• Archives of design research
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• v.20 no.3 s.71
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• pp.299-314
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• 2007

For the past 20 years, the growth and development of university-design-educational institutes contributed to the industrial development of our country. Due to the technological fluctuation and changes in the industrial structure in the latter half of the 20th century, the enterprise is demanding professionally-oriented design manpower. The principle which appears from instances of the advanced nations is to accommodate the demands in social changes and apply them to educational design programs. In order to respond promptly to the industrial demand especially, the advanced nations adopted "multidisciplinary design education programs" to lead innovation in the area of design globally. The objective of the research consequently is to suggest an educational system and a program through which the designer can be educated to obtain complex knowledge and the technique demanded by the industry and enterprise. Nowadays in order to adapt to a new business environment, designers specially should have both the knowledge and techniques in engineering and business administration. We suggest that the IPDI, a multidisciplinary design educational system and program is made up of the coordinated operation of major classes, on-the-job training connection, educational system for research base creation, renovation design development program for the application and the synthesis of alternative proposals about the training facility joint ownership by connecting with the education of design, business administration and engineering.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.4
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• pp.231-244
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• 2020

With the rapid progress of the 4th industrial revolution, technical human capitals are considered to be the core competing factors of the enterprise. Technical manpower training of the 4th industrial revolution through technical education has become an essential task of venture start-ups. The opening of technical training courses and the education support system of companies are increasing, but the shortage of technical manpower is getting worse. This study was conducted to analyze the factors affecting participation intention of the 4th industrial revolution technology education. The research model was established based on the model of goal-directed behavior. For the analysis, 250 valid questionnaire data were used to test with a structural equation model. The results of the study are as follows. First, attitude had a positive effect on the intention to participate in education. Second, subjective norms had a positive effect on the intention to participate in education. Third, the perceived behavioral control has not been tested for a significant influence on educational participation intention. Fourth, positive and negative anticipated emotions had a significant effect on educational intention. The impact of significant variables were found in the order of positive anticipated emotions, attitudes, negative anticipated emotions, subjective norms. On the other hand, as a result of testing the mediating effect of desires, it was found that desires plays a mediating role between attitude, subjective norm, perceived behavioral control, positive anticipated emotions, negative anticipated emotions, and participation intention. In particular, the causal relationship between perceived behavioral control and intention to participate in education was not significant, but perceived behavioral control had a significant effect(full mediation) on participation intention through desires. Based on the results of this study, the following implication were suggested. First, the model of goal-directed behavior(MGB) was applied to the technical education field. Second, the direct relationship between antecedent variables and behavioral intentions was simultaneously tested. Third, unlike the existing education-related research, the factors affecting participation in education were analyzed. Fourth, the importance of desires for education were suggested.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.12
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• pp.569-581
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• 2016

This experimental study employs a pretest -posttest method concerning the integrated therapy of neurofeedback training, brain gymnastics, and oriental herbal tea effects on seniors living alone. The purpose of the study is to identify effects on brain functions and quality of life. The study participants included 23 seniors living alone (male 10, female 13), ranging in age from 65~90. The experiment lasted 8 weeks, from December 22, 2014, to February 28, 2015. The neurofeedback training utilized the 2 Channel neurofeedback system by Braintech Corporation and was conducted a total of 16 times over 8 weeks, having two sessions per week lasting for 30 minutes focusing on relaxation, concentration and memory. Brain gymnastics, developed by the Korean Science Institute of Psychiatry, ran for 30 minutes, twice a week for a total of 16 sessions administered over 8 weeks. Participants were required to drink 3 cups of oriental herbal tea developed according to Donguibogam for 8 weeks. The results of applying integrated therapy found positive effects on brain function resulting from changes in level of tension and anti-stress quotient. Quality of life, daily life basic measurements, and depression symptoms were significantly influenced by decreases in blood pressure and blood sugar. Results of this study find the integrated therapy of neurofeedback training, brain gymnastics, and oriental herbal tea can significantly enhance brain functions and quality of life within seniors living alone. Therefore integrated therapy involving neurofeedback, brain gymnastics, and oriental herbal tea is a necessary intervention to improve the quality of life of seniors living alone, and will improve the quality of life through healing both mind and body in a more practical and systematical manner.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• Korean Security Journal
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• no.25
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• pp.109-130
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• 2010

As many countries in the world including the Republic of Korea have used all their national resources in the accelerating economic information warfare, illegal leakage of industrial technologies and information has increased rapidly. The costs required for damage prevention from 2007 to 2008 are estimated at approximately KRW 180 trillion which is expected to increase gradually in future. Because the tricks of leaking key technologies are also getting increasingly systematized, sophisticated and bigger, e.g., simple theft at the individual level or the conspiracy of all the staff taking part in the research activities, we should pay special attention to technology security in addition to technology development. While there are several factors affecting such the brain drain, they usually include personal, social, political and cultural factors, for instance, very heavy educational expenditure of children compared to relatively low pay, the speedy labor market circulation for experienced personnel, or political restrictions on researches. In this context, as part of efforts made to prevent the outflow of core personnel, individual companies and research institutes should establish systematically appropriate core personnel management systems for their own organizational or business goals and principles which are intented to ensure to give better treatment and benefit to core personnel and to exercise closer supervision over them. Furthermore, the conventional personnel management system should be radically and flexibly improved in the manner of encouraging the core personnel returning to the organization to combine their external experiences with practices, instead of penalizing them. At the same time, it is necessary to train and educate core personnel through mutual collaboration and in-house training facilities as well as external academic programs operated jointly at the level of the industry. Finally, as the issues concerning the outflow of core personnel are not just problems of relevant companies and other advanced countries have devoted their best efforts to secure their own key technologies at the national level, it is urgent for the industry and the competent authorities to cooperate closely.

• Industry Promotion Research
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• v.3 no.2
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• pp.9-20
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• 2018

The purpose of this study is to examine the influence of orgaizational capability(Organizational management capability, marketing capability, relationship formation capability, governance capability) of management perceived by the members of the social enterprise on performance of organization(both economic and social). For such goal, empirical analysis of research hypothesis 1 (organizational competence and economic performance) and research hypothesis 2 (organizational competence and social performance) was conducted using the statistical program of IBM SPSS 24.0 for the final 195 candidates who work in social enterprise. Both hypothesis 1 and 2 were adopted, as the result of the hypothesis 1 and 2, H1-1 H2-1 (organizational management competence and economic performance and social performance), H1-2 H2-2 (marketing competence and economic performance social performance), H1-3 H2-3 (relationship formation competence, economic performance, and social performance), and H1-4 H2-4 (governance capability and economic performance and social performance) all have a significant effect on economic and social performance. Therefore, the importance of organizational capability of management, executive body of social enterprises, was emphasized for the success and strive of social enterprise and sustainable management. Therefore, it is necessary to establish an education and training system to strategically develop and strengthen the organizational capability of the management, and provide a systematic and long-termed education system and training.

• Convergence Security Journal
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• v.14 no.1
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• pp.3-10
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• 2014

Private security organizations are complementary to the national safety of life and property of individuals as a social role to play in maintaining peace and order. Pursuit of profit is to the public practice according to the logic of capitalist markets and customers seeking to protect the lives and property. However, the legal and institutional constraints of private security is being requirements inhibited by the development. Crime prevention as a private security role that the private companies, which will pursue the public interest. After all, the expansion of the private security crime is results in an increase in unit. The current level of private security in the 1970s remain, and the constraints is being under goodwill and expertise outside of the training system on the market. Variety of crimes, including cyber crime increases and considering the reality of the constraints on private security requirements are able to improve or supplement shall be realistic. In particular, the legal, regulatory and institutional factors must be improved, with goodwill, and for the creation of new industrial policy as a complement to the public interest should be also provided. The private security law interests through integration of private security guards should be guaranteed, and the term of the theorem, sales activities, ensuring the training of professional staff with professional qualifications system is to be settled. As a private security guard industry growth and development can be based on this composition.

• Journal of Korea Water Resources Association
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• v.55 no.8
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• pp.565-575
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• 2022

Recently, in the field of water resource engineering, interest in predicting time series water levels and flow rates using deep learning technology that has rapidly developed along with the Fourth Industrial Revolution is increasing. In addition, although water-level and flow-rate prediction have been performed using the Long Short-Term Memory (LSTM) model and Gated Recurrent Unit (GRU) model that can predict time-series data, the accuracy of flow-rate prediction in rivers with rapid temporal fluctuations was predicted to be very low compared to that of water-level prediction. In this study, the Paldang Bridge Station of the Han River, which has a large flow-rate fluctuation and little influence from tidal waves in the estuary, was selected. In addition, time-series data with large flow fluctuations were selected to collect water-level and flow-rate data for 2 years and 7 months, which are relatively short in data length, to be used as training and prediction data for the LSTM and GRU models. When learning time-series water levels with very high time fluctuation in two models, the predicted water-level results in both models secured appropriate accuracy compared to observation water levels, but when training rapidly temporal fluctuation flow rates directly in two models, the predicted flow rates deteriorated significantly. Therefore, in this study, in order to accurately predict the rapidly changing flow rate, the water-level data predicted by the two models could be used as input data for the rating curve to significantly improve the prediction accuracy of the flow rates. Finally, the results of this study are expected to be sufficiently used as the data of flood warning system in urban rivers where the observation length of hydrological data is not relatively long and the flow-rate changes rapidly.

• Convergence Security Journal
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• v.22 no.4
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• pp.35-44
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• 2022

Among the five promotion strategies of Defense Innovation 4.0(DI 4.0), the military structure/operation optimization strategy aims to innovate the military structure based on advanced science&technology(S&T), and to integrate advanced S&T in the field of defense operation such as education&training and human resource development. As the future battlefield expands to AI-based unmanned/robot combat systems, space, cyberspace, and electromagnetic fields, it is necessary to train officers with the capabilities required in these battlefields. It is necessary to develop capabilities from junior officers who will lead the future battlefield to operating core advanced power based on the 4^th industrial revolution S&T. We review the education system of the military in universities and propose a method of redesigning the education system that is compatible with DI 4.0 and can develop technology-intensive capabilities based on advanced S&T. We propose a operation plan of major and extra-programs that can develop the capabilities of junior officers required for the future battlefield, and also suggest ways to support the army's practical training.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5247-5253
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• 2012

The purpose of this study was to apply in the HACCP(Hazard Analysis Critical control) system of liquefied coffee and sikhe. The establishment of Critical limit during sterilization processing was measured by sterilization temperature and sterilization time for 30 days from April 1~30, 2012, and it was conducted at P company in Jincheon (Chungcheongbuk-do), korea. As a result, microbial(coliform, bacillus cereus, Clostridium perfringens and yeast & mold) of sikhe and liquefied coffee were detected before sterilization. In contrat, all microbial was not detected to Sikhe(238mL Can, 500mL and 300mL PP, 1.8L PP) after sterilization ($15{\pm}1$, $35{\pm}1$ and $45{\pm}1$ mins at $121{\pm}1^{\circ}C$, respectively) and Liquefied coffee was not detected after sterilization($121{\pm}1^{\circ}C$, $20{\pm}1$ mins). The sterilizer condition for deciding the most temperature and time were $121{\pm}1^{\circ}C$, $20{\pm}1$ mins. In conclusion, the sterilization process would be a great alternative to prevention, decreasing and removing of harmful microorganism, such as general bacteria, coliform and pathogenic bacteria etc. Therefore, the critical limit of sterilization temperature and time for quality control and biosafety was established at $121{\pm}1^{\circ}C$, $20{\pm}1$ mins. And it suggests that HACCP plan is necessary for monitoring method, monitoring cycle, solving method, education, training and record management during sterilization processing.