• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.302-309
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• 2004

The transmission capacity of wireless communication systems may become dramatically high by employ multiple transmit and receive antennas with space-time coding techniques appropriate to multiple transmit antennas. For large number of transmit antennas and at high bandwidth efficiencies, the receiver may become too complex whenever correlation across transmit antennas is introduced. Reducing decoding complexity at receiver by combining array processing and space-time codes (STC) helps a communication system using STC to overcome the big obstacle that prevents it from achieving a desired high transmission rate. Multi-carrier CDMA (MC-CDMA) allows providing good performance in a channel with high inter-symbol interference. Antenna array, STC and MC-CDMA system have a similar characteristic that transmit-receive data streams are divided into sub-streams. Thus, there may be a noticeable reduction of receiver complexity when we combine them together. In this paper, the combination of array processing and STC in MC-CDMA system over slow selective-fading channel is investigated and compared with corresponding existing MC-CDMA system using STC. A refinement of this basic structure leads to a system design principle in which we have to make a trade off between transmission rate, decoding complexity, and length of spreading code to reach a given desired design goal.

• 한국분무공학회지
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• 제22권2호
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• pp.69-79
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• 2017

When designing a redox flow battery system, compression of battery stack is required to prevent leakage of electrolyte and to reduce contact resistance between cell components. In addition, stack compression leads to deformation of the porous carbon electrode, which results in lower porosity and smaller cross-sectional area for electrolyte flow. In this paper, we investigate the effects of electrode compression on the cell performance by applying multi-dimensional, transient model of all-vanadium redox flow battery (VRFB). Simulation result reveals that large compression leads to greater pressure drop throughout the electrodes, which requires large pumping power to circulate electrolyte while lowered ohmic resistance results in better power capability of the battery. Also, cell compression results in imbalance between anolyte and catholyte and convective crossover of vanadium ions through the separator due to large pressure difference between negative and positive electrodes. Although it is predicted that the battery power is quickly improved due to the reduced ohmic resistance, the capacity decay of the battery is accelerated in the long term operation when the battery cell is compressed. Therefore, it is important to optimize the battery performance by taking trade-off between power and capacity when designing VRFB system.

• International Journal of Aerospace System Engineering
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• 제2권2호
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• pp.29-33
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• 2015

The multidisciplinary design optimization (MDO) of a launch vehicle (LV) with a hybrid rocket engine (HRE) was carried out to investigate the ability of an HRE for a single-stage LV. The non-dominated sorting genetic algorithm-II (NSGA-II) was employed to solve two design problems. The design problems were formulated as two-objective cases involving maximization of the downrange distance over the target flight altitude and minimization of the gross weight, for two target altitudes: 50.0 km and 100.0 km. Each objective function was empirically estimated. Several non-dominated solutions were obtained using the NSGA-II for each design problem, and in each case, a trade-off was observed between the two objective functions. The results for the two design problem indicate that economical performance of the LV is limited with the HRE in terms of the maximum downrange distances achievable. The LV geometries determined from the non-dominated solutions were examined.

• 한국통신학회논문지
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• 제29권12C호
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• pp.1660-1668
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• 2004

본 논문에서는 간단한 구조, 적은 계산량과 안정된 빠른 수렴속도를 가진 RBF (Radial Basis Function) 신경회로망을 이용한 이중 임계값 방식의 음성구간 검출기 알고리즘을 제안하고 시뮬레이션을 통해 유용성을 확인하였다. 음성압축기에 사용되는 CELP (Code-Excited Linear Prediction) 파라미터들을 신경회로망 입력으로 하여 잡음에 강하게 반응하게 하였고, 음성구간 검출기의 성능향상을 위해 음성구간과 침묵구간에서 다른 임계값을 사용하는 이중 임계값 방식을 적용하였다. 실험 결과 이중 임계값을 이용한 RBF 신경망 음성구간 검출기는 G.729 Annex B 음성구간 검출기 보다 우수한 성능을 보였고, 기존의 MLP (Multi Layer Perceptron) 신경회로망을 이용한 음성구간 검출기와 비교하여 음성구간에서는 비슷한 성능을 보였으나 침묵구간에서 25% 정도의 성능향상을 보였다.

• Journal of Electrical Engineering and Technology
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• 제9권4호
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• pp.1411-1417
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• 2014

An MPEG-2 AAC Huffman decoding method based on the fixed length compacted codeword tables, where each codeword can contain multiple number of Huffman codes, was proposed. The proposed method enhances the searching efficiency by finding multiple symbols in a single search, i.e., a direct memory reading of the compacted codeword table. The memory usage is significantly saved by separately handling the Huffman codes that exceed the length of the compacted codewords. The trade-off relation between the computational complexity and the amount of memory usage was analytically derived to find the proper codeword length of the compacted codewords for the design of MPEG-2 AAC decoder. To validate the proposed algorithm, its performance was experimentally evaluated with an implemented MPEG-2 AAC decoder. The results showed that the computational complexity of the proposed method is reduced to 54% of that of the most up-to-date method.

• 산업공학
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• 제11권2호
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• pp.39-48
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• 1998

It is strongly believed that Video on Demand(VOD) will become one of the most promising services for Broadband Integrated Services Digital Network(B-ISDN). VOD service can be classified into two types of services: Near VOD(NVOD) and Interactive VOD(IVOD). Although VOD network requires many kinds of resources, we only consider video servers, programs. and storages. In the network. some video servers should be installed at some nodes(especially, at the root node for NVOD service). so that each node with video server stores video programs and distributes stored programs to customers. We take into account three kinds of costs related with the above resources: a program transmission cost, a program storage cost, and a video server installation cost. There exists a trade-off relationship among those three costs according to the locations of video servers and the kinds of programs stored at each video server. Given a multi-level VOD network and the total number of programs being served in the network. the resource. optimization problem for providing both IVOD and NVOD services is to determine where to install video servers, and which and how many programs should be stored at each video server, in order to minimize the total cost. In this paper we develop an efficient dynamic programming algorithm to solve the problem. We also implement the algorithm based on two different service policies assumed in this paper.

• 한국산학기술학회논문지
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• 제11권11호
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• pp.4597-4603
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• 2010

분해식 산출은 다단 논리식 산출에 매우 중요한 부분을 담당한다. 분해식의 리터럴 개수는 논리함수의 복잡도를 나타내는 기준이 되며, 또한 논리식을 회로로 구현할 경우 리터럴의 개수는 트랜지스터의 개수와 비례하게 된다. 분해식을 산출하는 수행시간과 최적화의 적정성을 맞추기 위해 분해식은 대수 분해식과 부울 분해식 산출로 구분하며, 부울 분해식이 대수 분해식보다 적은 리터럴 개수로 같은 논리식을 표현할 수 있다. 본 논문에서는 부울 분해식을 산출하기 위한 방법을 제시한다. 제안하는 핵심 방법은 2개의 2-큐브 비커널을 이용하여 이들의 곱을 구하여 부울 분해식을 산출하는 것이다. 벤치마크 회로를 통한 실험 결과 이전의 다른 분해식 산출 방법들보다 리터럴 개수를 줄일 수 있었다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.171-171
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• 2020

Decision making strategies should consider both adaptiveness and robustness in order to deal with two main characteristics of climate change: non-stationarity and deep uncertainty. Especially, robust strategies are different from traditional optimal strategies in the sense that they are satisfactory over a wider range of uncertainty and may act as a key when confronting climate change. In this study, a new framework named Robust Stochastic Dynamic Programming (R-SDP) is proposed, which couples previously developed robust optimization (RO) into the objective function and constraint of SDP. Two main approaches of RO, feasibility robustness and solution robustness, are considered in the optimization algorithm and consequently, three models to be tested are developed: conventional-SDP (CSDP), R-SDP-Feasibility (RSDP-F), and R-SDP-Solution (RSDP-S). The developed models were used to derive optimal monthly release rules in a single reservoir, and multiple simulations of the derived monthly policy under inflow scenarios with varying mean and standard deviations are undergone. Simulation results were then evaluated with a wide range of evaluation metrics from reliability, resiliency, vulnerability to additional robustness measures. Evaluation results were finally visualized with advanced visualization tools that are used in multi-objective robust decision making (MORDM) framework. As a result, RSDP-F and RSDP-S models yielded more risk averse, or conservative, results than the CSDP model, and a trade-off relationship between traditional and robustness metrics was discovered.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2021년도 학술발표회
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• pp.206-206
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• 2021

The necessity for appropriate management of water resources infrastructures such as reservoirs, levees, and dikes is increasing due to unexpected hydro-climate irregularities and rising water demands. To meet this need, past studies have focused on advancing theoretical optimization algorithms such as nonlinear programming, dynamic programming (DP), and genetic programming. Yet, the optimally derived theoretical solutions are limited to be directly implemented in making release decisions in the real-world systems for a variety of reasons. This study first aims to comparatively analyze the two prominent optimization methods, DP and evolutionary multi-objective direct policy search (EMODPS), under historical inflow series using K-fold cross validation. A total of six optimization models are formed each with a specific formulation. Then, one of the optimization models was coupled with the actual zone-based hedging rule that has been adopted in practice. The proposed methodology was applied to Boryeong Dam located in South Korea with conflicting objectives between supply and demand. As a result, the EMODPS models demonstrated a better performance than the DP models in terms of proximity to the ideal. Moreover, the incorporation of the real-world policy with the optimal solutions improved in all indices in terms of the supply side, while widening the range of the trade-off between frequency and magnitude measured in the sides of demand. The results from this study once again highlight the necessity of closing the gap between the theoretical solutions with the real-world implementable policies.

• 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.