INDED: a distributed knowledge-based learning system

The task of object identification is fundamental to the operations of an autonomous vehicle. It can be accomplished by using techniques based on a Multisensor Fusion framework, which allows the integration of data coming from different sensors. In this paper, an approach to the synergic interpretation of data provided by thermal and visual sensors is proposed. Such integration is justified by the necessity for solving the ambiguities that may arise from separate data interpretations. The architecture of a distributed Knowledge-Based system is described. It performs an Intelligent Data Fusion process by integrating, in an opportunistic way, data acquired with a thermal and a video (b/w) camera. Data integration is performed at various architecture levels in order to increase the robustness of the whole recognition process. A priori models allow the system to obtain interesting data from both sensors; to transform such data into intermediate symbolic objects; and, finally, to recognize environmental situations on which to perform further processing. Some results are reported for different environmental conditions (i.e. a road scene by day and by night, with and without the presence of obstacles).

Download Full-text

To Design an Effective E-Learning System in the Civil Servants' Job-Training

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.171-172.523 ◽

2010 ◽

Vol 171-172 ◽

pp. 523-526

Author(s):

Fu Lei Zhang

Keyword(s):

Learning Environment ◽

Job Training ◽

Learning System ◽

Chinese Government ◽

Educational Training ◽

Knowledge Based ◽

E Learning ◽

Learning Policies ◽

Uniform Manner

The Chinese government is pursuing e-learning policies which makes job-training with a knowledge-based society. To explain more fully the important role of the e-learning environment, this article undertakes some typical examples of the governments' job-training under e-learning environment. The main problems in servants' job-training in China are the low quantity in the servants' training, short of restriction, the uniform manner in the training and less fairness and availability of opportunities for educational training. In order to develop the e-learning system, the civil servant's job training policies are provided and the measures of the effective e-learning system are designed.

Download Full-text

Mobile Agent Assisted E-Learning System

Encyclopedia of E-Commerce, E-Government, and Mobile Commerce ◽

10.4018/978-1-59140-799-7.ch119 ◽

2011 ◽

pp. 740-746

Author(s):

Jon T.S. Quah ◽

Winnie C.H. Leow ◽

Y. K. Soh

Keyword(s):

Response Time ◽

Mobile Agent ◽

Workforce Training ◽

Learning System ◽

The Internet ◽

Knowledge Based ◽

Technology Industry ◽

Education Levels ◽

E Learning ◽

Traditional Classroom Teaching

In the past decades, the Internet has evolved so rapidly that it makes the information-technology industry grow extremely fast. Internet-based applications such as e-commerce, e-payment, e-billing, e-learning, and so forth have tremendous influence on society: There is a trend that our society will be reshaped by the Internet. Among these applications, e-learning is one of the killer applications. Currently, the traditional education system faces some challenges that arose from the development of the knowledge-based economy. School enrollment increases with the population growth, education levels also increase for the new economy, and the cost of higher education escalates. On the other hand, in the workforce-training market, as the information economy develops, the demand for skilled workers increases. As the technology keeps changing, the workforce needs continuous training to maintain its productivity level. Hence, both formal school-based education and continuous workforce training have become big business now, and they will be even bigger in the future (Kerrey & Isakson, 2000). A more sophisticated education model is required to take this challenge, and so e-learning came into being. Compared to traditional classroom teaching, e-learning provides one major advantage: It makes the access of information much easier and more convenient. Hence, it makes learning of all kinds, at all levels, anytime, anyplace, at any pace a practical reality (Kolar, 2001). E-learning also gives tremendous cost savings for both instructors and learners; the learning model is shifted from instructor centered to learner centered, which focuses primarily on the needs of learners. The updating of online material is also much easier. Many e-learning systems can develop personalized and interactive applications that allow users to customize their e-learning models to their own pace, and they can truly engage the user in that they involve the simulation of real-world events and sophisticated collaboration with other learners and instructors (Quah & Chen, 2002). In our e-learning system, we incorporated mobile-agent technology to enhance the response time of information retrieval. The purpose of this incorporation is to overcome the bottleneck problem faced by many pure client-server-based systems. Since mobile agents are able to traverse from one information server to another autonomously to search for relevant documents for users, only relevant articles are sent back. This saves bandwidth and enhances the efficiency of the e-learning system. As a result, the turnaround time for user queries or information searches reduces, and the feedback from the user community is positive as the response time is shorter and users find it easier to maintain their trains of thought in their study.

Download Full-text

MULTI‐LAYERED KNOWLEDGE‐BASED ARCHITECTURE OF THE ADAPTABLE DISTANCE LEARNING SYSTEM

Technological and Economic Development of Economy ◽

10.3846/1392-8619.2009.15.229-244 ◽

2009 ◽

Vol 15 (2) ◽

pp. 229-244 ◽

Cited By ~ 4

Author(s):

Dalė Dzemydienė ◽

Lina Tankelevičienė

Keyword(s):

Distance Learning ◽

Intelligent Agents ◽

Research Work ◽

Learning System ◽

Conceptual Approach ◽

Knowledge Based ◽

Distance Learning System ◽

Learning System Architecture ◽

Service Oriented ◽

E Learning

The quality of the distance learning courses is largely influenced by competently prepared educational resources and an effective study support system. One of the possible ways to improve distance learning infrastructure and increase its effectiveness is to extend the architecture of present e‐learning systems by the components for adaptable and sustainable learning. This research work is devoted to developing the service‐oriented distance learning environment adaptable to the user's needs. The proposed adaptable communication environment of distance learning is constructed by integration of new components of communication scenarios generation, adaptable for student's goals, multilayered domain ontology of learning subject and forming intelligent agents’ framework possible. The paper presents the knowledge‐based component architecture of the distance learning system, which enables a better adaptation of learning resources to students. The paper analyses the possibilities of integrating ontology into the e‐learning system. The issues of decomposing ontology into different levels of understanding are discussed in order to adapt to learner's tasks and goals. A conceptual approach is proposed for extending the existing distance learning system architecture by intelligent and deeper knowledge layers. Santrauka Nuotolinių studijų kokybė daugiausia priklauso nuo kompetentingai parengtų mokomųjų priemonių ir veiksmingai veikiančios studijų paramos sistemos. Ieškant priemonių, kaip pagerinti nuotolinių studijų sistemos infrastruktūrą ir padidinti jos darbo efektyvumą, nagrinėjamos galimybės praplėsti tradicinės nuotolinio mokymo sistemos architektūrą komponentėmis, kurios leistų išplėtoti adaptuotą ir darnų mokymosi procesą. Šio tyrimo uždaviniai skirti paslaugoms, skirtoms išvystyti nuotolinio mokymo aplinką. Siekiant sukurti tinkamą kompiuterizuotą bendradarbiavimo aplinką, lanksčiai prisitaikoma prie kintančių vartotojo poreikių studijų procese. Architektūra projektuojama integruojant naujas komponentes bendravimo scenarijams generuoti, daugelio lygių dalykinės srities ontologijai naudoti ir sudarant sąlygas automatizuotam intelektinių agentų bendravimui. Straipsnyje nagrinėjamos galimybės integruoti dalykinės srities ontologiją į tradicinės nuotolinio mokymo sistemos aplinką. Ontologijos detalizavimo pagal studento supratimo lygmenis klausimai nagrinėjami siekiant pateikti koncepcinį tokios nuotolinės adaptuotos sistemos darbo modelį.

Download Full-text