• 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.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.1-25
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• 2020

Sentiment Analysis (SA) is a Natural Language Processing (NLP) task that analyzes the sentiments consumers or the public feel about an arbitrary object from written texts. Furthermore, Aspect-Based Sentiment Analysis (ABSA) is a fine-grained analysis of the sentiments towards each aspect of an object. Since having a more practical value in terms of business, ABSA is drawing attention from both academic and industrial organizations. When there is a review that says "The restaurant is expensive but the food is really fantastic", for example, the general SA evaluates the overall sentiment towards the 'restaurant' as 'positive', while ABSA identifies the restaurant's aspect 'price' as 'negative' and 'food' aspect as 'positive'. Thus, ABSA enables a more specific and effective marketing strategy. In order to perform ABSA, it is necessary to identify what are the aspect terms or aspect categories included in the text, and judge the sentiments towards them. Accordingly, there exist four main areas in ABSA; aspect term extraction, aspect category detection, Aspect Term Sentiment Classification (ATSC), and Aspect Category Sentiment Classification (ACSC). It is usually conducted by extracting aspect terms and then performing ATSC to analyze sentiments for the given aspect terms, or by extracting aspect categories and then performing ACSC to analyze sentiments for the given aspect category. Here, an aspect category is expressed in one or more aspect terms, or indirectly inferred by other words. In the preceding example sentence, 'price' and 'food' are both aspect categories, and the aspect category 'food' is expressed by the aspect term 'food' included in the review. If the review sentence includes 'pasta', 'steak', or 'grilled chicken special', these can all be aspect terms for the aspect category 'food'. As such, an aspect category referred to by one or more specific aspect terms is called an explicit aspect. On the other hand, the aspect category like 'price', which does not have any specific aspect terms but can be indirectly guessed with an emotional word 'expensive,' is called an implicit aspect. So far, the 'aspect category' has been used to avoid confusion about 'aspect term'. From now on, we will consider 'aspect category' and 'aspect' as the same concept and use the word 'aspect' more for convenience. And one thing to note is that ATSC analyzes the sentiment towards given aspect terms, so it deals only with explicit aspects, and ACSC treats not only explicit aspects but also implicit aspects. This study seeks to find answers to the following issues ignored in the previous studies when applying the BERT pre-trained language model to ACSC and derives superior ACSC models. First, is it more effective to reflect the output vector of tokens for aspect categories than to use only the final output vector of [CLS] token as a classification vector? Second, is there any performance difference between QA (Question Answering) and NLI (Natural Language Inference) types in the sentence-pair configuration of input data? Third, is there any performance difference according to the order of sentence including aspect category in the QA or NLI type sentence-pair configuration of input data? To achieve these research objectives, we implemented 12 ACSC models and conducted experiments on 4 English benchmark datasets. As a result, ACSC models that provide performance beyond the existing studies without expanding the training dataset were derived. In addition, it was found that it is more effective to reflect the output vector of the aspect category token than to use only the output vector for the [CLS] token as a classification vector. It was also found that QA type input generally provides better performance than NLI, and the order of the sentence with the aspect category in QA type is irrelevant with performance. There may be some differences depending on the characteristics of the dataset, but when using NLI type sentence-pair input, placing the sentence containing the aspect category second seems to provide better performance. The new methodology for designing the ACSC model used in this study could be similarly applied to other studies such as ATSC.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.27-65
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• 2020

Many companies on information and communication technology make public their own developed AI technology, for example, Google's TensorFlow, Facebook's PyTorch, Microsoft's CNTK. By releasing deep learning open source software to the public, the relationship with the developer community and the artificial intelligence (AI) ecosystem can be strengthened, and users can perform experiment, implementation and improvement of it. Accordingly, the field of machine learning is growing rapidly, and developers are using and reproducing various learning algorithms in each field. Although various analysis of open source software has been made, there is a lack of studies to help develop or use deep learning open source software in the industry. This study thus attempts to derive a strategy for adopting the framework through case studies of a deep learning open source framework. Based on the technology-organization-environment (TOE) framework and literature review related to the adoption of open source software, we employed the case study framework that includes technological factors as perceived relative advantage, perceived compatibility, perceived complexity, and perceived trialability, organizational factors as management support and knowledge & expertise, and environmental factors as availability of technology skills and services, and platform long term viability. We conducted a case study analysis of three companies' adoption cases (two cases of success and one case of failure) and revealed that seven out of eight TOE factors and several factors regarding company, team and resource are significant for the adoption of deep learning open source framework. By organizing the case study analysis results, we provided five important success factors for adopting deep learning framework: the knowledge and expertise of developers in the team, hardware (GPU) environment, data enterprise cooperation system, deep learning framework platform, deep learning framework work tool service. In order for an organization to successfully adopt a deep learning open source framework, at the stage of using the framework, first, the hardware (GPU) environment for AI R&D group must support the knowledge and expertise of the developers in the team. Second, it is necessary to support the use of deep learning frameworks by research developers through collecting and managing data inside and outside the company with a data enterprise cooperation system. Third, deep learning research expertise must be supplemented through cooperation with researchers from academic institutions such as universities and research institutes. Satisfying three procedures in the stage of using the deep learning framework, companies will increase the number of deep learning research developers, the ability to use the deep learning framework, and the support of GPU resource. In the proliferation stage of the deep learning framework, fourth, a company makes the deep learning framework platform that improves the research efficiency and effectiveness of the developers, for example, the optimization of the hardware (GPU) environment automatically. Fifth, the deep learning framework tool service team complements the developers' expertise through sharing the information of the external deep learning open source framework community to the in-house community and activating developer retraining and seminars. To implement the identified five success factors, a step-by-step enterprise procedure for adoption of the deep learning framework was proposed: defining the project problem, confirming whether the deep learning methodology is the right method, confirming whether the deep learning framework is the right tool, using the deep learning framework by the enterprise, spreading the framework of the enterprise. The first three steps (i.e. defining the project problem, confirming whether the deep learning methodology is the right method, and confirming whether the deep learning framework is the right tool) are pre-considerations to adopt a deep learning open source framework. After the three pre-considerations steps are clear, next two steps (i.e. using the deep learning framework by the enterprise and spreading the framework of the enterprise) can be processed. In the fourth step, the knowledge and expertise of developers in the team are important in addition to hardware (GPU) environment and data enterprise cooperation system. In final step, five important factors are realized for a successful adoption of the deep learning open source framework. This study provides strategic implications for companies adopting or using deep learning framework according to the needs of each industry and business.

• Journal of Venture Innovation
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• v.5 no.3
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• pp.57-70
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• 2022

In modern industrial capitalism, the relationship between the provision of work and the receipt of wages has become an important principle governing society. According to the labor contract, the wages provided by entrusting the right to dispose of one's labor to the employer are directly compensated, and human life should be guaranteed and reproduced with proper rest. The establishment of labor relations under free contracts represents a problem in protecting workers, and accordingly, the maximum of working hours is set as a minimum right for workers, and the standard for minimum rest is set and assigned. The reduction of working hours is very important in terms of the quality of life of workers, but it is also an important issue in efficient corporate activities. As of 2020, Korea has 1,908 hours of annual working hours, the third lowest among OECD 37 countries in the happiness index surveyed by the Sustainable Development Solution Network(SDSN), an agency under the United Nations. Accordingly, the necessity of reducing working hours has been recognized, and the maximum working hours per week has been limited to 52 hours since 2018. In this situation, various working hours are legally excluded as a way to maintain the company's value-added creation and meet the diverse needs of workers, and Korea's Labor Standards Act restricts flexible working hours within three months, flexible working hours exceeding three months, selective working hours, and extended working hours. However, in the discussion on the application of the revised flexible working hours system in 2021 and the expansion of the settlement unit period recently discussed, there is a problem with the flexible working hours system, which needs to be improved. Therefore, this paper aims to examine the problems of the flexible working hours system and improvement measures. The flexible working hours system is a system that does not violate working hours even if the legal working hours are exceeded on a specific day or week according to a predetermined standard, and does not have to pay additional wages for excessive overtime work. It is mainly useful as a form of shift work in manufacturing, sales service, continuous business or electricity, gas, water, and transportation for long-term operations. It is also used as a way to shorten working hours, such as expanding holidays through short working days. However, if the settlement unit period is expanded, it is disadvantageous to workers as the additional wages that workers can receive will not be received. Therefore, First, in order to expand the settlement unit period currently under discussion, additional wages should be paid for the period expanded from the current standard. Second, it is necessary to improve the application of the flexible working hours system to individual workers to have sufficient consultation with individual workers in a written agreement with the worker representative, Third, clarify the allowable time for extended work during the settlement unit period, and Fourth, limit the daily working hours or apply to continuous rest. In addition, since the written agreement of the worker representative is an important issue in the application of the flexible working hours system, it is necessary to secure the representation of the worker representative.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.211-226
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• 2023

As we transition into the post-COVID era, economic activities that were stagnant are regaining momentum. In particular, there is a growing trend of technology entrepreneurship driven by the opportunities of digital transformation in the Fourth Industrial Revolution. However, entrepreneurship education content is struggling to keep up with the rapid pace of technological change. This study aims to emphasize the importance of entrepreneurship mentoring as a crucial component of entrepreneurship education content that requires adaptation and advancement due to the increasing demand for technology entrepreneurship. This study redefines startup mentoring, which is differentiated from general mentoring, at the present time when the demand for startups, which increases with the declining employment rate, increases, and the development of quality startup education contents and securing professional startup mentors are required. According to the start-up stage, it is divided into preliminary entrepreneurs and early entrepreneurs, and the effect of entrepreneurship knowledge and self-efficacy among start-up mentoring functions on entrepreneurial will and mentoring satisfaction is improved by empirically researching the effects of start-up mentoring functions in the case of initial entrepreneurs as a moderating effect. To confirm the importance of entrepreneurship mentoring effect for. To this end, among the mentoring functions, entrepreneurship knowledge and self-efficacy were set as independent variables, and entrepreneurial will and mentoring satisfaction were set as dependent variables. The research model was designed and hypotheses were established. In addition, empirical analysis was conducted by conducting a questionnaire survey on trainees who received entrepreneurship mentoring education at ICCE Startup School and Opus Startup School. To summarize the results of the empirical analysis, first, among the entrepreneurship mentoring functions, entrepreneurship knowledge and self-efficacy were analyzed to have a significant positive (+) effect on entrepreneurial will. Second, among the entrepreneurship mentoring functions, entrepreneurship knowledge and self-efficacy were analyzed to have a significant positive (+) effect on mentoring satisfaction. Third, it was analyzed that entrepreneurship had no significant moderating effect on entrepreneurial knowledge and entrepreneurial will. Fourth, it was analyzed that entrepreneurship had no significant moderating effect on mentoring satisfaction. Fifth, it was found that entrepreneurship had a significant moderating effect between self-efficacy and will to start a business. As a result of the research analysis, the first implication is that the mentoring function in start-up education is analyzed to produce meaningful results for both the initial entrepreneurs and the prospective entrepreneurs in the will to start a business and satisfaction. . Second, it was analyzed that there was no significant relationship between whether a business was started and the mentoring function and effect. However, it was analyzed that the will to start a business through improvement of self-efficacy through mentoring was significantly related to whether or not to start a business. turned out to be helpful. Many start-up education programs currently conducted in Korea educate both early-stage entrepreneurs and prospective entrepreneurs at the same time for reasons such as convenience. However, through the results of this study, even in small-scale entrepreneurship mentoring, it is suggested that customized mentoring through detailed classification such as whether the mentee has started a business can be a method for successful entrepreneurship and high satisfaction of the mentee.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.19 no.1
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• pp.75-91
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• 2024

Recently, global business environment is changing dramatically along with the acceleration of technological innovation amid the war, climatic change, and geopolitical instability. Accordingly, it is difficult to predict or plan for the future as the volatility, complexity, ambiguity, and uncertainty of the industrial ecosystem continue to increase. Therefore, organizations are undergoing inevitable restructuring in accordance with their survival strategy, for instance, removing marginal businesses or firing. Accordingly, office workers are seeking a startup as an alternative for their continuous economic activity amid rising anxiety factors that make them think they would lose their jobs unintentionally. Here, this study is aimed to verify through what paths office workers' self-determination influences the process of converting to a startup. For this study, an online survey was carried out, and 310 respondents' valid data were analyzed through SPSS and AMOS. To sum up the results, first, office workers' self-determination did not have significant effects on entrepreneurial intention. However, it was confirmed that self-determination had positive (+) effects on innovativeness and perception of the startup support system. This result shows that their psychology works to prepare step by step by accumulating innovative experiences and increasing perception of the startup support system from a long-term life path perspective rather than challenging startups right way. Second, innovativeness is found to have positive (+) effects on entrepreneurial intention. Also, perception of the startup support system had positive (+) effects on entrepreneurial intention. This implies that when considering startups, they are highly aware of the government's various startup support systems. Third, innovativeness is found to have positive (+) effects on perception of the startup support system. It is judged that perception of the startup support system is valid for prospective founders to exhibit their innovativeness and realize new ideas. Fourth, it was confirmed that innovativeness and perception of the startup support system mediated correlation between self-determination and entrepreneurial intention, and perception of the startup support system mediated correlation between innovativeness and entrepreneurial intention, which shows that it is a crucial factor in entrepreneurial intention. Although previous studies related to startups deal with students mostly, this study targets office workers who form a great part in economic activities, which makes it academically valuable in terms of being differentiated from others and extending the scope of research. Also, when we consider the fact that the motivation for self-determination alone fails to stimulate entrepreneurial intention and the complete mediation of innovativeness and the startup support system, it has great implications in practical aspects such as the government's human and material support systems. In the selection and analysis of samples, this study exhibits a limitation that the problem of common method bias is not completely resolved. Also, additional definitive research is needed on whether entrepreneurial intention is formed and converted into startup behavior. Academically and practically, this study deals with the relationship between humans' psychological motives and startups which has not been handled sufficiently in previous studies. The conversion of office workers to startups is expected to have effects on individuals' economic stability and the state's job creation; therefore, it needs to be investigated continuously for its great value.

• Journal of The Korean Society of Grassland and Forage Science
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• v.25 no.1
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• pp.71-82
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• 2005

Khori(高麗) refers to the Chaabog(reindeer) that live on lichens(蘚) on Mt. Soyon(鮮) in which pastures are the cold and dry plateau of North Eurasia. Thus, the origin region of the Khori or Koguryo that are the ancestors of the reindeer-herding pastoral nomads(馴鹿 遊牧民) can be said to be the Steppe-Taiga-Tundra pastoral areas of North Eurasia and North America. When the pastoral nomads moved on to the great mountain(大山) zone of the Jangbaek(長白) to the Baekdu(白頭) Mountains, they could have been in contact with pastoral farmers or agricultural farmers living there and they became the farmers remaining on agricultural farms. They were the Koryo people, the ancestors of Korea. Staying in one place, they gradually forgot the origin of their reindeer-herding pastoral nomadic history in the Northwest area of Mt. Soyon, the small mountain(小山) zone of the Steppe-Taiga-Tundra pastoral areas. In other words, they lost their identity as reindeer-herding pastoral nomads when they entered the agricultural area after leaving the pastoral area. However, since their basic genes had already formed when they lived on the cold and dry plateau of North Eurasia, it is possible to study their pastoral nomadic history focusing on 'the minority living in the broad area(廣域少數)', by utilizing highly advanced biotechnological science and focusing on genes and information technology innovation, and removing various past hindrances in research. Therefore, it is not so difficult to restore the reindeerherding pastoral nomadic history of the Koguryo(高句麗) people and secure their pastoral nomadic identity, of which the first steps have already been taken into their historical stages. The Eurasian continent and the Korean peninsula, especially the cold and dry plateau of North Eurasia and the Korean peninsula have been closely related to each other ecologically and historically. They can never be a separate space at all. The Eurasian continent lies horizontally east to west and thus, the continent forms an isothermal zone. Also, since the time of producing their own foods, it was relatively easy for people with their technology to move to other places owing to the pastoral nomadic characteristic of mobility. Unlike the Chungyen(中原) region, western Asia and the regions covering the Siberia-Manchu-Korean peninsula where food production revolution was first made were connected to the Mongolian lichens route(蘚苔之路: Ni, ukinii jam) and steppe roads. Although the ecological conditions of nature have changed a bit throughout a long history, it was natural for the many tribes in North Asia living on the largest Steppe-Taiga-Tundra area in the world to have believed 'the legends related to animals in relation to their founders and ancestors(獸祖傳說)'. Assuming that Siberian tigers and the tigers living on Mt. Baekdu were connected ecologically and genetically because of the ecological characteristics of the animals, and their migration from plateau to plateau, we would suspect that the Chosun(朝鮮) tribe living on Mt. Baekdu were ethnically and culturally more closely connected to the farther removed Ural-Altai tribes that lived on the cold and dry plateau region than to the Han(i14;) tribe who lived in Chungyen(中原) that was close to Mt. Baekdu. More evidence is the structure of the Korean language which has the form of 'Subject + Object + Verb', which is assumed to have originated from the speedy lifestyle of the reindeer-herding pastoral nomads. The structure is quite different from that of the Han(漢) language, which is based on agricultural life. Also, it is natural for reindeer riding reindeerherding pastoral nomads or horse-riding sheep-herding pastoral nomads(騎馬, 羊遊牧民) to have held military and political power over the region and eventually to have established an ancient pastoral nomadic empire in the process of their conquest of agricultural regions. The stages for founding global empires in the history of mankind maybe largely divided into two, in terms of ecological conditions and occupations. They are the steppes and the oceans. Of course, the steppe-based empires were established based on the skills to deal with horses and the ability to shoot arrows while riding horses, along with the use of iron ware in the 8th century BC. The steppe-based empires became the foundation for an oceanic empire, which could have been established by the use of warships and warship guns since the 15th Century. Based on those facts, we know that Chosun, Puyo(夫餘), and Koguryo are the products of a developmental process of pastoral nomadic empires on the steppes. Maybe we can easily find the pastoral nomadic identity of the Koguryo more than we expected when we trace the origins and history of the Korean tribe living in the pastures located in the northwest area of Mt. Jangbaek by focusing on pastoral nomadic mobility and organization just as we have investigated the historic origins of Anglo-Saxons in America by focusing on the times before the 15th Century. In the process, we should keep in mind that English culture originated from the Industrial Revolution and was directly delivered to the American continent, although America was far from England and was not an intermediate point on long sojourns either. Further, American culture came back to England in a more advanced form later. The most important thing currently to be resolved is to cause Koreans to look back on their own history in a freer way of thinking and with diverse, profound, and sharp insight, taking away the old and existing conventional recognition that is entangled with complicated interests with Korean people and other countries. The meanings of Chosun, Khori, and Solongos have been interpreted arbitrarily without any historic evidence by the scholars who followed conventional tradition of fixed-minded aristocrats in an agricultural society. If the Siberian cultural properties of the stone age, the earthenware age, the bronze age, and the iron age are analyzed in such a way, archaeological discovery will never be able to contribute to the restoration of the Koguryo's pastoral nomadic identity. One should transcend the errors that tend to interpret the cultural properties discovered in the pastoral nomadic regions as not being differentiated from those of agricultural regions and just interpret them altogether from the agricultural point of view. A more careful intention is required in the interpretation of cultural properties of ancient Korean empires that seem to have been formed due to mutual interactions of pastoral nomadic and agricultural cultures. Also, it is required that the conventional recognition chain of 'reverse-genes' be severed, which has placed more weight on agricultural properties than pastoral nomadic ones, since their settlement on agricultural farms was made after the establishment of their ancient pastoral nomadic empires. There is no reason at all to place priority on stoneware, earthenware, bronze ware, and iron ware than on wooden ware(木器) and other ware which were made of animal skins(皮器), bones and horns(骨角器), in analyzing the history in the regions of reindeer or sheep pastures. Reading ancient Korean history from the perspective of pastoral nomadic history, one feels strongly the instinctive emotions to return to the natural 'mother place'. The reindeer-herding pastoral nomadic identity of the Koguryo people that has been accumulated in volumes in their genes and hidden deep inside and have interacted organically could be reborn with Burqanism(Burqan refers to 不咸 in Chinese), which was their religion by birth and symbolized as the red willow(紅柳=不咸). The mother place of the Koguryo's people is the endless vast green pastures of North Eurasia and North America, where we anticipated the development of Korean livestock farming following the inherent properties in the genes of the reindeer-herding pastoral nomads with Korean ancestors. We anticipate that the place would be the core resource that could contribute to the development of life of living creatures following the inherent properties of their genes and biotechnological factors. In other words, biotechnology used for a search for clues on the well-being of humans could be the fruit brought by Burqanism of the Koguryo people and the fruit of the globalization of Korean livestock farming. It is the Chosun farmer in China come from the vast nomadic reindeer pastures of North Eurasia that resolved the food problem of a billion Chinese people with lowland paddy rice seeds (水稻) by transforming Heilongjiang Province(黑龍江省) into an oceanic lowland paddy rice field(水田). Even Mao Tse-tung(毛擇東) could not resolve the food problem by his revolution campaigns for tens of years. Today is the very time that requires the development of special livestock farming following the inherent properties of the ancient Korean reindeer-herding pastoral nomads that respected the dignity of life on the cold and dry plateau of North Eurasia and the America continent. I suggest that research should be started from the pastures of the Dariganga Steppe in East Mongolia that was the homeland of Hanwoo(韓牛) and the central horse-herding steppe place(牧馬場) of Chingis Khan's Mongolia. The Dariganga Steppe is awash with an affluent natural environment for pastoral nomadic living however, the quality of life of the pastoral nomads there is still low. I suggest we Koreans, the descendents of the Koguryo, should take our first steps for our livestock farming business project and develop the Northern nomadic pastures, here at the pastures of the Dariganga Steppe, which is the Mongolian core place of state-of-the-art technology for military weapons.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.17 no.6
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• pp.511-522
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• 1984

The Nagdong is one of the biggest rivers in Korea, which is very important water source not only for tap water of Pusan city but also for the industrial water. Therefore, authors tried to check the water quality year by year. In this experiment one hundred and twenty water samples collected from August 1983 to July 1984 were analyzed bacteriologically and physiologically. Fifteen sampling stations were established between near Samrangjin and estuary of the river. To evaluate the water quality, temperature, pH, chloride ion, salinity, chemical oxygen demand (COD), electrical conductivity, nutrients, total coliform, fecal coliform, fecal streptococcus, viable cell count and bacterial flora were observed. The variation of water temperature was ranged $-1.5{\sim}29.0^{\circ}C$ (Mean value $13.9{\sim}16.5^{\circ}C$), it in spring was higher as $10{\sim}15^{\circ}C$ about $10^{\circ}C$ than in winter and it in autumm was very stabilized as about $20^{\circ}C$ at each station. The pH variation of the samples was ranged $6.68{\sim}9.15$. The range of concentration of chloride ion and salinity varied $7.4{\sim}l,020.5$ mg/l and $1.05{\sim}33.0\%0$, respectively. Especially, salinity of the 3rd water war was the higher than others as $25.76{\sim}31.58\%0$. COD was ranged $1.45{\sim}14.94$ mg/l and the lower part of the Nagdong River was heavily contaminated by domesitc sewage and waste water from the adjacent factor area. The range of electrical conductivity was $1.360{\times}10^2{\sim}5.650{\times}10^4{\mu}{\mho}/cm$ and that was by far higher the estuary than the upper. Concentration of nutrients were $0.008{\sim}0.040$ mg/l (Mean value $0.019{\sim}0.068$ mg/l) for $NO_2-N,\;0.038{\sim}5.253$ mg/l ($0.351{\sim}2.347$ mg/l) for $NO_3-N,\;0.100{\sim}2.685$ mg/l($0.117{\sim}1.380$ mg/l) for $NH_4-N,\;0.003{\sim}0.084$ mg/l($0.014{\sim}0.065$ mg/l) for $PO_4-P$ and $0.154{\sim}6.123$ mg/l ($1.165{\sim}3.972$ mg/l) for $SiO_2-Si$, respectively. Usually nutrients contents of the water in the upper part(included station 1 to 5) were higher than those of the estuarine area. The bacterial density of the samples ranged 7.3 to 460,000/100 ml for total coliforms, 3.6 to 460,000/100 ml for fecal coliform, $0{\sim}46,000/100ml$ for fecal streptococcus and $<30{\sim}1.2{\times}10^5/ml$ for viable cell count. Composition of coliform was $28\%$ Escherichia coli group, $18\%$ Citrobacter freundii group, $31\%$ Enterobacter aerogenes group and $22\%$ others. Predominant species among the 659 strains isolated from the samples were Pseudomonas spp. ($42\%$), Flavobacterium spp. ($20\%$) and Moraxella spp. ($12\%$).

• Journal of Agricultural Extension & Community Development
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• v.7 no.1
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• pp.155-166
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• 2000

When the marcher visited Korea in fall 1994, he was shocked to see high rise apartment buildings around the capitol region including Seoul and Suwon, resulting from rising demand of housing because of urban migration followed by second and third industrial development. After 6 years in March 2000, the researcher witnessed more apartment buildings and vinyl house complexes, one of the evidences of continued economic progress in Korea. Korea had to receive the rescue finance from International Monetary Fund (IMF) because of financial crisis in 1997. However, the sign of recovery was seen in a year, and the growth rate of Gross Domestic Products (GDP) in 1999 recorded as high as 10.7 percent. During this period, the Korean government has been working on restructuring of banks, enterprises, labour and public sectors. The major directions of government were; localization, reducing administrative manpower, limiting agricultural budgets, privatization of public enterprises, integration of agricultural organization, and easing of various regulations. Thus, the power of central government shifted to local government resulting in a power increase for city mayors and county chiefs. Agricultural extension services was one of targets of government restructuring, transferred to local governments from central government. At the same time, the number of extension offices was reduced by 64 percent, extension personnel reduced by 24 percent, and extension budgets reduced. During the process of restructuring, the basic direction of extension services was set by central Rural Development Administration Personnel management, technology development and supports were transferred to provincial Rural Development Administrations, and operational responsibilities transferred to city/county governments. Agricultural extension services at the local levels changed the name to Agricultural Technology Extension Center, established under jurisdiction of city mayor or county chief. The function of technology development works were added, at the same time reducing the number of educators for agriculture and rural life. As a result of observations of rural areas and agricultural extension services at various levels, functional responsibilities of extension were not well recognized throughout the central, provincial, and local levels. Central agricultural extension services should be more concerned about effective rural development by monitoring provincial and local level extension activities more throughly. At county level extension services, it may be desirable to add a research function to reflect local agricultural technological needs. Sometimes, adding administrative tasks for extension educators may be helpful far farmers. However, tasks such as inspection and investigation should be avoided, since it may hinder the effectiveness of extension educational activities. It appeared that major contents of the agricultural extension service in Korea were focused on saving agricultural materials, developing new agricultural technology, enhancing agricultural export, increasing production and establishing market oriented farming. However these kinds of efforts may lead to non-sustainable agriculture. It would be better to put more emphasis on sustainable agriculture in the future. Agricultural extension methods in Korea may be better classified into two approaches or functions; consultation function for advanced farmers and technology transfer or educational function for small farmers. Advanced farmers were more interested in technology and management information, while small farmers were more concerned about information for farm management directions and timely diffusion of agricultural technology information. Agricultural extension service should put more emphasis on small farmer groups and active participation of farmers in these groups. Providing information and moderate advice in selecting alternatives should be the major activities for consultation for advanced farmers, while problem solving processes may be the major educational function for small farmers. Systems such as internet and e-mail should be utilized for functions of information exchange. These activities may not be an easy task for decreased numbers of extension educators along with increased administrative tasks. It may be difficult to practice a one-to-one approach However group guidance may improve the task to a certain degree.