NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, A- MUHANDISI -I BARQ
Year:2009 | Volume:7 | Issue:2|Papers Count:11

Consider an all-optical time-slotted OPS network in which Internet protocol has been used at upper layers. Contention is a major problem for such a network. It is shown in this paper that optical packet retransmission at the optical domain can improve Internet throughput and can even reduce cost of OPS network implementation. In this technique, a copy of transmitted optical packets are saved in ingress switches and retransmitted when required, independent of TCP layer retransmission. In other words, retransmission may happen both at the optical layer and at the TCP layer. In this paper, an approach is proposed to reduce cost of OPS network implementation. In addition, Internet throughput is studied in slotted OPS network and an approach is proposed to increase Internet throughput and to improve throughput of long-hop connections.

By the introduction of the concept of Next Generation Networks (NGN), the management of these networks has become an important issue. So, the requirements, goals and the overall architecture of NGN management systems are discussed in this paper. The functional classification of Operation Support Systems (OSS) used in NGN management is also presented. Because of the need of utility networks (such as telephony, data, water, electricity and gas) in the country to OSS, the amount of required capital investment for deployment of Network Management System (NMS) and Customer Care and Billing System (CCBS), as main parts of OSS, are calculated for the next four years in this paper. To reach these estimates, the total number of subscribers in mentioned networks is forecasted for this period and information about per customer capita is also extracted. Two frameworks of, distributed and centralized, are considered. This assessment shows an approximate investment of M606$ and M432$ is needed for NMS and CCBS in distributed scenario, respectively. The same requirement in centralized scenario is M433$ and M322$ for NMS and CCBS, respectively. So, an approximate investment of M1040$ and M750$ is needed for OSS in distributed and centralized scenarios, respectively.

The goal of this paper is to estimate the capital investment in mobile telephony network's equipments, by using Cobb-Douglas model to forecast the number of subscribers for the next years in the country. Then by presenting a master plan for Base Station Subsystem (BSS) and Network Switching Subsystem (NSS) parts of the network, the required equipments and also the capital investment amounts are estimated. In the BSS plan, the number of Base Transceiver Stations (BTS) with various configurations and also Base Station Controllers (BSC) with different capacities and required accessories (such as tower, antenna, feeder, power supply and transmission equipments between BTSs and BSCs) are determined. In the NSS plan, an architecture is proposed for network's traffic (including signaling). The routing plan and required interfaces with Public Switched Telephone Network (PSTN) and Public Data Network (PDN) are also presented and the capacity of network's nodes and E1 links are determined. Based on the mentioned plan and also the typical cost of different equipments, offered by domestic and foreign vendors, the capital investment of 26.7 trillion Rials seems to be necessary to increase the penetration rate from 12.4% to 48.4% in mobile telephony network.

Differential protective relay serves as the main protection of transformers against faults in the windings for many years. Unremitting tries for more smart of this protection relay have been done by different creative manufactures and up to now different methods and inventions have been proposed for better operational of the differential relay. However, a differential protection for differential currents would be handicapped by difficulties due to several natural phenomena which are the cause of false differential currents and misoperate of the relay. Some of these phenomena, such as the inrush current and saturation of instrument current transformers, are the main concern in designing an efficient differential protection algorithm. This paper at first, proposes a new algorithm based on the Wavelet Transform (WT) to identify internal fault from magnetizing inrush in three phase power transformers. The internal faults can be accurately discriminated from inrush current less than a quarter a cycle after the disturbance. At following with definition of an index which it is extracted from the high frequencies by WT, the restrain current in bias-current characteristic of differential relay has been improved. Obtained results demonstrate that the proposed algorithm can provide the desired response and can be used as a very fast and accurate method.

This paper presents a new impedance based fault location algorithm for practical radial distribution systems. The algorithm uses the fundamental components of voltages and currents recorded by a digital fault recorder usually installed at the head of main feeders.At first, the algorithm estimates the average loading and power factor of distribution transformers by using the pre-fault voltage and current phasors. Then from the post-fault voltage and current phasors, the preliminary candidates for fault location are determined by searching all the feeder sections. Finally, the actual fault location is determined by checking operated fuses/sectionalizers, or fault indicators.The fault location method has been developed as a software package named DFL (Digital Fault Locator) in “Electricity Networks Protection and Automation” research laboratory of Iran University of Science and Technology (IUST).The accuracy of the proposed algorithm has been validated by several fault conditions carried out on a 205-node 20 kV practical radial distribution feeder. The results of the developed software have shown very remarkable accuracy in fault location as presented in the paper.

Pathological changes within an organ can be reflected as proteomic patterns in blood. The mass spectrometry has been used as powerful tools to generate proteomic patterns from serum. The produced profiles can be viewed as high dimensional and correlation data for which the features of scientific interest are the peaks. Due to this complexity of data, an appropriate analysis method is needed such as wavelet transform. In this study, we proposed a pseudo-covariance wavelet-based feature extraction method for dimension reduction and de-correlation between mass spectra data. Our algorithm was applied to datasets of ovarian cancer obtained from the National Cancer Institute of USA. The proposed algorithm was used to extract the set of proteins as potential biomarkers in each dataset from reconstructed mass spectra. The selected biomarkers were able to diagnose ovarian cancer patients from non-cancer with high accurate results using standard diagnosis criteria. Using different classification algorithms, our approach yielded an accuracy of 98%, specificity of 97%, and sensitivity of 98%.

One of the important subjects in the wavelet-based image denoising based on the Bayes theorem is choosing the appropriate density function for modeling the wavelet coefficients.  The interscale dependency between parent and child coefficients is one of the statistical properties of wavelets. So, in the recent years instead of univariate distribution, bivariate density functions have been suggested by the researchers and in this paper we use a mixture of bivariate Laplacian densities for this reason. Using this distribution we are able to model both heavy-tailed property and interscale dependency of wavelets. Using the mentioned density function for a minimum mean squared error estimator, we obtain a new shrinkage function for denoising. Applying this function to each subband of discrete complex wavelet transform of abdominal computerized tomography images, we will be able to improve the quality of these images better than some reported methods.

In this paper, we propose some ideas to improve the performance of the traditional face detection based on support vector machine (SVM). The traditional SVM-based system for face detection detects faces by exhaustively scanning an image for face-like patterns at any possible scales. It divides the original image into overlapping sub-images by using a fixed-size cutting window and classifies them using the Support Vector Machine to determine the appropriate class (face or non-face). This approach has not an acceptable detection rate. In this paper to improve the performance, we use cutting windows with different sizes. We fuse the decisions obtained by using different windows. An important issue in the Support Vector Machine classifier is to shift the decision threshold adequately towards the better represented class. In this paper, a novel method is proposed for determining the threshold value adaptively. A post processing algorithm is also presented for reducing the false alarm rate. Experimental results using standard database show that the performance of the proposed SVM-based method is much better than the basic SVM classifier.

In this paper a new concept has been proposed to consider “Energy Efficiency” as a new commodity. The new commodity is based on DSM (Demand Side Management) and especially the strategic conservation techniques in the restructured environment.  In the proposed method the ability to improve efficiency is traded as a new commodity by some new players.The effect of new commodity trading is analyzed on the long-term market power reduction in parallel to available long-term solutions that mostly rely on generation solution.The numerical study according to real world data shows the potential and effectiveness of the proposed method.

Active filters are effective for eliminating harmonic currents and improving reactive power due to nonlinear loads and unbalanced sources. In this paper an effective and new method for Control of active filter is investigated. Direct Power Control (DPC) with space vector modulation is employed for this control scheme. Also, the AC line voltage sensors with a virtual flux (VF) estimator are replaced. The control system is resistant to the majority of line voltage disturbances using by the idea of virtual flux and synchronous double reference frame phase-locked loop (SDRF-PLL) approach. Superior advantages of this method are simple algorithm, good dynamic response, constant switching frequency and resistant to the majority of line voltage disturbances. The operation of proposed control strategy is verified in SIMULINK/MATLAB simulation environment. The simulations show that this active filter is effective for eliminating reactive power injected from nonlinear loads and unbalanced sources. (NF) of low noise amplifier (LNA) are compared with each other.