All human languages have words that can mean different things in different contexts, such words with multiple meanings are potentially “ambiguous”. The process of “deciding which of several meanings of a term is intended in a given context” is known as “word sense disambiguation (WSD)”. This paper presents a method of WSD that assigns a target word the sense that is most related to the senses of its neighbor words. We explore the use of measures of relatedness between word senses based on a novel hybrid approach. First, we investigate how to “literally” and “regularly” express a “concept”. We apply set algebra to WordNet’s synsets cooperating with WordNet’s word ontology. In this way we establish regular rules for constructing various representations (lexical notations) of a concept using Boolean operators and word forms in various synset(s) defined in WordNet. Then we establish a formal mechanism for quantifying and estimating the semantic relatedness between concepts—we facilitate “concept distribution statistics” to determine the degree of semantic relatedness between two lexically expressed concepts. The experimental results showed good performance on Semcor, a subset of Brown corpus. We observe that measures of semantic relatedness are useful sources of information for WSD.

In k-means clustering, we are given a set of n data points in d-dimensional space ^d and an integer k and the problem is to determine a set of k points in ^d, called centers, so as to minimize the mean squared distance from each data point to its nearest center. In this paper, we present a simple and efficient clustering algorithm based on the k-means algorithm, which we call enhanced k-means algorithm. This algorithm is easy to implement, requiring a simple data structure to keep some information in each iteration to be used in the next iteration. Our experimental results demonstrated that our scheme can improve the computational speed of the k-means algorithm by the magnitude in the total number of distance calculations and the overall time of computation.

Selecting appropriate resources for running a job efficiently is one of the common objectives in a computational grid. Resource scheduling should consider the specific characteristics of the application, and decide the metrics to be used accordingly. This paper presents a distributed resource scheduling framework mainly consisting of a job scheduler and a local scheduler. In order to meet the requirements of different applications, we adopt HGSA, a Heuristic-based Greedy Scheduling Algorithm, to schedule jobs in the grid, where the heuristic knowledge is the metric weights of the computing resources and the metric workload impact factors. The metric weight is used to control the effect of the metric on the application. For different applications, only metric weights and the metric workload impact factors need to be changed, while the scheduling algorithm remains the same. Experimental results are presented to demonstrate the adaptability of the HGSA.

Compression is an intuitive way to boost the performance of a database system. However, compared with other physical database design techniques, compression consumes large amount of CPU power. There is a trade-off between the reduction of disk access and the overhead of CPU processing. Automatic design and adaptive administration of database systems are widely demanded, and the automatic selection of compression schema to compromise the trade-off is very important. In this paper, we present a model with novel techniques to integrate a rapidly convergent agent-based evolution framework, i.e. the SWAF (SWarm Algorithm Framework), into adaptive attribute compression for relational database. The model evolutionally consults statistics of CPU load and IO bandwidth to select compression schemas considering both aspects of the trade-off. We have implemented a prototype model on Oscar RDBMS with experiments highlighting the correctness and efficiency of our techniques.

Model driven generative domain engineering (MDGDE) is a domain engineering method aiming to develop optimized, reusable architectures, components and aspects for application engineering. Agents are regarded in MDGDE as special objects having more autonomy, and taking more initiative. Design of the agent involves three levels of activities: logical analysis and design, physical analysis, physical design. This classification corresponds to domain analysis and design, application analysis, and application design. Agent is an important analysis and design tool for MDGDE because it facilitates development of complex distributed system—the mobile robot. According to MDGDE, we designed a distributed communication middleware and a set of event-driven agents, which enables the robot to initiate actions adaptively to the dynamical changes in the environment. This paper describes our approach as well as its motivations and our practice.

The wide use of Internet Service in distributed computing and e-business has made the evolution of Internet Service to be one of the most prevalent research fields in software development domain. Traditional methods for software development cannot adapt to the challenge of Internet Service oriented software development. In this paper, we propose a new paradigm for the evolution of Internet Service with active objects from the characteristics of Internet Service and principles of active objects. The paradigm uses an automatic monitoring mechanism of active object to detect and process evolution requirement in system based on Internet Service.

This paper firstly introduces the structure and working principle of DSP-based parallel system, parallel accelerating board and SHARC DSP chip. Then it pays attention to investigating the system’s programming characteristics, especially the mode of communication, discussing how to design parallel algorithms and presenting a domain-decomposition-based complete multi-grid parallel algorithm with virtual boundary forecast (VBF) to solve a lot of large-scale and complicated heat problems. In the end, Mandelbrot Set and a non-linear heat transfer equation of ceramic/metal composite material are taken as examples to illustrate the implementation of the proposed algorithm. The results showed that the solutions are highly efficient and have linear speedup.

This paper focuses on the design of the cross layer between the video application layer and the MIMO physical layer. MIMO physical layer research has promised an enormous increase in the capacity of wireless communication systems. Also MIMO wireless systems operate under fading conditions where the channel faces arbitrary fluctuations. Since the wireless channel changes over each coherence period, the capacity of the wireless channel, given the power constraints, changes. Hence to make efficient use of the available capacity one needs to adapt the video bit rate. However it is impossible to adapt at the application layer as changing the parameters of the video takes more time than the coherence period of the channel. In this paper we address this problem through a novel solution and also investigate its performance through a simulation study.

For video streaming over lossy channels, intra refresh can mitigate the error-propagation effect caused by packet losses. Besides some intra-mode macroblocks (MBs) generated by the “Lagrangian rate-distortion” or “Sum of absolute difference” mode decision, the encoder or transcoder possibly needs to increase some “forced” intra-mode MBs for robust video streaming. Based on the error-propagation analysis in a group of pictures (GOP), we propose an unequal Forced-Intra-Refresh (FIR) scheme to improve packet loss resilience of video streaming. According to a GOP-level error-propagation model, the proposed unequal FIR scheme can optimally increase the unequal number of forced intra-mode MBs for different frames in a GOP. Simulation results showed that the proposed scheme can effectively enhance the robustness of video streaming under different channel conditions, and achieve about 0.1~0.9 dB gains over the average FIR scheme in H.264/AVC tools.

Equation based TCP-friendly rate control (TFRC) protocol has been proposed to support video streaming applications. In order to improve TFRC performance in wireless channels, the link level automatic repeat request (ARQ) scheme is usually deployed. However, ARQ cannot ensure strict delay guarantees, especially over multihop links. This paper introduces a theoretical model to deduce an equation for packet size adjustment in transport layer to minimize retransmission delay by taking into consideration the causative reasons inducing retransmission in link layer. An enhanced TFRC (ETFRC) scheme is proposed integrating TFRC with variable packet size policy. Simulation results demonstrate that higher goodput, lower packet loss rate (PLR), lower frame transmission delay and jitter with good fairness can be achieved by our proposed mechanism.

A Matrix Inversion Normalized Least Mean Square (MI-NLMS) adaptive beamforming algorithm was developed for smart antenna application. The MI-NLMS which combined the individual good aspects of Sample Matrix Inversion (SMI) and the Normalized Least Mean Square (NLMS) algorithms is described. Simulation results showed that the less complexity MI-NLMS yields 15 dB improvements in interference suppression and 5 dB gain enhancement over LMS algorithm, converges from the initial iteration and achieves 24% BER improvements at cochannel interference equal to 5. For the case of 4-element uniform linear array antenna, MI-NLMS achieved 76% BER reduction over LMS algorithm.

An improved interacting multiple models particle filter (IMM-PF) algorithm is proposed for multi-measurement nonlinear system with parameter perturbation. It divides the perturbation region into sub-regions and assigns each of them a particle filter. Hence the perturbation problem is converted into a multi-model filters problem. It combines the multiple measurements into a fusion value according to their likelihood function. In the simulation study, we compared it with the IMM-KF and the H-infinite filter; the results testify to its advantage over the other two methods.

An extended robust model predictive control approach for input constrained discrete uncertain nonlinear systems with time-delay based on a class of uncertain T-S fuzzy models that satisfy sector bound condition is presented. In this approach, the minimization problem of the “worst-case” objective function is converted into the linear objective minimization problem involving linear matrix inequalities (LMIs) constraints. The state feedback control law is obtained by solving convex optimization of a set of LMIs. Sufficient condition for stability and a new upper bound on robust performance index are given for these kinds of uncertain fuzzy systems with state time-delay. Simulation results of CSTR process show that the proposed robust predictive control approach is effective and feasible.

In this paper, the robust fault detection filter (RFDF) design problems are studied for nonlinear time-delay systems with unknown inputs. First, a reference residual model is introduced to formulate the RFDF design problem as an H_∞ model-matching problem. Then appropriate input/output selection matrices are introduced to extend a performance index to the time-delay systems in time domain. The reference residual model designed according to the performance index is an optimal residual generator, which takes into account the robustness against disturbances and sensitivity to faults simultaneously. Applying robust H_∞ optimization control technique, the existence conditions of the RFDF for nonlinear time-delay systems with unknown inputs are presented in terms of linear matrix inequality (LMI) formulation, independently of time delay. An illustrative design example is used to demonstrate the validity and applicability of the proposed approach.

In this work, we investigate the stabilization control design of nonholonomic stochastic system in strict-feedback form. Under the condition of all states being available for feedback, a state feedback controller was developed via the stochastic Lyapunov-like theorem and backstepping design technique. The controllers guarantee all states of the closed-loop system are bounded in probability, and largely asymptotically stable when the stochastic disturbances equal to zero at the equilibrium point of the open-loop system. Besides, the time-varying technique was introduced to avoid the uncontrollable state of chained system.

In this paper, the inverse problem of reconstructing reflectivity function of a medium is examined within a blind deconvolution framework. The ultrasound pulse is estimated using higher-order statistics, and Wiener filter is used to obtain the ultrasonic reflectivity function through wavelet-based models. A new approach to the parameter estimation of the inverse filtering step is proposed in the nondestructive evaluation field, which is based on the theory of Fourier-Wavelet regularized deconvolution (ForWaRD). This new approach can be viewed as a solution to the open problem of adaptation of the ForWaRD framework to perform the convolution kernel estimation and deconvolution interdependently. The results indicate stable solutions of the estimated pulse and an improvement in the radio-frequency (RF) signal taking into account its signal-to-noise ratio (SNR) and axial resolution. Simulations and experiments showed that the proposed approach can provide robust and optimal estimates of the reflectivity function.

Doubly-Fed Induction Generator (DFIG), with vector control applied, is widely used in Variable-Speed Constant-Frequency (VSCF) wind energy generation system and shows good performance in maximum wind energy capture. But in two traditional vector control schemes, the equivalent stator magnetizing current is considered invariant in order to simplify the rotor current inner-loop controller. The two schemes can perform very well when the grid is in normal condition. However, when grid disturbance such as grid voltage dip or swell fault occurs, the control performance worsens, the rotor over current occurs and the Fault Ride-Through (FRT) capability of the DFIG wind energy generation system gets seriously deteriorated. An accurate DFIG model was used to deeply investigate the deficiency of the traditional vector control. The improved control schemes of two typical traditional vector control schemes used in DFIG were proposed, and simulation study of the proposed and traditional control schemes, with robust rotor current control using Internal Model Control (IMC) method, was carried out. The validity of the proposed modified schemes to control the rotor current and to improve the FRT capability of the DFIG wind energy generation system was proved by the comparison study.

The 13.56 MHz analog front-end circuit for ISO/IEC 15693-compatible radio frequency identification (RFID) transponder IC presented in this paper converts RF power to DC and extracts clock and data from the interrogator by 10% or 100% ASK modulation. The transponder sends data back to the interrogator by load modulation technology. The electrostatic discharge (ESD) protection circuits function to limit RF voltage to a safe level. An inductive coupling simulation modelling for 13.56 MHz RFID system is presented, with simulation results showing that the transponder operates over a wide range of electromagnetic field strength from H_min (150 mA/m) to H_max (5 A/m). The transponder IC is implemented in SMIC 0.35-μm three-metal two-poly mixed signal CMOS technology with embedded EEPROM.

Shaft alignment is an important technique during installation and maintenance of a rotating machine. A high-precision laser alignment system has been designed with dual PSDs (Position Sensing Detector) to change traditional manual way of shaft alignment and to make the measurement easier and more accurate. The system is comprised of two small measuring units (laser transmitter and detector) and a PDA (Personal Digital Assistant) with measurement software. The laser alignment system with dual PSDs was improved on a single PSD system, and yields higher measurement accuracy than the previous design, and has been successful for designing and implements actual shaft alignment. In the system, the range of offset measurement is ±4 mm, and the resolution is 1.5 μm, with accuracy being less than 2 μm.

A dual structure of composite right/left handed (CRLH) transmission line (TL) is analyzed in which an inductance L_R is in parallel with a capacitance C_L and a shunt capacitance C_R is in series with an inductance L_L. Both the distributed and lumped cases are considered. The dispersion diagram and transmission properties of the dual CRLH TL are given and compared with those of a standard CRLH TL. Contrary to the frequency response of a standard CRLH TL, a dual CRLH TL has a left-handed (negative phase shift) band at higher frequencies and a right-handed (positive phase shift) band at lower frequencies. A novel dual-band balun is presented as an application.

In the manufacturing grid’s architecture, Resources Management System (RMS) is the central component responsible for disseminating resource information across the grid, accepting requests for resources, discovering and scheduling the suitable resources that match the requests for the global grid resource, and executing the requests on scheduled resources. In order to resolve the problem of resources publication and discovery in Manufacturing Grid (MGrid), the classification of manufacturing resources is first researched after which the resources encapsulation class modes are put forward. Then, a scalable two-level resource management architecture is constructed on the model, which includes root nodes, domain nodes and leaf nodes. And then an RMS is proposed, and the resources publication and discovery mechanism are detailedly described. At last, an application prototype is developed to show the validity and the practicability of the proved theory and method.

This paper presents evaluation and comparison of the TCP performance in different mobile scenarios generated by Random Waypoint (RW) and Social Network (SN) mobility models. To our knowledge, TCP performance in SN mobility is discussed for the first time. The impact of AODV and DSDV routing protocols on the TCP goodput, delay and drop rate performance is also discussed. Extensive simulation results and analysis showed that TCP has better performance over AODV than over DSDV and has more stable performance in SN mobility than in RW mobility. We suggest using more mobility models, in particular, such as SN, in the evaluations of the transport layer or routing layer protocols because the mobility patterns have impacts on the protocol performance.