• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.770-778
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• 2023

Purpose: In order to reduce forklift industrial accidents, it is necessary to classify them into institutional, technical, and educational factors and conduct research on whether each factor affects disaster reduction. Method: Descriptive statistical analysis, validity analysis, reliability analysis, and multiple regression analysis were conducted using SPSS 18 program based on an offline questionnaire based on a 5-point Likert scale. Result: As a result of multiple regression analysis, it was found that institutional, technical, and educational factors, which are independent variables for disaster reduction, explain about 62.5% of the variance in disaster prevention, which is the dependent variable. The regression model verification was found to be statistically significant with F=118.775 and significance probability p<0.01. Conclusion: First, there is a need to prevent disasters by including electric forklifts weighing less than 3 tons in the inspection system. Second, there is a need to make it mandatory to install front and rear cameras and forklift line beams to prevent forklift collision disasters. Third, there is a need to conduct special training related to forklifts every year, and drivers and nearby workers need to be included in the special training for forklifts.

• 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.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.8 no.4
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• pp.319-327
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• 2010

A nuclear plant ESF ACS simulator was designed, built, and verified to perform experiment related to ESF ACS of nuclear power plants. The dimension of 3D CAD model was based on drawings of the main control room(MCR) of Yonggwang units 5 and 6. The CFD analysis was performed based on the measurement of the actual flow rate of ESF ACS. The air flowing in ACS was assumed to have $30^{\circ}C$ and uniform flow. The flow rate across the HEPA filter was estimated to be 1.83 m/s based on the MCR ACS flow rate of 12,986 CFM and HEPA filter area of 9 filters having effective area of $610{\times}610mm^2$ each. When MCR ACS was modeled, air flow blocking filter frames were considered for better simulation of the real ACS. In CFD analysis, the air flow rate in the lower part of the active carbon adsorber was simulated separately at higher than 7 m/s to reflect the measured value of 8 m/s. Through the CFD analyses of the ACSes of fuel building emergency ventilation system, emergency core cooling system equipment room ventilation cleanup system, it was confirmed that all three EFS ACSes can be simulated by controlling the flow rate of the simulator. After the CFD analysis, the simulator was built in nuclear grade and its reliability was verified through air flow distribution tests before it was used in main tests. The verification result showed that distribution of the internal flow was uniform except near the filter frames when medium filter was installed. The simulator was used in the tests to confirm the revised contents in Reg. Guide 1.52 (Rev. 3).

• Fire Science and Engineering
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• v.15 no.1
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• pp.23-33
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• 2001

The utility tunnels are the important facility as a mainstay of country because of the latest communication developments. However, the utilities tunnel is difficult to deal with in case of a fire accident. When a cable burns, the black smoke containing poisonous gas will be reduced. This black smoke goes into the tunnel, and makes it difficult to extinguish the fire. Therefore, when there was a fire in the utility tunnel, the central nerves of the country had been paralyzed, such as property damage, communication interruption, in addition to inconvenience for people. This paper is based on the fire occurred in the past, and reenacting the fire by making the real utilities tunnel model. The aim of this paper is the scientific analysis of the character image of the fire, and the verification of each fire protection system whether it works well after process of setting up a fire protection system in the utilities tunnel at a constant temperature. The fire experiment was equipped with the linear heat detector, the fire door, the connection water spray system and the ventilation system in the utilities tunnel. Fixed portion of an electric power supply cable was coated with a fire retardant coating, and a heating tube was covered with a fireproof. The result showed that the highest temperature was $932^{\circ}c$ and the linear heat detector was working at the constant temperature, and it pointed at the place of the fire on the receiving board, and Fixed portion of the electric power supply cable coated with the fire retardant coating did not work as the fireproof. The heating tube was covered with the fireproof about 30 minutes.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.4
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• pp.197-209
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• 2018

Recently, many start-up failures occur as the number of attempts to start a business increases in a social atmosphere that encourages start-up. In particular, young entrepreneurs have a lower survival rate than general entrepreneurs because young entrepreneurs are challenging just with a simple idea to overcome the difficulties of employment while lacking prior knowledge and experience of business. Therefore, the reason for the failure of start-up is lack of preparation for start-up and lack of entrepreneurship. The purpose of this study is to develop a measurement tool to build a basic framework for entrepreneurship development and start - up preparation activities for young people. To develop an entrepreneurship measurement tool, researchers developed a preliminary question through qualitative research methods such as literature research, focus group interview, and expert verification. After that, researchers surveyed 102 entrepreneurs using quantitative research method and to verify the construct validity of the measurement tool, the final entrepreneurship measurement tool was completed through exploratory factor analysis and confirmatory factor analysis. The entrepreneurship measurement tool developed through this research process consists of 7 components and 15 measurement items. First, in the step of 'confirming entrepreneurial intention', two items of 'self-analytic competence', three items of 'ability of establishing start-up philosophy'are contained. Second, in the step of 'drawing up a start-up model', two items are contained in each category such as, 'ability of eliciting entrepreneurial idea,' 'ability of analyzing idea validity,' 'competence of planning a venture start-up model'. Third, in the step of 'planning the venture start-up,' two items are contained in each category such as, 'business-plan presentation competency,' 'ability of implementing organizational system.'. The measurement tool of entrepreneurship is meaningful as it could help young entrepreneur find out their lacking competence in preparing their start-ups and strengthen necessary competences by measuring their own entrepreneurship. Rather in the entrepreneurship education, basic data that can diagnose the entrepreneurship of young entrepreneurs is provided.

• The Korean Journal of Health Service Management
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• v.2 no.1
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• pp.137-154
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• 2008

The increase of the supply of medical service and the increase of hospitals have intensified the competition of hospitals, and the advancement towards internationalization in the opening of medical industry has triggered the infinite competition of medical profession. In addition, the high expectation of customers and quality improvement in the medical care in accordance with the improvement of overall income, and the change of active role of medical consumers according to the popularization and the improvement of rights awareness reflect the customer needs and choice in the medical service. Customers wanted to receive the kind and pleasant service under the up-to-date medical service. Therefore, as a solution, hospital coordinators were emerged for the purpose of smooth treatment and customer satisfaction by generalizing all service of hospital. Accordingly, this thesis attempted to investigate the effect of hospital coordinator education curriculum on the education satisfaction and the quality of medical service. In order to solve the purpose of this study, I, author reviewed the existing literatures, established hypothesis, and verified hypothesis by using the variety of statistics techniques such as reliability, validity, frequency analysis, and regression analysis. The verification of hypothesis is as followings: First, among education training factors of hospital coordinators, the quality of instructor significantly affects the satisfaction of hospital coordinator education training. Second, among training factors of hospital coordinator, the attitude of trainee significantly affects the training satisfaction of hospital coordinator. Third, among education training factors of hospital coordinator, education course significantly affects the training satisfaction of hospital coordinator education. As the qualities of instructor are better equipped, the satisfaction of education becomes higher. It indicates that the education method of instructors is important as an index to represent the qualities of instructor such as the appropriateness of education method, preparation, passion, visual materials, the adequacy of education procession, and specialized knowledge, and it has important effect on the satisfaction of education. In order to enhance the satisfaction of hospital coordinator education, the creation of education environment, making trainee concentrate on the education, is required by appropriately allocating programs, arousing interest in education, based on the attitude of trainee, discussion, and preliminary programs, preparation, ahead of enforcement of education. Fourth, the satisfaction of hospital coordinator education training significantly affects the reliability among the qualities of medical service. Fifth, satisfaction of hospital coordinator education training significantly affects hospitality I kindness among the qualities of medical service. If the education satisfaction of trainee is high, it is effective in the practical application such as dealing with complaints, the duty performance for the patients, and so on in offering the medical service, related to reliability and furthermore, we can find the positive change in the attitude change of medical professions related to the reliability of hospital coordinator. In addition, in the process of offering medical services such as the kind explanation on the duty, rapid response to the customers inquiry, and tidy uniform, practical effect was verified. Sixth, the education training factor of hospital coordinator significantly affects the reliability among the quality of medical service. Seventh, the education training factors of hospital coordinator significantly affect hospitality/kindness. In the education of hospital coordinator, the methods to attract the interest of trainee by emphasizing reliability should be sought and for gaining the practical effect of hospital coordinator education, the sufficient preparation and investigation on the education curriculum should be prerequisite and under this condition, intensified discussion on the instructor and education course is needed. In the design of education course, more education hours and subjects should be allocated in the part of hospitality in order to improve the practical application of hospitality. Therefore, it is meaningful in a sense that this study newly approached the components of hospital coordinator education and the need to modify the quality components of medical service in accordance with the study subjects was raised. This study also finds its meaning in that it provides basic materials for the study of future hospital coordinator education by suggesting the system development model of hospital coordinator education through preliminary study of education training. In addition, this study is meaningful in the aspect that it suggested the direction of education training by showing how the hospital coordinator education training would applied to the hospital coordinator course of the Continuing Education Center at Pusan and Kyungnam National University to some extent. Since all investigation of this study was approached from the side of hospital coordinator, the thoughts of patients who are beneficiaries of medical service, and care givers cannot be identified. Therefore, the satisfaction of patients and care givers through the experience of medical service, which is the essential prerequisite of medical service, should be importantly considered and investigated. Accordingly, The study of comparing and analyzing the views of both patients and care givers should be carried out in the future.

• Journal of Korea Entertainment Industry Association
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• v.15 no.3
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• pp.231-241
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• 2021

This study intended to present strategies and implications for attracting new students and customized education to university officials through research on the participation of workers' academic aspirations in university education. Thus, variables were derived by analyzing prior data, and causal settings between variables and questionnaires were developed. Subject to the survey, 331 workers interested in participating in university education were collected through interpersonal interviews. The collected data were dataized, and reliability and feasibility verification and frequency analysis were conducted. Finally, we validate the fit of the structural equation model and the causal relationship for each concept. Therefore, the results of the validation show the following implications. First, university officials should be motivated by a mentor and mentee system with experienced people who have switched to a suitable vocational group through university education. It will also be necessary to develop and disseminate programs so that they can continue to develop themselves for the future. To this end, it will be necessary to help them understand their aptitude and strengths through consultation with experts. Second, university officials should strengthen public relations so that prospective students can know the cases and information of the job transformation of the admitted workers through recommendations. It will also be necessary to develop university education programs that can self-develop, accept various ideas through "public contest", and provide accurate information about university education to workers through re-processing. Third, university officials should provide workers with a program that allows them to catch two rabbits: job transformation and self-improvement through university education. In other words, it is necessary to stimulate the motivation of workers by providing various information such as visiting advanced overseas companies, obtaining various certificates, moving between departments of blue-collar and white-collar, and transfer opportunities. Fourth, university officials should actively promote university education programs related to this by participating in university education and receiving systematic education and the flow of social environment. Finally, university officials will need to consult and promote workers so that they can self-develop when they participate in college education, and they will have to figure out what they need for self-development through demand surveys and analysis.