• Journal of Distribution Science
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• v.17 no.3
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• pp.85-95
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• 2019

Purpose - The existing marketing studies using Social Network Analysis have assumed that network structure variables are time-invariant. However, a node's network position can fluctuate considerably over time and the node's network structure can be changed dynamically. Hence, if such a dynamic structural network characteristics are not specified for virtual goods purchase model, estimated parameters can be biased. In this paper, by comparing a time-invariant network structure specification model(base model) and time-varying network specification model(proposed model), the authors intend to prove whether the proposed model is superior to the base model. In addition, the authors also intend to investigate whether coefficients of network structure variables are random over time. Research design, data, and methodology - The data of this study are obtained from a Korean social network provider. The authors construct a monthly panel data by calculating the raw data. To fit the panel data, the authors derive random effects panel tobit model and multi-level mixed effects model. Results - First, the proposed model is better than that of the base model in terms of performance. Second, except for constraint, multi-level mixed effects models with random coefficient of every network structure variable(in-degree, out-degree, in-closeness centrality, out-closeness centrality, clustering coefficient) perform better than not random coefficient specification model. Conclusion - The size and importance of virtual goods market has been dramatically increasing. Notwithstanding such a strategic importance of virtual goods, there is little research on social influential factors which impact the intention of virtual good purchase. Even studies which investigated social influence factors have assumed that social network structure variables are time-invariant. However, the authors show that network structure variables are time-variant and coefficients of network structure variables are random over time. Thus, virtual goods purchase model with dynamic network structure variables performs better than that with static network structure model. Hence, if marketing practitioners intend to use social influences to sell virtual goods in social media, they had better consider time-varying social influences of network members. In addition, this study can be also differentiated from other related researches using survey data in that this study deals with actual field data.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.5
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• pp.291-304
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• 2020

This paper examines the factors that drive temporal income diversification in rural areas of the Mekong River Delta in Vietnam, based on a framework that conceptualized diversification as a function of a household's capacity to diversify and incentives (both push and pull factors) to diversify. Drawing from five rounds of the Vietnam Living Standard Measurement Surveys covering a 13-year span (1993-2006), two panel datasets made from five cross-sectional samples are used for the analyses. The data are drawn from the Vietnam General Statistics Office. Both tobit model and Ordinary Least Squares model with random and fixed effects are applied. The main points emerging from the analysis is that income diversification is strongly influenced by household labor capacity. The relationship between household labor capacity and increasing insertion in non-farming wage activities is not driven by unobserved time-invariant factors such as household ability and motivation, but is instead driven by the higher labor capacity of households. In terms of the other household capacity variables, the effect of farm size is much larger in terms of retaining households in traditional occupations as compared to pushing them towards non-farm wage employment. Other variables such as household access to financial capital do not play an important role.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.1
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• pp.17-24
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• 2013

In this paper, a micro-mechanical failure prediction program is developed based on SIFT (Strain Invariant Failure Theory) by using the multi-scale modeling method for fiber-reinforced composite materials. And the failure analysis are performed for open-hole composite laminate specimen in order to verify the developed program. First of all, the critical strain invariants are obtained through the tensile tests for three types of specimens. Also, the matrices of strain amplification factors are determined through the finite element analysis for micro-mechanical model, RVE (Representative Volume Element). Finally, the microscopic failure analysis is performed for the open-hole composite laminate specimen model by applying a failure load obtained from tensile test, and the predicted failure indices are evaluated for verification of the developed program.

• Journal of Digital Contents Society
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• v.12 no.3
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• pp.279-289
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• 2011

The latest hardware and software techniques are combined to give safe walking guidance and convenient service of realtime walking assistance system for visually impaired person. This system consists of obstacle detection and perception, place recognition, and sign recognition for pedestrian can safely walking to arrive at their destination. In this paper, we exploit the sign object detection system in subway station for sign recognition that one of the important factors of walking assistance system. This paper suggest the adaptive feature map that can be robustly extract the sign object region from complexed environment with light and noise. And recognize a sign using fast zernike moment features which is invariant under translation, rotation and scale of object during walking. We considered three types of signs as arrow, restroom, and exit number and perform the training and recognizing steps through adaboost classifier. The experimental results prove that our method can be suitable and stable for real-time system through yields on the average 87.16% stable detection rate and 20 frame/sec of operation time for three types of signs in 5000 images of sign database.

• Journal of the Korean Society of School Health
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• v.21 no.2
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• pp.23-33
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• 2008

Purpose: Internet is one of the essential tools in South Korean adolescent life. Recently, researchers suggest that Internet use is positively associated with teens' mental health problems such as depression and suicide. Thus, this study explored a relationship between Internet use and suicide ideation among South Korean adolescents. Methods:　Secondary data, the three-wave Korean Youth Panel Survey, were analyzed. First, in terms of the levels of Internet use and suicidal ideation, t-test was used for examining a gender difference, and Analysis of Variance were used for examining differences across three points in time(waves 2 - 4). Second, logistic analysis was performed to examine the significant association between Internet use and suicide ideation after controlling for the other factors' effects. In this analysis, Fixed Effect Regression Method(FERM) was incorporated as well. FERM was useful in adjusting for the effects of time-invariant factors even without measuring them. As a result, it was possible to obtain more accurate findings. Results: Adolescent depression was an important factor influencing the association between Internet use and suicide ideation. After controlling for the effect of depression, the relationship between Internet use and suicide ideation was no longer statistically significant. Conclusion:　As a proxy to identify teens who are obsessed with suicide ideation, levels of Internet use do not seem useful. Instead, it is necessary to examine teens' access to websites related to suicide.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup1
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• pp.55-63
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• 2016

Smoking and harmful drinking dramatically increase health risks but little is known about their cooccurrence and factors that influence this co-habit, limiting development and implementation of appropriately targeted prevention interventions. This study was conducted among youth aged 10-24 years old in the Chi Linh Demographic - Epidemiological Surveillance System (CHILILAB DESS). The total numbers in the first, second and third rounds in 2006, 2009 and 2013 were 12,406, 10,211, and 7,654, respectively. A random-effects logit model controlling for both time-variant and time-invariant variables was applied to explore factors associated with current smoking, harmful drinking, and occurrence of smoking and harmful drinking together. We found dramatically increasing trends in current smoking, harmful drinking and co-occurrence among youth. Our results indicate similar health problems among youth in peri-urban areas in Vietnam. Demographic characteristics (older age, being male, being unmarried, and having informal work) appeared to be predictors for smoking and drinking behaviour. Besides, peer and family members had significant influence on smoking, whereas having a close-friend who was smoking was the most important variable. The results suggested that smoking and harmful drinking should not be solved with separate, stand-alone interventions but rather with integrated efforts.

• International Journal of Aerospace System Engineering
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• v.2 no.2
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• pp.73-78
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• 2015

According to the characteristic of carrier-based aircraft, the method of solving safe set during arresting landing is discussed in this paper based on optimal control and invariant set theory. The safe sets of carrier aircraft are evaluated in different states on the characteristic of longitudinal augmented system by using the level set method. Then, the influence on the boundary of safe set under various factors is analyzed. At last, the maneuverability envelope protection is established based on the corresponding theory, and the validity of the system is verified through simulation. The results demonstrate preliminarily that: compared with mass and thrust, the elevator is the greatest influence factor for the boundary of safe set; the dynamic trajectory of carrier-based aircraft can be located at the interior of safe set effectively with the maneuverability envelope protection.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.413-423
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• 2022

The NHIS provides free or highly subsidized healthcare to all people by providing financial fortification. However, the financial sustainability of the scheme is threatened by numerous factors. Therefore, this work sought to provide a solution to process claims intelligently. The provided Petri net model demonstrated successful data flow among the various participant. For efficiency, scalability, and performance two main subsystems were modelled and integrated - data input and claims processing subsystems. We provided smart claims processing algorithm that has a simple and efficient error detection method. The complexity of the main algorithm is good but that of the error detection is excellent when compared to literature. Performance indicates that the model output is reachable from input and the token delivery rate is promising.

• Journal of KIISE:Software and Applications
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• v.36 no.11
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• pp.960-966
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• 2009

A manifold is used to represent a relationship between high-dimensional data samples in low-dimensional space. In human pose estimation, it is created in low-dimensional space for processing image and 3D body configuration data. Manifold learning is to build a manifold. But it is vulnerable to silhouette variations. Such silhouette variations are occurred due to view-change, person-change, distance-change, and noises. Representing silhouette variations in a single manifold is impossible. In this paper, we focus a silhouette variation problem occurred by view-change. In previous view invariant pose estimation methods based on manifold learning, there were two ways. One is modeling manifolds for all view points. The other is to extract view factors from mapping functions. But these methods do not support one by one mapping for silhouettes and corresponding body configurations because of unsupervised learning. Modeling manifold and extracting view factors are very complex. So we propose a method based on triple manifolds. These are view manifold, pose manifold, and body configuration manifold. In order to build manifolds, we employ biased manifold learning. After building manifolds, we learn mapping functions among spaces (2D image space, pose manifold space, view manifold space, body configuration manifold space, 3D body configuration space). In our experiments, we could estimate various body poses from 24 view points.

• Journal of Korean Society for Quality Management
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• v.17 no.2
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• pp.17-26
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• 1989

This paper is concerned with forecasting the existing number of errors in the computer software and optimizing the stopping time of the software test based upon the forecasted number of errors. The most commonly used models have assessed software reliability under the assumption that the software failure late is proportional to the current fault content of the software but invariant to time since software faults are independents of others and equally likely to cause a failure during testing. In practice, it has been observed that in many situations, the failure rate decrease. Hence, this paper proposes a mathematical model to describe testing situations where the failure rate of software limearly decreases proportional to testing time. The least square method is used to estimate parameters of the mathematical model. A cost model to optimize the software testing time is also proposed. In this cost mode two cost factors are considered. The first cost is to test execution cost directly proportional to test time and the second cost is the failure cost incurred after delivery of the software to user. The failure cost is assumed to be proportional to the number of errors remained in the software at the test stopping time. The optimal stopping time is determined to minimize the total cost, which is the sum of test execution cast and the failure cost. A numerical example is solved to illustrate the proposed procedure.