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Biennial Symposium on Communications, QBSC

作者： J. Jyoti S. El-Tawab M.N. El-Derini E. Aboelela H. Aly Department of Computer and Info Science University of Massachusetts Dartmouth Dartmouth MA USA Computers & Automatic Control Department Alexandria University Alexandria Egypt

Transmitting voice over the Internet, especially over long distances, is hampered by difference in available network resources at different locations over the world. For Instance, VoIP (voice over Internet protocol) services perform much better at locations having high-speed broadband network than locations with limited bandwidth. In this study, the effect of distance between communicating nodes and usage of diverse routes on QoS (quality of service) is studied for VoIP. RTP over UDP is used to transmit voice. RTCP provides feedback about delay, packet-loss and jitter. Routing diversity is implemented using NISTNet, an emulator. The statistics collected from the tests indicate that packet loss rate, delay and jitter are significantly affected by the distance between end nodes. In addition, results show that voice quality can be significantly increased for long distance links, where packet loss is high, by using routing diversity than just sending all the packets through one path

关键词： Quality of service Internet telephony Routing Delay Jitter IP networks Broadband communication Bandwidth Feedback Statistical analysis

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A Mixed H2/H∞ control Problem with controller Degree Constraint

A Mixed H2/H∞ Control Problem with Controller Degree Constr...

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IEEE Conference on Decision and control

作者： Ningbo Yu Li Qiu Automatic Control Laboratory ETH Zurich Zurich Switzerland Department of Electronic & Computer Engineering Hong Kong University of Science and Technology Hong Kong China

ISBN: (纸本)1424401704;9781424401703

In this paper, we consider a special mixed H 2 /H ∞ optimal control problem which is to obtain the optimal H 2 controller under H ∞ norm and controller degree constraints for an SISO plant. The H ∞ norm constraint on the controller is to achieve a certain level of closed-loop stability robustness against the gap metric, nu-gap metric, or normalized coprime factor uncertainties. The degree constraint requires the degree of the controller to be bounded by that of the plant. We first characterize the set of all feasible stabilizing controllers that meet both the degree and H ∞ norm constraints in terms of a finite dimensional convex set. We then carry out an optimization over the convex parameter set to find the controller that gives the optimal H 2 transient performance. Examples and observations are presented, and comparisons with the results obtained by other H 2 /H ∞ mixed optimization methods are made

关键词： Optimal control Hydrogen Upper bound Robust stability Robust control Feedback Attenuation measurement Riccati equations Centralized control USA Councils

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3D Medical images registration

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IFAC Proceedings Volumes 2006年第21期39卷 191-196页

作者： Piotr Zarychta Division of Telecomunications Institiute of Electronics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Postal address: Akademicka 16 44-100 Gliwice Poland Phone: (048) 32 2371495

Image registration is the process of overlaying images of the same scene. As we search for the best alignment of the two images by transforming one into the other, it is a very crucial issue to assess how similar two images actually are. The next step in computer aided diagnosis is called “assessment of the similarity”. There are two main classes of similarity measures namely feature-based and intensity-based. In this paper two similarity measures: NCC -normalized cross correlation and GD -gradient difference are mentioned. Normalized Cross Correlation has been used for various registration problems, because difference in contrast and brightness should not affect the similarity measure. Goal the current study is to align T1-weighted and T2-weighted MR knee slices. Both sequences are converted to a fuzzy representation. Then, the entropy and energy measures are employed in the NCC and GD methods. The alignment based on energy and entropy fuzzy mcasures shows a significant improvement in comparision with thc implementation of the original image.

关键词： image registration similarity measures(normalized cross correlation, gradient difference) entropy and energy measures of fuzziness

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Adaptive Predictive control of Nonlinear System Base on Multi-layer Recursive Method

Adaptive Predictive Control of Nonlinear System Base on Mult...

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World Congress on Intelligent control and Automation (WCICA)

作者： Qiubin Luo Qiuming Li Rupeng Feng Department of Computer Harbin University Harbin China Department of Control Science and Engineering Harbin Institute of Technology Harbin China Department of Automatic Test and Control Harbin Institute of Technology Harbin China

An adaptive predictive control method is presented for nonlinear discrete system by introducing multi-layer recursive method into the predictive control strategy. In this method, nonlinear system is substituted with a time-varying linear system firstly, and then multi-layer recursive is used to identify and to forecast the varied parameters in order to get the predictive output of system model. At last, adaptive predictive control is designed for the original nonlinear system. The simulation results show the effectiveness of the presented method

关键词： Programmable control Adaptive control Predictive control Nonlinear systems automatic control Nonlinear control systems control systems automatic testing System testing Time varying systems

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Live-wire method with wavelet cost map definition for mri images

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IFAC Proceedings Volumes 2006年第21期39卷 197-202页

作者： Wojciech Więlawek Division of Telecomunications Institiute of Electronics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Postal address: Akademicka 16 44-100 Gliwice Poland Phone: (048) 32 23714 95

Abstract There are edge based segmentation approaches among the set of methods utilized to image segmentation. This type of methods analyse image gradient features (like the first, the second derivative or them modification). Perfect tool to image processing is wavelet transformation which enables edges detection and often gets better results. In this paper wavelet transformation advantages was utilized. This tool was used to cost map definition. Cost map is a matrix which informs how many features of boundary each pixel possess. Then this cost map definition was applied to live-wire method. The method is semi-automatic and requires user interaction rely on points specification.

关键词： image segmentation live-wire method cost map Dijkstra algorithm wavelet transform MRI images

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Cruciate ligament localization in T1- and T2- weighted MR knee images

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IFAC Proceedings Volumes 2006年第21期39卷 203-207页

作者： Piotr Zarychta Division of Telecomunications Institiule of Electronics Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Postal address: Akademicka 16 44-100 Gliwice Poland Phone: (048) 32 2371495

Abstract This article shows a new method of the cruciate ligament localization in T1-and T2-weighted MR knee images. Cruciate ligament localization allows to reduce number of sliccs used in 3D rendering. The analysis is performed on T1-and T2-wcightcd MR knee images. Each slice is subjected to two-dimensional entropy and energy measurements of fuzziness. Then, a fuzzy c-means clustering technique modified by introducing additionally to the objective function a median estimator is implemented. The class reflecting soft tissue is subjected to similarity measures which compare a local image intensity. A detailed local analysis, based on image profile models, yields a 3D region of interest (ROI) which includes the posterior and anterior cruciate ligament. Finally, fuzzy techniques applied to the ROI histogram analysis enhances the contrast and views the 3D region.

关键词： FCM median entropy and energy measures of fuzziness

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INFLUENCE OF SCALING AND UNFOLDING IN PCA BASED MONITORING OF NUTRIENT REMOVING BATCH PROCESS

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IFAC Proceedings Volumes 2006年第13期39卷 114-119页

作者： Magda Ruiz Kris Villez Gurkan Sin Joan Colomer Peter Vanrrolleghem 1Control Engineering and Intelligent Systems Group –eXiT Department of Electronics Computer Science and Automatic Control University of Girona Campus Montilivi CP 17071 Building PIV Girona - Spain Department of Applied Mathematics Biometrics and Process Control Ghent University Coupure Links 653 B-9000 Ghent – Belgium

The data set of batch biological and biotechnological processes can be organized in a three-way data matrix. In this paper the usefulness of different PCA approaches for monitoring is analyzed. Different ways of unfolding and scaling of data have been applied to a pilot-scale SBR data. PCA is used to reduce the dimensionality and to remove the non-linearity dynamic of the data. Moreover, a new method to select the number of principal components is proposed. Loadings graphics are used to determinate the predominant variables for each one. The results show that whatever model can be applied depending on the goal of the monitoring, however the models implicate possible false alarms or faults omission.

关键词： Biological Process Process monitoring Multiway Principal Component Analysis (MPCA)

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Optimal Deployment of Distributed Passive Measurement Monitors

Optimal Deployment of Distributed Passive Measurement Monito...

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IEEE International Conference on Communications (ICC)

作者： Chengchen Hu Bin Liu Zhen Liu Shifang Gao Dapeng Wu Department of Computer Science and Technology Tsinghua University Beijing China Department of Automatic Control Northwest Polytechnical University Xi'an Shaanxi China Department of Electrical and Computer Engineering University of Florida Gainesville FL USA

Flow-level traffic measurement is important for network management. The widely used centralized per-flow measurement faces a great challenge due to the demanding requirement on both memory bandwidth and memory size within a single traffic monitor. This paper addresses the issue of deploying a Distributed Passive Measurement System (DPMS) in a large scale network; specifically, we study how to optimally place traffic monitors and sample stochastic traffic flows, so that the probability of a packet being sampled (a.k.a. measurement coverage) is maximized. We formulate this problem as a Stochastic Chance Constrained Optimization (SCCO) problem; and we propose a Hybrid Intelligent (HI) algorithm to solve this problem. The HI algorithm consists of two major components, namely, uncertain function approximation and genetic algorithm. Equipped with the HI algorithm, we are able to address the optimal tradeoff between measurement coverage and deployment cost for networks with random traffic, which has not been studied before. Our simulations and experiments demonstrate the effectiveness of our algorithm, i.e., a small deployment cost or a small number of monitors are sufficient to maintain a high level of measurement coverage.

关键词： Telecommunication traffic Size measurement Bandwidth Large-scale systems Stochastic systems Stochastic processes Constraint optimization Approximation algorithms Function approximation Genetic algorithms

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NON-DIAGONAL MULTIVARIABLE ROBUST QFT control OF A WASTEWATER TREATMENT PLANT FOR SIMULTANEOUS NITROGEN AND PHOSPHORUS REMOVAL

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IFAC Proceedings Volumes 2006年第9期39卷 137-142页

作者： M. Garcia-Sanz I. Eguinoa E. Ayesa C. Martín Automatic Control and Computer Science Department. Public University of Navarra. Campus Arrosadia 31006 Pamplona (Spain) CEIT and TECNUN (University of Navarra). Paseo de Manuel Lardizabal 15 20018 San Sebastian (Spain)

This paper presents the application of a robust non-diagonal multivariable control design method, based on the Quantitative Feedback Theory (QFT), to the control of a complex wastewater treatment plant (WWTP) with biological removal of nitrogen and phosphorus. The control objective is to simultaneously regulate the concentration of ammonia, nitrates and phosphorus in the plant effluent. The manipulated variables are the dissolved oxygen (DO) level in the aerobic reactor, the sludge recycling flow from the settler and the amount of ferric hydroxide added to chemically precipitate the phosphorus. Thus, the system becomes a three-input-three-output control structure with model parameter uncertainty. A robust non-diagonal multivariable QFT method is used to design a fully populated matrix controller. This sequential method reduces the interactions between control loops, increases the robust stability and fulfils the robust performance specifications defined by the user. It also considers non-minimum phase aspects by avoiding the introduction of right-half plane transmission zeros due to the controller elements. Simulations carried out by using the IWA ASM2d model under WEST® software validate the proposed control methodology.

关键词： Robust control Multivariable Systems QFT Wastewater Treatment Plants

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Using data mining techniques for the management of seismic vulnerability

Using data mining techniques for the management of seismic v...

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作者： Leon, Florin Atanasiu, Gabriela M. Gâlea, Dan Gh. Asachi Technical University of Iaşi Romania Faculty of Automatic Control and Computer Science 53A Dimitrie Mangeron Blvd. Iaşi 700050 Romania Gh. Asachi Technical University of Iaşi Romania Faculty of Civil Engineering 43 Dimitrie Mangeron Blvd. Iaşi 700050 Romania

Natural hazards, and especially earthquakes, are often recurring phenomena. Therefore, there is a permanent need for solutions to reduce earthquake losses by developing technologies, procedures, knowledge, and tools for seismic design and rehabilitation of buildings and infrastructure. A key point to an effective decision making process that aims at mitigating their effects is building a model of the underlying facts. A Geographical Information System (GIS) is a framework able to assemble, keep, process and display specific information, identified by geographical location, which can combine layers of information to give the user a better understanding about that location. By using a Geographical Information System containing geospatial data, one can develop useful scenarios to reduce natural disaster risk and vulnerability of structures. In this paper, we describe a way of applying data mining techniques from the artificial intelligence field to earthquake analysis in order to make a better investigation of the available data. These methods are capable of finding "hidden" correlations among different subsets of data, which cannot be revealed by means of simple statistics.

关键词： Data mining

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