• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.4
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• pp.115-123
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• 2017

The mutual cooperation among nodes is very important because mobile nodes participating in MANET communicate with limited resources and wireless environment. This characteristic is important especially in environment that supports group communication. In order to support the secure multicast environment, it is important enough to affect performance to provide accurate authentication method for multicast group members and increase the integrity of transmitted data. Therefore, we propose a technique to provide the multicast secure communication by providing efficient authentication and group key management for multicast member nodes in this paper. The cluster structure is used for authentication of nodes in the proposed technique. In order to efficient authentication of nodes, the reliability is measured using a combination of local trust information and global trust information measured by neighboring nodes. And issuing process of the group key has two steps. The issued security group key increases the integrity of the transmitted data. The superiority of the proposed technique was confirmed by comparative experiments.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.2
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• pp.13-20
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• 2021

Placement is a very important step in the VLSI physical design process. It is the problem of placing circuit modules to optimize the circuit performance and reliability of the circuit. It is used at the layout level to find strongly connected components that can be placed together in order to minimize the layout area and propagation delay. The most popular algorithms for circuit placement include the cluster growth, simulated annealing, integer linear programming and genetic algorithm. In this paper we propose a adapted genetic algorithm searching solution space for the placement problem, and then compare it with simulated annealing and genetic algorithm by analyzing the results of each implementation. As a result, it was found that the adaptive genetic algorithm approaches the optimal solution more effectively than the simulated annealing and genetic algorithm.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.4
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• pp.1-11
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• 2023

Clustering analysis is used in various fields including customer segmentation and clustering methods such as k-means are actively applied in the credit card customer segmentation. In this paper, we summarized the input features selection method of k-means clustering for the case of the credit card customer segmentation problem, and evaluated its feasibility through the analysis results. By using the label values of k-means clustering results as target features of a decision tree classification, we composed a method for prioritizing input features using the information gain of the branch. It is not easy to determine effectiveness with the clustering effectiveness index, but in the case of the CH index, cluster effectiveness is improved evidently in the method presented in this paper compared to the case of randomly determining priorities. The suggested method can be used for effectiveness of actively used clustering analysis including k-means method.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.4_1
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• pp.781-795
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• 2024

While an increasing number of people across diverse audience groups are engaging in discussions about the onset of the 4th industrial revolution, it remains challenging to pinpoint the symptoms of this phenomenon. This research, recognizing this difficulty, employed a time-series data-tuned cluster analysis to uncover evidence of industrial and technological convergence among the United States, Japan, and Korea by using time-series industrial R&D data and industrial wage data as indirect measures of industrial competitiveness and technology convergence. The results showed that the recent U.S. case of 2010-2019 data clearly featured the" phenomenon Tesla", which shows the convergence of Aerospace, Transportation equipment, and software. Supporting evidence for that comes from the results from the previous periods in the three countries, which shows a high concentration of cor manufacturing sectors, but no symptoms of convergence.

• Journal of Korea Entertainment Industry Association
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• v.14 no.6
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• pp.139-150
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• 2020

The data processing of this study focuses on the textom and social media words about three areas: 'Corona 19 and professional baseball', 'Corona 19 and professional baseball', and 'Corona 19 and professional sports' The data was collected and refined in a web environment and then processed in batch, and the Ucinet6 program was used to visualize it. Specifically, the web environment was collected using Naver, Daum, and Google's channels, and was summarized into 30 words through expert meetings among the extracted words and used in the final study. 30 extracted words were visualized through a matrix, and a CONCOR analysis was performed to identify clusters of similarity and commonality of words. As a result of analysis, the clusters related to Corona 19 and Pro Baseball were composed of one central cluster and five peripheral clusters, and it was found that the contents related to the opening of professional baseball according to the corona 19 wave were mainly searched. The cluster related to Corona 19 and unrelated to professional baseball consisted of one central cluster and five peripheral clusters, and it was found that the keyword of the position of professional baseball related to the professional baseball game according to Corona 19 was mainly searched. Corona 19 and the cluster related to professional sports consisted of one central cluster and five peripheral clusters, and it was found that the keywords related to the start of professional sports according to the aftermath of Corona 19 were mainly searched.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.237-258
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• 2022

As the global market environment changes, the domestic ICT industry has a growing influence on the world economy. This industry is regarded as an important driving force in the national economy from a technological and social point of view. In particular, small and medium-sized enterprises (SMEs) in the ICT industry are regarded as essential actors of domestic economic development in terms of company diversity, technology development and job creation. However, since it is small compared to large-sized enterprises, it is difficult for SMEs to survive with a differentiated strategy in an incomplete and rapidly changing environment. Therefore, SMEs must make a lot of efforts to improve their own capabilities, and the government needs to provide the desirable help suitable for corporate internal resources so that they can continue to be competitive. This study classifies the types of ICT SMEs participating in government support programs, and analyzes the relationship between resources and performance creation of each type. The data from the "ICT Small and Medium Enterprises Survey" conducted annually by the Ministry of Science and ICT was used. In the first stage, ICT SMEs were clustered based on common factors according to their experiences with government support programs. Three clusters were meaningfully classified, and each cluster was named "active participation type," "initial support type," and "soloist type." As a second step, this study compared the characteristics of each cluster through profiling analysis for each cluster. The third step carried out in this study was to find out the mechanism of R&D performance creation for each cluster through regression analysis. Different factors affected performance creation for each cluster, and the magnitude of the influence was also different. Specifically, for "active participation type", "current manpower", "technology competitiveness", and "R&D investment in the previous year" were found to be important factors in creating R&D performance. "Initial support type" was identified as "whether or not a dedicated R&D organization exists", "R&D investment amount in the previous year", "Ratio of sales to large companies", and "Ratio of vendors supplied to large companies" contributed to the performance. Lastly, in the case of "soloist type", "current workforce" and "future recruitment plan", "technological competitiveness", "R&D investment", "large company sales ratio", and "overseas sales ratio" showed a significant relationship with the performance. This study has practical implications of showing what strategy should be established when supporting SMEs in the future according to the government's participation in the startup program and providing a guide on what kind of support should be provided.

• Journal of the Economic Geographical Society of Korea
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• v.20 no.1
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• pp.105-120
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• 2017

Chung-ju enterprise city was selected as a model enterprise city in 2005, and the city is planned to finish the construction in 2020. The main purpose of this study is to suggest the developing strategy and activation plan for Chung-ju enterprise city based on the enterprise city of developed countries. Chung-ju enterprise city will grow into well-being self-sufficient city due to the cutting edge knowledge, industry-centered cluster which is the new growth industry of Chungchungbuk-do and the surrounding excellent nature. For the success of Chung-ju enterprise city, the cooperation between developing agents such as companies, universities, local government, and central government is important. The leading companies and researching facilities should be attracted as well. Also, non-profit exclusive organization must be installed. The successful development of Chung-ju enterprise city means the success of balanced region development policy which will solve overpopulation of capital region and unbalance of Korea.

• World Technopolis Review
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• v.5 no.1
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• pp.2-18
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• 2016

The development of Technopolis and the establishment of innovative ecosystem have made an important contribution in South Korea's latest industrial development and economic growth. Particularly, Daedeok INNOPOLIS which is responsible for the central role in the national science technology advancement was founded as the Science Town in the 1970s. Since then, it has undergone three-phases of development: Science Park, Technopolis and Innovation cluster. As the result of the transition, Daedeok INNOPOLIS currently serve as the leading role for achieving sustainable economic growth, employment promotion, national and regional innovation. In order to accelerate the progress for success, Daedeok INNOPOLIS have arranged an opportunity for 21st century new industry development, improved growth of technology-intensive SMEs, reinforced academic-industrial cooperation, and established innovative ecosystem. Daedeok INNOPOLIS is considered as an outstanding case of endogenous development strategy of Technopolis. This study attempts to consider the endogenous development strategy of Technopolis in Korea through the analysis of development characteristics of Daedeok INNOPOLIS in two different perspectives: changes of spatial structure and establishment of innovation ecosystem. Daedeok INNOPOLIS have experienced a series of endogenous growth that is consisted of advancement strategy and structural changes, which allowed Daedeok research town to grow into an innovative cluster. A sign of growth of Daedeok INNOPOLIS became apparent when its strategy to reinforce the academic-industry cooperation system by promoting participation from universities helped to overcome a functional limitation as a research institute integrated for the establishment of innovative ecosystem. Since then, the center for creative economy and innovation established in cooperation with large enterprise, has a role to build a startup ecosystem and to promote next level of development such as proactive fostering of venture companies for sustainable technopolis development.

• Journal of the Korean Society of Safety
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• v.32 no.6
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• pp.110-115
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• 2017

Currently, the Ministry of Employment and Labor is strengthening monitor programs in regards to occupational industrial safety and health act compliance in business operations. However, industrial accidents occur persistently. Therefore, the study strives to diagnose and understand the issues in its educational stature, targeting managing supervisors in large scale shipbuilding industry whose completed the regular safety and health act sessions. This research considered a total of 3,252 employees whose completed theory-based cluster sessions for three months since February, 2016. The group is divided into two categories; 551 participants whose completed 8 hours of training and 2,701 participants whose completed 4 hours of training. Technical statistics were used to measure the knowledge of safety and health, educational environment, curriculum and educational effects on managing supervisors. A t-test was used to analyze the difference between the training hours. The result indicated that the target participants' knowledge on safety and health before the session was 50.24 points average (100 point scale), showing low standards in general. In depth analysis indicated that both 8 hours and 4 hours groups scored lowest in educational methods and communications between the lecturer and participants factors within the educational curriculum category. Meanwhile, transition in knowledge acquirement, work attitude, and work behaviors scored the highest in the analysis, showing a high satisfaction factors in educational effects. Therefore, the improvement in educational time and period can increase the efficacy of the educational programs. Also, theory-based cluster programs based on lectures suggests positive influence in knowledge acquirement and behavioral transitions.

• Journal of Korea Society of Digital Industry and Information Management
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• v.15 no.4
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• pp.197-212
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• 2019

The purpose of this study is to identify the maturity stages of venture firms through classification analysis, which is widely used as a big data technique. Venture companies should develop a competitive advantage in the market. And the maturity stage of a company can be classified into five stages. I will analyze a difference in the growth stage of venture firms between the survey response and the statistical classification methods. The firm growth level distinguished five stages and was divided into the period of start-up and declines. A classification method of big data uses popularly k-mean cluster analysis, hierarchical cluster analysis, artificial neural network, and decision tree analysis. I used variables that asset increase, capital increase, sales increase, operating profit increase, R&D investment increase, operation period and retirement number. The research results, each big data analysis technique showed a large difference of samples sized in the group. In particular, the decision tree and neural networks' methods were classified as three groups rather than five groups. The groups size of all classification analysis was all different by the big data analysis methods. Furthermore, according to the variables' selection and the sample size may be dissimilar results. Also, each classed group showed a number of competitive differences. The research implication is that an analysts need to interpret statistics through management theory in order to interpret classification of big data results correctly. In addition, the choice of classification analysis should be determined by considering not only management theory but also practical experience. Finally, the growth of venture firms needs to be examined by time-series analysis and closely monitored by individual firms. And, future research will need to include significant variables of the company's maturity stages.