• 한국구조물진단유지관리공학회 논문집
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• 제6권2호
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• pp.145-155
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• 2002

It is essential for health monitoring of a cable-stayed bridge to provide more accurate and enough information from the sensors. In experimental modal testing, the chosen measurement locations and the number of measurements have a major influence on the quality of the results. The choice is often difficult for complex structures like a cable-stayed bridge. It is extremely important a cable-stayed bridge to minimize the number of sensing operations required to monitor the structural system. In order to obtain the desired accuracy for the structural test, several issues must take into consideration. Two important issues are the number and location of response sensors. There are usually several alternative locations where different sensors can be located. On the other hand, the number of sensors might be limited due to economic constraints. Therefore, techniques such as methodologies, algorithms etc., which address the issue of limited instrumentation and its effects on resolution and accuracy in health monitoring systems are paramount to a damage diagnosis approach. This paper discusses an optimum sensor placement criterion suitable to the identification of structural damage for continuous health monitoring. A Kinetic Energy optimization technique and an Effective Independence Method are analyzed and numerical and theoretical issues are addressed for a cable-stayed bridge. Its application to a cable-stayed bridge is discussed to optimize the sensor placement for identification and control purposes.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2016년도 춘계학술대회
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• pp.583-585
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• 2016

The recent advances in wireless networks area have led to new techniques, such as small cells or full-duplex (FD) transmission, have also been developed to further increase the network capacity. Particularly, full-duplex communication promises expected throughput gain by doubling the spectrum compared to half-duplex (HD) communication. Because this technique permits one set of frequencies to simultaneously transmit and receive signals. In this paper, we focus on the binary power control for the users and the base stations in full-duplex multiple cellulars wireless networks to obtain optimal sum-rate under the effect interference and noise. We investigate with a scenario in there one carrier is assigned to only one user in each cell and construct a model for this problem. In this work, we apply the binary power control by the its simplification in the implemented algorithm for both uplink and downlink simultaneously to maximize sum data rate of the system. At first, we realize the 2-cells case separately to check the optimal power allocation whether being binary. Then, we carry on with N-cells case in general through properties of binary power control.

• 한국전자통신학회논문지
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• 제15권4호
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• pp.651-658
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• 2020

5G 이동통신 네트워크에서, 상호작용 이동통신 게임 사용자들이 다수 늘어나고 있고, 이러한 사용자들은 상관 정보원으로 작용한다. 비직교 다중접속 기술은 5G 이동통신에서 중요한 기술로 고려되고 있다. 비직교 다중접속에서는, 사용자들이 채널 자원을 공유하기 때문에, 상관 정보원이 각각의 사용자의 BER 성능에 영향을 주며, 이러한 현상은 직교 다중접속에는 발생하지 않는다. 본 논문에서는 상관 정보원을 가진 비직교 다중접속에 대한 최적 수신기를 유도하고 각각의 사용자의 BER 성능에 상관 정보원의 영향을 고찰한다.

• Journal of Electrical Engineering and Technology
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• 제4권1호
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• pp.1-12
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• 2009

In recent years, integration of new distributed generation (DG) technology in distribution networks has become one of the major management concerns for professional engineers. This paper presents a dynamic methodology of optimal allocation and sizing of DG units for a given practical distribution network, so that the cost of active power can be minimized. The approach proposed is based on a combined Genetic/Fuzzy Rules. The genetic algorithm generates and optimizes combinations of distributed power generation for integration into the network in order to minimize power losses, and in second step simple fuzzy rules designs based upon practical expertise rules to control the reactive power of a multi dynamic shunt FACTS Compensator (SVC, STATCOM) in order to improve the system loadability. This proposed approach is implemented with the Matlab program and is applied to small case studies, IEEE 25-Bus and IEEE 30-Bus. The results obtained confirm the effectiveness in sizing and integration of an assigned number of DG units.

• 한국정보통신학회논문지
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• 제10권6호
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• pp.1032-1037
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• 2006

채널은 무선망에 있어서 한정된 주요 자원 중의 하나이다. 다양한 채널 관리 기법들이 제시되어 왔으며, 최근 들어 가드채널의 최적화 문제가 부각되고 있다. 본 논문에서는 신경망을 이용한 지능적인 채널 관리 기법을 제안한다. 신경망의 학습 데이터 생성과 성능분석을 위하여 SRN(Stochastic Reward Net) 채널 할당 모델이 개발된다. 제안된 기법에서 신경망은 지도학습 방법인 역전파 알고리즘을 이용하여 최적의 가드채널 값 g를 계산하도록 학습한다. 학습된 신경망을 이용하여 최적의 g를 계산하고, 이를 SRM모델에서 구해진 결과와 비교한다. 실험 결과는 신경망에서 구한 가드채널 수와 SRM모델로부터 구한 가드채널 수의 상대적 차이가 없음을 보여준다.

• 보건행정학회지
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• 제2권2호
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• pp.33-56
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• 1992

The objectives of this research are (i) to review the functional and financial distribution of public health adminstration between central and local governments, (ii) to find out, based on economic criteria, optimal distribution required to fullfil local need for public health, and finally, (iii) to suggest policy implications in health area in face of the newly arising local autonomy system in Korea. Judging from data on government expenditures and tax revenues, public health administration in Korea is highly concentrated into central government, both functionlally and financially. High dependency of public health on central government has often been critisized that local residents can not participate in the decision making process for local health problems. This study, however, shows that localization of public health administration does not necessarily result in efficient and equitable allocation of resource to satisfy local demand for public health. From this point of view, two eccnomic criteria are suggested, i.e. external effect and economies of scle, as distributive criteria of roles in public health administration between local and central government. In addition, superiority of central concentration of public health administration to localization is emphasized in that public health in a wide sense contains the nature of public good and is part of compulsory socil security system. As a consequence, planned intervention by government is desirable.

• Journal of Yeungnam Medical Science
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• 제7권1호
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• pp.133-144
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• 1990

귀중한 혈액을 적절량 수혈함으로써 불필요한 노력과 혈액의 소모를 방지하며, 필요한 수술에 맞추어 소요 혈액량을 파악함으로 해서 혈액공급의 원할을 기할 수 있다. 1987년 1월부터 1988년 12월까지 2년간 영남대학교 의과대학 부속병원에서 수술에 사용된 혈액량을 주요 수술의 방법별로 조사하여, 각 수술에서의 수혈 빈도, 평균수혈량 및 예상 적정수혈량 등을 산정하고, 수혈량과 수혈환자의 나이, 수술전 혈색소치, 체중, 성별, 혈액형과의 관계를 살펴보았으며, 이를 토대로 하여 수술전 의뢰혈액량의 지침이 되도록 하였다.

• ETRI Journal
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• 제41권5호
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• pp.585-598
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• 2019

A cyber-physical system (CPS) is a new mechanism controlled or monitored by computer algorithms that intertwine physical and software components. Advanced persistent threats (APTs) represent stealthy, powerful, and well-funded attacks against CPSs; they integrate physical processes and have recently become an active research area. Existing offensive and defensive processes for APTs in CPSs are usually modeled by incomplete information game theory. However, honeypots, which are effective security vulnerability defense mechanisms, have not been widely adopted or modeled for defense against APT attacks in CPSs. In this study, a honeypot game-theoretical model considering both low- and high-interaction modes is used to investigate the offensive and defensive interactions, so that defensive strategies against APTs can be optimized. In this model, human analysis and honeypot allocation costs are introduced as limited resources. We prove the existence of Bayesian Nash equilibrium strategies and obtain the optimal defensive strategy under limited resources. Finally, numerical simulations demonstrate that the proposed method is effective in obtaining the optimal defensive effect.

• International Journal of Computer Science & Network Security
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• 제21권3호
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• pp.304-310
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• 2021

The paper presents problems of optimization of the synthesis of embedded systems, in particular Pareto optimization. The model of such a system for its design for high-level of abstract is based on the classic approach known from the theory of task scheduling, but it is significantly extended, among others, by the characteristics of tasks and resources as well as additional criteria of optimal system in scope structure and operation. The metaheuristic algorithm operating according to this model introduces a new approach to system synthesis, in which parallelism of task scheduling and resources partition is applied. An algorithm based on a genetic approach with simulated annealing and Boltzmann tournaments, avoids local minima and generates optimized solutions. Such a synthesis is based on the implementation of task scheduling, resources identification and partition, allocation of tasks and resources and ultimately on the optimization of the designed system in accordance with the optimization criteria regarding cost of implementation, execution speed of processes and energy consumption by the system during operation. This paper presents examples and results for multi-criteria optimization, based on calculations for specifying non-dominated solutions and indicating a subset of Pareto solutions in the space of all solutions.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.196-203
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• 2022

The resource constrained scheduling problem (RCSP) constitutes one of the most challenging problems in Project Management, as it combines multiple parameters, contradicting objectives (project completion within certain deadlines, resource allocation within resource availability margins and with reduced fluctuations), strict constraints (precedence constraints between activities), while its complexity grows with the increase in the number of activities being executed. Due to the large solution space size, this work investigates the application of Genetic Algorithms to approximate the optimal resource alolocation and obtain optimal trade-offs between different project goals. This analysis uses the cost of exceeding the daily resource availability, the cost from the day-by-day resource movement in and out of the site and the cost for using resources day-by-day, to form the objective cost function. The model is applied in different case studies: 1 project consisting of 10 activities, 4 repetitive projects consisting of 40 activities in total and 16 repetitive projects consisting of 160 activities in total, in order to evaluate the effectiveness of the algorithm in different-size solution spaces and under alternative optimization criteria by examining the quality of the solution and the required computational time. The case studies 2 & 3 have been developed by building upon the recurrence of the unit/sub-project (10 activities), meaning that the initial problem is multiplied four and sixteen times respectively. The evaluation results indicate that the proposed model can efficiently provide reliable solutions with respect to the individual goals assigned in every case study regardless of the project scale.