• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.6
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• pp.549-553
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• 2002

This paper develops knowledge-based multiple fuzzy rules for researcher-selection by automatic ranking process. Inference rules for researcher-selection are created, then the multiple fuzzy rule system with max-min inference is applied. The way to handle for selection standards according to a certain criteria in dynamic manner, is also suggested in a simulation model. The model offers automatic, fair, and trust decision for researcher-selection processing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3333-3350
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• 2019

The smart jammer launches jamming attacks which degrade the transmission reliability. In this paper, smart jamming attacks based on the communication probability over different channels is considered, and an anti-jamming Q learning algorithm (AQLA) is developed to obtain anti-jamming knowledge for the local region. To accelerate the learning process across multiple regions, a multi-regional intelligent anti-jamming learning algorithm (MIALA) which utilizes transferred knowledge from neighboring regions is proposed. The MIALA algorithm is evaluated through simulations, and the results show that the it is capable of learning the jamming rules and effectively speed up the learning rate of the whole communication region when the jamming rules are similar in the neighboring regions.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.1
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• pp.107-118
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• 2002

This paper deals with an automated computer-aided process planning and die design system by which designer can determine operation sequences even if they have a little experience in process planning and die design of quasi-axisymmetric cold forging product by cold former working. The approach to the system is based on knowledge-based rules and a process knowledge base consisting of design rules is built. Knowledge for the system is formulated from plasticity theories, empirical results and the empirical knowledge of field experts. Programs for the system have been written in AutoLISP for the AutoCAD using a personal computer. An attempt is made to link programs incorporating a number of expert design rules with the process variables obtained by commercial FEM softwares, DEFORM and ANSYS, to form a useful package. The system is composed of three main modules and five sub-modules. The process planning and die design module considers several factors, such as the complexities of preform geometry, punch and die profiles, specifications of available cold farmer, and the availability of standard parts. As the system using 2D geometry recognition is integrated with the technology of process planning, die design, and CAE analysis, the standardization of die parts for wheel bolt requiring cold forging process is possible. The developed system makes it possible to design and manufacture quasi-axisymmetric cold forging product more efficiently.

• Proceedings of the KSPS conference
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• 2006.11a
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• pp.80-83
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• 2006

The purpose of this paper is to build a pronunciation lexicon with estimated likelihoods of the phonetic rules based on the phonetic realizations and therefore to improve the performance of CSR using the dictionary. In the baseline system, the phonetic rules and their application probabilities are defined with the knowledge of Korean phonology and experimental tuning. The advantage of this approach is to implement the phonetic rules easily and to get stable results on general domains. However, a possible drawback of this method is that it is hard to reflect characteristics of the phonetic realizations on a specific domain. In order to make the system reflect phonetic realizations, the likelihood of phonetic rules is reestimated based on the statistics of the realized phonemes using a forced-alignment method. In our experiment, we generates new lexica which include pronunciation variants created by reestimated phonetic rules and its performance is tested with 12 Gaussian mixture HMMs and back-off bigrams. The proposed method reduced the WER by 0.42%.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.99-106
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• 1998

In this paper, we have constructed an expert system for semiconductor chip encapsulation which combines a knowledge-based system with CAE software. The knowledge-base module includes heuristic and pre analysis knowledge for evaluation and redesign. Evaluation of the initial design and generation of redesign recommendations can be developed from the rules as applied to a given chip package. The CAE programs can be used for simulating the filling and packing stage of encapsulation process. The expert system is a new tool which enables package design or process conditions with high yields and high productivity.

• International Journal of Advanced Culture Technology
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• v.7 no.3
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• pp.158-165
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• 2019

Knowledge based system includes tools for constructing, testing, validating and refining the system along with user interfaces. An important issue in the design of a complete knowledge based system is the ability to produce explanations. Explanations are not just a series of rules involved in reasoning track. More detailed and explicit form of explanations is required not only for reliable reasoning but also for maintainability of the knowledge based system. This requires the explanation mechanisms to extend from knowledge oriented analysis to task oriented explanations. The explicit modeling of problem solving structures is suggested for explanation generation as well as for efficient and effective reasoning. Unlike other explanation scheme such as feedback explanation, the detailed, smaller and explicit representation of problem solving constructs can provide the system with capability of quality explanation. As a key step to development for explanation scheme, the problem solving methods are broken down into a finer grained problem solving primitives. The system records all the steps with problem solving primitives and knowledge involved in the reasoning. These are used to validate the conclusion of the consultation through explanations. The system provides user interfaces and uses specific templates for generating explanation text.

• Journal of the Korean Geographical Society
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• v.39 no.3
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• pp.444-456
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• 2004

Recently spatial modeling that combined GIS and Cellular Automata(CA) which are based on dynamic process modeling has been discussed and investigated. However, CA-based spatial modeling in previous research only provides the general modeling framework and environment, but lacks of providing simulation or transition rules for modeling. This study aims to propose a methodology for extracting spatial relation rules using GIS and Knowledge Discovery in Database(KDD) methods. This new methodology has great potentials to improve CA-based spatial modeling and is expected to be applied into several examples including urban growth simulation modeling.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.2
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• pp.83-93
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• 1993

Conventional computer programs developed and used by practicing engineers can be considered to contain expert knowledge and design experience. If these conventional programs are converted into expert systems, the difficult and time consuming process of knowledge acquisition can be simplified. Also the constructed knowledge-base can have higher confidence level than that constructed by the usual knowledge acquisition method of interviews. An existing computer program which is being used by ship structural designers has been reformulated as a design expert system by applying an expert system development shell-Nexpert. Utilizing the callable interface provided by the development shell, external design tools have also been integrated. The interfaced external functions are a graphical user interface (GUI) for the design process control, and graphics functions for the visualization of design results. It is observed that the developed system for design support is useful in two aspects. The trace-back function shows what portion of design rules are applied in arriving at certain design decisions. Also the knowledge-base can be conveniently updated as design rules of the classification societies are updated.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.505-511
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• 2003

Production rule based knowledge representation method has many advantages, but has the difficulties in maintaining the consistency of knowledge. Since the consistency maintenance of knowledge exercises a marked effect on the reliability of inference results, the system for consistency maintenance of knowledge is indispensable to increase the reliability. In the most popular pairwise checking method among consistency verification methods, the valuable rules can be omitted and it takes much time in checking the consistency when the rules are numerous. So, this paper is to propose and implement the verification system which can remove the structural errors and semantic ones, making up for the defects of pairwise checking method by using the certain property list and eventual property list and improving the steps of verification.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.6
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• pp.743-748
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• 2003

In this research, we propose a mechanism to develop an inference engine and expert systems based on relational database (RDB) and SQL (structured query language). Generally, former researchers had tried to develop an expert systems based on text-oriented knowledge base and backward/forward (chaining) inference engine. In these researches, however, the speed of inference was remained as a tackling point in the development of agile expert systems. Especially, the forward inference needs more times than backward inference. In addition, the size of knowledge base, complicate knowledge expression method, expansibility of knowledge base, and hierarchies among rules are the critical limitations to develop an expert system. To overcome the limitations in speed of inference and expansibility of knowledge base, we proposed a relational database-oriented knowledge base and forward inference engine. Therefore, our proposed mechanism could manipulate the huge size of knowledge base efficiently. and inference with the large scaled knowledge base in a short time. To this purpose, we designed and developed an SQL-based forward inference engine using relational database. In the implementation process, we also developed a prototype expert system and presented a real-world validation data set collected from medical diagnosis field.