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检索条件"主题词=Detection algorithms"

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Application of Community detection algorithms on Social Internet-of-things Networks

Application of Community Detection Algorithms on Social Inte...

引用

International Conference on Microelectronics, ICM

作者： Abdullah Khanfor Hakim Ghazzai Ye Yang Yehia Massoud School of Systems & Enterprises Stevens Institute of Technology Hoboken NJ USA

ISBN: (数字)9781728140582

ISBN: (纸本)9781728140599

The Internet-of-things (IoT) networks are witnessing a drastic increase over the years. Twenty billion devices connected to the Internet are expected in 2022. The need for identifying communities within such networks can serve as a strong complexity reduction mean for many discovery and identification services. The idea of communities in IoT networks is also motivated by the emerging concept of socializing IoT devices. In this paper, we investigate the application of two community detection algorithms, namely Louvain and Bron-Kerbosch algorithms, on IoT networks usually represented by large-scale graphs. The objective is to convert the complex IoT network into multiple overlapping and non-overlapping communities where its elements share common characteristics. Starting from a real-world IoT networks, we use its dataset to extract community-structured IoT network based on different types of relationships such as co-location, owner social relationships, and autonomously build object relationships among objects. Our analysis showcases how community detection algorithms structure the IoT network into communities based on the different relationships established between objects.

关键词： detection algorithms Sensors Complexity theory Internet Smart phones Quality of service Quality of experience

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Application of anomaly detection algorithms for detecting SYN flooding attacks

Application of anomaly detection algorithms for detecting SY...

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IEEE Conference and Exhibition on Global Telecommunications (GLOBECOM)

作者： V.A. Siris F. Papagalou Institute of Computer Science Foundation for Research and Technology Hellas Crete Greece

We investigate statistical anomaly detection algorithms for detecting SYN flooding, which is the most common type of denial of service (DoS) attack. The two algorithms considered are an adaptive threshold algorithm and a particular application of the cumulative sum (CUSUM) algorithm for change point detection. The performance is investigated in terms of the detection probability, the false alarm ratio, and the detection delay. Particular emphasis is on investigating the tradeoffs among these metrics and how they are affected by the parameters of the algorithm and the characteristics of the attacks. Such an investigation can provide guidelines to effectively tune the parameters of the detection algorithm to achieve specific performance requirements in terms of the above metrics.

关键词： detection algorithms Floods Computer crime Change detection algorithms Computer science Delay TCPIP Application software Guidelines Web and internet services

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A comparative study of harmonic detection algorithms for active filters and hybrid active filters

A comparative study of harmonic detection algorithms for act...

引用

Annual IEEE Conference on Power Electronics Specialists (PESC)

作者： S. Rechka E. Ngandui Jianhong Xu P. Sicard Hydro-Quebec Research Chair Power and Electrical Energy Universite Quebec a Trois-Rivieres Trois-Rivieres Canada

In this paper, the performance of three harmonic detection methods is evaluated in term of precision, speed of convergence and calculation complexity. The algorithms are respectively based on the recursive discrete Fourier transform (RDFT), Kalman filtering approach and the instantaneous reactive power theory. Results obtained by simulations with Matlab-Simulink and their real-time validation with dSPACE are presented to compare the detection methods. The effectiveness of the algorithms is demonstrated in their application to the control of a hybrid active filter dedicated to harmonic resonance damping in industrial power systems.

关键词： Active filters Power harmonic filters detection algorithms Power system harmonics Convergence Filtering algorithms Discrete Fourier transforms Kalman filters Filtering theory Reactive power

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Impulse noise detection algorithms for multicarrier communication systems -performance analysis

Impulse noise detection algorithms for multicarrier communic...

引用

International Symposium on Image and Signal Processing and Analysis

作者： M. Sliskovic Zagreb Croatia

ISBN: (纸本)9539676940

Impulse noise is known to be highly damaging to the performance of a multicarrier system. To be able to deal with impulsive disturbances, the receiver has to recognize which symbol was contaminated by the impulse noise. We analyze performance of a selection of impulse noise detection algorithms. Impulse noise can be detected in the time domain, in the frequency domain, or by combining the time and frequency domain analysis. The choice of the impulse noise detection algorithm depends on the characteristics of an impulse.

关键词： detection algorithms Performance analysis Frequency domain analysis OFDM modulation Filters Transmitters Discrete Fourier transforms Sampling methods AWGN Algorithm design and analysis

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Obstacle detection algorithms for Low Altitude Flight

Obstacle Detection Algorithms for Low Altitude Flight

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American Control Conference (ACC)

作者： Banavar Sridhar NASA Ames Research Center CA USA

This paper describes an approach to collision avoidance for rotorcraft flying at low altitudes. The method is based on extracting information from passive image-based sensors. These methods can be used to alert a pilo... 详细信息

关键词： detection algorithms Optical sensors Image motion analysis Safety Azimuth Data mining Optical noise Optical computing Infrared detectors Image sensors

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Poster: IoTSimSecure: Towards an IoT Simulator Supporting Cyber-Threat detection algorithms

Poster: IoTSimSecure: Towards an IoT Simulator Supporting Cy...

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IEEE International Conference on Fog and Edge Computing (ICFEC)

作者： Reham Almutairi Giacomo Bergami Graham Morgan School of Computing Newcastle University United Kingdom College of Computer Science and Engineering University of Hafr Albatin Saudi Arabia

ISBN: (数字)9798350361353

ISBN: (纸本)9798350361360

We introduce IoTSimSecure, a novel IoT simulator addressing the gap of IoT simulators for dealing with cyber-security threats, specifically battery draining attacks occurring in real-time. This will serve as a valuable testbed for evaluating current AI-driven security strategies. IoTSimSecure aims to address these needs by offering an architecture that combines signature-based and anomaly-based detection methods.

关键词： Time series analysis Computer architecture Real-time systems Batteries Security detection algorithms Monitoring Edge computing

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Performance analysis of dim moving point target detection algorithms

Performance analysis of dim moving point target detection al...

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International Conference on Communications, Circuits and Systems (ICCCAS)

作者： H. Askar Xiaofeng Li Zaiming Li College of communication and information Engineering University of Electronic Science and Technology of China Chengdu China

This paper studies the performance comparison of track-before-detect (TBD) and detect-before-track (DBT) multi-frame detection algorithms for the detection of weak moving point targets in infrared image sequences data collected from a scanning sensor. Results indicate that the performance of TBD is superior to that of DBT in all respects for low SNR. However, while computationally simple, DBT can have a reasonable performance only for high SNR. Simulations verify the results of the analysis and the conclusions drawn.

关键词： Performance analysis Object detection Infrared detectors Infrared image sensors Target tracking detection algorithms Image sequences High performance computing Computational modeling Analytical models

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Comparing image detection algorithms using resampling

Comparing image detection algorithms using resampling

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IEEE International Symposium on Biomedical Imaging

作者： F.W. Samuelson N. Petrick NIBIB/CDRH Joint Laboratory for the Assessment of Medical Imaging Systems U.S. Food and Drug Administration Center for Devices and Radiological Health Rockville MD USA

The ability to statistically compare the performance of two computer detection (CD) or computer-aided detection (CAD) algorithms is fundamental for the development and evaluation of medical image analysis tools. Automated detection tools for medical imaging are commonly characterized using free-response receiver operating characteristic (FROC) methods. However, few statistical tools are currently available to estimate statistical significance when comparing two FROC performance curves. In this study, we introduce a permutation and a bootstrap resampling method for the nonparametric estimation of statistical significance of performance metrics when comparing two FROC curves. We then provide an initial validation of the proposed methods using an area under the FROC performance metric and a simulation model for creating CD algorithm prompts. Validation is based on a comparison of the Type I error rate produced by two statistically identical CD algorithms. The results of 10 4 Monte Carlo trials show that both the permutation and bootstrap methods produced excellent estimates of the expected Type I error rate

关键词： detection algorithms Biomedical imaging Measurement Testing Image analysis Performance analysis Algorithm design and analysis Error analysis Coronary arteriosclerosis Drugs

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Wavelet transforms and change-point detection algorithms for tracking network traffic fractality

Wavelet transforms and change-point detection algorithms for...

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Conference on Next Generation Internet Networks, NGI

作者： P. Zuraniewski D. Rincon Department of Applied Mathematics AGH University of Science and Technology Cracow Poland Department of Telematics Engineering Technical University of Catalonia Barcelona Spain

Network traffic is known to present fractal characteristics such as LRD, which can be efficiently measured with wavelet transforms. Current methods of estimation of fractal parameters, such as the LogScale diagram, are not able to track the changes of the parameters. This paper proposes and studies the combined use of wavelet transforms (DWT, MODWT, DTWT) and change-point detection algorithms (ICSS, SIC) in order to detect the instants when fractality changes noticeably. The different approaches are contrasted and statistical assessment is provided, together with the results of the procedure when applied to synthetic traces

关键词： Wavelet transforms detection algorithms Telecommunication traffic Fractals Discrete wavelet transforms Change detection algorithms Silicon carbide Communication system traffic control Parameter estimation Bandwidth

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Robust template based corner detection algorithms for robotic vision

Robust template based corner detection algorithms for roboti...

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IEEE International Conference on Technologies for Practical Robot Applications (TePRA)

作者： Chen Gao Karen Panetta Sos Agaian Electrical and Computer Engineering Department Tufts University Medford MA USA Electrical and Computer Engineering Department University of Texas at San Antonio San Antonio TX USA

Image corners encapsulate gradient changes in multiple directions. Therefore, corners are considered as efficient features for use in robotic navigation algorithms. Template based corner detection has a low computational complexity and is straightforward to implement. With the appropriate design of templates, satisfactory detection accuracy can also be achieved. In this paper, we introduce two new template based corner detection algorithms to be used to assist robot vision: the matching based corner detection, namely, MBCD; and the correlation based corner detection, namely, CBCD. These two approaches outperform existing template based approaches in the means that they reduce detection of spurious corners by considering ideal corners with at least two-pixel length on the corner arm directions. Experimental results show that the proposed algorithms detect essential corners for synthetic images and natural images satisfactorily according to human visual perception. We also examine the robustness of the two corner detection approaches in terms of the average repeatability and localization error. Since our approaches are computationally efficient, it makes these template based corner detection algorithms suitable for real time support in robotic applications. Comparisons with existing corner detection algorithms are also presented.

关键词： detection algorithms Image edge detection Correlation Robustness Feature extraction Robot sensing systems

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