• 제목/요약/키워드: support functions

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Development of Information System for Product Redesign: Evaluation of Assembly Process and Characteristics of Product Functions

  • Arakawa, Masahiro
    • Industrial Engineering and Management Systems
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    • 제9권3호
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    • pp.215-226
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    • 2010
  • Since product design strongly depends on the experience and ability of the designers, and a long lead time is required for the product design stage, introducing a support system related to this experience and ability is an effective technique to reduce the lead time. In this paper, an information system is developed to support the development of engineering mechanisms with the evaluation of the assembly process on the basis of the abstract functions required for new products. The developed system is based on a database system involving the following data structure: (1) a hierarchical structure related to information about the product functions, (2) the relationship between the parts and engineering functions and/or mechanisms of products, and (3) the relationship between the parts and manufacturing characteristics. The system stores the relationships between the product functions, structure of parts, and assembly characteristics. This information can then be interactively retrieved using the data structure described in (1), (2), and (3). A procedure for designing new products is proposed that involves using the information about existing products. This paper presents the characteristics of the proposed procedure and the developed information system. In addition, a case study of the redesign of a simple structured robot by using the proposed procedure is discussed.

Restricted support vector quantile regression without crossing

  • Shim, Joo-Yong;Lee, Jang-Taek
    • Journal of the Korean Data and Information Science Society
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    • 제21권6호
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    • pp.1319-1325
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    • 2010
  • Quantile regression provides a more complete statistical analysis of the stochastic relationships among random variables. Sometimes quantile functions estimated at different orders can cross each other. We propose a new non-crossing quantile regression method applying support vector median regression to restricted regression quantile, restricted support vector quantile regression. The proposed method provides a satisfying solution to estimating non-crossing quantile functions when multiple quantiles for high dimensional data are needed. We also present the model selection method that employs cross validation techniques for choosing the parameters which aect the performance of the proposed method. One real example and a simulated example are provided to show the usefulness of the proposed method.

Two-step LS-SVR for censored regression

  • Bae, Jong-Sig;Hwang, Chang-Ha;Shim, Joo-Yong
    • Journal of the Korean Data and Information Science Society
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    • 제23권2호
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    • pp.393-401
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    • 2012
  • This paper deals with the estimations of the least squares support vector regression when the responses are subject to randomly right censoring. The estimation is performed via two steps - the ordinary least squares support vector regression and the least squares support vector regression with censored data. We use the empirical fact that the estimated regression functions subject to randomly right censoring are close to the true regression functions than the observed failure times subject to randomly right censoring. The hyper-parameters of model which affect the performance of the proposed procedure are selected by a generalized cross validation function. Experimental results are then presented which indicate the performance of the proposed procedure.

COMPARATIVE STUDY OF THE PERFORMANCE OF SUPPORT VECTOR MACHINES WITH VARIOUS KERNELS

  • Nam, Seong-Uk;Kim, Sangil;Kim, HyunMin;Yu, YongBin
    • East Asian mathematical journal
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    • 제37권3호
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    • pp.333-354
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    • 2021
  • A support vector machine (SVM) is a state-of-the-art machine learning model rooted in structural risk minimization. SVM is underestimated with regards to its application to real world problems because of the difficulties associated with its use. We aim at showing that the performance of SVM highly depends on which kernel function to use. To achieve these, after providing a summary of support vector machines and kernel function, we constructed experiments with various benchmark datasets to compare the performance of various kernel functions. For evaluating the performance of SVM, the F1-score and its Standard Deviation with 10-cross validation was used. Furthermore, we used taylor diagrams to reveal the difference between kernels. Finally, we provided Python codes for all our experiments to enable re-implementation of the experiments.

보조벡터 머신을 이용한 시계열 예측에 관한 연구 (A study on the Time Series Prediction Using the Support Vector Machine)

  • 강환일;정요원;송영기
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.315-315
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    • 2000
  • In this paper, we perform the time series prediction using the SVM(Support Vector Machine). We make use of two different loss functions and two different kernel functions; i) Quadratic and $\varepsilon$-insensitive loss function are used; ii) GRBF(Gaussian Radial Basis Function) and ERBF(Exponential Radial Basis Function) are used. Mackey-Glass time series are used for prediction. For both cases, we compare the results by the SVM to those by ANN(Artificial Neural Network) and show the better performance by SVM than that by ANN.

Simple Graphs for Complex Prediction Functions

  • Huh, Myung-Hoe;Lee, Yong-Goo
    • Communications for Statistical Applications and Methods
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    • 제15권3호
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    • pp.343-351
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    • 2008
  • By supervised learning with p predictors, we frequently obtain a prediction function of the form $y\;=\;f(x_1,...,x_p)$. When $p\;{\geq}\;3$, it is not easy to understand the inner structure of f, except for the case the function is formulated as additive. In this study, we propose to use p simple graphs for visual understanding of complex prediction functions produced by several supervised learning engines such as LOESS, neural networks, support vector machines and random forests.

고령장애인의 만성질환과 다차원적 장애 : 국제기능장애건강분류틀(ICF)을 적용하여 (Chronic Illnesses and Multidimensional Disability among Older Adults with Disabilities: Applying the ICF Framework)

  • 조상은
    • 사회복지연구
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    • 제48권4호
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    • pp.91-120
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    • 2017
  • 본 연구에서는 WHO의 국제기능장애건강분류틀(ICF)을 기반으로 고령장애인의 만성질환과 다차원적 장애 간의 관계, 공식 비공식 지지와 다차원적 장애 간의 관계를 살펴보고 공식 비공식 지지의 조절효과를 확인하고자 하였다. 이를 위해 만 50세 이상 고령장애인 450명을 대상으로 2014년도 9차 한국복지패널자료를 사용하여 구조방정식모델(structural equation modeling)로 분석하였다. ICF에 근거하여 건강조건은 고령장애인의 만성질환 수준으로 측정하였고 다차원적 장애는 심리 정서적 기능, 일상활동 수행능력, 사회활동 참여로 측정하였으며 환경요인인 공식 지지와 비공식 지지는 각각 공적서비스 이용 총 수와 지각된 사적 사회적 지지 수준으로 측정하였다. 분석 결과, 만성질환은 심리 정서적 기능에 부정적인 영향을 미쳤고 비공식 지지는 심리 정서적 기능과 일상활동 수행능력에 긍정적인 영향을 미쳤다. 반면 공식 지지의 경우, 일상활동 수행능력과 부적 관계를 나타냈고 만성질환과 심리 정서적 기능의 부적 관계에 부정적 영향을 미치는 것으로 나타났다. 연구결과를 바탕으로 고령장애인의 기능수행(functioning) 제고를 위한 실천적 정책적 제언을 제시하고자 하였다.

Construction of the shape functions of beam vibrations for analysis of the rectangular plates by Kantorovich-Vlasov's method

  • Olodo, Emmanuel E.T.;Degan, Gerard
    • Structural Engineering and Mechanics
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    • 제52권3호
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    • pp.595-601
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    • 2014
  • For analysis of the plates and membranes by numerical or analytical methods, the question of choice of the system of functions satisfying the different boundary conditions remains a major challenge to address. It is to this issue that is dedicated this work based on an approach of choice of combinations of trigonometric functions, which are shape functions of a bended beam with the boundary conditions corresponding to the plate support mode. To do this, the shape functions of beam vibrations for strength analysis of the rectangular plates by Kantorovich-Vlasov's method is considered. Using the properties of quasi-orthogonality of those functions allowed assessing to differential equation for every member of the series. Therefore it's proposed some new forms of integration of the beam functions, in order to simplify the problem.

도로공사의 최적 설계정보 지원을 위한 VR시뮬레이션 기능 구축 (Development of VR Simulation Functions for Supporting Optimal Design Information in Road Project)

  • 강인석;문현석;박서영;배철원;김민지
    • 한국건설관리학회:학술대회논문집
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    • 한국건설관리학회 2008년도 정기학술발표대회 논문집
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    • pp.662-665
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    • 2008
  • 본 연구는 기존 시공단계 중심의 4D CAD 활용체계를 설계단계까지 확장하여 도로의 최적 설계업무 지원을 위한 4D CAD 기능을 개발하는 것이 목적이다. 도로설계 지원 기능으로는 도로선형에 의한 토공 시뮬레이션, 대안 노선 선정 시뮬레이션 및 구조물 타입 선정 시뮬레이션 기능을 제안하고 있다. 이러한 VR 시뮬레이션 기능을 통해 도로선형지정에 의한 노선 및 토공 상태의 시각적 확인이 가능하다. 또한 대안 노선의 가상적인 모의 배치를 수행함으로써 최적의 대안 노선을 선정할 수 있다. 이와 함께 구조물의 다양한 모델을 지형에 배치하여 주위 환경에 적합한 구조물 형식을 결정할 수 있다. 본 연구에서 제시된 기능은 도로설계의 효율적인 지원을 위해 가상적인 모델 기반의 의사결정도구를 제공한다. 따라서 본 연구에서 구현된 기능 인터페이스를 통해 도로 설계업무의 효율성을 기대할 수 있다.

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초등학교 정보화 지원시설의 규모산정에 관한 연구 (A Study on the Scale Calculation of Information Support Facility of the Elementary School)

  • 조병성;이호진
    • 교육녹색환경연구
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    • 제4권4호
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    • pp.25-38
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    • 2004
  • Schools have focused so far on a student-oriented education. As the roles of schools, however, have been increasingly emphasized in the information society, community-centered functions are now additionally required. Beyond simply allowing communities to utilize selected facilities, schools can conduct re-education programs for community residents and actively use their facilities for such purposes. As explained above, schools must continuously evolve to meet current needs and demands, such as by offering special classes and utilizing learning facilities in the elementary levels to promote learning in ever-changing societies. This study analyzed the functions of school facilities to communities, as well as the educational functions involved in teaching-learning processes, in light of the advent of a knowledge and information society. Through analysis, the types of information facilities in elementary schools were derived. On the basis of such derived types, systematic and reasonable methods to estimate the scope were suggested.

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