• 한국재료학회:학술대회논문집
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• 한국재료학회 2009년도 추계학술발표대회
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• pp.32.1-32.1
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• 2009

본 연구에서는 산화 그라핀을 환원하여 얻은 그라핀 분말의 고온 XRD 패턴를 통해 그라핀의 열팽창계수를 정량하였다. 산화 그라핀은 Hummer method에 의해 제조되었다. 또한 그라핀은 산화그라핀을 1273K에서 열처리하여 얻어졌다. 1273K에서 그라핀의 열팽창계수($32.9{\pm}1.0$ X 10-6 K-1)는 원료인 흑연(30.3 X 10-6 K-1) 보다 8.6% 더 크게 나타내는것을 알 수 있었다. 그라핀은 화학적 처리에 의한 급격한 면간 팽창과 열처리에 의한 aggregation에 의해 심하게 굴곡지고 적층된 morphology를나타냈다. 이는 박리효과에 의한 것으로 XRD 패턴을 통해그라핀의 층수가 흑연보다 훨씬 적은 것을 알 수 있었다. 이에 따라 면간 규칙적인 배열을 보이는 흑연과는 달리 그라핀은 흑연구조에서 흔히 보이는 disorder 구조인turbostratic 적층 구조를 나타나고 면간인터렉션이 약화되어 열팽창계수가 크게 나타난다고 생각된다.

• 한국세라믹학회지
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• 제51권6호
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• pp.523-526
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• 2014

PZT($Pb(Zr_{0.53}Ti_{0.47})O_3$)/PVDF(poly vinylidene fluoride) nanofibers were prepared based on DMF (dimethylformamide) and acetone solvent by electrospinning. The optimum concentration of a PZT and PVDF composite solution for the formation of nanofibers was found by SEM (scanning electron microscopy) observations. XRD (X-ray diffraction) measurements indicated that the characteristics of PZT and PVDF coexisted. The effects of the PZT concentration on the tensile strength were investigated.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2011년도 추계학술대회
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• pp.659-661
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• 2011

본 논문은 특정 지역에서의 이동하는 객체의 검지에 대한 연구이다. 감찰이 필요한 특정 지역 내에서 센서 네트워크 기반 객체 검지를 위한 시스템 구축을 통하여 보행자의 이동 안전성을 확보하게 한다. 기존의 CCTV 대신 지능형 센서 네트워크와 이에 대한 서비스 구축을 통하여 보다 안전한 지역성을 확보함으로 서비스의 신뢰성을 높일 수 있다. 보행자의 이동 특성을 기반으로 행동에 대한 이상행위가 보일 경우 또한 사전에 주어진 시나리오의 범위 안에 포함될 경우 객체에 대한 안전 서비스가 진행되는 것이다.

• Journal of information and communication convergence engineering
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• 제17권1호
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• pp.84-90
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• 2019

Applications of unmanned aerial vehicles (UAVs) in the military environment have become popular because they require minimum human contribution and can avoid accidents during missions. UAVs are employed in various missions such as reconnaissance, observation, aggression, and protection. Consequently, counter-measures, known as anti-drone technologies, have been developed as well. In order to protect against threats from anti-drone technologies and enhance the survivability of UAVs, this study proposes an evasive measure. The proposed bio-inspired evasive maneuver of a UAV mimics a dragonfly's irregular flight. The unpredictable UAV movement is able to confuse enemies and avoid threats, thereby enhancing the UAV's survivability. The proposed system has been implemented on a commercial UAV platform (AR Drone 2.0) and tested in a real environment. The experiment results demonstrate that the proposed flight pattern has larger displacement values compared to a regular flight maneuver, thus making the UAV's position is difficult to predict.

• Nuclear Engineering and Technology
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• 제54권2호
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• pp.601-607
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• 2022

In recent years, monitoring of spent nuclear fuel inside dry cask storage has become an important area of national security. Muon tomography is a useful method for monitoring spent nuclear fuel because it uses high energy muons that penetrate deep into the target material and provides a 3-D structure of the inner materials. We designed a muon tomography system consisting of four 2-D position sensitive detector and characterized and optimized the system parameters. Each detector, measuring 200 × 200 cm², consists of a plastic scintillator, wavelength shifting (WLS) fibers and, SiPMs. The reconstructed image is obtained by extracting the intersection of the incoming and outgoing muon tracks using a Point-of-Closest-Approach (PoCA) algorithm. The Geant4 simulation was used to evaluate the performance of the muon tomography system and to optimize the design parameters including the pixel size of the muon detector, the field of view (FOV), and the distance between detectors. Based on the optimized design parameters, the spent fuel assemblies were modeled and the line profile was analyzed to conduct a feasibility study. Line profile analysis confirmed that muon tomography system can monitor nuclear spent fuel in dry storage container.

• Nuclear Engineering and Technology
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• 제54권6호
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• pp.1982-1990
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• 2022

The purpose of this study was to verify the possibility of fuel rod pattern analysis in a fresh fuel assembly using the Yonsei single-photon emission computed tomography (YSECT) system. The YSECT system consisted of three main parts: four trapezoidal-shaped bismuth germanate scintillator-based 64-channel detectors, a semiconductor-based multi-channel data acquisition system, and a rotary stage. In order to assess the performance of the prototype YSECT, tomographic images were obtained for three representative fuel rod patterns in the 6 × 6 array using two representative image-reconstruction algorithms. The fuel-rod patterns were then assessed using an in-house fuel rod pattern analysis algorithm. In the experimental results, the single-directional projection images for those three fuel-rod patterns well discriminated each fuel-rod location, showing a Gaussian-peak-shaped projection for a single 10 mm-diameter fuel rod with 12.1 mm full-width at half maximum. Finally, we successfully verified the possibility of the fuel rod pattern analysis for all three patterns of fresh fuel rods with the tomographic images obtained by the rotational YSECT system.

• Nuclear Engineering and Technology
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• 제54권10호
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• pp.3943-3948
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• 2022

Single-photon emission computed tomography is one of the reliable pin-by-pin verification techniques for spent-fuel assemblies. One of the challenges with this technique is to increase the total fuel assembly verification speed while maintaining high verification accuracy. The aim of the present study, therefore, was to develop an artificial intelligence (AI) algorithm-based tomographic image analysis technique for partial-defect verification of fuel assemblies. With the Monte Carlo (MC) simulation technique, a tomographic image dataset consisting of 511 fuel-rod patterns of a 3 × 3 fuel assembly was generated, and with these images, the VGG16, GoogLeNet, and ResNet models were trained. According to an evaluation of these models for different training dataset sizes, the ResNet model showed 100% pattern estimation accuracy. And, based on the different tomographic image qualities, all of the models showed almost 100% pattern estimation accuracy, even for low-quality images with unrecognizable fuel patterns. This study verified that an AI model can be effectively employed for accurate and fast partial-defect verification of fuel assemblies.

• 한국산업융합학회 논문집
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• 제25권5호
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• pp.783-789
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• 2022

In this study, STS316L rolled at five rolling degrees were treated with two types of subzero temperatures for 10, 30, and 60 minutes, respectively, and the dominant frequencies of elastic waves was investigated. The dominant frequency was higher as the subzero temperature was lower and the subzero treatment time was longer at each rolling degree. On the other hand, the dominant frequency was higher as the elongation decreased. In the time-frequency analysis for subzero temperature and time of the specimen with a rolling degree of 33%, the dominant frequency was higher at a subzero temperature of -196℃ than -50℃ regardless of subzero treatment time.

• Journal of information and communication convergence engineering
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• 제21권1호
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• pp.75-81
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• 2023

Video platforms, including YouTube, have a structure in which the number of video views is directly related to the publisher's profits. Therefore, video publishers induce viewers by using provocative titles and thumbnails to garner more views. The conventional technique used to limit such harmful videos has low detection accuracy and relies on follow-up measures based on user reports. To address these problems, this study proposes a technique to improve the accuracy of filtering harmful media using thumbnails, titles, and audio data from videos. This study analyzed these three pieces of multimodal information; if the number of harmful determinations was greater than the set threshold, the video was deemed to be harmful, and its upload was restricted. The experimental results showed that the proposed multimodal information extraction technique used for harmfulvideo filtering achieved a 9% better performance than YouTube's Restricted Mode with regard to detection accuracy and a 41% better performance than the YouTube automation system.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2022년도 제66차 하계학술대회논문집 30권2호
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• pp.285-288
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• 2022

최근 코로나 확진자가 감소함에 따라 집합금지 명령이 해제되고 단계적 일상 회복이 진행되고 있다. 이에 맞춰 온라인 수업을 진행하던 학교들이 대면 수업으로 전환됨에 따라 학생들이 학교로 돌아오게 되었다. 하지만 학교에 처음 온 학생들은 학교 주변 상권에 대해 잘 모르는 경향이 있다. 본 논문에서는 이러한 학생들의 고민을 줄여주기 위하여 카테고리별로 맞춤 식당을 추천해주는 서비스 개발하였다. Kotlin을 활용한 안드로이드 애플리케이션 형태로 개발하였으며, 네이버 지도를 활용하여 식당의 위치를 알려주도록 하였다. 또한 Firebase를 활용한 게시판을 통해 소통의 창구를 마련하고 간단한 게임 등을 통해 학우들 간의 친밀도를 높일 수 있는 콘텐츠를 제공하였다.