• Journal of the Korean Institute of Intelligent Systems
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• v.2 no.2
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• pp.34-41
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• 1992

A robust and reliable learning and reasoning mechanism is addressed based upon fuzzy set theory and fuzzy associative memories. The mechanism stores a priori an initial knowledge base via approximate learning and utilizes this information for decision-making systems via fuzzy inferencing. We called this fuzzy computer architecture a 'fuzzy hypercube' processing all the rules in one clock period in parallel. Fuzzy hypercubes can be applied to control of a class of complex and highly nonlinear systems which suffer from vagueness uncertainty. Moreover, evidential aspects of a fuzzy hypercube are treated to assess the degree of certainty or reliability together with parameter sensitivity.

• Proceedings of the Technology Innovation Conference
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• 2003.06a
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• pp.136-157
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• 2003

• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.107-113
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• 1998

Grinding operation has difficulty in satisfying the qualitative knowledge based on the skilful expert as well as the quantitative data for all user. Design of grinding database based on the frame-based model is more effective method for utilizing the empirical and qualitative knowledge. In this paper. basic strategy to develop the grinding database by taking frame-based model, which is strongly dependent upon experience and intuition, is described. Grinding database based on the frame based model for designing the interaction and inference among the slots is accomplised by the object-oriented paradigm system.

• Knowledge Management Research
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• v.19 no.3
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• pp.31-46
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• 2018

Despite the organizational benefits of knowledge sharing among employees, many workers are reluctant to share their knowledge with their colleagues. Most organizations have taken a lot of actions to facilitate knowledge sharing among employees, including developing reward systems, enhancing social networks and interpersonal relationships and crafting organizational cultures that support knowledge sharing. To date, however, earlier studies have demonstrated that knowledge doesn't flow easily when an organization makes a concerted effort to facilitate knowledge sharing. The issue whether or not employees are motivated to share their knowledge with others is definitely the main concern in knowledge sharing. The purpose of this study is to explore the conditions under which employees are inclined to share knowledge with other members. Specifically, we examine the effect of knowledge self-efficacy on knowledge sharing intention. In addition, we attempt to investigate medicating effects of personal outcome expectation and performance-related outcome expectation on the relationship between knowledge self-efficacy and knowledge sharing intention. To test the proposed hypotheses in our study, we collected data via a survey with a sample of 210 employees in 23 firms in Korea. The major findings of the empirical research are as follows: 1) knowledge self-efficacy was positively related with knowledge sharing intention. 2) personal outcome expectation has turned out to have a mediation effect on the relationship between knowledge self-efficacy and knowledge sharing intention. 3) performance-related outcome expectation also mediates the relationship between knowledge self-efficacy and knowledge sharing intention That is, this result indicates that knowledge self-efficacy has indirect effect on knowledge sharing intention through personal outcome expectation and performance-related outcome expectation. Based on these findings, implications of the research findings and recommendation for future research are discussed.

• Journal of Intelligence and Information Systems
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• v.13 no.4
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• pp.1-16
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• 2007

According to the expansion of the Internet use and the utilization of e-business, there are an increasing number of studies of intelligent-based systems for the preparation of ubiquitous environment. In addition, expert systems have been developed from Stand Alone types to web-based Client-Server types, which are now used in various Internet environments. In this paper, we investigated the environment of development for web-based expert systems, we classified and analyzed them according to type, and suggested general typical models of web-based expert systems and their architectures. We classified the web-based expert systems with two perspectives. First, we classified them into the Server Oriented model and Client Oriented model based on the Load Balancing aspect between client and server. Second, based on the degree of knowledge and inference-sharing, we classified them into the No Sharing model, Server Sharing model, Client Sharing model and Client-Server Sharing model. By combining them we derived eight types of web-based expert systems. We also analyzed the location problems of Knowledge Bases, Fact Bases, and Inference Engines on the Internet, and analyzed the pros & cons, the technologies, the considerations, and the service types for each model. With the framework proposed from this study, we can develop more efficient expert systems in future environments.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1071-1076
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• 2003

In this work, we propose a new framework of robot control for a variety of applications to our unstructured everyday environments. Programming robots can be a very time-consuming process and seems almost impossible for ordinary end users. To cope with this, this work is to provide a software framework for building robot application programs automatically, where we have robots learn how to accomplish a commanded task from the object. An integrated sensing and computing tag is embedded into every single object in the environment. In the robot controller, only the basic software libraries for low-level robot motion control are provided from the robot manufacturer. The main contributions of this work is to develop a server platform that we call Omniscient Server that generates the application programs and send them to the robot controller through the network. The object-related information from the object server merges into robot control software to generate a detailed application program based on the task commands from the human. We have built a test bed and demonstrated that a robot can perform a common household task within the proposed framework.

• Journal of the Korea Society of Computer and Information
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• v.21 no.8
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• pp.41-48
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• 2016

In this paper, we propose an election protocol based on mobile ad-hoc network. In distributed systems, a group of computer should continue to do cooperation in order to finish some jobs. In such a system, an election protocol is especially practical and important elements to provide processes in a group with a consistent common knowledge about the membership of the group. Whenever a membership change occurs, processes should agree on which of them should do to accomplish an unfinished job or begins a new job. The problem of electing a leader is very same with the agreeing common predicate in a distributed system such as the consensus problem. Based on the termination detection protocol that is traditional one in asynchronous distributed systems, we present the new election protocol in distributed systems that are based on MANET, i.e. mobile ad hoc network.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1309-1314
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• 2003

If an agent has a learning ability using previous knowledge, then it is expected that the agent can speed up learning by interacting with environment. In this paper, we present an improved reinforcement learning algorithm using domain knowledge which can be represented by problem-independent features and their classifiers. Here, neural networks are employed as knowledge classifiers. To show the validity of our proposed algorithm, computer simulations are illustrated, where navigation problem of a mobile robot and a micro aerial vehicle(MAV) are considered.

• Knowledge Management Research
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• v.9 no.1
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• pp.117-128
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• 2008

It is very crucial to establishing an evaluation framework for anayzing the investment effects of IT asset such as knowledge managment systems. However, evaluation by quantitative measures, in spite of its usefulness and reliability, may have weakness in examining wide range of effects of the IT investment. Hence, the purpose of this paper is to propose a novel framework to evaluate the performance in terms of wider range of informatization effects. To do so, knowledge management concepts has been adopted in the evaluation method, and Impact Of Investment(IOI) has been suggested. IOI is used to derive Value Of Investment(VOI) and then ROI.

• Journal of Information Processing Systems
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• v.13 no.1
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• pp.57-67
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• 2017

In this paper, Atanassov's intuitionistic fuzzy set theory is used to handle the uncertainty of students' knowledgeon domain concepts in an E-learning system. Their knowledge on these domain concepts has been collected from tests that were conducted during their learning phase. Atanassov's intuitionistic fuzzy user model is proposed to deal with vagueness in the user's knowledge description in domain concepts. The user model uses Atanassov's intuitionistic fuzzy sets for knowledge representation and linguistic rules for updating the user model. The scores obtained by each student were collected in this model and the decision about the students' knowledge acquisition for each concept whether completely learned, completely known, partially known or completely unknown were placed into the information table. Finally, it has been found that the proposed scheme is more appropriate than the fuzzy scheme.