• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2329-2334
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• 2006

In this paper, we proposed a method complementing failure of combining DNA fragments, defect of conventional contig assembly programs. In the proposed method, very long DNA sequence data are made into a prototype of fragment of about 700 bases that can be analyzed by automatic sequence analyzer at one time, and then matching ratio is calculated by comparing a standard prototype with 3 fragmented clones of about 700 bases generated by the PCR method. In this process, the time for calculation of matching ratio is reduced by Compute Agreement algorithm. Two candidates of combined fragments of every prototype are extracted by the degree of overlapping of calculated fragment pairs, and then degree of combination is decided using a fuzzy reasoning method that utilizes the matching ratios of each extracted fragment, and A, C, G, T membership degrees of each DNA sequence, and previous frequencies of each A, C, G, T. In this paper. DNA sequence combination is completed by the iteration of the process to combine decided optimal test fragments until no fragment remains. For the experiments, fragments or about 700 bases were generated from each sequence of 10,000 bases and 100,000 bases extracted from 'PCC6803', complete protein genome. From the experiments by applying random notations on these fragments, we could see that the proposed method was faster than FAP program, and combination failure, defect of conventional contig assembly programs, did not occur.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.421-426
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• 2018

With regard to LED lighting devices which have currently been commercialized, LED operating sequences are being sold in a fixed state. In such a state, the external environmental factors are not taken into consideration as only the illumination environment application is considered. Currently, it is difficult to create an optimal lighting environment which can adapt to changes in external environmental factors in the ship. Therefore, it was concluded that there is a need to input the external environment value so that the optimal illumination value can be reflected in real time in order to adapt more organically and actively to the change of external environmental factors. In this paper, we used a microprocessor as an integrated management system for environmental data that changes in real time according to existing external environmental factors. In addition, a controller capable of lighting control of RGB LED module by combining fuzzy inference system. For this, a fuzzy control algorithm is designed and a fuzzy control system is constructed. The distance and the illuminance value from the external environment element are input to the sensor, and these values are converted to the optimum illumination value through the fuzzy control algorithm, and are expressed through the dimming control of the RGB LED module and the practical effectiveness of the fuzzy control system is confirmed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.11
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• pp.2083-2090
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• 2008

In this paper, we propose a method for control of temperature and the direction of wind in an air-cooler using thermal images and fuzzy inference rules in order to achieve energy saving. In a simulation for controlling temperature, a thermal image is transformed to a color distribution image of $300{\times}400$ size to analyze the thermal image. A color distribution image is composed of R, G and B values haying temperature values of Red, Magenta, Yellow, Green, Cyan and Blue. Each color has a temperature value from $24.0^{\circ}C$ to $27.0^{\circ}C$ and a color distribution image is classified into height hierarchies from level 1 to level 10. The classified hierarchies have their peculiar color distributions and temperature values are assigned to each level by temperature values of the peculiar colors. The process for controlling overall balance of temperature and the direction of wind in an indoor space is as follows. Fuzzy membership functions are designed by the direction of wind, duration time, and temperature and height values of a color distribution image to calculate the strength of wind. After then, the strength of wind is calculated by membership values of membership functions.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.296-300
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• 2012

최근 지구 온난화에 따른 이상 기후변화로 인해 게릴라성 집중호우와 같은 다양한 강우패턴이 발생되고 있다. 특히 집중호우의 빈도 및 규모가 커지고 있으며 피해 또한 증가하고 있다. 이에 대한 대안으로 하도의 정비, 댐 건설, 제방의 증고와 같은 구조적인 대책과 홍수예경보, 홍수보험, 통합홍수관리와 같은 비구조적인 대책에 대한 접근이 이루어지고 있다. 그러나 미래 기후변화에 대한 예측의 한계와 구조적 대책의 물리적 한계를 감안할 때 구조적 대책에 의한 방법만으로 변화하는 기후에 대응하여 홍수재해를 완벽하게 대처하기에는 부족한 것이 사실이다. 따라서 비구조적 대책에 의한 홍수피해저감이 절실히 필요하다. 따라서 본 연구에서는 국제수문개발계획 대표유역인 낙동강유역에 위치한 위천유역을 연구대상으로 선택하였고 이러한 중소규모의 유역에서 홍수예경보의 한계를 극복하고 신뢰성을 높이기 위하여 홍수유출시에 일어나는 유역내의 복잡한 물리적인 현상을 직접 고려하지 않고 입력자료와 출력자료의 관계로부터 학습과 추론을 통해 결론을 도출해내는 신경망, 퍼지, 유전자 알고리즘과 같은 Date Mining 기법을 사용하여 자동우량과 자동수위에 의한 하류 홍수예경보시스템을 구축하기 위해 수위를 예측하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.6
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• pp.586-591
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• 2014

In this study, we introduce Radial Basis Function Neural Networks(RBFNNs) classifier using Artificial Bee Colony(ABC) algorithm in order to classify between precipitation event and non-precipitation event from given radar data. Input information data is rebuilt up through feature analysis of meteorological radar data used in Korea Meteorological Administration. In the condition phase of the proposed classifier, the values of fitness are obtained by using Fuzzy C-Mean clustering method, and the coefficients of polynomial function used in the conclusion phase are estimated by least square method. In the aggregation phase, the final output is obtained by using fuzzy inference method. The performance results of the proposed classifier are compared and analyzed by considering both QC(Quality control) data and CZ(corrected reflectivity) data being used in Korea Meteorological Administration.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.6
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• pp.749-754
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• 2011

In this study, we propose the design of optimized pRBFNNs-based face recognition system using two-dimensional Image and ASM algorithm. usually the existing 2 dimensional face recognition methods have the effects of the scale change of the image, position variation or the backgrounds of an image. In this paper, the face region information obtained from the detected face region is used for the compensation of these defects. In this paper, we use a CCD camera to obtain a picture frame directly. By using histogram equalization method, we can partially enhance the distorted image influenced by natural as well as artificial illumination. AdaBoost algorithm is used for the detection of face image between face and non-face image area. We can butt up personal profile by extracting the both face contour and shape using ASM(Active Shape Model) and then reduce dimension of image data using PCA. The proposed pRBFNNs consists of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of RBFNNs is represented as three kinds of polynomials such as constant, linear, and quadratic. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. The proposed pRBFNNs are applied to real-time face image database and then demonstrated from viewpoint of the output performance and recognition rate.

• Proceedings of the KIEE Conference
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• 1991.11a
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• pp.345-348
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• 1991

This paper describes a new auto tuning method for the intelligent PID control system. This new method is hosed on the settling time of the process and has been introduced into auto-tuning PID controller using fuzzy logic. The performance of the controller is measured by computer simulation. Simulation shows good results that controller searches well the optimal values of PID parameters in any conditions and the response characteristic of the control system is improved.

• Proceedings of the KIEE Conference
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• 1991.07a
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• pp.703-707
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• 1991

During the past several years, fuzzy control has emerged as one of the most active and fruitful areas for reaserch in the applications of fuzzy set theory. A key component of the fuzzy controller is a rule-based system which provides a linguistic description of control strategy. This strategy has the form of a collection of fuzzy conditional statements which are implemented and manipulated using fuzzy set theory. In this paper, we propose the rule-based controller for DC motor speed control. The result of performance compare with PID controller to verify the validity of proposed algorithm.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.259-262
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• 2011

최근 들어 소리의 세기나 하모니, 템포, 리듬 등의 다양한 음악 신호 특성을 기반으로 한 음악 무드 분류에 대한 연구가 활발하게 진행되고 있다. 본 논문에서는 음악 무드 분류의 정확도를 높이기 위하여 음악 신호 특성과 더불어 노래 가사와 소셜 네트워크 상에서의 사용자 평가 등을 함께 고려하는 멀티 모달 음악 무드 분류 기법을 제안한다. 이를 위해, 우선 음악 신호 특성에 대해 퍼지 추론 기반의 음악 무드 추출 기법을 적용하여 다수의 가능한 음악 무드를 추출한다. 다음으로 음악 가사에 대해 TF-IDF 기법을 적용하여 대표 감정 키워드를 추출하고 학습시킨 가사 무드 분류기를 사용하여 가사 음악 무드를 추출한다. 마지막으로 소셜 네트워크 상에서의 사용자 태그 등 사용자 피드백을 통한 음악 무드를 추출한다. 특정 음악에 대해 이러한 다양한 경로를 통한 음악 무드를 교차 분석하여 최종적으로 음악 무드를 결정한다. 음악 분류를 기반한 자동 음악 추천을 수행하는 사용자 만족도 평가 실험을 통해서 제안하는 기법의 효율성을 검증한다.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.415-418
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• 1996

Etching Process, one of the most important process in semiconductor fabrication, has input control part of which components are pressure, gas flow, RF power and etc., and plasma gas which is complex and not exactly understood is used to etch wafer in etching chamber. So this process has not real-time feedback controller based on input-output relation, then it uses EPD(End Point Detection) signal to determine when to start or when to stop etching. Various type EPD controller control etching process using EPD signal obtained from optical intensity of etching chamber. In development EPD controller we concentrate on compensation of this signal intensity and setting the relative signal magnitude at first of etching. We compensate signal intensity using neural network learning method and set the relative signal magnitude using fuzzy inference method. Potential of this method which improves EPD system capability is proved by experiences.