Unsteady free convection flow over a continuous moving vertical surface

Summary The problem of heat transfer in the unsteady free convection flow over a continuous moving vertical sheet in an ambient fluid has been investigated. Both constant surface temperature and constant surface heat flux conditions have been considered. The nonlinear coupled partial differential equations governing the flow have been solved numerically using the Keller box method and the Nakamura method which both give closely similar solutions. The results indicate that the cooling rate of the sheet can be enhanced by increasing the buoancy parameter or the velocity of the sheet. It is found that a better cooling performance could be achieved by using a liquid as a cooling medium rather than a gas. The overshoot in the velocity occurs near the surface when the buoyancy parameter exceeds a certain critical value.     

Text-independent speaker identification using Radon and discrete cosine transforms based features from speech spectrogram

This paper presents a new feature extraction technique for speaker recognition using Radon transform (RT) and discrete cosine transform (DCT). The spectrogram is compact, efficient in representation and carries information about acoustic features in the form of pattern. In the proposed method, speaker specific features have been extracted by applying image processing techniques to the pattern available in the spectrogram. Radon transform has been used to derive the effective acoustic features from the speech spectrogram. Radon transform adds up the pixel values in the given image along a straight line in a particular direction and at a specific displacement. The proposed technique computes Radon projections for seven orientations and captures the acoustic characteristics of the spectrogram. DCT applied on Radon projections yields low dimensional feature vector. The technique is computationally efficient, text-independent, robust to session variations and insensitive to additive noise. The performance of the proposed algorithm has been evaluated using the Texas Instruments and Massachusetts Institute of Technology (TIMIT) and our own created Shri Guru Gobind Singhji (SGGS) databases. The recognition rate of the proposed algorithm on TIMIT database (consisting of 630 speakers) is 96.69% and for SGGS database (consisting of 151 speakers) is 98.41%. These results highlight the superiority of the proposed method over some of the existing algorithms.     

Rough set based 1-v-1 and 1-v-r approaches to support vector machine multi-classification

Support vector machines (SVMs) are essentially binary classifiers. To improve their applicability, several methods have been suggested for extending SVMs for multi-classification, including one-versus-one (1-v-1), one-versus-rest (1-v-r) and DAGSVM. In this paper, we first describe how binary classification with SVMs can be interpreted using rough sets. A rough set approach to SVM classification removes the necessity of exact classification and is especially useful when dealing with noisy data. Next, by utilizing the boundary region in rough sets, we suggest two new approaches, extensions of 1-v-r and 1-v-1, to SVM multi-classification that allow for an error rate. We explicitly demonstrate how our extended 1-v-r may shorten the training time of the conventional 1-v-r approach. In addition, we show that our 1-v-1 approach may have reduced storage requirements compared to the conventional 1-v-1 and DAGSVM techniques. Our techniques also provide better semantic interpretations of the classification process. The theoretical conclusions are supported by experimental findings involving a synthetic dataset.     

Short-Term Traffic Prediction on Different Types of Roads with Genetically Designed Regression and Time Delay Neural Network Models

Research for advanced traveler information systems (ATIS) has been focused on urban roads. However, research for short-term traffic prediction on all categories of highways is needed, as highway agencies expect to implement intelligent transportation systems across their jurisdictions. In this study, genetic algorithms were used to design time delay neural network (TDNN) models as well as locally weighted regression models to predict short-term traffic for six rural roads from Alberta, Canada. These roads are from various trip-pattern groups and functional classes. Refined TDNN models developed in this study can limit most average errors less than 10% for all study roads. Refined regression models show even higher accuracy. Average errors for the refined regression models are less than 2% for roads with stable patterns. Even for roads with unstable patterns, average errors are below 4%, and the 95th percentile errors are less than 7%. It is believed that such accurate predictions would be useful for highway agencies to implement statewide ATIS.     

Unsteady axisymmetric stagnation-point flow of a viscous fluid on a cylinder

The unsteady viscous flow in the vicinity of an axisymmetric stagnation point of an infinite circular cylinder is investigated when both the free stream velocity and the velocity of the cylinder vary arbitrarily with time. The cylinder moves either in the same direction as that of the free stream or in the opposite direction. The flow is initially (t=0) steady and then at t>0 it becomes unsteady. The semi-similar solution of the unsteady Navier–Stokes equations has been obtained numerically using an implicit finite-difference scheme. Also the self-similar solution of the Navier–Stokes equations is obtained when the velocity of the cylinder and the free stream velocity vary inversely as a linear function of time. For small Reynolds number, a closed form solution is obtained. When the Reynolds number tends to infinity, the Navier–Stokes equations reduce to those of the two-dimensional stagnation-point flow. The shear stresses corresponding to stationary and the moving cylinder increase with the Reynolds number. The shear stresses increase with time for the accelerating flow but decrease with increasing time for the decelerating flow. For the decelerating case flow reversal occurs in the velocity profiles after a certain instant of time.     

Transient performance estimation of charge plasma based negative capacitance ewline junctionless tunnel FET

We investigate the transient behavior of an n-type double gate negative capacitance junctionless tunnel field effect transistor (NC-JLTFET). The structure is realized by using the work-function engineering of metal electrodes over a heavily doped n⁺ silicon channel and a ferroelectric gate stack to get negative capacitance behavior. The positive feedback in the electric dipoles of ferroelectric materials results in applied gate bias boosting. Various device transient parameters viz. transconductance, output resistance, output conductance, intrinsic gain, intrinsic gate delay, transconductance generation factor and unity gain frequency are analyzed using ac analysis of the device. To study the impact of the work-function variation of control and source gate on device performance, sensitivity analysis of the device has been carried out by varying these parameters. Simulation study reveals that it preserves inherent advantages of charge-plasma junctionless structure and exhibits improved transient behavior as well.     

Face Recognition by Computers and Humans

Research into face recognition offers research opportunities that will challenge scientists and engineers for years to come. Robust face-recognition systems, for example, can be used in projects related to homeland security, human-computer interaction, and many consumer applications.     

Structural and Thermo-Physical Properties of 3C-SiC: High-Temperature and High-Pressure Effects

Silicon - Based on the density functional theory (DFT), a systematic theoretical investigation on the structural parameters and finite temperature thermo-physical properties of cubic silicon...     

Modification of structural,thermal, and electrical properties of PVA by addition of silicon carbide nanocrystals

SiC‐PVA nanocomposite films, synthesized using solution‐casting technique were structurally characterized using X‐ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR) and Raman spectroscopy. Morphological studies of the SiC‐PVA nanocomposite films were carried out using Transmission electron microscopy (TEM) and Scanning electron microscopy (SEM). TEM analysis confirms that the size of SiC nanocrystals present in PVA matrix are 23 ± 9 nm, which is consistent with size calculated using XRD. SiC‐PVA nanocomposite films were further characterized for their thermal and electrical properties. Thermogravimetric/differential thermal analysis (TG/DTA) indicates that the char yield of nanocomposite films containing 3 wt % SiC nanocrystal is ～30% more than PVA. This increase in char yield is an indication of the potency of flame retardation of SiC‐PVA nanocomposite films. I‐V analysis reveals that Schottky mechanism is the dominant conduction mechanism which is responsible for the increase in conductivity of PVA with the addition of SiC nanocrystals. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 42464.