)

Fleurke, F.; Hulst, J.R.

2006-01-01

After decades of centralization, in 1980 the central government of the Netherlands embarked upon an ambitious project to decentralize the administrative system. It proclaimed a series of general decentralization measures that aimed to improve the performance of the administrative system and to boost

Bidirectional decentralized energy management in the low voltage grid based on centralized and decentralized informations; Bidirektionales dezentrales Energiemanagement im Niederspannungsnetz auf Basis zentraler und dezentraler Informationen

Energy Technology Data Exchange (ETDEWEB)

Bendel, C.; Nestle, D.; Ringelstein, J. [Inst. fuer Solare Energieversorgungstechnik e.V., Verein an der Univ. Kassel (Germany)

2006-07-01

Decentralized electrical generation units (DG units) are connected to the network in Europe with an increasing number and generation capacity. This includes renewable energy sources with fluctuating generation characteristics as well as more controllable generation from biomass and co-generation. Severe problems with grid operation are expected among experts when the share of DG without controllability exceeds approx. 20 to 25% of the total generation within the power system, so a new strategy for the integration of DG into grid operation will be required. This strategy will include energy management with controllable generators as well as controllable loads. Today, however, this potential in most cases cannot be activated due to lack of standards and missing economical incentives. In the concept presented in this work the grid connection point is extended by intelligent components to a Bidirectional Energy Management Interface (BEMI). This allows a technically efficienct design of an energy management system and avoids fundamental organizational changes to the current grid regime. The concept of decentralized decision based on information from a central control station covers the requirements of the system operators as well as the local customer. Using the same concept the management of a pool of devices, containing BEMI-equipped households as well as other decentralized resources is possible. This is expected to bring additional benefits for both system operators and local customers. Therefore an approach for upscaling the existing BEMI technology is outlined as an outlook. (orig.)

Beyond adaptive-critic creative learning for intelligent mobile robots

Science.gov (United States)

Liao, Xiaoqun; Cao, Ming; Hall, Ernest L.

2001-10-01

Intelligent industrial and mobile robots may be considered proven technology in structured environments. Teach programming and supervised learning methods permit solutions to a variety of applications. However, we believe that to extend the operation of these machines to more unstructured environments requires a new learning method. Both unsupervised learning and reinforcement learning are potential candidates for these new tasks. The adaptive critic method has been shown to provide useful approximations or even optimal control policies to non-linear systems. The purpose of this paper is to explore the use of new learning methods that goes beyond the adaptive critic method for unstructured environments. The adaptive critic is a form of reinforcement learning. A critic element provides only high level grading corrections to a cognition module that controls the action module. In the proposed system the critic's grades are modeled and forecasted, so that an anticipated set of sub-grades are available to the cognition model. The forecasting grades are interpolated and are available on the time scale needed by the action model. The success of the system is highly dependent on the accuracy of the forecasted grades and adaptability of the action module. Examples from the guidance of a mobile robot are provided to illustrate the method for simple line following and for the more complex navigation and control in an unstructured environment. The theory presented that is beyond the adaptive critic may be called creative theory. Creative theory is a form of learning that models the highest level of human learning - imagination. The application of the creative theory appears to not only be to mobile robots but also to many other forms of human endeavor such as educational learning and business forecasting. Reinforcement learning such as the adaptive critic may be applied to known problems to aid in the discovery of their solutions. The significance of creative theory is that it

Adaptive Kalman filtering for histogram-based appearance learning in infrared imagery.

Science.gov (United States)

Venkataraman, Vijay; Fan, Guoliang; Havlicek, Joseph P; Fan, Xin; Zhai, Yan; Yeary, Mark B

2012-11-01

Targets of interest in video acquired from imaging infrared sensors often exhibit profound appearance variations due to a variety of factors, including complex target maneuvers, ego-motion of the sensor platform, background clutter, etc., making it difficult to maintain a reliable detection process and track lock over extended time periods. Two key issues in overcoming this problem are how to represent the target and how to learn its appearance online. In this paper, we adopt a recent appearance model that estimates the pixel intensity histograms as well as the distribution of local standard deviations in both the foreground and background regions for robust target representation. Appearance learning is then cast as an adaptive Kalman filtering problem where the process and measurement noise variances are both unknown. We formulate this problem using both covariance matching and, for the first time in a visual tracking application, the recent autocovariance least-squares (ALS) method. Although convergence of the ALS algorithm is guaranteed only for the case of globally wide sense stationary process and measurement noises, we demonstrate for the first time that the technique can often be applied with great effectiveness under the much weaker assumption of piecewise stationarity. The performance advantages of the ALS method relative to the classical covariance matching are illustrated by means of simulated stationary and nonstationary systems. Against real data, our results show that the ALS-based algorithm outperforms the covariance matching as well as the traditional histogram similarity-based methods, achieving sub-pixel tracking accuracy against the well-known AMCOM closure sequences and the recent SENSIAC automatic target recognition dataset.

On Decentralization and Life Satisfaction

DEFF Research Database (Denmark)

Bjørnskov, Christian; Dreher, Axel; Fischer, Justina A.V.

2008-01-01

We empirically analyze the impact of fiscal and political decentralization on subjective well-being in a cross-section of 60,000 individuals from 66 countries. More spending or revenue decentralization raises well-being while greater local autonomy is beneficial only via government consumption sp...

Wage Dispersion and Decentralization of Wage Bargaining

DEFF Research Database (Denmark)

Dahl, Christian M.; Le Maire, Christian Daniel; Munch, Jakob Roland

in the individual worker's wage-setting system that facilitates identification of the effects of decentralization. Consistent with predictions we find that wages are more dispersed under firm-level bargaining compared to more centralized wage-setting systems. However, the differences across wage-setting systems......This paper studies how decentralization of wage bargaining from sector to firm level influences wage levels and wage dispersion. We use a detailed panel data set covering a period of decentralization in the Danish labor market. The decentralization process provides exogenous variation...

Decentralized Procurement in Light of Strategic Inventories

DEFF Research Database (Denmark)

Frimor, Hans; Arya, Anil; Mittendorf, Brian

2015-01-01

The centralization versus decentralization choice is perhaps the quintessential organizational structure decision. In the operations realm, this choice is particularly critical when it comes to the procurement function. Why firms may opt to decentralize procurement has been often studied and conf......The centralization versus decentralization choice is perhaps the quintessential organizational structure decision. In the operations realm, this choice is particularly critical when it comes to the procurement function. Why firms may opt to decentralize procurement has been often studied...... and confirmed to be a multifaceted choice. This paper complements existing studies by detailing the trade-offs in the centralization versus decentralization decision in light of firm's decision to cede procurement choices to its individual devisions can help moderate inventory levels and provide a natural salve...

A P2P Botnet detection scheme based on decision tree and adaptive multilayer neural networks.

Science.gov (United States)

Alauthaman, Mohammad; Aslam, Nauman; Zhang, Li; Alasem, Rafe; Hossain, M A

2018-01-01

In recent years, Botnets have been adopted as a popular method to carry and spread many malicious codes on the Internet. These malicious codes pave the way to execute many fraudulent activities including spam mail, distributed denial-of-service attacks and click fraud. While many Botnets are set up using centralized communication architecture, the peer-to-peer (P2P) Botnets can adopt a decentralized architecture using an overlay network for exchanging command and control data making their detection even more difficult. This work presents a method of P2P Bot detection based on an adaptive multilayer feed-forward neural network in cooperation with decision trees. A classification and regression tree is applied as a feature selection technique to select relevant features. With these features, a multilayer feed-forward neural network training model is created using a resilient back-propagation learning algorithm. A comparison of feature set selection based on the decision tree, principal component analysis and the ReliefF algorithm indicated that the neural network model with features selection based on decision tree has a better identification accuracy along with lower rates of false positives. The usefulness of the proposed approach is demonstrated by conducting experiments on real network traffic datasets. In these experiments, an average detection rate of 99.08 % with false positive rate of 0.75 % was observed.

Facilitating peer based learning through summative assessment - An adaptation of the Objective Structured Clinical Assessment tool for the blended learning environment.

Science.gov (United States)

Wikander, Lolita; Bouchoucha, Stéphane L

2018-01-01

Adapting a course from face to face to blended delivery necessitates that assessments are modified accordingly. In Australia the Objective Structured Clinical Assessment tool, as a derivative from the Objective Structured Clinical Examination, has been used in the face-to-face delivery mode as a formative or summative assessment tool in medicine and nursing since 1990. The Objective Structured Clinical Assessment has been used at Charles Darwin University to assess nursing students' simulated clinical skills prior to the commencement of their clinical placements since 2008. Although the majority of the course is delivered online, students attend a one-week intensive clinical simulation block yearly, prior to attending clinical placements. Initially, the Objective Structured Clinical Assessment was introduced as a lecturer assessed summative assessment, over time it was adapted to better suit the blended learning environment. The modification of the tool from an academic to peer assessed assessment tool, was based on the empirical literature, student feedback and a cross-sectional, qualitative study exploring academics' perceptions of the Objective Structured Clinical Assessment (Bouchoucha et al., 2013a, b). This paper presents an overview of the process leading to the successful adaptation of the Objective Structured Clinical Assessment to suit the requirements of a preregistration nursing course delivered through blended learning. This is significant as many universities are moving their curriculum to fully online or blended delivery, yet little attention has been paid to adapting the assessment of simulated clinical skills. The aim is to identify the benefits and drawbacks of using the peer assessed Objective Structured Clinical Assessment and share recommendations for successful implementation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Decentralized State-Observer-Based Traffic Density Estimation of Large-Scale Urban Freeway Network by Dynamic Model

Directory of Open Access Journals (Sweden)

Yuqi Guo

2017-08-01

Full Text Available In order to estimate traffic densities in a large-scale urban freeway network in an accurate and timely fashion when traffic sensors do not cover the freeway network completely and thus only local measurement data can be utilized, this paper proposes a decentralized state observer approach based on a macroscopic traffic flow model. Firstly, by using the well-known cell transmission model (CTM, the urban freeway network is modeled in the way of distributed systems. Secondly, based on the model, a decentralized observer is designed. With the help of the Lyapunov function and S-procedure theory, the observer gains are computed by using linear matrix inequality (LMI technique. So, the traffic densities of the whole road network can be estimated by the designed observer. Finally, this method is applied to the outer ring of the Beijing’s second ring road and experimental results demonstrate the effectiveness and applicability of the proposed approach.

Fast But Fleeting: Adaptive Motor Learning Processes Associated with Aging and Cognitive Decline

Science.gov (United States)

Trewartha, Kevin M.; Garcia, Angeles; Wolpert, Daniel M.

2014-01-01

Motor learning has been shown to depend on multiple interacting learning processes. For example, learning to adapt when moving grasped objects with novel dynamics involves a fast process that adapts and decays quickly—and that has been linked to explicit memory—and a slower process that adapts and decays more gradually. Each process is characterized by a learning rate that controls how strongly motor memory is updated based on experienced errors and a retention factor determining the movement-to-movement decay in motor memory. Here we examined whether fast and slow motor learning processes involved in learning novel dynamics differ between younger and older adults. In addition, we investigated how age-related decline in explicit memory performance influences learning and retention parameters. Although the groups adapted equally well, they did so with markedly different underlying processes. Whereas the groups had similar fast processes, they had different slow processes. Specifically, the older adults exhibited decreased retention in their slow process compared with younger adults. Within the older group, who exhibited considerable variation in explicit memory performance, we found that poor explicit memory was associated with reduced retention in the fast process, as well as the slow process. These findings suggest that explicit memory resources are a determining factor in impairments in the both the fast and slow processes for motor learning but that aging effects on the slow process are independent of explicit memory declines. PMID:25274819

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

Science.gov (United States)

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

2014-10-01

Motor learning has been shown to depend on multiple interacting learning processes. For example, learning to adapt when moving grasped objects with novel dynamics involves a fast process that adapts and decays quickly-and that has been linked to explicit memory-and a slower process that adapts and decays more gradually. Each process is characterized by a learning rate that controls how strongly motor memory is updated based on experienced errors and a retention factor determining the movement-to-movement decay in motor memory. Here we examined whether fast and slow motor learning processes involved in learning novel dynamics differ between younger and older adults. In addition, we investigated how age-related decline in explicit memory performance influences learning and retention parameters. Although the groups adapted equally well, they did so with markedly different underlying processes. Whereas the groups had similar fast processes, they had different slow processes. Specifically, the older adults exhibited decreased retention in their slow process compared with younger adults. Within the older group, who exhibited considerable variation in explicit memory performance, we found that poor explicit memory was associated with reduced retention in the fast process, as well as the slow process. These findings suggest that explicit memory resources are a determining factor in impairments in the both the fast and slow processes for motor learning but that aging effects on the slow process are independent of explicit memory declines. Copyright © 2014 the authors 0270-6474/14/3413411-11$15.00/0.

Adaptive structured dictionary learning for image fusion based on group-sparse-representation

Science.gov (United States)

Yang, Jiajie; Sun, Bin; Luo, Chengwei; Wu, Yuzhong; Xu, Limei

2018-04-01

Dictionary learning is the key process of sparse representation which is one of the most widely used image representation theories in image fusion. The existing dictionary learning method does not use the group structure information and the sparse coefficients well. In this paper, we propose a new adaptive structured dictionary learning algorithm and a l1-norm maximum fusion rule that innovatively utilizes grouped sparse coefficients to merge the images. In the dictionary learning algorithm, we do not need prior knowledge about any group structure of the dictionary. By using the characteristics of the dictionary in expressing the signal, our algorithm can automatically find the desired potential structure information that hidden in the dictionary. The fusion rule takes the physical meaning of the group structure dictionary, and makes activity-level judgement on the structure information when the images are being merged. Therefore, the fused image can retain more significant information. Comparisons have been made with several state-of-the-art dictionary learning methods and fusion rules. The experimental results demonstrate that, the dictionary learning algorithm and the fusion rule both outperform others in terms of several objective evaluation metrics.

Wind Farm Decentralized Dynamic Modeling With Parameters

DEFF Research Database (Denmark)

Soltani, Mohsen; Shakeri, Sayyed Mojtaba; Grunnet, Jacob Deleuran

2010-01-01

Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...... local models. The results of this report are especially useful, but not limited, to design a decentralized wind farm controller, since in centralized controller design one can also use the model and update it in a central computing node.......Development of dynamic wind flow models for wind farms is part of the research in European research FP7 project AEOLUS. The objective of this report is to provide decentralized dynamic wind flow models with parameters. The report presents a structure for decentralized flow models with inputs from...

Preference learning with evolutionary Multivariate Adaptive Regression Spline model

DEFF Research Database (Denmark)

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

2015-01-01

This paper introduces a novel approach for pairwise preference learning through combining an evolutionary method with Multivariate Adaptive Regression Spline (MARS). Collecting users' feedback through pairwise preferences is recommended over other ranking approaches as this method is more appealing...... for function approximation as well as being relatively easy to interpret. MARS models are evolved based on their efficiency in learning pairwise data. The method is tested on two datasets that collectively provide pairwise preference data of five cognitive states expressed by users. The method is analysed...

Ubiquitous consultation tool for decentral knowledge workers

OpenAIRE

Nazari Shirehjini, A.A.; Rühl, C.; Noll, S.

2003-01-01

The special issue of this initial study is to examine the current work situation of consulting companies, and to elaborate a concept for supporting decentralized working consultants. The concept addresses significant challenges of decentralized work processes by deploying the Peer-to-Peer methodology to decentralized expert and Knowledge Management, cooperation, and enterprise resource planning.

promoting self directed learning in simulation based discovery learning environments through intelligent support.

NARCIS (Netherlands)

Veermans, K.H.; de Jong, Anthonius J.M.; van Joolingen, Wouter

2000-01-01

Providing learners with computer-generated feedback on their learning process in simulationbased discovery environments cannot be based on a detailed model of the learning process due to the “open” character of discovery learning. This paper describes a method for generating adaptive feedback for

Query Optimizations over Decentralized RDF Graphs

KAUST Repository

Abdelaziz, Ibrahim; Mansour, Essam; Ouzzani, Mourad; Aboulnaga, Ashraf; Kalnis, Panos

2017-01-01

Applications in life sciences, decentralized social networks, Internet of Things, and statistical linked dataspaces integrate data from multiple decentralized RDF graphs via SPARQL queries. Several approaches have been proposed to optimize query

Adaptive and accelerated tracking-learning-detection

Science.gov (United States)

Guo, Pengyu; Li, Xin; Ding, Shaowen; Tian, Zunhua; Zhang, Xiaohu

2013-08-01

An improved online long-term visual tracking algorithm, named adaptive and accelerated TLD (AA-TLD) based on Tracking-Learning-Detection (TLD) which is a novel tracking framework has been introduced in this paper. The improvement focuses on two aspects, one is adaption, which makes the algorithm not dependent on the pre-defined scanning grids by online generating scale space, and the other is efficiency, which uses not only algorithm-level acceleration like scale prediction that employs auto-regression and moving average (ARMA) model to learn the object motion to lessen the detector's searching range and the fixed number of positive and negative samples that ensures a constant retrieving time, but also CPU and GPU parallel technology to achieve hardware acceleration. In addition, in order to obtain a better effect, some TLD's details are redesigned, which uses a weight including both normalized correlation coefficient and scale size to integrate results, and adjusts distance metric thresholds online. A contrastive experiment on success rate, center location error and execution time, is carried out to show a performance and efficiency upgrade over state-of-the-art TLD with partial TLD datasets and Shenzhou IX return capsule image sequences. The algorithm can be used in the field of video surveillance to meet the need of real-time video tracking.

Evaluation of an Adaptive Learning Technology in a First-year Extended Curriculum Programme Physics course

Directory of Open Access Journals (Sweden)

Moses Mushe Basitere

2017-12-01

Full Text Available Personalised, adaptive online learning platforms that form part of web-based proficiency tests play a major role in the improvement of the quality of learning in physics and assist learners in building proficiency, preparing for tests and using their time more effectively. In this study, the effectiveness of an adaptive learning platform, Wiley Plus ORION, was evaluated using proficiency test scores compared to paper-based test scores in a first-year introductory engineering physics course. Learners’ performance activities on the adaptive learning platform as well as their performance on the proficiency tests and their impact on the paper-based midterm averaged test were investigated using both qualitative and quantitative methods of data collection. A comparison between learners’ performance on the proficiency tests and a paper-based midterm test was done to evaluate whether there was a correlation between their performance on the proficiency tests and the midterm test. Focus group interviews were carried out with three categories of learners to elicit their experiences. Results showed that there was a positive relationship between high-performing learners’ proficiency score in the midterm averaged test and that the proficiency test enhanced learners’ performance in the paper-based midterm averaged test.

Adaptive learning fuzzy control of a mobile robot

International Nuclear Information System (INIS)

Tsukada, Akira; Suzuki, Katsuo; Fujii, Yoshio; Shinohara, Yoshikuni

1989-11-01

In this report a problem is studied to construct a fuzzy controller for a mobile robot to move autonomously along a given reference direction curve, for which control rules are generated and acquired through an adaptive learning process. An adaptive learning fuzzy controller has been developed for a mobile robot. Good properties of the controller are shown through the travelling experiments of the mobile robot. (author)

Decentralization of health care systems and health outcomes: Evidence from a natural experiment.

Science.gov (United States)

Jiménez-Rubio, Dolores; García-Gómez, Pilar

2017-09-01

While many countries worldwide are shifting responsibilities for their health systems to local levels of government, there is to date insufficient evidence about the potential impact of these policy reforms. We estimate the impact of decentralization of the health services on infant and neonatal mortality using a natural experiment: the devolution of health care decision making powers to Spanish regions. The devolution was implemented gradually and asymmetrically over a twenty-year period (1981-2002). The order in which the regions were decentralized was driven by political factors and hence can be considered exogenous to health outcomes. In addition, we exploit the dynamic effect of decentralization of health services and allow for heterogeneous effects by the two main types of decentralization implemented across regions: full decentralization (political and fiscal powers) versus political decentralization only. Our difference in differences results based on a panel dataset for the 50 Spanish provinces over the period 1980 to 2010 show that the lasting benefit of decentralization accrues only to regions which enjoy almost full fiscal and political powers and which are also among the richest regions. Copyright © 2017 Elsevier Ltd. All rights reserved.

SpikeTemp: An Enhanced Rank-Order-Based Learning Approach for Spiking Neural Networks With Adaptive Structure.

Science.gov (United States)

Wang, Jinling; Belatreche, Ammar; Maguire, Liam P; McGinnity, Thomas Martin

2017-01-01

This paper presents an enhanced rank-order-based learning algorithm, called SpikeTemp, for spiking neural networks (SNNs) with a dynamically adaptive structure. The trained feed-forward SNN consists of two layers of spiking neurons: 1) an encoding layer which temporally encodes real-valued features into spatio-temporal spike patterns and 2) an output layer of dynamically grown neurons which perform spatio-temporal classification. Both Gaussian receptive fields and square cosine population encoding schemes are employed to encode real-valued features into spatio-temporal spike patterns. Unlike the rank-order-based learning approach, SpikeTemp uses the precise times of the incoming spikes for adjusting the synaptic weights such that early spikes result in a large weight change and late spikes lead to a smaller weight change. This removes the need to rank all the incoming spikes and, thus, reduces the computational cost of SpikeTemp. The proposed SpikeTemp algorithm is demonstrated on several benchmark data sets and on an image recognition task. The results show that SpikeTemp can achieve better classification performance and is much faster than the existing rank-order-based learning approach. In addition, the number of output neurons is much smaller when the square cosine encoding scheme is employed. Furthermore, SpikeTemp is benchmarked against a selection of existing machine learning algorithms, and the results demonstrate the ability of SpikeTemp to classify different data sets after just one presentation of the training samples with comparable classification performance.

How Language Supports Adaptive Teaching through a Responsive Learning Culture

Science.gov (United States)

Johnston, Peter; Dozier, Cheryl; Smit, Julie

2016-01-01

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

Project-Based Learning Not Just for STEM Anymore

Science.gov (United States)

Duke, Nell K.; Halvorsen, Anne-Lise; Strachan, Stephanie L.

2016-01-01

The popularity of project-based learning has been driven in part by a growing number of STEM schools and programs. But STEM subjects are not the only fertile ground for project-based learning (PBL). Social studies and literacy content, too, can be adapted into PBL units to benefit teaching and learning, the authors argue. They review key studies…

Decentralized Local Services for Improvement of Quality of Life in the Republic of Macedonia, Case Study Tetovo Municipality

Directory of Open Access Journals (Sweden)

Memet Memeti

2012-05-01

Full Text Available The process of decentralization in Macedonia began in July 2005, after the adaption of theconstitutional amendments made which triggered the process of the decentralization in the Republic ofMacedonia. Having in mind that the decentralization implied structural changes in the Macedonian politicalsystem and in relations between the central and the local government, the implementation of the process ofthe decentralization was designed with a phased approach in order to accommodate the local governmentinstitutions with the new competencies. Among others the process of decentralization had an objective tobring the local authorities closer to the citizens through provision of quality local services. In addition it aimsto provide an opportunity for broader participation and representation of the citizens in their communities.This paper attempts to answer three main questions related to quality public services: - The process ofdecentralization has helped to improve the quality of public services? - What areas of public services undermunicipal jurisdiction are satisfied with it? - How much would you like to be informed about communityactivities? In this paper we are going to analyze the findings from the field research about the quality ofpublic service that provide the municipality of Tetovo of R. Macedonia. The paper focuses on the satisfactionon the public services and provides recommendations for future improvement of the decentralized publicservices in the Republic of Macedonia.

Adaptive learning and complex dynamics

International Nuclear Information System (INIS)

Gomes, Orlando

2009-01-01

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

A web-based adaptive tutor to teach PCR primer design

NARCIS (Netherlands)

van Seters, Janneke R.; Wellink, Joan; Tramper, Johannes; Goedhart, Martin J.; Ossevoort, Miriam A.

2012-01-01

When students have varying prior knowledge, personalized instruction is desirable. One way to personalize instruction is by using adaptive e-learning to offer training of varying complexity. In this study, we developed a web-based adaptive tutor to teach PCR primer design: the PCR Tutor. We used

A Web-based Adaptive Tutor to Teach PCR Primer Design

NARCIS (Netherlands)

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

2012-01-01

When students have varying prior knowledge, personalized instruction is desirable. One way to personalize instruction is by using adaptive e-learning to offer training of varying complexity. In this study, we developed a web-based adaptive tutor to teach PCR primer design: the PCR Tutor. We used

Decentralized or Centralized Systems for Colleges and Universities?

Science.gov (United States)

Heydinger, Richard B.; Norris, Donald M.

1979-01-01

Arguments for and against decentralization of data management, analysis, and planning systems are presented. It is suggested that technological advances have encouraged decentralization. Caution in this direction is urged and the development of an articulated decentralization program is proposed. (SF)

Analysis for corruption and decentralization (Case study: earlier decentralization era in Indonesia)

OpenAIRE

Haryanto, Joko Tri; Astuti S.A., Esther Sri

2017-01-01

In many countries, relationship between decentralization of government activities and the extent of rent extraction by private parties is an important element in the recent debate on institutional design. The topic of corruption was actively, openly and debated in Indonesia by government, its development partners, and a broadly based group of political and civil society leaders are engaged in meetings and exchange on a daily basis. In the ongoing debate on corruption a lot of attention is pai...

Minimal-Learning-Parameter Technique Based Adaptive Neural Sliding Mode Control of MEMS Gyroscope

Directory of Open Access Journals (Sweden)

Bin Xu

2017-01-01

Full Text Available This paper investigates an adaptive neural sliding mode controller for MEMS gyroscopes with minimal-learning-parameter technique. Considering the system uncertainty in dynamics, neural network is employed for approximation. Minimal-learning-parameter technique is constructed to decrease the number of update parameters, and in this way the computation burden is greatly reduced. Sliding mode control is designed to cancel the effect of time-varying disturbance. The closed-loop stability analysis is established via Lyapunov approach. Simulation results are presented to demonstrate the effectiveness of the method.

A METHODOLOGICAL APPROACH FOR IMPLEMENTATION OF ADAPTIVE E-LEARNING

OpenAIRE

Valia Arnaudova; Todorka Terzieva; Asen Rahnev

2016-01-01

The purpose of adaptive e-Learning is to ensure effective teaching by providing an opportunity for students to connect with an environment that suits their needs, behavior, and knowledge. The reason adaptive e-Learning is important is that, for a learning process to be successful, it is necessary to consider teaching materials that address specific characteristics of the student, such as their particular goals, preferences, knowledge, and style of studying, to provide an appropriate teaching ...

Adaptive web-based educational hypermedia

NARCIS (Netherlands)

De Bra, P.M.E.; Aroyo, L.M.; Cristea, A.I.; Levene, M.; Poulavassis, A.

2004-01-01

This chapter describes recent and ongoing research to automatically personalize a learning experience through adaptive educational hypermedia. The Web had made it possible to give a very large audience access to the same learning material. Rather than offering several versions of learning material

Adaptive Web-based Educational Hypermedia

NARCIS (Netherlands)

De Bra, Paul; Aroyo, Lora; Cristea, Alexandra; Levene, Mark; Poulovassilis, Alexandra

2004-01-01

This chapter describes recent and ongoing research to automatically personalize a learning experience through adaptive educational hypermedia. The Web has made it possible to give a very large audience access to the same learning material. Rather than offering several versions of learning material

Decentralization and Economic Growth per capita in Europe

NARCIS (Netherlands)

Crucq, Pieter; Hemminga, Hendrik-Jan

2007-01-01

In this paper the relationship between decentralization and economic growth is investigated. The focus is on decentralization from the national government to the highest substate level in a country, which we define as regional decentralization. Section 2 discusses the different dimensions of

Micro perspectives for decentralized energy supply. Proceedings of the international conference

Energy Technology Data Exchange (ETDEWEB)

Schaefer, Martina; Kebir, Noara; Philipp, Daniel (eds.)

2011-07-01

criteria analysis for sustainability assessments of electricity generation systems in a rural community in South Africa (B. Amigun); (17) Comparative Analysis between grid extension and decentralized solutions for rural electrification - case study: Sofala Province in Mozambique (J. Graf); (18) A mathematical approach for the analysis of energy scenarios for production in India (A. Fuegenschuh); (19) Changing behaviour: Individual energy use, strategic behavioural niche management and decentralised energy conservation in the UK (D.S. Theiss); (20) Local acceptance of wind energy: A comparison between Germany, Argentina and Spain (M. Jimeno); (21) Rural electrification in developing countries: Social acceptance of small photovoltaic lanterns in Ethiopia (H. Mueggenberg); (22) Taking the user's perspective regarding knowledge on solar home systems in Uganda (A. Tillmans); (23) Micro-energy systems in low-income countries: Learning to articulate the solar home system niche in Tanzania (R. Byrne); (24) Quality issues in the marked based dissemination of solar home systems (K. Lindner); (25) Introducing integrated food-energy systems that work for people and climate (A. Bagdanski); (26) Development of adaptive technologies in the project biogas support for Tanzania 'Biogas ST' (P. Becker); (27) Hydrothermal carbonization as innovative technology in sustainable sanitation in Tanzania (A. Krause); (28) Small hydropower in rural Uganda (M.S. Abbo); (29) Presenting automatic demand control (ADC) as a new frequency control method in smart grids (M.T. Ameli); (30) Capitalizing on the asset nature of micro energy systems to promote social transformation in economically marginalized and structurally neglected rural areas of Kenya (R. Mutsaers); (31) Developing microfinance models to facilitate adoption of biogas systems in rural Northwest China (G. Harris); (32) Microfinancing decentralized solar energy systems in India: Experiences of rural banks and the way forward (S

MACROECONOMIC IMPACT OF DECENTRALIZATION

Directory of Open Access Journals (Sweden)

Emilia Cornelia STOICA

2014-05-01

Full Text Available The concept of decentralization has a variety of expressions, but the meaning generally accepted refers to the transfer of authority and responsibility of the public functions from central government to sub-national public entities or even to the private sector. Decentralization process is complex, affecting many aspects of social and economic life and public management, and its design and implementation cover several stages, depending on the cyclical and structural developments of the country. From an economic perspective, decentralization is seen as a means of primary importance in terms of improving the effectiveness and efficiency of public services and macroeconomic stability due to the redistribution of public finances while in a much closer logic of the government policy objectives. But the decentralization process behaves as well some risks, because it involves the implementation of appropriate mechanisms for the establishment of income and expenditure programming at the subnational level, which, if is not correlated with macroeconomic policy imperatives can lead to major imbalances, both financially as in termes of economic and social life. Equally, ensuring the balance of the budget at the local level is imperative to fulfill, this goal imposing a legal framework and specific procedures to size transfers of public funds, targeted or untargeted. Also, public and local authorities have to adopt appropriate laws and regulations such that sub-national public entities can access loans - such as bank loans or debentures from domestic or external market - in terms of a strict monitoring national financial stability. In all aspects of decentralization - political, administrative, financial -, public authorities should develop and implement the most effective mechanisms to coordinate macroeconomic objectives and both sectoral and local interests and establish clear responsibilities - exclusive or shared - for all parties involved in the

Neuromodulatory Adaptive Combination of Correlation-based Learning in Cerebellum and Reward-based Learning in Basal Ganglia for Goal-directed Behavior Control

DEFF Research Database (Denmark)

Dasgupta, Sakyasingha; Wörgötter, Florentin; Manoonpong, Poramate

2014-01-01

Goal-directed decision making in biological systems is broadly based on associations between conditional and unconditional stimuli. This can be further classified as classical conditioning (correlation-based learning) and operant conditioning (reward-based learning). A number of computational...... and experimental studies have well established the role of the basal ganglia in reward-based learning, where as the cerebellum plays an important role in developing specific conditioned responses. Although viewed as distinct learning systems, recent animal experiments point toward their complementary role...... in behavioral learning, and also show the existence of substantial two-way communication between these two brain structures. Based on this notion of co-operative learning, in this paper we hypothesize that the basal ganglia and cerebellar learning systems work in parallel and interact with each other. We...

Learning Motivation and Adaptive Video Caption Filtering for EFL Learners Using Handheld Devices

Science.gov (United States)

Hsu, Ching-Kun

2015-01-01

The aim of this study was to provide adaptive assistance to improve the listening comprehension of eleventh grade students. This study developed a video-based language learning system for handheld devices, using three levels of caption filtering adapted to student needs. Elementary level captioning excluded 220 English sight words (see Section 1…

Developing the learning physical science curriculum: Adapting a small enrollment, laboratory and discussion based physical science course for large enrollments

Science.gov (United States)

Goldberg, Fred; Price, Edward; Robinson, Stephen; Boyd-Harlow, Danielle; McKean, Michael

2012-06-01

We report on the adaptation of the small enrollment, lab and discussion based physical science course, Physical Science and Everyday Thinking (PSET), for a large-enrollment, lecture-style setting. Like PSET, the new Learning Physical Science (LEPS) curriculum was designed around specific principles based on research on learning to meet the needs of nonscience students, especially prospective and practicing elementary and middle school teachers. We describe the structure of the two curricula and the adaptation process, including a detailed comparison of similar activities from the two curricula and a case study of a LEPS classroom implementation. In LEPS, short instructor-guided lessons replace lengthier small group activities, and movies, rather than hands-on investigations, provide the evidence used to support and test ideas. LEPS promotes student peer interaction as an important part of sense making via “clicker” questions, rather than small group and whole class discussions typical of PSET. Examples of student dialog indicate that this format is capable of generating substantive student discussion and successfully enacting the design principles. Field-test data show similar student content learning gains with the two curricula. Nevertheless, because of classroom constraints, some important practices of science that were an integral part of PSET were not included in LEPS.

Developing the learning physical science curriculum: Adapting a small enrollment, laboratory and discussion based physical science course for large enrollments

Directory of Open Access Journals (Sweden)

Fred Goldberg1

2012-05-01

Full Text Available We report on the adaptation of the small enrollment, lab and discussion based physical science course, Physical Science and Everyday Thinking (PSET, for a large-enrollment, lecture-style setting. Like PSET, the new Learning Physical Science (LEPS curriculum was designed around specific principles based on research on learning to meet the needs of nonscience students, especially prospective and practicing elementary and middle school teachers. We describe the structure of the two curricula and the adaptation process, including a detailed comparison of similar activities from the two curricula and a case study of a LEPS classroom implementation. In LEPS, short instructor-guided lessons replace lengthier small group activities, and movies, rather than hands-on investigations, provide the evidence used to support and test ideas. LEPS promotes student peer interaction as an important part of sense making via “clicker” questions, rather than small group and whole class discussions typical of PSET. Examples of student dialog indicate that this format is capable of generating substantive student discussion and successfully enacting the design principles. Field-test data show similar student content learning gains with the two curricula. Nevertheless, because of classroom constraints, some important practices of science that were an integral part of PSET were not included in LEPS.

Intelligent and Adaptive Educational-Learning Systems Achievements and Trends

CERN Document Server

2013-01-01

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

Seamless Integration of Desktop and Mobile Learning Experience through an Ontology-Based Adaptation Engine: Report of a Pilot-Project

Science.gov (United States)

Mercurio, Marco; Torre, Ilaria; Torsani, Simone

2014-01-01

The paper describes a module within the distance language learning environment of the Language Centre at the Genoa University which adapts, through an ontology, learning activities to the device in use. Adaptation means not simply resizing a page but also the ability to transform the nature of a task so that it fits the device with the smallest…

Decentralized Economic Dispatch Scheme With Online Power Reserve for Microgrids

DEFF Research Database (Denmark)

Nutkani, I. U.; Loh, Poh Chiang; Wang, P.

2017-01-01

Decentralized economic operation schemes have several advantages when compared with the traditional centralized management system for microgrids. Specifically, decentralized schemes are more flexible, less computationally intensive, and easier to implement without relying on communication...... costs, their power ratings, and other necessary constraints, before deciding the DG dispatch priorities and droop characteristics. The proposed scheme also allows online power reserve to be set and regulated within the microgrid. This, together with the generation cost saved, has been verified...... infrastructure. Economic operation of existing decentralized schemes is also usually achieved by either tuning the droop characteristics of distributed generators (DGs) or prioritizing their dispatch order. For the latter, an earlier scheme has tried to prioritize the DG dispatch based on their no...

Decentralized Optimization for a Novel Control Structure of HVAC System

Directory of Open Access Journals (Sweden)

Shiqiang Wang

2016-01-01

Full Text Available A decentralized control structure is introduced into the heating, ventilation, and air conditioning (HVAC system to solve the high maintenance and labor cost problem in actual engineering. Based on this new control system, a decentralized optimization method is presented for sensor fault repair and optimal group control of HVAC equipment. Convergence property of the novel method is theoretically analyzed considering both convex and nonconvex systems with constraints. In this decentralized control system, traditional device is fitted with a control chip such that it becomes a smart device. The smart device can communicate and operate collaboratively with the other devices to accomplish some designated tasks. The effectiveness of the presented method is verified by simulations and hardware tests.

Distributed and decentralized control architectures for converter-interfaced microgrids

DEFF Research Database (Denmark)

Dragicevic, Tomislav; Wu, Dan; Shafiee, Qobad

2017-01-01

This paper gives a summary on recently available technologies for decentralized and distributed control of microgrids. They can be classified into two general categories: 1) power line communication based architectures and 2) multi-agent based architectures. The essential control methods and info......This paper gives a summary on recently available technologies for decentralized and distributed control of microgrids. They can be classified into two general categories: 1) power line communication based architectures and 2) multi-agent based architectures. The essential control methods...... and information sharing algorithms applied in these architectures are reviewed and examined in a hierarchical manner, in order to point out benefits they will bring to future microgrid applications. The paper is concluded with a summary on existing methods and a discussion on future development trends....

Fundamentals of Adaptive Intelligent Tutoring Systems for Self-Regulated Learning

Science.gov (United States)

2015-03-01

ARL-SR-0318 ● MAR 2015 US Army Research Laboratory Fundamentals of Adaptive Intelligent Tutoring Systems for Self-Regulated...Adaptive Intelligent Tutoring Systems for Self-Regulated Learning by Robert A Sottilare Human Research and Engineering Directorate, ARL...TITLE AND SUBTITLE Fundamentals of Adaptive Intelligent Tutoring Systems for Self-Regulated Learning 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c

How adaptive learning affects evolution: reviewing theory on the Baldwin effect

NARCIS (Netherlands)

Sznajder, B.; Sabelis, M.W.; Egas, M.

2012-01-01

We review models of the Baldwin effect, i.e., the hypothesis that adaptive learning (i.e., learning to improve fitness) accelerates genetic evolution of the phenotype. Numerous theoretical studies scrutinized the hypothesis that a non-evolving ability of adaptive learning accelerates evolution of

Project Based Learning in Multi-Grade Class

Science.gov (United States)

Ciftci, Sabahattin; Baykan, Ayse Aysun

2013-01-01

The purpose of this study is to evaluate project based learning in multi-grade classes. This study, based on a student-centered learning approach, aims to analyze students' and parents' interpretations. The study was done in a primary village school belonging to the Centre of Batman, already adapting multi-grade classes in their education system,…

CMAC-based adaptive backstepping synchronization of uncertain chaotic systems

International Nuclear Information System (INIS)

Lin, C.-M.; Peng, Y.-F.; Lin, M.-H.

2009-01-01

This study proposes an adaptive backstepping control system for synchronizing uncertain chaotic system by using cerebellar model articulation controller (CMAC). CMAC is a nonlinear network with simple computation, good generalization capability and fast learning property. The proposed CMAC-based adaptive backstepping control (CABC) system uses backstepping method and adaptive cerebellar model articulation controller (ACMAC) for synchronizing uncertain chaotic system. Finally, simulation results for the Genesio system are presented to illustrate the effectiveness of the proposed control system.

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

Science.gov (United States)

Squires, David R.

2014-01-01

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

(De)centralization of the global informational ecosystem

OpenAIRE

Möller, Johanna; Rimscha, M. Bjørn von

2017-01-01

Centralization and decentralization are key concepts in debates that focus on the (anti)democratic character of digital societies. Centralization is understood as the control over communication and data flows, and decentralization as giving it (back) to users. Communication and media research focuses on centralization put forward by dominant digital media platforms, such as Facebook and Google, and governments. Decentralization is investigated regarding its potential in civil society, i.e., h...

The influence of decentralization on effectiveness of extension ...

African Journals Online (AJOL)

Against the background of frequent organisational changes and restructuring, often based on impulsive decisions rather than structured feasibility studies or evaluations, this article examines the influence of decentralization on the performance of an extension organization. Based on a survey of 353 respondents from ...

MEAT: An Authoring Tool for Generating Adaptable Learning Resources

Science.gov (United States)

Kuo, Yen-Hung; Huang, Yueh-Min

2009-01-01

Mobile learning (m-learning) is a new trend in the e-learning field. The learning services in m-learning environments are supported by fundamental functions, especially the content and assessment services, which need an authoring tool to rapidly generate adaptable learning resources. To fulfill the imperious demand, this study proposes an…

Decentralized control using compositional analysis techniques

NARCIS (Netherlands)

Kerber, F.; van der Schaft, A. J.

2011-01-01

Decentralized control strategies aim at achieving a global control target by means of distributed local controllers acting on individual subsystems of the overall plant. In this sense, decentralized control is a dual problem to compositional analysis where a global verification task is decomposed

Implementation of Evidence-Based Practice From a Learning Perspective.

Science.gov (United States)

Nilsen, Per; Neher, Margit; Ellström, Per-Erik; Gardner, Benjamin

2017-06-01

For many nurses and other health care practitioners, implementing evidence-based practice (EBP) presents two interlinked challenges: acquisition of EBP skills and adoption of evidence-based interventions and abandonment of ingrained non-evidence-based practices. The purpose of this study to describe two modes of learning and use these as lenses for analyzing the challenges of implementing EBP in health care. The article is theoretical, drawing on learning and habit theory. Adaptive learning involves a gradual shift from slower, deliberate behaviors to faster, smoother, and more efficient behaviors. Developmental learning is conceptualized as a process in the "opposite" direction, whereby more or less automatically enacted behaviors become deliberate and conscious. Achieving a more EBP depends on both adaptive and developmental learning, which involves both forming EBP-conducive habits and breaking clinical practice habits that do not contribute to realizing the goals of EBP. From a learning perspective, EBP will be best supported by means of adaptive learning that yields a habitual practice of EBP such that it becomes natural and instinctive to instigate EBP in appropriate contexts by means of seeking out, critiquing, and integrating research into everyday clinical practice as well as learning new interventions best supported by empirical evidence. However, the context must also support developmental learning that facilitates disruption of existing habits to ascertain that the execution of the EBP process or the use of evidence-based interventions in routine practice is carefully and consciously considered to arrive at the most appropriate response. © 2017 Sigma Theta Tau International.

Decentralization of Health System in Islamic Republic of Iran

Directory of Open Access Journals (Sweden)

MJ Kabir

2008-10-01

Full Text Available Decentralization is the process of dispersing decision-making closer to the point of peripheral area, service or action. Basically decentralized governance, if properly planned and implemented, offers important opportunities for enhanced human development. The studies about this issue in different countries show that most of the decentralizations have been implemented in European countries and in comparison, the Middle East countries have been utilized lower degrees of the decentralization process. In fact, decentralization in the health system is a policy pursued for a variety of purposes including; increase in service delivery effectiveness and equity, improving efficiency and quality, fairness of financial contribution and planning for choosing the most appropriate interventions for the health priorities in peripheral regions. To implement decentralized governance, there is a spectrum of different choices that the government should regulate their degrees. Providing an appropriate atmosphere for decentralization is essential, otherwise lack of planning and achievement can result in complications for the system.

Applying Adaptive Swarm Intelligence Technology with Structuration in Web-Based Collaborative Learning

Science.gov (United States)

Huang, Yueh-Min; Liu, Chien-Hung

2009-01-01

One of the key challenges in the promotion of web-based learning is the development of effective collaborative learning environments. We posit that the structuration process strongly influences the effectiveness of technology used in web-based collaborative learning activities. In this paper, we propose an ant swarm collaborative learning (ASCL)…

Centralized vs. de-centralized multinationals and taxes

OpenAIRE

Nielsen, Søren Bo; Raimondos-Møller, Pascalis; Schjelderup, Guttorm

2005-01-01

The paper examines how country tax differences affect a multinational enterprise's choice to centralize or de-centralize its decision structure. Within a simple model that emphasizes the multiple conflicting roles of transfer prices in MNEs – here, as a strategic pre-commitment device and a tax manipulation instrument –, we show that (de-)centralized decisions are more profitable when tax differentials are (small) large. Keywords: Centralized vs. de-centralized decisions, taxes, MNEs. ...

Internet-based Interactive Construction Management Learning System.

Science.gov (United States)

Sawhney, Anil; Mund, Andre; Koczenasz, Jeremy

2001-01-01

Describes a way to incorporate practical content into the construction engineering and management curricula: the Internet-based Interactive Construction Management Learning System, which uses interactive and adaptive learning environments to train students in the areas of construction methods, equipment and processes using multimedia, databases,…

L1-norm locally linear representation regularization multi-source adaptation learning.

Science.gov (United States)

Tao, Jianwen; Wen, Shiting; Hu, Wenjun

2015-09-01

In most supervised domain adaptation learning (DAL) tasks, one has access only to a small number of labeled examples from target domain. Therefore the success of supervised DAL in this "small sample" regime needs the effective utilization of the large amounts of unlabeled data to extract information that is useful for generalization. Toward this end, we here use the geometric intuition of manifold assumption to extend the established frameworks in existing model-based DAL methods for function learning by incorporating additional information about the target geometric structure of the marginal distribution. We would like to ensure that the solution is smooth with respect to both the ambient space and the target marginal distribution. In doing this, we propose a novel L1-norm locally linear representation regularization multi-source adaptation learning framework which exploits the geometry of the probability distribution, which has two techniques. Firstly, an L1-norm locally linear representation method is presented for robust graph construction by replacing the L2-norm reconstruction measure in LLE with L1-norm one, which is termed as L1-LLR for short. Secondly, considering the robust graph regularization, we replace traditional graph Laplacian regularization with our new L1-LLR graph Laplacian regularization and therefore construct new graph-based semi-supervised learning framework with multi-source adaptation constraint, which is coined as L1-MSAL method. Moreover, to deal with the nonlinear learning problem, we also generalize the L1-MSAL method by mapping the input data points from the input space to a high-dimensional reproducing kernel Hilbert space (RKHS) via a nonlinear mapping. Promising experimental results have been obtained on several real-world datasets such as face, visual video and object. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

Sustainability evaluation of decentralized electricity generation

International Nuclear Information System (INIS)

Karger, Cornelia R.; Hennings, Wilfried

2009-01-01

Decentralized power generation is gaining significance in liberalized electricity markets. An increasing decentralization of power supply is expected to make a particular contribution to climate protection. This article investigates the advantages and disadvantages of decentralized electricity generation according to the overall concept of sustainable development. On the basis of a hierarchically structured set of sustainability criteria, four future scenarios for Germany are assessed, all of which describe different concepts of electricity supply in the context of the corresponding social and economic developments. The scenarios are developed in an explorative way according to the scenario method and the sustainability criteria are established by a discursive method with societal actors. The evaluation is carried out by scientific experts. By applying an expanded analytic hierarchy process (AHP), a multicriteria evaluation is conducted that identifies dissent among the experts. The results demonstrate that decentralized electricity generation can contribute to climate protection. The extent to which it simultaneously guarantees security of supply is still a matter of controversy. However, experts agree that technical and economic boundary conditions are of major importance in this field. In the final section, the article discusses the method employed here as well as implications for future decentralized energy supply. (author)

Promoting evaluation capacity building in a complex adaptive system.

Science.gov (United States)

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

2018-04-10

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

RLAM: A Dynamic and Efficient Reinforcement Learning-Based Adaptive Mapping Scheme in Mobile WiMAX Networks

Directory of Open Access Journals (Sweden)

M. Louta

2014-01-01

Full Text Available WiMAX (Worldwide Interoperability for Microwave Access constitutes a candidate networking technology towards the 4G vision realization. By adopting the Orthogonal Frequency Division Multiple Access (OFDMA technique, the latest IEEE 802.16x amendments manage to provide QoS-aware access services with full mobility support. A number of interesting scheduling and mapping schemes have been proposed in research literature. However, they neglect a considerable asset of the OFDMA-based wireless systems: the dynamic adjustment of the downlink-to-uplink width ratio. In order to fully exploit the supported mobile WiMAX features, we design, develop, and evaluate a rigorous adaptive model, which inherits its main aspects from the reinforcement learning field. The model proposed endeavours to efficiently determine the downlink-to-uplinkwidth ratio, on a frame-by-frame basis, taking into account both the downlink and uplink traffic in the Base Station (BS. Extensive evaluation results indicate that the model proposed succeeds in providing quite accurate estimations, keeping the average error rate below 15% with respect to the optimal sub-frame configurations. Additionally, it presents improved performance compared to other learning methods (e.g., learning automata and notable improvements compared to static schemes that maintain a fixed predefined ratio in terms of service ratio and resource utilization.

Decentralized Decision Making Toward Educational Goals.

Science.gov (United States)

Monahan, William W.; Johnson, Homer M.

This monograph provides guidelines to help those school districts considering a more decentralized form of management. The authors discuss the levels at which different types of decisions should be made, describe the changing nature of the educational environment, identify different centralization-decentralization models, and suggest a flexible…

Development of a completely decentralized control system for modular continuous conveyors

OpenAIRE

Mayer, Stephan H.

2009-01-01

To increase the flexibility of application of continuous conveyor systems, a completely decentralized control system for a modular conveyor system is introduced in the paper. This system is able to carry conveyor units without any centralized infrastructure. Based on existing methods of decentralized data transfer in IT networks, single modules operate autonomously and, after being positioned into the required topology, independently connect together to become a functioning conveyor system.

Closed-loop adaptation of neurofeedback based on mental effort facilitates reinforcement learning of brain self-regulation.

Science.gov (United States)

Bauer, Robert; Fels, Meike; Royter, Vladislav; Raco, Valerio; Gharabaghi, Alireza

2016-09-01

Considering self-rated mental effort during neurofeedback may improve training of brain self-regulation. Twenty-one healthy, right-handed subjects performed kinesthetic motor imagery of opening their left hand, while threshold-based classification of beta-band desynchronization resulted in proprioceptive robotic feedback. The experiment consisted of two blocks in a cross-over design. The participants rated their perceived mental effort nine times per block. In the adaptive block, the threshold was adjusted on the basis of these ratings whereas adjustments were carried out at random in the other block. Electroencephalography was used to examine the cortical activation patterns during the training sessions. The perceived mental effort was correlated with the difficulty threshold of neurofeedback training. Adaptive threshold-setting reduced mental effort and increased the classification accuracy and positive predictive value. This was paralleled by an inter-hemispheric cortical activation pattern in low frequency bands connecting the right frontal and left parietal areas. Optimal balance of mental effort was achieved at thresholds significantly higher than maximum classification accuracy. Rating of mental effort is a feasible approach for effective threshold-adaptation during neurofeedback training. Closed-loop adaptation of the neurofeedback difficulty level facilitates reinforcement learning of brain self-regulation. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Decentralized Software Architecture

National Research Council Canada - National Science Library

Khare, Rohit

2002-01-01

.... While the term "decentralization" is familiar from political and economic contexts, it has been applied extensively, if indiscriminately, to describe recent trends in software architecture towards...

Lyapunov-based decentralized control of a rougher flotation phenomenological simulator

International Nuclear Information System (INIS)

Benaskeur, A.R.; Desbiens, A.

1999-01-01

In this paper a new approach to decentralized control of linear two-by-two plants is presented. The novelty lies in the use of a modified control function of Lyapunov and the introduction of an integral action in each manipulated variable, to ensure zero tracking errors. An appropriate choice of the regulated errors, allows the elimination of the cross terms in the obtained backstepping-based multivariable controller. It will be proven that if the H ∞ -norm of the plant interaction quotient is less than one, the centralized controller can be split up into two independent scalar output feedback regulators. Under these conditions, the global stability and zero tracking errors will still be guaranteed. The developed scheme is successfully applied to the control of a rougher flotation phenomenological simulator. (author)

Computing for Decentralized Systems (lecture 1)

CERN Multimedia

CERN. Geneva

2018-01-01

With the rise of Bitcoin, Ethereum, and other cryptocurrencies it is becoming apparent the paradigm shift towards decentralized computing. Computer engineers will need to understand this shift when developing systems in the coming years. Transferring value over the Internet is just one of the first working use cases of decentralized systems, but it is expected they will be used for a number of different services such as general purpose computing, data storage, or even new forms of governance. Decentralized systems, however, pose a series of challenges that cannot be addressed with traditional approaches in computing. Not having a central authority implies truth must be agreed upon rather than simply trusted and, so, consensus protocols, cryptographic data structures like the blockchain, and incentive models like mining rewards become critical for the correct behavior of decentralized system. This series of lectures will be a fast track to introduce these fundamental concepts through working examples and pra...

Computing for Decentralized Systems (lecture 2)

CERN Multimedia

CERN. Geneva

2018-01-01

With the rise of Bitcoin, Ethereum, and other cryptocurrencies it is becoming apparent the paradigm shift towards decentralized computing. Computer engineers will need to understand this shift when developing systems in the coming years. Transferring value over the Internet is just one of the first working use cases of decentralized systems, but it is expected they will be used for a number of different services such as general purpose computing, data storage, or even new forms of governance. Decentralized systems, however, pose a series of challenges that cannot be addressed with traditional approaches in computing. Not having a central authority implies truth must be agreed upon rather than simply trusted and, so, consensus protocols, cryptographic data structures like the blockchain, and incentive models like mining rewards become critical for the correct behavior of decentralized system. This series of lectures will be a fast track to introduce these fundamental concepts through working examples and pra...

A Web-Based Adaptive Tutor to Teach PCR Primer Design

Science.gov (United States)

van Seters, Janneke R.; Wellink, Joan; Tramper, Johannes; Goedhart, Martin J.; Ossevoort, Miriam A.

2012-01-01

When students have varying prior knowledge, personalized instruction is desirable. One way to personalize instruction is by using adaptive e-learning to offer training of varying complexity. In this study, we developed a web-based adaptive tutor to teach PCR primer design: the PCR Tutor. We used part of the Taxonomy of Educational Objectives (the…

Centralized Control/Decentralized Execution: A Valid Tenet of Airpower

National Research Council Canada - National Science Library

Santicola, Henry J

2005-01-01

...) and Effects-Based Operations (EBO). This paper examines the history of the concept of centralized control/decentralized execution from the advent of modern warfare through Operation Enduring Freedom...

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.

Designing monitoring arrangements for collaborative learning about adaptation pathways

NARCIS (Netherlands)

Hermans, L.M.; Haasnoot, M.; ter Maat, Judith; Kwakkel, J.H.

2017-01-01

Adaptation pathways approaches support long-term planning under uncertainty. The use of adaptation pathways implies a systematic monitoring effort to inform future adaptation decisions. Such monitoring should feed into a long-term collaborative learning process between multiple actors at various

Decentralization or centralization: striking a balance.

Science.gov (United States)

Dirschel, K M

1994-09-01

An Executive Vice President for Nursing can provide the necessary link to meet diverse clinical demands when encountering centralization--decentralization decisions. Centralized communication links hospital departments giving nurses a unified voice. Decentralization acknowledges the need for diversity and achieves the right balance of uniformity through a responsive communications network.

PERSO: Towards an Adaptive e-Learning System

Science.gov (United States)

Chorfi, Henda; Jemni, Mohamed

2004-01-01

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

The Influence of Learning Behaviour on Team Adaptability

Science.gov (United States)

Murray, Peter A.; Millett, Bruce

2011-01-01

Multiple contexts shape team activities and how they learn, and group learning is a dynamic construct that reflects a repertoire of potential behaviour. The purpose of this developmental paper is to examine how better learning behaviours in semi-autonomous teams improves the level of team adaptability and performance. The discussion suggests that…

Decentralized Bribery and Market Participation

OpenAIRE

Popov, Sergey V.

2012-01-01

I propose a bribery model that examines decentralized bureaucratic decision-making. There are multiple stable equilibria. High levels of bribery reduce an economy's productivity because corruption suppresses small business, and reduces the total graft, even though the size of an individual bribe might increase. Decentralization prevents movement towards a Pareto-dominant equilibrium. Anticorruption efforts, even temporary ones, might be useful to improve participation, if they lower the bribe...

Decentralized substations for low-temperature district heating with no Legionella risk, and low return temperatures

DEFF Research Database (Denmark)

Yang, Xiaochen; Li, Hongwei; Svendsen, Svend

2016-01-01

. From the results, realizing LTDH by the decentralized substation unit, 30% of the annual distribution heat loss inside the building can be saved compared to a conventional system with medium-temperature district heating. Replacing the bypass pipe with an in-line supply pipe and a heat pump...... with domestic hot water (DHW) circulation. In this study, a system with decentralized substations was analysed as a solution to this problem. Furthermore, a modification for the decentralized substation system were proposed in order to reduce the average return temperature. Models of conventional system...... with medium-temperature district heating, decentralized substation system with LTDH, and innovative decentralized substation system with LTDH were built based on the information of a case building. The annual distribution heat loss and the operating costs of the three scenarios were calculated and compared...

Algebraic and adaptive learning in neural control systems

Science.gov (United States)

Ferrari, Silvia

A systematic approach is developed for designing adaptive and reconfigurable nonlinear control systems that are applicable to plants modeled by ordinary differential equations. The nonlinear controller comprising a network of neural networks is taught using a two-phase learning procedure realized through novel techniques for initialization, on-line training, and adaptive critic design. A critical observation is that the gradients of the functions defined by the neural networks must equal corresponding linear gain matrices at chosen operating points. On-line training is based on a dual heuristic adaptive critic architecture that improves control for large, coupled motions by accounting for actual plant dynamics and nonlinear effects. An action network computes the optimal control law; a critic network predicts the derivative of the cost-to-go with respect to the state. Both networks are algebraically initialized based on prior knowledge of satisfactory pointwise linear controllers and continue to adapt on line during full-scale simulations of the plant. On-line training takes place sequentially over discrete periods of time and involves several numerical procedures. A backpropagating algorithm called Resilient Backpropagation is modified and successfully implemented to meet these objectives, without excessive computational expense. This adaptive controller is as conservative as the linear designs and as effective as a global nonlinear controller. The method is successfully implemented for the full-envelope control of a six-degree-of-freedom aircraft simulation. The results show that the on-line adaptation brings about improved performance with respect to the initialization phase during aircraft maneuvers that involve large-angle and coupled dynamics, and parameter variations.

Query Optimizations over Decentralized RDF Graphs

KAUST Repository

Abdelaziz, Ibrahim

2017-05-18

Applications in life sciences, decentralized social networks, Internet of Things, and statistical linked dataspaces integrate data from multiple decentralized RDF graphs via SPARQL queries. Several approaches have been proposed to optimize query processing over a small number of heterogeneous data sources by utilizing schema information. In the case of schema similarity and interlinks among sources, these approaches cause unnecessary data retrieval and communication, leading to poor scalability and response time. This paper addresses these limitations and presents Lusail, a system for scalable and efficient SPARQL query processing over decentralized graphs. Lusail achieves scalability and low query response time through various optimizations at compile and run times. At compile time, we use a novel locality-aware query decomposition technique that maximizes the number of query triple patterns sent together to a source based on the actual location of the instances satisfying these triple patterns. At run time, we use selectivity-awareness and parallel query execution to reduce network latency and to increase parallelism by delaying the execution of subqueries expected to return large results. We evaluate Lusail using real and synthetic benchmarks, with data sizes up to billions of triples on an in-house cluster and a public cloud. We show that Lusail outperforms state-of-the-art systems by orders of magnitude in terms of scalability and response time.

Decentralization in Zambia: resource allocation and district performance.

Science.gov (United States)

Bossert, Thomas; Chitah, Mukosha Bona; Bowser, Diana

2003-12-01

Zambia implemented an ambitious process of health sector decentralization in the mid 1990s. This article presents an assessment of the degree of decentralization, called 'decision space', that was allowed to districts in Zambia, and an analysis of data on districts available at the national level to assess allocation choices made by local authorities and some indicators of the performance of the health systems under decentralization. The Zambian officials in health districts had a moderate range of choice over expenditures, user fees, contracting, targeting and governance. Their choices were quite limited over salaries and allowances and they did not have control over additional major sources of revenue, like local taxes. The study found that the formula for allocation of government funding which was based on population size and hospital beds resulted in relatively equal per capita expenditures among districts. Decentralization allowed the districts to make decisions on internal allocation of resources and on user fee levels and expenditures. General guidelines for the allocation of resources established a maximum and minimum percentage to be allocated to district offices, hospitals, health centres and communities. Districts tended to exceed the maximum for district offices, but the large urban districts and those without public district hospitals were not even reaching the minimum for hospital allocations. Wealthier and urban districts were more successful in raising revenue through user fees, although the proportion of total expenditures that came from user fees was low. An analysis of available indicators of performance, such as the utilization of health services, immunization coverage and family planning activities, found little variation during the period 1995-98 except for a decline in immunization coverage, which may have also been affected by changes in donor funding. These findings suggest that decentralization may not have had either a positive or

Centralized or decentralized electricity production

International Nuclear Information System (INIS)

Boer, H.A. de.

1975-01-01

Because of low overall efficiency in electric power generation, it is argued that energy provision based on gas, combined with locally decentralized electricity production, saves for the Netherlands slightly more fossile fuel than nuclear technologies and makes the country independent of uranium resources. The reason the Netherlands persues this approach is that a big part of the energy is finally used for heating in the normal or moderate temperatures

Adaptive Tuning of Frequency Thresholds Using Voltage Drop Data in Decentralized Load Shedding

DEFF Research Database (Denmark)

Hoseinzadeh, Bakhtyar; Faria Da Silva, Filipe Miguel; Bak, Claus Leth

2015-01-01

Load shedding (LS) is the last firewall and the most expensive control action against power system blackout. In the conventional under frequency LS (UFLS) schemes, the load drop locations are already determined independently of the event location. Furthermore, the frequency thresholds of LS relays...... are prespecified and constant values which may not be a comprehensive solution for widespread range of possible events. This paper addresses the decentralized LS in which the instantaneous voltage deviation of load buses is used to determine the frequency thresholds of LS relays. The higher frequency thresholds...

A microeconomic analysis of decentralized small scale biomass based CHP plants—The case of Germany

International Nuclear Information System (INIS)

Wittmann, Nadine; Yildiz, Özgür

2013-01-01

Alternative energy sources, such as biomass CHP plants, have recently gained significantly in importance and action is due both on the large scale corporate level and on the small scale. Hence, making the scope and economic outline of such projects easily intelligible without losing relevant details seems a key factor to further promote the necessary developments. The model setup presented in this paper may therefore serve as a starting point for generating numerical results based on real life cases or scenarios. Its focus lies on the economic analysis of decentralized biomass CHP plants. It presents a new approach to analyzing the economic aspects of biomass CHP plants implementing a formal microeconomic approach. As Germany claims a leading role in the market for renewable energy production, the paper also takes a closer look on the effects of German energy policy with respect to biomass CHP plants. - Highlights: • A formal microeconomic model is used to analyse a decentralized biomass CHP plant. • Model setup is used to generate numerical results based on real life scenarios. • Nested CES production function is a new approach to model economics of biomass CHP. • Analysis presents insight into microeconomics and cost drivers of biomass CHP. • Evaluation of energy policy design with respect to environmental policy goals

Neural network-based model reference adaptive control system.

Science.gov (United States)

Patino, H D; Liu, D

2000-01-01

In this paper, an approach to model reference adaptive control based on neural networks is proposed and analyzed for a class of first-order continuous-time nonlinear dynamical systems. The controller structure can employ either a radial basis function network or a feedforward neural network to compensate adaptively the nonlinearities in the plant. A stable controller-parameter adjustment mechanism, which is determined using the Lyapunov theory, is constructed using a sigma-modification-type updating law. The evaluation of control error in terms of the neural network learning error is performed. That is, the control error converges asymptotically to a neighborhood of zero, whose size is evaluated and depends on the approximation error of the neural network. In the design and analysis of neural network-based control systems, it is important to take into account the neural network learning error and its influence on the control error of the plant. Simulation results showing the feasibility and performance of the proposed approach are given.

Different Futures of Adaptive Collaborative Learning Support

Science.gov (United States)

Rummel, Nikol; Walker, Erin; Aleven, Vincent

2016-01-01

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

Web-Based Learning Support System

Science.gov (United States)

Fan, Lisa

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

Decentralized manufacturing of cell and gene therapies: Overcoming challenges and identifying opportunities.

Science.gov (United States)

Harrison, Richard P; Ruck, Steven; Medcalf, Nicholas; Rafiq, Qasim A

2017-10-01

Decentralized or "redistributed" manufacturing has the potential to revolutionize the manufacturing approach for cell and gene therapies (CGTs), moving away from the "Fordist" paradigm, delivering health care locally, customized to the end user and, by its very nature, overcoming many of the challenges associated with manufacturing and distribution of high volume goods. In departing from the traditional centralized model of manufacturing, decentralized manufacturing divides production across sites or geographic regions. This paradigm shift imposes significant structural and organisational changes on a business presenting both hidden challenges that must be addressed and opportunities to be embraced. By profoundly adapting business practices, significant advantages can be realized through a democratized value chain, creation of professional-level jobs without geographic restriction to the central hub and a flexibility in response to external pressures and demands. To realize these potential opportunities, however, advances in manufacturing technology and support systems are required, as well as significant changes in the way CGTs are regulated to facilitate multi-site manufacturing. Decentralized manufacturing is likely to be the manufacturing platform of choice for advanced health care therapies-in particular, those with a high degree of personalization. The future success of these promising products will be enhanced by adopting sound business strategies early in development. To realize the benefits that decentralized manufacturing of CGTs has to offer, it is important to examine both the risks and the substantial opportunities present. In this research, we examine both the challenges and the opportunities this shift in business strategy represents in an effort to maximize the success of adoption. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Coordinating a multi-retailer decentralized distribution system with random demand based on buyback and compensation contracts

Directory of Open Access Journals (Sweden)

Jinyu Ren

2015-01-01

Full Text Available Purpose: The purpose of this paper is to set up the coordinating mechanism for a decentralized distribution system consisting of a manufacturer and multiple independent retailers by means of contracts. It is in the two-stage supply chain system that all retailers sell an identical product made by the manufacturer and determine their order quantities which directly affect the expected profit of the supply chain with random demand. Design/methodology/approach: First comparison of the optimal order quantities in the centralized and decentralized system shows that the supply chain needs coordination. Then the coordination model is given based on buyback cost and compensation benefit. Finally the coordination mechanism is set up in which the manufacturer as the leader uses a buyback policy to incentive these retailers and the retailers pay profit returns to compensate the manufacturer. Findings: The results of a numerical example show that the perfect supply chain coordination and the flexible allocation of the profit can be achieved in the multi-retailer supply chain by the buyback and compensation contracts. Research limitations: The results based on assumptions might not completely hold in practice and the paper only focuses on studying a single product in two-stage supply chain. Practical implications: The coordination mechanism is applicable to a realistic supply chain under a private information setting and the research results is the foundation of further developing the coordination mechanism for a realistic multi-stage supply chain system with more products. Originality/value: This paper focused on studying the coordination mechanism for a decentralized multi-retailer supply chain by the joint application of the buyback and compensation contracts. Furthermore the perfect supply chain coordination and the flexible allocation of the profit are achieved.

Decentralized Consistency Checking in Cross-organizational Workflows

NARCIS (Netherlands)

Wombacher, Andreas

Service Oriented Architectures facilitate loosely coupled composed services, which are established in a decentralized way. One challenge for such composed services is to guarantee consistency, i.e., deadlock-freeness. This paper presents a decentralized approach to consistency checking, which

Decentralization and Participatory Rural Development: A Literature Review

Directory of Open Access Journals (Sweden)

Muhammad Shakil Ahmad

2011-12-01

Full Text Available Most of the developing nations are still struggling for efficient use of their resources. In order to overcome physical and administrative constraints of the development, it is necessary to transfer the power from the central government to local authorities. Distribution of power from improves the management of resources and community participation which is considered key to sustainable development. Advocates of decentralization argue that decentralized government is source to improve community participation in rural development. Decentralized government is considered more responsive towards local needs and development of poor peoples. There are many obstacles to expand the citizen participation in rural areas. There are many approaches for participatory development but all have to face the same challenges. Current paper highlights the literature about Decentralization and participatory rural development. Concept and modalities of Decentralization, dimensions of participation, types of rural participation and obstacles to participation are also the part of this paper.

Trends in research on forestry decentralization policies

DEFF Research Database (Denmark)

Lund, Jens Friis; Rutt, Rebecca Leigh; Ribot, Jesse

2018-01-01

institutions; studies focusing on power and the role of elites in forestry decentralization, and; studies that historicize and contextualize forestry decentralization as reflective of broader societal phenomena. We argue that these strands reflect disciplinary differences in values, epistemologies, and methods...

Comparison of centralized and decentralized energy supply systems

OpenAIRE

Pfeifer, Thomas; Fahl, Ulrich; Voß, Alfred

1991-01-01

Communal energy programs are often embedded in a conception of a decentralized energy supply system where electricity is produced by a number of smaller power plants. For a comprehensive survey the question arises whether these decentralized systems are more advantageous than centralized systems with regard to the criterions energy consumption, safety of supply, environmental compatibility and economy. In the following, after a definition of the term "decentralized", the present structure of ...

Decentralized Control of Autonomous Vehicles

Science.gov (United States)

2003-01-01

Autonomous Vehicles by John S. Baras, Xiaobo Tan, Pedram Hovareshti CSHCN TR 2003-8 (ISR TR 2003-14) Report Documentation Page Form ApprovedOMB No. 0704...AND SUBTITLE Decentralized Control of Autonomous Vehicles 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT...Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 Decentralized Control of Autonomous Vehicles ∗ John S. Baras, Xiaobo Tan, and Pedram

BROA: An agent-based model to recommend relevant Learning Objects from Repository Federations adapted to learner profile

Directory of Open Access Journals (Sweden)

Paula A. Rodríguez

2013-03-01

Full Text Available Learning Objects (LOs are distinguished from traditional educational resources for their easy and quickly availability through Web-based repositories, from which they are accessed through their metadata. In addition, having a user profile allows an educational recommender system to help the learner to find the most relevant LOs based on their needs and preferences. The aim of this paper is to propose an agent-based model so-called BROA to recommend relevant LOs recovered from Repository Federations as well as LOs adapted to learner profile. The model proposed uses both role and service models of GAIA methodology, and the analysis models of the MAS-CommonKADS methodology. A prototype was built based on this model and validated to obtain some assessing results that are finally presented.

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

Directory of Open Access Journals (Sweden)

Lun-Hui Xu

2013-01-01

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

Robust Decentralized Formation Flight Control

Directory of Open Access Journals (Sweden)

Zhao Weihua

2011-01-01

Full Text Available Motivated by the idea of multiplexed model predictive control (MMPC, this paper introduces a new framework for unmanned aerial vehicles (UAVs formation flight and coordination. Formulated using MMPC approach, the whole centralized formation flight system is considered as a linear periodic system with control inputs of each UAV subsystem as its periodic inputs. Divided into decentralized subsystems, the whole formation flight system is guaranteed stable if proper terminal cost and terminal constraints are added to each decentralized MPC formulation of the UAV subsystem. The decentralized robust MPC formulation for each UAV subsystem with bounded input disturbances and model uncertainties is also presented. Furthermore, an obstacle avoidance control scheme for any shape and size of obstacles, including the nonapriorily known ones, is integrated under the unified MPC framework. The results from simulations demonstrate that the proposed framework can successfully achieve robust collision-free formation flights.

Adaptive Management and Social Learning in Collaborative and Community-Based Monitoring: a Study of Five Community-Based Forestry Organizations in the western USA

Directory of Open Access Journals (Sweden)

Maria E. Fernandez-Gimenez

2008-12-01

Full Text Available Collaborative and community-based monitoring are becoming more frequent, yet few studies have examined the process and outcomes of these monitoring approaches. We studied 18 collaborative or community-based ecological assessment or monitoring projects undertaken by five community-based forestry organizations (CBFs, to investigate the objectives, process, and outcomes of collaborative ecological monitoring by CBF organizations. We found that collaborative monitoring can lead to shared ecological understanding among diverse participants, build trust internally and credibility externally, foster social learning and community-building, and advance adaptive management. The CBFs experienced challenges in recruiting and sustaining community participation in monitoring, building needed technical capacity for monitoring, and communicating monitoring results back to the broader community. Our results suggest that involving diverse and sometimes adversarial interests at key points in the monitoring process can help resolve conflicts and advance social learning, while also strengthening the link between social and ecological systems by improving the information base for management and increasing collective awareness of the interdependence of human and natural forest communities.

Conformal prediction for reliable machine learning theory, adaptations and applications

CERN Document Server

Balasubramanian, Vineeth; Vovk, Vladimir

2014-01-01

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

Decentralization: Another Perspective

Science.gov (United States)

Chapman, Robin

1973-01-01

This paper attempts to pursue the centralization-decentralization dilemma. A setting for this discussion is provided by noting some of the uses of terminology, followed by a consideration of inherent difficulties in conceptualizing. (Author)

Enhancing Adaptive Capacity in Food Systems: Learning at Farmers' Markets in Sweden

Directory of Open Access Journals (Sweden)

Rebecka Milestad

2010-09-01

Full Text Available This article examines how local food systems in the form of farmers' markets can enhance adaptive capacity and build social-ecological resilience. It does this by exploring the learning potential among farmers and customers. Learning can enable actors to adapt successfully and thus build adaptive capacity. Three forms of learning are investigated: instrumental, communicative, and emancipatory. These forms of learning constitute the foundation for lasting changes of behaviors. Local food systems are characterized by close links and opportunities for face-to-face interactions between consumers and producers of food, and are also institutions where farmers and customers can express and act upon their ethical values concerning food. However, local food systems are still a marginal phenomenon and cannot be accessed by all consumers. Interviews were held with customers and farmers, and the interactions between farmers and customers were observed at two farmers' markets in Sweden. Customers and farmers were found to learn and adapt to each other due to the opportunities offered by the farmers' markets. We found that farmers and customers learned in the instrumental and communicative domains, but could not confirm emancipatory learning. We concluded that the feedback between customers and farmers offers the potential for learning, which in turn contributes to adaptive capacity. This can be a driving force for building resilience in the food system.

Decentralized central heating

Energy Technology Data Exchange (ETDEWEB)

Savic, S.; Hudjera, A.

1994-08-04

The decentralized central heating is essentially based on new technical solutions for an independent heating unit, which allows up to 20% collectible energy savings and up to 15% savings in built-in-material. These savings are already made possible by the fact that the elements described under point A are thus eliminated from the classical heating. The thus superfluous made elements are replaced by new technical solutions described under point B - technical problem - and point E - patent claim. The technical solutions described in detail under point B and point E form together a technical unit and are essential parts of the invention protected by the patent. (author)

Negotiating Service Learning through Community Engagement: Adaptive Leadership, Knowledge, Dialogue and Power

Science.gov (United States)

Preece, Julia

2016-01-01

This article builds on two recent publications (Preece 2013; 2013a) concerning the application of asset-based community development and adaptive leadership theories when negotiating university service learning placements with community organisations in one South African province. The first publication introduced the concept of 'adaptive…

Patient Experiences of Decentralized HIV Treatment and Care in Plateau State, North Central Nigeria: A Qualitative Study

Directory of Open Access Journals (Sweden)

Grace O. Kolawole

2017-01-01

Full Text Available Background. Decentralization of care and treatment for HIV infection in Africa makes services available in local health facilities. Decentralization has been associated with improved retention and comparable or superior treatment outcomes, but patient experiences are not well understood. Methods. We conducted a qualitative study of patient experiences in decentralized HIV care in Plateau State, north central Nigeria. Five decentralized care sites in the Plateau State Decentralization Initiative were purposefully selected. Ninety-three patients and 16 providers at these sites participated in individual interviews and focus groups. Data collection activities were audio-recorded and transcribed. Transcripts were inductively content analyzed to derive descriptive categories representing patient experiences of decentralized care. Results. Patient participants in this study experienced the transition to decentralized care as a series of “trade-offs.” Advantages cited included saving time and money on travel to clinic visits, avoiding dangers on the road, and the “family-like atmosphere” found in some decentralized clinics. Disadvantages were loss of access to ancillary services, reduced opportunities for interaction with providers, and increased risk of disclosure. Participants preferred decentralized services overall. Conclusion. Difficulty and cost of travel remain a fundamental barrier to accessing HIV care outside urban centers, suggesting increased availability of community-based services will be enthusiastically received.

Distribution of decentralized renewable energy resources

International Nuclear Information System (INIS)

Bal, J.L.; Benque, J.P.

1996-01-01

The existence of a great number of inhabitants without electricity, living in areas of low population density, with modest energy requirements and low income provides a major potential market for decentralized renewable energy sources. Ademe and EDF in 1993 made two agreements concerning the development of Renewable Energy Sources. The first aims at promoting their decentralized use in France in pertinent cases. The second agreement concerns other countries and has two ambitions: facilitate short-term developments and produce in the longer term a standardised proposal for decentralized energy production using Renewable Energy Sources to a considerable extent. These ideas are explained, and the principles behind the implementation of both Ademe-EDF agreements as well as their future prospects are described. (R.P.)

Towards Automatic Decentralized Control Structure Selection

DEFF Research Database (Denmark)

for decentralized control is determined automatically, and the resulting decentralized control structure is automatically tuned using standard techniques. Dynamic simulation of the resulting process system gives immediate feedback to the process design engineer regarding practical operability of the process......A subtask in integration of design and control of chemical processes is the selection of a control structure. Automating the selection of the control structure enables sequential integration of process and controld esign. As soon as the process is specified or computed, a structure....... The control structure selection problem is formulated as a special MILP employing cost coefficients which are computed using Parseval's theorem combined with RGA and IMC concepts. This approach enables selection and tuning of large-scale plant-wide decentralized controllers through efficient combination...

Towards Automatic Decentralized Control Structure Selection

DEFF Research Database (Denmark)

Jørgensen, John Bagterp; Jørgensen, Sten Bay

2000-01-01

for decentralized control is determined automatically, and the resulting decentralized control structure is automatically tuned using standard techniques. Dynamic simulation of the resulting process system gives immediate feedback to the process design engineer regarding practical operability of the process......A subtask in integration of design and control of chemical processes is the selection of a control structure. Automating the selection of the control structure enables sequential integration of process and control design. As soon as the process is specified or computed, a structure....... The control structure selection problem is formulated as a special MILP employing cost coefficients which are computed using Parseval's theorem combined with RGA and IMC concepts. This approach enables selection and tuning of large-scale plant-wide decentralized controllers through efficient combination...

Decentral Smart Grid Control

Science.gov (United States)

Schäfer, Benjamin; Matthiae, Moritz; Timme, Marc; Witthaut, Dirk

2015-01-01

Stable operation of complex flow and transportation networks requires balanced supply and demand. For the operation of electric power grids—due to their increasing fraction of renewable energy sources—a pressing challenge is to fit the fluctuations in decentralized supply to the distributed and temporally varying demands. To achieve this goal, common smart grid concepts suggest to collect consumer demand data, centrally evaluate them given current supply and send price information back to customers for them to decide about usage. Besides restrictions regarding cyber security, privacy protection and large required investments, it remains unclear how such central smart grid options guarantee overall stability. Here we propose a Decentral Smart Grid Control, where the price is directly linked to the local grid frequency at each customer. The grid frequency provides all necessary information about the current power balance such that it is sufficient to match supply and demand without the need for a centralized IT infrastructure. We analyze the performance and the dynamical stability of the power grid with such a control system. Our results suggest that the proposed Decentral Smart Grid Control is feasible independent of effective measurement delays, if frequencies are averaged over sufficiently large time intervals.

Decentral Smart Grid Control

International Nuclear Information System (INIS)

Schäfer, Benjamin; Matthiae, Moritz; Timme, Marc; Witthaut, Dirk

2015-01-01

Stable operation of complex flow and transportation networks requires balanced supply and demand. For the operation of electric power grids—due to their increasing fraction of renewable energy sources—a pressing challenge is to fit the fluctuations in decentralized supply to the distributed and temporally varying demands. To achieve this goal, common smart grid concepts suggest to collect consumer demand data, centrally evaluate them given current supply and send price information back to customers for them to decide about usage. Besides restrictions regarding cyber security, privacy protection and large required investments, it remains unclear how such central smart grid options guarantee overall stability. Here we propose a Decentral Smart Grid Control, where the price is directly linked to the local grid frequency at each customer. The grid frequency provides all necessary information about the current power balance such that it is sufficient to match supply and demand without the need for a centralized IT infrastructure. We analyze the performance and the dynamical stability of the power grid with such a control system. Our results suggest that the proposed Decentral Smart Grid Control is feasible independent of effective measurement delays, if frequencies are averaged over sufficiently large time intervals. (paper)

Policy Recommendations on Decentralization, Local Power and ...

International Development Research Centre (IDRC) Digital Library (Canada)

2010-12-22

Policy Recommendations on Decentralization, Local Power and Women's Rights. December 22, 2010. Image. The present document comprises a set of policy recommendations that define a global agenda on gender and decentralization. It emerged from the analysis and experiences shared during the Conference and the ...

Rethinking Decentralization in Education in terms of Administrative Problems

Directory of Open Access Journals (Sweden)

Vasiliki Papadopoulou

2013-11-01

Full Text Available The general purpose of this study is to thoroughly examine decentralization in education according to the literature and previous research, and to discuss the applicability of educational decentralization practices in Turkey. The literature was reviewed for the study and findings reported. It has been observed that decentralization in education practices were realized in many countries after the 1980’s. It is obvious that the educational system in Turkey has difficulty in meeting the needs, and encounters many problems due to its present centralist state. Educational decentralization can provide effective solutions for stakeholder engagement, educational financing and for problems in decision making and operation within the education system. However, the present state of local governments, the legal framework, geographical, cultural and social features indicate that Turkey’s conditions are not ready for decentralization in education. A decentralization model realized in the long run according to Turkey’s conditions, and as a result of a social consensus, can help resolve the problems of the Turkish education system.

Decentralized substations for low-temperature district heating with no Legionella risk, and low return temperatures

International Nuclear Information System (INIS)

Yang, Xiaochen; Li, Hongwei; Svendsen, Svend

2016-01-01

To improve energy efficiency and give more access to renewable energy sources, low-temperature district heating (LTDH) is a promising concept to be realized in the future. However, concern about Legionella proliferation restricts applying low-temperature district heating in conventional systems with domestic hot water (DHW) circulation. In this study, a system with decentralized substations was analysed as a solution to this problem. Furthermore, a modification for the decentralized substation system were proposed in order to reduce the average return temperature. Models of conventional system with medium-temperature district heating, decentralized substation system with LTDH, and innovative decentralized substation system with LTDH were built based on the information of a case building. The annual distribution heat loss and the operating costs of the three scenarios were calculated and compared. From the results, realizing LTDH by the decentralized substation unit, 30% of the annual distribution heat loss inside the building can be saved compared to a conventional system with medium-temperature district heating. Replacing the bypass pipe with an in-line supply pipe and a heat pump, the innovative decentralized substation system can reduce distribution heat loss by 39% compared to the conventional system and by 12% compared to the normal decentralized substation system with bypass. - Highlights: • The system of decentralized substations can realize low-temperature district heating without running the risk of Legionella. • Decentralized substations help reduce the distribution heat loss inside the building compared to conventional system. • A new concept that can reduce the return temperature for district heating is proposed and analysed.

Knowledge-light adaptation approaches in case-based reasoning for radiotherapy treatment planning.

Science.gov (United States)

Petrovic, Sanja; Khussainova, Gulmira; Jagannathan, Rupa

2016-03-01

Radiotherapy treatment planning aims at delivering a sufficient radiation dose to cancerous tumour cells while sparing healthy organs in the tumour-surrounding area. It is a time-consuming trial-and-error process that requires the expertise of a group of medical experts including oncologists and medical physicists and can take from 2 to 3h to a few days. Our objective is to improve the performance of our previously built case-based reasoning (CBR) system for brain tumour radiotherapy treatment planning. In this system, a treatment plan for a new patient is retrieved from a case base containing patient cases treated in the past and their treatment plans. However, this system does not perform any adaptation, which is needed to account for any difference between the new and retrieved cases. Generally, the adaptation phase is considered to be intrinsically knowledge-intensive and domain-dependent. Therefore, an adaptation often requires a large amount of domain-specific knowledge, which can be difficult to acquire and often is not readily available. In this study, we investigate approaches to adaptation that do not require much domain knowledge, referred to as knowledge-light adaptation. We developed two adaptation approaches: adaptation based on machine-learning tools and adaptation-guided retrieval. They were used to adapt the beam number and beam angles suggested in the retrieved case. Two machine-learning tools, neural networks and naive Bayes classifier, were used in the adaptation to learn how the difference in attribute values between the retrieved and new cases affects the output of these two cases. The adaptation-guided retrieval takes into consideration not only the similarity between the new and retrieved cases, but also how to adapt the retrieved case. The research was carried out in collaboration with medical physicists at the Nottingham University Hospitals NHS Trust, City Hospital Campus, UK. All experiments were performed using real-world brain cancer

Adaptive Learning in Weighted Network Games

NARCIS (Netherlands)

Bayer, Péter; Herings, P. Jean-Jacques; Peeters, Ronald; Thuijsman, Frank

2017-01-01

This paper studies adaptive learning in the class of weighted network games. This class of games includes applications like research and development within interlinked firms, crime within social networks, the economics of pollution, and defense expenditures within allied nations. We show that for

Intelligent Adaptation and Personalization Techniques in Computer-Supported Collaborative Learning

CERN Document Server

Demetriadis, Stavros; Xhafa, Fatos

2012-01-01

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

Energy and air emission implications of a decentralized wastewater system

International Nuclear Information System (INIS)

Shehabi, Arman; Stokes, Jennifer R; Horvath, Arpad

2012-01-01

Both centralized and decentralized wastewater systems have distinct engineering, financial and societal benefits. This paper presents a framework for analyzing the environmental effects of decentralized wastewater systems and an evaluation of the environmental impacts associated with two currently operating systems in California, one centralized and one decentralized. A comparison of energy use, greenhouse gas emissions and criteria air pollutants from the systems shows that the scale economies of the centralized plant help lower the environmental burden to less than a fifth of that of the decentralized utility for the same volume treated. The energy and emission burdens of the decentralized plant are reduced when accounting for high-yield wastewater reuse if it supplants an energy-intensive water supply like a desalination one. The centralized facility also reduces greenhouse gases by flaring methane generated during the treatment process, while methane is directly emitted from the decentralized system. The results are compelling enough to indicate that the life-cycle environmental impacts of decentralized designs should be carefully evaluated as part of the design process. (letter)

Community Development in the context of the power decentralization in Ukraine

Directory of Open Access Journals (Sweden)

V. P. Berezinskiy

2017-03-01

Full Text Available The aim of the study is to define opportunities of development of the community in the implementation of the power decentralization reform in Ukraine. It has been shown that the principle of decentralization provides for territorial and political unity of the state by a legal delimitation of powers between central government agencies and regional public authorities (or local authorities. It makes it clear that the issue of power decentralization in Ukraine has a constitutional and legal framework, as the Main Law states that the power system is based on a combination of centralization and decentralization. The requirement of power decentralization has been constitutionally justified. It has been revealed that according to the State Regional Development Strategy, the following priorities of the state regional policy are: increase of the competitiveness of regions; territorial socio-economic integration and spatial development; effective governance in regional development. It has been disclosed that in Ukraine the deepening of the decentralization is aimed at the strengthening of the role of local self-government, empowerment of the representative authorities of local communities to get more authority for managing local affairs, deprivation of local power authorities for the preparation and fulfilment of budgets in regions, the transfer of significant powers and financial resources from government to local self-governmental authorities. It has been proved that decentralization contributes to the democratization of the local government and the development of local community as the ultimate goals of the reform of the power decentralization are the creation and maintenance of good living environment for citizens. This reform should correspond to interests of citizens in all spheres of life, and it must support on the relevant territory. In this regard, series of legislative acts were adopted («On a voluntary association of local communities», �

Adaptive Learning in Medical Education: The Final Piece of Technology Enhanced Learning?

Science.gov (United States)

Sharma, Neel; Doherty, Iain; Dong, Chaoyan

2017-09-01

Technology enhanced learning (TEL) is now common practice in the field of medical education. One of the primary examples of its use is that of high fidelity simulation and computerised mannequins. Further examples include online learning modules, electronic portfolios, virtual patient interactions, massive open online courses and the flipped classroom movement. The rise of TEL has occurred primarily due to the ease of internet access enabling the retrieval and sharing of information in an instant. Furthermore, the compact nature of internet ready devices such as smartphones and laptops has meant that access to information can occur anytime and anywhere. From an educational perspective however, the current utilisation of TEL has been hindered by its lack of understanding of learners' needs. This is concerning, particularly as evidence highlights that during medical training, each individual learner has their own learning requirements and often achieves competency at different rates. In view of this, there has been interest in ensuring TEL is more learner aware and that the learning process should be more personalised. Adaptive learning can aim to achieve this by ensuring content is delivered according to the needs of the learner. This commentary highlights the move towards adaptive learning and the benefits of such an intervention.

Adaptive capacity and community-based natural resource management.

Science.gov (United States)

Armitage, Derek

2005-06-01

Why do some community-based natural resource management strategies perform better than others? Commons theorists have approached this question by developing institutional design principles to address collective choice situations, while other analysts have critiqued the underlying assumptions of community-based resource management. However, efforts to enhance community-based natural resource management performance also require an analysis of exogenous and endogenous variables that influence how social actors not only act collectively but do so in ways that respond to changing circumstances, foster learning, and build capacity for management adaptation. Drawing on examples from northern Canada and Southeast Asia, this article examines the relationship among adaptive capacity, community-based resource management performance, and the socio-institutional determinants of collective action, such as technical, financial, and legal constraints, and complex issues of politics, scale, knowledge, community and culture. An emphasis on adaptive capacity responds to a conceptual weakness in community-based natural resource management and highlights an emerging research and policy discourse that builds upon static design principles and the contested concepts in current management practice.

Decentralization in Botswana: the reluctant process | Dipholo ...

African Journals Online (AJOL)

Botswana\\'s decentralization process has always been justified in terms of democracy and development. Consequently, the government has always argued that it is fully committed to decentralization in order to promote popular participation as well as facilitating sustainable rural development. Yet the government does not ...

Learning to bridge the gap between adaptive management and organisational culture

Directory of Open Access Journals (Sweden)

Richard J. Stirzaker

2011-05-01

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

Decentralizing conservation and diversifying livelihoods within Kanchenjunga Conservation Area, Nepal.

Science.gov (United States)

Parker, Pete; Thapa, Brijesh; Jacob, Aerin

2015-12-01

To alleviate poverty and enhance conservation in resource dependent communities, managers must identify existing livelihood strategies and the associated factors that impede household access to livelihood assets. Researchers increasingly advocate reallocating management power from exclusionary central institutions to a decentralized system of management based on local and inclusive participation. However, it is yet to be shown if decentralizing conservation leads to diversified livelihoods within a protected area. The purpose of this study was to identify and assess factors affecting household livelihood diversification within Nepal's Kanchenjunga Conservation Area Project, the first protected area in Asia to decentralize conservation. We randomly surveyed 25% of Kanchenjunga households to assess household socioeconomic and demographic characteristics and access to livelihood assets. We used a cluster analysis with the ten most common income generating activities (both on- and off-farm) to group the strategies households use to diversify livelihoods, and a multinomial logistic regression to identify predictors of livelihood diversification. We found four distinct groups of household livelihood strategies with a range of diversification that directly corresponded to household income. The predictors of livelihood diversification were more related to pre-existing socioeconomic and demographic factors (e.g., more landholdings and livestock, fewer dependents, receiving remittances) than activities sponsored by decentralizing conservation (e.g., microcredit, training, education, interaction with project staff). Taken together, our findings indicate that without direct policies to target marginalized groups, decentralized conservation in Kanchenjunga will continue to exclude marginalized groups, limiting a household's ability to diversify their livelihood and perpetuating their dependence on natural resources. Copyright © 2015 Elsevier Ltd. All rights reserved.

The effects of fiscal decentralization in Albania

Directory of Open Access Journals (Sweden)

Dr.Sc. Blerta Dragusha

2012-06-01

Full Text Available “Basically decentralization is a democratic reform which seeks to transfer the political, administrative, financial and planning authority from central to local government. It seeks to develop civic participation, empowerment of local people in decision making process and to promote accountability and reliability: To achieve efficiency and effectiveness in the collection and management of resources and service delivery”1 The interest and curiosity of knowing how our country is doing in this process, still unfinished, served as a motivation forme to treat this topic: fiscal decentralization as a process of giving 'power' to local governments, not only in terms of rights deriving from this process but also on the responsibilities that come with it. Which are the stages before and after decentralization, and how has it affected the process in several key indicators? Is decentralization a good process only, or can any of its effects be seen as an disadvantage?

Adaptive Control Using Fully Online Sequential-Extreme Learning Machine and a Case Study on Engine Air-Fuel Ratio Regulation

Directory of Open Access Journals (Sweden)

Pak Kin Wong

2014-01-01

Full Text Available Most adaptive neural control schemes are based on stochastic gradient-descent backpropagation (SGBP, which suffers from local minima problem. Although the recently proposed regularized online sequential-extreme learning machine (ReOS-ELM can overcome this issue, it requires a batch of representative initial training data to construct a base model before online learning. The initial data is usually difficult to collect in adaptive control applications. Therefore, this paper proposes an improved version of ReOS-ELM, entitled fully online sequential-extreme learning machine (FOS-ELM. While retaining the advantages of ReOS-ELM, FOS-ELM discards the initial training phase, and hence becomes suitable for adaptive control applications. To demonstrate its effectiveness, FOS-ELM was applied to the adaptive control of engine air-fuel ratio based on a simulated engine model. Besides, controller parameters were also analyzed, in which it is found that large hidden node number with small regularization parameter leads to the best performance. A comparison among FOS-ELM and SGBP was also conducted. The result indicates that FOS-ELM achieves better tracking and convergence performance than SGBP, since FOS-ELM tends to learn the unknown engine model globally whereas SGBP tends to “forget” what it has learnt. This implies that FOS-ELM is more preferable for adaptive control applications.

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

OpenAIRE

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

2015-01-01

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

Adaptive critic learning techniques for engine torque and air-fuel ratio control.

Science.gov (United States)

Liu, Derong; Javaherian, Hossein; Kovalenko, Olesia; Huang, Ting

2008-08-01

A new approach for engine calibration and control is proposed. In this paper, we present our research results on the implementation of adaptive critic designs for self-learning control of automotive engines. A class of adaptive critic designs that can be classified as (model-free) action-dependent heuristic dynamic programming is used in this research project. The goals of the present learning control design for automotive engines include improved performance, reduced emissions, and maintained optimum performance under various operating conditions. Using the data from a test vehicle with a V8 engine, we developed a neural network model of the engine and neural network controllers based on the idea of approximate dynamic programming to achieve optimal control. We have developed and simulated self-learning neural network controllers for both engine torque (TRQ) and exhaust air-fuel ratio (AFR) control. The goal of TRQ control and AFR control is to track the commanded values. For both control problems, excellent neural network controller transient performance has been achieved.

Decentralization's impact on the health workforce: Perspectives of managers, workers and national leaders

Directory of Open Access Journals (Sweden)

Kolehmainen-Aitken Riitta-Liisa

2004-05-01

Full Text Available Abstract Designers and implementers of decentralization and other reform measures have focused much attention on financial and structural reform measures, but ignored their human resource implications. Concern is mounting about the impact that the reallocation of roles and responsibilities has had on the health workforce and its management, but the experiences and lessons of different countries have not been widely shared. This paper examines evidence from published literature on decentralization's impact on the demand side of the human resource equation, as well as the factors that have contributed to the impact. The elements that make such an impact analysis exceptionally complex are identified. They include the mode of decentralization that a country is implementing, the level of responsibility for the salary budget and pay determination, and the civil service status of transferred health workers. The main body of the paper is devoted to examining decentralization's impact on human resource issues from three different perspectives: that of local health managers, health workers themselves, and national health leaders. These three groups have different concerns in the human resource realm, and consequently, have been differently affected by decentralization processes. The paper concludes with recommendations regarding three key concerns that national authorities and international agencies should give prompt attention to. They are (1 defining the essential human resource policy, planning and management skills for national human resource managers who work in decentralized countries, and developing training programs to equip them with such skills; (2 supporting research that focuses on improving the knowledge base of how different modes of decentralization impact on staffing equity; and (3 identifying factors that most critically influence health worker motivation and performance under decentralization, and documenting the most cost-effective best

Decentralization's impact on the health workforce: Perspectives of managers, workers and national leaders.

Science.gov (United States)

Kolehmainen-Aitken, Riitta-Liisa

2004-05-14

Designers and implementers of decentralization and other reform measures have focused much attention on financial and structural reform measures, but ignored their human resource implications. Concern is mounting about the impact that the reallocation of roles and responsibilities has had on the health workforce and its management, but the experiences and lessons of different countries have not been widely shared. This paper examines evidence from published literature on decentralization's impact on the demand side of the human resource equation, as well as the factors that have contributed to the impact. The elements that make such an impact analysis exceptionally complex are identified. They include the mode of decentralization that a country is implementing, the level of responsibility for the salary budget and pay determination, and the civil service status of transferred health workers.The main body of the paper is devoted to examining decentralization's impact on human resource issues from three different perspectives: that of local health managers, health workers themselves, and national health leaders. These three groups have different concerns in the human resource realm, and consequently, have been differently affected by decentralization processes. The paper concludes with recommendations regarding three key concerns that national authorities and international agencies should give prompt attention to. They are (1) defining the essential human resource policy, planning and management skills for national human resource managers who work in decentralized countries, and developing training programs to equip them with such skills; (2) supporting research that focuses on improving the knowledge base of how different modes of decentralization impact on staffing equity; and (3) identifying factors that most critically influence health worker motivation and performance under decentralization, and documenting the most cost-effective best practices to improve them

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

Directory of Open Access Journals (Sweden)

Iain Davidson-Hunt

2003-12-01

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

Effects of aging on strategic-based visuomotor learning.

Science.gov (United States)

Alfonso Uresti-Cabrera, Luis; Vaca-Palomares, Israel; Diaz, Rosalinda; Beltran-Parrazal, Luis; Fernandez-Ruiz, Juan

2015-08-27

There are different kinds of visuomotor learnings. One of the most studied is error-based learning where the information about the sign and magnitude of the error is used to update the motor commands. However, there are other instances where subjects show visuomotor learning even if the use of error sign and magnitude information is precluded. In those instances subjects could be using strategic instead of procedural adaptation mechanisms. Here, we present the results of the effect of aging on visuomotor strategic learning under a reversed error feedback condition, and its contrast with procedural visuomotor learning within the same participants. A number of measures were obtained from a task consisting of throwing clay balls to a target before, during and after wearing lateral displacing or reversing prisms. The displacing prism results show an age dependent decrease on the learning rate that corroborates previous findings. The reversing prism results also show significant adaptation impairment in the aged population. However, decreased reversing learning in the older group was the result of an increase in the number of subjects that could not adapt to the reversing prism, and not on a reduction of the learning capacity of all the individuals of the group. These results suggest a significant deleterious effect of aging on visuomotor strategic learning implementation. Copyright © 2015 Elsevier B.V. All rights reserved.

FISCAL DECENTRALIZATION IN THE DRC: EVIDENCE OFREVENUE ASSIGNMENT

Directory of Open Access Journals (Sweden)

Angelita Kithatu-Kiwekete

2017-07-01

Full Text Available The rationalefor central government to devolve resources for service provisionhas been debated in decentralization literature. Decentralization enhancesdemocracy,encouragesparticipation in local development initiativesandpromotes local political accountability.This discourse has been complemented bythe implementation of fiscal decentralization to increase the ability of sub-nationalgovernment in financing municipal service delivery. Fiscal decentralization hasoften been adopted by African statessince the onset ofthe New PublicManagement erain an effortto improvethe standard ofgovernance. The concernis that African states have taken minimal steps to adopt fiscal devolution thatpromotes revenue assignment which in turn limits sub-nationalgovernments’ability to generate own source revenues.This article examines the revenue assignment function of fiscal decentralization inthe Democratic Republic of Congo(DRCinthelight of decentralizationconcerns that have been raised by civil society, as the country charts its course todemocracy. The article is a desktop study that will consider documents andpoliciesin theDRCon thenational, provincialand locallevel as far asstaterevenue sourcesare concerned. Revenue assignment should enable DRC’sprovinces and local authoritiestogeneratesignificantrevenueindependently.However, post-conflict reconstruction and development efforts in the Great Lakesregion and in the DRC have largely isolated decentralization which wouldotherwise entrench local fiscalautonomy infinancing for local services anddevelopment. The article concludes that revenue generation for local authoritiesandtheprovinces in the DRC is still very centralised by the national government.Thearticleproposes policy recommendations that will be useful for the country toensurethatdecentralization effortsinclude fiscal devolution toenhance thefinancing for local development initiatives.

Dynamic Output Feedback Based Active Decentralized Fault-Tolerant Control for Reconfigurable Manipulator with Concurrent Failures

Directory of Open Access Journals (Sweden)

Yuanchun Li

2015-01-01

Full Text Available The goal of this paper is to describe an active decentralized fault-tolerant control (ADFTC strategy based on dynamic output feedback for reconfigurable manipulators with concurrent actuator and sensor failures. Consider each joint module of the reconfigurable manipulator as a subsystem, and treat the fault as the unknown input of the subsystem. Firstly, by virtue of linear matrix inequality (LMI technique, the decentralized proportional-integral observer (DPIO is designed to estimate and compensate the sensor fault online; hereafter, the compensated system model could be derived. Then, the actuator fault is estimated similarly by another DPIO using LMI as well, and the sufficient condition of the existence of H∞ fault-tolerant controller in the dynamic output feedback is presented for the compensated system model. Furthermore, the dynamic output feedback controller is presented based on the estimation of actuator fault to realize active fault-tolerant control. Finally, two 3-DOF reconfigurable manipulators with different configurations are employed to verify the effectiveness of the proposed scheme in simulation. The main advantages of the proposed scheme lie in that it can handle the concurrent faults act on the actuator and sensor on the same joint module, as well as there is no requirement of fault detection and isolation process; moreover, it is more feasible to the modularity of the reconfigurable manipulator.

Optimal placement and decentralized robust vibration control for spacecraft smart solar panel structures

International Nuclear Information System (INIS)

Jiang, Jian-ping; Li, Dong-xu

2010-01-01

The decentralized robust vibration control with collocated piezoelectric actuator and strain sensor pairs is considered in this paper for spacecraft solar panel structures. Each actuator is driven individually by the output of the corresponding sensor so that only local feedback control is implemented, with each actuator, sensor and controller operating independently. Firstly, an optimal placement method for the location of the collocated piezoelectric actuator and strain gauge sensor pairs is developed based on the degree of observability and controllability indices for solar panel structures. Secondly, a decentralized robust H ∞ controller is designed to suppress the vibration induced by external disturbance. Finally, a numerical comparison between centralized and decentralized control systems is performed in order to investigate their effectiveness to suppress vibration of the smart solar panel. The simulation results show that the vibration can be significantly suppressed with permitted actuator voltages by the controllers. The decentralized control system almost has the same disturbance attenuation level as the centralized control system with a bit higher control voltages. More importantly, the decentralized controller composed of four three-order systems is a better practical implementation than a high-order centralized controller is

Decentralized control of the COFS-I Mast using linear dc motors

Science.gov (United States)

Lindner, Douglas K.; Celano, Tom; Ide, Eric

1989-01-01

Consideration is given to a decentralized control design for vibration suppression in the COFS-I Mast using linear dc motors for actuators. The decentralized control design is based results from power systems using root locus techniques that are not well known. The approach is effective because the loop gain is low due to low actuator authority. The frequency-dependent nonlinearities of the actuator are taken into account. Because of the tendency of the transients to saturate the the stroke length of the actuator, its effectiveness is limited.

Evolutionary online behaviour learning and adaptation in real robots.

Science.gov (United States)

Silva, Fernando; Correia, Luís; Christensen, Anders Lyhne

2017-07-01

Online evolution of behavioural control on real robots is an open-ended approach to autonomous learning and adaptation: robots have the potential to automatically learn new tasks and to adapt to changes in environmental conditions, or to failures in sensors and/or actuators. However, studies have so far almost exclusively been carried out in simulation because evolution in real hardware has required several days or weeks to produce capable robots. In this article, we successfully evolve neural network-based controllers in real robotic hardware to solve two single-robot tasks and one collective robotics task. Controllers are evolved either from random solutions or from solutions pre-evolved in simulation. In all cases, capable solutions are found in a timely manner (1 h or less). Results show that more accurate simulations may lead to higher-performing controllers, and that completing the optimization process in real robots is meaningful, even if solutions found in simulation differ from solutions in reality. We furthermore demonstrate for the first time the adaptive capabilities of online evolution in real robotic hardware, including robots able to overcome faults injected in the motors of multiple units simultaneously, and to modify their behaviour in response to changes in the task requirements. We conclude by assessing the contribution of each algorithmic component on the performance of the underlying evolutionary algorithm.

A three-level atomicity model for decentralized workflow management systems

Science.gov (United States)

Ben-Shaul, Israel Z.; Heineman, George T.

1996-12-01

A workflow management system (WFMS) employs a workflow manager (WM) to execute and automate the various activities within a workflow. To protect the consistency of data, the WM encapsulates each activity with a transaction; a transaction manager (TM) then guarantees the atomicity of activities. Since workflows often group several activities together, the TM is responsible for guaranteeing the atomicity of these units. There are scalability issues, however, with centralized WFMSs. Decentralized WFMSs provide an architecture for multiple autonomous WFMSs to interoperate, thus accommodating multiple workflows and geographically-dispersed teams. When atomic units are composed of activities spread across multiple WFMSs, however, there is a conflict between global atomicity and local autonomy of each WFMS. This paper describes a decentralized atomicity model that enables workflow administrators to specify the scope of multi-site atomicity based upon the desired semantics of multi-site tasks in the decentralized WFMS. We describe an architecture that realizes our model and execution paradigm.

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

NARCIS (Netherlands)

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

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

Learning for Climate Change Adaptation among Selected ...

African Journals Online (AJOL)

Learning for Climate Change Adaptation among Selected Communities of Lusaka ... This research was aimed at surveying perceptions of climate change and ... This work is licensed under a Creative Commons Attribution 3.0 License.

Heterogeneous Users in MOOC and their Adaptive Learning Needs

Directory of Open Access Journals (Sweden)

María Luisa SEIN-ECHALUCE LACLETA

2017-02-01

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

Least-cost network evaluation of centralized and decentralized contributions to global electrification

International Nuclear Information System (INIS)

Levin, Todd; Thomas, Valerie M.

2012-01-01

The choice between centralized and decentralized electricity generation is examined for 150 countries as a function of population distribution, electricity consumption, transmission cost, and the cost difference between decentralized and centralized electricity generation. A network algorithm is developed to find the shortest centralized transmission network that spans a given fraction of the population in a country. The least-cost combination of centralized and decentralized electricity that serves the country is determined. Case studies of Botswana, Uganda, and Bangladesh illustrate situations that are more and less suited for decentralized electrification. Specific maps for centralized and decentralized generation are presented to show how the least-cost option varies with the relative costs of centralized and decentralized generation and transmission cost. Centralized and decentralized fractions are calculated for 150 countries. For most of the world's population, centralized electricity is the least-cost option. For a number of countries, particularly in Africa, substantial populations and regions may be most cost-effectively served by decentralized electricity. - Highlights: ► Centralized and decentralized electrification are compared for 150 countries. ► A cost-optimized network algorithm finds the least-cost electrification system. ► Least-cost infrastructures combine centralized and decentralized portions. ► For most people, centralized electricity is cheapest option. ► In much of Africa, decentralized electricity may be cheaper than centralized.

An Autonomous Mobile Agent-Based Distributed Learning Architecture-A Proposal and Analytical Analysis

Directory of Open Access Journals (Sweden)

I. Ahmed M. J. SADIIG

2005-10-01

Full Text Available An Autonomous Mobile Agent-Based Distributed Learning Architecture-A Proposal and Analytical Analysis Dr. I. Ahmed M. J. SADIIG Department of Electrical & Computer EngineeringInternational Islamic University GombakKuala Lumpur-MALAYSIA ABSTRACT The traditional learning paradigm invoving face-to-face interaction with students is shifting to highly data-intensive electronic learning with the advances in Information and Communication Technology. An important component of the e-learning process is the delivery of the learning contents to their intended audience over a network. A distributed learning system is dependent on the network for the efficient delivery of its contents to the user. However, as the demand of information provision and utilization increases on the Internet, the current information service provision and utilization methods are becoming increasingly inefficient. Although new technologies have been employed for efficient learning methodologies within the context of an e-learning environment, the overall efficiency of the learning system is dependent on the mode of distribution and utilization of its learning contents. It is therefore imperative to employ new techniques to meet the service demands of current and future e-learning systems. In this paper, an architecture based on autonomous mobile agents creating a Faded Information Field is proposed. Unlike the centralized information distribution in a conventional e-learning system, the information is decentralized in the proposed architecture resulting in increased efficiency of the overall system for distribution and utilization of system learning contents efficiently and fairly. This architecture holds the potential to address the heterogeneous user requirements as well as the changing conditions of the underlying network.

Decentralized Formation Flying Control in a Multiple-Team Hierarchy

Science.gov (United States)

Mueller, Joseph .; Thomas, Stephanie J.

2005-01-01

This paper presents the prototype of a system that addresses these objectives-a decentralized guidance and control system that is distributed across spacecraft using a multiple-team framework. The objective is to divide large clusters into teams of manageable size, so that the communication and computational demands driven by N decentralized units are related to the number of satellites in a team rather than the entire cluster. The system is designed to provide a high-level of autonomy, to support clusters with large numbers of satellites, to enable the number of spacecraft in the cluster to change post-launch, and to provide for on-orbit software modification. The distributed guidance and control system will be implemented in an object-oriented style using MANTA (Messaging Architecture for Networking and Threaded Applications). In this architecture, tasks may be remotely added, removed or replaced post-launch to increase mission flexibility and robustness. This built-in adaptability will allow software modifications to be made on-orbit in a robust manner. The prototype system, which is implemented in MATLAB, emulates the object-oriented and message-passing features of the MANTA software. In this paper, the multiple-team organization of the cluster is described, and the modular software architecture is presented. The relative dynamics in eccentric reference orbits is reviewed, and families of periodic, relative trajectories are identified, expressed as sets of static geometric parameters. The guidance law design is presented, and an example reconfiguration scenario is used to illustrate the distributed process of assigning geometric goals to the cluster. Next, a decentralized maneuver planning approach is presented that utilizes linear-programming methods to enact reconfiguration and coarse formation keeping maneuvers. Finally, a method for performing online collision avoidance is discussed, and an example is provided to gauge its performance.

Learn-and-Adapt Stochastic Dual Gradients for Network Resource Allocation

OpenAIRE

Chen, Tianyi; Ling, Qing; Giannakis, Georgios B.

2017-01-01

Network resource allocation shows revived popularity in the era of data deluge and information explosion. Existing stochastic optimization approaches fall short in attaining a desirable cost-delay tradeoff. Recognizing the central role of Lagrange multipliers in network resource allocation, a novel learn-and-adapt stochastic dual gradient (LA-SDG) method is developed in this paper to learn the sample-optimal Lagrange multiplier from historical data, and accordingly adapt the upcoming resource...

Learning Transferable Features with Deep Adaptation Networks

OpenAIRE

Long, Mingsheng; Cao, Yue; Wang, Jianmin; Jordan, Michael I.

2015-01-01

Recent studies reveal that a deep neural network can learn transferable features which generalize well to novel tasks for domain adaptation. However, as deep features eventually transition from general to specific along the network, the feature transferability drops significantly in higher layers with increasing domain discrepancy. Hence, it is important to formally reduce the dataset bias and enhance the transferability in task-specific layers. In this paper, we propose a new Deep Adaptation...

Studying citizen science through adaptive management and learning feedbacks as mechanisms for improving conservation.

Science.gov (United States)

Jordan, Rebecca; Gray, Steven; Sorensen, Amanda; Newman, Greg; Mellor, David; Newman, Greg; Hmelo-Silver, Cindy; LaDeau, Shannon; Biehler, Dawn; Crall, Alycia

2016-06-01

Citizen science has generated a growing interest among scientists and community groups, and citizen science programs have been created specifically for conservation. We examined collaborative science, a highly interactive form of citizen science, which we developed within a theoretically informed framework. In this essay, we focused on 2 aspects of our framework: social learning and adaptive management. Social learning, in contrast to individual-based learning, stresses collaborative and generative insight making and is well-suited for adaptive management. Adaptive-management integrates feedback loops that are informed by what is learned and is guided by iterative decision making. Participants engaged in citizen science are able to add to what they are learning through primary data collection, which can result in the real-time information that is often necessary for conservation. Our work is particularly timely because research publications consistently report a lack of established frameworks and evaluation plans to address the extent of conservation outcomes in citizen science. To illustrate how our framework supports conservation through citizen science, we examined how 2 programs enacted our collaborative science framework. Further, we inspected preliminary conservation outcomes of our case-study programs. These programs, despite their recent implementation, are demonstrating promise with regard to positive conservation outcomes. To date, they are independently earning funds to support research, earning buy-in from local partners to engage in experimentation, and, in the absence of leading scientists, are collecting data to test ideas. We argue that this success is due to citizen scientists being organized around local issues and engaging in iterative, collaborative, and adaptive learning. © 2016 Society for Conservation Biology.

DECENTRALIZATION OF PUBLIC AND LOCAL AUTHORITIES IN UKRAINE

Directory of Open Access Journals (Sweden)

Lyudmila Pron’ko

2016-11-01

Full Text Available The purpose of research is to examine the purpose of a modern system of local government in Ukraine, scientific analysis of the feasibility and benefits of implemented reforms for decentralization and subsidiary of local authorities, decentralization of public power and public control, and the need to strengthen the political status of local governments. Methodology. The methodological base for research on decentralization and local government reforms to strengthen the political status of local government and decentralization of public power is the Constitution of Ukraine, Laws of Ukraine, Decrees of the President of Ukraine, as well as publications on these issues of domestic and foreign authors. As a result (Results study determined that according to Article 5 of the Law of Ukraine “On local government in Ukraine” The elements of local government are: local community; Village, town, city council; Village, town, city mayor; executive bodies of village, town and city councils; district (in the city Council, created in cities with district division by the decision of the territorial community, or city council; district and regional councils, which represent common interests of territorial communities of villages, towns and cities; BSP; system of government in Ukraine is not fulfilling the role assigned to it, because there is twofold subordination and uncertainty powers of representative and executive bodies. Today there is a three-level administrative division: basic level (village, town or city, district level and level area. There is a local government council and executive body (all the decisions and programs approved by the Regional Council performed by RSA, those public authorities. Thus there is a need for continued reform of local government on the principles of decentralization and subsidiary principle because they are building the foundation of the state; One of the hallmarks of a modern democratic society has become political

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

Science.gov (United States)

Wong, Lung-Hsiang; Looi, Chee-Kit

2012-01-01

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

Cloud Pedagogy: Utilizing Web-Based Technologies for the Promotion of Social Constructivist Learning in Science Teacher Preparation Courses

Science.gov (United States)

Barak, Miri

2017-10-01

The new guidelines for science education emphasize the need to introduce computers and digital technologies as a means of enabling visualization and data collection and analysis. This requires science teachers to bring advanced technologies into the classroom and use them wisely. Hence, the goal of this study was twofold: to examine the application of web-based technologies in science teacher preparation courses and to examine pre-service teachers' perceptions of "cloud pedagogy"—an instructional framework that applies technologies for the promotion of social constructivist learning. The study included university teachers ( N = 48) and pre-service science teachers ( N = 73). Data were collected from an online survey, written reflections, and interviews. The findings indicated that university teachers use technologies mainly for information management and the distribution of learning materials and less for applying social constructivist pedagogy. University teachers expect their students (i.e., pre-service science teachers) to use digital tools in their future classroom to a greater extent than they themselves do. The findings also indicated that the "cloud pedagogy" was perceived as an appropriate instructional framework for contemporary science education. The application of the cloud pedagogy fosters four attributes: the ability to adapt to frequent changes and uncertain situations, the ability to collaborate and communicate in decentralized environments, the ability to generate data and manage it, and the ability to explore new venous.

Empowering health personnel for decentralized health planning in India: The Public Health Resource Network

Directory of Open Access Journals (Sweden)

Prasad Vandana

2009-07-01

Full Text Available Abstract The Public Health Resource Network is an innovative distance-learning course in training, motivating, empowering and building a network of health personnel from government and civil society groups. Its aim is to build human resource capacity for strengthening decentralized health planning, especially at the district level, to improve accountability of health systems, elicit community participation for health, ensure equitable and accessible health facilities and to bring about convergence in programmes and services. The question confronting health systems in India is how best to reform, revitalize and resource primary health systems to deliver different levels of service aligned to local realities, ensuring universal coverage, equitable access, efficiency and effectiveness, through an empowered cadre of health personnel. To achieve these outcomes it is essential that health planning be decentralized. Districts vary widely according to the specific needs of their population, and even more so in terms of existing interventions and available resources. Strategies, therefore, have to be district-specific, not only because health needs vary, but also because people's perceptions and capacities to intervene and implement programmes vary. In centrally designed plans there is little scope for such adaptation and contextualization, and hence decentralized planning becomes crucial. To undertake these initiatives, there is a strong need for trained, motivated, empowered and networked health personnel. It is precisely at this level that a lack of technical knowledge and skills and the absence of a supportive network or adequate educational opportunities impede personnel from making improvements. The absence of in-service training and of training curricula that reflect field realities also adds to this, discouraging health workers from pursuing effective strategies. The Public Health Resource Network is thus an attempt to reach out to motivated

Empowering health personnel for decentralized health planning in India: The Public Health Resource Network.

Science.gov (United States)

Kalita, Anuska; Zaidi, Sarover; Prasad, Vandana; Raman, V R

2009-07-20

The Public Health Resource Network is an innovative distance-learning course in training, motivating, empowering and building a network of health personnel from government and civil society groups. Its aim is to build human resource capacity for strengthening decentralized health planning, especially at the district level, to improve accountability of health systems, elicit community participation for health, ensure equitable and accessible health facilities and to bring about convergence in programmes and services. The question confronting health systems in India is how best to reform, revitalize and resource primary health systems to deliver different levels of service aligned to local realities, ensuring universal coverage, equitable access, efficiency and effectiveness, through an empowered cadre of health personnel. To achieve these outcomes it is essential that health planning be decentralized. Districts vary widely according to the specific needs of their population, and even more so in terms of existing interventions and available resources. Strategies, therefore, have to be district-specific, not only because health needs vary, but also because people's perceptions and capacities to intervene and implement programmes vary. In centrally designed plans there is little scope for such adaptation and contextualization, and hence decentralized planning becomes crucial. To undertake these initiatives, there is a strong need for trained, motivated, empowered and networked health personnel. It is precisely at this level that a lack of technical knowledge and skills and the absence of a supportive network or adequate educational opportunities impede personnel from making improvements. The absence of in-service training and of training curricula that reflect field realities also adds to this, discouraging health workers from pursuing effective strategies. The Public Health Resource Network is thus an attempt to reach out to motivated though often isolated health

Decentralized Portfolio Management

Directory of Open Access Journals (Sweden)

Benjamin Miranda Tabak

2003-12-01

Full Text Available We use a mean-variance model to analyze the problem of decentralized portfolio management. We find the solution for the optimal portfolio allocation for a head trader operating in n different markets, which is called the optimal centralized portfolio. However, as there are many traders specialized in different markets, the solution to the problem of optimal decentralized allocation should be different from the centralized case. In this paper we derive conditions for the solutions to be equivalent. We use multivariate normal returns and a negative exponential function to solve the problem analytically. We generate the equivalence of solutions by assuming that different traders face different interest rates for borrowing and lending. This interest rate is dependent on the ratio of the degrees of risk aversion of the trader and the head trader, on the excess return, and on the correlation between asset returns.

Decentralized Electric Vehicle Charging Strategies for Reduced Load Variation and Guaranteed Charge Completion in Regional Distribution Grids

Directory of Open Access Journals (Sweden)

Weige Zhang

2017-01-01

Full Text Available A novel, fully decentralized strategy to coordinate charge operation of electric vehicles is proposed in this paper. Based on stochastic switching control of on-board chargers, this strategy ensures high-efficiency charging, reduces load variations to the grid during charging periods, achieves charge completion with high probability, and accomplishes approximate “valley-filling”. Further improvements on the core strategy, including individualized power management, adaptive strategies, and battery support systems, are introduced to further reduce power fluctuation variances and to guarantee charge completion. Stochastic analysis is performed to establish the main properties of the strategies and to quantitatively show the performance improvements. Compared with the existing decentralized charging strategies, the strategies proposed in this paper can be implemented without any information exchange between grid operators and electric vehicles (EVs, resulting in a communications cost reduction. Additionally, it is shown that by using stochastic charging rules, a grid-supporting battery system with a very small energy capacity can achieve substantial reduction of EV load fluctuations with high confidence. An extensive set of simulations and case studies with real-world data are used to demonstrate the benefits of the proposed strategies.

Decentralization, Local Rights and the Construction of Women's ...

International Development Research Centre (IDRC) Digital Library (Canada)

Decentralization, Local Rights and the Construction of Women's Citizenship : a Comparative Study in Kenya, Tanzania and Uganda - Phase II. Kenya, Tanzania and Uganda have adopted new land laws, policies and institutional arrangements to accommodate decentralization of land administration and management.

Adaptive enhancement of learning protocol in hippocampal cultured networks grown on multielectrode arrays

Science.gov (United States)

Pimashkin, Alexey; Gladkov, Arseniy; Mukhina, Irina; Kazantsev, Victor

2013-01-01

Learning in neuronal networks can be investigated using dissociated cultures on multielectrode arrays supplied with appropriate closed-loop stimulation. It was shown in previous studies that weakly respondent neurons on the electrodes can be trained to increase their evoked spiking rate within a predefined time window after the stimulus. Such neurons can be associated with weak synaptic connections in nearby culture network. The stimulation leads to the increase in the connectivity and in the response. However, it was not possible to perform the learning protocol for the neurons on electrodes with relatively strong synaptic inputs and responding at higher rates. We proposed an adaptive closed-loop stimulation protocol capable to achieve learning even for the highly respondent electrodes. It means that the culture network can reorganize appropriately its synaptic connectivity to generate a desired response. We introduced an adaptive reinforcement condition accounting for the response variability in control stimulation. It significantly enhanced the learning protocol to a large number of responding electrodes independently on its base response level. We also found that learning effect preserved after 4–6 h after training. PMID:23745105

Adaptive E-learning System in Secondary Education

Directory of Open Access Journals (Sweden)

Sofija Tosheva

2012-02-01

Full Text Available In this paper we describe an adaptive web application E-school, where students can adjust some features according to their preferences and learning style. This e-learning environment enables monitoring students progress, total time students have spent in the system, their activity on the forums, the overall achievements in lessons learned, tests performed and solutions to given projects. Personalized assistance that teacher provides in a traditional classroom is not easy to implement. Students have regular contact with teachers using e-mail tools and conversation, so teacher get mentoring role for each student. The results of exploitation of the e-learning system show positive impact in acquiring the material and improvement of student’s achievements.

Decentralized Blended Acquisition

NARCIS (Netherlands)

Berkhout, A.J.

2013-01-01

The concept of blending and deblending is reviewed, making use of traditional and dispersed source arrays. The network concept of distributed blended acquisition is introduced. A million-trace robot system is proposed, illustrating that decentralization may bring about a revolution in the way we

Blockchain technology and decentralized governance: Is the state still necessary?

Directory of Open Access Journals (Sweden)

Marcella Atzori

2017-03-01

Full Text Available The core technology of Bitcoin, the blockchain, has recently emerged as a disruptive innovation with a wide range of applications, potentially able to redesign our interactions in business, politics and society at large. Although scholarly interest in this subject is growing, a comprehensive analysis of blockchain applications from a political perspective is severely lacking to date. This paper aims to fill this gap and it discusses the key points of blockchain-based decentralized governance, which challenges to varying degrees the traditional mechanisms of State authority, citizenship and democracy. In particular, the paper verifies to which extent blockchain and decentralized platforms can be considered as hyper-political tools, capable to manage social interactions on large scale and dismiss traditional central authorities. The analysis highlights risks related to a dominant position of private powers in distributed ecosystems, which may lead to a general disempowerment of citizens and to the emergence of a stateless global society. While technological utopians urge the demise of any centralized institution, this paper advocates the role of the State as a necessary central point of coordination in society, showing that decentralization through algorithm-based consensus is an organizational theory, not a stand-alone political theory.

Lexmeter: validation of an automated system for the assessment of lexical competence of medical students as a base for an adaptive e-learning system

Directory of Open Access Journals (Sweden)

Fabrizio eConsorti

2015-02-01

Full Text Available Distance learning is used in medical education, even if some recent meta-analyses indicated that it is no more effective than traditional methods. To exploit the technological capabilities, adaptive distance learning systems aim to bridge the gap between the educational offer and the learner’s need. A decrease of lexical competence has been noted in many western countries, so lexical competence could be a possible target for adaptation. The Adaptive message learning project (Am-learning is aimed at designing and implementing an adaptive e-learning system, driven by lexical competence. The goal of the project is to modulate texts according to the estimated skill of learners, to allow a better comprehension. Lexmeter is the first of the four modules of the Am-learning system. It outlines an initial profile of the learner’s lexical competence and can also produce cloze tests, a test based on a completion task.A validation test of Lexmeter was run on 443 medical students of the 1st, 3rd and 6th year at the University Sapienza of Rome. Six cloze tests were automatically produced, with ten gaps each. The tests were different for each year and with varying levels of difficulty. A last cloze test was manually created as a control. The difference of the mean score between the easy tests and the tests with a medium level of difficulty was statistically significant for the 3rd year students but not for 1st and 6th year. The score of the automatically generated tests showed a slight but significant correlation with the control test. The reliability (Cronbach alpha of the different tests fluctuated under and above .60, as an acceptable level. In fact, classical item analysis revealed that the tests were on the average too simple.Lexical competence is a relevant outcome and its assessment allows an early detection of students at risk. Cloze tests can also be used to assess specific knowledge of technical jargon and to train reasoning skill.

Stimulating the cerebellum affects visuomotor adaptation but not intermanual transfer of learning.

Science.gov (United States)

Block, Hannah; Celnik, Pablo

2013-12-01

When systematic movement errors occur, the brain responds with a systematic change in motor behavior. This type of adaptive motor learning can transfer intermanually; adaptation of movements of the right hand in response to training with a perturbed visual signal (visuomotor adaptation) may carry over to the left hand. While visuomotor adaptation has been studied extensively, it is unclear whether the cerebellum, a structure involved in adaptation, is important for intermanual transfer as well. We addressed this question with three experiments in which subjects reached with their right hands as a 30° visuomotor rotation was introduced. Subjects received anodal or sham transcranial direct current stimulation on the trained (experiment 1) or untrained (experiment 2) hemisphere of the cerebellum, or, for comparison, motor cortex (M1). After the training period, subjects reached with their left hand, without visual feedback, to assess intermanual transfer of learning aftereffects. Stimulation of the right cerebellum caused faster adaptation, but none of the stimulation sites affected transfer. To ascertain whether cerebellar stimulation would increase transfer if subjects learned faster as well as a larger amount, in experiment 3 anodal and sham cerebellar groups experienced a shortened training block such that the anodal group learned more than sham. Despite the difference in adaptation magnitude, transfer was similar across these groups, although smaller than in experiment 1. Our results suggest that intermanual transfer of visuomotor learning does not depend on cerebellar activity and that the number of movements performed at plateau is an important predictor of transfer.

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

Directory of Open Access Journals (Sweden)

Harry Biggs

2011-05-01

Two other studies in the Kruger National Park, which have examined learning specifically, are also discussed. One of them suggests that in a complex environment, learning necessarily has a dual nature, with each component of seven contrasting pairs of the aspects of learning in partial tension with the other. We use these dualities to further probe assessment, reflection, inter-relatedness and learning in the cases presented. Each contrasting aspect of a ‘learning duality’ turns out to emphasise either assessment or reflection, which reinforces the idea that both are needed to facilitate sufficient learning for successful adaptive management. We hope this analysis can act as a springboard for further study, practice and reflection on these important and often underrated components of adaptive management. Conservation implications: The better understanding of assessment and reflection as being largely separate but complementary actions will assist adaptive management practitioners to give explicit attention to both, and to relate them better to each other.

The Two Edge Knife of Decentralization

OpenAIRE

Umam, Ahmad Khoirul

2011-01-01

A centralistic government model has become a trend in a number of developing countries, in which the ideosycretic aspect becomes pivotal key in the policy making. The situation constitutes authoritarianism, cronyism, and corruption. To break the impasse, the decentralized system is proposed to make people closer to the public policy making. Decentralization is also convinced to be the solution to create a good governance. But a number of facts in the developing countries demonstrates that dec...

Effects of practice schedule and task specificity on the adaptive process of motor learning.

Science.gov (United States)

Barros, João Augusto de Camargo; Tani, Go; Corrêa, Umberto Cesar

2017-10-01

This study investigated the effects of practice schedule and task specificity based on the perspective of adaptive process of motor learning. For this purpose, tasks with temporal and force control learning requirements were manipulated in experiments 1 and 2, respectively. Specifically, the task consisted of touching with the dominant hand the three sequential targets with specific movement time or force for each touch. Participants were children (N=120), both boys and girls, with an average age of 11.2years (SD=1.0). The design in both experiments involved four practice groups (constant, random, constant-random, and random-constant) and two phases (stabilisation and adaptation). The dependent variables included measures related to the task goal (accuracy and variability of error of the overall movement and force patterns) and movement pattern (macro- and microstructures). Results revealed a similar error of the overall patterns for all groups in both experiments and that they adapted themselves differently in terms of the macro- and microstructures of movement patterns. The study concludes that the effects of practice schedules on the adaptive process of motor learning were both general and specific to the task. That is, they were general to the task goal performance and specific regarding the movement pattern. Copyright © 2017 Elsevier B.V. All rights reserved.

Anatomy of Student Models in Adaptive Learning Systems: A Systematic Literature Review of Individual Differences from 2001 to 2013

Science.gov (United States)

Nakic, Jelena; Granic, Andrina; Glavinic, Vlado

2015-01-01

This study brings an evidence-based review of user individual characteristics employed as sources of adaptation in recent adaptive learning systems. Twenty-two user individual characteristics were explored in a systematically designed search procedure, while 17 of them were identified as sources of adaptation in final selection. The content…

Decentralization : Local Partnerships for Health Services in the ...

International Development Research Centre (IDRC) Digital Library (Canada)

Cameroon, like most other sub-Saharan African countries, has adopted laws devolving various responsibilities to local administrations. In the local political discourse, decentralization is seen as bringing essential services closer to the users, especially those in greatest need. However, the national decentralization program ...

Adaptive Learning in Cartesian Product of Reproducing Kernel Hilbert Spaces

OpenAIRE

Yukawa, Masahiro

2014-01-01

We propose a novel adaptive learning algorithm based on iterative orthogonal projections in the Cartesian product of multiple reproducing kernel Hilbert spaces (RKHSs). The task is estimating/tracking nonlinear functions which are supposed to contain multiple components such as (i) linear and nonlinear components, (ii) high- and low- frequency components etc. In this case, the use of multiple RKHSs permits a compact representation of multicomponent functions. The proposed algorithm is where t...

Decentralization and financial autonomy: a challenge for local public authorities in the Republic of Moldova

Directory of Open Access Journals (Sweden)

Tatiana MANOLE

2017-09-01

Full Text Available This article reflects the decentralization process currently taking place in the Republic of Moldova. The purpose of the research is to acquaint readers with the fundamental concept of decentralization, with the areas of administrative decentralization, with the forms of manifestation of financial decentralization: fiscal decentralization and budget decentralization. The priorities of the decentralization process are identified.

A Decentralized Control Architecture applied to DC Nanogrid Clusters for Rural Electrification in Developing Regions

DEFF Research Database (Denmark)

Nasir, Mashood; Jin, Zheming; Khan, Hassan

2018-01-01

resources with the community. An adaptive I-V droop method is used which relies on local measurements of SOC and DC bus voltage for the coordinated power sharing among the contributing nanogrids. PV generation capability of individual nanogrids is synchronized with the grid stability conditions through......DC microgrids built through bottom-up approach are becoming very popular for swarm electrification due to their scalability and resource sharing capabilities. However, they typically require sophisticated control techniques involving communication among the distributed resources for stable...... and coordinated operation. In this work, we present a communication-less strategy for the decentralized control of a PV/battery-based highly distributed DC microgrid. The architecture consists of clusters of nanogrids (households), where each nanogrid can work independently along with provisions of sharing...

Learning to adapt: Organisational adaptation to climate change impacts

NARCIS (Netherlands)

Berkhout, F.G.H.; Hertin, J.; Gann, D.M.

2006-01-01

Analysis of human adaptation to climate change should be based on realistic models of adaptive behaviour at the level of organisations and individuals. The paper sets out a framework for analysing adaptation to the direct and indirect impacts of climate change in business organisations with new

Adaptation and learning: characteristic time scales of performance dynamics.

Science.gov (United States)

Newell, Karl M; Mayer-Kress, Gottfried; Hong, S Lee; Liu, Yeou-Teh

2009-12-01

A multiple time scales landscape model is presented that reveals structures of performance dynamics that were not resolved in the traditional power law analysis of motor learning. It shows the co-existence of separate processes during and between practice sessions that evolve in two independent dimensions characterized by time scales that differ by about an order of magnitude. Performance along the slow persistent dimension of learning improves often as much and sometimes more during rest (memory consolidation and/or insight generation processes) than during a practice session itself. In contrast, the process characterized by the fast, transient dimension of adaptation reverses direction between practice sessions, thereby significantly degrading performance at the beginning of the next practice session (warm-up decrement). The theoretical model fits qualitatively and quantitatively the data from Snoddy's [Snoddy, G. S. (1926). Learning and stability. Journal of Applied Psychology, 10, 1-36] classic learning study of mirror tracing and other averaged and individual data sets, and provides a new account of the processes of change in adaptation and learning. 2009 Elsevier B.V. All rights reserved.

Applications of Adaptive Learning Controller to Synthetic Aperture Radar.

Science.gov (United States)

1985-02-01

TERMS (Continue on retuerse if necessary and identify by block num ber) FIELD YGROUP SUB. GR. Adaptive control, aritificial intelligence , synthetic aetr1...application of Artificial Intelligence methods to Synthetic Aperture Radars (SARs) is investigated. It was shown that the neuron-like Adaptive Learning...wavelength Al SE!RI M RADAR DIVISION REFERENCES 1. Barto, A.G. and R.S. Sutton, Goal Seeking Components for Adaptive Intelligence : An Initial Assessment

The Dynamics of Learning and the Emergence of Distributed Adaption

National Research Council Canada - National Science Library

Crutchfield, James P

2006-01-01

.... The second goal was to adapt this single-agent learning theory and associated learning algorithms to the distributed setting in which a population of autonomous agents communicate to achieve a desired group task...

Social capital, conflict, and adaptive collaborative governance

NARCIS (Netherlands)

McDougall, C.L.; Ram Banjade, Mani

2015-01-01

Previously lineal and centralized natural resource management and development paradigms have shifted toward the recognition of complexity and dynamism of social-ecological systems, and toward more adaptive, decentralized, and collaborative models. However, certain messy and surprising dynamics

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

Science.gov (United States)

Chen, Ching-Huei; Chang, Shu-Wei

2015-01-01

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

Data mining methods application in reflexive adaptation realization in e-learning systems

Directory of Open Access Journals (Sweden)

A. S. Bozhday

2017-01-01

Full Text Available In recent years, e-learning technologies are rapidly gaining momentum in their evolution. In this regard, issues related to improving the quality of software for virtual educational systems are becoming topical: increasing the period of exploitation of programs, increasing their reliability and flexibility. The above characteristics directly depend on the ability of the software system to adapt to changes in the domain, environment and user characteristics. In some cases, this ability is reduced to the timely optimization of the program’s own interfaces and data structure. At present, several approaches to creating mechanisms for self-optimization of software systems are known, but all of them have an insufficient degree of formalization and, as a consequence, weak universality. The purpose of this work is to develop the basics of the technology of self-optimization of software systems in the structure of e-learning. The proposed technology is based on the formulated and formalized principle of reflexive adaptation of software, applicable to a wide class of software systems and based on the discovery of new knowledge in the behavioral products of the system.To solve this problem, methods of data mining were applied. Data mining allows finding regularities in the functioning of software systems, which may not be obvious at the stage of their development. Finding such regularities and their subsequent analysis will make it possible to reorganize the structure of the system in a more optimal way and without human intervention, which will prolong the life cycle of the software and reduce the costs of its maintenance. Achieving this effect is important for e-learning systems, since they are quite expensive.The main results of the work include: the proposed classification of software adaptation mechanisms, taking into account the latest trends in the IT field in general and in the field of e-learning in particular; Formulation and formalization of

Study on autonomous decentralized-cooperative function monitoring system

International Nuclear Information System (INIS)

Matsuoka, Takeshi; Numano, Masayoshi; Someya, Minoru; Fukuto, Junji; Mitomo, Nobuo; Miyazaki, Keiko; Matsukura, Hiroshi; Tanba, Yasuyuki

1999-01-01

In this study, a study further advanced on a base of results of study on artificial intelligence for nuclear power', one of nuclear basis crossover studies, conducted at five years planning from 1989 fiscal year was executed. Here was conducted on study on a system technology for supplying cooperation, judgement process, judgement results, and so forth between decentralized artificial intelligent elements (agents) to operation managers (supervisors) by focussing a system for monitoring if autonomous decentralized system containing plant operation and robot group action functioned appropriately. In 1997 fiscal year, by mainly conducting development for displaying working state of robot group, some investigations on integrated management of each function already development and maintained were executed. Furthermore, some periodical meetings on realization of its integration with operation control system and maintenance system with other research institutes were conducted. (G.K.)

Decentralized Feedback Controllers for Exponential Stabilization of Hybrid Periodic Orbits: Application to Robotic Walking*

Science.gov (United States)

Hamed, Kaveh Akbari; Gregg, Robert D.

2016-01-01

This paper presents a systematic algorithm to design time-invariant decentralized feedback controllers to exponentially stabilize periodic orbits for a class of hybrid dynamical systems arising from bipedal walking. The algorithm assumes a class of parameterized and nonlinear decentralized feedback controllers which coordinate lower-dimensional hybrid subsystems based on a common phasing variable. The exponential stabilization problem is translated into an iterative sequence of optimization problems involving bilinear and linear matrix inequalities, which can be easily solved with available software packages. A set of sufficient conditions for the convergence of the iterative algorithm to a stabilizing decentralized feedback control solution is presented. The power of the algorithm is demonstrated by designing a set of local nonlinear controllers that cooperatively produce stable walking for a 3D autonomous biped with 9 degrees of freedom, 3 degrees of underactuation, and a decentralization scheme motivated by amputee locomotion with a transpelvic prosthetic leg. PMID:27990059

Classification of multiple sclerosis lesions using adaptive dictionary learning.

Science.gov (United States)

Deshpande, Hrishikesh; Maurel, Pierre; Barillot, Christian

2015-12-01

This paper presents a sparse representation and an adaptive dictionary learning based method for automated classification of multiple sclerosis (MS) lesions in magnetic resonance (MR) images. Manual delineation of MS lesions is a time-consuming task, requiring neuroradiology experts to analyze huge volume of MR data. This, in addition to the high intra- and inter-observer variability necessitates the requirement of automated MS lesion classification methods. Among many image representation models and classification methods that can be used for such purpose, we investigate the use of sparse modeling. In the recent years, sparse representation has evolved as a tool in modeling data using a few basis elements of an over-complete dictionary and has found applications in many image processing tasks including classification. We propose a supervised classification approach by learning dictionaries specific to the lesions and individual healthy brain tissues, which include white matter (WM), gray matter (GM) and cerebrospinal fluid (CSF). The size of the dictionaries learned for each class plays a major role in data representation but it is an even more crucial element in the case of competitive classification. Our approach adapts the size of the dictionary for each class, depending on the complexity of the underlying data. The algorithm is validated using 52 multi-sequence MR images acquired from 13 MS patients. The results demonstrate the effectiveness of our approach in MS lesion classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

Switching Reinforcement Learning for Continuous Action Space

Science.gov (United States)

Nagayoshi, Masato; Murao, Hajime; Tamaki, Hisashi

Reinforcement Learning (RL) attracts much attention as a technique of realizing computational intelligence such as adaptive and autonomous decentralized systems. In general, however, it is not easy to put RL into practical use. This difficulty includes a problem of designing a suitable action space of an agent, i.e., satisfying two requirements in trade-off: (i) to keep the characteristics (or structure) of an original search space as much as possible in order to seek strategies that lie close to the optimal, and (ii) to reduce the search space as much as possible in order to expedite the learning process. In order to design a suitable action space adaptively, we propose switching RL model to mimic a process of an infant's motor development in which gross motor skills develop before fine motor skills. Then, a method for switching controllers is constructed by introducing and referring to the “entropy”. Further, through computational experiments by using robot navigation problems with one and two-dimensional continuous action space, the validity of the proposed method has been confirmed.

A decentralized control method for direct smart grid control of refrigeration systems

DEFF Research Database (Denmark)

Shafiei, Seyed Ehsan; Izadi-Zamanabadi, Roozbeh; Rasmussen, Henrik

2013-01-01

. No model information is required in this method. The temperature limits/constraints are respected. A novel adaptive saturation filter is also proposed to increase the system flexibility in storing and delivering the energy. The proposed control strategy is applied to a simulation benchmark that fairly......A decentralized control method is proposed to govern the electrical power consumption of supermarket refrigeration systems (SRS) for demand-side management in the smart grid. The control structure is designed in a supervisory level to provide desired set-points for distributed level controllers...

A globally convergent MC algorithm with an adaptive learning rate.

Science.gov (United States)

Peng, Dezhong; Yi, Zhang; Xiang, Yong; Zhang, Haixian

2012-02-01

This brief deals with the problem of minor component analysis (MCA). Artificial neural networks can be exploited to achieve the task of MCA. Recent research works show that convergence of neural networks based MCA algorithms can be guaranteed if the learning rates are less than certain thresholds. However, the computation of these thresholds needs information about the eigenvalues of the autocorrelation matrix of data set, which is unavailable in online extraction of minor component from input data stream. In this correspondence, we introduce an adaptive learning rate into the OJAn MCA algorithm, such that its convergence condition does not depend on any unobtainable information, and can be easily satisfied in practical applications.

Professor Eric Can't See: A Project-Based Learning Case for Neurobiology Students.

Science.gov (United States)

Ogilvie, Judith Mosinger; Ribbens, Eric

2016-01-01

"Professor Eric Can't See" is a semi-biographical case study written for an upper level undergraduate Neurobiology of Disease course. The case is integrated into a unit using a project-based learning approach to investigate the retinal degenerative disorder Retinitis pigmentosa and the visual system. Some case study scenes provide specific questions for student discussion and problem-based learning, while others provide background for student inquiry and related active learning exercises. The case was adapted from "'Chemical Eric' Can't See," and could be adapted for courses in general neuroscience or sensory neuroscience.

Decentralized cooperative spectrum sensing for ad-hoc disaster relief network clusters

DEFF Research Database (Denmark)

Pratas, Nuno; Marchetti, Nicola; Prasad, Neeli R.

2010-01-01

cooperative schemes becomes essential. A cluster based decentralized orchestration cooperative sensing scheme is proposed, where each node in the cluster decides which spectrum it should monitor, according to the past sensing decisions of all the cluster nodes. The proposed scheme performance is evaluated...... through a framework, which allows gauging the accuracy of multi narrow-band spectrum sensing cooperative schemes as well as to gauge the error in the estimation of each of the channels un-occupancy. Through that evaluation it is shown that the proposed decentralized scheme performance reaches...... the performance of the correspondent centralized scheme while outperforming the Round Robin scheme....

Centralized, Decentralized, and Hybrid Purchasing Organizations

DEFF Research Database (Denmark)

Bals, Lydia; Turkulainen, Virpi

This paper addresses one of the focal issues in purchasing and supply management – global sourcing – from an organizational design perspective. In particular, we elaborate the traditional classification of global sourcing organization designs into centralized, decentralized, and hybrid models. We...... organization we can identify organization designs beyond the classical centralization-decentralization continuum. We also provide explanations for the observed organization design at GCC. The study contributes to research on purchasing and supply management as well as research on organization design....

Analysis of an Interactive Technology Supported Problem-Based Learning STEM Project Using Selected Learning Sciences Interest Areas (SLSIA)

Science.gov (United States)

Kumar, David Devraj

2017-01-01

This paper reports an analysis of an interactive technology-supported, problem-based learning (PBL) project in science, technology, engineering and mathematics (STEM) from a Learning Sciences perspective using the Selected Learning Sciences Interest Areas (SLSIA). The SLSIA was adapted from the "What kinds of topics do ISLS [International…

State-of-Charge Balance Using Adaptive Droop Control for Distributed Energy Storage Systems in DC MicroGrid Applications

DEFF Research Database (Denmark)

Lu, Xiaonan; Sun, Kai; Guerrero, Josep M.

2014-01-01

This paper presents the coordinated control of distributed energy storage systems (DESSs) in DC micro-grids. In order to balance the state-of-charge (SoC) of each energy storage unit (ESU), an SoC-based adaptive droop control method is proposed. In this decentralized control method, the droop...

Managing Cognitive Load in Adaptive ICT-Based Learning

Directory of Open Access Journals (Sweden)

Slava Kalyuga

2009-10-01

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

Computer-based learning for the enhancement of breastfeeding ...

African Journals Online (AJOL)

In this study, computer-based learning (CBL) was explored in the context of breastfeeding training for undergraduate Dietetic students. Aim: To adapt and validate an Indian computer-based undergraduate breastfeeding training module for use by South African undergraduate Dietetic students. Methods and materials: The ...

Adaptation, postpartum concerns, and learning needs in the first two weeks after caesarean birth.

Science.gov (United States)

Weiss, Marianne; Fawcett, Jacqueline; Aber, Cynthia

2009-11-01

The purpose of this Roy Adaptation Model-based study was to describe women's physical, emotional, functional and social adaptation; postpartum concerns; and learning needs during the first two weeks following caesarean birth and identify relevant nursing interventions. Studies of caesarean-delivered women indicated a trend toward normalisation of the caesarean birth experience. Escalating caesarean birth rates mandate continued study of contemporary caesarean-delivered women. Mixed methods (qualitative and quantitative) descriptive research design. Nursing students collected data from 233 culturally diverse caesarean-delivered women in urban areas of the Midwestern and Northeastern USA between 2002-2004. The focal stimulus was the planned or unplanned caesarean birth; contextual stimuli were cultural identity and parity. Adaptation was measured by open-ended interview questions, fixed choice questionnaires about postpartum concerns and learning needs and nurse assessment of post-discharge problems. Potential interventions were identified using the Omaha System Intervention Scheme. More positive than negative responses were reported for functional and social adaptation than for physical and emotional adaptation. Women with unplanned caesarean births and primiparous women reported less favourable adaptation than planned caesarean mothers and multiparas. Black women reported lower social adaptation, Hispanic women had more role function concerns and Black and Hispanic women had more learning needs than White women. Post-discharge nursing assessments revealed that actual problems accounted for 40% of identified actual or potential problems or needs. Health teaching was the most commonly recommended postpartum intervention strategy followed by case management, treatment and surveillance interventions. Caesarean-delivered women continue to experience some problems with adapting to childbirth. Recommended intervention strategies reflect the importance of health teaching

On the role of model-based monitoring for adaptive planning under uncertainty

Science.gov (United States)

Raso, Luciano; Kwakkel, Jan; Timmermans, Jos; Haasnoot, Mariolijn

2016-04-01

, triggered by the challenge of uncertainty in operational control, may offer solutions from which monitoring for adaptive planning can benefit. Specifically: (i) in control, observations are incorporated into the model through data assimilation, updating the present state, boundary conditions, and parameters based on new observations, diminishing the shadow of the past; (ii) adaptive control is a way to modify the characteristics of the internal model, incorporating new knowledge on the system, countervailing the inhibition of learning; and (iii) in closed-loop control, a continuous system update equips the controller with "inherent robustness", i.e. to capacity to adapts to new conditions even when these were not initially considered. We aim to explore how inherent robustness addresses the challenge of surprise. Innovations in model-based control might help to improve and adapt the models used to support adaptive delta management to new information (reducing uncertainty). Moreover, this would offer a starting point for using these models not only in the design of adaptive plans, but also as part of the monitoring. The proposed research requires multidisciplinary cooperation between control theory, the policy sciences, and integrated assessment modeling.

MRSA model of learning and adaptation: a qualitative study among the general public

Science.gov (United States)

2012-01-01

Background More people in the US now die from Methicillin Resistant Staphylococcus aureus (MRSA) infections than from HIV/AIDS. Often acquired in healthcare facilities or during healthcare procedures, the extremely high incidence of MRSA infections and the dangerously low levels of literacy regarding antibiotic resistance in the general public are on a collision course. Traditional medical approaches to infection control and the conventional attitude healthcare practitioners adopt toward public education are no longer adequate to avoid this collision. This study helps us understand how people acquire and process new information and then adapt behaviours based on learning. Methods Using constructivist theory, semi-structured face-to-face and phone interviews were conducted to gather pertinent data. This allowed participants to tell their stories so their experiences could deepen our understanding of this crucial health issue. Interview transcripts were analysed using grounded theory and sensitizing concepts. Results Our findings were classified into two main categories, each of which in turn included three subthemes. First, in the category of Learning, we identified how individuals used their Experiences with MRSA, to answer the questions: What was learned? and, How did learning occur? The second category, Adaptation gave us insights into Self-reliance, Reliance on others, and Reflections on the MRSA journey. Conclusions This study underscores the critical importance of educational programs for patients, and improved continuing education for healthcare providers. Five specific results of this study can reduce the vacuum that currently exists between the knowledge and information available to healthcare professionals, and how that information is conveyed to the public. These points include: 1) a common model of MRSA learning and adaptation; 2) the self-directed nature of adult learning; 3) the focus on general MRSA information, care and prevention, and antibiotic

MRSA model of learning and adaptation: a qualitative study among the general public

Directory of Open Access Journals (Sweden)

Rohde Rodney E

2012-04-01

Full Text Available Abstract Background More people in the US now die from Methicillin Resistant Staphylococcus aureus (MRSA infections than from HIV/AIDS. Often acquired in healthcare facilities or during healthcare procedures, the extremely high incidence of MRSA infections and the dangerously low levels of literacy regarding antibiotic resistance in the general public are on a collision course. Traditional medical approaches to infection control and the conventional attitude healthcare practitioners adopt toward public education are no longer adequate to avoid this collision. This study helps us understand how people acquire and process new information and then adapt behaviours based on learning. Methods Using constructivist theory, semi-structured face-to-face and phone interviews were conducted to gather pertinent data. This allowed participants to tell their stories so their experiences could deepen our understanding of this crucial health issue. Interview transcripts were analysed using grounded theory and sensitizing concepts. Results Our findings were classified into two main categories, each of which in turn included three subthemes. First, in the category of Learning, we identified how individuals used their Experiences with MRSA, to answer the questions: What was learned? and, How did learning occur? The second category, Adaptation gave us insights into Self-reliance, Reliance on others, and Reflections on the MRSA journey. Conclusions This study underscores the critical importance of educational programs for patients, and improved continuing education for healthcare providers. Five specific results of this study can reduce the vacuum that currently exists between the knowledge and information available to healthcare professionals, and how that information is conveyed to the public. These points include: 1 a common model of MRSA learning and adaptation; 2 the self-directed nature of adult learning; 3 the focus on general MRSA information, care and

Decentralization: A panacea for functional education and national ...

African Journals Online (AJOL)

Decentralization of power from the federal government to state and local governments is the way to go, especially in the management of our education system. Education can be best delivered at the state and local government levels. Decentralization of educational management in Nigeria will encourage creativity and ...

Is the Korean public willing to pay for a decentralized generation source? The case of natural gas-based combined heat and power

International Nuclear Information System (INIS)

Kim, Hyo-Jin; Lim, Seul-Ye; Yoo, Seung-Hoon

2017-01-01

Natural gas (NG)-based combined heat and power (CHP) plants can be installed near electricity-consuming areas and do not require large-scale and long-distance power transmission facilities. This paper attempts to assess the public's additional willingness to pay (WTP) for substituting consumption of a unit of electricity generated from nuclear power plant, currently a dominant power generation source in Korea, with that produced from NG-based CHP plant in terms of decentralized generation using the contingent valuation (CV) method. To this end, a CV survey of 1,000 households was implemented. The results show that the mean additional WTP for substituting nuclear power plant by NG-based CHP plant is estimated to be KRW 55.3 (USD 0.047) per kWh of electricity, which is statistically significant at the 1% level. This value amounts to 44.7% of the average price for electricity, KRW 123.69 (USD 0.106) in 2015, which implies that the public are ready to shoulder a significant financial burden to achieve the substitution. Moreover, the value can be interpreted as an external cost of nuclear power generation relative to NG-based CHP generation, or as an external benefit of NG-based CHP generation relative to nuclear power generation with a view to decentralized generation. - Highlights: • Combined heat and power (CHP) is a representative decentralized generation source. • Nuclear power requires large-scale and long-distance power transmission facilities. • We assess people's additional willingness to pay (WTP) for CHP over nuclear power. • We conduct a contingent valuation survey of 1,000 households in Korea. • The mean additional WTP amounts to 44.2% of the average price for electricity.

Coordinating decentralized optimization of truck and shovel mining operations

Energy Technology Data Exchange (ETDEWEB)

Cheng, R.; Fraser Forbes, J. [Alberta Univ., Edmonton, AB (Canada). Dept. of Chemical and Materials Engineering; San Yip, W. [Suncor Energy, Fort McMurray, AB (Canada)

2006-07-01

Canada's oil sands contain the largest known reserve of oil in the world. Oil sands mining uses 3 functional processes, ore hauling, overburden removal and mechanical maintenance. The industry relies mainly on truck-and-shovel technology in its open-pit mining operations which contributes greatly to the overall mining operation cost. Coordination between operating units is crucial for achieving an enterprise-wide optimal operation level. Some of the challenges facing the industry include multiple or conflicting objectives such as minimizing the use of raw materials and energy while maximizing production. The large sets of constraints that define the feasible domain pose as challenge, as does the uncertainty in system parameters. One solution lies in assigning truck resources to various activities. This fully decentralized approach would treat the optimization of ore production, waste removal and equipment maintenance independently. It was emphasized that mine-wide optimal operation can only be achieved by coordinating ore hauling and overburden removal processes. For that reason, this presentation proposed a coordination approach for a decentralized optimization system. The approach is based on the Dantzig-Wolfe decomposition and auction-based methods that have been previously used to decompose large-scale optimization problems. The treatment of discrete variables and coordinator design was described and the method was illustrated with a simple truck and shovel mining simulation study. The approach can be applied to a wide range of applications such as coordinating decentralized optimal control systems and scheduling. 16 refs., 3 tabs., 2 figs.

QoS-based experience-aware adaptation in multimedia e-learning - A learner, is a learner, is a user, is a customer

OpenAIRE

Moebs, Sabine

2011-01-01

One of the challenges for the future of technology-enhanced learning is the retention of learners. On-line learning environments should engage learners and provide an appropriate “Quality of Experience” (QoE). For more than a decade, adaptive hypermedia systems have been used to adapt content and instruction to individual knowledge, goals and preferences in an effort to engage learners. However, even if the content is highly engaging it can be very difficult to achieve good Quality ...

Decentralized energy: technology assessment and systems description. [Potential for implementation for years 2000 and 2025

Energy Technology Data Exchange (ETDEWEB)

Reckard, M K

1979-06-01

Decentralized energy systems and their characteristic features are examined in the report. These systems have been divided into six groups for the purpose of analysis: solar, wind, hydro, biomass, geothermal, and coproduction (total energy). The technical and economic potential for the implementation of these systems is discussed for the years 2000 and 2025. The results of a comparison of base-case and decentralized scenarios for the year 2000, using a computer systems model, are presented. Social and institutional factors are also addressed, both as motivations for and results of energy system decentralization. Appendices are included with more detailed technical information on each of the systems groups.

Integrating Adaptive Games in Student-Centered Virtual Learning Environments

Science.gov (United States)

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

2010-01-01

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

Adaptive metric learning with deep neural networks for video-based facial expression recognition

Science.gov (United States)

Liu, Xiaofeng; Ge, Yubin; Yang, Chao; Jia, Ping

2018-01-01

Video-based facial expression recognition has become increasingly important for plenty of applications in the real world. Despite that numerous efforts have been made for the single sequence, how to balance the complex distribution of intra- and interclass variations well between sequences has remained a great difficulty in this area. We propose the adaptive (N+M)-tuplet clusters loss function and optimize it with the softmax loss simultaneously in the training phrase. The variations introduced by personal attributes are alleviated using the similarity measurements of multiple samples in the feature space with many fewer comparison times as conventional deep metric learning approaches, which enables the metric calculations for large data applications (e.g., videos). Both the spatial and temporal relations are well explored by a unified framework that consists of an Inception-ResNet network with long short term memory and the two fully connected layer branches structure. Our proposed method has been evaluated with three well-known databases, and the experimental results show that our method outperforms many state-of-the-art approaches.

Reinforcement Learning Based on the Bayesian Theorem for Electricity Markets Decision Support

DEFF Research Database (Denmark)

Sousa, Tiago; Pinto, Tiago; Praca, Isabel

2014-01-01

This paper presents the applicability of a reinforcement learning algorithm based on the application of the Bayesian theorem of probability. The proposed reinforcement learning algorithm is an advantageous and indispensable tool for ALBidS (Adaptive Learning strategic Bidding System), a multi...

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