Comprehensive study of RF analysis of G/GO-based NEMS shunt switch

Microsystem Technologies - High isolation and low insertion loss are the key design parameters for the NEMS switch at high frequency. The comprehensive study of radio frequency (RF) performance...     

Wii remote–based low-cost motion capture for automated assembly simulation

This paper describes the development of a Wii remote (Wiimote)–based low-cost motion capture system and demonstrates its application for automated assembly simulation. Multiple Wiimotes are used to form a vision system to perform motion capture in 3D space. A hybrid algorithm for calibrating a multi-camera stereo vision system has been developed based on Zhang’s and Svoboda’s calibration algorithms. This hybrid algorithm has been evaluated and shown accuracy improvement over Svoboda’s algorithm for motion capture with multiple cameras. The captured motion data are used to automatically generate an assembly simulation of objects represented by CAD models in real time. The Wiimote-based motion capture system is practically attractive because it is inexpensive, wireless, and easily portable. Application examples have been developed for a single vision system with two Wiimotes to track the assembly of a microsatellite prototype frame and for an integrated vision system with four Wiimotes to track the assembly of a bookshelf.     

Automated bank cheque verification using image processing and deep learning methods

Multimedia Tools and Applications - Automated bank cheque verification using image processing is an attempt to complement the present cheque truncation system, as well as to provide an alternate...     

Target based image fusion using multi-scale feature selection in three regions

Image captured by low dynamic range (LDR) camera fails to capture entire exposure level of scene, and instead only covers certain range of exposures. In order to cover entire exposure level in single image, bracketed exposure LDR images are combined. The range of exposures in different images results in information loss in certain regions. These regions need to be addressed and based on this motive a novel methodology of layer based fusion is proposed to generate high dynamic range image. High and low-frequency layers are formed by dividing each image based on pixel intensity variations. The regions are identified based on information loss section created in differently exposed images. High-frequency layers are combined using region based fusion with Dense SIFT which is used as activity level testing measure. Low-frequency layers are combined using weighted sum. Finally combined high and low-frequency layers are merged together on pixel to pixel basis to synthesize fused image. Objective analysis is performed to compare the quality of proposed method with state-of-the-art. The measures indicate superiority of the proposed method.

     

Magneto-electro-elastic analysis of piezoelectric–flexoelectric nanobeams rested on silica aerogel foundation

This article explores that the study on bending of magneto-electric-elastic nanobeams relies on nonlocal elasticity theory. The Vlasov’s model foundation utilizes the silica aerogel foundation. The guiding expressions of nonlocal nanobeams in the considered framework are used extensively and where parabolic third-order beam theory is achieved after using Hamilton’s principle. Parametric work is introduced to scrutinize the influence of the magneto-electro-mechanical loadings, nonlocal parameter, and aspect ratio on the deflection characteristics of nanobeams. It is noticed that the boundary conditions, nonlocal parameter, and beam geometrical parameters have significant effects on dimensionless deflection of nanoscale beams.

     

Design of backtracking search heuristics for parameter estimation of power signals

Neural Computing and Applications - This study presents a novel implementation of evolutionary heuristics through backtracking search optimization algorithm (BSA) for accurate, efficient and robust...     

A survey on resource allocation in high performance distributed computing systems

An efficient resource allocation is a fundamental requirement in high performance computing (HPC) systems. Many projects are dedicated to large-scale distributed computing systems that have designed and developed resource allocation mechanisms with a variety of architectures and services. In our study, through analysis, a comprehensive survey for describing resource allocation in various HPCs is reported. The aim of the work is to aggregate under a joint framework, the existing solutions for HPC to provide a thorough analysis and characteristics of the resource management and allocation strategies. Resource allocation mechanisms and strategies play a vital role towards the performance improvement of all the HPCs classifications. Therefore, a comprehensive discussion of widely used resource allocation strategies deployed in HPC environment is required, which is one of the motivations of this survey. Moreover, we have classified the HPC systems into three broad categories, namely: (a) cluster, (b) grid, and (c) cloud systems and define the characteristics of each class by extracting sets of common attributes. All of the aforementioned systems are cataloged into pure software and hybrid/hardware solutions. The system classification is used to identify approaches followed by the implementation of existing resource allocation strategies that are widely presented in the literature.     

A SAS macro for the analysis of cell survival curves

This paper describes a SAS macro for the statistical analyses of cell survival data obtained after radiation treatment using the methods of R.E. Tarone et al. (Mutation Research 111 (1983) 79-96). These analyses are usually required on a routine basis by all biomedical research laboratories involved in cell survival assays generating dose-response curves aimed at characterizing radiosensitive mutant cell strains or individuals whose body cells exhibit enhanced sensitivity to radiation and other genotoxic agents. Statistical methods of linear regression are applied to data from repeated experiments with a cell line/strain and weighted estimates of a common slope and its variance are obtained. The methods are currently implemented in two APL programs. These programs are not easily accessible to most biomedical statisticians and researchers because APL is not a common software tool for statistical analysis. Implementation of these methods in SAS, a widely used commercial software for statistical analysis, is expected to help resolve this issue. We illustrate the application of the macro using an example data set obtained in our laboratory, and hope that other investigators may find it useful in analyzing their data.     

Effective Moduli Evaluation of Carbon Nanotube Reinforced Polymers Using Micromechanics

A multistep homogenization method is adopted to compute the effective moduli of carbon nanotube reinforced composites. The composite is assumed to be reinforced with isolated individual fibers and clustered fibers. A uniform agglomeration model is introduced assuming constant carbon nanotube cluster size throughout the matrix. Agglomeration volume fraction—a critical parameter in the simulation—is considered to be an explicit function of inter-particle distance and quality of dispersion of fibers. The micromechanics model also incorporates random fiber orientation using a statistical approach. It is seen that these parameters reduce the stiffening effect of carbon nanotubes significantly in the composite.