WCCI 2008 CALL FOR PAPERS IEEE World Congress on Computational Intelligence HongKong June 1-6, 2008

The 2008 IEEE Wodd Congress on Computational Intelligence （WCCI 2008） will be held at the Hong Kong Convention and Exhibition Centre during June 1-6, 2008. WCCI 2008 will be the fifth milestone in this series with a glorious history from WCCI 1994 in Orlando, WCCI 1998 in Anchorage, WCCI 2002 in Honolulu, to WCCI 2006 in Vancouver. Sponsored by the IEEE Computational Intelligence Society, co-sponsored by the International Neural Network Society, Evolutionary Programming Society, and the Institution of Engineering and Technology, and composed of the 2008 International Joint Conference on Neural Networks （IJCNN2008）, 2008 IEEE International Conference on Fuzzy Syrtems （FUZZ-IEEE2008）, and 2008 IEEE Congress on Evolutionary Computation （CEC2008）, WCC12008 will be the largest technical event on computational intelligence in the world with the biggest impact. WCCI 2008 will provide a stimulating forum for thousands of scientists, engineers, educators and students from all over the world to disseminate their new research findingsand exchange information on emerging areas of research in the fields. WCCI 2008 will also create a pleasant environment for the participants to meet old friends and make new friends who share similar research interests.     

WCCI 2008 CALL FOR PAPERS IEEE World Congress on Computational Intelligence HongKong June 1 - 6, 2008

)The 2008 IEEE World Congress on Computational Intelligence (WCCI 2008) will be held at the HongKong Convention and Exhibition Centre during June 1-6, 2008. WCCI 2008 will be the fifth milestone inthis series with a glorious history from WCCI 1994 in Orlando, WCCI 1998 in Anchorage, WCCI 2002in Honolulu, to WCCI 2006 in Vancouver. Sponsored by the IEEE Computational Intelligence Society,     

WCCI 2008 CALL FOR PAPERS IEEE World Congress on Computational Intelligence

The 2008 IEEE World Congress on Computational Intelligence (WCCI 2008) will be held at the Hong Kong Convention and Exhibition Centre during June 1-6, 2008. WCCI 2008 will be the fifth milestone in this series with a glorious history from WCCI 1994 in Orlando, WCCI 1998 in Anchorage, WCCI     

2014 IEEE模糊系统国际会议(英文)

The IEEE World Congress on Computational Intelligence(IEEE WCCI)is the largest technical event in the field of computational intelligence.IEEE WCCI 2014 will host three conferences:The 2014 International Joint Conference on Neural Networks(IJCNN 2014),the 2014 IEEE International Conference on Fuzzy Systems(FUZZ-IEEE 2014),and the 2014IEEE Congress on Evolutionary Computation(IEEE CEC 2014).IEEE WCCI 2014 will engage in cross-fertilization a-     

Stochastic gradient algorithm for a dual-rate Box-Jenkins model based on auxiliary model and FIR model简

Based on the work in Ding and Ding （2008）, we develop a modifi ed stochastic gradient （SG） parameter estimation algorithm for a dual-rate Box-Jenkins model by using an auxiliary model. We simplify the complex dual-rate Box-Jenkins model to two fi nite impulse response （FIR） models, present an auxiliary model to estimate the missing outputs and the unknown noise variables, and compute all the unknown parameters of the system with colored noises. Simulation results indicate that the proposed method is effective.     

The 22nd IEEE International Conference on Advanced Information Networking and Applications

Sponsored by IEEE Computer Society TCDP As one of the most important international conferences sponsored by the TCDP of the IEEE Computer Society, the International Conference on Advanced Information Networking and Applications （AINA-08） will be held in Ginowan City （URL http//www.city.ginowan.okinawa.jp/2735/2410.html）, Okinawa, Japan, on March 25-28, 2008. The conference covers theory, design and application of computer networks and distributed computing systems. Aside from the regular presentations, the conference will include keynote addresses with speakers from both industry and academia.     

2008年IEEE机械制造及自动化国际会议

2008 IEEE International Conference on Mechatronics and Automation （ICMA 2008） will take place in Takamatsu, Kagawa, Japan from June 24 to June 27, 2008. Takamatsuis the small city located at Sikoku which is the smallest island in 4 main islands of Japan. Shikoku contains a lot of temples including Zentsuji, where one of the most famous Buddhists, Kukai, was born. In addition, you can feel the Japanese history through several historical architectures.     

Seventeenth International World Wide Web Conference （WWW2008）

The International World Wide Web Conferences Steering Committee （IW3C2） cordially invites you to participate in the 17th International World Wide Web Conference （WWW2008）, to be held on April 21-25, 2008 in Beijing, China. The conference series has become the premier venue for academics and industry to present, demonstrate, and discuss the latest ideas about the Web. The technical program for the five-day conference will include refereed paper presentations, plenary sessions, panels, and poster sessions. The WWW2008 program will also include Tutorials and Workshops, a W3C track, a Developers track, a WWW in China track, and Exhibitions.     

Performance evaluation for PCC-OFDM systems impaired by carrier frequency offset over AWGN channels

Orthogonal frequency division multiplexing （OFDM） is sensitive to carrier frequency offset （CFO）, which destroys the orthogonality and causes inter-carrier interference （ICI）. ICI self-cancellation schemes based on polynomial cancellation coding （PCC-OFDM） can evidently reduce the sensitivity to CFO. In this paper, we analyze the performance of PCC-OFDM systems impaired by CFO over additive white gaussian noise （AWGN） channels. Two criteria are used to evaluate the effect of CFO on performance degradations. Firstly, the closed-form expressions of the average carrier-to-interference power ratio （CIR） and the statistical average ICI power, both of which reflect the desired power loss, are presented. Simulation and analytical results show that the theoretical expressions depend crucially on the normalized frequency offset and are hardly relevant to the number of subcarriers. Secondly, by exploiting the properties of the Beaulieu series, the effect of CFO on symbol error rate （SER） and bit error rate （BER） performance for PCC-OFDM systems are exactly expressed as the sum of an infinite series in terms of the charac- teristic function （CHF） of ICI. We consider the systems modulated with binary phase shift keying （BPSK）, quadrature PSK （QPSK）, 8-ary PSK （8-PSK）, and 16-ary quadrature amplitude modulation （16-QAM）, and all above modulation schemes are mapped with Gray codes for the evaluations of BER.     

The Influence of the Color Model on the Performance of a CBIR System Based on Color Moments

In this paper, we evaluate the influence of color models on the performance of a CBIR system based on color moments signature. The color models considered are： RGB （red, green, blue）, HSV （hue, saturation, value） and the mixture RGB-HSV. We specifically investigate also the effect of the moment＇s degree （0： mean, 1： variance, 2： skewness） and their conjunction on the system relevance. Practically, many scenarios have been checked： three, six, nine, twelve and eighteen values extracted from moments over the three color models. For the evaluation, we use the precision recall curves on the Wang database. We also employ the utility concept in the evaluation of the ranking quality of the returned images. Results show that the combination （RGB-HSV, mean） is the best configuration. In addition, results show also that the mean （three values） is the best signature regardless of the color space and the HSV color model is the best regardless of the number of values to consider.     

SO（3） classifier of Lie group machine learning

This paper gives the method to design classifiers of Lie group Machine Learning （LML） based on the basic conceptions and the theory framework of it, which contains the following steps： （1） Map the observed data set in the learning system to the nonempty set G. （2） Construct the corresponding Lie group structure according to G. （3） Apply the obtained Lie group to build the LML model. （4） Form the corresponding classifier. （5） Test classification abilities and so on. At last, the design of SO（3） classifier and an example are given to test its classification ability.     

Improved Blocking Time Analysis and Evaluation for the Multiprocessor Priority Ceiling Protocol

The Multiprocessor Priority Ceiling Protocol （MPCP） is a classic suspension-based real-time locking protocol for partitioned fixed-priority （P-FP） scheduling. However, existing blocking time analysis is pessimistic under the P-FP ＋ MPCP scheduling, which negatively impacts the schedulability for real-time tasks. In this paper, we model each task as an alternating sequence of normal and critical sections, and use both the best-case execution time （BCET） and the worst-case execution time （WCET） to describe the execution requirement for each section. Based on this model, a novel analysis is proposed to bound shared resource requests. This analysis uses BCET to derive the lower bound on the inter-arrival time for shared resource requests, and uses WCET to obtain the upper bound on the execution time of a task on critical sections during an arbitrary time interval of △t. Based on this analysis, improved blocking analysis and its associated worst-case response time （WCRT） analysis are proposed for P-FP ＋ MPCP scheduling. Schedulability experiments indicate that the proposed method outperforms the existing methods and improves the schedulability significantly.     

On the ?2 stability of time varying linear and nonlinear discrete time MIMO systems

New conditions are derived for the l2-stability of time-varying linear and nonlinear discrete-time multiple-input multipleoutput （MIMO） systems, having a linear time time-invariant block with the transfer function F（z）, in negative feedback with a matrix of periodic/aperiodic gains A（k）, k = 0,1, 2,... and a vector of certain classes of non-monotone/monotone nonlinearities φp（-）, without restrictions on their slopes and also not requiring path-independence of their line integrals. The stability conditions, which are derived in the frequency domain, have the following features： i） They involve the positive definiteness of the real part （as evaluated on ｜z｜ = 1） of the product of Г （z） and a matrix multiplier function of z. ii） For periodic A（k）, one class of multiplier functions can be chosen so as to impose no constraint on the rate of variations A（k）, but for aperiodic A（k）, which allows a more general multiplier function, constraints are imposed on certain global averages of the generalized eigenvalues of （A（k ＋ 1）,A（k））, k = 1, 2 iii） They are distinct from and less restrictive than recent results in the literature.     

Joint adaptive power allocation and interference suppression algorithms based on theMSER criterion for wireless sensor networks

In this study, a two-hop wireless sensor network with multiple relay nodes is considered where the amplify-and-forward （AF） scheme is employed. Two algorithms are presented to jointly consider interference suppression and power allocation （PA） based on the minimization of the symbol error rate （SER） criterion. A stochastic gradient （SG） algorithm is developed on the basis of the minimum-SER （MSER） criterion to jointly update the parameter vectors that allocate the power levels among the relay sensors subject to a total power constraint and the linear receiver. In addition, a conjugate gradient （CG） algorithm is developed on the basis of the SER criterion. A centralized algorithm is designed at the fusion center. Destination nodes transmit the quantized information of the PA vector to the relay nodes through a limited-feedback channel. The complexity and convergence analysis of the proposed algorithms are carried out. Simulation results show that the proposed two adaptive algorithms significantly outperform the other previously reported algorithms.     

New Cloud Consolidation Architecture for Electrical Energy Consumption Management

Cloud computing is taking more extensive space in the research field. Cloud architectures will need to worry about energy in its various forms, to be profitable, on the one hand, and comply with environmental constraints （energy consumption and CO2 emission） on the other hand. VM （virtual machines） consolidation （VMs in this document）, among other techniques, must take into account the consumption of electrical energy, for example, while providing a level of performance that meets the requirements of SLAs （service level agreements）. In our work, we focus on an architecture configuration to manage virtual machines in a data center, in order to optimize the consumption of energy, and meet SLAs＇s constraints at the same time, by grafting a tracing component of the multiple consolidation plans that leads to an optimal configuration to finally give the order of the migration machinery to a minimum number of servers switched on, knowing that VMs （virtual machines） that coexist in the same server, are at risk of congestion and interference.     

An extended processing scheme for coherent integration and parameter estimation based on matched filtering in passive radar

In passive radars, coherent integration is an essential method to achieve processing gain for target detection. The cross ambiguity function （CAF） and the method based on matched filtering are the most common approaches. The method based on matched filtering is an approximation to CAF and the procedure is： （1） divide the signal into snapshots; （2） perform matched filtering on each snapshot; （3） perform fast Fourier transform （FFT） across the snapshots. The matched filtering method is com- putationally affordable and can offer savings of an order of 1000 times in execution speed over that of CAF. However, matched filtering suffers from severe energy loss for high speed targets. In this paper we concentrate mainly on the matched filtering method and we use keystone transform to rectify range migration. Several factors affecting the performance of coherent integration are discussed based on the matched filtering method and keystone transform. Modified methods are introduced to improve the performance by analyzing the impacts of mismatching, precision of the keystone transform, and discretization. The modified discrete chirp Fourier transform （MDCFT） is adopted to rectify the Doppler expansion in a multi-target scenario. A novel velocity estimation method is proposed, and an extended processing scheme presented. Simulations show that the proposed algorithms improve the performance of matched filtering for high speed targets.     

A new method for correcting vehicle license plate tilt

In the course of vehicle license plate （VLP） automatic recognition, tilt correction is a very crucial process. According to Karhunen-Loeve （K-L） transformation, the coordinates of characters in the image are arranged into a two-dimensional covariance matrix, on the basis of which the centered process is carried out. Then, the eigenvector and the rotation angle α are computed in turn. The whole image is rotated by -α. Thus, image horizontal tilt correction is performed. In the vertical tilt correction process, three correction methods, which are K-L transformation method, the line fitting method based on K -means clustering （LFMBKC）, and the line fitting based on least squares （LFMBLS）, are put forward to compute the vertical tilt angle θ. After shear transformation （ST） is imposed on the rotated image, the final correction image is obtained. The experimental results verify that this proposed method can be easily implemented, and can quickly and accurately get the tilt angle. It provides a new effective way for the VLP image tilt correction as well.     

A linear search scheme for effective order of channel impulse response in OFDM systems

This paper deals with the estimation of the channel impulse response （CIR） in orthogonal frequency division multiplexing （OFDM） systems. In particular, we focus on the maximum likelihood （ML） estimator. The ML estimator is simpler to implement as it needs no information on the channel statistics, but its performance depends on the assumed effective order of channel impulse response （EOCIR）. In this paper, we propose a novel ML channel estimator which combines the ML estimation with a strategy of linear search. The proposed method introduces a few complexities, but, compared with the existing ML channel estimators, it is highly robust to variation of EOCIR Its performance has been proved using theoretical analysis and simulations.     

Net Detection of Soccer Video

Video event retrieval is to infer the video event and use it as the content to perform the video retrieval. Here the event is defined as the medium-level spatiotemporal entity interesting to users having certain context cues corresponding to the specific domain knowledge model. This paper mainly discusses the net detection as one of context cues ＇to infer the soccer video event, The net detection algorithm mainly includes the following four steps： （1） Select the appropriate color space and perform the binary segmentation based on the white pixel; （2） Determine the representative connective image; （3） Perform the connectivity enhancement based on dilation; （4） Verify the net detection result based on grids＇ statistic, To determine the thresholds involved in the algorithm the training method is adopted. After threshold training the net detection experiments are performed to evaluate the performance of the algorithm. Experiments show that the proposed net detection algorithm is effective.     

Study on Cache Configuration of A Muitithreaded Approach

By exploiting both Instruction Level Parallelism （ILP） and Thread Level Parallelism （TLP）, the simultaneous multithread architecture can be expected to achieve better tradeoff between performance and hardware cost. This paper studies the impact to performance on different cache configurations quantitatively on the same benchmarks. It can help to find the exploitability of this architecture to different application area,