• Communications for Statistical Applications and Methods
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• v.2 no.1
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• pp.137-144
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• 1995

Hierarchical Bayes estimations of exchangeable mean vector of a multivariate Poisson distribution are obtained. Since sophiscated analytic integration procedures are needed, the Laplace method is employed in order tocompute these estimations approximately. An example is presented.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.53 no.5
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• pp.249-256
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• 2004

This paper suggests a novel evaluation scheme of protective effectiveness in distribution systems. The adequacy of every parameter in a protective device is evaluated for the setting or correction rules. Then, the protective effectiveness of a device, device-wise effectiveness, is obtained by the combination of the parametric evaluation results. The coordination-wise effectiveness between devices can be calculated by evaluating the parameters which contribute the performance of coordination. The protective effectiveness of the whole system can be obtained by combining the device-wise and coordination-wise effectiveness values. The rules, in this paper, are categorized into three groups; rules for single parameter, rules for coordination between parameters, and rules for coordination between protective devices to form a hierarchical calculation model. The proposed method is applied to a typical distribution network to show its effectiveness.

• 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.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.12 no.6
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• pp.47-58
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• 2002

The access control techniques, which can control unauthorized members to access to multicast service, have not been studied very often while there are a lot of on-going study on secure multicast architecture, multicast key distribution and sender authentication scheme have been studied. Multi level access control scheme in multicast can be used in a remote secure conference or to provide graduated multimedia services to each customers. In fact, multicast network has its own virtual networks according to different security levels. However, Early schemes are not effective when it protects unauthorized access in multi-access network environment. Furthermore this scheme does not provide us with hierarchical access control mechanism. This paper, therefore, proposes hierarchical access control scheme to provide the effectiveness in network layer by security level comparison. And we also suggests hierarchical key distribution scheme for multi level access control in application layer and effective hierarchical key renewal scheme in dynamic multicast environment which is easy to join and leaving the multicast group.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1188-1195
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• 2014

This paper presents an analytical technique for reliability evaluation of electrical distribution network (EDN) containing distributed generation (DG). Based on hierarchical levels of circuit breaker controlling zones and feeder sections, a directed-relation-graph (DRG) for an END is formed to describe the hierarchical structure of the EDN. The reliability indices of EDN and load points can be evaluated directly using the formed DRG, and the reliability evaluation of an EDN containing DGs can also be done without re-forming the DRG. The proposed technique incorporates multi-state models of photovoltaic and diesel generations, as well as weather factors. The IEEE-RBTS Bus 6 EDN is used to validate the proposed technique; and a practical campus EDN containing DG was also analyzed using the proposed technique.

• Journal of Korea Water Resources Association
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• v.54 no.9
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• pp.643-656
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• 2021

Recently, water supply management technology is highly developed, and a computer simulation model plays a critical role for estimating hydraulics and water quality in water distribution networks (WDNs). However, a simulation of complex large water networks is computationally intensive, especially for the water quality simulations, which require a short simulation time step and a long simulation time period. Thus, it is often prohibitive to analyze the water quality in real-scale water networks. In this study, in order to improve the computational efficiency of water quality simulations in complex water networks, a hierarchical water-quality-simulation technique was proposed. The water network is hierarchically divided into two sub-networks for improvement of computing efficiency while preserving water quality simulation accuracy. The proposed approach was applied to a large-scale real-life water network that is currently operating in South Korea, and demonstrated a spatiotemporal distribution of chlorine concentration under diverse chlorine injection scenarios.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.7
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• pp.1344-1356
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• 2009

The DDS (Data Distribution Service) is a data-centric communication technology that provides an efficient communication service that supports a dynamic plug & play through an automatic setting of participants' location information for each data (Topic) by using DDS discovery technique. This paper proposes the hierarchical-structured DDS discovery technique (SPDP-TBF) suitable for the large-scale distributed systems by comparing and analyzing the existing DDS discovery techniques in terms of performance and problem areas. The proposed SPDP-TBF performs the periodic discovery of the involved participants only by having separate hierarchical managers which take charge of the registration and search (of participants) so that a participant sends its information to the related participants only, and it enhances the effectiveness of the message transfer. Moreover, the proposed SPDP-TBF provides the improved scalability by performing the hierarchical discovery through hierarchical manager nodes so that it can be applied to the large-scale distributed system.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.499-505
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• 1998

In developing an automated surface inspect algorithm, we have designed a hierarchical classifier using neural network. The defects which exist on the surface of cold mill strip have a scattering or singular distribution. We have considered three major problems, that is preprocessing, feature extraction and defect classification. In preprocessing, Top-hit transform, adaptive thresholding, thinning and noise rejection are used Especially, Top-hit transform using local minimax operation diminishes the effect of bad lighting. In feature extraction, geometric, moment, co-occurrence matrix, and histogram ratio features are calculated. The histogram ratio feature is taken from the gray-level image. For defect classification, we suggest a hierarchical structure of which nodes are multilayer neural network classifiers. The proposed algorithm reduced error rate by comparing to one-stage structure.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.2C
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• pp.193-200
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• 2003

In this paper, we propose a motion estimation method using hierarchical triangulation that changes the triangular mesh structure according to it's motion activity. The subdivision of triangular mesh is performed from the amount of motion that is calculated from the variance of image difference. As a result, node distribution is concentrated on the region of high activity. The subdivision method that makes it possible to yield hierarchical triangular mesh is proposed as well as the additional information reduction coding method for hierarchical mesh structure is described. By the simulation, proposed method have better performance than the conventional BMA(Block Match Algorithm) and the other mesh based method.

• ETRI Journal
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• v.45 no.1
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• pp.93-104
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• 2023

Coreference resolution is a task in discourse analysis that links several headwords used in any document object. We suggest pointer networks-based coreference resolution for Korean using multi-task learning (MTL) with an attention mechanism for a hierarchical structure. As Korean is a head-final language, the head can easily be found. Our model learns the distribution by referring to the same entity position and utilizes a pointer network to conduct coreference resolution depending on the input headword. As the input is a document, the input sequence is very long. Thus, the core idea is to learn the word- and sentence-level distributions in parallel with MTL, while using a shared representation to address the long sequence problem. The suggested technique is used to generate word representations for Korean based on contextual information using pre-trained language models for Korean. In the same experimental conditions, our model performed roughly 1.8% better on CoNLL F1 than previous research without hierarchical structure.