• International Journal of Safety
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• v.4 no.2
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• pp.12-17
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• 2005

This paper aims at the development of an knowledge base for an electrical fire cause diagnosis system using the entity relation database. The relation database which provides a very simple but powerful way of representing data is widely used. The system focused on database construction and cause diagnosis can diagnose the causes of electrical fires easily and efficiently. In order to store and access to the information concerned with electrical fires, the key index items which identify electrical fires uniquely are derived out. The knowledge base consists of a case base which contains information from the past fires and a rule base with rules from expertise. To implement the knowledge base, Access 2000, one of DB development tools under windows environment and Visual Basic 6.0 are used as a DB building tool. For the reasoning technique, a mixed reasoning approach of a case based inference and a rule based inference has been adopted. Knowledge-based reasoning could present the cause of a newly occurred fire to be diagnosed by searching the knowledge base for reasonable matching. The knowledge-based database has not only searching functions with multiple attributes by using the collected various information(such as fire evidence, structure, and weather of a fire scene), but also more improved diagnosis functions which can be easily wed for the electrical fire cause diagnosis system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.46
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• pp.181-196
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• 1998

The aim of this research is the development of a CAPP system which can use the old experience of process planning to generate a process plan for a new part and learn from its own experience using the concept of stratified case-based reasoning(CBR). A process plan is determined through the hierarchical process planning procedure that is based on the hierarchical feature structure of a part. Each part and case have their own multiple abstractions that are determined by the feature structure of the part. Retrieving the case in stratified case-based process planning is accomplished by retrieving the abstraction that is most similar to the input part abstraction in each abstraction level of the case-base. A new process plan is made by the adaptation that translates the old case's process plan into the process plan of a new part. Operations, machines and tools, setups and operation sequence in each setup are determined in the adaptation of abstraction using some algorithms and the reasoning based on knowledge-base. By saving a new part and its process plan as a case, the system can use this new case in the future to generate a process plan of a similar part. That is, the system can learn its own experience of process planning. A new case is stored by adding the new abstractions that are required to save as the new abstraction to the existing abstractions in the case-base.

• Journal of Korean Institute of Industrial Engineers
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• v.29 no.1
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• pp.32-40
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• 2003

In this study, we develop the Genetic Fuzzy System(GFS) to estimate the link traveling speed. Based on the genetic algorithm, we can get the fuzzy rules and membership functions that reflect more accurate correlation between traffic data and speed. From the fact that there exist missing links that lack traffic data, we added a Case Base Reasoning(CBR) to GFS to support estimating the speed of missing links. The case base stores the fuzzy rules and membership functions as its instances. As cases are accumulated, the case base comes to offer appropriate cases to missing links. Experiments show that the proposed GFS provides the more accurate estimation of link traveling speed than existing methods.

• Journal of the Korean GEO-environmental Society
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• v.14 no.11
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• pp.47-54
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• 2013

This study is the basic research to develop the customized base module for modular road system. A case study was carried out on designs of base module for soft soil condition. Two types of base module was proposed; crossbeam module and crossbeam-pile module. Based on the case study, it was verified crossbeam-pile module is suitable for soft soil condition and the optimum dimension of crossbeam-pile module for modular road system constructed on soft soil was determined. For development of the optimal base modular for modular road system, it is needed in the future to build a data base about ground and roadbed of road construction sites and to classify and systemized base modules according to soil conditions through many case studies.

• Computational Structural Engineering
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• v.9 no.3
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• pp.125-134
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• 1996

The base-isolation of building, as appeared in many studies, has shown remarkable performance in seismic response attenuation of the internal system as well as the building structure itself. But for the case that the internal system is submerged and hence subject to a considerable hydrodynamic effect, the seismic response of the system due to the base-isolation of building can be greater than the case that they are in air. This paper presents the dynamic analysis of a submerged internal system on base-isolated building to show such an example. The results show that an additional treatment is required to reduce the adverse effects on the seismic response of such a system when the building is base-isolated, and that the system response can be reduced to some extent by an appropriate control of fluid gap between the system and the building structure.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.110-113
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• 2003

Most traffic accidents are caused by drivers' carelessness and lack of information on the surrounding objects. In this paper we proposed a model of human intention recognition through case-base learning and to build up an experiment system. The system can help us recognize object's intention (e.g. turn left, turn right or straight) by using detected data about human's motion, speed of the car and the distance between the car and the intersection. Furthermore, we included an example using case-base learning in this paper to improve the precision of recognition as well as an example to explain the use of the system. PC can be used to predict the driving reaction beforehand and send a warning signal to the driver in time if there is any danger.

• Smart Structures and Systems
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• v.18 no.2
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• pp.293-315
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• 2016

Seismic isolation is often used in protecting mission-critical structures including hospitals, data centers, telecommunication buildings, etc. Such structures typically house vibration-sensitive equipment which has to provide continued service but may fail in case sustained accelerations during earthquakes exceed threshold limit values. Thus, peak floor acceleration is one of the two main parameters that control the design of such structures while the other one is peak base displacement since the overall safety of the structure depends on the safety of the isolation system. And in case peak base displacement exceeds the design base displacement during an earthquake, rupture and/or buckling of isolators as well as bumping against stops around the seismic gap may occur. Therefore, obtaining accurate peak floor accelerations and peak base displacement is vital. However, although nominal design values for isolation system and superstructure parameters are calculated in order to meet target peak design base displacement and peak floor accelerations, their actual values may potentially deviate from these nominal design values. In this study, the sensitivity of the seismic performance of structures equipped with linear and nonlinear seismic isolation systems to the aforementioned potential deviations is assessed in the context of a benchmark shear building under different earthquake records with near-fault and far-fault characteristics. The results put forth the degree of sensitivity of peak top floor acceleration and peak base displacement to superstructure parameters including mass, stiffness, and damping and isolation system parameters including stiffness, damping, yield strength, yield displacement, and post-yield to pre-yield stiffness ratio.

• The Journal of Information Systems
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• v.18 no.3
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• pp.231-249
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• 2009

Recently, plant construction industries are enjoying a favorable business climate centering around developing countries and oil producing countries rich in oil money. This paper proposes a methodology of implementing case-based reasoning(CBR) system for managing knowledge like lessons learned and various documents accumulated in performing power plant construction projects which are receiving a lot of order from foreign countries such as the Middle East, etc. Our methodology is consisted of 10 steps : user requirement gathering, information modeling, case modeling, case base design, similarity function design, user interface design, case base building, CBR module development, user interface implementation, integration test. Also, to illustrate the effectiveness of proposed methodology, the real CBR system is implemented for the plant business division of 'H' company which has international competitiveness in the field of plant construction industry. At present, the implemented CBR system is successfully utilizing as storing, sharing, and reusing knowledge which is accumulated in performing power plant construction projects in the target enterprise.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.11 no.6
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• pp.799-807
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• 1999

Exergy analysis is widely used in energy system analysis for more efficient energy use. Pinch technology has focused on chemical plants, such as pure heat exchanger networks. In this study, the objective is to seek more effective means with integrating above two methods. In order to demonstrate effective result and to prove possibility for pinch analysis, the steam turbine is adopted to make heat recovery in the heat exchanger network. Three cases are introduced using the integration of exergy and pinch analysis. The standard steam turbine utility is the base case, and adding the heat pump to this system is the second case. The third case is the system with the heat pump and minimum utilities. The results show that the output power of steam turbine in the case(2) and case(3) are increased up to 42% and 46%, respectively, compared with that of base case.

• The Transactions of the Korea Information Processing Society
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• v.6 no.1
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• pp.96-106
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• 1999

Case-Base Reasoning(CBR) solves the new problems by reusing the solutions to previously solved problems. But, there are differences between previously known case and a new problems. To solve this problem Case-Based System have to adapt the solution of the case to suit a new situation. In current CBR systems, case adaptation is usually performed by rule-based method that use rules hand-coded by the system developer. So, CBR system designer faces knowledge acquisition bottleneck akin to those found in traditional expert system design. To solve this problem, in this thesis, we present an automatic learning method of case adaptation knowledge using case base, we use a method of comparing cases in the case base to learn adaptation knowledge. The system is tested in the domain for the decision of travel-price. The result shows accuracy improvement in comparison with case retrieval-only system.