Toward Development of Distance Learning Environment in the Grid

ERIC Educational Resources Information Center

Li, Kuan-Ching; Tsai, Yin-Te; Tsai, Chuan-Ko

2008-01-01

In recent years, with the rapid development of communication and network technologies, distance learning has been popularized and it became one of the most well-known teaching methods, due to its practicability. Over the Internet, learners are free to access new knowledge without restrictions on time or location. However, current distance learning…

Collaborative Learning: A Critical Success Factor in Distance Education.

ERIC Educational Resources Information Center

Levin, David S.; Ben-Jacob, Marion G.

This paper discusses the use of new technologies for distance learning-- including interactive video, computers, and the Internet-- at Mercy College (New York) and DePaul University (Illinois). The description of a course on discrete mathematics that is taught using the Mercy College Long-distance Instructional Network (MerLIN) focuses on the use…

Multimedia and the Future of Distance Learning Technology.

ERIC Educational Resources Information Center

Barnard, John

1992-01-01

Describes recent innovations in distance learning technology, including the use of video technology; personal computers, including computer conferencing, computer-mediated communication, and workstations; multimedia, including hypermedia; Integrated Services Digital Networks (ISDN); and fiber optics. Research implications for multimedia and…

Modeling positional effects of regulatory sequences with spline transformations increases prediction accuracy of deep neural networks

PubMed Central

Avsec, Žiga; Cheng, Jun; Gagneur, Julien

2018-01-01

Abstract Motivation Regulatory sequences are not solely defined by their nucleic acid sequence but also by their relative distances to genomic landmarks such as transcription start site, exon boundaries or polyadenylation site. Deep learning has become the approach of choice for modeling regulatory sequences because of its strength to learn complex sequence features. However, modeling relative distances to genomic landmarks in deep neural networks has not been addressed. Results Here we developed spline transformation, a neural network module based on splines to flexibly and robustly model distances. Modeling distances to various genomic landmarks with spline transformations significantly increased state-of-the-art prediction accuracy of in vivo RNA-binding protein binding sites for 120 out of 123 proteins. We also developed a deep neural network for human splice branchpoint based on spline transformations that outperformed the current best, already distance-based, machine learning model. Compared to piecewise linear transformation, as obtained by composition of rectified linear units, spline transformation yields higher prediction accuracy as well as faster and more robust training. As spline transformation can be applied to further quantities beyond distances, such as methylation or conservation, we foresee it as a versatile component in the genomics deep learning toolbox. Availability and implementation Spline transformation is implemented as a Keras layer in the CONCISE python package: https://github.com/gagneurlab/concise. Analysis code is available at https://github.com/gagneurlab/Manuscript_Avsec_Bioinformatics_2017. Contact avsec@in.tum.de or gagneur@in.tum.de Supplementary information Supplementary data are available at Bioinformatics online. PMID:29155928

Planning the Networking of ODL Institutions for Establishing Integrated Distance Education System in India

ERIC Educational Resources Information Center

Khanna, Pankaj; Basak, P. C.

2011-01-01

It is proposed to establish an Integrated Distance Education System in India by designing modern technology based information communication network, connecting all its ODL (Open and Distance Learning) institutions to the headquarters of the ODL system in India. The principle roles to be performed by such a system have been discussed; according to…

The Role of the Australian Open Learning Information Network.

ERIC Educational Resources Information Center

Bishop, Robin; And Others

Three documents are presented which describe the Australian Open Learning Information Network (AOLIN)--a national, independent, and self-supporting network of educational researchers with a common interest in the use of information technology for open and distance education--and discuss two evaluative studies undertaken by the organization. The…

Developing Strategies for Networked Education.

ERIC Educational Resources Information Center

Peregoy, Richard; Kroder, Stanley

2000-01-01

Assesses the strengths, weaknesses, opportunities and threats (SWOT) of the distance learning approach to education, and discusses how one institution, the University of Dallas Graduate School of Management, has developed a progressively expanding networked distance education program. Includes quotes from three students that suggest the quality of…

Disrupting the Implementation Gap with Digital Technology in Healthcare Distance Education: Critical Insights from an e-Mentoring Intensional Network Practitioner Research Project

ERIC Educational Resources Information Center

Singh, Gurmit

2013-01-01

Effective professional distance education is urgently needed to develop a well-trained workforce and improve impact on healthcare. However, distance education initiatives have had mixed results in improving practice. Often, successful implementation fails to leverage insights on the social and emergent nature of learning in networks. This paper…

Wishart Deep Stacking Network for Fast POLSAR Image Classification.

PubMed

Jiao, Licheng; Liu, Fang

2016-05-11

Inspired by the popular deep learning architecture - Deep Stacking Network (DSN), a specific deep model for polarimetric synthetic aperture radar (POLSAR) image classification is proposed in this paper, which is named as Wishart Deep Stacking Network (W-DSN). First of all, a fast implementation of Wishart distance is achieved by a special linear transformation, which speeds up the classification of POLSAR image and makes it possible to use this polarimetric information in the following Neural Network (NN). Then a single-hidden-layer neural network based on the fast Wishart distance is defined for POLSAR image classification, which is named as Wishart Network (WN) and improves the classification accuracy. Finally, a multi-layer neural network is formed by stacking WNs, which is in fact the proposed deep learning architecture W-DSN for POLSAR image classification and improves the classification accuracy further. In addition, the structure of WN can be expanded in a straightforward way by adding hidden units if necessary, as well as the structure of the W-DSN. As a preliminary exploration on formulating specific deep learning architecture for POLSAR image classification, the proposed methods may establish a simple but clever connection between POLSAR image interpretation and deep learning. The experiment results tested on real POLSAR image show that the fast implementation of Wishart distance is very efficient (a POLSAR image with 768000 pixels can be classified in 0.53s), and both the single-hidden-layer architecture WN and the deep learning architecture W-DSN for POLSAR image classification perform well and work efficiently.

77 FR 27015 - Distance Learning and Telemedicine Grant Program

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-08

... aforementioned Notice, which have been evaluated and scored, represent exemplary projects in their use of telecommunications, computer networks, and related advanced technologies to encourage and improve telemedicine services and distance learning services in rural areas. Only a limited number of these projects, however...

Distance Learning. Transforming Libraries Number 6.

ERIC Educational Resources Information Center

Jones, William G.

1998-01-01

This report explores the diverse ways that libraries are currently supporting distance learning, both in its traditional and newer Internet-based forms. Based on interviews with administrators and staff, the following "Reports from the Field" reflect developments in public institutions: "UNET (University of Maine System Network)…

Around the Globe.

ERIC Educational Resources Information Center

Wheeler, Steve

2001-01-01

Provides an overview of current activities in Web-based learning and development in Romania. Discusses promotion of online learning by various societies and institutions; the distance courses based on traditional procedures; problems of the current state of distance education, including shortage of teachers and network administration and poor and…

Oscillatory neural network for pattern recognition: trajectory based classification and supervised learning.

PubMed

Miller, Vonda H; Jansen, Ben H

2008-12-01

Computer algorithms that match human performance in recognizing written text or spoken conversation remain elusive. The reasons why the human brain far exceeds any existing recognition scheme to date in the ability to generalize and to extract invariant characteristics relevant to category matching are not clear. However, it has been postulated that the dynamic distribution of brain activity (spatiotemporal activation patterns) is the mechanism by which stimuli are encoded and matched to categories. This research focuses on supervised learning using a trajectory based distance metric for category discrimination in an oscillatory neural network model. Classification is accomplished using a trajectory based distance metric. Since the distance metric is differentiable, a supervised learning algorithm based on gradient descent is demonstrated. Classification of spatiotemporal frequency transitions and their relation to a priori assessed categories is shown along with the improved classification results after supervised training. The results indicate that this spatiotemporal representation of stimuli and the associated distance metric is useful for simple pattern recognition tasks and that supervised learning improves classification results.

A Managerial Analysis of ATM in Facilitating Distance Education.

ERIC Educational Resources Information Center

Littman, Marlyn Kemper

In this paper, the fundamental characteristics and capabilities of ATM (Asynchronous Transfer Mode) networks in a distance learning environment are examined. Current and projected ATM applications are described, and issues and challenges associated with developing ATM networking solutions for instructional delivery are explored. Other topics…

Improving Audio Quality in Distance Learning Applications.

ERIC Educational Resources Information Center

Richardson, Craig H.

This paper discusses common causes of problems encountered with audio systems in distance learning networks and offers practical suggestions for correcting the problems. Problems and discussions are divided into nine categories: (1) acoustics, including reverberant classrooms leading to distorted or garbled voices, as well as one-dimensional audio…

Remote Teacher Observation at the University of Kentucky

ERIC Educational Resources Information Center

Hager, Karen D.; Baird, Constance M.; Spriggs, Amy D.

2012-01-01

Faculty and staff from three university departments (Special Education, Distance Learning Programs, and Distance Learning Networks) collaborated to develop a system for remote observation of student teachers. Colleges across the campus currently use the system. The development process from inception to implementation is described, and the specific…

Distance Learning and the Future of Kamehameha Schools Bishop Estate.

ERIC Educational Resources Information Center

Meyer, Henry E.

1995-01-01

This article details some of the ways that the Kamehameha Schools Bishop Estate (Hawaii) is dealing with the challenge of education in the computer age, including distance learning, Internet linkups, the Hawaii Educational Wide Area Network, and campus closed-circuit and cable television. (SM)

Exploring the Use of MXit: A Cell-Phone Social Network to Facilitate Learning in Distance Education

ERIC Educational Resources Information Center

Makoe, Mpine

2010-01-01

The aim of this paper is to investigate the pedagogical suitability of using cell phones to enhance learning through social interaction in distance education. Social interaction was used as a conceptual framework to explore the potential for using "MXit"--a cell-phone instant messaging system--to support and enhance learning for distance…

Regulatory Enhancements, Infrastructure Modernization, and Connecticut's Interactive, Distance Learning Network.

ERIC Educational Resources Information Center

Pietras, Jesse John

This paper presents an overview of the regulatory, technological, and economic status of interactive distance learning in Connecticut as it relates to the current and future provisioning of services by the telecommunications and cable television industries. The review is predicated upon the following questions: (1) What obligations should the…

Connecticut's Evolving Interactive Distance Learning Network in the Cable and Telecommunications Industries.

ERIC Educational Resources Information Center

Pietras, Jesse John

This paper describes the state of interactive distance learning in Connecticut, particularly the current and future provision of these services by the telecommunications and cable television industries. The overview examines questions of where obligation and responsibility lie (with schools, local exchange companies, cable franchises, etc.) in…

Teaching Russian Via Distance Learning, the EdNet Experience.

ERIC Educational Resources Information Center

Zsiray, Stephen W., Jr.; And Others

In Utah, the statewide distance education network (EdNet) enables students from five rural and suburban high schools to learn Russian and earn college credits. Courses in Russian are offered through a partnership involving the Cache County School District, Utah State University, and the Utah State Office of Education. Classes are taught on one…

Demonstrating a Web-Design Technique in a Distance-Learning Environment

ERIC Educational Resources Information Center

Zdenek, Sean

2004-01-01

Objective: To lead a brief training session over a distance-learning network. Type of speech: Informative. Point value: 20% of course grade. Requirements: (a) References: Not specified; (b) Length: 15 minutes; (c) Visual aid: Yes; (d) Outline: No; (e) Prerequisite reading: Chapters 12-16, 18 (Bailey, 2002); (f) Additional requirements: None. This…

Doctoral Students' Identity Positioning in Networked Learning Environments

ERIC Educational Resources Information Center

Koole, Marguerite; Stack, Sara

2016-01-01

In this study, the authors explored identity positioning as perceived by doctoral learners in online, networked-learning environments. The study examined two distance doctoral programs at a Canadian university. It was a qualitative study based on methodologies involving open coding and discourse analysis. The social positioning cycle, based on…

Telecommunications, Internationalism, and Distance Education.

ERIC Educational Resources Information Center

Moore, Michael G.

1988-01-01

Discussion of the role of telecommunications in distance education focuses on teleconference networks and international cooperation. Highlights include the TELECON VII Distance Learning Conference, the use of teleconferencing by corporations for continuing education and training, and questions to be addressed concerning the future potential of…

Got Bandwidth?

ERIC Educational Resources Information Center

Villano, Matt

2009-01-01

Video-heavy distance learning programs can put a strain on the campus network. This article describes how three institutions are managing bandwidth to ensure high-quality service for eLearning students.

Pattern classification and recognition of invertebrate functional groups using self-organizing neural networks.

PubMed

Zhang, WenJun

2007-07-01

Self-organizing neural networks can be used to mimic non-linear systems. The main objective of this study is to make pattern classification and recognition on sampling information using two self-organizing neural network models. Invertebrate functional groups sampled in the irrigated rice field were classified and recognized using one-dimensional self-organizing map and self-organizing competitive learning neural networks. Comparisons between neural network models, distance (similarity) measures, and number of neurons were conducted. The results showed that self-organizing map and self-organizing competitive learning neural network models were effective in pattern classification and recognition of sampling information. Overall the performance of one-dimensional self-organizing map neural network was better than self-organizing competitive learning neural network. The number of neurons could determine the number of classes in the classification. Different neural network models with various distance (similarity) measures yielded similar classifications. Some differences, dependent upon the specific network structure, would be found. The pattern of an unrecognized functional group was recognized with the self-organizing neural network. A relative consistent classification indicated that the following invertebrate functional groups, terrestrial blood sucker; terrestrial flyer; tourist (nonpredatory species with no known functional role other than as prey in ecosystem); gall former; collector (gather, deposit feeder); predator and parasitoid; leaf miner; idiobiont (acarine ectoparasitoid), were classified into the same group, and the following invertebrate functional groups, external plant feeder; terrestrial crawler, walker, jumper or hunter; neustonic (water surface) swimmer (semi-aquatic), were classified into another group. It was concluded that reliable conclusions could be drawn from comparisons of different neural network models that use different distance (similarity) measures. Results with the larger consistency will be more reliable.

Problems of Implementing SCORM in an Enterprise Distance Learning Architecture: SCORM Incompatibility across Multiple Web Domains.

ERIC Educational Resources Information Center

Engelbrecht, Jeffrey C.

2003-01-01

Delivering content to distant users located in dispersed networks, separated by firewalls and different web domains requires extensive customization and integration. This article outlines some of the problems of implementing the Sharable Content Object Reference Model (SCORM) in the Marine Corps' Distance Learning System (MarineNet) and extends…

Improving Students' Educational Experience by Harnessing Digital Technology: elgg in the ODL Environment

ERIC Educational Resources Information Center

Tung, Lai Cheng

2013-01-01

Given the rising popularity of both open and distance learning (ODL) and social networking tools, it seems logical to merge and harness these two popular technologies with the goal of improving student educational experience. The integration seems to hold tremendous promise for the open and distance learning mode. To reduce the gap in the…

A Review of MS-DOS Bulletin Board Software Suitable for Long Distance Learning.

ERIC Educational Resources Information Center

Sessa, Anneliese

This paper describes the advantages of using computer bulletin boards systems (BBS) for distance learning, including the use of the New York City Education Network (NYCENET) to access various databases and to communicate with individuals or the public. Questions to be answered in order to determine the most appropriate software for running a BBS…

Acceptability of an Asynchronous Learning Forum on Mobile Devices

ERIC Educational Resources Information Center

Chang, Chih-Kai

2010-01-01

Mobile learning has recently become noteworthy because mobile devices have become popular. To construct an asynchronous learning forum on mobile devices is important because an asynchronous learning forum is always an essential part of networked asynchronous distance learning. However, the input interface in handheld learning devices, which is…

Around the Globe.

ERIC Educational Resources Information Center

Wheeler, Steve

2001-01-01

Presents a report by Rigmor Sterner (Lulea University of Technology) on the 10th annual European Distance Education Network (EDEN) conference (June 10-13, 2001, Stockholm, Sweden). EDEN is a non-governmental educational association whose aim is to foster the development of open and distance learning and distance education. (AEF)

Distance Learning and Cloud Computing: "Just Another Buzzword or a Major E-Learning Breakthrough?"

ERIC Educational Resources Information Center

Romiszowski, Alexander J.

2012-01-01

"Cloud computing is a model for the enabling of ubiquitous, convenient, and on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and other services) that can be rapidly provisioned and released with minimal management effort or service provider interaction." This…

Information Resources Usage in Project Management Digital Learning System

ERIC Educational Resources Information Center

Davidovitch, Nitza; Belichenko, Margarita; Kravchenko, Yurii

2017-01-01

The article combines a theoretical approach to structuring knowledge that is based on the integrated use of fuzzy semantic network theory predicates, Boolean functions, theory of complexity of network structures and some practical aspects to be considered in the distance learning at the university. The paper proposes a methodological approach that…

Usefulness of an Internet-based thematic learning network: comparison of effectiveness with traditional teaching.

PubMed

Coma Del Corral, María Jesús; Guevara, José Cordero; Luquin, Pedro Abáigar; Peña, Horacio J; Mateos Otero, Juan José

2006-03-01

UniNet is an Internet-based thematic network for a virtual community of users (VCU). It supports one multidisciplinary community of doctoral students, who receive most of the courses on the network. The evident advantages of distance learning by Internet, in terms of costs, comfort, etc., require a previous evaluation of the system, focusing on the learning outcomes of the student. The aim was to evaluate the real learning of the students of doctorate courses, by comparing the effectiveness of distance learning in UniNet with traditional classroom-based teaching. Five doctorate courses were taught simultaneously to two independent groups of students in two ways: one, through the UniNet Network, and the other in a traditional classroom. The academic knowledge of students was evaluated at the beginning and end of each course. The difference in score was considered as a knowledge increase. The comparison was made using Student's t-test for independent groups. There were no significant statistical differences in the outcomes of the two groups of students. This suggests that both teaching systems were equivalent in increasing the knowledge of the students. Both educational methods, the traditional system and the online system in a thematic network, are effective and similar for increasing knowledge.

Enhancing the Internationalisation of Distance Education in the Biological Sciences: The DUNE Project and Genetic Engineering.

ERIC Educational Resources Information Center

Leach, C. K.; And Others

1997-01-01

Describes the Distance Educational Network of Europe (DUNE) project that aims at enhancing the development of distance education in an international context. Highlights issues relating to the delivery of distance-learning courses in a transnational forum. Describes the genetic engineering course that aims at explaining the core techniques of…

How do general practice residents use social networking sites in asynchronous distance learning?

PubMed

Maisonneuve, Hubert; Chambe, Juliette; Lorenzo, Mathieu; Pelaccia, Thierry

2015-09-21

Blended learning environments - involving both face-to-face and remote interactions - make it easier to adapt learning programs to constraints such as residents' location and low teacher-student ratio. Social networking sites (SNS) such as Facebook®, while not originally intended to be used as learning environments, may be adapted for the distance-learning part of training programs. The purpose of our study was to explore the use of SNS for asynchronous distance learning in a blended learning environment as well as its influence on learners' face-to-face interactions. We conducted a qualitative study and carried out semi-structured interviews. We performed purposeful sampling for maximal variation to include eight general practice residents in 2(nd) and 3(rd) year training. A thematic analysis was performed. The social integration of SNS facilitates the engagement of users in their learning tasks. This may also stimulate students' interactions and group cohesion when members meet up in person. Most of the general practice residents who work in the blended learning environment we studied had a positive appraisal on their use of SNS. In particular, we report a positive impact on their engagement in learning and their participation in discussions during face-to-face instruction. Further studies are needed in order to evaluate the effectiveness of SNS in blended learning environments and the appropriation of SNS by teachers.

Telematic Infrastructures for Flexible and Distance Learning "Electronic Universities." A Report from DELTA Workshops on Telematic Networks for Distance Education and Training "Electronic Universities" and on Learning Technology (October 1990, November 1990).

ERIC Educational Resources Information Center

Moller, Morten, Ed.; Shaughnessy, Haydn, Ed.

This report is based on contributions to two workshops arranged jointly by Task Force Human Resources and the DELTA (Developing European Learning through Technological Advance) Unit. The purpose of collecting these papers was to provide an overview of the implications of the DELTA Exploratory Action outcomes for future research. After the preface…

Autofocusing in digital holography using deep learning

NASA Astrophysics Data System (ADS)

Ren, Zhenbo; Xu, Zhimin; Lam, Edmund Y.

2018-02-01

In digital holography, it is critical to know the distance in order to reconstruct the multi-sectional object. This autofocusing is traditionally solved by reconstructing a stack of in-focus and out-of-focus images and using some focus metric, such as entropy or variance, to calculate the sharpness of each reconstructed image. Then the distance corresponding to the sharpest image is determined as the focal position. This method is effective but computationally demanding and time-consuming. To get an accurate estimation, one has to reconstruct many images. Sometimes after a coarse search, a refinement is needed. To overcome this problem in autofocusing, we propose to use deep learning, i.e., a convolutional neural network (CNN), to solve this problem. Autofocusing is viewed as a classification problem, in which the true distance is transferred as a label. To estimate the distance is equated to labeling a hologram correctly. To train such an algorithm, totally 1000 holograms are captured under the same environment, i.e., exposure time, incident angle, object, except the distance. There are 5 labels corresponding to 5 distances. These data are randomly split into three datasets to train, validate and test a CNN network. Experimental results show that the trained network is capable of predicting the distance without reconstructing or knowing any physical parameters about the setup. The prediction time using this method is far less than traditional autofocusing methods.

A position paper of the EFLM Committee on Education and Training and Working Group on Distance Education Programmes/E-Learning: developing an e-learning platform for the education of stakeholders in laboratory medicine.

PubMed

Gruson, Damien; Faure, Gilbert; Gouget, Bernard; Haliassos, Alexandre; Kisikuchin, Darya; Reguengo, Henrique; Topic, Elizabeta; Blaton, Victor

2013-04-01

The progress of information and communication technologies has strongly influenced changes in healthcare and laboratory medicine. E-learning, the learning or teaching through electronic means, contributes to the effective knowledge translation in medicine and healthcare, which is an essential element of a modern healthcare system and for the improvement of patient care. E-learning also represents a great vector for the transfer knowledge into laboratory practice, stimulate multidisciplinary interactions, enhance continuing professional development and promote laboratory medicine. The European Federation of Laboratory Medicine (EFLM) has initiated a distance learning program and the development of a collaborative network for e-learning. The EFLM dedicated working group encourages the organization of distance education programs and e-learning courses as well as critically evaluate information from courses, lectures and documents including electronic learning tools. The objectives of the present paper are to provide some specifications for distance learning and be compatible with laboratory medicine practices.

Collaborative Learning in Advanced Supply Systems: The KLASS Pilot Project.

ERIC Educational Resources Information Center

Rhodes, Ed; Carter, Ruth

2003-01-01

The Knowledge and Learning in Advanced Supply Systems (KLASS) project developed collaborative learning networks of suppliers in the British automotive and aerospace industries. Methods included face-to-face and distance learning, work toward National Vocational Qualifications, and diagnostic workshops for senior managers on improving quality,…

ATM: The Key To Harnessing the Power of Networked Multimedia.

ERIC Educational Resources Information Center

Gross, Rod

1996-01-01

ATM (Asynchronous Transfer Mode) network technology handles the real-time continuous traffic flow necessary to support desktop multimedia applications. Describes network applications already used: desktop video collaboration, distance learning, and broadcasting video delivery. Examines the architecture of ATM technology, video delivery and sound…

Competitive STDP Learning of Overlapping Spatial Patterns.

PubMed

Krunglevicius, Dalius

2015-08-01

Spike-timing-dependent plasticity (STDP) is a set of Hebbian learning rules firmly based on biological evidence. It has been demonstrated that one of the STDP learning rules is suited for learning spatiotemporal patterns. When multiple neurons are organized in a simple competitive spiking neural network, this network is capable of learning multiple distinct patterns. If patterns overlap significantly (i.e., patterns are mutually inclusive), however, competition would not preclude trained neuron's responding to a new pattern and adjusting synaptic weights accordingly. This letter presents a simple neural network that combines vertical inhibition and Euclidean distance-dependent synaptic strength factor. This approach helps to solve the problem of pattern size-dependent parameter optimality and significantly reduces the probability of a neuron's forgetting an already learned pattern. For demonstration purposes, the network was trained for the first ten letters of the Braille alphabet.

A Technology Primer for Distance Educators.

ERIC Educational Resources Information Center

Wagner, Ellen D.

An introduction to instructional technology systems used for distance learning applications is provided, with a compilation of technical information in straightforward terms. Broadcast communications theory is discussed, and several models of communications are considered, including transport mechanics and network facilities. The most prevalent…

Social Networking Sites as Communication, Interaction, and Learning Environments: Perceptions and Preferences of Distance Education Students

ERIC Educational Resources Information Center

Bozkurt, Aras; Karadeniz, Abdulkadir; Kocdar, Serpil

2017-01-01

The advent of Web 2.0 technologies transformed online networks into interactive spaces in which user-generated content has become the core material. With the possibilities that emerged from Web 2.0, social networking sites became very popular. The capability of social networking sites promises opportunities for communication and interaction,…

The Hospital Satellite Network. A National/International Perspective.

ERIC Educational Resources Information Center

Linder, Ronald L.

1985-01-01

Describes how continuing distance education through satellite transmitted-television can help health service professionals, and how such networks operate. The development of such a program is described, including audience, title, learning objectives, program text, and onsite instructional materials. (CT)

Development of a Distance Education Network in the OECS. Feasibility Study. Filling a Gap in a Way that Makes Sense. Report of a Consultancy to the Commonwealth of Learning.

ERIC Educational Resources Information Center

Roberts, Judy

A study was conducted to determine the feasibility of a distance education network in the Eastern Caribbean. Two types of consultations were completed: a brief site survey of four Eastern Caribbean states (Grenada, Dominica, Antigua, and Saint Lucia) and a workshop in Saint Lucia to which education officials from government agencies and higher…

Ontology-Based Multimedia Authoring Tool for Adaptive E-Learning

ERIC Educational Resources Information Center

Deng, Lawrence Y.; Keh, Huan-Chao; Liu, Yi-Jen

2010-01-01

More video streaming technologies supporting distance learning systems are becoming popular among distributed network environments. In this paper, the authors develop a multimedia authoring tool for adaptive e-learning by using characterization of extended media streaming technologies. The distributed approach is based on an ontology-based model.…

The Slothfulness Quotient.

ERIC Educational Resources Information Center

Joyce, Peter J.

2001-01-01

E-Learning eliminates time and distance barriers, creating universal learning-on-demand opportunities. Cisco Systems has invested over $50 million in the world's largest e-learning laboratory. Starting with 64 academies in 7 U.S. states in 1997, the Networking Academy program now serves 140,000 students in over 5,800 sites in 96 countries. (MLH)

A Survey of Student Attitudes on the Use of Social Networking to Build Learning Communities

ERIC Educational Resources Information Center

Arndt, Timothy

2012-01-01

Post-secondary students are increasingly receiving instruction by distance learning. This mode of learning can result in the students learning in isolation, with bad results in learning outcomes. The same type of isolation can occur for part-time students and those who are working while taking classes. In such circumstances, we believe that it…

Technology-Mediated Open and Distance Education for Agricultural Education and Improved Livelihoods in Sub-Saharan Africa. Country Case Studies

ERIC Educational Resources Information Center

Alluri, Krishna, Ed.; Zachmann, Rainer, Ed.

2008-01-01

The Learning for Livelihoods Sector of the Commonwealth of Learning (COL) addresses the major challenges related to learning and skills development that are key for living and for improvement of livelihoods. Developing conceptual frameworks, influencing policy, enabling technology-mediated learning, and strengthening networks and partnerships are…

7 CFR 1942.306 - Purposes of grants.

Code of Federal Regulations, 2012 CFR

2012-01-01

... importance to farmers and rural residents. (10) Create, expand, and operate rural distance learning networks or rural learning programs, that provide educational instruction or job training instruction related...-COOPERATIVE SERVICE, RURAL UTILITIES SERVICE, AND FARM SERVICE AGENCY, DEPARTMENT OF AGRICULTURE (CONTINUED...

7 CFR 1942.306 - Purposes of grants.

Code of Federal Regulations, 2013 CFR

2013-01-01

... importance to farmers and rural residents. (10) Create, expand, and operate rural distance learning networks or rural learning programs, that provide educational instruction or job training instruction related...-COOPERATIVE SERVICE, RURAL UTILITIES SERVICE, AND FARM SERVICE AGENCY, DEPARTMENT OF AGRICULTURE (CONTINUED...

7 CFR 1942.306 - Purposes of grants.

Code of Federal Regulations, 2014 CFR

2014-01-01

... importance to farmers and rural residents. (10) Create, expand, and operate rural distance learning networks or rural learning programs, that provide educational instruction or job training instruction related...-COOPERATIVE SERVICE, RURAL UTILITIES SERVICE, AND FARM SERVICE AGENCY, DEPARTMENT OF AGRICULTURE (CONTINUED...

7 CFR 1942.306 - Purposes of grants.

Code of Federal Regulations, 2011 CFR

2011-01-01

...-COOPERATIVE SERVICE, RURAL UTILITIES SERVICE, AND FARM SERVICE AGENCY, DEPARTMENT OF AGRICULTURE (CONTINUED... importance to farmers and rural residents. (10) Create, expand, and operate rural distance learning networks or rural learning programs, that provide educational instruction or job training instruction related...

And They're Off! The Race to Fiber Optics.

ERIC Educational Resources Information Center

Lewis, Joan E.

1993-01-01

Describes fiber optic technology and discusses its use in distance learning and educational reform. Highlights include the quality of communications transmission systems; costs; Federal Communications Commission rules and regulations; cable television; networks, including the National Research and Education Network (NREN); government versus…

Use of webboards for distance learning: a physical therapy model.

PubMed

Teyhen, D S; Flynn, T; Allison, S

2001-04-01

In today's world of ever-increasing knowledge and technology, mastering the use of information is critical for success. U.S. Army physical therapists have successfully used the Knowledge Management Network as a tool to foster communication, education, and training. The model outlined in this article can serve both as a model for promoting distance learning and as a success story of how to merge today's technology with the medical community to improve productivity and communication.

Study on the Implementation of Interaction Teaching Mode in Distance Education

ERIC Educational Resources Information Center

Zhou, Chunyu; Xu, Zhenhui

2015-01-01

By analyzing the learning characteristics of learners and the features of interactive teaching in distance education, this paper proposes the curriculum implementation subject of network education, namely objects multi-directional interaction teaching mode, so as to improve teaching effectiveness and achieve teaching objectives to ensure the…

Telemedicine in Western Africa: lessons learned from a pilot project in Mali, perspectives and recommendations.

PubMed

Geissbuhler, Antoine; Ly, Ousmane; Lovis, Christian; L'Haire, Jean-François

2003-01-01

to evaluate the feasibility, potential and risks of an internet-based telemedicine network in developing countries of Western Africa. a project for the development of a national telemedicine network in Mali was initiated in 2001, using internet-based technologies for distance learning and teleconsultations. the telemedicine network has been in productive use for 12 months and has enabled various collaboration channels, including North-South, South-South, and South-North distance learning and teleconsultations. It also unveiled a set of potential problems: a) limited pertinence of North-South collaborations when there are major differences in available resources or socio-cultural contexts between the collaborating parties; b) risk of induced digital divide if the periphery of the health system is not involved in the development of the network, and c) need for the development of local medical contents management skills. the identified risks must be taken into account when designing large-scale telemedicine projects in developing countries and can be mitigated by the fostering of South-South collaboration channels, the use of satellite-based internet connectivity in remote areas, and the valorization of local knowledge and its publication on-line.

Computer Networks as Instructional and Collaborative Distance Learning Environments.

ERIC Educational Resources Information Center

Schrum, Lynne; Lamb, Theodore A.

1997-01-01

Reports on the early stages of a project at the U.S. Air Force Academy, in which the instructional applications of a networked classroom laboratory, an intranet, and the Internet are explored as well as the effectiveness and efficiency of groupware and computer networks as instructional environments. Presents the results of the first pilot tests.…

Emerging Trends in the Development of School Networking Initiatives. Perspectives on Distance Education

ERIC Educational Resources Information Center

Naidoo, Vis, Ed.; Ramzy, Heba, Ed.

2004-01-01

This collection of research and case studies provides snapshots of developments in school networking in seven regions of the world, and focuses on the variety of school networking models that have emerged in different regions and the resulting trends and issues that need to be considered in terms of supporting the learning, teaching, management…

Exploring the Role of Distributed Learning in Distance Education at Allama Iqbal Open University: Academic Challenges at Postgraduate Level

ERIC Educational Resources Information Center

Bukhsh, Qadir; Chaudhary, Muhammad Ajmal

2015-01-01

Distributed learning is derived from the concept of distributed resources. Different institutions around the globe connected through network and the learners are diverse, located in the different cultures and communities. Distributed learning provides global standards of quality to all learners through synchronous and asynchronous communications…

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

ERIC Educational Resources Information Center

Ahmed, Iftikhar; Sadeq, Muhammad Jafar

2006-01-01

Current distance learning systems are increasingly packing highly data-intensive contents on servers, resulting in the congestion of network and server resources at peak service times. A distributed learning system based on faded information field (FIF) architecture that employs mobile agents (MAs) has been proposed and simulated in this work. The…

Past, Present, and Future Trends in Teaching Clinical Skills through Web-Based Learning Environments

ERIC Educational Resources Information Center

Coe Regan, Jo Ann R.; Youn, Eric J.

2008-01-01

Distance education in social work has grown significantly due to the use of interactive television and computer networks. Given the recent developments in delivering distance education utilizing Web-based technology, this article presents a literature review focused on identifying generational trends in the development of Web-based learning…

Distance Learner Ecologies of the University of the West Indies Open Campus Program

ERIC Educational Resources Information Center

Beaubrun, Elizabeth

2012-01-01

This research project examined the learner ecologies of University of the West Indies (UWI) distance learning program participants in two countries within the regional university's network: Dominica, and Antigua and Barbuda. The descriptive study focused on a period of transition from dual-mode delivery (teleconference and in-person tutorial…

The Organization of the Distance Teaching Sub-System in an Open University.

ERIC Educational Resources Information Center

Chacon, Fabio J.

The problem of finding an adequate organization for the distance teaching subsystem in the Open University of Venezuela (Universidad Nacional Abierta) is analyzed. Problems facing this subsystem concern: communications with the headquarters and within the learning centers network, interaction with the environment in order to create a favorable…

State Network Utilization Study: Mississippi Educational Television.

ERIC Educational Resources Information Center

Wilson, Savan; And Others

This document is the result of a utilization study of Mississippi Educational Television where 27 target audiences were identified and surveyed. The following information is included: a draft of and updated state network utilization studies; planning and management strategies; a profile of the survey populations; a distance learning survey report;…

Telepractice: Creating a Statewide Network of Support in Rural Maine

ERIC Educational Resources Information Center

Hopkins, Karen; Keefe, Barbara; Bruno, Angela

2012-01-01

The Maine Educational Center for the Deaf and Hard of Hearing's (MECDHH's) "POINT" (Providing Opportunities for Integrating New Technologies) project is implementing a telepractice, distance learning collaborative in Maine with eight hub sites and 18 end points using Tandberg videoconferencing technology. This network is planned to be a…

Teacher Education and Change: The First Decade of IT.

ERIC Educational Resources Information Center

Gwyn, Rhys

1988-01-01

The convergence of computer technology with telecommunications may transform our concept of classroom and school. The PLUTO Network Project, which links several countries in Europe in a collaborative distance learning network, is described. Three phases in the growth of educational uses of computer technologies are outlined. (IAH)

Advances in Computer-Supported Learning

ERIC Educational Resources Information Center

Neto, Francisco; Brasileiro, Francisco

2007-01-01

The Internet and growth of computer networks have eliminated geographic barriers, creating an environment where education can be brought to a student no matter where that student may be. The success of distance learning programs and the availability of many Web-supported applications and multimedia resources have increased the effectiveness of…

Learning with Security

ERIC Educational Resources Information Center

Jokela, Paivi; Karlsudd, Peter

2007-01-01

The current higher education, both distance education and traditional campus courses, relies more and more on modern information and communication technologies (ICT). The use of computer systems and networks results in a wide range of security issues that must be dealt with in order to create a safe learning environment. In this work, we study the…

"We're living what we're learning": student perspectives in distance learning degree and certificate programs in public health.

PubMed

Cannon, M M; Umble, K E; Steckler, A; Shay, S

2001-01-01

The authors used surveys and interviews to study participants' motivations for enrolling and perceptions of the weaknesses and strengths of two distance learning programs administered by the University of North Carolina at Chapel Hill School of Public Health (SPH): the MPH in Public Health Leadership and a certificate program organized collaboratively with the Mahidol University SPH in Thailand. Chief motivations were career advancement, job performance improvement, convenience, and obtaining a degree from a reputable institution. Strengths included the curriculum, networking opportunities, and administrative and technical support. Concerns included quality of interaction with faculty and instructional methods.

The Loneliness of the Long-Distance Learner: Social Networking and Student Support. A Case Study of the Distance-Learning MA in Translation at Bristol University

ERIC Educational Resources Information Center

Duranton, Helene; Mason, Adrienne

2012-01-01

Using the translation programme at the University of Bristol as a case study, we shall argue in this paper that distance delivery can have a very positive impact on recruitment but that the quality of the students' experience depends upon the capacity of the organisation to support course development and delivery, both in terms of instructional…

American Government: An Introduction Using MicroCase with Distance Learners.

ERIC Educational Resources Information Center

Rosberg, William H.

In spring 1997, a project used MicroCase, a computer-based statistical analysis and data retrieval system, to offer an American Government class to distance students at Iowa's Kirkwood Community College (KCC). Students participated in the course at one of the college's 10 learning centers via a statewide fiber-optic network. MicroCase provided the…

The Roles That Librarians and Libraries Play in Distance Education Settings

ERIC Educational Resources Information Center

Corbett, Amanda; Brown, Abbie

2015-01-01

This article explores the literature that focuses on the various roles librarians and libraries play in distance education settings. Learners visit libraries either in person or via networked computing technology to ask for help with their online courses. Questions range from how to upload a document with a learning management system, to how to…

Computers as Media for Communication: Learning and Development in a Whole Earth Context.

ERIC Educational Resources Information Center

Levin, James A.

Educationally successful electronic network activities involving microcomputers and long-distance networks include a student newswire, joint social science projects, and joint science projects. A newswire activity, such as "The Computer Chronicles," can provide a wide range of audiences for writing, a functional environment for reading, and a…

Teleassessment: A Model for Team Developmental Assessment of High-Risk Infants Using a Televideo Network.

ERIC Educational Resources Information Center

Smith, Douglas L.

1997-01-01

Describes a model for team developmental assessment of high-risk infants using a fiber-optic "distance learning" televideo network in south-central New York. An arena style transdisciplinary play-based assessment model was adapted for use across the televideo connection and close simulation of convention assessment procedures was…

Global Rural Autism Asperger Information Network: A Distance Learning Inservice Training Program.

ERIC Educational Resources Information Center

Bock, Marjorie A.; Swinney, Lori; Smart, Kathy

The University of North Dakota's Global Rural Autism Asperger Information Network (GRAAIN) provides a special graduate certificate program in Autistic Spectrum Disorder (ASD) consisting of six online courses. The program started over 4 years ago as a pilot program to provide specialized ASD training to educators and personnel serving children with…

View-invariant gait recognition method by three-dimensional convolutional neural network

NASA Astrophysics Data System (ADS)

Xing, Weiwei; Li, Ying; Zhang, Shunli

2018-01-01

Gait as an important biometric feature can identify a human at a long distance. View change is one of the most challenging factors for gait recognition. To address the cross view issues in gait recognition, we propose a view-invariant gait recognition method by three-dimensional (3-D) convolutional neural network. First, 3-D convolutional neural network (3DCNN) is introduced to learn view-invariant feature, which can capture the spatial information and temporal information simultaneously on normalized silhouette sequences. Second, a network training method based on cross-domain transfer learning is proposed to solve the problem of the limited gait training samples. We choose the C3D as the basic model, which is pretrained on the Sports-1M and then fine-tune C3D model to adapt gait recognition. In the recognition stage, we use the fine-tuned model to extract gait features and use Euclidean distance to measure the similarity of gait sequences. Sufficient experiments are carried out on the CASIA-B dataset and the experimental results demonstrate that our method outperforms many other methods.

Ring-push metric learning for person reidentification

NASA Astrophysics Data System (ADS)

He, Botao; Yu, Shaohua

2017-05-01

Person reidentification (re-id) has been widely studied because of its extensive use in video surveillance and forensics applications. It aims to search a specific person among a nonoverlapping camera network, which is highly challenging due to large variations in the cluttered background, human pose, and camera viewpoint. We present a metric learning algorithm for learning a Mahalanobis distance for re-id. Generally speaking, there exist two forces in the conventional metric learning process, one pulling force that pulls points of the same class closer and the other pushing force that pushes points of different classes as far apart as possible. We argue that, when only a limited number of training data are given, forcing interclass distances to be as large as possible may drive the metric to overfit the uninformative part of the images, such as noises and backgrounds. To alleviate overfitting, we propose the ring-push metric learning algorithm. Different from other metric learning methods that only punish too small interclass distances, in the proposed method, both too small and too large inter-class distances are punished. By introducing the generalized logistic function as the loss, we formulate the ring-push metric learning as a convex optimization problem and utilize the projected gradient descent method to solve it. The experimental results on four public datasets demonstrate the effectiveness of the proposed algorithm.

Understanding Knowledge-Sharing Breakdowns: A Meeting of the Quantitative and Qualitative Minds

ERIC Educational Resources Information Center

Soller, Amy

2004-01-01

The rapid advance of distance learning and networking technology has enabled universities and corporations to reach out and educate students across time and space barriers. Although this technology enables structured collaborative learning activities, online groups often do not enjoy the same benefits as face-to-face learners, and their…

Learning in the model space for cognitive fault diagnosis.

PubMed

Chen, Huanhuan; Tino, Peter; Rodan, Ali; Yao, Xin

2014-01-01

The emergence of large sensor networks has facilitated the collection of large amounts of real-time data to monitor and control complex engineering systems. However, in many cases the collected data may be incomplete or inconsistent, while the underlying environment may be time-varying or unformulated. In this paper, we develop an innovative cognitive fault diagnosis framework that tackles the above challenges. This framework investigates fault diagnosis in the model space instead of the signal space. Learning in the model space is implemented by fitting a series of models using a series of signal segments selected with a sliding window. By investigating the learning techniques in the fitted model space, faulty models can be discriminated from healthy models using a one-class learning algorithm. The framework enables us to construct a fault library when unknown faults occur, which can be regarded as cognitive fault isolation. This paper also theoretically investigates how to measure the pairwise distance between two models in the model space and incorporates the model distance into the learning algorithm in the model space. The results on three benchmark applications and one simulated model for the Barcelona water distribution network confirm the effectiveness of the proposed framework.

A distance constrained synaptic plasticity model of C. elegans neuronal network

NASA Astrophysics Data System (ADS)

Badhwar, Rahul; Bagler, Ganesh

2017-03-01

Brain research has been driven by enquiry for principles of brain structure organization and its control mechanisms. The neuronal wiring map of C. elegans, the only complete connectome available till date, presents an incredible opportunity to learn basic governing principles that drive structure and function of its neuronal architecture. Despite its apparently simple nervous system, C. elegans is known to possess complex functions. The nervous system forms an important underlying framework which specifies phenotypic features associated to sensation, movement, conditioning and memory. In this study, with the help of graph theoretical models, we investigated the C. elegans neuronal network to identify network features that are critical for its control. The 'driver neurons' are associated with important biological functions such as reproduction, signalling processes and anatomical structural development. We created 1D and 2D network models of C. elegans neuronal system to probe the role of features that confer controllability and small world nature. The simple 1D ring model is critically poised for the number of feed forward motifs, neuronal clustering and characteristic path-length in response to synaptic rewiring, indicating optimal rewiring. Using empirically observed distance constraint in the neuronal network as a guiding principle, we created a distance constrained synaptic plasticity model that simultaneously explains small world nature, saturation of feed forward motifs as well as observed number of driver neurons. The distance constrained model suggests optimum long distance synaptic connections as a key feature specifying control of the network.

Analysing Interactions in a Teacher Network Forum: A Sociometric Approach

ERIC Educational Resources Information Center

Lisboa, Eliana Santana; Coutinho, Clara Pereira

2013-01-01

This article presents the sociometric analysis of the interactions in a forum of a social network created for the professional development of Portuguese-speaking teachers. The main goal of the forum, which was titled Stricto Sensu, was to discuss the educational value of programmes that joined the distance learning model in Brazil. The empirical…

Learning deep features with adaptive triplet loss for person reidentification

NASA Astrophysics Data System (ADS)

Li, Zhiqiang; Sang, Nong; Chen, Kezhou; Gao, Changxin; Wang, Ruolin

2018-03-01

Person reidentification (re-id) aims to match a specified person across non-overlapping cameras, which remains a very challenging problem. While previous methods mostly focus on feature extraction or metric learning, this paper makes the attempt in jointly learning both the global full-body and local body-parts features of the input persons with a multichannel convolutional neural network (CNN) model, which is trained by an adaptive triplet loss function that serves to minimize the distance between the same person and maximize the distance between different persons. The experimental results show that our approach achieves very promising results on the large-scale Market-1501 and DukeMTMC-reID datasets.

Learning and Digital Environment of Dance--The Case of Greek Traditional Dance in Youtube

ERIC Educational Resources Information Center

Gratsiouni, Dimitra; Koutsouba, Maria; Venetsanou, Foteini; Tyrovola, Vasiliki

2016-01-01

The incorporation of Information and Communication Technologies (ICT) in education has changed the educational procedures through the creation and use of new teaching and learning environments with the use of computers and network applications that afford new dimensions to distance education. In turn, these emerging and in progress technologies,…

A Design and Development of Distance Learning Support Environment for Collaborative Problem Solving in Group Learners

ERIC Educational Resources Information Center

Nitta, Takuya; Takaoka, Ryo; Ahama, Shigeki; Shimokawa, Masayuki

2014-01-01

The competency and curriculum for human resource development in knowledge based society are proposed in each country. We think the keywords are "collaborative problem solving" and "effective use of ICT". In particular, the competency to perform the collaborative problem solving and learning with others on the network is…

Brain dynamics that correlate with effects of learning on auditory distance perception.

PubMed

Wisniewski, Matthew G; Mercado, Eduardo; Church, Barbara A; Gramann, Klaus; Makeig, Scott

2014-01-01

Accuracy in auditory distance perception can improve with practice and varies for sounds differing in familiarity. Here, listeners were trained to judge the distances of English, Bengali, and backwards speech sources pre-recorded at near (2-m) and far (30-m) distances. Listeners' accuracy was tested before and after training. Improvements from pre-test to post-test were greater for forward speech, demonstrating a learning advantage for forward speech sounds. Independent component (IC) processes identified in electroencephalographic (EEG) data collected during pre- and post-testing revealed three clusters of ICs across subjects with stimulus-locked spectral perturbations related to learning and accuracy. One cluster exhibited a transient stimulus-locked increase in 4-8 Hz power (theta event-related synchronization; ERS) that was smaller after training and largest for backwards speech. For a left temporal cluster, 8-12 Hz decreases in power (alpha event-related desynchronization; ERD) were greatest for English speech and less prominent after training. In contrast, a cluster of IC processes centered at or near anterior portions of the medial frontal cortex showed learning-related enhancement of sustained increases in 10-16 Hz power (upper-alpha/low-beta ERS). The degree of this enhancement was positively correlated with the degree of behavioral improvements. Results suggest that neural dynamics in non-auditory cortical areas support distance judgments. Further, frontal cortical networks associated with attentional and/or working memory processes appear to play a role in perceptual learning for source distance.

Tele-education as method of medical education.

PubMed

Masic, Izet; Pandza, Haris; Kulasin, Igor; Masic, Zlatan; Valjevac, Salih

2009-01-01

Development of computer networks and introduction and application of new technologies in all aspects of human activity needs to be followed by universities in their transformation on how to approach scientific, research, and education teaching curricula. Development and increased use of distance learning (DL) over the past decade have clearly shown the potential and efficiency of information technology applied in education. Use of information technology in medical education is where medical informatics takes its place as important scientific discipline which ensures benefit from IT in teaching and learning process involved. Definition of telemedicine as "use of technologies based on health care delivered on distance" covers areas such as electronic health, tele-health (eHealth), telematics, but also tele-education. Web based medical education today is offered in different forms--from online lectures, online exams, web based continuous education programs, use of electronic libraries, online medical and scientific databases etc. Department of Medical Informatics of Medical Faculty of University of Sarajevo has taken many steps to introduce distance learning in medical curricula--from organising professional--scientific events (congresses, workshop etc), organizing first tele-exam at the faculty and among first at the university, to offering online lectures and online education material at the Department's website (www.unsa-medinfo.org). Distance learning in medical education, as well as telemedicine, significantly influence health care in general and are shaping the future model of medical practice. Basic computer and networks skills must be a part of all future medical curricula. The impact of technical equipment on patient-doctor relationship must be taken into account, and doctors have to be trained and prepared for diagnosing or consulting patients by use of IT. Telemedicine requires special approach in certain medical fields--tele-consultation, tele-surgery, tele-radiology and other specific telemedicine applications should be introduced to the curricula. Telemedicine and distance learning are best suited for medical education and doctor-to-doctor consultation--first contact between doctor and a patient should stay face-to-face when possible. In this paper, we present the results of the project Introduction and Implementation of Distance Learning at the Medical Faculty of University of Sarajevo and compare it with the following expected outcomes: development and integration of information technology in medical education; creation of flexible infrastructure which will enable access to e-learning to all students and teaching staff; improvement of digital literacy of academic population; ensuring high educational standards to students and teaching staff; helping medical staffto develop "life-long learning" approach in work and education.

A networking approach to reduce academic and social isolation for junior doctors working in rural hospitals in India.

PubMed

Vyas, R; Zachariah, A; Swamidasan, I; Doris, P; Harris, I

2012-07-01

Graduates from Christian Medical College (CMC) Vellore face many challenges while doing their service obligation in smaller hospitals, including academic and social isolation. To overcome these challenges, CMC aspired through its Fellowship in Secondary Hospital Medicine (FSHM), a 1-year blended on-site and distance-learning program, to provide academic and social support through networking for junior doctors working in rural areas. The purpose of this paper is to report the evaluation of the networking components of the FSHM program, with a focus on whether it succeeded in providing academic and social support for these junior doctors. A mixed method evaluation was done using written surveys for students and faculty and telephone interviews for students. Evidence for validity was gathered for the written survey. Criteria for validity were also applied for the qualitative data analysis. The major strengths of networking with faculty and peers identified were that it provided social support,, academic support through discussion about patient management problems and a variety of cases seen in the hospital, guidance on projects and reminders about deadlines. Recommendations for improvement included use of videoconferencing and Yahoo Groups. It is useful to incorporate networking into distance-learning educational programs for providing support to junior doctors working in rural hospitals.

Using of Teleconference as a Medium to Establish an "E-Global-Learning-System": An Experience of 1000guru-Association on Facilitates Open and Distance Learning Activities with Schools in Indonesia

ERIC Educational Resources Information Center

Haris, Ikhfan

2014-01-01

Information communication and technology (ICT) has been used in various fields. The use of teleconference for teaching and learning activities is currently not a new topic in global world. In Indonesia, through IMHERE Program from Directorate of Higher Education, some universities have been connected with a network of teleconference as a medium of…

Preparing public health nurses for pandemic influenza through distance learning.

PubMed

Macario, Everly; Benton, Lisa D; Yuen, Janet; Torres, Mara; Macias-Reynolds, Violet; Holsclaw, Patricia; Nakahara, Natalie; Jones, Marcy Connell

2007-01-01

As a global influenza pandemic appears imminent with the spread of avian influenza, the California Department of Health Services (CDHS) and the California Distance Learning Health Network (CDLHN) presented a live 90-min satellite broadcast and subsequent 2-hr small group problem-solving tabletop exercise to practice interventions needed to minimize the consequences of a pandemic event. Public health nurses (PHNs), managers, and other staff in laboratories, clinical care, veterinary medicine, environmental health, public information and safety, emergency management, and transportation down linked the program, broadcast by satellite from the CDHS Richmond Laboratory Campus, to view on-site locally. PHNs represented the professional category with the highest number of participants for those conducting the program outside of California. For those in California, PHNs represented the professional category with the second highest number of participants. Participants and distance-learning facilitators completed a training evaluation survey. Continuing education credits were provided by the Centers for Disease Control and Prevention to participants who completed the satellite broadcast evaluation. This distance-learning-by-satellite method of education paired with an activities-based tabletop exercise, and a focus on local rather than State-based responsibility, marks an innovative method of training PHNs and other staff in emergency preparedness response.

Potentiality of Disaster Management Education through Open and Distance Learning System in Bangladesh Open University

ERIC Educational Resources Information Center

Ahmad, Saima; Numan, Sharker Md.

2015-01-01

Bangladesh Open University (BOU) is the only public educational institution in Bangladesh, where, a dual-mode method of learning system has been introduced. Established in 21st October, 1992, the University now accommodates 174,459 learners in 2012. The wide range networking of this university provides it a great prospect to execute a broad…

Social Presence and Transactional Distance as an Antecedent to Knowledge Sharing in Virtual Learning Communities

ERIC Educational Resources Information Center

Karaoglan Yilmaz, Fatma Gizem

2017-01-01

Today, the use of social network-based virtual learning communities is increasing rapidly in terms of knowledge management. An important dynamic of knowledge management processes is the knowledge sharing behaviors (KSB) in community. The purpose of this study is to examine the KSB of the students in a Facebook-based virtual community created…

A Novel Learning Environment: Case Study of the Pan African e-Network Project

ERIC Educational Resources Information Center

Nanda, Silima; Saxena, Ashlesh

2013-01-01

The constructivist form of learning creates such an environment where the learners are not only active but they become actors' i.e members and contributors of the social and information space without taking into consideration the geographic boundaries. Such an innovative form of distance education was initiated in India in the year 2007 and it was…

Telecommunications Is Here and Now.

ERIC Educational Resources Information Center

Clark, Chris

1988-01-01

Presents an overview of telecommunications and its use in the field of education. Topics discussed include conferencing, electronic messaging, distance learning, networking, database searching, and projects relating to educational telecommunications sponsored by the International Council for Computers in Education (ICCE). (LRW)

Videoconferencing Comes of Age.

ERIC Educational Resources Information Center

Bosak, Steve

2000-01-01

Hundreds of districts are using high-speed videoconferencing for distance learning and resource sharing, inservice training, and districtwide meetings. Speed matters. Districts will need either Ethernet or ATM (asynchronous transfer mode) forms of wide-area networks to connect schools and offices. (MLH)

Overview of codes and tools for nuclear engineering education

NASA Astrophysics Data System (ADS)

Yakovlev, D.; Pryakhin, A.; Medvedeva, L.

2017-01-01

The recent world trends in nuclear education have been developed in the direction of social education, networking, virtual tools and codes. MEPhI as a global leader on the world education market implements new advanced technologies for the distance and online learning and for student research work. MEPhI produced special codes, tools and web resources based on the internet platform to support education in the field of nuclear technology. At the same time, MEPhI actively uses codes and tools from the third parties. Several types of the tools are considered: calculation codes, nuclear data visualization tools, virtual labs, PC-based educational simulators for nuclear power plants (NPP), CLP4NET, education web-platforms, distance courses (MOOCs and controlled and managed content systems). The university pays special attention to integrated products such as CLP4NET, which is not a learning course, but serves to automate the process of learning through distance technologies. CLP4NET organizes all tools in the same information space. Up to now, MEPhI has achieved significant results in the field of distance education and online system implementation.

A study of network education application on nursing staff continuing education effectiveness and staff's satisfaction.

PubMed

Lin, Juin-Shu; Yen-Chi, Liao; Lee, Ting-Ting

2006-01-01

The rapid development of computer technology pushes Internet's popularity and makes daily services more timely and convenient. Meanwhile, it also becomes a trend for nursing practice to implement network education model to break the distance barriers and for nurses to obtain more knowledge. The purpose of this study was to investigate the relationship of nursing staff's information competency, satisfaction and outcomes of network education. After completing 4 weeks of network education, a total of 218 nurses answered the on-line questionnaires. The results revealed that nurses who joined the computer training course for less than 3 hours per week, without networking connection devices and with college degree, had the lower nursing informatics competency; while nurses who were older, at N4 position, with on-line course experience and participated for more than 4 hours each week, had higher nursing informatics competency. Those who participated in the network education course less than 4 hours per week were less satisfied. There were significant differences between nursing positions before and after having the network education. Nurses who had higher nursing information competency also had higher satisfaction toward the network education. Network education not only enhances learners' computer competency but also improves their learning satisfaction. By promoting the network education and improving nurses' hardware/software skills and knowledge, nurses can use networks to access learning resources. Healthcare institutions should also enhance computer infrastructure, and to establish the standards for certificate courses to increase the learning motivation and learning outcome.

Performance evaluation of a distance learning program.

PubMed

Dailey, D J; Eno, K R; Brinkley, J F

1994-01-01

This paper presents a performance metric which uses a single number to characterize the response time for a non-deterministic client-server application operating over the Internet. When applied to a Macintosh-based distance learning application called the Digital Anatomist Browser, the metric allowed us to observe that "A typical student doing a typical mix of Browser commands on a typical data set will experience the same delay if they use a slow Macintosh on a local network or a fast Macintosh on the other side of the country accessing the data over the Internet." The methodology presented is applicable to other client-server applications that are rapidly appearing on the Internet.

A Hybrid Approach to Develop an Analytical Model for Enhancing the Service Quality of E-Learning

ERIC Educational Resources Information Center

Wu, Hung-Yi; Lin, Hsin-Yu

2012-01-01

The digital content industry is flourishing as a result of the rapid development of technology and the widespread use of computer networks. As has been reported, the market size of the global e-learning (i.e., distance education and telelearning) will reach USD 49.6 billion in 2014. However, to retain and/or increase the market share associated…

A Large-Scale Multi-Hop Localization Algorithm Based on Regularized Extreme Learning for Wireless Networks.

PubMed

Zheng, Wei; Yan, Xiaoyong; Zhao, Wei; Qian, Chengshan

2017-12-20

A novel large-scale multi-hop localization algorithm based on regularized extreme learning is proposed in this paper. The large-scale multi-hop localization problem is formulated as a learning problem. Unlike other similar localization algorithms, the proposed algorithm overcomes the shortcoming of the traditional algorithms which are only applicable to an isotropic network, therefore has a strong adaptability to the complex deployment environment. The proposed algorithm is composed of three stages: data acquisition, modeling and location estimation. In data acquisition stage, the training information between nodes of the given network is collected. In modeling stage, the model among the hop-counts and the physical distances between nodes is constructed using regularized extreme learning. In location estimation stage, each node finds its specific location in a distributed manner. Theoretical analysis and several experiments show that the proposed algorithm can adapt to the different topological environments with low computational cost. Furthermore, high accuracy can be achieved by this method without setting complex parameters.

Network formation: neighborhood structures, establishment costs, and distributed learning.

PubMed

Chasparis, Georgios C; Shamma, Jeff S

2013-12-01

We consider the problem of network formation in a distributed fashion. Network formation is modeled as a strategic-form game, where agents represent nodes that form and sever unidirectional links with other nodes and derive utilities from these links. Furthermore, agents can form links only with a limited set of neighbors. Agents trade off the benefit from links, which is determined by a distance-dependent reward function, and the cost of maintaining links. When each agent acts independently, trying to maximize its own utility function, we can characterize “stable” networks through the notion of Nash equilibrium. In fact, the introduced reward and cost functions lead to Nash equilibria (networks), which exhibit several desirable properties such as connectivity, bounded-hop diameter, and efficiency (i.e., minimum number of links). Since Nash networks may not necessarily be efficient, we also explore the possibility of “shaping” the set of Nash networks through the introduction of state-based utility functions. Such utility functions may represent dynamic phenomena such as establishment costs (either positive or negative). Finally, we show how Nash networks can be the outcome of a distributed learning process. In particular, we extend previous learning processes to so-called “state-based” weakly acyclic games, and we show that the proposed network formation games belong to this class of games.

Application of a feedforward neural network in the search for kuroko deposits in the Hokuroku District, Japan

USGS Publications Warehouse

Singer, Donald A.; Kouda, Ryoichi

1996-01-01

A feedforward neural network with one hidden layer and five neurons was trained to recognize the distance to kuroko mineral deposits. Average amounts per hole of pyrite, sericite, and gypsum plus anhydrite as measured by X-rays in 69 drillholes were used to train the net. Drillholes near and between the Fukazawa, Furutobe, and Shakanai mines were used. The training data were selected carefully to represent well-explored areas where some confidence of the distance to ore was assured. A logarithmic transform was applied to remove the skewness of distance and each variable was scaled and centered by subtracting the median and dividing by the interquartile range. The learning algorithm of annealing plus conjugate gradients was used to minimize the mean squared error of the scaled distance to ore. The trained network then was applied to all of the 152 drillholes that had measured gypsum, sericite, and pyrite. A contour plot of the neural net predicted distance to ore shows fairly wide areas of 1 km or less to ore; each of the known deposit groups is within the 1 km contour. The high and low distances on the margins of the contoured distance plot are in part the result of boundary effects of the contouring algorithm. For example, the short distances to ore predicted west of the Shakanai (Hanaoka) deposits are in basement. However, the short distances to ore predicted northeast of Furotobe, just off the figure, coincide with the location of the Nurukawa kuroko deposit and the Omaki deposit, south of the Shakanai-Hanaoka deposits, seems to be on an extension of short distance to ore contour, but is beyond the 3 km limit from drillholes. Also of interest are some areas only a few kilometers from the Fukazawa and Shakanai groups of deposits that are estimated to be many kilometers from ore, apparently reflecting the network's recognition of the extreme local variability of the geology near some deposits.

Maryland: Sailing into the Electronic Future.

ERIC Educational Resources Information Center

Smith, Barbara G., Ed.

1996-01-01

Describes information technology programs in Maryland, including the Sailor Project, that created a statewide telecommunications network providing Internet access without charge from libraries, homes, offices, schools, and shopping malls; University of Maryland initiatives; distance learning in higher education; and a project that allows worldwide…

Visualizing and enhancing a deep learning framework using patients age and gender for chest x-ray image retrieval

NASA Astrophysics Data System (ADS)

Anavi, Yaron; Kogan, Ilya; Gelbart, Elad; Geva, Ofer; Greenspan, Hayit

2016-03-01

We explore the combination of text metadata, such as patients' age and gender, with image-based features, for X-ray chest pathology image retrieval. We focus on a feature set extracted from a pre-trained deep convolutional network shown in earlier work to achieve state-of-the-art results. Two distance measures are explored: a descriptor-based measure, which computes the distance between image descriptors, and a classification-based measure, which performed by a comparison of the corresponding SVM classification probabilities. We show that retrieval results increase once the age and gender information combined with the features extracted from the last layers of the network, with best results using the classification-based scheme. Visualization of the X-ray data is presented by embedding the high dimensional deep learning features in a 2-D dimensional space while preserving the pairwise distances using the t-SNE algorithm. The 2-D visualization gives the unique ability to find groups of X-ray images that are similar to the query image and among themselves, which is a characteristic we do not see in a 1-D traditional ranking.

Low Data Drug Discovery with One-Shot Learning.

PubMed

Altae-Tran, Han; Ramsundar, Bharath; Pappu, Aneesh S; Pande, Vijay

2017-04-26

Recent advances in machine learning have made significant contributions to drug discovery. Deep neural networks in particular have been demonstrated to provide significant boosts in predictive power when inferring the properties and activities of small-molecule compounds (Ma, J. et al. J. Chem. Inf. 2015, 55, 263-274). However, the applicability of these techniques has been limited by the requirement for large amounts of training data. In this work, we demonstrate how one-shot learning can be used to significantly lower the amounts of data required to make meaningful predictions in drug discovery applications. We introduce a new architecture, the iterative refinement long short-term memory, that, when combined with graph convolutional neural networks, significantly improves learning of meaningful distance metrics over small-molecules. We open source all models introduced in this work as part of DeepChem, an open-source framework for deep-learning in drug discovery (Ramsundar, B. deepchem.io. https://github.com/deepchem/deepchem, 2016).

Report on Distance Learning Technologies.

DTIC Science & Technology

1995-09-01

26 cities. The CSX system includes full-motion video, animations , audio, and interactive examples and testing to teach the use of a new computer...video. The change to all-digital media now permits the use of full-motion video, animation , and audio on networks. It is possible to have independent...is possible to download entire multimedia presentations from the network. To date there is not a great deal known about teaching courses using the

DATA MAYHEM VERSUS NIMBLE INFORMATION: TRANSFORMING HECTIC IMAGERY INTELLIGENCE DATA INTO ACTIONABLE INFORMATION USING ARTIFICIAL NEURAL NETWORKS

DTIC Science & Technology

2017-10-01

AU/ACSC/MORALES/AY17 AIR COMMAND AND STAFF COLLEGE DISTANCE LEARNING AIR UNIVERSITY DATA MAYHEM VERSUS NIMBLE INFORMATION : TRANSFORMING...HECTIC IMAGERY INTELLIGENCE DATA INTO ACTIONABLE INFORMATION USING ARTIFICIAL NEURAL NETWORKS by Luis A. Morales, Major, USAF A Research...finding solutions to compliment and supplement human analysts’ capacity, so intelligence and information can reach operators and end-users at the

Phylogenetic convolutional neural networks in metagenomics.

PubMed

Fioravanti, Diego; Giarratano, Ylenia; Maggio, Valerio; Agostinelli, Claudio; Chierici, Marco; Jurman, Giuseppe; Furlanello, Cesare

2018-03-08

Convolutional Neural Networks can be effectively used only when data are endowed with an intrinsic concept of neighbourhood in the input space, as is the case of pixels in images. We introduce here Ph-CNN, a novel deep learning architecture for the classification of metagenomics data based on the Convolutional Neural Networks, with the patristic distance defined on the phylogenetic tree being used as the proximity measure. The patristic distance between variables is used together with a sparsified version of MultiDimensional Scaling to embed the phylogenetic tree in a Euclidean space. Ph-CNN is tested with a domain adaptation approach on synthetic data and on a metagenomics collection of gut microbiota of 38 healthy subjects and 222 Inflammatory Bowel Disease patients, divided in 6 subclasses. Classification performance is promising when compared to classical algorithms like Support Vector Machines and Random Forest and a baseline fully connected neural network, e.g. the Multi-Layer Perceptron. Ph-CNN represents a novel deep learning approach for the classification of metagenomics data. Operatively, the algorithm has been implemented as a custom Keras layer taking care of passing to the following convolutional layer not only the data but also the ranked list of neighbourhood of each sample, thus mimicking the case of image data, transparently to the user.

Collaborative Visualization Project: shared-technology learning environments for science learning

NASA Astrophysics Data System (ADS)

Pea, Roy D.; Gomez, Louis M.

1993-01-01

Project-enhanced science learning (PESL) provides students with opportunities for `cognitive apprenticeships' in authentic scientific inquiry using computers for data-collection and analysis. Student teams work on projects with teacher guidance to develop and apply their understanding of science concepts and skills. We are applying advanced computing and communications technologies to augment and transform PESL at-a-distance (beyond the boundaries of the individual school), which is limited today to asynchronous, text-only networking and unsuitable for collaborative science learning involving shared access to multimedia resources such as data, graphs, tables, pictures, and audio-video communication. Our work creates user technology (a Collaborative Science Workbench providing PESL design support and shared synchronous document views, program, and data access; a Science Learning Resource Directory for easy access to resources including two-way video links to collaborators, mentors, museum exhibits, media-rich resources such as scientific visualization graphics), and refine enabling technologies (audiovisual and shared-data telephony, networking) for this PESL niche. We characterize participation scenarios for using these resources and we discuss national networked access to science education expertise.

Fiber Optics: Deregulate and Deploy.

ERIC Educational Resources Information Center

Suwinski, Jan H.

1993-01-01

Describes fiber optic technology, explains its use in education and commercial settings, and recommends regulations and legislation that will speed its use to create broadband information networks. Topics discussed include distance learning; interactive video; costs; and the roles of policy makers, lawmakers, public advocacy groups, and consumers.…

Efficient DV-HOP Localization for Wireless Cyber-Physical Social Sensing System: A Correntropy-Based Neural Network Learning Scheme

PubMed Central

Xu, Yang; Luo, Xiong; Wang, Weiping; Zhao, Wenbing

2017-01-01

Integrating wireless sensor network (WSN) into the emerging computing paradigm, e.g., cyber-physical social sensing (CPSS), has witnessed a growing interest, and WSN can serve as a social network while receiving more attention from the social computing research field. Then, the localization of sensor nodes has become an essential requirement for many applications over WSN. Meanwhile, the localization information of unknown nodes has strongly affected the performance of WSN. The received signal strength indication (RSSI) as a typical range-based algorithm for positioning sensor nodes in WSN could achieve accurate location with hardware saving, but is sensitive to environmental noises. Moreover, the original distance vector hop (DV-HOP) as an important range-free localization algorithm is simple, inexpensive and not related to the environment factors, but performs poorly when lacking anchor nodes. Motivated by these, various improved DV-HOP schemes with RSSI have been introduced, and we present a new neural network (NN)-based node localization scheme, named RHOP-ELM-RCC, through the use of DV-HOP, RSSI and a regularized correntropy criterion (RCC)-based extreme learning machine (ELM) algorithm (ELM-RCC). Firstly, the proposed scheme employs both RSSI and DV-HOP to evaluate the distances between nodes to enhance the accuracy of distance estimation at a reasonable cost. Then, with the help of ELM featured with a fast learning speed with a good generalization performance and minimal human intervention, a single hidden layer feedforward network (SLFN) on the basis of ELM-RCC is used to implement the optimization task for obtaining the location of unknown nodes. Since the RSSI may be influenced by the environmental noises and may bring estimation error, the RCC instead of the mean square error (MSE) estimation, which is sensitive to noises, is exploited in ELM. Hence, it may make the estimation more robust against outliers. Additionally, the least square estimation (LSE) in ELM is replaced by the half-quadratic optimization technique. Simulation results show that our proposed scheme outperforms other traditional localization schemes. PMID:28085084

PatterNet: a system to learn compact physical design pattern representations for pattern-based analytics

NASA Astrophysics Data System (ADS)

Lutich, Andrey

2017-07-01

This research considers the problem of generating compact vector representations of physical design patterns for analytics purposes in semiconductor patterning domain. PatterNet uses a deep artificial neural network to learn mapping of physical design patterns to a compact Euclidean hyperspace. Distances among mapped patterns in this space correspond to dissimilarities among patterns defined at the time of the network training. Once the mapping network has been trained, PatterNet embeddings can be used as feature vectors with standard machine learning algorithms, and pattern search, comparison, and clustering become trivial problems. PatterNet is inspired by the concepts developed within the framework of generative adversarial networks as well as the FaceNet. Our method facilitates a deep neural network (DNN) to learn directly the compact representation by supplying it with pairs of design patterns and dissimilarity among these patterns defined by a user. In the simplest case, the dissimilarity is represented by an area of the XOR of two patterns. Important to realize that our PatterNet approach is very different to the methods developed for deep learning on image data. In contrast to "conventional" pictures, the patterns in the CAD world are the lists of polygon vertex coordinates. The method solely relies on the promise of deep learning to discover internal structure of the incoming data and learn its hierarchical representations. Artificial intelligence arising from the combination of PatterNet and clustering analysis very precisely follows intuition of patterning/optical proximity correction experts paving the way toward human-like and human-friendly engineering tools.

Lead or Bleed: Colleges, Universities, and the E-Universe.

ERIC Educational Resources Information Center

Grills, Caroline M.

2000-01-01

Summarizes presentations at the 21st Century Executive Symposium (Washington, DC, February 13-15, 2000) of 150 higher education senior business officers. Presentations focused on such topics as e-commerce, private sector competition in distance education and lifelong learning, the emerging networked technology grid, higher education as an…

Back to School at Work: Training Strategies for the 90's.

ERIC Educational Resources Information Center

Klinck, Nancy A.

1993-01-01

Describes corporate training programs that use technology, including videotapes, hypermedia curriculum, and distance learning systems in the automotive industry, using fiber optics and cable to transmit university courses; the petroleum industry, using a video network; and the health care industry, via an interactive video conferencing system.…

Distance Learning Partnerships for Underserved Learners.

ERIC Educational Resources Information Center

Chavkin, Nancy Feyl; And Others

1994-01-01

Describes a partnership that was formed to develop a fiber optic interactive network and its interface with the development of algebra curriculum and social services in the PATH (Partnership for Access to Higher) Mathematics project in Texas. Equipment connections, costs, and classroom layout are described; and social work components are…

Processes and Planning Structure Required for Implementing a Collegewide Area Network.

ERIC Educational Resources Information Center

Lapenta, Susan; Lutz, Todd

Since 1984, Arizona's Mohave Community College (MCC) has implemented innovative educational technology to better serve students, including an instructional television system to serve remote locations and a distance learning program. In 1993, the college initiated a project to upgrade its technological capabilities through the establishment of a…

Intrinsic noise and deviations from criticality in Boolean gene-regulatory networks

NASA Astrophysics Data System (ADS)

Villegas, Pablo; Ruiz-Franco, José; Hidalgo, Jorge; Muñoz, Miguel A.

2016-10-01

Gene regulatory networks can be successfully modeled as Boolean networks. A much discussed hypothesis says that such model networks reproduce empirical findings the best if they are tuned to operate at criticality, i.e. at the borderline between their ordered and disordered phases. Critical networks have been argued to lead to a number of functional advantages such as maximal dynamical range, maximal sensitivity to environmental changes, as well as to an excellent tradeoff between stability and flexibility. Here, we study the effect of noise within the context of Boolean networks trained to learn complex tasks under supervision. We verify that quasi-critical networks are the ones learning in the fastest possible way -even for asynchronous updating rules- and that the larger the task complexity the smaller the distance to criticality. On the other hand, when additional sources of intrinsic noise in the network states and/or in its wiring pattern are introduced, the optimally performing networks become clearly subcritical. These results suggest that in order to compensate for inherent stochasticity, regulatory and other type of biological networks might become subcritical rather than being critical, all the most if the task to be performed has limited complexity.

Low Data Drug Discovery with One-Shot Learning

PubMed Central

2017-01-01

Recent advances in machine learning have made significant contributions to drug discovery. Deep neural networks in particular have been demonstrated to provide significant boosts in predictive power when inferring the properties and activities of small-molecule compounds (Ma, J. et al. J. Chem. Inf. Model.2015, 55, 263–27425635324). However, the applicability of these techniques has been limited by the requirement for large amounts of training data. In this work, we demonstrate how one-shot learning can be used to significantly lower the amounts of data required to make meaningful predictions in drug discovery applications. We introduce a new architecture, the iterative refinement long short-term memory, that, when combined with graph convolutional neural networks, significantly improves learning of meaningful distance metrics over small-molecules. We open source all models introduced in this work as part of DeepChem, an open-source framework for deep-learning in drug discovery (Ramsundar, B. deepchem.io. https://github.com/deepchem/deepchem, 2016). PMID:28470045

Persistence and storage of activity patterns in spiking recurrent cortical networks: modulation of sigmoid signals by after-hyperpolarization currents and acetylcholine

PubMed Central

Palma, Jesse; Grossberg, Stephen; Versace, Massimiliano

2012-01-01

Many cortical networks contain recurrent architectures that transform input patterns before storing them in short-term memory (STM). Theorems in the 1970's showed how feedback signal functions in rate-based recurrent on-center off-surround networks control this process. A sigmoid signal function induces a quenching threshold below which inputs are suppressed as noise and above which they are contrast-enhanced before pattern storage. This article describes how changes in feedback signaling, neuromodulation, and recurrent connectivity may alter pattern processing in recurrent on-center off-surround networks of spiking neurons. In spiking neurons, fast, medium, and slow after-hyperpolarization (AHP) currents control sigmoid signal threshold and slope. Modulation of AHP currents by acetylcholine (ACh) can change sigmoid shape and, with it, network dynamics. For example, decreasing signal function threshold and increasing slope can lengthen the persistence of a partially contrast-enhanced pattern, increase the number of active cells stored in STM, or, if connectivity is distance-dependent, cause cell activities to cluster. These results clarify how cholinergic modulation by the basal forebrain may alter the vigilance of category learning circuits, and thus their sensitivity to predictive mismatches, thereby controlling whether learned categories code concrete or abstract features, as predicted by Adaptive Resonance Theory. The analysis includes global, distance-dependent, and interneuron-mediated circuits. With an appropriate degree of recurrent excitation and inhibition, spiking networks maintain a partially contrast-enhanced pattern for 800 ms or longer after stimuli offset, then resolve to no stored pattern, or to winner-take-all (WTA) stored patterns with one or multiple winners. Strengthening inhibition prolongs a partially contrast-enhanced pattern by slowing the transition to stability, while strengthening excitation causes more winners when the network stabilizes. PMID:22754524

Locomotion training of legged robots using hybrid machine learning techniques

NASA Technical Reports Server (NTRS)

Simon, William E.; Doerschuk, Peggy I.; Zhang, Wen-Ran; Li, Andrew L.

1995-01-01

In this study artificial neural networks and fuzzy logic are used to control the jumping behavior of a three-link uniped robot. The biped locomotion control problem is an increment of the uniped locomotion control. Study of legged locomotion dynamics indicates that a hierarchical controller is required to control the behavior of a legged robot. A structured control strategy is suggested which includes navigator, motion planner, biped coordinator and uniped controllers. A three-link uniped robot simulation is developed to be used as the plant. Neurocontrollers were trained both online and offline. In the case of on-line training, a reinforcement learning technique was used to train the neurocontroller to make the robot jump to a specified height. After several hundred iterations of training, the plant output achieved an accuracy of 7.4%. However, when jump distance and body angular momentum were also included in the control objectives, training time became impractically long. In the case of off-line training, a three-layered backpropagation (BP) network was first used with three inputs, three outputs and 15 to 40 hidden nodes. Pre-generated data were presented to the network with a learning rate as low as 0.003 in order to reach convergence. The low learning rate required for convergence resulted in a very slow training process which took weeks to learn 460 examples. After training, performance of the neurocontroller was rather poor. Consequently, the BP network was replaced by a Cerebeller Model Articulation Controller (CMAC) network. Subsequent experiments described in this document show that the CMAC network is more suitable to the solution of uniped locomotion control problems in terms of both learning efficiency and performance. A new approach is introduced in this report, viz., a self-organizing multiagent cerebeller model for fuzzy-neural control of uniped locomotion is suggested to improve training efficiency. This is currently being evaluated for a possible patent by NASA, Johnson Space Center. An alternative modular approach is also developed which uses separate controllers for each stage of the running stride. A self-organizing fuzzy-neural controller controls the height, distance and angular momentum of the stride. A CMAC-based controller controls the movement of the leg from the time the foot leaves the ground to the time of landing. Because the leg joints are controlled at each time step during flight, movement is smooth and obstacles can be avoided. Initial results indicate that this approach can yield fast, accurate results.

Prediction of Short-Distance Aerial Movement of Phakopsora pachyrhizi Urediniospores Using Machine Learning.

PubMed

Wen, L; Bowen, C R; Hartman, G L

2017-10-01

Dispersal of urediniospores by wind is the primary means of spread for Phakopsora pachyrhizi, the cause of soybean rust. Our research focused on the short-distance movement of urediniospores from within the soybean canopy and up to 61 m from field-grown rust-infected soybean plants. Environmental variables were used to develop and compare models including the least absolute shrinkage and selection operator regression, zero-inflated Poisson/regular Poisson regression, random forest, and neural network to describe deposition of urediniospores collected in passive and active traps. All four models identified distance of trap from source, humidity, temperature, wind direction, and wind speed as the five most important variables influencing short-distance movement of urediniospores. The random forest model provided the best predictions, explaining 76.1 and 86.8% of the total variation in the passive- and active-trap datasets, respectively. The prediction accuracy based on the correlation coefficient (r) between predicted values and the true values were 0.83 (P < 0.0001) and 0.94 (P < 0.0001) for the passive and active trap datasets, respectively. Overall, multiple machine learning techniques identified the most important variables to make the most accurate predictions of movement of P. pachyrhizi urediniospores short-distance.

Electronic Resource Sharing in Community Colleges: A Snapshot of Florida, Wisconsin, Texas, and Louisiana.

ERIC Educational Resources Information Center

Mahoney, Brian D.

2000-01-01

States that several states are establishing networks for resource sharing. Florida offers these resources through the Florida Distance Learning Library Initiative, Wisconsin has BadgerLink and WISCAT, TexShare provides library resource sharing in Texas, and Louisiana has LOUIS and LLN. These are some of the states successfully demonstrating…

Communication is the key to success in pragmatic clinical trials in Practice-based Research Networks (PBRNs).

PubMed

Bertram, Susan; Graham, Deborah; Kurland, Marge; Pace, Wilson; Madison, Suzanne; Yawn, Barbara P

2013-01-01

Effective communication is the foundation of feasibility and fidelity in practice-based pragmatic research studies. Doing a study with practices spread over several states requires long-distance communication strategies, including E-mails, faxes, telephone calls, conference calls, and texting. Compared with face-to-face communication, distance communication strategies are less familiar to most study coordinators and research teams. Developing and ensuring comfort with distance communications requires additional time and use of different talents and expertise than those required for face-to-face communication. It is necessary to make sure that messages are appropriate for the medium, clearly crafted, and presented in a manner that facilitates practices receiving and understanding the information. This discussion is based on extensive experience of 2 groups who have worked collaboratively on several large, federally funded, pragmatic trials in a practice-based research network. The goal of this article is to summarize lessons learned to facilitate the work of other research teams.

CNN: a speaker recognition system using a cascaded neural network.

PubMed

Zaki, M; Ghalwash, A; Elkouny, A A

1996-05-01

The main emphasis of this paper is to present an approach for combining supervised and unsupervised neural network models to the issue of speaker recognition. To enhance the overall operation and performance of recognition, the proposed strategy integrates the two techniques, forming one global model called the cascaded model. We first present a simple conventional technique based on the distance measured between a test vector and a reference vector for different speakers in the population. This particular distance metric has the property of weighting down the components in those directions along which the intraspeaker variance is large. The reason for presenting this method is to clarify the discrepancy in performance between the conventional and neural network approach. We then introduce the idea of using unsupervised learning technique, presented by the winner-take-all model, as a means of recognition. Due to several tests that have been conducted and in order to enhance the performance of this model, dealing with noisy patterns, we have preceded it with a supervised learning model--the pattern association model--which acts as a filtration stage. This work includes both the design and implementation of both conventional and neural network approaches to recognize the speakers templates--which are introduced to the system via a voice master card and preprocessed before extracting the features used in the recognition. The conclusion indicates that the system performance in case of neural network is better than that of the conventional one, achieving a smooth degradation in respect of noisy patterns, and higher performance in respect of noise-free patterns.

A network-based training environment: a medical image processing paradigm.

PubMed

Costaridou, L; Panayiotakis, G; Sakellaropoulos, P; Cavouras, D; Dimopoulos, J

1998-01-01

The capability of interactive multimedia and Internet technologies is investigated with respect to the implementation of a distance learning environment. The system is built according to a client-server architecture, based on the Internet infrastructure, composed of server nodes conceptually modelled as WWW sites. Sites are implemented by customization of available components. The environment integrates network-delivered interactive multimedia courses, network-based tutoring, SIG support, information databases of professional interest, as well as course and tutoring management. This capability has been demonstrated by means of an implemented system, validated with digital image processing content, specifically image enhancement. Image enhancement methods are theoretically described and applied to mammograms. Emphasis is given to the interactive presentation of the effects of algorithm parameters on images. The system end-user access depends on available bandwidth, so high-speed access can be achieved via LAN or local ISDN connections. Network based training offers new means of improved access and sharing of learning resources and expertise, as promising supplements in training.

A label distance maximum-based classifier for multi-label learning.

PubMed

Liu, Xiaoli; Bao, Hang; Zhao, Dazhe; Cao, Peng

2015-01-01

Multi-label classification is useful in many bioinformatics tasks such as gene function prediction and protein site localization. This paper presents an improved neural network algorithm, Max Label Distance Back Propagation Algorithm for Multi-Label Classification. The method was formulated by modifying the total error function of the standard BP by adding a penalty term, which was realized by maximizing the distance between the positive and negative labels. Extensive experiments were conducted to compare this method against state-of-the-art multi-label methods on three popular bioinformatic benchmark datasets. The results illustrated that this proposed method is more effective for bioinformatic multi-label classification compared to commonly used techniques.

Minimal perceptrons for memorizing complex patterns

NASA Astrophysics Data System (ADS)

Pastor, Marissa; Song, Juyong; Hoang, Danh-Tai; Jo, Junghyo

2016-11-01

Feedforward neural networks have been investigated to understand learning and memory, as well as applied to numerous practical problems in pattern classification. It is a rule of thumb that more complex tasks require larger networks. However, the design of optimal network architectures for specific tasks is still an unsolved fundamental problem. In this study, we consider three-layered neural networks for memorizing binary patterns. We developed a new complexity measure of binary patterns, and estimated the minimal network size for memorizing them as a function of their complexity. We formulated the minimal network size for regular, random, and complex patterns. In particular, the minimal size for complex patterns, which are neither ordered nor disordered, was predicted by measuring their Hamming distances from known ordered patterns. Our predictions agree with simulations based on the back-propagation algorithm.

Spatial Learning and Action Planning in a Prefrontal Cortical Network Model

PubMed Central

Martinet, Louis-Emmanuel; Sheynikhovich, Denis; Benchenane, Karim; Arleo, Angelo

2011-01-01

The interplay between hippocampus and prefrontal cortex (PFC) is fundamental to spatial cognition. Complementing hippocampal place coding, prefrontal representations provide more abstract and hierarchically organized memories suitable for decision making. We model a prefrontal network mediating distributed information processing for spatial learning and action planning. Specific connectivity and synaptic adaptation principles shape the recurrent dynamics of the network arranged in cortical minicolumns. We show how the PFC columnar organization is suitable for learning sparse topological-metrical representations from redundant hippocampal inputs. The recurrent nature of the network supports multilevel spatial processing, allowing structural features of the environment to be encoded. An activation diffusion mechanism spreads the neural activity through the column population leading to trajectory planning. The model provides a functional framework for interpreting the activity of PFC neurons recorded during navigation tasks. We illustrate the link from single unit activity to behavioral responses. The results suggest plausible neural mechanisms subserving the cognitive “insight” capability originally attributed to rodents by Tolman & Honzik. Our time course analysis of neural responses shows how the interaction between hippocampus and PFC can yield the encoding of manifold information pertinent to spatial planning, including prospective coding and distance-to-goal correlates. PMID:21625569

Second Language Word Learning through Repetition and Imitation: Functional Networks as a Function of Learning Phase and Language Distance.

PubMed

Ghazi-Saidi, Ladan; Ansaldo, Ana Ines

2017-01-01

Introduction and Aim : Repetition and imitation are among the oldest second language (L2) teaching approaches and are frequently used in the context of L2 learning and language therapy, despite some heavy criticism. Current neuroimaging techniques allow the neural mechanisms underlying repetition and imitation to be examined. This fMRI study examines the influence of verbal repetition and imitation on network configuration. Integration changes within and between the cognitive control and language networks were studied, in a pair of linguistically close languages (Spanish and French), and compared to our previous work on a distant language pair (Ghazi-Saidi et al., 2013). Methods : Twelve healthy native Spanish-speaking (L1) adults, and 12 healthy native Persian-speaking adults learned 130 new French (L2) words, through a computerized audiovisual repetition and imitation program. The program presented colored photos of objects. Participants were instructed to look at each photo and pronounce its name as closely as possible to the native template (imitate). Repetition was encouraged as many times as necessary to learn the object's name; phonological cues were provided if necessary. Participants practiced for 15 min, over 30 days, and were tested while naming the same items during fMRI scanning, at week 1 (shallow learning phase) and week 4 (consolidation phase) of training. To compare this set of data with our previous work on Persian speakers, a similar data analysis plan including accuracy rates (AR), response times (RT), and functional integration values for the language and cognitive control network at each measure point was included, with further L1-L2 direct comparisons across the two populations. Results and Discussion : The evidence shows that learning L2 words through repetition induces neuroplasticity at the network level. Specifically, L2 word learners showed increased network integration after 3 weeks of training, with both close and distant language pairs. Moreover, higher network integration was observed in the learners with the close language pair, suggesting that repetition effects on network configuration vary as a function of task complexity.

Transitioning from Traditional Courses to Technologically Supported Classrooms. IDEA Paper #62

ERIC Educational Resources Information Center

Proctor, Janice; Bumgardner, Tiffany

2016-01-01

This paper focuses on the authors' experiences teaching on Ohio University's Learning Network (OULN), which uses interactive television and real-time face-to-face interaction as a distance-education (DE) delivery tool. One of the authors is a sociology professor, and the other is her former student and an experienced OULN system operator. The…

Challenges in Fibromyalgia Management: A Study of Anxiety, Depression, and Motivation Using Distance Learning and Social Networking

ERIC Educational Resources Information Center

Caines, Matthew J.

2010-01-01

Patients with fibromyalgia have difficulty managing symptoms (e.g., fatigue, chronic pain). The challenges in fibromyalgia management may vary from patient to patient, from painful physical exercise to pharmaceutical side-effects. Since the management of fibromyalgia greatly varies, there seems to be an individualist or personal component to…

Academic Program Life Cycle: A Redefined Approach to Understanding Market Demands

ERIC Educational Resources Information Center

Mukerji, Siran; Tripathi, Purnendu

2004-01-01

Education can develop intellectual capability in people, which may in turn lead toward development of a more humane society. Open and distance learning (ODL) has provided one means of achieving social objectives democratically. In India significant success has been achieved through a network of 10 open universities and 104 institutes of open and…

Trans-Pacific Astronomy Experiment Project Status

NASA Technical Reports Server (NTRS)

Hsu, Eddie

2000-01-01

The Trans-Pacific Astronomy Experiment is Phase 2 of the Trans-Pacific High Data Rate Satcom Experiments following the Trans-Pacific High Definition Video Experiment. It is a part of the Global Information Infrastructure-Global Interoperability for Broadband Networks Project (GII-GIBN). Provides global information infrastructure involving broadband satellites and terrestrial networks and access to information by anyone, anywhere, at any time. Collaboration of government, industry, and academic organizations demonstrate the use of broadband satellite links in a global information infrastructure with emphasis on astronomical observations, collaborative discussions and distance learning.

Distance learning in academic health education.

PubMed

Mattheos, N; Schittek, M; Attström, R; Lyon, H C

2001-05-01

Distance learning is an apparent alternative to traditional methods in education of health care professionals. Non-interactive distance learning, interactive courses and virtual learning environments exist as three different generations in distance learning, each with unique methodologies, strengths and potential. Different methodologies have been recommended for distance learning, varying from a didactic approach to a problem-based learning procedure. Accreditation, teamwork and personal contact between the tutors and the students during a course provided by distance learning are recommended as motivating factors in order to enhance the effectiveness of the learning. Numerous assessment methods for distance learning courses have been proposed. However, few studies report adequate tests for the effectiveness of the distance-learning environment. Available information indicates that distance learning may significantly decrease the cost of academic health education at all levels. Furthermore, such courses can provide education to students and professionals not accessible by traditional methods. Distance learning applications still lack the support of a solid theoretical framework and are only evaluated to a limited extent. Cases reported so far tend to present enthusiastic results, while more carefully-controlled studies suggest a cautious attitude towards distance learning. There is a vital need for research evidence to identify the factors of importance and variables involved in distance learning. The effectiveness of distance learning courses, especially in relation to traditional teaching methods, must therefore be further investigated.

Machine learning framework for analysis of transport through complex networks in porous, granular media: A focus on permeability

NASA Astrophysics Data System (ADS)

van der Linden, Joost H.; Narsilio, Guillermo A.; Tordesillas, Antoinette

2016-08-01

We present a data-driven framework to study the relationship between fluid flow at the macroscale and the internal pore structure, across the micro- and mesoscales, in porous, granular media. Sphere packings with varying particle size distribution and confining pressure are generated using the discrete element method. For each sample, a finite element analysis of the fluid flow is performed to compute the permeability. We construct a pore network and a particle contact network to quantify the connectivity of the pores and particles across the mesoscopic spatial scales. Machine learning techniques for feature selection are employed to identify sets of microstructural properties and multiscale complex network features that optimally characterize permeability. We find a linear correlation (in log-log scale) between permeability and the average closeness centrality of the weighted pore network. With the pore network links weighted by the local conductance, the average closeness centrality represents a multiscale measure of efficiency of flow through the pore network in terms of the mean geodesic distance (or shortest path) between all pore bodies in the pore network. Specifically, this study objectively quantifies a hypothesized link between high permeability and efficient shortest paths that thread through relatively large pore bodies connected to each other by high conductance pore throats, embodying connectivity and pore structure.

Topological Distances Between Brain Networks

PubMed Central

Lee, Hyekyoung; Solo, Victor; Davidson, Richard J.; Pollak, Seth D.

2018-01-01

Many existing brain network distances are based on matrix norms. The element-wise differences may fail to capture underlying topological differences. Further, matrix norms are sensitive to outliers. A few extreme edge weights may severely affect the distance. Thus it is necessary to develop network distances that recognize topology. In this paper, we introduce Gromov-Hausdorff (GH) and Kolmogorov-Smirnov (KS) distances. GH-distance is often used in persistent homology based brain network models. The superior performance of KS-distance is contrasted against matrix norms and GH-distance in random network simulations with the ground truths. The KS-distance is then applied in characterizing the multimodal MRI and DTI study of maltreated children.

The Influence of Personality and Chronotype on Distance Learning Willingness and Anxiety among Vocational High School Students in Turkey

ERIC Educational Resources Information Center

Randler, Christoph; Horzum, Mehmet Baris; Vollmer, Christian

2014-01-01

There are many studies related to distance learning. Willingness and anxiety are important variables for distance learning. Recent research has shown that anxiety and willingness towards distance learning are moderated by personality. This study sought to investigate whether distance learning willingness and distance learning anxiety are…

The diabolo classifier

PubMed

Schwenk

1998-11-15

We present a new classification architecture based on autoassociative neural networks that are used to learn discriminant models of each class. The proposed architecture has several interesting properties with respect to other model-based classifiers like nearest-neighbors or radial basis functions: it has a low computational complexity and uses a compact distributed representation of the models. The classifier is also well suited for the incorporation of a priori knowledge by means of a problem-specific distance measure. In particular, we will show that tangent distance (Simard, Le Cun, & Denker, 1993) can be used to achieve transformation invariance during learning and recognition. We demonstrate the application of this classifier to optical character recognition, where it has achieved state-of-the-art results on several reference databases. Relations to other models, in particular those based on principal component analysis, are also discussed.

Distance Training in the European Union. ZIFF Papiere 96.

ERIC Educational Resources Information Center

Keegan, Desmond

A study examined distance training in the European Union (EU) countries. First, recent literature on the following topics was reviewed: technology-supported learning, flexible and distance learning, development of open distance learning, and teleconferencing and distance learning. Next, enrollments and trends in distance learning in the EU as a…

The Use of Facebook to Build a Community for Distance Learning Students: A Case Study from the Open University

ERIC Educational Resources Information Center

Callaghan, George; Fribbance, Ian

2016-01-01

Social media platforms such as Facebook are commonplace throughout society. However, within higher education institutions such networking environments are still in the developmental stage. This paper describes and discusses case study data from the Open University's Faculty of Social Science Facebook page. It starts by giving an overview of the…

The Use of Facebook for Online Discussions among Distance Learners

ERIC Educational Resources Information Center

Lim, Tina

2010-01-01

With the advent of Web 2.0 tools, educators are looking to these new technological tools to examine its potential in enhancing teaching and learning. While its runaway success as a social networking tool is now renowned, the use of Facebook for educational purposes may be considered still at its infancy stage. This paper describes the use of…

Flexible Fusion Structure-Based Performance Optimization Learning for Multisensor Target Tracking

PubMed Central

Ge, Quanbo; Wei, Zhongliang; Cheng, Tianfa; Chen, Shaodong; Wang, Xiangfeng

2017-01-01

Compared with the fixed fusion structure, the flexible fusion structure with mixed fusion methods has better adjustment performance for the complex air task network systems, and it can effectively help the system to achieve the goal under the given constraints. Because of the time-varying situation of the task network system induced by moving nodes and non-cooperative target, and limitations such as communication bandwidth and measurement distance, it is necessary to dynamically adjust the system fusion structure including sensors and fusion methods in a given adjustment period. Aiming at this, this paper studies the design of a flexible fusion algorithm by using an optimization learning technology. The purpose is to dynamically determine the sensors’ numbers and the associated sensors to take part in the centralized and distributed fusion processes, respectively, herein termed sensor subsets selection. Firstly, two system performance indexes are introduced. Especially, the survivability index is presented and defined. Secondly, based on the two indexes and considering other conditions such as communication bandwidth and measurement distance, optimization models for both single target tracking and multi-target tracking are established. Correspondingly, solution steps are given for the two optimization models in detail. Simulation examples are demonstrated to validate the proposed algorithms. PMID:28481243

The Quake Catcher Network: Cyberinfrastructure Bringing Seismology into Schools and Homes

NASA Astrophysics Data System (ADS)

Lawrence, J. F.; Cochran, E. S.

2007-12-01

We propose to implement a high density, low cost strong-motion network for rapid response and early warning by placing sensors in schools, homes, and offices. The Quake Catcher Network (QCN) will employ existing networked laptops and desktops to form the world's largest high-density, distributed computing seismic network. Costs for this network will be minimal because the QCN will use 1) strong motion sensors (accelerometers) already internal to many laptops and 2) nearly identical low-cost universal serial bus (USB) accelerometers for use with desktops. The Berkeley Open Infrastructure for Network Computing (BOINC!) provides a free, proven paradigm for involving the public in large-scale computational research projects. As evidenced by the SETI@home program and others, individuals are especially willing to donate their unused computing power to projects that they deem relevant, worthwhile, and educational. The client- and server-side software will rapidly monitor incoming seismic signals, detect the magnitudes and locations of significant earthquakes, and may even provide early warnings to other computers and users before they can feel the earthquake. The software will provide the client-user with a screen-saver displaying seismic data recorded on their laptop, recently detected earthquakes, and general information about earthquakes and the geosciences. Furthermore, this project will install USB sensors in K-12 classrooms as an educational tool for teaching science. Through a variety of interactive experiments students will learn about earthquakes and the hazards earthquakes pose. For example, students can learn how the vibrations of an earthquake decrease with distance by jumping up and down at increasing distances from the sensor and plotting the decreased amplitude of the seismic signal measured on their computer. We hope to include an audio component so that students can hear and better understand the difference between low and high frequency seismic signals. The QCN will provide a natural way to engage students and the public in earthquake detection and research.

Nearest neighbor imputation using spatial–temporal correlations in wireless sensor networks

PubMed Central

Li, YuanYuan; Parker, Lynne E.

2016-01-01

Missing data is common in Wireless Sensor Networks (WSNs), especially with multi-hop communications. There are many reasons for this phenomenon, such as unstable wireless communications, synchronization issues, and unreliable sensors. Unfortunately, missing data creates a number of problems for WSNs. First, since most sensor nodes in the network are battery-powered, it is too expensive to have the nodes retransmit missing data across the network. Data re-transmission may also cause time delays when detecting abnormal changes in an environment. Furthermore, localized reasoning techniques on sensor nodes (such as machine learning algorithms to classify states of the environment) are generally not robust enough to handle missing data. Since sensor data collected by a WSN is generally correlated in time and space, we illustrate how replacing missing sensor values with spatially and temporally correlated sensor values can significantly improve the network’s performance. However, our studies show that it is important to determine which nodes are spatially and temporally correlated with each other. Simple techniques based on Euclidean distance are not sufficient for complex environmental deployments. Thus, we have developed a novel Nearest Neighbor (NN) imputation method that estimates missing data in WSNs by learning spatial and temporal correlations between sensor nodes. To improve the search time, we utilize a kd-tree data structure, which is a non-parametric, data-driven binary search tree. Instead of using traditional mean and variance of each dimension for kd-tree construction, and Euclidean distance for kd-tree search, we use weighted variances and weighted Euclidean distances based on measured percentages of missing data. We have evaluated this approach through experiments on sensor data from a volcano dataset collected by a network of Crossbow motes, as well as experiments using sensor data from a highway traffic monitoring application. Our experimental results show that our proposed 𝒦-NN imputation method has a competitive accuracy with state-of-the-art Expectation–Maximization (EM) techniques, while using much simpler computational techniques, thus making it suitable for use in resource-constrained WSNs. PMID:28435414

The educational impact of the Specialty Care Access Network-Extension of Community Healthcare Outcomes program.

PubMed

Salgia, Reena J; Mullan, Patricia B; McCurdy, Heather; Sales, Anne; Moseley, Richard H; Su, Grace L

2014-11-01

With the aging hepatitis C cohort and increasing prevalence of fatty liver disease, the burden on primary care providers (PCPs) to care for patients with liver disease is growing. In response, the Veterans Administration implemented initiatives for primary care-specialty referral to increase PCP competency in complex disease management. The Specialty Care Access Network-Extension of Community Healthcare Outcomes (SCAN-ECHO) program initiative was designed to transfer subspecialty knowledge to PCPs through case-based distance learning combined with real-time consultation. There is limited information regarding the initiative's ability to engage PCPs to learn and influence their practice. We surveyed PCPs to determine the factors that led to their participation in this program and the educational impact of participation. Of 51 potential participants, 24 responded to an anonymous survey. More than 75% of respondents participated more than one time in a SCAN-ECHO clinic. Providers were motivated to participate by a desire to learn more about liver disease, to apply the knowledge gained to future patients, and to save their patients time traveling to another center for specialty consultation. Seventy-one percent responded that the didactic component and case-based discussion were equally important. It is important that participation changed clinical practice: 75% of providers indicated they had personally discussed the information they learned from the case presentations with their colleague(s), and 42% indicated they helped a colleague care for their patient with the knowledge learned during discussions of other participants' cases. This study shows that the SCAN-ECHO videoconferencing program between PCPs and specialists can educate providers in the delivery of specialty care from a distance and potentially improve healthcare delivery.

Graph distance for complex networks

NASA Astrophysics Data System (ADS)

Shimada, Yutaka; Hirata, Yoshito; Ikeguchi, Tohru; Aihara, Kazuyuki

2016-10-01

Networks are widely used as a tool for describing diverse real complex systems and have been successfully applied to many fields. The distance between networks is one of the most fundamental concepts for properly classifying real networks, detecting temporal changes in network structures, and effectively predicting their temporal evolution. However, this distance has rarely been discussed in the theory of complex networks. Here, we propose a graph distance between networks based on a Laplacian matrix that reflects the structural and dynamical properties of networked dynamical systems. Our results indicate that the Laplacian-based graph distance effectively quantifies the structural difference between complex networks. We further show that our approach successfully elucidates the temporal properties underlying temporal networks observed in the context of face-to-face human interactions.

Retrieval Capabilities of Hierarchical Networks: From Dyson to Hopfield

NASA Astrophysics Data System (ADS)

Agliari, Elena; Barra, Adriano; Galluzzi, Andrea; Guerra, Francesco; Tantari, Daniele; Tavani, Flavia

2015-01-01

We consider statistical-mechanics models for spin systems built on hierarchical structures, which provide a simple example of non-mean-field framework. We show that the coupling decay with spin distance can give rise to peculiar features and phase diagrams much richer than their mean-field counterpart. In particular, we consider the Dyson model, mimicking ferromagnetism in lattices, and we prove the existence of a number of metastabilities, beyond the ordered state, which become stable in the thermodynamic limit. Such a feature is retained when the hierarchical structure is coupled with the Hebb rule for learning, hence mimicking the modular architecture of neurons, and gives rise to an associative network able to perform single pattern retrieval as well as multiple-pattern retrieval, depending crucially on the external stimuli and on the rate of interaction decay with distance; however, those emergent multitasking features reduce the network capacity with respect to the mean-field counterpart. The analysis is accomplished through statistical mechanics, Markov chain theory, signal-to-noise ratio technique, and numerical simulations in full consistency. Our results shed light on the biological complexity shown by real networks, and suggest future directions for understanding more realistic models.

Artificial Neural Networks as an Architectural Design Tool-Generating New Detail Forms Based On the Roman Corinthian Order Capital

NASA Astrophysics Data System (ADS)

Radziszewski, Kacper

2017-10-01

The following paper presents the results of the research in the field of the machine learning, investigating the scope of application of the artificial neural networks algorithms as a tool in architectural design. The computational experiment was held using the backward propagation of errors method of training the artificial neural network, which was trained based on the geometry of the details of the Roman Corinthian order capital. During the experiment, as an input training data set, five local geometry parameters combined has given the best results: Theta, Pi, Rho in spherical coordinate system based on the capital volume centroid, followed by Z value of the Cartesian coordinate system and a distance from vertical planes created based on the capital symmetry. Additionally during the experiment, artificial neural network hidden layers optimal count and structure was found, giving results of the error below 0.2% for the mentioned before input parameters. Once successfully trained artificial network, was able to mimic the details composition on any other geometry type given. Despite of calculating the transformed geometry locally and separately for each of the thousands of surface points, system could create visually attractive and diverse, complex patterns. Designed tool, based on the supervised learning method of machine learning, gives possibility of generating new architectural forms- free of the designer’s imagination bounds. Implementing the infinitely broad computational methods of machine learning, or Artificial Intelligence in general, not only could accelerate and simplify the design process, but give an opportunity to explore never seen before, unpredictable forms or everyday architectural practice solutions.

Distance learning through synchronous interactive television.

PubMed

Hall, Janis L

2007-01-01

The advent and popularity of asynchronous online learning has somewhat obscured a standby technology developed over the last two decades. Interactive videoconferencing, sometimes called "interactive television," though not as glamorous and popular a topic at distance-learning conferences, is still alive and well at many institutions. Three or four years ago, many of us were led to believe that interactive television would go the way of the dinosaurs-everything would soon be in an asynchronous format or on individual desktops. There would no longer be any need for elaborately designed classrooms, networks, and operations staff. To date, this prediction has not come true. In fact, synchronous interactive television has experienced significant growth as newer, easier, and cheaper technologies allow institutions to reach more students with less resource investment. Faculty and students, while appreciating the convenience of asynchronous delivery, still express a need for synchronous communication. This article explores the issues involved in synchronous distance education, the current technologies and proposed future developments, and best practices in terms of classroom design, faculty use, and operational issues. It is not a research article but an anecdotal case study based on Washington State University's experiences over the last 20 years in developing and adapting to new synchronous technologies and creating the support and technical infrastructure to best deliver academic courses through this medium.

CTS focus about the information and communication technologies on the development of Angola

NASA Astrophysics Data System (ADS)

Patrocínio, Gilberto; Ferreira, Orlando Rodrigues; Schimiguel, Juliano; Silveira, Ismar; Voelzke, Marcos Rincon

2012-10-01

This paper aims at developing a systematic analysis on the Information and Communication Technologies (ICT) and Distance Learning in the development of Angola. Currently Angola as one of the most important African countries, the protagonist of the African Union (AU), is in extensive development and rebuilding themselves socially, economically and politically. In the process, Education becomes essential and, together with a proposal to insert through the Information and Communication Technologies (ICTs), proceeds to the achievement of a future process where science and technology apply in favor of a society, a real action CTS. In this effort we analyzed the most sensitive aspects of the Angolan reality, trying to identify the main points that require dependence on imports in the ICT sector, were also exposed fundamental strategies and initiatives for the implementation of an ICT industry in Angola. It also presented the main center of the Angolan Network for Distance Learning (NDL) and its major partners. And as a proposed application, was taken into consideration the statement of partnership between Southern Cross University and the University Agostinho Neto (UAN) for Distance Education.

Two web-based laboratories of the FisL@bs network: Hooke's and Snell's laws

NASA Astrophysics Data System (ADS)

de la Torre, L.; Sánchez, J.; Dormido, S.; Sánchez, J. P.; Yuste, M.; Carreras, C.

2011-03-01

FisL@bs is a network of remote and virtual laboratories for physics university education via the Internet that offers students the possibility of performing hands-on experiments in different fields of physics in two ways: simulation and real remote operation. This paper gives a detailed account of a novel way in physics in which distance learning students can gain practical experience autonomously. FisL@bs uses the same structure as AutomatL@bs, a network of virtual and remote laboratories for learning/teaching of control engineering, which has been in operation for four years. Students can experiment with the laboratories offered using an Internet connection and a Java-compatible web browser. This paper, specially intended for university educators but easily comprehensible even for undergraduate students, explains how the portal works and the hardware and software tools used to create it. In addition, it also describes two physics experiments already available: spring elasticity and the laws of reflection and refraction.

Has Distance Learning Become More Flexible? Reflections of a Distance Learning Student

ERIC Educational Resources Information Center

Thomas, Theda

2012-01-01

This paper provides insight into the way in which distance learning had changed over the past 30 years from the perspective of the author as a distance learning student. The question is then asked as to whether current practice is reducing flexibility for distance learning students? The paper starts with a discussion of flexible learning and the…

Efficient embedding of complex networks to hyperbolic space via their Laplacian

PubMed Central

Alanis-Lobato, Gregorio; Mier, Pablo; Andrade-Navarro, Miguel A.

2016-01-01

The different factors involved in the growth process of complex networks imprint valuable information in their observable topologies. How to exploit this information to accurately predict structural network changes is the subject of active research. A recent model of network growth sustains that the emergence of properties common to most complex systems is the result of certain trade-offs between node birth-time and similarity. This model has a geometric interpretation in hyperbolic space, where distances between nodes abstract this optimisation process. Current methods for network hyperbolic embedding search for node coordinates that maximise the likelihood that the network was produced by the afore-mentioned model. Here, a different strategy is followed in the form of the Laplacian-based Network Embedding, a simple yet accurate, efficient and data driven manifold learning approach, which allows for the quick geometric analysis of big networks. Comparisons against existing embedding and prediction techniques highlight its applicability to network evolution and link prediction. PMID:27445157

Efficient embedding of complex networks to hyperbolic space via their Laplacian

NASA Astrophysics Data System (ADS)

Alanis-Lobato, Gregorio; Mier, Pablo; Andrade-Navarro, Miguel A.

2016-07-01

The different factors involved in the growth process of complex networks imprint valuable information in their observable topologies. How to exploit this information to accurately predict structural network changes is the subject of active research. A recent model of network growth sustains that the emergence of properties common to most complex systems is the result of certain trade-offs between node birth-time and similarity. This model has a geometric interpretation in hyperbolic space, where distances between nodes abstract this optimisation process. Current methods for network hyperbolic embedding search for node coordinates that maximise the likelihood that the network was produced by the afore-mentioned model. Here, a different strategy is followed in the form of the Laplacian-based Network Embedding, a simple yet accurate, efficient and data driven manifold learning approach, which allows for the quick geometric analysis of big networks. Comparisons against existing embedding and prediction techniques highlight its applicability to network evolution and link prediction.

Impact of VoIP and QoS on Open and Distance Learning

ERIC Educational Resources Information Center

Saxena, P. C.; Jasola, Sanjay; Sharma, Ramesh C.

2006-01-01

Voice over Internet Protocol (VoIP) is becoming a reality in many organizations. The potential for mobility in voice over wi-fi networks will derive demand for the technology. Wireless VoIP is poised to rival VoIP as an alternative telephony tool. Internet has been used to transport data in the form of packet. In the past, Internet did not support…

2011 Technology Expo

NASA Image and Video Library

2011-05-26

Phillip Stallcup with Agilent Technologies in Huntsville, Ala., talks with NASA employees Leslie Ladner (l) and Kelly Sullivan about spectrum analyzers and other test equipment during the Stennis Technology Expo on May 26. The expo was hosted by NASA Solutions for Enterprise-Wide Procurement and featured various exhibitors demonstrating the latest in a range of technologies, such as training equipment, secure data storage, video networks, distance learning and data management.

Predicting Flavonoid UGT Regioselectivity

PubMed Central

Jackson, Rhydon; Knisley, Debra; McIntosh, Cecilia; Pfeiffer, Phillip

2011-01-01

Machine learning was applied to a challenging and biologically significant protein classification problem: the prediction of avonoid UGT acceptor regioselectivity from primary sequence. Novel indices characterizing graphical models of residues were proposed and found to be widely distributed among existing amino acid indices and to cluster residues appropriately. UGT subsequences biochemically linked to regioselectivity were modeled as sets of index sequences. Several learning techniques incorporating these UGT models were compared with classifications based on standard sequence alignment scores. These techniques included an application of time series distance functions to protein classification. Time series distances defined on the index sequences were used in nearest neighbor and support vector machine classifiers. Additionally, Bayesian neural network classifiers were applied to the index sequences. The experiments identified improvements over the nearest neighbor and support vector machine classifications relying on standard alignment similarity scores, as well as strong correlations between specific subsequences and regioselectivities. PMID:21747849

Network-level accident-mapping: Distance based pattern matching using artificial neural network.

PubMed

Deka, Lipika; Quddus, Mohammed

2014-04-01

The objective of an accident-mapping algorithm is to snap traffic accidents onto the correct road segments. Assigning accidents onto the correct segments facilitate to robustly carry out some key analyses in accident research including the identification of accident hot-spots, network-level risk mapping and segment-level accident risk modelling. Existing risk mapping algorithms have some severe limitations: (i) they are not easily 'transferable' as the algorithms are specific to given accident datasets; (ii) they do not perform well in all road-network environments such as in areas of dense road network; and (iii) the methods used do not perform well in addressing inaccuracies inherent in and type of road environment. The purpose of this paper is to develop a new accident mapping algorithm based on the common variables observed in most accident databases (e.g. road name and type, direction of vehicle movement before the accident and recorded accident location). The challenges here are to: (i) develop a method that takes into account uncertainties inherent to the recorded traffic accident data and the underlying digital road network data, (ii) accurately determine the type and proportion of inaccuracies, and (iii) develop a robust algorithm that can be adapted for any accident set and road network of varying complexity. In order to overcome these challenges, a distance based pattern-matching approach is used to identify the correct road segment. This is based on vectors containing feature values that are common in the accident data and the network data. Since each feature does not contribute equally towards the identification of the correct road segments, an ANN approach using the single-layer perceptron is used to assist in "learning" the relative importance of each feature in the distance calculation and hence the correct link identification. The performance of the developed algorithm was evaluated based on a reference accident dataset from the UK confirming that the accuracy is much better than other methods. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Efficient Training of Supervised Spiking Neural Network via Accurate Synaptic-Efficiency Adjustment Method.

PubMed

Xie, Xiurui; Qu, Hong; Yi, Zhang; Kurths, Jurgen

2017-06-01

The spiking neural network (SNN) is the third generation of neural networks and performs remarkably well in cognitive tasks, such as pattern recognition. The temporal neural encode mechanism found in biological hippocampus enables SNN to possess more powerful computation capability than networks with other encoding schemes. However, this temporal encoding approach requires neurons to process information serially on time, which reduces learning efficiency significantly. To keep the powerful computation capability of the temporal encoding mechanism and to overcome its low efficiency in the training of SNNs, a new training algorithm, the accurate synaptic-efficiency adjustment method is proposed in this paper. Inspired by the selective attention mechanism of the primate visual system, our algorithm selects only the target spike time as attention areas, and ignores voltage states of the untarget ones, resulting in a significant reduction of training time. Besides, our algorithm employs a cost function based on the voltage difference between the potential of the output neuron and the firing threshold of the SNN, instead of the traditional precise firing time distance. A normalized spike-timing-dependent-plasticity learning window is applied to assigning this error to different synapses for instructing their training. Comprehensive simulations are conducted to investigate the learning properties of our algorithm, with input neurons emitting both single spike and multiple spikes. Simulation results indicate that our algorithm possesses higher learning performance than the existing other methods and achieves the state-of-the-art efficiency in the training of SNN.

A robust sound perception model suitable for neuromorphic implementation.

PubMed

Coath, Martin; Sheik, Sadique; Chicca, Elisabetta; Indiveri, Giacomo; Denham, Susan L; Wennekers, Thomas

2013-01-01

We have recently demonstrated the emergence of dynamic feature sensitivity through exposure to formative stimuli in a real-time neuromorphic system implementing a hybrid analog/digital network of spiking neurons. This network, inspired by models of auditory processing in mammals, includes several mutually connected layers with distance-dependent transmission delays and learning in the form of spike timing dependent plasticity, which effects stimulus-driven changes in the network connectivity. Here we present results that demonstrate that the network is robust to a range of variations in the stimulus pattern, such as are found in naturalistic stimuli and neural responses. This robustness is a property critical to the development of realistic, electronic neuromorphic systems. We analyze the variability of the response of the network to "noisy" stimuli which allows us to characterize the acuity in information-theoretic terms. This provides an objective basis for the quantitative comparison of networks, their connectivity patterns, and learning strategies, which can inform future design decisions. We also show, using stimuli derived from speech samples, that the principles are robust to other challenges, such as variable presentation rate, that would have to be met by systems deployed in the real world. Finally we demonstrate the potential applicability of the approach to real sounds.

A fast community detection method in bipartite networks by distance dynamics

NASA Astrophysics Data System (ADS)

Sun, Hong-liang; Ch'ng, Eugene; Yong, Xi; Garibaldi, Jonathan M.; See, Simon; Chen, Duan-bing

2018-04-01

Many real bipartite networks are found to be divided into two-mode communities. In this paper, we formulate a new two-mode community detection algorithm BiAttractor. It is based on distance dynamics model Attractor proposed by Shao et al. with extension from unipartite to bipartite networks. Since Jaccard coefficient of distance dynamics model is incapable to measure distances of different types of vertices in bipartite networks, our main contribution is to extend distance dynamics model from unipartite to bipartite networks using a novel measure Local Jaccard Distance (LJD). Furthermore, distances between different types of vertices are not affected by common neighbors in the original method. This new idea makes clear assumptions and yields interpretable results in linear time complexity O(| E |) in sparse networks, where | E | is the number of edges. Experiments on synthetic networks demonstrate it is capable to overcome resolution limit compared with existing other methods. Further research on real networks shows that this model can accurately detect interpretable community structures in a short time.

Predicting backbone Cα angles and dihedrals from protein sequences by stacked sparse auto-encoder deep neural network.

PubMed

Lyons, James; Dehzangi, Abdollah; Heffernan, Rhys; Sharma, Alok; Paliwal, Kuldip; Sattar, Abdul; Zhou, Yaoqi; Yang, Yuedong

2014-10-30

Because a nearly constant distance between two neighbouring Cα atoms, local backbone structure of proteins can be represented accurately by the angle between C(αi-1)-C(αi)-C(αi+1) (θ) and a dihedral angle rotated about the C(αi)-C(αi+1) bond (τ). θ and τ angles, as the representative of structural properties of three to four amino-acid residues, offer a description of backbone conformations that is complementary to φ and ψ angles (single residue) and secondary structures (>3 residues). Here, we report the first machine-learning technique for sequence-based prediction of θ and τ angles. Predicted angles based on an independent test have a mean absolute error of 9° for θ and 34° for τ with a distribution on the θ-τ plane close to that of native values. The average root-mean-square distance of 10-residue fragment structures constructed from predicted θ and τ angles is only 1.9Å from their corresponding native structures. Predicted θ and τ angles are expected to be complementary to predicted ϕ and ψ angles and secondary structures for using in model validation and template-based as well as template-free structure prediction. The deep neural network learning technique is available as an on-line server called Structural Property prediction with Integrated DEep neuRal network (SPIDER) at http://sparks-lab.org. Copyright © 2014 Wiley Periodicals, Inc.

Inclusive Approach to the Psycho-Pedagogical Assistance of Distance Learning

ERIC Educational Resources Information Center

Akhmetova, Daniya Z.

2014-01-01

Author focuses on three groups of problems: quality of distance learning and e-learning; necessity to develop the facilitation skills for teachers who work using distance learning technologies; realization of inclusive approach for the organization of distance learning in inclusive groups where people with disabilities study with people without…

Developing an online professional network for veterinary education: the NOVICE project.

PubMed

Baillie, Sarah; Kinnison, Tierney; Forrest, Neil; Dale, Vicki H M; Ehlers, Jan P; Koch, Michael; Mándoki, Mira; Ciobotaru, Emilia; de Groot, Esther; Boerboom, Tobias B B; van Beukelen, Peter

2011-01-01

An online professional network for veterinarians, veterinary students, veterinary educationalists, and ICT (Information and Communication Technology) educationalists is being developed under the EU (European Union) Lifelong Learning Programme. The network uses Web 2.0, a term used to describe the new, more interactive version of the Internet, and includes tools such as wikis, blogs, and discussion boards. Focus groups conducted with qualified and student veterinarians within the project's five founding countries (The Netherlands, Germany, United Kingdom, Hungary, Romania) demonstrated that online professional communities can be valuable for accessing information and establishing contacts. Online networks have the potential to overcome common challenges to face-to-face communities-such as distance, cost, and timing-but they have their own drawbacks, such as security and professionalism issues. The Network Of Veterinary ICt in Education (NOVICE) was developed using Elgg, an open-source, free social networking platform, after several software options had been considered. NOVICE aims to promote the understanding of Web 2.0, confidence to use social software tools, and participation in an online community. Therefore, the Web site contains help sections, Frequently Asked Questions, and access to support from ICT experts. Five months after the network's launch (and just over one year into the project) 515 members from 28 countries had registered. Further research will include analysis of a core group's activities, which will inform ongoing support for and development of informal, lifelong learning in a veterinary context.

Emergent Auditory Feature Tuning in a Real-Time Neuromorphic VLSI System.

PubMed

Sheik, Sadique; Coath, Martin; Indiveri, Giacomo; Denham, Susan L; Wennekers, Thomas; Chicca, Elisabetta

2012-01-01

Many sounds of ecological importance, such as communication calls, are characterized by time-varying spectra. However, most neuromorphic auditory models to date have focused on distinguishing mainly static patterns, under the assumption that dynamic patterns can be learned as sequences of static ones. In contrast, the emergence of dynamic feature sensitivity through exposure to formative stimuli has been recently modeled in a network of spiking neurons based on the thalamo-cortical architecture. The proposed network models the effect of lateral and recurrent connections between cortical layers, distance-dependent axonal transmission delays, and learning in the form of Spike Timing Dependent Plasticity (STDP), which effects stimulus-driven changes in the pattern of network connectivity. In this paper we demonstrate how these principles can be efficiently implemented in neuromorphic hardware. In doing so we address two principle problems in the design of neuromorphic systems: real-time event-based asynchronous communication in multi-chip systems, and the realization in hybrid analog/digital VLSI technology of neural computational principles that we propose underlie plasticity in neural processing of dynamic stimuli. The result is a hardware neural network that learns in real-time and shows preferential responses, after exposure, to stimuli exhibiting particular spectro-temporal patterns. The availability of hardware on which the model can be implemented, makes this a significant step toward the development of adaptive, neurobiologically plausible, spike-based, artificial sensory systems.

Emergent Auditory Feature Tuning in a Real-Time Neuromorphic VLSI System

PubMed Central

Sheik, Sadique; Coath, Martin; Indiveri, Giacomo; Denham, Susan L.; Wennekers, Thomas; Chicca, Elisabetta

2011-01-01

Many sounds of ecological importance, such as communication calls, are characterized by time-varying spectra. However, most neuromorphic auditory models to date have focused on distinguishing mainly static patterns, under the assumption that dynamic patterns can be learned as sequences of static ones. In contrast, the emergence of dynamic feature sensitivity through exposure to formative stimuli has been recently modeled in a network of spiking neurons based on the thalamo-cortical architecture. The proposed network models the effect of lateral and recurrent connections between cortical layers, distance-dependent axonal transmission delays, and learning in the form of Spike Timing Dependent Plasticity (STDP), which effects stimulus-driven changes in the pattern of network connectivity. In this paper we demonstrate how these principles can be efficiently implemented in neuromorphic hardware. In doing so we address two principle problems in the design of neuromorphic systems: real-time event-based asynchronous communication in multi-chip systems, and the realization in hybrid analog/digital VLSI technology of neural computational principles that we propose underlie plasticity in neural processing of dynamic stimuli. The result is a hardware neural network that learns in real-time and shows preferential responses, after exposure, to stimuli exhibiting particular spectro-temporal patterns. The availability of hardware on which the model can be implemented, makes this a significant step toward the development of adaptive, neurobiologically plausible, spike-based, artificial sensory systems. PMID:22347163

Distance Learning.

ERIC Educational Resources Information Center

Orey, Michael; Koenecke, Lynne; Snider, Richard C.; Perkins, Ross A.; Holmes, Glen A.; Lockee, Barbara B.; Moller, Leslie A.; Harvey, Douglas; Downs, Margaret; Godshalk, Veronica M.

2003-01-01

Contains four articles covering trends and issues on distance learning including: the experience of two learners learning via the Internet; a systematic approach to determining the scalability of a distance education program; identifying factors that affect learning community development and performance in asynchronous distance education; and…

46 CFR 10.412 - Distance and e-learning.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 1 2014-10-01 2014-10-01 false Distance and e-learning. 10.412 Section 10.412 Shipping... CREDENTIAL Training Courses and Programs § 10.412 Distance and e-learning. The Coast Guard may allow the training of mariners by means of distance learning and e-learning in accordance with the standards of...

Self-Regulated Learning Ability of Chinese Distance Learners

ERIC Educational Resources Information Center

Zhao, Hong; Chen, Li; Panda, Santosh

2014-01-01

This study reports on self-regulated learning (SRL) of Chinese distance learners by using a structured SRL scale. SRL of adult and lifelong learners is a well-researched area, though its application within distance education is a new area of investigation. Open and distance learning lean heavily on self-learning and self-learning resources, though…

Learning characteristics of veterinary technology students in a distance-education and an on-campus program.

PubMed

Varnhagen, Connie K; Wright, David L

2008-01-01

Distance-education programs have the potential to greatly increase the number of veterinary technicians. The demographic characteristics, readiness for independent and online learning, learning styles, and academic locus of control of a group of distance-education and on-campus veterinary technology students were examined. Distance-education students preferred independent learning and were more internally motivated to learn. Distance-education students with greater degrees of independence and internal motivation participated more fully, were more satisfied with their learning, and achieved higher grades. Students who preferred problem solving and active experimentation were particularly successful in distance education. These findings could have important implications for advising students interested in distance-education programs.

Automatic 3D liver location and segmentation via convolutional neural network and graph cut.

PubMed

Lu, Fang; Wu, Fa; Hu, Peijun; Peng, Zhiyi; Kong, Dexing

2017-02-01

Segmentation of the liver from abdominal computed tomography (CT) images is an essential step in some computer-assisted clinical interventions, such as surgery planning for living donor liver transplant, radiotherapy and volume measurement. In this work, we develop a deep learning algorithm with graph cut refinement to automatically segment the liver in CT scans. The proposed method consists of two main steps: (i) simultaneously liver detection and probabilistic segmentation using 3D convolutional neural network; (ii) accuracy refinement of the initial segmentation with graph cut and the previously learned probability map. The proposed approach was validated on forty CT volumes taken from two public databases MICCAI-Sliver07 and 3Dircadb1. For the MICCAI-Sliver07 test dataset, the calculated mean ratios of volumetric overlap error (VOE), relative volume difference (RVD), average symmetric surface distance (ASD), root-mean-square symmetric surface distance (RMSD) and maximum symmetric surface distance (MSD) are 5.9, 2.7 %, 0.91, 1.88 and 18.94 mm, respectively. For the 3Dircadb1 dataset, the calculated mean ratios of VOE, RVD, ASD, RMSD and MSD are 9.36, 0.97 %, 1.89, 4.15 and 33.14 mm, respectively. The proposed method is fully automatic without any user interaction. Quantitative results reveal that the proposed approach is efficient and accurate for hepatic volume estimation in a clinical setup. The high correlation between the automatic and manual references shows that the proposed method can be good enough to replace the time-consuming and nonreproducible manual segmentation method.

Locality preserving non-negative basis learning with graph embedding.

PubMed

Ghanbari, Yasser; Herrington, John; Gur, Ruben C; Schultz, Robert T; Verma, Ragini

2013-01-01

The high dimensionality of connectivity networks necessitates the development of methods identifying the connectivity building blocks that not only characterize the patterns of brain pathology but also reveal representative population patterns. In this paper, we present a non-negative component analysis framework for learning localized and sparse sub-network patterns of connectivity matrices by decomposing them into two sets of discriminative and reconstructive bases. In order to obtain components that are designed towards extracting population differences, we exploit the geometry of the population by using a graphtheoretical scheme that imposes locality-preserving properties as well as maintaining the underlying distance between distant nodes in the original and the projected space. The effectiveness of the proposed framework is demonstrated by applying it to two clinical studies using connectivity matrices derived from DTI to study a population of subjects with ASD, as well as a developmental study of structural brain connectivity that extracts gender differences.

Joint learning of labels and distance metric.

PubMed

Liu, Bo; Wang, Meng; Hong, Richang; Zha, Zhengjun; Hua, Xian-Sheng

2010-06-01

Machine learning algorithms frequently suffer from the insufficiency of training data and the usage of inappropriate distance metric. In this paper, we propose a joint learning of labels and distance metric (JLLDM) approach, which is able to simultaneously address the two difficulties. In comparison with the existing semi-supervised learning and distance metric learning methods that focus only on label prediction or distance metric construction, the JLLDM algorithm optimizes the labels of unlabeled samples and a Mahalanobis distance metric in a unified scheme. The advantage of JLLDM is multifold: 1) the problem of training data insufficiency can be tackled; 2) a good distance metric can be constructed with only very few training samples; and 3) no radius parameter is needed since the algorithm automatically determines the scale of the metric. Extensive experiments are conducted to compare the JLLDM approach with different semi-supervised learning and distance metric learning methods, and empirical results demonstrate its effectiveness.

Distance and Face-to-Face Learning Culture and Values: A Conceptual Analysis

ERIC Educational Resources Information Center

Tejeda-Delgado, Carmen; Millan, Brett J.; Slate, John R.

2011-01-01

With distance learning increasing in popularity across the country and the world, a review of the extant literature as it relates to distance learning and face-to-face learning is warranted. In particular, this paper examined distance learning, including a historical overview, prevailing themes in past research, and studies relating the importance…

Astronautics degrees for the space industry

NASA Astrophysics Data System (ADS)

Gruntman, M.; Brodsky, R. F.; Erwin, D. A.; Kunc, J. A.

2004-01-01

The Astronautics Program (http://astronautics.usc.edu) of the University of Southern California (USC) offers a full set of undergraduate and graduate degree programs in Aerospace Engineering with emphasis in Astronautics. The Bachelor of Science and Master of Science degree programs in Astronautics combine basic science and engineering classes with specialized classes in space technology. The Certificate in Astronautics targets practicing engineers and scientists who enter space-related fields and/or who want to obtain training in specific space-related areas. Many specialized graduate classes are taught by adjunct faculty working at the leading space companies. The Master of Science degree and Certificate are available entirely through the USC Distance Education Network (DEN). Today, the Internet allows us to reach students anywhere in the world through webcasting. The majority of our graduate students, as well as those pursuing the Certificate, work full time as engineers in the space industry and government research and development centers while earning their degrees. The new world of distance learning presents new challenges and opens new opportunities. Distance learning, and particularly the introduction of webcasting, transform the organization of the graduate program and class delivery. We describe in detail the program's academic focus, student reach, and structure of program components. Program development is illustrated by the student enrollment dynamics and related industrial trends; the lessons learned emphasize the importance of feedback from the students and from the space industry.

International Perspectives of Distance Learning in Higher Education

ERIC Educational Resources Information Center

Moore, Joi L., Ed.; Benson, Angela D., Ed.

2012-01-01

This book, written by authors representing 12 countries and five continents, is a collection of international perspectives on distance learning and distance learning implementations in higher education. The perspectives are presented in the form of practical case studies of distance learning implementations, research studies on teaching and…

Internet-Based Distance Learning in Higher Education.

ERIC Educational Resources Information Center

Hofmann, Donald W.

2002-01-01

Suggests that the effectiveness of Internet-based distance learning has increased with its increased popularity. Looks at the differences between the effectiveness of Internet-based distance learning and traditional methods. Indicates that distance learning is more effective because of the necessity for students to become active learners.…

Distance Education and Distance Learning: Some Psychological Considerations.

ERIC Educational Resources Information Center

Cropley, Arthur J.; Kahl, Thomas N.

1983-01-01

Compares and contrasts distance education and face-to-face education in terms of selected psychological dimensions, i.e., organization and learning, motivation, learning and communication processes, didactic activities and materials, and evaluation and feedback. Psychological aspects of distance education that may be favorable to learning are also…

Evaluation of a distance-learning immunology and pathology module in a postgraduate biomedical science course.

PubMed

Ryan, M T; Mulholland, C W

2005-01-01

An electronic presentation of materials for a distance-learning immunology and pathology module from a postgraduate biomedical science course is evaluated. Two different electronic presentation formats for the delivery of the educational material to distance learners are assessed. Responses from users of this material highlighted a preference for a format that has a design tailored to distance learning. There was no significant difference in learning outcome between those taking the module on campus and by distance learning. This suggests that the prerequisites for entry, learning materials and direction given to the students studying by distance learning are adequate for these students to achieve the learning objectives outlined in the course. The evaluation also gave direction for areas within the (CAL) application that can be improved for future students.

Neural networks for satellite remote sensing and robotic sensor interpretation

NASA Astrophysics Data System (ADS)

Martens, Siegfried

Remote sensing of forests and robotic sensor fusion can be viewed, in part, as supervised learning problems, mapping from sensory input to perceptual output. This dissertation develops ARTMAP neural networks for real-time category learning, pattern recognition, and prediction tailored to remote sensing and robotics applications. Three studies are presented. The first two use ARTMAP to create maps from remotely sensed data, while the third uses an ARTMAP system for sensor fusion on a mobile robot. The first study uses ARTMAP to predict vegetation mixtures in the Plumas National Forest based on spectral data from the Landsat Thematic Mapper satellite. While most previous ARTMAP systems have predicted discrete output classes, this project develops new capabilities for multi-valued prediction. On the mixture prediction task, the new network is shown to perform better than maximum likelihood and linear mixture models. The second remote sensing study uses an ARTMAP classification system to evaluate the relative importance of spectral and terrain data for map-making. This project has produced a large-scale map of remotely sensed vegetation in the Sierra National Forest. Network predictions are validated with ground truth data, and maps produced using the ARTMAP system are compared to a map produced by human experts. The ARTMAP Sierra map was generated in an afternoon, while the labor intensive expert method required nearly a year to perform the same task. The robotics research uses an ARTMAP system to integrate visual information and ultrasonic sensory information on a B14 mobile robot. The goal is to produce a more accurate measure of distance than is provided by the raw sensors. ARTMAP effectively combines sensory sources both within and between modalities. The improved distance percept is used to produce occupancy grid visualizations of the robot's environment. The maps produced point to specific problems of raw sensory information processing and demonstrate the benefits of using a neural network system for sensor fusion.

Convolutional neural network features based change detection in satellite images

NASA Astrophysics Data System (ADS)

Mohammed El Amin, Arabi; Liu, Qingjie; Wang, Yunhong

2016-07-01

With the popular use of high resolution remote sensing (HRRS) satellite images, a huge research efforts have been placed on change detection (CD) problem. An effective feature selection method can significantly boost the final result. While hand-designed features have proven difficulties to design features that effectively capture high and mid-level representations, the recent developments in machine learning (Deep Learning) omit this problem by learning hierarchical representation in an unsupervised manner directly from data without human intervention. In this letter, we propose approaching the change detection problem from a feature learning perspective. A novel deep Convolutional Neural Networks (CNN) features based HR satellite images change detection method is proposed. The main guideline is to produce a change detection map directly from two images using a pretrained CNN. This method can omit the limited performance of hand-crafted features. Firstly, CNN features are extracted through different convolutional layers. Then, a concatenation step is evaluated after an normalization step, resulting in a unique higher dimensional feature map. Finally, a change map was computed using pixel-wise Euclidean distance. Our method has been validated on real bitemporal HRRS satellite images according to qualitative and quantitative analyses. The results obtained confirm the interest of the proposed method.

Skin Lesion Analysis towards Melanoma Detection Using Deep Learning Network.

PubMed

Li, Yuexiang; Shen, Linlin

2018-02-11

Skin lesions are a severe disease globally. Early detection of melanoma in dermoscopy images significantly increases the survival rate. However, the accurate recognition of melanoma is extremely challenging due to the following reasons: low contrast between lesions and skin, visual similarity between melanoma and non-melanoma lesions, etc. Hence, reliable automatic detection of skin tumors is very useful to increase the accuracy and efficiency of pathologists. In this paper, we proposed two deep learning methods to address three main tasks emerging in the area of skin lesion image processing, i.e., lesion segmentation (task 1), lesion dermoscopic feature extraction (task 2) and lesion classification (task 3). A deep learning framework consisting of two fully convolutional residual networks (FCRN) is proposed to simultaneously produce the segmentation result and the coarse classification result. A lesion index calculation unit (LICU) is developed to refine the coarse classification results by calculating the distance heat-map. A straight-forward CNN is proposed for the dermoscopic feature extraction task. The proposed deep learning frameworks were evaluated on the ISIC 2017 dataset. Experimental results show the promising accuracies of our frameworks, i.e., 0.753 for task 1, 0.848 for task 2 and 0.912 for task 3 were achieved.

A Delphi Study on Collaborative Learning in Distance Education: The Faculty Perspective

ERIC Educational Resources Information Center

O'Neill, Susan; Scott, Murray; Conboy, Kieran

2011-01-01

This paper focuses on the factors that influence collaborative learning in distance education. Distance education has been around for many years and the use of collaborative learning techniques in distance education is becoming increasingly popular. Several studies have demonstrated the superiority of collaborative learning over traditional modes…

Distance Learning in Higher Education. CHEA Update Number 3.

ERIC Educational Resources Information Center

Council for Higher Education Accreditation, Washington, DC.

This report discusses issues related to distance learning in higher education. Section 1, "The Expanding Universe of Distance Learning," examines: data from a new national survey on higher education distance learning; Internet access in elementary and secondary schools; the 1999 national survey of information technology in higher…

7 CFR 1700.31 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 11 2010-01-01 2010-01-01 false Distance Learning and Telemedicine Loan and Grant... § 1700.31 Distance Learning and Telemedicine Loan and Grant Program. RUS, through the Telecommunications Program, makes grants and loans to furnish and improve telemedicine services and distance learning...

Tidewater Community College Distance Learning Report.

ERIC Educational Resources Information Center

Tidewater Community Coll., Norfolk, VA.

This study of distance learning at Tidewater Community College (TCC) was conducted to determine enrollment patterns, retention, and success in distance learning courses and student perceptions. Distance learning was defined as students enrolled in one of three modes of course delivery: telecourse, online, and compressed video. The time frame for…

7 CFR 1700.31 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 11 2013-01-01 2013-01-01 false Distance Learning and Telemedicine Loan and Grant... § 1700.31 Distance Learning and Telemedicine Loan and Grant Program. RUS, through the Telecommunications Program, makes grants and loans to furnish and improve telemedicine services and distance learning...

7 CFR 1700.31 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 11 2011-01-01 2011-01-01 false Distance Learning and Telemedicine Loan and Grant... § 1700.31 Distance Learning and Telemedicine Loan and Grant Program. RUS, through the Telecommunications Program, makes grants and loans to furnish and improve telemedicine services and distance learning...

7 CFR 1700.31 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 11 2012-01-01 2012-01-01 false Distance Learning and Telemedicine Loan and Grant... § 1700.31 Distance Learning and Telemedicine Loan and Grant Program. RUS, through the Telecommunications Program, makes grants and loans to furnish and improve telemedicine services and distance learning...

7 CFR 1700.31 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 11 2014-01-01 2014-01-01 false Distance Learning and Telemedicine Loan and Grant... § 1700.31 Distance Learning and Telemedicine Loan and Grant Program. RUS, through the Telecommunications Program, makes grants and loans to furnish and improve telemedicine services and distance learning...

Distance Learning: A Way of Life-Long Learning

DTIC Science & Technology

2005-09-01

promise of future benefits. 15. SUBJECT TERMS training, educational technology , distributed learning , distance learning , collaboration, online instruction...knowledge." - Aristotle Introduction Modern learning technology assumes various names: distance learning , distributed training, computer-based...training, web-based learning , or advanced distributed learning . No matter the name, the basic concept is using computer technology for instruction with no

General Services Administration: FY 1998 Congressional Justification.

DTIC Science & Technology

1997-03-20

APPROPRIATIONS: Consumer Information Center CIC GSA InSite STATEMENT OF DAVID J. BARRAM ACTING ADMINISTRATOR, GENERAL SERVICES ADMINISTRATION BEFORE THE...in every area in which we operate. I think three impulses drive us toward change. First, we believe the customer is king. We’re learning what that...really means. We thrill our customers with GSA Advantage!, with less than 2 cents a network minute for long distance on-net telephone service, and

Continuous Chinese sign language recognition with CNN-LSTM

NASA Astrophysics Data System (ADS)

Yang, Su; Zhu, Qing

2017-07-01

The goal of sign language recognition (SLR) is to translate the sign language into text, and provide a convenient tool for the communication between the deaf-mute and the ordinary. In this paper, we formulate an appropriate model based on convolutional neural network (CNN) combined with Long Short-Term Memory (LSTM) network, in order to accomplish the continuous recognition work. With the strong ability of CNN, the information of pictures captured from Chinese sign language (CSL) videos can be learned and transformed into vector. Since the video can be regarded as an ordered sequence of frames, LSTM model is employed to connect with the fully-connected layer of CNN. As a recurrent neural network (RNN), it is suitable for sequence learning tasks with the capability of recognizing patterns defined by temporal distance. Compared with traditional RNN, LSTM has performed better on storing and accessing information. We evaluate this method on our self-built dataset including 40 daily vocabularies. The experimental results show that the recognition method with CNN-LSTM can achieve a high recognition rate with small training sets, which will meet the needs of real-time SLR system.

Application of artificial neural network to search for gravitational-wave signals associated with short gamma-ray bursts

NASA Astrophysics Data System (ADS)

Kim, Kyungmin; Harry, Ian W.; Hodge, Kari A.; Kim, Young-Min; Lee, Chang-Hwan; Lee, Hyun Kyu; Oh, John J.; Oh, Sang Hoon; Son, Edwin J.

2015-12-01

We apply a machine learning algorithm, the artificial neural network, to the search for gravitational-wave signals associated with short gamma-ray bursts (GRBs). The multi-dimensional samples consisting of data corresponding to the statistical and physical quantities from the coherent search pipeline are fed into the artificial neural network to distinguish simulated gravitational-wave signals from background noise artifacts. Our result shows that the data classification efficiency at a fixed false alarm probability (FAP) is improved by the artificial neural network in comparison to the conventional detection statistic. Specifically, the distance at 50% detection probability at a fixed false positive rate is increased about 8%-14% for the considered waveform models. We also evaluate a few seconds of the gravitational-wave data segment using the trained networks and obtain the FAP. We suggest that the artificial neural network can be a complementary method to the conventional detection statistic for identifying gravitational-wave signals related to the short GRBs.

Innovation in Open & Distance Learning: Successful Development of Online and Web-Based Learning.

ERIC Educational Resources Information Center

Lockwood, Fred, Ed.; Gooley, Anne, Ed.

This book contains 19 papers examining innovation in open and distance learning through development of online and World Wide Web-based learning. The following papers are included: "Innovation in Distributed Learning: Creating the Environment" (Fred Lockwood); "Innovation in Open and Distance Learning: Some Lessons from Experience…

Higher Education through Open and Distance Learning. World Review of Distance Education and Open Learning, Volume 1. A Commonwealth of Learning Series.

ERIC Educational Resources Information Center

Harry, Keith, Ed.

This book reports on the expansion of open and distance learning during the past decade, examining ways in which open and distance learning for higher education has responded to the needs of the new society, and summarizing the lessons of recent practice for policymakers and educators. After an introductory chapter, "Open and Distance…

Distance-Learning for Advanced Military Education: Using Wargame Simulation Course as an Example

ERIC Educational Resources Information Center

Keh, Huan-Chao; Wang, Kuei-Min; Wai, Shu-Shen; Huang, Jiung-yao; Hui, Lin; Wu, Ji-Jen

2008-01-01

Distance learning in advanced military education can assist officers around the world to become more skilled and qualified for future challenges. Through well-chosen technology, the efficiency of distance-learning can be improved significantly. In this paper we present the architecture of Advanced Military Education-Distance Learning (AME-DL)…

Making Distance Learning E.R.O.T.I.C.: Applying Interpretation Principles to Distance Learning

ERIC Educational Resources Information Center

Ross, Anne; Siepen, Greg; O'Connor, Sue

2003-01-01

Distance learners are self-directed learners traditionally taught via study books, collections of readings, and exercises to test understanding of learning packages. Despite advances in e-Learning environments and computer-based teaching interfaces, distance learners still lack opportunities to participate in exercises and debates available to…

Accreditation and Assuring Quality in Distance Learning. CHEA Monograph Series, 2002.

ERIC Educational Resources Information Center

Council for Higher Education Accreditation, Washington, DC.

This report describes the scope and impact of distance learning on higher education and identifies the primary challenges that distance learning poses for accreditation. The responses of the accrediting community designed to assure quality in distance learning are outlined. Data from a variety of sources show that 5,655 institutions are accredited…

Distance Learning and Non-Formal Education: Existing Trends and New Possibilities of Distance Learning Experiences.

ERIC Educational Resources Information Center

Romi, Shlomo

2000-01-01

Reviews the characteristics of non-formal education as expressed in various academic-theoretical definitions, presents the links in this field to distance learning, and recommends future directions for exploring distance learning in non-formal education. Discusses the use of information and communication technology and considers problems with…

The Anatomical Distance of Functional Connections Predicts Brain Network Topology in Health and Schizophrenia

PubMed Central

Vértes, Petra E.; Stidd, Reva; Lalonde, François; Clasen, Liv; Rapoport, Judith; Giedd, Jay; Bullmore, Edward T.; Gogtay, Nitin

2013-01-01

The human brain is a topologically complex network embedded in anatomical space. Here, we systematically explored relationships between functional connectivity, complex network topology, and anatomical (Euclidean) distance between connected brain regions, in the resting-state functional magnetic resonance imaging brain networks of 20 healthy volunteers and 19 patients with childhood-onset schizophrenia (COS). Normal between-subject differences in average distance of connected edges in brain graphs were strongly associated with variation in topological properties of functional networks. In addition, a club or subset of connector hubs was identified, in lateral temporal, parietal, dorsal prefrontal, and medial prefrontal/cingulate cortical regions. In COS, there was reduced strength of functional connectivity over short distances especially, and therefore, global mean connection distance of thresholded graphs was significantly greater than normal. As predicted from relationships between spatial and topological properties of normal networks, this disorder-related proportional increase in connection distance was associated with reduced clustering and modularity and increased global efficiency of COS networks. Between-group differences in connection distance were localized specifically to connector hubs of multimodal association cortex. In relation to the neurodevelopmental pathogenesis of schizophrenia, we argue that the data are consistent with the interpretation that spatial and topological disturbances of functional network organization could arise from excessive “pruning” of short-distance functional connections in schizophrenia. PMID:22275481

Transform- and multi-domain deep learning for single-frame rapid autofocusing in whole slide imaging.

PubMed

Jiang, Shaowei; Liao, Jun; Bian, Zichao; Guo, Kaikai; Zhang, Yongbing; Zheng, Guoan

2018-04-01

A whole slide imaging (WSI) system has recently been approved for primary diagnostic use in the US. The image quality and system throughput of WSI is largely determined by the autofocusing process. Traditional approaches acquire multiple images along the optical axis and maximize a figure of merit for autofocusing. Here we explore the use of deep convolution neural networks (CNNs) to predict the focal position of the acquired image without axial scanning. We investigate the autofocusing performance with three illumination settings: incoherent Kohler illumination, partially coherent illumination with two plane waves, and one-plane-wave illumination. We acquire ~130,000 images with different defocus distances as the training data set. Different defocus distances lead to different spatial features of the captured images. However, solely relying on the spatial information leads to a relatively bad performance of the autofocusing process. It is better to extract defocus features from transform domains of the acquired image. For incoherent illumination, the Fourier cutoff frequency is directly related to the defocus distance. Similarly, autocorrelation peaks are directly related to the defocus distance for two-plane-wave illumination. In our implementation, we use the spatial image, the Fourier spectrum, the autocorrelation of the spatial image, and combinations thereof as the inputs for the CNNs. We show that the information from the transform domains can improve the performance and robustness of the autofocusing process. The resulting focusing error is ~0.5 µm, which is within the 0.8-µm depth-of-field range. The reported approach requires little hardware modification for conventional WSI systems and the images can be captured on the fly without focus map surveying. It may find applications in WSI and time-lapse microscopy. The transform- and multi-domain approaches may also provide new insights for developing microscopy-related deep-learning networks. We have made our training and testing data set (~12 GB) open-source for the broad research community.

The Leadership Roles of Distance Learning Administrators (DLAs) in Increasing Educational Value and Quality Perceptions

ERIC Educational Resources Information Center

McFarlane, Donovan A.

2011-01-01

This paper examines the leadership roles of distance learning administrators (DLAs) in light of the demand and need for value and quality in educational distance learning programs and schools. The author explores the development of distance learning using available and emerging technologies in relation to increased demand for education, training,…

Teaching and Learning at a Distance: What it Takes To Effectively Design, Deliver, and Evaluate Programs.

ERIC Educational Resources Information Center

Cyrs, Thomas E., Ed.; Menges, Robert J., Ed.; Svinicki, Marilla D., Ed.

1997-01-01

In this volume, experienced distance educators provide insights into new trends in computer-based teaching and learning in postsecondary education. The book is divided into four parts: (1) Issues and Trends; (2) Instructional Design Principles for Distance Learning; (3) Alternative Delivery Systems for Distance Learning; and (4) Administrative…

Facebook Mediated Interaction and Learning in Distance Learning at Makerere University

ERIC Educational Resources Information Center

Mayende, Godfrey; Muyinda, Paul Birevu; Isabwe, Ghislain Maurice Norbert; Walimbwa, Michael; Siminyu, Samuel Ndeda

2014-01-01

This paper reports on an investigation of the use of Facebook as a tool to mediate learning amongst distance learners at Makerere University, a dual-mode institution offering both conventional and distance learning programs. While conventional courses take 17 weeks in a semester, the distance learners come in for two residential sessions, each…

Distance Learning 2001: Proceedings of the Annual Conference on Distance Teaching & Learning (17th, Madison, Wisconsin, August 8-10, 2001).

ERIC Educational Resources Information Center

Wisconsin Univ. System, Madison.

This document contains 82 papers and 6 workshop presentations from a conference on distance teaching and learning. The following are among the papers included: "Examples and Tools for Building Web-Based Learning Experiences" (Steven A. Ackerman, Thomas Whittaker); "Online Testing in Distance Education" (Tricia Ahern);…

Distance Learning for Food Security and Rural Development: A Perspective from the United Nations Food and Agriculture Organization.

ERIC Educational Resources Information Center

McLean, Scott; Gasperini, Lavinia; Rudgard, Stephen

2002-01-01

The distance learning experiences of the United Nations Food and Agriculture Organization led to the following suggestions for applying distance learning strategies to the challenges of food security and rural development: use distance learning for the right reasons, be sensitive to context, use existing infrastructure, engage stakeholders, and…

Topics on Distance Learning Conference Proceedings (Hammond, Indiana, June 5-6, 2001).

ERIC Educational Resources Information Center

Purdue Univ., Hammond, IN. Calumet Campus.

The purpose of this conference was to focus attention on the increasing role of distance learning in academia and industry and to inform and educate the participants in several key aspects of distance learning. In addition, the conference spotlights the accomplishments of technology in education and showcases the many leaders in distance learning.…

The Evolution of Distance Learning: Technology-Mediated Interactive Learning.

ERIC Educational Resources Information Center

Dede, Christopher J.

1990-01-01

Summarizes a paper prepared for the Office of Technology Assessment (OTA) on the evolution of distance learning which begins by describing technological, the demographic, economic, political, and pedagogical forces involved. A new field is proposed called technology-mediated interactive learning (TMIL), which synthesizes distance learning,…

Complex networks in the Euclidean space of communicability distances

NASA Astrophysics Data System (ADS)

Estrada, Ernesto

2012-06-01

We study the properties of complex networks embedded in a Euclidean space of communicability distances. The communicability distance between two nodes is defined as the difference between the weighted sum of walks self-returning to the nodes and the weighted sum of walks going from one node to the other. We give some indications that the communicability distance identifies the least crowded routes in networks where simultaneous submission of packages is taking place. We define an index Q based on communicability and shortest path distances, which allows reinterpreting the “small-world” phenomenon as the region of minimum Q in the Watts-Strogatz model. It also allows the classification and analysis of networks with different efficiency of spatial uses. Consequently, the communicability distance displays unique features for the analysis of complex networks in different scenarios.

Confession-building, long-distance networks, and the organization of Jesuit science.

PubMed

Harris, S J

1996-01-01

The ability of the Society of Jesus to engage in a broad and enduring tradition of scientific activity is here addressed in terms of its programmatic commitment to the consolidation and extension of the Catholic confession (i.e., to a multipronged program of confession-building) and its mastery of the administrative apparatus necessary to operate long-distance networks. The Society's early move into two major apostolates, one in education and the other in the overseas missions, brought Jesuits into regular contact with the educated elites of Europe and at the same time placed the society's missionaries in remote parts of the natural world. The modes of organization of travel and communication required by the Society's long-distance networks (i.e., the training and deployment of reliable agents willing to work under direction in remote locations and capable of providing trustworthy reports and observations to their superiors through regular exchange of correspondence) not only facilitated scientific communication and collaboration within the order, it also provided Jesuits with the resources they needed to engage successfully in 'ministries among the learned'. Evidence of a sustained attempt by Jesuit authors to assume the role of Kulturträger is found in the several genres of scientific publications that dominate the society's scientific corpus. Thus the society's early recognition of the "apostolic value" of scientific publications in recruiting friends and allies among Europe's intellectual elites, I argue, allowed a robust interest in natural knowledge to emerge as a legitimate part of the Jesuit vocation.

A Conceptual Model for Effective Distance Learning in Higher Education

ERIC Educational Resources Information Center

Farajollahi, Mehran; Zare, Hosein; Hormozi, Mahmood; Sarmadi, Mohammad Reza; Zarifsanaee, Nahid

2010-01-01

The present research aims at presenting a conceptual model for effective distance learning in higher education. Findings of this research shows that an understanding of the technological capabilities and learning theories especially constructive theory and independent learning theory and communicative and interaction theory in Distance learning is…

Distance Learning: What's Holding Back This Boundless Delivery System?

ERIC Educational Resources Information Center

Bruder, Isabelle

1989-01-01

Discusses distance learning, identifies who distance learners may be, and examines issues involved in establishing distance learning systems. Topics discussed include teacher concerns, including job security and certification; curriculum concerns, including state and local requirements and cross-cultural issues; cooperative development,…

Rethinking Lifelong Learning through Online Distance Learning in Chinese Educational Policies, Practices and Research

ERIC Educational Resources Information Center

Yang, Min

2008-01-01

This paper offers a critique of the Chinese philosophy of online distance learning as a means of building a lifelong learning society. Literature about lifelong learning and its implications for online distance learning is reviewed. Documents, reports and research papers are examined to explore the characteristics of the Chinese philosophy of…

Facilities Offered by the University of Ibadan (Nigeria) Distance Learning Centre towards Learners' Academic Goal--An Evaluation

ERIC Educational Resources Information Center

Adegbile, J. A.; Oyekanmi, J. O.

2011-01-01

Distance learners in the University of Ibadan, Nigeria unlike other distance learners of different parts of the world are faced with various educational, social and psychological problems associated with the code of distance learning. The facilities offered by the University of Ibadan distance learning centre towards the users' multifarious needs…

New Ways of Learning: Comparing the Effectiveness of Interactive Online Media in Distance Education with the European Textbook Tradition

ERIC Educational Resources Information Center

Krämer, Bernd J.; Neugebauer, Jonas; Magenheim, Johannes; Huppertz, Helga

2015-01-01

Although many innovations exploiting web technologies have been suggested in distance higher education, very little original research exists investigating the impact of web-based learning environments on distance students' learning processes and outcomes. To close this gap, four sets of data have been collected in a distance-learning course:…

Application of Distance Learning Technology to Strategic Education.

DTIC Science & Technology

1996-02-26

service or government agency. STRATEGY RESEARCH PROJECT APPLICATION OF DISTANCE LEARNING TECHNOLOGY TO STRATEGIC EDUCATION BY LIEUTENANT COLONEL...APPLICATION OF DISTANCE LEARNING TECHNOLOGY TO STRATEGIC EDUCATION by Lieutenant Colonel Greig W. Mitchell United States Army Commander David M...distance learning technology can also enhance the functions of research and public service. The purpose of research programs in higher education is

Community of inquiry model: advancing distance learning in nurse anesthesia education.

PubMed

Pecka, Shannon L; Kotcherlakota, Suhasini; Berger, Ann M

2014-06-01

The number of distance education courses offered by nurse anesthesia programs has increased substantially. Emerging distance learning trends must be researched to ensure high-quality education for student registered nurse anesthetists. However, research to examine distance learning has been hampered by a lack of theoretical models. This article introduces the Community of Inquiry model for use in nurse anesthesia education. This model has been used for more than a decade to guide and research distance learning in higher education. A major strength of this model learning. However, it lacks applicability to the development of higher order thinking for student registered nurse anesthetists. Thus, a new derived Community of Inquiry model was designed to improve these students' higher order thinking in distance learning. The derived model integrates Bloom's revised taxonomy into the original Community of Inquiry model and provides a means to design, evaluate, and research higher order thinking in nurse anesthesia distance education courses.

47 CFR 32.4999 - General.

Code of Federal Regulations, 2010 CFR

2010-10-01

... system of accounts shall be comprised of six major groups—Local Network Services Revenues, Network Access... Group. (j) Long Distance Network Service revenues. Long Distance Network Service revenues shall include... revenues derived from the following categories: Unbundled network element revenues, Resale revenues...

Occasional Papers in Open and Distance Learning, Number 18.

ERIC Educational Resources Information Center

Donnan, Peter, Ed.

Six papers examine innovations and trends in distance learning, frequently drawing upon empirical research or informal observations on distance learning students at Charles Sturt University (Australia). "On-Line Study Packages for Distance Education: Some Considerations of Conceptual Parameters" (Dirk M. R. Spennemann) discusses issues…

Transformation of social networks in the late pre-Hispanic US Southwest.

PubMed

Mills, Barbara J; Clark, Jeffery J; Peeples, Matthew A; Haas, W R; Roberts, John M; Hill, J Brett; Huntley, Deborah L; Borck, Lewis; Breiger, Ronald L; Clauset, Aaron; Shackley, M Steven

2013-04-09

The late pre-Hispanic period in the US Southwest (A.D. 1200-1450) was characterized by large-scale demographic changes, including long-distance migration and population aggregation. To reconstruct how these processes reshaped social networks, we compiled a comprehensive artifact database from major sites dating to this interval in the western Southwest. We combine social network analysis with geographic information systems approaches to reconstruct network dynamics over 250 y. We show how social networks were transformed across the region at previously undocumented spatial, temporal, and social scales. Using well-dated decorated ceramics, we track changes in network topology at 50-y intervals to show a dramatic shift in network density and settlement centrality from the northern to the southern Southwest after A.D. 1300. Both obsidian sourcing and ceramic data demonstrate that long-distance network relationships also shifted from north to south after migration. Surprisingly, social distance does not always correlate with spatial distance because of the presence of network relationships spanning long geographic distances. Our research shows how a large network in the southern Southwest grew and then collapsed, whereas networks became more fragmented in the northern Southwest but persisted. The study also illustrates how formal social network analysis may be applied to large-scale databases of material culture to illustrate multigenerational changes in network structure.

Transformation of social networks in the late pre-Hispanic US Southwest

PubMed Central

Mills, Barbara J.; Clark, Jeffery J.; Peeples, Matthew A.; Haas, W. R.; Roberts, John M.; Hill, J. Brett; Huntley, Deborah L.; Borck, Lewis; Breiger, Ronald L.; Clauset, Aaron; Shackley, M. Steven

2013-01-01

The late pre-Hispanic period in the US Southwest (A.D. 1200–1450) was characterized by large-scale demographic changes, including long-distance migration and population aggregation. To reconstruct how these processes reshaped social networks, we compiled a comprehensive artifact database from major sites dating to this interval in the western Southwest. We combine social network analysis with geographic information systems approaches to reconstruct network dynamics over 250 y. We show how social networks were transformed across the region at previously undocumented spatial, temporal, and social scales. Using well-dated decorated ceramics, we track changes in network topology at 50-y intervals to show a dramatic shift in network density and settlement centrality from the northern to the southern Southwest after A.D. 1300. Both obsidian sourcing and ceramic data demonstrate that long-distance network relationships also shifted from north to south after migration. Surprisingly, social distance does not always correlate with spatial distance because of the presence of network relationships spanning long geographic distances. Our research shows how a large network in the southern Southwest grew and then collapsed, whereas networks became more fragmented in the northern Southwest but persisted. The study also illustrates how formal social network analysis may be applied to large-scale databases of material culture to illustrate multigenerational changes in network structure. PMID:23530201

Tutors' Influence on Distance Language Students' Learning Motivation: Voices from Learners and Tutors

ERIC Educational Resources Information Center

Xiao, Junhong

2012-01-01

Teachers' influence on students' learning motivation is a well-researched topic. Nevertheless, the majority of such studies are situated in the conventional learning context despite the rapid growth of distance language learning. This study set out to investigate tutors' influence on students' learning motivation in the Chinese distance language…

Challenges Encountered by a Distance Learning Organisation

ERIC Educational Resources Information Center

Malik, Sangeeta

2012-01-01

Distance learning as the name indicates is a learning, learner gets from distant places. In this learning system, learner and educators are separated by space & time. Lots of distance learning organizations are spreading to meet the increased demand of current & future needs of adult education. The rapid spread of these organizations doesn't mean…

Path optimisation of a mobile robot using an artificial neural network controller

NASA Astrophysics Data System (ADS)

Singh, M. K.; Parhi, D. R.

2011-01-01

This article proposed a novel approach for design of an intelligent controller for an autonomous mobile robot using a multilayer feed forward neural network, which enables the robot to navigate in a real world dynamic environment. The inputs to the proposed neural controller consist of left, right and front obstacle distance with respect to its position and target angle. The output of the neural network is steering angle. A four layer neural network has been designed to solve the path and time optimisation problem of mobile robots, which deals with the cognitive tasks such as learning, adaptation, generalisation and optimisation. A back propagation algorithm is used to train the network. This article also analyses the kinematic design of mobile robots for dynamic movements. The simulation results are compared with experimental results, which are satisfactory and show very good agreement. The training of the neural nets and the control performance analysis has been done in a real experimental setup.

Challenges in Delivering Library Services for Distance Learning.

ERIC Educational Resources Information Center

Swaine, Cynthia Wright

The first section of this paper on library services for distance education discusses the status of distance learning in higher education. What distance learning means for libraries is addressed in the second section, including considerations related to diverse locations, agreements with participating institutions, delivery limitations, librarian…

Educational technology integration and distance learning in respiratory care: practices and attitudes.

PubMed

Hopper, Keith B; Johns, Carol L

2007-11-01

Educational technologies have had an important role in respiratory care. Distance learning via postal correspondence has been used extensively in respiratory care, and Internet-based distance learning is now used in the training of respiratory therapists (RTs), clinical continuing education, and in baccalaureate degree and higher programs for RTs and educators. To describe the current scope of respiratory care educational technology integration, including distance learning. To investigate online research potential in respiratory care. A probabilistic online survey of United States respiratory care program directors was conducted on educational technology practices and attitudes, including distance learning. A parallel exploratory study of United States respiratory care managers was conducted. One-hundred seventy-seven (53%) program directors participated. One-hundred twenty-eight respiratory care managers participated. For instructional purposes, the respiratory care programs heavily use office-productivity software, the Internet, e-mail, and commercial respiratory care content-based computer-based instruction. The programs use, or would use, online resources provided by text publishers, but there is a paucity. Many program directors reported that their faculty use personal digital assistants (PDAs), often in instructional roles. 74.6% of the programs offer no fully online courses, but 61.0% reported at least one course delivered partially online. The managers considered continuing education via online technologies appropriate, but one third reported that they have not/will not hire RTs trained via distance learning. Neither group considered fully online courses a good match for RT training, nor did they consider training via distance learning of comparable quality to on-campus programs. Both groups rated baccalaureate and higher degrees via distance learning higher if the program included face-to-face instruction. Online distance-learning participatory experience generally improved attitudes toward distance learning. There was a good match between manager RT expectations in office-productivity software and program instructional practices. Educational technologies have an important role in respiratory care. Online distance learning for baccalaureate and higher degrees in respiratory care is promising. Online distance learning in respiratory care must include face-to-face instruction. Distance-learning deployment in respiratory care will require resources. A follow-up probabilistic survey of United States respiratory care managers is needed. Online surveys conducted for respiratory care are promising, but neither less expensive nor easier than conventional means.

Assessment of topographic and drainage network controls on debris-flow travel distance along the west coast of the United States

USGS Publications Warehouse

Coe, Jeffrey A.; Reid, Mark E.; Brien, Dainne L.; Michael, John A.

2011-01-01

To better understand controls on debris-flow entrainment and travel distance, we examined topographic and drainage network characteristics of initiation locations in two separate debris-flow prone areas located 700 km apart along the west coast of the U.S. One area was located in northern California, the other in southern Oregon. In both areas, debris flows mobilized from slides during large storms, but, when stratified by number of contributing initiation locations, median debris-flow travel distances in Oregon were 5 to 8 times longer than median distances in California. Debris flows in Oregon readily entrained channel material; entrainment in California was minimal. To elucidate this difference, we registered initiation locations to high-resolution airborne LiDAR, and then examined travel distances with respect to values of slope, upslope contributing area, planform curvature, distance from initiation locations to the drainage network, and number of initiation areas that contributed to flows. Results show distinct differences in the topographic and drainage network characteristics of debris-flow initiation locations between the two study areas. Slope and planform curvature of initiation locations (landslide headscarps), commonly used to predict landslide-prone areas, were not useful for predicting debris-flow travel distances. However, a positive, power-law relation exists between median debris-flow travel distance and the number of contributing debris-flow initiation locations. Moreover, contributing area and the proximity of the initiation locations to the drainage network both influenced travel distances, but proximity to the drainage network was the better predictor of travel distance. In both study areas, flows that interacted with the drainage network flowed significantly farther than those that did not. In California, initiation sites within 60 m of the network were likely to reach the network and generate longtraveled flows; in Oregon, the threshold was 80 m.

A Path-Analytic Study of Some Correlates Predicting Persistence and Student's Success in Distance Education in Nigeria

ERIC Educational Resources Information Center

Ojokheta, K. O.

2010-01-01

This study examined the influence of some predictors in the enhancement of persistence and students success in distance education in the two most recognised and respected distance learning institutions in Nigeria--the Distance Learning Institute (DLI) of University of Lagos and Distance Learning Centre of University of Ibadan. The need for this…

The Challenges of Quality Assurance in a Distance Learning Environment. A Report and Recommendations in a Series on Distance Learning Policy Issues.

ERIC Educational Resources Information Center

Southern Regional Education Board, Atlanta, GA.

The Distance Learning Policy Laboratory of the Southern Regional Education Board (SREB) and many states and regional organizations are coming to a consensus on the principles and goals that should shape distance learning policies. In the case of quality assurance, the SREB believes there are four guiding principles that states should follow.…

Using Finance Policy To Reduce Barriers to Distance Learning. A Report and Recommendations in a Series on Distance Learning Policy Issues.

ERIC Educational Resources Information Center

Southern Regional Education Board, Atlanta, GA.

This study explored the ways in which state and system financing policies can advance the use of distance learning technologies and the goals outlined in other reports by the Distance Learning Policy Laboratory more effectively. The subcommittee on finance that examined the issue approached the task by establishing a framework that considered:…

The Role of Gender in Distance Learning: A Meta-Analytic Review of Gender Differences in Academic Performance and Self-Efficacy in Distance Learning

ERIC Educational Resources Information Center

Perkowski, Justine

2013-01-01

This meta-analytic review was performed to determine the relationship between gender and two constructs measuring success in distance learning--academic performance and self-efficacy--with a particular interest in identifying whether females or males have an advantage in distance learning environments. Data from 15 studies resulted in 18 effect…

Can you go the distance? Attending the virtual classroom.

PubMed

Bigony, Lorraine

2010-01-01

Distance learning via the World Wide Web offers convenience and flexibility. Online education connects nurses geographically in a manner that the traditional face-to-face learning environment lacks. Delivered in both a synchronous (real time interaction) or asynchronous (delayed interaction) format, distance programs continue to provide nurses with choice, especially in the pursuit of advanced degrees. This article explores the pros and cons of distance education, in addition to the most popular platform used in distance learning today, the Blackboard Academic Suite. Characteristics of the potential enrollee to ensure a successful distance education experience are also discussed. Distance nursing programs are here to stay. Although rigorous, the ease of accessibility makes distance learning a viable alternative for busy nurses.

Astronautics Degrees for Space Industry

NASA Astrophysics Data System (ADS)

Gruntman, M.; Brodsky, R.; Erwin, D.; Kunc, J.

The Astronautics Program (http://astronautics.usc.edu) of the University of Southern California (USC) offers a full set of undergraduate and graduate degree programs in Aerospace Engineering with emphasis in Astronautics. The Bachelor of Science degree program in Astronautics combines basic science and engineering classes with specialized astronautics classes. The Master of Science degree program in Astronautics offers classes in various areas of space technology. The Certificate in Astronautics targets practicing engineers and scientists who enter space-related fields and/or who want to obtain training in specific space-related areas. Many specialized graduate classes are taught by adjunct faculty working at the leading space companies. The Master of Science degree and Certificate are available through the USC Distance Education Network (DEN). Today, the Internet allows us to reach students anywhere in the world through webcasting. The majority of our graduate students, as well as those pursuing the Certificate, work full time as engineers in the space industry and government research and development centers. The new world of distance learning presents new challenges and opens new opportunities. We show how the transformation of distance learning and particularly the introduction of webcasting transform organization of the program and class delivery. We will describe in detail the academic focus of the program, student reach, and structure of program components. Program development is illustrated by the student enrollment dynamics and related industrial trends; the lessons learned emphasize the importance of feedback from the students and from the space industry.

Potential of Social Networking Sites for Distance Education Student Engagement

ERIC Educational Resources Information Center

Lester, Jaime; Perini, Michael

2010-01-01

This chapter explores the potential of social networking sites for increasing student engagement for distance education learners. The authors present a modified student engagement model with a focus on the integration of technology, specifically social networking sites for community college distance education learners. The chapter concludes with…

Effectiveness of Mobile Learning in Distance Education

ERIC Educational Resources Information Center

Yousuf, Muhammad Imran

2007-01-01

The main aim of this research is to better understand and measure students' attitudes and perceptions towards the importance of mobile learning in distance education. Results of this survey clearly indicate that facilitating mobile learning can improve the entire distance education by enhancing ways of communication among distance learners, tutors…

A Journey to Legitimacy: The Historical Development of Distance Education through Technology

ERIC Educational Resources Information Center

Casey, Denise M.

2008-01-01

This article demonstrates the parallels between development of technology and the increased acceptance of distance learning. First, definitions of distance learning are provided. Second, the history of distance learning and its use of technological innovations are presented. Third, an overview of the academic institutions that are offering…

Using Multimedia for Distance Learning in Adult, Career, and Vocational Education. Information Series No. 362.

ERIC Educational Resources Information Center

Stammen, Ronald M.

This paper explores how educators are using multimedia for distance learning, beginning with definitions of the concepts of multimedia, hypermedia, hypertext, distance education and distance learning. Three types of telecommunications technologies are described: multimedia with broadcast television, multimedia with interactive video (television),…

Online dimensionality reduction using competitive learning and Radial Basis Function network.

PubMed

Tomenko, Vladimir

2011-06-01

The general purpose dimensionality reduction method should preserve data interrelations at all scales. Additional desired features include online projection of new data, processing nonlinearly embedded manifolds and large amounts of data. The proposed method, called RBF-NDR, combines these features. RBF-NDR is comprised of two modules. The first module learns manifolds by utilizing modified topology representing networks and geodesic distance in data space and approximates sampled or streaming data with a finite set of reference patterns, thus achieving scalability. Using input from the first module, the dimensionality reduction module constructs mappings between observation and target spaces. Introduction of specific loss function and synthesis of the training algorithm for Radial Basis Function network results in global preservation of data structures and online processing of new patterns. The RBF-NDR was applied for feature extraction and visualization and compared with Principal Component Analysis (PCA), neural network for Sammon's projection (SAMANN) and Isomap. With respect to feature extraction, the method outperformed PCA and yielded increased performance of the model describing wastewater treatment process. As for visualization, RBF-NDR produced superior results compared to PCA and SAMANN and matched Isomap. For the Topic Detection and Tracking corpus, the method successfully separated semantically different topics. Copyright © 2011 Elsevier Ltd. All rights reserved.

Open Classroom: Distance Learning In and Out of Schools. Open and Distance Learning Series.

ERIC Educational Resources Information Center

Bradley, Jo, Ed.

This collection of essays, which is separated into 4 sections, concerns open and distance learning at school level, or grades K-12. The first section, "The Knowledge Society," includes the following chapters: "Classroom Open Learning: A Case of Old Wine in New Bottles?" (Jenkins); "Living and Learning in the Information…

Supporting Distance Learners for Collaborative Problem Solving.

ERIC Educational Resources Information Center

Verdejo, M. F.; Barros, B.; Abad, M. T.

This paper describes a computer-supported environment designed to facilitate distance learning through collaborative problem-solving. The goal is to encourage distance learning students to work together, in order to promote both learning of collaboration and learning through collaboration. Collaboration is defined as working together on a common…

Distance Learning in British Universities: Is It Possible?

ERIC Educational Resources Information Center

Lentell, Helen

2012-01-01

The wider context (political and economic) for developing sustainable distance learning in UK universities is encouraging and new learning technologies promise much improved products and services. But conventional campus-based universities struggle to build and/or expand sustainable distance learning provision. This article identifies the core…

Inner and Outer Recursive Neural Networks for Chemoinformatics Applications.

PubMed

Urban, Gregor; Subrahmanya, Niranjan; Baldi, Pierre

2018-02-26

Deep learning methods applied to problems in chemoinformatics often require the use of recursive neural networks to handle data with graphical structure and variable size. We present a useful classification of recursive neural network approaches into two classes, the inner and outer approach. The inner approach uses recursion inside the underlying graph, to essentially "crawl" the edges of the graph, while the outer approach uses recursion outside the underlying graph, to aggregate information over progressively longer distances in an orthogonal direction. We illustrate the inner and outer approaches on several examples. More importantly, we provide open-source implementations [available at www.github.com/Chemoinformatics/InnerOuterRNN and cdb.ics.uci.edu ] for both approaches in Tensorflow which can be used in combination with training data to produce efficient models for predicting the physical, chemical, and biological properties of small molecules.

Using Satellite Classes to Optimise Access to and Participation in First-Year Business Management: A Case at an Open and Distance-Learning University in South Africa

ERIC Educational Resources Information Center

Swanepoel, Elana; De Beer, Andreas; Muller, Helene

2009-01-01

We investigated the effect of satellite classes as a component of blended learning, to enhance student performance of the Business Management I and Management I students at an open and distance-learning university. We discuss the evolution of distance education, the interactivities promoted by open and distance learning and the concept of blended…

Skin Lesion Analysis towards Melanoma Detection Using Deep Learning Network

PubMed Central

2018-01-01

Skin lesions are a severe disease globally. Early detection of melanoma in dermoscopy images significantly increases the survival rate. However, the accurate recognition of melanoma is extremely challenging due to the following reasons: low contrast between lesions and skin, visual similarity between melanoma and non-melanoma lesions, etc. Hence, reliable automatic detection of skin tumors is very useful to increase the accuracy and efficiency of pathologists. In this paper, we proposed two deep learning methods to address three main tasks emerging in the area of skin lesion image processing, i.e., lesion segmentation (task 1), lesion dermoscopic feature extraction (task 2) and lesion classification (task 3). A deep learning framework consisting of two fully convolutional residual networks (FCRN) is proposed to simultaneously produce the segmentation result and the coarse classification result. A lesion index calculation unit (LICU) is developed to refine the coarse classification results by calculating the distance heat-map. A straight-forward CNN is proposed for the dermoscopic feature extraction task. The proposed deep learning frameworks were evaluated on the ISIC 2017 dataset. Experimental results show the promising accuracies of our frameworks, i.e., 0.753 for task 1, 0.848 for task 2 and 0.912 for task 3 were achieved. PMID:29439500

Exploring Cloud Computing for Distance Learning

ERIC Educational Resources Information Center

He, Wu; Cernusca, Dan; Abdous, M'hammed

2011-01-01

The use of distance courses in learning is growing exponentially. To better support faculty and students for teaching and learning, distance learning programs need to constantly innovate and optimize their IT infrastructures. The new IT paradigm called "cloud computing" has the potential to transform the way that IT resources are utilized and…

Cooperative Learning at a Distance: An Experiment with Wikis

ERIC Educational Resources Information Center

Campbell, Katherine; Ellingson, Dee Ann

2010-01-01

The merits of incorporating group work into learning environments are well established. Online classes and other distance learning settings, however, can make it challenging to introduce traditional group projects. Wikis use technology to facilitate group work in distance learning settings. Wikis allow individuals in different locations to…

Topics on Distance Learning: Proceedings 2000 (Hammond, Indiana, June 6-7, 2000).

ERIC Educational Resources Information Center

Purdue Univ., Hammond, IN. Calumet Campus.

This proceedings of the 2000 Topics on Distance Learning conference contains summaries of the following presentations: "The ABC's of Distance Learning via Full Motion Video" (Liz Owens); "Assessing the Cost of Technology in Instruction Using an Economic Model" (Joseph Lovrinic); "Collaboration Lessons Learned from the…

A Begrudging, Recalcitrant Academic Observes What She's Learning: Distance Learning in Leadership Formation

ERIC Educational Resources Information Center

Hess, Lisa M.

2014-01-01

Neither advocacy nor condemnation of distance learning, this essay offers observations and critical reflection on four years' longitudinal engagement with distance learning pedagogies for formation in higher theological education. Instead, readers are invited to curiosity, communal-institutional discernment, and intense ambivalence.…

Map for Decision Making in Operating Distance Learning System--Research Results.

ERIC Educational Resources Information Center

Offir, Baruch

2000-01-01

Examines decision-making aspects of the introduction of distance learning into university instruction and learning based on experiences in Israel. Discusses the introduction of information technology into the classroom; examines teacher/student interactions; and suggests a model for introducing distance learning that focuses on the role of the…

Greeting You Online: Selecting Web-Based Conferencing Tools for Instruction in E-Learning Mode

ERIC Educational Resources Information Center

Li, Judy

2014-01-01

Academic distance learning programs have gained popularity and added to the demand for online library services. Librarians are now conducting instruction for distance learning students beyond their traditional work. Technology advancements have enhanced the delivery mode in distance learning across academic disciplines. Online conference tools…

Blended Learning in Distance Education: Sri Lankan Perspective

ERIC Educational Resources Information Center

Liyanagunawardena, T. R.; Adams, A. A.; Rassool, N.; Williams, S. A.

2014-01-01

The purpose of this paper is to explore the implementation of online learning in distance educational delivery at Yellow Fields University (pseudonymous) in Sri Lanka. The implementation of online distance education at the University included the use of blended learning. The policy initiative to introduce online for distance education in Sri Lanka…

Transactional Distance and Second Life: The Effects of Video Game Experience

ERIC Educational Resources Information Center

Atkinson, Mark

2013-01-01

As a subset of distance education, online learning takes place primarily in learning management systems through asynchronous interaction, that can cause transactional distance between instructor and learners. This study investigated how transactional distance may be affected by the use of Second Life, a 3-D virtual world, as a learning environment…

From Add-On to Mainstream: Applying Distance Learning Models for ALL Students

ERIC Educational Resources Information Center

Zai, Robert, III.; Wesley, Threasa L.

2013-01-01

The use of distance learning technology has allowed Northern Kentucky University's W. Frank Steely Library to remove traditional boundaries between both distance and on-campus students. An emerging model that applies these distance learning methodologies to all students has proven effective for enhancing reference and instructional services. This…

E-Learning and Distance Education in Nigeria

ERIC Educational Resources Information Center

Ajadi, Timothy Olugbenga; Salawu, Ibrahim Olatunde; Adeoye, Femi Adetunji

2008-01-01

This paper discusses the relevance of e-learning in the position of distance education in Nigeria. It commences by discussing the meaning of e-learning and distance education. It also discusses the historical background of distance education in Nigeria as well as the operations of National Open University of Nigeria (NOUN) as the first federal…

Implications of Online Learning for the Conceptual Development and Practice of Distance Education

ERIC Educational Resources Information Center

Garrison, Randy

2009-01-01

The purpose of this article is to examine the foundational principles and practices of distance education for the purpose of understanding recent developments in the areas of online and blended learning. It is argued that mainstream distance education has not embraced the full collaborative potential of online learning. Distance education…

Measuring Self-Regulation in Self-Paced Open and Distance Learning Environments

ERIC Educational Resources Information Center

Kocdar, Serpil; Karadeniz, Abdulkadir; Bozkurt, Aras; Buyuk, Koksal

2018-01-01

Previous studies have described many scales for measuring self-regulation; however, no scale has been developed specifically for self-paced open and distance learning environments. Therefore, the aim of this study is to develop a scale for determining the self-regulated learning skills of distance learners in selfpaced open and distance learning…

Mobile Distance Learning with PDAs: Development and Testing of Pedagogical and System Solutions Supporting Mobile Distance Learners

ERIC Educational Resources Information Center

Rekkedal, Torstein; Dye, Aleksander

2007-01-01

The article discusses basic teaching-learning philosophies and experiences from the development and testing of mobile learning integrated with the online distance education system at NKI (Norwegian Knowledge Institute) Distance Education. The article builds on experiences from three European Union (EU) supported "Leonardo da Vinci"…

Collaborative distance learning: Developing an online learning community

NASA Astrophysics Data System (ADS)

Stoytcheva, Maria

2017-12-01

The method of collaborative distance learning has been applied for years in a number of distance learning courses, but they are relatively few in foreign language learning. The context of this research is a hybrid distance learning of French for specific purposes, delivered through the platform UNIV-RcT (Strasbourg University), which combines collaborative activities for the realization of a common problem-solving task online. The study focuses on a couple of aspects: on-line interactions carried out in small, tutored groups and the process of community building online. By analyzing the learner's perceptions of community and collaborative learning, we have tried to understand the process of building and maintenance of online learning community and to see to what extent the collaborative distance learning contribute to the development of the competence expectations at the end of the course. The analysis of the results allows us to distinguish the advantages and limitations of this type of e-learning and thus evaluate their pertinence.

Professional development in photonics: the advanced technology education projects of the New England Board of Education

NASA Astrophysics Data System (ADS)

Donnelly, Judith; Hanes, Fenna; Massa, Nicholas

2007-09-01

Since 1995, the New England Board of Education (NEBHE) has been providing curriculum and professional development as well as laboratory improvement in optics/photonics to middle school and high school teachers and college faculty across the United States. With funding from the National Science Foundation's Advanced Technology Education program, NEBHE's optics/photonics education projects have created a national network of educational and industry alliances resulting in opportunities in optics and photonics for students at participating schools and colleges. The cornerstone of NEBHE projects is collaboration among educational levels, career counselors and teachers/faculty, and industry and academia. In such a rich atmosphere of cooperation, participants have been encouraged to create their own regional projects and activities involving students from middle school through four-year universities. In this paper we will describe the evolution of teacher/faculty professional development from a traditional week-long summer workshop to a collaborative distance learning laboratory course based on adult learning principles and supported by a national network of industry mentors.

System impairment compensation in coherent optical communications by using a bio-inspired detector based on artificial neural network and genetic algorithm

NASA Astrophysics Data System (ADS)

Wang, Danshi; Zhang, Min; Li, Ze; Song, Chuang; Fu, Meixia; Li, Jin; Chen, Xue

2017-09-01

A bio-inspired detector based on the artificial neural network (ANN) and genetic algorithm is proposed in the context of a coherent optical transmission system. The ANN is designed to mitigate 16-quadrature amplitude modulation system impairments, including linear impairment: Gaussian white noise, laser phase noise, in-phase/quadrature component imbalance, and nonlinear impairment: nonlinear phase. Without prior information or heuristic assumptions, the ANN, functioning as a machine learning algorithm, can learn and capture the characteristics of impairments from observed data. Numerical simulations were performed, and dispersion-shifted, dispersion-managed, and dispersion-unmanaged fiber links were investigated. The launch power dynamic range and maximum transmission distance for the bio-inspired method were 2.7 dBm and 240 km greater, respectively, than those of the maximum likelihood estimation algorithm. Moreover, the linewidth tolerance of the bio-inspired technique was 170 kHz greater than that of the k-means method, demonstrating its usability for digital signal processing in coherent systems.

Effects of help-seeking in a blended high school Biology class

NASA Astrophysics Data System (ADS)

Deguzman, Paolo

Distance learning provides an opportunity for students to learn valuable information through technology and interactive media. Distance learning additionally offers educational institutions the flexibility of synchronous and asynchronous instruction while increasing enrollment and lowering cost. However, distance education has not been well documented within the context of urban high schools. Distance learning may allow high school students to understand material at an individualized pace for either enrichment or remediation. A successful high school student who participates in distance learning should exhibit high self regulatory skills. However, most urban high school students have not been exposed to distance learning and should be introduced to proper self regulatory strategies that should increase the likelihood of understanding the material. To help facilitate a move into distance learning, a blended distance learning model, the combination of distance learning and traditional learning, will be used. According to O'Neil's (in preparation) revised problem solving model, self regulation is a component of problem solving. Within the Blended Biology course, urban high school students will be trained in help-seeking strategies to further their understanding of genetics and Punnett Square problem solving. This study investigated the effects of help-seeking in a blended high school Biology course. The main study consisted of a help-seeking group (n=55) and a control group (n=53). Both the help-seeking group and the control group were taught by one teacher for two weeks. The help-seeking group had access to Blended Biology with Help-Seeking while the control group only had access to Blended Biology. The main study used a pretest and posttest to measure Genetics Content Understanding, Punnett Square Problem Solving, Adaptive Help-Seeking, Maladaptive Help-Seeking, and Self Regulation. The analysis showed no significant difference in any of the measures in terms of help seeking. However, blended distance learning appeared to work as posttest means increased significantly from the pretest means. Future studies should consider the method of communication for help-seeking and help-giving within a high school distance learning context. Further studies should consider developing instruments to measure the difference in knowing when help is needed versus active choice.

A Critical Examination of the Teaching Methodologies Pertaining to Distance Learning in Geographic Education: Andragogy in an Adult Online Certificate Program

ERIC Educational Resources Information Center

Schultz, Richard B.

2012-01-01

Differences between student audiences are an important aspect not only of traditional learning in higher education, but also in the distance learning environment. Facilitators of distance learning coursework must be cognizant of the differences which adult students bring to the classroom and their varying expectations and reasons for learning.…

Research on spatial economic structure for different economic sectors from a perspective of a complex network

NASA Astrophysics Data System (ADS)

Hu, Sen; Yang, Hualei; Cai, Boliang; Yang, Chunxia

2013-09-01

The economy system is a complex system, and the complex network is a powerful tool to study its complexity. Here we calculate the economic distance matrices based on annual GDP of nine economic sectors from 1995-2010 in 31 Chinese provinces and autonomous regions,1 then build several spatial economic networks through the threshold method and the Minimal Spanning Tree method. After the analysis on the structure of the networks and the influence of geographic distance, some conclusions are drawn. First, connectivity distribution of a spatial economic network does not follow the power law. Second, according to the network structure, nine economic sectors could be divided into two groups, and there is significant discrepancy of network structure between these two groups. Moreover, the influence of the geographic distance plays an important role on the structure of a spatial economic network, network parameters are changed with the influence of the geographic distance. At last, 2000 km is the critical value for geographic distance: for real estate and finance, the spearman’s rho with l<2000 is bigger than that with l>2000, and the case is opposite for other economic sectors.

Machine learning enhanced optical distance sensor

NASA Astrophysics Data System (ADS)

Amin, M. Junaid; Riza, N. A.

2018-01-01

Presented for the first time is a machine learning enhanced optical distance sensor. The distance sensor is based on our previously demonstrated distance measurement technique that uses an Electronically Controlled Variable Focus Lens (ECVFL) with a laser source to illuminate a target plane with a controlled optical beam spot. This spot with varying spot sizes is viewed by an off-axis camera and the spot size data is processed to compute the distance. In particular, proposed and demonstrated in this paper is the use of a regularized polynomial regression based supervised machine learning algorithm to enhance the accuracy of the operational sensor. The algorithm uses the acquired features and corresponding labels that are the actual target distance values to train a machine learning model. The optimized training model is trained over a 1000 mm (or 1 m) experimental target distance range. Using the machine learning algorithm produces a training set and testing set distance measurement errors of <0.8 mm and <2.2 mm, respectively. The test measurement error is at least a factor of 4 improvement over our prior sensor demonstration without the use of machine learning. Applications for the proposed sensor include industrial scenario distance sensing where target material specific training models can be generated to realize low <1% measurement error distance measurements.

Distance Learning With NASA Lewis Research Center's Learning Technologies Project

NASA Technical Reports Server (NTRS)

Petersen, Ruth

1998-01-01

The NASA Lewis Research Center's Learning Technologies Project (LTP) has responded to requests from local school district technology coordinators to provide content for videoconferencing workshops. Over the past year we have offered three teacher professional development workshops that showcase NASA Lewis-developed educational products and NASA educational Internet sites. In order to determine the direction of our involvement with distance learning, the LTP staff conducted a survey of 500 U.S. schools. We received responses from 72 schools that either currently use distance learning or will be using distance learning in 98-99 school year. The results of the survey are summarized in the article. In addition, the article provides information on distance learners, distance learning technologies, and the NASA Lewis LTP videoconferencing workshops. The LTP staff will continue to offer teacher development workshops through videoconferencing during the 98-99 school year. We hope to add workshops on new educational products as they are developed at NASA Lewis.

Learning styles and preferences for live and distance education: an example of a specialisation course in epidemiology.

PubMed

Groenwold, Rolf H H; Knol, Mirjam J

2013-07-02

Distance learning through the internet is increasingly popular in higher education. However, it is unknown how participants in epidemiology courses value live vs. distance education. All participants of a 5-day specialisation course in epidemiology were asked to keep a diary on the number of hours they spent on course activities (both live and distance education). Attendance was not compulsory during the course and participants were therefore also asked for the reasons to attend live education (lectures and practicals). In addition, the relation between participants' learning styles (Index of Learning Styles) and their participation in live and distance education was studied. All 54 (100%) participants in the course completed the questionnaire on attendance and 46 (85%) completed the questionnaire on learning styles. The number of hours attending live education was negatively correlated with the number of hours going studying distance learning materials (Pearson correlation -0.5; p < 0.001). The most important reasons to attend live education was to stay focused during lectures (50%), and to ask questions during practicals (50%). A lack of time was the most important reason not to attend lectures (52%) or practicals (61%). Learning styles were not association with the number of hours spent on live or distance education. Distance learning may play an important role in epidemiology courses, since it allows participants to study whenever and wherever they prefer, which provides the opportunity to combine courses with clinical duties. An important requirement for distance learning education appears to be the possibility to ask questions and to interact with instructors.

[Scale effect of Nanjing urban green infrastructure network pattern and connectivity analysis.

PubMed

Yu, Ya Ping; Yin, Hai Wei; Kong, Fan Hua; Wang, Jing Jing; Xu, Wen Bin

2016-07-01

Based on ArcGIS, Erdas, GuidosToolbox, Conefor and other software platforms, using morphological spatial pattern analysis (MSPA) and landscape connectivity analysis methods, this paper quantitatively analysed the scale effect, edge effect and distance effect of the Nanjing urban green infrastructure network pattern in 2013 by setting different pixel sizes (P) and edge widths in MSPA analysis, and setting different dispersal distance thresholds in landscape connectivity analysis. The results showed that the type of landscape acquired based on the MSPA had a clear scale effect and edge effect, and scale effects only slightly affected landscape types, whereas edge effects were more obvious. Different dispersal distances had a great impact on the landscape connectivity, 2 km or 2.5 km dispersal distance was a critical threshold for Nanjing. When selecting the pixel size 30 m of the input data and the edge wide 30 m used in the morphological model, we could get more detailed landscape information of Nanjing UGI network. Based on MSPA and landscape connectivity, analysis of the scale effect, edge effect, and distance effect on the landscape types of the urban green infrastructure (UGI) network was helpful for selecting the appropriate size, edge width, and dispersal distance when developing these networks, and for better understanding the spatial pattern of UGI networks and the effects of scale and distance on the ecology of a UGI network. This would facilitate a more scientifically valid set of design parameters for UGI network spatiotemporal pattern analysis. The results of this study provided an important reference for Nanjing UGI networks and a basis for the analysis of the spatial and temporal patterns of medium-scale UGI landscape networks in other regions.

Assessing the Applicability of 3D Holographic Technology as an Enhanced Technology for Distance Learning

ERIC Educational Resources Information Center

Kalansooriya, Pradeep; Marasinghe, Ashu; Bandara, K. M. D. N.

2015-01-01

Distance learning has provided an excellent platform for students in geographically remote locations while enabling them to learn at their own pace and convenience. A number of technologies are currently being utilized to conceptualize, design, enhance and foster distance learning. Teleconferences, electronic field trips, podcasts, webinars, video…

Automated Categorization Scheme for Digital Libraries in Distance Learning: A Pattern Recognition Approach

ERIC Educational Resources Information Center

Gunal, Serkan

2008-01-01

Digital libraries play a crucial role in distance learning. Nowadays, they are one of the fundamental information sources for the students enrolled in this learning system. These libraries contain huge amount of instructional data (text, audio and video) offered by the distance learning program. Organization of the digital libraries is…

Distance Learning for Mobile Internet Users

ERIC Educational Resources Information Center

Necat, Beran

2007-01-01

This paper provides an overview on the current state of art in the field of Distance learning for mobile users. It mentions a large range of technologies, services and approaches that may be used to bring distance learning to mobile internet users. These technologies are supposed to considerably increase innovative e-learning solutions for the…

Connecting Multiple Intelligences through Open and Distance Learning: Going towards a Collective Intelligence?

ERIC Educational Resources Information Center

Medeiros Vieira, Leandro Mauricio; Ferasso, Marcos; Schröeder, Christine da Silva

2014-01-01

This theoretical essay is a learning approach reflexion on Howard Gardner's Theory of Multiple Intelligences and the possibilities provided by the education model known as open and distance learning. Open and distance learning can revolutionize traditional pedagogical practice, meeting the needs of those who have different forms of cognitive…

Vocational Education Distance Learning Delivery System. Final Report.

ERIC Educational Resources Information Center

Hardy, Darcy Walsh

A project was conducted to identify criteria and procedures for using a distance learning delivery system at the University of Texas TeleLearning Center to teach Health Occupations II to high school seniors. Another objective was expanding the current distance learning program for health occupations to include between 15 and 20 school districts.…

The Impact of Student Motivation on Participation and Academic Performance in Distance Learning

ERIC Educational Resources Information Center

Pittman, Candice Nicole

2013-01-01

This study investigated the impact of motivation on students' participation and academic performance in distance learning. Distance learning continues to grow in popularity as more and more students enroll in distance education courses. These courses require more responsibility on the part of the student. Some students are unaware of the amount of…

NASA Innovations in Climate Education Connects Audiences Coast-to-Coast for Climate Literacy via the NASA Digital Learning Network

NASA Astrophysics Data System (ADS)

Murray, B.; Barnes, M. H.; Chambers, L. H.; Pippin, M. R.; Martin, A. M.; Geyer, A. J.; Leber, M.; Joyner, E.; Small, C.; Dublin, D.

2013-12-01

The Minority University Research and Education Program (MUREP) NASA Innovations in Climate Education (NICE) project advances NASA's Office of Education's strategic initiative to improve the quality of the nation's Science, Technology, Engineering and Mathematics (STEM) education and enhance literacy about climate and other Earth systems environmental changes. NICE also strategically supports the United States' progressive initiative to enhance the science and technology enterprise for successful competition in the 21st century global community. To extend to wider networks in 2013, MUREP NICE partnered with the NASA Digital Learning Network (DLNTM) in a unique, non-traditional collaborative model to significantly increase the impact and connection with formal and informal educators, curriculum developers, science education specialists, and researchers regarding climate literacy. DLN offers an expansive distance learning capability that bridges presenters with education audiences for interactive, web-based, synchronous and asynchronous Educator Professional Development (EPD). DLN services over 10,000 educators each year. In 3rd quarter FY13 alone DLN totaled 3,361 connections with educators. The DLN allows for cost effective (no travel) engagement of multiple geographically dispersed audiences with presenters from remote locations. This facilitates interactive communication among participants through distance education, allowing them to share local experiences with one another. A comprehensive four-part EPD workshop, featuring several NICE Principal Investigators (PI) and NASA subject matter experts was developed for NICE in April 2013. Topics covered in the workshop progressed from a simple introduction of Earth's energy budget, through explanation of temperature data collection and evidence of temperature rise, impacts on phenology, and finally consequences for bugs and birds. This event was an innovative hybrid workshop, connecting onsite teachers interactively with remotely connected participants and presenters across the nation. In addition to the 19 educators who participated live, 298 watched the sessions via a webcast. A similar workshop series experienced 300% growth in 2 years indicating the potential for comparable growth of NICE events. Due to unanimous requests for more information on these and other topics, beginning Fall 2013, NICE will reach into additional educators' classrooms via the DLN to deliver continued EPD from NICE PIs and other NASA researchers. With DLN capability, hundreds of additional unique viewers have been exposed to NICE via the DLN this year. This large-scale effort allows for long term, sustained engagement of the global community. We intend to take advantage of capabilities of the DLN as we continue to scale NICE events to wider audiences. The use of distance education allows for immediate release of new information and more frequent connections, resulting in sustained engagement of participants. This presentation will explore the various successes and future opportunities for expanding the impact of climate literacy via the NASA DLN, a large-scale collaborative network.

Efficient data communication protocols for wireless networks

NASA Astrophysics Data System (ADS)

Zeydan, Engin

In this dissertation, efficient decentralized algorithms are investigated for cost minimization problems in wireless networks. For wireless sensor networks, we investigate both the reduction in the energy consumption and throughput maximization problems separately using multi-hop data aggregation for correlated data in wireless sensor networks. The proposed algorithms exploit data redundancy using a game theoretic framework. For energy minimization, routes are chosen to minimize the total energy expended by the network using best response dynamics to local data. The cost function used in routing takes into account distance, interference and in-network data aggregation. The proposed energy-efficient correlation-aware routing algorithm significantly reduces the energy consumption in the network and converges in a finite number of steps iteratively. For throughput maximization, we consider both the interference distribution across the network and correlation between forwarded data when establishing routes. Nodes along each route are chosen to minimize the interference impact in their neighborhood and to maximize the in-network data aggregation. The resulting network topology maximizes the global network throughput and the algorithm is guaranteed to converge with a finite number of steps using best response dynamics. For multiple antenna wireless ad-hoc networks, we present distributed cooperative and regret-matching based learning schemes for joint transmit beanformer and power level selection problem for nodes operating in multi-user interference environment. Total network transmit power is minimized while ensuring a constant received signal-to-interference and noise ratio at each receiver. In cooperative and regret-matching based power minimization algorithms, transmit beanformers are selected from a predefined codebook to minimize the total power. By selecting transmit beamformers judiciously and performing power adaptation, the cooperative algorithm is shown to converge to pure strategy Nash equilibrium with high probability throughout the iterations in the interference impaired network. On the other hand, the regret-matching learning algorithm is noncooperative and requires minimum amount of overhead. The proposed cooperative and regret-matching based distributed algorithms are also compared with centralized solutions through simulation results.

Average geodesic distance of skeleton networks of Sierpinski tetrahedron

NASA Astrophysics Data System (ADS)

Yang, Jinjin; Wang, Songjing; Xi, Lifeng; Ye, Yongchao

2018-04-01

The average distance is concerned in the research of complex networks and is related to Wiener sum which is a topological invariant in chemical graph theory. In this paper, we study the skeleton networks of the Sierpinski tetrahedron, an important self-similar fractal, and obtain their asymptotic formula for average distances. To provide the formula, we develop some technique named finite patterns of integral of geodesic distance on self-similar measure for the Sierpinski tetrahedron.

Distance learning perspectives.

PubMed

Pandza, Haris; Masic, Izet

2013-01-01

The development of modern technology and the Internet has enabled the explosive growth of distance learning. distance learning is a process that is increasingly present in the world. This is the field of education focused on educating students who are not physically present in the traditional classrooms or student's campus. described as a process where the source of information is separated from the students in space and time. If there are situations that require the physical presence of students, such as when a student is required to physically attend the exam, this is called a hybrid form of distance learning. This technology is increasingly used worldwide. The Internet has become the main communication channel for the development of distance learning.

Video-based face recognition via convolutional neural networks

NASA Astrophysics Data System (ADS)

Bao, Tianlong; Ding, Chunhui; Karmoshi, Saleem; Zhu, Ming

2017-06-01

Face recognition has been widely studied recently while video-based face recognition still remains a challenging task because of the low quality and large intra-class variation of video captured face images. In this paper, we focus on two scenarios of video-based face recognition: 1)Still-to-Video(S2V) face recognition, i.e., querying a still face image against a gallery of video sequences; 2)Video-to-Still(V2S) face recognition, in contrast to S2V scenario. A novel method was proposed in this paper to transfer still and video face images to an Euclidean space by a carefully designed convolutional neural network, then Euclidean metrics are used to measure the distance between still and video images. Identities of still and video images that group as pairs are used as supervision. In the training stage, a joint loss function that measures the Euclidean distance between the predicted features of training pairs and expanding vectors of still images is optimized to minimize the intra-class variation while the inter-class variation is guaranteed due to the large margin of still images. Transferred features are finally learned via the designed convolutional neural network. Experiments are performed on COX face dataset. Experimental results show that our method achieves reliable performance compared with other state-of-the-art methods.

Open and Distance Learning Today. Routledge Studies in Distance Education Series.

ERIC Educational Resources Information Center

Lockwood, Fred, Ed.

This book contains the following papers on open and distance learning today: "Preface" (Daniel); "Big Bang Theory in Distance Education" (Hawkridge); "Practical Agenda for Theorists of Distance Education" (Perraton); "Trends, Directions and Needs: A View from Developing Countries" (Koul); "American…

Improving CNN Performance Accuracies With Min-Max Objective.

PubMed

Shi, Weiwei; Gong, Yihong; Tao, Xiaoyu; Wang, Jinjun; Zheng, Nanning

2017-06-09

We propose a novel method for improving performance accuracies of convolutional neural network (CNN) without the need to increase the network complexity. We accomplish the goal by applying the proposed Min-Max objective to a layer below the output layer of a CNN model in the course of training. The Min-Max objective explicitly ensures that the feature maps learned by a CNN model have the minimum within-manifold distance for each object manifold and the maximum between-manifold distances among different object manifolds. The Min-Max objective is general and able to be applied to different CNNs with insignificant increases in computation cost. Moreover, an incremental minibatch training procedure is also proposed in conjunction with the Min-Max objective to enable the handling of large-scale training data. Comprehensive experimental evaluations on several benchmark data sets with both the image classification and face verification tasks reveal that employing the proposed Min-Max objective in the training process can remarkably improve performance accuracies of a CNN model in comparison with the same model trained without using this objective.

Statistical classification approach to discrimination between weak earthquakes and quarry blasts recorded by the Israel Seismic Network

NASA Astrophysics Data System (ADS)

Kushnir, A. F.; Troitsky, E. V.; Haikin, L. M.; Dainty, A.

1999-06-01

A semi-automatic procedure has been developed to achieve statistically optimum discrimination between earthquakes and explosions at local or regional distances based on a learning set specific to a given region. The method is used for step-by-step testing of candidate discrimination features to find the optimum (combination) subset of features, with the decision taken on a rigorous statistical basis. Linear (LDF) and Quadratic (QDF) Discriminant Functions based on Gaussian distributions of the discrimination features are implemented and statistically grounded; the features may be transformed by the Box-Cox transformation z=(1/ α)( yα-1) to make them more Gaussian. Tests of the method were successfully conducted on seismograms from the Israel Seismic Network using features consisting of spectral ratios between and within phases. Results showed that the QDF was more effective than the LDF and required five features out of 18 candidates for the optimum set. It was found that discrimination improved with increasing distance within the local range, and that eliminating transformation of the features and failing to correct for noise led to degradation of discrimination.

Guidance on the Use of Learning Strategies in Distance Education (DE) as a Function of Age and Gender

ERIC Educational Resources Information Center

Alliprandini, Paula Mariza Zedu; Pavesi, Marilza Aparecida; Dayanne, Vicentini; Sekitani, Juliane Tiemi

2015-01-01

This study aims to determine whether there are differences in the use of learning strategies used by students enrolled in courses offered in the format of Distance Learning (DL) by gender and age of participants. A total of 402 students responded to a range of learning strategies evaluations-version adapted for distance learning, containing 49…

Transactional Distance as a Predictor of Perceived Learner Satisfaction in Distance Learning Courses: A Case Study of Bachelor of Education Arts Program, University of Nairobi, Kenya

ERIC Educational Resources Information Center

Mbwesa, Joyce Kanini

2014-01-01

There is a long history of study and recognition of the critical role of interaction in supporting and even defining distance education. Interaction has been identified as key to the success of distance learning. It is key in fostering, supporting and engaging in the learning process. Moore (1989) posits that the physical distance that exists in…

Testing the limits of long-distance learning: Learning beyond a three-segment window

PubMed Central

Finley, Sara

2012-01-01

Traditional flat-structured bigram and trigram models of phonotactics are useful because they capture a large number of facts about phonological processes. Additionally, these models predict that local interactions should be easier to learn than long-distance ones since long-distance dependencies are difficult to capture with these models. Long-distance phonotactic patterns have been observed by linguists in many languages, who have proposed different kinds of models, including feature-based bigram and trigram models, as well as precedence models. Contrary to flat-structured bigram and trigram models, these alternatives capture unbounded dependencies because at an abstract level of representation, the relevant elements are locally dependent, even if they are not adjacent at the observable level. Using an artificial grammar learning paradigm, we provide additional support for these alternative models of phonotactics. Participants in two experiments were exposed to a long-distance consonant harmony pattern in which the first consonant of a five-syllable word was [s] or [∫] ('sh') and triggered a suffix that was either [−su] or [−∫u] depending on the sibilant quality of this first consonant. Participants learned this pattern, despite the large distance between the trigger and the target, suggesting that when participants learn long-distance phonological patterns, that pattern is learned without specific reference to distance. PMID:22303815

Facilitating Distance Education.

ERIC Educational Resources Information Center

Rossman, Mark H., Ed.; Rossman, Maxine E., Ed.

1995-01-01

This collection of articles on distance learning reflects the perspectives and concerns of the learner and the facilitator of learning in distance education setting. Eight chapters are included: (1) "The Evolution and Advantages of Distance Education" (John E. Cantelon) traces the history of distance education and demonstrates how it transcends…

Distance Learning '99. Proceedings of the Annual Conference on Distance Teaching and Learning (15th, Madison, Wisconsin, August 4-6, 1999).

ERIC Educational Resources Information Center

Wisconsin Univ. System, Madison.

This document contains 71 papers and 11 workshop presentations on distance teaching and learning from a conference on educational research. The following are among the papers included: "Bridging Distances and Differences" (Nancy Anderson); "The Role of Site Directors in Faculty and Student Success" (Edith M. Barnett, Jeanie P.…

What's the Difference, Still? A Follow-Up Review of the Quantitative Research Methodology in Distance Learning

ERIC Educational Resources Information Center

Randolph, Justus

2005-01-01

A high quality review of the distance learning literature from 1992-1999 concluded that most of the research on distance learning had serious methodological flaws. This paper presents the results of a small-scale replication of that review. From three leading distance education journals, a sample of 66 articles was categorized by study type and…

A Comparative Study of Student Satisfaction Level in Distance Learning and Live Classroom at Higher Education Level

ERIC Educational Resources Information Center

Mahmood, Azhar; Mahmood, Sheikh Tariq; Malik, Allah Bakhsh

2012-01-01

The technology has embraced the innovative learning methodologies. Distance Learning has taken the place of traditional face-to-face educational environment. The purpose of this study was to compare the level of student satisfaction of graduate distance learning educational psychology course to a traditional classroom educational psychology course…

Effectiveness of Computer-Based Educational Technology in Distance Learning: A Review of the Literature.

ERIC Educational Resources Information Center

Lesh, Steven G.; Rampp, Lary C.

Learning at a distance has been on the fringe of educational acceptance since the first correspondence course was delivered through the mail system in return for academic credit. As distance learning has matured, elements of enhanced instructional design and advances in educational technology have migrated this medium of learning closer to the…

Distance Learning: Practice and Dilemmas

ERIC Educational Resources Information Center

Tatkovic, Nevenka; Sehanovic, Jusuf; Ruzic, Maja

2006-01-01

In accordance with the European processes of integrated and homogeneous education, the paper presents the essential viewpoints and questions covering the establishment and development of "distance learning" (DL) in Republic of Croatia. It starts from the advantages of distance learning versus traditional education taking into account…

7 CFR 1703.100 - Purpose.

Code of Federal Regulations, 2011 CFR

2011-01-01

... RURAL DEVELOPMENT Distance Learning and Telemedicine Loan and Grant Program-General § 1703.100 Purpose. The purpose of the Distance Learning and Telemedicine (DLT) Loan and Grant Program is to encourage and improve telemedicine services and distance learning services in rural areas through the use of...

7 CFR 1703.100 - Purpose.

Code of Federal Regulations, 2014 CFR

2014-01-01

... RURAL DEVELOPMENT Distance Learning and Telemedicine Loan and Grant Program-General § 1703.100 Purpose. The purpose of the Distance Learning and Telemedicine (DLT) Loan and Grant Program is to encourage and improve telemedicine services and distance learning services in rural areas through the use of...

7 CFR 1703.100 - Purpose.

Code of Federal Regulations, 2012 CFR

2012-01-01

... RURAL DEVELOPMENT Distance Learning and Telemedicine Loan and Grant Program-General § 1703.100 Purpose. The purpose of the Distance Learning and Telemedicine (DLT) Loan and Grant Program is to encourage and improve telemedicine services and distance learning services in rural areas through the use of...

7 CFR 1703.100 - Purpose.

Code of Federal Regulations, 2013 CFR

2013-01-01

... RURAL DEVELOPMENT Distance Learning and Telemedicine Loan and Grant Program-General § 1703.100 Purpose. The purpose of the Distance Learning and Telemedicine (DLT) Loan and Grant Program is to encourage and improve telemedicine services and distance learning services in rural areas through the use of...

Distance Learning and the Music Teacher: Before Signing Up for a Distance-Learning Program, It Is Essential to Learn as much about the Program as Possible

ERIC Educational Resources Information Center

Sherbon, James W.; Kish, David L.

2005-01-01

Most music teachers today are accustomed to teaching and learning practices that have undergone little change throughout many decades. Face-to-face instruction in music education has been the norm at all levels, although elements of technology and distance learning have filtered into their personal and professional lives, often in small and…

Adaptive distance metric learning for diffusion tensor image segmentation.

PubMed

Kong, Youyong; Wang, Defeng; Shi, Lin; Hui, Steve C N; Chu, Winnie C W

2014-01-01

High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework.

Adaptive Distance Metric Learning for Diffusion Tensor Image Segmentation

PubMed Central

Kong, Youyong; Wang, Defeng; Shi, Lin; Hui, Steve C. N.; Chu, Winnie C. W.

2014-01-01

High quality segmentation of diffusion tensor images (DTI) is of key interest in biomedical research and clinical application. In previous studies, most efforts have been made to construct predefined metrics for different DTI segmentation tasks. These methods require adequate prior knowledge and tuning parameters. To overcome these disadvantages, we proposed to automatically learn an adaptive distance metric by a graph based semi-supervised learning model for DTI segmentation. An original discriminative distance vector was first formulated by combining both geometry and orientation distances derived from diffusion tensors. The kernel metric over the original distance and labels of all voxels were then simultaneously optimized in a graph based semi-supervised learning approach. Finally, the optimization task was efficiently solved with an iterative gradient descent method to achieve the optimal solution. With our approach, an adaptive distance metric could be available for each specific segmentation task. Experiments on synthetic and real brain DTI datasets were performed to demonstrate the effectiveness and robustness of the proposed distance metric learning approach. The performance of our approach was compared with three classical metrics in the graph based semi-supervised learning framework. PMID:24651858

Robustness of spatial micronetworks

NASA Astrophysics Data System (ADS)

McAndrew, Thomas C.; Danforth, Christopher M.; Bagrow, James P.

2015-04-01

Power lines, roadways, pipelines, and other physical infrastructure are critical to modern society. These structures may be viewed as spatial networks where geographic distances play a role in the functionality and construction cost of links. Traditionally, studies of network robustness have primarily considered the connectedness of large, random networks. Yet for spatial infrastructure, physical distances must also play a role in network robustness. Understanding the robustness of small spatial networks is particularly important with the increasing interest in microgrids, i.e., small-area distributed power grids that are well suited to using renewable energy resources. We study the random failures of links in small networks where functionality depends on both spatial distance and topological connectedness. By introducing a percolation model where the failure of each link is proportional to its spatial length, we find that when failures depend on spatial distances, networks are more fragile than expected. Accounting for spatial effects in both construction and robustness is important for designing efficient microgrids and other network infrastructure.

Learning styles and preferences for live and distance education: an example of a specialisation course in epidemiology

PubMed Central

2013-01-01

Background Distance learning through the internet is increasingly popular in higher education. However, it is unknown how participants in epidemiology courses value live vs. distance education. Methods All participants of a 5-day specialisation course in epidemiology were asked to keep a diary on the number of hours they spent on course activities (both live and distance education). Attendance was not compulsory during the course and participants were therefore also asked for the reasons to attend live education (lectures and practicals). In addition, the relation between participants’ learning styles (Index of Learning Styles) and their participation in live and distance education was studied. Results All 54 (100%) participants in the course completed the questionnaire on attendance and 46 (85%) completed the questionnaire on learning styles. The number of hours attending live education was negatively correlated with the number of hours going studying distance learning materials (Pearson correlation −0.5; p < 0.001). The most important reasons to attend live education was to stay focused during lectures (50%), and to ask questions during practicals (50%). A lack of time was the most important reason not to attend lectures (52%) or practicals (61%). Learning styles were not association with the number of hours spent on live or distance education. Conclusion Distance learning may play an important role in epidemiology courses, since it allows participants to study whenever and wherever they prefer, which provides the opportunity to combine courses with clinical duties. An important requirement for distance learning education appears to be the possibility to ask questions and to interact with instructors. PMID:23819522

Trend of E-Learning: The Service Mashup

ERIC Educational Resources Information Center

Yen, Neil Y.; Shih, Timothy K.; Jin, Qun; Hsu, Hui-Huang; Chao, Louis R.

2010-01-01

With the improvement of internet technologies and multimedia resources, traditional learning has been replaced by distance learning, web-based learning or others' e-learning learning styles. According to distance learning, there are many research organizations and companies who make efforts in developing the relevant systems. But they lack…

Image texture segmentation using a neural network

NASA Astrophysics Data System (ADS)

Sayeh, Mohammed R.; Athinarayanan, Ragu; Dhali, Pushpuak

1992-09-01

In this paper we use a neural network called the Lyapunov associative memory (LYAM) system to segment image texture into different categories or clusters. The LYAM system is constructed by a set of ordinary differential equations which are simulated on a digital computer. The clustering can be achieved by using a single tuning parameter in the simplest model. Pattern classes are represented by the stable equilibrium states of the system. Design of the system is based on synthesizing two local energy functions, namely, the learning and recall energy functions. Before the implementation of the segmentation process, a Gauss-Markov random field (GMRF) model is applied to the raw image. This application suitably reduces the image data and prepares the texture information for the neural network process. We give a simple image example illustrating the capability of the technique. The GMRF-generated features are also used for a clustering, based on the Euclidean distance.

An Ensemble Deep Convolutional Neural Network Model with Improved D-S Evidence Fusion for Bearing Fault Diagnosis.

PubMed

Li, Shaobo; Liu, Guokai; Tang, Xianghong; Lu, Jianguang; Hu, Jianjun

2017-07-28

Intelligent machine health monitoring and fault diagnosis are becoming increasingly important for modern manufacturing industries. Current fault diagnosis approaches mostly depend on expert-designed features for building prediction models. In this paper, we proposed IDSCNN, a novel bearing fault diagnosis algorithm based on ensemble deep convolutional neural networks and an improved Dempster-Shafer theory based evidence fusion. The convolutional neural networks take the root mean square (RMS) maps from the FFT (Fast Fourier Transformation) features of the vibration signals from two sensors as inputs. The improved D-S evidence theory is implemented via distance matrix from evidences and modified Gini Index. Extensive evaluations of the IDSCNN on the Case Western Reserve Dataset showed that our IDSCNN algorithm can achieve better fault diagnosis performance than existing machine learning methods by fusing complementary or conflicting evidences from different models and sensors and adapting to different load conditions.

Improving Odometric Accuracy for an Autonomous Electric Cart.

PubMed

Toledo, Jonay; Piñeiro, Jose D; Arnay, Rafael; Acosta, Daniel; Acosta, Leopoldo

2018-01-12

In this paper, a study of the odometric system for the autonomous cart Verdino, which is an electric vehicle based on a golf cart, is presented. A mathematical model of the odometric system is derived from cart movement equations, and is used to compute the vehicle position and orientation. The inputs of the system are the odometry encoders, and the model uses the wheels diameter and distance between wheels as parameters. With this model, a least square minimization is made in order to get the nominal best parameters. This model is updated, including a real time wheel diameter measurement improving the accuracy of the results. A neural network model is used in order to learn the odometric model from data. Tests are made using this neural network in several configurations and the results are compared to the mathematical model, showing that the neural network can outperform the first proposed model.

An Ensemble Deep Convolutional Neural Network Model with Improved D-S Evidence Fusion for Bearing Fault Diagnosis

PubMed Central

Li, Shaobo; Liu, Guokai; Tang, Xianghong; Lu, Jianguang

2017-01-01

Intelligent machine health monitoring and fault diagnosis are becoming increasingly important for modern manufacturing industries. Current fault diagnosis approaches mostly depend on expert-designed features for building prediction models. In this paper, we proposed IDSCNN, a novel bearing fault diagnosis algorithm based on ensemble deep convolutional neural networks and an improved Dempster–Shafer theory based evidence fusion. The convolutional neural networks take the root mean square (RMS) maps from the FFT (Fast Fourier Transformation) features of the vibration signals from two sensors as inputs. The improved D-S evidence theory is implemented via distance matrix from evidences and modified Gini Index. Extensive evaluations of the IDSCNN on the Case Western Reserve Dataset showed that our IDSCNN algorithm can achieve better fault diagnosis performance than existing machine learning methods by fusing complementary or conflicting evidences from different models and sensors and adapting to different load conditions. PMID:28788099

Future Directions in Distance Learning and Communication Technologies

ERIC Educational Resources Information Center

Shih, Timothy; Hung, Jason

2007-01-01

Future Directions in Distance Learning and Communication Technologies presents theoretical studies and practical solutions for engineers, educational professionals, and graduate students in the research areas of e-learning, distance education, and instructional design. This book provides readers with cutting-edge solutions and research directions…

A Review of Two Distance Learning Books [book review].

ERIC Educational Resources Information Center

Koszalka, Tiffany A.; Spector, J. Michael

2003-01-01

Reviews two books that are representative of the substantive books aimed at those who wish to design effective distance learning. Together these books provide a reasonably complete perspective on how to design effective distance learning. They have many strengths, and few weaknesses. (SLD)

A deep learning approach for real time prostate segmentation in freehand ultrasound guided biopsy.

PubMed

Anas, Emran Mohammad Abu; Mousavi, Parvin; Abolmaesumi, Purang

2018-06-01

Targeted prostate biopsy, incorporating multi-parametric magnetic resonance imaging (mp-MRI) and its registration with ultrasound, is currently the state-of-the-art in prostate cancer diagnosis. The registration process in most targeted biopsy systems today relies heavily on accurate segmentation of ultrasound images. Automatic or semi-automatic segmentation is typically performed offline prior to the start of the biopsy procedure. In this paper, we present a deep neural network based real-time prostate segmentation technique during the biopsy procedure, hence paving the way for dynamic registration of mp-MRI and ultrasound data. In addition to using convolutional networks for extracting spatial features, the proposed approach employs recurrent networks to exploit the temporal information among a series of ultrasound images. One of the key contributions in the architecture is to use residual convolution in the recurrent networks to improve optimization. We also exploit recurrent connections within and across different layers of the deep networks to maximize the utilization of the temporal information. Furthermore, we perform dense and sparse sampling of the input ultrasound sequence to make the network robust to ultrasound artifacts. Our architecture is trained on 2,238 labeled transrectal ultrasound images, with an additional 637 and 1,017 unseen images used for validation and testing, respectively. We obtain a mean Dice similarity coefficient of 93%, a mean surface distance error of 1.10 mm and a mean Hausdorff distance error of 3.0 mm. A comparison of the reported results with those of a state-of-the-art technique indicates statistically significant improvement achieved by the proposed approach. Copyright © 2018 Elsevier B.V. All rights reserved.

Globalization, Information and Communication Technologies (ICTs) and Open/Distance Learning in Nigeria: Trends, Issues and Solution

ERIC Educational Resources Information Center

Olusola, Akande Joshua; Alaba, Sofowora Olaniyi

2011-01-01

The main thrust of this paper is to discuss the development of open and distance education in Nigeria and the major manifestations of the use of information and communication technologies (ICTs) in education in open and distance learning. This study further discusses the importance and use of ICTs in open and distance learning in making education…

Blending Face-to-Face and Distance Learning Methods in Adult and Career-Technical Education. Practice Application Brief No. 23.

ERIC Educational Resources Information Center

Wonacott, Michael E.

Both face-to-face and distance learning methods are currently being used in adult education and career and technical education. In theory, the advantages of face-to-face and distance learning methods complement each other. In practice, however, both face-to-face and information and communications technology (ICT)-based distance programs often rely…

Dental hygiene students' perceptions of distance learning: do they change over time?

PubMed

Sledge, Rhonda; Vuk, Jasna; Long, Susan

2014-02-01

The University of Arkansas for Medical Sciences dental hygiene program established a distant site where the didactic curriculum was broadcast via interactive video from the main campus to the distant site, supplemented with on-line learning via Blackboard. This study compared the perceptions of students towards distance learning as they progressed through the 21 month curriculum. Specifically, the study sought to answer the following questions: Is there a difference in the initial perceptions of students on the main campus and at the distant site toward distance learning? Do students' perceptions change over time with exposure to synchronous distance learning over the course of the curriculum? All 39 subjects were women between the ages of 20 and 35 years. Of the 39 subjects, 37 were Caucasian and 2 were African-American. A 15-question Likert scale survey was administered at 4 different periods during the 21 month program to compare changes in perceptions toward distance learning as students progressed through the program. An independent sample t-test and ANOVA were utilized for statistical analysis. At the beginning of the program, independent samples t-test revealed that students at the main campus (n=34) perceived statistically significantly higher effectiveness of distance learning than students at the distant site (n=5). Repeated measures of ANOVA revealed that perceptions of students at the main campus on effectiveness and advantages of distance learning statistically significantly decreased whereas perceptions of students at distant site statistically significantly increased over time. Distance learning in the dental hygiene program was discussed, and replication of the study with larger samples of students was recommended.

Exploring Differences between Self-Regulated Learning Strategies of High and Low Achievers in Open Distance Learning

ERIC Educational Resources Information Center

Geduld, Bernadette

2016-01-01

Open distance students differ in their preparedness for higher education studies. Students who are less self-regulated risk failure and drop out in the challenging milieu of open distance learning. In this study, the differences between the application of self-regulated learning strategies by low and high achievers were explored. A multi-method…

e-Learning for Expanding Distance Education in Tertiary Level in Bangladesh: Problems and Progress

ERIC Educational Resources Information Center

Al-Masum, Md. Abdullah; Chowdhury, Saiful Islam

2013-01-01

E-learning has broadly become an important enabler to promote distance education (DE) and lifelong learning in most of the developed countries, but in Bangladesh it is still a new successful progressive system for the learning communities. Distance education is thought to be introduced as an effective way of educating people of all sections in…

Learner Agency in Language Learning: The Story of a Distance Learner of EFL in China

ERIC Educational Resources Information Center

Xiao, Junhong

2014-01-01

Learner agency plays a key role in self-regulated learning. Yet, there is a paucity of research into its role in the distance learning context. Using reflective narratives written by a distance learner of English in China, this longitudinal case study aims to investigate the ways in which learner agency mediates the language learning in the…

Reducing the distance: equity issues in distance learning in public education

NASA Astrophysics Data System (ADS)

Campbell, Patricia B.; Storo, Jennifer

1996-12-01

Distance learning and educational equity both began with an emphasis on access, on providing underserved students with an increased access to education. Today definitions of equity have gone beyond simple access to include equal or equivalent treatment and outcomes while definitions of underserved students have expanded to include girls, children of color, children with limited English proficiency and children with disabilities. At the same time the definition of distance learning has expanded to include new technologies, new audiences and new roles. Based on these new definitions and roles, the article raises a number of equity challenges for distance learning educators centering around who is taught, what is taught and how the teaching is done. To answer these challenges, a series of recommendations are suggested that educators can implement to make distance learning a leader in increasing educational equity for all students. The time to act is now.

The use of multimodal strategies for distance education in the GRECCs.

PubMed

Kresevic, Denise; Burant, Christopher; Denton, Jennifer; Heath, Barbara; Kypriotakis, George

2011-01-01

The Department of Veterans Affairs (VA) has found distance education to be particularly valuable as a means to disseminate information to large numbers of busy learners in geographically diverse settings. Specifically, Geriatric Research, Education and Clinical Centers (GRECCs) of the VA have used various forms of distance learning to provide geriatrics-focused education to diverse health care providers. Such formats allow programs to be available to audiences regardless of distance or time. Although the distance-learning format has clear benefits, there are also some barriers that have hindered its wider adoption, including technical difficulties and ease of use. Organizers of distance education programs are challenged to overcome these barriers to provide a quality learning experience for the audience. The GRECCs will likely continue to be leaders in exploring innovative distance-learning strategies to accomplish their mission of quality geriatric education.

Designing Instruction for the Distance Learner

ERIC Educational Resources Information Center

Asunda, Paul A.

2010-01-01

A changing education landscape, diverse learner needs and technological advancements make this the perfect time for online and distance learning. Distance learning is increasingly becoming a preferred means for individuals to gain access to education and job preparation opportunities; this meets the public's learning needs "and" that of an…

Instructor and Student Attitudes Toward Distance Learning.

ERIC Educational Resources Information Center

Inman, Elliot; Kerwin, Michael; Mayes, Larry

1999-01-01

Discusses data collected from 11 distance-learning classes. The instructors were willing to teach distance-learning classes again, but said the courses were of equal or lesser quality than traditional classes. The 334 students surveyed were highly satisfied with the courses and instructors. Contains 17 references. (TGO)

Testing the limits of long-distance learning: learning beyond a three-segment window.

PubMed

Finley, Sara

2012-01-01

Traditional flat-structured bigram and trigram models of phonotactics are useful because they capture a large number of facts about phonological processes. Additionally, these models predict that local interactions should be easier to learn than long-distance ones because long-distance dependencies are difficult to capture with these models. Long-distance phonotactic patterns have been observed by linguists in many languages, who have proposed different kinds of models, including feature-based bigram and trigram models, as well as precedence models. Contrary to flat-structured bigram and trigram models, these alternatives capture unbounded dependencies because at an abstract level of representation, the relevant elements are locally dependent, even if they are not adjacent at the observable level. Using an artificial grammar learning paradigm, we provide additional support for these alternative models of phonotactics. Participants in two experiments were exposed to a long-distance consonant-harmony pattern in which the first consonant of a five-syllable word was [s] or [∫] ("sh") and triggered a suffix that was either [-su] or [-∫u] depending on the sibilant quality of this first consonant. Participants learned this pattern, despite the large distance between the trigger and the target, suggesting that when participants learn long-distance phonological patterns, that pattern is learned without specific reference to distance. Copyright © 2012 Cognitive Science Society, Inc.

Learning non-local dependencies.

PubMed

Kuhn, Gustav; Dienes, Zoltán

2008-01-01

This paper addresses the nature of the temporary storage buffer used in implicit or statistical learning. Kuhn and Dienes [Kuhn, G., and Dienes, Z. (2005). Implicit learning of nonlocal musical rules: implicitly learning more than chunks. Journal of Experimental Psychology-Learning Memory and Cognition, 31(6) 1417-1432] showed that people could implicitly learn a musical rule that was solely based on non-local dependencies. These results seriously challenge models of implicit learning that assume knowledge merely takes the form of linking adjacent elements (chunking). We compare two models that use a buffer to allow learning of long distance dependencies, the Simple Recurrent Network (SRN) and the memory buffer model. We argue that these models - as models of the mind - should not be evaluated simply by fitting them to human data but by determining the characteristic behaviour of each model. Simulations showed for the first time that the SRN could rapidly learn non-local dependencies. However, the characteristic performance of the memory buffer model rather than SRN more closely matched how people came to like different musical structures. We conclude that the SRN is more powerful than previous demonstrations have shown, but it's flexible learned buffer does not explain people's implicit learning (at least, the affective learning of musical structures) as well as fixed memory buffer models do.

Five Years of BEACO2N: First Results and Lessons Learned

NASA Astrophysics Data System (ADS)

Shusterman, A.; Cohen, R. C.

2017-12-01

The BErkeley Atmospheric CO2 Observation Network (BEACO2N) is an ongoing greenhouse gas and air quality monitoring campaign based in the San Francisco Bay Area of Northern California. BEACO2N is a distributed network instrument consisting of low- to moderate-cost commercial sensors for CO2 and other pollutants installed on top of schools, museums, and other outreach-minded institutions. The reduced cost of each individual sensor "node" enables the deployment of a larger volume of total nodes, resulting in a web of approximately 50 sites with an average node-to-node distance of 2 km. Operating in some variation of this configuration since 2012, BEACO2N offers greater spatio-temporal coverage than any other fixed CO2 monitoring network to date. This high-resolution information allows us to faithfully represent the true heterogeneity of urban emission processes and distinguish between specific sources that are often regulated independently, but typically treated en masse by sparser, conventional surface monitors. However, maintaining and appropriately interpreting a network of BEACO2N's size presents a number of unique data quality and data coverage challenges. Here we describe the quantitative capabilities of the BEACO2N platform, first results from initial attempts at constraining greenhouse gas emission estimates, as well as other lessons learned over the first five years of operation.

Practice Makes Learning.

ERIC Educational Resources Information Center

Neill, Judy

This paper focuses on how people learn to help educators design curriculum that will enable students to successfully complete a distance learning class. Up-front organization, clear communication about performance expectations, outcome driven assessment, and imaginative learning strategies are critical to successful distance learning.…

Neural Networks for Signal Processing and Control

NASA Astrophysics Data System (ADS)

Hesselroth, Ted Daniel

Neural networks are developed for controlling a robot-arm and camera system and for processing images. The networks are based upon computational schemes that may be found in the brain. In the first network, a neural map algorithm is employed to control a five-joint pneumatic robot arm and gripper through feedback from two video cameras. The pneumatically driven robot arm employed shares essential mechanical characteristics with skeletal muscle systems. To control the position of the arm, 200 neurons formed a network representing the three-dimensional workspace embedded in a four-dimensional system of coordinates from the two cameras, and learned a set of pressures corresponding to the end effector positions, as well as a set of Jacobian matrices for interpolating between these positions. Because of the properties of the rubber-tube actuators of the arm, the position as a function of supplied pressure is nonlinear, nonseparable, and exhibits hysteresis. Nevertheless, through the neural network learning algorithm the position could be controlled to an accuracy of about one pixel (~3 mm) after two hundred learning steps. Applications of repeated corrections in each step via the Jacobian matrices leads to a very robust control algorithm since the Jacobians learned by the network have to satisfy the weak requirement that they yield a reduction of the distance between gripper and target. The second network is proposed as a model for the mammalian vision system in which backward connections from the primary visual cortex (V1) to the lateral geniculate nucleus play a key role. The application of hebbian learning to the forward and backward connections causes the formation of receptive fields which are sensitive to edges, bars, and spatial frequencies of preferred orientations. The receptive fields are learned in such a way as to maximize the rate of transfer of information from the LGN to V1. Orientational preferences are organized into a feature map in the primary visual cortex by the application of lateral interactions during the learning phase. The organization of the mature network is compared to that found in the macaque monkey by several analytical tests. The capacity of the network to process images is investigated. By a method of reconstructing the input images in terms of V1 activities, the simulations show that images can be faithfully represented in V1 by the proposed network. The signal-to-noise ratio of the image is improved by the representation, and compression ratios of well over two-hundred are possible. Lateral interactions between V1 neurons sharpen their orientational tuning. We further study the dynamics of the processing, showing that the rate of decrease of the error of the reconstruction is maximized for the receptive fields used. Lastly, we employ a Fokker-Planck equation for a more detailed prediction of the error value vs. time. The Fokker-Planck equation for an underdamped system with a driving force is derived, yielding an energy-dependent diffusion coefficient which is the integral of the spectral densities of the force and the velocity of the system. The theory is applied to correlated noise activation and resonant activation. Simulation results for the error of the network vs time are compared to the solution of the Fokker-Planck equation.

Developing Distance Learning Courses in a "Traditional" University.

ERIC Educational Resources Information Center

Lawton, Sally; Barnes, Richard

1998-01-01

Comparison of distance learning that was developed with a business-planning approach (market research, cost-benefit analysis, feasibility study, strategic marketing) with one that did not use these techniques showed that business planning ensures that distance-learning courses are not viewed as a "cheap" option. The method identifies…

Designing, Developing and Implementing WWW-Based Distance Learning.

ERIC Educational Resources Information Center

Riley, Peter C.

The rapid advancement of communication technologies is resulting in a wide array of design and development choices for distance learning projects. The 58th Special Operations Wing at Kirtland Air Force Base, New Mexico, is developing a prototype distance learning project designed to serve geographically separated learner populations. Project staff…

Development of a Framework for Guiding Interaction Design in Distance Learning

ERIC Educational Resources Information Center

Li, Wei

2015-01-01

As one of the most critical elements in distance learning, interaction has been identified empirically as increasing learner motivation, satisfaction, participation, communication, and achievement. Fostering pedagogically effective interaction is a major challenge for educators in distance learning. In response to this challenge, the goal of this…

An Investigation of Teaching Strategy in the Distance Learning Mathematics Classroom

ERIC Educational Resources Information Center

DePriter, Tiffany

2013-01-01

Distance learning has become increasingly popular among higher learning institutions, and more academic disciplines, such as mathematics, are now being offered at a distance. This experimental study investigated whether an objectivist-based teaching strategy or a constructivist-based teaching strategy yields greater achievement scores for adult…

Language Distance Learning for the Digital Generation

ERIC Educational Resources Information Center

Duran-Cerda, Dolores

2010-01-01

The purpose of this article was to shed light on the potential of distance learning to overcome challenges in distance, space, time, and human and economic resources that limit access to language learning opportunities in cultural, literary, historical, geographical, and cross-cultural frames. Language and literature educators collectively have…

Manpower Development for Workers in Tertiary Institutions: Distance Learning Approach

ERIC Educational Resources Information Center

Hassan, Moshood Ayinde

2011-01-01

The purpose of this study is to determine the extent to which workers patronize distance learning approach to further their education. Other purposes include: determine problems facing workers in the process of improving their knowledge and skills through distance learning approach; establish the level of attainment of manpower development…

The Distance Learning of Foreign Languages: A Research Agenda

ERIC Educational Resources Information Center

White, Cynthia

2014-01-01

Research into the distance learning of languages is now established as a significant avenue of enquiry in language teaching, with evident research trajectories in several domains. This article selects and analyses significant areas of investigation in distance language learning and teaching to identify new and emerging gaps, along with research…

Distance Learning in Scientific and Professional Fields of Communication (Interdisciplinary Approach)

ERIC Educational Resources Information Center

Skorikova, Tatyana Petrovna; Khromova, Sergey Sergeevich; Dneprovskaya, Natalia Vitalievna

2016-01-01

Modern level of informational technologies development allows the authors of educational courses to decrease their dependence from technical specialists and to independently develop distance-learning courses and their separate online components, which require special methodical learning. The aim of present study is to develop a distance-learning…

Evaluation of Hybrid and Distance Education Learning Environments in Spain

ERIC Educational Resources Information Center

Ferrer-Cascales, Rosario; Walker, Scott L.; Reig-Ferrer, Abilio; Fernandez-Pascual, Maria Dolores; Albaladejo-Blazquez, Natalia

2011-01-01

This article describes the adaptation and validation of the "Distance Education Learning Environments Survey" (DELES) for use in investigating the qualities found in distance and hybrid education psycho-social learning environments in Spain. As Europe moves toward post-secondary student mobility, equanimity in access to higher education,…

Effects of Distance Learning on Learning Effectiveness

ERIC Educational Resources Information Center

Liu, Hong-Cheng; Yen, Jih-Rong

2014-01-01

The development of computers in the past two decades has resulted in the changes of education in enterprises and schools. The advance of computer hardware and platforms allow colleges generally applying distance courses to instruction that both Ministry of Education and colleges have paid attention to the development of Distance Learning. To…

7 CFR 1700.57 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 11 2010-01-01 2010-01-01 false Distance Learning and Telemedicine Loan and Grant Program. 1700.57 Section 1700.57 Agriculture Regulations of the Department of Agriculture (Continued... Authorities § 1700.57 Distance Learning and Telemedicine Loan and Grant Program. (a) Administrator: The...

Nursing Distance Learning Course Comparison of Assignments and Examination Scores

ERIC Educational Resources Information Center

Mundine, Jennifer

2016-01-01

Nursing programs have embraced distance learning in their curricula, but discussion is ongoing about course assignments and grading criteria to increase examination scores in nursing distance learning courses. Because course examinations are a predictor of success on the postgraduate licensing examination (NCLEX-RN), the purpose of this study was…

7 CFR 1700.57 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 11 2011-01-01 2011-01-01 false Distance Learning and Telemedicine Loan and Grant Program. 1700.57 Section 1700.57 Agriculture Regulations of the Department of Agriculture (Continued... Authorities § 1700.57 Distance Learning and Telemedicine Loan and Grant Program. (a) Administrator: The...

7 CFR 1700.57 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 11 2012-01-01 2012-01-01 false Distance Learning and Telemedicine Loan and Grant Program. 1700.57 Section 1700.57 Agriculture Regulations of the Department of Agriculture (Continued... Authorities § 1700.57 Distance Learning and Telemedicine Loan and Grant Program. (a) Administrator: The...

7 CFR 1700.57 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 11 2013-01-01 2013-01-01 false Distance Learning and Telemedicine Loan and Grant Program. 1700.57 Section 1700.57 Agriculture Regulations of the Department of Agriculture (Continued... Authorities § 1700.57 Distance Learning and Telemedicine Loan and Grant Program. (a) Administrator: The...

7 CFR 1700.57 - Distance Learning and Telemedicine Loan and Grant Program.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 11 2014-01-01 2014-01-01 false Distance Learning and Telemedicine Loan and Grant Program. 1700.57 Section 1700.57 Agriculture Regulations of the Department of Agriculture (Continued... Authorities § 1700.57 Distance Learning and Telemedicine Loan and Grant Program. (a) Administrator: The...

Virtual Bioinformatics Distance Learning Suite

ERIC Educational Resources Information Center

Tolvanen, Martti; Vihinen, Mauno

2004-01-01

Distance learning as a computer-aided concept allows students to take courses from anywhere at any time. In bioinformatics, computers are needed to collect, store, process, and analyze massive amounts of biological and biomedical data. We have applied the concept of distance learning in virtual bioinformatics to provide university course material…

Sustainable Assessment and Evaluation Strategies for Open and Distance Learning

ERIC Educational Resources Information Center

Okonkwo, Charity Akuadi

2010-01-01

This paper first presents an overview of the concepts of assessment and evaluation in Open and Distance Learning (ODL) environment. The large numbers of students and numerous courses make assessment and evaluation very difficult and administrative nightmare at Distance Learning (DL) institutions. These challenges informed exploring issues relating…

Costing Distance Education and Open Learning in Sub-Saharan Africa: Working Group on Distance Education and Open Learning-- A Survey of Policy and Practice. Final Report

ERIC Educational Resources Information Center

Commonwealth of Learning, 2004

2004-01-01

Ideological arguments are made for open learning, economic ones for distance education. If it can produce similar results to those of conventional education at a lower cost, then distance education has a powerful appeal. With increasing demand for access to educational opportunities at all levels, and often decreasing budgets in real terms for…

Strategy for a Sustained Quality Delivery Mode of ODL Programmes for Massive Enrollments and E-Learning: The Case for Zimbabwe Open University

ERIC Educational Resources Information Center

Kabanda, Gabriel

2014-01-01

The market dynamics in distance education has precipitated phenomenal growth opportunities in enrollments and e-learning. The purpose of the paper was to develop a strategy for sustained quality delivery mode of distance education progammes that precipitate massive enrollments and e-learning in an open and distance learning (ODL) institution using…

Assessing Learning Styles among Students with and without Learning Disabilities at a Distance-Learning University

ERIC Educational Resources Information Center

Heiman, Tali

2006-01-01

Differences in the learning styles of students with and without learning disabilities (LD) at a distance-learning university were examined. Two hundred and twelve students answered self-report questionnaires on their learning styles. Results revealed that students with LD preferred to use more stepwise processing, including memorizing and…

E-Learning in Malaysia: Moving forward in Open Distance Learning

ERIC Educational Resources Information Center

Abas, Zoraini Wati

2009-01-01

Many higher education institutions have embarked on e-learning as a means to support their learning and teaching activities. In distance learning institutions, e-learning has enabled them to reach out to students dispersed over a wide geographical area, locally and internationally. In some countries, e-learning has also given students the…

E-Learning and Technologies for Open Distance Learning in Management Accounting

ERIC Educational Resources Information Center

Kashora, Trust; van der Poll, Huibrecht M.; van der Poll, John A.

2016-01-01

This research develops a knowledge acquisition and construction framework for e-learning for Management Accounting students at the University of South Africa, an Open Distance Learning institution which utilises e-learning. E-learning refers to the use of electronic applications and processes for learning, including the transfer of skills and…

The Future of Learning: From eLearning to mLearning.

ERIC Educational Resources Information Center

Keegan, Desmond

The future of electronic learning was explored in an analysis that viewed the provision of learning at a distance as a continuum and traced the evolution from distance learning to electronic learning to mobile learning in Europe and elsewhere. Special attention was paid to the following topics: (1) the impact of the industrial revolution, the…

New Definitions for New Higher Education Institutions

ERIC Educational Resources Information Center

Meyer, Katrina A.

2009-01-01

New terms were exploding early in the development of distance learning and virtual universities. Distance learning, online learning, e-learning, and distributed learning were applied to the various new forms of learning using online or Web-based materials and processes. However, largely thanks to the immediate popularity of the Western Governors'…

Integrating E-Learning into the Workplace.

ERIC Educational Resources Information Center

Harun, Mohd Hishamuddin

2001-01-01

Discussion of electronic learning and knowledge management in the workplace focuses on learning and training in the medical and health care setting in Malaysia. Highlights include learning and the knowledge economy; just-in-time continuing medical education; distance education; and modular distance learning. (Author/LRW)

Scaling of flow distance in random self-similar channel networks

USGS Publications Warehouse

Troutman, B.M.

2005-01-01

Natural river channel networks have been shown in empirical studies to exhibit power-law scaling behavior characteristic of self-similar and self-affine structures. Of particular interest is to describe how the distribution of distance to the outlet changes as a function of network size. In this paper, networks are modeled as random self-similar rooted tree graphs and scaling of distance to the root is studied using methods in stochastic branching theory. In particular, the asymptotic expectation of the width function (number of nodes as a function of distance to the outlet) is derived under conditions on the replacement generators. It is demonstrated further that the branching number describing rate of growth of node distance to the outlet is identical to the length ratio under a Horton-Strahler ordering scheme as order gets large, again under certain restrictions on the generators. These results are discussed in relation to drainage basin allometry and an application to an actual drainage network is presented. ?? World Scientific Publishing Company.

Learning of Multimodal Representations With Random Walks on the Click Graph.

PubMed

Wu, Fei; Lu, Xinyan; Song, Jun; Yan, Shuicheng; Zhang, Zhongfei Mark; Rui, Yong; Zhuang, Yueting

2016-02-01

In multimedia information retrieval, most classic approaches tend to represent different modalities of media in the same feature space. With the click data collected from the users' searching behavior, existing approaches take either one-to-one paired data (text-image pairs) or ranking examples (text-query-image and/or image-query-text ranking lists) as training examples, which do not make full use of the click data, particularly the implicit connections among the data objects. In this paper, we treat the click data as a large click graph, in which vertices are images/text queries and edges indicate the clicks between an image and a query. We consider learning a multimodal representation from the perspective of encoding the explicit/implicit relevance relationship between the vertices in the click graph. By minimizing both the truncated random walk loss as well as the distance between the learned representation of vertices and their corresponding deep neural network output, the proposed model which is named multimodal random walk neural network (MRW-NN) can be applied to not only learn robust representation of the existing multimodal data in the click graph, but also deal with the unseen queries and images to support cross-modal retrieval. We evaluate the latent representation learned by MRW-NN on a public large-scale click log data set Clickture and further show that MRW-NN achieves much better cross-modal retrieval performance on the unseen queries/images than the other state-of-the-art methods.

Multistrategy Self-Organizing Map Learning for Classification Problems

PubMed Central

Hasan, S.; Shamsuddin, S. M.

2011-01-01

Multistrategy Learning of Self-Organizing Map (SOM) and Particle Swarm Optimization (PSO) is commonly implemented in clustering domain due to its capabilities in handling complex data characteristics. However, some of these multistrategy learning architectures have weaknesses such as slow convergence time always being trapped in the local minima. This paper proposes multistrategy learning of SOM lattice structure with Particle Swarm Optimisation which is called ESOMPSO for solving various classification problems. The enhancement of SOM lattice structure is implemented by introducing a new hexagon formulation for better mapping quality in data classification and labeling. The weights of the enhanced SOM are optimised using PSO to obtain better output quality. The proposed method has been tested on various standard datasets with substantial comparisons with existing SOM network and various distance measurement. The results show that our proposed method yields a promising result with better average accuracy and quantisation errors compared to the other methods as well as convincing significant test. PMID:21876686

Effects of the distance among multiple spreaders on the spreading

NASA Astrophysics Data System (ADS)

Hu, Z.-L.; Liu, J.-G.; Yang, G.-Y.; Ren, Z.-M.

2014-04-01

It is very important to investigate the multiple spreaders' effects since the spreading phenomenon is ubiquitous in many complex systems. In this letter, we investigate the effects of the distance among the initial multiple spreaders for regular networks and WS (Watts-Strogatz) small-world networks based on the SIR (Susceptible-Infected-Recovered) model. Assuming the epidemics can spread over the network, the theoretical and experimental results show that for regular networks the larger the distance between spreaders is, the more effective the spreading is. For WS networks, the spreading efficiency will decrease when the distance exceeds a certain value, and a larger connection probability and average degree will result in a smaller distance of the most effective spreading. A better spreading strategy using n spreaders is to choose either the highest k or ks nodes with the condition that there are not any pairs of the n spreaders linked directly (Kitsak M. et al., Nat. Phys., 6 (2010) 888). However, we find that the spreading will be more effective when the distances among the largest-degree spreaders increase. All these results are independent of the network size for the two initial spreaders case. This work may give new insights to explore more effective methods to inhibit the epidemic spreading or increase the information diffusion.

Improving Distance Courses: Understanding Teacher Trainees and Their Learning Styles for the Design of Teacher Training Courses and Materials at a Distance

ERIC Educational Resources Information Center

Dzakiria, Hisham; Razak, Asmahan Abdul; Mohamed, Abdul Halim

2004-01-01

Literature on distance education and teacher education seems to show that what we do not know about Distance Teacher Trainees (DTT) and their learning process involved exceeds what we know about it. As more DTT enroll in distance education programmes globally, distance education providers and institutions will witness trainees coming with…

Overlapping community detection based on link graph using distance dynamics

NASA Astrophysics Data System (ADS)

Chen, Lei; Zhang, Jing; Cai, Li-Jun

2018-01-01

The distance dynamics model was recently proposed to detect the disjoint community of a complex network. To identify the overlapping structure of a network using the distance dynamics model, an overlapping community detection algorithm, called L-Attractor, is proposed in this paper. The process of L-Attractor mainly consists of three phases. In the first phase, L-Attractor transforms the original graph to a link graph (a new edge graph) to assure that one node has multiple distances. In the second phase, using the improved distance dynamics model, a dynamic interaction process is introduced to simulate the distance dynamics (shrink or stretch). Through the dynamic interaction process, all distances converge, and the disjoint community structure of the link graph naturally manifests itself. In the third phase, a recovery method is designed to convert the disjoint community structure of the link graph to the overlapping community structure of the original graph. Extensive experiments are conducted on the LFR benchmark networks as well as real-world networks. Based on the results, our algorithm demonstrates higher accuracy and quality than other state-of-the-art algorithms.

Determination of Critical Achievement Factors in Distance Education by Using Structural Equality Model: A Case Study of E-MBA Program Held in Sakarya University

ERIC Educational Resources Information Center

Evirgen, Hayrettin; Cengel, Metin

2012-01-01

Nowadays, distance learning education has started to become familiar in behalf of classical face to face education (F2F) model. Web based learning is a major part of distance education systems. Web based distance learning can be defined shortly as an education type which doesn't force students and educators being into the same mediums. This…

A Comparative Analysis of the Academic Performance of Distance and On-Campus Learners

ERIC Educational Resources Information Center

Magagula, C. M.; Ngwenya, A. P.

2004-01-01

This study examined (1) the profile of the distance and on-campus learners, (2) the academic performance of distance and on-campus learners, (3) the advantages and disadvantages of learning through distance education and on-campus education, and (4) how the disadvantages of learning through distance education could be reduced. The study found that…

Learning across Distance

ERIC Educational Resources Information Center

Cowan, Kristina

2009-01-01

A 2008 report, "Keeping Pace with K-12 Online Learning," commissioned by North American Council for Online Learning (NACOL) and others, defines online learning as "teacher-led education that takes place over the Internet, with the teacher and student separated geographically." The term "distance learning" includes online education, but is…

Distance Learning and University Effectiveness: Changing Educational Paradigms for Online Learning

ERIC Educational Resources Information Center

Howard, Caroline; Schenk, Karen; Discenza, Richard

2004-01-01

"Distance Learning and University Effectiveness: Changing Educational Paradigms for Online Learning" addresses the challenges and opportunities associated with information and communication technologies (ICTs) as related to education. From discussing new and innovative educational paradigms and learning models resulting from ICTs to addressing…

Distance Learning and the Health Professions: A Synthesis Report of the Literature Investigating Continuing Professional Health Education at a Distance.

ERIC Educational Resources Information Center

Curran, Vernon; Noseworthy, Tanya

This synthesis report provides an extensive overview of literature evaluating use and effectiveness of distance learning technologies in delivering continuing education (CE) for health professionals. Chapter 2 discusses advantages and disadvantages of correspondence materials, explores suggestions for improving print-based learning materials, and…

Distance Learning Courses on the Web: The Authoring Approach.

ERIC Educational Resources Information Center

Santos, Neide; Diaz, Alicia; Bibbo, Luis Mariano

This paper proposes a framework for supporting the authoring process of distance learning courses. An overview of distance learning courses and the World Wide Web is presented. The proposed framework is then described, including: (1) components of the framework--a hypermedia design methodology for authoring the course, links to related Web sites,…

A Study of Distance Learning Technology in Utah: A Statewide Overview.

ERIC Educational Resources Information Center

Chow, Stanley H. L.; And Others

This report was commissioned by the Utah State Office of Education (USOE) to provide USOE with information about the potential applications of distance learning technology in schools. The study includes: (1) a statewide assessment of instructional, staff development, and administrative needs which may be met by distance learning technology; and…

Distance Learning 2000: Proceedings of the Annual Conference on Distance Teaching & Learning (16th, Madison, Wisconsin, August 2-4, 2000).

ERIC Educational Resources Information Center

Wisconsin Univ. System, Madison.

These proceedings contain 75 papers from information sessions that address important human factors in distance education from several perspectives, including implementation planning, management and policy, instructional design, teaching methods, faculty development, learning environments, learner supports, and evaluation. Among the papers are:…

Characteristics and Activities of Teachers on Distance Learning Programs That Affect Their Ratings

ERIC Educational Resources Information Center

Stanišic Stojic, Svetlana M.; Dobrijevic, Gordana; Stanišic, Nemanja; Stanic, Nenad

2014-01-01

This paper presents an analysis of teachers' ratings on distance learning undergraduate study programs: 7,156 students enrolled in traditional and 528 students enrolled in distance learning studies took part in the evaluation questionnaire, assessing 71 teachers. The data were collected from the Moodle platform and from the Singidunum University…

Distance Education in the United States: From Correspondence Courses to the Internet

ERIC Educational Resources Information Center

Caruth, Gail D.; Caruth, Donald L.

2013-01-01

Online learning is a descendant of distance education. Online education has a shared history with correspondence learning. In 1873, Anna Eliot Ticknor founded the Society to Encourage Studies at Home. Ticknor's Society established one of America's first correspondence schools, a distance learning option conducted through the mail. This Society was…

Incorporating Distance Learning into Counselor Education Programs: A Research Study.

ERIC Educational Resources Information Center

Wantz, Richard A.; Tromski, Donna M.; Mortsolf, Christina Joelle; Yoxtheimer, Greggory; Brill, Samantha; Cole, Alison

The purpose of this study is to determine the number of counselor education programs that utilize distance learning, to identify the distance learning software delivery products used, and to identify features of software used. The researchers also attempt to identify faculty perceptions related to and experience with the importance of distance…

The Open College of the North West, Distance Learning, and the "Open Tech" Programme.

ERIC Educational Resources Information Center

Percy, Keith; Saunders, Murray

1982-01-01

A regional program of pre-university courses in northwestern England open to adults with no entry qualifications is discussed. It uses some distance learning techniques but is investigating expansion to technical education through distance learning. The complexities and potential costs of such a substantial directional change are examined. (MSE)

Effectiveness of Asynchronous Reference Services for Distance Learning Students within Florida's Community College System

ERIC Educational Resources Information Center

Profeta, Patricia C.

2007-01-01

The provision of equitable library services to distance learning students emerged as a critical area during the 1990s. Library services available to distance learning students included digital reference and instructional services, remote access to online research tools, database and research tutorials, interlibrary loan, and document delivery.…

NASA Langley/CNU Distance Learning Programs.

ERIC Educational Resources Information Center

Caton, Randall; Pinelli, Thomas E.

NASA Langley Research Center and Christopher Newport University (CNU) provide, free to the public, distance learning programs that focus on math, science, and/or technology over a spectrum of education levels from K-adult. The effort started in 1997, and currently there are a suite of five distance-learning programs. This paper presents the major…

New-to-College "Academic Transformation" Distance Learning: A Paradox

ERIC Educational Resources Information Center

Goomas, David T.; Clayton, Alexis

2013-01-01

At an urban Dallas community college, first-time-in-college (FTIC) distance learning students enrolled in a three-credit academic transformation class were compared with FTIC students enrolled in the same course in on-campus classes. The distance-learning students were more at risk as measured by final semester grades and retention compared to…

Digital Competence Model of Distance Learning Students

ERIC Educational Resources Information Center

da Silva, Ketia Kellen A.; Behar, Patricia A.

2017-01-01

This article presents the development of a digital competency model of Distance Learning (DL) students in Brazil called CompDigAl_EAD. The following topics were addressed in this study: Educational Competences, Digital Competences, and Distance Learning students. The model was developed between 2015 and 2016 and is being validated in 2017. It was…

Distance-Learning Programs. Case Studies in TESOL Practice Series.

ERIC Educational Resources Information Center

Henrichsen, Lynn E., Ed.

The 14 cases in this book show how distance learning takes a variety of forms in teaching English to speakers of other languages (TESOL). The 15 chapters include the following: (1) "Beyond Adding Telecommunications to a Traditional Course: Insights into Human and Instructional Factors Affecting Distance Learning in TESOL" (Lynn E.…

Implementing a Learning Model for a Practical Subject in Distance Education.

ERIC Educational Resources Information Center

Weller, M. J.; Hopgood, A. A.

1997-01-01

Artificial Intelligence for Technology, a distance learning course at the Open University, is based on a learning model that combines conceptualization, construction, and dialog. This allows a practical emphasis which has been difficult to implement in distance education. The course uses commercial software, real-world-based assignments, and a…

Adding Interactivity to Web Based Distance Learning.

ERIC Educational Resources Information Center

Cafolla, Ralph; Knee, Richard

Web Based Distance Learning (WBDL) is a form of distance learning based on providing instruction mainly on the World Wide Web. This paradigm has limitations, especially the lack of interactivity inherent in the Web. The purpose of this paper is to discuss some of the technologies the authors have used in their courses at Florida Atlantic…

Student Support Gaps in an Open Distance Learning Context

ERIC Educational Resources Information Center

Arko-Achemfuor, Akwasi

2017-01-01

Studying through distance education can be problematic for any student, but it can be worse for rural students for diverse reasons. To ensure that students studying through the open distance learning (ODL) system have an enduring learning experience, ODL builds student support as one of its components. The University of South Africa (Unisa)…

The Effects of Videoconferenced Distance-Learning Instruction in a Taiwanese Company

ERIC Educational Resources Information Center

Lin, Chin-Hung; Yang, Shu-Ching

2011-01-01

Distance learning, where instruction is given to students despite wide separations of students and teachers, is increasingly popular. Videoconferencing, which is examined in this study, is a distance learning mode of featuring real-time interaction of students and teachers and provides sequence, real-time, vision, and actual interaction. This…

Embracing Distance Education in a Blended Learning Model: Challenges and Prospects

ERIC Educational Resources Information Center

Fresen, Jill W.

2018-01-01

Distance education reaches out to non-traditional students in geographically dispersed locations, who are unable to attend face-to-face classes. Contact institutions have been quick to realise the many advantages of distance (online) learning, such as easy access to learning materials, interactive activities, assessment and communication tools.…

Assessment of Readiness to Participate in Distance Learning of the Certified Florida Behavioral Workforce

ERIC Educational Resources Information Center

Baston, George R.

2011-01-01

This research study explored perceptions of readiness to participate in distance learning among the certified behavioral workforce in Florida. The study sought to determine if there were significant differences in perception of readiness to participate in distance learning between certified behavioral health professionals at the administrator…

Distance Learning and Jihad: The Dark Side of the Force

ERIC Educational Resources Information Center

Bates, Rodger; Mooney, Mara

2014-01-01

The ability to reach a variety of audiences in diverse environments has made distance learning a major form of education and training in the 21st century. Though traditionally encountered in the educational and business communities, distance learning has proven an important resource for a variety of other constituencies. Terrorist groups have…

Factors Affecting Corporate Image from the Perspective of Distance Learning Students in Public Higher Education Institutions

ERIC Educational Resources Information Center

da Costa, Fábio Reis; Pelissari, Anderson Soncini

2016-01-01

New information technologies enable different interactions in the educational environment, affecting how the image of educational institutions adopting distance-learning programmes is perceived. This article identifies factors affecting the perception of corporate image from the viewpoint of distance-learning students at public higher education…

Distance Learning for Gifted Students: Outcomes for Elementary, Middle, and High School Aged Students

ERIC Educational Resources Information Center

Wallace, Patricia

2009-01-01

Although distance learning often is cited as a potentially useful strategy to provide appropriately challenging academic coursework to gifted students, little research has been conducted on its use or effectiveness with this population, particularly with younger students in elementary school. In this study, distance learning outcomes for gifted…

Access and Success in Learning: Technologies for Scaling Up Open and Distance Learning Programme in the Institute of Distance Learning, KNUST, Kumasi, Ghana

ERIC Educational Resources Information Center

Essel, Rebecca; Owusu-Boateng, William

2011-01-01

ODL (Open and Distance Learning) has come to stay. In recent years, there has been some extra-ordinary increasing international interest in it and Ghana is no exception. Currently, new ways of providing education are inevitable and ODL provides an effective alternate way. It represents approaches that focus on opening access to education and…

A regularized approach for geodesic-based semisupervised multimanifold learning.

PubMed

Fan, Mingyu; Zhang, Xiaoqin; Lin, Zhouchen; Zhang, Zhongfei; Bao, Hujun

2014-05-01

Geodesic distance, as an essential measurement for data dissimilarity, has been successfully used in manifold learning. However, most geodesic distance-based manifold learning algorithms have two limitations when applied to classification: 1) class information is rarely used in computing the geodesic distances between data points on manifolds and 2) little attention has been paid to building an explicit dimension reduction mapping for extracting the discriminative information hidden in the geodesic distances. In this paper, we regard geodesic distance as a kind of kernel, which maps data from linearly inseparable space to linear separable distance space. In doing this, a new semisupervised manifold learning algorithm, namely regularized geodesic feature learning algorithm, is proposed. The method consists of three techniques: a semisupervised graph construction method, replacement of original data points with feature vectors which are built by geodesic distances, and a new semisupervised dimension reduction method for feature vectors. Experiments on the MNIST, USPS handwritten digit data sets, MIT CBCL face versus nonface data set, and an intelligent traffic data set show the effectiveness of the proposed algorithm.

College Students Attitudes toward Learning Process and Outcome of Online Instruction and Distance Learning across Learning Styles

ERIC Educational Resources Information Center

Nguyen, Dat-Dao; Zhang, Yue

2011-01-01

This study uses the Learning-Style Inventory--LSI (Smith & Kolb, 1985) to explore to what extent student attitudes toward learning process and outcome of online instruction and Distance Learning are affected by their cognitive styles and learning behaviors. It finds that there are not much statistically significant differences in perceptions…

A spectral method to detect community structure based on distance modularity matrix

NASA Astrophysics Data System (ADS)

Yang, Jin-Xuan; Zhang, Xiao-Dong

2017-08-01

There are many community organizations in social and biological networks. How to identify these community structure in complex networks has become a hot issue. In this paper, an algorithm to detect community structure of networks is proposed by using spectra of distance modularity matrix. The proposed algorithm focuses on the distance of vertices within communities, rather than the most weakly connected vertex pairs or number of edges between communities. The experimental results show that our method achieves better effectiveness to identify community structure for a variety of real-world networks and computer generated networks with a little more time-consumption.

Designing, delivering and evaluating a distance learning nursing course responsive to students needs.

PubMed

Sowan, Azizeh K; Jenkins, Louise S

2013-06-01

The majority of available studies in distance learning in nursing and health lack the sufficient details of course design and delivery processes which greatly affect the learning outcomes. Also, little is available about the fairness of this method of education to students with limited access to course resources. We describe the design and delivery processes and experience, in terms of satisfaction and achievement, of undergraduate nursing students in a distance course. The difference in achievement between the distance students and a comparable cohort of hybrid students is also examined. We also demonstrate the possibility of providing accessible education to students with limited technological resources. Participants included all undergraduate nursing students who were enrolled in a distance and a hybrid section of a communication skills course offered at a School of Nursing in Jordan. The distance course was created using Blackboard and Tegrity learning management systems. The design and delivery processes of the distance course incorporated three pedagogical principles that enhance: (a) course access and navigation; (b) communication and interaction; and (c) active and collaborative learning experiences. After course completion, distance students completed a 27-item satisfaction questionnaire. Achievement in the course and correlates of satisfaction were measured. The final sample included 25 students in the distance section and 35 in the hybrid section (N=60). The mean score of overall satisfaction in the distance section was 4.14 (0.32) out of a 5-point scale, indicating a high satisfaction. Results revealed significant associations between total satisfaction score and achievement in the distance course, grade expected in the course, and frequency of accessing the course materials (p<.05). All distance students, including students with limited technological resources available at home, managed to successfully complete the course. Major concerns reported by distance students were related to lack of time management skills and negative attitudes toward group assignments. The mean final course grade of the distance section (80±8.2) was significantly higher than the hybrid section (72.2±9.5), (t=3.5, p<.05). The use of effective instructional strategies resulted in delivering successful distance learning, even for students with limited resources. Institutions have to make strategic decisions on how to optimize the use of technology to fit their individualized learning environments. Instructors need to become familiar with the characteristics of students cohort served by the course and design the course accordingly. In addition, students should be guided on how to manage their time in distance learning environments and work effectively in group assignments. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Enhancing SCORM Metadata for Assessment Authoring in E-Learning

ERIC Educational Resources Information Center

Chang, Wen-Chih; Hsu, Hui-Huang; Smith, Timothy K.; Wang, Chun-Chia

2004-01-01

With the rapid development of distance learning and the XML technology, metadata play an important role in e-Learning. Nowadays, many distance learning standards, such as SCORM, AICC CMI, IEEE LTSC LOM and IMS, use metadata to tag learning materials. However, most metadata models are used to define learning materials and test problems. Few…

An Assistive Computerized Learning Environment for Distance Learning Students with Learning Disabilities

ERIC Educational Resources Information Center

Klemes, Joel; Epstein, Alit; Zuker, Michal; Grinberg, Nira; Ilovitch, Tamar

2006-01-01

The current study examines how a computerized learning environment assists students with learning disabilities (LD) enrolled in a distance learning course at the Open University of Israel. The technology provides computer display of the text, synchronized with auditory output and accompanied by additional computerized study skill tools which…

Data-Driven Neural Network Model for Robust Reconstruction of Automobile Casting

NASA Astrophysics Data System (ADS)

Lin, Jinhua; Wang, Yanjie; Li, Xin; Wang, Lu

2017-09-01

In computer vision system, it is a challenging task to robustly reconstruct complex 3D geometries of automobile castings. However, 3D scanning data is usually interfered by noises, the scanning resolution is low, these effects normally lead to incomplete matching and drift phenomenon. In order to solve these problems, a data-driven local geometric learning model is proposed to achieve robust reconstruction of automobile casting. In order to relieve the interference of sensor noise and to be compatible with incomplete scanning data, a 3D convolution neural network is established to match the local geometric features of automobile casting. The proposed neural network combines the geometric feature representation with the correlation metric function to robustly match the local correspondence. We use the truncated distance field(TDF) around the key point to represent the 3D surface of casting geometry, so that the model can be directly embedded into the 3D space to learn the geometric feature representation; Finally, the training labels is automatically generated for depth learning based on the existing RGB-D reconstruction algorithm, which accesses to the same global key matching descriptor. The experimental results show that the matching accuracy of our network is 92.2% for automobile castings, the closed loop rate is about 74.0% when the matching tolerance threshold τ is 0.2. The matching descriptors performed well and retained 81.6% matching accuracy at 95% closed loop. For the sparse geometric castings with initial matching failure, the 3D matching object can be reconstructed robustly by training the key descriptors. Our method performs 3D reconstruction robustly for complex automobile castings.

A distance learning model in a physical therapy curriculum.

PubMed

English, T; Harrison, A L; Hart, A L

1998-01-01

In response to the rural health initiative established in 1991, the University of Kentucky has developed an innovative distance learning program of physical therapy instruction that combines classroom lecture and discussion via compressed video technology with laboratory experiences. The authors describe the process of planning, implementing, and evaluating a specific distance learning course in pathomechanics for the professional-level master's-degree physical therapy students at the University of Kentucky. This presentation may serve as a model for teaching distance learning. Descriptions of optimal approaches to preclass preparation, scheduling, course delivery, use of audiovisual aids, use of handout material, and video production are given. Special activities that may enhance or deter the achievement of the learning objectives are outlined, and a problem-solving approach to common problems encountered is presented. An approach to evaluating and comparing course outcomes for the distance learnere is presented. For this particular course, there was no statistically significant difference in the outcome measures utilized to compare the distance learners with the on-site learners.

Distance Education and Open Learning in Sub-Saharan Africa: Criteria and Conditions for Quality and Critical Success Factor-- Working Group on Distance Education and Open Learning. A Survey of Policy and Practice. Final Report

ERIC Educational Resources Information Center

Commonwealth of Learning, 2004

2004-01-01

Both of these "Surveys of policy and practice" were conducted on behalf of COL by the South African Institute for Distance Education (SAIDE) as part of COL's partnership agreement with the Association for the Development of Education in Africa (ADEA) Working Group on Distance Education and Open Learning. The first report identifies…

Homeostatic plasticity for single node delay-coupled reservoir computing.

PubMed

Toutounji, Hazem; Schumacher, Johannes; Pipa, Gordon

2015-06-01

Supplementing a differential equation with delays results in an infinite-dimensional dynamical system. This property provides the basis for a reservoir computing architecture, where the recurrent neural network is replaced by a single nonlinear node, delay-coupled to itself. Instead of the spatial topology of a network, subunits in the delay-coupled reservoir are multiplexed in time along one delay span of the system. The computational power of the reservoir is contingent on this temporal multiplexing. Here, we learn optimal temporal multiplexing by means of a biologically inspired homeostatic plasticity mechanism. Plasticity acts locally and changes the distances between the subunits along the delay, depending on how responsive these subunits are to the input. After analytically deriving the learning mechanism, we illustrate its role in improving the reservoir's computational power. To this end, we investigate, first, the increase of the reservoir's memory capacity. Second, we predict a NARMA-10 time series, showing that plasticity reduces the normalized root-mean-square error by more than 20%. Third, we discuss plasticity's influence on the reservoir's input-information capacity, the coupling strength between subunits, and the distribution of the readout coefficients.

INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Dynamic Evolution with Limited Learning Information on a Small-World Network

NASA Astrophysics Data System (ADS)

Dong, Lin-Rong

2010-09-01

This paper investigates the dynamic evolution with limited learning information on a small-world network. In the system, the information among the interaction players is not very lucid, and the players are not allowed to inspect the profit collected by its neighbors, thus the focal player cannot choose randomly a neighbor or the wealthiest one and compare its payoff to copy its strategy. It is assumed that the information acquainted by the player declines in the form of the exponential with the geographical distance between the players, and a parameter V is introduced to denote the inspect-ability about the players. It is found that under the hospitable conditions, cooperation increases with the randomness and is inhibited by the large connectivity for the prisoner's dilemma; however, cooperation is maximal at the moderate rewiring probability and is chaos with the connectivity for the snowdrift game. For the two games, the acuminous sight is in favor of the cooperation under the hospitable conditions; whereas, the myopic eyes are advantageous to cooperation and cooperation increases with the randomness under the hostile condition.

DeepSite: protein-binding site predictor using 3D-convolutional neural networks.

PubMed

Jiménez, J; Doerr, S; Martínez-Rosell, G; Rose, A S; De Fabritiis, G

2017-10-01

An important step in structure-based drug design consists in the prediction of druggable binding sites. Several algorithms for detecting binding cavities, those likely to bind to a small drug compound, have been developed over the years by clever exploitation of geometric, chemical and evolutionary features of the protein. Here we present a novel knowledge-based approach that uses state-of-the-art convolutional neural networks, where the algorithm is learned by examples. In total, 7622 proteins from the scPDB database of binding sites have been evaluated using both a distance and a volumetric overlap approach. Our machine-learning based method demonstrates superior performance to two other competitive algorithmic strategies. DeepSite is freely available at www.playmolecule.org. Users can submit either a PDB ID or PDB file for pocket detection to our NVIDIA GPU-equipped servers through a WebGL graphical interface. gianni.defabritiis@upf.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

A Strategic Planning Process Model for Distance Education

ERIC Educational Resources Information Center

Pisel, Kenneth P.

2008-01-01

As more institutions seek to implement or expand distance learning programs, it becomes critical to integrate distance learning programs into broader strategic visions and plans. Using the informed opinion from a panel of peer-nominated experts via iterative Delphi questionnaires, a 10-phased strategic planning process model for distance education…

Quality Assurance, Open and Distance Learning, and Australian Universities

ERIC Educational Resources Information Center

Reid, Ian C.

2005-01-01

Open and distance education has integrated quality assurance processes since its inception. Recently, the increased use of distance teaching systems, technologies, and pedagogies by universities without a distance education heritage has enabled them to provide flexible learning opportunities. They have done this in addition to, or instead of,…

Quality Assurance in Distance Learning Libraries

ERIC Educational Resources Information Center

Tripathi, Manorama; Jeevan, V. K. J.

2009-01-01

Purpose: The paper aims to study how the present distance learning libraries can improve upon their existing services and introduce new ones to enhance quality of services to distance learners. Design/methodology/approach: The paper includes a review of literature on quality assurance in open and distance education in general and student support…

Distance Education and Distributed Learning. Current Perspectives on Applied Information Technologies.

ERIC Educational Resources Information Center

Vrasidas, Charalambos, Ed.; Glass, Gene V., Ed.

This book describes the current state of developments in distance education and distributed learning. The volume brings together some of the leading contemporary contributors in the areas of educational technology and distance education. Topics covered include research and evaluation in distance education, online communities, faculty productivity,…

Strategic Plan for the Academic Component of the Army National Guard Distance Learning Demonstration.

DTIC Science & Technology

1998-07-01

II - Directed study on Distance Learning Technologies - Action Memorandum. a reserve unit where they perform the same job as they did as full-time...a virtual learning community and provide a classroom without walls. The harnessing of appropriate technology to meet the training needs offers...its force through training, the Distance Learning capabilities also becomes part of community resources that advance the education of local residents

Burnout Syndrome in Students of a Distance Learning Program: The Open University of Cyprus Experience

ERIC Educational Resources Information Center

Pavlakis, Andreas; Kaitelidou, Dafni

2012-01-01

Introduction: Distance learning seems to have a crucial impact on the social and emotional life of students. Within the framework of distance learning at the Open University of Cyprus, the "Healthcare Management" department conducted a study regarding the levels of stress, anxiety and depression reported by the student population. The…

From Radio, to Satellite, to M-Learning: Interactive Distance Education in Australia

ERIC Educational Resources Information Center

Crump, Stephen

2013-01-01

This paper provides reflections on M-learning as a form of "distance education," based on a summary of the findings of the Interactive Distance e-Learning (IDL) research project in rural and remote Australia under an Australian Research Council Linkage grant. This project was a joint undertaking between 3 government agencies and an…

Distance Learning Course Design Expectations in China and the United Kingdom

ERIC Educational Resources Information Center

Xu, Jingjing; Rees, Terri

2016-01-01

This article provides insight into different expectations between Chinese and British academic culture for distance learning. The article is based on a pedagogic research project, a case study, and is centered on a distance learning course in maritime law proposed by a British university for a university in China. Some important commonalities and…

The Development of a Survey Instrument to Measure Transactional Distance in Secondary Blended Learning Environments

ERIC Educational Resources Information Center

Lane, Dennis Glenn

2017-01-01

The goal of this study was to develop a survey instrument to measure transactional distance in secondary blended learning environments. This study resulted in a 35-item survey instrument, the Blended Learning Assessment Scale of Transactional Distance (BLASTD), which was tested using a convenience sample of secondary students (n = 222) at a…

Automated Inattention and Fatigue Detection System in Distance Education for Elementary School Students

ERIC Educational Resources Information Center

Hwang, Kuo-An; Yang, Chia-Hao

2009-01-01

Most courses based on distance learning focus on the cognitive domain of learning. Because students are sometimes inattentive or tired, they may neglect the attention goal of learning. This study proposes an auto-detection and reinforcement mechanism for the distance-education system based on the reinforcement teaching strategy. If a student is…

Distance Training: How Innovative Organizations Are Using Technology To Maximize Learning and Meet Business Objectives. Jossey-Bass Business and Management Series.

ERIC Educational Resources Information Center

Schreiber, Deborah A.; Berge, Zane L.

This book contains 19 papers examining ways in which innovative organizations are using distance learning technology to maximize learning and meet business objectives. The following papers are included: "Preface" (Deborah A. Schreiber, Zane L. Berge); "Organizational Technology and Its Impact on Distance Training" (Deborah A.…

What Is the Role of Distance Learning in the State University System? Information Brief. Volume 6, Issue 2

ERIC Educational Resources Information Center

Florida Board of Governors, State University System, 2008

2008-01-01

Distance learning is the term used when the delivery of instruction involves the separation of student(s) and the instructor by time and/or space. Some forms of distance learning include correspondence, telecourses, online instruction, computer assisted instruction, and instructional delivery that relies upon satellite, cable, broadcast (TV or…

Supporting Students in Open and Distance Learning. Open and Distance Learning Series.

ERIC Educational Resources Information Center

Simpson, Ormond

This book, which is intended for individuals involved in recruiting and teaching students in open and distance learning (ODL) situations, examines academic and nonacademic student support issues in ODL. The following are among the topics discussed in the book's 14 chapters: (1) models and definitions of ODL systems; (2) rationale for student…

The Resonance Factor: Probing the Impact of Video on Student Retention in Distance Learning

ERIC Educational Resources Information Center

Geri, Nitza

2012-01-01

Teaching and instructing is one of the challenging manifestations of informing, within which distance learning is considered harder than face-to-face instruction. Student retention is one of the major challenges of distance learning. Current innovative technologies enable widespread use of video lectures that may ease the loneliness of the…

Perspectives on Distance Education and Social Media

ERIC Educational Resources Information Center

Powers, Lisa; Alhussain, Ruqaya; Averbeck, Clemens; Warner, Andre

2012-01-01

There is a dramatic shift in the tools that are used in today's technology-based distance education. While distance education is not new, there are new types of socially rich, mobile technologies that empower learners to be more in control of what they learn, when they learn it, and how they learn it. Students are taking more responsibility for…

A Framework for Developing Competencies in Open and Distance Learning

ERIC Educational Resources Information Center

Arinto, Patricia B.

2013-01-01

Many open universities and distance education institutions have shifted from a predominantly print-based mode of delivery to an online mode characterised by the use of virtual learning environments and various web technologies. This paper describes the impact of the shift to open and distance e-learning (ODeL), as this trend might be called, on…

Transactional Distance among Open University Students: How Does it Affect the Learning Process?

ERIC Educational Resources Information Center

Kassandrinou, Amanda; Angelaki, Christina; Mavroidis, Ilias

2014-01-01

This study examines the presence of transactional distance among students, the factors affecting it, as well as the way it influences the learning process of students in a blended distance learning setting in Greece. The present study involved 12 postgraduate students of the Hellenic Open University (HOU). A qualitative research was conducted,…

Survey on Uses of Distance Learning in the U.S.

ERIC Educational Resources Information Center

Downing, Diane E.

A December 1983 survey queried the chief state school officers of the 50 states on the extent to which distance learning techniques are used in public education in their states. Respondents were asked to focus on interactive forms of distance learning, such as audio and video teleconferencing. A total of 28 states (56%) responded, with the…

Cross-Sectional Evaluation of Distance Education Students' Learning Styles and Critical Thinking Dispositions in Turkey

ERIC Educational Resources Information Center

Yüksel, Ismail; Türkses, Ercüment

2015-01-01

This study aims to examine distance education students' learning styles and critical thinking dispositions. This cross sectional survey was conducted on 114 Turkish distance education students from various departments in a state university. The data of the study were collected through Grasha-Riechmann Student Learning Style Scale (GRSLSS) and…

China's Radio and TV Universities: Reflections on Theory and Practice of Open and Distance Learning

ERIC Educational Resources Information Center

Wei, Runfang

2010-01-01

Distance education and open learning are western innovations, representing the educational concepts, cultures and societies of western countries. The introduction of distance education and the adoption of open learning in China's radio and TV universities are by no means an indication that they will and can be copied wholesale. Open and distance…

High School Students in the New Learning Environment: A Profile of Distance E-Learners

ERIC Educational Resources Information Center

Kirby, Dale; Sharpe, Dennis

2010-01-01

The relative ubiquity of computer access and the rapid development of information and communication technology have profoundly impacted teaching and learning at a distance. Relatively little is currently known about the characteristics of those students who participate in distance e-learning courses at the secondary school level. In an effort to…

Attitudes and Perceptions of Students to Open and Distance Learning in Nigeria

ERIC Educational Resources Information Center

Ojo, David Olugbenga; Olakulehin, Felix Kayode

2006-01-01

In the West African Region of Africa, the National Open University of Nigeria (NOUN) is the first full fledged university that operates in an exclusively open and distance learning (ODL) mode of education. NOUN focuses mainly on open and distance teaching and learning system, and delivers its courses materials via print in conjunction with…

An Analysis of the Market Potential for Distance Learning Opportunities in Transportation Professional Development.

ERIC Educational Resources Information Center

Durkop, Brooke R.; Jasek, Debbie; Kuhn, Beverly T.

The feasibility and sustainability of a distance learning program at the Texas Transportation Institute, which is part of the Texas A&M University system, was investigated. A literature review and online survey of current transportation professionals were conducted to examine the market potential for a distance learning program and to identify…

Curriculum Integration in Distance Learning at Primary and Secondary Educational Levels on the Example of eTwinning Projects

ERIC Educational Resources Information Center

Gajek, Elzbieta

2018-01-01

Curriculum integration is one of the concepts which has been discussed for years. Telecollaborative projects, which employ elements of distance learning, provide opportunities for putting the idea into practice. Analysis of eTwinning projects undertaken in Polish schools aims at demonstrating the integrative role of distance learning approaches…

Survey of Distance Learning Provision in Continuing Health Professional Education in Canada

ERIC Educational Resources Information Center

Curran, Vernon; Kirby, Fran; Fleet, Lisa

2003-01-01

In Canada, the trend is towards greater use of distance learning technologies in the provision of continuing professional education in the health professions. Lack of access to professional development is a common deterrent to practice in rural and remote areas. Distance learning technologies have an important role to play in addressing the…

Application of the Classification Tree Model in Predicting Learner Dropout Behaviour in Open and Distance Learning

ERIC Educational Resources Information Center

Yasmin, Dr.

2013-01-01

This paper demonstrates the meaningful application of learning analytics for determining dropout predictors in the context of open and distance learning in a large developing country. The study was conducted at the Directorate of Distance Education at the University of North Bengal, West Bengal, India. This study employed a quantitative research…

Analysis of Risks in a Learning Management System: A Case Study in the Spanish National University of Distance Education (UNED)

ERIC Educational Resources Information Center

Vázquez-Cano, Esteban; Sevillano García, Ma. Luisa

2015-01-01

This article presents a research that examines the university students' risk perception when using a Learning Management System called "aLF" and implemented by the Spanish National University of Distance Education (UNED) for the development of its university distance studies. The development of comprehensive Learning Management Systems…

Television and Learning Systems (Distance Education). Papers on Information Technology No. 245.

ERIC Educational Resources Information Center

Bates, A. W.

Arguing that television has a very important role to play in distance education courses, this paper outlines some of the unique roles that television can play and gives examples of how television can provide learning material not otherwise available to distance learners and help in the development of thinking and learning. Examples of how…

A Flow Theory Perspective on Learner Motivation and Behavior in Distance Education

ERIC Educational Resources Information Center

Liao, Li-Fen

2006-01-01

Motivating learners to continue to study and enjoy learning is one of the critical factors in distance education. Flow theory is a useful framework for studying the individual experience of learning through using computers. In this study, I examine students' emotional and cognitive responses to distance learning systems by constructing two models…

Science Practical Work Instructional Technologies and Open Distance Learning in Science Teacher Training: A Case Study in Zimbabwe

ERIC Educational Resources Information Center

Bhukuvhani, Crispen; Mupa, Mathew; Mhishi, Misheck; Dziva, Daimond

2012-01-01

The practical work component offers unique challenges for university science courses. This is even more pertinent in an Open and Distance Learning (ODL) environment like the Bindura University of Science Education's Virtual and Open Distance Learning (VODL) programme. Effective ODL education should be flexible enough to accommodate science…

Empirical Investigation into Motives for Choosing Web-Based Distance Learning Programs

ERIC Educational Resources Information Center

Alkhattabi, Mona

2016-01-01

Today, in association with rapid social and economic changes, there is an increasing level of demand for distance and online learning programs. This study will focus on identifying the main motivational factors for choosing a web-based distance-learning program. Moreover, it will investigate how these factors relate to age, gender, marital status…

Learning in networks: individual teacher learning versus organizational learning in a regional health-promoting schools network.

PubMed

Flaschberger, Edith; Gugglberger, Lisa; Dietscher, Christina

2013-12-01

To change a school into a health-promoting organization, organizational learning is required. The evaluation of an Austrian regional health-promoting schools network provides qualitative data on the views of the different stakeholders on learning in this network (steering group, network coordinator and representatives of the network schools; n = 26). Through thematic analysis and deep-structure analyses, the following three forms of learning in the network were identified: (A) individual learning through input offered by the network coordination, (B) individual learning between the network schools, i.e. through exchange between the representatives of different schools and (C) learning within the participating schools, i.e. organizational learning. Learning between (B) or within the participating schools (C) seems to be rare in the network; concepts of individual teacher learning are prevalent. Difficulties detected relating to the transfer of information from the network to the member schools included barriers to organizational learning such as the lack of collaboration, coordination and communication in the network schools, which might be effects of the school system in which the observed network is located. To ensure connectivity of the information offered by the network, more emphasis should be put on linking health promotion to school development and the core processes of schools.

Going the Distance: A National Distance Learning Initiative.

ERIC Educational Resources Information Center

Dubois, Jaques R.

1996-01-01

Going the Distance is a Public Broadcasting Service project through which over 130 colleges and universities are offering telecourses for adults seeking associate degrees. It is the beginning of a global learning community. (SK)

Student outcomes of distance learning in nursing education: an integrative review.

PubMed

Patterson, Barbara J; Krouse, Anne M; Roy, Linda

2012-09-01

Distance learning offers a distinctive environment to educate nursing students. While there is a significant body of evidence in the literature related to course, program, and faculty outcomes of distance education, little attention has been given by researchers to evaluate student outcomes, with the exception of student satisfaction. There is a need to evaluate and translate findings related to student outcomes in distance learning into educational practice. Integrative reviews offer one strategy to contribute to evidence-based teaching practice initiatives. A search of available published qualitative and quantitative research on student outcomes of distance learning from 1999 to 2009 was conducted using a number of databases. Astin's Input-Environment-Output conceptual model provided a framework for this review. Thirty-three studies met the inclusion criteria. Bothcognitive and affective student outcomes emerged. The cognitive outcomes were student learning, learning process, and technology proficiency. Affective outcomes included personal and professional growth, satisfaction, and connectedness. Implications, recommendations, and future research are discussed.

Building a Model for Distance Collaboration in the Computer-Assisted Business Communication Classroom.

ERIC Educational Resources Information Center

Lopez, Elizabeth Sanders; Nagelhout, Edwin

1995-01-01

Outlines a model for distance collaboration between business writing classrooms using network technology. Discusses ways to teach national and international audience awareness, problem solving, and the contextual nature of cases. Discusses goals for distance collaboration, sample assignments, and the pros and cons of network technologies. (SR)

Hypothetical Network Adequacy Schemes For Children Fail To Ensure Patients' Access To In-Network Children's Hospital.

PubMed

Colvin, Jeffrey D; Hall, Matt; Thurm, Cary; Bettenhausen, Jessica L; Gottlieb, Laura; Shah, Samir S; Fieldston, Evan S; Goldin, Adam B; Melzer, Sanford M; Conway, Patrick H; Chung, Paul J

2018-06-01

Insurers are increasingly adopting narrow network strategies. Little is known about how these strategies may affect children's access to needed specialty care. We examined the percentage of pediatric specialty hospitalizations that would be beyond existing Medicare Advantage network adequacy distance requirements for adult hospital care and, as a secondary analysis, a pediatric adaptation of the Medicare Advantage requirements. We examined 748,920 hospitalizations at eighty-one children's hospitals that submitted data for the period October 2014-September 2015. Nearly half of specialty hospitalizations were outside the Medicare Advantage distance requirements. Under the pediatric adaptation, there was great variability among the hospitals, with the percent of hospitalizations beyond the distance requirements ranging from less than 1 percent to 35 percent. Instead of, or in addition to, time and distance standards, policy makers may need to consider more nuanced network definitions, including functional capabilities of the pediatric care network or clear exception policies for essential specialty care services.

Structural covariance networks are coupled to expression of genes enriched in supragranular layers of the human cortex.

PubMed

Romero-Garcia, Rafael; Whitaker, Kirstie J; Váša, František; Seidlitz, Jakob; Shinn, Maxwell; Fonagy, Peter; Dolan, Raymond J; Jones, Peter B; Goodyer, Ian M; Bullmore, Edward T; Vértes, Petra E

2018-05-01

Complex network topology is characteristic of many biological systems, including anatomical and functional brain networks (connectomes). Here, we first constructed a structural covariance network from MRI measures of cortical thickness on 296 healthy volunteers, aged 14-24 years. Next, we designed a new algorithm for matching sample locations from the Allen Brain Atlas to the nodes of the SCN. Subsequently we used this to define, transcriptomic brain networks by estimating gene co-expression between pairs of cortical regions. Finally, we explored the hypothesis that transcriptional networks and structural MRI connectomes are coupled. A transcriptional brain network (TBN) and a structural covariance network (SCN) were correlated across connection weights and showed qualitatively similar complex topological properties: assortativity, small-worldness, modularity, and a rich-club. In both networks, the weight of an edge was inversely related to the anatomical (Euclidean) distance between regions. There were differences between networks in degree and distance distributions: the transcriptional network had a less fat-tailed degree distribution and a less positively skewed distance distribution than the SCN. However, cortical areas connected to each other within modules of the SCN had significantly higher levels of whole genome co-expression than expected by chance. Nodes connected in the SCN had especially high levels of expression and co-expression of a human supragranular enriched (HSE) gene set that has been specifically located to supragranular layers of human cerebral cortex and is known to be important for large-scale, long-distance cortico-cortical connectivity. This coupling of brain transcriptome and connectome topologies was largely but not entirely accounted for by the common constraint of physical distance on both networks. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

eHealth for Remote Regions: Findings from Central Asia Health Systems Strengthening Project.

PubMed

Sajwani, Afroz; Qureshi, Kiran; Shaikh, Tehniat; Sayani, Saleem

2015-01-01

Isolated communities in remote regions of Afghanistan, Kyrgyz Republic, Pakistan and Tajikistan lack access to high-quality, low-cost health care services, forcing them to travel to distant parts of the country, bearing an unnecessary financial burden. The eHealth Programme under Central Asia Health Systems Strengthening (CAHSS) Project, a joint initiative between the Aga Khan Foundation, Canada and the Government of Canada, was initiated in 2013 with the aim to utilize Information and Communication Technologies to link health care institutions and providers with rural communities to provide comprehensive and coordinated care, helping minimize the barriers of distance and time. Under the CAHSS Project, access to low-cost, quality health care is provided through a regional hub and spoke teleconsultation network of government and non-government health facilities. In addition, capacity building initiatives are offered to health professionals. By 2017, the network is expected to connect seven Tier 1 tertiary care facilities with 14 Tier 2 secondary care facilities for teleconsultation and eLearning. From April 2013 to September 2014, 6140 teleconsultations have been provided across the project sites. Additionally, 52 new eLearning sessions have been developed and 2020 staff members have benefitted from eLearning sessions. Ethics and patient rights are respected during project implementation.

Tree-average distances on certain phylogenetic networks have their weights uniquely determined.

PubMed

Willson, Stephen J

2012-01-01

A phylogenetic network N has vertices corresponding to species and arcs corresponding to direct genetic inheritance from the species at the tail to the species at the head. Measurements of DNA are often made on species in the leaf set, and one seeks to infer properties of the network, possibly including the graph itself. In the case of phylogenetic trees, distances between extant species are frequently used to infer the phylogenetic trees by methods such as neighbor-joining. This paper proposes a tree-average distance for networks more general than trees. The notion requires a weight on each arc measuring the genetic change along the arc. For each displayed tree the distance between two leaves is the sum of the weights along the path joining them. At a hybrid vertex, each character is inherited from one of its parents. We will assume that for each hybrid there is a probability that the inheritance of a character is from a specified parent. Assume that the inheritance events at different hybrids are independent. Then for each displayed tree there will be a probability that the inheritance of a given character follows the tree; this probability may be interpreted as the probability of the tree. The tree-average distance between the leaves is defined to be the expected value of their distance in the displayed trees. For a class of rooted networks that includes rooted trees, it is shown that the weights and the probabilities at each hybrid vertex can be calculated given the network and the tree-average distances between the leaves. Hence these weights and probabilities are uniquely determined. The hypotheses on the networks include that hybrid vertices have indegree exactly 2 and that vertices that are not leaves have a tree-child.

A New Distance Metric for Unsupervised Learning of Categorical Data.

PubMed

Jia, Hong; Cheung, Yiu-Ming; Liu, Jiming

2016-05-01

Distance metric is the basis of many learning algorithms, and its effectiveness usually has a significant influence on the learning results. In general, measuring distance for numerical data is a tractable task, but it could be a nontrivial problem for categorical data sets. This paper, therefore, presents a new distance metric for categorical data based on the characteristics of categorical values. In particular, the distance between two values from one attribute measured by this metric is determined by both the frequency probabilities of these two values and the values of other attributes that have high interdependence with the calculated one. Dynamic attribute weight is further designed to adjust the contribution of each attribute-distance to the distance between the whole data objects. Promising experimental results on different real data sets have shown the effectiveness of the proposed distance metric.

US long distance fiber optic networks: Technology, evolution and advanced concepts. Volume 2: Fiber optic technology and long distance networks

NASA Astrophysics Data System (ADS)

1986-10-01

The study projects until 2000 the evolution of long distance fiber optic networks in the U.S. Volume 1 is the Executive Summary. Volume 2 focuses on fiber optic components and systems that are directly related to the operation of long-haul networks. Optimistic, pessimistic and most likely scenarios of technology development are presented. The activities of national and regional companies implementing fiber long haul networks are also highlighted, along with an analysis of the market and regulatory forces affecting network evolution. Volume 3 presents advanced fiber optic network concept definitions. Inter-LATA traffic is quantified and forms the basis for the construction of 11-, 15-, 17-, and 23-node networks. Using the technology projections from Volume 2, a financial model identifies cost drivers and determines circuit mile costs between any two LATAs. A comparison of fiber optics with alternative transmission concludes the report.

US long distance fiber optic networks: Technology, evolution and advanced concepts. Volume 2: Fiber optic technology and long distance networks

NASA Technical Reports Server (NTRS)

1986-01-01

The study projects until 2000 the evolution of long distance fiber optic networks in the U.S. Volume 1 is the Executive Summary. Volume 2 focuses on fiber optic components and systems that are directly related to the operation of long-haul networks. Optimistic, pessimistic and most likely scenarios of technology development are presented. The activities of national and regional companies implementing fiber long haul networks are also highlighted, along with an analysis of the market and regulatory forces affecting network evolution. Volume 3 presents advanced fiber optic network concept definitions. Inter-LATA traffic is quantified and forms the basis for the construction of 11-, 15-, 17-, and 23-node networks. Using the technology projections from Volume 2, a financial model identifies cost drivers and determines circuit mile costs between any two LATAs. A comparison of fiber optics with alternative transmission concludes the report.

Local CD-ROM in interaction with HTML documents over the Internet.

PubMed

Mattheos, N; Nattestad, A; Attström, R

2000-08-01

The internet and computer assisted learning have enhanced the possibilities of providing quality distance learning in dentistry. The use of multimedia material is an essential part of such distance learning courses. However the Internet technology available has limitations regarding transmission of large multimedia files. Therefore especially when addressing undergraduate students or geographically isolated professionals, large download times make distance learning unattractive. This problem was technically solved in a distance learning course for undergraduate students from all over Europe. The present communication describes a method to bypass the problem of transmitting large multimedia files by the use of a specially designed CD-ROM. This CD-ROM was run locally on the students' PC interacting with HTML documents sent over the Internet.

Distance Learning as a Tool for Poverty Reduction and Economic Development: A Focus on China and Mexico

NASA Astrophysics Data System (ADS)

Larson, Richard C.; Murray, M. Elizabeth

2008-04-01

This paper uses case studies to focus on distance learning in developing countries as an enabler for economic development and poverty reduction. To provide perspective, we first review the history of telecottages, local technology-equipped facilities to foster community-based learning, which have evolved into "telecenters" or "Community Learning Centers" (CLCs). Second, we describe extensive site visits to CLCs in impoverished portions of China and Mexico, the centers operated by premier universities in each respective country. These CLCs constitute the core of new emerging systems of distance education, and their newness poses challenges and opportunities, which are discussed. Finally, we offer 12 points to develop further the concept and reality of distance learning in support of economic development.

E-Learning and North-South collaboration: the experience of two public health schools in France and Benin.

PubMed

Edouard, Guévart; Dominique, Billot; Moussiliou, Paraïso Noël; Francis, Guillemin; Khaled, Bessaoud; Serge, Briançon

2009-10-14

Distance learning (e-learning) can facilitate access to training. Yet few public health E-learning experiments have been reported; institutes in developing countries experience difficulties in establishing on-line curricula, while developed countries struggle with adapting existing curricula to realities on the ground. In 2005, two schools of public health, one in France and one in Benin, began collaborating through contact sessions organised for Nancy University distance-learning students. This experience gave rise to a partnership aimed at developing training materials for e-Learning for African students. The distance-learning public health course at Nancy teaches public health professionals through a module entitled "Health and Development." The module is specifically tailored for professionals from developing countries. To promote student-teacher exchanges, clarify content and supervise dissertations, contact sessions are organized in centres proximate and accessible to African students. The Benin Institute's main feature is residential team learning; distance-learning courses are currently being prepared. The two collaborating institutions have developed a joint distance-learning module geared toward developing countries. The collaboration provides for the development, diffusion, and joint delivery of teaching modules featuring issues that are familiar to African staff, gives the French Institute credibility in assessing research work produced, and enables modules on specific African issues and approaches to be put online. While E-learning is a viable educational option for public health professionals, periodic contact can be advantageous. Our analysis showed that the benefit of the collaboration between the two institutions is mutual; the French Institute extends its geographical, cultural and contextual reach and expands its pool of teaching staff. The Benin Institute benefits from the technical partnership and expertise, which allow it to offer distance learning for Africa-specific contexts and applications.

Lifelong Learning & Distance Higher Education. Perspectives on Distance Education

ERIC Educational Resources Information Center

McIntosh, Christopher, Ed.

2005-01-01

Reflecting a common objective of ensuring quality Education for All, this book is a joint initiative of UNESCO and COL and jointly published. Lifelong Learning in Distance Higher Education brings together a diverse group of experts from many countries. The book provides a clear picture of the challenges, problems and potential of distance higher…

Use of Distance Education by Christian Religion to Train, Edify and Educate Adherents

ERIC Educational Resources Information Center

Satyanarayana, P.; DK Meduri, Emmanuel

2013-01-01

Distance Education has been growing fast, in a marvelously diverse fashion. The efficiency, effectiveness, validity and utility of distance teaching-learning are on increase. All communities and religious groups are making use of distance learning methodology to upgrade their knowledge, skills and attitudes. Christian educational institutions in…

A Basic Hybrid Library Support Model to Distance Learners in Sudan

ERIC Educational Resources Information Center

Abdelrahman, Omer Hassan

2012-01-01

Distance learning has flourished in Sudan during the last two decades; more and more higher education institutions offer distance learning programmes to off-campus students. Like on-campus students, distance learners should have access to appropriate library and information support services. They also have specific needs for library and…

The Knowledge Base as an Extension of Distance Learning Reference Service

ERIC Educational Resources Information Center

Casey, Anne Marie

2012-01-01

This study explores knowledge bases as extension of reference services for distance learners. Through a survey and follow-up interviews with distance learning librarians, this paper discusses their interest in creating and maintaining a knowledge base as a resource for reference services to distance learners. It also investigates their perceptions…

Implications of the University of South Africa's (UNISA) Shift to Open Distance e-Learning on Teacher Education

ERIC Educational Resources Information Center

Ngubane-Mokiwa, Sindile A.

2017-01-01

This conceptual and exploratory article seeks to explore the implications of the University of South Africa's (Unisa) shift from open distance learning (ODL) to open distance e-learning (ODeL) on Teacher Education. In addition, the article problematizes the shift as a policy imperative. Unisa's mandate to provide teacher education opportunities to…

An Evolution of Distance Learning Issues: From Exporting to Enhancing the Classroom Experience

ERIC Educational Resources Information Center

Johnstone, Sally M.

2004-01-01

There are many different formats being used for distance learning and each has implications for institutional and public policies. With almost 90% of U.S. public colleges and universities offering distance learning courses, it is important for all members of the academy to be aware of these implications as they consider their own involvement in…

Increasing Access to Higher Education through Open and Distance Learning: Empirical Findings from Mzuzu University, Malawi

ERIC Educational Resources Information Center

Chawinga, Winner Dominic; Zozie, Paxton Andrew

2016-01-01

Slowly but surely, open and distance learning (ODL) programmes are being regarded as one of the most practical ways that universities across the world are increasingly adopting in order to increase access to university education. Likewise, Mzuzu University (MZUNI) set up the Centre for Open and Distance Learning (CODL) to oversee the running of…

The Place of Multiple Intelligence in Achieving the Objectives and Goals of Open and Distance Learning Institutions: A Critical Analysis

ERIC Educational Resources Information Center

Ojo, Olugbenga David; Olakulehin, Felix Kayode

2006-01-01

This paper examined the nature of open and distance learning institutions as organizations where synergy of efforts of all personnel is required in order to achieve the aims and objectives of the institution. It explored the huge infrastructural and personnel requirements of distance learning institutions, especially at inception, and the…

Building Capacity for Open and Distance Learning (ODL) in West Africa Sub-Region: The Pivotal Role of RETRIDAL

ERIC Educational Resources Information Center

Amini, Clifford; Oluyide, Oluwaseun

2016-01-01

The paper posits the Regional Training and Research Institute for Distance and Open Learning (RETRIDAL) as an institution established for the purpose of enhancing Open and Distance Learning in the West African sub-region. The institute has pursued this mandate with an unparalleled vigour since its establishment in 2003--a partnership of the…

Quality Assurance in Open and Distance Learning. Knowledge Series. A Topical, Start-Up Guide to Distance Education Practice and Delivery

ERIC Educational Resources Information Center

Kirkpatrick, Denise

2005-01-01

Assuring the quality of education provision is a fundamental aspect of gaining and maintaining credibility for programmes, institutions and national systems of higher education worldwide. Despite a long and generally successful track record, open and distance learning (ODL) is still required to prove that the quality of student learning is at…

Factors Affecting Student Success in Distance Learning Courses at a Local California Community College: Joint Governance Perspectives

ERIC Educational Resources Information Center

Gonzalez, Luis A.

2012-01-01

The purpose of this study was to explore the perspectives of staff and faculty regarding factors affecting student success in distance learning at a California community college (CCC). Participants were members of the leadership group known as the distance learning committee. Data were collected through in-depth interviews using open-ended…

A boosting framework for visuality-preserving distance metric learning and its application to medical image retrieval.

PubMed

Yang, Liu; Jin, Rong; Mummert, Lily; Sukthankar, Rahul; Goode, Adam; Zheng, Bin; Hoi, Steven C H; Satyanarayanan, Mahadev

2010-01-01

Similarity measurement is a critical component in content-based image retrieval systems, and learning a good distance metric can significantly improve retrieval performance. However, despite extensive study, there are several major shortcomings with the existing approaches for distance metric learning that can significantly affect their application to medical image retrieval. In particular, "similarity" can mean very different things in image retrieval: resemblance in visual appearance (e.g., two images that look like one another) or similarity in semantic annotation (e.g., two images of tumors that look quite different yet are both malignant). Current approaches for distance metric learning typically address only one goal without consideration of the other. This is problematic for medical image retrieval where the goal is to assist doctors in decision making. In these applications, given a query image, the goal is to retrieve similar images from a reference library whose semantic annotations could provide the medical professional with greater insight into the possible interpretations of the query image. If the system were to retrieve images that did not look like the query, then users would be less likely to trust the system; on the other hand, retrieving images that appear superficially similar to the query but are semantically unrelated is undesirable because that could lead users toward an incorrect diagnosis. Hence, learning a distance metric that preserves both visual resemblance and semantic similarity is important. We emphasize that, although our study is focused on medical image retrieval, the problem addressed in this work is critical to many image retrieval systems. We present a boosting framework for distance metric learning that aims to preserve both visual and semantic similarities. The boosting framework first learns a binary representation using side information, in the form of labeled pairs, and then computes the distance as a weighted Hamming distance using the learned binary representation. A boosting algorithm is presented to efficiently learn the distance function. We evaluate the proposed algorithm on a mammographic image reference library with an Interactive Search-Assisted Decision Support (ISADS) system and on the medical image data set from ImageCLEF. Our results show that the boosting framework compares favorably to state-of-the-art approaches for distance metric learning in retrieval accuracy, with much lower computational cost. Additional evaluation with the COREL collection shows that our algorithm works well for regular image data sets.

The gravitational law of social interaction

NASA Astrophysics Data System (ADS)

Levy, Moshe; Goldenberg, Jacob

2014-01-01

While a great deal is known about the topology of social networks, there is much less agreement about the geographical structure of these networks. The fundamental question in this context is: how does the probability of a social link between two individuals depend on the physical distance between them? While it is clear that the probability decreases with the distance, various studies have found different functional forms for this dependence. The exact form of the distance dependence has crucial implications for network searchability and dynamics: Kleinberg (2000) [15] shows that the small-world property holds if the probability of a social link is a power-law function of the distance with power -2, but not with any other power. We investigate the distance dependence of link probability empirically by analyzing four very different sets of data: Facebook links, data from the electronic version of the Small-World experiment, email messages, and data from detailed personal interviews. All four datasets reveal the same empirical regularity: the probability of a social link is proportional to the inverse of the square of the distance between the two individuals, analogously to the distance dependence of the gravitational force. Thus, it seems that social networks spontaneously converge to the exact unique distance dependence that ensures the Small-World property.

Expanding Learning Opportunities for High School Students with Distance Learning

ERIC Educational Resources Information Center

Beese, Jane

2014-01-01

The purpose of the Synchronous Interactive Video Conference Distance Learning pilot program was to use emerging technologies to expand learning opportunities for students at an urban public high school. Through grant funding, students were able to enroll in Advanced Placement and foreign language courses through an online learning provider. Using…

New Learning Design in Distance Education: The Impact on Student Perception and Motivation

ERIC Educational Resources Information Center

Martens, Rob; Bastiaens, Theo; Kirschner, Paul A.

2007-01-01

Many forms of e-learning (such as online courses with authentic tasks and computer-supported collaborative learning) have become important in distance education. Very often, such e-learning courses or tasks are set up following constructivist design principles. Often, this leads to learning environments with authentic problems in ill-structured…

Increased Technology Provision and Learning: Giving More for Nothing?

ERIC Educational Resources Information Center

Quillerou, Emmanuelle

2011-01-01

The development of new communication technologies has led to a push for greater technology use for teaching and learning. This is most true for distance learning education, which relies heavily on new technologies. Distance learning students, however, seem to have very limited time available for studying and learning because of work and/or family…

Determinants of Student Satisfaction in Online Tutorial: A Study of A Distance Education Institution

ERIC Educational Resources Information Center

Harsasi, Meirani; Sutawijaya, Adrian

2018-01-01

Education system nowadays tends to utilize online learning, including in higher education. Online learning system becomes a major requirement in implementing learning process, including in Indonesia. Universitas Terbuka has implemented online learning system known as online tutorials to support the distance learning system. One interesting issue…

Enhancing Online Teaching and Learning from Students' Perspectives

ERIC Educational Resources Information Center

Edwards, Francisca

2014-01-01

The vast growth of technology has brought about new ways of learning. Distance learning has evolved over the years and, due to the growth of the Internet, has presented itself to be a growing phenomenon. Distance learning changed the way educational institutes and organizations train, learn, and do research. Past studies have shown academia's…

Adventure Learning: Transformative Hybrid Online Education

ERIC Educational Resources Information Center

Doering, Aaron

2006-01-01

Adventure learning (AL) is a hybrid distance education approach that provides students with opportunities to explore real-world issues through authentic learning experiences within collaborative learning environments. This article defines this online distance education approach, outlines an AL framework, and showcases an AL archetype. In AL…

In a year, memory will benefit from learning, tomorrow it won't: distance and construal level effects on the basis of metamemory judgments.

PubMed

Halamish, Vered; Nussinson, Ravit; Ben-Ari, Liat

2013-09-01

Metamemory judgments may rely on 2 bases of information: subjective experience and abstract theories about memory. On the basis of construal level theory, we predicted that psychological distance and construal level (i.e., concrete vs. abstract thinking) would have a qualitative impact on the relative reliance on these 2 bases: When considering learning from proximity or under a low-construal mindset, learners would rely more heavily on their experience, whereas when considering learning from a distance or under a high-construal mindset, they would rely more heavily on their abstract theories. Consistent with this prediction, results of 2 experiments revealed that temporal distance (Experiment 1) and construal level (Experiment 2) affected the stability bias--the failure to predict the benefits of learning. When considering learning from proximity or using a low-construal mindset, participants relied less heavily on their theory regarding the benefits of learning and were therefore insensitive to future learning. However, when considering learning from temporal distance or using a high-construal mindset, participants relied more heavily on their theory and were therefore better able to predict the benefits of future learning, thus overcoming the stability bias. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Distance Learning Can Be as Effective as Traditional Learning for Medical Students in the Initial Assessment of Trauma Patients.

PubMed

Farahmand, Shervin; Jalili, Ebrahim; Arbab, Mona; Sedaghat, Mojtaba; Shirazi, Mandana; Keshmiri, Fatemeh; Azizpour, Arsalan; Valadkhani, Somayeh; Bagheri-Hariri, Shahram

2016-09-01

Distance learning is expanding and replacing the traditional academic medical settings. Managing trauma patients seems to be a prerequisite skill for medical students. This study has been done to evaluate the efficiency of distance learning on performing the initial assessment and management in trauma patients, compared with the traditional learning among senior medical students. One hundred and twenty senior medical students enrolled in this single-blind quasi-experimental study and were equally divided into the experimental (distance learning) and control group (traditional learning). All participants did a written MCQ before the study. The control group attended a workshop with a 50-minute lecture on initial management of trauma patients and a case simulation scenario followed by a hands-on session. On the other hand, the experimental group was given a DVD with a similar 50-minute lecture and a case simulation scenario, and they also attended a hands-on session to practice the skills. Both groups were evaluated by a trauma station in an objective structured clinical examination (OSCE) after a month. The performance in the experimental group was statistically better (P=0.001) in OSCE. Distance learning seems to be an appropriate adjunct to traditional learning.

From language identification to language distance

NASA Astrophysics Data System (ADS)

Gamallo, Pablo; Pichel, José Ramom; Alegria, Iñaki

2017-10-01

In this paper, we define two quantitative distances to measure how far apart two languages are. The distance measure that we have identified as more accurate is based on the perplexity of n-gram models extracted from text corpora. An experiment to compare forty-four European languages has been performed. For this purpose, we computed the distances for all the possible language pairs and built a network whose nodes are languages and edges are distances. The network we have built on the basis of linguistic distances represents the current map of similarities and divergences among the main languages of Europe.

Self-Learning through Programmed Learning in Distance Mode.

ERIC Educational Resources Information Center

Rao, D. Prakasa; Reddy, B. Sudhakar

2002-01-01

Presents the characteristics and development of self-learning material (SLM) in distance education. Discusses teaching with programmed learning; structure of SLM; and how SLM helps in self-study. Discusses the advantages of print materials as accompanying programmed instruction, because they are portable, well-structured, compact, and easily…

Cooperative Learning in Distance Learning: A Mixed Methods Study

ERIC Educational Resources Information Center

Kupczynski, Lori; Mundy, Marie Anne; Goswami, Jaya; Meling, Vanessa

2012-01-01

Distance learning has facilitated innovative means to include Cooperative Learning (CL) in virtual settings. This study, conducted at a Hispanic-Serving Institution, compared the effectiveness of online CL strategies in discussion forums with traditional online forums. Quantitative and qualitative data were collected from 56 graduate student…

A Question of Questions.

ERIC Educational Resources Information Center

Fenwick, John; McMillan, Rod

In a conventional teaching situation, a lecturer may use a wide range of questioning techniques aimed at helping students to become active learners. In distance learning, students are often isolated and have limited opportunities for interaction in a social learning environment. Hence, learning strategies in distance learning need to be structured…

Event Recognition Based on Deep Learning in Chinese Texts

PubMed Central

Zhang, Yajun; Liu, Zongtian; Zhou, Wen

2016-01-01

Event recognition is the most fundamental and critical task in event-based natural language processing systems. Existing event recognition methods based on rules and shallow neural networks have certain limitations. For example, extracting features using methods based on rules is difficult; methods based on shallow neural networks converge too quickly to a local minimum, resulting in low recognition precision. To address these problems, we propose the Chinese emergency event recognition model based on deep learning (CEERM). Firstly, we use a word segmentation system to segment sentences. According to event elements labeled in the CEC 2.0 corpus, we classify words into five categories: trigger words, participants, objects, time and location. Each word is vectorized according to the following six feature layers: part of speech, dependency grammar, length, location, distance between trigger word and core word and trigger word frequency. We obtain deep semantic features of words by training a feature vector set using a deep belief network (DBN), then analyze those features in order to identify trigger words by means of a back propagation neural network. Extensive testing shows that the CEERM achieves excellent recognition performance, with a maximum F-measure value of 85.17%. Moreover, we propose the dynamic-supervised DBN, which adds supervised fine-tuning to a restricted Boltzmann machine layer by monitoring its training performance. Test analysis reveals that the new DBN improves recognition performance and effectively controls the training time. Although the F-measure increases to 88.11%, the training time increases by only 25.35%. PMID:27501231

A Support Vector Learning-Based Particle Filter Scheme for Target Localization in Communication-Constrained Underwater Acoustic Sensor Networks

PubMed Central

Zhang, Chenglin; Yan, Lei; Han, Song; Guan, Xinping

2017-01-01

Target localization, which aims to estimate the location of an unknown target, is one of the key issues in applications of underwater acoustic sensor networks (UASNs). However, the constrained property of an underwater environment, such as restricted communication capacity of sensor nodes and sensing noises, makes target localization a challenging problem. This paper relies on fractional sensor nodes to formulate a support vector learning-based particle filter algorithm for the localization problem in communication-constrained underwater acoustic sensor networks. A node-selection strategy is exploited to pick fractional sensor nodes with short-distance pattern to participate in the sensing process at each time frame. Subsequently, we propose a least-square support vector regression (LSSVR)-based observation function, through which an iterative regression strategy is used to deal with the distorted data caused by sensing noises, to improve the observation accuracy. At the same time, we integrate the observation to formulate the likelihood function, which effectively update the weights of particles. Thus, the particle effectiveness is enhanced to avoid “particle degeneracy” problem and improve localization accuracy. In order to validate the performance of the proposed localization algorithm, two different noise scenarios are investigated. The simulation results show that the proposed localization algorithm can efficiently improve the localization accuracy. In addition, the node-selection strategy can effectively select the subset of sensor nodes to improve the communication efficiency of the sensor network. PMID:29267252

A Support Vector Learning-Based Particle Filter Scheme for Target Localization in Communication-Constrained Underwater Acoustic Sensor Networks.

PubMed

Li, Xinbin; Zhang, Chenglin; Yan, Lei; Han, Song; Guan, Xinping

2017-12-21

Target localization, which aims to estimate the location of an unknown target, is one of the key issues in applications of underwater acoustic sensor networks (UASNs). However, the constrained property of an underwater environment, such as restricted communication capacity of sensor nodes and sensing noises, makes target localization a challenging problem. This paper relies on fractional sensor nodes to formulate a support vector learning-based particle filter algorithm for the localization problem in communication-constrained underwater acoustic sensor networks. A node-selection strategy is exploited to pick fractional sensor nodes with short-distance pattern to participate in the sensing process at each time frame. Subsequently, we propose a least-square support vector regression (LSSVR)-based observation function, through which an iterative regression strategy is used to deal with the distorted data caused by sensing noises, to improve the observation accuracy. At the same time, we integrate the observation to formulate the likelihood function, which effectively update the weights of particles. Thus, the particle effectiveness is enhanced to avoid "particle degeneracy" problem and improve localization accuracy. In order to validate the performance of the proposed localization algorithm, two different noise scenarios are investigated. The simulation results show that the proposed localization algorithm can efficiently improve the localization accuracy. In addition, the node-selection strategy can effectively select the subset of sensor nodes to improve the communication efficiency of the sensor network.

Event Recognition Based on Deep Learning in Chinese Texts.

PubMed

Zhang, Yajun; Liu, Zongtian; Zhou, Wen

2016-01-01

Event recognition is the most fundamental and critical task in event-based natural language processing systems. Existing event recognition methods based on rules and shallow neural networks have certain limitations. For example, extracting features using methods based on rules is difficult; methods based on shallow neural networks converge too quickly to a local minimum, resulting in low recognition precision. To address these problems, we propose the Chinese emergency event recognition model based on deep learning (CEERM). Firstly, we use a word segmentation system to segment sentences. According to event elements labeled in the CEC 2.0 corpus, we classify words into five categories: trigger words, participants, objects, time and location. Each word is vectorized according to the following six feature layers: part of speech, dependency grammar, length, location, distance between trigger word and core word and trigger word frequency. We obtain deep semantic features of words by training a feature vector set using a deep belief network (DBN), then analyze those features in order to identify trigger words by means of a back propagation neural network. Extensive testing shows that the CEERM achieves excellent recognition performance, with a maximum F-measure value of 85.17%. Moreover, we propose the dynamic-supervised DBN, which adds supervised fine-tuning to a restricted Boltzmann machine layer by monitoring its training performance. Test analysis reveals that the new DBN improves recognition performance and effectively controls the training time. Although the F-measure increases to 88.11%, the training time increases by only 25.35%.

National Knowledge Commission

NASA Astrophysics Data System (ADS)

Pitroda, Sam

2007-04-01

India's National Knowledge Commission (NKC) established by the prime minister is focused on building institutions and infrastructure in Education, Science and Technology, Innovation etc. to meet the challenges of the knowledge economy in the 21st century and increase India's competitive advantage in the global market. India today stands poised to reap the benefits of a rapidly growing economy and a major demographic advantage, with 550 million young people below the age of 25 years, the largest in the world. The NKC is focused on five critical areas of knowledge related to access, concepts, creation, applications and services. This includes a variety of subject areas such as language, translations, libraries, networks, portals, affirmative action, distance learning, intellectual property, Entrepreneurship, application in Agriculture, health, small and medium scale industries, e-governance etc. One of the keys to this effort is to build a national broadband gigabit of networks of 500 nodes to connect universities, Libraries, Laboratories, Hospitals, Agriculture institutions etc. to share resources and collaborate on multidisciplinary activities. This presentation will introduce the NKC, discuss methodology, subject areas, specific recommendation and outline a plan to build knowledge networks and specifics on network architecture, applications, and utilities.

Combining Feminist Pedagogy and Transactional Distance to Create Gender-Sensitive Technology-Enhanced Learning

ERIC Educational Resources Information Center

Herman, Clem; Kirkup, Gill

2017-01-01

In this paper, we argue for a new synthesis of two pedagogic theories: feminist pedagogy and transactional distance, which explain why and how distance education has been such a positive system for women in a national distance learning university. We illustrate this with examples of positive action initiatives for women. The concept of…

Going the Distance: Are There Common Factors in High Performance Distance Learning? Research Report.

ERIC Educational Resources Information Center

Hawksley, Rosemary; Owen, Jane

Common factors among high-performing distance learning (DL) programs were examined through case studies at 9 further education colleges and 2 nonsector organizations in the United Kingdom and a backup survey of a sample of 50 distance learners at 5 of the colleges. The study methodology incorporated numerous principles of process benchmarking. The…

Assessment of the Effectiveness of Internet-Based Distance Learning through the VClass e-Education Platform

ERIC Educational Resources Information Center

Pukkaew, Chadchadaporn

2013-01-01

This study assesses the effectiveness of internet-based distance learning (IBDL) through the VClass live e-education platform. The research examines (1) the effectiveness of IBDL for regular and distance students and (2) the distance students' experience of VClass in the IBDL course entitled Computer Programming 1. The study employed the common…

Distance Teaching of Environmental Engineering Courses at the Open University.

ERIC Educational Resources Information Center

Porteous, Andrew; Nesaratnam, Suresh T.; Anderson, Judith

1997-01-01

Describes two integrated distance learning environmental engineering degree courses offered by the environmental engineering group of the Open University in Great Britain. Discusses admission requirements for courses, advantages offered by distance learning, professional accreditation, site visits, and tutors. (AIM)

Embracing Change: Adapting and Evolving Your Distance Learning Library Services to Meet the New ACRL Distance Learning Library Services Standards

ERIC Educational Resources Information Center

Marcum, Brad

2016-01-01

This article examines the update and revision of the current Association of College and Research Libraries (ACRL) Distance Learning Standards that has been proposed and submitted to the ACRL Standards Committee. An in-depth analysis of the update is included, along with some comparisons between the old and new. Practical advice detailing…

Open and Distance Learning: Case Studies from Industry and Education. Open and Distance Learning Series.

ERIC Educational Resources Information Center

Brown, Stephen C., Ed.

This book contains 14 case studies, written by those involved in the teaching and training initiatives, that illustrate the use of open and distance learning strategies. The case studies, drawn from many parts of the world (but mostly British based), feature efforts in large and small companies in a variety of industries. The first part of the…

The Relationship between Academic Integration and Student Success in Distance Learning in the Kentucky Community and Technical College System

ERIC Educational Resources Information Center

Johnson, Robert White

2009-01-01

This dissertation is a study of factors that contribute to dropout from distance learning classes in the Kentucky Community and Technical College System (KCTCS). It is divided into five chapters. Chapter One gives a history of distance learning through in KCTCS. It includes the background of the study, statement of the problem, purpose of the…

Exploring Distance Learning Experiences of In-Service Music Teachers from Puerto Rico in a Master's Program

ERIC Educational Resources Information Center

Vega-Martinez, Juan Carlos

2013-01-01

The purpose of this study was to explore the experiences of in-service music teachers who chose to pursue a master's degree in music education through distance learning. In this study, I examined the motivations of in-service music teachers for choosing to pursue a master's degree in music education through distance learning; the benefits teachers…

Increasing health worker capacity through distance learning: a comprehensive review of programmes in Tanzania.

PubMed

Nartker, Anya J; Stevens, Liz; Shumays, Alyson; Kalowela, Martin; Kisimbo, Daniel; Potter, Katy

2010-12-31

Tanzania, like many developing countries, faces a crisis in human resources for health. The government has looked for ways to increase the number and skills of health workers, including using distance learning in their training. In 2008, the authors reviewed and assessed the country's current distance learning programmes for health care workers, as well as those in countries with similar human resource challenges, to determine the feasibility of distance learning to meet the need of an increased and more skilled health workforce. Data were collected from 25 distance learning programmes at health training institutions, universities, and non-governmental organizations throughout the country from May to August 2008. Methods included internet research; desk review; telephone, email and mail-in surveys; on-site observations; interviews with programme managers, instructors, students, information technology specialists, preceptors, health care workers and Ministry of Health and Social Welfare representatives; and a focus group with national HIV/AIDS care and treatment organizations. Challenges include lack of guidelines for administrators, instructors and preceptors of distance learning programmes regarding roles and responsibilities; absence of competencies for clinical components of curricula; and technological constraints such as lack of access to computers and to the internet. Insufficient funding resulted in personnel shortages, lack of appropriate training for personnel, and lack of materials for students.Nonetheless, current and prospective students expressed overwhelming enthusiasm for scale-up of distance learning because of the unique financial and social benefits offered by these programs. Participants were retained as employees in their health care facilities, and remained in their communities and supported their families while advancing their careers. Space in health training institutions was freed up for new students entering in-residence pre-service training. A blended print-based distance learning model is most feasible at the national level due to current resource and infrastructure constraints. With an increase in staffing; improvement of infrastructure, coordination and curricula; and decentralization to the zonal or district level, distance learning can be an effective method to increase both the skills and the numbers of qualified health care workers capable of meeting the health care needs of the Tanzanian population.

Increasing health worker capacity through distance learning: a comprehensive review of programmes in Tanzania

PubMed Central

2010-01-01

Background Tanzania, like many developing countries, faces a crisis in human resources for health. The government has looked for ways to increase the number and skills of health workers, including using distance learning in their training. In 2008, the authors reviewed and assessed the country's current distance learning programmes for health care workers, as well as those in countries with similar human resource challenges, to determine the feasibility of distance learning to meet the need of an increased and more skilled health workforce. Methods Data were collected from 25 distance learning programmes at health training institutions, universities, and non-governmental organizations throughout the country from May to August 2008. Methods included internet research; desk review; telephone, email and mail-in surveys; on-site observations; interviews with programme managers, instructors, students, information technology specialists, preceptors, health care workers and Ministry of Health and Social Welfare representatives; and a focus group with national HIV/AIDS care and treatment organizations. Results Challenges include lack of guidelines for administrators, instructors and preceptors of distance learning programmes regarding roles and responsibilities; absence of competencies for clinical components of curricula; and technological constraints such as lack of access to computers and to the internet. Insufficient funding resulted in personnel shortages, lack of appropriate training for personnel, and lack of materials for students. Nonetheless, current and prospective students expressed overwhelming enthusiasm for scale-up of distance learning because of the unique financial and social benefits offered by these programs. Participants were retained as employees in their health care facilities, and remained in their communities and supported their families while advancing their careers. Space in health training institutions was freed up for new students entering in-residence pre-service training. Conclusions A blended print-based distance learning model is most feasible at the national level due to current resource and infrastructure constraints. With an increase in staffing; improvement of infrastructure, coordination and curricula; and decentralization to the zonal or district level, distance learning can be an effective method to increase both the skills and the numbers of qualified health care workers capable of meeting the health care needs of the Tanzanian population. PMID:21194417