• 산업경영시스템학회지
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• 제41권1호
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• pp.110-117
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• 2018

Machines and facilities are physically or chemically degenerated by continuous usage. One of the results of this degeneration is the process mean shift. By the result of degeneration, non-conforming products and malfunction of machine occur. Therefore a periodic preventive resetting the process is necessary. This type of preventive action is called 'preventive maintenance policy.' Preventive maintenance presupposes that the preventive (resetting the process) cost is smaller than the cost of failure caused by the malfunction of machine. The process mean shift problem is a field of preventive maintenance. This field deals the interrelationship between the quality cost and the process resetting cost before machine breaks down. Quality cost is the sum of the non-conforming item cost and quality loss cost. Quality loss cost is due to the deviation between the quality characteristics from the target value. Under the process mean shift, the quality cost is increasing continuously whereas the process resetting cost is constant value. The objective function is total costs per unit wear, the decision variables are the wear limit (resetting period) and the initial process mean. Comparing the previous studies, we set the process variance as an increasing concave function and set the quality loss function as Cpm+ simultaneously. In the Cpm+, loss function has different cost coefficients according to the direction of the quality characteristics from target value. A numerical example is presented.

• 전기학회논문지
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• 제61권5호
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• pp.757-762
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• 2012

In this paper, the multi feature extraction algorithm for estimation of wrist movements based on Electromyogram(EMG) is proposed. For the extraction of precise features from the EMG signals, the difference absolute mean value(DAMV), the mean absolute value(MAV), the root mean square(RMS) and the difference absolute standard deviation value(DASDV) to consider amplitude characteristic of EMG signals are used. We figure out a more accurate feature-set by combination of two features out of these, because of multi feature extraction algorithm is more precise than single feature method. Also, for the motion classification based on EMG, the linear discriminant analysis(LDA), the quadratic discriminant analysis(QDA) and k-nearest neighbor(k-NN) are used. We implemented a test targeting twenty adult male to identify the accuracy of EMG pattern classification of wrist movements such as up, down, right, left and rest. As a result of our study, the LDA, QDA and k-NN classification method using feature-set with MAV and DASDV showed respectively 87.59%, 89.06%, 91.75% accuracy.

• 제어로봇시스템학회논문지
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• 제10권9호
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• pp.847-854
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• 2004

In this paper, It is studied to control and to monitor the remote system state using HTTP(Hyper Text Transfer Protocol) object communication. The remote control system is controlled by using a web browser or a application program. This system is organized by three different part depending on functionality-server part, client part, controller part. The java technology is used to composite the server part and the client part and C language is used for a controller. The server part is waiting for the request of client part and then the request is reached, the server part saves client data to the database and send a command set to the client part. The administrator can control the remote system just using a web browser. Remote part is worked by timer that is activated per 1 second. It gets the measurement data of the controller part, and then send the request to the server part and get a command set in the command repository of server part using the client ID. After interpreting the command set, the client part transfers the command set to the controller part. Controller part can be activated by the client part. If send command is transmitted by the client part, it sends sensor monitoring data to the client part and command set is transmitted then setting up the value of the controlled system.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2006년도 하계학술발표대회 논문집
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• pp.1043-1048
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• 2006

This paper aimed to verify and develop lighting design data for offices in Korea. It focused on a Korean standard office value relative to lighting density and the evaluation of lighting energy and cooling load. When planning indoor lighting design, we generally utilize the lighting density value which is set $14W/m^2$ by the ASHRAE/IES standard office value. However, the value is not appropriate to apply in Korea where higher efficiency lamps are more popular than others. For calculation of a proper lighting density of Korea, we analysed distribution curves of luminous intensity(2-lamp fluorescent lighting fixture with Parabolic) and derived the new lighting density $12.64W/m^2$ as Korea standard office value. In the simulation using this value, it was shown that lighting energy and cooling load could be reduced.

• Journal of the Korean Data and Information Science Society
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• 제25권1호
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• pp.255-261
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• 2014

Many studies have estimated a mixture of binomial distributions. This paper considers an extension, a mixture of shifted binomial distributions, and the estimation of the distribution. The range of each component binomial distribution is rst evaluated and then for each possible value of shifted parameters, the EM algorithm is employed to estimate those parameters. From a set of possible value of shifted parameters and corresponding estimated parameters of the distribution, the likelihood of given data is determined. The simulation results verify the performance of the proposed method.

• 한국정보시스템학회:학술대회논문집
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• 한국정보시스템학회 1996년도 추계학술발표회 발표논문집
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• pp.211-216
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• 1996

This paper propose a fuzzy regression method using fuzzy neural networks when a membership value is attached to each input-output pair. First, an architecture o fuzzy neural networks with fuzzy weights and fuzzy biases is shown. Next, a cost function is defined using the fuzzy output from the fuzzy neural network and the corresponding target output with a membership value. A learning algorithm is derived from the cost function. The derived learning algorithm trains the fuzzy neural network so 솜 t the level set of the fuzzy output includes the target output. Last, the proposed method is applied to the quality evaluation problem of injection molding

• Journal of applied mathematics & informatics
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• 제29권3_4호
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• pp.713-719
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• 2011

The problem of approximation from a set of scattered data arises in a wide range of applied mathematics and scientific applications. In this study, we present a quasi-interpolatory approximation scheme for scattered data approximation problem, which reproduces a certain space of polynomials. The proposed scheme is local in the sense that for an evaluation point, the contribution of a data value to the approximating value is decreasing rapidly as the distance between two data points is increasing.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 1996년도 추계 학술 발표회 발표논문집
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• pp.211-216
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• 1996

This paper propose a fuzzy regression method using fuzzy neural networks when a membership value is attached to each input-output pair. First, an architecture of fuzzy nerual networks with fuzzy weights and fuzzy biases is shown. Next a cost function is defined using the fuzzy output from the fuzzy neural network and the corresponding target output with a membership value.A learning algorithm is derived from the cost function. The derived learning algorithm trains the fuzzy neural network so that the level set of the fuzzy output includes the target output. Last, the proposed method is applied to the quality evaluation problem of injection molding.

• 정보보호학회논문지
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• 제28권5호
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• pp.1233-1246
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• 2018

스마트 모바일의 보급에 따라, 컴퓨터 보안에서 ARM 아키텍처 명령어로 구성된 위치 독립적 코드의 역어셈블리 기법이 중요해지고 있다. 그러나 대부분의 기존 기법들은 x86 아키텍처 대상으로 연구되었으며, 위치 종속적 코드의 문제 해결과 범용성에 초점이 맞추어져 있다. 따라서, ARM 아키텍처의 고정 길이 명령어와 위치 독립적 코드의 특징이 제대로 반영되지 않아, 바이너리 계측과 같이 바이너리 자체를 직접 수정하는 수준의 고도화된 응용 보안 기술에 적용하기에는 수집되는 주소 정보의 정확도가 낮다. 본 논문에서, 우리는 ARM 명령어로 구성된 위치 독립적인 코드의 특성을 반영한 역어셈블리 기법을 제안한다. 정확하고 추적 가능한 주소의 수집을 위해, 도메인이 기호화된 값-집합 분석을 설계하였다. 또한, 역어셈블의 주요 문제점을 해결하기 위해, 컴파일러가 생성하는 코드의 특징을 활용한 휴리스틱을 고안하였다. 우리 기법의 정확도와 유효성을 검증하기 위해, 안드로이드 8.1 빌드에 포함된 669개의 공유라이브러리 및 실행 파일을 대상으로 실험하였으며, 그 결과 완전한 역어셈블의 비율이 91.47%로 나왔다.

• 전기전자학회논문지
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• 제17권1호
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• pp.29-35
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• 2013

본 연구에서는 임의의 정렬되지 않은 점집합에서 정렬을 고려한 개선된 Convex Hull 알고리즘을 제안한다. 이 알고리즘은 Convex Hull의 극점 특성을 이용하여 처리 데이터를 한정하기 때문에 계산복잡도가 낮다. 각 단계마다 볼록 정점을 판별하는 조건을 이용하여 한 번의 스캔으로 완전한 Convex Set을 구한다. 알고리즘 초기에 점집합의 정렬이 필요한데, 이때 걸리는 시간이 알고리즘 전체 동작시간의 대부분을 차지하기 때문에 값과 인덱스를 대치하여 빠르게 정렬하였다. 일반적인 상황을 가정하여 랜덤한 점집합으로 알고리즘의 동작시간을 측정하였으며 기존의 알고리즘에 비해 약 두 배의 속도 향상이 있음을 확인하였다.