Search results for "Names"

MBE growth and properties of low-density InAs/GaAs quantum dot structures.

2011

We present the results of a comprehensive study carried out on morphological, structural and optical properties of InAs/GaAs quantum dot structures grown by Molecular Beam Epitaxy. InAs quantum dots were deposited at low growth rate and high growth temperature and were capped with InGaAs upper confining layers. Owing to these particular design and growth parameters, quantum dot densities are in the order of 4-5x109 cm-2 with emission wavelengths ranging from 1.20 to 1.33 µm at 10 K, features that make these structures interesting for single-photon operation at telecom wavelength. High resolution structural techniques show that In content and composition profiles in the structures depend on …

1981

The anionic polymerization of tert-butyl methacrylate (TBMA) in tetrahydrofuran, using Na+ and Cs+ as counterions proceeds without side reactions even at room temperature. The resulting molecular weight distributions are nearly monodisperse (Mw/Mn ⩽ 1,01). The rate constants for the propagation of ion pairs were measured in the range from + 15 to −100°C. The Arrhenius plots are linear, but different for the two counterions, resulting in the following numerical values for the frequency exponent A and the activation energy Ea: A = 8,5 and Ea = 7,2 kcal/mol = 30 kJ/mol for Na+; A = 9,5 and Ea = 5,6 kcal/mol = 23 kJ/mol for Cs+. The difference between the counterions, which is in contrast to th…

1986

The aminolysis of diphenyl terephthalate by means of hexylamine was studied in dimethyl sulfoxide as a model reaction for polyamidation. The kinetic analysis showed that the two ester groups of the diphenyl ester do not react independently. Furthermore, the reaction of the first ester group was of mixed second and third order, while the reaction of the second ester group contained only a second order term. The rate constants found were used to determine the Arrhenius activation parameters.

Modelling and Analysis of Nonstationary Vehicle-to-Infrastructure Channels with Time-Variant Angles of Arrival

2018

In mobile radio channel modelling, it is generally assumed that the angles of arrival (AOAs) are independent of time. This assumption does not in general agree with real-world channels in which the AOAs vary with the position of a moving receiver. In this paper, we first present a mathematical model for the time-variant AOAs. This model serves as the basis for the development of two nonstationary multipath fading channels models for vehicle-to-infrastructure communications. The statistical properties of both channel models are analysed with emphasis on the time-dependent autocorrelation function (ACF), time-dependent mean Doppler shift, time-dependent Doppler spread, and the Wigner-Ville sp…

A Fast Imaging Technique Applied to 2D Electrical Resistivity Data

2014

A new technique is proposed to process 2D apparent resistivity datasets, in order to obtain a fast and contrasted resistivity image, useful for a rapid data check in field or as a starting model to constrain the inversion procedure. In the past some modifications to the back-projection algorithm, as well as the use of filtering techniques for the sensitivity matrix were proposed. An implementation of this technique is proposed here, considering a two-step approach. Initially a damped least squares solution is obtained after a full matrix inversion of the linearized geoelectrical problem. Furthermore, on the basis of the results, a subsequent filtering algorithm is applied to the Jacobian ma…

Dirichlet Boundary Value Problem for the Second Order Asymptotically Linear System

2016

We consider the second order system x′′=f(x) with the Dirichlet boundary conditions x(0)=0=x(1), where the vector field f∈C1(Rn,Rn) is asymptotically linear and f(0)=0. We provide the existence and multiplicity results using the vector field rotation theory.

New Objective Refraction Metric Based on Sphere Fitting to the Wavefront

2017

Purpose. To develop an objective refraction formula based on the ocular wavefront error (WFE) expressed in terms of Zernike coefficients and pupil radius, which would be an accurate predictor of subjective spherical equivalent (SE) for different pupil sizes.Methods. A sphere is fitted to the ocular wavefront at the center and at a variable distance,t. The optimal fitting distance,topt, is obtained empirically from a dataset of 308 eyes as a function of objective refraction pupil radius,r0, and used to define the formula of a new wavefront refraction metric (MTR). The metric is tested in another, independent dataset of 200 eyes.Results. For pupil radiir0≤2 mm, the new metric predicts the equ…

Localization Operators and an Uncertainty Principle for the Discrete Short Time Fourier Transform

2014

Localization operators in the discrete setting are used to obtain information on a signalffrom the knowledge on the support of its short time Fourier transform. In particular, the extremal functions of the uncertainty principle for the discrete short time Fourier transform are characterized and their connection with functions that generate a time-frequency basis is studied.

A neural network-based approach to determine FDTD eigenfunctions in quantum devices

2009

This article combines a Neural Network (NN) algorithm with the Finite Difference Time Domain (FDTD) technique to estimate the eigenfunctions in quantum devices. A NN based on the Least Mean Squares (LMS) algorithm is combined with the FDTD technique to provide a first approach to the confined states in quantum wires. The proposed technique is in good agreement with analytical results and is more efficient than FDTD combined with the Fourier Transform. This technique is used to cal- culate a numerical approximation to the eigenfunctions associated to quan- tum wire potentials. The performance and convergence of the proposed technique are also presented in this article. © 2009 Wiley Periodica…

The Use of Artificial Intelligence in Disaster Management - A Systematic Literature Review

2019

Whenever a disaster occurs, users in social media, sensors, cameras, satellites, and the like generate vast amounts of data. Emergency responders and victims use this data for situational awareness, decision-making, and safe evacuations. However, making sense of the generated information under time-bound situations is a challenging task as the amount of data can be significant, and there is a need for intelligent systems to analyze, process, and visualize it. With recent advancements in Artificial Intelligence (AI), numerous researchers have begun exploring AI, machine learning (ML), and deep learning (DL) techniques for big data analytics in managing disasters efficiently. This paper adopt…