• Journal of the Korean Society of Marine Environment & Safety
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• v.16 no.1
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• pp.49-55
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• 2010

Marine oil spill accidents not only devastates marine ecosystem but also Ins significant adverse socio-economic impact on local community whose living is dependent on clean marine system Although the Marine Environment Management Act of the Republic of Korea stipulates tim marine pollution impact survey must be conducted at the time of the oil spill, the articles do not provide specifics or concrete survey items for socio-economic impact assessment Moreover, there are redundancy questions in the provisions related to socio-economic impact assessment. This paper examined several difficulties encountered in carrying out the socio-economic impact assessment for marine oil spill as required in the law, and presented some recommendation., for the plan to improve the assessment mechanism systematically through the development of the research categories and indicators of socio-economic impact assessment.

• Hwankyungkyoyuk
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• v.19 no.1 s.29
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• pp.30-42
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• 2006

The Ministry of Environment supports environmental education mainly in two ways ; one is by supporting schools engaged in environment conservation model school and the other is by extending grants for experiential environmental education programs. This research aims to evaluate the current status of grant for experiential environmental education programs while proposing possible improvement for constructive and continuing development of the support measures. Grant for experiential environmental education programs is divided into two areas of grant for schools and grant for community-based civil organizations. The diagnosis and evaluation were conducted in terms of 7 areas, such as time, facilities, programs, manpower (professional expertise), operation, administrative and financial support mechanism and others. Research process involved the review of previous studies in 2001 and 2003, comparison of the grant program with other grants in and out of Korea for environment education, and the following areas considered when identifying improvement options: i) Overall review of objectives and operations, ii) expansion supports programs oriented problem solving as well as those focused ecological sensitivity, iii) change from expendable, one-time program to productive, continuous program, iv) link to social changes and issues, v) principles for operation and evaluation, vi) criteria and methods for program selection and evaluation, and vii) improving operation system. Based on review and the overall evaluation on the experiential environmental education program grant, the recommendation for improving operation system were provided, which included stages of passive improvement, active improvement and building infrastructure for environment education, and building capacity of the members related in the initiatives.

• Journal of the Korean Society for Railway
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• v.17 no.6
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• pp.423-432
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• 2014

The purchasing behavior of consumers is related to service quality and corporate social responsibility (CSR). Therefore, CSR is recognized as an important factor in company strategies. This study determines the relationship between the CSR activities of KORAIL and the reuse intention and recommendation intention of the consumer. CSR is composed of economic, legal, philanthropic, ethical, and environmental responsibilities. In the results of the structural equation modeling analyses, legal responsibility and economic reliability affect the reliability of KORAIL and this reliability affects the customers' reliability and loyalty. This paper proposes a compliance program, wagon safety information, customized tour packages, and communication strategy that will increase customer's reliability and loyalty.

• Journal of KIISE:Software and Applications
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• v.31 no.12
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• pp.1672-1683
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• 2004

Recommender system is a kind of web intelligence techniques to make a daily information filtering for people. Researchers have developed collaborative recommenders (social recommenders), content-based recommenders, and some hybrid systems. In this paper, we introduce a new hybrid recommender method - ICHM where clustering techniques have been applied to the item-based collaborative filtering framework. It provides a way to integrate the content information into the collaborative filtering, which contributes to not only reducing the sparsity of data set but also solving the cold start problem. Extensive experiments have been conducted on MovieLense data to analyze the characteristics of our technique. The results show that our approach contributes to the improvement of prediction quality of the item-based collaborative filtering, especially for the cold start problem.

• Smart Media Journal
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• v.6 no.2
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• pp.50-56
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• 2017

Due to new social environment, expenditure on eating out has increased over the last few year, thereafter the food-tech industries have steadily grown as well. We have studied what variable would affect customer's choices when they plan to eat out or order in. There are two variables are taken into account to prove it. Firstly, it is climate changes, such as an amount of rainfall, snowfall and clouds. Secondly, it is days, such as seasons and holidays. Based on this, we looked up the SikSin user's behaviors patterns, then did analysis of the daily data provided by the Meteorological office. By the end of the study, it turned out that two variables, climate changes and days, both have a strong influence on customer's choices. It is considered that this research outcome will make contributions to small businesses founders who want to take the initiative, marketing managers and people who are engaged in the food-tech industry.

• Women's Health Nursing
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• v.17 no.5
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• pp.439-446
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• 2011

Purpose: Early diagnosis is the primary method aimed at controlling breast cancer. The purpose of this study was to analyze some factors affecting the performance of mammography screening among women with a family history of breast cancer in Korea. Methods: This study applied a descriptive design method through structured self-report questionnaires. The Care Seeking Behavior Theory provided a theoretical framework for the study. Factors measured in this study represent demographic, clinical, and psychosocial variables including anxiety, barriers, utility, habits, perception, and facilitators. A total of 212 participants, of at least 20 years old, were sampled from April 8, 2010 to March 31, 2011. The data was analyzed by logistic regression method using the Statistical Package for the Social Science 18.0 software. Results: Of the 212 participants, 122 women (57.5%) went through mammography screening. The results of the analysis showed that (a) age (Odds Ratio [OR] =1.10, p<.001), (b) facilitating influences (OR=1.83, p=.008), (c) perception of mammography importance (OR=1.92, p=.011), (d) barriers to mammography (OR=0.60, p=.031), and (e) utility of mammography (OR=2.01, p=.050) significantly affect mammography screening. Conclusion: The results underscore the impact that psychosocial variables in obtaining mammography have on adherence to screening. Women with a family history of breast cancer should be given accurate information and recommendation about mammography by healthcare provider and a regular source of healthcare.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.730-737
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• 2018

With the increasing number of health consumers aiming for a happy quality of life, the O2O medical marketing market is activated by choosing reliable health care facilities and receiving high quality medical services based on the medical information distributed on web's blog. Because unstructured text data used on the Internet, mobile, and social networks directly or indirectly reflects authors' interests, preferences, and expectations in addition to their expertise, it is difficult to guarantee credibility of medical information. In this study, we propose a blog reading system that provides users with a higher quality medical information service by classifying medical information blogs (medical blog, ad blog) using bigdata and MLP processing. We collect and analyze many domestic medical information blogs on the Internet based on the proposed big data and machine learning technology, and develop a personalized health information recommendation system for each disease. It is expected that the user will be able to maintain his / her health condition by continuously checking his / her health problems and taking the most appropriate measures.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.413-416
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• 2014

Recently, demand for various leisure sports gradually increases, as people's sense of values changes into leisure-centered one according to the change of given social circumstance and the change of customer needs all over the world. The actual condition is that an interest and participation rate especially in water leports during the summer increases. And needs for various hull design of standardized boat for water leisure increase. Therefore, this paper is intended to develop a recommendation system to design a boat for water leisure by using the collaborative filtering technique in order to make it possible to actively cope with the change of various customer needs for hull design. To this end, emotion relating to kayak design was selected through consumer survey, and emotion was derived by factor analysis and assessment, and then a kayak design layout in the aspect of customer's emotional preference was presented. Besides, an analysis was made according to the elements such as hull, body, and propulsion system of kayak in order to select emotional words according to the kayak design reflecting user's preference, and then a boat model for water leisure in conformance with user's preference was presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1321-1329
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• 2019

With the development of social information networks, the marketing methods are also changing in various ways. Unlike successful marketing methods based on existing celebrities and financial support, Influencer-based marketing is a big trend and very famous. In this paper, we first extract influencer features from more than 54 YouTube channels using the multi-dimensional qualitative analysis based on the meta information and comment data analysis of YouTube, model representative themes to maximize a personalized video satisfaction. Plus, the purpose of this study is to provide supplementary means for the successful promotion and marketing by creating and distributing videos of new items by referring to the existing Influencer features. For that we assume all comments of various videos for each channel as each document, TF-IDF (Term Frequency and Inverse Document Frequency) and LDA (Latent Dirichlet Allocation) algorithms are applied to maximize performance of the proposed scheme. Based on the performance evaluation, we proved the proposed scheme is better than other schemes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.89-96
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• 2021

The number of confirmed cases of coronavirus-19 is soaring around the world and has caused numerous deaths. Wearing a mask is very important to prevent infection. Incidents and accidents have occurred due to the recommendation to wear a mask in public places such as buses and subways, and it has emerged as a serious social problem. To solve this problem, this paper proposes an open source-based face mask wearing monitoring system. We used open source software, web-based artificial intelligence tool teachable machine and open source hardware Arduino. It judges whether the mask is worn, and performs commands such as guidance messages and alarms. The learning parameters of the teachable machine were learned with the optimal values of 50 learning times, 32 batch sizes, and 0.001 learning rate, resulting in an accuracy of 1 and a learning error of 0.003. We designed and implemented a mask wearing monitoring system that can perform commands such as guidance messages and alarms by determining whether to wear a mask using a web-based artificial intelligence tool teachable machine and Arduino to prove its validity.