• Proceedings of the KSME Conference
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• 2003.11a
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• pp.1310-1315
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• 2003

In many practical engineering design problems, there are some design and manufacturing considerations that are difficult or infeasible to express in terms of an objective function or a constraint. In this situation, a set of optimal candidate designs having different topological complexities, not just a single optimal design, is preferred. To generate systematically such design candidates, we propose a hierarchical multiscale design resolution control scheme. In order to adjust its topological complexity by choosing a different starting resolution level in the hierarchical design space, we propose to employ a general M-band wavelet transform in transforming the original design space into the multiscale design space.

• Journal of Korean Society for Quality Management
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• v.41 no.1
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• pp.109-118
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• 2013

Purpose: Given the several proper models for given mixture components-process variables experimental data, we propose a strategy to find the optimal condition in which the performance of the responses is well-behaved under those models. Methods: Given the mixture experimental data with process variables, first we choose the reasonable starting models among the class of admissible product models based on the model selection criteria and then, search for the candidate models that are the subset models of the starting model by the sequential variable selection method or all possible regressions procedure. Good candidate models are screened by the evaluation of model selection criteria and checking the residual plots for the validity of the model assumption. Results: We propose a strategy to find the optimal condition in which the performance of the responses is well-behaved under those good candidate models by adopting the optimization methods developed in multiple responses surface methodology. Conclusion: A strategy is proposed to find the optimal condition in which the performance of the responses is well-behaved under those proper combined models. This strategy to find the optimal condition is illustrated with the example in this paper.

• Nuclear Engineering and Technology
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• v.48 no.6
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• pp.1291-1302
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• 2016

This paper presents a new and efficient scheme to determine the optimal neutron source position in a model near-equilibrium pressurized water reactor, which is based on the OPR1000 Hanul Unit 3 Cycle 7 configuration. The proposed scheme particularly assigns importance of source positions according to the local adjoint flux distribution. In this research, detailed pin-by-pin reactor adjoint fluxes are determined by using the Monte Carlo KENO-VI code from solutions of the reactor homogeneous critical adjoint transport equations. The adjoint fluxes at each allowable source position are subsequently ranked to yield four candidate positions with the four highest adjoint fluxes. The study next simulates ex-core detector responses using the Monte Carlo MAVRIC code by assuming a neutron source is installed in one of the four candidate positions. The calculation is repeated for all positions. These detector responses are later converted into an inverse count rate ratio curve for each candidate source position. The study confirms that the optimal source position is the one with very high adjoint fluxes and detector responses, which is interestingly the original source position in the OPR1000 core, as it yields an inverse count rate ratio curve closest to the traditional 1/M line. The current work also clearly demonstrates that the proposed adjoint flux-based approach can be used to efficiently determine the optimal geometry for a neutron source and a detector in a modern pressurized water reactor core.

• Journal of KIISE:Software and Applications
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• v.26 no.12
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• pp.1468-1481
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• 1999

didates.본 논문은 절차 중심 소프트웨어를 객체 지향 소프트웨어로 재/역공학하기 위한 다단계 절차중 첫 절차인 객체 추출 절차에 대하여 기술한다. 사용한 객체 추출 방법은 전처리, 기본 분할 및 결합, 정제 결합, 결정 및 통합의 다섯 단계로 이루어진다 : 1) 전처리 과정에서는 객체 추출을 위한 FTV(Function, Type, Variable) 그래프를 생성/분할 및 클러스터링하고, 2) 기본 분할 및 결합 단계에서는 다중 객체 추출을 위한 그래프를 생성하고 생성된 그래프의 정적 객체를 추출하며, 3) 정제 결합 단계에서는 동적 객체를 추출하며, 4) 결정 단계에서는 영역 모델링과 다중 객체 후보군과의 유사도를 측정하여 영역 전문가가 하나의 최적합 후보를 선택할 수 있는 측정 결과를 제시하며, 5) 통합 단계에서는 전처리 과정에서 분리된 그래프가 여러 개 존재할 경우 각각의 처리된 그래프를 통합한다. 본 논문에서는 클러스터링 순서가 고정된 결정론적 방법을 사용하였으며, 가능한 경우의 수에 따른 다중 객체 후보, 객관적이고 의미가 있는 객체 추출 방법으로의 정제와 결정, 영역 모델링을 통한 의미적 관점에 기초한 방법 등을 사용한다. 이러한 방법을 사용함으로써 전문가는 객체 추출 단계에서 좀더 다양하고 객관적인 선택을 할 수 있다.Abstract This paper presents an object extraction process, which is the first phase of a methodology to transform procedural software to object-oriented software. The process consists of five steps: the preliminary, basic clustering & inclusion, refinement, decision and integration. In the preliminary step, FTV(Function, Type, Variable) graph for object extraction is created, divided and clustered. In the clustering & inclusion step, multiple graphs for static object candidate groups are generated. In the refinement step, each graph is refined to determine dynamic object candidate groups. In the decision step, the best candidate group is determined based on the highest similarity to class group modeled from domain engineering. In the final step, the best group is integrated with the domain model. The paper presents a new clustering method based on static clustering steps, possible object candidate grouping cases based on abstraction concept, a new refinement algorithm, a similarity algorithm for multiple n object and m classes, etc. This process provides reengineering experts an comprehensive and integrated environment to select the best or optimal object candidates.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4157-4175
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• 2020

Moving target defense, as a 'game-changing' security technique for network warfare, realizes proactive defense by increasing network dynamics, uncertainty and redundancy. How to select the best countermeasure from the candidate countermeasures to maximize defense payoff becomes one of the core issues. In order to improve the dynamic analysis for existing decision-making, a novel approach of selecting the optimal countermeasure using game theory is proposed. Based on the signal game theory, a multi-stage adversary model for dynamic defense is established. Afterwards, the payoffs of candidate attack-defense strategies are quantified from the viewpoint of attack surface transfer. Then the perfect Bayesian equilibrium is calculated. The inference of attacker type is presented through signal reception and recognition. Finally the countermeasure for selecting optimal defense strategy is designed on the tradeoff between defense cost and benefit for dynamic network. A case study of attack-defense confrontation in small-scale LAN shows that the proposed approach is correct and efficient.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.209-214
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• 2018

This paper suggests simple algorithm of facility location problem in perishable commodities that satisfy with minimum total transportation cost and within the transportation time constraint $L^*$. For this problem, Lee[4] suggests very complex algorithm that decides candidate facility locations, computes total transportation cost for each candidate facility location, then moving the location to optimal location for top two facilities. On the other hand, this paper simply determines the candidate facility locations within $L^*$ using subtree concept, and decides optimal minimal total transportation cost for top two locations in centralized area of required quantity using neighborhood concept.

• Journal of the military operations research society of Korea
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• v.23 no.2
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• pp.135-154
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• 1997

This paper deals with the perishable inventory models with uncertainties of demand functions. The traditional perishable inventory costs of holding and stockout are incorporated into the cost function. The average expected cost will be minimized to find the optimal quantile estimator. After three candidate estimators are proposed on the basis of order statistics, they will be evaluated by the simulation results and statistical analysis. Then the transition procedure algorithm using this estimator will be proposed to make the optimal decision under uncertainty.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2787-2790
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• 2003

In this paper, we predict tracking performance of the multiple hypothesis tracking (MHT) algorithm. The MHT algorithm is known to be an optimal Bayesian approach and is superior to asly other tracking filters because it takes into account the events that the measurements can be originated from new targets and false alarms 3s well as interesting targets. In the MHT algorithm, a number of candidate hypotheses are generated and evaluated later as more data are received. The probability of each candidate hypotheses is approximately evaluated by using the hybrid conditional average approach (HYCA). We performed numerical experiments to show the validity of our performance prediction.

• Korean Management Science Review
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• v.8 no.1
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• pp.91-108
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• 1991

This paper presents an efficient optimization algorithm for the crude oil tanker scheduling problem. The algorithm consists of two stages. In stage one, all the potentially optimal schedules (called 'candidate schedules') are generated from feasible schedules for each ship. In the second stage, a multiple ship scheduling problem is formulated as 0-1 integer programming problem considering only the those candidate schedules. The efficiency of the suggested algorithm was improved by exploiting the special structure of the formulation. The algorithm was illustrated by a numerical example and tested on practical ship scheduling problems.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.46-54
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• 2023

To improve the railway transportation capacity and maximize the benefits of railway transportation, a method for layout optimization of railway transportation route based on deep convolution neural network is proposed in this study. Considering the transportation cost of railway transportation and other factors, the layout model of railway transportation route is constructed. Based on improved ant colony algorithm, the layout model of railway transportation route was optimized, and multiple candidate railway transportation routes were output. Taking into account external information such as regional information, weather conditions and actual information of railway transportation routes, optimization of the candidate railway transportation routes obtained by the improved ant colony algorithm was performed based on deep convolution neural network, and the optimal railway transportation routes were output, and finally layout optimization of railway transportation routes was realized. The experimental results show that the proposed method can obtain the optimal railway transportation route, the shortest transportation length, and the least transportation time, maximizing the interests of railway transportation enterprises.