Predictive models for emission of hydrogen powered car using various artificial intelligent tools

This paper investigates the use of artificial intelligent models as virtual sensors to predict relevant emissions such as carbon dioxide, carbon monoxide, unburnt hydrocarbons and oxides of nitrogen for a hydrogen powered car. The virtual sensors are developed by means of application of various Artificial Intelligent (AI) models namely; AI software built at the University of Tasmania, back-propagation neural networks with Levenberg–Marquardt algorithm, and adaptive neuro-fuzzy inference systems. These predictions are based on the study of qualitative and quantitative effects of engine process parameters such as mass airflow, engine speed, air-to-fuel ratio, exhaust gas temperature and engine power on the harmful exhaust gas emissions. All AI models show good predictive capability in estimating the emissions. However, excellent accuracy is achieved when using back-propagation neural networks with Levenberg–Marquardt algorithm in estimating emissions for various hydrogen engine operating conditions with the predicted values less than 6% of percentage average root mean square error.     

Transmission characteristics of finite-width conductor-backedcoplanar waveguide

This paper presents theoretical and experimental results for a finite-width conductor-backed coplanar waveguide (FW-CBCPW). The guiding characteristics of FW-CBCPW are investigated first by the rigorous method of mode matching. An FW-CBCPW through line is then placed within a test fixture commonly used in laboratories, and the scattering parameters of the through line are obtained theoretically by approximating the FW-CBCPW as a simple system of coupled transmission lines. Experimental results are shown to agree very well with the theoretical ones. In particular, the anomalous behavior observed in the transmission characteristic of the through line is related to the resonant phenomenon of the terminated side planes which are short-circuited at both input and output ends due to the test fixture. Finally, a technique of mode suppression in the side-plane regions is suggested for the improvement of signal transmission over a broad band of frequency spectrum. The effects of extra higher order modes on the transmission characteristics at high frequencies are also discussed     

The effects of substrate bias,substrate temperature,and pulse frequency on the microstructures of chromium nitride coatings deposited by pulsed direct current reactive magnetron sputtering

Recently, great attention has been devoted to the pulsed direct current (DC) reactive magnetron sputtering technique, due to its ability to reduce arcing and target poisoning, and its capability of producing insulating thin films. In this study, chromium nitride (CrN) coatings were deposited by the bipolar symmetric pulsed DC magnetron reactive sputtering process at different pulse frequency, substrate bias voltage, and the substrate temperature. It was observed that the texture of CrN changed from (111) to (200) as substrate temperature increased to 300°C as deposited at 2 kHz without substrate bias. With increasing pulsing bias and pulse frequency of target, predominated (200) orientation of CrN film was shown due to the ion bombardment/channeling effect to preferentially sputter those unaligned planes. For the CrN coatings deposited with pulsed biasing, the grain size decreased with increasing pulse frequency and substrate bias, whereas the surface roughness showed a reverse trend. The deposition rate of the CrN films decreased with increasing pulse frequency. It was concluded that the pulse frequency, substrate bias, and substrate temperature played important role in the texture, microstructure, and surface roughness of the CrN coatings deposited by the pulsed DC magnetron sputtering process.     

Intelligent voice smoother for silence-suppressed voice overInternet

When transporting voice data with silence suppression over the Internet, the problem of jitter introduced from the network often renders the speech unintelligible. It is thus indispensable to offer intramedia synchronization to remove jitter while retaining minimal playout delay (PD). We propose a neural network (NN)-based intravoice synchronization mechanism, called the intelligent voice smoother (IVoS). The IVoS is composed of three components: (1) the smoother buffer; (2) the NN traffic predictor; and (3) the constant bit rate (CBR) enforcer. Newly arriving frames, assumed to follow a generic Markov modulated Bernoulli process (MMBP), are queued in the smoother buffer. The NN traffic predictor employs an online-trained back propagation NN (BPNN) to predict three traffic characteristics of every newly encountered talkspurt period. Based on the predicted characteristics, the CBR enforcer derives an adaptive buffering delay (ABD) by means of a near-optimal simple closed-form formula. It then imposes the delay on the playout of the first frame in the talkspurt period. The CBR enforcer in turn regulates CBR-based departures for the remaining frames of the talkspurt, aiming at assuring minimal mean and variance of distortion of talkspurts (DOT) and mean PD. Simulation results reveal that, compared to three other playout approaches, the IVoS achieves superior playout, yielding negligible DOT and PD, irrespective of traffic variation     

Multiple access control with intelligent bandwidth allocation forwireless ATM networks

Two major challenges pertaining to wireless asynchronous transfer mode (ATM) networks are the design of multiple access control (MAC), and dynamic bandwidth allocation. While the former draws more attention, the latter has been considered nontrivial and remains mostly unresolved. We propose a new intelligent multiple access control system (IMACS) which includes a versatile MAC scheme augmented with dynamic bandwidth allocation, for wireless ATM networks. IMACS supports four types of traffic-CBR, VBR, ABR, and signaling control (SCR). It aims to efficiently satisfy their diverse quality-of-service (QoS) requirements while retaining maximal network throughput. IMACS is composed of three components: multiple access controller (MACER), traffic estimator/predictor (TEP), and intelligent bandwidth allocator (IBA). MACER employs a hybrid-mode TDMA scheme, in which its contention access is based on a new dynamic-tree-splitting (DTS) collision resolution algorithm parameterized by an optimal splitting depth (SD). TEP performs periodic estimation and on-line prediction of ABR self-similar traffic characteristics based on wavelet analysis and a neural-fuzzy technique. IBA is responsible for static bandwidth allocation for CBR/VBR traffic following a closed-form formula. In cooperation with TEP, IBA governs dynamic bandwidth allocation for ABR/SCR traffic through determining the optimal SD. The optimal SDs under various traffic conditions are postulated via experimental results, and then off-line constructed using a back propagation neural network (BPNN), being used on-line by IBA. Consequently, with dynamic bandwidth allocation, IMACS offers various QoS guarantees and maximizes network throughput irrelevant to traffic variation     

ZnO spintronics and nanowire devices

ZnO is a very promising material for spintronics applications, with many groups reporting room-temperature ferromagnetism in films doped with transition metals during growth or by ion implantation. In films doped with Mn during pulsed laser deposition (PLD), we find an inverse correlation between magnetization and electron density as controlled by Sn-doping. The saturation magnetization and coercivity of the implanted single-phase films were both strong functions of the initial anneal temperature, suggesting that carrier concentration alone cannot account for the magnetic properties of ZnO:Mn and factors such as crystalline quality and residual defects play a role. Plausible mechanisms for ferromagnetism include the bound magnetic polaron model or exchange that is mediated by carriers in a spin-split impurity band derived from extended donor orbitals. The progress in ZnO nanowires is also reviewed. The large surface area of nanorods makes them attractive for gas and chemical sensing, and the ability to control their nucleation sites makes them candidates for microlasers or memory arrays. Single ZnO nanowire depletion-mode metal-oxide semiconductor field effect transistors exhibit good saturation behavior, threshold voltage of ∼−3 V, and a maximum transconductance of 0.3 mS/mm. Under ultraviolet (UV) illumination, the drain-source current increased by approximately a factor of 5 and the maximum transconductance was ∼5 mS/mm. The channel mobility is estimated to be ∼3 cm²/Vss, comparable to that for thin film ZnO enhancement mode metal-oxide semiconductor field effect transistors (MOSFETs), and the on/off ratio was ∼25 in the dark and ∼125 under UV illumination. The Pt Schottky diodes exhibit excellent ideality factors of 1.1 at 25°C, very low reverse currents, and a strong photoresponse, with only a minor component with long decay times thought to originate from surface states. In the temperature range from 25°C to 150°C, the resistivity of nanorods treated in H₂ at 400°C prior to measurement showed an activation energy of 0.089 eV and was insensitive to ambient used. By contrast, the conductivity of nanorods not treated in H₂ was sensitive to trace concentrations of gases in the measurement ambient even at room temperature, demonstrating their potential as gas sensors. Sensitive pH sensors using single ZnO nanowires have also been fabricated.     

On the effects of a spacecraft subcarrier unbalanced modulator

This paper presents mathematical models with associated analysis of the deleterious effects which a spacecraft's subcarrier unbalanced modulator has on the performance of a phase-modulated residual carrier communications link. The undesired spectral components produced by the phase and amplitude imbalances in the subcarrier modulator can cause (1) potential interference to the carrier tracking and (2) degradation in the telemetry bit signal-to-noise ratio (SNR). A suitable model for the unbalanced modulator is developed and the threshold levels of undesired components that fall into the carrier tracking loop are determined. The distribution of the carrier phase error caused by the additive White Gaussian noise (AWGN) and undesired component at the residual RF carrier is derived for the limiting cases. Further, this paper analyses the telemetry bit signal-to-noise ratio degradations due to undesirable spectral components as well as the carrier tracking phase error induced by phase and amplitude imbalances. Numerical results which indicate the sensitivity of the carrier tracking loop and the telemetry symbol-error rate (SER) to various parameters of the models are also provided as a tool in the design of the subcarrier balanced modulator.     

大尺寸TFT-LCD电视的彩色和图像增强

最近几年,薄膜晶体管液晶显示器(TFT-LCD)技术取得了快速而显著的进步,其性能超过了PDP、CRT以及投影显示。毫无疑问,TFT-LCD已经成为高清电视应用的最佳实现方案。本文将介绍进一步增强大尺寸LCD电视的彩色和图像性能的技术。