• 한국정보전자통신기술학회논문지
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• 제10권2호
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• pp.192-197
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• 2017

본 논문은 저전력 영상 특징 추출 하드웨어 설계를 위한 공통 부분식 제거 기법 기반 이미지 필터 하드웨어 최적화 기법을 제안한다. 저전력 및 고성능 물체인식 하드웨어는 공장 자동화를 위한 산업용 로봇에 필수 모듈로 채택되고 있다. 따라서 물체인식 하드웨어의 영상 특징 추출 알고리즘에 다양하게 적용되는 Gaussian gradient 필터 하드웨어의 저면적 설계가 필수적이다. Gaussian gradient 필터의 하드웨어 복잡도를 줄이기 위해 필터에 사용되는 계수의 Symmetric한 특징과 Transposed form FIR 필터 하드웨어 구조를 이용했다. 제안된 이미지 필터의 하드웨어 구조는 알고리즘에 적용된 계수의 변형 없이 구현되었기 때문에 윤곽선 검출 알고리즘에 적용했을 때 검출 데이터의 열화 없이 구현될 수 있다. 제안된 이미지 필터 하드웨어 구조는 기존 구조와 비교했을 때 곱셈기의 수를 50% 절감할 수 있음을 확인했다.

• 한국시뮬레이션학회논문지
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• 제3권2호
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• pp.57-67
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• 1994

For many practical and industrial optimization problems where some or all of the system components are stochastic, the objective functions cannot be represented analytically. Therefore, modeling by computer simulation is one of the most effective means of studying such complex systems. In this paper, with discussion of simulation optimization techniques, a case study in machining process for application of simulation optimization is presented. Most of optimization techniques can be classified as single-or multiple-response techniques. The optimization of single-response category, these strategies are gradient based search methods, stochastic approximate method, response surface method, and heuristic search methods. In the multiple-response category, there are basically five distinct strategies for treating the responses and finding the optimum solution. These strategies are graphical method, direct search method, constrained optimization, unconstrained optimization, and goal programming methods. The choice of the procedure to employ in simulation optimization depends on the analyst and the problem to be solved.

• 한국게임학회 논문지
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• 제19권3호
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• pp.5-14
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• 2019

게임 서버는 분산 서버를 기본으로 하고 있다. 분산 게임서버는 서버의 작업 부하를 분산하기 위한 일련의 알고리즘에 의해 각 게임 서버의 부하를 일정하게 나누어서 클라이언트들의 요청에 대한 서버의 응답시간 및 서버의 가용성을 효율적으로 관리한다. 본 논문에서는 시뮬레이션 환경에서 기존 연구 방식인 Greedy 알고리즘과, Reinforcement Learning의 한 줄기인 Policy Gradient 중 PPO(Proximal Policy Optimazation)을 이용한 부하 분산 Agent를 제안하고, 시뮬레이션 한 후 기존 연구들과의 비교 분석을 통해 성능을 평가하였다.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2002년도 봄 학술발표회 논문집
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• pp.335-342
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• 2002

A continuum-based design sensitivity analysis (DSA) method fur non-shape problems is developed for geometrically nonlinear elastic structures. The non-shape problem is characterized by the design variables that are not associated with the domain of system like sizing, material property, loading, and so on. Total Lagrangian formulation with the Green-Lagrange strain and the second Piola-Kirchhoff stress is employed to describe the geometrically nonlinear structures. The spatial domain is discretized using the 4-node isoparametric plane stress/strain elements. The resulting nonlinear system is solved using the Newton-Raphson iterative method. To take advantage of the derived analytical sensitivity In topology optimization, a fast and efficient design sensitivity analysis method, adjoint variable method, is employed and the material property of each element is selected as non-shape design variable. Combining the design sensitivity analysis method and a gradient-based design optimization algorithm, an automated design optimization method is developed. The comparison of the analytical sensitivity with the finite difference results shows excellent agreement. Also application to the topology design optimization problem suggests a very good insight for the layout design.

• 전기학회논문지
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• 제58권1호
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• pp.77-85
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• 2009

With the advent of power semiconductor switching devices, power electronics relating to high frequency electromagnetic eddy current based induction heating technology have become more suitable and acceptable. This paper presents high-frequency induction heating cooking appliance circuit based on the zero current switching-PWM single ended push-pull(ZCS-PWM SEPP) resonant inverter added AC-DC converter. This inverter uses pulse-width-modulation(PWM) control method with active auxiliary quasi-resonant lossless inductor snubbers and a switched capacitor. To improved the transient performance, the PI controller is applied for this system. For the systematic parameter optimization of the PI controller, the gradient-based optimization algorithm is applied. The performance of optimized parameters is evaluated using simulation and experimental test. These results show that the proposed systematic optimal tuning method improve the transient performances of this system.

• Journal of the Optical Society of Korea
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• 제20권1호
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• pp.118-124
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• 2016

The shape and location of the cutoff shield in a projection-type headlight system were optimized by a ray-tracing technique. A shield based on a Petsval surface showed better cutoff characteristics than a flat or cylindrical shield, such as a sharp intensity gradient and less color separation at the cutoff line. Adjustment of the shield’s location between the reflector and the aspheric lens further improved its cutoff characteristics.

• Steel and Composite Structures
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• 제51권6호
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• pp.679-695
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• 2024

This paper presents a novel technique that combines machine learning (ML) with moth-flame optimization (MFO) methods to predict the axial compressive strength (ACS) of concrete filled double skin steel tubes (CFDST) columns. The proposed model is trained and tested with a dataset containing 125 tests of the CFDST column subjected to compressive loading. Five ML models, including extreme gradient boosting (XGBoost), gradient tree boosting (GBT), categorical gradient boosting (CAT), support vector machines (SVM), and decision tree (DT) algorithms, are utilized in this work. The MFO algorithm is applied to find optimal hyperparameters of these ML models and to determine the most effective model in predicting the ACS of CFDST columns. Predictive results given by some performance metrics reveal that the MFO-CAT model provides superior accuracy compared to other considered models. The accuracy of the MFO-CAT model is validated by comparing its predictive results with existing design codes and formulae. Moreover, the significance and contribution of each feature in the dataset are examined by employing the SHapley Additive exPlanations (SHAP) method. A comprehensive uncertainty quantification on probabilistic characteristics of the ACS of CFDST columns is conducted for the first time to examine the models' responses to variations of input variables in the stochastic environments. Finally, a web-based application is developed to predict ACS of the CFDST column, enabling rapid practical utilization without requesting any programing or machine learning expertise.

• 대한기계학회논문집A
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• 제37권12호
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• pp.1513-1519
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• 2013

유전 알고리즘은 자연의 진화 과정에 기초한 계산 모델로서 전역 최적화 결과를 제공할 수 있다. 변화율(gradient)을 기반으로 하는 방법들과는 달리, 민감도 해석이 요구되지 않으므로 민감도 해석이 어려운 전계(electric field)에서의 나노 단위 구조물의 형상 설계에 적합하다. 본 연구는 유전 알고리즘과 ON/OFF 방법을 기반으로 위상최적화를 수행하여 가시광선 영역에서 새로운 형태의 나노개구 설계를 목표로 하였다. 연구의 목적은 나노개구 아래10nm에 위치한 측정영역에서의 전계 투과효율(transmission rate)을 최대화하며, 동시에 다른 영역에서의 전계 분포를 최소화하는 것이다. 유한요소해석 및 최적화 과정은 상용 프로그램 COMSOl과 Matlab 프로그램의 연동에 의하여 수행되었다. 최적화 모델의 결과는 초기 모델과의 전계 강도 (electric field intensity) 및 근접장의 초점치수(spot size)를 비교하여 분석하였다.

• 한국의학물리학회:학술대회논문집
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• 한국의학물리학회 2002년도 Proceedings
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• pp.65-67
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• 2002

A PC based software, the RTP Research Tool Box (RTB), was developed for IMRT optimization research. The software was consisted of an image module, a beam registration module, a dose calculation module, a dose optimization module and a dose display module. The modules and the Graphical User Interface (GUI) were designed to easily amendable by negotiating the speed of performing tasks. Each module can be easily replaced to new functions for research purpose. IDL 5.5 (RSI, USA) language was used for this software. Five major modules enable one to perform the research on the dose calculation, on the dose optimization and on the objective function. The comparison of three cost functions, such as the uncomplicated tumor control probability (UTCP), the physical objective function and the pseudo-biological objective function, which was designed in this study, were performed with the RTB. The optimizations were compared to the simulated annealing and the gradient search optimization technique for all of the optimization objective functions. No significant differences were found among the objective functions with the dose gradient search technique. But the DVH analysis showed that the pseudo-biological objective function is superior to the physical objective function when with the simulated annealing for the optimization.

• International Journal of Fluid Machinery and Systems
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• 제2권1호
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• pp.1-12
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• 2009

Surrogate modeling is applied to a compressor blade shape optimization to modify its stacking line and thickness to enhance adiabatic efficiency and total pressure ratio. Six design variables are defined by parametric curves and three objectives; efficiency, total pressure and a combined objective of efficiency and total pressure are considered to enhance the performance of compressor blade. Latin hypercube sampling of design of experiments is used to generate 55 designs within design space constituted by the lower and upper limits of variables. Optimum designs are found by formulating a PRESS (predicted error sum of squares) based averaging (PBA) surrogate model with the help of a gradient based optimization algorithm. The optimum designs using the current variables show that, to optimize the performance of turbomachinery blade, the adiabatic efficiency objective is improved substantially while total pressure ratio objective is increased a very small amount. The multi-objective optimization shows that the efficiency can be increased with the less compensation of total pressure reduction or both objectives can be increased simultaneously.