Analysis of a diffusive effective mass model for nanowires

We propose in this paper to derive and analyze a self-consistent model describing the diffusive transport in a nanowire. From a physical point of view, it describes the electron transport in an ultra-scaled confined structure, taking in account the interactions of charged particles with phonons. The transport direction is assumed to be large compared to the wire section and is described by a drift-diffusion equation including effective quantities computed from a Bloch problem in the crystal lattice. The electrostatic potential solves a Poisson equation where the particle density couples on each energy band a two dimensional confinement density with the monodimensional transport density given by the Boltzmann statistics. On the one hand, we study the derivation of this Nanowire Drift-Diffusion Poisson model from a kinetic level description. On the other hand, we present an existence result for this model in a bounded domain

An effective mass theorem for the bidimensional electron gas in a strong magnetic field

We study the limiting behavior of a singularly perturbed Schr\"odinger-Poisson system describing a 3-dimensional electron gas strongly confined in the vicinity of a plane $(x,y)$ and subject to a strong uniform magnetic field in the plane of the gas. The coupled effects of the confinement and of the magnetic field induce fast oscillations in time that need to be averaged out. We obtain at the limit a system of 2-dimensional Schr\"odinger equations in the plane $(x,y)$, coupled through an effective selfconsistent electrical potential. In the direction perpendicular to the magnetic field, the electron mass is modified by the field, as the result of an averaging of the cyclotron motion. The main tools of the analysis are the adaptation of the second order long-time averaging theory of ODEs to our PDEs context, and the use of a Sobolev scale adapted to the confinement operator

Heat and mass transfer investigation of rotating hydrocarbons droplet which behaves as a hard sphere

AbstractThe steady state boundary layer equations around rotating pure hydrocarbon droplet are solved numerically. The droplet is simulated to behave as a hard sphere. The transfer equations are discretized using an implicit finite difference method where Thomas algorithm solves the system of algebraic equations. Moreover, dimensionless parameters of heat and mass transfer phenomena around a rotating hexane droplet concluded. The thickness of the boundary layer is unknown for this model and therefore, it is determined. Further, this work proposes correlations of Nusselt and Sherwood numbers for monocomponent hydrocarbon droplets in evaporation. These correlations consider the rotation phenomena and further, the variation of the thermophysical and transport properties in the vapour phase

Aloe Vera Mucilage as Drag Reducing Agent in Oil-Water Flow

Drag reduction is the deliberate reduction of the frictional pressure drop in flow systems by the addition of heavy molecular weight polymeric materials as well as other means such as pipeline modifications. Environmentally friendly and cheaper heavy molecular weight polymeric drag reducing agents (DRAs) has become a necessity in the transportation of fluids particularly in the oil and gas industry. However, very few reports exist on the potentials of natural polymers such as extracts from the Aloe Vera plant. In this study, the effects of Reynolds number and polymer concentration on the drag reduction effectiveness of Aloe barbadensis miller were tested. An experimental flow facility using unplasticized  Polyvinylchloride (uPVC) pipe of 12 mm ID was constructed with diesel (density = 832 kg/m3, dynamic viscosity = 1.664 mPa.s at 25°C) and water (density = 1000 kg/m3, dynamic viscosity = 0.891 mPa.s at 25°C) as test fluids. Drag reduction as a function of Aloe polymer concentration in the range 50 ppm to 500 ppm and Reynolds number 20000<Re<90000 were investigated by comparing the U-tube manometer pressure drop readings with and without aloe polymer. The pressure drop difference expressed as a percentage of the pressure drop without aloe polymer is termed drag reduction and was used to demonstrate the effectiveness of the Aloe Vera extracts or polymer as a DRA. In single phase horizontal (water) flow, a maximum drag reduction of 64% (U = 4.67 m/s) was measured, while in multiphase horizontal flow, a maximum drag reduction of 53.80% (α = 25%, Um = 4.67 m/s) was measured. Furthermore, measurements showed that pipe inclination had minimal effect on the drag reduction achieved. It was deduced that Aloe Vera mucilage can be used as a drag reducing agent in oil-water flows for Reynolds number below 63,00

Mapping and Masking Targets Comparison using Different Deep Learning based Speech Enhancement Architectures

Mapping and Masking targets are both widely used in recent Deep Neural Network (DNN) based supervised speech enhancement. Masking targets are proved to have a positive impact on the intelligibility of the output speech, while mapping targets are found, in other studies, to generate speech with better quality. However, most of the studies are based on comparing the two approaches using the Multilayer Perceptron (MLP) architecture only. With the emergence of new architectures that outperform the MLP, a more generalized comparison is needed between mapping and masking approaches. In this paper, a complete comparison will be conducted between mapping and masking targets using four different DNN based speech enhancement architectures, to work out how the performance of the networks changes with the chosen training target. The results show that there is no perfect training target with respect to all the different speech quality evaluation metrics, and that there is a tradeoff between the denoising process and the intelligibility of the output speech. Furthermore, the generalization ability of the networks was evaluated, and it is concluded that the design of the architecture restricts the choice of the training target, because masking targets result in significant performance degradation for deep convolutional autoencoder architecture

A Comparative Study of Time and Frequency Domain Approaches to Deep Learning based Speech Enhancement

Deep learning has recently made a breakthrough in the speech enhancement process. Some architectures are based on a time domain representation, while others operate in the frequency domain; however, the study and comparison of different networks working in time and frequency is not reported in the literature. In this paper, this comparison between time and frequency domain learning for five Deep Neural Network (DNN) based speech enhancement architectures is presented. The comparison covers the evaluation of the output speech using four objective evaluation metrics: PESQ, STOI, LSD, and SSNR increase. Furthermore, the complexity of the five networks was investigated by comparing the number of parameters and processing time for each architecture. Finally some of the factors that affect learning in time and frequency were discussed. The primary results of this paper show that fully connected based architectures generate speech with low overall perception when learning in the time domain. On the other hand, convolutional based designs give acceptable performance in both frequency and time domains. However, time domain implementations show an inferior generalization ability. Frequency domain based learning was proved to be better than time domain when the complex spectrogram is used in the training process. Additionally, feature extraction is also proved to be very effective in DNN based supervised speech enhancement, whether it is performed at the beginning, or implicitly by bottleneck layer features. Finally, it was concluded that the choice of the working domain is mainly restricted by the type and design of the architecture used

Minimal conditions on Clifford semigroup congruences

A known result in groups concerning the inheritance of minimal conditions on normal subgroups by subgroups with finite indexes is extended to semilattices of groups [E(S),Se,ϕe,f] with identities in which all ϕe,f are epimorphisms (called q partial groups). Formulation of this result in terms of q congruences is also obtained

The impact of ceo characteristics on financial performance of Malaysian construction listed firms

This study investigates the impact of CEO characteristics on the financial performance of companies listed in Bursa Malaysia (Malaysia Stock Exchange) within the construction sector from 2017 to 2019. This study uses descriptive and inferential statistics, to examine the influence of CEO characteristics (CEO ownership, tenure, financial education, and founder) on the dependent variable (return on asset). The findings indicate that CEO financial education and founder CEO have no statistically significant effect on ROA. In contrast, CEO tenure and CEO ownership have a significant positive relationship with ROA. The collected data from annual reports were statistically processed using the program (STATA) to obtain the study's results since the study is based on a panel model. Future research can investigate the exact relationship between CEO characteristics with firm financial performance in other countries. In addition, future researchers can extend the research or studies of CEO characteristics such as CEO gender, power, expertise, et cetera. In addition, the research could be extended to other sectors; therefore, applying the theoretical model to othersmay be a significant contribution

Experimental studies of the cross-excitation instability in a relativistic backward wave oscillator

Our group first reported the operation of a relativistic backward wave oscillator (BWO) in the so-called “cross-excitation” regime in 1998. This instability, whose general properties were predicted earlier through numerical studies, was a consequence of using a particularly shallow rippled-wall waveguide (slow wave structure – SWS) that was installed in the experiment to diagnose pulse shortening in a long pulse electron beam-driven high power microwave (HPM) source. This particular SWS was required to accommodate laser interferometry measurements during the course of microwave generation. Since those early experiments we have further studied this regime in greater detail using two different SWS lengths. We have invoked time-frequency analysis, the smoothed-pseudo Wigner-Ville distribution in particular, to interpret the heterodyned signals of the radiated power measurements. These recent results are consistent with earlier theoretical predictions for the onset, voltage scaling, and general behavior for this instability. This paper presents data for a relativistic BWO operating in the single frequency regime for two axial modes, operating in the cross-excitation regime, and discusses the interpretation of the data, as well as the methodology used for its analysis. Although operation in the cross-excitation regime is typically avoided due to its poorer efficiency, we discuss how it may be exploited in HPM effects studies