• The KIPS Transactions:PartD
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• v.17D no.6
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• pp.453-462
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• 2010

The switch from analog to digital broadcast television is extended rapidly. The DTV can offer multiple programming choices, interactive capabilities and so on. Moreover, with the spread of Internet, the information exchange between the communities is increasing, too. These facts lead to the new TV service environment which can offer customized TV programs to personal/community users. This paper proposes a 'Customized Digital TV System for Individuals/Communities based on Data Stream Mining' which can analyze user's pattern of TV watching behavior. Due to the characteristics of TV program data stream and EPG(electronic program guide), the data stream mining methods are employed in the proposed system. When a user is watching DTV, the proposed system can control the surrounding circumstances as using the user behavior profiles. Furthermore, the channel recommendation system on the smart phone environment is proposed to utilize the profiles widely.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.1010-1014
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• 2010

Article-related product recommender system is an emerging e-commerce service which recommends items based on association in contexts between items and articles. Current services recommend based on the similarity between tags of articles and items, which is deficient not only due to the high cost in manual tagging but also low accuracies in recommendation. As a component of novel article-related item recommender system, we propose a new method for tagging item images based on pre-defined categories. We suggest a hypernetwork-based algorithm for learning association between images, which is represented by visual words, and categories of products. Learned hypernetwork are used to assign multiple tags to unlabeled item images. We show the ability of our method with a product set of real-world online shopping-mall including 1,251 product images with 10 categories. Experimental results not only show that the proposed method has competitive tagging performance compared with other classifiers but also present that the proposed multi-tagging method based on hypernetworks improves the accuracy of tagging.

• 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.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.31 no.2
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• pp.147-155
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• 2021

Objective: The purpose of this study was to find ways for strengthening occupational health services through monitoring exposure to health hazards. Methods: About 70,000 workplaces that have conducted the work environment measurement(WEM) over the last three years(2017~2019) were classified according to the Korean Standard Industry Classification(KSIC), and the current status of WEM by industry was analyzed. The authors considered ways to monitor exposure to health hazards in order to strengthen occupational health services and protect workers' health. Results: Based on the KSIC, 934 of the 1,196 total sub-classified industries have conducted WEM in at least one workplace over the last three year(2017~2019). In the case of manufacturing, out of a total of 477 sub-classified industries, 474 have conducted WEM at more than one workplace. However, in some industries, WEM was not conducted or the implementation rate was low, so it was necessary to examine whether WEM should be expanded based on a detailed analysis of the WEM database. To this end, it is necessary to form an exposure monitoring committee in which various experts from different fields can participate. The committee needs to discuss the overall matters necessary for selecting industries that require detailed investigation or research, review the results, and prepare a final recommendation. Conclusion: In conclusion, the government needs to come up with a plan to strengthen occupational health services through surveys and research on the current status of WEM and work environment management models by industry.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1567-1573
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• 2020

The development of Internet technology has brought the era of one-man media. An individual produces content on user own and uploads it to related online services, and many users watch the content of online services using devices that allow them to use the Internet. Currently, most users find and watch content they want through search functions provided by existing online services. These features are provided based on information entered by the user who uploaded the content. In an environment where content needs to be retrieved based on these limited word data, user unwanted information is presented to users in the search results. To solve this problem, in this paper, the system actively analyzes the video in the online service, and presents a way to extract and reflect the characteristics held by the video. The research was conducted to extract morphemes based on the story content based on the voice data of a video and analyze them with big data technology.

• Journal of Sport and Applied Science
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• v.5 no.2
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• pp.63-71
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• 2021

Purpose: The purpose of this study, we will evaluate and analyze the importance and performance of Seongnam Football Club visitors using IPA analysis to present new marketing strategies and improvement plans based on the basis of the audience's perception of the team's priority, low priority, and excessive effort. Research design, data, and methodology: In order to achieve the purpose of the study, the survey was conducted on 120 home spectators of Seongnam Football Club, and the analysis of the data was conducted using SPSS Window Version 21.0. Data were analyzed via frequency analysis, exploratory factor analysis, corresponding sample t-test, and IPA analysis. Findings are as follows. Results: First, the first quadrant showed 'The convenience of access to the stadium', 'Parking lot convenience', 'Tournament schedule guidance', 'Providing information about player', 'Providing information about the team', 'Ticket reservation method'. Second, the second quadrant showed 'Players' fan service', 'Cleanliness of toilets', 'A player's level of performance', 'Team's level of play', 'A match against a rival team'. Third, the third quadrant showed 'Indication of facility guidance', 'Seat comfort', 'Team's Star Player Possession', 'Various participation events', 'Gift recommendation'. Fourth, the fourth quadrant showed 'Player-related promotion through media', 'Promote match schedules through media', 'Entrance convenience', 'Ticket Price'. Conclusions: Based on these findings, Factor in first quadrant, fourth quadrant should be kept. On the other hand, factors in second quadrant should be improved as soon as possible while factors in third quadrant can be improved through new marketing strategies in the future. Future implications were discussed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.877-883
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• 2021

Artificial intelligence technology is widely used in industrial and smart home fields such as manufacturing robots, artificial intelligence speakers, and robot vacuum cleaners. In this paper, we designed and implemented a 1:1 chatbot system based on artificial intelligence for use in RCMS (Real-time Cash Management System). The RCMS chatbot implemented in this paper was constructed with a total of 210 query scenarios in nine areas, including research expenses and system usage, based on 13,500 questions and answers from existing online bulletin boards. The chatbot is expected to solve the problem of insufficient number of counselors and to increase user satisfaction by responding to the researcher's inquiries after working hours, and the recommendation service for the cost of use, which had the most inquiries from researchers, reduces the number of consultations. It is expected to improve the quality of answers to other counseling inquiries.

• Journal of Korean Clinical Nursing Research
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• v.28 no.2
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• pp.122-136
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• 2022

Purpose: This study attempted to recommend a revision of inpatient nursing fees based on analyzing current and appropriate staffing levels. Methods: Staffing grades and their inpatient nursing fees as of the first quarter of 2022 were analyzed. Nurse managers and staff nurses answered surveys about the current and appropriate staffing levels, working days, and monthly salary. A total of 101 nurse managers and 588 staff nurses working in general wards at tertiary hospitals and general hospitals participated in the study. Results: The results showed that grade 1 staffing was found in 73.3% of tertiary hospitals and 63.7% of general hospitals. The current staffing ratios of tertiary hospitals and general hospitals were 1:9.3 and 1:10.4, respectively. The appropriate staffing ratios according to nurse managers and staff nurses at tertiary hospitals were 1:7.6 and 1:7.0, respectively, and 1:8.7 and 1:8.8 in general hospitals, respectively. The average estimated annual working days of staff nurses were 235.2 days in tertiary hospitals and 240.0 days in general hospitals. The median monthly salary for staff nurses was 4.957 million won in tertiary hospitals and 4.140 million won in general hospitals. The new staffing grade system was suggested from 1:6 (Grade 1) to 1:12 (Grade 5). The new inpatient nursing fee schedules were recommended to be paid based on nursing hours per patient day of each grade. Conclusion: The new staffing grade and inpatient nursing fee schedules are expected to increase staffing levels, improve the quality of nursing care, and provide a better work environment for nurses.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.927-934
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• 2021

AI(Artificial intelligence) is gradually taking up a large part of our lives, and the pace of AI development is accelerating. It is called ACT that develop students' computational thinking in the way artificial intelligence learns. Among ACTs, pattern recognition is an essential factor in efficiently solving problems. Pattern analysis is part of the pattern recognition process. In fact, Netflix's personalized movie recommendation service and what it named Covid-19 after repeated symptoms are all the results of pattern analysis. While the importance of ACT, including pattern recognition, is highlighted, software education for kindergarten and elementary school lower grades is much insufficient compared to foreign countries. Therefore, this study aims to design and develop textbooks for the development of artificial intelligence-based computational thinking through pattern analysis for kindergarten students.

• Journal of Acupuncture Research
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• v.40 no.3
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• pp.238-244
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• 2023

Background: Occipital neuralgia (ON) is an established risk factor for headaches in the posterior cervical region. Several conservative treatments by nerve decompression and pain relief are available for ON, but these treatments have limitations. Acupuncture treatment, which is known to demonstrate analgesic effects, involves various stimulation methods, and several studies have reported their clinical benefit. No recent systematic review (SR) has compared each acupuncture type for ON treatment. Thus, this SR aims to investigate the clinical effectiveness of each acupuncture type for treating ON. Methods: We will identify relevant studies using electronic databases, including EMBASE, MEDLINE, Cochrane Library, China National Knowledge Infrastructure (CNKI), Korean Studies Information Service System (KISS), Korean Medical Database, KoreaMed, and National Digital Science Library (NDSL) from the inception until August 2023. The primary outcome will include the numerical change of pain symptoms (visual analog scale and numerical rating scale) and effective rate. Safety and secondary outcomes will include adverse events and quality of life. We will compare the conservative treatment with the acupuncture treatment using network meta-analysis. The Cochrane Collaboration "risk of bias" tools will be used to assess the quality of included trials. The Grades of Recommendation, Assessment, Development, and Evaluation will be used to examine the evidence level. Conclusion: This study will provide clinical evidence of several acupuncture types for ON and help clinicians decide on the best.