• Journal of KIISE:Computing Practices and Letters
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• v.15 no.7
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• pp.500-504
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• 2009

A reliability of software is a type of nonfunctional requirement. Traditionally, a validation of the reliability is processed at the integration phase in software development life cycle. However, it increases the cost and the risk for the development. In this paper, we propose reliability analysis method based on mathematical analytic model at the architecture design phase of the development process as follows. First, we propose the software modeling methodology for reliability analysis using Hierarchical combined Queueing Petri Nets(HQPN). Second, we derive the Markov Reward Model from the HQPN based model. We apply our approach to the video conference system to verify the usefulness of our approach. Our approach supports quantitative evaluation of the reliability.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.4
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• pp.375-380
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• 2009

Bit error rate(BER) performance of each bit for hierarchical M-ary phase shift keying(H-MPSK) modulation scheme is changed according to the phase parameters. Thus, a method to find the phase parameters appropriate to the requests of the system is needed. In this paper, we propose a method to obtain the phase parameters from an approximate approach of BER for H-MPSK and verify a validity of the proposed method through the previously provided expression for analyzing an exact error probability of H-MPSK.

• 한국경영정보학회:학술대회논문집
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• 2007.11a
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• pp.300-305
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• 2007

재무성과와 지식자산을 함께 관리할 수 있는 통합적 성과평가 방법을 도입함으로써 미래 기업가치를 제고시킬 수 있는 필요성이 증가하고 있다. 국제적인 추세에 발맞추어 본 연구의 목적은 지식자산 평가에 대한 기존 연구와 Kaplan & Norton이 주창(1992)한 균형잡힌 성과기록표(Balanced Score Card : BSC)를 이용하여 지식자산 평가 지표 개발과 이러한 평가를 위해 Saaty가 개발한(1980) 계층적 분석과정(Analytic Hierarchy Process : AHP)방법론을 적용한 평가모델을 제시하고, 국내 A은행을 대상으로 지점을 평가하는 연구를 수행하였다.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.4
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• pp.205-211
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• 2019

Steganalysis is a technique that aims to detect and recover data hidden by steganography. Steganalytic methods detect hidden data by analyzing visual and statistical distortions caused during data embedding. However, for recovering the hidden data, they need to know which steganographic methods the hidden data has been embedded by. Therefore, we propose a hierarchical convolutional neural network (CNN) structure that identifies a steganographic method applied to an input image through multi-level classification. We trained four base CNNs (each is a binary classifier that determines whether or not a steganographic method has been applied to an input image or which of two different steganographic methods has been applied to an input image) and connected them hierarchically. Experimental results demonstrate that the proposed hierarchical CNN structure can identify four different steganographic methods (LSB, PVD, WOW, and UNIWARD) with an accuracy of 79%.

• Proceedings of the Korean Society of Computer Information Conference
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• 2009.01a
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• pp.337-344
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• 2009

본 연구는 노인복지시설의 성과평가에 미치는 우선순위 결정요인을 파악한다. 이론적 고찰과 선행연구를 통하여 노인 복지시설에 미치는 결정요인을 설정하였다. Saaty의 계층분석과정(Analytic Hierarchy Process; AHP)를 활용하여 각각의 결정요인들에 대한 가중치와 우선순위를 분석하였다. 노인복지는 특정한 분야로 한정되어 있지 않기 때문에 양적인 방법만으로 설명하는 것은 한계가 있다. 따라서 질적 및 양적 방법을 활용할 수 있는 계층분석과정방법과 SPSS프로그램을 이용하여 실증분석을 하였다. 노인복지시설의 분석결과를 요약하면 투입에 대한 상대적 중요도를 분석한 결과 예산이 가장 높게 나왔으며, 산출에 대한 상대적 중요도를 분석한 결과는 운영체계화와 노인복지성이 가장 높게 나타났다. 세부항목 간의 상대적 중요도를 분석한 결과는 결산서와 전문인력이 가장 높게 나타났다. 시설유형별 투입요인은 이용시설과 생활시설 모두 예산이 가장 높게 나타났으며, 산출요인은 이용시설은 운영체계화, 생활시설은 노인복지성이 가장 높게 나타났다. 노인복지시설에 미치는 결정요인에 따른 몇 가지 구체적인 정책적 시사점을 대안으로 제시하였다.

• Journal of Korea Water Resources Association
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• v.42 no.3
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• pp.177-190
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• 2009

Rehabilitation projects for old water mains typically require considerable capital investments. One of the economical ways of pursuing the rehabilitation projects is to focus on a specific area within the entire region under management. In this paper the hierarchical clustering methods that analyze spatial inter-relationship of location data are applied to about 8,000 water leak location data recorded in a case study area from 1992 to 1997. Among the hierarchical clustering methods Single, Complete, and Average Linkage Methods are used to identify clusters of the water leak locations and to divide the area according to the defined clusters. By comparing the clusters identified by the clustering methods, the best clustering method for the case study area is suggested. Prioritization of the area for maintenance is obtained based on the water leak incident intensity for the clustered area using the suggested best clustering method.

• The Korean Journal of Applied Statistics
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• v.16 no.1
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• pp.101-115
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• 2003

Lately there has been much theoretical and applied interest in linear models with non-normal heavy tailed error distributions. Starting Zellner(1976)'s study, many authors have explored the consequences of non-normality and heavy-tailed error distributions. We consider hierarchical models including selection models under a skewed heavy-tailed e..o. distribution proposed originally by Chen, Dey and Shao(1999) and Branco and Dey(2001) with Dirichlet process prior(Ferguson, 1973) in order to use a meta-analysis. A general calss of skewed elliptical distribution is reviewed and developed. Also, we consider the detail computational scheme under skew normal and skew t distribution using MCMC method. Finally, we introduce one example from Johnson(1993)'s real data and apply our proposed methodology.

• Journal of the Korean Society for Library and Information Science
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• v.38 no.3
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• pp.103-118
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• 2004

Much investment has been to improve quality of web service as internet service is in pursuit of equilibrium. Web site of electronic library which offers various information has to be set a new standard for improving users service satisfaction by developing objsctive evaluation system. In this research we acquired standard of evaluation parameter such as contents, design, navigation, feedback, reference, privacy by analyzing domestic web site of electronic library We evaluated constructed model of usability evaluation using AHP(Analytic Hierarchy Process). We develop 'digital library web site evaluation model' based systematic analysis through polling category selected as evaluation guide.

• Journal of KIISE:Databases
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• v.29 no.5
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• pp.367-380
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• 2002

Due to recent increase in applications requiring huge amount of data such as spatial data analysis and image analysis, clustering on large databases has been actively studied. In a hierarchical clustering method, a tree representing hierarchical decomposition of the database is first created, and then, used for efficient clustering. Existing hierarchical clustering methods mainly adopted the bottom-up approach, which creates a tree from the bottom to the topmost level of the hierarchy. These bottom-up methods require at least one scan over the entire database in order to build the tree and need to search most nodes of the tree since the clustering algorithm starts from the leaf level. In this paper, we propose a novel top-down hierarchical clustering method that uses multidimensional indexes that are already maintained in most database applications. Generally, multidimensional indexes have the clustering property storing similar objects in the same (or adjacent) data pares. Using this property we can find adjacent objects without calculating distances among them. We first formally define the cluster based on the density of objects. For the definition, we propose the concept of the region contrast partition based on the density of the region. To speed up the clustering algorithm, we use the branch-and-bound algorithm. We propose the bounds and formally prove their correctness. Experimental results show that the proposed method is at least as effective in quality of clustering as BIRCH, a bottom-up hierarchical clustering method, while reducing the number of page accesses by up to 26～187 times depending on the size of the database. As a result, we believe that the proposed method significantly improves the clustering performance in large databases and is practically usable in various database applications.

• Asian Journal of Turfgrass Science
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• v.16 no.1
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• pp.41-47
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• 2002

For this study grasp quantitative humidity variation with planting stratification to various green space of calculation method, observed humidity distribution in the green space. with this data, coverage condition and humidity distribution, planting calculation method and humidity, planting stratification calculation method and humidity, analyzed by revolution analysis. In this result, as well as coverage condition, planting stratification effect humidity variation. increasing planting ratio (area) and planting volume (capacity) effect higher humidity. especially, if we compared between planting stratification calculation method and higher humidity, effect by a revolution coefficient and a correlation coefficient, effect relatively planting volume (capacity) higher than stratification ratio (area). today, in the index of higher humidity, planting calculation propose application of capacity method.