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检索条件"主题词=Detection algorithms"

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On detection algorithms for Spurious Retransmissions in TCP

On Detection Algorithms for Spurious Retransmissions in TCP

引用

IEEE Conference on Wireless Communications and Networking

作者： Zheng Wen Kwan L. Yeung Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong China

In TCP, a spurious packet retransmission can be caused by either spurious timeout (STO) or spurious fast retransmit (SFR). The “lost” packets are unnecessarily retransmitted and the evoked congestion control process causes network underutilization. In this paper, we focus on spurious retransmission detection. We first present a survey on some important and interesting spurious retransmission detection algorithms. Based on the insights obtained, we propose a novel yet simple detection algorithm called split-and-retransmit (SnR). SnR only requires a minor modification to the TCP sender while leaving the receiver intact. The key idea is to split the retransmitted packet into two smaller ones before retransmitting them. As the packet size is different, the ACK triggered will carry different ACK numbers. This allows the sender to easily distinguish between the original transmission and the retransmission of a packet without relying on, e.g., TCP options. We then compare our SnR with STODER, F-RTO and Newreno under both loss-free and lossy network environments. We show that our SnR is resilient to packet loss and yields good performance under various simulation settings.

关键词： detection algorithms Process control Wireless networks Communications Society Performance loss Protocols Bit error rate Propagation losses Delay effects Councils

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Investigation of Source detection algorithms for Gross Counting Portal Monitors

Investigation of Source Detection Algorithms for Gross Count...

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IEEE Sensors Applications Symposium, SAS

作者： C. G. Wahl D. Alderson L. Pibida

In recent years, heightened security concerns have prompted increased interest in radiation portal monitors, instruments capable of detecting, and in some cases identifying, gamma-ray and neutron-emitting radioactive material passing through them. Along with efficient and reliable physical detectors, such monitors need software capable of analyzing the resulting signals in order to effectively catch weak radioactive sources. The software should be able to distinguish between the sometimes subtle signals due to weak sources and the varying background. After investigating several possible source-detection algorithms, a program has been developed to locate signals from weakly radioactive sources in real time. By including corrections for background suppression due to trucks shielding the detector and changing background levels, this program is capable of detecting significantly weaker sources than current software. The limitations of this method will also be discussed.

关键词： detection algorithms Portals Radioactive materials Gamma ray detectors Gamma ray detection Radiation detectors Fluctuations Algorithm design and analysis Synthetic aperture sonar USA Councils

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Comparison of eyelid and eyelash detection algorithms for performance improvement of iris recognition

Comparison of eyelid and eyelash detection algorithms for pe...

引用

IEEE International Conference on Image Processing

作者： Tae-Hong Min Rae-Hong Park Department of Electronic Engineering Sogang University Seoul South Korea Interdisciplinary Program of Integrated Biotechnology Sogang University Seoul South Korea

Eyelids and eyelashes occluding the iris region are noise factors that degrade the performance of iris recognition. If they are incorrectly classified as the iris region, the false iris pattern information will increase, decreasing the recognition rate. Thus, reliable detection of eyelids and eyelashes is required to improve the performance of iris recognition. The objective of this paper is to present a research direction for reduction of noise factors based on analysis and performance comparison of existing eyelid and eyelash detection algorithms. With CASIA version 3 database we compare six existing eyelid and eyelash detection algorithms and analyze the characteristics and performance of each algorithm. The performance of each algorithm is evaluated in terms of different performance measures such as the decidability, the equal error rate, and the detection error trade-off curve.

关键词： Eyelids Eyelashes detection algorithms Iris recognition Performance analysis Algorithm design and analysis Degradation Pattern recognition Noise reduction Databases

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Comparison of three change detection algorithms for an electronics manufacturing process

Comparison of three change detection algorithms for an elect...

引用

IEEE International Symposium on Computational Intelligence in Robotics and Automation (CIRA)

作者： M. Ruusunen M. Paavola M. Pirttimaa K. Leiviska Control Engineering Laboratory University of Oulu Oulun yliopisto Finland Nokia Corporation Oulu Finland VTI Technologies Helsinki Finland

In a sequential manufacturing process, a product proceeds through different manufacturing stages. At these stages, sensors monitor the features of the product. In this paper, the information produced by the sensors is employed to detect abrupt changes in process variables. The developed algorithms contribute to an on-line application to a manufacturing system. A literature survey revealed the most common methods utilized in change detection. On-line applicability and transferability to new manufacturing lines are the most important features for real applications. During both on-line and off-line tests, some of the presented methods showed satisfactory results. Real-time, on-line manufacturing environment sets also its requirements for the applications. In the future, the possibility of combining expert knowledge with the aforementioned methods is the crucial point to study. The information thus received has usage in the preventive maintenance and quality control.

关键词： detection algorithms Manufacturing processes Testing Quality control Change detection algorithms Monitoring Preventive maintenance Event detection Signal processing Image edge detection

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Evaluating Fraud detection algorithms Using an Auction Data Generator

Evaluating Fraud Detection Algorithms Using an Auction Data ...

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IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： Sidney Tsang Gillian Dobbie Yun Sing Koh The University of Auckland

Online auction sites are a target for fraud. Researchers have developed fraud detection and prevention methods. However, there are difficulties when using either commercial or synthetic auction data to evaluate the effectiveness of these methods. When using commercial data, it is not possible to accurately identify cases of fraud. Using synthetic data, the conclusions drawn may not extend to the real world. The availability of realistic synthetic auction data, which models real auction data, will be invaluable for effective evaluation of fraud detection algorithms. We present an agent-based simulator that is capable of generating realistic English auction data. The agents and model are based on data collected from the Trade Me online auction site. We evaluate the generated data in two ways to show that it is similar to the Trade Me auction data we have collected. In addition, we demonstrate that the simulator can have additional agents added to simulate fraudulent behaviour, and be used to evaluate fraud detection algorithms: we implement three different fraud behaviours and three detection algorithms, and using the simulator, compare the ability of the detection algorithms to correctly identify fraudulent agents.

关键词： Correlation Generators Biological system modeling Data models detection algorithms Accuracy Conferences

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Research on pedestrian detection algorithms based on video

Research on pedestrian detection algorithms based on video

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International Conference on Computer Design and Applications (ICCDA)

作者： Jinhao Deng Juan Zhu School of Computer Science & Engineering South China University of Technology Guangzhou China

ISBN: (纸本)9781424471645

On the basic of the video traffic surveillance system, the pedestrian detection is a crucial part. A study on vehicle and pedestrian recognition based on back propagation (BP) neural network is presented in this paper, and the author puts forward an effective algorithm for pedestrian detection. First, extract the moving objects from the image sequence using background subtraction. Second, select part of the objects for further detected. Most of the moving objects, which can be determined as vehicles would be excluded in the pretreatment. Third, extract several significant eigenvalues from the rest objects, which can indicate the differences of contour between pedestrian and vehicle. Finally, eigenvector is formed and used as the input of the back propagation neural network, the output of which is the detecting result. The BP neural network is trained and used to identify pedestrian, experiment results of which are analyzed. It has been proved that the algorithms proposed in this paper have satisfactory real-time performance and accuracy.

关键词： detection algorithms Neural networks Vehicle detection Eigenvalues and eigenfunctions Humans Biological system modeling Object detection Shape Computer science Automotive engineering

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Polarimetric approach to detection of probable aircraft Icing zones. icing detection algorithms

Polarimetric approach to detection of probable aircraft Icin...

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European Radar Conference (EURAD)

作者： A.A. Pitertsev F.J Yanovsky Department of Air Navigation Systems National Aviation University Kiev Ukraine

Aircraft icing is a dangerous meteorological phenomenon. Most important conditions for growing of ice coating on aircraft body or wings are presence of supercooled liquid water (SLW) drops, high humidity and negative temperature of air. Remote sensing of the clouds with the help of polarimetric radar can detect the SLW in cloud. It can be used to avoid dangerous situations during the flight. Mathematical simulation of microwave backscattering from ice crystals of different forms and water drops in rain and clouds have been done. Different icing detection algorithms are described and analyzed.

关键词： Aircraft detection algorithms Clouds Ice Meteorology Coatings Humidity Temperature sensors Remote sensing Meteorological radar

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Outlier detection algorithms in Data Mining

Outlier Detection Algorithms in Data Mining

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International Symposium on Intelligent Information Technology Application, IITA

作者： Jingke Xi School of Computer Science and Technology China University of Mining and Technology Xuzhou Jiangsu China

Outlier is defined as an observation that deviates too much from other observations. The identification of outliers can lead to the discovery of useful and meaningful knowledge. Outlier detection has been extensively studied in the past decades. However, most existing research focuses on the algorithm based on special background, compared with outlier detection approach is still rare. This paper mainly discusses and compares approach of different outlier detection from data mining perspective, which can be categorized into two categories: classic outlier approach and spatial outlier approach. The classic outlier approach analyzes outlier based on transaction dataset, which can be grouped into statistical-based approach, distance-based approach, deviation-based approach, density-based approach. The spatial outlier approach analyzes outlier based on spatial dataset that non-spatial and spatial data are significantly different from transaction data, which can be grouped into space-based approach and graph-based approach. Finally, the paper concludes some advances in outlier detection recently.

关键词： detection algorithms Data mining Information technology Application software Computer science Statistical distributions Probability distribution Decision making Transportation Environmental factors

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Evaluation Methodology for Multiclass Novelty detection algorithms

Evaluation Methodology for Multiclass Novelty Detection Algo...

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Brazilian Conference on Intelligent Systems (BRACIS)

作者： Elaine R. Faria Isabel J.C.R. Gonçalves João Gama Andre C.P.L.F. Carvalho University of são Paulo Federal University of Uberlândia Uberlândia Brazil Viana do Castelo Instituto Politécnico de Viana do Castelo Portugal LIAAD-INESC Porto University of Porto Porto Portugal ICMC University of são Paulo São Carlos Brazil

Novelty detection is a useful ability for learning systems, especially in data stream scenarios, where new concepts can appear, known concepts can disappear and concepts can evolve over time. There are several studies in the literature investigating the use of machine learning classification techniques for novelty detection in data streams. However, there is no consensus regarding how to evaluate the performance of these techniques, particular for multiclass problems. In this study, we propose a new evaluation approach for multiclass data streams novelty detection problems. This approach is able to deal with: i) multiclass problems, ii) confusion matrix with a column representing the unknown examples, iii) confusion matrix that increases over time, iv) unsupervised learning, that generates novelties without an association with the problem classes and v) representation of the evaluation measures over time. We evaluate the performance of the proposed approach by known novelty detection algorithms with artificial and real data sets.

关键词： Measurement uncertainty detection algorithms Accuracy Clustering algorithms Bipartite graph Time measurement Equations

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A new deadlock detection algorithms for distributed real-time database systems

A new deadlock detection algorithms for distributed real-tim...

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Reliable Distributed Systems

作者： Chim-fu Yeung Sheung-lun Hung Department of Computer Science City University of Hong Kong Hong Kong China

ISBN: (纸本)081867153X

Recently the concurrency control issue of real-time transactions is gaining increasing attention of researchers in the database community. One of the major design issue in concurrency control of real-time transactions is the resolution of local as well as distributed deadlocks while at the same time meeting the timing requirements of the transactions. In this paper, a new deadlock detection algorithm specially designed for distributed real-time database systems is proposed. The performance of the proposed algorithm is evaluated through extensive simulation experiments. Studies have also been carried out to compare the performance of the real-time deadlock detection algorithm with a non real-time algorithm for both firm and soft real-time transactions. Results indicated that the real-time deadlock detection algorithm performs better than the non real-lime deadlock detection algorithm. Results also indicated that the performance of the new algorithm is substantially better for soft real-time than that of firm real-time systems.

关键词： System recovery detection algorithms Real time systems Database systems Concurrency control Protocols Timing Scheduling algorithm Computer science Transaction databases

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