• Land and Housing Review
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• v.2 no.3
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• pp.249-258
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• 2011

In order to achieve an efficient urban regeneration of the nation, it is required to determine the extent of decline nation-wide and the declined areas for each district and also to evaluate the potentials of the concerned areas. For this task to be accomplished, a construction of a comprehensive diagnostic system based on spatial information considering diversity and complexity is required. In this study, a total information system architecture for urban regeneration is designed as part of the construction of such a diagnostic system. In order to develop the system, a city and district level unit decline diagnostic indicators has been constructed and a decline diagnostic system has been developed. Also, a scheme to promote the advancement of the system is proposed. The DB construction is based on the city and district level nation-wide and metadata for the concerned level is constructed as well. The system is based on the Open API and designed to be flexible for extension. Also, an RIA-based intuitive UI has been implemented. Main features of the system consist of the management of the indicators, diagnostic analysis (city and district level decline diagnosis), related information, etc. As for methods for the advancement, an information model in consideration of the spation relations of the urban regeneration DB has been designed and application methods of semantic webs. Also, for improvement methods for district unit analytical model, district level analysis models, GIS based spatial analysis platforms and linked utiliation of KOPSS analysis modules are suggested. A use of a total information system for urban regeneration is anticipated to facilitate concerned policy making through the identification of the status of city declines to identify and the understanding of the demands for regeneration.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.634-642
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• 2020

With the proliferation of Internet of Things (IoT) devices, using the Linux operating system in various architectures has increased. Also, security threats against Linux-based IoT devices are increasing, and malware variants based on existing malware are constantly appearing. In this paper, we propose a system where the binary data of a visualized Executable and Linkable Format (ELF) file is applied to Local Binary Pattern (LBP) image processing techniques and a median filter to classify malware in a Convolutional Neural Network (CNN). As a result, the original image showed the highest accuracy and F1-score at 98.77%, and reproducibility also showed the highest score at 98.55%. For the median filter, the highest precision was 99.19%, and the lowest false positive rate was 0.008%. Using the LBP technique confirmed that the overall result was lower than putting the original ELF file through the median filter. When the results of putting the original file through image processing techniques were classified by majority, it was confirmed that the accuracy, precision, F1-score, and false positive rate were better than putting the original file through the median filter. In the future, the proposed system will be used to classify malware families or add other image processing techniques to improve the accuracy of majority vote classification. Or maybe we mean "the use of Linux O/S distributions for various architectures has increased" instead? If not, please rephrase as intended.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.3
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• pp.81-90
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• 2018

Due to the dramatic advancement of IoT (Internet of Things), it is expected that tens of billions of IoT devices will be connected by the year 2024. Furthermore, as IoT technologies evolves, the security management in IoT platforms has become a critical issue. For example, there are interworking problems between heterogeneous IoT platforms caused by differences from communication protocols, security policies, etc. in each platform. In addition, unsecured interworking can cause major security issues including the information leakage. In this paper, in order to solve these problems, a security interworking architecture is proposed and implemented in both FIWARE and oneM2M, which are representative IoT platforms. First, the security architecture of FIWARE is analyzed and implemented, and then the security framework based on OAuth 2.0 is developed on Mobius platform. Finally, in order to validate the proposed security interworking architecture, a LED (Light-Emitting Diode) example, where the LED is controlled by only authorized users, is developed. The proposed architecture can be extended to the diverse IoT platforms and devices.

• The Journal of Society for e-Business Studies
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• v.13 no.2
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• pp.101-115
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• 2008

Recently in the human society, the crime using small arms has increased. Also, many accidents happen because of incomplete management of chemicals and radiation. Accordingly, it is necessary to manage dangerous objects by tracing the position of dangerous objects and rapidly providing the correct information for them. This paper presents a web-based system for real-time monitoring of dangerous objects using RFID in order to overcome the limitations and problems of current dangerous objects management techniques. In this paper, we define the architecture for web-based dangerous objects monitoring system and the scheme for storing information of a dangerous object in the RFID tag. We also implement the web-based monitoring system and present the execution result of the system. The proposed real-time monitoring system is composed of the dangerous objects monitoring server which manages information of dangerous objects and controls them, the dangerous objects monitoring middleware which is mediator between dangerous objects and the server, the RFID reader which reads information of dangerous objects from RFID tags attached to the objects and the database which stores information, status and position of dangerous object. The proposed system manages diverse dangerous objects such as small arms, radiation and harmful chemicals based on the position of them using RFID, so the user can check dangerous objects when they are checked in and checked out and the user can acquire the real-time position information of them through the system. Furthermore, the user can visually monitor dangerous objects through web browser from any where and at any time because the system is web-based system and it provides graphical user interface.

• Korean Journal of Construction Engineering and Management
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• v.10 no.6
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• pp.13-27
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• 2009

Construction companies are trying to apply process management to their business to improve efficiency in business circumstance of high competition and globalization. Since 1990s, construction firms adopted process management to improve internal and external business structure based on process. It however has a few improvement functions. In addition, business support systems for business process efficiency improvement were developed, but separation between business process and IT system occurred because it focused on function-based individual construction and data input/output. To solve this problem, this study proposed business process and IT integration model for supporting user to use business information and system based on visualized business process and improving use of previous business support system. Business efficiency is expected to be improved with this model which based on integration required business condition(stakeholder, business data, functions of business supporting system). This study developved process model, architecture, and BPA of whole construction management business. According to BPA, it analyzed business process stakeholder, detail activities, and input-output data. And also it examined 12 main business supporting system of Korean construction firms. Based on analyzed data, this study developed business process supporting integration model based on business process through PDCA and CRUD analysis.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.1022-1025
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• 2009

USN(Ubiquitous Sensor Network) is a core infrastructure that makes come true the u-life in the ubiquitous society through various services of area such as u-city and u-Health. Therefore, we need to reseach about the domestic standards to establish the core technique of USN. Currently, the status of USN standards is most of technical standard and reseach that are technology for sensor node implementation and a protocol for energy-efficient communication and interlock with existing network. But, Standard and reseach for sensor network, integration management of heterogeneous sensor networks for USN application, sensing data management and USN database structure definition such as application and middleware are weak level. In this paper, we researched for standard development of the domestic sensor network service and relevant standard analysis to configure SWE(Sensor Web Enablement) of OGC(Open Geospatial Consortium) for standarded plattform technoloy in part of the middleware. Also we researched that it's a connection between domestic TTA (Telecommunications Technology Association) standards and SWE Standard. Finally, we researched for standard service plattform architecture on sensor network through analysis on the possibility of applying OGC-based services platform.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.12
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• pp.387-402
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• 2020

Conventional automotive development has mainly focused on ensuring correctness and safety and security has been relatively neglected. However, as the number of automotive hacking cases has increased due to the increased Internet connectivity of automobiles, international organizations such as the United Nations Economic Commission for Europe(UNECE) are preparing cybersecurity regulations to ensure security for automotive development. As with other IT products, automotive cybersecurity regulation also emphasize the concept of "Security by Design", which considers security from the beginning of development. In particular, since automotive development has a long lifecycle and complex supply chain, it is very difficult to change the architecture after development, and thus Security by Design is much more important than existing IT products. The problem, however, is that no specific methodology for Security by Design has been proposed on automotive development process. This paper, therefore, proposes a specific methodology for Security by Design on Automotive development. Through this methodology, automotive manufacturers can simultaneously consider aspects of functional safety, and security in automotive development process, and will also be able to respond to the upcoming certification of UNECE automotive cybersecurity regulations.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.2
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• pp.29-38
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• 2021

The Internet including mobile networks is developing to overcoming the limitation of physical distance and providing or acquiring information from remote locations. However, the systems that use video as primary information require higher bandwidth for recognizing the situation in remote places more accurately through high-quality video as well as lower latency for faster interaction between devices and users. The emergence of the 5th generation mobile network provides features such as high bandwidth and precise location recognition that were not experienced in previous-generation technologies. In addition, the Mobile Edge Computing that minimizes network latency in the mobile network requires a change in the traditional system architecture that was composed of the existing smart device and high availability server system. However, even with 5G and MEC, since there is a limit to overcome the mobile network state fluctuations only by enhancing the network infrastructure, this study proposes a high-definition video streaming system in ultra-low latency based on the SRT protocol that provides Forward Error Correction and Fast Retransmission. The proposed system shows how to deploy software components that are developed in consideration of the nature of 5G and MEC to achieve sub-1 second latency for 4K real-time video streaming. In the last of this paper, we analyze the most significant factor in the entire video transmission process to achieve the lowest possible latency.

• Journal of Korean Society of Forest Science
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• v.112 no.3
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• pp.267-279
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• 2023

This research assessed the feasibility of using high-resolution aerial images and deep learning algorithms for estimating the land-use and land-cover areas at the Approach 3 level, as outlined by the Intergovernmental Panel on Climate Change. The results from different sampling densities of high-resolution (51 cm) aerial images were compared with the land-cover map, provided by the Ministry of Environment, and analyzed to estimate the accuracy of the land-use and land-cover areas. Transfer learning was applied to the VGG16 architecture for the deep learning model, and sampling densities of 4 × 4 km, 2 × 4 km, 2 × 2 km, 1 × 2 km, 1 × 1 km, 500 × 500 m, and 250 × 250 m were used for estimating and evaluating the areas. The overall accuracy and kappa coefficient of the deep learning model were 91.1% and 88.8%, respectively. The F-scores, except for the pasture category, were >90% for all categories, indicating superior accuracy of the model. Chi-square tests of the sampling densities showed no significant difference in the area ratios of the land-cover map provided by the Ministry of Environment among all sampling densities except for 4 × 4 km at a significance level of p = 0.1. As the sampling density increased, the standard error and relative efficiency decreased. The relative standard error decreased to ≤15% for all land-cover categories at 1 × 1 km sampling density. These results indicated that a sampling density more detailed than 1 x 1 km is appropriate for estimating land-cover area at the local level.

• Journal of the Korea Society for Simulation
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• v.32 no.1
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• pp.35-44
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• 2023

In recent, there are many research cases that analyze trends or research trends with text analysis. When collecting documents by searching for keywords in abbreviations for data analysis, it is necessary to disambiguate abbreviations. In many studies, documents are classified by hand-work reading the data one by one to find the data necessary for the study. Most of the studies to disambiguate abbreviations are studies that clarify the meaning of words and use supervised learning. The previous method to disambiguate abbreviation is not suitable for classification studies of documents looking for research data from abbreviation search documents, and related studies are also insufficient. This paper proposes a method of semi-automatically classifying documents collected by abbreviations by going topic modeling with Non-Negative Matrix Factorization, an unsupervised learning method, in the data pre-processing step. To verify the proposed method, papers were collected from academic DB with the abbreviation 'MSA'. The proposed method found 316 papers related to Micro Services Architecture in 1,401 papers. The document classification accuracy of the proposed method was measured at 92.36%. It is expected that the proposed method can reduce the researcher's time and cost due to hand work.