Jacquard image segmentation is one of the primary steps in image analysis for jacquard pattern identification. The main aim is to recognize homogeneous regions within a jacquard image as distinct, which belongs to different patterns. Active contour models have become popular for finding the contours of a pattern with a complex shape. However, the performance of active contour models is often inadequate under noisy environment. In this paper, a robust algorithm based on the Mumford-Shah model is proposed for the segmentation of noisy jacquard images. First, the Mumford-Shah model is discretized on piecewise linear finite element spaces to yield greater stability. Then, an iterative relaxation algorithm for numerically solving the discrete version of the model is presented. In this algorithm, an adaptive triangular mesh is refined to generate Delaunay type triangular mesh defined on structured triangulations, and then a quasi-Newton numerical method is applied to find the absolute minimum of the discrete model. Experimental results on noisy jacquard images demonstrated the efficacy of the proposed algorithm.

This paper proposes a novel region based image fusion scheme based on multiresolution analysis. The low frequency band of the image multiresolution representation is segmented into important regions, sub-important regions and background regions. Each feature of the regions is used to determine the region’s degree of membership in the multiresolution representation, and then to achieve multiresolution representation of the fusion result. The final image fusion result can be obtained by using the inverse multiresolution transform. Experiments showed that the proposed image fusion method can have better performance than existing image fusion methods.

This paper describes a new framework for reusing hand-drawn cartoon clips based on language understanding approach. Our framework involves two stages: a preprocessing phase, in which a hand-drawn clip library with mixed architecture is constructed, and the on-line phase, in which the domain dependent language instructions parsing is carried out and clips in the clip library are matched by use of some matching values calculated from the information derived from instruction parsing. An important feature of our approach is its ability to preserve the artistic quality of clips in the produced cartoon animations.

This paper proposes a time-domain clustered transmitter power adaptation scheme for orthogonal frequency division multiplexing (OFDM) system, which can significantly reduce the feedback amount during power adaptation comparison with conventional frequency-domain adaptation schemes. It was found that the cluster size plays an important role on the adaptation performance, especially for the vehicular environment. Simulation results showed that using Lagrange interpolation to obtain an explicit curve of Doppler frequency vs cluster size yields good trade-off between the resulted bit error rate (BER) and the amount of feedback.

Differential space-time coding was proposed recently in the literature for multi-antenna systems, where neither the transmitter nor the receiver knows the fading coefficients. Among existing schemes, double differential space-time (DDST) coding is of special interest because it is applicable to continuous fast time-varying channels. However, it is less effective in frequency-selective fading channels. This paper’s authors derived a novel time-frequency double differential space-time (TF-DDST) coding scheme for multi-antenna orthogonal frequency division multiplexing (OFDM) systems in a time-varying frequency-selective fading environment, where double differential space-time coding is introduced into both time domain and frequency domain. Our proposed TF-DDST-OFDM system has a low-complexity non-coherent decoding scheme and is robust for time- and frequency-selective Rayleigh fading. In this paper, we also propose the use of state-of-the-art low-density parity-check ΛLDPC) code in serial concatenation with our TF-DDST scheme as a channel code. Simulations revealed that the LDPC based TF-DDST OFDM system has low decoding complexity and relatively better performance.

This paper addresses the problem of channel estimation for broadband MIMO-OFDM systems. An improved channel estimator with multipath time delay detection and channel gain estimation is proposed. In the algorithm, we used the correlation of the channel taps and a well-designed adjustment scheme to increase the accuracy of the time delay detection. The most attractive advantage is that the complicated matrix calculation is replaced by search steps which can acquire the channel order and estimate the channel parameters without significantly increasing the complexity of the system. Computer simulation showed that the proposed algorithm can track the time delays adaptively and, consequently, improve the channel estimation performance.

This paper proposes an effective heuristic algorithm for dynamic multicast routing with delay-constrained DDMR. The tree constructed by DDMR has the following characteristics: (1) multicast tree changes with the dynamic memberships; (2) the cost of the tree is as small as possible at each node addition/removal event; (3) all of the path delay meet a fixed delay constraint; (4) minimal perturbation to an existing tree. The proposed algorithm is based on “damage” and “usefulness” concepts proposed in previous work, and has a new parameter bf (Balancing Factor) for judging whether or not to rearrange a tree region when membership changes. Mutation operation in Genetic Algorithm (GA) is also employed to find an attached node for a new adding node. Simulation showed that our algorithm performs well and is better than static heuristic algorithms, in term of cost especially.

TCP/IP is a next generation key technology in the wireless communication network where the different characteristics of wireless and wired links result in performance degradation. We can use the proxy and automatic repeat request (ARQ) schemes to deal with this problem. In this work, we investigate the TCP performance over proxy and ARQ in the wireless network. Our analysis results showed that using the proxy can result in lower transfer latency and higher throughput and that ARQ can decrease the loss rate of wireless link and improve the performance with little additional latency. The analytical results were validated against simulations using the NS-2 with some more realistic parameters.

The congestion control mechanisms of the current standard TCP constrain the congestion windows that can be achieved by TCP in high-speed networks, which leads to low link utilization. HSTCP is one solution to solve this problem by modifying the congestion control mechanism to have the characteristics of TCP friendliness in high loss rate environment and high scalability in low loss rate environment. However, experiments revealed that HSTCP has severe RTT unfairness. After analyzing the RTT unfairness in HSTCP with a model, we proposed CW-HSTCP, which added a fair factor to decrease the difference of congestion window caused by different RTT. Fair factor of long RTT flows can cause a sharp window increment that is easy to cause a bursty traffic, so a method called block-pacing was adopted. Simulation results showed that our new proposal could alleviate the RTT unfairness while keeping advantages of HSTCP.

The high-accuracy, wide-range frequency estimation algorithm for multi-component signals presented in this paper, is based on a numerical differentiation and central Lagrange interpolation. With the sample sequences, which need at most 7 points and are sampled at a sample frequency of 25600 Hz, and computation sequences, using employed a formulation proposed in this paper, the frequencies of each component of the signal are all estimated at an accuracy of 0.001% over 1 Hz to 800 kHz with the amplitudes of each component of the signal varying from 1 V to 200 V and the phase angle of each component of the signal varying from 0° to 360°. The proposed algorithm needs at most a half cycle for the frequencies of each component of the signal under noisy or non-noisy conditions. A testing example is given to illustrate the proposed algorithm in Matlab environment.

Block-matching motion estimation plays an important role in video coding. The simple and efficient fast block-matching algorithm using Variable Shape Search (VSS) proposed in this paper is based on diamond search and hexagon search. The initial big diamond search is designed to fit the directional centre-biased characteristics of the real-world video sequence, and the directional hexagon search is designed to identify a small region where the best motion vector is expected to locate. Finally, the small diamond search is used to select the best motion vector in the located small region. Experimental results showed that the proposed VSS algorithm can significantly reduce the computational complexity, and provide competitive computational speedup with similar distortion performance as compared with the popular Diamond-based Search (DS) algorithm in the MPEG-4 Simple Profile.

Effects of the speed relaxation time on the optimal velocity car-following model (OVM) with delay time due to driver reaction time proposed by Bando et al.(1995) were studied by numerical methods. Results showed that the OVM including the delay is not physically sensitive to the speed relaxation times. A modified car-following model is proposed to overcome the deficiency. Analyses of the linear stability of the modified model were conducted. It is shown that coexisting flows appear if the initial homogeneous headway of the traffic flow is between critical values. In addition, phase transitions occur on varying the initially homogeneous headway.

A module M is called closed weak supplemented if for any closed submodule N of M, there is a submodule K of M such that M=K+N and K∩N<<M. Any direct summand of closed weak supplemented module is also closed weak supplemented. Any nonsingular image of closed weak supplemented module is closed weak supplemented. Nonsingular V-rings in which all nonsingular modules are closed weak supplemented are characterized in Section 4.

Current technology for frequent itemset mining mostly applies to the data stored in a single transaction database. This paper presents a novel algorithm MultiClose for frequent itemset mining in data warehouses. MultiClose respectively computes the results in single dimension tables and merges the results with a very efficient approach. Close itemsets technique is used to improve the performance of the algorithm. The authors propose an efficient implementation for star schemas in which their algorithm outperforms state-of-the-art single-table algorithms.

An integrated model is presented to schedule the container handling system. The objective is to improve the cooperation between different types of equipments, and to increase the productivity of the terminal. The problem is formulated as a Hybrid Flow Shop Scheduling problem with precedence constraint, setup times and blocking (HFSS-B). A tabu search algorithm is proposed to solve this problem. The quality and efficiency of the proposed algorithm is analyzed from the computational point of view.

With the rapid development of Virtual Private Network (VPN), many companies and organizations use VPN to implement their private communication. Traditionally, VPN uses security protocols to protect the confidentiality of data, the message integrity and the endpoint authentication. One core technique of VPN is tunneling, by which clients can access the internal servers traversing VPN. However, the tunneling technique also introduces a concealed security hole. It is possible that if one vicious user can establish tunneling by the VPN server, he can compromise the internal servers behind the VPN server. So this paper presents a novel Application-layer based Centralized Information Access Control (ACIAC) for VPN to solve this problem. To implement an efficient, flexible and multi-decision access control model, we present two key techniques to ACIAC—the centralized management mechanism and the stream-based access control. Firstly, we implement the information center and the constraints/events center for ACIAC. By the two centers, we can provide an abstract access control mechanism, and the material access control can be decided dynamically by the ACIAC’s constraint/event mechanism. Then we logically classify the VPN communication traffic into the access stream and the data stream so that we can tightly couple the features of VPN communication with the access control model. We also provide the design of our ACIAC prototype in this paper.

The modelling and formal characterization of spatial vagueness plays an increasingly important role in the implementation of Geographic Information System (GIS). The concepts involved in spatial objects of GIS have been investigated and acknowledged as being vague and ambiguous. Models and methods which describe and handle fuzzy or vague (rather than crisp or determinate) spatial objects, will be more necessary in GIS. This paper proposes a new method for modelling spatial vagueness based on type-2 fuzzy set, which is distinguished from the traditional type-1 fuzzy methods and more suitable for describing and implementing the vague concepts and objects in GIS.

An immune algorithm solution is proposed in this paper to deal with the problem of optimal coordination of local physically based controllers in order to preserve or retain mid and long term voltage stability. This problem is in fact a global coordination control problem which involves not only sequencing and timing different control devices but also tuning the parameters of controllers. A multi-stage coordinated control scheme is presented, aiming at retaining good voltage levels with minimal control efforts and costs after severe disturbances in power systems. A self-pattern-recognized vaccination procedure is developed to transfer effective heuristic information into the new generation of solution candidates to speed up the convergence of the search procedure to global optima. An example of four bus power system case study is investigated to show the effectiveness and efficiency of the proposed algorithm, compared with several existing approaches such as differential dynamic programming and tree-search.

Under unbalanced source voltage supply, considerable output second harmonics and input low-order harmonics in 3-phase PWM current-source converters (PWM-CSC) are generated. This paper proposes a new deadbeat controller based on compensation for unbalanced source voltage and current. With the proposed scheme, the second harmonics of the output current are eliminated and low-order harmonics of the source current are reduced effectively. Simulation and experimental results confirmed the feasibility of the proposed method.

The 32-bit extensible embedded processor RISC3200 originating from an RTL prototype core is intended for low-cost consumer multimedia products. In order to incorporate the reduced instruction set and the multimedia extension instruction set in a unifying pipeline, a scalable super-pipeline technique is adopted. Several other optimization techniques are proposed to boost the frequency and reduce the average CPI of the unifying pipeline. Based on a data flow graph (DFG) with delay information, the critical path of the pipeline stage can be located and shortened. This paper presents a distributed data bypass unit and a centralized pipeline control scheme for achieving lower CPI. Synthesis and simulation showed that the optimization techniques enable RISC3200 to operate at 200 MHz with an average CPI of 1.16. The core was integrated into a media SOC chip taped out in SMIC 0.18-micron technology. Preliminary testing result showed that the processor works well as we expected.

In this paper, a detection technique for locating and determining the extent of defects and cracks in oil pipelines based on Hilbert-Huang time-frequency analysis is proposed. The ultrasonic signals reflected from defect-free pipelines and from pipelines with defects were processed using Hilbert-Huang transform, a recently developed signal processing technique based on direct extraction of the energy associated with the intrinsic time scales in the signal. Experimental results showed that the proposed method is feasible and can accurately and efficiently determine the location and size of defects in pipelines.

Position and orientation estimation with high accuracy based on GPS and encoders for a four-wheel-steering vehicle (4WS) mobile robot is presented. A GPS receiver working in Real-Time Kinematics (RTK) mode can offer centimeter-level accuracy for our vehicle. In addition to GPS, the vehicle is equipped with four incremental encoders and two absolute encoders to provide information on wheels for estimation of velocity and sideslip angle of vehicle. The proposed architecture of position and orientation estimation consists of two extended Kalman filters and a processing unit of Runga-Kutta based dead reckoning. The first EKF fuses data from six encoders to estimate the vehicle velocity and the sideslip angle. The second EKF is applied to the estimation of position and orientation based on the measurement from precise RTK GPS data and output from first EKF. To obtain higher accuracy of estimation, an arbitrator is designed to switch between EKF2 and dead reckoning. The results and analysis of experiments are presented to show the effectiveness of the proposed approach. Limitations of the proposed approach and future works are also pointed out and discussed in this paper.

In Chinese, dependency analysis has been shown to be a powerful syntactic parser because the order of phrases in a sentence is relatively free compared with English. Conventional dependency parsers require a number of sophisticated rules that have to be handcrafted by linguists, and are too cumbersome to maintain. To solve the problem, a parser using SVM (Support Vector Machine) is introduced. First, a new strategy of dependency analysis is proposed. Then some chosen feature types are used for learning and for creating the modification matrix using SVM. Finally, the dependency of phrases in the sentence is generated. Experiments conducted to analyze how each type of feature affects parsing accuracy, showed that the model can increase accuracy of the dependency parser by 9.2%.

A new framework for networked control system based on Generalized Predictive Control (GPC) is proposed in this paper. Clock-driven sensors, event-driven controller, and clock-driven actuators are required in this framework. A queuing strategy is proposed to overcome the network induced delay. Without redesigning, the proposed framework enables the existing GPC controller to be used in a network environment. It also does not require clock synchronization and is only slightly affected by bad network condition such as package loss. Various experiments are designed over the real network to test the proposed approach, which verify that the proposed approach can stabilize the Networked Control System (NCS) and is robust.

Support Vector Machines (SVMs) have been widely used in pattern recognition and have also drawn considerable interest in control areas. Based on a method of least squares SVM (LS-SVM) for multivariate function estimation, a generalized inverse system is developed for the linearization and decoupling control of a general nonlinear continuous system. The approach of inverse modelling via LS-SVM and parameters optimization using the Bayesian evidence framework is discussed in detail. In this paper, complex high-order nonlinear system is decoupled into a number of pseudo-linear Single Input Single Output (SISO) subsystems with linear dynamic components. The poles of pseudo-linear subsystems can be configured to desired positions. The proposed method provides an effective alternative to the controller design of plants whose accurate mathematical model is unknown or state variables are difficult or impossible to measure. Simulation results showed the efficacy of the method.