Journal of Korean Library and Information Science Society
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v.44
no.4
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pp.93-122
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2013
This study purpose to identifying the roles of Health Information Librarian which its role is increasing according to increase recent interest in wellness and health. In other words, this study will present the Education, careen duties and so on, which should be possed by Health Information Librarian, based on the analysis of Job Site. As as result, first, health information professional librarian's name appears very diverse, and consumer health information librarian will be appropriate name for public libraries and medical librarian will be appropriate for medical library and hospital library. Second, education experience required for health information librarian is master's degree of library and information science and bachelor's or more health related degree. Third, at least two years of health-related field experience, particularly health information service experience, is required. Forth, excellent communication skills and interpersonal skills are required, expecially higher knowledge for health-related information resources is required. Fifth, the main duties what health information librarian need to perform, are library management services, training services, research services, access to and sharing of information resources, collection management, information management, information management technology, and advocacy.
Journal of the Korea Institute of Information and Communication Engineering
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v.19
no.3
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pp.607-612
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2015
As the amount of vehicle's diagnostics data increases, the actors in automotive ecosystem will encounter difficulties to perform a real time analysis in order to simulate or to design new services according to the data gathered from the connected cars. In this paper, we have conducted a study of a Big Data solution that expresses the essential deep analytics to process and analyze vast quantities of vehicles on board diagnostics data generated by cars. Hadoop and its ecosystems have been deployed to process a large data and delivered useful outcomes that may be used by actors in automotive ecosystem to deliver new services to car owners. As the Intelligent transport system is involved to guarantee safety, reduce rate of crash and injured in the accident due to speed, addressing big data solution based on vehicle diagnostics data is upcoming to monitor real time outcome from it and making collection of data from several connected cars, facilitating reliable processing and easier storage of data collected.
Since the organization of civil servants has been divided and stratified according to the characteristics of the bureaucracy, it is inevitable that the organization and personnel will increase when new tasks arise. Even in the process of informatization, only the processing method was brought online while leaving the existing business processing procedures as they were, so there was no reduction in manpower through informatization. In order to maintain or upgrade the current administrative services while reducing the number of civil servants, it is inevitable to use AI technology. By using data and AI to integrate the 'powers and responsibilities assigned to the officials in charge', manpower can be reduced, and the reduced costs can be reinvested in the collection, analysis, and utilization of on-site data to further promote intelligent informatization. In this study, as a way for the government's success in intelligent informatization innovation, we proposed a 'Civil Servants-AI Collaboration Platform'. This Platform based on the civil servant proposal system as a reward system and the characteristics of intelligent informatization that are different from the informatization. By establishing a 'Civil Servants-AI Collaboration Platform', the performance evaluation system of the short-term evaluation method by superiors can be improved to a data-driven always-on evaluation method, thereby alleviating the rigid hierarchy of government organizations. In addition, through the operation of Collaboration Platform, it will become common to define and solve problems using data and AI, and the intelligence informatization of government organizations will be activated.
Journal of the Korea Institute of Information Security & Cryptology
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v.34
no.4
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pp.725-734
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2024
The rapidly growing metaverse environment has received widespread attention across various fields such as health and medicine, culture and gaming, as well as politics. However, the excessive collection of personal data by the diverse sensors and devices used in the metaverse environment poses a substantial threat to user privacy. In this paper, we investigate existing cases of secure Multi-Party Computation(MPC) applications, examine the services anticipated to be necessary for the expansion of the metaverse environment, and analyze the privacy issues present in the metaverse environment as well as the limitations of current real-world services. Based on these findings, we propose application scenarios that utilize MPC to preserve user privacy in the metaverse environment. These proposed MPC application scenarios present a new perspective in metaverse security research. In the future, they are expected to be utilized in the development of secure metaverse services.
Occupational health services in Korea have been operated as dual types: one is operated by occupational health care manager and the other is health care agency without their own personnel. The performance of occupational health service should be different due to the variety of characteristics of health care manager and workplace, qualification of health care manager. This study is to analyze performance of occupational health care services with a particular consideration of job, based on comparing those two types of health care management to show on the basic data for the settlement of more qualitative. health care management system at workplace. For this study, total 391 places in Seoul and Inchon city area: 154 places (39.4%) managed by designated. health care manager and 237 places (60.6%) by the agency with their commission are selected as research samples. Tools for data collection are questionnares have been investigated during the period of 20 September 1993-20 December 1993. Those data are compared with percentiles, mean, standard deviation due to the characterstics of each variable and analyzed for impacting factors with relation to the using multiple regression analysis using SPSS PC program, especially using t -test method in order to compare each type of health care management. Conclusions observed from the tests and each comparison could be summerized as follows : 1. Occupational health care have been accomplished at workplaces with designated people than with agencies people, and coverage rate of the occupational health care services has differences, due to management types. The reason of these results is due to visit only one or two times monthly by the agencies, while their own health care manager obsess, at the workplaces all the times. 2. The common sickness management is the most accomplished item in health care area of occupational health care services, while the preventive care and control for the workers who have serious health problems are insufficient in workers health care area. 3. An insufficient accomplishment of overall health education has been shown because it is difficult to perform health education due to almost no chance of the direct introduction at workplaces. Therefore a strong support system for making and supplying the media is necessary in order to activate indirect health education by means of media. 4. Because health care managers and the agencies managers where take the workplaces for this study are almost nurses who have been comparatively high work site rounding rate about an environmental management at the workplaces, that non-profession can also do it, the activities about the professional area not enough. Therefore, an appropriate referral system should be established in order to complement professional area. 5. Two factors which have an effect on the coverage rate of occupational health care services are : one is those from the workplaces such as type of services, the number of workers, the number of harzadous factors and safety & health committee, the other from health care organization about whether there is its own manager or not.
The World Wide Web is transitioning from being a mere collection of documents that contain useful information toward providing a collection of services that perform useful tasks. The emerging Web service technology has been envisioned as the next technological wave and is expected to play an important role in this recent transformation of the Web. By providing interoperable interface standards for application-to-application communication, Web services can be combined with component based software development to promote application interaction and integration both within and across enterprises. To make Web services for service-oriented computing operational, it is important that Web service repositories not only be well-structured but also provide efficient tools for developers to find reusable Web service components that meet their needs. As the potential of Web services for service-oriented computing is being widely recognized, the demand for effective Web service discovery mechanisms is concomitantly growing. A number of techniques for Web service discovery have been proposed, but the discovery challenge has not been satisfactorily addressed. Unfortunately, most existing solutions are either too rudimentary to be useful or too domain dependent to be generalizable. In this paper, we propose a Web service organizing framework that combines clustering techniques with string matching and leverages the semantics of the XML-based service specification in WSDL documents. We believe that this is one of the first attempts at applying data mining techniques in the Web service discovery domain. Our proposed approach has several appealing features : (1) It minimizes the requirement of prior knowledge from both service consumers and publishers; (2) It avoids exploiting domain dependent ontologies; and (3) It is able to visualize the semantic relationships among Web services. We have developed a prototype system based on the proposed framework using an unsupervised artificial neural network and empirically evaluated the proposed approach and tool using real Web service descriptions drawn from operational Web service registries. We report on some preliminary results demonstrating the efficacy of the proposed approach.
Journal of Korean Library and Information Science Society
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v.48
no.3
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pp.63-81
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2017
This study investigated general problems concerning the social welfare field in the KDC 6th edition based comparative analysis academic characteristics and classification system, and suggested on some ideas for the improvements of them. Results of the study are summarized as follows. First, a main field of the social welfare is generally divided into a general social welfare, social works, and social welfare services to special classes and groups including people with disabilities, young people, aged, women, and families. Second, I analyzed on social welfare from the collection database at the National Library of Korea. Based on analysis of the data. the keyword frequency of social welfare policy and management, pensions, care services, and support works for the underprivileged was relatively high. Third, modified classification of items was basically performed through the academic characteristics of the social welfare and the keyword analysis, and maintaining the existing KDC classification system caused less confusion as much as possible.
Because people's interest of the stock market has been increased with the development of economy, a lot of studies have been going to predict fluctuation of stock prices. Latterly many studies have been made using scientific and technological method among the various forecasting method, and also data using for study are becoming diverse. So, in this paper we propose stock prices prediction models using sentiment analysis and machine learning based on news articles and SNS data to improve the accuracy of prediction of stock prices. Stock prices prediction models that we propose are generated through the four-step process that contain data collection, sentiment dictionary construction, sentiment analysis, and machine learning. The data have been collected to target newspapers related to economy in the case of news article and to target twitter in the case of SNS data. Sentiment dictionary was built using news articles among the collected data, and we utilize it to process sentiment analysis. In machine learning phase, we generate prediction models using various techniques of classification and the data that was made through sentiment analysis. After generating prediction models, we conducted 10-fold cross-validation to measure the performance of they. The experimental result showed that accuracy is over 80% in a number of ways and F1 score is closer to 0.8. The result can be seen as significantly enhanced result compared with conventional researches utilizing opinion mining or data mining techniques.
As children's participation in online activities has recently increased, online services for children are also rapidly increasing, but children are not sufficiently guaranteed their rights. The purpose of this study is to classify and analyze issues related to the children's online privacy issues in Korea through the current status and case studies of application services mainly used by children. For this purpose, this research analyzed problems related to the children's online privacy protection according to the stage of using the application. As a result of the application content analysis, 1) issues of child identification, 2) effectiveness of notice and consent, and 3) issues of children's rights as subjects of information were derived. Based on the current status analysis, the policy implications were drawn based on the children's online privacy protection in the online environment, and suggestions were made for improvement.
Journal of the Korea Society of Computer and Information
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v.21
no.8
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pp.57-64
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2016
Initial prevention activities and rapid propagation conditions is the most important to prevent diffusion of water pollution. If water pollutants flow into streams river or main stresm located in environmental conservation area or water intake facilities, we must predict immediately arrival time and the diffusion concentration to the proactive. National Institute of Environmental Research developed water pollution incident response prediction system linking dam and movable weir. the system is mathematical model which is updated daily. Therefore it can quickly predict the arrival time and the diffusion concentration when there are accident of oil spills and hazardous chemicals. Also we equipped with mathematical model and toxicity model of EFDC(Environmental Fluid Dynamics Code) to calculate the arrival time and the diffusion concentration. However these systems offer the services of an offline manner than real-time control services. we have ensured the reliability of data collection and have developed a real-time water quality measurement data transmission device by using the data linkage utilizing a mode bus communication and a commercial SCADA system, in particular, we implemented to be able to do real-time water quality prediction through information infrastructure of the water quality integrated management business created by utilizing the construction of the real-time prediction system that utilizes the data collected, the Open map, the visual representation using charts API and development of integrated management system development based on web maps.
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