• Journal of the Korea Society for Simulation
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• v.23 no.1
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• pp.21-31
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• 2014

In this article, data mining simulation is applied to find a proper approach and results of analysis for study of variables related to organization. Also, turnover intention and organizational commitment are used as target (dependent) variables in this simulation. Classification and regression tree (CART) with ensemble methods are used in this study for simulation. Human capital corporate panel data of Korea Research Institute for Vocation Education & Training (KRIVET) is used. The panel data is collected in 2005, 2007, and 2009. Organizational commitment variables are analyzed with combined measure variables which are created after investigation of reliability and single dimensionality for multiple-item measurement details. The results of this study are as follows. First, major determinants of turnover intention are trust, communication, and talent management-oriented trend. Second, the main determining factors for organizational commitment are trust, the number of years worked, innovation, communication. CART with ensemble methods has two ensemble CART methods which are CART with Bagging and CART with Arcing. Comparing two methods, CART with Arcing (Arc-x4) extracted scenarios with very high coefficients of determination. In this study, a scenario with maximum coefficient of determinant and minimum error is obtained and practical implications are presented. Using one of data mining methods, CART with ensemble method. Also, the limitation and future research are discussed.

• Journal of the Korean earth science society
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• v.41 no.2
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• pp.129-136
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• 2020

Drought is an environmental disaster typically defined as an unusual deficiency of water supply over an extended period. Satellite remote sensing provides an alternative approach to monitoring drought over large areas. In this study, we monitored drought patterns over about 30 years (1985-2015), using satellite imagery of Lake Soyang, Gangwondo, South Korea. Landsat images were classified using ISODATA, maximum likelihood analysis, and an artificial neural network to derive the lake area. In addition, the relationship between areas of Lake Soyang and the Standardized Precipitation Index (SPI) was analyzed. The results showed that the artificial neural network was a better method for determining the area of the lake. Based on the relationship between the SPI value and changes in area, the R² value was 0.52. This means that the area of the lake varied depending on SPI value. This study was able to detect and monitor drought conditions in the Lake Soyang area. The results of this study are used in the development of a regional drought monitoring program.

• Korean Journal of Clinical Laboratory Science
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• v.51 no.2
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• pp.125-133
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• 2019

A microscope is the fundamental research and diagnostic apparatus for clinical investigation of signaling transduction, morphological changes and physiological tracking of cells and intact tissues from patients in the biomedical laboratory science. Proper use, care and maintenance of microscope with comprehensive understanding in mechanism are fully requested for reliable image data and accurate interpretation for diagnosis in the clinical laboratory. The standard operating procedure (SOP) for light microscopes includes performance procedure, brief information of all mechanical parts of microscopes with systematic troubleshooting mechanism depending on the laboratory capacity. Maintenance program encompasses cleaning objective, ocular lenses and inner optics; replacement and calibration of light source; XY sample stage management; point spread function (PSF) measurement for confocal laser scanning microscope (CLSM); quality control (QC) program in fluorescent microscopy; and systematic troubleshooting. Laser safety is one of the concern for medical technologists engaged in CLSM laboratory. Laser safety guideline based on the laser classification and risk level, and advisory lab wear for CLSM users are also expatiated in this overview. Since acquired image data presents a wide range of information at the moment of acquisition, well-maintained microscopes with proper microscopic maintenance program are impulsive for its interpretation and diagnosis in the clinical laboratory.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.5
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• pp.131-138
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• 2018

In this study, we investigated the trend of technological development in major countries related to the propulsion equipment of railway vehicles. The propulsion system is the main equipment of electric vehicles. A lot of time and investment are required in order to ensure the development of technology. Therefore, developed countries have maximized their effort to develop technologies with safety, reliability, and convenience of maintenance. They have also done their utmost to prevent technology transfer to other countries after the development of new technologies. For example, Toshiba of Japan developed a new 3,300V/1,500 A class IGBT power device, but was reluctant to export it to foreign countries in order to protect this technology. In this study, we analyzed the patents applied for related to propulsion control systems and presented the direction of development during the technical development of these systems. The patent analysis of the core technologies was conducted using the Thomson Innovation DB. We examined the number of patents applied for by country, year and major applicant. As a result of the analysis, it was found that the proportion of patent applications per country was in the order of China, 48%, Europe 16.6%, and the United States 14.9%. The patent situation of the top 10 principal applicants revealed that (the top three were?) ABB 14%, GE 13%, and CRRC 12%. At the same time, we also conducted a qualitative analysis of the level of technical development by evaluating such factors as the influence index, quotation, market securing power and citation. Based on the result of the patent analysis, we presented the direction of technical development of the propulsion control equipment of railway vehicles. Based on the analysis results, it was found that domestic applicants considerably reduced their efforts to protect their patents from foreign companies. Nowadays, most of the electric motors used in Korea are induction motors. In advanced countries, permanent magnet electric motors are employed in new railway lines. Therefore, intensive investment is needed in new developments.

• Journal of Venture Innovation
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• v.4 no.2
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• pp.57-75
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• 2021

KHNP's shared growth activities are based on such public good. Reflecting the characteristics of a comprehensive energy company, a high-tech plant company, and a leading company for shared growth, it presents strategies to link performance indicators with its partners and implements various measures. Key tasks include maintaining the nuclear power plant ecosystem, improving management conditions for partner companies, strengthening future capabilities of the nuclear power plant industry, and supporting a virtuous cycle of regional development. This is made by reflecting the specificity of nuclear power generation as much as possible, and is designed to reflect the spirit of shared growth through win-win and cooperation in order to solve the challenges of the times while considering the characteristics as much as possible as possible. KHNP's shared growth activities can be said to be the practice of the spirit of the times(Zeitgeist). The spirit of the times given to us now is that companies should strive for sustainable growth as social air. KHNP has been striving to establish a creative and leading shared growth ecosystem. In particular, considering the positions of partners, it has been promoting continuous system improvement to establish a fair trade culture and deregulation. In addition, it has continuously discovered and implemented new customized support projects that are effective for partner companies and local communities. To this end, efforts have been made for shared growth through organic collaboration with partners and stakeholders. As detailed tasks, it also presents fostering new markets and new industries, maintaining supply chains, and emergency support for COVID-19 to maintain the nuclear power plant ecosystem. This reflects the social public good after the recent COVID-19 incident. In order to improve the management conditions of partner companies, productivity improvement, human resources enhancement, and customized funding are being implemented as detailed tasks. This is a plan to practice win-win growth with partner companies emphasized by corporate social responsibility (CSR) and ISO 26000 while being faithful to the main job. Until now, ESG management has focused on the environmental field to cope with the catastrophe of climate change. According to KHNP is presenting a public enterprise-type model in the environmental field. In order to strengthen the future capabilities of the nuclear power plant industry as a state-of-the-art energy company, it has set tasks to attract investment from partner companies, localization and new technologies R&D, and commercialization of innovative technologies. This is an effort to develop advanced nuclear power plant technology as a concrete practical measure of eco-friendly development. Meanwhile, the EU is preparing a social taxonomy to focus on the social sector, another important axis in ESG management, following the Green Taxonomy, a classification system in the environmental sector. KHNP includes enhancing local vitality, increasing income for the underprivileged, and overcoming the COVID-19 crisis as part of its shared growth activities, which is a representative social taxonomy field. The draft social taxonomy being promoted by the EU was announced in July, and the contents promoted by KHNP are consistent with this, leading the practice of social taxonomy

• Journal of Korean Home Economics Education Association
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• v.26 no.4
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• pp.129-146
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• 2014

This study is a fundamental research in the field of home economics education to enforce vocational competencies. It was carried out in the purpose of examining the recent economical and social environmental changes and its management system related to the vocational training in the field of home economics education. It seeks change in direction in relation to the National Competency Standard(NCS) based on revisions in the educational system. The method of study was mostly through reference and data analysis, professional advisory and public hearing. The main research results are as follows. First, the main environmental change factors in relation to vocational training have been integrated to the changes in; population structure, gender related economic activities, generation composition, communications technology, and innovation of living technique. These change factors are forecasting innovations in related industries, lifestyle changes, demand for manpower and changes in capabilities required for each specific profession. Second, according to the analysis of current home economics education training, vocational home educations high school accounts for 9.4% of the total number of specialized high schools, where 8 standard departments are specialized in and characterized into 137 different department names. Despite differences among departments, overall employment rate of graduates were measured 44.7%, which rates above the entrance rate of 41.9%. These numbers show great change since 2010(overall employment rate 16.9%, entrance rate 75.2%), a meaningful outcome resulting from changes in policy from the previous employment-centered education system. Third, NCS based on high school vocational home economics education system revision and investigations in change of direction in vocational home economics, this study attempts to provide background for revision from the development of NCS. It also provides proposals for restructuring division of current classification and departments of home economics education, and propositions for further future research.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Information Systems Review
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• v.19 no.2
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• pp.1-19
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• 2017

Original scripts of e-learning lectures for the CEOs of corporation S were analyzed using topic analysis, which is a text mining method. Twenty-two topics were extracted based on the keywords chosen from five-year records that ranged from 2011 to 2015. Research analysis was then conducted on various issues. Promising topics were selected through evaluation and element analysis of the members of each topic. In management and economics, members demonstrated high satisfaction and interest toward topics in marketing strategy, human resource management, and communication. Philosophy, history of war, and history demonstrated high interest and satisfaction in the field of humanities, whereas mind health showed high interest and satisfaction in the field of in lifestyle. Studies were also conducted to identify topics on the proportion of content, but these studies failed to increase member satisfaction. In the field of IT, educational content responds sensitively to change of the times, but it may not increase the interest and satisfaction of members. The present study found that content production for CEOs should draw out deep implications for value innovation through technology application instead of simply ending the technical aspect of information delivery. Previous studies classified contents superficially based on the name of content program when analyzing the status of content operation. However, text mining can derive deep content and subject classification based on the contents of unstructured data script. This approach can examine current shortages and necessary fields if the service contents of the themes are displayed by year. This study was based on data obtained from influential e-learning companies in Korea. Obtaining practical results was difficult because data were not acquired from portal sites or social networking service. The content of e-learning trends of CEOs were analyzed. Data analysis was also conducted on the intellectual interests of CEOs in each field.

• Management & Information Systems Review
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• v.39 no.1
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• pp.93-114
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• 2020

Platform is considered as an alternative strategy to the traditional linear pipeline based business. Moreover, in the 4th industrial revolution period, efficiency driven pipeline business model needs to be changed to platform business. We have such success stories about platform as Apple, Google, Amazon, Uber, and so on. However, for those smaller corporations, it is not easy to find out the transformation strategy. The essence of platform business is to leverage network effect in management. Thus platform based management can be rephrased as network management across the business functions. Research on platform business is popular and related to diverse facets. But few scholars cover what the research trend of the domain is. The main purpose of this paper is to identify the research trend on platform business in Korea. To do that we first propose the analytical model for platform architecture whose components are consumers, suppliers, artifacts, and IT platform system. We conjecture that mapping of the research work on platform to the components of the model will make us understand the hidden domain of platform research. We propose three hypotheses regarding the characteristics of research and one proposition for the transitional path from pipeline to platform business model. The mapping is based on the research articles filtered from the Korea Citation Index, using keyword search. Research papers are searched through the keywords provided by authors using the word of "platform". The filtered articles are summarized in terms of the attributes such as major component of platform considered, platform type, main purpose of the research, and research method. Using the filtered data, we test the hypotheses in exploratory ways. The contribution of our research is as follows: First, based on the findings, scholars can find the areas of research on the domain: areas where research has been matured and territory where future research is actively sought. Second, the proposition provided can give business practitioners the guideline for changing their strategy from pipeline to platform oriented. This research needs to be considered as exploratory not inferential since subjective judgments are involved in data collection, classification, and interpretation of research articles.