• 대한공업교육학회지
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• v.38 no.1
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• pp.221-238
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• 2013

The purpose of this study was to revise and reorganize the direction of the department of ${\bigcirc}{\bigcirc}$Industrial High School though analysis of manufacturing status and workforce demand in Chungnam province focused on the Geumsan Area. In the study, ${\bigcirc}{\bigcirc}$Industrial High School of the status and actual conditions were identified through interview, literature review and data analysis. Surveys of the school teachers, parents and students was conducted in order to investigate the awareness of renaming and reorganization of school departments, curriculum revision of the school. Statistical data was collected and analyzed in order to figure out manufacturing industry and its workforce demand of Chungnam Province in Korea. Findings of the study were as follows: Small and medium enterprises of manufacturing industry have been developed a lot in Geumsan Area in Chungnam province. Four major industries including (1) automobile parts, (2) electronic and information equipment, (3) Cutting edge culture, and (4) Agricultural-livestock and bio are intensively fostered as regional strategic industries in the Chungnam province. The manufacturing industry has a 33.6-percent, and then service-mining and manufacturing industry has a 80.0-percent of total number of employee in Geumsan Area. It is expected that industrial workforce demand of Geumsan Area come out of manufacturing and service-mining industrial sector. The following is recommended for the school curriculum revision: (1) focussing on mechanical control for the revision of computer applying mechanical department, (2) focussing on automation electric equipment for the revision of electric control department, (3) focussing on food process control for revising of bio-food industrial department. It's helpful to make a progress of the school that establish identification of industrial specialized high school as an institution of vocational education at the secondary level through supplying qualified workforce to Manufacturing industry in Chungnam Province.

• Journal of Distribution Research
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• v.15 no.5
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• pp.237-255
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• 2010

The Korean Pharmacist Law has limited the sales of medicine to pharmacies. This has caused difficulty in purchasing medicine late at night or on holidays, which has limited the range of customers' selections and accelerated customers' discomfort, accordingly. Also, the rapid progress of aging has quickly boosted medical expenses for seniors, and has served as a factor that aggravates the budget of national medical insurance. Meanwhile, advanced countries, including the USA and Japan, have allowed the sales of general medicine, of which the safety and efficacy have been tested, in general retail stores such as convenience stores or super markets from the perspective of supporting self-medication. In particular, Japan, which has a strong tendency of pursuing safety in the world, diversified sales channels for general medicine in order to control quickly rising medical expenses. As a result, Japan has achieved the effect of easing various regulations as follows in the economic and social fields. First, the increasing distribution channels of general medicine from pharmacies to general retail stores provoked a potential demand, which also expanded related markets. Second, the competition between sales channels resulted in the reduction of the price of medicine. Third, the growing sales channels of medicine have extended the options of consumers and, subsequently, the convenience in the use of consumers has increased. Fourth, the creation of a competitive environment owing to the diversification of sales channels has accelerated an effort to enhance corporate competitiveness. Fifth, the foundation of enhancing the financial soundness of medical expenses has been prepared through the formation of a self-medication environment. In 2000, the Korean population aged 65 or over exceeded 7%, and it is anticipated to be over 14% by 2018; thus, the increase of national medical expenses will be sped up. As a way of being prepared for the era of aging, we, just as other advanced countries, need to create a self-treatment environment by diversifying the sellers of general medicine, and, thus, reduce spending on personal medical expenses, enhance the financial soundness of national medical insurance, and, further, promote the welfare of consumers.

• Journal of Digital Convergence
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• v.18 no.10
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• pp.81-93
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• 2020

This study is based on workplace learning, which has revealed its significant influence in the previous enterprise case studies. Why do small business owners have the opportunity to participate in workplace learning based on authenticity? It was intended to clarify whether it was necessary and to increase the growth and development potential of small business owners based on its contents. Moreover, this study is focused on identifying the influence of workplace learning on management performance through this series of processes. In order to investigate the influence of small enterprise workplace learning on management performance, research hypotheses were set based on a review of previous studies, and empirical analysis was carried out. A total of 203 questionnaires were empirically analyzed using SPSS 18.0 program. As a result, first, workplace learning had partially significant positive influence on job satisfaction. Second, workplace learning had significant positive influence on management performance. Third, job satisfaction had significant positive influence on management performance. Fourth, job satisfaction had partial mediating effect in the relationship between workplace learning and management performance. The analysis result showed that among sub-factors of workplace learning, only formal learning did not affect job satisfaction and that job satisfaction did not have mediating effect in the relationship between formal learning and management performance. According to analysis, this was because in poor small enterprise environments, opportunities to participate in formal learning like external training or in-house training were not kept. In other words, poor small enterprise environments were plainly revealed from the managerial, economic and social standpoint. Therefore, there is a need to establish the foundation of growth for them to solve problems and develop win-win development capabilities and an institutional system that can make a contribution to policy and education, and management, by helping small enterprises keep opportunities to participate in workplace learning. In spite of these significant study results, there can be a limitation. For improving this limitation, further research will need to target diverse fields focusing on samples, which can explain relations of many different variables. Also, working-level relation research connected to studies that can highly enhance management performance will be required.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.