Group communication in wireless multimedia networks must consider the Quality of Service (QoS) parameters for efficient and quality aware multicast route computation. QoS parameters such as bandwidth, channel reliability, buffers, delays, jitters, etc. play a vital role in wireless multimedia networks. Multicast tree development for group communication must press for more than one or two QoS parameters for better services. This paper proposes a scheme for constructing a multicast tree based on a spanning tree by employing a fuzzy controller. Fuzzy controller uses three fuzzy input parameters namely, link bandwidth, link delay and link reliability for the construction of multicast spanning tree. The scheme is simulated to test its effectiveness in terms of multicast tree computation time, iterations required for multicast tree computation, packet delay and packet delivery ratio.

It is now well-admitted that formal methods are helpful for many issues raised in the Web services area. It is a feasible method of the design and the verification of Web services using process algebras. BPEL4WE can correctly combine Web services actions. It is a important part of Web Services. In this paper, we present a mapping from BPEL4WS code to value-passing CCS, which offer an available way of obtaining a formal model of BPEL4WS.

This paper investigates the modified projective synchronization (MPS) of a new hyperchaotic system. The different nonlinear feedback controllers are designed by an active control method for synchronization of two hyperchaotic systems with the same or different structures. In addition, the MPS of the new hyperchaotic system with unknown parameters including the unknown coefficients of nonlinear terms is studied by using adaptive control. Numerical simulations are presented to show the effective of the proposed hyperchaos synchronization scheme.

Phase unwrapping arises as a key step in several imaging technologies, from which we emphasize remote sensing applications like terrain analysis and generation, topographic mapping, interferometric synthetic aperture radar (ISAR). Due to various decorrelation factors, there is much noise in phase images. Phase noise degrades the visual quality of images and interferograms, increases the errors of results derived from the ISAR interferogram, and obstruct phase unwrapping. Hilbert transform (HT) as a phase unwrapping techniques was recently proposed, and its behavior in presence of noise is unknown. In this paper, one-dimensional (1-D) HT phase unwrapping algorithm is proposed to detect and eliminate phase discontinuities in N-dimensional (N-D) noisy phase arrays. The behavior of this method in presence of different noise levels is studied and compared with the other approach of phase jump detection. The phase noise filtration problem and its effect on proposed algorithm behavior are considered. Tests of method presented illustrate the validity and effectiveness of proposed algorithm for difficult problems with noisy and discontinuous original phases.

A wireless broadcast retransmission scheme based on the random network coding is put forward for the reliable broadcast in wireless broadcast system. With the strategy to allow the sender to combine and retransmit lost packets by using the random linear codes, the scheme can effectively reduce the number of retransmissions and improve the throughput efficiency. Based on the burst error channel modeled by a two- state Markov chain, analytic solutions are derived for the throughput efficiency of three schemes including the traditional Selective-Repeat ARQ (SR-ARQ), the XOR network coding-based ARQ (XOR-ARQ) and the random network coding-based ARQ (RNC-ARQ).The theoretical and simulation results show that the throughput efficiency of RNC-ARQ is considerably better than the SR-ARQ, while it can achieve the upper bound of throughput performance of the XOR-ARQ under the same channel conditions.

This paper presents a new feature vector set for noisy speech recognition in autocorrelation domain. The autocorrelation domain is well known for its pole preserving and noise separation properties. In this paper we will use the autocorrelation domain as an appropriate candidate for robust feature extraction. In our approach, extraction of mel frequency cepstral coefficients (MFCC) of the speech signals are proposed based on novel Differentiated Relative Higher Order Autocorrelation Coefficient Sequence Spectrum (DRHOASS). In this approach, initially the lower lags of the noisy speech autocorrelation sequence are discarded and then, the effect of noise is further suppressed using a high pass filter in autocorrelation domain. Finally, the feature vector set of the speech signal is found using the spectral peaks of the filtered autocorrelation sequence. We tested our features on the Hindi isolated-word task and found that it led to noticeable improvements over other autocorrelation-based and differential spetral-based methods.

In this paper, we define intuitionistic neutrosophic set (INSs) and truth-value based INSs. In fact, all INSs are neutrosophic set but all neutrosophic sets are not INSs. We define some new operations on INSs with examples for the implementation of the operations in real life problems. Also, we studied some properties of INSs.

The aim of this paper is to construct a parallel algorithm for the model developed in software testing process. The model treats software testing as a control problem. The software under test serves as a controlled object that is modeled as second order equation. The ordinary simulation to such type of model deteriorates in the vicinity of quality, efforts and complexity. The new approach based on parallel alternating group explicit algorithm shows superiority over corresponding sequential algorithm. Computational results are provided to illustrate the viability of the proposed technique.