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检索条件"主题词=Detection algorithms"

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Adaptive detection with time series models

Adaptive detection with time series models

引用

RADAR 2002

作者： S. de Waele P.M.T. Broersen Delft University of Technnology Netherlands

Adaptive detectors based on time series models can yield accurate detection algorithms, if an appropriate model order and model type is used. Using models of a model order that is either too high or too low will result in reduced detection performance. Statistical order selection offers a practical solution for the adaptive selection of a model order from data. With the combined information criterion CIC as an order selection criterion an optimal trade-off of underfit and overfit is made. An adaptive detection algorithm has been developed that is based on this selected model. This detector has been compared to detectors based on fixed order models and detectors based on the periodogram in a simulation study. Also, the new detector has been applied to experimental data.

关键词： Detectors Testing Clutter detection algorithms Reflection Radar detection Time series analysis Appropriate technology Matched filters Additive noise

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Computational intelligence based anomaly detection for Building Energy Management Systems

Computational intelligence based anomaly detection for Build...

引用

International Symposium on Resilient Control Systems, ISRCS

作者： Ondrej Linda Dumidu Wijayasekara Milos Manic Craig Rieger University of Idaho Idaho Falls ID USA Idaho National Laboratory Idaho Falls ID USA

In the past several decades Building Energy Management Systems (BEMSs) have become vital components of most modern buildings. BEMSs utilize advanced microprocessor technology combined with extensive sensor data collection and communication to minimize energy consumption while maintaining high human comfort levels. When properly tuned and operated, BEMSs can provide significant energy savings. However, the complexity of the acquired sensory data and the overwhelming amount of presented information renders them difficult to adjust or even understand by responsible building managers. This inevitably results in suboptimal BEMS operation and performance. To address this issue, this paper reports on a research effort that utilizes Computational Intelligence techniques to fuse multiple heterogeneous sources of BEMS data and to extract relevant actionable information. This actionable information can then be easily understood and acted upon by responsible building managers. In particular, this paper describes the use of anomaly detection algorithms for improving the understandability of BEMS data and for increasing the state-awareness of building managers. The developed system utilizes modified nearest neighbor clustering algorithm and fuzzy logic rule extraction technique to automatically build a model of normal BEMS operations and detect possible anomalous behavior. In addition, linguistic summaries based on fuzzy set representation of the input values are generated for the detected anomalies which increase the understandability of the presented results.

关键词： Floors Pragmatics Temperature measurement Clustering algorithms Feature extraction detection algorithms

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A CMOS imager with focal-plane computation for feature detection

A CMOS imager with focal-plane computation for feature detec...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： A. Pesavento C. Koch Department of Electrical Engineering California Institute of Technology Pasadena CA Computation and Neural Systems Program California Institute of Technology Pasadena CA USA

ISBN: (纸本)0780366859

Feature detection and tracking is a fundamental problem in computer vision research. By detecting and tracking features in an image sequence it is possible to recover information about both the motion of the viewer and the structure of the environment. We designed, fabricated and tested a CMOS imager with analog VLSI focal-plane computation for feature detection. The chip implements a feature detection algorithm that is suitable for integration in a compact analog VLSI chip. We review the algorithm, its analog VLSI implementation and experimental results from the chip.

关键词： Computer vision Cameras Very large scale integration Eigenvalues and eigenfunctions CMOS technology Image sequences Streaming media detection algorithms Brightness Motion detection

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Privacy-Aware Role Based Access Control Model: Revisited for Multi-Policy Conflict detection

Privacy-Aware Role Based Access Control Model: Revisited for...

引用

International Conference on Information Science and Applications (ICISA)

作者： Yoonjeong Kim Eunjee Song Major in Information Security Seoul Women''s University Seoul South Korea Department of Computer Science Baylor University Waco TX USA

ISBN: (纸本)9781424459421;9781424459438

Privacy-aware Role-based Access Control (P-RBAC) model is one of Role-Based Access Control (RBAC) model extensions that has been proposed to help the enforcement of privacy policies. Despite the enhanced privacy protection mechanism by P-RBAC, its pair-wise policy conflict detection algorithm has been pointed out as one of its limitations because conflicts within more than two policies are not detected. In this paper, we review and extend P-RBAC's existing conflict detection algorithm so that it can check conflicts in multiple policies. Our review includes the performance comparison on two conflict detection algorithms, triple-policy conflict detection vs. double-policy conflict detection. We find out that as the number of policies increases and the number of same condition variables in the policies increases, the running time complexity gets bigger. Especially for tripe-policy conflict, the probability of triple policy conflict also affects the complexity.

关键词： Access control Privacy detection algorithms Permission Power system modeling Performance analysis Protection Writing Information security Computer science

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Development of Automated Neonatal Sleep-Wake Cycle Intelligent detection Algorithm

Development of Automated Neonatal Sleep-Wake Cycle Intellige...

引用

International Conference on Sensing Technology, ICST

作者： Jiaxi Wu Xin Wang Ke Zhang Weimin Huang Lina Men Shixiong Chen School of Medicine The Chinese University of Hong Kong Shenzhen Shenzhen China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Chinese Academy of Sciences Shenzhen Institute of Advanced Technology Shenzhen China Department of Otolaryngology Shenzhen Children's Hospital Shenzhen China Department of Neonatology Shenzhen Children's Hospital Shenzhen China School of Medicine The Chinese University of Hong Kong Shenzhen

ISBN: (数字)9798350374827

ISBN: (纸本)9798350374834

While there are various algorithms for automatic identification of sleep-wake cycles based on electroencephalography (EEG), there is a notable lack of approaches utilizing amplitude-integrated electroencephalography (aEEG). As EEG is increasingly replaced by aEEG in many contexts due to its large data size and challenges in information capture, it is essential to advance sleep-wake cycle (SWC) detection algorithms based on aEEG. Previous research primarily established a threshold to differentiate between quiet sleep (QS) and non-QS, but this required manual adjustment of individual thresholds for each patient's data, leading to considerable inconvenience. Facing this challenge, the study developed an algorithm for the automatic identification of boundaries between QS and non-QS segments in the dataset. Each entry can have its own QS/non-QS boundary, eliminating the need for manual setting. The algorithm was developed under EEG recordings from seven neonates with post-menstrual ages ranging from 32 to 41 weeks. First, EEG data was converted into aEEG and subjected to smoothing. The upper and lower boundaries of the smoothed signal were utilized as the foundation for boundary assessment. The stable segment selection method was then applied to identify wide segments with limited variability, which were classified as QS periods. The analysis reveals that the detection algorithm performed well for extended QS periods (lasting over 15 minutes). In contrast, detection for shorter QS periods (less than 3 minutes) presented variability, with both false positives and false negatives observed. However, with proper adjustments, this method can effectively assist physicians in identifying suspicious QS phases and directly reviewing the corresponding video for validation.

关键词： Pediatrics Smoothing methods Sleep Manuals Medical services Electroencephalography Sensors Recording detection algorithms Monitoring

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Study on an Improved Single-phase Harmonic Current detection Algorithm

Study on an Improved Single-phase Harmonic Current Detection...

引用

International Conference on Computer Distributed Control and Intelligent Environmental Monitoring (CDCIEM)

作者： Zujun Ding Sen Wang Zhen Guo Guang Zeng Faculty of Electronic and Electrical Engineering Huaiyin Institute of Technology China Electrical Department Xi'an University of Technology Xi'an China

Bases on present harmonic detection algorithms, single-phase load current is decomposed and a novel single-phase current detection algorithm, which is simple, reliable, response quickly and favors the hardware realization, is proposed, in order to solve complexity of algorithm and slow response of common used single-phase harmonic detection methods. Meanwhile, as the method need to use low pass filter, an improved method is is analysed. By increasing time delay unit, the effect of 2nd harmonic was eliminated, and the cut-off frequency of the low-pass filter was increased without adding the filter order. The response time of improved detection was shorten about half period. Correctness and validity of the proposed method were verified through simulating and experiment.

关键词： Power harmonic filters Harmonic analysis detection algorithms Active filters Cutoff frequency Filtering theory

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Improving the Two-stage detection of Cyberattacks in SDN Environment Using Dynamic Thresholding

Improving the Two-stage Detection of Cyberattacks in SDN Env...

引用

International Conference on Ubiquitous Information Management and Communication (IMCOM)

作者： Tao Wang Yaokai Feng Kouichi Sakurai Kyushu University Fukuoka Japan

ISBN: (数字)9781665423182

ISBN: (纸本)9781665446198

In recent years, the DDoS (Distributed Denial of Service) attack continues to be one of the most dangerous threats even in the SDN (Software Defined Networking) environment. Many approaches have been proposed to deal with the DDoS attacks in the SDN environment. Among those approaches, the two-step detection, in which a trigger mechanism is added before the detection algorithm is called, is gaining more and more attention. In other words, it is the trigger, not the resource-consuming detection algorithm, that constantly monitors network traffic. Thus, the detection algorithm is only called when it is triggered. However, in the existing two-step methods, the trigger uses a static threshold to determine whether or not to start the detection process. In practice, it is difficult to determine an appropriate threshold, and the threshold has a decisive effect on the frequency of the detection process being called and ultimately, it impacts detection performance. In this paper, we propose a self-feedback dynamic thresholding system in which the threshold used in the trigger is dynamically adjusted based on the previous results of trigger and detection. Experimental results and our discussion show that our proposal significantly reduces the number of calls to the resource-consuming detection algorithm with no sacrifice of detection result.

关键词： Telecommunication traffic Information management Proposals detection algorithms Computer crime Software defined networking Monitoring

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Fast joint detection with cyclic reduction exploiting displacement structures

Fast joint detection with cyclic reduction exploiting displa...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Weidong Yang Sang-Youb Kim Guanghan Xu A. Kavak Department of Electrical and Computer Engineering University of Texas Austin Austin TX USA

Joint detection with the minimum-mean square error (MMSE) criterion has been explored in previous works. Yang, Liu, Xu and Kim (see Asilomar Conference on Signals, Systems and Computers, Asilomar, CA, 1999) discussed joint detection with cyclic reduction, which has been proved to be faster than the popular Cholesky decomposition based algorithm under many scenarios. In this paper, a faster version of cyclic reduction which exploits displacement structures is presented. The proposed fast algorithm is useful when the channel length is long. Simulation results are given for a wireless communication setup.

关键词： Equations detection algorithms Bismuth Computer errors Computational modeling Wireless communication Matrix decomposition Multiaccess communication Partitioning algorithms

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Exploiting the polarimetric information for the detection of ship targets in non-homogeneous SAR images

Exploiting the polarimetric information for the detection of...

引用

IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： M. Sciotti D. Pastina P. Lombardo Department INFOCOM University of Roma La Sapienza Rome Italy

Ship detection in polarimetric SAR images of non-homogeneous sea areas is considered. We demonstrate the impact of non-homogeneous sea features on the false alarm rate and the need of extracting the image structure. We thus introduce polarimetric segmentation procedures that cooperate with high-resolution polarimetric detection features for the control of the false alarms. Different polarimetric segmentation-plus-detection procedures are tested over real data to devise the appropriate method to exploit the polarimetric information.

关键词： Marine vehicles Image segmentation Detectors Testing Data mining Computer vision Sea surface detection algorithms Image edge detection Surveillance

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Improved blood cell detection method based on YOLOv5 algorithm

Improved blood cell detection method based on YOLOv5 algorit...

引用

IEEE Information Technology, Networking, Electronic and Automation Control Conference

作者： Meigen Huang Binjie Wang Jiangcheng Wan Cheng Zhou College of Computer Chongqing University of Posts and Telecommunications Chongqing China Laboratory of Broadband Network Innovation Chongqing China

The proposed blood cell target detection algorithm based on YOLOv5 addresses the issue of low average accuracy and serious miss detection due to small blood cells and serious cell adhesion in blood cell detection by target detection algorithms. By adding the CBAM (Convolutional Block Attention Module) to the YOLOv5 framework's backbone network and the BIFPN (bidirectional feature pyramid network) to the neck network, the algorithm improves the model's ability to extract features. The experimental results show that the average accuracy (mAP) of the improved YOLOv5 blood cell target detection algorithm is 89.9%, representing a increase over the native YOLOv5s type, and the recall rate and accuracy rate are also increased by 3.2% and 4.2%, respectively. This meets the requirements of the actual scene for blood cell detection.

关键词： Automation Adhesives Object detection Feature extraction Neck detection algorithms Blood

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