• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.313-315
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• 2021

Timely and accurate diagnosis of lung diseases using Chest X-ray images has been gained much attention from the computer vision and medical imaging communities. Although previous studies have presented the capability of deep convolutional neural networks by achieving competitive binary classification results, their models were seemingly unreliable to effectively distinguish multiple disease groups using a large number of x-ray images. In this paper, we aim to build an advanced approach, so-called Ensemble Knowledge Distillation (EKD), to significantly boost the classification accuracies, compared to traditional KD methods by distilling knowledge from a cumbersome teacher model into an ensemble of lightweight student models with parallel branches trained with ground truth labels. Therefore, learning features at different branches of the student models could enable the network to learn diverse patterns and improve the qualify of final predictions through an ensemble learning solution. Although we observed that experiments on the well-established ChestX-ray14 dataset showed the classification improvements of traditional KD compared to the base transfer learning approach, the EKD performance would be expected to potentially enhance classification accuracy and model generalization, especially in situations of the imbalanced dataset and the interdependency of 14 weakly annotated thorax diseases.

• Journal of the Korean Institute of Navigation
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• v.15 no.2
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• pp.13-38
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• 1991

This paper intends to develop a Prototype Expert Collision Avoidance System by introducing expert system techniques into the decision block of anti-collision loop. The problem domain of this study is characterized and specified by combining the concepts of anti-collision loop and knowledge -based system for collision avoidance. Domain in knowledge which may originates from the appropriate sources such as the International Regulations for Preventing Collision at Sea 1972, Marine Traffic Laws, and many texts on the subject of anticollision navigation and good seamanship is acquired and formalized into the knowledge-base system using production rule. Finally, a Prototype Expert Collision Avoidance System is built by using the CLIPS, developed by AIS NASA written in and fully integrated with the C language, and some test-and-run results of the system are demonstrated and examined. The author considers the proposed system which is named PECAS to be meaningful as a test bed for a further refined Expert Collision Avoidance System on board the Automated Ship.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1989.04a
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• pp.71-76
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• 1989

Structural design, generally engineering design, is a complex process combinding design knowledges and analysis techniques. While analysis techniques can be automated in an algorithmic fashion, relatively little work has been done in the area of the design automation. An effect approach method for the automation of the engineering design may be a hybrid system, in which design knowledges, specification requirements and interpretations are represented using an expert system methodology and numerically intensive operations of the design process are implemented using an algorithmic language such as FORTRAN. The purpose of this paper is concentrated on the knowledge of K-CLIPS(KAIST-C Language Integrated Production System) used to design and implement this hybrid system. In K-CLIPS, some representation methods : frame, production rule, fact and user defined function are used to construct the knowledge base. The hierarchical knowledges could be expressed more naturally with a little number of rules than other plain production systems.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.47-50
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• 1991

This paper discusses a knowledge-based system being developed by KAIST and KEPCO to assist planning the annual maintenance schedule of power units. To meet users' requirements, we have designed the system with several features: man-machine interaction, catalog system, user-friendliness, the hybrid-system of math-model and knowledge-base. In this paper, we introduce the outline of our system.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.2
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• pp.15-24
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• 2000

An intelligent software system which can support efficiently and systematically machine tool design by utilizing deign knowledge is described in this paper. The process of embodiment design of a machining center was modelled represented by IDEF0 and embedded in the system. A hybrid type inference engine has been introduced so that the system can effec-tively deal with knowledge represented in diversified forms The design system was developed on the basis of object-ori-ented programming and has been coded into one software system which can be ported on Windows NT.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.04a
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• pp.102-106
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• 1997

Grinding has difficulty in satisfying the qualitative knowledge based on the skilled expert as well as quantitative data for all user. Design of grinding database is based on the frame-based model for utilizing the empirical and qualitative knowledge. Inthis paper, basic strategy to develop the grinding database by frame-based model, which is strongly dependent upon experience and intuition, frame-base model, which is strongly dependent upon experience and intuition, is described. Design of grinding database is based on the frame-based model for utilizing the ambiguous knowledge and inference is accomplised by the object-oriented paradigm system.

• Journal of Biosystems Engineering
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• v.18 no.2
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• pp.133-143
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• 1993

In developing an Expert System(ES), there are two ways. One is to develop an ES using AI(artificial Intelligence) languages and another using ES-development tools. CLIPS is an ES-development tool and has a powerful inference engine in it. Using the tool like CLIPS, knowledge engineer can concentrate on constructing a knowledge base without wasting time in developing an inference engine. However, CLIPS is lack of user-friendly interfaces for both knowledge enginners and users. Because CLIPS was developed in USA, it can not afford to use Korean language. Therefore, several user-friendly interfaces including hmenu, htille, hpcxdisplay were develpoed and added to CLIPS. CLIPS with the interfaces is called HCLIPS(Hangul CLIPS) in this paper. HCLIPS provides a new I/O device to be utilized for expert systems in Korean. HCLIPS can be efficiently used for developing expert systems in agriculture and consulting farmers interactively who are not familiar with computer programming and ES itself.

• Journal of Electrical Engineering and Technology
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• v.3 no.3
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• pp.363-372
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• 2008

In this paper, knowledge-based approach using Support Vector Machines (SVMs) are used for estimating the coordinated zonal settings of a distance relay. The approach depends on the detailed simulation studies of apparent impedance loci as seen by distance relay during disturbance, considering various operating conditions including fault resistance. In a distance relay, the impedance loci given at the relay location is obtained from extensive transient stability studies. SVMs are used as a pattern classifier for obtaining distance relay co-ordination. The scheme utilizes the apparent impedance values observed during a fault as inputs. An improved performance with the use of SVMs, keeping the reach when faced with different fault conditions as well as system power flow changes, are illustrated with an equivalent 265 bus system of a practical Indian Western Grid.

• Korean Management Science Review
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• v.14 no.1
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• pp.205-227
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• 1997

Higher level representation splay an important role in model management systems. The role is to make decision makers friendly represent their problem using the representations. In this research, we address higher level representations including five distinctivenesses: Objective, Node, Link, Topological Constraint including five components, and Decision, Therefore, it is developed a system called HLRNET that implements the building procedure of network models using structural knowledge and object data The paper particularly elaborates all components included in each of distinctiveness extracted from structural characteristics of a lot of telecommunication network models. Higher level representations represented with five destinctivenesses should be converted into base level representations which are employed for semantic representations of linear and integer programming problems in a knowledge-assisted optimization modeling system. The system is illustrated with an example of the local access network model.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.79-90
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• 1995

The material handling equipment selection, that is a key task in the material handling system design, is a complex, difficult task, and requires a massive technical knowledge and systematic analysis. It is invaluable to justify the selected equipment model by the performance evaluation before its actual implementation. This paper presents an intelligent knowledge-based expert system called "IMESE" created by authors, for the selection and evaluation of material handling equipment model suitable for movement and storage of materials in a manufacturing facility. The IMESE is consisted of four modules: a knowledge base to select an appropriate equipment type, a multiple criteria decision making procedure to choose the most favorable commercial model of the selected equipment type, a database to store the list of commercial models of equipment types with their specifications, and simulators to evaluate the performance of the equipment model. The whole process of IMESE is executed under VP-Expert expert system environment.vironment.