• 한국정보시스템학회지:정보시스템연구
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• 제14권3호
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• pp.89-96
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• 2005

Though studies on negotiations have actively been conducted in the field of e-Commerce so far, some problems have yet to be solved and many application fields of negotiation systems exist. Currently, many businesses shift from various fields to e-Commerce market, due to recent social changes and expansion of e-Commerce market; however, we need to develop the study of automated agents to resolve the issue of negotiation, which is an essential element in the e-Commerce, by minimizing human interference under the e-Commerce environment. In this study, we intend to propose a new negotiation protocol considering the negotiation alternatives through continuous negotiation rounds in relation to an automated negotiation issue whose participants are one to N (seller to buyers). We also present an agent-facilitated negotiation methodology by which negotiation alternative generation process is automated, in consideration of buyer's negotiation attributes and strategies in the negotiation system.

• Journal of Electrical Engineering and Technology
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• 제13권4호
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• pp.1586-1595
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• 2018

For the problem that the complexity of 3-D modeling and multi parameter optimization, as well as the uncertainty of the winding factor of axial flux permanent magnet generator with coreless windings. The complex 3-D model was simplified into 2-D analytic model, and an analytical formula for the winding factor that adapting different coreless stator winding is proposed in this paper. The analytical solution for air-gap magnetic fields, no-load back EMF, electromagnetic torque, and efficiency are calculated by using this method. The multiple objective and multivariable optimization of the maximum fundamental and the minimum harmonic content of back EMF are performed by using response surface methodology. The proposed optimum design method was applied to make a generator. The generator was tested and the calculated results are compared with the proposed method, which show good agreements.

• Nuclear Engineering and Technology
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• 제53권10호
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• pp.3379-3397
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• 2021

In this study, a multi-physics modeling method was developed to analyze a nuclear fuel rod's thermo-mechanical behavior especially for high temperature anisotropic creep deformation during ballooning and burst occurring in Loss of Coolant Accident (LOCA). Based on transient heat transfer and nonlinear mechanical analysis, the present work newly incorporated the nuclear fuel rod's special characteristics which include gap heat transfer, temperature and burnup dependent material properties, and especially for high temperature creep with material anisotropy. The proposed method was tested through various benchmark analyses and showed good agreements with analytical solutions. From the validation study with a cladding burst experiment which postulates the LOCA scenario, it was shown that the present development could predict the ballooning and burst behaviors accurately and showed the capability to predict anisotropic creep behavior during the LOCA. Moreover, in order to verify the anisotropic creep methodology proposed in this study, the comparison between modeling and experiment was made with isotropic material assumption. It was found that the present methodology with anisotropic creep could predict ballooning and burst more accurately and showed more realistic behavior of the cladding.

• 지식경영연구
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• 제20권3호
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• pp.39-47
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• 2019

Response surface methodology (RSM) is a group of statistical modeling and optimization methods to improve the quality of design systematically in the quality engineering field. Its final goal is to identify the optimal setting of input variables optimizing a response. RSM is a kind of knowledge management tool since it studies a manufacturing or service process and extracts an important knowledge about it. In a real problem of RSM, it is a quite frequent situation that considers multiple responses simultaneously. To date, many approaches are proposed for solving (i.e., optimizing) a multi-response problem: process capability function approach, desirability function approach, loss function approach, and so on. The process capability function approach first estimates the mean and standard deviation models of each response. Then, it derives an individual process capability function for each response. The overall process capability function is obtained by aggregating the individual process capability function. The optimal setting is given by maximizing the overall process capability function. The existing process capability function methods usually use the arithmetic mean or geometric mean as an aggregation operator. However, these operators do not guarantee the Pareto optimality of their solution. Moreover, they may bring out an unacceptable result in terms of individual process capability function values. In this paper, we propose a maximin-based process capability function method which uses a maximin criterion as an aggregation operator. The proposed method is illustrated through a well-known multiresponse problem.

• Steel and Composite Structures
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• 제49권1호
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• pp.47-64
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• 2023

Due to their efficient use of materials, hybrid reinforced concrete-steel (RCS) systems provide more practical and economic advantages than traditional steel and concrete moment frames. This study evaluated the seismic design factors and response modification factor 'R' of RCS composite moment frames composed of reinforced concrete (RC) columns and steel (S) beams. The current International Building Code (IBC) and ASCE/SEI 7-05 classify RCS systems as special moment frames and provide an R factor of 8 for these systems. In this study, seismic design parameters were initially quantified for this structural system using an R factor of 8 based on the global methodology provided in FEMA P695. For analyses, multi-story (3, 5, 10, and 15) and multi-span (3 and 5) archetypes were used to conduct nonlinear static pushover analysis and incremental dynamic analysis (IDA) under near-field and far-field ground motions. The analyses were performed using the OpenSees software. The procedure was reiterated with a larger R factor of 9. Results of the performance evaluation of the investigated archetypes demonstrated that an R factor of 9 achieved the safety margin against collapse outlined by FEMA P695 and can be used for the design of RCS systems.

• 대한전기학회논문지:시스템및제어부문D
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• 제50권5호
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• pp.226-232
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• 2001

The ability to efficiently and robustly recover accurate 3D terrain models from sets of stereoscopic images is important to many civilian and military applications. To develop an effective and practical terrain modeling system, we propose a new multi-image stereo method which detect unreliable elevations in DEM(Digital Elevation Map), and fuse several DEMs from multiple sources into an accurate and reliable results. This paper focuses on two key factors for generating robust 3D terrain models: the ability to detect unreliable elevation estimates and the ability to fuse the reliable elevations into a single optimal terrain model. We apply the self-consistency methodology to reconstruct accurate DEM from multi-image and show the method is more effective than the conventional stereo image 3D reconstruction method. Using photo-realistic simulator, four synthetic image are generated from ground truth DEM and orthoimage to evaluate the accuracy of the proposed method quantitatively.

• 전기학회논문지
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• 제58권4호
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• pp.700-707
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• 2009

The application of renewable energy in electric power systems is growing rapidly in order to make provision for the inequality of the climate, the dwindling supplies of coal, oil and natural gas and a further rise in oil prices. Solar cell generators(SCG) is one of the fastest growing renewable energy. This paper presents a methodology on probabilistic production cost simulation of a power system including SCGs. The generated power by SCGs is variable due to the random variation of solar radiation. In order to solve this problem, the SCGs is modeled as multi-state operational model in this paper. Probabilistic production cost of a power system can be calculated by proposed method considering SCGs with multi-state. The results show that the impacts of SCGs added to a power system can be analyzed in view point of production cost using the proposed method.

• 한국항공운항학회지
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• 제18권3호
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• pp.92-98
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• 2010

The AHP methodology compares criteria, or alternatives with respect to a criterion, in a natural, pairwise mode. AHP has been applied in a wide variety of applications multi objective decision making being just one. If a group of expert with different aspect, they need some way to revise expert group. We proposed the concatenation of expert to survey the AHP pairwise question for multi-attribute decision making. In this paper, we suggest a way to revise the expert's priorities in hierarch using concept of different group opinion.

• 상하수도학회지
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• 제32권2호
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• pp.115-122
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• 2018

Direct spring loaded pressure relief valve(DSLPRV) is a safety valve to relax surge pressure of the pipeline system. DSLPRV is one of widely used safety valves for its simplicity and efficiency. However, instability of the DSLPRV can caused by various reasons such as insufficient valve volume, natural vibration of the spring, etc. In order to improve reliability of DSLPRV, proper selection of design factors of DSLPRV is important. In this study, methodology for selecting design factors for DSLPRV was proposed. Dynamics of the DSLPRV disk was integrated into conventional 1D surge pressure analysis. Multi-objective genetic algorithm was also used to search optimum design factors for DSLPRV.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.155-157
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• 2005

We propose a new category of hybrid multi-layer neural networks with hetero nodes such as Fuzzy Set based Polynomial Neurons (FSPNs) and Polynomial Neurons (PNs). These networks are based on a genetically optimized multi-layer perceptron. We develop a comprehensive design methodology involving mechanisms of genetic optimization and genetic algorithms, in particular. The augmented genetically optimized HFPNN (namely gHFPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional HFPNN. The GA-based design procedure being applied at each layer of HFPNN leads to the selection of preferred nodes (FPNs or PNs) available within the HFPNN. In the sequel, two general optimization mechanisms are explored. First, the structural optimization is realized via GAs whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gHFPNNs quantified through experimentation where we use a number of modeling benchmarks-synthetic and experimental data already experimented with in fuzzy or neurofuzzy modeling.