• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.433-435
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• 2022

In this paper, we introduce a computing resource standard metadata schema design plan for registering, retrieving, and managing computing resources used for research data analysis and utilization in the Korea Research Data Commons(KRDC). KRDC is a joint utilization system of research data and computing resources to maximize the sharing and utilization of research data. Computing resources refer to all resources in the computing environment, such as analysis infrastructure and analysis software, necessary to analyze and utilize research data used in the entire research process. The standard metadata schema for KRDC computing resource management is designed by considering common attributes for computing resource management and other attributes according to each computing resource feature. The standard metadata schema for computing resource management consists of a computing resource metadata schema and a computing resource provider metadata schema. In addition, the metadata schema of computing resources and providers was designed as a service schema and a system schema group according to their characteristics. The standard metadata schema designed in this paper is used for computing resource registration, retrieval, management, and workflow services for computing resource providers and computing resource users through the KRDC web service, and is designed in a scalable form for various computing resource links.

• Journal of the Korea Convergence Society
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• v.11 no.7
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• pp.217-222
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• 2020

This study is about the data quality management evaluation model. As the information and communication technology is advanced and the importance of storage and management begins to increase, the guam feeling for data is increasing. In particular, interest in the fourth industrial revolution and artificial intelligence has been increasing recently. Data is important in the fourth industrial revolution and the era of artificial intelligence. In the 21st century, data will likely play a role as a new crude oil. It can be said that the management of the quality of this data is very important. However, research is being conducted at a practical level, but research at an academic level is insufficient. Therefore, this study examined factors affecting data quality management for experts and suggested implications. As a result of the analysis, there was a difference in the importance of data quality management.

• Journal of the Korean Society for Nondestructive Testing
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• v.20 no.3
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• pp.200-205
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• 2000

In a previous paper, we have discussed the intelligent Windows 95-based data management program(IDPIN) which was developed for effective and efficient management of large amounts of pre-/in-service inspection(PSI/ISI) data of Kori nuclear power plants. The IDPIN program enables the prompt extraction of previously conducted PSI/ISI conditions and results so that the time-consuming data management, painstaking data processing and analysis of the past are avoided. In this study, the intelligent Windows based data management program(WS-IDPIN) has been developed as an effective data management of PSI/ISI data for the Wolsong nuclear power plants. The WS-IDPIN program includes the modules of comprehensive management and analysis of PSI/ISI results, statistical reliability assessment program of PSI/ISI results(depth and length sizing performance etc), standardization of UT report form and computerization of UT results. In addition, the program can be further developed as a unique PSI/ISI data management expert system which can be part of the PSI/ISI total support system for Korean nuclear power plants.

• Journal of Distribution Science
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• v.20 no.4
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• pp.65-75
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• 2022

Purpose: Environmental pollution problems have become more and more serious, how to effectively protect the environment has become a hot spot of concern to all sectors of society. The way to solve this problem is environmentally friendly management. However, theoretical perspectives and research frameworks of existing research on environmentally friendly management are still unclear. This study aims to examine how the CEO's beliefs for SMEs of Chinese distribution industry affect the environmentally friendly management based on institutional theory. Research design, data, and methodology: This paper collected data from 215 SMEs in China distribution industry and conducted a series of data analysis and hypothesis testing based on an institutional theory perspective using Amos and SPSS to verify the effects of regulatory pressure, normative pressure, and imitation pressure on firms' environmentally friendly management. Results: Through the analysis, this paper tests that normative pressure and imitative pressure have a positive effect on CEO's beliefs. However, regulatory pressure did not have a significant effect on beliefs of CEO. Meanwhile, the degree of CEO's beliefs has a positive effect on environmentally friendly management in Chinese distribution SMEs. Conclusions: Theoretical contributions, practical implications, and future research directions are discussed.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.9
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• pp.351-362
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• 2020

This research investigates the credit management guidelines to strengthen Thai industrial sector. The research has been simulated from the findings of both qualitative and quantitative of 500 questionnaires distributed to industrial business executives in Thailand. The data were analyzed by descriptive analysis categorized into SME and large enterprises, and SEM to conduct the model in consistent with the empirical data. The results show that: (1) the credit management guidelines consist of 4 factors: a) characteristics management b) financial management c) operations management and d) assets management. The business executives gave overall importance on the guidelines at a high level with an average of 3.86. (2) The development of SEM shows that the model fits with the empirical data at Chi-Square probability level = 0.084, CMIN/DF = 1.164, GFI = 0.965 and RMSEA = 0.018. (3) The characteristics management directly influences the financial management and the operation management. The financial management directly influences on the assets management. The assets management has direct influence on the operations management. The findings show that the characteristics management is the essential starting component in SEM and the financial management factor has the most influence in the assets management variable with standard regression weight of 0.990.

• Proceedings of the Korean Geotechical Society Conference
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• 2008.10a
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• pp.980-983
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• 2008

KICT has been carrying out inventory research on the cut slopes of national roads. Inventory research results are basic data used in cut slope management system. Inventory data are classified by general status, cut slope characteristics and inspector opinion. Cut slope inventory data are utilized to figure out dangerous slopes and decide survey ranking of detailed safety diagnostication. This paper will draw dangerous cut slope and more important inventory data in Chungcheongdo via correlation analysis.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.4
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• pp.311-332
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• 2016

Academic libraries have actively responded to social requirements and changes in scholarly communication system. In recent years, social and scholarly requirements for systematic management and sharing of research data have become apparent. Major countries including U.S., UK and Australia have begun national policies requiring management and sharing of research data from publicly funded R&D projects. This case study identified four academic libraries in the US with active research data support services and analyzed them in terms of how they established dedicated unit and the extent of services in the areas of instruction, consulting and system support. The analysis provides context for academic libraries in Korea in formulating their future research data strategies. The core of the recommendation is primarily concerned with developing instructional services and strengthening library's capabilities for research data management and sharing.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.2
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• pp.259-268
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• 2016

KEPCO installed AMI (Advanced Metering Infrastructure) metering system for low-voltage customers from 2008. AMI metering system of KEPCO has operated 2.55 million customers and will plan to operate 22 million customers until 2020. KEPCO developed AMI NMS (Network Management System) to operate the meter reading network efficiently. NMS monitors the network status of DCUs (Data Concentration Unit) and modems. NMS provides functionalities of data collection and analysis. It collects property data of network device, network topology information, communication performance information, fault information, and etc. It analyzes collected data and controls network devices by remote access. AMI NMS collects about 370 MIBs (Mangement Information Bases) using SNMP (Simple Network Management Protocol). This paper introduces main functionalities, designed context, and implemented service screen.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.2
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• pp.91-100
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• 2009

"How does advertising affect sales?" is the fundamental issue of modern advertising research. There is an interesting issue for estimating carryover effects of advertising on sales, and the aggregated data biases exist in the duration of advertising effect. This research suggests an extended model of Koyck Model which is employed for micro-data (Koyck 1954) to estimate aggregated advertising data, and empirically shows the aggregated data bias. Our developed model with the aggregated level of actual advertising data is more appropriate than the basic Koyck model for micro-data. The result figures out that it is important to consider the disaggregated data level in the analysis of dynamic effects of adverting such as carryover effects.

• Journal of Korean Society on Water Environment
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• v.29 no.3
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• pp.343-353
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• 2013

Flow duration curve (FDC) can be developed by linking the daily flow data of stream flow monitoring network to 8-day interval flow data of the unit watersheds for the management of Total Maximum Daily Loads. This study investigated the applicable method for the development of long term FDC with the selection of the stream flow reference sites, and suggested the development of the FDC in 4 river basins. Out of 142 unit watersheds in 4 river basins, 107 unit watersheds were shown to estimate daily flow data for the unit watersheds from 2006 to 2010. Short term FDC could be developed in 64 unit watersheds (45%) and long term FDC in 43 unit watersheds (30%), while other 35 unit watersheds (25%) were revealed to have difficulties in the development of FDC itself. Limits in the development of the long term FDC includes no stream monitoring sites in certain unit watersheds, short duration of stream flow data set and missing data by abnormal water level measurements on the stream flow monitoring sites. To improve these limits, it is necessary to install new monitoring sites in the required areas, to keep up continuous monitoring and make normal water level observations on the stream flow monitoring sites, and to build up a special management system to enhance data reliability. The development of long term FDC for the unit watersheds can be established appropriately with the normal and durable measurement on the selected reference sites in the stream flow monitoring network.