• Proceedings of the IEEK Conference
• /
• 2002.07a
• /
• pp.235-237
• /
• 2002

As the integrated circuit technology gets developed, a circuit size of more than thousands of transistors becomes normal. A hierarchical design is unavoidable due to a huge circuit size. It is important how we can consider hierarchical structure in circuit delay analysis. In this paper we present an accurate method to analyze the delay of circuit with hierarchical structure. Adding the notion of global false path to the hierarchical timing analysis performs more accurate timing analysis.

• Communications for Statistical Applications and Methods
• /
• v.9 no.1
• /
• pp.115-128
• /
• 2002

Hierarchical models are widely used for inference on correlated parameters as a compromise between underfitting and overfilling problems. In this paper, we take a Bayesian approach to analyzing hierarchical models and suggest a Markov chain Monte Carlo methods to get around computational difficulties in Bayesian analysis of the hierarchical models. We apply the method to a real data on smoking and lung cancer which are collected from cities in China.

• Journal of the Korean Data and Information Science Society
• /
• v.13 no.2
• /
• pp.227-234
• /
• 2002

In this paper, we consider hierarchical Bayes generalized linear models for the analysis of longitudinal count data. Specifically we introduce the hierarchical Bayes random effects models. We discuss implementation of the Bayes procedures via Markov chain Monte Carlo (MCMC) integration techniques. The hierarchical Baye method is illustrated with a real dataset and is compared with other statistical methods.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.21 no.6
• /
• pp.933-941
• /
• 1997

In the analysis of thin elastic structures such as plate and shell-like structures, classical lower-order theories like Kirchhoff and Reissner-Mindin theories are insufficient to describe the behavior of such structures in the region where the state of stresses is complex. On the other hand, the fully three dimensional theory of linear elasticity can provide desired analysis accuracy, but requires expensive computational implementation compared to the classical theories. This paper is concerned with the development of hierarchical models for elastic structures which can be used for hierarchical modeling for the analysis of such structures. Derivation and limit model analysis (when the thickness of structures tends to zero) of hierarchical models are presented together with a introduction of modeling error estimation. Also, numerical results supporting theoretical results are given.

• 한국정보통신설비학회:학술대회논문집
• /
• 2008.08a
• /
• pp.556-558
• /
• 2008

Secure broadcasting is requirement for payment of TV systems, government or company. Hierarchical key management for access control provides efficient key management in those environment. Also, time-bound hierarchical key management technique generates different keys in each time period. In 2004, Tzeng proposed a time-bound cryptgraphic key assignment scheme for access control in a hierarchy and in 2008, Bertino et al proposed an efficient time-bound hierarchical key management scheme for secure broadcasting. Tzeng's scheme and Bertino et al's scheme are organized in different environment and primitive. In this paper, we analysis above two time-bound hierarchical key management scheme.

• The Korean Journal of Applied Statistics
• /
• v.5 no.1
• /
• pp.1-8
• /
• 1992

Using the partitioned matrices, we presents a method of analysis which are not needed inverse matrix for Hierarchical Group Divisible(HGD) designs whose treatments are composed of 2.2.2.

• The Korean Journal of Applied Statistics
• /
• v.14 no.1
• /
• pp.161-175
• /
• 2001

Meta-analysis refers to quantitative methods for combining results from independent studies in order to draw overall conclusions. Hierarchical models including selection models are introduced and shown to be useful in such Bayesian meta-analysis. Semiparametric hierarchical models are proposed using the Dirichlet process prior. These rich class of models combine the information of independent studies, allowing investigation of variability both between and within studies, and weight function. Here we investigate sensitivity of results to unobserved studies by considering a hierachical selection model with including unknown weight function and use Markov chain Monte Carlo methods to develop inference for the parameters of interest. Using Bayesian method, this model is used on a meta-analysis of twelve studies comparing the effectiveness of two different types of flouride, in preventing cavities. Clinical informative prior is assumed. Summaries and plots of model parameters are analyzed to address questions of interest.

• Journal of KIISE:Computer Systems and Theory
• /
• v.30 no.10
• /
• pp.544-555
• /
• 2003

Since the result data from DNA microarray experiments contain a lot of gene expression information, adequate analysis methods are required. Hierarchical clustering is widely used for analysis of gene expression profiles. In this paper, we study leaf-ordering, which is a post-processing for the dendrograms output by hierarchical clusterings to improve the efficiency of DNA microarray data analysis. At first, we analyze existing leaf-ordering algorithms and then present new approaches for leaf-ordering. And we introduce a software HCLO(Hierarchical Clustering ＆ Leaf-Ordering Tool) that is our implementation of hierarchical clustering, some of existing leaf-ordering algorithms and those presented in this paper.

• Journal of Information Technology Services
• /
• v.17 no.2
• /
• pp.165-177
• /
• 2018

Recently, online commerces are becoming more common due to factors such as mobile technology development and smart device dissemination, and online review has a big influence on potential buyer's purchase decision. This study presents a set of analytical methodologies for understanding the meaning of customer reviews of products in online transaction. Using techniques currently developed in deep learning are implemented Hierarchical Attention Network for analyze meaning in online reviews. By using these techniques, we could solve time consuming pre-data analysis time problem and multiple topic problems. To this end, this study analyzes customer reviews of laptops sold in domestic online shopping malls. Our result successfully demonstrates over 90% classification accuracy. Therefore, this study classified the unstructured text data in the semantic analysis and confirmed the practical application possibility of the review analysis process.

• Communications for Statistical Applications and Methods
• /
• v.9 no.2
• /
• pp.315-324
• /
• 2002

For estimating the error variance under the relative squared error loss in two-way analysis of variance models, we provide a class of hierarchical Bayes estimators and then derive a subclass of the hierarchical Bayes estimators, each member of which dominates the best multiple of the error sum of squares which is known to be minimax. We also identify a subclass of non-minimax hierarchical Bayes estimators.