• The Korean Journal of Applied Statistics
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• v.22 no.4
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• pp.745-758
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• 2009

Cluster analysis is the automated search for groups of related observations in a data set. To group the observations into clusters many techniques has been proposed, and a variety measures aimed at validating the results of a cluster analysis have been suggested. In this paper, we compare complete linkage, Ward's method, K-means and model-based clustering and compute validity measures such as connectivity, Dunn Index and silhouette with simulated data from multivariate distributions. We also select a clustering algorithm and determine the number of clusters of Korean consumers based on Korean consumers' palatability scores for Hanwoo bull in BBQ cooking method.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.269-278
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• 2011

There are many researches that have considered the distribution functions and appropriate covariates corresponding to the scores in order to improve the accuracy of a diagnostic test, including the ROC curve that is represented with the relations of the sensitivity and the specificity. The ROC analysis was used by the regression model including some covariates under the assumptions that its distribution function is known or estimable. In this work, we consider a general situation that both the distribution function and the elects of covariates are unknown. For the ROC analysis, the mixtures of normal distributions are used to estimate the distribution function fitted to the credit evaluation data that is consisted of the score random variable and two sub-populations of parameters. The AUC measure is explored to compare with the nonparametric and empirical ROC curve. We conclude that the method using normal mixtures is fitted to the classical one better than other methods.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.12
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• pp.1476-1484
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• 1999

TV 방송 분야에서 다양한 정보와 상호 작용성을 제공하기 위해서 최근 기존 방송 내용인 A/V 스트림 외 부가정보 방송이 시도되고 있다. 데이타 방송에 대한 기존 연구는 대부분 고정된 내용의 데이타를 방송하는 환경을 가정하고 있어서 그 결과가 방송 내용의 변화가 많은 환경에 부적합하다. 본 논문에서는 데이타에 대한 접근이 반복되지 않을 가능성이 높고 사용자 접근 확률을 예상하기 어려운 상황에서 응답 시간을 개선하는 방안으로 수신 데이타를 무조건 캐쉬에 반입하고 교체가 필요한 경우 다음 방송 시각이 가장 가까운 페이지를 축출하는 사용자 단말 시스템에서의 캐슁 정책을 제안하였다. 제안된 캐쉬 관리 정책은 평균적인 캐쉬 접근 실패 비용을 줄임으로써 사용자 응답 시간을 개선하며, 서로 다른 스케줄링 기법을 사용하는 다양한 방송 제공자가 공존하는 환경에서 보편적으로 효과를 가져올 수 있다.Abstract Recently, many television broadcasters have tried to disseminate digital multimedia data in addition to the traditional content (audio-visual stream). The broadcast data need to be cached by a client system, to provide a reasonable response time for a user request. Previous studies assumed the dissemination of a fixed set of items, and the results are not suitable when broadcast items are frequently changed. In this paper, we propose a novel cache management scheme that chooses the replacement victim based on the remaining time to the next broadcast instance. The proposed scheme reduces response time, where it is hard to predict the probability distribution of user accesses. The caching policy we present here significantly reduces expected response time by minimizing expected cache miss penalty, and can be applied without difficulty to different scheduling algorithms.

• Journal of KIISE:Information Networking
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• v.36 no.2
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• pp.130-136
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• 2009

Delay and Disruption Tolerant Network (DTN) employs message delivery based on a store-and-forward method to conquer no guarantee of continuous end-to-end connectivity. Different from general networks, it is hard for the existing TCP/IP-based routing protocols to correctly work, due to the characteristics such as large latency and unstable link connectivity. Thus, many recent studies focus on routing protocols for DTN. In this paper, we propose a novel routing protocol for DTN with efficient message delivery utilizing mobility information such as direction or destination of mobile nodes. And this protocol is enhanced in terms of delivery ratio, decreases latency and overhead compared to the previously proposed solutions. Simulation results prove its superiority.

• The KIPS Transactions:PartC
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• v.16C no.5
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• pp.621-628
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• 2009

Wireless sensor networks (WSNs) have been considered as a promising method for reliably monitoring both civil and military environments under hazardous or dangerous conditions. Due to the special property and difference from the traditional wireless network, the lifetime of the whole network is the most important aspect. The bottleneck nodes widely exist in WSNs and lead to decrease the lifetime of the whole network. In order to find out the bottleneck nodes, the traditional centralized bottleneck detection method MINCUT has been proposed as a solution for WSNs. However they are impractical for the networks that have a huge number of nodes. This paper first proposes a distributed algorithm called DBND (Distributed Bottleneck Node detection) that can reduce the time for location information collection, lower the algorithm complexity and find out the bottleneck nodes quickly. We also give two simple suggestions of how to solve the bottleneck problem. The simulation results and analysis show that our algorithm achieves much better performance and our solutions can relax the bottleneck problem, resulting in the prolonging of the network lifetime.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.4
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• pp.675-683
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• 1992

Mapping and navigation system based on certainty grids for an autonomous mobile robt operating in unknown and unstructured environment is described. The system uses sonar range data to build a map of robot's surroundings. The range data from sonar sensor are integrated into a probability map that is composed of two dimensional grids which contain the probabilities of being occupied by the objects in the environment. A Bayesian model is used to estimate the uncertainty of the sensor information and to update the existing probability map with new range data. The resulting two dimensional map is used for path planning and navigation. In this paper, the Bayesian updating model which was successfully simulated in our earlier work is implemented on a mobile robot and is shown to be valid in the real world through experiment. This paper also proposes a technique for reducing for reducing specular reflection problem of sonar system which seriousely deteriorates the map quality, and a new path planning method based on weighted distance, which enables the robot to efficiently navigate in an unknown area.

• Journal of Educational Research in Mathematics
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• v.15 no.4
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• pp.445-459
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• 2005

Statistics education is considered within the mathematics curriculum and, thus, can be integrated into other areas of mathematics. However, statistical concepts and thinking skills have to be considered as very different from those of other areas. It is possible to make statistics more meaningful for the learner by making definitions or explanations of concepts in textbooks more clear and consistent. In 'Math I' and 'Probability & Statistics' of the 7th curriculum, the definitions of sample standard deviation are different, which might confuse students. In this study, firstly, some issues relevant to sample standard deviation concept are discussed through the analysis in terms of didactical situation and curriculum. Secondly, the characteristics of sample standard deviation concept as a scholarly knowledge are examined. Finally, the characteristics of didactic transposition of sample standard deviation concept in Japanese, American, and British textbooks are investigated and some suggestions are elicited.

• Journal of the Korean Society for Railway
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• v.13 no.3
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• pp.290-297
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• 2010

At present, the design live load of railway is divided into common railway and high speed railway separately in Korea. L22 which is based on American railway standards is used for common railway and HL25 which is based on Eurocode is used for high speed railway. Although, the design load is the starting point for design of railway, any research for developing design load does not exist at all. However, Europe and Japan develops the design load model consistently for advanced design. Recently, deterministic, probabilistic and cost performance approaches are investigated for developing new design load in Europe which is called LM2000. In the present paper, as a step for developing new design live load model for Korean railway, deterministic processes will be introduced. The safety margins are analyzed based on serviced real trains versus proposed new design load model and a necessity for new design live load will be presented quantitatively.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.501-501
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• 2015

댐과 같은 수공구조물의 치수능력부족은 구조물의 파손이나 붕괴로 직결되며, 대규모 재산피해와 인명피해가 불가피하다. 또한 최근 기후변화 현상에 의해 발생되고 있는 예상치 못한 큰 강우와 홍수는 댐 안전을 저하하는 요소로 간주되며, 복합적으로 발생시 댐의 치수능력이 크게 저하되어 댐 파괴에 영향을 미칠 가능성이 크다. 또한 ICOLD, 세계대댐회 등의 조사 결과 댐 파괴에 큰 영향을 미치고 있는 수문학적 요소로서 예상치 못한 강우, 홍수 및 월류로 조사되었다. 이러한 이유로 수문학적 위험인자를 효과적으로 고려하기 위해 2000년도 이후 선진국에서는 위험도 해석 기법을 기반으로 파괴모드, 다양한 하중조건 등을 조합하여 위험도 해석을 통해 댐의 안전도 검토를 실시하고 있다. 따라서 최근 증가하는 기상변동성을 능동적으로 고려하기 위해서는 위험도 해석기반의 수공구조물 안정성 평가기법을 기반으로 하는 종합적인 위험도 해석 방안수립이 요구된다. 이러한 이유로 본 연구에서는 BN 모형 기반의 댐 위험도 적용에 앞서 실증댐을 대상으로 분석을 수행하였으며, 분석 절차는 다음과 같다. 첫째, ICOLD 및 세계대댐회 등 다양한 논문, 보고서 등을 조사하여 댐 붕괴에 가장 큰 영향을 미치는 수문학적 파괴인자를 도출하였다. 둘째, BN 모형 구축시 각 노드는 앞서 도출된 수문학적 파괴인자를 이용하였으며, 각 파괴인자에 적합한 확률분포형을 부여하였다. 마지막으로, 노드별 임계값을 부여하여 상황별 파괴인자의 변화 양상을 도출하였다. 본 연구의 결과로 인해 연구대상댐의 가장 취약한 수문학적 파괴인자 도출이 가능하며, 댐의 보수 보강시 우선순위 의사결정의 지원이 가능 할 것으로 판단된다.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.4
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• pp.37-45
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• 2022

In this paper, a multi agent-multi task assignment problem, which is a representative problem of combinatorial optimization, is presented. The objective of the problem is to determine the coordinated agent-task assignment that maximizes the sum of the achievement rates of each task. The achievement rate is represented as a concave down increasing function according to the number of agents assigned to the task. The problem is expressed as an NP-hard problem with a non-linear objective function. In this paper, to solve the assignment problem, we propose a hybrid cross-entropy algorithm as an effective and efficient solution methodology. In fact, the general cross-entropy algorithm might have drawbacks (e.g., slow update of parameters and premature convergence) according to problem situations. Compared to the general cross-entropy algorithm, the proposed method is designed to be less likely to have the two drawbacks. We show that the performances of the proposed methods are better than those of the general cross-entropy algorithm through numerical experiments.