• The Korean Journal of Zoology
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• v.28 no.1
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• pp.21-30
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• 1985

By two-dimensional gel electrophoresis loss of a cell-specific protein was detected in tD strain of Amoeba proteus that had been infected by symbiotic bacteria extracted from xD strain. In 50 days of experimental infection by induced phagocytosis the host amoeba lost the ability to synthesize the tD cell-specific protein even after removal of the infective bacteria and xD cell-specific protein by growing the amoebae at $27^\\circC$. By this time the host amoebae were obligately dependent on the bacteria. From these and other results (Lorch and Jeon, Science 221:549), it is clear that the incompatibility of the infected nuclei with the cytoplasm of the uninfected amoeba and the obligate dependence of the host on bacteria are due to the irreversible inactivation or the loss of the cell-specific gene by bacterial infection in this amoeba.

• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.436-443
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• 2009

There have been rapid increases to the demands for modeling diverse and complex spatial phenomena and utilizing spatial data through the computer across all the aspects of society. As a result, the importance and utilization of remote sensing and GIS's(geographic information systems) have also increased. It can produce digital data of enormous accuracy and value by incorporating remote sensing images into GIS analysis technology and make various thematic maps by classifying and analyzing land cover. Once such a map is made for the target area, it can easily do modeling and constant monitoring based on the map, revise the database with ease, and thus efficiently update geo-spatial information. Under the goal of analyzing changes to land cover along the road by combining the remote sensing and GIS technology, this study classified land cover from the images of two periods, detected changes to the six classes over ten years, and obtained statistics about the study area's quantitative area changes in order to provide basic decision making data for urban planning and development. By analyzing land use along the road, one can set up plans for the area along the road and the downtown to supplement each other.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.1
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• pp.131-138
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• 2003

With the Internet winning a huge popularity, there rise urgent problems which are related to Network Security Managements such as Protecting Network and Communication from un-authorized user. Accordingly, Using Security equipments have been common lately such as Intrusion Detection Systems, Firewalls and VPNs. Those systems. however, operate in individual system which are independent to me another. Their usage are so limited according to their vendors that they can not provide a corporate Security Solution. In this paper, we present a Hierarchical Security Management Model which can be applicable to a Network Security Policies consistently. We also propose a Policy Negotiation Mechanism and a Prototype which help us to manage Security Policies and Negotiations easier. The results of this research also can be one of the useful guides to developing a Security Policy Server or Security Techniques which can be useful in different environments. This study also shows that it is also possible to improve a Security Characteristics as a whole network and also to support Policy Associations among hosts using our mechanisms.

• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.18-25
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• 2021

In many developed countries, such as South Korea, efficiently maintaining the aging infrastructures is an important issue. Currently, inspectors visually inspect the infrastructure for maintenance needs, but this method is inefficient due to its high costs, long logistic times, and hazards to the inspectors. Thus, in this paper, a novel crack inspection approach for concrete bridges is proposed using integrated image processing techniques. The proposed approach consists of four steps: (1) training a deep learning model to automatically detect cracks on concrete bridges, (2) acquiring in-situ images using a drone, (3) generating orthomosaic images based on 3D modeling, and (4) detecting cracks on the orthmosaic image using the trained deep learning model. Cascade Mask R-CNN, a state-of-the-art instance segmentation deep learning model, was trained with 3235 crack images that included 2415 hard negative images. We selected the Tancheon overpass, located in Seoul, South Korea, as a testbed for the proposed approach, and we captured images of pier 34-37 and slab 34-36 using a commercial drone. Agisoft Metashape was utilized as a 3D model generation program to generate an orthomosaic of the captured images. We applied the proposed approach to four orthomosaic images that displayed the front, back, left, and right sides of pier 37. Using pixel-level precision referencing visual inspection of the captured images, we evaluated the trained Cascade Mask R-CNN's crack detection performance. At the coping of the front side of pier 37, the model obtained its best precision: 94.34%. It achieved an average precision of 72.93% for the orthomosaics of the four sides of the pier. The test results show that this proposed approach for crack detection can be a suitable alternative to the conventional visual inspection method.

• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.127-132
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• 2022

As the IoT technology is more developed, it is more important for the accuracy of IoT data. Since the IoT data supports a different formats and protocols, it is often happened that the IoT system is failed or the incorrect data is generated with the unreliable IoT devices(sensor, actuator). Because the abnormality of IoT device or the user situation is not detected correctly, this problem makes the user to be unsatisfied with the IoT system. This study proposes the decision methodology of IoT data consistency whether the IoT data is generated in normal range or not by using the mathematical functions('gradient descent function' and 'linear regression function'). It may be concluded that the gradient function method is suitable for the IoT data which the 'increasing velocity' is related with the next generated pattern(eg. sensor devices), the linear regression function method is suitable for the IoT data which the 'the difference from linear regression function' is related with the next generated pattern in case the data has a linear pattern(eg. water meter, electric meter).

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.346-346
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• 2020

홍수기 효과적인 하천관리를 위해서는 광역 모니터링을 위한 기술 확보가 매우 중요하며, 최근 드론을 활용한 하천 모니터링에 관한 관심이 점차 증가되고 있다. 하천관리에 필요한 드론 탑재용 센서는 기본적으로 RGB 광학센서를 비롯하여 근적외선(Nir) 및 열적외선 센서가 함께 운용되는 것이 효과적이다. 그러나 현재 판매되는 드론 카메라를 살펴보면 근적외선과 열적외선 센서가 별도로 분리되어 있고 광학센서에 비해 상대적으로 매우 고가로 판매되고 있는 실정이다. 따라서 하천 모니터링을 위해서는 광학(RGB), 근적외선 그리고 열적외선 센서가 통합된 저가의 탑재체 개발이 시급하고 이를 활용한 하천 모니터링 프로세스를 정립할 필요가 있다. 본 연구에서는 일반 드론에 쉽게 탑재 가능한 하천 모니터링용 탑재체를 개발하였으며, 이를 기반으로 하천 홍수 및 부유사 모니터링에 활용하였다. 광학센서는 하천의 주요 형상을 확인하는데 이용하였으며, 근적외선 센서는 홍수 및 부유사 탐지에 활용하였다. 특히 본 연구에서는 비교적 넓은 하천 구역에 대한 공간정보를 구축하기 위해 75% 이상의 중복도를 가지고 촬영하도록 세팅하였으며 영상접합 SW를 활용하여 정사영상을 생성하였다. 구축한 근적외선 정사영상으로부터 영상분석 프로그램을 활용하여 홍수 및 부유사 영역을 추출하였으며 이를 통해 홍수기 하천 모니터링 및 치수 업무 의사결정을 위한 정보를 제공할 수 있었다. 저가용 드론 센서는 상용 SW와의 연계가 어렵기 때문에 자동비행 프로그램처럼 해당 위치별 영상 촬영이 어려운 한계가 있었으며, 본 연구에서는 센서의 제원특성을 활용하여 자동비행 SW에서도 일정 이상의 중복도를 확보할 수 있는 비행고도별 촬영시간 등을 종합적으로 설계하였다. 이를 통해 해당 지역에 대한 하천 모니터링용 정사영상을 구축할 수 있었으며 기존의 고가용 드론 센서와 유사한 효과를 가져올 수 있었다.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.277-281
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• 2023

Recent aggressive threats by North Korea using small drones have heavily impacted on ROK(Republic of Korea) society and it seems to be agreed that counter-drone systems are required to protect our properties. ROK government has been investigating current counter-drone systems for national important facilities. However, there is no consensus standard to evaluate the systems. This paper is to propose a counter-drone system evaluation framework which is the outcome through RMA(Revolution in Military Affairs) thinking process. The RMA thinking process is currently well-implemented in ROK army to develop future military strategy. The proposed framework has 4 categories - threat analysis of North Korea small drones, convergence of detection, tracking and neutralizing systems, integrated operations and available experts and organization - which have corresponding criteria.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.369-377
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• 2023

In the industrial manufacturing sector, quality control is pivotal for minimizing defect rates; inadequate management can result in additional costs and production delays. This study underscores the significance of detecting texture defects in manufactured goods and proposes a more precise defect detection technique. While the DFR(Deep Feature Reconstruction) model adopted an approach based on feature map amalgamation and reconstruction, it had inherent limitations. Consequently, we incorporated a new loss function using statistical methodologies, integrated a skip connection structure, and conducted parameter tuning to overcome constraints. When this enhanced model was applied to the texture category of the MVTec-AD dataset, it recorded a 2.3% higher Defect Segmentation AUC compared to previous methods, and the overall defect detection performance was improved. These findings attest to the significant contribution of the proposed method in defect detection through the reconstruction of feature map combinations.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.77-89
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• 2024

This paper presents an unmanned store management system that can provide inventory management and theft prevention for displayed products using a small camera that can monitor the shelves of sold products in small and medium-sized stores. This system is a service solution that integrates object recognition, real-time communication, security management, access management, and mobile authentication. The proposed system uses a custom YOLOv5-x model to recognize objects on the display, measure quantities in real time, and support real-time data communication with servers through Raspberry Pie. In addition, the number of objects in the database and the object recognition results are compared to detect suspected theft situations and provide burial images at the time of theft. The proposed unmanned store solution is expected to improve the efficiency of small and medium-sized unmanned store operations and contribute to responding to theft.

• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.27-36
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• 2024

In this paper, we analyze the unified requirements of international association of classification societies - cyber resilience of ships, ahead of implementation of the agreement on July 1, 2024, and respond to ship cyber security and resilience programs based on 5 requirements, 17 details, and documents that must be submitted or maintained according to the ship's cyber resilience,. Measures include document management such as classification certification documents and design documents, configuration of a network with enhanced security, establishment of processes for accident response, configuration management using software tools, integrated network management, malware protection, and detection of ship network security threats with security management solutions. proposed a technology capable of real-time response.