• Journal of Navigation and Port Research
• /
• v.37 no.6
• /
• pp.727-732
• /
• 2013

This primary purpose of this study is to suggest strategies for developing the Gwangyagn region as a logistics city. In order to achieve such purpose, the following methodology is used. First, the literature survey on papers, related-organization's homepage, reports and journals related to Gwangyang Bay and Gwangyang port. Second, an pilot survey and field survey for suggesting SWOT analysis are carried out. Finally, questionnaire survey using a AHP analysis technique is distributed and analyzed. The strategies for developing as a logistics city are suggested as followings. First, ST strategy such as the development of the international hinterland logistics center related to the port logistics function is considered as the most important factor and followed by ST strategy, WT strategy and WO strategy. Second, creation of the revenue-creating logistics business model is to be considered as the most important factor and followed by development of the international hinterland logistics center related to the port logistics function, operation of the logistics center, creating high value-added of free trade area etc. For further research, more concrete and empirical study have to be carried out.

• Journal of Korea Port Economic Association
• /
• v.27 no.2
• /
• pp.313-331
• /
• 2011

Due to have been more keen in East-North Asia Hub Port competition, to be accelerated Busan New Port development, and to result to supply excess position, Busan port has been confronted by many problems. Also, as facilities of North Port is old, it is impossible to secure 16m depth of water at North Port, and North Port redevelopment is being, container traffic of North Port is accelerated to shift at New Port. Therefore, it. is time to seek for connection growth plan of succeeding together-Busan North & New Port as soon as possible. Connection growth plan of succeeding together-Busan North & New Port is focused, as follows. First, it is required to set up model for connection growth plan of succeeding together-Busan North & New Port. It is valid to specialize for ULCC, to promote to global port at New Port, and it is effective to focus on feeder service and general cargo handling, and to include most space to North Port redevelopment. Second, through port function reorganization, it is required to create a synergy by port function clustering. Third, through effective connection traffic network expansion for moving T/S cargo effectively, it is required to develop Busan Port for T/S cargo-focused port. Fourth, it is required to develop port hinterland logistics zone for creating container traffic through connection development of New Port-BJFEZ. Finally, it is required to build SCM system for creating container traffic among shipper, carrier, freight forwarder and related institution.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2005.10a
• /
• pp.111-116
• /
• 2005

The approaching waters of Po-hang port will be increased the traffic volume and passage of larger vessel according to the opening of Young-il new port in 2006. But the adjacent area of Po-hang port still exist the danger elements of safe navigation, the disordered navigation and traffic congestion. Therefore the safety of traffic must be improved in Po-hang vicinity area. This paper describes the status of marine traffic flow and navigational characteristics based on the marine traffic survey using the exclusive software, and the results of marine traffic survey classify into the ship's types and tonnage and track history of passing ships through the statistical method. Finally the examinations of main traffic route, traffic flow and navigational characteristics are discussed, and these results can be utilized the best design of ship's routing at the Po-hang approaching water.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.2
• /
• pp.468-474
• /
• 2021

Forest healing is a natural method that utilizes various natural environmental factors of forests to enhance immunity and to heal mental and physical pathologies. The aim of this study is to suggest implications for the future development of forest healing by analyzing the characteristics of facilities and programs in 28 national and public healing forests in Korea. The concept of forest healing and programs is defined, and healing forests operating in Korea are classified by size. The facility operation and program characteristics of healing forests were analyzed according to size, and the results were used to suggest a future direction for the development of domestic forest healing. The research results are as follows. First, domestic healing forests have gradually been reduced in size since they were first opened in 2009, which is the cause of the competitive creation of local governments. Second, healing spaces, forest paths, and programs for the elderly, pregnant women and disabled should be expanded. Third, lodging programs need to be expanded, and subsidies for usage fees from local governments are required. Institutional supplementation should be provided to link program development and facilities and to clarify procedures and standards for forest healing facilities.

• Korean Journal of Medicinal Crop Science
• /
• v.5 no.3
• /
• pp.177-185
• /
• 1997

Twenty-four major ecological and physiolosical characters of the 54 accessions of taro(Colocasia antiquorum) were observed in the growing seasons of 1995 and 1996 in $Ch{\breve{o}}nju$, Korea. The average days to emergence of the 54 accessions were 21.7 and the accession which had the shortest days to emergence was Kurye #2. Petiole color of most accessions was green, except $Ich{\breve{o}}n$ #1, Iri #1, Puan #1 and Taiwan #1 which had purple petioles. All the accessions had cormels except Taiwan #1 which had long runners without cormels. Average yield of the accessions was 3,719 kg/10a and total carmel weight, average carmel number, average carmel and average corm weight were 787g/plant, 39.2/plant, 20.3g/cormel, and 263.6g/plant, respectively. Accessions $Ch{\breve{o}}ngju$ #1 and Wanju #1 showed superiority in the three important characters, total carmel weight/plant, average carmel weight, and corm weight. Multivariate analysis for the 24 characters indicated that petiole color and carmel type had relatively higher coefficient of variation, 56.8 and 44.4 %, respectively. Fifty four taro accessions could be classified into 11 groups with D(${\sqrt{D^{2}}$) value of 110 on the basis of phenotypical characteristics. Most accessions were inclued in Group II. The Group I in which Taiwan #1 was included was genetically the most distant from the other groups. Accessions with purple petioles were grouped into the three different subgroups in which green petiole accessions were not included, indicating high dissimilarity between the different petiole color accessions. All the accessions grouped into the Group VIII, $Ch{\breve{o}}ngju$ #1, Wanju #1, Wanju #3, and $Taech{\breve{o}}n$ #2, had higher bioogical yield. Some accessions collected from the same district showed a high dissimilarity by being classified into the different subgroups.

• Journal of Intelligence and Information Systems
• /
• v.18 no.2
• /
• pp.143-156
• /
• 2012

People easily believe that news and stock index are closely related. They think that securing news before anyone else can help them forecast the stock prices and enjoy great profit, or perhaps capture the investment opportunity. However, it is no easy feat to determine to what extent the two are related, come up with the investment decision based on news, or find out such investment information is valid. If the significance of news and its impact on the stock market are analyzed, it will be possible to extract the information that can assist the investment decisions. The reality however is that the world is inundated with a massive wave of news in real time. And news is not patterned text. This study suggests the stock-index invest model based on "News Big Data" opinion mining that systematically collects, categorizes and analyzes the news and creates investment information. To verify the validity of the model, the relationship between the result of news opinion mining and stock-index was empirically analyzed by using statistics. Steps in the mining that converts news into information for investment decision making, are as follows. First, it is indexing information of news after getting a supply of news from news provider that collects news on real-time basis. Not only contents of news but also various information such as media, time, and news type and so on are collected and classified, and then are reworked as variable from which investment decision making can be inferred. Next step is to derive word that can judge polarity by separating text of news contents into morpheme, and to tag positive/negative polarity of each word by comparing this with sentimental dictionary. Third, positive/negative polarity of news is judged by using indexed classification information and scoring rule, and then final investment decision making information is derived according to daily scoring criteria. For this study, KOSPI index and its fluctuation range has been collected for 63 days that stock market was open during 3 months from July 2011 to September in Korea Exchange, and news data was collected by parsing 766 articles of economic news media M company on web page among article carried on stock information>news>main news of portal site Naver.com. In change of the price index of stocks during 3 months, it rose on 33 days and fell on 30 days, and news contents included 197 news articles before opening of stock market, 385 news articles during the session, 184 news articles after closing of market. Results of mining of collected news contents and of comparison with stock price showed that positive/negative opinion of news contents had significant relation with stock price, and change of the price index of stocks could be better explained in case of applying news opinion by deriving in positive/negative ratio instead of judging between simplified positive and negative opinion. And in order to check whether news had an effect on fluctuation of stock price, or at least went ahead of fluctuation of stock price, in the results that change of stock price was compared only with news happening before opening of stock market, it was verified to be statistically significant as well. In addition, because news contained various type and information such as social, economic, and overseas news, and corporate earnings, the present condition of type of industry, market outlook, the present condition of market and so on, it was expected that influence on stock market or significance of the relation would be different according to the type of news, and therefore each type of news was compared with fluctuation of stock price, and the results showed that market condition, outlook, and overseas news was the most useful to explain fluctuation of news. On the contrary, news about individual company was not statistically significant, but opinion mining value showed tendency opposite to stock price, and the reason can be thought to be the appearance of promotional and planned news for preventing stock price from falling. Finally, multiple regression analysis and logistic regression analysis was carried out in order to derive function of investment decision making on the basis of relation between positive/negative opinion of news and stock price, and the results showed that regression equation using variable of market conditions, outlook, and overseas news before opening of stock market was statistically significant, and classification accuracy of logistic regression accuracy results was shown to be 70.0% in rise of stock price, 78.8% in fall of stock price, and 74.6% on average. This study first analyzed relation between news and stock price through analyzing and quantifying sensitivity of atypical news contents by using opinion mining among big data analysis techniques, and furthermore, proposed and verified smart investment decision making model that could systematically carry out opinion mining and derive and support investment information. This shows that news can be used as variable to predict the price index of stocks for investment, and it is expected the model can be used as real investment support system if it is implemented as system and verified in the future.