• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.6
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• pp.127-139
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• 2012

This study aims to figure out the main agent of management in the 69 recently constructed neighborhood parks in Busan, and to analyze the present status of the main agents. For this purpose, the work resources on park and landscape management, interview to related staff, and the budget on urban parks were found as the main agents of management. In case the parks were managed by consignment or by other separate organization, this study collected resources through the homepage or personal visits. As a result for the management method on parks, about 48 parks(69.6%) were under direct management by the local governments' main office and its business offices. Eighteen parks(26.1%) were commissioned to corporation or private organizations and three parks(4.3%) were operated by both direct and commissioned management. Because of the overall management result on urban parks, the company under outsourced management is not sufficient for a comprehensive management. Such is mainly focused on the maintenance like landscape or cleaning, but have fewer programs for the users. Forty-six parks cared by the local governments are mainly small sized neighborhood parks. For the management, contract workers or short-term workers are hired. It demonstrates an urgent need to improve professional personnel and organizational system for park management. In addition, any educational or cultural facility in the park is managed by separate institutions. Thus, it is not controlled as a park facility but an independent facility with separate controls. Moreover, to solve such problems, it needs legalization on the proper employment for parks, institutional improvement, cooperative network with NGO, planning and development of the program used according to the change of time, and customer oriented program management.

• Journal of the Korean Institute of Navigation
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• v.13 no.1
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• pp.21-53
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• 1989

In the past twenty years, there has been a rapid increase in the volume of traffic in Korea due to the Korean great growth of the Korean economy. Since transformation provides an infrastructure vital to economic growth, it becomes more and more an integral part of the Korea economy. The importance of coastal shipping stands out in particular, not only because of the expansion limit on the road network, but also because of saturation in the capacity of rail transportation. In spite of this increase and its importance, coastal shipping is falling behind partly because it is givenless emphasis than ocean-going shipping and other inland transportation systems and partly because of overcompetition due to excessive ship tonnage. Therefore, estimating and planning optimum ship tonnage is the first take to develop Korean coastal shipping. This paper aims to estimate the optimum coastal ship tonnage by computer simulation and finally to draw up plans for the ship tonnage balance according to supply and demand. The estimation of the optimum ship tonnage is peformed by the method of Origin -Destimation and time series analysis. The result are as follows : (1) The optimum ship tonnage in 1987 was 358, 680 DWT, which is 54% of the current ship tonnage (481 ships, 662, 664DWT) that is equal to the optimum ship tonnage in 1998. this overcapacity result is in excessive competition and financial difficulties in Korea coastal shipping. (2) The excessive ship tonnage can be broken down into ship types as follows : oil carrier 250, 926 DWT(350%), cement carrier 9, 977 DWT(119%), iron material/machinery carrier 25, 665 DWT(117%), general cargo carrier 17, 416DWT(112%). (3) the current total ship crew of 5, 079 is more than the verified optimally efficient figure of 3, 808 by 1271. (4) From the viewpoint of management strategy, it is necessary that excessive ship tonnage be reduced and uneconomic outdated vessels be broken up. And its found that the diversion into economically efficient fleets is urgently required in order to meet increasing annual rate in the amounts of cargo(23, 877DWT). (5) The plans for the ship tonnage balance according to supply and demand are as follows 1) The establishment of a legislative system for the arrangement of ship tonnage. This would involve; (a) The announcement of an optimum tonnage which guides the licensing of cargo vessels and ship tonnage supply. (b) The establishment of an organization that substantially arrangement tonnage in Korea coastal shipping. 2) The announcement of an optimum ship tonnage both per year and short-term that guides current tonnage supply plans. 3) The settlement of elastic tariffs resulting in the protect6ion of coastal shipping's share from other tonnage supply plans. 4) The settlement of elastic tariffs resulting in the protection of coastal shipping's share from other transportation systems. 4) Restriction of ocean-going vessels from participating in coastal shipping routes. 5) Business rationalization of coastal shipping company which reduces uneconomic outdated vessels and boosts the national economy. If we are to achieve these ends, the followings are prerequisites; I) Because many non-licensed vessels are actually operating and threatening the safe voyage of the others in Korea coastal routes, it is necessary that those ind of vessels be controlled and punished by the authorities. II) The supply of ship tonnage in Korean coastal routes should be predently monitored because most of the coastal vessels are to small to be diverted into ocean-going routes in case of excessive supply. III) Every ship type which is engaged in coastal shipping should be specialized according to the characteristics of its routes as soon possible.

• Cartoon and Animation Studies
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• s.20
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• pp.75-86
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• 2010

Recently, as the number of female players has increased rapidly, the electronic gaming industry has begun to look at ways to appeal to the largely untapped female market. According to the latest game market investigative report by China Internet Network Information Center (CNNIC), the total number of game players in China increased by 24.8% in 2009, reached 69,130,000 people, and 38.9% of them are female players. This growth in the number of female player is corroborated by a series of investigative reports from IResearch Company in Shanghai, China: from 2003 to 2009, the number of female players grew from 8% to more than 49%. Therefore, no matter how much attention the game production companies have given to male players or how they have ignored the female players before, the companies would be sensible to face up this reality and adjust their marketing policy a bit more. This article analyzes gender preferences in video games which shows that male players are more likely to be attracted to elements of aggression, violence, competition and fast action in electronic game-playing, while female players are drawn to emotional and social aspects of the games such as an understanding of character relationships. The literatures cited indicates that female players also show apparent preference for games with familiar environments, games that allow players to work together, games that have more than one way to win, and games in which characters do not die. It also discusses the characteristics of female-friendly games from the aspect of emotion, pointing out that the simulation games involving pet, dressing-up, and social simulation games are very popular with female players. Because these are the most suitable game types to fill with emotions of love, share, jealousy, superiority, mystery, these are absolutely attractive to female players. Finally, in accord with the above, I propose some principles of designing female-oriented games, including presenting a good-looking leading character, making the story interesting with "live" NPCs(Non-Playing Characters), and finding ways to satisfy female nature instincts such as taking care of others and the inborn interest of classifying and selecting.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.213-225
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• 2010

Data mining has empowered the managers who are charge of the tasks in their company to present personalized and differentiated marketing programs to their customers with the rapid growth of information technology. Most studies on customer' response have focused on predicting whether they would respond or not for their marketing promotion as marketing managers have been eager to identify who would respond to their marketing promotion. So many studies utilizing data mining have tried to resolve the binary decision problems such as bankruptcy prediction, network intrusion detection, and fraud detection in credit card usages. The prediction of customer's response has been studied with similar methods mentioned above because the prediction of customer's response is a kind of dichotomous decision problem. In addition, a number of competitive data mining techniques such as neural networks, SVM(support vector machine), decision trees, logit, and genetic algorithms have been applied to the prediction of customer's response for marketing promotion. The marketing managers also have tried to classify their customers with quantitative measures such as recency, frequency, and monetary acquired from their transaction database. The measures mean that their customers came to purchase in recent or old days, how frequent in a period, and how much they spent once. Using segmented customers we proposed an approach that could enable to differentiate customers in the same rating among the segmented customers. Our approach employed support vector regression to forecast the purchase amount of customers for each customer rating. Our study used the sample that included 41,924 customers extracted from DMEF04 Data Set, who purchased at least once in the last two years. We classified customers from first rating to fifth rating based on the purchase amount after giving a marketing promotion. Here, we divided customers into first rating who has a large amount of purchase and fifth rating who are non-respondents for the promotion. Our proposed model forecasted the purchase amount of the customers in the same rating and the marketing managers could make a differentiated and personalized marketing program for each customer even though they were belong to the same rating. In addition, we proposed more efficient learning method by separating the learning samples. We employed two learning methods to compare the performance of proposed learning method with general learning method for SVRs. LMW (Learning Method using Whole data for purchasing customers) is a general learning method for forecasting the purchase amount of customers. And we proposed a method, LMS (Learning Method using Separated data for classification purchasing customers), that makes four different SVR models for each class of customers. To evaluate the performance of models, we calculated MAE (Mean Absolute Error) and MAPE (Mean Absolute Percent Error) for each model to predict the purchase amount of customers. In LMW, the overall performance was 0.670 MAPE and the best performance showed 0.327 MAPE. Generally, the performances of the proposed LMS model were analyzed as more superior compared to the performance of the LMW model. In LMS, we found that the best performance was 0.275 MAPE. The performance of LMS was higher than LMW in each class of customers. After comparing the performance of our proposed method LMS to LMW, our proposed model had more significant performance for forecasting the purchase amount of customers in each class. In addition, our approach will be useful for marketing managers when they need to customers for their promotion. Even if customers were belonging to same class, marketing managers could offer customers a differentiated and personalized marketing promotion.

• Management & Information Systems Review
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• v.31 no.3
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• pp.223-248
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• 2012

This study analyses support policy and structural change of textile industry in Daegu Kyungbuk region, and suggests major issues for textile industry's innovation. In Daegu Kyungbuk, it was 1999 that a policy, so called Milano Project, in order to promote a textile industry was devised. In 2004, the Regional Industrial Promotion Plan was devised. The plan was born from a view point of establishing a regional innovation system and of promoting the innovative clusters under a knowledge based economy. After then, the Regional Industry Promotion Project or Regional Strategic Industry Promotion Project became a core of regional textile industrial policy. Research results indicated that the first stage Milano project (1999-2003) showed both positive and negative effects. There were no long-term development plan, clear vision and strategy. But, core industrial infrastructure for differentiated product development, such as New product Development Support Center and Dyeing Design Practical Application Center, was constructed. The second stage Daegu Textile Industry Promotion Plan (2004-2008) displayed a significant technological performance and new product sales with the assistance of Kyungbuk province. Also, textile industry revealed positive fruits such as financial structure, productivity, and profitability as a result of strong restructuring. In industrial structure, there was a important change from clothe textile material to industry textile material. Most of textile companies did not showed high capability in CEO's technology innovation intention, entrepreneurship, R&D and human resource competency in compare with other industry. We suggested that Daegu Kyungbuk has to select and concentrate on the high-tech textile material and living textile for sustainable development and competitiveness. We also proposed a confidence and cooperation based innovation network and company oriented innovation cluster.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.101-116
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• 2015

Recently, due to the development of smart devices and social media, vast amounts of information with the various forms were accumulated. Particularly, considerable research efforts are being directed towards analyzing unstructured big data to resolve various social problems. Accordingly, focus of data-driven decision-making is being moved from structured data analysis to unstructured one. Also, in the field of recommendation system, which is the typical area of data-driven decision-making, the need of using unstructured data has been steadily increased to improve system performance. Approaches to improve the performance of recommendation systems can be found in two aspects- improving algorithms and acquiring useful data with high quality. Traditionally, most efforts to improve the performance of recommendation system were made by the former approach, while the latter approach has not attracted much attention relatively. In this sense, efforts to utilize unstructured data from variable sources are very timely and necessary. Particularly, as the interests of users are directly connected with their needs, identifying the interests of the user through unstructured big data analysis can be a crew for improving performance of recommendation systems. In this sense, this study proposes the methodology of improving recommendation system by measuring interests of the user. Specially, this study proposes the method to quantify interests of the user by analyzing user's internet usage patterns, and to predict user's repurchase based upon the discovered preferences. There are two important modules in this study. The first module predicts repurchase probability of each category through analyzing users' purchase history. We include the first module to our research scope for comparing the accuracy of traditional purchase-based prediction model to our new model presented in the second module. This procedure extracts purchase history of users. The core part of our methodology is in the second module. This module extracts users' interests by analyzing news articles the users have read. The second module constructs a correspondence matrix between topics and news articles by performing topic modeling on real world news articles. And then, the module analyzes users' news access patterns and then constructs a correspondence matrix between articles and users. After that, by merging the results of the previous processes in the second module, we can obtain a correspondence matrix between users and topics. This matrix describes users' interests in a structured manner. Finally, by using the matrix, the second module builds a model for predicting repurchase probability of each category. In this paper, we also provide experimental results of our performance evaluation. The outline of data used our experiments is as follows. We acquired web transaction data of 5,000 panels from a company that is specialized to analyzing ranks of internet sites. At first we extracted 15,000 URLs of news articles published from July 2012 to June 2013 from the original data and we crawled main contents of the news articles. After that we selected 2,615 users who have read at least one of the extracted news articles. Among the 2,615 users, we discovered that the number of target users who purchase at least one items from our target shopping mall 'G' is 359. In the experiments, we analyzed purchase history and news access records of the 359 internet users. From the performance evaluation, we found that our prediction model using both users' interests and purchase history outperforms a prediction model using only users' purchase history from a view point of misclassification ratio. In detail, our model outperformed the traditional one in appliance, beauty, computer, culture, digital, fashion, and sports categories when artificial neural network based models were used. Similarly, our model outperformed the traditional one in beauty, computer, digital, fashion, food, and furniture categories when decision tree based models were used although the improvement is very small.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.29-56
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• 2021

Recently, various types of products have been launched with the rapid growth of the e-commerce market. As a result, many users face information overload problems, which is time-consuming in the purchasing decision-making process. Therefore, the importance of a personalized recommendation service that can provide customized products and services to users is emerging. For example, global companies such as Netflix, Amazon, and Google have introduced personalized recommendation services to support users' purchasing decisions. Accordingly, the user's information search cost can reduce which can positively affect the company's sales increase. The existing personalized recommendation service research applied Collaborative Filtering (CF) technique predicts user preference mainly use quantified information. However, the recommendation performance may have decreased if only use quantitative information. To improve the problems of such existing studies, many studies using reviews to enhance recommendation performance. However, reviews contain factors that hinder purchasing decisions, such as advertising content, false comments, meaningless or irrelevant content. When providing recommendation service uses a review that includes these factors can lead to decrease recommendation performance. Therefore, we proposed a novel recommendation methodology through CNN-based review usefulness score prediction to improve these problems. The results show that the proposed methodology has better prediction performance than the recommendation method considering all existing preference ratings. In addition, the results suggest that can enhance the performance of traditional CF when the information on review usefulness reflects in the personalized recommendation service.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.275-285
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• 2021

COVID-19 is threatening the safety of ships and seafarers by delaying seafarer rotation. Shipping companies and governments have a blindspot in case of the onboard environment of seafarers. An effective, alternative plan should be devised to eliminate the possibility of human accidents in an emergency that threatens the safety of seafarers. According to the survey of former and current seafarers, the most important factor in boarding life was safety, and the most necessary thing during emergencies was to secure smooth seafarer rotation rather than improve wages and welfare. By analyzing the major routes of national shipping companies by continent, ports with a large number of calls and a high Air Connectivity Index were selected as the base port. In addition, the route was designed for effective, domestic seafarer rotation during international shipping. Other countries must be consulted to establish a travel route linking ships, ports, and airports for the safe return of sailors to their home countries during an emergency. In addition, it is necessary to work together for the seafarers who are in trouble of seafarer rotation through cooperation with the International Maritime Organization(IMO). Starting with this, the government should have a monitoring system for the return and non-return routes as well as the number of seafarers on board. If such a system is established, it will be able to determine the response direction of our country's policy in case of an emergency. Along with the shipping company's ef orts to improve the treatment of seafarers, national and social attention will be needed to review domestic laws and improve awareness about seafarers.

• Journal of the International Relations & Interdisciplinary Education
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• v.3 no.1
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• pp.1-28
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• 2023

This study was conducted to examine the quantitative trend of domestic studies in invention gifted education, identify the intrinsic meaning and connection attributes in these research analysis, and provide basic data to explore future development plans. To this end, 97 domestic academic papers were finally selected as "Invention Gifted Education" by the Korea Research and Information Service (RISS), technical statistical analysis was conducted with SPSS on publication year, author composition, researcher's affiliation and location area, and published journal. The trend, which had been on the rise since 2007, confirmed by academic papers on gifted education in invention, peaked at the time of the 3rd comprehensive plan for gifted education and has since declined again. As a result of technical statistical analysis of the author's characteristics, half of the papers were jointly published, followed by a number of independent authors. The papers published alone were identified as belonging to universities, research institutes, elementary schools, and middle schools, and the cooperative papers were many studies cooperated with young researchers and professional researchers, and only one collaborative study was conducted between young researchers. When looking at the regions and journals in which the Invention Gifted Education thesis was published, it was concentrated in some regions or journals, and the deviation was very large. As a result of language network analysis using academic paper keywords, creativity and programs were identified as meaningful keywords that showed top appearance, and the keyword pair with high co-appearance was invention gifted-creativity. The keyword of connection-centeredness at the top served as an intermediary for creativity, problem-solving, development, and company to expand to other research topics, and served as a research topic that could be expanded to various topics. In the case of mediation-centeredness, creativity, programs, and effects showed high mediation-centeredness, indicating that it is an important keyword that plays a role in mediating or mediating other keywords. Through these research results, national policy measures need to be prepared for the development of gifted education, and the need to create an invention ecological culture that can enhance teachers' expertise while increasing social responsibility for gifted education.

• Journal of the Korean Society of Food Culture
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• v.24 no.3
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• pp.331-337
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• 2009

The principal objective of the present study was to survey the demands of an education program for evaluations of the efficacy of health functional foods. A questionnaire was developed and sent to 2,225 members of the Biofood Network Center. A total of 101 (4.6%) individuals responded, 54.5% of the respondents were male and 45.5% were female; the respondents' occupations (in order of prevalence) were as follows: company worker (48.5%)>researcher (27.7%)>student (13.9%)>professor (5.0%)>pharmacist (2%), and dietitian (2%). The businesses in which the respondents worked were (again in order of prevalence) as follows: research & development (64.4%)>marketing (11.9%)>consultation and education (5.9%)>manufacturing and others (17.9%). 41.6% of the respondents reported experience in businesses relevant to KFDA approval for functional ingredients and health functional foods. The results showed that 63.4% of the respondents had previously been educated about functional foods; the types of education program reported were (in order of prevalence): 'overview and acts of health functional food' (n=49)>'standards and specification for health functional food' (n=41)>'efficacy evaluation-human study' (n=24)>'safety evaluation' (n=21)>'efficacy evaluation-in vivo study' (n=13)>and 'others' (n=10). Respondents preferred off-line education programs (62.4%) to on-line programs (22.8%). The preferred duration of an educational program was '$2{\sim}3$ days: total $14{\sim}24$ hours' (30.7%); thus, short-term programs were favored. The primary requirements of a program, from the perspective of the learner, were as follows (scored on a 7-point scale); 'efficacy evaluation and case study-human study' (5.80 points)>'standards and specification for health functional food' (5.72 points)>safety evaluation' (5.7 points)>'overview and acts of health functional food' (5.67 points) and 'efficacy evaluation methods of health functional food by efficacy (intensive)' (5.67 points). Preference for functionality was as follows; 'body weight & body fat' (21.8%), 'immune function' (18.8%) > 'blood glucose' (10.9%). In summary, the educational demand for 'efficacy evaluation and case study' was highest among the curriculum options provided, and with regard to functionality, 'body weight & body fat', 'immune function' and 'skin care' were considered most important by respondents. These results differed among respondents with different jobs and duties, and this suggests that customized education programs for health functional food should be developed.