Electrical and Electronics

Nowadays, there are innumerable innovative technologies are emerging in the era of image processing and pattern recognition field. One of the challenging and interesting fields of research in image processing and pattern recognition is the “Optical Character Recognition”. Genetic algorithm is class of evolutionary algorithm which is based on the ideas of natural selection and natural genetic system. Genetic algorithm is an impartial optimization algorithm which makes parameter selection in an optimized way so as to obtain the global optimum. Devnagari script is very popular script in India for Marathi, Hindi, Nepali, Sanskrit, Konkani etc. In past few years, the enormous amount of innovations in research work related to the character recognition of printed as well as handwritten documents is established for numerous types of scripts. But the accuracy of recognition will not provide the satisfactory results. The genetic algorithm is used for optimizing the classification error and also improving the recognition rates. So, this is an attempt of improving the accuracy and optimizing the classification error by introducing the genetic algorithm for feature extraction as well as the classification for the handwritten devnagari script.

Transmission Network Expansion Planning (TNEP) is a basic part of the power system planning that verifies where, when and how many new transmission lines should be added to the network. In this paper, expansion planning has been implemented by merging lines loading parameter in the TNEP problem using an improved Discrete Honey Bee Mating Optimization (DHBMO) algorithm. Expanded network will possess a maximum adequacy to provide load demand and also the transmission lines overloaded later. DHBMO algorithm combines the power of genetic algorithms and simulated annealing with a fast problem specific local search heuristic to find the best possible solution within a reasonable computation time. For this reason, the potential of the proposed approach for optimal solution of TNEP problem has been investigated and tested on the Garvers network and a real transmission network in Iran in comparison with the Discrete Particle Swarm Optimization (DPSO) method. The results evaluation show that the using the proposed DHBMO based method, the expansion costs is significantly reduced and the network adequacy is increased considerably than the DPSO algorithm. Also, regarding the convergence curves of both approaches, it can be seen that precision of the proposed algorithm to solve the TNEP problem is more than DPSO one.

Several compression for 3-D medical images have been proposed in the past year, some of which proved resolution and quality scalability up to lossless reconstruction. A novel 3-D scalable compression method for medical images with optimized volume of interest (VOI) coding were presented in this paper. The method is presented within the framework of interactive telemedicine applications, where different remote clients may access the compressed 3-D medical imaging data stored on a central server and request the transmission of different VOIs from an initial lossy to a final lossless representation. The VOI are decoded at the highest quality possible at any bit-rate, while allowing for the decoding of background information. The objective and subjective quality evaluation on various medical volumetric datasets shows that the proposed algorithms provide competitive lossy to lossless compression. The modified version of the embedded block coder with optimized truncation (modified EBCOT), tailored according to the characteristics of the data, encodes the residual data generated after prediction to provide resolution and quality scalability. The Digital watermarking is the process of embedding information into a digital signal which may be used to verify its authenticity or the identity of its owners, in the same manner as paper bearing a watermark for visible identification. Performance evaluations based on real 3-D medical imaging data showed that the proposed method achieves a higher reconstruction quality, in terms of the peak signal-to-noise ratio, than that achieved by 3D-JPEG2000 with VOI coding, when using the MAXSHIFT and general scaling-based methods.

In this research, optimization of electromagnetic shielding tester process parameters for conducting textile composite materials through Taguchi design and ANOVA has been reported. The electromagnetic shielding tester process parameters were selected to optimize the EMSE. The effect of the size of the test Conductive Textile Material Composite sample on EMSE, effect of distance between Conductive Textile Material Composite sample and transmitting antenna on EMSE, effect of distance between the Conductive Textile Material Composite sample and receiving antenna on EMSE, and effect of RH% on EMSE were analyzed and optimized by Taguchi design and ANOVA. It was observed that the electromagnetic shielding effectiveness of conductive textile Composite materials were dominantly influenced by Conductive Textile Material Composite sample size and significantly influenced by distance between Conductive Textile Material Composite sample and transmitting antenna.

In this paper, an attempt has been made to develop a new algorithm for distribution system planning. The proposed algorithm does not require prior knowledge of candidate substation location and can obtain the “number, location and service area” of HV/MV substations, the optimal feeder configuration and the optimal sizes of branch conductors while satisfying constraints such as current capacity, voltage drop and heuristic rules. Several algorithms are proposed for distribution systems planning. A comprehensive algorithm is developed for obtaining the optimal “number, location and service area” of substation using GA and a generalized algorithm is modified to optimal feeder path on minimum loss criterion. Direct approach load flow is used for solving radial distribution networks and branch conductor optimization algorithm. The load flow algorithm and branch conductor optimization techniques are used as subroutine in the generalized distribution systems planning algorithm. Through numerical example the validity of proposed method is verified.

The main goal of this study is finding optimal place of unified power flow controller (UPFC) and phase shifter (PST) in the power systems. In other words, the main concentration is on connecting FACTS and OPF tools opinion using PST and UPFC power injection model to find the best place of setting these elements in power networks. The objective function of maximizing static voltage stability edge (system loadability factor) is discussed in this paper. Simulation results are offered on IEEE 118_ bus standard network and they suggest that proposed algorithm includes the better resolution and there is a more little time than the other placement methods.

The transfer reactive power from production source to consumption areas during steady-state operating conditions is a major problem of voltage stability. Hence voltage stability enhancement margin is interrelated with Reactive power loss (RPL). In practical, the power system network has 80-90% inductive loads. When the loads are increased, the line currents are increased, reflecting to the increase in Reactive power loss. This will leads to voltage instability that means the power system gets closer to the instability point. Reactive power can be dispatched effectively to maintain acceptable voltage levels. Maintaining viable voltage levels are very important to avoid voltage collapse. The optimal allocation of a VAR compensator is implemented using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). These two algorithms are implemented considering its less memory requirement and inherent simplicity. Simulation is carried out by using MATLAB Software for IEEE 14 bus system and the results are presented and analysed.

This paper presents an optimization model to calculation of the minimum number of phasor measurement units (PMUs) for complete observability of electrical power networks. Minimum PMU placement problem has multiple solutions. We propose a flow chart and indicators in order to find all solution and rank these multiple solutions, respectively. The proposed model is capable of obtaining the full set of optimal solutions instead of only one or partial solutions. The integer linear programming (ILP) approach is implemented to solve this model. We propose a procedure for multistaging of PMU placement in a given time horizon due to financial and physical constraints using an ILP framework. In addition, network expansion scenarios associated with intermediate stages are taken into account. Numerical studies are conducted on a nine-bus system and the IEEE 57-bus system and the results are analyzed.

The sustainable power source systems (RESs) are an appealing alternative to energize the group as they are condition amicable, free of cost, and all-overrunning. The effectiveness of these vitality systems is low and can be enhanced by coordinating them in parallel. In this paper, hydro (7.5?kW) and PV (10?kW) are taken as RESs and associated with the utility grid. Because of the discontinuous idea of both the hydro and photovoltaic energy sources, utility grid is associated with the system for guaranteeing the ceaseless power stream. The hydro power generation system uses the 3-phase synchronous machine and converters. The AC/DC/AC converter is used as interface to connect the hydro turbine to the utility grid to adjust the generated voltage to the utility grid voltage. The solar generation system is the combination of PV array, boost converter, and solar inverter. The control of both the hydro and solar power plants is provided through the constant current controller. The analysis has been done to verify the existence of the proposed system. Results demonstrate that the proposed system is able to be put into service and can feed the community.

Technologies have advanced rapidly in the field of digital signal processing due to advances made in high speed, low cost digital integrated chips. These technologies have further stimulated ever increasing use of signal representation in digital form for purposes of transmission, measurement, control and storage. Design of digital filters especially adaptive or semi adaptive is the necessity of the hour for SAR applications. In this research work Butter worth digital FIR semi adaptive band pass filter for 700-800 KHz for 128 order Kaiser window with 0.5 Beta was designed using XILINX and MATLAB soft wares. As part of practical research work 700 -800 KHz Butter worth digital FIR semi adaptive band pass filter for 700-800KHz for 128 order Kaiser window with 0.5 Beta was designed using FPGA kit using SPARTAN-3E. These were optimized, analyzed, compared and evaluated keeping the sampling frequency at 5 GHz. Both these filters were tested by passing a sinusoidal test signal of 781 KHz along with noise and the filtered output signals are presented.