• Journal of Korean Society for Atmospheric Environment
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• v.24 no.1
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• pp.1-15
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• 2008

Chemical Accident Response Information System (CARIS) which has been designed for the efficient emergency response of chemical accidents produces the real-time atmospheric fields through the Regional Atmospheric Modeling System, RAMS. The previous studies were emphasized that improving an initial input data had more effective results in developing prediction ability of atmospheric model. In a continuous effort to improve an initial input data, we replaced the land-use dataset using in the RAMS, which is a high resolution USGS digital data constructed in April, 1993, with the latest land-use data of the Korea Ministry of Environment over the South Korea and simulated atmospheric fields for developing a real-time prediction in dispersion of chemicals. The results showed that the new land-use data was written in a standard RAMS format and shown the modified surface characteristics and the landscape heterogeneity resulting from land-use change. In the results of sensitivity experiment we got the improved atmospheric fields and assured that it will give more reliable real-time atmospheric fields to all users of CARIS for the dispersion forecast in associated with hazardous chemical releases as well as general air pollutants.

• Journal of the Korean Society for Nondestructive Testing
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• v.26 no.4
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• pp.246-254
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• 2006

A computation program has been developed for automatic data processing in the calibration process of gamma survey meter. The automatic processing program has been developed based on Visual Basic. The program has been coded according to steps of calibration procedure. The OLE(object linking an embedding) Excel automation method fur automatic data processing is used in this program, which is a kind of programming technique for the Excel control. The performance test on the basis of reference data has been carried out by using the developed program. In the results of performance test, the values of calibration factors and uncertainties by the developed program were equal to those obtained from the reference data. In addition, It was revealed that the efficiency and precision of working are significantly increased by using the developed program.

• Journal of Korean Library and Information Science Society
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• v.51 no.4
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• pp.249-278
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• 2020

The purpose of this study is to design metadata for management and sharing of Yeogu data produced in the ecological field. Specifically, metadata is designed based on DCAT, which is designed to facilitate interoperability between data catalogs published on the web. In addition, ABCD, Darwin Core, and EML were analyzed and applied to metadata design to reflect the characteristics of the ecological field. As a result of the research, a total of 51 metadata elements were derived for managing research data in the ecological field, and 6 essential elements, 23 recommended elements, and 22 optional elements were included. The results of this study can be used to design a DB when building a research data management and sharing system based on metadata elements, and to suggest a metadata exchange format when linking with other systems.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.81-92
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• 2023

A privacy model is a technique that quantitatively restricts the possibility and degree of privacy breaches through privacy attacks. Representative models include k-anonymity, l-diversity, t-closeness, and differential privacy. While many privacy models have been studied, research on selecting the most suitable model for a given dataset has been relatively limited. In this study, we develop a system for recommending the suitable privacy model to prevent privacy breaches. To achieve this, we analyze the data features that need to be considered when selecting a model, such as data type, distribution, frequency, and range. Based on privacy model background knowledge that includes information about the relationships between data features and models, we recommend the most appropriate model. Finally, we validate the feasibility and usefulness by implementing a recommendation prototype system.

• KNOM Review
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• v.22 no.2
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• pp.22-28
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• 2019

A Science DeMilitarized Zone (DMZ) is an optimized network technology tailored to research data nature. The Science DMZ guarantees end-to-end network performance by forming a closed research network without redundant networking and security devices for the authorized researchers. Data Transfer Node (DTN) is an essential component for the high performance and security of the Science DMZ, since only transfer functions of research data are allowed to the DTN without any security- and performance-threatening functions such as commercial internet service. Current Science DMZ requires per-user DTN server installation which turns out a scalability limitation of the networks in terms of management overhead, entry barrier of the user, and networks-wise CAPEX. In order to relax the aforementioned scalability issues, this paper suggests a centralized DTN design where end users in a group can share the centralized DTN. We evaluate the effectiveness of the suggested sharable DTN design by comparing CAPEX against to that of current design with respect to the diverse network load and the state-of-the-art computing machine.

• Proceedings of the Korean Vacuum Society Conference
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• 2015.08a
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• pp.64-64
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• 2015

Control of plasma processing methodologies can only occur by obtaining a thorough understanding of the physical and chemical properties of plasmas. However, all plasma processes are currently used in the industry with an incomplete understanding of the coupled chemical and physical properties of the plasma involved. Thus, they are often 'non-predictive' and hence it is not possible to alter the manufacturing process without the risk of considerable product loss. Only a more comprehensive understanding of such processes will allow models of such plasmas to be constructed that in turn can be used to design the next generation of plasma reactors. Developing such models and gaining a detailed understanding of the physical and chemical mechanisms within plasma systems is intricately linked to our knowledge of the key interactions within the plasma and thus the status of the database for characterizing electron, ion and photon interactions with those atomic and molecular species within the plasma and knowledge of both the cross-sections and reaction rates for such collisions, both in the gaseous phase and on the surfaces of the plasma reactor. The compilation of databases required for understanding most plasmas remains inadequate. The spectroscopic database required for monitoring both technological and fusion plasmas and thence deriving fundamental quantities such as chemical composition, neutral, electron and ion temperatures is incomplete with several gaps in our knowledge of many molecular spectra, particularly for radicals and excited (vibrational and electronic) species. However, the compilation of fundamental atomic and molecular data required for such plasma databases is rarely a coherent, planned research program, instead it is a parasitic process. The plasma community is a rapacious user of atomic and molecular data but is increasingly faced with a deficit of data necessary to both interpret observations and build models that can be used to develop the next-generation plasma tools that will continue the scientific and technological progress of the late 20th and early 21st century. It is therefore necessary to both compile and curate the A&M data we do have and thence identify missing data needed by the plasma community (and other user communities). Such data may then be acquired using a mixture of benchmarking experiments and theoretical formalisms. However, equally important is the need for the scientific/technological community to recognize the need to support the value of such databases and the underlying fundamental A&M that populates them. This must be conveyed to funders who are currently attracted to more apparent high-profile projects.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.47-57
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• 2007

Real-time oceanographic information system was developed using platforms of aquaculture farms to examine causes of mass mortality of hatchery fishes, and to reduce the damage of mass mortality which has been occurred frequently off coast by abnormal change of ocean conditions. The system had the advantages of direct data distribution to fishermen at the farm and instant maintenance of equipments due to easy access to the farms and residents at the farms in comparison with offshore mooring buoy system. To avoid discontinued measurement of the system, repairs caused by malfunction of equipments, bimonthly preventive maintenances and daily monitoring of measured data were systematized. Confidence intervals calculated by a statistical method using accumulated data were applied to data management. Such activities could minimize discontinuance of measurement and keep information more trustful. In addition, the system has various ways of data distribution. Through homepage and e-mail in the internet, information was provided to public. Display units which were connected to equipments at the farm gave the measured data directly to fishermen, which guided them to run their farm scientifically. Finally large display unit was installed at a fish market and showed the measured data at the nearest station with tide and weather information. Proper region for aquaculture and wintering region were studied using temperature data obtained by the system in 2006. The system will contribute to reduce economic damage of coastal fishery and to understand coastal marine environment.

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.403-428
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• 2023

This study investigates the development path and intellectual structure of data literacy research, aiming to identify emerging topics in the field. A comprehensive search for data literacy-related articles on the Web of Science reveals that the field is primarily concentrated in Education & Educational Research and Information Science & Library Science, accounting for nearly 60% of the total. Citation network analysis, employing the PageRank algorithm, identifies key papers with high citation impact across various topics. To accurately trace the development path of data literacy research, an enhanced PageRank main path algorithm is developed, which overcomes the limitations of existing methods confined to the Education & Educational Research field. Keyword bibliographic coupling analysis is employed to unravel the intellectual structure of data literacy research. Utilizing the PNNC algorithm, the detailed structure and clusters of the derived keyword bibliographic coupling network are revealed, including two large clusters, one with two smaller clusters and the other with five smaller clusters. The growth index and mean publishing year of each keyword and cluster are measured to pinpoint emerging topics. The analysis highlights the emergence of critical data literacy for social justice in higher education amidst the ongoing pandemic and the rise of AI chatbots. The enhanced PageRank main path algorithm, developed in this study, demonstrates its effectiveness in identifying parallel research streams developing across different fields.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3543-3548
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• 2023

Shutdown chemistry evolution is performed in nuclear power plants at each refueling outage (RFO) to establish safe conditions to open system and minimize inventory of corrosion products in the reactor coolant system (RCS). After hydrogen peroxide is added to RCS during shutdown chemistry evolution, corrosion products are released and are removed by filters and ion exchange resins in the chemical volume control system (CVCS). Shutdown chemistry evolution including RCS clean-up time to remove released corrosion products impacts the critical path schedule during RFOs. The estimation of clean-up time prior to RFO can provide more reliable actions for RCS clean-up operations and transients to operators during shutdown chemistry. Electric Power Research Institute (EPRI) shutdown calculator (SDC) enables to provide clean-up time by Co-58 peak activity through operational data from nuclear power plants (NPPs). In this study, we have investigated the results of EPRI SDC by shutdown chemistry data of Co-58 activity using NPP data from previous cycles and modeled the estimated clean-up time by EPRI SDC using average Co-58 activity of the NPP. We selected two RFO data from the NPP to evaluate EPRI SDC results using the purification time to reach to 1.3 mCi/cc of Co-58 after hydrogen peroxide addition. Comparing two RFO data, the similar purification time between actual and computed data by EPRI SDC, 0.92 and 1.74 h respectively, was observed with the deviation of 3.7-7.2%. As the modeling the estimated clean-up time, we calculated average Co-58 peak concentration for normal cycles after cycle 10 and applied two-sigma (2σ, 95.4%) for predicted Co-58 peak concentration as upper and lower values compared to the average data. For the verification of modeling, shutdown chemistry data for RFO 17 was used. Predicted RCS clean-up time with lower and upper values was between 21.05 and 27.58 h, and clean-up time for RFO 17 was 24.75 h, within the predicted time band. Therefore, our calculated modeling band was validated. This approach can be identified that the advantage of the modeling for clean-up time with SDC is that the primary prediction of shutdown chemistry plans can be performed more reliably during shutdown chemistry. This research can contribute to improving the efficiency and safety of shutdown chemistry evolution in nuclear power plants.

• Journal of the Korean Society for information Management
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• v.34 no.3
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• pp.109-124
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• 2017

Through a wide variety of disciplines, practices on data access and re-use have been increased recently. In fact, there has been an emerging phenomenon that researchers tend to use the data sets produced by other researchers and give scholarly credit as citation. With respect to this practice, in 2012, Thomson Reuters launched Data Citation Index (DCI). With the DCI, citation to research data published by researchers are collected and analyzed in a similar way for citation to journal articles. The purpose of this study is to identify the characteristics and intellectual structure of sociology field based on research data, which is one of actively data-citing fields. To accomplish this purpose, two data sets were collected and analyzed. First, from DCI, a total of 8,365 data were collected in the field of sociology. Second, a total of 12,132 data were collected from Web of Science with a topic search with 'Sociology'. As a result of the co-word analysis of author provided-keywords for both data sets, the intellectual structure of research data-based sociology was composed of two areas and 15 clusters and that of article-based sociology was composed with three areas and 17 clusters. More importantly, medical science area was found to be actively studied in research data-based sociology and public health and psychology are identified to be central areas from data citation.