Electrical and Electronics

Advancement in the field of embedded system and VLSI has induced the researcher in designing low power embedded systems and VLSI circuit design. The embedded systems are mostly batteries operated in nature. The power loss during static, dynamic and switching characteristics are tabulated. The switching nature in cmos constitutes a large value of power loss during the switching condition. Many research papers have been proposed in reducing the switching loss, and low power estimation, this paper clearly demonstrates the comparison of them. The main features of the dominated design techniques and methodologies of transistor level, gate level, RTL level, behavior level and system level are reviewed. The corresponding advantages and drawbacks, as well as comparisons between the techniques and the methodologies are also presented. The low-power design process such as transistor level, gate level, RTL level, behavior level and system-level models are explained.

The range of brightness levels and Histogram shows how individual brightness levels are occupied in any image, for image contrast measurement .Low-level image processing is one of the most important issues of image enhancement. To control and enhance the contrast, Histogram Equalization (HE) is the simple and effective technique, but this approach causes some unnatural look in output image. For best effect the brightness of input image must be retained. Fuzzy techniques can manage the vagueness and ambiguity efficiently. Fuzzy logic is a powerful tool to represent and process human knowledge in form of fuzzy if-then rules. In this work we are using fuzzy membership function in the proposed algorithm. The proposed concept in this paper is named as Brightness Preservation by Fuzzy based Multi-peak Generalized Histogram Equalization (BPFMGHE) and it is simulated by MATLAB; this technique first combined the global histogram equalization of image with local information and then after calculating noise free generalised multi-peak histogram by equalization, the image was again decomposed into several sub-images, and then applied the fuzzy membership function dependent HE process to each of them to preserve image brightness.The distribution of grey level is in complete control with the given method and image improvement is effective. Image is improved and brightness is preserved effectively with the discussed process.

Digital image processing is now increasingly being used in electron accelerators to characterize electron beam. Measurement of electron beam parameters like beam size, beam centroid with high accuracy is required to optimize accelerator performance. Measurement accuracy of these parameters using digital image processing is limited by the noise present in the images. Reduction of noise without altering the features present in the image is a desired goal of image processing. In this paper we evaluate the noise reduction capability of median, mean, gaussian and wiener filters from digital images of electron beam image. The images were collected from Transport Line-1 in Indus Accelerator Complex at Raja Ramanna Centre for Advanced Technology (RRCAT), Indore, India. We also evaluate the effect of these filters on the measurement accuracy of beam parameters like beam size and beam centroid. It has been observed that performance of median filter for noise reduction is better than mean, gaussian and wiener filter. Median filter also creates less distortion in beam size and centroid of the beam in comparison with other filters.

Selection of feature extraction method is most important factor in achieving high recognition performance in automatic pattern recognition systems. Similarly selection of suitable classifier also plays a very important role for the same. Plenty of feature selection methods and classifiers are existing in computer domain and choice of each of these mainly depends on task in hand. This paper presents an efficient and novel method for recognition of handwritten numerals using bar codes. Handwritten numerals are scan converted to binary images and normalized to a size of 30 x 30 pixels. The features are extracted using barcodes and are classified successfully using the statistical technique.

Variation in load frequency is an index for normal operation of power systems. When load Perturbation takes place anywhere in any area of the system, it will affect the frequency at other areas also. To control load frequency of power systems various controllers are used in different areas, but due to non-linearity's in the system components and alternators, these controllers cannot control the frequency quickly and efficiently. The simple neural networks can alleviate this difficulty. This paper deals with the Artificial Neural Network ( ANN) is applied to self tune the parameters of Proportional-Integral-Derivative(PID) ontroller. The single, Two Area non-reheat system has been considered for simulation of the proposed self tuning ANN based PID controller. In the PID controller parameters are continuously adjusted according to the change in area-control error (ACE). Simulations of the networks are carried out for different load changes 1% and change of 1% in governor time constant and turbine time constant parameters. The proposed method for simulation results are obtained by the other controllers of PI and PID compared highlighting the performance of PID-ANN controller. The simulation works developed by MATLAB- SIMULINK Environment. The simulink results are obtained by qualitatively and quantitatively .The qualitative comparison is used for the Integral Square Error (ISE), Integral Absolute Error (IAE) and Integral Time Absolute Error (ITAE) is minimized in single and multi area power system. Therefore the Comparison of responses with conventional integral controller(PI) & PID controller show that the neural-network controller (ANN-PID) has quite satisfactory generalization capability, feasibility and reliability, as well as accuracy in both single and multi area power system.

An efficient VLSI implementation of Adaptive Rank Order Filter (AROF) and Adaptive Median Filter (AMF) is proposed in this paper. Impulse noise is introduced in digital images during image acquisition and transmission. The noise reduction algorithms remove noise without degrading image information. Linear filters tend to blur an image; hence they are not commonly used. Non-linear filters provide more satisfactory results in comparison to linear filters. The proposed paper adapts the filter based on the level of noise intensity in the image. AMF provides better filtering properties than standard median filters for images corrupted with 60% noise density. AROF provides better filtering properties than it is possible with AMF for images corrupted with higher noise densities (>60%). The VLSI architecture for AROF and AMF implements pipelining with parallel processing in order to speed up the filtering process. The performance of the proposed algorithm is compared with Peak Signal to Noise Ratio (PSNR) and Image Enhancement Factor (IEF).

In this paper the transmitter intelligently adapts the transmission parameters like coding scheme, modulation symbol, power etc. w.r.t the varying wireless CSI. If channel is having poor transmission conditions then a channel code with smaller code rate and a smaller modulation symbol can be used. Similarly, if channel conditions are good, a comparatively high code rate or even no coding need be used. Paper gives an overview about the WiMAX standard and studies the performance of a WiMAX transmitter and receiver.

Industrial automation is the use of machines, control systems and information technologies to optimize productivity in the production of goods and delivery of services. The correct incentive for applying automation is to increase productivity, and/or quality beyond that possible with current human labor levels so as to realize economies of scale, and/or realize predictable quality levels. In the scope of industrialisation, automation is a step beyond mechanization. Whereas mechanization provides human operators with machinery to assist them with the muscular requirements of work, automation greatly decreases the need for human sensory and mental requirements while increasing load capacity, speed, and repeatability. Generally PLC Is used for the task of industrial automation, here we introduce new concept in automation is use of “Embedded PLC”for the industrial automation which overcome all the limitation of conventional PLC. For the purpose of automating some task we use neumerous wired or wireless sensors with Embedded PLC. It provide smooth control over the Industrial Systems. After investigated the conception and features of PLC and embedded system, in this paper the development of low-cost embedded PLC for Industrial Controls & Monitoring. This paper describes the real-time industrial automation using Embedded PLC.

This paper presents the effective approach to harness electrical energy from the highways by means of vertical axis wind turbine. The wind turbine consists of stationary shaft which is mounted on the ball bearing on top and bottom end of the shaft. In addition, dynamo is connected to upper and lower part of the wind turbine. As the vehicles are moving at faster rate on two different directions in highways, the wind turbine, which is placed on the highways sides, is able to rotate effectively on its own axis in any of the direction. As a result, the large amount of electrical energy gets generated in both day and night time. This wind power generation is an alternative way for power generation instead of depleting non-renewable energy sources.

The proposed work gives a method of cancer diagnosis using artificial intelligence. The method involves the use of MRI images which are processed and segmented before the display of the tumor portion. The tumor portion will be having a denser background as compared to the general image; this has been set up in our algorithm. Some image enhancement and noise reductions are done to enhance the image quality, after that some morphological operations are applied to detect the tumor in the image.