• Journal of Food Hygiene and Safety
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• v.35 no.6
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• pp.607-617
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• 2020

Human bio-monitoring (HBM) data is a very important resource for tracking total exposure and concentrations of a parent chemical or its metabolites in human biomarkers. However, until now, it was difficult to execute the integration of different types of HBM data due to incompatibility problems caused by gaps in study design, chemical description and coding system between different sources in Korea. In this study, we presented a standardized code system and HBM knowledge model (KM) based on relational database modeling methodology. For this purpose, we used 11 raw datasets collected from the Ministry of Food and Drug Safety (MFDS) between 2006 and 2018. We then constructed the HBM database (DB) using a total of 205,491 concentration-related data points for 18,870 participants and 86 chemicals. In addition, we developed a summary report-type statistical analysis program to verify the inputted HBM datasets. This study will contribute to promoting the sustainable creation and versatile utilization of big-data for HBM results at the MFDS.

• Journal of agricultural medicine and community health
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• v.34 no.1
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• pp.67-75
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• 2009

Objectives: This study was conducted to examine health inequality for gender and region in Korea. Especially it focused on health status such as disease prevalence and medical utilization of rural women. Methods: Data from the Korea national health and nutrition survey in 2001 were used. The final sample size was 37,108 individuals with age 20 and over. This study applied the logistic regression for nominal variables such as disease prevalence and unmet care needs and with the regression for continuos variables such as the length and costs of medical services. Results: Rates of disease prevalence and unmet care needs for chronic disease in rural area are higher than those in middle cities and big cities, and regional differences of those for women are more than those for mens with controlling ages. There could be interaction effect with region and sex. Conclusions: This study suggests that health policy maker should take consider of special status of rural women who are in health inequality.

• Spatial Information Research
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• v.22 no.5
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• pp.27-41
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• 2014

Recently, BIM(Building Information Modeling) has been applied to the infrastructure such as road and bridge, and information about the outside environment of buildings is needed for maintaining and managing the large urban facilities. In addition, the convergence between spatial information and Big-data has a large potentiality, in respect that considerable profits and developments in other application problems such as various simulations and urban plans, national land security, may be brought about on the basis of the interoperability of information between BIM and GIS. Therefore, this study attempted to suggest the development direction of a model integrating building for spatial information analysis and city on the subject by comparing and analyzing difference between information system and shape expression of IFC, CityGML and LandXML to efficiently link information between IFC as a standard model of BIM and CityGML as a standard model in the GIS sector and to prepare a basic fusion strategy and a method of utilization between BIM and GIS. The result of the study are as follow. Firstly, contents and structure of IFC, CityGML and LandXML are compared and analyzed. Secondly, the development direction of iBUM(Integrated Building and Urban Model) suggested, which is based on convergence technology for analysis of space information. Finally, a strategy and method of the BIM and GIS are proposed in the iBUM environment.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.4
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• pp.73-89
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• 2023

This study aims to analyze the frequency of keywords used in Korean abstracts, which are unstructured text data in the domestic record management research field, using text mining techniques to identify domestic record management research trends through distance analysis between keywords. To this end, 1,157 keywords of 77,578 journals were visualized by extracting 1,157 articles from 7 journal types (28 types) searched by major category (complex study) and middle category (literature informatics) from the institutional statistics (registered site, candidate site) of the Korean Citation Index (KCI). Analysis of t-Distributed Stochastic Neighbor Embedding (t-SNE) and Scattertext using Word2vec was performed. As a result of the analysis, first, it was confirmed that keywords such as "record management" (889 times), "analysis" (888 times), "archive" (742 times), "record" (562 times), and "utilization" (449 times) were treated as significant topics by researchers. Second, Word2vec analysis generated vector representations between keywords, and similarity distances were investigated and visualized using t-SNE and Scattertext. In the visualization results, the research area for record management was divided into two groups, with keywords such as "archiving," "national record management," "standardization," "official documents," and "record management systems" occurring frequently in the first group (past). On the other hand, keywords such as "community," "data," "record information service," "online," and "digital archives" in the second group (current) were garnering substantial focus.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.5
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• pp.409-416
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• 2020

Artificial intelligence, which is in the spotlight as the core driving force of the 4th industrial revolution, is expanding its scope to various industrial fields such as smart factories and autonomous driving with the development of high-performance hardware, big data, data processing technology, learning methods and algorithms. In the field of defense, as the security environment has changed due to decreasing defense budget, reducing military service resources, and universalizing unmanned combat systems, advanced countries are also conducting technical and policy research to incorporate artificial intelligence into their work by including recognition systems, decision support, simplification of the work processes, and efficient resource utilization. For this reason, the importance of technology-driven planning and investigation is also increasing to discover and research potential defense future technologies. In this study, based on the research data that was collected to derive future defense technologies, we analyzed the characteristic evaluation indicators for future technologies in the field of artificial intelligence and conducted empirical studies. The study results confirmed that in the future technologies of the defense AI field, the applicability of the weapon system and the economic ripple effect will show a significant relationship with the prospect.

• The Journal of Information Systems
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• v.26 no.3
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• pp.171-185
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• 2017

Purpose Recently, there has been an increase in attempts to analyze social phenomena, consumption trends, and consumption behavior through a vast amount of customer data such as web search traffic information and social buzz information in various fields such as flu prediction and real estate price prediction. Internet portal service providers such as google and naver are disclosing web search traffic information of online users as services such as google trends and naver trends. Academic and industry are paying attention to research on information search behavior and utilization of online users based on the web search traffic information. Although there are many studies predicting social phenomena, consumption trends, political polls, etc. based on web search traffic information, it is hard to find the research to explain and predict tourism demand and establish tourism policy using it. In this study, we try to use web search traffic information to explain the tourism demand for major cities in Gangwon-do, the representative tourist area in Korea, and to develop a nowcasting model for the demand. Design/methodology/approach In the first step, the literature review on travel demand and web search traffic was conducted in parallel in two directions. In the second stage, we conducted a qualitative research to confirm the information retrieval behavior of the traveler. In the next step, we extracted the representative tourist cities of Gangwon-do and confirmed which keywords were used for the search. In the fourth step, we collected tourist demand data to be used as a dependent variable and collected web search traffic information of each keyword to be used as an independent variable. In the fifth step, we set up a time series benchmark model, and added the web search traffic information to this model to confirm whether the prediction model improved. In the last stage, we analyze the prediction models that are finally selected as optimal and confirm whether the influence of the keywords on the prediction of travel demand. Findings This study has developed a tourism demand forecasting model of Gangwon-do, a representative tourist destination in Korea, by expanding and applying web search traffic information to tourism demand forecasting. We compared the existing time series model with the benchmarking model and confirmed the superiority of the proposed model. In addition, this study also confirms that web search traffic information has a positive correlation with travel demand and precedes it by one or two months, thereby asserting its suitability as a prediction model. Furthermore, by deriving search keywords that have a significant effect on tourism demand forecast for each city, representative characteristics of each region can be selected.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.1
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• pp.15-25
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• 2013

The RIMGIS(River Information Management GIS) has been developed since 2000 for public service and practical applications of related works after the standardization of national river data such as the river facility register report, river survey map, attached map, and etc. The RIMGIS has been improved in order to respond proactively to change in the information environment. Recently, Smart River-based river information services and related data have become so large as to be overwhelming, making necessary improvements in managing big data. In this study a plan was suggested both to respond to these changes in the information environment and to provide a future Smart River-based river information service by understanding the current state of RIMGIS, improving RIMGIS itself, redesigning the database, developing distribution, and integrating river information systems. Therefore, primary and foreign key, which can distinguish attribute information and entity linkages, were redefined to increase the usability of RIMGIS. Database construction of attribute information and entity relationship diagram have been newly redefined to redesign linkages among tables from the perspective of a river standard database. In addition, this study was undertaken to expand the current supplier-oriented operating system to a demand-oriented operating system by establishing an efficient management of river-related information and a utilization system capable of adapting to the changes of a river management paradigm.

• Journal of Korea Water Resources Association
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• v.31 no.6
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• pp.779-793
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• 1998

In this study, for the purpose of water supply planning, we propose a sophisticated multi-period mixed integer programming model that can coordinate the behavior of multi-reservoir operation, minimizing unnecessary spill. It can simulate the system with operating rules which are self- generated by the optimization engine in the algorithm. It is an optimization model in structure, but it indeed simulates the coordinating behavior of multi-reservoir operation. It minimizes the water shortfalls in demand requirements, maintaining flood reserve volume, minimizing unnecessary spill, maximizing hydropower generation release, keeping water storage levels high for efficient hydroelectric turbine operation. This optimization model is a large scale mixed integer programming problem that consists of 3.920 integer variables and 68.658 by 132.384 node-arc incidence matrix for 28 years of data. In order to handle the enormous amount of data generated by a big mathematical model, the utilization of DBMS (data base management system)seems to be inevitable. It has been tested with the Han River multi-reservoir system in Korea, which consists of 2 large multipurpose dams and 3 hydroelectric dams. We demonstrated successfully that there is a good chance of saving substantial amount of water should it be put to use in real time with a good inflow forecasting system.

• Journal of Preventive Medicine and Public Health
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• v.25 no.3 s.39
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• pp.303-311
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• 1992

It is very important to estimate the future medical care expenditure, because medical care expenditure escalation is a big problem not only in the health industry but also in the Korean economy today. This study was designed to project the medical care expenditure in view of population age change. The data of this study were the population projection data based on National Census Data(1990) of the National Statistical Office and the Statistical Reports of the Korea Medical Insurance Corporation. The future medical care expenditure was eatimated by the regression model and the optional simulation model. The significant results are as follows : 1. The future medical care expenditure will be 3,963 billion Won in the year 2000, 4,483 billion Won in 2010, and 4,826 billion Won in 2020, based on the 1990 market price considering only the population age change. 2. The proportion of the total medical care expenditure in the elderly over 65 will be 10.4% in 2000, 13.5% in 2010, and 16.9% in 2020. 3. The future medical care expenditure will be 4,306 billion Won in the year 2000, 5,101 billion Won in 2010, and 5,699 billion Won in 2020 based on the 1990 market price considering the age structure change and the change of the case-cost estimated by the regression model. 4. When we consider the age-structure change and inflation compared with the preceding year, the future medical care expenditurein 2020 will be 21 trillion Won based on a 5% inflation rate, 42 trillion Won based on a 7.5% inflation rate, and 84 trillion Won based on a 10% inflation rate. Consideration of the aged(65 years old and over) will be essential to understand the acute increase of medical care expenditure due to changes in age structure of the population. Therefore, alternative policies and programs for the caring of the aged should be further studied.

• Korean Chemical Engineering Research
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• v.57 no.2
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• pp.274-282
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• 2019

In recent years, big data analysis has been expanded to include automatic control through reinforcement learning as well as prediction through modeling. Research on the utilization of image data is actively carried out in various industrial fields such as chemical, manufacturing, agriculture, and bio-industry. In this paper, we applied NASNet, which is an AutoML reinforced learning algorithm, to DeepU-Net neural network that modified U-Net to improve image semantic segmentation performance. We used BRATS2015 MRI data for performance verification. Simulation results show that DeepU-Net has more performance than the U-Net neural network. In order to improve the image segmentation performance, remove dropouts that are typically applied to neural networks, when the number of kernels and filters obtained through reinforcement learning in DeepU-Net was selected as a hyperparameter of neural network. The results show that the training accuracy is 0.5% and the verification accuracy is 0.3% better than DeepU-Net. The results of this study can be applied to various fields such as MRI brain imaging diagnosis, thermal imaging camera abnormality diagnosis, Nondestructive inspection diagnosis, chemical leakage monitoring, and monitoring forest fire through CCTV.