• Journal of Information Technology Applications and Management
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• v.27 no.1
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• pp.59-73
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• 2020

There is a growing interest in convergence. National R & D is also providing various policies and institutional support to promote convergence research. Convergence research, however, does not clearly specify its characteristics at the academic and government levels. This research proceeds with the process of collecting, refining, analyzing, modeling, verifying and visualizing national R & D data through the National Science and Technology Information Service (NTIS). The method is to derive the convergence research characteristics and to derive through text mining, focusing on the unstructured information of national R & D project data. The study confirmed that there was a difference in perception between the definition of converged research and the research site. In order to improve this, the research suggested that convergence among research subjects, collaboration among research topics reflecting various backgrounds and characteristics of researchers, and analysis of characteristics of convergence research using information were suggested in the process of establishing convergence policy.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.8
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• pp.1111-1115
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• 2014

With the increasing interest of a demand side management using a Smart Grid infrastructure, the demand resources and energy usage data management becomes an important factor in energy industry. In addition, with the help of Advanced Measuring Infrastructure(AMI), energy usage data becomes a Big Data System. Therefore, it becomes difficult to store and manage the demand resources big data using a traditional relational database management system. Furthermore, not many researches have been done to analyze the big energy data collected using AMI. In this paper, we are proposing a Hadoop based Big Data system to manage the demand resources energy data and we will also show how the demand side management systems can be used to improve energy efficiency.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.4
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• pp.97-110
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• 2022

The purpose of this study is to analyze the level of public data convergence capabilities of administrative organizations and to explore important variables in data-based organizational capabilities. The theoretical background was summarized on public data and use activation, joint use, convergence, administrative organization, and convergence constraints. These contents were explained Public Data Act, the Electronic Government Act, and the Data-Based Administrative Act. The research model was set as the data-based organizational capabilities effect by a data-based administrative capability, public data operation capabilities, and public data operation constraints. It was also set whether there is a capabilities difference data-based on an organizational operation by the level of data convergence capabilities. This study analysis was conducted with hierarchical cluster analysis and multiple regression analysis. As the research result, First, hierarchical cluster analysis was classified into three groups. It was classified into a group that uses only public data and structured data, a group that uses public data on both structured and unstructured data, and a group that uses both public and private data. Second, the critical variables of data-based organizational operation capabilities were found in the data-based administrative planning and administrative technology, the supervisory organizations and technical systems by public data convergence, and the data sharing and market transaction constraints. Finally, the essential independent variables on data-based organizational competencies differ by group. This study contributed. As a theoretical implication, this research is updated on management information systems by explaining the Public Data Act, the Electronic Government Act, and the Data-Based Administrative Act. As a practical implication, the activity reinforcement of public data should be promoting the establishment of data standardization and search convenience and elimination of the lukewarm attitudes and Selfishness behavior for data sharing.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.4
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• pp.216-224
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• 2013

Facility data is created throughout the design and construction phase. But the most facility managers bear significant costs that arise from the lack of interoperability with facility lifecycle. This paper is concerned with the way to collect facility data using BIM technology. The aim of this paper is to suggest BIM data modeling guide for the facility management using the information that need to be delivered from design and construction phase to operation and management phase. The BIM data modeling guide focus on the properties of mechanical equipment. It is to be hoped that this study will contribute to collect facility data from as-built BIM data and to build facility management system database without difficulty.

• Journal of Korean Society for Quality Management
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• v.30 no.4
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• pp.68-77
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• 2002

EM algorithm has good convergence rate for numerical procedures which converges on very small step. In the case of proportion estimation in a mixed distribution which has very big incomplete data or of update of new data continuously, however, EM algorithm highly depends on a initial value with slow convergence ratio. There have been many studies to improve the convergence rate of EM algorithm in estimating the proportion parameter of a mixed data. Among them, dynamic EM algorithm by Hurray Jorgensen and Titterington algorithm by D. M. Titterington are proven to have better convergence rate than the standard EM algorithm, when a new data is continuously updated. In this paper we suggest dynamic EM algorithm and Titterington algorithm for the estimation of a mixed Poisson distribution and compare them in terms of convergence rate by using a simulation method.

• International journal of advanced smart convergence
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• v.5 no.4
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• pp.26-31
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• 2016

In a cloud computing environment, a cryptographic service allows an information owner to encrypt the information and send it to a cloud server as well as to receive and decode encrypted data from the server which guarantees the confidentiality of shared information. However, if an attacker gains a coded data and has access to an encryption key via cloud server, then the server will be unable to prevent data leaks by a cloud service provider. In this paper, we proposed a key management server which does not allow an attacker to access to a coded key of the owners and prevents data leaks by a cloud service provider. A key management server provides a service where a server receives a coded public key of an information user from an owner and delivers a coded key to a user. Using a key management server proposed in this paper, we validated that the server can secure the confidentiality of an encryption key of data owners and efficiently distribute keys to data users.

• Journal of Wellbeing Management and Applied Psychology
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• v.4 no.4
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• pp.1-14
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• 2021

Purpose: This study aims to measure the level of satisfaction with the overall education of current students, who are major consumers of education by department at the Health Care Convergence University, and to establish development strategies such as improving education quality and satisfaction by deriving problems and improvements. Research design, data and methodology: This study drew conclusions through secondary data analysis based on data surveyed by the Educational Performance Management Center of a university in the academic year of 2020. The target of the education consumer satisfaction survey was 470 students of the College in the academic year 2020. Frequency analysis and correlation analysis were applied to the data using the statistical package program SPSS 25 version. Results: In the major curriculum satisfaction survey, the department with the highest score was optics and optics, 4.11, and the department with the lowest score was medical IT, 3.29. Conclusions: The department with the highest correlation in the correlation analysis result of the demand survey by department was the Department of Medical Management and the Department of Medical IT, with a correlation coefficient r=0.984, and the lowest correlation in the correlation analysis result of the demand survey by department was the Department of Medical IT and Dental Hygiene, with a correlation coefficient r= -0.085.

• ETRI Journal
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• v.31 no.2
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• pp.215-224
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• 2009

Analyzing the diffusion of a convergence product is a new and challenging research field. It is very difficult to find research dealing with this issue due to the inherent complexity and lack of data. In analyzing the diffusion of a convergence product, we should simultaneously take into account its relationship with related single-function products because of their similarities in terms of technology and functionality. In this study, we empirically analyze the diffusion of the convergence mobile phones in South Korea and find that the convergence products can affect the diffusion of MP3 players and digital cameras positively or negatively. This research may be significant for business strategies in technology management and product development.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.3
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• pp.483-497
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• 2023

This study aims to provide strategic recommendations for promoting the development of the global satellite data services industry by analyzing the startup landscape. Based on the analysis of startup data, such as number of startups, market segment, and funding amount, we examined the paradigm shift in the global satellite data services market, particularly its convergence with other market segments. To this end, we derived the cumulative funding-convergence dynamics matrix, which classifies the converging areas into four quadrants by considering the growth rate of converging segments and the cumulative funding amount. In this way, we can specify converging areas in the satellite data services market that bear potential importance for the creation of new markets. The findings of this study are expected to contribute to the advancement of the satellite data services industry and facilitate the exploration of new market opportunities. Furthermore, they can serve as a valuable reference for policy makers, industry stakeholders, government officials, and researchers involved in the satellite data services industry in capitalizing on the emerging space economy.

• Journal of the Korea Convergence Society
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• v.11 no.8
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• pp.15-22
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• 2020

In order to strengthen the disaster prevention phase and the management of social disasters, we will examine the plan of To-Be disaster management system interconnected by using intelligent information technologies such as IoT, Cloud, Big Data, Mobile and AI. The disaster management system can be upgraded by constructing an intelligent infrastructure based on Big Data analysis of the disaster signals before and after the disasters generated by private mobile and IoT. Big Data of disaster Signals can be customized to users in a timely manner through AI methodologies of supervised and unsupervised learning and reinforcement training. In the long term, it is expected that not only will the capacity of disaster response be improved, but the management ability centering on prevention will be enhanced as well.