• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.653-662
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• 1989

Cerebellar Model Arithmetic Controller (CMAC) has been introduced as an adaptive control function generator. CMAC computes control functions referring to a distributed memory table storing functional values rather than by solving equations analytically or numerically. CMAC has a unique mapping structure as a coarse coding and supervisory delta-rule learning property. In this paper, learning aspects and a convergence of the CMAC were investigated. The efficient training algorithms were developed to overcome the limitations caused by the conventional maximum error correction training and to eliminate the accumulated learning error caused by a sequential node training. A nonlinear function generator and a motion generator for a two d.o.f. manipulator were simulated. The efficiency of the various learning algorithms was demonstrated through the cpu time used and the convergence of the rms and maximum errors accumulated during a learning process. A generalization property and a learning effect due to the various gains were simulated. A uniform quantizing method was applied to cope with various ranges of input variables efficiently.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.728-731
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• 1997

This paper proposes the systematic auto-tuning method for fuzzy controller using genetic algorithm(GA). In general, the design of fuzzy logic controller has difficulties in the acquisition of expert's knowledge and relies to a great extent on heuristic knowledge which, in many cases, cannot be objectively justified. So, the performance of the controller can be degraded in the case of plant parameter variations or unpredictable incident which the designer may have ignored. Proposed genetic algorithm searches the optimal rule structure, parameters of membership functions and scaling factors simultaneously and automatically by a new genetic coding format. Inverted pendrum system is provided to show the advantages of the proposed method.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.390-393
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• 1997

Fuzzy logic and neural networks are complemetary technologies in the design of intelligent system. Fuzzy neural network(FNN) as an auto-tuning method is actually known to an excellent method for the adjustment of the fuzzy rule. However, this has a weak point, because the convergence to the optimum depends on the initial condition. In this paper we develop a coding format to determine a FNN model by chromosome in GA and present systematic approach to identify the parameters and structure of FNN. The proposed hybrid tuning method realizes to construct minimal and optimal structure of the fuzzy mode simultaneously and automatically. This paper shows effectiveness of the tuning system by simulations compared with conventional methods.

• 한국기계연구소 소보
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• s.19
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• pp.93-115
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• 1989

Cerebellar Model Arithmetic Controller(CMAC) has been introduced as an adaptive control function generator. CMAC computes control functions referring to a distributed memory table storing functional values rather than by solving equations analytically or numerically. CMAC has a unique mapping structure as a coarse coding and supervisory delta-rule learning property. In this paper, learning aspects and a convergence of the CMAC were investigated. The efficient training algorithms were developed to overcome the limitations caused by the conventional maximum error correction training and to eliminate the accumulated learning error caused by a sequential node training. A nonlinear function generator and a motion generator for a two d. o. f. manipulator were simulated. The efficiency of the various learning algorithms was demonstrated through the cpu time used and the convergence of the rms and maximum errors accumulated during a learning process; A generalization property and a learning effect due to the various gains were simulated. A uniform quantizing method was applied to cope with various ranges of input variables efficiently.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.05
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• pp.49-53
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• 1995

In this paper, we classify between the chromosome and blood cell, and find the location of chromosome. First, the gray level images be the binary images using the threshold method. Then, the spot noises are removed by the morphological filtering. Features are obtained using the updated Run length(RL) coding and are classified using the Bayes decision rule. The performances of classification are 83.3% in chromosome and 93.3% in blood cell. Because each sub-images ($256{\times}256$) is obtained from the full image($512{\times}512$), we realize the location of chromosome if we get the corrected chromosome classifications.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.244-247
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• 2010

최근 Application 의 취약성을 악용한 해커들의 시스템 공격 사례가 증가하고 있다. 본 논문에서 다루는 코드 분석기는 이러한 해커의 공격을 사전에 차단하기 위해 사용자로부터 입력받은 Application 의 소스 코드가 사전에 탑재해 놓은 일련의 보안 규칙(Security Rule)을 제대로 준수하는지의 여부를 어휘 분석(Lexical Analysis)과 구문 분석(Semantic Analysis)을 통해 판별해 낸다. 본 코드 분석기는 미국 카네기멜론대학(CMU) 산하의 인터넷 해킹 보안 기구인 CERT 에서 제시하는 규칙을 그대로 적용하여 분석 결과의 정확도와 객관성을 높였으며, 이 분석기를 통해 프로그래머가 신뢰도와 보안성이 높은 소프트웨어를 개발할 수 있도록 하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.7
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• pp.1017-1023
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• 2013

Datacommunications transmit the source codes that are coded in information devices, such as computer to the transmission line by means of the line coded signal. AMI method is applied to the line coding method to transmit the signal for long distance. The disadvantage of the AMI method is to loss the bit synchronization when consecutive binary bit '0' over 4ea is coming into line coder. The scrambling technique is used to overcome the problem. The HDB-3 scrambling method is used in Korea standard which standard in ITU-T. When the HDB-3 technology is used. the method should convert the consecutive bit '0' over 4ea to certain bits format. As a result, when there are many such kind of '0' bit stream in source codes, data transmission efficiency will be decreased to treat in line coder, etc. This paper is directed to study the Roman character code system in $KS{\times}1001$, Korea standard for information exchange code in datacommunication systems. Based on the study result, this paper proposed the maximum optimized Roman character code system. In the study, Character coding rule for $4{\times}4$bits and the statistical data for roman character using frequency were considered to simulate. The paper shows the result that when the proposed new roman character coding system is applied to use, the data transmission efficiency could be increased to about 134% compared to existing code system.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.4
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• pp.761-776
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• 2012

This paper proposes the revised Roman character code system using Unicode 3.0. The background of the paper is whether the Latin character code system th using in the world in Unicode V.3 is proper or not in the side of the transmission efficiency in data communications. In data communications, when the consecutive 4 bits or 8 bits of "0" bit from the information devices input into the line coder, its consecutive "0" bits are scrambled to the predetermined bit patterns to avoid the syncronization loss. The paper was based on the statistical data for the using frequency of the alphabet letter and the proposed rule for characters coding in [1]. The paper was focused to improve of Unicode itself and UTF-8 code system. As a result of the paper, when the proposed coding systems for Latin character in Unicode 3.0 itself and UTF-8 code system, the scrambler efficiency using HDB-3 in the line coder of the data transmission system could be improved about 3645 ~ 31400% and 480 ~ 1700% respectively.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.37-44
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• 2001

This paper describes the modeling of work environment for the extraction of abstract operation rules for cooperative work with multiple agent. We propose the modeling method using a potential field. In the method, it is applied to a box pushing problem, which is to move a box from a start to a goal b multiple agent. The agents follow the potential value when they move and work in the work environment. The work environment is represented as the grid space. The potential field is generated by Genetic Algorithm(GA) for each agent. GA explores the positions of a potential peak value in the grid space, and then the potential value stretching in the grid space is spread by a potential diffusion function in each grid. However it is difficult to explore suitable setting using hand coding of the position of peak potential value. Thus, we use an evlolutionary computation way because it is possible to explore the large search space. So we make experiments the environment modeling using the proposed method and verify the performance of the exploration by GA. And we classify some types from acquired the environment model and extract the abstract operation rule, As results, we find out some types of the environment models and operation rules by the observation, and the performance of GA exploration is almost same as the hand coding set because these are nearly same performance on the evaluation of the consumption of agent's energy and the work step from point to the goal point.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.227-247
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• 2018

For intermittently connected wireless sensor networks deployed in hash environments, sensor nodes may fail due to internal or external reasons at any time. In the process of data collection and recovery, we need to speed up as much as possible so that all the sensory data can be restored by accessing as few survivors as possible. In this paper a novel redundant data storage algorithm based on minimum spanning tree and quasi-randomized matrix-QRNCDS is proposed. QRNCDS disseminates k source data packets to n sensor nodes in the network (n>k) according to the minimum spanning tree traversal mechanism. Every node stores only one encoded data packet in its storage which is the XOR result of the received source data packets in accordance with the quasi-randomized matrix theory. The algorithm adopts the minimum spanning tree traversal rule to reduce the complexity of the traversal message of the source packets. In order to solve the problem that some source packets cannot be restored if the random matrix is not full column rank, the semi-randomized network coding method is used in QRNCDS. Each source node only needs to store its own source data packet, and the storage nodes choose to receive or not. In the decoding phase, Gaussian Elimination and Belief Propagation are combined to improve the probability and efficiency of data decoding. As a result, part of the source data can be recovered in the case of semi-random matrix without full column rank. The simulation results show that QRNCDS has lower energy consumption, higher data collection efficiency, higher decoding efficiency, smaller data storage redundancy and larger network fault tolerance.