A joint correlation noise estimation and decoding algorithm for distributed video coding

Multimedia Tools and Applications - Distributed video coding is relatively a novel video coding paradigm that enables a lower complex video encoding compared to conventional video coding schemes,...     

Modeling of spectrum sharing using ITLinQ scheme in device-to-device networks with full-duplex relays

Telecommunication Systems - This paper considers simultaneous wireless information and power transfer enabled full-duplex multi-user multiple-input multiple-output cognitive networks. By taking...     

PSO-DS: a scheduling engine for scientific workflow managers

Cloud computing, an important source of computing power for the scientific community, requires enhanced tools for an efficient use of resources. Current solutions for workflows execution lack frameworks to deeply analyze applications and consider realistic execution times as well as computation costs. In this study, we propose cloud user–provider affiliation (CUPA) to guide workflow’s owners in identifying the required tools to have his/her application running. Additionally, we develop PSO-DS, a specialized scheduling algorithm based on particle swarm optimization. CUPA encompasses the interaction of cloud resources, workflow manager system and scheduling algorithm. Its featured scheduler PSO-DS is capable of converging strategic tasks distribution among resources to efficiently optimize makespan and monetary cost. We compared PSO-DS performance against four well-known scientific workflow schedulers. In a test bed based on VMware vSphere, schedulers mapped five up-to-date benchmarks representing different scientific areas. PSO-DS proved its efficiency by reducing makespan and monetary cost of tested workflows by 75 and 78%, respectively, when compared with other algorithms. CUPA, with the featured PSO-DS, opens the path to develop a full system in which scientific cloud users can run their computationally expensive experiments.     

Alkylendiamide und Alkylendiisoimide von Äthyleniminocarbonsäuren und -dicarbonsäuren

Alkylenediamides and Alkylenediisoimides from Ethyleneimino Carboxylic Acids and Ethyleneimino Dicarboxylic Acids Preparation and properties of some alkylenediamides from β-ethyleneiminopropionic acid and ethyleneiminosuccinic acid as well as of two alkylenediisoimides of ethyleneiminosuccinic acid are described.     

Effect of polyethylenimine addition and washing on stability and electrophoretic deposition of Co3O4 nanoparticles

In this work, the parameters of cobalt oxide suspension such as conductivity, zeta potential, particle size, stability, and finally the electrophoretic behavior of particles in the absence and presence of polyethylenimine (PEI) in acetone medium were investigated. Also, the effects of washing on the stability and electrophoretic deposition of Co₃O₄ were studied. Characterization of the obtained layer by optical microscopy revealed that there was no deposition in the suspension without PEI, while a uniform layer was formed in the presence of PEI additive. Scanning electron microscopy (SEM) results confirmed the uniformity of layer obtained in acetone using PEI additive. Moreover, SEM results demonstrated that more porous microstructures were obtained at longer deposition durations. The difference in the porosity of the layers, as indicated by the SEM micrographs, is attributed to increase in the deposition time.     

Selecting model for treatment of oily wastewater by MF-PAC hybrid process using mullite-alumina ceramic membranes

Hermia’s models for cross flow filtration were used to investigate the fouling mechanisms of mullite-alumina ceramic membranes in treatment of oily wastewaters in a hybrid microfiltration-powdered activated carbon process (MF-PAC). Results show that cake filtration model can be applied for prediction of permeation flux decline for MF and MF-PAC process up to 400 ppm PAC. The complete pore blocking model and the intermediate pore blocking model can predict permeation flux decline with time for MF-PAC with 800 and 1200 ppm PAC respectively. Average error for prediction of permeation flux with cake filtration model is 2.19% for MF process and 2.16, 2.06 and 1.31% for MF-PAC process with 100, 200 and 400 ppm PAC respectively. Also for MF-PAC process with 800 and 1200 ppm PAC, average error for prediction of permeation flux with complete pore blocking model and intermediate pore blocking model was 6.11 and 6% respectively.     

Analytical modeling of fatigue crack propagation in metals coupled with elasto-plastic deformation

In the present investigation, the G _max criterion, which is based on the elastic strain energy principle, is extended to study the fatigue crack growth characteristics of mixed mode cracks. A modification has been made to this criterion to implement the plastic strain energy and, hence, a new elasto-plastic energy-based model is presented. Subsequently, the proposed model is employed to predict fatigue crack growth in rectangular steel plates under complex stress states. The results obtained using the elasto-plastic energy model proposed are compared with those obtained using the commonly used Paris law and our experimental data.     

A high step‐up half‐bridge DC/DC converter with a special coupled inductor for input current ripple cancelation and extended voltage doubler circuit for power conditioning of fuel cell systems

This paper presents a high step‐up soft switched dc–dc converter having the feature of current ripple cancelation in the input stage that is specialized for power conditioning of fuel cell systems. The converter comprises a special half‐bridge converter and a rectifier stage based upon the voltage‐doubler circuit, in which the coupled‐inductor technology is amalgamated with switched‐capacitor circuit. The input current with no ripple is the principal characteristics of this topology that is achieved by utilizing a small coupled inductor. In addition, the low clamped voltage stress across both power switches and output diodes is another advantage of the proposed converter, which allows employing the metal–oxide–semiconductor field‐effect transistors with minuscule on‐state resistance and diodes with lower forward voltage‐drop, and thereby, the semiconductors' conduction losses diminish considerably. The inherent nature of this topology handles the switching scheme based on the asymmetrical pulse width modulation in order for switches to establish the zero voltage switching, leading to lower switching losses. Besides, because of the absence of the reverse‐recovery phenomenon, all diodes turn off with zero current switching. At last, a 250‐W laboratory prototype with the input voltage 24 V and output voltage 380 V is implemented to verify the especial features of the proposed converter. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.     

An optimization method for radial forging process using ANN and Taguchi method

In this study, the artificial neural network (ANN) and the Taguchi method are employed to optimize the radial force and strain inhomogeneity in radial forging process. The finite element analysis of the process verified by the microhardness test (to confirm the predicted strain distribution) and the experimental forging load published by the previous researcher are used to predict the strain distribution in the final product and the radial force. At first, a combination of process parameters are selected by orthogonal array for numerical experimenting by Taguchi method and then simulated by FEM. Then the optimum conditions are predicted via the Taguchi method. After that, by using the FEM results, an ANN model was trained and the optimum conditions are predicted by means of ANN (using genetic algorithm as global optimization procedure) and compared with those achieved by the Taguchi method. The optimum conditions are verified by FEM, and good agreement is found between the two sets of results.