• 제목/요약/키워드: center detection

검색결과 3,723건 처리시간 0.04초

Improvement of Antigen Blotting in a Tissue Blot Immunobinding Assay for the Detection of Two Chili Pepper Viruses

  • Han, Jung-Heon;Shin, Jun-Sung;Kim, Young-Ho;Kim, Byung-Dong
    • Journal of Microbiology and Biotechnology
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    • 제17권11호
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    • pp.1885-1889
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    • 2007
  • The tissue blot immunobinding assay (TBIA) is widely used for the detection and localization of plant viruses in various plant tissues. The basic experimental procedures of TBIA sampling and blotting were simplified using commercially available micropipette tips. This method was termed the ring-blot immunobinding assay (R-BIA), as the blot on the membrane forms a ring shape. The detection efficacy of R-BIA was tested for two chili pepper viruses, pepper mild mottle tobamovirus (PMMoV) and pepper mottle potyvirus (PepMoV), following the optimized serological procedures of TBIA (length of the incubation period and BSA concentration, and primary and secondary antibodies). Sensitivity of the R-BIA was about 1 ng/ml of purified PMMoV in pepper leaf sap from a healthy pepper plant. R-BIA also showed high specificity in the detection of PMMoV and PepMoV. Moreover, the modified sampling and blotting procedures were simpler and more reliable than other TBIA methods (such as whole-leaf blotting and crushed-leaf blotting), suggesting that the R-BIA may be used for medium- to large-scale detection of plant viruses in laboratories with minimal facilities.

가변 Threshold를 이용한 Wafer Align Mark 중점 검출 정밀도 향상 연구 (A Study on Improving the Accuracy of Wafer Align Mark Center Detection Using Variable Thresholds)

  • 김현규;이학준;박재현
    • 반도체디스플레이기술학회지
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    • 제22권4호
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    • pp.108-112
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    • 2023
  • Precision manufacturing technology is rapidly developing due to the extreme miniaturization of semiconductor processes to comply with Moore's Law. Accurate and precise alignment, which is one of the key elements of the semiconductor pre-process and post-process, is very important in the semiconductor process. The center detection of wafer align marks plays a key role in improving yield by reducing defects and research on accurate detection methods for this is necessary. Methods for accurate alignment using traditional image sensors can cause problems due to changes in image brightness and noise. To solve this problem, engineers must go directly into the line and perform maintenance work. This paper emphasizes that the development of AI technology can provide innovative solutions in the semiconductor process as high-resolution image and image processing technology also develops. This study proposes a new wafer center detection method through variable thresholding. And this study introduces a method for detecting the center that is less sensitive to the brightness of LEDs by utilizing a high-performance object detection model such as YOLOv8 without relying on existing algorithms. Through this, we aim to enable precise wafer focus detection using artificial intelligence.

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Flow-based Anomaly Detection Using Access Behavior Profiling and Time-sequenced Relation Mining

  • Liu, Weixin;Zheng, Kangfeng;Wu, Bin;Wu, Chunhua;Niu, Xinxin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제10권6호
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    • pp.2781-2800
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    • 2016
  • Emerging attacks aim to access proprietary assets and steal data for business or political motives, such as Operation Aurora and Operation Shady RAT. Skilled Intruders would likely remove their traces on targeted hosts, but their network movements, which are continuously recorded by network devices, cannot be easily eliminated by themselves. However, without complete knowledge about both inbound/outbound and internal traffic, it is difficult for security team to unveil hidden traces of intruders. In this paper, we propose an autonomous anomaly detection system based on behavior profiling and relation mining. The single-hop access profiling model employ a novel linear grouping algorithm PSOLGA to create behavior profiles for each individual server application discovered automatically in historical flow analysis. Besides that, the double-hop access relation model utilizes in-memory graph to mine time-sequenced access relations between different server applications. Using the behavior profiles and relation rules, this approach is able to detect possible anomalies and violations in real-time detection. Finally, the experimental results demonstrate that the designed models are promising in terms of accuracy and computational efficiency.

분포형 광음향센싱 기반 부분방전 모니터링 기술 연구 (Partial Discharge Monitoring Technology based on Distributed Acoustic Sensing)

  • 김희운;이주영;정효영;김영호;김명진
    • 센서학회지
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    • 제31권6호
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    • pp.441-447
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    • 2022
  • This study describes a novel method for detecting and measuring partial discharge (PD) on an electrical facility such as an insulated power cable or switchgear using fiber optic sensing technology, and a distributed acoustic sensing (DAS) system. This method has distinct advantages over traditional PD sensing techniques based on an electrical method, including immunity to electromagnetic interference (EMI), long range detection, simultaneous detection for multiple points, and exact location. In this study, we present a DAS system for PD detection with performance evaluation and experimental results in a simulated environment. The results show that the system can be applied to PD detection.

사이버 위협 탐지대응시간 모델링 (Cyber threat Detection and Response Time Modeling)

  • 한충희;한창희
    • 인터넷정보학회논문지
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    • 제22권3호
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    • pp.53-58
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    • 2021
  • 보안관제 분야의 실제 업무활동에 대해서는 거의 연구가 없는 실정이다. 이에 본 논문에서는 보안관제의 위협정보 탐지 대응시간 모델링을 통해 적정 투입인력 규모 산정에 기여하고 최신 보안솔루션 투입시의 효과성 분석 등에 활용할 수 있는 실질적인 연구 방법론을 제시하고자 한다. 보안관제센터에서 수행하는 전체 위협정보 탐지대응시간은 TIDRT(Total Intelligence Detection & Response Time)로 정의한다. 전체 위협정보 탐지 대응시간(TIDRT)는 내부 위협정보 탐지대응시간(IIDRT, Internal Intelligence Detection & Response Time)과 외부 위협정보(EIDRT, External Intelligence Detection & Response Time)의 합으로 구성된다. 내부위협정보 탐지대응시간(IIDRT)는 다섯 단계의 소요시간의 합으로 계산할 수 있다. 본 연구의 궁극적인 목표는 보안관제센터의 주요한 업무활동들을 수식으로 모델링하여 보안관제센터의 사이버 위협정보 탐지대응시간 계산식을 산정하는데 있다. 2장에서는 선행연구를 살펴보고, 3장에서는 전체 위협정보 탐지대응시간의 계산식을 모델링한다. 4장에서 결론으로 끝을 맺는다.

코호넨 네트워크 및 시간 지연 신경망을 이용한 움직이는 물체의 중심점 탐지 및 동작특성 분석에 관한 연구 (A Study on Center Detection and Motion Analysis of a Moving Object by Using Kohonen Networks and Time Delay Neural Networks)

  • 황정구;김종영;장태정
    • 산업기술연구
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    • 제21권B호
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    • pp.91-98
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    • 2001
  • In this paper, center detection and motion analysis of a moving object are studied. Kohonen's self-organizing neural network models are used for the moving objects tracking and time delay neural networks are used for dynamic characteristic analysis. Instead of objects brightness, neuron projections by Kohonen Networks are used. The motion of target objects can be analyzed by using the differential neuron image between the two projections. The differential neuron image which is made by two consecutive neuron projections is used for center detection and moving objects tracking. The two differential neuron images which are made by three consecutive neuron projections are used for the moving trajectory estimation. It is possible to distinguish 8 directions of a moving trajectory with two frames and 16 directions with three frames.

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Motion Compensation Based on Signal Processing Method for Airborne SAR

  • Song, Won-Gyu;Shin, Hee-Sub;Lee, Ho-Jin;Lim, Jong-Tae
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.1199-1201
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    • 2005
  • In the synthetic aperture radar (SAR) system, the motion error is the main phase error sources and the motion compensation is very important. The phase gradient autofocus (PGA) is a state of art technique for phase error correction of SAR. It exploits the redundancy of the phase-error information among range bins by selecting the strongest scatter for each range bin and synthesizes them. The motivation of this paper is based on the observation that the redundancy of phase error is also among the cross-range direction. Moreover, the proposed method applies the weighting function to better utilize the phase error information. The validity of the proposed scheme for PGA is tested with some numerical simulation.

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Rapid, Sensitive, and Specific Detection of Salmonella Enteritidis in Contaminated Dairy Foods using Quantum Dot Biolabeling Coupled with Immunomagnetic Separation

  • Kim, Hong-Seok;Chon, Jung-Whan;Kim, Hyunsook;Kim, Dong-Hyeon;Yim, Jin-Hyuk;Song, Kwang-Young;Kang, Il-Byung;Kim, Young-Ji;Lee, Soo-Kyung;Seo, Kun-Ho
    • Journal of Dairy Science and Biotechnology
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    • 제33권4호
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    • pp.271-275
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    • 2015
  • Colloidal semiconductor CdSe-ZnS core-shell nanocrystal quantum dot (Qdot) are luminescent inorganic fluorophores that show potential to overcome some of the functional limitations encountered with organic dyes in fluorescence labeling applications. Salmonella Enteritidis has emerged as a major cause of human salmonellosis worldwide since the 1980s. A rapid, specific, and sensitive method for the detection of Salmonella Enteritidis was developed using Qdot as a fluorescence marker coupled with immunomagnetic separation. Magnetic beads coated with anti-Salmonella Enteritidis antibodies were employed to selectively capture the target bacteria, and biotin-conjugated anti-Salmonella antibodies were added to form sandwich immune complexes. After magnetic separation, the immune complexes were labeled with Qdot via biotin-streptavidin conjugation, and fluorescence measurement was carried out using a fluorescence measurement system. The detection limit of the Qdot method was a Salmonella Enteritidis concentration of $10^3$ colony-forming units (CFU)/mL, whereas the conventional fluorescein isothiocyanate-based method required over $10^5CFU/mL$. The total detection time was within 2 h. In addition to the potential for general nanotechnology development, these results suggest a new rapid detection method of various pathogenic bacteria from a complex food matrix.

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가우시안 배경혼합모델을 이용한 Tracking기반 사고검지 알고리즘의 적용 및 평가 (Measuring of Effectiveness of Tracking Based Accident Detection Algorithm Using Gaussian Mixture Model)

  • 오주택;민준영
    • 한국도로학회논문집
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    • 제14권3호
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    • pp.77-85
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    • 2012
  • 자동사고검지 알고리즘의 대부분은 사고가 발생했을 때 사고로 검지하지 못하고, 혼잡으로 검지하는 경우가 많다는 문제점을 가지고 있다. 또한 교통정보센터 운영자들은 교통사고검지시스템을 운영하면서 대부분 CCTV 육안감시 또는 운전자들의 신고에 의존하여 사고처리를 하고 있는 실정이다. 그 이유는 현재 운영되고 있는 교통사고검지시스템에서는 실제 사고가 아닌데도 불구하고, 사고라는 오검지 경고가 많이 발생되어 시스템 전체의 신뢰도가 떨어진다는 문제점이 있기 때문이다. 다시 말해 교통사고검지시스템의 알고리즘은 검지율(Detection probability)이 높아야 함과 동시에, 오검지율(False alarm probability)은 낮아야 하고, 정확한 사고지점과 시간을 검지해 낼 수 있어야 한다. 이에 본 연구는 검지율을 높이고 동시에, 오검지율을 낮추는 방법으로 기 개발된 가우시안 혼합모델(Gaussian Mixture Model)과 개별차량 Tracking을 이용하여 개발한 사고검지 알고리즘을 교통정보센터 관리시스템(Center Management System)에 적용하고, 실제 교통상황에서 사고검지율과 오검지의 빈도를 측정하여 그 효과를 검증 및 평가하고자 한다.

The Fluorescence Immunoassay of lung Cancer Serum Diomarkers using Quantum dots

  • Kang, Ji-Min;Ahn, Jin-Seok;Kim, Jin-Hoon;Kong, Won-Ho;Park, Keun-Chil;Kim, Won-Seog;Seo, Soo-Won
    • 대한의용생체공학회:의공학회지
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    • 제30권2호
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    • pp.122-128
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    • 2009
  • Cancer serum biomarkers have advanced our ability to more accurately predict tumor classification, prognostic/metastatic potential, and response potential to novel chemotherapies. Serum amyloid A (SAA) and Vascular endothelial growth factor (VEGF) have potential utility as a serum biomarker for lung cancer. Quantum dots, nanometer-sized crystals, have a high quantum yield, sensitivity, and pronounced photostability. The properties of quantum dots can be efficiently applied to the detection of serum biomarkers in immunoassays as fluorescent probe. We used quantum dots as fluorescent probes in immunoassays and attempted to detect serum amyloid A and vascular endothelial growth factor as serum biomarkers of lung cancer. This fluorescence immunoassay based on the properties of quantum dots is applicable to the detection of serum biomarkers for lung cancer. The fluorescence immunoassay with quantum dots should allow the efficient and specific detection of serum amyloid A (SAA) for the possible diagnosis of lung cancer.