• The Korean Journal of Health Service Management
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• v.13 no.4
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• pp.33-44
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• 2019

Objectives: This study aimed to analyze the papers on nursing in the KJHSM (Korean Journal of Health Service Management) (2007-2018), to identify the research trends and to help the future development of nursing research. Methods: The data collection was carried out from September 1, 2019 to September 30, 2019. The 78 copies of the original text were provided by the KSHSM website, DBpia, and NDSL (National Digital Science Library) electronic database. Results: Forty-seven studies had a non-experimental design, with most having a descriptive research design (89.3%). The most common participants were nurses (55.7%) and nursing college students (26.1%). A questionnaire was the most commonly used research tools (96.2%) and data collection methods (95.0%). The major keywords were the terms included in the environmental domain among the meta-paradigms of nursing (43.6%). Conclusions: In order to expand the quantity and quality of nursing science in the KSHSM, efforts are needed to improve the quality of research participants, research tools, and sampling methods.

• Journal of Korean Society on Water Environment
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• v.35 no.4
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• pp.370-378
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• 2019

In the recent years, various studies have presented stable and economic methods for increased regulations and compliance in sewage treatment plants. In some sewage treatment plants, the effluent concentration exceeded the regulations, or the effluent concentration was manipulated. This indicates that the process is currently inefficient to operate and control sewage treatment plants. The operation and control method of sewage treatment plant is mathematically dealing with a physical and chemical mechanism for the anticipated situation during operation. In addition, there are some limitations, such as situations that are different from the actual sewage treatment plant. Therefore, it is necessary to find a more stable and economical way to enhance the operational and control method. AI (Artificial Intelligence) technology is selected among various methods. There are very few cases of applying and utilizing AI technology in domestic sewage treatment plants. In addition, it failed to define specific definitions of applying AI technologies. The purpose of this study is to present the application of AI technology to domestic sewage treatment plants by comparing and analyzing various cases. This study presented the AI technology algorithm system, verification method, data collection, energy and operating costs as methods of applying AI technology.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1301-1311
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• 2017

Manufacturing big data systems have supported decision making that can improve preemptive manufacturing activities through collection, storage, management, and predictive analysis of related 4M data in pre-manufacturing processes. Effective visualization of data is crucial for efficient management and operation of data in these systems. This paper presents visualization techniques that can be used to effectively show data collection, analysis, and prediction results in the manufacturing big data systems. Through the visualization technique presented in this paper, we have confirmed that it was not only easy to identify the problems that occurred at the manufacturing site, but also it was very useful to reply to these problems.

• Journal of Digital Convergence
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• v.16 no.10
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• pp.445-452
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• 2018

In a world where everything in life is being digitized, the amount of data is increasing exponentially. These data are processed into new data through collection and analysis. New data is used for a variety of purposes in hospitals, finance, and businesses. However, since existing data contains sensitive information of individuals, there is a fear of personal privacy exposure during collection and analysis. As a solution, there is privacy-preserving data mining (PPDM) technology. PPDM is a method of extracting useful information from data while preserving privacy. In this paper, we investigate PPDM and analyze various measures for evaluating the privacy and utility of data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.6
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• pp.81-91
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• 2008

In this study, data collection delay time generated in bus information system is analysed and improvement on system reliability by minimizing the delay time is suggested. To minimize the data collection delay time (call setup time), factors on data collection phase are analyzed. Each connecting time that it occurs from wireless communication during data collection phase, is selected as a main effective variable and a model for selecting an optimum communication point to minimize the effect of data delay time by each connecting time is suggested. In this model, minimization of the point between the time carrying out wireless communication and vehicle moving time, is calculated and the difference between the bus arrival time and information delivered time to the passenger is reduced. The test results for the proposed model in BIS using a CDMA (Code Division Multiple Access) communication show that delay time in real system operation has been improved. The minimum data collection delay time based on optimal communication position leads to the better reliability for Bus Information System. This study can be applied to the selection of optimal communication position and detection position instead of empirical methods.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.241-250
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• 2008

With the ever-growing amount of traffic, there is an increasing need for good quality travel time information. Various existing outlier filtering and missing data imputation algorithms using AVI data for interrupted and uninterrupted traffic flow have been proposed. This paper is devoted to development of an outlier filtering and missing data imputation algorithm by using Toll Collection System (TCS) data. TCS travel time data collected from August to September 2007 were employed. Travel time data from TCS are made out of records of every passing vehicle; these data have potential for providing real-time travel time information. However, the authors found that as the distance between entry tollgates and exit tollgates increases, the variance of travel time also increases. Also, time gaps appeared in the case of long distances between tollgates. Finally, the authors propose a new method for making representative values after removal of abnormal and "noise" data and after analyzing existing methods. The proposed algorithm is effective.

• Journal of Fisheries and Marine Sciences Education
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• v.26 no.1
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• pp.156-165
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• 2014

The purpose of this study was to find research trends of smart learning. For this, we identified the research's characteristics such as the subject or keyword of research, method, data collection, and statistical analysis method. The 2,865 articles published from 1995 to 2013 were gathered from five Korean academic journals related to smart learning. Among them, research keyword, areas, research method, data collection method, and statistical analysis method were analyzed on 596 papers. The findings of this study were as follows: (a) Smart learning papers such keyword likes u-learning, m-learning, and smart-learning were emerging after 2006. Smart learning papers with ICT related topics were highly increased after 2000, but they were decreased after 2006. Smart learning papers with e-learning related keywords were steadily increased after 2000 through 2013. (b) The research field of deign had the highest portion in smart learning research, but managing had the lowest portion. (c) Development was mainly used as a research method. Both questionnaire and experiment were mainly used for collecting data methods. T-test and frequency analysis were mainly used as statistical analysis methods.

• Korean Journal of Clinical Pharmacy
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• v.30 no.2
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• pp.73-80
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• 2020

Objective: The Australian Pharmaceutical Benefits Scheme (PBS) is a national drug subsidy program. Given the similarity and comprehensiveness of the Australian PBS and the Korean National Health Insurance (NHI) data, these data are increasingly used for pharmacoepidemiological investigations, as well as international comparative studies. This study aims to introduce the various sources of publicly available PBS data and provide a practical guide to researchers conducting drug utilization studies. Methods: We searched literature and websites to detail and compare the collection, structure, components, and characteristics of each PBS data format. We identified different characteristics of the PBS data from the Korean NHI claims data which are mainly owing to their unique co-payment policies and data collection processes. In addition, the utilization and expenditure of atorvastatin, a widely used treatment for hyperlipidemia, were analyzed using two different sources of PBS data and the different results were interpreted. Results: There exist differences in when data were collected or non-subsidized uses of medicine were included among sources of PBS data. Additionally, two countries have different cost sharing methods inmedicine subsidy scheme; co-payment in Australia and co-insurance in Korea. Therefore, it should be noted that prescriptions under co-payment are not included in some data sources in Australia. Conclusion: Despite several analytical challenges, open access and easy data management are the strengths of the PBS data sources. A detailed knowledge of the PBS data can ensure robust methodology and interpretation of pharmacoepidemiological investigations or international comparative studies.

• Journal of the Korea Society for Simulation
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• v.33 no.2
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• pp.1-11
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• 2024

A cyber-physical system is a technology that connects the physical systems of a manufacturing environment with a cyber space to enable simulation. One of the major challenges in this technology is the seamless communication between these two environments. In complex manufacturing processes, it is crucial to adapt to various protocols of manufacturing equipment and ensure the transmission and reception of a large volume of data without delays or errors. In this study, we propose a method for constructing agent models for real-time simulation-capable cyberphysical systems. To achieve this, we design data collection units as independent agent models and effectively integrate them with existing simulation tools to develop the overall system architecture. To validate the proposed structure and ensure reliability, we conducted empirical testing by integrating various equipment from a real-world smart microfactory system to assess the data collection capabilities. The experiments involved testing data delay and data gaps related to data collection cycles. As a result, the proposed approach demonstrates flexibility by enabling the application of various internal data collection methods and accommodating different data formats and communication protocols for various equipment with relatively low communication delays. Consequently, it is expected that this approach will promote innovation in the manufacturing industry, enhance production line efficiency, and contribute to cost savings in maintenance.

• Journal of Korean Library and Information Science Society
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• v.43 no.3
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• pp.457-479
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• 2012

This paper strives to illustrate the selection processes in public libraries. It specifically attempts to survey the budget allocation, collection development policy, usage of selection criteria, and priority of selection decision in collection development units in public libraries. Staff structure, committee activities, methods of selection, usage of selection tools and librarians' recognitions about selection process are also investigated. Data are drawn from a survey with 315 public libraries in the country. Specific statistics to be analyzed via literature, although not detailed in nature, are scrutinized as well. As a conclusion, the paper discusses such an issue as current situation in selection of materials public libraries and possible impetus toward a better collection development process.