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Fusion Based Approach for Distributed Alarm Correlation in computer Networks

Fusion Based Approach for Distributed Alarm Correlation in C...

引用

International Conference on Communication Software and Networks, ICCSN

作者： Abduljalil A. Mohamed Otman Basir Department of Systems Design Engineering University of Waterloo Waterloo Canada Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada

ISBN: (纸本)9781424457267;9780769539614

We propose a new distributed alarm correlation and fault identification in computer networks. The managed network is divided into a disjoint management domains and each management domain is assigned a dedicated intelligent agent. The intelligent agent is responsible for collecting, analyzing, and correlating alarms emitted form emitted from its constituent entities in its domain. In the framework of Dempster-Shafer evidence theory, each agent perceives each alarm as a piece of evidence in the occurrence of a certain fault hypothesis and correlates the received alarms into a single alarm called local composite alarm, which encapsulates the agent's partial view of the current status of the managed system. While the alarm correlation process is performed locally, each intelligent agent is able to correlate its alarms globally. These local composite alarms are, in turn, sent to a higher agent whose task is to fuse these alarms and form a global view of operation status of the running network. Extensive experimentations have demonstrated that the proposed approach is more alarm loss tolerant than the codebook based approaches and hence shown its effectiveness in a usually noisy network environment.

关键词： computer networks computer network management Fault diagnosis Protocols Intelligent agent ISO standards Fault detection Neural networks Management training Communication system software

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Oppositional fuzzy image thresholding

Oppositional fuzzy image thresholding

引用

IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Fares S. Al-Qunaieer Hamid R. Tizhoosh Shahryar Rahnamayan Systems Design Engineering University of Waterloo Waterloo ONT Canada Electrical and Computer Engineering Ontario Institute of Technology Oshawa ONT Canada

In many image processing applications, image thresholding is considered to be an important task. Opposition-Based Learning (OBL) was recently introduced and used to enhance different computation algorithms. In this paper, a new thresholding algorithm is proposed by utilizing the concept of opposite fuzzy sets. The algorithm is applied on general set of images and compared with the previous opposition-based thresholding algorithm [1] and a commonly used thresholding method, namely the Otsu method. The most reliable results on the test data are achieved using the proposed algorithm.

关键词： Fuzzy sets Pixel Entropy Histograms Algorithm design and analysis Image segmentation

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Temporal Conditional Random Fields: A conditional state space predictor for visual tracking

Temporal Conditional Random Fields: A conditional state spac...

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Iranian Machine Vision and Image Processing (MVIP)

作者： M. J. Shafiee Z. Azimifar P. Fieguth Computer Vision and Pattern Recognition Laboratory School of Electrical & Computer Engineering Shiraz University Shiraz Iran Systems Design Engineering University of Waterloo Waterloo Canada

We present a modified Temporal Conditional Random Fields framework for modeling and predicting object motion. To facilitate such a powerful graphical model with prediction and come up with a CRF-based predictor, we propose a set of new temporal relations for object tracking, with feature functions such as optical flow (calculated among consequent frames). We evaluate our proposed Temporal Conditional Random Field method with real and synthetic data sequences and will show that the TCRF prediction is nearly equivalent with result of template matching. Experimental results show that our proposed method estimates future target state with zero error until target dynamic changes. Our proposed modified CRF method with simple and easy to implement feature functions, can learn any target dynamic, thus, it can predict next state of target with zero error.

关键词： Computational modeling Hidden Markov models computer vision Predictive models Kalman filters Image motion analysis Dynamics

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Sampling Spiking Neural Network electronic nose on a tiny-chip

Sampling Spiking Neural Network electronic nose on a tiny-ch...

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Midwest Symposium on Circuits and systems (MWSCAS)

作者： Hoda S. Abdel-Aty-Zohdy Jacob N. Allen Microelectronics & Bio-Inspired Systems Design Department of electrical and Computer Engineering Oakland University Rochester MI USA

Chemicals classification using a new Sampling Spiking Neural Network (SSNN) approach is presented in this paper with experimental measurements using the Cyranose 320 sensor array. The network is unique in its minimal yet powerful design which implements on chip learning and parallel monitoring to detect binary odor patterns with high noise environment. The SSNN architecture is further implemented on a 0.5 um CMOS technology tiny-chip designed to work in conjunction with a 256 K external SRAM memory. It handles the routing of spike signal among 32,000 synapses and 255 neurons. At the same time, it tracks and records learning statistics. The chip can be used in parallel with other SSNN co processors for very large systems. Experimental measurements of our SSNN E-Nose classifier, compared to other E-nose systems proved superior in capability, size, and correctness.

关键词： Sampling methods Neural networks Electronic noses Sensor arrays Chemical sensors Semiconductor device measurement CMOS technology Network-on-a-chip Monitoring Working environment noise

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Relationship Between Power Loss and Network Topology in Power systems

Relationship Between Power Loss and Network Topology in Powe...

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2010 49th IEEE Conference on Decision and Control

作者： Javad Lavaei Steven H. Low Department of Control and Dynamical Systems California Institute of Technology Computer Science and Electrical Engineering Departments California Institute of Technology

ISBN: (纸本)9781424477456

This paper is concerned with studying how the minimum power loss in a power system is related to its network topology. The existing algorithms in the literature all exploit nonlinear, heuristic, or local search algorithms to find the minimum power loss, which make them blind to the network topology. Given certain constraints on power level, bus voltages, etc., a linear-matrix-inequality (LMI) optimization problem is derived, which provides a lower bound on the minimum active loss in the network. The proposed LMI problem has the property that its objective function depends on the loads and its matrix inequality constraint is related to the topology of the power system. This property makes it possible to address many important power problems, such as the optimal network reconfiguration and the optimal placement/sizing of distributed generation units in power systems. Moreover, a condition is provided under which the solution of the given LMI problem is guaranteed to be exactly equal to the minimum power loss. As justified mathematically and verified on IEEE test systems, this condition is expected to hold widely in practice, implying that a practical power loss minimization problem is likely to be solvable using a convex algorithm.

关键词： power loss power systems Network topology SEARCHING ALGORITHM inequality constraint Network reconfiguration

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Stochastic analysis of a local distribution company voltage profile under uncertain energy supply from a photovoltaic system

Stochastic analysis of a local distribution company voltage ...

引用

International Conference on European Electricity Market, EEM

作者： Yousef El-Mabruk Saad K. Ponnambalam R. A. El-Shatshat Department of Electrical and Computer Engineering University of Waterloo Waterloo ONT Canada Systems Design Engineering Department University of Waterloo Waterloo ONT Canada

Recently in Ontario, Canada new installations of renewable distributed generation are being encouraged. Incentives are provided to producers directly by the government when energy is fed to the grid. This however has brought the attention of operators of local distribution companies to the issue of assuring the quality of supply to downstream customers when the grid receives this new and highly varying energy. As a result of these variations, the voltage may deviate from the standard levels. This paper investigates the impacts of installing a PV system, with considerable capacity compared to the network demand, on the voltage profile of an existing distribution network. Monte Carlo technique is applied focusing on the voltage profile by solving the steady state load flow model every 15-min time interval. A distribution system supplying a significant part of the region is considered as a case study.

关键词： Niobium Biological system modeling Green products

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An Intelligent Model to Construct Specialized Domain Ontologies

An Intelligent Model to Construct Specialized Domain Ontolog...

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2010 3rd IEEE International Conference on computer Science and Information Technology—ICCSIT 2010

作者： A. Mooman O. Basir A. Younes Dept. of Electrical and Computer Engineering University of Waterloo Waterloo Canada Dept. of Systems Design Engineering University of Waterloo Waterloo Canada

Search engines and information retrieval (IR) systems provide a mechanism for users to access large amounts of information available through the Internet. However, in order to find the desired information, the user has to go through a staggering amount of information retrieved from highly dynamic resources. Experimental results show that the approach proposed for constructing specialized domains improves the precision of information retrieval. Our approach involves enriching the user's query with related linguistic semantic and statistical semantic related concept terms. We employ natural language process (NLP) techniques such as WordNet engine to enrich the user's query with semantic lexical synonymous terms and a probabilistic topic model such as latent dirichet allocation (LDA) to extract highly ranked topic from a query's retrieved information. Furthermore, an intelligent learning algorithm, reinforcement learning (RL) is integrated into the design to assist end users in selecting the concept domains that are most relevant to their needs.

关键词： Internet LDA domain WordNet An Intelligent Model to Construct Specialized Domain Ontologies Model

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Opposition based computing — A survey

Opposition based computing — A survey

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Fares S. Al-Qunaieer Hamid R. Tizhoosh Shahryar Rahnamayan Systems Design Engineering University of Waterloo Waterloo ONT Canada Electrical and Computer Engineering University of Ontario Institute of Technology (UOIT) Oshawa ONT Canada

In algorithms design, one of the important aspects is to consider efficiency. Many algorithm design paradigms are existed and used in order to enhance algorithms' efficiency. Opposition-based Learning (OBL) paradigm was recently introduced as a new way of thinking during the design of algorithms. The concepts of opposition have already been used and applied in several applications. These applications are from different fields, such as optimization algorithms, learning algorithms and fuzzy logic. The reported results confirm that OBL paradigm was promising to accelerate or to enhance accuracy of soft computing algorithms. In this paper, a survey of existing applications of opposition-based computing is presented.

关键词： Benchmark testing Convergence Algorithm design and analysis Optimization Artificial neural networks Accuracy Learning

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An intelligent system for diagnosing sleep stages using wavelet coefficients

An intelligent system for diagnosing sleep stages using wave...

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International Joint Conference on Neural Networks (IJCNN)

作者： Maryam Vatankhah Mohammad-R. Akbarzadeh-T. Ali Moghimi Departments of Electrical Engineering and Computer Engineering Ferdowsi University of Mashhad Iran Mashhad Branch ungyo researcher club members Islamic Azad University Center for Applied Research on Intelligent Systems and Soft Computing Departments of Electrical Engineering and Computer Engineering Ferdowsi University of Mashhad Iran Department of Biology Faculty of Sciences University of Mashhad Iran

Human sleep is divided into two segments, Rapid Eye Movement (REM) sleep and Non-REM (NREM) sleep. NREM sleep is further divided into 4 stages. Sleep staging attempts to identify these stages based on the signals collected in PSG. Significant information can be derived from the EEG signals collected during PSG. Wavelet coefficients are extracted from EEG signals. In order to reduce the amount of data set, the statistical features are calculated from wavelet coefficients. For performing decision making, six ANFIS classifiers and SVM classifier are used to differentiate between REM and Non-REM sleep stages. That is to say, pattern varies under the different sleep stages. Therefore, healthy humans with a regular night's sleep will follow these sleep stages in a particular pattern.

关键词： Support vector machines Time frequency analysis

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A Simple and Robust Dissemination protocol for VANETs

A Simple and Robust Dissemination protocol for VANETs

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European Wireless Conference (EW)

作者： Ramon S. Schwartz Rafael R. R. Barbosa Nirvana Meratnia Geert Heijenk Hans Scholten Pervasive Systems (PS) Faculty of Electrical Engineering Mathematics and Computer Science (EWI) University of Twente Enschede Netherlands Design and Analysis of Communication Systems (DACS) Faculty of Electrical Engineering Mathematics and Computer Science (EWI) University of Twente Enschede Netherlands

Several promising applications for Vehicular Ad-hoc Networks (VANETs) exist. For most of these applications, the communication among vehicles is envisioned to be based on the broadcasting of messages. This is due to the inherent highly mobile environment and importance of these messages to vehicles nearby. To deal with broadcast communication, dissemination protocols must be defined in such a way as to (i) prevent the so-called broadcast storm problem in dense networks and (ii) deal with disconnected networks in sparse topologies. In this paper, we present a Simple and Robust Dissemination (SRD) protocol that deals with these requirements in both sparse and dense networks. Its novelty lies in its simplicity and robustness. Simplicity is achieved by considering only two states (cluster tail and non-tail) for a vehicle. Robustness is achieved by assigning message delivery responsibility to multiple vehicles in sparse networks. Our simulation results show that SRD achieves high delivery ratio and low end-to-end delay under diverse traffic conditions.

关键词： Robustness Protocols Vehicles Broadcasting Mobile communication Ad hoc networks Storms Network topology Tail Delay

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