• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.6
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• pp.1151-1158
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• 2011

Proximity magnetic sensor is able to detect the object target accurately in close range and it has been widely used in the underwater guided weapon system because there is no countermeasures from the target. In order to increase the damage of target by shock wave due to explosion of the underwater guided weapon system, the maximum detection range of the proximity magnetic sensor needs to be increased. In this paper, we describe the techniques of the optimum transmitting and receiving coils design using the Finite Element Method for the output power enhancement of the transmitter and the sensitivity improvement of the receiver. Finally, the proposed design techniques of the transmitter and the receiver were verified using a experimental setup and a prototype.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.5
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• pp.174-180
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• 2015

In this paper, we propose the passive sonar signal processing technique for estimating target information using proximity sensor. This algorithm is performed by single sensor which is constituted underwater sensor network and has a hierarchical structure. The estimated parameter is the velocity, the depth, the distance and bearing at CPA situations and we can improve the accuracy of signal processing techniques through having a hierarchical structure. We verify the performance of the proposed method by computer simulation and then we check the result that 20% error can be occurred in maximum detectable range. We also confirm that proposed method has the reliability in the actual sea environment through the sea experiment.

• Journal of Korean Tunnelling and Underground Space Association
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• v.9 no.1
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• pp.19-28
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• 2007

Tunnel management is a time-consuming and expensive task. In particular, visual analysis of tunnel inspection often requires extended time and cost and shows problems on data gathering, storage and analysis. This study proposes a new approach to extract information for tunnel management by using a laser scanning technology. A prototype tunnel laser scanner developed was used to obtain point clouds of a railway tunnel surface. Initial processing of laser scanning data was to separate those laser pulses returned from the installations attached to tunnel liner using radiometric and geometric characteristics of laser returns. Once the laser returns from the installations were separated and removed, physically damaged parts on tunnel lining are detected. Based on the plane formed by laser scanner data, damaged parts are detected by analysis of proximity. The algorithms presented in this study successfully detect the physically damaged parts which can be verified by the digital photography of the corresponding location on the tunnel surface.

• Journal of Korean Tunnelling and Underground Space Association
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• v.22 no.5
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• pp.515-528
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• 2020

Underground concrete structures are usually designed to be used for decades, but in recent years, many of them are nearing their original life expectancy. As a result, it is necessary to promptly inspect and repair the structure, since it can cause lost of fundamental functions and bring unexpected problems. Therefore, personnel-based inspections and repairs have been underway for maintenance of underground structures, but nowadays, objective inspection technologies have been actively developed through the fusion of deep learning and image process. In particular, various researches have been conducted on developing a concrete crack detection algorithm based on supervised learning. Most of these studies requires a large amount of image data, especially, label images. In order to secure those images, it takes a lot of time and labor in reality. To resolve this problem, we introduce a method to increase the accuracy of crack area detection, improved by 0.25% on average by applying adversarial learning in this paper. The adversarial learning consists of a segmentation neural network and a discriminator neural network, and it is an algorithm that improves recognition performance by generating a virtual label image in a competitive structure. In this study, an efficient deep neural network learning method was proposed using this method, and it is expected to be used for accurate crack detection in the future.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.1
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• pp.81-88
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• 2013

This paper describes the fundamentals, design, realization and test results of a BPSK(Bi Phase Shift Keying) transceiver for the direction finding proximity fuze sensor for anti-aircrafts or air missiles. The BPSK transceiver for the direction finding fuze sensor has been designed to detect a moving target by Doppler signal processing with the code correlation method and to distinguish direction by comparing received powers of each Doppler signal from adjacent three receiving antennas. The electrical and ESS(Environmental Stress Screening) tests of the BPSK transceiver showed satisfactory results and target detection and direction finding performances proved to be successful through dynamic operation tests by 155 mm gun firing.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.01a
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• pp.37-38
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• 2018

본 논문에서 제안하는 시각장애인용 스마트장갑은 시각장애인들이 지팡이를 사용할 때 발생하는 불필요한 접촉을 방지하고, 초음파센서를 이용해 전방의 장애물을 탐지하여 서보모터를 이용해 손등을 두드려 장애물의 유무를 알려준다. 또한 손가락에 있는 정전식 근접 터치 모듈은 손가락끼리 접촉하였을 때 블루투스로 연결된 스마트폰의 특정 어플리케이션을 실행하여 길을 잃거나 긴급 상황이 발생 했을 때 시각장애인도 불편함 없이 문자나 전화를 이용할 수 있도록 고안하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.174-177
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• 2018

스마트폰 키 애플리케이션이 널리 사용되면서, 이에 대한 중계 공격의 위협도 증가하고 있다. 중계공격은 공격자가 차량과 키 애플리케이션 사이에서 오고가는 신호를 중계하여 허용 범위 밖의 통신을 시스템이 유요한 것으로 판단하게 하는 공격이다. 본 논문에서는 중계 공격을 막기 위해, 추가 지연시간을 탐지하여, 임계 지연 시간을 넘었을 경우 차량과 스마트키가 충분히 근접하지 않았다고 판단하여 차량 문 개폐 요청을 거부하는 시스템을 제안하였다. 또한 실제 환경에서의 유동성을 고려하여 임계 지연 시간을 지속적으로 업데이트하는 적응 임계 지연 시간(Adaptive Delay Threshold) 기술을 제시하였다. 그리고 실제 임베디드 기기를 이용해 시스템을 구현하여 시스템의 실효성을 검증하였다.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.3
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• pp.58-72
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• 2021

In July 2021, UNCTAD classified Korea as a developed country. After the Korean War in the 1950s, economic development was promoted despite difficult conditions, resulting in epoch-making national growth. However, in order to respond to the rapidly changing global economy, it is necessary to continuously study the domestic industrial ecosystem and prepare strategies for continuous change and growth. This study analyzed the industrial ecosystem of the automobile industry where it is possible to obtain transaction data between companies by applying complexity spatial network analysis. For data, 295 corporate data(node data) and 607 transaction data (link data) were used. As a result of checking the spatial distribution by geocoding the address of the company, the automobile industry-related companies were concentrated in the Seoul metropolitan area and the Southeastern(Dongnam) region. The node importance was measured through degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality, and the network structure was confirmed by identifying density, distance, community detection, and assortativity and disassortivity. As a result, among the automakers, Hyundai Motor, Kia Motors, and GM Korea were included in the top 15 in 4 indicators of node centrality. In terms of company location, companies located in the Seoul metropolitan area were included in the top 15. In terms of company size, most of the large companies with more than 1,000 employees were included in the top 15 for degree centrality and betweenness centrality. Regarding closeness centrality and eigenvector centrality, most of the companies with 500 or less employees were included in the top 15, except for automakers. In the structure of the network, the density was 0.01390522 and the average distance was 3.422481. As a result of community detection using the fast greedy algorithm, 11 communities were finally derived.

• Tunnel and Underground Space
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• v.27 no.5
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• pp.282-294
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• 2017

This study analyzed the development status and applications of collision avoidance systems for mine safety management. The definitions of collision avoidance system used in Australia and USA were compared. Sensing technologies utilized in the collision avoidance systems were reviewed. In addition, several collision avoidance systems developed in oversea mining company, such as $MineAlert^{TM}$ Collision Awareness System, Cat $MineStar^{TM}$, and Intelligent Proximity Detection, were reviewed. In the domestic mining industry, no collision avoidance system was used. However, similar systems were utilized in the construction and railroad industry. Collision avoidance system can prevent unexpected collision accident and thus improve worker's safety in mine. Therefore, it is necessary to analyze and apply sensors and system appropriate for the domestic mining environment via review of overseas collision avoidance system.

• Korean Journal of Cognitive Science
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• v.10 no.3
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• pp.17-28
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• 1999

Systematic distortions in perceived 3-D shape were obtained for elliptical and parabolic stereoscopic surfaces viewed at different distances under full and reduced cue conditions. In both conditions of Experiments 1 and 3, elliptical hemi-cylinders a appeared near veridical at the 45 cm viewing distances and flattened up to 74% of veridical at 135 cm. In Experiment 2, under full cue conditions, parabolic hemi-cylinders a appeared stretched to 118% of veridical at 45 cm, near veridical at 90 cm, and flattened to 85% of veridical at 135 cm. Under reduced cue conditions parabolas appeared flatter overall: veridical curvature was obtained at 45 cm viewing distance with flatness increasing to 68% of veridical at 135 cm. Results support a scaling explanation of perceived 3-D shape from disparity and rule out the alternative hypothesis that disparity curvature, an optical invariant, provides information for the direct perception of 3-D s shape.