Grafting of methyl methacrylate onto guar gum by hydrogen peroxide initiation

Graft copolymerization of methyl methacrylate (MMA) onto guar gum (GG) in aqueous slurry has been carried out using hydrogen peroxide (H₂O₂) as initiator. The copolymers were characterized by infrared spectroscopy. The grafting parameters like percent grafting, grafting efficiency, percent add-on, and the grafting frequency were determined, and the effect of reaction time, concentration of initiator, and [GG]/[MMA] ratios on the grafting parameters have been discussed. The decrease in % add-on at increasing concentration of H₂O₂ indicated enhancement in the rate of homopolymerization of methyl methacrylate.     

The differential effect of polymyxin B1 on guinea pig lung mitochondrial and microsomal glycerophosphate acyltransferase

The activities of guinea pig lung mitochondrial and microsomal glycerophosphate acyltransferase differed in sensitivity to polymyxin B₁. At an antibiotic concentration of 1 mg/ml, the mitochondrial enzyme activity was stimulated twofold, but the microsomal enzyme activity was completely inhibited. Furthermore, the mitochondrial enzyme activity was stimulated by polymyxin B₁ without the addition of exogenous acyl-CoA. Additional experiments ruled out the possibility of polymyxin B₁ acting as a substrate for the mitochondrial acyltransferase. These results suggest either that the polymyxin B₁ sensitivity of mitochondrial and microsomal glycerophosphate acyltransferase is different or that their accessibility to substrates is different because the two isoenzymes are located differently in the different phospholipid microenvironment of the membranes.     

Electrical properties of vanadium pentoxide doped with lithium and sodium in the α-phase range

The electrical conductivity and Seebeck coefficients have been measured from room temperature to 500° C for polycrystalline V₂O₅ and V₂O₅ doped with lithium and sodium in the -phase range. The conductivity increases with doping and the energy of activation decreases. The Seebeck coefficient indicates that electrons are the majority carriers. The results have been discussed in terms of the two-level hopping model.     

Evolutionary optimization of Haferman carpet fractal patterned antenna array

This article investigates radiation characteristics of a new type of fractal shaped antenna array based on Haferman carpet geometry. An iterative feed matrix eases the complexity of array factor calculation that makes the array factor suitable for the application of any evolutionary optimization techniques. It is seen that Haferman carpet array produces peak side lobe level (PSLL) better than Sierpinski carpet that produces ?10 dB PSLL at every stage of growth. Optimization techniques have been applied for array element reduction and PSLL minimization at different stages of growth. Here, PSLL is minimized by turning off array elements and also by varying inter element spacing between the array elements. The optimized version of Haferman carpet array produces better characteristics (49.38% thinning with ?20.5 dB PSLL for stage‐2, 46.3% thinning with ?22 dB PSLL for stage‐3 and 42.3% thinning with ?21dB PSLL for stage‐4) than its original counterpart in terms of reduced element count and PSLL. Numerical results for obtaining optimized array performance exploit both DE as well as PSO. A comparative study on the performance is also presented. As a whole, Haferman carpet is seen to be more effective approach than Sierpinski carpet in fractal antenna paradigm. © 2015 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:719–729, 2015.     

A Call-Admission Control (CAC) Algorithm for Providing Guaranteed QoS in Cellular Networks

Future broadband wireless access systems are expected to integrate various classes of mobile terminals (MTs), each class with a different type of quality of service (QoS) requirement. When the load on a wireless network is high, the guarantee of QoS for each class of MTs is a challenging task. This study considers two classes of MTs—profiled MTs and nonprofiled or regular MTs. It is assumed that profiled users require a guaranteed QoS. The measure of QoS is the probability of forced termination of a call that was allowed to access the network. Two previous handoff prioritization schemes—(i) prerequest scheme and (ii) guard channel scheme—decrease handoff failure (and hence forced termination). In this work, we compare and contrast both the schemes through extensive simulation and we find that neither guard channel nor channel prerequest scheme can guarantee a desired level of QoS for the profiled MTs. We then propose a novel call-admission control (CAC) algorithm that can maintain any desired level of QoS, while the successful call completion rate is very high. In the proposed algorithm, the new call arrival rate is estimated continuously, and when the estimated arrival rate is higher than a predetermined level, some new calls are blocked irrespective of the availability of channels. The objective of this new call preblocking is to maintain a cell's observed new call arrival rate at no more than the predetermined rate. We show that the proposed method can guarantee any desired level of QoS for profiled users.     

On an algorithm for Vision-based hand gesture recognition

A vision-based static hand gesture recognition method which consists of preprocessing, feature extraction, feature selection and classification stages is presented in this work. The preprocessing stage involves image enhancement, segmentation, rotation and filtering. This work proposes an image rotation technique that makes segmented image rotation invariant and explores a combined feature set, using localized contour sequences and block-based features for better representation of static hand gesture. Genetic algorithm is used here to select optimized feature subset from the combined feature set. This work also proposes an improved version of radial basis function (RBF) neural network to classify hand gesture images using selected combined features. In the proposed RBF neural network, the centers are automatically selected using k-means algorithm and estimated weight matrix is recursively updated, utilizing least-mean-square algorithm for better recognition of hand gesture images. The comparative performances are tested on two indigenously developed databases of 24 American sign language hand alphabet.