• 한국IT서비스학회:학술대회논문집
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• 한국IT서비스학회 2002년도 추계학술대회
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• pp.425-430
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• 2002

Over the years, several different approaches have been proposed to enhance the practice of software reuse. These approaches vary in reuse abstraction levels or application domains they focus on. However, it seems that they do not adequately meet the needs of software designers in planning and managing reuse. One reason may be the lack of conceptually well-established framework supporting work domain analysis and modeling. As a new viable solution to this problem, Sutcliffe and his colleagues developed Domain Theory , which is introduced in this paper. Utilizing multidisciplinary perspective, such as cognitive psychology, management science, human-computer interaction, and software engineering. it provides a schematic framework that defines a comprehensive library of generic and reusable models of domain knowledge in terms of generic tasks and meta-domains. It also provides useful methods and guidelines for software reuse, emphasizing the concept of abstraction process in a designer s mind. This paper firstly gives a brief overview of fundamentals of software reuse. Next, it explains the foundation of domain theory and discusses its applicability to software reuse. In particular, the taxonomy of meta-domains and the types of generic tasks are described in more detail. Finally, the future research framework, which primarily addresses the problem of how to apply the domain theory to various work domains, is proposed.

• Journal of applied mathematics & informatics
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• 제10권1_2호
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• pp.333-351
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• 2002

This paper introduces a search method based on conceptual graph. A hyperlink information is essential to construct conceptual graph in web. The information is very useful as it provides summary and further linkage to construct conceptual graph that has been provided by human. It also has a property which shows review, relation, hierarchy, generality, and visibility. Using this property, we extracted the keywords of web documents and made up of the conceptual graph among the keywords sampled from web pages. This paper extracts the keywords of web pages using anchor text one out of hyperlink information and makes hyperlink of web pages abstract as the link relation between keywords of each web page. 1 suggest this useful search method providing querying word extension or domain knowledge by conceptual graph of keywords. Domain knowledge was conceptualized knowledged as the conceptual graph. Then it is not listing web documents which is the defect of previous search system. And it gives the index of concept associating with querying word.

• 한국정밀공학회지
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• 제24권11호
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• pp.126-133
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• 2007

Tuberculosis (TB) is a chronic or acute infectious disease which damages more people than any other infectious diseases according to WHO estimates. In this paper, a new automatic detection system of tuberculosis bacilli by using their color information is proposed. Through the deep investigation of color and intensity compositions of tuberculosis images, new pre-processing and segmentation algorithms are suggested. Specific features of bacilli are extracted from the processed images and number counting is done by using domain-specific knowledge rules.

• Journal of Computing Science and Engineering
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• 제6권4호
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• pp.243-256
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• 2012

In this paper we present a framework for a novel kind of context-aware preference query composition whereby queries for the Preference SQL system are created. We choose a commercial e-business platform for outdoor activities as a use case and develop a context model for this domain within our framework. The suggested model considers explicit user input, domain-specific knowledge, contextual knowledge and location-based sensor data in a comprehensive approach. Aside from the theoretical background of preferences, the optimization of preference queries and our novel generator based model we give special attention to the aspects of the implementation and the practical experiences. We provide a sketch of the implementation and summarize our user studies which have been done in a joint project with an industrial partner.

• Journal of information and communication convergence engineering
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• 제6권2호
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• pp.222-227
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• 2008

The important problem in designing a Fuzzy Logic Controller(FLC) is generation of fuzzy control rules and it is usually the case that they are given by human experts of the problem domain. However, it is difficult to find an well-trained expert to any given problem. In this paper, I describes an application of genetic algorithm, a well-known global search algorithm to automatic generation of fuzzy control rules for FLC design. Fuzzy rules are automatically generated by evolving initially given fuzzy rules and membership functions associated fuzzy linguistic terms. Using genetic algorithm efficient fuzzy rules can be generated without any prior knowledge about the domain problem. In addition expert knowledge can be easily incorporated into rule generation for performance enhancement. We experimented genetic algorithm with a non-trivial vehicle controling problem. Our experimental results showed that genetic algorithm is efficient for designing any complex control system and the resulting system is robust.

• 한국과학교육학회지
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• 제14권1호
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• pp.12-23
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• 1994

This study was conducted to investigate the status and the problem of environmental education in schools. For this investigation, sub-goals to the general goal for environmental education such as knowledge, awareness, attitude, skill, participation, and evaluation were classified. The contents and objects of the environment-related chapters in elementary and secondary school science texts and of the materials for environmental education were analyzed. Resultingly, the content and objects focused on the cognitive domain such as knowledge and skill category in science texts($85{\sim}92\;%$) and in the materials for environmental education($70{\sim}84\;%$). The result indicated that the objects of the cognitive domain were heavily emphasized in the present environmental education.

• 로봇학회논문지
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• 제18권2호
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• pp.225-232
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• 2023

With the recent increase of multiple robots cooperating in smart manufacturing logistics environments, it has become very important how to predict the safety and efficiency of the individual tasks and dynamically assign them to the best one of available robots. In this paper, we propose a novel task policy learner based on deep relational reinforcement learning for predicting the safety and efficiency of tasks in a multi-robot manufacturing logistics environment. To reduce learning complexity, the proposed system divides the entire safety/efficiency prediction process into two distinct steps: the policy parameter estimation and the rule-based policy inference. It also makes full use of domain-specific knowledge for policy rule learning. Through experiments conducted with virtual dynamic manufacturing logistics environments using NVIDIA's Isaac simulator, we show the effectiveness and superiority of the proposed system.

• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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• pp.343-351
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• 2005

It will not be impossible to develop an Information Systems and Information Technologies (IS/IT) program and a curriculum that represents the true needs of the IS/IT industry until IS/IT educator, reduce the gap perception and IS/IT practitioner's perception of IS/IT knowledge and technical skills that the industry might need. This paper represents and analysis of perceptions about IS/IT knowledge and skills that IS/IT practitioners might consider important. This study is based in Korean. The findings give us a very important lesson for IS/IT academicians that their understanding about the required knowledge and skills for the IS/IT career is not in line with that of IS/IT industry. Classifies the critical knowledge/skill set according to content or domain of knowledge by means of a survey. This is conducted in accordance with what IS/IT practitioners and educators can easily relate. The survey uses this approach and includes four broad categories of critical information Systems and Information technologies (IS/IT) knowledge/skills: IS/IT technology knowledge/skills, organizational and societal knowledge/skills, interpersonal knowledge/skills, and personal trait knowledge/skills.

• 한국실내디자인학회논문집
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• 제7호
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• pp.70-78
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• 1996

Artificial Intelligence is generally concerned with tasks whose execution appears to involve some intelligence if done by humans, and knowledge-based system ( in other word, expert system) is the research about the specific domain. This concept also can be applied to interior design field. So the purpose of this study is in reconstructing the accomplishment of artificial Intelligence and knowledge engineering, searching basic theories and cased to knowledge engineering , searching basic theories and cases to formulate knowledge -based design system, and testing the posibilities how the design information can be dealt in computer system. Given that recognition , two major problems must be solved before knowledge-based CAD systems could be come practical : Firstly , identification of the interior of designers use .Secondly , representing this knowledge in a computationally effective manner. I had discussed the basic concepts on which to base a knowledge- based design model, knowledge representation schemes, and problem solving, I could find the possibility which the knowledge-based system can be applied to the interior design according to this study. But there are non-deductive, often irrational and now easily computerized design process in interior design. Those are problems which are relevant to the machine learning and the creativity in design. So there should be a lot of research about the machine learning and the creatively in design in order to construct successfully intelligent knowledge-based design system.

• 지능정보연구
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• 제9권2호
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• pp.19-38
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• 2003

In this research, we propose the mechanism to develop self-evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most researchers had tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, this approach had some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, knowledge engineers had tried to develop an automatic knowledge extraction mechanism. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference engine. Our proposed mechanism has five advantages. First, it can extract and reduce the specific domain knowledge from incomplete database by using data mining technology. Second, our proposed mechanism can manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it can construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems) module. Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy relationships. Fifth, RDB-driven forward and backward inference time is shorter than the traditional text-oriented inference time.