Entity

Time filter

Source Type


Arebi P.,Technical and Vocational University
Proceedings - 2012 4th International Conference on Computational Intelligence, Communication Systems and Networks, CICSyN 2012 | Year: 2012

Ad Hoc networks allow a set of wireless hosts to exchange information without any special infrastructure. One of the most important issues in wireless adhoc Network improves routing protocol process. Among the various factors which cause disorder in such a network and routing protocol process, broken links due to the lack of energy is the most important ones. This paper proposes a novel method based on energy estimation to restore broken links and reconstruct the paths of them. So investigate Effect of broken links on topology control and routing process in Ad Hoc network. It was indicated that these effects were harmful in the mentioned couple of network portions. In this paper has been used Hardware Method for estimation energy in adhoc node, so this method has a high speed. © 2012 IEEE. Source


Modabbernia M.R.,Technical and Vocational University
International Journal on Electrical Engineering and Informatics | Year: 2013

In this paper a complete state-space average model for the buck switching regulators is presented. The presented model includes the most of the regulator's parameters and uncertainties. In modeling, the load current is assumed to be unknown, and it is assumed that the inductor, capacitor, diode and regulator active switch are non ideal and they have a resistance in conduction condition. Some other non ideal effects look like voltage drop of conduction mode of the diode and active switch are also considered. This model can be used to design a precise and robust controller that can satisfy stability and performance conditions of the buck regulator. Also the effects of the boost parameters on the performance of the regulator can be shown easily with this model. After presenting the complete model, the buck converter Benchmark circuit is simulated in PSpice and its results are compared with our model simulation results in MATLAB. The results show the merit of our model. Source


Rayeni M.M.,Technical and Vocational University | Saljooghi F.H.,University of Sistan and Baluchestan
International Journal of Services and Operations Management | Year: 2016

This paper investigates the impact of risk on banks performance. Banks, as a major source of financial intermediation and payment channel, play a vital role in the economic development of each country. The banking industry has been analysed through data envelopment analysis (DEA) by a number of researchers. DEA is a non-parametric method for relative evaluating the decision-making units (DMUs) with multiple inputs and outputs. In this study, due to the complexity and the subdivisions of the banks, the network DEA model was used. A three-stage model for evaluating the performance of bank branches was proposed and moreover, performance measurement and analysis was done through three models. In order to measure the effectiveness of risk in the first model, the risk-free efficiency was measured. Then, by adding risk to the model, risk-efficiency was obtained which considered as an undesirable indicator. In the third model, to consider the importance of risk, weight restriction was used in the model. The results of the three models show that the performance of the third model is much more desirable than the other models. Copyright © 2016 Inderscience Enterprises Ltd. Source


Seyed Aghamiry H.,Technical and Vocational University | Siahkoohi H.R.,University of Tehran
Journal of the Earth and Space Physics | Year: 2014

Near-surface variations can be very complex and may distort amplitudes and arrival times of the reflections events from target reflectors. Near-surface complexities include topographic variations, near-surface irregularities, variations in soil conditions and the weathered layer. These perturbations generally have a significant impact on seismic recordings. Although there is a general agreement that near-surface distortions are very complex and we usually rely on a rather simplified parameterization to compensate for these perturbations. Determinatin of time shifts is generally referred to as static corrections and residual static correction. Underlying concept of static corrections is the assumption that a simple time shift of an entire seismic trace will yield the seismic record that would have been observed if the geophones had been placed on the reference datum. Hence, static time shifts corrections are assumed to be surface consistent. Surface consistency means that the effects associated with a particular source or receiver affect all wave types similarly, regardless of the direction of propagation. Conventional methods of static time shift corrections need information on velocities and depths of near-surface layers to determine and compensate the time shifts. These methods rely on simple models for near-surface layers. In this paper, we develop an approach to compensate for complex time shift using blind channel identification, as it does not use near-surface information. The blind channel identification deals with the recovery of either the input signal or the channel response from the observed transmitted signal only. This method differs from conventional methods for seismic deconvolution. The latter resolve the undetermined nature of the problem by making assumptions about the reflectivity sequence (whiteness, sparsity) and/or the seismic wavelet (minimum phase/zero phase). The blind channel identification method does not rely on these assumptions. It uses multichannel recordings to fully constrain the problem and is therefore purely data driven. Many recent blind channel estimation techniques exploitsubspace structures of observation. The key idea in subspace methods of blind channel identification that the channel vector (or part of the channel vector) is in a one dimensional subspace of a block of noiseless observations. These methods, which are often referred to as subspace algorithms, have the attractive property that the channel estimates can often be obtained in a closed form from optimizing a quadratic cost function. We use blind channel identification to estimate for near-surface source and receiver perturbations. These perturbations are parameterized as finite-impulse response (FIR) filters, and are referred to as the channels. Because the channels describe the near-surface perturbations, we can estimate time shifts from correlation of the channels. We applied the method to synthetic data and to part of a field data set acquired in an area with significant near-surface heterogeneity. The application of new static corrections greatly improves the trace-to-trace consistency in prestack data. The procedure delineates reflection events that are difficult to detect prior to the application of new static corrections. Based on these results, we conclude that the new static corrections can successfully remove complex time shifts from land seismic data. The field data example demonstrates that the new static corrections can greatly enhance the imaging capabilities of land seismic data. Source


Razbani M.A.,Technical and Vocational University
Journal of Dispersion Science and Technology | Year: 2015

In this paper, a feed forward neural network is built and trained using experimental data reported in the literature to model interfacial tension of n-alkane/water-salt systems. Temperature, pressure, molecular weight of n-alkane, and ionic strength of electrolyte solution are used as input to the neural network. The model succeeded to predict interfacial tension of liquid n-alkane/water system with or without the presence of electrolyte and yielded average absolute deviation of 0.58% over all data points. The performance of the model is analyzed and compared against the performance of the other alternative models. It was found out that the proposed model outperforms the other alternatives. © 2015, Copyright © Taylor & Francis Group, LLC. Source

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