• Journal of the Society of Naval Architects of Korea
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• v.32 no.4
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• pp.136-141
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• 1995

Determination and optimization of proper welding condition are very important tasks to be directly related to weld quality and productivity. On this research the relationship between welding parameters and results is investigated systematically. Theoretical method, statistical analysis of experimental data and analysis of empirical knowledge are applied for this work. These results are represented by empirical equations, fuzzy rules and artificial intelligent knowledge forms in the knowledge base. The approximate reasoning of fuzzy expert system and the information in the knowledge base are used for recommendation of suitable welding condition, and optimization of welding parameter which is based on the evaluation of welding results by user.

• Science of Emotion and Sensibility
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• v.15 no.1
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• pp.133-140
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• 2012

We designed a novel individualization process for improving personal emotion recognitions in real time. The designed individualization process was performed by a neutralization algorithm of physiological signals, a subjective emotion reflection of a user updated by personal emotion rules in real time. The physiological signals such as PPG(Photoplethysmography), GSR(Galvanic skin reflex), and SKT(Skin temperature) were measured and analyzed to estimate an emotion states of users. Regulating the emotion status using by emotion rules was performed by reflecting subjective evaluations. The agreement of emotion recognition between of individualization and non-individualization method was estimated by 10 undergraduates (5 females, mean age: $22.1{\pm}2.2$) of Sangmyung University. During the emotion recognition test, 45 images were randomly presented to each participant five times. In results, the proposed individualization process showed the agreement of 71.67 % which was five times higher than when the process was not applied. Therefore, in this study, we demonstrated that the individualization process was significantly useful for customizing emotion recognitions of personal users in real time. The individualization process will be able to improve satisfactions in various emotion related applications and services in the nearer future.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.1
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• pp.57-64
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• 2006

This paper is proposed for a artificial neural network(ANN) sensorless control based on the vector controlled induction motor drive, or proposes a adaptive fuzzy teaming control(AFLC). The fuzzy logic principle is first utilized for the control rotor speed. AFLC scheme is then proposed in which the adaptation mechanism is executed using fuzzy logic. Also, this paper is proposed for a method of the estimation of speed of induction motor using ANN Controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The error between the desired state variable and the actual one is back-propagated to adjust the rotor speed, so that the actual state variable coincide with the desired one. The back propagation mechanism is easy to derive and the estimated speed tracks precisely the actual motor speed. This paper is proposed the analysis results to verify the effectiveness of the new method.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2009.05a
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• pp.67-70
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• 2009

본 논문에서는 생리신호를 이용한 감성인식의 정확도를 높이기 위한 개인화 방안에 대해 연구하였다. 이전연구 결과인 TDP(Time Dependent Parameters)를 이용한 감성인식방법은 자율신경계 반응을 4 단계로 세분화하여 감성인식의 정확도를 높일 수 있었다. 하지만 평균 정확도는 향상된 반면 개인별로 정확도의 개인차가 발생하였다. 본 연구는 개인차를 줄이기 위해서, 개인의 반응에 따라 감성인식을 위한 룰베이스가 변화하는 적응적 TDP 알고리즘을 개발하였다. 시각자극을 이용한 감성유발 실험결과를 분석하여 감성인식 개인차가 감소하였는지 확인하였다. 실험은 4 명을 대상으로 하였으며 한 명당 24번의 시각 자극을 제시하여 96개의 데이터가 수집되었다. 데이터는 자율신경계 반응과 주관적 감성을 측정하였나 TDP 를 이용한 분석과 적응적 TDP 분석방법으로 감성을 인식한 결과를 비교한 결과 평균 정확도는 증가하지 않았지만 전반적인 정확도 수준은 상승하는 것을 확인하였다. 그러므로 적응적 TDP를 이용할 경우 개인차를 줄일 수 있다는 것을 확인하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.1
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• pp.39-43
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• 2002

In the frequency response analysis using a modal method, it is very important to determine the number of modes involved with the formulation of a frequency response function. Most engineers are inclined to determine mode truncation with their experience. But it is difficult for non-experts to decide the mode truncation reasonably in many problems of dynamic analyses. In this study, fuzzy theory is used to standardize the empirical determination of mode truncation so that not only the experts but also non-experts can decide a Proper mode truncation easily. Fuzzy rule base is based on the simulation results using finite element method. Numerical simulations show that the developed mode truncation method is a very effective method to choose the number of the considered modes.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.235-241
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• 2011

A large number of industry and trade circulation enterprises integrate logistics resource. They give links of product transport to some professional logistics enterprises in order to reduce costs. We call these professional logistics enterprises as the Third-party Logistics. As the development of the computer and internet, the suppliers, buyers and the Third-party Enterprises connect each other with internet. And different company use different management software, so heterogeneous data become a big problem of the information system for Third-party Enterprises. We built the logistics ontology with prot$\'{e}$g$\'{e}$, and translate it in OWL. We also built the rules for Logistics Ontology to improve the limitations of the OWL. Then we design the intelligent system for 3PL Enterprises Distribution Center based on Logistics Ontology and Logistics Rules. At final, we give an example to show the workflow visually.

• The Journal of the Korea Contents Association
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• v.18 no.2
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• pp.370-377
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• 2018

Focus level has been important mental state in user study. Cardiac response has been related to focus and less clarified. The study was to determine cardiac parameters for recognizing focus level. The sixty participants were asked to play shooting game designed to control two focus levels. Electrocardiogram was measured during task. The parameters of time domain and frequency domain were determined from ECG. As a result of independent t-test, RRI, SDNN, rMSSD and pNN50 of time domain indicator were statistically significant in recognizing focus level. LF, HF, lnLF and lnHF of frequency domain were observed to be significant indicator. The rule base for recognition has been developed by the combination of RRI, rMSSD and lnHF. The rule base has been verified from another sixty data samples. The recognition accuracy were 95%. This study proposed significant cardiac indicators for recognizing focus level. The results provides objective measurement of focus in user interaction design in the fields of contents industry and service design.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.506-512
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• 2000

In this paper, we propose a Fuzzy Classifier System(FCS) makes the classifier system be able to carry out the mapping from continuous inputs to outputs. The FCS is based on the fuzzy controller system combined with machine learning. Therefore the antecedent and consequent of a classifier in FCS are the same as those of a fuzzy rule. In this paper, the FCS modifies input message to fuzzified message and stores those in the message list. The FCS constructs rule-base through matching between messages of message list and classifiers of fuzzy classifier list. The FCS verifies the effectiveness of classifiers using Bucket Brigade algorithm. Also the FCS employs the Genetic Algorithms to generate new rules and modifY rules when performance of the system needs to be improved. Then the FCS finds the set of the effective rules. We will verifY the effectiveness of the poposed FCS by applying it to Autonomous Mobile Robot avoiding the obstacle and reaching the goal.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.2
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• pp.206-215
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• 2013

In recent years, many companies have heavily invested in introducing production informatization systems in order to strengthen the competitiveness and to satisfy consumer's desires in quickly changing market environment. However, it is not effective due to the lack of understanding of systems and of non-existence of an optimal system for each company. Therefore, in this paper, manufacturing companies were classified according to its properties; size of the firm, type of business, production method and job production. After that, a model has been built to calculate the production informatization level, and it has been applied to 450 companies. Results of 450 surveys would be the base for figuring out strategies of introducing the production informatization to the companies which are wishing to build production informatization systems. Finally, Developed in this paper rule base system refer customized guideline to company that wants to adapt production information system.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.5
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• pp.1-10
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• 2000

In this paper, we propose a Fuzzy Classifier System(FCS) makes the classifier system be able to carry out the mapping from continuous inputs to outputs. The FCS is based on the fuzzy controller system combined with machine learning. Therefore the antecedent and consequent of a classifier in FCS are the same as those of a fuzzy rule. In this paper, the FCS modifies input message to fuzzified message and stores those in the message list. The FCS constructs rule-base through matching between messages of message list and classifiers of fuzzy classifier list. The FCS verifies the effectiveness of classifiers using Bucket Brigade algorithm. Also the FCS employs the Genetic Algorithms to generate new rules and modify rules when performance of the system needs to be improved. Then the FCS finds the set of the effective rules. We will verify the effectiveness of the poposed FCS by applying it to Autonomous Mobile Robot avoiding the obstacle and reaching the goal.