• 제목/요약/키워드: tool support

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A Note on Linear SVM in Gaussian Classes

  • Jeon, Yongho
    • Communications for Statistical Applications and Methods
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    • v.20 no.3
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    • pp.225-233
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    • 2013
  • The linear support vector machine(SVM) is motivated by the maximal margin separating hyperplane and is a popular tool for binary classification tasks. Many studies exist on the consistency properties of SVM; however, it is unknown whether the linear SVM is consistent for estimating the optimal classification boundary even in the simple case of two Gaussian classes with a common covariance, where the optimal classification boundary is linear. In this paper we show that the linear SVM can be inconsistent in the univariate Gaussian classification problem with a common variance, even when the best tuning parameter is used.

A Decision Support System using Multiattribute Utility Model

  • Song, Soo-Sup
    • Journal of the military operations research society of Korea
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    • v.16 no.2
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    • pp.43-55
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    • 1990
  • When people choose one way of action from various alternatives, they make value judgement. Due to limited capacity of human information processing, however, a decision maker cannot reflect his true subjective utility in evaluating alternatives especially for a problem which has multiattribute. The analytic hierachy model is a tool which converts scores derived from pairwise comparison with respect to each attribute to overall scores of the alternatives. Then the overall scores are utilized to choose an alternative. Therefore this model can be used to support people's value judgement.

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DECISION SUPPORT SYSTEM FOR CUTTING PARAMETERS SELECTION IN MACHINING PROCESSES USING FUZZY KNOWLEDGE

  • Balazinski, M.;Bellerose, M.;Czogala, E.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.798-801
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    • 1993
  • This paper presents the decision support system using fuzzy knowledge to adapt the cutting conditions chosen by a conventional expert system to a particular machine tool, workpiece and clamping system. These preliminary results demonstrate the capability of fuzzy logic to adjust cutting parameters taking into account parameters difficult to quantify.

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The Impact of State Financial Support on Active-Collaborative Learning Activities and Faculty-Student Interaction

  • Choi, Eun-Mee;Park, Young-Sool;Kwon, Lee-Seung
    • The Journal of Industrial Distribution & Business
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    • v.10 no.2
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    • pp.25-37
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    • 2019
  • Purpose - The goal of this study is to analyze the differences in education performances between students of the government's financial support program and those who do not receive support at a local university in Korea. Research design, data, and methodology - The questionnaire used was NASEL. NASEL is considered a highly suitable survey tool for professors, courses, and performances in Korean universities. The 290 students who participated and 44 students do not participate in the financial support program were surveyed for 10 days. The characteristics of students were investigated by frequency analysis and technical statistics. The analysis of student collective characteristics used independent t and f-tests,and one-way ANOVA with IBM SPSS Statistics 22.0 for statistical purposes. Results - The p-value of the group receiving financial support and the group without financial support in active-collaborative learning is 0.167. The p-value of the economically supported group and the non-supported group of the faculty-student interaction is 0.281. The confidence coefficient of the active-collaborative learning questionnaire is 0.861. The reliability coefficient of the questionnaire for the faculty-student interaction questionnaire is 0.871. Conclusions - There are no clear differences in active-collaborative learning and faculty-student interaction between participating and non-participating students in the economic program.

The Effectiveness of the Use of Custom-Made Foot Orthotics on Temporal-Spatial Gait Parameters in Children With Spastic Cerebral Palsy

  • Kim, Sung-Gyung;Ryu, Young-Uk
    • Physical Therapy Korea
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    • v.19 no.4
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    • pp.16-23
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    • 2012
  • This study examined the effects of custom-made foot orthotics on the temporal-spatial gait parameters in children with cerebral palsy. Twenty spastic bilateral cerebral palsy (spastic CP) children (11 boys and 9 girls) participated in this study. GAITRite was used to examine the velocity, cadence, step length differential, step length, stride length, stance time, single support time, double support time, base of support, and toe angle while walking with and without foot orthotics. The differences in temporal-spatial parameters were analyzed using paired t-test. The significance level was set at .05. The velocity, cadence, both step lengths, both stride lengths, both bases of support and right toe angle significantly increased when the children with spastic CP with foot orthotics compared to without foot orthotics (p<.05). The step length differential between the two extremities, left stance time and left single support time, significantly decreased with foot orthotics (p<.05). Right stance time, right single support time, both double support times and left toe angle showed little change (p>.05). This study demonstrated that foot orthotics were beneficial for children with spastic CP as a gait assistance tool.

A Building Scheme on LAMIS for ROK Army (한국군 종합군수지원 관리정보체계 (LAMIS) 구축방안)

  • Hong Jang-Ui;Yun Hyeon-Cheol;Byeon Jae-Jeong
    • Journal of the military operations research society of Korea
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    • v.18 no.2
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    • pp.1-22
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    • 1992
  • Computer-aided logistics support system is recognized an essential system to reduce supply and maintenance cost, and to improve readiness of weapon system or operationable composite machines. According to these trends, this paper focuses on the design scheme and the computerization strategy of information management system for Integrated Logistics Support (ILS) work. Suggested system. LAMIS(Logistics support Analysis Management Information System) is a total system that composed of Logistics Support Analysis Management information system (LSAM), Configuration Management Information System (CMIS), Maintenance Management Information System (MMIS), Project Management System (PMS) and Information Retrival System(IRS) etc. Also, LAMIS is a computerized tool that improves current supply and maintenance support program, that attempts to reliable requirment analysis of logistics support elements, and that supports to use the existing technical specification of similar one when weapon system acquisition project is started newly. When LAMIS implication is completed, it can be applied to logistics support of defense or commercial site. Straightway, LAMIS will be enhanced with computer - aided design system, engineering drawing system, interactive electronic technical manual system, electronic data interchange system, and three dimensional simulation system to weapon system configuration. When that is done, LAMIS is CALS system.

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Functional Requirements for VTS Decision Support System (VTS 의사결정지원 시스템 기능 요구 사항)

  • Lee, Sang-Woo;Lee, Byung-Gil
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2015.07a
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    • pp.338-339
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    • 2015
  • VTS Decision Support System can be defined a tool which assists VTS operator for decision-making at operational, planning and management level especially for the safety and efficiency of vessel traffic. This paper presents classification of VTS Decision Support System, detailed definition of alerts, and operational and functional requirements of VTS Decision Support System.

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Make-or-buy Decision Model Using Fuzzy-AHP Method for School Foodservice System

  • Hwang, Heung-Suk;Ko, Wen-Hwa
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2007.11a
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    • pp.121-129
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    • 2007
  • Recently a multi-attribute structure analysis method is one of the evident areas of important points in the decision support system analysis. This research developed an internet/intranet-based solution builder for a three-step decision support system using fuzzy-AHP in the view of 1) brainstorming far the idea generation, 2) fuzzy-AHP (fuzzy analytic hierarchy process) as a multi-attribute structured analysis method and 3) aggregation logic model to integrate the results of individual analysis. We applied this decision support system to the make-or-buy decision problem for school foodservice system considering the multi-attributes in the decision making. A computer program is developed and demonstrated it internet/intranet-based decision problem. It was known that this solution builder provides decision makers a good tool for mate-of-buy group decision making.

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Fuzzy Semiparametric Support Vector Regression for Seasonal Time Series Analysis

  • Shim, Joo-Yong;Hwang, Chang-Ha;Hong, Dug-Hun
    • Communications for Statistical Applications and Methods
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    • v.16 no.2
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    • pp.335-348
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    • 2009
  • Fuzzy regression is used as a complement or an alternative to represent the relation between variables among the forecasting models especially when the data is insufficient to evaluate the relation. Such phenomenon often occurs in seasonal time series data which require large amount of data to describe the underlying pattern. Semiparametric model is useful tool in the case where domain knowledge exists about the function to be estimated or emphasis is put onto understandability of the model. In this paper we propose fuzzy semiparametric support vector regression so that it can provide good performance on forecasting of the seasonal time series by incorporating into fuzzy support vector regression the basis functions which indicate the seasonal variation of time series. In order to indicate the performance of this method, we present two examples of predicting the seasonal time series. Experimental results show that the proposed method is very attractive for the seasonal time series in fuzzy environments.

A concise overview of principal support vector machines and its generalization

  • Jungmin Shin;Seung Jun Shin
    • Communications for Statistical Applications and Methods
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    • v.31 no.2
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    • pp.235-246
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    • 2024
  • In high-dimensional data analysis, sufficient dimension reduction (SDR) has been considered as an attractive tool for reducing the dimensionality of predictors while preserving regression information. The principal support vector machine (PSVM) (Li et al., 2011) offers a unified approach for both linear and nonlinear SDR. This article comprehensively explores a variety of SDR methods based on the PSVM, which we call principal machines (PM) for SDR. The PM achieves SDR by solving a sequence of convex optimizations akin to popular supervised learning methods, such as the support vector machine, logistic regression, and quantile regression, to name a few. This makes the PM straightforward to handle and extend in both theoretical and computational aspects, as we will see throughout this article.