• The Korean Journal of Emergency Medical Services
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• v.6 no.1
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• pp.27-37
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• 2002

The health and medical service attracts more public attention as the economy of Korea is rapidly growing up and the standard of living is elevated. Especially, the interest and demand on the prehospital emergency medical service that consists of the important part of primary medical service that is directly related to the life of patients are gradually increased. However, as compared with other advanced countries such as America in this area, Korea actually fell behind in the utilization of IT (Information Technology) to maximize the efficiency of emergency service system as well as has a problem in the general service system. This study suggested the necessity to introduce EMD (Emergency Medical Dispatch) system that takes a great role as the core part in the prehospital emergency medical service that is not systemized in Korea yet. In addition, this study proposed the implementation model of EMD ASP system using ASP (Application Service Provider) in EMD system to flexibly deal with the change of IT and efficient implementation and integration of information system as well as to significantly reduce cost through wire/wireless high speed Internet network that is politically promoted in Korea on the basis of EMD. The system analysis and design was executed by HIPO (Hierarchy Plus Input Process Output) analysis that was the conceptual design technology for EMD information system modeling based on ASP and DFD (Data Flow Diagram). This study proposed DB table configuration and data schema to implement the application of web browser interface in EMD system through ERD(ER-Diagram) of EMD ASP system. Finally, this study described how to implement and utilize EMD information system. This study aims to facilitate the qualitative development of emergency medical service in the future as suggesting the concrete models for the implementation of high value-added prehospital emergency medical information system as applying ASP concept to EMD system of prehospital emergency medical service area.

• Korean Journal of Health Education and Promotion
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• v.26 no.2
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• pp.1-13
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• 2009

Objectives: This study identified how personal characteristics, family environment, governmental policy for the prevention and cessation of smoking might influence on adolescent smoking. Methods: This study used data from the 2006 Korea Youth Risk Behavior Web-based Survey of 71,404 middle school and high school students, giving a response rate of 90.9%. We selected 61,508 adolescents subjects of the final analysis without missing data on independent variables and dependent variables which are used in this study. This study used $\chi^2$ tests and logistic regression models. Variables were added to the regression model in three groups using a hierarchical approach.Results: Adolescents were significantly more likely to become current smokers if they were boys, were in a higher grade, and had lower academic achievement. Adolescents experiencing stress and depression were associated with increased risk of current smoking. Adolescents with single parents or students of non-living with parents comparing with students of living with parents showed the high possibility of smoking. Lower father's education was associated with increased likelihood of current smoking. Adolescents who were exposed to smoking at home were more likely to smoke. Adolescents without contacting with the antismoking media campaign was associated with increased likelihood of current smoking. Conclusion: Promoting antismoking media campaigns targeted at adolescent is required, and the smoking prevention education which are proper for subjects are required. Proper plans which could decrease the exposure of secondhand smoking should be established.

• Journal of KIISE
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• v.42 no.1
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• pp.54-67
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• 2015

Nowadays, studies on the fusion of Semantic Web technologies are being carried out to promote the interoperability and value of sensor data in an IoT environment. To accomplish this, the semantic translation of sensor data is essential for convergence with service domain knowledge. The existing semantic translation technique, however, involves translating from static metadata into semantic data(RDF), and cannot properly process real-time and large-scale features in an IoT environment. Therefore, in this paper, we propose a technique for translating large-scale streaming sensor data generated in an IoT environment into semantic data, using real-time and parallel processing. In this technique, we define rules for semantic translation and store them in the semantic repository. The sensor data is translated in real-time with parallel processing using these pre-defined rules and an ontology-based semantic model. To improve the performance, we use the Apache Storm, a real-time big data analysis framework for parallel processing. The proposed technique was subjected to performance testing with the AWS observation data of the Meteorological Administration, which are large-scale streaming sensor data for demonstration purposes.

• Journal of Internet Computing and Services
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• v.2 no.2
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• pp.71-93
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• 2001

Commonly to design a database system. a conceptual database has to be designed and then it is transformed into a logical database schema prior to building a target database system. This paper proposes a method which transforms a Temporal Entity-Relationship Model(TERM) into a Temporal Object-Oriented Model(TOOM) to build an efficient database schema. I formalize the time concept in view of object versioning and specify the constraints required during transformation procedure. The proposed transformation method contributes to getting the logical temporal data from the conceptual temporal events Without any loss of semantics, Compared to other approaches of supporting various properties, this approach is more general and efficient because it is the semantically seamless transformation method by using the orthogonality of types of objects, semantics of relationships and constraints over roles.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.43-61
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• 2019

Development of technologies in artificial intelligence has been rapidly increasing with the Fourth Industrial Revolution, and researches related to AI have been actively conducted in a variety of fields such as autonomous vehicles, natural language processing, and robotics. These researches have been focused on solving cognitive problems such as learning and problem solving related to human intelligence from the 1950s. The field of artificial intelligence has achieved more technological advance than ever, due to recent interest in technology and research on various algorithms. The knowledge-based system is a sub-domain of artificial intelligence, and it aims to enable artificial intelligence agents to make decisions by using machine-readable and processible knowledge constructed from complex and informal human knowledge and rules in various fields. A knowledge base is used to optimize information collection, organization, and retrieval, and recently it is used with statistical artificial intelligence such as machine learning. Recently, the purpose of the knowledge base is to express, publish, and share knowledge on the web by describing and connecting web resources such as pages and data. These knowledge bases are used for intelligent processing in various fields of artificial intelligence such as question answering system of the smart speaker. However, building a useful knowledge base is a time-consuming task and still requires a lot of effort of the experts. In recent years, many kinds of research and technologies of knowledge based artificial intelligence use DBpedia that is one of the biggest knowledge base aiming to extract structured content from the various information of Wikipedia. DBpedia contains various information extracted from Wikipedia such as a title, categories, and links, but the most useful knowledge is from infobox of Wikipedia that presents a summary of some unifying aspect created by users. These knowledge are created by the mapping rule between infobox structures and DBpedia ontology schema defined in DBpedia Extraction Framework. In this way, DBpedia can expect high reliability in terms of accuracy of knowledge by using the method of generating knowledge from semi-structured infobox data created by users. However, since only about 50% of all wiki pages contain infobox in Korean Wikipedia, DBpedia has limitations in term of knowledge scalability. This paper proposes a method to extract knowledge from text documents according to the ontology schema using machine learning. In order to demonstrate the appropriateness of this method, we explain a knowledge extraction model according to the DBpedia ontology schema by learning Wikipedia infoboxes. Our knowledge extraction model consists of three steps, document classification as ontology classes, proper sentence classification to extract triples, and value selection and transformation into RDF triple structure. The structure of Wikipedia infobox are defined as infobox templates that provide standardized information across related articles, and DBpedia ontology schema can be mapped these infobox templates. Based on these mapping relations, we classify the input document according to infobox categories which means ontology classes. After determining the classification of the input document, we classify the appropriate sentence according to attributes belonging to the classification. Finally, we extract knowledge from sentences that are classified as appropriate, and we convert knowledge into a form of triples. In order to train models, we generated training data set from Wikipedia dump using a method to add BIO tags to sentences, so we trained about 200 classes and about 2,500 relations for extracting knowledge. Furthermore, we evaluated comparative experiments of CRF and Bi-LSTM-CRF for the knowledge extraction process. Through this proposed process, it is possible to utilize structured knowledge by extracting knowledge according to the ontology schema from text documents. In addition, this methodology can significantly reduce the effort of the experts to construct instances according to the ontology schema.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.728-739
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• 2020

Using webometric big data, this study examines the diversity of online information sources about the novel coronavirus causing the COVID-19 pandemic. Specifically, it focuses on some 28 countries where confirmed coronavirus cases occurred in February 2020. In the results, the online visibility of Australia, Canada, and Italy was the highest, based on their producing the most relevant information. There was a statistically significant correlation between the hit counts per country and the frequency of visiting the domains that act as information channels. Interestingly, Japan, China, and Singapore, which had a large number of confirmed cases at that time, were providing web data related to the novel coronavirus. Online sources were classified using an N-tuple helix model. The results showed that government agencies were the largest supplier of coronavirus information in cyberspace. Furthermore, the two-mode network technique revealed that media companies, university hospitals, and public healthcare centers had taken a positive attitude towards online circulation of coronavirus research and epidemic prevention information. However, semantic network analysis showed that health, school, home, and public had high centrality values. This means that people were concerned not only about personal prevention rules caused by the coronavirus outbreak, but also about response plans caused by life inconveniences and operational obstacles.

• Journal of the Korea Society of Computer and Information
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• v.9 no.3
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• pp.115-120
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• 2004

As a part of working on development of the learning management system, a adaptive learning management system which is able to provide individual learner with different learning contents or paths customized to learner's learning behaviors by expanding SCORM was proposed in this dissertation. In terms of instructional technology interrelated with technology of CBI and ITS, new learning environments and learner preferences were analyzed. A related laboratory system was implemented by packaging a process on how to expand the meta data for contents and a process on how to utilize the web-based learning contents dynamically. In order to evaluate the usability of the implemented system, a sample content was provided to some selected learners and their learning achievement resulted from the new learning environment was analysed. A result of the experiment indicated that the adaptive learning management system proposed in this dissertation could provide every learner with the different content tailored to their individual learning preference and behavior. and it worked also to promote the learning performance of every learner.

• Journal of Internet Computing and Services
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• v.12 no.2
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• pp.135-147
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• 2011

As the number of elderly people living alone has been increasing in the recent years, systems for their safety have been required, and some related services or pilot systems have been operating. These systems provide the monitoring service for the activities of the elderly people living alone with indoor location tracking technology using the various sensors. However, most systems provide services on expensive infrastructure such as attached tags and mobile devices. In this point, this paper attempts to suggest a system based on low cost sensors to collect event data in home environment. And a main characteristic of the system is that people can monitor the results of provided services through web browser in real time and the system can provide related context information to guardians and health care managers through SMS of mobile phone.

• The Journal of the Korea Contents Association
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• v.12 no.2
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• pp.19-29
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• 2012

Currently, cloud computing technology is being supplied in various service forms and it is becoming a ground breaking service which provides usage of storage service, data and software while user is not involved in technical background such as physical location of service or system environment. cloud computing technology has advantages that it can use easily as many IT resources as it wants freely regardless of hardware issues required by a variety of systems and service level required by infrastructure. Also, since it has a strength that it can choose usage of resource about business model due to various internet-based technologies, provisioning technology and virtualization technology are being paid attention as main technologies. These technologies are ones of important technology elements which help web-based users approach freely and install according to user environment. Therefore, this thesis introduces software-related technologies and architectures in an aspect of grid for building up high availability cloud computing environment by analysis about cloud computing technology trend.

• Archives of design research
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• v.15 no.3
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• pp.271-280
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• 2002

These days information technology and internet have made startling progress. In these developing environments, the strategy or marketing based on existing off-line is getting more difficult to accomplish the role of the improvement of business competitive power, and they are bringing out a lot of changes in information management and marketing performance method about consumers due to digital networking between companies and consumers. These developments and changes make many varieties in the way of design studying methodology. Therefore, in this study, considering the aspects of design, society and environment, after I developed the consumer response framework about products design which is argued by Bloch(1995) ; distinct relationship model among preference degree- design image adjective - design factors, we established design information abstraction solution combined with the interaction based on IT as eCRM in real time. This suggested solutions will provide product designers with good information in finding the design factors which consumers prefer.