• Title/Summary/Keyword: 감지 시스템

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The Development of Fiber-Optic Hydrogen Gas Sensor for Non-Destructive Test Application (비파괴 검사 응용을 위한 광섬유 수소 가스 센서의 개발)

  • 윤의중;정명희
    • Journal of the Korean Magnetics Society
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    • v.8 no.6
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    • pp.380-387
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    • 1998
  • In this paper, a sensor material with Fe/Zr multilayer thin film, in which the change in the magnetization and strain with hydrogenation is maximized, were developed. Compositionally modulated (CM) Fe/Zr multilayers with a $Fe_{80}Zr_{20}$ composition and modulation wavelengths ($\lambda$) $3~50{\AA}$ were deposited by sequentially sputtering (RF diode) elemental Fe and Zr targets. The films were electrolytically hydrogenated to select the optimum Fe/Zr multilayers that show the maximum increases in the magnetization and strain with hydrogenation. The changes in the magnetic properties of the thin films after hydrogenation, were measured using a hysteresis graph and a vibrating sample magnetometer (VSM), and the strains induced in the films by hydrogenation were also measured using a laser heterodyne interferometer (LHI). The optimum sensor material selected was incorporated in a fiber-optic hydrogen sensor (that can sense indirectly amount of hydrogen injected) by depositing it directly on the sensing arm of a single-mode fiber Michelson interferometer. The developed sensor holds significant promise for non-destructive test evaluation (NDE) applications because it is expected to be useful for detecting easily and accurately the subsurface corrosion in structural systems.

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Comparative Analysis of CNN Deep Learning Model Performance Based on Quantification Application for High-Speed Marine Object Classification (고속 해상 객체 분류를 위한 양자화 적용 기반 CNN 딥러닝 모델 성능 비교 분석)

  • Lee, Seong-Ju;Lee, Hyo-Chan;Song, Hyun-Hak;Jeon, Ho-Seok;Im, Tae-ho
    • Journal of Internet Computing and Services
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    • v.22 no.2
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    • pp.59-68
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    • 2021
  • As artificial intelligence(AI) technologies, which have made rapid growth recently, began to be applied to the marine environment such as ships, there have been active researches on the application of CNN-based models specialized for digital videos. In E-Navigation service, which is combined with various technologies to detect floating objects of clash risk to reduce human errors and prevent fires inside ships, real-time processing is of huge importance. More functions added, however, mean a need for high-performance processes, which raises prices and poses a cost burden on shipowners. This study thus set out to propose a method capable of processing information at a high rate while maintaining the accuracy by applying Quantization techniques of a deep learning model. First, videos were pre-processed fit for the detection of floating matters in the sea to ensure the efficient transmission of video data to the deep learning entry. Secondly, the quantization technique, one of lightweight techniques for a deep learning model, was applied to reduce the usage rate of memory and increase the processing speed. Finally, the proposed deep learning model to which video pre-processing and quantization were applied was applied to various embedded boards to measure its accuracy and processing speed and test its performance. The proposed method was able to reduce the usage of memory capacity four times and improve the processing speed about four to five times while maintaining the old accuracy of recognition.

Estimation of Traffic Safety Improvement Effect of Forward Collision Warning (FCW) (전방충돌경보(FCW)의 교통안전 증진효과 추정)

  • Kim, Hyung-kyu;Lee, Soo-beom;Lee, Hye-rin;Hong, Su-jeong;Min, hye-Ryung
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.20 no.2
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    • pp.43-57
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    • 2021
  • The Forward Collision Warning, a representative technology of the Advanced Driver Assistance Systems, was selected as the target technology. The cognitive response time, deceleration, and impact were selected as the measures of effectiveness. And the amount of change with and without the Forward Collision Warning was measured. The experimental scenarios included a sudden stop event (1) of the vehicle in front of the driver and an event (2) in which the vehicle intervened in the next lane. All experiments were divided into day and night. As a result of the analysis, response time and the deceleration rate decreased when the forward collision warning system was installed. It was analyzed that the driver's risk situation could be detected quickly and the number of front-end collisions could be reduced as a result. Reflecting the driver's operating habits and diversifying the experimental scenarios will increase the installation effectiveness of ADAS and be used to estimate the effectiveness of other technologies.

Patent Trend and Characteristics of Major Companies in the Field of Seismic Nodal System (탄성파 탐사 무선 수진기 특허동향 및 주요 기업의 기술 분석)

  • Park, Jung Kyu
    • Journal of the Korean Society of Mineral and Energy Resources Engineers
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    • v.55 no.6
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    • pp.635-648
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    • 2018
  • This study analyzed patent trends of seismic nodal systems and the technical characteristics of core patents of three major companies, including Fairfield, Sercel, and Wireless Seismic, to examine the focus of technology development of each company. From the analysis, the patent application growth rate of seismic nodal systems has steadily increased since early to mid-2000s and has recently shown a higher growth rate. Over the same period, the patent application growth rate of the three major companies examined was higher than that of the global trend, and patent infringement cases was also examined to evaluate market competition in this field. Analysis of the technical characteristics of the three companies' 33 core patents showed that they are generally focused on seismic signal detection. Sub-technologies included improved reliability of data acquisition, data transmission efficiency, and overall operating of the seismic nodal system. New entrants in field of technology development or manufacturing of seismic nodal systems where the market is growing must closely analyze the contents of major companies' products and patents to prevent possible patent disputes or duplicate research.

Research on Impact Sensors for Developing the Electronic Body Protector of Taekwondo (태권도 전자호구 개발을 위한 충격감지 센서 연구)

  • Ki, Jae-Sug;Jeong, Dong-Hwa;Lee, Hyun-Jun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.4
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    • pp.648-655
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    • 2019
  • This paper proposes the differential development of a Taekwondo electronic body protector. For this development, the most suitable sensor system was selected after analyzing and testing various sensor methods (magnetic sensors, electric capacity sensors, contact switch sensors, and piezo-film sensors) that could be applied in the electronic body protector, the selected sensors were distributed to the body and feet to make a more precise hit score, unlike the existing system in which all sensors are centralized on the body. Furthermore, it aims to illuminate using a lightweight film-type piezoelectric sensor on the body protector. In the case of an existing electronic body protector, all sensors and network device were concentrated on the body protector, so users need to purchase a set if they want it. On the other hand, the proposed system cloud can be used individually using a smart scoring WEP program. The effects of decreasing weight by up to 20% were compared with those of the existing system. Setting up a test facility is very difficult, so more study will be needed to analyze the effects of a hit.

The Status of Personal Information Protection for Original Text Information Disclosure Service (원문정보공개 서비스에서의 개인정보 보호 실태)

  • Ahn, Hye-mi
    • Journal of Korean Society of Archives and Records Management
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    • v.19 no.2
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    • pp.147-172
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    • 2019
  • With the provision of the original text information disclosure service, the time spent on determining the disclosure of the original text information decreased, and the number of original text information disclosure significantly increased. In public institutions, the risk of the exposure of personal information also increased. In this study, the status of personal information protection in the original text information disclosure service was investigated. Moreover, the causes of the exposure of personal information were analyzed, and improvements were proposed. The survey presented the following results. First, 13% of the original text information collected contains personal information, which is the nondisclosure information. Second, among the original text information that includes personal information, the original text information, including the personal information of the public official, was the most important. In particular, many records about vacation and medical leaves were found. Third, there were many cases in which information about the individual of the representative was exposed in the agency that deals mainly with the contract work. Fourth, a large volume of personal information was not detected by filtering personal information. Upon analyzing the cause of the exposure of personal information, the following improvements are suggested. First, privacy guidelines should be redesigned. Second, the person in charge of the task of deciding whether or not to disclose original text information should be trained further. Third, the excessive disclosure of information based on the government's quantitative performance should be eased. Fourth, the filtering function of the personal information of the original text information disclosure system should be improved.

Multi-fidelity Data-fusion for Improving Strain accuracy using Optical Fiber Sensors (이종 광섬유 센서 데이터 융합을 통한 변형률 정확도 향상 기법)

  • Park, Young-Soo;Jin, Seung-Seop;Yoo, Chul-Hwan;Kim, Sungtae;Park, Young-Hwan
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.40 no.6
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    • pp.547-553
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    • 2020
  • As aging infrastructures increase along with time, the efficient maintenance becomes more significant and accurate responses from the sensors are pre-requisite. Among various responses, strain is commonly used to detect damage such as crack and fatigue. Optical fiber sensor is one of the promising sensing techniques to measure strains with high-durability, immunity for electrical noise, long transmission distance. Fiber Bragg Grating (FBG) is a point sensor to measure the strain based on reflected signals from the grating, while Brillouin Optic Correlation Domain Analysis (BOCDA) is a distributed sensor to measure the strain along with the optical fiber based on scattering signals. Although the FBG provides the signal with high accuracy and reproducibility, the number of sensing points is limited. On the other hand, the BOCDA can measure a quasi-continuous strain along with the optical fiber. However, the measured signals from BOCDA have low accuracy and reproducibility. This paper proposed a multi-fidelity data-fusion method based on Gaussian Process Regression to improve the fidelity of the strain distribution by fusing the advantages of both systems. The proposed method was evaluated by laboratory test. The result shows that the proposed method is promising to improve the fidelity of the strain.

Research on Pilot Decision Model for the Fast-Time Simulation of UAS Operation (무인항공기 운항의 배속 시뮬레이션을 위한 조종사 의사결정 모델 연구)

  • Park, Seung-Hyun;Lee, Hyeonwoong;Lee, Hak-Tae
    • Journal of Advanced Navigation Technology
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    • v.25 no.1
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    • pp.1-7
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    • 2021
  • Detect and avoid (DAA) system, which is essential for the operation of UAS, detects intruding aircraft and offers the ranges of turn and climb/descent maneuver that are required to avoid the intruder. This paper uses detect and avoid alerting logic for unmanned systems (DAIDALUS) developed at NASA as a DAA algorithm. Since DAIDALUS offers ranges of avoidance maneuvers, the actual avoidance maneuver must be decided by the UAS pilot as well as the timing and method of returning to the original route. It can be readily used in real-time human-in-the-loop (HiTL) simulations where a human pilot is making the decision, but a pilot decision model is required in fast-time simulations that proceed without human pilot intervention. This paper proposes a pilot decision model that maneuvers the aircraft based on the DAIDALUS avoidance maneuver range. A series of tests were conducted using test vectors from radio technical commission for aeronautics (RTCA) minimum operational performance standards (MOPS). The alert levels differed by the types of encounters, but loss of well clear (LoWC) was avoided. This model will be useful in fast-time simulation of high-volume traffic involving UAS.

Design of an Visitor Identification system for the Front Door of an Apartment using Deep learning (딥러닝 기반 이용한 공동주택현관문의 출입자 식별 시스템 설계)

  • Lee, Min-Hye;Mun, Hyung-Jin
    • Journal of the Korea Convergence Society
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    • v.13 no.4
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    • pp.45-51
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    • 2022
  • Fear of contact exists due to the prevention of the spread of infectious diseases such as COVID-19. When using the common entrance door of an apartment, access is possible only if the resident enters a password or obtains the resident's permission. There is the inconvenience of having to manually enter the number and password for the common entrance door to enter. Also, contactless entry is required due to COVID-19. Due to the development of ICT, users can be easily identified through the development of face recognition and voice recognition technology. The proposed method detects a visitor's face through a CCTV or camera attached to the common entrance door, recognizes the face, and identifies it as a registered resident. Then, based on the registered information of the resident, it is possible to operate without contact by interworking with the elevator on the server. In particular, if face recognition fails with a hat or mask, the visitor is identified by voice or additional authentication of the visitor is performed based on the voice message. It is possible to block the spread of contagiousness without leaving any contactless function and fingerprint information when entering and exiting the front door of an apartment house, and without the inconvenience of access.

Development on Metallic Nanoparticles-enhanced Ultrasensitive Sensors for Alkaline Fuel Concentrations (금속 나노입자 도입형의 초고감도 센서 개발 및 알칼라인 연료 측정에 적용 연구)

  • Nde, Dieudonne Tanue;Lee, Ji Won;Lee, Hye Jin
    • Applied Chemistry for Engineering
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    • v.33 no.2
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    • pp.126-132
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    • 2022
  • Alkaline fuel cells using liquid fuels such as hydrazine and ammonia are gaining great attention as a clean and renewable energy solution possibly owing to advantages such as excellent energy density, simple structure, compact size in fuel container, and ease of storage and transportation. However, common shortcomings including cathode flooding, fuel crossover, side yield reactions, and fuel security and toxicity are still challenging issues. Real time monitoring of fuel concentrations integrated into a fuel cell device can help improving fuel cell performance via predicting any loss of fuels used at a cathode for efficient energy production. There have been extensive research efforts made on developing real-time sensing platforms for hydrazine and ammonia. Among these, recent advancements in electrochemical sensors offering high sensitivity and selectivity, easy fabrication, and fast monitoring capability for analysis of hydrazine and ammonia concentrations will be introduced. In particular, research trend on the integration of metallic and metal oxide nanoparticles and also their hybrids with carbon-based nanomaterials into electrochemical sensing platforms for improvement in sensitivity and selectivity will be highlighted.