• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.1-17
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• 2015

In this paper, we report what we have observed with regards to a prediction model for the military based on enlisted men's internal(cumulative records) and external data(SNS data). This work is significant in the military's efforts to supervise them. In spite of their effort, many commanders have failed to prevent accidents by their subordinates. One of the important duties of officers' work is to take care of their subordinates in prevention unexpected accidents. However, it is hard to prevent accidents so we must attempt to determine a proper method. Our motivation for presenting this paper is to mate it possible to predict accidents using enlisted men's internal and external data. The biggest issue facing the military is the occurrence of accidents by enlisted men related to maladjustment and the relaxation of military discipline. The core method of preventing accidents by soldiers is to identify problems and manage them quickly. Commanders predict accidents by interviewing their soldiers and observing their surroundings. It requires considerable time and effort and results in a significant difference depending on the capabilities of the commanders. In this paper, we seek to predict accidents with objective data which can easily be obtained. Recently, records of enlisted men as well as SNS communication between commanders and soldiers, make it possible to predict and prevent accidents. This paper concerns the application of data mining to identify their interests, predict accidents and make use of internal and external data (SNS). We propose both a topic analysis and decision tree method. The study is conducted in two steps. First, topic analysis is conducted through the SNS of enlisted men. Second, the decision tree method is used to analyze the internal data with the results of the first analysis. The dependent variable for these analysis is the presence of any accidents. In order to analyze their SNS, we require tools such as text mining and topic analysis. We used SAS Enterprise Miner 12.1, which provides a text miner module. Our approach for finding their interests is composed of three main phases; collecting, topic analysis, and converting topic analysis results into points for using independent variables. In the first phase, we collect enlisted men's SNS data by commender's ID. After gathering unstructured SNS data, the topic analysis phase extracts issues from them. For simplicity, 5 topics(vacation, friends, stress, training, and sports) are extracted from 20,000 articles. In the third phase, using these 5 topics, we quantify them as personal points. After quantifying their topic, we include these results in independent variables which are composed of 15 internal data sets. Then, we make two decision trees. The first tree is composed of their internal data only. The second tree is composed of their external data(SNS) as well as their internal data. After that, we compare the results of misclassification from SAS E-miner. The first model's misclassification is 12.1%. On the other hand, second model's misclassification is 7.8%. This method predicts accidents with an accuracy of approximately 92%. The gap of the two models is 4.3%. Finally, we test if the difference between them is meaningful or not, using the McNemar test. The result of test is considered relevant.(p-value : 0.0003) This study has two limitations. First, the results of the experiments cannot be generalized, mainly because the experiment is limited to a small number of enlisted men's data. Additionally, various independent variables used in the decision tree model are used as categorical variables instead of continuous variables. So it suffers a loss of information. In spite of extensive efforts to provide prediction models for the military, commanders' predictions are accurate only when they have sufficient data about their subordinates. Our proposed methodology can provide support to decision-making in the military. This study is expected to contribute to the prevention of accidents in the military based on scientific analysis of enlisted men and proper management of them.

• Journal of Digital Convergence
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• v.15 no.1
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• pp.61-67
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• 2017

In order to establish and operate a rapid and effective disaster safety management system in an emergency situation that threatens the safety of citizens, such as disaster, accident or terrorism, appropriate responses are necessary. An integrated task execution system for rapid response and restoration should be implemented not only by the central ministries related to disaster management and response, but also by local governments, NGO, and individuals, under clear role sharing. In the case of Seoul city, it is urgent to establish an effective disaster management system for preventing and responding to disasters, because of the increasing possibility of natural disasters due to climate change, the threat of terrorism, urban decay and the industrial accidents. From the perspective of governance, this study tried to seek out countermeasures such as disaster response system and command system at disaster site centering on Seoul city government interdepartmental organization system, implementation process and systematization of response procedures.

• Journal of the Korea Convergence Society
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• v.7 no.6
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• pp.29-34
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• 2016

Nowadays, real-time devices that provide health care for a companion animal is being developed by IoT technology and its demand such as smart puppy tag is increasing. However, it is difficult for IoT devices of companion animals to process complex nature due to miniaturized hardware and constructive nature. There is a clear limit to custom advanced features like health care implementation. This paper designs an integrated platform with statistical analysis which makes it possible to customized services such as feed production, pharmaceutical production, and health care for each companion animal. Middleware that collects sensor information, customer's spending pattern and information from Social Network Service is also designed by making use of IoT devices which companion animals wear. Furthermore, the paper designed data analyzer which analyzes and refines data from collected information that can be applied to personalized services.

• Journal of the Korea Convergence Society
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• v.7 no.2
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• pp.19-24
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• 2016

On a huge space of information called the Internet, users can use a smart mobile web to get information on various intellectual fields and can access to various Medias such as personal blogs and social networking sites (SNS). This is why a vast amount of information on the web has been effectively managed and researched nowadays through a technology named Semantic Web. However, it still needs for an improvement for studies on searching for intellectual information, though it is enhanced to integrate variously spread information and search for intellectual information user-oriented. Thus, this study aims to research on searching information and knowledge spread around a knowledge-filled information space, which can improve credibility according to user-oriented logic.

• Journal of the Korean Society for Railway
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• v.18 no.4
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• pp.317-324
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• 2015

A super speed maglev is a complicated system integrating electric, electronic, mechanic, civil and construction engineering. So, there must be an integrative system to monitor and manage operation requirements and standard features of each subsystem and the interfaces between each technology. As an indispensable part that can ensure whole system performance, a secure interface for each individual subsystem is an important management item of system engineering. By securing the interface performance of each individual subsystem, system failure can be effectively prevented in advance. Based on system engineering techniques, improvement of security and reliability for a super speed maglev is described in this research.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.1
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• pp.47-62
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• 2012

To propagate clinical disease management service, there should be built a ecosystem where service developers, service providers, device suppliers closely cooperate for u-Health platform. However, most u-Health platform is difficult to build an effective ecosystem due to the lack of secure and effective PHR(Personal Health Record) management, the lack of personalized and intelligent service, difficulties of N-screen service. To solve these problems we suggest the CDMP(Chronic Disease Management Platform) architecture. The CDMP is a software platform that provides the core functions to develop the chronic disease management services and performs a hub function for the link and integration rbetween various services and systems. CDMP is SOA based platform that enables a provision of reusability, expansibility and it provides open API where everybody can share information, contents and services easily. CDMP supports the multi platform system foN-screen service and the self management functions via SNS. In this paper, we design and implement the CDMP including PHR service based on hybrid data model for privacy preservation. Experiment results prove the effectiveness of hybrid model-based PHR service.

• Trans-
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• v.16
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• pp.1-31
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• 2024

The advent of digital media has facilitated easy access for adolescents to environments conducive to the purchase of narcotics. In particular, there's an increasing trend in the purchase and consumption of narcotics mediated through Social Network Services (SNS) and messenger services. Adolescents, sensitive to such environments, are at risk of experiencing neurological and mental health issues due to narcotic addiction, increasing their exposure to criminal activities, hence necessitating national-level management and support. Consequently, the quest for sustainable treatment methods for adolescents exposed to narcotics emerges as a critical challenge. In the context of high relapse rates in narcotic addiction, the necessity for cost-effective and user-friendly treatment programs is emphasized. This study conducts a literature review aimed at utilizing digital platforms to create an environment where adolescents can voluntarily participate, focusing on the development of therapeutic content through art. Specifically, it reviews societal perceptions and treatment statuses of adolescent drug addiction, analyzes the impact of narcotic addiction on adolescent brain activity and cognitive function degradation, and explores approaches for developing digital therapeutics to promote the rehabilitation of the addicted brain through analysis of precedential case studies. Moreover, the study investigates the benefits that the integration of digital therapeutic approaches and art therapy can provide in the treatment process and proposes the possibility of enhancing therapeutic effects through various treatment programs such as drama therapy, music therapy, and art therapy. The application of art therapy methods is anticipated to offer positive effects in terms of tool expansion, diversification of expression, data acquisition, and motivation. Through such approaches, an enhancement in the effectiveness of treatments for adolescent narcotic addiction is anticipated. Overall, this study undertakes foundational research for the development of digital therapeutics and related applications, offering economically viable and sustainable treatment options in consideration of the societal context of adolescent narcotic addiction.