• 제목/요약/키워드: journal profiling

검색결과 1,244건 처리시간 0.025초

NMR Metabolomic Profiles for Quality Control of Korean Green Tea (Camellia sinensis) Classified by the Plucking Season

  • Choi, Kwang-Ho;Park, Ji Su;Kim, Hyeon Su;Choi, Ye Hun;Jeon, Jun Hyeok;Lee, Joon-Hwa
    • 한국자기공명학회논문지
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    • 제21권4호
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    • pp.119-125
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    • 2017
  • The plucking season of green tea leaves is one of the important parameters that decide their metabolic diversity, quality, and prices. The effects of plucking sghlwleasons on green tea metabolites were investigated through metabolite profiling by $^1H$ NMR spectroscopy. The orthogonal projection on latent structure-discriminant analysis (OPLS-DA) showed clear discriminations of green teas by three different grades depending on plucking seasons: Ujeon, Sejak, and Jungjak. These results suggested that the nine peak groups could be used for diagnostics for identification of high quality Ujeon grade of green tea.

프로파일 기반 악성 로더 공격탐지 및 필터링 기법 (Profile based Malicious Loader Attack Detection and Filtering Method)

  • 윤이중;김요식
    • 융합보안논문지
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    • 제6권2호
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    • pp.21-29
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    • 2006
  • 소프트웨어를 대상으로 하는 다양한 공격방법이 등장하고 있는 가운데 컴퓨터 소프트웨어에 대한 불법 조작 및 변조 등의 위협이 증가하고 있다. 특히, 온라인상에서 동작하는 어플리케이션 클라이언트를 대상으로 악의적인 로더 프로그램을 이용하여 프로그램의 코드를 조작하고, 흐름을 변조하여 정상적인 동작을 방해하는 행위가 날로 늘어나고 있다. 본 논문에서는 악의적인 용도로 사용되는 로더가 가지는 패턴을 분석하여 시그너처를 생성하고, 변형된 패턴을 탐지할 수 있고 시그너처 기법을 보완한 프로파일 기반의 탐지 기법을 제시한다.

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Recent advances in deep learning-based side-channel analysis

  • Jin, Sunghyun;Kim, Suhri;Kim, HeeSeok;Hong, Seokhie
    • ETRI Journal
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    • 제42권2호
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    • pp.292-304
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    • 2020
  • As side-channel analysis and machine learning algorithms share the same objective of classifying data, numerous studies have been proposed for adapting machine learning to side-channel analysis. However, a drawback of machine learning algorithms is that their performance depends on human engineering. Therefore, recent studies in the field focus on exploiting deep learning algorithms, which can extract features automatically from data. In this study, we survey recent advances in deep learning-based side-channel analysis. In particular, we outline how deep learning is applied to side-channel analysis, based on deep learning architectures and application methods. Furthermore, we describe its properties when using different architectures and application methods. Finally, we discuss our perspective on future research directions in this field.

실시간 주행성 분석에 기반한 6×6 스키드 차량의 야지 고속 자율주행 방법 (A High-Speed Autonomous Navigation Based on Real Time Traversability for 6×6 Skid Vehicle)

  • 주상현;이지홍
    • 제어로봇시스템학회논문지
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    • 제18권3호
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    • pp.251-257
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    • 2012
  • Unmanned ground vehicles have important military, reconnaissance, and materials handling application. Many of these applications require the UGVs to move at high speeds through uneven, natural terrain with various compositions and physical parameters. This paper presents a framework for high speed autonomous navigation based on the integrated real time traversability. Specifically, the proposed system performs real-time dynamic simulation and calculate maximum traversing velocity guaranteeing safe motion over rough terrain. The architecture of autonomous navigation is firstly presented for high-speed autonomous navigation. Then, the integrated real time traversability, which is composed of initial velocity profiling step, dynamic analysis step, road classification step and stable velocity profiling step, is introduced. Experimental results are presented that demonstrate the method for a $6{\times}6$ autonomous vehicle moving on flat terrain with bump.

광섬유 공초점 간섭 현미경과 위상 변위법을 결합한 표면 검색 (Surface profiling by the phase shifting method in fiber-optical confocal scanning interference microscopes)

  • 김대찬;이승걸
    • 한국광학회지
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    • 제10권3호
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    • pp.201-207
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    • 1999
  • 단일모드 광섬유와 결합기를 이용하여 간결한 구조의 광섬유 공초점 간섭 현미경을 구성하였으며, 위상 변위법을 응용한 표면 검색 방법을 제안하여 통신용의 반도체 레이저와 같이 비교적 긴 파장의 광원과, 낮은 NA의 대물렌즈를 사용하더라도 정밀한 시료 표면 검색이 가능함을 보였다. 이때 시료 표면의 높낮이는 시료로부터 반사된 빛의 위상으로부터 결정되며, 종래의 공초점 현미경에 비하여 주사시간을 크게 단축할 수 있었다. 끝으로 종래의 방법에 비해 제안된 방법은 시료의 반사율 변화에 덜 민감함을 확인할 수 있었다.

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대형 Tubular K-Joint의 피로수명에 관한 연구 (A Study on the Fatigue Life of Large-Scale Tubular K-joints)

  • 임성우;장인화
    • 한국해양공학회지
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    • 제22권2호
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    • pp.58-64
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    • 2008
  • Large-scale tests of welded tubular K-joint sunder balanced in-plane bending braces were carried out to observe the fatigue behavior of the API 2W Gr.60 steel plate produced by POSCO. Toe grinding and weld profiling were used to improve the fatigue life of a tubular K-joint. The effects of the steel grade and chord wall thickness on the fatigue life were also investigated. The present results were compared with the UK DEn design curve.

영양성분 프로파일링 기반 사료추천 알고리듬 (Nutrient Profiling-based Pet Food Recommendation Algorithm)

  • 송희석
    • Journal of Information Technology Applications and Management
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    • 제25권4호
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    • pp.145-156
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    • 2018
  • This study proposes a content-based recommendation algorithm (NRA) for pet food. The proposed algorithm tries to recommend appropriate or inappropriate feed by using collective intelligence based on user experience and prior knowledge of experts. Based on the physical and health status of the dogs, this study suggests what kind of nutrients are necessary for the dogs and the most recommended pet food containing these nutrients. Performance evaluation was performed in terms of recall, precision, F1 and AUC. As a result of the performance evaluation, the AUC and F1 value of the proposed NRA was 15% and 42% higher than that of the baseline model, respectively. In addition, the performance of NRA is shown higher for recommendation of normal dogs than disease dogs.

멀티코어 시스템에서 TLB Lockdown에 의한 TLB Miss 영향 분석 (Investigation on TLB Miss Impact through TLB Lockdown in Multi-core Systems)

  • 송대영;박시형;김형신
    • 대한임베디드공학회논문지
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    • 제17권1호
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    • pp.59-65
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    • 2022
  • Virtual memory is used as the method to ensure the safety of the system through memory protection in the real-time system. TLB miss caused by using virtual memory makes the real-time system WCET more pessimistically. TLB lockdown can be applied as a method to improve this problem. However, processors with limited TLB lockdown entries, a selection criterion is needed to efficiently utilize the TLB lockdown entry. In this paper, the most frequently accessed virtual pages in the process are applied to the TLB lockdown by analyzing memory profiling. The results showed that micro data TLB miss stall cycle and main data TLB miss stall cycle of the processor decreased by at least 4.7% and up to 29.7%.

Resolution in Carrier Profiling Semiconductors by Scanning Spreading Resistance Microscopy and Scanning Frequency Comb Microscopy

  • Hagmann, Mark J.;Mousa, Marwan S.;Yarotski, Dmitry A.
    • Applied Microscopy
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    • 제47권3호
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    • pp.95-100
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    • 2017
  • High resolution measurements of the carrier profile in semiconductor devices is required as the semiconductor industry progresses from the 10-nm lithography node to 7-nm and beyond. We examine the factors which determine the resolution of the present method of scanning spreading resistance microscopy as well as such factors for the newer method of scanning frequency comb microscopy that is now under development. Also, for the first time, we consider the sensitivity of both methods to the location of heterogeneities in the semiconductor. In addition, mesoscopic effects on these measurements are considered for the first time. Two simple analytical models are extended to study the sensitivity to heterogeneities as well as mesoscopic effects.

프로파일링을 한 원통형 로울러의 탄성유체윤활 (I) (Elastohydrodynamic Lubrication of a Profiled Cylindrical Roller (I))

  • 박태조;김경웅
    • 대한기계학회논문집
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    • 제12권2호
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    • pp.262-270
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    • 1988
  • 본 연구에서는 필자들의 수치해석방법을 발전시켜 프로파일링을 한 로울러의 프로파일 시작점부근에서의 압력과 유막의 거동을 보다 상세하게 해석하고자 한다.이를 위하여, 수치해석시 로울러 길이방향의 분할을 불균일하게 하여 프로파일 시작점부근에서의 절점의 간격을 조밀하게 하였으며 윤활유의 압축성효과도 고려하였다.