• Journal of the Korean Society of Clothing and Textiles
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• v.10 no.3
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• pp.37-48
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• 1986

The purpose of this study was to analyze 'the natural groupings' of subjects in order to classify highly similar somatotype for clothing construction. The sample for the study was drawn randomly out of senior high school boys in Seoul urban area. The sample size was 425 boys between age 16 and 18. Cluster analysis was more concerned with finding the hierarchical structure of subjects by three dimensional distance of stature. bust girth and sleeve length. The groups forming a partition can be subdivided into 5 and 6 sets by the hierarchical tree of the given subjects. Ward's Minimum Variance Method was applied after extraction of distance matrix by the Standardized Euclidean Distance. All of the above data was analyzed by the computer installed at Korea Advanced Institute of Science and Technology. The major findings, take for instance, of 16 age group can be summarized as follows. The results of cluster analysis of this study: 1. Cluster 1 (32 persons means $18.29\%$ of the total) is characterized with smaller bust girth than that of cluster 5, but stature and sleeve length of the cluster 1 are the largest group. 2. Cluster 2 (18 Persons means $10.29\%$ of the total) is characterized with the group of the smallest stature and sleeve length, but bust girth larger than that of cluster 3. 3. Cluster 3(35persons means $20\%$ of the total) is classified with the smallest group of all the stature, bust girth and sleeve length. 4. Cluster 4(60 persons means $34.29\%$ of the total) is grouped with the same value of sleeve length with the mean value of 16 age group, but the stature and bust girth is smaller than the mean value of this age group. 5. Cluster 5(30 persons means $17.14\%$ of the total) is characterized with smaller stature than that of cluster 1, and with larger bust girth than that of cluster 1, but with the same value of the sleeve length with the mean value of the 16 age group.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.481-486
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• 2021

Machine learning algorithms adopt criterion function as a key component to measure the quality of their model derived from data. Cluster analysis also uses this function to rate the clustering result. All the criterion functions have in general certain types of favoritism in producing high quality clusters. These clusters are then described by attributes and their values. Category utility and partition utility play an important role in cluster analysis. These are fully analyzed in this research particularly in terms of how they are related to the favoritism in the final results. In this research, several data sets are selected and analyzed to show how different results are induced from these criterion functions.

• International Journal of Advanced Culture Technology
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• v.5 no.3
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• pp.40-45
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• 2017

This data mining technique was used to extract useful information from percutaneous coronary intervention data obtained from the US public data homepage. The experiment was performed by extracting data on the area, frequency of operation, and the number of deaths. It led us to finding of meaningful correlations, patterns, and trends using various algorithms, pattern techniques, and statistical techniques. In this paper, information is obtained through efficient decision tree and cluster analysis in predicting the incidence of percutaneous coronary intervention and mortality. In the cluster analysis, EM algorithm was used to evaluate the suitability of the algorithm for each situation based on performance tests and verification of results. In the cluster analysis, the experimental data were classified using the EM algorithm, and we evaluated which models are more effective in comparing functions. Using data mining technique, it was identified which areas had effective treatment techniques and which areas were vulnerable, and we can predict the frequency and mortality of percutaneous coronary intervention for heart disease.

• Knowledge Management Research
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• v.13 no.5
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• pp.43-64
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• 2012

Emerging technologies have significant implications in establishing competitive advantages and are characterized by continuous rapid development. Efficient benchmarking is more and more important in the development of emerging technologies. Similar input level and importance are two necessary criteria need to be considered for emerging technology's benchmarking. In this study, we proposed a sequential use of self-organizing map(SOM), data envelopment analysis(DEA) and analytical hierarchy process(AHP) method for the stepwise benchmarking of emerging technology. The proposed method uses two-level SOM to cluster the emerging technologies with similar required input levels together, then, in each cluster, uses DEA-BCC model to evaluate the efficiencies of the emerging technologies and do tier analysis to form tiers. On each tier, AHP rating method is used to calculate each emerging technology's importance priority. The optimal benchmarking path of each cluster is established by connecting the emerging technologies with the highest importance priority. In order to validate the proposed method, we apply it to a case of biotechnology. The result shows the proposed method can overcome difficulties in benchmarking, select suitable benchmarking targets and make the benchmarking process more efficient and reasonable.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.3
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• pp.351-379
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• 2023

The goal of this study is to investigate the domestic and international research trends on metaverse related researches. To achieve this goal, a set of 913 journal articles were collected from KCI (Korea Citation Index), 232 articles from WoS (Web of Science), and 277 articles from WoS-CPCI (Conference Proceeding Citation Index). A descriptive analysis shows the number of researches has been increased radically, and the mostly researched subject areas are interdisciplinary, computer science, and education in KCI, business and economics in WoS, and computer science in WoS-CPCI. The co-occurrence network analysis using author keywords revealed that technology related terms such as virtual reality and augmented reality showed high centrality measures in all of the databases, and the cluster analysis resulted in education and metaverse platform related keywords cluster from KCI, bibliometric analysis related keywords cluster from WoS, and all the metaverse technology related keywords cluster from WoS-CPCI.

• World Technopolis Review
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• v.4 no.3
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• pp.144-156
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• 2015

Globalization and knowledge-based economy have increased the importance of local areas as the units of global competition. Therefore, the meaning of localities has been emphasized as the core value of economic activities. In this context, innovation cluster has been recognised and emphasized as effective policy measure for innovation. Therefore, most countries have been trying to develop innovation clusters with their expectation for a rapid growth of economy. Nevertheless, there have been minimal empirical researches on innovation cluster. Therefore, for suggesting implications that activation factors of innovation cluster are to have an effect on tenant's business activities, this study conducted a literature review for the theories of regional innovation system(RIS) and innovation cluster. As a result, the activation factors of innovation cluster were classified into institutional, physicals, and social factor. The case of Gyeonggi province's innovation cluster policy was examined for an empirical analysis. Data were analyzed using ordered logistic regression. The results were as follows:First, Institutional and Infra factors had a positive influence on firms' business activities in every empirical test, so they were the most important activation factors of innovation cluster. Second, regarding the interactive effects of financial support, the interactive effects between financial support and Infra factor had a positive influence on the firms' business activities, according to the result of the empirical test.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.2042-2060
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• 2013

In wireless sensor networks (WSNs), energy efficiency is one of the most essential design considerations, since sensor nodes are resource constrained. Group communication can reduce WSNs communication overhead by sending a message to multiple nodes in one packet. In this paper, in order to simultaneously resolve the transmission security and scalability in WSNs group communications, we propose a hierarchical cluster-based secure and scalable group key management scheme, called HRKT, based on logic key tree and route key tree structure. The HRKT scheme divides the group key into cluster head key and cluster key. The cluster head generates a route key tree according to the route topology of the cluster. This hierarchical key structure facilitates local secure communications taking advantage of the fact that the nodes at a contiguous place usually communicate with each other more frequently. In HRKT scheme, the key updates are confined in a cluster, so the cost of the key updates is reduced efficiently, especially in the case of massive membership changes. The security analysis shows that the HRKT scheme meets the requirements of group communication. In addition, performance simulation results also demonstrate its efficiency in terms of low storage and flexibility when membership changes massively.

• World Technopolis Review
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• v.8 no.2
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• pp.104-119
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• 2019

Innovation clusters are essential in the economic development of many developed countries across the world. While they present ways for under-developed and developing countries to grow their economies, fully operational innovation clusters are yet to be established in Nigeria. Many experts argue that learning from experience is an effective way of galvanizing economic development. Therefore, in this study, an empirical analysis involving a multi-variable quantitative analysis was used to examine the factors that influence the performance of the Daedeok Innopolis Innovation Cluster (South Korea). The results obtained show that the investment in education, Research and Development (R&D), labor capacity of key players within the innovation cluster, and the transfer of technology (within the cluster) were essential factors that influence the performance of the Daedeok Innopolis Innovation Cluster.

• Journal of Korea Technology Innovation Society
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• v.13 no.4
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• pp.738-757
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• 2010

Generally, it is known that the agglomeration economies appear in some industry clusters which were developed naturally. But, in Korea, most of industry clusters were built by government. This research was carried out to evaluate the performance of governments zoning investment, in other words, industry cluster policy. In this research, we use the data of manufacturing firms in Kyunggi-province. For the microeconomic analysis, we use the KIS-VALUE data of 2008. As the empirical test methods we use both multiple regressions and Propensity Score Matching. In conclusion, there is no evidences that firms in industry cluster have better performances. Surprisingly, in PSM analysis, we find the evidence that firms in industry cluster show less innovative performance.

• Proceedings of the Technology Innovation Conference
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• 2005.06a
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• pp.116-139
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• 2005

ICT(information and communication technology) has played a pivotal role in the world economy, and the out look for ICT has improved markedly. One of the noticeable characteristics in the ICT sector Is the global rationalization of its technology and service. Specialization on the specific ICT capability is a pressing problem for many countries. Along the line of classical innovation cluster and network studies, this paper suggests a way to find and analyze the role of core technologies on the ICT network First, technology network is constructed by using patent citation data from USPTO. Then, a couple of cluster is generated by K-means clustering technique. Finally, brokerage analysis is applied to manifest the role of principal technologies. The network visualization and some stylized facts on dynamics are briefly given altogether Based on the role and relationship of technologies across clusters, it is expected that this research could contribute to the ICT cluster formation and the vision-making for ICT specialization at the viewpoint of technology Policy.