• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.6
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• pp.191-196
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• 2004

The measurement method is proposed for performance-evaluation of bus system in this paper. The cycle tin in manufacturing system that sensor and actuator play on the role is important factor for performance-evaluation. In order to measure cycle time, proposed method is based on simple algorithm. But it must consider delay elements in PLC and it's peripheral. The test of the cycle time is divided into the best case and the worst case and parameters are set corresponding to two cases for the improvement of measurement result It is shown that the proposed method is efficient by measuring the cycle time of the fieldbus basing on the mathematics model. As a result, due to simplicity and convenience of proposed method, the engineering cost and time demanding for test of cycling time can much reduce.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.5
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• pp.429-432
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• 2004

In this paper, we propose a new sorting algorithm for ATM switch with a shared buffer which has a sequencer architecture with single queue. The proposed switch performs a sorting procedure of ATM cell based on the output port number of ATM cell with hardware implementation. The proposed architecture has a single buffer physically but logically it has function of multi-queue which is designed at most to control the conflicts in output port. In the future, this architecture will take various applications for routing switch and has flexibility for the extension of system structure. therefore, this structure is expected on good structure in effective transmission.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.4
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• pp.826-832
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• 2007

A recurrent neural network has been frequently used in equalizing the channel for fast communication systems. The existing techniques, however, have mainly dealt with time-invariant chamois. The modern environments of communication systems such as mobile ones have the time-varying feature due to fading. In this paper, powerful decision feedback - recurrent neural network is used as channel equalizer for nonlinear and time-varying system, and two kinds of algorithms, such as extended Kalman filter (EKF) and sigma-point Kalman filter (SPKF), are proposed; EKF is for fast convergence and good tracing function, and SPKF for overcoming the problems which can be developed during the process of first linearization for nonlinear system EKF.

• Proceedings of the CALSEC Conference
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• 2001.08a
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• pp.457-465
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• 2001

■ 필요성 1. 교통 혼잡으로 인한 물류비 상승으로 국가 경쟁력 약화 2. 기존 최단경로 알고리즘(Dijkstra, Floyd-Warshall 등)의 한계 3. 대규모 네트워크(NP-hard문제)→정보 사용자가 제시하는 시간 내에 정보를 제공 필요 4. 교통 제약(회전금지, U턴, U턴 금지, P-턴) → 실제 교통 상황과 순환 노드 고려가 필요 ■목적 1. 교통제약을 포함한 대규모 교통네트워크에서 실시간 교통정보를 바탕으로 제한된 시간 내에 차별화 된 다수 최적경로 산출 함 2. 유전자알고리즘(GA)을 적용한 동적경로안내시스템 개발(중략)

• Journal of Industrial Convergence
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• v.20 no.4
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• pp.23-30
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• 2022

Recently, with the development of artificial intelligence (AI) and deep learning, the importance of conversational artificial intelligence chatbots is being highlighted. In addition, chatbot research is being conducted in various fields. To build a chatbot, it is developed using an open source platform or a commercial platform for ease of development. These chatbot platforms mainly use RNN and application algorithms. The RNN algorithm has the advantages of fast learning speed, ease of monitoring and verification, and good inference performance. In this paper, a method for improving the inference performance of RNNs and applied algorithms was studied. The proposed method used the word group expansion learning technique of key words for each sentence when RNN and applied algorithm were applied. As a result of this study, the RNN, GRU, and LSTM three algorithms with a cyclic structure achieved a minimum of 0.37% and a maximum of 1.25% inference performance improvement. The research results obtained through this study can accelerate the adoption of artificial intelligence chatbots in related industries. In addition, it can contribute to utilizing various RNN application algorithms. In future research, it will be necessary to study the effect of various activation functions on the performance improvement of artificial neural network algorithms.

• Journal of Korea Multimedia Society
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• v.2 no.4
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• pp.468-475
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• 1999

Learning algorithm of SRNN doesn't use analytic maximum epoch, so that its performance is inefficient and its cost is high. In this paper, with the proper maximum epoch, we improve teaming efficiency. We first describe cost function of maximum epoch and computation time theoretically Then, using it, we propose that maximum epoch must be between 400 and 500. Estimated maximum epoch is verified by experiment.

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.83-90
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• 2004

In this paper, we study the CCD(Clustering with Circular Distance) and the COD(Clustering with Obstructed Distance) problems to be considered when objects are being clustered in a circularly search space and a search space with the presence of obstacles. We also propose a now clustering algorithm for clustering efficiently objects that the insertion or the deletion is occurring frequently in multi-dimensional search space. The distance function for solving the CCD and COD Problems is defined in the Proposed clustering algorithm. This algorithm is included a clustering method to create clusters that have a high spatial locality by minimum computation time.

• Proceedings of the KIPE Conference
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• 2015.11a
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• pp.59-60
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• 2015

본 논문에서는 직류송전 적용을 위해 전력계통과 연계된 모듈형 멀터레벨 컨버터(Modular Multi-level Converter)의 유 무효 전력제어에 대해 시뮬레이션 모델을 개발하고 그 특성을 분석하였다. 분석에 고려한 모듈형 멀티레벨 컨버터는 한 암당 12개의 서브모듈로 구성되어 있고 모듈레이션은 NLC (Nearest Level Control) 방식을 사용한다. 또한 DC 커패시터의 밸런싱은 버블소팅 방식을 적용하였고 순환전류를 억제하는 알고리즘을 고려하였다. 시뮬레이션을 통해 분석한 유 무효전류제어를 실험적으로 검증하기 위해 10kVA DC 1000V 하드웨어 축소모형을 제작하고 실험을 실시하였다. 실험결과는 시뮬레이션 결과와 일치함을 확인할 수 있었다. 향후에는 교류전압 불평형 보상과 순환전류 제어, 컨버터 보호에 대한 다양한 알고리즘을 도출할 예정이다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.39
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• pp.193-204
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• 1996

본 연구는 FMC(Flexible Manufacturing Cell)에 있어 상호 간섭이 없는 부품의 흐름을 제어하기 위한 교착제거방법(Deadlock Avoidance Method)에 대한 제안으로서, 이 방법이 주요한 장점은 첫째, FMC의 환경을 쉽게 적용시킬 수 있고 둘째, 공정상의 부품에 대한 dispatching 모듈이 협력하도록 설계되어 있다는 것이다. 교착제거방법은 두 개의 모듈로 구성되어 있는데 이는 순환발견알고리즘(A Cycle Detection Algorithm)과 원료주문 정책으로서, 특이할 만한 사항은 순환발견알고리즘을 채용하더라도 원료주문정책이 잘못될 수 있기 때문에 교착제거방법에 있어서 원료주문정책은 매우 중요하다는 것이다. 이를 위하여 교착전의 N-step 교착을 제거하고, 발견할 수 있는 교착제거방법과 N-step의 사전주무정책을 제시하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.592-595
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• 2021

양자 알고리즘인 그루버나 쇼어 알고리즘에 의해 현존하는 암호 체계들이 무너질 수 있으며, 블록체인 네트워크를 기반으로 타원곡선 암호 및 타원곡선 전자서명을 사용하는 암호화폐의 안전성 또한 위협받고 있다. 따라서 암호화폐에도 양자 컴퓨터에 대한 대응책이 필요하다. 본 논문에서는 시계열 예측에 적합한 순환형 신경망을 활용하여 양자 저항성을 가지는 암호화폐들의 가격을 예측하고 분석한다. 데이터가 부족하였으나 학습 결과 0.005 이하의 손실을 달성하였으며, 최근 15일의 데이터를 통해 예측한 결과, 모두 소폭 상승할 것으로 나타났다. 향후에는 더 많은 데이터를 통해 더 정확한 예측이 가능한 신경망을 설계하고 다양한 양자 관련 이슈들을 참고하여 분석을 수행하고자 한다.