• The Journal of Economics, Marketing and Management
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• v.10 no.3
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• pp.1-8
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• 2022

Purpose: This study aims to examine the effect of SMEs' R&D competence on management performance. Research design, data, and methodology: The empirical data of this study are derived from 2,375 SMEs that participated in the material, parts, and equipment research and development support project conducted from 2014 to 2018. Among them, 2,230 data were analyzed by classifying them into high-tech and low-tech fields. SPSS 24.0 was used for statistical analysis and correlation analysis and T-TEST were applied. Results: It was analyzed that the level of R&D organization, research personnel, and the number of patent registrations all affected operating profit and sales. In particular, it has been proven that research personnel have a greater impact on management performance among the level of R&D organization, research personnel, and the number of patent registrations. In addition, there was a difference between high-tech and low-tech industries in the impact on operating profit and sales, which are indicators of management performance. Conclusions: This study suggests that R&D competence are strengthened to advance the material, parts, and equipment industries and to promote future growth, while differentiated support is needed according to each company's R&D competence and technology level.

• The Journal of Economics, Marketing and Management
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• v.5 no.2
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• pp.1-9
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• 2017

This study has reviewed the "A survey on the relation between the employees' viewpoint with knowledge management and cultural intelligence among the employees working in Social Security Organization of Ardabil". The present study is functional in terms of objective and the method is descriptive and survey. This has asked the others' ideas and viewpoints concerning a specific subject and has analyzed them. About the nature and the method used, the present research is of correlation research. The population applied in this research includes all employees working in Social Security Organization of Ardabil consisting of 400. The method used for sampling is simple random sampling. To collect the information in the first step of the research the library method has been used. In this research the data has been collected through standard questionnaires. Then, via descriptive and inferential statistics the research data has been characterized and regarding the spatial scaling of the measurement to test the hypothesis the, correlation analysis of Pearson has been used and also to specify the reliability of the questionnaire the Chronbach's Alpha has been taken in use and the SPSS software to analyze the data also. The findings resulted from the study showed that there is a significant relation between the factors concerning employees' efficiency with knowledge management and the cultural intelligence and all hypotheses was confirmed.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05a
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• pp.291-296
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• 1998

The DAta management and Communication NETworks (DACONET), Which it is designed as a subsystem for Man-Machine Interface System of Korea Advanced LIquid MEtal Reactor(KALIMER MMIS) and advanced design concept is approached, is described. The DACONET has its roles of providing the real-time data transmission and communication paths between MMIS systems, providing the quality data for protection, monitoring and control of KALIMER and logging the static and dynamic behavioral data during KALIMER operation. The DACONET is characterised as the distributed real-time system architecture with high performance, Future direction, in which advanced technology is being continually applied to Man-Machine interface System Development of Nuclear Power Plants, will be considered for designing data management and communication networks of KALIMER MMIS

• Journal of Information Science Theory and Practice
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• v.8 no.4
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• pp.20-28
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• 2020

In this study, the RDA DMP Common Standard (RDCS), a data model for implementing a machine actionable Data Management Plan (maDMP), was analyzed in four aspects. First, the twelve class models proposed by RDCS were analyzed. Second, whether the DMP attribute was included in the class attribute was analyzed. Third, we analyzed the namespace used for RDCS properties. Fourth, the values and identifiers used in RDCS properties were analyzed. As a result of the analysis, four directions for improvement were derived. First, it is necessary to add an academic record class to describe information such as papers and reports, which are representative academic documents. Second, the primary research institution, responsibility, resources, option attribute, and additional attributes are needed to describe the researcher's affiliation information. Third, it is necessary to additionally use a namespace such as Friend of a Friend that can be used universally. Fourth, the use of digital object identifier should be considered to identify academic literature.

• Journal of the Korean Operations Research and Management Science Society
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• v.42 no.3
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• pp.25-34
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• 2017

K-means is a popular and efficient data clustering method that only uses intra-cluster distance to establish a valid index with a previously fixed number of clusters. K-means is useless without a suitable number of clusters for unsupervised data. This paper aimsto propose the Group Search Optimization (GSO) using Silhouette to find the optimal data clustering solution with a number of clusters for unsupervised data. Silhouette can be used as valid index to decide the number of clusters and optimal solution by simultaneously considering intra- and inter-cluster distances. The performance of GSO using Silhouette is validated through several experiment and analysis of data sets.

• Genomics & Informatics
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• v.3 no.1
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• pp.39-42
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• 2005

DNA microarray is a high-throughput biomedical technology that monitors gene expression for thousands of genes in parallel. The abundance and complexity of the gene expression data have given rise to a requirement for their systematic management and analysis to support many laboratories performing microarray research. On these demands, we developed Xperanto for integrated data management and analysis using user-friendly web-based interface. Xperanto provides an integrated environment for management and analysis by linking the computational tools and rich sources of biological annotation. With the growing needs of data sharing, it is designed to be compliant to MGED (Microarray Gene Expression Data) standards for microarray data annotation and exchange. Xperanto enables a fast and efficient management of vast amounts of data, and serves as a communication channel among multiple researchers within an emerging interdisciplinary field.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.25 no.3
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• pp.165-189
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• 2014

This study examined the current practices of Research Data Management (RDM) services recently built and implemented at research university libraries in the U.S. by analyzing the components of the services and the contents presented in their web sites. The study then analyzed the content of web pages describing the services provided by 31 Research Universities/Very High research activity determined based on the Carnegie Classification. The analysis was based on 9 components of the services suggested by previous studies, including (1) DMP support; (2) File organization; (3) Data description; (4) Data storage; (5) Data sharing and access; (6) Data preservation; (7) Data citation; (8) Data management training; (9) Intellectual property of data. As a result, the vast majority of the universities offered the service of DMP support. More than half of the universities provided the services for describing and preserving data, as well as data management training. Specifically, RDM services focused on offering the guidance to disciplinary metadata and repositories of relevance, or training via individual consulting services. More research and discussion is necessary to better understand an intra- or inter-institutional collaboration for implementing the services and knowledge and competency of librarians in charge of the services.

• The Journal of Engineering Geology
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• v.33 no.2
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• pp.323-334
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• 2023

The vast volumes of data that are generated during site characterization and associated research for the disposal of high-level radioactive waste require effective data management to properly chronicle and archive this information. The Swedish Nuclear Fuel and Waste Management Company, SKB, established the SICADA database for site selection, evaluation, analysis, and modeling. The German Federal Company for Radioactive Waste Disposal, BGE, established ArbeitsDB, a database and document management system, and the ELO data system to manage data collected according to the Repository Site Selection Act. The U.K. Nuclear Waste Services established the Data Management System to manage any research and survey data pertaining to nuclear waste storage and disposal. The U.S. Department of Energy and Office of Civilian Radioactive Waste Management established the Technical Data Management System for data management and subsequent licensing procedures during site characterization surveys. The presented cases undertaken by these national agencies highlight the importance of data quality management and the scalability of data utilization to ensure effective data management. Korea should also pursue the establishment of both a data management concept for radioactive waste disposal that considers data quality management and scalability from a long-term perspective and an associated data management system.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.2
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• pp.1-19
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• 2014

Recently, one of the core keywords in information technology (IT) as well as areas such as business management is big data. Big data is a term that includes technology, personnel, and organization required to gather/manage/analyze collection of data sets so large and complex that it becomes difficult to manage and analyze using traditional tools. The military has been accumulating data for a long period due to the organization's characteristic in placing emphasis on reporting and records. Considering such characteristic of the military, this study verifies the possibility of improving the performance of the military organization through use of big data and furthermore, create scientific development of operation, strategy, and support environment. For this purpose, the study organizes general status and case studies related to big data, traces back examples of data utilization by Korean's national defense sector through US military data collection and case studies, and proposes the possibility of using and applying big data in the national defense sector.

• Journal of the Korean Society for Library and Information Science
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• v.53 no.4
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• pp.309-340
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• 2019

Although overseas countries have already developed data life cycle for the preservation and curation of data since the 1990s, the research in Korea has been very insufficient. In this study, we analyzed the data life cycles developed in DCC, ICPSR, IWGDD, DataONE, USGS and UKDA to propose data life cycle for efficient management of research data. As a result of the analysis, the common components derived are 'Plan', 'Create & Collect', 'Process', 'Preserve', 'Dispose', 'Access & Use', 'Describe', 'Assure' and 'Backup & Secure'. In addition, the nine components were subdivided into stages to describe the details to be carried out at that stage. It is expected that the content of this study will be applicable in the future development of data life cycle for research data management in Korea.