• The Journal of Industrial Distribution & Business
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• v.11 no.12
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• pp.7-15
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• 2020

Purpose: This study aims to explore the feasibility of expanding complex wards to provide efficient hospital management and high-quality medical services to local residents of Gangneung Medical Center (GMC). Research Design, Data and Methodology: There are four research designs to achieve the research objectives. We analyzed Big Data for 3 months on Social Network Services (SNS). A questionnaire survey conducted on 219 patients visiting the GMC. Surveys of 20 employees of the GMC applied. The feasibility to expand the GMC ward measured through Focus Group Interview by 12 internal and external experts. Data analysis methods derived from various surveys applied with data mining technique, frequency analysis, and Importance-Performance Analysis methods, and IBM SPSS statistical package program applied for data processing. Results: In the result of the big data analysis, the GMC's recognition on SNS is high. 95.9% of the residents and 100.0% of the employees required the need for the complex ward extension. In the analysis of expert opinion, in the future functions of GMC, specialized care (△3.3) and public medicine (△1.4) increased significantly. Conclusion: GMC's complex ward extension is an urgent and indispensable project to provide efficient hospital management and service quality.

• New & Renewable Energy
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• v.19 no.4
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• pp.98-107
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• 2023

A study was conducted to analyze data from 1981 to 2020 for understanding the impact of climate on solar energy generation. A significant increase of 104.6 kWhm^-2 was observed in the annual cumulative solar radiation over this period. Notably, the distribution of solar radiation shifted, with the solar radiation in Busan rising from the seventh place in 1981 to the second place in 2020 in South Korea. This study also examined the correlation between long-term temperature trends and solar radiation. Areas with the highest solar radiation in 2020, such as Busan, Gwangju, Daegu, and Jinju, exhibited strong positive correlations, suggesting that increased solar radiation contributed to higher temperatures. Conversely, regions like Seosan and Mokpo showed lower temperature increases due to factors such as reduced cloud cover. To evaluate the impact on solar energy production, simulations were conducted using climate data from both years. The results revealed that relying solely on historical data for solar energy predictions could lead to overestimations in some areas, including Seosan or Jinju, and underestimations in others such as Busan. Hence, considering long-term climate variability is vital for accurate solar energy forecasting and ensuring the economic feasibility of solar projects.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.287-296
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• 2024

Artificial intelligence (AI), the Internet of Things (IoT), and Big Data are playing important roles in improving or upgrading energy efficiency. Furthermore, their roles in energy efficiency are expected to become more and more essential. This study conducted a bibliometric comparative analysis on the features in the articles on the AI, the IoT, and the Big Data in energy efficiency by using the Web of Science database and compared the features in their trends in article publications, citations, countries, research areas, journals, and funding agencies from 2012 to 2022. This study attempted to make significant contributions by shedding new light on the following features. Among the AI, the IoT, and the Big Data in energy efficiency, the most articles were published and the most article citations were received in the AI in energy efficiency. China was found out to be the most leading country. Engineering and computer science were revealed to be the first research area. IEEE Access and IEEE Internet of Things were ranked with first journal. National Natural Science Foundation of China was the first research funding agency concerning the articles published in the AI, the IoT, and the Big Data in energy efficiency from 2012 to 2022.

• Ocean and Polar Research
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• v.42 no.2
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• pp.115-131
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• 2020

The effective range of surface current data observed by high-frequency radar (HFR) operated in the northern coastal area of Jeju Island by Korea Institute of Ocean Science and Technology was estimated and the distribution and variability of the M₂ tidal current of the Jeju Strait was analyzed. To evaluate the HFR data, the M₂ tidal current corrected from 25 hours current data observed by the Korea Hydrographic and Oceanographic Agency (KHOA) was compared with the M₂ tidal current in the Jeju Strait analyzed from the surface currents of HFR. The reliability of HFR data was confirmed by analyzing the characteristics of the tide components of these two data sets, and the effective range of HFR data was estimated through temporal and spatial analysis. The observation periods of HFR used in the analysis were from 2012 to 2014, and it was confirmed that there is a difference in the effective range of HFR data according to the observation time. During the analysis periods, the difference between the M₂ current ellipses from the data of KHOA and the HFR was greater in the eastern than in the western part of the Jeju Strait, and represented a high reliability in the western and central parts of the Jeju Strait. The tidal current of the Jeju Strait analyzed using the HFR data revealed a seasonal variability a relatively weak in summer and a strong in winter, about a 17% fluctuations between the summer and winter based on the length of the semi-major axis of tidal ellipse. Appraisals and results of regarding the characteristics and seasonal variability of the M₂ tidal current in the Jeju Strait using HFR data have not been previously reported, so the results of this study are considered meaningful.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.2
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• pp.67-78
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• 2006

Local governments began to construct geographic information system to improve government productivity and performance. In support, central government organized a national commission for GIS. The master plan by NGIS has been the base for local government to participate in the construction of GIS at the local level in the under ground facilities management including water and sewers. The challenge faced by sewer facility managers includes controlling 'data accuracy'. The input for sewer data handling for efficient performance in local government requires accurate data. However data manipulation to get the 'good quality' data can be burdensome. Thus, the aim of this research is to provide the appropriate tool to guarantee the high quality of digital data in sewer facility management. It is helpful to pass the data examination by government as well as to insure confidence of decision and data analysis works in local government. In this research, error types of sewer data were classified and pointed the limitation of traditional examination methods. Thus this research suggested more improved method for finding and correcting errors in data input using sewer volume analysis and prediction model as immigrating sewer facility management work to Geographic Information System.

• Nuclear Engineering and Technology
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• v.39 no.2
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• pp.129-132
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• 2007

It is generally known that software reliability growth models such as the Jelinski-Moranda model and the Goel-Okumoto's non-homogeneous Poisson process (NHPP) model cannot be applied to safety-critical software due to a lack of software failure data. In this paper, by applying two of the most widely known software reliability growth models to sample software failure data, we demonstrate the possibility of using the software reliability growth models to prove the high reliability of safety-critical software. The high sensitivity of a piece of software's reliability to software failure data, as well as a lack of sufficient software failure data, is also identified as a possible limitation when applying the software reliability growth models to safety-critical software.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.08a
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• pp.77-77
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• 2012

As interest has increased in the interaction between low-temperature plasmas and materials, the role of modeling and simulation of processing in plasma has become important in understanding the effects of charged particles and radicals in plasma applications. Thus in this presentation, we present the theoretical and experimental studies of electron impact cross section for plasma processing gas, such as plasma etching and deposition processes. Also, here the work conducted at the Data Center for Plasma Properties (DCPP) over last 7 years on the systematic synthesis and assessment of fundamental knowledge on low-energy electron interactions with plasma processing gases is briefly summarized and discussed.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.100-103
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• 2008

Recently Development of construction system that subjective operators share and control information efficiently based on the three-dimensional space and design information throughout life cycle of construction project is progressing dynamically. In case of civil structures which are infrastructure, Demand for structure of complex system which has multi-functions such as super and smart bridges and express rails is increasing and system development which computerizes and integrates process of structure design is in need. For that, research about link way between three dimensional modeling data and structure analysis programs should be preceded. In this research, therefore, research about interface design between three dimensional virtual modeling data to automate efficient civil-structure-design and nonlinear finite element analysis program which is made up of reinforced concrete material model that express material's character clearly.

• Culinary science and hospitality research
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• v.22 no.1
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• pp.126-134
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• 2016

This study examines effect in customer satisfaction of the emotional intelligence of members at service providing department in the hotel; A case of five star hotels in Dajeon Research hypotheses were developed based on previous literature, and data were collected from 350 employees working at the hotel restaurant service business located in Daejeon, ROK, were investigated herein The collected data were then analysed using frequence reliability For this research analysis, a self-recording method was used where and examiner explains the survey and respondents writhen down their answers to survey questions Statistical processing in this study was done through data cidubg and data cleaning then with the SPSS(Statistical Package for Social Science)v. 18.0. This result the emotional intelligence of service-providing employees at food service department of hotel was found to have a positive effect on customer satisfaction via understanding of others and emotional control. And the understanding of oneself, understanding of others and emotional control in emotional intelligence had a positive effect on job satisfaction. Emotional control, and emotioal use were found to affect organizational commitment positively.

• Asian Journal for Public Opinion Research
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• v.5 no.4
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• pp.266-284
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• 2018

This paper adopts the big data research method, and draws 491 data from the Tianya Forum about the Simultaneous Renting and Purchasing policy of Guangzhou. The qualitative analysis software Nvivo11 is used to cluster the main questions about the Simultaneous Renting and Purchasing policy in the forum. The 36 high-frequency word frequencies are obtained through text clustering. Through rooted theory analysis, the main driving factors for summarizing people's doubts are 9 main categories, 3 core categories, and the model of driving factors for online forums is established. The study finds that resource factors are the most key factor, economic factors are the important drivers, and policy guiding factors are sub-important drivers.