• Title/Summary/Keyword: Decision scaling

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Development of a decision scaling framework for drought vulnerability assessment of dam operation under climate change (Decision Scaling 기반 댐 운영 기후변화 가뭄 취약성 평가)

  • Kim, Jiheun;Seo, Seung Beom;Cho, Jaepil
    • Journal of Korea Water Resources Association
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    • v.56 no.4
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    • pp.273-284
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    • 2023
  • Water supply is continuously suffering from frequent droughts under climate change, and such extreme events are expected to become more frequent due to climate change. In this study, the decision scaling method was introduced to evaluate the drought vulnerability under future climate change in a wider range. As a result, the water supply reliability of the Boryeong Dam ranged from 95.80% to 98.13% to the condition of the aqueduct which was constructed at the Boryeong Dam. Furthermore, the Boryeong Dam was discovered to be vulnerable under climate change scenarios. Hence, genetic algorithm-based hedging rules were developed to evaluate the reduction effect of drought vulnerability. Moreover, three demand scenarios (high, standard, and low demand) were also considered to reflect the future socio-economic change in the Boryeong Dam. By analyzing quantitative reliability and the probability of extreme drought occurrence under 5% of the water storage rate, all hedging rules demonstrated that they were superior in preparing for extreme drought under low-demand scenarios.

Statistical Methodologies for Scaling Factor Implementation: Part 1. Overview of Current Scaling Factor Method for Radioactive Waste Characterization

  • Kim, Tae-Hyeong;Park, Junghwan;Lee, Jeongmook;Kim, Junhyuck;Kim, Jong-Yun;Lim, Sang Ho
    • Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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    • v.18 no.4
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    • pp.517-536
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    • 2020
  • The radionuclide inventory in radioactive waste from nuclear power plants should be determined to secure the safety of final repositories. As an alternative to time-consuming, labor-intensive, and destructive radiochemical analysis, the indirect scaling factor (SF) method has been used to determine the concentrations of difficult-to-measure radionuclides. Despite its long history, the original SF methodology remains almost unchanged and now needs to be improved for advanced SF implementation. Intense public attention and interest have been strongly directed to the reliability of the procedures and data regarding repository safety since the first operation of the low- and intermediate-level radioactive waste disposal facility in Gyeongju, Korea. In this review, statistical methodologies for SF implementation are described and evaluated to achieve reasonable and advanced decision-making. The first part of this review begins with an overview of the current status of the scaling factor method and global experiences, including some specific statistical issues associated with SF implementation. In addition, this review aims to extend the applicability of SF to the characterization of large quantities of waste from the decommissioning of nuclear facilities.

An optimal scaling gain tuning method for designing a fuzzy logic controller (퍼지로직제어기를 설계하기 위한 최적 비율 이득 조정방법)

  • Shin, Hyunseok;Shim, Hansoo;Kwon, Cheol;Kang, Hyungjin;Park, Mignon
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.192-194
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    • 1996
  • This paper propose an optimal scaling gain tuning method of the fuzzy PI controller using Genetic Algorithm(GA). Scaling gains can reflect the control resolution and fuzziness of input/output variables. By the scaling gain method, the design of a fuzzy logic controller(FLC) can be simplified without affecting the system performance in comparison with multi-decision table method. In designing a fuzzy logic controller, the analytic approach method for the optimization is unavailable. Therefore GA is excellent optimization algorithms for scaling gain tuning. Using this optimal scaling gain tuning method, a good performance can be achieved both in transient and steady state.

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The Analysis of Fabric Impact and Consumer′s Preference for Fabric on Clothing Purchase (의류 제품 구매시 소재의 영향과 소비자 소재 선호 구조 분석)

  • 정인희
    • Journal of the Korean Society of Clothing and Textiles
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    • v.26 no.1
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    • pp.83-94
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    • 2002
  • This study was intended to identify fabric impact on decision-making process for clothing purchase, to determine evaluation factors of clothing, and to analyze consumer's preference for fabric on clothing purchase. 396 questionnaires distributed to college students were analyzed by descriptive statistics, oneway ANOVA, correlation, factor analysis and multidimensional scaling. The results are as follows; (1) Fabric impacted on the pre-purchase evaluation and the post-purchase process. (2) 4 factors - physical properties, outer-consciousness, self-satisfaction, and appropriateness- were determined as evaluation factors. Though fabric was included in the physical properties, fabric presented high correlations with other evaluative elements. (3) The most preferred fabric was being composed of natural fiber in fiber contents and having softness in sensation. As a result of multidimensional scaling, 2 dimensions of fabric sensation were developed as 'soft-hard'and 'thin-thick'.

Conceptual Design Based on Scale Laws and Algorithms Sub-critical Transmutation Reactors

  • Lee, Kwang-Gu;Chang, Soon-Heung
    • Proceedings of the Korean Nuclear Society Conference
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    • 1997.10a
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    • pp.475-480
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    • 1997
  • In order to conduct the effective integration of computer-aided conceptual design for integrated nuclear power reactor, not only is a smooth information flow required, but also decision making fur both conceptual design and construction process design must be synthesized. In addition to the aboves, the relations between the one step and another step and the methodologies to optimize the decision variables are verified, in this paper especially, that is, scaling laws and scaling criteria. In the respect with the running of the system, the integrated optimization process is proposed in which decisions concerning both conceptual design are simultaneously made. According to the proposed reactor types and power levels, an integrated optimization problems are formulated. This optimization is expressed as a multi-objective optimization problem. The algorithm for solving the problem is also presented. The proposed method is applied to designing a integrated sub-critical reactors.

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A New Decision-Directed Equalization with Improved Blind Convergence Properties by Error Scaling (오차 스케일링에 의해 블라인드 수렴 특성을 개선한 새로운 판정의거 등화)

  • Oh, Kil Nam
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.3
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    • pp.419-424
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    • 2015
  • The Decision-directed (DD) algorithm is known to be not effective to initialize a blind equalizer in the channel conditions when the eye diagram of received signals is completely closed because it can not open the eye diagram enough. In this paper, we propose a new error to replace the error of the conventional DD algorithm. The new DD error is the conventional DD error scaled by the modulus of symbol decision, new DD algorithm using this error is effective to open the closed eye diagram in early stage of equalization unlike the conventional DD. The new DD algorithm appling the new error is showed excellent convergence characteristics as compared to the CMA widely used in blind initialization, particularly, is useful for equalization of signals having multimodulus. The performance of the new DD algorithm is verified through the simulation for the higher-order QAM signals.

Decision Methods for Evaluation of Alternatives (대안 평가를 위한 의사결정 기법)

  • Nam, Kie-Chang;Hong, Sang-Pyo
    • Journal of Environmental Impact Assessment
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    • v.9 no.4
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    • pp.363-372
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    • 2000
  • For any particular development project or environmental regulations, decision-making criteria is required and conflicts among criteria should be resolved. It is necessary to investigate criteria that government agencies employ in making decisions that influence the environment. The evaluation of alternative development proposals and regulatory measures involves much more than environmental issues. Economic, technical, and social factors should be considered along with environmental impacts when making evaluations. Evaluation should be based on values of all individuals who may be affected by public or private decisions. There are many evaluation methods for determining how individuals and groups value alternative public actions. Numerous weighting-scaling methodologies can be used in such evaluations. These methodologies represent adaptations of multiple-criteria or multiple-attribute decision-making techniques. Environmental risk assessment which accounts for uncertainties in choosing among alternative policies and projects is increasingly used.

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Determination of Installation Priority of Washlands Using Multi-Dimensional Scaling Method (다차원척도법을 이용한 강변저류지 설치 우선순위 선정)

  • Ahn, Tae-Jin;Kim, Do-Hyeon;Baek, Chun-Woo
    • Journal of Korea Water Resources Association
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    • v.44 no.7
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    • pp.565-576
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    • 2011
  • Within a basin, there are potentially multiple locations that can be used as a washland, given their relatively small size when compared with other hydraulic facilities such a dam. However, it is unreasonable to install washlands in all these potential locations due to economic and environmental considerations. In this study, a new methodology for determination of installation priority of washlands is presented. How to integrate the decision variables in this decision making problem has been a key issue in previous studies because a washland can provide many benefits such as flood reduction, agricultural benefit and recreational benefit. In particular, a methodology is needed to integrate all decision variables realistically, properly and reasonably, in situations where there is not sufficient data for direct integration of all these decision variables such as construction cost or benefits a washland can provide. This new methodology aims to suggest how to integrate methodologies used in previous studies. The suggested methodology uses four different rankings which are determined based on a flood reduction effect, a relative significance index, an economic analysis, and a space planning suitability index. These rankings are integrated to determine a final installation priority ranking of washlands by a multi-dimensional scaling method. The new methodology has been applied to the Anseong river basin, to show its applicability, and the application result compared with those of previous studies.

An Efficient VM-Level Scaling Scheme in an IaaS Cloud Computing System: A Queueing Theory Approach

  • Lee, Doo Ho
    • International Journal of Contents
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    • v.13 no.2
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    • pp.29-34
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    • 2017
  • Cloud computing is becoming an effective and efficient way of computing resources and computing service integration. Through centralized management of resources and services, cloud computing delivers hosted services over the internet, such that access to shared hardware, software, applications, information, and all resources is elastically provided to the consumer on-demand. The main enabling technology for cloud computing is virtualization. Virtualization software creates a temporarily simulated or extended version of computing and network resources. The objectives of virtualization are as follows: first, to fully utilize the shared resources by applying partitioning and time-sharing; second, to centralize resource management; third, to enhance cloud data center agility and provide the required scalability and elasticity for on-demand capabilities; fourth, to improve testing and running software diagnostics on different operating platforms; and fifth, to improve the portability of applications and workload migration capabilities. One of the key features of cloud computing is elasticity. It enables users to create and remove virtual computing resources dynamically according to the changing demand, but it is not easy to make a decision regarding the right amount of resources. Indeed, proper provisioning of the resources to applications is an important issue in IaaS cloud computing. Most web applications encounter large and fluctuating task requests. In predictable situations, the resources can be provisioned in advance through capacity planning techniques. But in case of unplanned and spike requests, it would be desirable to automatically scale the resources, called auto-scaling, which adjusts the resources allocated to applications based on its need at any given time. This would free the user from the burden of deciding how many resources are necessary each time. In this work, we propose an analytical and efficient VM-level scaling scheme by modeling each VM in a data center as an M/M/1 processor sharing queue. Our proposed VM-level scaling scheme is validated via a numerical experiment.

Optimization of Sheet Metal Forming Process by using Decision-Making Theory (의사결정이론을 이용한 박판성형공정의 최적화)

  • Kim, Kyung-Mo;Yin, Jeong-Je
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.11 no.2
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    • pp.125-136
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    • 2012
  • Wrinkle and fracture are two major defects frequently found in the sheet metal forming process. In this process there are more than one design attributes to optimize and several uncontrollable factors which cannot be ignored in determining the optimal values of design variables. Therefore, attempts to reduce defects through a traditional optimization technique are often led to failures. In this research, a new design method for reducing the wrinkle and fracture under uncontrollable factors is presented by using decision-making theory. To avoid the psychological difficulties in determining the scaling constants of the multi-attribute utility function by using the ordinary lottery questions, a pair-wise comparison procedure is adapted to avoid this problem. The effectiveness of the proposed method is illustrated through a robust design of sheet metal forming process of a side member of an automotive body.