A parallel elliptic curve crypto-processor architecture with reduced clock cycle for FPGA platforms

The Journal of Supercomputing - The Elliptic curve cryptosystem is a public-key cryptosystem that receives more focus in recent years due to its higher security with smaller key size when compared...     

Fuzzy Based Ant Colony Optimization Scheduling in Cloud Computing

Cloud computing is an Information Technology deployment model established on virtualization. Task scheduling states the set of rules for task allocations to an exact virtual machine in the cloud computing environment. However, task scheduling challenges such as optimal task scheduling performance solutions, are addressed in cloud computing. First, the cloud computing performance due to task scheduling is improved by proposing a Dynamic Weighted Round-Robin algorithm. This recommended DWRR algorithm improves the task scheduling performance by considering resource competencies, task priorities, and length. Second, a heuristic algorithm called Hybrid Particle Swarm Parallel Ant Colony Optimization is proposed to solve the task execution delay problem in DWRR based task scheduling. In the end, a fuzzy logic system is designed for HPSPACO that expands task scheduling in the cloud environment. A fuzzy method is proposed for the inertia weight update of the PSO and pheromone trails update of the PACO. Thus, the proposed Fuzzy Hybrid Particle Swarm Parallel Ant Colony Optimization on cloud computing achieves improved task scheduling by minimizing the execution and waiting time, system throughput, and maximizing resource utilization.     

Mesoporous titanium dioxide nanocatalyst: a recyclable approach for one‐pot synthesis of 5‐hydroxymethylfurfural

The present study deals with the production of 5‐hydroxymethyl furfural (HMF) from fructose by chemo‐conversion method using chemical catalyst, conventionally achieved by microwave‐assisted dehydration process. Five different chemical catalysts, namely oxalic acid, phosphotungstic acid and mesoporous titanium dioxide nanoparticles (TNPs) were compared at constant conditions of which TNPs yielded a maxima of 33.95%. The optimum temperature and catalyst loading were found to be 200°C and 20%, respectively, at a 5% optimum substrate concentration during 15 min optimum reaction time to yield 61.53% HMF. The efficiency of synthesised TNPs was investigated further through reusability studies. TNPs were properly recycled and the catalytic activity recovery was good even after a 14 batch reactions. The specific surface area of the TNP obtained is about 105.46 m² /g and its pore‐volume is about 0.42 cm³ /g according to single point adsorption. A large accessible surface area combined with a minimal pore size (15.92 nm) obtained with mesoporous TNPs is desirable for better catalyst loading, high‐yield HMF, retention and reduced diffusion constraints.Inspec keywords: mesoporous materials, recycling, production management, dissociation, nanoparticles, nanotechnologyOther keywords: mesoporous titanium dioxide nanocatalyst, recyclable approach, one‐pot synthesis, 5‐hydroxymethyl furfural production, HMF, chemo‐conversion method, chemical catalyst, microwave‐assisted dehydration process, oxalic acid, phosphotungstic acid, mesoporous titanium dioxide nanoparticles, TNP     

Spectral Measurement of the Film-Substrate Index Difference in Proton-Exchanged LiNbO(3) Waveguides

We report the spectral characterization of proton-exchanged lithium niobate (PE:LiNbO(3)) waveguides in terms of the variation of the refractive-index difference between the waveguiding layer and the substrate. The dispersion of the extraordinary refractive-index increase (deltan(e)) is measured from 405 to 1319 nm with several light sources. Two types of proton-exchanged waveguide, prepared under different conditions, are studied. These measurements should be of use in the optimization of PE:LiNbO(3) waveguides for nonlinear optical applications, particularly in second-harmonic generation in the blue-green wavelength region.     

CHIR99021 Augmented the Function of Late Endothelial Progenitor Cells by Preventing Replicative Senescence

Endothelial progenitor cells (EPCs) are specialized cells in circulating blood, well known for their ability to form new vascular structures. Aging and various ailments such as diabetes, atherosclerosis and cardiovascular disease make EPCs vulnerable to decreasing in number, which affects their migration, proliferation and angiogenesis. Myocardial ischemia is also linked to a reduced number of EPCs and their endothelial functional role, which hinders proper blood circulation to the myocardium. The current study shows that an aminopyrimidine derivative compound (CHIR99021) induces the inhibition of GSK-3β in cultured late EPCs. GSK-3β inhibition subsequently inhibits mTOR by blocking the phosphorylation of TSC2 and lysosomal localization of mTOR. Furthermore, suppression of GSK-3β activity considerably increased lysosomal activation and autophagy. The activation of lysosomes and autophagy by GSK-3β inhibition not only prevented replicative senescence of the late EPCs but also directed their migration, proliferation and angiogenesis. To conclude, our results demonstrate that lysosome activation and autophagy play a crucial role in blocking the replicative senescence of EPCs and in increasing their endothelial function. Thus, the findings provide an insight towards the treatment of ischemia-associated cardiovascular diseases based on the role of late EPCs.     

RF magnetron sputtered Cd doped ZnO thin films for gas-sensing applications

RF magnetron sputtering has been employed to manufacture undoped and Cd doped (3%, 10%, and 20%) ZnO (CZO) films. X-ray diffraction (XRD) results revealed that the films have preferential orientation along (002) plane with hexagonal structure, and there are no secondary peaks. It is observed from the Hall Effect measurement that CZO films posses n-type conductivity, and the carrier concentration does not vary much with Cd concentration. On the other hand, the band gap estimated from Tauc’s plot shows that band gap decreased with increase in Cd concentration. Red shift was observed in photoluminescence spectrum. Ethanol, methanol, and ammonia at gas concentration range of 50–200?ppm were exposed on the grown CZO films at different temperatures. Among the various concentrations of the films, CZO having 20% Cd exhibited better gas response toward methanol, while CZO with 10% Cd showed maximum gas response toward ammonia gas. This has been explained by grain boundary barrier (GBB) and double Schottky potential barrier mechanisms.     

Performance analysis of neural networks for classification of medical images with wavelets as a feature extractor

In this article, we analyze the performance of artificial neural network, in classification of medical images using wavelets as feature extractor. This work classifies the mammographic image, MRI images, CT images, and ultrasound images as either normal or abnormal. We have tested the proposed approach using 50 mammogram images (13 normal and 37 abnormal), 24 MRI brain images (9 normal and 15 abnormal), 33 CT images (11 normal and 22 abnormal), and 20 ultrasound images (6 normal and 14 abnormal). Four kind of neural network models such as BPN (Back Propagation Network), Hopfield, RBF (Radial Basis Function), and PNN (Probabilistic neural network) were chosen for study. To improve diagnostic accuracy, the feature extracted using wavelets such as Harr, Daubechies (db2, db4, and db8), Biorthogonal and Coiflet wavelets are given as input to the neural network models. Good classification percentage of 96% was achieved using the RBF when Daubechies (db4) wavelet based feature extraction was used. We observed that the classification rate is almost high under the RBF neural network for all the dataset considered. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 33–40, 2015     

Slope instability analysis in Phyllitic rock in the Lesser Himalayan using three different modeling approach

Bulletin of Engineering Geology and the Environment - The numerical methods for slope stability problems always have a serious concern related to their continuum and discontinuum nature. In...     

MULTI-OBJECTIVE RECONFIGURABLE OUTPUT FEEDBACK CONTROLLER FOR MIMO SYSTEM USING MOEAS

This article deals with the design of a parametric eigenstructure assignment (PEA)-based multi-objective reconfigurable output feedback controller for a multiple-input multiple-output (MIMO) system against partial actuator failure. The significance of the PEA technique is that it provides more design degrees of freedom to obtain multi-objective functions, namely robust stability and improved transient response. Robust stability and transient response are ensured by a minimum condition number of the eigenvector and a minimum norm of controller gain. These two objectives are conflicting in nature, and, hence, the main aim is to minimize both objectives simultaneously by means of a multi-objective evolutionary algorithm (MOEA). In this study, a multi-objective optimization problem is formulated and is solved by non-dominated sorting genetic algorithm-II (NSGA-II) and strength Pareto evolutionary algorithm-II (SPEA-II). Four indicators are used to evaluate each algorithm performance: spacing, error ratio, generational distance, and hypervolume. Then a reconfigurable controller is designed using PEA against actuator failure, which guarantees closed-loop stability. The effectiveness of the proposed controllers is demonstrated by implementing them in an interacting three-tank benchmark system.     

Opposition Based Artificial Flora Algorithm for Load Balancing in LTE Network

In recent years, telecommunication is progressed due to the development of Long-Term Evolution (LTE) standards. This LTE network provides high-speed wireless communication for mobile devices and satisfies the requirements of customers from multi-cells. However, due to the congestion of mobile devices, each cell in the network may get overloaded. So, load balancing is the main challenge to the LTE network for reducing congestion or load in the cell. For load balancing, the optimal cell selection method is presented in this paper. Initially, the load factor of each cell is estimated. Then the load factor is compared with the predefined threshold load value. After the comparison, the heavy loaded cell handover the users to the optimal cell or cell with minimum load. This optimal cell is selected with the Opposition Based Artificial Flora (OAF) algorithm. Simulation results show that the proposed approach decreases 6% of the call blocking ratio (CBR) and 14% of Call Dropping Ratio (CDR) than the previous approaches.