• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.5
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• pp.60-70
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• 2018

A software defined storage (SDS) is being deployed in cloud environment to allow multiple users to virtualize physical servers, but a solution for optimizing space efficiency with limited physical resources is needed. In the conventional data deduplication system, it is difficult to deduplicate redundant data uploaded to distributed storages. In this paper, we propose a distributed deduplication method using similarity-based clustering and multi-layer bloom filter. Rabin hash is applied to determine the degree of similarity between virtual machine servers and cluster similar virtual machines. Therefore, it improves the performance compared to deduplication efficiency for individual storage nodes. In addition, a multi-layer bloom filter incorporated into the deduplication process to shorten processing time by reducing the number of the false positives. Experimental results show that the proposed method improves the deduplication ratio by 9% compared to deduplication method using IP address based clusters without any difference in processing time.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.2
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• pp.131-138
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• 2011

The previous FPGA cluster systems for a brute force search of DES keyspace have showed cost efficient performance, but the research on optimized implementation of the DES algorithm on a single FPGA has been insufficient. In this paper, the optimized DES implementation for a single FPGA of the commercial FPGA cluster system with 77 Xilinx Virtex5-LX50 FPGAs is proposed. Design space exploration using the number of pipeline stages in a DES core, the number of DES cores and the maximum clock frequency of a DES core is performed which leads to integrating 16 DES cores running at 333MHz. Also low power design is applied to reduce the loss of performance caused by limitation of power supply on each FPGA which results in fitting 8 DES cores running at 333MHz. When the proposed DES implementations would be used in the FPGA cluster system, it is estimated that the DES key would be found at most 2.03 days and 4.06 days respectively.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.482-482
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• 2022

하천의 합류부에서는 수질이 다른 유체가 혼합하여 합류 전과 다른 특성을 보인다. 하천의 합류부에서 수질을 효율적으로 관리하기 위해서는 수질의 공간적인 혼합 특성을 규명하는 것이 중요하다. 합류부에서 수질의 공간적인 혼합 특성을 분석하기 위해 본 연구에서는 토폴로지 데이터 분석(topological data analysis, TDA), 자기 조직화 지도(Self-Organizing Map, SOM), k-평균 알고리즘(K-means clustering algorithm) 세 가지 기법을 이용하였다. 세 가지 기법을 비교하여 어떤 알고리즘이 합류부의 수질 변화 특성을 더 뚜렷하게 나타내는지 분석하였다. 수질 변화 비교 인자들은 pH, chlorophyll, DO, Turbidity 등이 있고, 수질 인자들은 YSI를 활용해 측정하였다. 자료의 측정 지역은 낙동강과 황강이 합류하는 지역이며, 보트에 YSI 장비를 부착하고 횡단하여 측정하였다. 측정한 데이터를 R 프로그램을 통해 세 가지 기법을 적용시켜 수질 변화 비교를 분석한다. 토폴로지 데이터 분석(topological data analysis, TDA)은 거대하고 복잡한 데이터로부터 유의미한 정보를 추출하는 데 사용하고, 자기조직화지도(Self-Organizing Map, SOM) 기법은 차원 축소와 군집화를 동시에 수행한다. k-평균 알고리즘(K-means clustering algorithm) 기법은 주어진 데이터를 k개의 클러스터로 묶는 머신러닝 비지도학습에 속하는 알고리즘이다. 세 가지 방법들의 주목적은 클러스터링이다. 클러스터 분석(Cluster analysis)이란 주어진 데이터들의 특성을 고려해 동일한 성격을 가진 여러 개의 그룹으로 대상을 분류하는 데이터 마이닝의 한 방법이다. 군집화 방법들인 TDA, SOM, K-means를 이용해 합류 지역의 수질 특성들을 클러스터링하여 수질 패턴들을 분석해 하천 수질 오염을 방지할 수 있을 것이다. 본 연구에서는 토폴로지 데이터 분석(topological data analysis, TDA), 자기조직화지도(Self-Organizing Map, SOM), k-평균 알고리즘(K-means clustering algorithm) 세 가지 기법을 이용하여 합류부에서의 수질 특성을 비교하며 어떤 기법이 합류의 특성을 더욱 뚜렷하게 나타내는지 규명했다. 합류의 특성을 군집화 방법을 이용해 알게 된다면, 합류부의 수질 변화 패턴을 다른 합류 지역에서도 적용할 수 있을 것으로 기대된다.

• Journal of the Korean Geographical Society
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• v.48 no.1
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• pp.56-71
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• 2013

The purpose of this study is to examine the spatial distributional characteristics of industries among the Korean cities and to conduct industry classification using the findings. For this purpose, 82 cities in Korea are investigated with respect to 15 industrial sectors. In the analysis, concentration of and association between industries are recognized using both geographic and non-geographic measures. In order to measure concentration and association, locational Gini coefficient, Moran's I, correlation coefficient, and bivatiate Moran are used and 15 industrial sectors are classified based on these estimates. The findings reveal that the chemical sector shows strong geographic and non-geographic concentrations while the assembly, machinery and electronics sector only shows a strong geographic concentration. Printing and publishing, wholesale, and business services show a strong non-geographic association with other sectors. The remaining ten sectors show no explicit distribution patterns among cities. This study contributes to providing the methodology that analyzes the spatial distribution patterns of industries in a comprehensive way and is able to provide useful information in implementing industrial location policies including industrial clusters.

• Journal of the Economic Geographical Society of Korea
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• v.17 no.4
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• pp.660-674
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• 2014

This paper analyzes the social cohesion effects of creative industrial as a core role player of emerging new economic paradigm of the creative economy using the case of Seoul Metropolitan Area(SMA) that is a typical cluster of creative industries in Korea. This study reclassified the creative industries in a Korean context into 13 industries in 6 sectors. Based on this reclassification, the study found out that the spatial pattern of creative industries in SMA is spatially much differentiated in terms of specialization, which demands more differentiated cluster strategy with different policy mix. This paper also investigates the social cohesion effects of creative industries using structural equation modelling. It turns out that the growth of creative industries is likely to contribute to the regional development capacity and also to provide positive effects on various aspects of the social cohesion.

• Journal of the Korean Institute of Educational Facilities
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• v.24 no.4
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• pp.15-24
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• 2017

This paper aims to investigate in what extent subject-centered clusters are different from one another in terms of message system, which is composed of curriculum, pedagogy and evaluation. For this, Bernstein's pedagogic transmission code(i.e., classification and framing) and school typology(i.e., open-type or close-type) have been explored, and then applied into Shimin Junior School, Japan, in order to find out substantial characteristics between subject-centered clusters. In this case study, VGA(visibility graph analysis), as one of syntactical methodologies in space syntax theory, has been used to measure to what degree they are actually different. Throughout in-depth investigation of spatial configurations, it can be said that the square of clusters is strongly connected and integrated very well, so that it acts as an anchor place for school life within a cluster. However, it works in different ways according to message systems. In the subjects like Japanese and Science whose message system are characterized by strong classification and strong framing, integration values are relatively low, and this means that it is hard to expect cross-referencing activities through the subject squares. On the contrary, the subject of Social Studies defined by weak classification and weak framing shows the highest mean integration values, and this can be expected that there are inter-changeable learning activities in the square.

• Journal of KIISE:Software and Applications
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• v.30 no.11
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• pp.1054-1061
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• 2003

Q-Learning, a representative algorithm of reinforcement learning, experiences repeatedly until estimation values about all state-action pairs of state space converge and achieve optimal policies. When the state space is high dimensional or continuous, complex reinforcement learning tasks involve very large state space and suffer from storing all individual state values in a single table. We introduce Q-Map that is new function approximation method to get classified policies. As an agent learns on-line, Q-Map groups states of similar situations and adapts to new experiences repeatedly. State-action pairs necessary for fine control are treated in the form of rule. As a result of experiment in maze environment and mountain car problem, we can achieve classified knowledge and extract easily rules from Q-Map

• Journal of the Economic Geographical Society of Korea
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• v.19 no.4
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• pp.597-615
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• 2016

Since 1997 the United Kingdom has pursued creative industry and creative city development in accordance with the New Labor Party policy, strengthening its cluster policy by assigning creative city policies to traditional manufacturing-oriented regions. Tech City in London, one of the most successful examples of digital clusters, is an area in which diverse ecosystems for venture business integration have been established, as the once barren space began to spontaneously develop. For this region, systematic linkages including universities, private companies, start-ups, and accelerators have been added, along with the UK government's active support system. As a result of this opportunity, the scale of the UK start-up ecosystem has significantly grown, the number of local companies has surged, and brand effect has greatly improved. Tech City is an example of a well-balanced combination of public effort and private governance, based on the region's historical background and its potential for growth. It is an effective coordination of public policy and private active investment, services, research, and education. The market platform for institutional technology and commercialization, and aggressive investment shares in the risk, have lead to its growth as a start-up and an innovative city. Britain's efforts to expand the nationwide cluster for the future-oriented digital economy is most noteworthy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.630-637
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• 2018

Harmony search (HS) is a recently developed metaheuristic optimization algorithm. HS is inspired by the process of musical improvisation and repeatedly searches for the optimal solution using three operations: random selection, memory recall (or harmony memory consideration), and pitch adjustment. HS has been applied by many researchers in various fields. The increasing complexity of real-world optimization problems has created enormous challenges for the current technique, and improved techniques of optimization algorithms and HS are required. We propose an improved clustering harmony search (ICHS) that uses a clustering technique to group solutions in harmony memory based on their objective function values. The proposed ICHS performs modified harmony memory consideration in which decision variables of solutions in a high-ranked cluster have higher probability of being selected than those in a low-ranked cluster. The ICHS is demonstrated in various optimization problems, including mathematical benchmark functions and water distribution system pipe design problems. The results show that the proposed ICHS outperforms other improved versions of HS.

• Journal of Korea Water Resources Association
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• v.49 no.4
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• pp.335-346
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• 2016

This study produced the parameter maps of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) stochastic rainfall generation model across South Korea and developed and validated the web application that automates the process of rainfall generation based on the produced parameter maps. To achieve this purpose, three deferent sets of parameters of the MBLRP model were estimated at 62 ground gage locations in South Korea depending on the distinct purpose of the synthetic rainfall time series to be used in hydrologic modeling (i.e. flood modeling, runoff modeling, and general purpose). The estimated parameters were spatially interpolated using the Ordinary Kriging method to produce the parameter maps across South Korea. Then, a web application has been developed to automate the process of synthetic rainfall generation based on the parameter maps. For validation, the synthetic rainfall time series has been created using the web application and then various rainfall statistics including mean, variance, autocorrelation, probability of zero rainfall, extreme rainfall, extreme flood, and runoff depth were calculated, then these values were compared to the ones based on the observed rainfall time series. The mean, variance, autocorrelation, and probability of zero rainfall of the synthetic rainfall were similar to the ones of the observed rainfall while the extreme rainfall and extreme flood value were smaller than the ones derived from the observed rainfall by the degree of 16%-40%. Lastly, the web application developed in this study automates the entire process of synthetic rainfall generation, so we expect the application to be used in a variety of hydrologic analysis needing rainfall data.