The influence of gate dielectric materials on the performance of a carbon nanotube field-effect transistor has been studied by a numerical simulation model. This model is based on a two-dimensional nonequilibrium Green’s function formalism performed with the self-consistent solution of the Poisson and Schrödinger equations. The device performance is investigated in terms of leakage current, on-state current, ION/IOFF" id="MathJax-Element-1-Frame" role="presentation" style="position:relative;" tabindex="0">ION/IOFF current ratio, subthreshold slope, drain-induced barrier lowering, as well as transconductance, drain conductance, and intrinsic gate delay. This study is carried out over a wide range of dielectric permittivities at low temperatures ranging from room temperature down to 100 K.

In this paper, new sensors based on a double-gate (DG) graphene nanoribbon field-effect transistor (GNRFET), for high-performance DNA and gas detection, are proposed through a simulation-based study. The proposed sensors are simulated by solving the Schrödinger equation using the mode space non-equilibrium Green's function formalism coupled self-consistently with a 2D Poisson equation under the ballistic limits. The dielectric and work function modulation techniques are used for the electrical detection of DNA and gas molecules, respectively. The behaviors of both the sensors have been investigated, and the impacts of variation in geometrical and electrical parameters on the sensitivity of sensors have also been studied. In comparison to other FET-based sensors, the proposed sensors provide not only higher sensitivity but also better electrical and scaling performances. The obtained results make the proposed DG-GNRFET-based sensors as promising candidates for ultra-sensitive, small-size, low-power and reliable CMOS-based DNA, and gas sensors.

In this paper, we propose a new Double Gate Junctionless (DGJ) MOSFET design based on both gate material engineering and drain/source extensions. Analytical models for the long channel device associated to the drain current, analog and radio-frequency (RF) performance parameters are developed incorporating the impact of dual-material gate engineering and two highly doped extension regions on the analog/RF performance of DGJ MOSFET. The transistor performance figures-of-merit (FoM), governing the analog/RF behavior, have also been analyzed. The analog/RF performance is compared between the proposed design and a conventional DGJ MOSFET of similar dimensions, where the proposed device shows excellent ability in improving the analog/RF performance and provides higher drain current and improved figures-of-merit as compared to the conventional DGJ MOSFET. The obtained results have been validated against the data obtained from TCAD software for a wide range of design parameters. Moreover, the developed analytical models are used as mono-objective function to optimize the device analog/RF performance using Genetic Algorithms (GAs). In comparison with the reported numerical data for Inversion-Mode (IM) DG MOSFET, our optimized performance metrics for JL device exhibit enhancement over the reported data for IM device at the same channel length.

In this paper, the analytical investigation of a new design including drain and source extensions is presented to assess the electrical behavior of cylindrical gate-all-around junctionless (GAAJ) MOSFET for high performance RF and analog applications. Analytical models for drain current and performance parameters are derived incorporating the effect of two highly doped extension regions. Various analog and RF parameters like transconductance, cut-off frequency, drain current drivability, voltage gain and linearity characteristics have also been investigated. The proposed design shows excellent ability in improving the analog performance and provides a good solution to enhance the RF behavior and linearity of GAAJ MOSFET for low cost and high performance analog/RF applications. The proposed model results have been validated against the data obtained from a commercially available numerical device simulator. Moreover, the developed analytical approaches are easy to be implemented into microelectronic software simulators and therefore allow the study of the GAAJ-based deep submicron circuits

The paper proposes a new reliable fault-tolerant scheduling algorithm for real-time embedded systems. The proposed scheduling algorithm takes into consideration only one bus fault in multi-bus heterogeneous architectures, caused by hardware faults and compensated by software redundancy solutions. The proposed algorithm is based on both active and passive backup copies, to minimize the scheduling length of data on buses. In the experiments, this paper evaluates the proposed methods in terms of data scheduling length for a set of DAG benchmarks. The experimental results show the effectiveness of our technique.

The paper proposes a new reliable fault-tolerant scheduling algorithm for real-time embedded systems. The proposed algorithm is based on static scheduling that allows to include the dependencies and the execution cost of tasks and data dependencies in its scheduling decisions. Our scheduling algorithm is dedicated to multi-bus heterogeneous architectures with multiple processors linked by several shared buses. This scheduling algorithm is considering only one bus fault caused by hardware faults and compensated by software redundancy solutions. The proposed algorithm is based on both active and passive backup copies to minimize the scheduling length of data on buses. In the experiments, the proposed methods are evaluated in terms of data scheduling length for a set of DSP benchmarks. The experimental results show the effectiveness of our technique.

This paper presents an intelligent control strategy that uses a feedforward artificial neural network in order to improve the performance of the MPPT (Maximum Power Point Tracker) MPPT photovoltaic (PV) power system based on a modified Cuk converter. The proposed neural network control (NNC) strategy is designed to produce regulated variable DC output voltage. The mathematical model of Cuk converter and artificial neural network algorithm is derived. Cuk converter has some advantages compared to other type of converters. However the nonlinearity characteristic of the Cuk converter due to the switching technique is difficult to be handled by conventional controller. To overcome this problem, a neural network controller with online learning back propagation algorithm is developed. The NNC designed tracked the converter voltage output and improve the dynamic performance regardless load disturbances and supply variations. The proposed controller effectiveness during dynamic transient response is then analyze and verified using MATLAB-Simulink. Simulation results confirm the excellent performance of the proposed NNC technique for the studied PV system. 

In this paper, a simulation study of the maximum power point tracking (MPPT) for a photovoltaic system using an artificial neural network is presented. Maximum power point tracking (MPPT) plays an important role in photovoltaic systems because it maximizes the power output from a PV solar system for all temperature and irradiation conditions, and therefore maximizes the power efficiency. Since the maximum power point (MPP) varies, based on the PV irradiation and temperature, appropriate algorithms must be utilized to track it in order maintain the optimal operation of the system. The software Matlab/Simulink is used to develop the model of PV solar system MPPT controller. The system simulation is elaborated by combining the models established of solar PV module and a DC/DC Boost converter. The system is studied using various irradiance shading conditions. Simulation results show that the photovoltaic simulation system tracks optimally the maximum power point even under severe disturbances conditions.

The back propagation (BP) algorithm has been very successful in training multilayer perceptron-based equalisers; despite its success BP convergence is still too slow. Within this paper we present a new approach to enhance the training efficiency of the multilayer perceptron-based equaliser (MLPE). Our approach consists on modifying the conventional back propagation algorithm, through creating an adaptive nonlinearity in the activation function. Experiment results evaluates the performance of the MLPE trained using the conventional BP and the improved back propagation with adaptive gain (IBPAG). Due to the adaptability of the activation function gain the nonlinear capacity and flexibility of the MLP is enhanced significantly. Therefore, the convergence properties of the proposed algorithm are more improved compared to the BP. The proposed algorithm achieves the best performance in the entire simulation experiments.

Impact of nonlinear piezoelectric constants on surface acoustic wave propagation on a piezoelectric substrate is investigated in this work. Propagation of acoustic wave propagation under uniform stress is analyzed; the wave equation is obtained by incorporating the applied uniform stress in the equation of motion and taking account of the set of linear and nonlinear piezoelectric constants. A new method of separation between the different modes of propagation is proposed regarding the attenuation coefficients and not to the displacement vectors. Detail calculations and simulations have made for Lithium Niobate (LiNbO3); transformations between modes of propagation, under uniform stress, have been found. These results leads to conclusion that nonlinear terms affect the acoustic wave propagation and also we can make controllable acoustic devices.

Neural network based equalizers can easily compensate channel impairments; such additive noise and inter symbol interference (ISI). The authors present a new approach to improve the training efficiency of the multilayer perceptron (MLP) based equalizer. Their improvement consists on modifying the back propagation (BP) algorithm, by adapting the activation function in addition to the other parameters of the MLP structure. The authors report on experiment results evaluating the performance of the proposed approach namely the back propagation with adaptive activation function (BPAAF) next to the BP algorithm. To further prove its effectiveness, the proposed approach is also compared beside a so known nonlinear equalizer explicitly the multilayer perceptron with decision feedback equalizer MLPDFE. The authors consider various performance measures specifically: signal resorted quality, lower steady state MSE reached and minimum bit error rate (BER) achieved, where nonlinear channel equalization problems are employed.

This paper presents a full-wave method to calculate the resonant characteristics of rectangular microstrip antenna with and without dielectric cover, to explain the difference of performance with temperature between superconducting and normal conducting antenna. Especially the characteristics of high temperature superconducting (HTS) antenna were almost ideal around the critical temperature (T_c). The dyadic Green's functions of the considered structure are efficiently determined in the vector Fourier transform domain. The effect of the superconductivity of the patch is taken into account using the concept of the complex resistive boundary condition. The computed results are found to be in good agreement with results obtained using other methods. Also, the effects of the superstrate on the resonant frequency and bandwidth of rectangular microstrip patch in a substrate–superstrate configuration are investigated. This type of configuration can be used for wider bandwidth by proper selection of superstrate thickness and its dielectric constants.

This paper presents a simple approach for accurate determination of the resonant frequency of an elliptical microstrip patch printed on isotropic or anisotropic substrate materials. In this approach, some modifications are made to account for fringe fields, dispersion effects, and losses by calculating effective dimensions, effective permittivity of anisotropy in the layer, and effective loss tangent, respectively. The theoretical resonant frequency results are in very good agreement with the experimental results reported elsewhere. Numerical results show that the change in the resonant frequency of the antenna is due primarily to a small disturbance of the substrate's nature. Then the effect of the uniaxial anisotropic materials is a significant parameter and most essential on the microstrip antenna characterization.

A miniature (30 × 10 mm2) efficient planar monopole antenna with stable radiation pattern for UWB applications (3.1-10.6 GHz) is proposed in this paper. These characteristics, wide bandwidth and radiation stability, are achieved by using original design solutions with maintaining a small size and good efficiency of the system. Based on modified ground plane and loop feeding structure, the first design solution consist to propose a simple technique which not requires any discrete additional elements or circuits and does not affect the overall dimensions of the basic structure. This technique enhances the (-6 dB) bandwidth of the planar monopole antenna by approximately 50% compared to the basic structure while maintaining the same dimension (30 × 10 mm2). The optimized proposed antenna presents a large bandwidth, good radiation stability, total efficiency higher than 70% over the entire band and small size (30 × 10 mm2) which will enable to use it in different UWB applications. In the second step, two L slots are added in the printed circuit board of the proposed UWB antenna to reach a good stability of the radiation pattern on the overall desired band.

In this paper, the resonance and radiation characteristics of rectangular microstrip patch printed on suspended and composite substrates are investigated theoretically. The analysis approach is based on the spectral-domain method of moments in conjunction with the stationary phase method. The complex resonant frequency of the microstrip antenna on suspended and composite substrates is studied with sinusoidal functions as basis functions, which show fast numerical convergence. Using a matrix representation of each layer, the far-field pattern of the suspended-composite configuration is efficiently determined by the (TM, TE) representation. The validity of the solution is tested by comparison of the computed results with experimental data. Finally, numerical results for the effects of suspended and composite substrates on the resonant frequency and half-power bandwidth are also presented.

An 8-bit 40-MS/s low power Multiplying Digital-toAnalog Converter (MDAC) for a pipelined-to-Analog to Digital converter (ADC) is presented.The conventional dedicated operational amplifier (Op-Amp) isperformed by using telescopic architecture that features low power and less-area. Further reduction of power and area is achieved by using multifunction 1.5bit/stage MDAC architecture. The design of the Op-Amp is performed by the elaboration of a program based on multiobjective genetic algorithms to allow automated optimization. The proposed program is used tofind the optimal transistors sizes (length and width) in order to obtain the best Op-Amp performances for the MDAC. In this study, six performances are considered, direct current gain, unity-gain bandwidth, phase margin, power consumption, area, slew rate, thermal noise, and signal to noise ratio. The Matlab optimization toolbox is used to implement the program. Simulations were performed by using Cadence Virtuoso Spectre circuit simulator in standard AMS 0.18μm CMOS technology. A goodagreement is observed between the results obtained bythe program optimization and simulation, after that the Op-Ampis introduced in the MDAC circuit to extract its performances.