Theoretical research on structural, electronic, mechanical, lattice dynamical and thermodynamic properties of layered ternary nitrides Ti(2)AN (A = Si, Ge and Sn)

WOS: 000449621500085First-principles density functional theory (DFT) calculations within generalized gradient approximation (GGA) are carried out to investigate the structural, electronic, mechanical, lattice dynamical and thermodynamic properties of Ti(2)AN (A = Si, Ge and Sn) MAX phases. The optimized geometrical parameters such as lattice constants (a, c) and the internal coordinates have been calculated. Electronic band structure and corresponding density of states (DOS) have been obtained. The analysis of the band structures and density of states have shown that these compounds are electrical conductors. The elastic constants have been ascertained using the stress-strain method. The isotropic elastic moduli, known as bulk modulus (B), shear modulus (G), young's modulus (E), poisson's ratio (nu), vickers hardness (H-nu) and linear compressibility coefficients (alpha) have been studied within framework of the Voigt-Reuss-Hill approximation for ideal polycrystalline Ti(2)AN (A = Si, Ge and Sn) MAX aggregates. Furthermore, the phonon dispersion curves as well as accompanying phonon density of states have been comprehensively computed. And also raman and infrared modes at the G point have been obtained. Within the thermodynamic properties, specific heat capacity, entropy, helmholtz free energy and internal energy changes were analyzed depending on the temperature of Ti(2)AN (A = Si, Ge and Sn) compounds. The obtained results are presented in comparison with present theoretical data for Ti2SiN. This is the first quantitative theoretical study of the electronic properties and other properties for Ti2GeN and Ti2SnN compounds and therefore theoretical results for these compounds need to be verified experimentally. (C) 2018 Elsevier B.V. All rights reserved

Identifying attack surfaces in the evolving space industry using reference architectures

The space environment is currently undergoing a substantial change and many new entrants to the market are deploying devices, satellites and systems in space; this evolution has been termed as NewSpace. The change is complicated by technological developments such as deploying machine learning based autonomous space systems and the Internet of Space Things (IoST). In the IoST, space systems will rely on satellite-to-x communication and interactions with wider aspects of the ground segment to a greater degree than existing systems. Such developments will inevitably lead to a change in the cyber security threat landscape of space systems. Inevitably, there will be a greater number of attack vectors for adversaries to exploit, and previously infeasible threats can be realised, and thus require mitigation. In this paper, we present a reference architecture (RA) that can be used to abstractly model in situ applications of this new space landscape. The RA specifies high-level system components and their interactions. By instantiating the RA for two scenarios we demonstrate how to analyse the attack surface using attack trees

SAR image reconstruction and autofocus by compressed sensing

Cataloged from PDF version of article.A new SAR signal processing technique based on compressed sensing is proposed for autofocused image reconstruction on subsampled raw SAR data. It is shown that, if the residual phase error after INS/GPS corrected platform motion is captured in the signal model, then the optimal autofocused image formation can be formulated as a sparse reconstruction problem. To further improve image quality, the total variation of the reconstruction is used as a penalty term. In order to demonstrate the performance of the proposed technique in wide-band SAR systems, the measurements used in the reconstruction are formed by a new under-sampling pattern that can be easily implemented in practice by using slower rate A/D converters. Under a variety of metrics for the reconstruction quality, it is demonstrated that, even at high under-sampling ratios, the proposed technique provides reconstruction quality comparable to that obtained by the classical techniques which require full-band data without any under-sampling. (C) 2012 Elsevier Inc. All rights reserved

Invariant Painleve analysis and coherent structures of two families of reaction-diffusion equations

Exact closed-form coherent structures (pulses/fronts/domain walls) having the form of complicated traveling waves are constructed for two families of reaction-diffusion equations by the use of invariant Painleveacute analysis. These analytical solutions, which are derived directly from the underlying PDE\u27s, are investigated in the light of restrictions imposed by the ODE that any traveling wave reduction of the corresponding PDE must satisfy. In particular, it is shown that the coherent structures (a) asymptotically satisfy the ODE governing traveling wave reductions, and (b) are accessible to the PDE from compact support initial conditions. The solutions are compared with each other, and with previously known solutions of the equations

Values, taboos, and votes:How basic human values affect populist electoral support

How do individuals' underlying value orientations affect populist voting? Building on the congruency model in social psychology, we theorize that voters holding non-conformist values feel closest to political actors who employ a taboo-breaking populist style in the political debate. Moreover, we hypothesize that security and universalism values feed into vote choices between right-wing and left-wing parties. Leveraging structural equation modeling (SEM) and data from the 2017 German Longitudinal Election Study (GLES), we find that non-conformist values predict voting for the populist far-right Alternative for Germany (AfD), but not for the left-wing populist The Left. Further, security and universalism values are associated with a higher probability of voting for not only populist but also mainstream parties. These findings point to the underlying role of basic human values in electoral support for populist parties and political behavior in general.ISSN:1424-7755ISSN:1420-3529ISSN:1662-637

An Experiment on Bare-Metal BigData Provisioning

Many BigData customers use on-demand platforms in the cloud, where they can get a dedicated virtual cluster in a couple of minutes and pay only for the time they use. Increasingly, there is a demand for bare-metal bigdata solutions for applications that cannot tolerate the unpredictability and performance degradation of virtualized systems. Existing bare-metal solutions can introduce delays of 10s of minutes to provision a cluster by installing operating systems and applications on the local disks of servers. This has motivated recent research developing sophisticated mechanisms to optimize this installation. These approaches assume that using network mounted boot disks incur unacceptable run-time overhead. Our analysis suggest that while this assumption is true for application data, it is incorrect for operating systems and applications, and network mounting the boot disk and applications result in negligible run-time impact while leading to faster provisioning time.This research was supported in part by the MassTech Collaborative Research Matching Grant Program, NSF awards 1347525 and 1414119 and several commercial partners of the Massachusetts Open Cloud who may be found at http://www.massopencloud.or

SAR image reconstruction by expectation maximization based matching pursuit

Cataloged from PDF version of article.Synthetic Aperture Radar (SAR) provides high resolution images of terrain and target reflectivity. SAR systems are indispensable in many remote sensing applications. Phase errors due to uncompensated platform motion degrade resolution in reconstructed images. A multitude of autofocusing techniques has been proposed to estimate and correct phase errors in SAR images. Some autofocus techniques work as a post-processor on reconstructed images and some are integrated into the image reconstruction algorithms. Compressed Sensing (CS), as a relatively new theory, can be applied to sparse SAR image reconstruction especially in detection of strong targets. Autofocus can also be integrated into CS based SAR image reconstruction techniques. However, due to their high computational complexity, CS based techniques are not commonly used in practice. To improve efficiency of image reconstruction we propose a novel CS based SAR imaging technique which utilizes recently proposed Expectation Maximization based Matching Pursuit (EMMP) algorithm. EMMP algorithm is greedy and computationally less complex enabling fast SAR image reconstructions. The proposed EMMP based SAR image reconstruction technique also performs autofocus and image reconstruction simultaneously. Based on a variety of metrics, performance of the proposed EMMP based SAR image reconstruction technique is investigated. The obtained results show that the proposed technique provides high resolution images of sparse target scenes while performing highly accurate motion compensation. (C) 2014 Elsevier Inc. All rights reserved