• Journal of Labour Economics
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• v.17 no.2
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• pp.291-318
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• 1995

• Korean Journal of Social Welfare
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• v.62 no.4
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• pp.171-192
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• 2010

The purpose of this study is to examine factors on wage of the Disabled. This study attempts to identify organizational effects on wage of the disabled. Then, this study adopts hierarchical linear model for the study purpose. Data used for this article is the survey on the vocational rehabilitation facilities in Seoul. The results are as follows. First, wage of the disabled is different from organizations as well as individuals. So, there are necessities in the consideration of organizational effects and the application of hierarchical linear model. Second, effects on wage of the disabilities controlling individual factors such as age, educational level, period using the facilities, sex, whether or not beneficiary, type of disability are different from organization. Finally, there are interaction effects of type of disability and organizational character variables. The implications of these findings are as follows. First, more political concerns should be given on the management of vocational rehabilitation facilities. Second, it is needed to concern about vocational rehabilitation of the mentally disabled.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2068-2086
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• 2011

Based on the quincunx sub-sampling grid, the New Interleaved Hierarchical INTerpolation (NIHINT) method is recognized as a superior pyramid data structure for the lossless and progressive coding of natural images. In this paper, we propose a new image interpolation algorithm, Edge Adaptive Hierarchical INTerpolation (EAHINT), for a further reduction in the entropy of interpolation errors. We compute the local variance of the causal context to model the strength of a local edge around a target pixel and then apply three statistical decision rules to classify the local edge into a strong edge, a weak edge, or a medium edge. According to these local edge types, we apply an interpolation method to the target pixel using a one-directional interpolator for a strong edge, a multi-directional adaptive weighting interpolator for a medium edge, or a non-directional static weighting linear interpolator for a weak edge. Experimental results show that the proposed algorithm achieves a better compression bit rate than the NIHINT method for lossless image coding. It is shown that the compression bit rate is much better for images that are rich in directional edges and textures. Our algorithm also shows better rate-distortion performance and visual quality for progressive image transmission.

• Journal of Information Technology Applications and Management
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• v.17 no.4
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• pp.19-38
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• 2010

This paper investigates the effect of stress on knowledge creation. The goal stress of resource inadequacy and job stress had negative influences on knowledge creation. However, the cohesion and mastery climate of team had positive influence on knowledge creation. Therefore this paper verifies the moderate role of the cohesion and mastery climate of team on the relationship between stress and knowledge creation. The model developed was tested using data collected from knowledge based industry with 375 members in 69 teams in 12 different firms. A Hierarchical Linear Model (HLM) was used to test the hypotheses generated from the model. Results show that job stress had a negative influence on knowledge creation as we expected but the goal stress didn't. The mastery climate of team affected knowledge creation positively and moderated the relationship between the goal stress and knowledge creation. Furthermore, the team cohesion had a positive influence on knowledge creation. The study provided some implications that practitioners should consider the stress when they design jobs for team members and suggest them the way to manage their job stress when they work.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.12
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• pp.6017-6037
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• 2017

In a multi-resolution image encoding system, the image is encoded into a single file as a layer of bit streams, and then it is transmitted layer by layer progressively to reduce the transmission time across a low bandwidth connection. This encoding scheme is also suitable for multiple decoders, each with different capabilities ranging from a handheld device to a PC. In our previous work, we proposed an edge adaptive hierarchical interpolation algorithm for multi-resolution image coding system. In this paper, we enhanced its compression efficiency by adding three major components. First, its prediction accuracy is improved using context adaptive error modeling as a feedback. Second, the conditional probability of prediction errors is sharpened by removing the sign redundancy among local prediction errors by applying sign flipping. Third, the conditional probability is sharpened further by reducing the number of distinct error symbols using error remapping function. Experimental results on benchmark data sets reveal that the enhanced algorithm achieves a better compression bit rate than our previous algorithm and other algorithms. It is shown that compression bit rate is much better for images that are rich in directional edges and textures. The enhanced algorithm also shows better rate-distortion performance and visual quality at the intermediate stages of progressive image transmission.

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.132-139
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• 2004

A range $Top-\kappa$ query returns top k records in order of a measure attribute within a specified region on multi-dimensional data, and it is a powerful tool for analysis in spatial databases and data warehouse environments. In this paper, we propose an algorithm for answering the query via selective traverse of a Hierarchical Max R-Tree(HMR-tree). It is possible to execute the query by accessing only a small part of the leaf nodes in the query region, and the query performance is nearly constant regardless of the size of the query region. The algorithm manages the priority queue efficiently to reduce cost of handling the queue and the proposed HMR-tree can guarantee the same fan-out as the original R-tree.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.8
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• pp.1168-1179
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• 2007

The objective of this research is to validate the BRQ(Brand Relationship Quality) Construct perceived by fashion product consumers. In order to establish and verify the BRQ scale, qualitative survey and quantitative survey were conducted together. 1592 copies of questionnaire were distributed to women in their 20s to 40s living in Seoul and other metropolitan areas from Dec. 26, 2005 to Jan. 8, 2006, and 723 copies of them were used for statistical data. Samplel(n=482)was used for empirical analysis, and sample2(n=241) was used for cross validity test. The data was analyzed using Exploratory Factor Analysis, Confirmatory Factor Analysis, and Pearson's Correlation Analysis. BRQ emerged from exploratory factor analysis as the hierarchical construct composed of six facets including 'self-connective attachment', 'symbol/mystery', 'trust', 'nostalgia', 'intimacy', and 'knowledge'. As the fit of this structural model was not good as a result of Confirmatory Factor Analysis, it was revised to have better fitting. Finally, empirical survey results indicate the hierarchical construct consisting of eight distinct BRQ facets including 'love/commitment', 'self-connection', 'symbol', 'mystery', 'trust', 'nostalgia', 'intimacy', and 'knowledge' as best representing the final 39item BRQ Scale. Reliability, construct validity, and cross validity of the construct were verified.

• Communications for Statistical Applications and Methods
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• v.28 no.1
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• pp.59-79
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• 2021

Value at Risk (VaR) is one of the most common risk management tools in finance. Since a portfolio of several assets, rather than one asset portfolio, is advantageous in the risk diversification for investment, VaR for a portfolio of two or more assets is often used. In such cases, multivariate distributions of asset returns are considered to calculate VaR of the corresponding portfolio. Copulas are one way of generating a multivariate distribution by identifying the dependence structure of asset returns while allowing many different marginal distributions. However, they are used mainly for bivariate distributions and are not widely used in modeling joint distributions for many variables in finance. In this study, we would like to examine the performance of various copulas for high dimensional data and several different dependence structures. This paper compares copulas such as elliptical, vine, and hierarchical copulas in computing the VaR of portfolios to find appropriate copula functions in various dependence structures among asset return distributions. In the simulation studies under various dependence structures and real data analysis, the hierarchical Clayton copula shows the best performance in the VaR calculation using four assets. For marginal distributions of single asset returns, normal inverse Gaussian distribution was used to model asset return distributions, which are generally high-peaked and heavy-tailed.

• Korean Journal of Childcare and Education
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• v.20 no.2
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• pp.83-103
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• 2024

Objective: This study aimed to investigate the effects of children's characteristics and childcare teachers' attributes on the frequency and level of imaginative play in two-year-old classrooms. Methods: The study involved 191 toddlers, their mothers, and 32 teachers from childcare centers. Toddler characteristics encompassed temperament along with demographic variables such as gender and age. Teacher' attributes related to play included playfulness, play-support belief, and interactions with toddlers. Data analysis was conducted using SPSS 22.0 and HLM 8.2 software, employing basic analysis, hierarchical linear analysis, and hierarchical regression analysis. Results: First, as toddlers' age increased, both the frequency and level of their imaginative play increased. Second, individual-level model analysis revealed a positive effect of toddlers' extroversion on the level of imaginative play. Third, the class-level model results indicated that teachers' emotions had a negative effect, whereas their encouragement positively influenced the level of imaginative play. Conclusion/Implications: The significance of this study lies in its utilization of a multilayered model analysis, which offers a more robust examination of variable influences by accounting for hierarchical data structures.

• Journal of Creative Information Culture
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• v.6 no.1
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• pp.41-48
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• 2020

In order to represent and process spatial data, hierarchical data structures such as a quadtree or a bintree are used. Various approaches for linearly representing the bintree have been proposed. S-Tree has the advantage of compressing the storage space by expressing binary region image data as a linear binary bit stream, but the higher the resolution of the image, the longer the length of the binary bit stream, the longer the storage space and the lower the search performance. In this paper, we construct a hierarchical structure of multiple separated bintrees with a full binary tree structure and express each bintree as two linear binary bit streams to reduce the range required for image search. It improves the overall search performance by performing a simple number conversion instead of searching directly the binary bit string path. Through the performance evaluation by the worst-case space-time complexity analysis, it was analyzed that the proposed method has better search performance and space efficiency than the previous one.