Quintessence Ghost Dark Energy Model

A so called "ghost dark energy" was recently proposed to explain the present acceleration of the universe expansion. The energy density of ghost dark energy, which originates from Veneziano ghost of QCD, is proportional to the Hubble parameter, $\rho_D=\alpha H$, where $\alpha$ is a constant which is related to the QCD mass scale. In this paper, we establish the correspondence between ghost dark energy and quintessence scalar field energy density. This connection allows us to reconstruct the potential and the dynamics of the quintessence scalar field according to the evolution of ghost energy density.Comment: 8 pages, 7 figures, version to appear in Europhys. Let

Memristor Crossbar-based Hardware Implementation of IDS Method

Ink Drop Spread (IDS) is the engine of Active Learning Method (ALM), which is the methodology of soft computing. IDS, as a pattern-based processing unit, extracts useful information from a system subjected to modeling. In spite of its excellent potential in solving problems such as classification and modeling compared to other soft computing tools, finding its simple and fast hardware implementation is still a challenge. This paper describes a new hardware implementation of IDS method based on the memristor crossbar structure. In addition of simplicity, being completely real-time, having low latency and the ability to continue working after the occurrence of power breakdown are some of the advantages of our proposed circuit.Comment: 16 pages, 13 figures, Submitted to IEEE Transaction on Fuzzy System

Inference on P(Y<X) in Bivariate Rayleigh Distribution

This paper deals with the estimation of reliability $R=P(Y<X)$ when $X$ is a random strength of a component subjected to a random stress $Y$ and $(X,Y)$ follows a bivariate Rayleigh distribution. The maximum likelihood estimator of $R$ and its asymptotic distribution are obtained. An asymptotic confidence interval of $R$ is constructed using the asymptotic distribution. Also, two confidence intervals are proposed based on Bootstrap method and a computational approach. Testing of the reliability based on asymptotic distribution of $R$ is discussed. Simulation study to investigate performance of the confidence intervals and tests has been carried out. Also, a numerical example is given to illustrate the proposed approaches.Comment: Accepted for publication. Communications in Statistics- Theory and Methods, 201

Microstructural Behavior And Multiscale Structure-Property Relations For Cyclic Loading Of Metallic Alloys Procured From Additive Manufacturing (Laser Engineered Net Shaping -- LENS)

The goal of this study is to investigate the microstructure and microstructure-based fatigue (MSF) model of additively-manufactured (AM) metallic materials. Several challenges associated with different metals produced through additive manufacturing (Laser Enhanced Net Shaping – LENS®) have been addressed experimentally and numerically. Significant research efforts are focused on optimizing the process parameters for AM manufacturing; however, achieving a homogenous, defectree AM product immediately after its fabrication without postabrication processing has not been fully established yet. Thus, in order to adopt AM materials for applications, a thorough understanding of the impact of AM process parameters on the mechanical behavior of AM parts based on their resultant microstructure is required. Therefore, experiments in this study elucidate the effects of process parameters – i.e. laser power, traverse speed and powder feed rate – on the microstructural characteristics and mechanical properties of AM specimens. A majority of fatigue data in the literature are on rotation/bending test of wrought specimens; however, few studies examined the fatigue behavior of AM specimens. So, investigating the fatigue resistance and failure mechanism of AM specimens fabricated via LENS® is crucial. Finally, a microstructure-based MultiStage Fatigue (MSF) model for AM specimens is proposed. For calibration of the model, fatigue experiments were exploited to determine structure-property relations for an AM alloy. Additional modifications to the microstructurally-based MSF Model were implemented based on microstructural analysis of the fracture surfaces – e.g. grain misorientation and grain orientation angles were added to the MSF code

Interpretive structural modeling of knowledge network in car industry’ R&D centers

The current research has been done with the aim of knowledge network interpretive structural modeling in car industry’s R&amp;D centers. The key factors for implementing a knowledge network in car industry’s R&amp;D centers have been determined and then the final graphical model has been drawn by Interpretive Structural Modeling (ISM) approach.The method of the current applied research includes a survey of experts and then the variables extracted through investigating research background, after that the MATLAB R2013 software is used for making compatible matrix as well as drawing graphical relations of the model by Interpretive Structural Modeling approach.After studying related works &amp; interviewing with under-studied firms’ managers, interpretive structural modeling (ISM) &amp; MICMAC analysis was used to generate a model for knowledge network. Previous studies had not investigated the knowledge network in car industry’s R&amp;D centers; however, the present study implemented the knowledge network model in R&amp;D Centers