• Title, Summary, Keyword: support function

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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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    • v.23 no.2
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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.

Multimedia Conferencing System with Intramedia and Intermedia Synchronization Support

  • Yoo, Sang-Shin;Kim, Duck-Jin
    • Journal of Electrical Engineering and information Science
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    • v.2 no.3
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    • pp.41-50
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    • 1997
  • In this paper, we describe the design, implementation and evaluation for a multimedia conferencing system with intramedia and intermedia synchronization support between audio and video. The synchronization mechanism proposed here is capable of dynamically adapting to various network conditions thus providing an optimized QoS. In realizing the system based on this mechanism, NeVoT on Mbone is used for audio and VIC for video. Furthermore a synchromization controller is designed and realized with a unique process in supporting intermedia synchronization. Each media agents handling its media stream are modified with intramedia synchronization function. And a communicative function between media agents and synchronization controller is added as well for intermedia synchronization function. Each media agents function reports its buffering status to the synchronization control process which in turn send out optimized buffering delay value thus supporting intermedia synchronization. The realized system is configured and tested on Ethernet and ATM network where performance measurements were performed and its effective synchronization support has been assured.

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Factors Influencing Adolescent's Relationship With Non-Custodial Parents (이혼가족 청소년의 비양육부모와의 관계에 관한 연구)

  • Cho, Sung Hui
    • Korean Journal of Child Studies
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    • v.37 no.2
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    • pp.157-168
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    • 2016
  • Objective: This study examined the facotrs influencing the relationship of adolescents with non-custodial parent. Specifically, this study focused on the comparative influence of the family function as a factor controlling other factors such as socio-demographic characteristics, beliefs about parental divorce, and social support. Methods: Data were collected from 322 adolescents from divorced families using a structured questionnaire. SPSS 22.0, descriptive statistical analysis, correlation analysis, and hierarchical multiple regression were performed to analyze the data. Results and Conclusion: The results revealed that beliefs about parental divorce, social support, and family function affected the relationship with non-custodial parent. After controlling the influence of other factors, family function was found to have a significant influence on the relationship with non-custodial parents. Based on the results, practical suggestions were provided to enhance the relationship between adolescents and non-custodial parents.

Readjustment and Social Support of the Post Hospitalized Stroke Patients (퇴원후 뇌졸중환자의 재적응과 사회적 지지와의 관계분석)

  • ;Samuel Noh;Gerald M. Devins
    • Journal of Korean Academy of Nursing
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    • v.29 no.3
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    • pp.639-655
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    • 1999
  • An explanatory design was employed to identify the relationship of physical, emotional & social readjustment and social support of post hospitalized stroke patients and their caregivers. A convenient sample of 254 patients who given follow-up care at the outpatient department after discharge and 225 caregivers were recruited. Mental Status Questionnaire (MSQ), Social Support Inventory Stroke Survivors (SSISS), Illness intrusiveness(II), Instument Activity of Daily Living(IADL), Center of Epidemilogic Studies-Depression(CES-D), social activity and caregiver burden were used for measurement in this study. Results showed patient's physical level measured by IADL and psychological level measured by depression were high. But social activity was low. Cognitive function, depression & social activity were not significantly different by the posthospitalized period, but IADL was. The source of professional support was mostly the physician at the outpatient department. The family support was found significantly related to patient's depression & social activity and caregiver's subjective burden. Professional support was found significantly related to patient's IADL & depression. Illness intrusiveness as a mediating variable was a sig nificantly predicting power on patient's IADL & depression. The path analysis was used to identify the variables to predict the physical, emotional, and social status of patients. As a result, patient's age, cognitive function, illness intursiveness and professional support significantly predicted the level of IADL ; patient's cognitive function, illness intrusiveness and family support significantly predicted the level of depression ; and patient's age and family support significantly predicted the level of social activity of posthospitalized stroke patients. Based upon these results, the rehabilitation programs to reduce the illness intrusiveness and improve cognitive funtion were recommended for the readjustment of the stroke patients. This model of the readjustment of the posthospitalized stroke patients is recommended as the framework for care of the stroke patients.

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SVQR with asymmetric quadratic loss function

  • Shim, Jooyong;Kim, Malsuk;Seok, Kyungha
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.6
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    • pp.1537-1545
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    • 2015
  • Support vector quantile regression (SVQR) can be obtained by applying support vector machine with a check function instead of an e-insensitive loss function into the quantile regression, which still requires to solve a quadratic program (QP) problem which is time and memory expensive. In this paper we propose an SVQR whose objective function is composed of an asymmetric quadratic loss function. The proposed method overcomes the weak point of the SVQR with the check function. We use the iterative procedure to solve the objective problem. Furthermore, we introduce the generalized cross validation function to select the hyper-parameters which affect the performance of SVQR. Experimental results are then presented, which illustrate the performance of proposed SVQR.

Improvement of Support Vector Clustering using Evolutionary Programming and Bootstrap

  • Jun, Sung-Hae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.8 no.3
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    • pp.196-201
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    • 2008
  • Statistical learning theory has three analytical tools which are support vector machine, support vector regression, and support vector clustering for classification, regression, and clustering respectively. In general, their performances are good because they are constructed by convex optimization. But, there are some problems in the methods. One of the problems is the subjective determination of the parameters for kernel function and regularization by the arts of researchers. Also, the results of the learning machines are depended on the selected parameters. In this paper, we propose an efficient method for objective determination of the parameters of support vector clustering which is the clustering method of statistical learning theory. Using evolutionary algorithm and bootstrap method, we select the parameters of kernel function and regularization constant objectively. To verify improved performances of proposed research, we compare our method with established learning algorithms using the data sets form ucr machine learning repository and synthetic data.

Support Vector Median Regression

  • Hwang, Chang-Ha
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.1
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    • pp.67-74
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    • 2003
  • Median regression analysis has robustness properties which make it an attractive alternative to regression based on the mean. Support vector machine (SVM) is used widely in real-world regression tasks. In this paper, we propose a new SV median regression based on check function. And we illustrate how this proposed SVM performs and compare this with the SVM based on absolute deviation loss function.

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Least-Squares Support Vector Machine for Regression Model with Crisp Inputs-Gaussian Fuzzy Output

  • Hwang, Chang-Ha
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.2
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    • pp.507-513
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    • 2004
  • Least-squares support vector machine (LS-SVM) has been very successful in pattern recognition and function estimation problems for crisp data. In this paper, we propose LS-SVM approach to evaluating fuzzy regression model with multiple crisp inputs and a Gaussian fuzzy output. The proposed algorithm here is model-free method in the sense that we do not need assume the underlying model function. Experimental result is then presented which indicate the performance of this algorithm.

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Quadratic Loss Support Vector Interval Regression Machine for Crisp Input-Output Data

  • Hwang, Chang-Ha
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.2
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    • pp.449-455
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    • 2004
  • Support vector machine (SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate interval regression models for crisp input-output data. The proposed method is based on quadratic loss SVM, which implements quadratic programming approach giving more diverse spread coefficients than a linear programming one. The proposed algorithm here is model-free method in the sense that we do not have to assume the underlying model function. Experimental result is then presented which indicate the performance of this algorithm.

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Covariance Structure Analysis of the Influence of Social Support, Physical and Mental Health Status on Quality of Life among the Elderly at Care Facilities (요양시설 노인의 사회적지지, 신체적 및 정신적 건강수준이 삶의 질에 미치는 영향에 대한 공분산구조분석)

  • Lim, Young-A;Cho, Young-Chae
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.18 no.8
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    • pp.210-220
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    • 2017
  • This study investigated the effect of social support (MOS-SSS), and physical (ADL, IADL) and mental (CES-D, MMSE-K) function on the quality of life (WHOQOL- BREF) among the elderly at care facilities. The survey respondents were 524 elderly aged 65 and older living in 15 care facilities located in D city. Data were collected through a personal interview conducted by interviewers who visited each care facility from November 2015 to January 2016. As a result, the quality of life was significantly lower in the elderly group with lower social support, with dysfunction in ADL and IADL than in the normal range group, with depression and cognitive impairment group than in the normal range group. The quality of life had a significant positive correlation with social support, ADL, IADL and cognitive impairment, but a significant negative correlation with depression. According to the results of covariance structure analysis, physical function had a greater impact on the quality of life than mental function or social support. Lower quality of life was associated with lower physical and mental function and lower social support. Therefore, concrete measures need to be devised to enhance physical function in order to improve the quality of life among the elderly in care facilities.