• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.4
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• pp.73-92
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• 2022

This study intends to design a model that can effectively service policy data necessary for the implementation of new national agenda in order to provide high-quality policy information services that go beyond those of the existing Policy Information Portal (POINT) of National Sejong Library. To this end, it was determined that providing an integrated search environment, in lieu of data search through individual access, was necessary. Subsequently, four possible models for a national agenda service model were presented. First, designing a computerized system for both interface and electronic information source aspects was proposed for the national agenda service system operation. Second, designing the Linked Open Data system and the time-series service system for national policy information, providing the translation service of overseas original data, and securing the researcher's desired data were presented for the national agenda service information source operation. Third, strengthening public relations for policy users, building and promoting the site brand, operating SNS channels, and reinforcing the activation of auxiliary materials and the accessibility of external services were proposed for public relations of national agenda service. Fourth, expanding the information network with Open API, cloud service, and overseas libraries was proposed for collaborating and cooperating with the agenda service.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.1
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• pp.51-58
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• 2023

In this paper, we propose an organ segmentation technique for the automatic extraction of medical diagnostic indicators from X-ray images. In order to calculate diagnostic indicators of heart disease and spinal disease such as VHS(vertebral heart scale) and Cobb angle, it is necessary to accurately segment the thoracic spine, carina, and heart in a chest X-ray image. A deep neural network model in which the high-resolution representation of the image for each layer and the structure converted into a low-resolution feature map are connected in parallel was adopted. This structure enables the relative position information in the image to be effectively reflected in the segmentation process. It is shown that learning performance can be improved by combining the OCR module, in which pixel information and object information are mutually interacted in a multi-step process, and the channel attention module, which allows each channel of the network to be reflected as different weight values. In addition, a method of augmenting learning data is presented in order to provide robust performance against changes in the position, shape, and size of the subject in the X-ray image. The effectiveness of the proposed theory was evaluated through an experiment using 145 human chest X-ray images and 118 animal X-ray images.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.2
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• pp.59-71
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• 2022

This study considered regional differences in the university-industry collaboration of Korean universities and performed cluster analysis to identify the spatial range with high university-industry collaboration connectivity. By university establishment type, it was found that the university-industry collaboration capacity of the major national university was superior overall, especially in the technology transfer & commercialization sector and the infrastructure sector, compared to private universities and general national universities. The spatial pattern of university-industry collaboration capacity showed relatively clear differences by city and province. In terms of university-industry collaboration capacity by sector, it was confirmed that the regional gap was not large in the talent training sector and the infrastructure sector, but the regional gap was relatively large in the technology transfer & commercialization sector and the start-up sector. As a result of the cluster analysis to identify a spatial range with high connectivity in terms of similarity and spatial proximity of university-industry collaboration patterns, it is divided into 15 clusters. It is found that most of major national universities are included in one of 15 clusters where all sectors of university-industry collaboration are strong. Therefore, as a policy measure to achieve regional innovative growth through enhancing the effectiveness of university-industry collaboration, we propose the establishment of a hub & spoke network-type collaboration system in which a major national university acts as a hub and nearby local universities play a spoke role.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.305-316
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• 2022

With the flood of digital data owing to the Internet of Things and big data, cloud service providers that process and store vast amount of data from multiple users can apply duplicate data elimination technique for efficient data management. The user experience can be improved as the notion of edge computing paradigm is introduced as an extension of the cloud computing to improve problems such as network congestion to a central cloud server and reduced computational efficiency. However, the addition of a new edge device that is not entirely reliable in the edge computing may cause increase in the computational complexity for additional cryptographic operations to preserve data privacy in duplicate identification and elimination process. In this paper, we propose an efficiency-improved duplicate data elimination protocol while preserving data privacy with an optimized user-edge-cloud communication framework by utilizing a trusted execution environment. Direct sharing of secret information between the user and the central cloud server can minimize the computational complexity in edge devices and enables the use of efficient encryption algorithms at the side of cloud service providers. Users also improve the user experience by offloading data to edge devices, enabling duplicate elimination and independent activity. Through experiments, efficiency of the proposed scheme has been analyzed such as up to 78x improvements in computation during data outsourcing process compared to the previous study which does not exploit trusted execution environment in edge computing architecture.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.6
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• pp.437-456
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• 2021

In the field of remote sensing in Korea, starting in 2017, deep learning has begun to show efficient research results compared to existing research methods. Currently, research is being conducted to apply deep learning in almost all fields of remote sensing, from image preprocessing to applications. To analyze the research trend of deep learning applied to the remote sensing field, Korean domestic journal papers, published until October 2021, related to deep learning applied to the remote sensing field were collected. Based on the collected 60 papers, research trend analysis was performed while focusing on deep learning network purpose, remote sensing application field, and remote sensing image acquisition platform. In addition, open source data that can be effectively used to build training data for performing deep learning were summarized in the paper. Through this study, we presented the problems that need to be solved in order for deep learning to be established in the remote sensing field. Moreover, we intended to provide help in finding research directions for researchers to apply deep learning technology into the remote sensing field in the future.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.119-131
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• 2021

With the boom of platform businesses, digital transformation has become the most important topic for businesses. Digital transformation has now become the most urgent strategy for survival, from a strategy considered as an option to choose in the past. Many companies are desperately seeking the ways to be digitally transformed. Even though there have been many studies on digital transformation, most of them are on strategic and conceptual model levels based on simple case analyses. In this study, we analyze the benefits of data integration and network effects from it, based on platform business model at the core of digital transformation. The change based on platform can be categorized into the internal one for the integration of data and better decision making, and the external one for the expansion of the businesses and better prediction of consumer behaviors through the integration of external data sets by the platform business model based enterprises. While the progress for digital transformation is not mature enough yet, financial industry is one of the most promising industries for the change and realization of the aim of it with its relatively much more advanced IT infrastructure. Many companies are making various efforts for the integration of external data, and if the good results can be accomplished, financial industry will contribute to the advancement of digital transformation in other industries as well. For "My Data" project by Korean government, we suggest the data structure and transaction of data (of Korea) should be advanced and established more quickly.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.399-407
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• 2022

Although Companies are forming cooperation and networks with various companies such as technology and R&D, but it is urgently necessary to secure multiple competencies of companies that can effectively adapt. This study investigated the effects of corporate strategic orientation, technological innovation capability, and organizational capability on corporate performance targeting SMEs located in the Daegu area. The survey was conducted from September 1 to November 30, 2021 for employees of Daegu companies, and a total of 183 cases were used for the final analysis. Looking at the results of the analysis, as a result of multiple regression analysis on Daegu companies, it was found that the strategic orientation, technological innovation capability, and organizational capability of managers, all independent variables, had a significant positive (+) effect on corporate performance. It can be seen that efforts should be made to improve education and R&D according to various competency bases and innovations because of the large impact on the manager's mind, the company's core technical competency, and the company's organizational performance. This study aimed to understand the importance of corporate strategic orientation, technological innovation capability, and organizational capability on corporate performance targeting relevant SMEs that can have a significant impact on national and regional economies.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.295-303
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• 2023

As the cloud computing market grows, a variety of cloud services are now reliably delivered. Administrative agencies and public institutions of South Korea are transferring all their information systems to cloud systems. It is essential to develop security solutions in advance in order to safely operate cloud services, as protecting cloud services from misuse and malicious access by insiders and outsiders over the Internet is challenging. In this paper, we propose a zero trust model for cloud storage services that store sensitive data. We then verify the effectiveness of the proposed model by operating a cloud storage service. Memory, web, and network forensics are also performed to track access and usage of cloud users depending on the adoption of the zero trust model. As a cloud storage service, we use Amazon S3(Simple Storage Service) and deploy zero trust techniques such as access control lists and key management systems. In order to consider the different types of access to S3, furthermore, we generate service requests inside and outside AWS(Amazon Web Services) and then analyze the results of the zero trust techniques depending on the location of the service request.

• Journal of the Korea Society of Computer and Information
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• v.14 no.2
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• pp.157-168
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• 2009

In this paper, a photovoltaic system is designed with a step up chopper and single phase PWM(Pulse Width Modulation) voltage source inverter. Where proposed Synchronous signal and control signal was processed by one-chip microprocessor for stable modulation. The step up chopper operates in continuous mode by adjusting the duty ratio so that the photovoltaic system tracks the maximum power point of solar cell without any influence on the variation of insolation and temperature because solar cell has typical voltage and current dropping character. The single phase PWM voltage source the inverter using inverter consists of complex type of electric power converter to compensate for the defect, that is, solar cell cannot be developed continuously by connecting with the source of electric power for ordinary use. It can cause the effect of saving electric power. from 10 to 20[%]. The single phase PWM voltage source inverter operates in situation that its output voltage is in same phase with the utility voltage. In order to enhance the efficiency of photovoltaic cells, photovoltaic positioning system using sensor and microprocessor was design so that the fixed type of photovoltaic cells and photovoltaic positioning system were compared. In result, photovoltaic positioning system can improved 5% than fixed type of photovoltaic cells. In addition, I connected extra power to the system through operating the system voltage and inverter power in a synchronized way by extracting the system voltage so that the phase of the system and the phase of single-phase inverter of PWM voltage type can be synchronized. And, It controlled in order to provide stable pier to the load and the system through maintaining high lurer factor and low output power of harmonics.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.119-125
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• 2023

IT infrastructure operation has advanced, and the methods for managing systems have become widely adopted. Recently, research has focused on improving system management using Syslog. However, utilizing log data collected through these methods presents challenges, as logs are extracted in various formats that require expert analysis. This paper proposes a system that utilizes edge computing to distribute the collection of Syslog data and preprocesses duplicate data before storing it in a central database. Additionally, the system constructs a data dictionary to classify and count data in real-time, with restrictions on transmitting registered data to the central database. This approach ensures the maintenance of predefined patterns in the data dictionary, controls duplicate data and temporal duplicates, and enables the storage of refined data in the central database, thereby securing fundamental data for big data analysis. The proposed algorithms and procedures are demonstrated through simulations and examples. Real syslog data, including extracted examples, is used to accurately extract necessary information from log data and verify the successful execution of the classification and storage processes. This system can serve as an efficient solution for collecting and managing log data in edge environments, offering potential benefits in terms of technology diffusion.