• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.201-204
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• 2007

In this paper, we research the content-based analysis and classification according to the composition of the feature parameters pool for the auditory signals to implement the auditory indexing and searching system. Auditory data is classified to the primitive various auditory types. we described the analysis and feature extraction method for the feature parameters available to the auditory data classification. And we compose the feature parameters pool in the indexing group unit, then compare and analysis the auditory data centering around the including level and indexing criterion into the audio categories. Based on this result, we composit feature vectors of audio data according to the classification categories, then experiment the classification using discrimination function.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.491-498
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• 2001

IN this Paper we propose an encryption algorithm for security in data communication. this algorithm acts encryption operation after the compression of data in order to reduce the transmission time and storage an encryption key is generated by using a parameter. as soon as key value is generated the parameter is transmitted and key is recreated every 26 times of parameter changing. the random number which is a constituent unit of encryption key is stored in a table the table is reorganized when the key is generated 40 times in order to intensity the security of encryption key. the encryption of data is made through the operation process of the generated key and sour data and the decryption performs the revers operation of encryption after getting decryption key by searching the transmitted parameter. as this algorithm is performed lastly it is possible to be used in practice.

• Journal of the Korea Society for Simulation
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• v.18 no.2
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• pp.49-55
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• 2009

In this paper, we investigate an optimal allocation of constant service resources in stochastic system to optimize the expected performance of interest. For this purpose, we use the control variates to estimate the gradients of expected performance with respect to given resource parameters, and apply these estimated gradients in stochastic optimization algorithm to find the optimal allocation of resources. The proposed gradient estimation method is advantageous in that it uses simulation results of a single design point without increasing the number of design points in simulation experiments and does not need to describe the logical relationship among realized performance of interest and perturbations in input parameters. We consider the applications of this research to various models and extension of input parameter space as the future research.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.5
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• pp.39-50
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• 2017

Moving object tracking techniques can be considered as one of the most essential technique in the video understanding of which the importance is much more emphasized recently. However, irregularity of light condition in the video, variations in shape and size of object, camera motion, and occlusion make it difficult to tracking moving object in the video. Swarm based methods are developed to improve the performance of Kalman filter and particle filter which are known as the most representative conventional methods, but these methods also need to consider dynamic property of moving object. This paper proposes adaptive parameter control method which can dynamically change weight value among parameters in particle swarm optimization. The proposed method classifies each particle to 3 groups, and assigns different weight values to improve object tracking performance. Experimental results show that our scheme shows considerable improvement of performance in tracking objects which have nonlinear movements such as occlusion or unexpected movement.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.4
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• pp.21-28
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• 2004

This paper presents a direct multivariable self-tuning controller using neural network which adapts to the changing parameters of the higher order multivariable nonlinear system with nonminimum phase behavior, mutual interactions and time delays. The nonlinearities are assumed to be globally bounded, and a multivariable nonlinear system is divided linear part and nonlinear part. The neural network is used to estimate the controller parameters, and the control output is obtained through estimated controller parameter. In order to demonstrate the effectiveness of the proposed algorithm the computer simulation is done to adapt the multivariable nonlinear nonminimm phase system with time delays and changed system parameter after a constant time. The proposed method compared with direct multivariable adaptive controller using neural network.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.383-384
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• 2012

• Journal of the Korean Society of Marine Environment & Safety
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• v.13 no.2 s.29
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• pp.161-167
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• 2007

The goal of this paper is to develop the speech recognition system which can control the ship's auto pilot. The feature parameters predicting the speaker's intention was extracted from the sample wheel orders written in SMCP(IMO Standard Marine Communication Phrases). And we designed the post-recognition procedure based on the parameters which could make a final decision from the list of candidate words. To evaluate the effectiveness of these parameters and the procedure, the basic experiment was conducted with total 525 wheel orders. From the experimental results, the proposed pattern recognition procedure has enhanced about 42.3% over the pre-recognition procedure.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.4
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• pp.1-7
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• 2003

습공기에 포함된 수증기가 상(Phase)변화를 일으킬 때 잠열이 발생하고 이 잠열은 익형 주위의 압축성 유동 상태량들을 변화시키므로, 이러한 열 증가가 유동에 끼치는 영향에 대하여 수치해석을 통하여 연구 수행하였다. 수치해석은 Rusak 과 Lee [1]가 최근에 연구 수행한 미교란 방법(small-disturbance approach)에 근거하여 이루어졌다. 고전적 핵 생성 모델과 작은 물방울 성장(droplet growth)모델을 이용한 이 방법에서는 비평형 균질 응축과정에서 일어나는 열 방출을 묘사한다. 응축에 의한 열전달, 압축성 유동의 운동에너지, 그리고 유동의 열적 상태량들 사이에서 일어나는 비선형 상호영향을 조사하고, 또한 주어진 문제를 지배가호 있는 상사 파라미터들을 제시하였다. 계산 결과들은 Euler 방정식을 사용하여 얻은 선행 수치계산들과 비교하여 잘 일치됨을 보였다. 상사법칙은 유동 동역학과 응축 상태량들이 상당히 비슷하게 거동하는 다양한 유동 형태들을 제안한다. 압축성 습공기 유동은 유체기계에 사용되는 익형들의 공력 성능을 증가시키는데 응용될 수 있다.

• Electronics and Telecommunications Trends
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• v.29 no.6
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• pp.71-81
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• 2014

5G 무선통신시스템은 동일한 영역에서 스펙트럼 사용 효율성을 개선하기 위해 매크로셀과 소형셀이 공존하는 이종 네트워크(HetNet: Heterogeneous Network) 형태로 진화하고 있으며, 급증하는 모바일 트래픽을 효율적으로 처리하기 위해 소형셀들을 고밀도 네트워크(High dense network)로 구축하는 방안이 연구되고 있다. 매크로셀과 고밀도 소형셀들이 중첩되어 구축되는 HetNet 기반 셀룰러 네트워크에서 소형셀 시스템의 구성과 파라미터 최적화를 통한 성능 유지를 운영자가 수동으로 조정하는 것은 한계가 있으므로 네트워크 환경변화에 따라 시스템에서 자율적으로 파라미터를 조정하여 시스템 성능을 유지하는 기술이 요구되고 있다. 본고에서는 시스템 운용 중 자율적인 최적화를 통해 시스템 성능을 최적으로 유지하고 유지비용을 최소화하는 3GPP 자율적 네트워크 최적화 기술을 소개한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.269-272
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• 2004

본 논문은 비선형 시스템의 퍼지모델을 위해 정보 granules 기반 퍼지 추론 시스템의 새로운 설계 및 이의 최적화를 제시한다. 퍼지모델은 주로 경험적 방법에 의해 추출되기 때문에 보다 구체적이고 체계적인 방법에 의한 동정 및 최적화 될 필요성이 요구된다. 일반적으로, 정보 granules는 근접성, 유사성 또는 기능성 둥에 인하여 서로 결합되는 요소(특히, 수치 데이터)의 실체이다. 제안된 퍼지 모델은 정보 데이터의 특성을 살리기 위해 HCM 클러스터링 방법에 의해 전반부/후반부 구조 및 파라미터 동정을 시행한다. 두 가지 형태의 퍼지 추론 방법은 간략 추론과 선형추론에 의해 수행되며 삼각형 멤버쉽 함수를 사용한다. 구축된 정보 granule 기반 퍼지 모델은 유전자 알고리즘을 이용하여 전반부 파라미터를 최적으로 동정한다. 제안된 비선형 모델의 성능평가는 수치적인 예를 통해 비교 평가한다.