• Journal of Internet Computing and Services
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• v.8 no.6
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• pp.43-53
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• 2007

Intrusion detection system(IDS) has recently evolved while combining signature-based detection approach with anomaly detection approach. Although signature-based IDS tools have been commonly used by utilizing machine learning algorithms, they only detect network intrusions with already known patterns, Ideal IDS tools should always keep the signature database of your detection system up-to-date. The system needs to generate the signatures to detect new possible attacks while monitoring and analyzing incoming network data. In this paper, we propose a new outlier cluster detection algorithm with density (or influence) function, Our method assumes that an outlier is a kind of cluster with similar instances instead of a single object in the context of network intrusion, Through extensive experiments using KDD 1999 Cup Intrusion Detection dataset. we show that the proposed method outperform the conventional outlier detection method using Euclidean distance function, specially when attacks occurs frequently.

• Journal of Electrical Engineering and Technology
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• v.1 no.4
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• pp.435-447
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• 2006

This paper presents an application of the parallel Adaptive Evolutionary Algorithm (AEA) to search an optimal solution of the service restoration in electric power distribution systems, which is a discrete optimization problem. The main objective of service restoration is, when a fault or overload occurs, to restore as much load as possible by transferring the de-energized load in the out of service area via network reconfiguration to the appropriate adjacent feeders at minimum operational cost without violating operating constraints. This problem has many constraints and it is very difficult to find the optimal solution because of its numerous local minima. In this investigation, a parallel AEA was developed for the service restoration of the distribution systems. In parallel AEA, a genetic algorithm (GA) and an evolution strategy (ES) in an adaptive manner are used in order to combine the merits of two different evolutionary algorithms: the global search capability of the GA and the local search capability of the ES. In the reproduction procedure, proportions of the population by GA and ES are adaptively modulated according to the fitness. After AEA operations, the best solutions of AEA processors are transferred to the neighboring processors. For parallel computing, a PC cluster system consisting of 8 PCs was developed. Each PC employs the 2 GHz Pentium IV CPU and is connected with others through switch based fast Ethernet. To show the validity of the proposed method, the developed algorithm has been tested with a practical distribution system in Korea. From the simulation results, the proposed method found the optimal service restoration strategy. The obtained results were the same as that of the explicit exhaustive search method. Also, it is found that the proposed algorithm is efficient and robust for service restoration of distribution systems in terms of solution quality, speedup, efficiency, and computation time.

• Journal of Korea Technology Innovation Society
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• v.14 no.3
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• pp.599-621
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• 2011

The role of local economies in pursuing national economic development has expanded with greater influence. So a number of countries have adopted industrial cluster policies for regional and national economic development. Korean government, by the same token, puts emphasis on industrial cluster policies. But the academic studies on the necessities and effects of industrial clusters for Korean shipbuilding industry have been carried out little in Korean due to the lack of empirical studies on Korean industrial clusters. So this study focuses on analysing the industrial clusters in the Busan, Ulsan, Koungnam as southeast area of Korea. To be more specific, this study intends to provide answers to the following question: Are there industrial clusters in the Busan, Ulsan, Koungnam as southeast area of Korea analysed by the Location Quotient(LQ) analysis method? And as a consequence, Shipbuilding industrial clusters of southeast area of Korea were not identified.

• The Journal of the Korea Contents Association
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• v.8 no.2
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• pp.18-26
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• 2008

This paper presents a phased visualization method of facial expression space that enables the user to control facial expression of 3D avatars by select a sequence of facial frames from the facial expression space. Our system based on this method creates the 2D facial expression space from approximately 2400 facial expression frames, which is the set of neutral expression and 11 motions. The facial expression control of 3D avatars is carried out in realtime when users navigate through facial expression space. But because facial expression space can phased expression control from radical expressions to detail expressions. So this system need phased visualization method. To phased visualization the facial expression space, this paper use fuzzy clustering. In the beginning, the system creates 11 clusters from the space of 2400 facial expressions. Every time the level of phase increases, the system doubles the number of clusters. At this time, the positions of cluster center and expression of the expression space were not equal. So, we fix the shortest expression from cluster center for cluster center. We let users use the system to control phased facial expression of 3D avatar, and evaluate the system based on the results.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.4
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• pp.239-244
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• 2009

Image contrast enhancement has an important role in image processing applications. Conventional contrast enhancement techniques, histogram stretching and histogram equalization, and many methods based on histogram equalization often fail to produce satisfactory results for broad variety of low-contrast images. So, this paper proposes a new image contrast enhancement method based on the clustering method. The number of cluster of histogram is found by analysing the histogram of original image. The histogram components is classified using K-means algorithm. And then these histogram components are performed histogram stretching and histogram equalization selectively by comparing cluster range with pixel rate of cluster. From the expremental results, the proposed method was more effective than conventional contrast enhancement techniques.

• Journal of Korean Society of Water and Wastewater
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• v.35 no.6
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• pp.517-531
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• 2021

The water supply facilities of Korea have achieved a rapid growth, along with the other social infrastructures consisting a city, due to the phenomenon of urbanization according to economic development. Meanwhile, the level of water supply service demanded by consumer is also steadily getting higher in keeping with economic growth. However, as an adverse effect of rapid growth, the quantity of aged water supply pipes are increasing rapidly, Bursts caused by pipe aging brought about an enormous economic loss of about 6,161 billion won as of 2019. These problems are not only worsening water supply management, also increasing the regional gap in water supply services. The purpose of this study is to classify hazard evaluation indicators and to rank the water distribution network hazard by cluster using the TOPSIS method. In conclusion, in this study, the entropy-based multi-criteria decision-making methods was applied to rank the hazard management of the water distribution network, and the hazard management ranking for each cluster according to the water supply conditions of the county-level municipalities was determined according to the evaluation indicators of water outage, water leakage, and pipe aging. As such, the hazard ranking method proposed in this study can consider various factors that can impede the tap water supply service in the water distribution network from a macroscopic point of view, and it can be reflected in evaluating the degree of hazard management of the water distribution network from a preventive point of view. Also, it can be utilized in the implementation of the maintenance plan and water distribution network management project considering the equity of water supply service and the stability of service supply.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.121-124
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• 2000

We introduce an advanced mountain clustering method which uses a normalized data space, a gaussian type mountain function and a deconstruction method using mountain slope. This is more useful than Yagers mountain method because it needs just one parameter to tune instead of three and finds out more resonable cluster centers. Computational examples are presented to show the validity of the advanced mountain method.

• International Journal of Highway Engineering
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• v.7 no.4 s.26
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• pp.211-219
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• 2005

A selection of the analysis section for traffic accidents is used to analyze definitely the cause of accidents sorting similar accidents by a group and to raise the effect of improvement projects deciding the priority of accidents. In the existing method, an uniformly dividing method based on road mileages has been used, which has no consideration for similarities among accidents. Consequently, in recent, a slider-length method considering accident types rather than road mileages is widely used. In this study, using K-mean method, a non-hierarchical grouping technique used in the Cluster Analysis ai a applicatory method for the slider length method, a method classifies accidents that occurred the most nearby mileages into one group is proposed. To verify the proposed method, a comparison between the f-mean method and the dividing method at regular intervals on the data of a total of 25.6km lengths along Kyung-bu freeway in Pusan direction was made so that the K-mean method was proved to an effective method considering the similarities and adjacencies of accidents.

• Atmosphere
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• v.22 no.2
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• pp.149-161
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• 2012

Going by the research results of the past, of all the uncertainties resulting from the research on climate change, the uncertainty caused by the climate change scenario has the highest degree of uncertainty. Therefore, depending upon what kind of climate change scenario one adopts, the projection of the water resources in the future will differ significantly. As a matter of principle, it is highly recommended to utilize all the GCM scenarios offered by the IPCC. However, this could be considered to be an impractical alternative if a decision has to be made at an action officer's level. Hence, as an alternative, it is deemed necessary to select several scenarios so as to express the possible number of cases to the maximum extent possible. The objective standards in selecting the climate change scenarios have not been properly established and the scenarios have been selected, either at random or subject to the researcher's discretion. In this research, a new scenario selection process, in which it is possible to have the effect of having utilized all the possible scenarios, with using only a few principal scenarios and maintaining some of the uncertainties, has been suggested. In this research, the use of cluster analysis and the selection of a representative scenario in each cluster have efficiently reduced the number of climate change scenarios. In the cluster analysis method, the K-means clustering method, which takes advantage of the statistical features of scenarios has been employed; in the selection of a representative scenario in each cluster, the selection method was analyzed and reviewed and the PDF method was used to select the best scenarios with the closest simulation accuracy and the principal scenarios that is suggested by this research. In the selection of the best scenarios, it has been shown that the GCM scenario which demonstrated high level of simulation accuracy in the past need not necessarily demonstrate the similarly high level of simulation accuracy in the future and various GCM scenarios were selected for the principal scenarios. Secondly, the "Maximum entropy" which can quantify the uncertainties of the climate change scenario has been used to both quantify and compare the uncertainties associated with all the scenarios, best scenarios and the principal scenarios. Comparison has shown that the principal scenarios do maintain and are able to better explain the uncertainties of all the scenarios than the best scenarios. Therefore, through the scenario selection process, it has been proven that the principal scenarios have the effect of having utilized all the scenarios and retaining the uncertainties associated with the climate change to the maximum extent possible, while reducing the number of scenarios at the same time. Lastly, the climate change scenario most suitable for the climate on the Korean peninsula has been suggested. Through the scenario selection process, of all the scenarios found in the 4th IPCC report, principal climate change scenarios, which are suitable for the Korean peninsula and maintain most of the uncertainties, have been suggested. Therefore, it is assessed that the use of the scenario most suitable for the future projection of water resources on the Korean peninsula will be able to provide the projection of the water resources management that maintains more than 70~80% level of uncertainties of all the scenarios.

• Journal of Environmental Impact Assessment
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• v.24 no.2
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• pp.111-118
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• 2015

This study was conducted for the establishment of statistical method to determine the representative air quality monitoring station representing long-term ozone trends of Seoul. In this study, hourly ozone concentrations from 2002 to 2011 were used for further analysis. KZ-filter, correlation matrix, cluster analysis, and Kriging method were applied to select the representative station. The analysis based on correlation matrix found that long-term trend of ozone concentrations measured at Sinjung, Sadang, and Bun-dong showed a high correlation. The cluster analysis found that the former three stations belonged to the same cluster. The analysis based on Kriging method also showed that the former three stations were highly correlated with other stations in spatial distribution. Considering these results and the highest correlation coefficient of Sinjung station, the Sinjung station was the most suitable as the representative station used to understand the long-term ozone trend of Seoul. This result could be applied to understand long-term trend of other pollutants. Furthermore, this result can also be used to assess the appropriacy of spatial distribution of national air quality monitoring stations.