• Korean Journal of Agricultural Science
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• v.46 no.4
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• pp.755-768
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• 2019

The forestry development policies and projects in Korea have been implemented under various related acts. These acts include the Framework Act on the National Land and Framework Act on Forestry enacted by each administration. However, there are some limitations to encourage a variety of mountain villages and forestry development policies due to duplication and overlap between the relevant acts. Nowadays, the fields of local development have evolved and become integrated not only by infrastructures but also in various fields such as multi-functional industries including tourism, green care, cultural welfare, etc. Therefore, the current legal system may not effectively accept and support various mountain village development policies and projects. This study tried to determine the necessity of reorganizing th-e related legal system through a field survey of planners, residents and analysts regarding the correlation between legal systems and projects. For these reasons, this study tried to determine the problems of the current legal system and then, suggested alternative methods related to the legal system for integrated rural development. The scope of the study is as follows: 1) correlation analysis between relevant laws and development projects and 2) field survey to determine the legitimacy and validity for the reorganization of the legal system.

• The Journal of Fisheries Business Administration
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• v.30 no.1
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• pp.31-50
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• 1999

The purpose of this paper is to offer policies or laws governing the future of Korean seafood markets in view of societal marketing concept. The environment surrounding those markets is changing quickly and constantly. The proposals in this paper are meant to help the Korean seafood market coping with this swiftly changing environment. This paper sorts this changing environment in terms of institutional side and secio-economical side. The institutional side involves the enforcement of international and domestic seafood trade standards, the increase of seafood importation, the adoption of optional seafood sales system, the openness of distribution market, and the adoption of TAC system. The secio-economical side involves the development of telecommunication and transportation, and the changing of seafood consumption pattern. The forecast about the future of seafood market could be classified into three fields, that is, the production field, the distribution field, and the consumption field of seafood. In the production field of seafood, the stabilization of supply of seafood and the production management oriented seafood market could be forecasted. In the distribution field, the formulating of enforced trade standards, the dispersion of marketing function among fisher, wholesaler and retailer, the development of marketing skills, and the promotion of marketing information system could be forecasted. Finally, in consumption field, the promotion of standardization and diversification, the appearance of intellectual consumers could be forecasted. This paper seeks to offer policies or laws fur the three categories of the seafood market-the government, the fisher, and the distributor-coping with the changing environment on the above three fields, thereby benefiting the consumer's long-term welfare. For the government, this paper suggests the construction of a Seafood Transaction Information Infrastructure, a Seafood Dealer License System, and a Seafood Safety Security System. For the fishers, this paper proposes an Eco-labelling System, a Sustainable Production System, and a Real Naming System in dealing seafood. Finally, for the distributors, this paper offers a Seafood Production Controlling System, a Nature-friendly Marketing System, and a Consumer-oriented Marketing System.

• Journal of the Korea Convergence Society
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• v.11 no.5
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• pp.199-207
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• 2020

Recently, big data analysis has drawn attention in various fields as it can generate value from large amounts of data and is also used to run political campaigns or predict results. However, existing research had limitations in compiling information about candidates at a high-level by analyzing only specific SNS data. Therefore, this study analyses news trends, topics extraction, sentiment analysis, keyword analysis, comment analysis for the 2017 presidential election of South Korea. The results show that various topics had been generated, and online opinions are extracted for trending keywords of respective candidates. This study also shows that portal news and comments can serve as useful tools for predicting the public's opinion on social issues. This study will This paper advances a building strategic course of action by providing a method of analyzing public opinion across various fields.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.5
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• pp.416-426
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• 2005

A B2Bi system needs a message storage subsystem that efficiently logs and searches XML messages which have been sent from orreceived by it. XML database systems and XML enabled relational databases systems are not adequate as a message storage system because of their expensiveness and excessiveness in functionality. Storage schemes that split XML messages into database records are also unacceptable because of either low performance or implementation hardness. In this paper, we propose a storage scheme that can be applied to implement a message storage system based on a relational database system. In this scheme, messages are examined only through the index fields that have been registered for each message types. Therefore, the proposed storage scheme cannot support such a powerful search facility like XQL, but it provides high performance message legging and restricted search facility. There are three alternative database schemas to store the index fields. This paper compares the advantages and disadvantages of the three schemas through experimental tests.

• Journal of Fashion Business
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• v.25 no.3
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• pp.51-70
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• 2021

The study aims to evaluate changes in textiles for automotive interior and suggest directions that the textile-development should take in order to achieve sustainability, and enter a circular economy system in the future. The main content and results of the study are as follows: First, we cover the overall sustainability study in the fashion and textile fields; in particular, the certification system is well established through the provision of information on the whereabouts of products to consumers and verification by external environmental auditors. Second, we considered the criteria of C2C in order to derive the necessary criteria for sustainability certification in the field of textiles. Third, we looked at the latest development trends of textile materials for automobile interiors which were divided into three categories: natural originated materials, circular economic consideration materials, and functional supplementary lightweight materials. In addition, we identified to what extent the trend of changes aggregated in the examples was satisfied and what was lacking when applied to the Basic criterion of C2C. As such, this study links and applies the sustainability criteria pursued in the fashion and textile fields to the textile for automotive interior materials, suggesting a direction for the textile field for automotive internal materials in the future. Based on the results of this study, it is hoped that studies on textiles for automotive interior considering the net economy will continue, and practical development in the industry will be realized.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.87-98
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• 2019

As artificial intelligence is actively studied, it is being applied to various fields such as image, video and natural language processing. The natural language processing, in particular, is being studied to enable computers to understand the languages spoken and spoken by people and is considered one of the most important areas in artificial intelligence technology. In natural language processing, it is a complex, but important to make computers learn to understand a person's common sense and generate results based on the person's common sense. Knowledge graphs, which are linked using the relationship of words, have the advantage of being able to learn common sense easily from computers. However, the existing knowledge graphs are organized only by focusing on specific languages and fields and have limitations that cannot respond to neologisms. In this paper, we propose an intelligent chatbotsystem that collects and analyzed data in real time to build an automatically scalable knowledge graph and utilizes it as the base data. In particular, the fine-tuned BERT-based for relation extraction is to be applied to auto-growing graph to improve performance. And, we have developed a chatbot that can learn human common sense using auto-growing knowledge graph, it verifies the availability and performance of the knowledge graph.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.85-100
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• 2022

Recently, with the widespread expansion of convergence based on digital connectivity, the transportation and mobility fields are rapidly changing, and research related to this is also diversifying. This study aims to analyze the research trends in the mobility field and identify key research areas and topics. Topic modeling analysis has been proved as a useful approach for analyzing the research trends. The abstracts of 142 research papers concerning mobility from the Korean academic citation index were analyzed, derived 9 research topics and linked to 6 key elements of research framework. The result showed that 'Advanced vehicle and transportaion technology' and 'Linkage and integrated services among means for mobility' were most actively studied research fields. It also found that research on insurance, law, regulation for securing user's safety and conflict-resolving with the existing industry has been conducted.

• Journal of the Korean Geosynthetics Society
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• v.23 no.1
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• pp.27-37
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• 2024

In this study, direct algorithm-based back analysis was utilized to perform back analysis on two actual earth retaining wall fields, which was then compared with genetic algorithm-based method to evaluate the suitability of the back analysis. Additionally, in order to propose effective utilization methods of the program, the measurement data, as the input for the back analysis, was varied for each excavation step, and the applicability of the back analysis results(displacement, axial force) was examined. The research findings indicate that both direct algorithm and genetic algorithm show high applicability; however, the optimization for this program is better predicted by the direct algorithm. Moreover, in order to effectively use the back analysis program employing the direct algorithm, it was evaluated that relatively accurate prediction of the earth retaining wall behavior could be achieved by inputting measurement data from the 7th excavation step for fields with final excavation steps ranging from 8 to 11.

• 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.

• The Research Journal of the Costume Culture
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• v.8 no.6
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• pp.853-863
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• 2000

This study is planned to present the future direction of the study of Korean clothes through the realistic recognition of the changes of studying issues of each area of the related clothes. For this purpose, the writer of this thesis have collected, classified and analyzed those various kinds of papers and theses published in the professional magazines of clothes such as Journal of Korean Home Economics, Journal of the Korean Society of Clothing and Textiles, Journal of the Korean Society of Costume, The Research Journal of the Costume Culture so that I might examine and study the main trend of the related study. The result of the study is as follows. 1. Since the first publication of Journal of Korean Home Economics in 1959 and Journal of the Korea Society of Clothing and Textiles, and Journal of the Korean Society of Costume, the study of clothes has been gradually increased. Furthermore, since 1990 the issuing times of various kinds of Journals have been continuously increased with the foundation of The Research Journal of the Costume Culture and Journal of Fashion Business. 2. Theses and papers published in the four greatest Journals of Korean Clothing and Textiles have been studies for the detailed classification and analysis of the data. According to the study, It is found that the theses in Journal of the Korea Society of Clothing and Textiles have actively studied textiles as they had studied before 1990s and those in Journal of the Korean Society of Costume have studied history of costumes and those in The Research Journal of the Costume Culture have studied the composition and science of clothes. 3. The order of studying subjects was 1) Design and Aesthetics, 2) Fashion Merchandising 3) Textiles, 4) Clothing Construction, 5) History of Costumes, 6) Costume Culture, 7) Socio-Psychology of clothing, 8) Others. Considering the above mentioned result of the study, most of the main fields of the clothing and textiles study have been studied continuously in balance since 1990 unlike the past although the past studies had been performed largely in some main fields only. And it was found that fields of clothing styles and clothing goods have been studied most actively since 1990s. 4. The studying field of Design and Aesthetics has showed to have the trend to be studied very actively since 1990s, which has utilized various relevant data with scholastic approach to psychology and aesthetics. Regarding Fashion Merchandising, the study of consumers decision process has been performed most actively. And theses on the international trades have been published considerably more than ever before, which resulted in gradual increase in gradual increase in the study of the fields related with global marketing, internet marketing, textile products exports, and overseas brands, etc. Regarding Textiles, the field of clothing sanitation and management has been studied more actively than that of clothing materials. In case of clothing construction, the study of physical styles and pattern making has been more active than the other related fields. Fields of socio-psychology of clothing and history costume have been a little reduced. Field of costume culture has been firmly rooted as an independent subject to be studied in the clothing related study. And study of the clothes has shown various trends of studies of ethnic & folk clothes, religious and ceremonial garments, linguistic & favorite approach to clothes and academic analysis of the data.