• Journal of Korean Society of Industrial and Systems Engineering
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• v.25 no.1
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• pp.1-8
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• 2002

The traditional approaches of association rule mining have relied on high support condition to find interesting rules. However, in some application such as analyzing the web page link and discovering some unusual combinations of some factors that have always caused some disease, we are interested in rules with high confidence that have very low support or need not have high support. In these cases, the traditional algorithms are not suitable since it relies on first satisfying high support. In this paper, we propose a new model, CP(Confidence Pattern)-Tree, to identify high confidence rule between 2-items without support constraint. constraint. In addition, we discuss confidence association rule between two more items without support constraint.

• Journal of Information Technology Applications and Management
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• v.23 no.2
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• pp.1-10
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• 2016

When implementing a new information system, the success has been infrequent even though implementing a new IS can bring about various benefits to organizations. Employee resistance has been identified as a critical reason for such failure of implementing and operating a new IS. The vital role of orgazniational support with employee personality traits (e.g., tolerance for ambiguity and openness to expeirence) to reduce employee resistance has been missing when explaining to the failure of impleneting a new IS. The purpose of this study was to test a research model regarding employee resistnace, investigating the relationship bewteen organizational support and employee personality traits in that how organizational support influences employee resistance and also how employee personality traits (e.g., tolerance for ambiguity and openness to expeirence) interact with organizational support to decrease employee resistance the most. The results of this study supported our hypotheses and theoretical and practical implications are discussed.

• Journal of the Korean Home Economics Association
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• v.47 no.7
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• pp.33-43
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• 2009

Depression has a direct relationship with lower quality of life for elderly with cerebral vascular accidents(CVA). Daily hassles worsen depression for elderly with CVA disability and thus an effective intervention is necessary. This research examined the direct influence of daily hassles on depression and the mediation effect of family support among 161 elderly with CVA disability living in Seoul using Structural Equation Modeling. The direct effect of daily hassles on depression was statistically significant (p < .001) while family support was shown to be a mediator between daily hassles and depression. The mediation model of family support was examined using $x^2$ difference and Soble test. As a result, family support was proven to be a partial mediator. Implications are discussed.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.625-636
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• 2013

In this paper we study four kernel machines for estimating expected shortfall, which are constructed through combinations of support vector quantile regression (SVQR), restricted SVQR (RSVQR), least squares support vector machine (LS-SVM) and support vector expectile regression (SVER). These kernel machines have obvious advantages such that they achieve nonlinear model but they do not require the explicit form of nonlinear mapping function. Moreover they need no assumption about the underlying probability distribution of errors. Through numerical studies on two artificial an two real data sets we show their effectiveness on the estimation performance at various confidence levels.

• Smart Structures and Systems
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• v.19 no.4
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• pp.431-439
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• 2017

This investigation is aimed to develop a model of experimental-computation determination of a support moment of a cantilever beam loaded with concentrated force at its end including the optimal choice of coordinates of deflection data points and parameters of transformation of deflection data in case of insufficient accuracy of the assignment of initial parameters (support settlement, angle of rotation of the bearing section) and cantilever beam length. The influence of distribution and characteristics of sensors on the cantilever beam on the accuracy of determining the support moment which improves in the course of transition from the uniform distribution of sensors to optimal non-uniform distribution is shown. On the basis of the theory of inverse problems the method of transformation reduction at numerical differentiation of deflection functions has been studied. For engineering evaluation formulae of uncertainty estimate to determine a support moment of a cantilever beam at predetermined uncertainty of measurements using sensors have been obtained.

• Journal of Korean Society for Quality Management
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• v.40 no.2
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• pp.145-155
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• 2012

The purpose of this study is to suggest the direction of improving service quality in the defense logistics support. For this, this study compares and analyzes the perceived service quality between customer(using unit) and defense logistics support unit by using SERVPERF model. Supply, military meals, and maintenance are carrying out the mission as core function of defense logistics support and also encounter with customer. In this empirical analysis, the service quality is composed of four factors, and there are significant difference in perception level of service quality between them. Also, the relationship between factors of service quality and revisit intention shows significant difference statistically, and the customer orientation and responsiveness are key affecting factors on revisit intention.

• Journal of Family Resource Management and Policy Review
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• v.10 no.3
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• pp.1-21
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• 2006

The purpose of this study was to examine the variables which account for grandchildren caregivers' subjective well-being. The subjects of this research were 100 grandmothers who are currently caring for grandchildren. The instruments used for this study were 'Job Content Questionnaire' by Karasek(1979), 'Family Support Inventory for Worker' by King, Mattimore, King, & Adams(1995), 'Social Support Scale' by Park(1985) and 'Psychological Positive Functioning' by Ryff(1989). Data was analyzed by descriptive statistics, Pearson's correlations and hierarchical multiple regression. The major results of this study are as follows; First, grandchildren caregiving's demand level was negatively related to grandmothers' subjective well-being, but it's control and support level were positively related to them. Second, the variables that explained grandchildren caregivers' sutjective well-being were their marital status, income, material reward, and family support. When they had a husband, the more money they had, and with more rewards for caregiving plus family support given, the more positive subjective well-being they had.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.861-864
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• 2005

A LCD glass plate is supported by multi-pin and golf-tee type support. In the FEM analysis, the support condition is treated as simply supported boundary .condition. In this study, the optimization on the location of multi-simply support is conducted. The size optimization method of ANSYS 8.0 is used as the optimization tool to search for the optimal support location of LCD glass plate. In the manufacturing process, the support condition is a fatal factor of quality control of LCD production. From the results of optimization, deflection decreases 51% compared with the original model.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.422-432
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• 2019

A hybrid kernel function of support vector machine is proposed to improve the classification performance of power quality disturbances. The kernel function mathematical model of support vector machine directly affects the classification performance. Different types of kernel functions have different generalization ability and learning ability. The single kernel function cannot have better ability both in learning and generalization. To overcome this problem, we propose a hybrid kernel function that is composed of two single kernel functions to improve both the ability in generation and learning. In simulations, we respectively used the single and multiple power quality disturbances to test classification performance of support vector machine algorithm with the proposed hybrid kernel function. Compared with other support vector machine algorithms, the improved support vector machine algorithm has better performance for the classification of power quality signals with single and multiple disturbances.

• Journal of Wind Energy
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• v.9 no.4
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• pp.16-23
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• 2018

A damage detection method for the tripod support structure of offshore wind turbines is presented for structural health monitoring. A finite element model of a prototype tripod support structure is established and the modal properties are calculated. The degree and location of the damage are estimated based on the neural network technique using the changes of natural frequencies and mode shape due to the damage. The stress distribution occurring in the support structure is obtained by a dynamic analysis for the wind turbine system to select the output data of the neural network. The natural frequencies and mode shapes for 36 possible damage scenarios were used for the input data of the learned neural network for damage assessment. The estimated damages agreed reasonably well with the accurate ones. The presented method could be effectively applied for damage detection and structural health monitoring of various types of support structures of offshore wind turbines.