• Journal of Information Processing Systems
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• v.16 no.4
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• pp.915-934
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• 2020

Software refactoring is a process to restructure an existing software code while keeping its external behavior the same. Currently, various refactoring techniques are being used to develop more readable and less complex codes by improving the non-functional attributes of software. Refactoring can further improve code maintainability by applying various techniques to the source code, which in turn preserves the behavior of code. Refactoring facilitates bug removal and extends the capabilities of the program. In this paper, an exhaustive review is conducted regarding bad smells present in source code, applications of specific refactoring methods to remove that bad smell and its effect on software quality. A total of 68 studies belonging to 32 journals, 31 conferences, and 5 other sources that were published between the years 2001 and 2019 were shortlisted. The studies were analyzed based on of bad smells identified, refactoring techniques used, and their effects on software metrics. We found that "long method", "feature envy", and "data class" bad smells were identified or corrected in the majority of studies. "Feature envy" smell was detected in 36.66% of the total shortlisted studies. Extract class refactoring approach was used in 38.77% of the total studies, followed by the move method and extract method techniques that were used in 34.69% and 30.61% of the total studies, respectively. The effects of refactoring on complexity and coupling metrics of software were also analyzed in the majority of studies, i.e., 29 studies each. Interestingly, the majority of selected studies (41%) used large open source datasets written in Java language instead of proprietary software. At the end, this study provides future guidelines for conducting research in the field of code refactoring.

• The Journal of the Korea Contents Association
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• v.9 no.9
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• pp.90-96
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• 2009

The aim of the research is that disease database of the glycosuria and heart's blood is designed to manage the condition of the glycosuria and heart's blood patients periodically and continuously. Also we integrate patient database of existing OCS, PACS, EMR, ERP etc. and support optimal service timely that the patients want through intelligent integrated interface environment. For this, we will develop customized medical information convergence system. We construct intelligent database for disease of the glycosuria and heart's blood. And we support data integration environment for connection with existing systems - OCS, EMR, PACS etc. Also, in consideration of QoS, reliability, and expandability of customized medical information convergence system, we will design H/W, S/W, and data compatibility method.

• Journal of Intelligence and Information Systems
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• v.13 no.4
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• pp.91-104
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• 2007

Ontology matching technique is one of the most important techniques in the Semantic Web as well as in other areas. Ontology matching algorithm takes two ontologies as input, and finds out the matching relations between the two ontologies by using some parameters in the matching process. Ontology matching is very useful in various areas such as the integration of large-scale ontologies, the implementation of intelligent unified search, and the share of domain knowledge for various applications. In general cases, the performance of ontology matching is estimated by measuring the matching results such as precision and recall regardless of the requirements that came from the matching environment. Therefore, most research focuses on controlling parameters for the optimization of precision and recall separately. In this paper, we focused on the harmony of precision and recall rather than independent performance of each. The purpose of this paper is to propose a methodology that determines parameters for the desired ratio of precision and recall that is appropriate for the requirements of the matching environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.773-776
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• 2009

Last of the car industry can be grouped in one-vehicle electronic equipment, the development of the network, and accordingly the communication between each of the network is important. The network currently being used in vehicles include CAN, LIN, MOST, FlexRay, etc. are used. Network of several different kinds of applications using the federation said they were also germ, which causes the driver some more convenient environment, the desire to drive a vehicle that is increasing. If vehicle for other network environments with one integrated environment to make it a gateway for research done actively, the more applications are expected to be developed. In this paper, using gateway between CAN bus used for Body Train-side control of the vehicle network and MOST provided for infotainment systems. In vehicle automatic safety control system will be designed by One of CAN Nodes car speed information sending to MOST Navigation while don't received GPS information in the tunnel.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.138-145
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• 2018

In the field of optimization, many studies have been performed on various types of Vehicle Routing Problem (VRP) for a long time. A variety of models have been derived to extend the basic VRP model, to consider multiple truck terminal, multiple pickup and delivery, and time windows characteristics. A lot of research has been performed to find better solutions in a reasonable time for these models with heuristic approaches. In this paper, by considering realtime traffic characteristics in Map Navigation environment, we proposed a method to manage realistic optimal path allocation for the logistics trucks and cargoes, which are dispersed, in order to realize the realistic cargo mixing allowance and time constraint enforcement which were required as the most important points for an online logistics brokerage service company. Then we developed a prototype system that can support above functionality together with delivery status monitoring on Map Navigation environment. First, through Map Navigation system, we derived information such as navigation-based travel time required for logistics allocation scheduling based on multiple terminal multiple pickup and delivery models with time constraints. Especially, the travel time can be actually obtained by using the Map Navigation system by reflecting the road situation and traffic. Second, we made a mathematical model for optimal path allocation using the derived information, and solved it using an optimization solver. Third, we constructed the prototype system to provide the proposed method together with realtime logistics monitoring by arranging the allocation results in the Map Navigation environment.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.539-544
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• 2021

The tactical data link is a military data network to improve the ability to recognize battlefield situations. The ROK military is promoting the tactical data link performance improvement programs. Tactical data link is essential to combine and integrate various platforms, sensor data, and command and control (C2) systems. Therefore, the research on related technical fields is required. However, the tactical data link has not disclosed detailed technical information due to the characteristics of military operation. In this paper, we propose a data-based automated analysis methodology using intellectual property information to understand the technology trend of tactical data link. In this paper, data related to intellectual property is automatically collected and pre-processed, and analyzed in terms of time series. In addition, the current status of each institution of patent technology information was generated, and the process of identifying key-researchers through network analysis was presented with providing results of our approach in this paper.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.4
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• pp.125-136
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• 2011

The vulnerabilities existed in Korean electricity control systems is unexposed because it is being operated in a closed network with superior security. The threat will become greater once the closed network develops into a smart grid environment with superior intelligence. Security will have a greater impact once each household will be connected to the power plant via the smart meter. This research focuses on stable data transfer in harsh external environment and whole-nation coverage network, and suggested standardized and optimized Virtual Private Network (VPN) Gateway architecture to support Power Line Communication (PLC). The functionality and stability of the prototype has been verified with field tests. For implementation of outdoor type VPN device for smart grid, we adopted PLC low voltage remote-meter-net for data communication. Also, IPSec type tunneling and ARIA algorithm based encryption of data collected by PLC low voltage remote meter is transmitted.

• Journal of Information Technology Services
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• v.20 no.6
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• pp.1-16
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• 2021

The health functional food market continues to grow, and according to that trend, the subdivision sales of personalized health functional foods, which have been legally prohibited, will be operated as a special regulatory pilot project. Personalized health functional food recommendations have a variety of personalized indicators to consider, and it is believed that algorithmic methods will be needed to proceed in a customized manner considering all of them. This study aims to contribute to the development of the AI-based health functional food recommendation service by studying factors that affect the use of the AI-based health functional food recommendation service. This paper analyzed the intention of use for AI-based health functional food recommendation service based on the information system success model and Technology Acceptance Model. This study considered information quality factors, service quality factor, and system quality factor as independent variables influencing perceived usefulness, perceived ease of use and trust. For empirical analysis, 406 questionnaires were used and the collected data were performed using AMOS 22.0 and SPSS 22.0. Research has shown that the accuracy, timeliness, empathy and availability have a positive effect on usefulness. Understandability and availability has been shown to have a positive effect on ease of use. The accuracy, understandability, empathy and availibility has been shown to have a positive impact on Trust. Usefulness, ease of use and trust all have been shown to have a positive influence on intention of use.

• Journal of the Korea Safety Management & Science
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• v.24 no.1
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• pp.31-38
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• 2022

The most common symptoms of COVID-19 are high fever, cough, headache, and fever. These symptoms may vary from person to person, but checking for "fever" is the government's most basic measure. To confirm this, many facilities use thermographic cameras. Since the previously developed thermographic camera measures body temperature one by one, it takes a lot of time to measure body temperature in places where many people enter and exit, such as multi-use facilities. In order to prevent malfunctions and errors and to prevent sensitive personal information collection, this research team attempted to develop a facial recognition thermographic camera. The purpose of this study is to compensate for the shortcomings of existing thermographic cameras with disaster safety IoT integrated solution products and to provide quarantine systems using advanced facial recognition technologies. In addition, the captured image information should be protected as personal sensitive information, and a recent leak to China occurred. In order to prevent another case of personal information leakage, it is urgent to develop a thermographic camera that reflects this part. The thermal imaging camera system based on facial recognition technology developed in this study received two patents and one application as of January 2022. In the COVID-19 infectious disease disaster, 'quarantine' is an essential element that must be done at the preventive stage. Therefore, we hope that this development will be useful in the quarantine management field.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.225-232
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• 2022

The purpose of this study was to analyze the effect of offline leisure activities and online leisure activities on depressive symptoms in the COVID-19 endemic. To do this, this study proposed a theoretical model consisting of demographic characteristics such as gender, age, academic background, and monthly income, offline leisure activity types such as socially-oriented activities, online leisure activity types such as information searching activities, entertainment activities, and the level of depressive symptoms. A survey was conducted to confirm research hypotheses, and a total of 99 questionnaires were used for statistical analysis. The major results of analysis reveal that first, monthly income is an important factor in predicting the level of depressive symptoms. Second, both offline socially-oriented activities and online entertainment activities have a negative effect on the level of depressive symptoms. This study has implications in that it identified the characteristics of leisure activities that can reduce the level of depressive symptoms.