• 기술혁신연구
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• 제7권2호
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• pp.21-36
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• 1999

This paper presents a R&D investment model for Information and telecommunications (I&T) technology, which can be used by group decision makers, using multiple objective linear programming (MOLP). The MOLP model involves the simultaneous maximization of three linear objective functions associated with three criteria, which are social, technological, and economic criterion. This model is different from the traditional one which only involves the maximization of economic criterion. The presented problem in this model can be formulated as a problem of optimizing a linear function over an efficient set of MOLP. Its application to the National R&D Project in I&T Industry is also presented. In this application, the Analytic Hierarchy Process (AHP) is proposed to estimate the weights, which are used as the coefficients in each objective function of the MOLP model and in a linear decision function. By solving this problem, it yields a suitable R&D investment ratio to each technology field. It is showed that the MOLP model can be useful decision aid in formulating R&D investment plan in I&T industry which needs to be decided by group decision makers, not by an individual. It is expected that the MOLP model works as the basis for planning R&D investment strategy in I&T industry.

• IEIE Transactions on Smart Processing and Computing
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• 제6권1호
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• pp.18-20
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• 2017

In this paper, we propose a new classification method to complement a $na{\ddot{i}}ve$ Bayesian classifier. This classifier assumes data distribution to be Gaussian, finds the discriminant function, and derives the decision curve. However, this method does not investigate finding the decision curve in much detail, and there are some minor problems that arise in finding an accurate discriminant function. Our findings also show that this method could produce errors when finding the decision curve. The aim of this study has therefore been to investigate existing problems and suggest a more reliable classification method. To do this, we utilize the gradient to find the decision curve. We then compare/analyze our algorithm with the $na{\ddot{i}}ve$ Bayesian method. Performance evaluation indicates that the average accuracy of our classification method is about 10% higher than $na{\ddot{i}}ve$ Bayes.

• 디지털산업정보학회논문지
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• 제7권1호
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• pp.111-125
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• 2011

Smartphone is becoming as a core device of mobile environment. The purpose of this study is to investigate the factors affecting customer's buying decision on smartphone. Based on prior studies and cases, this study identifies network effect, switching cost, function, design, brand, after service, price as affecting factors of customer's buying decision on smartphone. It also aims to investigate the relationship between network effect/switching cost and re-purchasing. Result shows that network effect brand, after service are significantly related to customer's buying decision on smartphone by device types, but switching cost, function, design, price are not. Network effect also was found to be significantly related to the re-purchasing. The result of this study may provide a guideline of supply strategy with smartphone suppliers.

• 한국정보통신학회논문지
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• 제19권8호
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• pp.1765-1772
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• 2015

수중음향통신 채널은 다중 경로 전달이 주요 장애 요인이 되며, 일반적으로 이러한 문제점을 극복하기 위해 등화기가 적용된다. 본 논문에서는 결정 궤환 등화기의 탭 길이를 유전자 알고리즘을 통해 최적화하는 방법을 제안하였다. 유전자 알고리즘의 유전 정보를 전방향 필터와 후방향 필터의 길이로 입력받은 후, 목적함수에 따라 훈련 신호 구간에서의 BER(bit error rate)을 계산하여 필터 길이를 최적화한다. 목적함수는 결정 궤환 등화기, BER 계산으로 설정되었다. 실험 결과, 수심 25 m에 배치된 수신기에 수신된 신호에 훈련 신호만을 이용하였을 때, BER이 0.0355로 나타났다. 모든 데이터를 목적함수 내의 BER계산에 이용하였을 때, BER이 0.0215로 나타났다.

• 산업경영시스템학회지
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• 제6권9호
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• pp.111-124
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• 1983

The basic model of decision problem the enterprise is conforonted with includes the following 3 elements ; 1) Elements that can not be controlled by the decision maker : In the thesis elements are named environmental variables, and varied itself according to the change of environmental condition. 2) Elements that can be controlled by the decision maker ; These elements are called decision elements in the thesis and variable according to the event. 3) object of decision making : The degree of achievement to the object is identified by taking various criteria- The index indicating the degree of achievement to the object whatever criterion is applied is called object function in the thesis. It's the fanetion of environmental variable, decision variable and object function. The relation between them brings forth the relation formula that characterize the each problem. The basic types of decision making model use in the thesis are as following ; 1) The problem of decision making under conditions of certainty. 2) The problem of decision making under conditions of risk. 3) The problem of decision making under conditions of uncertainty. 4) The problem of decision making under competitive condition. in general case that the Profit of two decision makers varies, what we regard the decision that make the sum of profit of two men maximum as the best choice for two men has a reasonability in certain case. When the sum of profit two men is zero, by taking toe promise that ail of them art according to the min-max criteria and by extending the object of choice to the mixed strategy. We certify the existance of equilibrium solution and admit them as the best solution of competitive model in general.

• 대한안전경영과학회:학술대회논문집
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• 대한안전경영과학회 2003년도 춘계학술대회
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• pp.1-5
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• 2003

We purpose a decision model to select the optimal facilities for the Decision Making problems with multiple characteristics(nominal-is-best characteristics, larger-is -better characteristics, smaller- is -better characteristics). Using this model, concept of the loss function is used in this comprehensive method of for select the optimal preferred facilities. To solve the issue on the optimal preferred facilities for multiple characteristics, this study propose the loss function with cross-product terms among the characteristics and derived range of the coefficients of the terms.

• 한국통신학회논문지
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• 제22권9호
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• pp.2035-2042
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• 1997

비동기 부호 분할 다중 접속(Code Division Multiple Access: CDMA) 시스템을 위한 다단(mutistage) 간섭 제거 검출기의 매 단에서 기존에 사용되어 온 경판정(hard decision)을 대신할 수 있는 연판정(soft decision) 함수의 설계를 고려한다. 특히, 평균 제곱 오류(mean square error: MSE)의 관점에서 최적인 시그모이드(sigmoid) 함수와 구현시 복잡도를 줄이면서 시그모이드 함수를 가장 잘 근사화하는 다단계 양자화기(multu-level quantizer)들을 유도한다. 다단 검출기의 매 단에서 이들 판정 함수들의 변수는 산출된 입력 특성에 의해 조정된다. 컴퓨터 모의 실험을 통하여 이들 연판정 함수를 갖는 다단 검출기가 경판정을 사용하는 경우보다 현저하게 성능을 향상시킴을 보인다.

• Journal of the Optical Society of Korea
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• 제18권4호
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• pp.317-329
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• 2014

In vision measurement systems based on structured light, the key point of detection precision is to determine accurately the central position of the projected laser line in the image. The purpose of this research is to extract laser line centers based on a decision function generated to distinguish the real centers from candidate points with a high recognition rate. First, preprocessing of an image adopting a difference image method is conducted to realize image segmentation of the laser line. Second, the feature points in an integral pixel level are selected as the initiating light line centers by the eigenvalues of the Hessian matrix. Third, according to the light intensity distribution of a laser line obeying a Gaussian distribution in transverse section and a constant distribution in longitudinal section, a normalized model of Hessian matrix eigenvalues for the candidate centers of the laser line is presented to balance reasonably the two eigenvalues that indicate the variation tendencies of the second-order partial derivatives of the Gaussian function and constant function, respectively. The proposed model integrates a Gaussian recognition function and a sinusoidal recognition function. The Gaussian recognition function estimates the characteristic that one eigenvalue approaches zero, and enhances the sensitivity of the decision function to that characteristic, which corresponds to the longitudinal direction of the laser line. The sinusoidal recognition function evaluates the feature that the other eigenvalue is negative with a large absolute value, making the decision function more sensitive to that feature, which is related to the transverse direction of the laser line. In the proposed model the decision function is weighted for higher values to the real centers synthetically, considering the properties in the longitudinal and transverse directions of the laser line. Moreover, this method provides a decision value from 0 to 1 for arbitrary candidate centers, which yields a normalized measure for different laser lines in different images. The normalized results of pixels close to 1 are determined to be the real centers by progressive scanning of the image columns. Finally, the zero point of a second-order Taylor expansion in the eigenvector's direction is employed to refine further the extraction results of the central points at the subpixel level. The experimental results show that the method based on this normalization model accurately extracts the coordinates of laser line centers and obtains a higher recognition rate in two group experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4549-4567
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• 2016

To cope with the complex electromagnetic environment of wireless communication systems, anti-jamming decision methods are necessary to keep the reliability of communication. Basing on the rule-reduced genetic algorithm (RRGA), an anti-jamming decision method is proposed in this paper to adapt to the fast channel variations. Firstly, the reduced decision rules are obtained according to the rough set (RS) theory. Secondly, the randomly generated initial population of the genetic algorithm (GA) is screened and the individuals are preserved in accordance with the reduced decision rules. Finally, the initial population after screening is utilized in the genetic algorithm to optimize the communication parameters. In order to remove the dependency on the weights, this paper deploys an anti-jamming decision objective function, which aims at maximizing the normalized transmission rate under the constraints of minimizing the normalized transmitting power with the pre-defined bit error rate (BER). Simulations are carried out to verify the performance of both the traditional genetic algorithm and the adaptive genetic algorithm. Simulation results show that the convergence rates of the two algorithms increase significantly thanks to the initial population determined by the reduced-rules, without losing the accuracy of the decision-making. Meanwhile, the weight-independent objective function makes the algorithm more practical than the traditional methods.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1987년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 16-17 Oct. 1987
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• pp.694-698
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• 1987

In this paper, the primitive and double combined motion classification of the arm is discussed using pattern recognition of EM signal. The EM signals are detected from Ag-Ag/Cl surface electrodes, and IBM PC, calculated the Likelyhood probability and the decision function on the feature space of integral absolute value. Multiclass decision rule is introduced for higher decision rate. On our experimental results from expert simulator, the decision rate of more than 78% can be obtained.