Electrical and Electronics

This paper presents change detection approach for synthetic aperture radar images based on log and mean ratio operators, image fusion and a novel fuzzy local information c means Clustering algorithm. The two multi-temporal SAR images are subjected to ratio operators. The log ratio operator is used to produce the difference image with enhanced low intensity pixels. The mean ratio operator suppresses the unchanged region and improves the homogeneity of the changed region. The difference image is then subjected to image fusion. To improve the intensity of the background pixels Wavelet based image fusion technique is used. The fused image is then subjected to a novel fuzzy algorithm which is Reformulated Fuzzy Local Information C Means Clustering Algorithm. Finally the total number of pixels varied from the difference image is calculated. The kappa and Percentage of correct classification values are more than other algorithms.

This paper is based on a real time embedded system using ARM7 processor LPC2138 to build a system that helps in achieving remote monitoring of patient's physiological parameters such as Body Temperature, Pulse Rate, Oxygen Saturation in blood and Electronic Cardiogram. If any of the patient's parameters go out of the optimum limits of the human body then an alert SMS is sent to the doctor using a GSM interface and the buzzer is activated on the patient's side to alert the patient's caretaker. The system comprises of low cost transducers for acquiring the parameters and uses MATLAB software to build the GUI for displaying the ECG of the patient on a computer. This system eases the need to keep a patient requiring continuous monitoring at the hospital. The monitoring is achieved by allowing the patient to stay at home.

Hiding the information is a vital issue in the 21st century in the field of Data Communication security .It is an important issue because the virtual and digital information transmission faces critical setbacks due to hacking and hackers threats. The transmission of information via the Internet may expose it to detect and theft. So data embedding technologies are developed to provide personal privacy, commercial and national security interests. In this work we consider the problem of extracting blindly data embedded over a wide band in a spectrum (transform) domain of a digital medium (image, audio, video).We develop a novel multicarrier/signature iterative generalized least-squares (M-IGLS) core procedure to seek unknown data hidden in hosts via multicarrier spread-spectrum embedding. Here the original host and the embedding carriers both are assumed as not available. Experimental results shows that the proposed algorithm can achieve recovery probability of error close to what may be attained with known embedding carriers and host autocorrelation matrix.

The automatic identification of the modulation type of a signal at the receiver is a major task of an intelligent receiver, such as software defined radio (SDR), which is used in different communication systems. With no knowledge of the transmitted data, recognition of the modulation type is a difficult task. A communication system, in which receiver is designed based on Machine learning is trained to detect the message using statistical parameters. In this work, machine learning algorithm is developed for identifying 6 different modulated signal types at the receiving end. MATLAB tool is used to generate different modulated signals. Identification of modulation type is done by analyzing different statistical features such as normalized PSD, kurtosis and sum-fft which are calculated using the sampled version of received signal. The algorithm is tested for different frequency and amplitude signals at the receiving end and results are tested for correctness.

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.

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.

This paper presents various types of interpolation techniques to obtain a high quality image The difference between the proposed algorithm and conventional algorithms (in estimation of missing pixel value) is that if standard deviation of image is used to calculate pixel value rather than the value of near most neighbor, the image gives the better result .. The proposed method demonstrated higher performances in terms of PSNR and SSIM when compared to the conventional interpolation algorithms mentioned.

Biometric is a tool of identification that has been broadly used in many applications. A biometric identification system is based on physical characteristic. Dental biometrics has emerged as vital biometric information of human being on account of its stability, invariant nature and uniqueness. It utilizes dental photograph and dental radiograph for human identification because it provides information about teeth including tooth contour, relative position of neighboring teeth and shapes of dental work like crown, fillings and bridges. A biometric identification system is based on physical characteristics such as face, fingerprint, palmprint, fingerprint, eyes (iris, retina ) and DNA. However, many of those characteristics are only suitable for ante mortem identification when a person to be identified is still alive. They cannot be used for post mortem identification specially in such cases of decay or severe body damage caused by fire or collision, due to this dental biometrics plays an important role in human identification and post mortem identification. This paper address review of such different techniques used in dental biometrics.

This paper presents design and analysis of an LCL-based voltage source converter using for delivering power of a distributed generation source to power utility and local load. LCL filer in output of the converter analytically is designed and its different transfer functions are obtained for assessment on elimination of any probable parallel resonant in power system. The power converter uses a controller system to work on two modes of operation, stand-alone and grid-connected modes, and also has a seamless transfer between these two modes of operation. Furthermore, a fast semiconductor-based protection system is designed for the power converter. Performance of the designed grid interface converter is evaluated by using an 85-kVA industrial setup.

Cognitive radio (CR) can successfully deal with the growing demand and scarcity of the wireless spectrum. To exploit limited spectrum efficiently, CR technology allows unlicensed users to access licensed spectrum bands. Since licensed users have priorities to use the bands, the unlicensed users need to continuously monitor the licensed user’s activities to avoid interference and collisions. How to obtain reliable results of the licensed user’s activities is the main task for spectrum sensing. This work will mainly focus on the spectrum sensing based on energy detection algorithm.