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Development of cloud monitoring system for cosmic microwave background observations
Jeong Hoyong,Ahn Yongheon,Won Eunil,이경민 한국물리학회 2022 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.80 No.1
The cloud between a ground-based telescope and the sky signal, such as cosmic microwave background, can distort the measured temperature signal from the sky, or even obstruct it. We developed a cloud monitoring system for cosmic microwave background observations. This system uses infrared imaging sensors; therefore, it is independent of visible legibility and the monitoring is capable day and night. The sensors and their controller are protected by a weather-proof container and able to be installed at the bare ground exposed to the external environment. By our system, information of sky area covered by clouds can be provided for ground-based telescopes by 0.37◦ resolution. The design and fabrication of the cloud monitoring system as well as its initial performance are described.
정호용(Hoyong Jeong),류도현(Dohyun Ryu),허준범(Junbeom Hur) 한국정보보호학회 2020 정보보호학회논문지 Vol.30 No.6
클라우드 컴퓨팅 환경에서 기계학습 서비스를 제공하는 Machine-Learning-as-a-Service(MLaaS) 등이 활발히 개발됨에 따라 보다 다양한 분야에서 인공지능 기술을 손쉽고 효과적인 방법으로 활용할 수 있게 되었다. 클라우드 환경에서는 가상화 기술을 통해 각 사용자에게 논리적으로 독립된 컴퓨팅 공간을 제공하는데, 최근 시스템의 취약점을 이용해 클라우드 테넌트(tenant) 사이에 다양한 부채널이 존재할 수 있다는 연구 결과가 발표되고 있다. 본 논문에서는 이러한 멀티-테넌시(multi-tenancy) 환경에서 멜트다운 취약점을 이용하여 딥러닝 모델의 내부 정보를 추출할 수 있는 현실적인 공격 시나리오를 제시한다. 이후 TensorFlow 딥러닝 서비스에 대한 실험을 통해 92.875%의 정확도와 1.325kB/s의 속도로 인공신경망의 모든 정보를 추출할 수 있음을 보인다. Cloud computing technology plays an important role in the deep learning industry as deep learning services are deployed frequently on top of cloud infrastructures. In such cloud environment, virtualization technology provides logically independent and isolated computing space for each tenant. However, recent studies demonstrate that by leveraging vulnerabilities of virtualization techniques and shared processor architectures in the cloud system, various side-channels can be established between cloud tenants. In this paper, we propose a novel attack scenario that can steal internal information of deep learning models by exploiting the Meltdown vulnerability in a multi-tenant system environment. On the basis of our experiment, the proposed attack method could extract internal information of a TensorFlow deep-learning service with 92.875% accuracy and 1.325kB/s extraction speed.
Comparison the Mapping Accuracy of Construction Sites Using UAVs with Low-Cost Cameras
Jeong, Hohyun,Ahn, Hoyong,Shin, Dongyoon,Choi, Chuluong The Korean Society of Remote Sensing 2019 大韓遠隔探査學會誌 Vol.35 No.1
The advent of a fourth industrial revolution, built on advances in digital technology, has coincided with studies using various unmanned aerial vehicles (UAVs) being performed worldwide. However, the accuracy of different sensors and their suitability for particular research studies are factors that need to be carefully evaluated. In this study, we evaluated UAV photogrammetry using smart technology. To assess the performance of digital photogrammetry, the accuracy of common procedures for generating orthomosaic images and digital surface models (DSMs) using terrestrial laser scanning (TLS) techniques was measured. Two different type of non-surveying camera(Smartphone camera, fisheye camera) were attached to UAV platform. For fisheye camera, lens distortion was corrected by considering characteristics of lens. Accuracy of orthoimage and DSM generated were comparatively analyzed using aerial and TLS data. Accuracy comparison analysis proceeded as follows. First, we used Ortho mosaic image to compare the check point with a certain area. In addition, vertical errors of camera DSM were compared and analyzed based on TLS. In this study, we propose and evaluate the feasibility of UAV photogrammetry which can acquire 3 - D spatial information at low cost in a construction site.
Hoyong Kim,Han-Seob Jeong,Seon-Hong Kim,Se-Yeong Park,Joon Weon Choi,In-Gyu Choi 한국산림바이오에너지학회 2020 산림바이오에너지 Vol.30 No.2
In this study, ethanol organosolv lignin (EOL) yield and structural characteristics of EOL depending on the production condition were evaluated to understand the lignin fractionation behavior and to determine the optimal condition for the production of phenolic compounds. EOL yield was enlarged until combined severity factor (CSF) reached 1.2, while molecular weight and nitrobenzene oxidation (NBO) yield of EOL were declined more than a half compare to those from CSF 0 to 0.6. Both EOL and NBO yields were predictable as a function of CSF with very high coefficient of determination. Concentration of phenolic compounds released from pyrolysis GC/MS was relatively stable until reaching CSF 1.5. However, it was significantly affected by not only CSF but also the concentration of acid used for the fractionation of EOL. Therefore, in order to produce phenolic compounds from EOL, production condition should be controlled between CSF 1.2 and 1.5 with low acid concentration.
정용군,최호용 충북대학교 컴퓨터 정보통신 연구소 1998 컴퓨터정보통신연구 Vol.6 No.1
본 논문에서는 움직임 추정(motion estimation), 오브젝트 부호화(object coding), 벡터 양자화(vector quantization)를 통해 저비트율에서의 고압축 고화질을 얻기 위한 오브젝트 베이스 동화상 부호화 방법을 제안한다. 오브젝트 부호화에서는 움직임 추정과 예지 검출 처리로부터 움직이는 물체를 오브젝트로서 추출한다. 오브젝트의 에지 검출에서는 (1)움직임 벡터를 이용한 블록 단위, (2)휘도 신호 차를 이용한 화소 단위, 의 2단계 에지 검출을 통해 연산량을 삭감한다. 추출된 오브젝트는 벡터 양자화를 통하여 정보량을 더욱 압축한다. 본 방법에 대해 부호화 비트율 및 벡터 양자화에서는 코드워드 수와 화질에 관계를 평가하였다. 본 알고리듬을 40kbps 이하의 저비트율에서 QCIF(186x144 for Y, 88x7 2 for Cb, Cr) 포맷을 대상으로 실험한 결과, 양호한 화질을 얻을 수 있었다.