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检索条件"主题词=Detection Algorithms"

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Automated beat onset and peak detection algorithm for field-collected photoplethysmograms

Automated beat onset and peak detection algorithm for field-...

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Liangyou Chen Andrew T. Reisner Jaques Reifman USAMRMC Telemedicine and Advanced Technology Research Center Fort Detrick MD USA Department of Emergency Medicine Massachusetts General Hospital Boston MA USA USAMRMC ATTN: MCMR-TT TATRC Fort Detrick MD USA

Recent reports suggest that photoplethysmo-graphy (PPG), which is a component of routine pulse oximetry, may be useful for detecting hypovolemia. An essential step in extracting and analyzing common PPG features is the robust identification of onset and peak locations of the vascular beats, despite varying beat morphologies and major oscillations in the baseline. Some prior reports used manual analysis of the PPG waveform; however, for systematic widespread use, an automated method is required. In this paper, we report an algorithm that automatically detects beat onsets and peaks from noisy field-collected PPG waveforms. We validated the algorithm by clinician evaluation of 100 randomly selected PPG waveform samples. For 99% of the beats, the algorithm was able to credibly identify the onsets and peaks of vascular beats, although the precise locations were ambiguous, given the very noisy data from actual clinical operations. The algorithm appears promising, and future consideration of its diagnostic capabilities and limitations is warranted.

关键词： detection algorithms Biomedical measurements Bioinformatics Morphology Arterial blood pressure Medical diagnostic imaging Pulse measurements USA Councils Robustness Patient monitoring

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detection of lane-blocking on freeway segments using relative speed and lane changing trajectory

Detection of lane-blocking on freeway segments using relativ...

引用

International Conference on ITS Telecommunications (ITST)

作者： S. Thajchayapong J. A. Barria Department of Electrical and Electronics Engineering Imperial College London London UK

This paper proposes and assesses a lane-blocking detection methodology using relative speed and the correlations of lane changing trajectories of the vehicles to detect a lane-blocking incident. Using a microscopic traffic simulation environment, we show that the proposed algorithm has higher detection rate and lower false alarm rate than an existing algorithm using lane changing probabilities when the pre-determined window size is small. The proposed algorithm also performs well even when the relative speed and the lane information are available only from a fraction of the complete population of vehicles.

关键词： Traffic control Road vehicles Vehicle detection detection algorithms Detectors Velocity measurement Satellite navigation systems Wireless communication Position measurement Automotive engineering

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A Danger Model Based Anomaly detection Method for Wireless Sensor Networks

A Danger Model Based Anomaly Detection Method for Wireless S...

引用

International Symposium on Knowledge Acquisition and Modeling, KAM

作者： Kui Zhang College of Computer Science and Technology Wuhan University of Science and Engineering Wuhan China

Wireless sensor network (WSN) is the hot research subject in the field of network technologies currently, and its security problem also attracts more attentions. Especially, intrusion detection in wireless sensor networks remains an open problem. In this paper, we study a novel danger model based anomaly detection algorithm for wireless sensor networks. The danger model is built on a sensitive tissue(ST). The sensitive tissue consists of a population of sensitive cells(SCs) that are abstracted characteristics from a node of wireless sensor networks which are sensitive to attacks. ST plays a role as an interface between problems and immune cells for danger recognition and estimation. The results of the application of this novel model to the detection of the syscalls data show that the model is valid.

关键词： Wireless sensor networks Immune system Intrusion detection Biomedical monitoring Remote monitoring Data security detection algorithms Protection Information security Biological system modeling

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Incremental Clone detection

Incremental Clone Detection

引用

(CSMR) European Conference on Software Maintenance and Reengineering

作者： Nils Göde Rainer Koschke University of Brethemen Germany University of Bremen Germany

Finding, understanding and managing software clones -- passages of duplicated source code - is of large interest in research and practice. There is an abundance of techniques to detect clones. However, all these techniques are limited to a single revision of a program. When the code changes, the analysis must be run again from scratch even though only small parts may have changed. In this paper, we present an incremental clone detection algorithm, which detects clones based on the results of the previous revision's analysis. Moreover, it creates a mapping between clones of one revision to the next, supplying information about the addition and deletion of clones. Our empirical results demonstrate that the incremental technique requires considerably less time than a non-incremental approach if the changes do not exceed a certain fraction of the source code. An incremental analysis is useful for on-the-fly detection and evolutionary clone analysis. On-the-fly detection may be integrated in an IDE and allows to re-run clone detection immediately when a programmer saves his changes or even while he/she is typing. In evolutionary clone analysis, many revisions of a system need to be analyzed in order to understand how clones evolve.

关键词： Cloning Software maintenance Tree graphs Conference management detection algorithms Algorithm design and analysis Programming profession Information analysis Detectors Tree data structures

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On the Influence of Region Mismatch at Training and Testing in Region-Related Concept detection

On the Influence of Region Mismatch at Training and Testing ...

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International Conference on Computational Intelligence and Natural Computing, CINC

作者： Zan Gao Zhicheng Zhao Tao Liu Xiaoming Nan Anni Cai School of Information and Communication Engineering BUPT Beijing China

A great deal of region-related concept detection algorithms have been proposed so far, but there are few of them concerning about the problem of mismatched regions at training and testing stages. In order to investigate the mismatch problem in region-related concept detection, we introduce three kinds of methods to annotate the datasets, and then conduct experiments on differently annotated training and testing datasets. We find from these experiments that the detection performance is the best when the regions of a region-related concept are well defined and matched during training and testing, or the detection performance will be decreased. Based on these observations, we propose a fusion scheme to combine the results of classifiers trained with datasets which are annotated by different methods. Experiments on Trecvid-2007 test corpus show that the proposed fusion scheme can obtain performance improvement up to 6~12%.

关键词： Testing Concrete detection algorithms Feature extraction Telephony Information retrieval Computational intelligence Support vector machines Support vector machine classification Video sequences

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A low-power implantable event-based seizure detection algorithm

A low-power implantable event-based seizure detection algori...

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International IEEE/EMBS Conference on Neural Engineering, CNE

作者： Shriram Raghunathan Matthew P. Ward Kaushik Roy Pedro P. Irazoqui Department of Biomedical Engineering Purdue University West Lafayette IN USA Epartment of Electrical and Computer Engineering Purdue University West Lafayette IN USA

Closed-loop neurostimulation has shown great promise as an alternate therapy for over 30% of the epileptic patient population that remain non-responsive to other forms of treatment. We present an event-based seizure detection algorithm that can be implemented in real-time using low power digital CMOS circuits to form an implantable epilepsy prosthesis. Seizures are detected by classifying and marking out dasiaeventspsila in the recorded local field potential data and measuring the inter-event-intervals (IEI). The circuit implementation can be programmed post-implantation to custom fit the thresholds for detection. Hippocampal depth electrode recordings are used to validate the efficacy of a designed hardware prototype and thresholds are tuned to produce less than 5% false positives from recorded data.

关键词： detection algorithms Medical treatment Event detection Frequency Neurons Biomedical engineering Epilepsy Circuits Electrodes Hardware

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C2A: Controlled conservative advancement for continuous collision detection of polygonal models

C2A: Controlled conservative advancement for continuous coll...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Min Tang Young J. Kim Dinesh Manocha Department of Computer Science and Engineering Ewha Womans University Seoul South Korea Department of Computer Science North Carolina State University Chapel Hill USA

We present a simple and fast algorithm to perform continuous collision detection between polygonal models undergoing rigid motion for interactive applications. Our approach can handle all triangulated models and makes no assumption about the underlying geometry and topology. The algorithm uses the notion of conservative advancement (CA), originally developed for convex polytopes. We extend this formulation to general models using swept sphere volume hierarchy and present a compact formulation to compute the motion bounds along with a novel controlling scheme. We have implemented the algorithm and highlight its performance on various benchmarks. In practice, our algorithm can perform continuous collision queries in few milli-seconds on models composed of tens of thousands of triangles.

关键词： Charge coupled devices Motion planning Motion detection Solid modeling detection algorithms Motion control Geometry Topology Robot motion Layout

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Iterative detection for OFDMA Uplink with Frequency Offsets

Iterative Detection for OFDMA Uplink with Frequency Offsets

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IEEE Conference on Wireless Communications and Networking

作者： S. Ahmed Li Zhang School of Electronics and Electrical Engineering University of Leeds UK

In this work, we propose an iterative algorithm for the detection of transmitted symbols at the uplink of an orthogonal frequency-division multiple access (OFDMA) system. The algorithm allows distinct frequency-offsets (FO)s from each user that cause self- and multiple-access-interference. The proposed algorithm squeezes the interference of subcarrier k into 2D + 1 nearby subcarriers by preprocessing the received signal, which yields a banded structure interference matrix. This banded structure is exploited to realize a low complexity iterative soft-interference-cancellation minimum mean-squared error (SIC-MMSE) equalizer that can be used in Turbo equalization. Simulation results show that the bit-error-rate (BER) performance of the proposed algorithm outperforms existing detection algorithms and is very much close to the zero-FO frequency- domain-equalization (zero-FO-FDE) at low computational cost.

关键词： Interference Iterative algorithms Equalizers Computational complexity Matrix decomposition Bit error rate detection algorithms OFDM Sparse matrices Filters

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A New Joint detection Algorithm of Conveyer Belt X-Ray Imaging Using the BP Neural Networks

A New Joint Detection Algorithm of Conveyer Belt X-Ray Imagi...

引用

Congress on Image and Signal Processing, CISP

作者： Xian-guo Li Chang-yun Miao Yan Zhang Tianjin Polytechnic University Tianjin Tianjin CN Department of Electronics & Information Engineering Tianjin Institute of Urban Constructions Tianjin China

A new joint detection algorithm of conveyer belt with steel ropes using the BP(back propagation) neural networks model in X-ray imaging system is proposed. Detecting the state of conveyer belt is important in production process such as coal mine. And the joint detection is a primary task for further processing. Because of the neural networks' massive parallelism and easy implementation, this paper uses the BP neural networks to implement the joint detection. The result shows that, the correct recognition rate of the joint image applying the trained neural network is up to 100%, and the detecting speed is very rapid. This new algorithm for joint detecting can greatly improve the performance of processing, especial for the on-line nondestructive detection of product line. And the result demonstrates that the algorithm is effective.

关键词： detection algorithms Belts X-ray imaging Neural networks Steel Production Image recognition Optical imaging X-ray detection X-ray detectors

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The Study of Spatial Outliers detection Based on Knowledge Discovery and Data Mining

The Study of Spatial Outliers Detection Based on Knowledge D...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Li Zhang Zhong Qu Library Hezhou University Hezhou Guangxi China College of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China

This paper proposes spatial outliers detection method of studying multiple non-spatial attributes based on special objects. The spatial outliers detection algorithm based on the Mahalanobis distance is proposed in this paper. The simulated experiment results demonstrate this method is feasible and effective, simultaneously the time complexity of center algorithm is analysed. Except the research type mentioned, spatial outliers detection still includes time-order data and time-space data outliers detections, which are related to the attribute values of other neighbors.

关键词： Data mining detection algorithms Object detection Spatial databases Graph theory Testing Scattering Fuzzy systems Libraries Analytical models

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