Throughput analysis of wireless-powered decode-and-forward relay systems with interference

Wireless Networks - This paper investigates the throughput of a wireless-powered dual-hop relaying system with the presence of co-channel interference. Specifically, an energy-constrained source...     

Ram bending of a cylindrical pipe in the elastic range

The problem of ram bending of a straight cylindrical pipe is considered. Separate shell theory and finite element method (FEM) solutions are presented. The loading is idealized as a set of pads of uniform radial pressure, and results are given for the elastic range. Particular attention is paid to the FEM solution characteristics and the pipe springback behavior. The present study is a necessary preliminary step to the full elastic-plastic solution of the problem.     

Influence of pH on the photocatalytic activity of ZnO nanoparticles

In this study, ZnO nanoparticles were fabricated by co-precipitation method. The synthesized nanoparticles possessed monodispersity with the average size 20–30 nm. Since the industrial effluents may not be at neutral pH, the effect of pH on the rate of degradation is important and need to be considered. In order to investigate the effect of pH on ZnO nanoparticles photocatalytic activity, the photocatalytic degradation of Rose Bengal, Methylene blue, and Bromocresol green dyes, was studied with different pH values. It was observed that the adsorption of the dyes onto ZnO nanoparticles surface is strongly dependent on the pH of the solution which plays an important role in photocatalytic degradation.     

Adaptive noise-reducing anisotropic diffusion filter

In image processing and computer vision, the denoising process is an important step before several processing tasks. This paper presents a new adaptive noise-reducing anisotropic diffusion (ANRAD) method to improve the image quality, which can be considered as a modified version of a speckle-reducing anisotropic diffusion (SRAD) filter. The SRAD works very well for monochrome images with speckle noise. However, in the case of images corrupted with other types of noise, it cannot provide optimal image quality due to the inaccurate noise model. The ANRAD method introduces an automatic RGB noise model estimator in a partial differential equation system similar to the SRAD diffusion, which estimates at each iteration an upper bound of the real noise level function by fitting a lower envelope to the standard deviations of pre-segment image variances. Compared to the conventional SRAD filter, the proposed filter has the advantage of being adapted to the color noise produced by today’s CCD digital camera. The simulation results show that the ANRAD filter can reduce the noise while preserving image edges and fine details very well. Also, it is favorably compared to the fast non-local means filter, showing an improvement in the quality of the restored image. A quantitative comparison measure is given by the parameters like the mean structural similarity index and the peak signal-to-noise ratio.     

A novel one-step microemulsion method for preparation of quercetin encapsulated poly(methyl methacrylate) nanoparticles

A series of drug-loaded poly(methyl methacrylate) (PMMA) nanoparticles were prepared and studied as controlled release carrier of quercetin drug using a simple one-step differential microemulsion method. The polymer carriers were prepared in different monomer/surfactant ratios. The encapsulated PMMA nanoparticles were characterized by Fourier transform infrared spectroscopy, dynamic light scattering and transmission electron microscopy analysis. The particle size was obtained below 10 nm with spherical shape and narrow size distribution. In vitro drug release studies were performed using a dissolution medium such as sodium phosphate buffer saline simulating body fluids. Based on a full factorial 3² experimental design, nine formulations for quercetin-loaded PMMA nanoparticles were prepared and the molar ratio of monomer/surfactant and amount of initiator were considered as independent variables, while the encapsulation efficiency, solid content and drug release were taken into account as responses. Based on ANOVA analysis, with desirability factor of 0.952, the software F3 was suggested as an optimized formulation. This formulation was composed using a monomer/surfactant molar ratio of 3 and initiator amount of 0.02 g as independent variables, while the amounts of 71.10, 25.34, and 61.54%, in the order given, for encapsulation efficiency, solid content and drug release, were obtained as responses. To estimate release mechanism, the obtained cumulative release data were fitted to zero-order, first-order, Higuchi and Korsmeyer-Peppas kinetic models. In vitro release experiments in all cases revealed that the controlled release behavior followed from Korsmeyer-Peppas kinetic model exhibited non-Fickian diffusion mechanism. Consequently, this research offers useful pharmaceutical carriers with the purpose of providing prolonged release for targeting delivery.     

The formation and properties of single nuclei

The formation and growth of single metallic nuclei of silver, mercury and copper have been studied at microscopically small electrodes of platinum and carbon. Once formed, metallic nuclei act as point sinks, growing under hemispherical mass-transfer control. The rate of growth at low overpotential is a function of the mean surface concentration as determined by the Nernst relation.The rate of formation of isolated nuclei has been determined as the inverse of the delay time attending their birth as indicated by the onset of the growth current. A distribution of delay times is observed in keeping with the statistical nature of the nucleation process.The nuclei or crystallites formed are spherical droplets in the case of mercury or microscopic single crystals in the case of solid metals, their size being accessible from the current—time integral of their growth. They are stable on open circuit and exhibit the residual overpotential of their excess surface free energy, ie their Gibbs—Kelvin potential. This potential is a linear function of their inverse equivalent spherical radius. The surface tensions calculated from the simplest application of the Gibbs—Kelvin equations appear to be higher than the known or estimated bulk values.The microscopic metallic crystallites have been used as reactive electrodes. The high mass-transfer flux to their surface enabled the exchange current to be determined by a simple, steady state small amplitude dc procedure.These studies confirm the considerable promise of microscopically small electrodes in electrochemistry.     

Feature selection using swarm-based relative reduct technique for fetal heart rate

Fetal heart rate helps in diagnosing the well-being and also the distress of fetal. Cardiotocograph (CTG) monitors the fetal heart activity to estimate the fetal tachogram based on the evaluation of ultrasound pulses reflected from the fetal heart. It consists in a simultaneous recording and analysis of fetal heart rate signal, uterine contraction activity and fetal movements. Generally CTG comprises more number of features. Feature selection also called as attribute selection is a process of selecting a subset of highly relevant features which is responsible for future analysis. In general, medical datasets require more number of features to predict an activity. This paper aims at identifying the relevant and ignores the redundant features, consequently reducing the number of features to assess the fetal heart rate. The features are selected by using unsupervised particle swarm optimization (PSO)-based relative reduct (US-PSO-RR) and compared with unsupervised relative reduct and principal component analysis. The proposed method is then tested by applying various classification algorithms such as single decision tree, multilayer perceptron neural network, probabilistic neural network and random forest for maximum number of classes and clustering accuracies like root mean square error, mean absolute error, Davies–Bouldin index and Xie–Beni index for minimum number of classes. Empirical results show that the US-PSO-RR feature selection technique outperforms the existing methods by producing sensitivity of 72.72 %, specificity of 97.66 %, F-measure of 74.19 % which is remarkable, and clustering results demonstrate error rate produced by US-PSO-RR is less as well.     

Minimax PAC bounds on the sample complexity of reinforcement learning with a generative model

We consider the problems of learning the optimal action-value function and the optimal policy in discounted-reward Markov decision processes (MDPs). We prove new PAC bounds on the sample-complexity of two well-known model-based reinforcement learning (RL) algorithms in the presence of a generative model of the MDP: value iteration and policy iteration. The first result indicates that for an MDP with N state-action pairs and the discount factor γ∈[0,1) only O(Nlog(N/δ)/((1?γ)³ ε ²)) state-transition samples are required to find an ε-optimal estimation of the action-value function with the probability (w.p.) 1?δ. Further, we prove that, for small values of ε, an order of O(Nlog(N/δ)/((1?γ)³ ε ²)) samples is required to find an ε-optimal policy w.p. 1?δ. We also prove a matching lower bound of Θ(Nlog(N/δ)/((1?γ)³ ε ²)) on the sample complexity of estimating the optimal action-value function with ε accuracy. To the best of our knowledge, this is the first minimax result on the sample complexity of RL: the upper bounds match the lower bound in terms of N, ε, δ and 1/(1?γ) up to a constant factor. Also, both our lower bound and upper bound improve on the state-of-the-art in terms of their dependence on 1/(1?γ).