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检索条件"主题词=detection algorithms"

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Anomaly detection from the operation history of DLNA devices

Anomaly detection from the operation history of DLNA devices

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International Conference on Ubiquitous and Future Networks, ICUFN

作者： Sunhye Baek Hua Si Shunsuke Saruwatari Hiroyuki Morikawa Johan Hjelm Toshikane Oda Research Center for Advanced Science and Technology University of Tokyo Tokyo Japan Ericsson Research Japan Tokyo Japan

With the development of DLNA technology, more and more DLNA devices appear in our lives. We can extract users' activity events from the operation history of DLNA devices, and provide various services based on them. In this paper, we discuss how to detect anomalous events from operation history of DLNA devices. As the basic technology, we first propose DLNA Probe, a system to acquire operation history from communication between DLNA devices by using ARP spoofing. Then, we discuss the selection of anomaly detection algorithms. Finally, we introduce a system for detecting anomalies from one of DLNA device.

关键词： History Probes TV Throughput detection algorithms Delay Turning

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detection and punishment of malicious wireless stations in IEEE 802.11e EDCA network

Detection and punishment of malicious wireless stations in I...

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IEEE Princeton Section Sarnoff Symposium

作者： Yong woon Ahn Albert Mo Kim Cheng Jinsuk Baek Paul S. Fisher Department of Computer Science University of Houston Houston TX USA Department of Computer Science Winston-Salem State University Winston Salem NC USA

ISBN: (纸本)9781424455928;9781424455935

We propose a malicious detection algorithm that permits identification of misbehaving wireless stations, and then meeting out punishment by not supplying an ACK packet permitting transmission by the malicious stations. The proposed algorithm is designed for IEEE 802.11e network and based upon detecting a change in QoS moving a station up in terms of a measure of permission to a level which is not justified. The impact of non-detection will be for honest stations to set their retransmit attempts to times longer than the deadline set in order to sustain continuous receipt of their data. Our simulation within the ns-2 framework of the IEEE 802.11e EDCA network shows how our algorithm actually detects and adjusts the punishment phase for stations that maybe misbehaving as well as stations which are misbehaving.

关键词： Quality of service Computer science Streaming media Media Access Protocol Broadcasting Communication system traffic control Jitter detection algorithms Change detection algorithms Algorithm design and analysis

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Context-aware saliency detection

Context-aware saliency detection

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Stas Goferman Lihi Zelnik-Manor Ayellet Tal Technion Israel Institute of Technology Haifa Haifa IL

We propose a new type of saliency - context-aware saliency - which aims at detecting the image regions that represent the scene. This definition differs from previous definitions whose goal is to either identify fixation points or detect the dominant object. In accordance with our saliency definition, we present a detection algorithm which is based on four principles observed in the psychological literature. The benefits of the proposed approach are evaluated in two applications where the context of the dominant objects is just as essential as the objects themselves. In image retargeting we demonstrate that using our saliency prevents distortions in the important regions. In summarization we show that our saliency helps to produce compact, appealing, and informative summaries.

关键词： Layout Object detection Object recognition detection algorithms Humans Psychology Springs Computer vision Application software Focusing

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An Outlier detection Algorithm Based on Clustering Analysis

An Outlier Detection Algorithm Based on Clustering Analysis

引用

International Conference on Pervasive Computing Signal Processing and Applications (PCSPA)

作者： Yue Zhang Jie Liu Hang Li Software College Shenyang Normal University Shenyang China

Outlier detection is a hot topic of data mining. After analyzing current detection technologies, a detection method of outlier based on clustering analysis is proposed, in which an effective sample is screened out from original data. According to agglomerative of hierarchical clustering, credible sample set is found. Then mathematical expectation and standard deviation are obtained by credible sample. Finally, global data will detected by the definition of outlier which is proposed in this paper. The data disposed by this method can be irrelative to the time scales. And it needs not to presuppose the number of outlier. The experiment results on IRIS show that this method can detect outliers effectively.

关键词： Clustering algorithms Algorithm design and analysis Data mining Chebyshev approximation Iris detection algorithms Software

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Cloth grasp point detection based on multiple-view geometric cues with application to robotic towel folding

Cloth grasp point detection based on multiple-view geometric...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jeremy Maitin-Shepard Marco Cusumano-Towner Jinna Lei Pieter Abbeel Department of Electrical Engineering and Computer Sciences University of California Berkeley CA USA

We present a novel vision-based grasp point detection algorithm that can reliably detect the corners of a piece of cloth, using only geometric cues that are robust to variation in texture. Furthermore, we demonstrate the effectiveness of our algorithm in the context of folding a towel using a general-purpose two-armed mobile robotic platform without the use of specialized end-effectors or tools. The robot begins by picking up a randomly dropped towel from a table, goes through a sequence of vision-based re-grasps and manipulations-partially in the air, partially on the table-and finally stacks the folded towel in a target location. The reliability and robustness of our algorithm enables for the first time a robot with general purpose manipulators to reliably and fully-autonomously fold previously unseen towels, demonstrating success on all 50 out of 50 single-towel trials as well as on a pile of 5 towels.

关键词： Robotics and automation Robot vision systems Clothing Collaborative work Robustness Manipulators Machine learning algorithms USA Councils detection algorithms Mobile robots

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New detection algorithm for weak target signal embedded in direct path interference using Signal Phase Matching Principle

New detection algorithm for weak target signal embedded in d...

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International Conference on Information and Automation (ICIA)

作者： Dong-ze Lv Feng Shen Department of Automation Harbin Engineering of Technology Harbin Heilongjiang China

A detection method for weak signals embedded in direct-path interference is discussed. This method is based on FM radio signals as the illuminator of passive radar. On the basic of Signal Phase Matching Principle, a new algorithm for suppressing the direct-path interference is proposed in wave-beam domain. To improve the declining performances of the algorithm when the amplitude fluctuates, a compensatory factor is presented. The simulation results show the validity of the algorithm and the compensatory method.

关键词： detection algorithms Frequency conversion Passive radar Interference suppression Echo interference Phase detection Radio transmitters Spaceborne radar Attenuation Automation

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Improving the Reliability of the K-Best algorithm for MIMO detection with ordering

Improving the Reliability of the K-Best algorithm for MIMO d...

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International Conference on Wireless and Optical Communications ( WOCC)

作者： Xuebin Wu Yongmei Dai Zhiyuan Yan Ying Wang Department of ECE Lehigh University Bethlehem PA USA Qualcomm Flarion Technologies Bridgewater NJ USA

ISBN: (纸本)9781424475971;9781424475964

It is well known that the order of the channel matrix columns has significant impact on a MIMO detector's performance in terms of the computational complexity, memory requirement, and/or the detection error rate. In our previous work, novel ordering schemes have been proposed to reduce the computational complexities and/or memory requirements of various maximum likelihood (ML) MIMO detectors. In this paper, we incorporate our ordering schemes with the K-Best detector, which is a near-ML detector and is particularly suitable for hardware implementation. Our simulation results show that our ordering schemes greatly improve the reliability of the K-Best detector. Given a fixed detection error rate, our ordering schemes either result in SNR gains or enable the usage of even smaller K, thereby leading to small area and power consumption and higher throughput for their hardware implementations.

关键词： MIMO Computational complexity Detectors Hardware Error analysis Maximum likelihood detection Throughput detection algorithms Computational modeling Energy consumption

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Evaluation of Anomaly detection Based on Sketch and PCA

Evaluation of Anomaly Detection Based on Sketch and PCA

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2010 IEEE Global Telecommunications Conference GLOBECOM 2010

作者： Yoshiki Kanda Kensuke Fukuda Toshiharu Sugawara Graduate School of Fundamental Science and Engineering Waseda University Tokyo Japan PRESTO Tokyo Japan

Using traffic random projections (sketches) and Principal Component Analysis (PCA) for Internet traffic anomaly detection has become popular topics in the anomaly detection fields, but few studies have been undertaken on the subjective and quantitative comparison of multiple methods using the data traces open to the community. In this paper, we propose a new method that combines sketches and PCA to detect and identify the source IP addresses associated with the traffic anomalies in the backbone traces measured at a single link. We compare the results with those of a method incorporating sketches and multi-resolution gamma modeling using the trans-Pacific link traces. The comparison indicates that each method has its own advantages and disadvantages. Our method is good at detecting worm activities with many packets, whereas the gamma method is good at detecting scan activities for peer hosts with only a few packets, but it reports many false positives for traces of worm outbreaks. Therefore, their use in combination would be effective. We also examined the impact of adaptive decision making on a parameter (the number of normal subspaces in PCA) on the basis of the cumulative proportion of each sketched traffic and conclude that it performs at a higher level than the previous method deciding only on one specific value of the parameter for every divided traffics.

关键词： IP networks Principal component analysis Time series analysis Internet Grippers IEEE Communications Society detection algorithms

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Outlier detection methods of low SNR nodes for cooperative spectrum sensing

Outlier detection methods of low SNR nodes for cooperative s...

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International Symposium on Wireless Communication Systems (ISWCS)

作者： Hung Vu Le Mai Ohta Kei Inage Takeo Fujii Kazushi Muraoka Masayuki Ariyoshi Advanced Wireless Communication research Center University of Electro-Communications Chofu Tokyo Japan System Platforms Research Laboratories NEC Corporation Limited Kawasaki Kanagawa Japan

In this paper, we have studied methods of detecting low signal-to-noise ratio (SNR) nodes by outlier detection in cooperative spectrum sensing. In many studies in the field of cooperative sensing, it is assumed that an average received energy among sensing nodes is equal. However, in practical wireless environment, the performance of cooperative sensing with low SNR nodes located underground, indoor, and so on, is severely degraded. The goal of this research is to detect the low SNR nodes and minimizes the impacts caused by these low SNR nodes to the cooperative sensing performance. We propose an outlier detection algorithm to exclude low SNR nodes from cooperative sensing nodes by using past accumulated energy data. Several outlier detection methods are compared, and a suitable method for the low SNR node detection algorithm is selected. In addition, the required length of estimation period for the outlier detection is revealed. Simulation results show that the performance of cooperative sensing is improved even if the low SNR nodes exist in the cooperative nodes.

关键词： Signal to noise ratio Sensors detection algorithms Estimation Fading Probability Wireless communication

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Dynamic threshold cloud detection algorithm improvement for AVHRR and SEVIRI images

Dynamic threshold cloud detection algorithm improvement for ...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Gabriele Poli Giulia Adembri Monica Gherardelli Maurizio Tommasini Department of Electronics and Telecommunications University of Florence Italy

The aim of this work is to present a simple and fast automatic cloud detection algorithm for Advanced Very High Resolution Radiometer (AVHRR) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) satellite images. The algorithm was developed by the Department of Electronics and Telecommunications (University of Florence) for the Satellite Receiving Station of Prato Campus (University of Florence), where AVHRR and SEVIRI data have been directly received since 1997. The algorithm is designed to meet the need for real-time operational processing of land and sea products, such as vegetation indexes and regional land/sea surface temperature maps (i.e. Italy). It is developed as simple and fast processing which does not need to use ancillary data. The algorithm is tested for AVHRR and SEVIRI images directly received at the Station which are characterized by different percentages of cloudy pixels. Algorithm results are compared with control cloud masks, which are created manually by a visual inspection of the image to be cloud screened.

关键词： Clouds Pixel Heuristic algorithms Ocean temperature Reflectivity Algorithm design and analysis detection algorithms

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