NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, A- MUHANDISI -I BARQ
Year:2009 | Volume:7 | Issue:3|Papers Count:8

For several years, many efforts have been done to use the electro-encephalogram (EEG) as a new communication channel between human brain and computer. This new communication channel is called EEG-based brain-computer interface (BCI). The aim of brain-computer interface (BCI) research is to establish a new communication channel that directly translates brain activities into sequences of control commands for an output device such as a computer application or a neuroprosthesis. The major advantage of EEG-based BCI is that no physical movement is required. The motor imagery is the essential part of the most EEG-based communication systems. One of the major problems in developing a real-time Brain Computer Interface (BCI) is the eye blink artifact suppression. Recently, a more effective method has been introduced for removing a wide variety of artifacts from multi-channel EEG signals based on blind source separation by Independent Component Analysis (ICA). However, the method requires visual inspection of ICA components and manual classification of the interference components. This can be time-consuming and is not desirable for real-time artifact suppression. Moreover, the real-time application of this method for artifact rejection has not been considered so far. In this paper, various ICA methods with adaptive learning algorithm are presented and evaluated by computer simulation. The results from real-data demonstrate that the proposed scheme removes perfectly eye blink artifacts from the contaminated EEG signals and is suitable for use during on-line EEG monitoring and EEG-based brain computer interface.

Recently, wind farms are used to generate electric power in some parts of the world. With increasing penetration level of wind farms in electric power systems, modification of current tools to evaluate and manage the system is an important issue. Evaluation of total transfer capability (TTC) is one of the considerable tools in restructured power systems which is used to schedule future transactions between areas in multi area power systems to ensure security of network. In this paper, a method is proposed for probabilistic evaluation of TTC of multi area power systems in the presence of wind farms. Firstly, a general approach based on Monte Carlo simulation is used to simulate a system state considering system load and power output of wind farm and optimal power flow (OPF) is used to calculate TTC level for each state. Then risk analysis is used as a decision making tool to determine the appropriate TTC level for a fixed system load level. Finally, both of system load and power output of wind farm are considered and clustered input data are used to accelerate Monte Carlo convergence speed. To demonstrate the effectiveness of the proposed approaches IEEE-RTS is used.

One of the important applications of underwater communication is speech transmission between two divers or between divers and ship or submarine. This paper describes a project designed to investigate and demonstrate underwater communication system in Persian Gulf for speech transmission in a real channel. At first, transmitter is designed, then channel with real data is simulated by neural network and at last receiver is designed. Transmitted data is speech signal that for more secure transmission and low frequency bandwidth, a cryptography algorithm and speech coding algorithm is applied in transmitter. Quadrature phase shift keying (QPSK) signaling is employed to make efficient use of the available channel bandwidth. In the receiver, linear equalizer and decision feedback equalizer (DFE) are tested and the best scheme is applied. Also, ray tracing method is used for simulation of sound waves propagation in Persian Gulf underwater communication channel.

This paper presents a new approach to economic dispatch (ED) problems with nonconvex cost functions using Memetic Algorithm (MA). The practical ED problem have nonconvex cost functions with equality and inequality constraints that make the problem of finding the global optimum difficult using any mathematical approaches. In this paper, MA with three different local searches is suggested to deal with the equality and inequality constraints in the ED problem. To validate the results obtained by proposed MAs, a Real Genetic Algorithm (RGA) and an MA adopted from the literature are applied for comparison. Also, the results obtained by MAs and RGA are compared with the previous approaches reported in the literature. The results show that the MAs produce optimal or nearly optimal solutions for all study systems.

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.

In this paper, the use of the supplementary controller of a Unified Power Flow Controller (UPFC) to improve damping of oscillations in Single Machine Infinite Bus (SMIB) system is investigated. The controller was designed based on a linearized modified Phillips Heffron model of SMIB in state space form. In practice systems use simple Proportional Integral (PI) controllers to control UPFC. However, since the PI control parameters are usually tuned based on classical or trial-and-error approaches, they are incapable of obtaining a good dynamic performance for a wide range of operation conditions. To address this problem, in this research an optimization approach, based on the Genetic Algorithms (GA) method is proposed for the design of UPFC controller (supplementary damping controller) for increasing damping of  power system oscillations is developed. Several linear and nonlinear time-domain simulation tests clearly show the effectiveness and validity of the proposed method in enhancing of oscillations damping. Comparisons between the performances of both the proposed and conventional supplementary controllers are made. Computer test results show that proposed method is very effective in oscillations damping and in the meantime is more robust than its conventional counterpart.

In this paper, for the first time, we have reported the possibility of designing wavelength converter for second order femtosecond solitons, by studying its decaying behavior after confronting a localized perturbation in dispersion along an optical fiber. In our studies, in addition to the important nonlinearities for femtosecond pulses, such as self steeping and stimulated Ramman scattering, we have investigated the effects of the third and fourth order dispersions. We have realized that inclusion of the fourth order dispersion effect in our calculations makes the soliton decay behavior somewhat symmetric. On the contrary, when b4=0, the soliton decay behave in an asymmetric manner. The nearly symmetric behavior of the emerging pulses from an upward step-like dispersion, made us to change b4 from –0.0002 ps4/km given in references, to –0.001 ps4/km, to achieve a symmetric behavior suitable for wavelength conversion.