• Journal of KIISE:Computer Systems and Theory
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• v.30 no.5_6
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• pp.223-231
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• 2003

Video-on-Demand (VOD) service needs high resource consumption because of high bandwidth and long playback duration which are characteristics of multimedia. Various techniques such as Patching and Channel-Reserving Patching have been proposed to reduce the demand on the network-I/O bandwidth. Patching allows new clients to join an existing multicast for realization of true VOD, and Channel-Reserving Patching reserves the part of total channel capacity of video server in order to serve the requests for popular videos on which requests of users concentrate. To improve the performance of Channel-Reserving Patching, we propose the method that determines the reserved channel capacity of video server for the popular videos in this paper. The performance of our method is evaluated in terms of average servile latency, defection ratio and fairness through simulation, and is compared with those of Patching and another Channel-Reserving Patching.

• Journal of KIISE:Software and Applications
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• v.34 no.11
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• pp.971-983
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• 2007

Cellular Genetic Algorithms(CGAs) are a subclass of Genetic Algorithms(GAs) in which each individuals are placed in a given geographical distribution. In general, CGAs# population space is a regular network that has relatively long characteristic path length and high clustering coefficient in the view of the Networks Theory. Long average path length makes the genetic interaction of remote nodes slow. If we have the population#s path length shorter with keeping the high clustering coefficient value, CGAs# population space will converge faster without loss of diversity. In this paper, we propose Smallest-Small-World Cellular Genetic Algorithms(SSWCGAs). In SSWCGAs, each individual lives in a population space that is highly clustered but having shorter characteristic path length, so that the SSWCGAs promote exploration of the search space with no loss of exploitation tendency that comes from being clustered. Some experiments along with four real variable functions and two GA-hard problems show that the SSWCGAs are more effective than SGAs and CGAs.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.10
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• pp.1225-1236
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• 1999

기존의 오류 제어 방법들은 실시간 특성과 신축적인 신뢰성을 가지는 멀티미디어 통신 응용의 특징을 충분히 반영하지 못하고 있다. 본 연구는 기존의 재전송을 기반으로 하는 방법에 두 가지 기법을 추가하여 이 문제에 접근하였다. 첫째, 실시간 데이타의 마감 시간을 고려하여 미리 재전송을 실시하는 사전 재전송과 시간적으로 불가능하다고 판단될 때 복구를 포기하는 재전송 포기를 통한 적시 재전송 기법이다. 둘째, 요구되는 신뢰성에 근접하도록 오류가 많이 발생하였을 때만 재전송을 하는 선택적 오류 제어 기법이다. 본 연구는 두 기법을 적용한 오류 제어 프로토콜을 구현하고 네트워크 환경을 바꾸어 가며 성능을 검사하였다. 실험 결과, 제안된 오류 제어 방법은 전체적인 오류 제어 부하는 감소시키면서 오류 복구율을 높인다는 점을 확인하였다.Abstract The current error control schemes do not fit well to the characteristics of multimedia communications: real-time transmission and flexible reliability requirements. This research proposes a new error control scheme, which extends the retransmission-based error control with the following two mechanisms. First, error recovery is performed in two timely fashions: one is retransmission in advance where a retransmission is performed early enough for the deadline if an error is suspected, and the other is retransmission abort where a retransmission is given up if its recovery within the deadline seems to be impossible. Second, error control is selectively performed only when an actual error rate approaches to the threshold on a given reliability requirement. The proposed scheme has been implemented and experimented in various network environments. The performance results show that it has lower control overhead and higher error recovery than the existing schemes.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.7_8
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• pp.352-358
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• 2003

A cluster of servers is the most promising solution to provide highly scalable and highly available network services with low implementation cost. One of popular solutions is using dispatcher as a request distributor. However this solution has the problem that is can be the bottleneck or single-point of failure point of itself. ONE-IP, the previous work, solves this serious problem by using broadcast message for distributing the request packet in LAN. Using simple scheduling technique, in addition, the overhead due to dispatching the request becomes minimal. However, as ONE-IP using very simple static scheduling algorithm, it would spread the request among servers unevenly and downgrades the cluster performance consequently. In this paper, we propose an improved TCP connection scheduling technique solving this unbalanced distributing problem. Using Round-Robin(RR) scheduling instead of hashing clients IP address, proposed technique can more evenly distribute incoming service requests among the servers. Experiments show average 3.8% improved performance in throughput compared to original ONE-IP technique.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.7_8
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• pp.359-369
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• 2003

We present efficient generalized algorithms for all-to-all personalized communication operations in a 2D torus. All-to-all personalized communication, or complete exchange, is at the heart of numerous applications, such as matrix transposition, Fast Fourier Transform(FFT), and distributed table lookup. Some algorithms have been Presented when the number of nodes is power-of-2 or multiple-of-four form, but there has been no result for general cases yet. We first present complete exchange algorithm called multiple-Hop-2D when the number of nodes is in the form of multiple-of-two. Then by extending this algorithm, we present two algorithms for an arbitrary number of nodes. Split-and-Merge algorithm first splits the whole network into zones. After each zone performs complete exchange, merge is applied to finish the desired complete exchange. By handling extra steps in Double-Hop-2D algorithm, Modified Double-Hop-2D algorithm performs complete exchange operation for general cases. Finally, we compare the required start-up time for these algorithms.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.635-642
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• 2002

There is a rapidly growing demand for the intellectualization of information technology. Especially, in the area of KDD (Knowledge Discovery in Database) which should make an optimal decision of finding knowledge from a large amount of data, the demand is enormous. A large volume of Knowledge Base should be efficiently managed for a more intellectual choice. This study is proposing a Hybrid SOM for an efficient search and renewal of knowledge base, which combines a self-study nerve network, Self-Organization Map with a probable distribution theory in order to get knowledge needed for decision-making management from the Knowledge Base. The efficient knowledge base management through this proposed method is carried out by a stimulation test. This test confirmed that the proposed Hybrid SOM can manage with efficiency Knowledge Base.

• Journal of the Korean Institute of Gas
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• v.11 no.2 s.35
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• pp.71-77
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• 2007

This research proposes the U-drawing information system (U-DIS) based on risk assessment. One of the most outstanding features of U-DIS is to perform the Quantitative Risk Assessment directly on the screen utilizing the Process Information. U-DIS revolutionizes the existing way to do a risk assessment and helps finding information more efficiently and simply. It is designed to open all CAD drawing files on the web-based environment without having the CAD S/W installed on the PC. The U terminal platform in U-DIS supports IPv6 and wireless broadband network and U-DIS can be accessible through a sensor or personal authorization. This results in providing a systematic safety enhancement tool considering not only the operation of the process but also its risk level in the equipment industry. Additionally to aid the decision making process it offers comprehensive and thorough information based on engineering technical theory.

• International Journal of Highway Engineering
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• v.9 no.3
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• pp.63-74
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• 2007

Traffic information provision plays an important role in increasing the efficiency of network operation and in providing convenience for roadway users. As a typical device for disseminating real-time traffic information for collective general public, VMS is a prevalent device nowadays and it is being expanded. However, the actual monetary value of traffic information is not quantified up to now. The previous studies regarding VMS traffic information are mainly focused on the behavioral aspects of road users such as departure time and route choices under traffic information provision conditions. This paper tried to estimate the monetary value of VMS traffic information using discrete choice theory and logit model through the stated preference study(SP). The methodological framework adopted in this paper can also be used in evaluating the monetary value of other traffic information providers including PDA, CNS, and mobile phone.

• The Korean Journal of Applied Statistics
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• v.28 no.2
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• pp.251-267
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• 2015

The Indian Buffet Process is a stochastic process on equivalence classes of binary matrices having finite rows and infinite columns. The Indian Buffet Process can be imposed as the prior distribution on the binary matrix in an infinite feature model. We describe the derivation of the Indian buffet process from a finite feature model, and briefly explain the relation between the Indian buffet process and the beta process. Using a Gaussian linear model, we describe three algorithms: Gibbs sampling algorithm, Stick-breaking algorithm and variational method, with application for finding features in image data. We also illustrate the use of the Indian Buffet Process in various type of analysis such as dyadic data analysis, network data analysis and independent component analysis.

• Safety and Health at Work
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• v.9 no.1
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• pp.42-52
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• 2018

Background: Maintenance operations on-board ships are highly demanding. Maintenance operations are intensive activities requiring high man-machine interactions in challenging and evolving conditions. The evolving conditions are weather conditions, workplace temperature, ship motion, noise and vibration, and workload and stress. For example, extreme weather condition affects seafarers' performance, increasing the chances of error, and, consequently, can cause injuries or fatalities to personnel. An effective human error probability model is required to better manage maintenance on-board ships. The developed model would assist in developing and maintaining effective risk management protocols. Thus, the objective of this study is to develop a human error probability model considering various internal and external factors affecting seafarers' performance. Methods: The human error probability model is developed using probability theory applied to Bayesian network. The model is tested using the data received through the developed questionnaire survey of >200 experienced seafarers with >5 years of experience. The model developed in this study is used to find out the reliability of human performance on particular maintenance activities. Results: The developed methodology is tested on the maintenance of marine engine's cooling water pump for engine department and anchor windlass for deck department. In the considered case studies, human error probabilities are estimated in various scenarios and the results are compared between the scenarios and the different seafarer categories. The results of the case studies for both departments are also compared. Conclusion: The developed model is effective in assessing human error probabilities. These probabilities would get dynamically updated as and when new information is available on changes in either internal (i.e., training, experience, and fatigue) or external (i.e., environmental and operational conditions such as weather conditions, workplace temperature, ship motion, noise and vibration, and workload and stress) factors.