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Self-excited induction generators (SEIGs) are used in wind turbine system because of high reliability, rigidity, simple structure, and capability to work under severe badly operating conditions. This type of generator has a poor terminal voltage and frequency regulation during changing the connected loads due to the absence of constant excitation current. Therefore, it is essential to stabilize the generated voltage and frequency besides suppress the injected harmonic current components. In this work, the dynamic performance of SEIG with distribution static series compensator (DSSC) is analyzed. The DSSC based on neuro-fuzzy controlled (NFC) is applied to control both voltage and frequency to enhance the regulation of SEIG. The NFC is used to control the DSSC which leads to balance the requirement of the reactive and active power of stand-alone grid under load variation and attempts to obtain a constant terminal voltage. The model is simulated using MATLAB/Simulink. The NFC structure designed to regulate and control the output voltage of the SEIG driven by a wind turbine to feed a consumer in remote and rural places. Furthermore, the power system parameters calculated depending on the d-q theory. Modeling results explained that the suggested controller is consistent and tough related to the conventional types.

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The operation of medical image fusion is to merge various images from different imaging modalities in to one image fused. The quality of image fused is improved especially decrease randomness, that’s done by extracting the useful information of multiple images in one image. To rise the diagnosis and estimate of many medical problems by using clinical application of medical images and improving the accuracy medical imaging clinical is the most important goal of multi_modal image fusion algorithms. There are many types of modality used as a reference in medical image fusion like X_ray, Ultrasound, Magnetic Resonance Imaging (MRI), Positron Emission Tomography (PET) and Computed Tomography (CT). In this work, a multi solution images are used and coming from (CT) and (MRI) by Discrete Wavelet Transform (DWT) techniques to get a high quality image fusion. It can be proved the improvement in performance of image quality after fusion techniques by using some popular parameters of image metrics to test the image as Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Structural Similarity Index Measure (SSIM). The quality improve of the fused image by tested and analyzed as low MSE of 0.02632, higher PSNR of 15.7955 and higher SSIM of 0.75434.

Tracking systems of moving objects provide a useful means to better control, manage and secure them. Tracking systems are used in different scales of applications such as indoors, outdoors and even used to track vehicles, ships and air planes moving over the globe. This paper presents the design and implementation of a system for tracking objects moving over a wide geographical area. The system depends on the Global Positioning System (GPS) and Global System for Mobile Communications (GSM) technologies without requiring the Internet service. The implemented system uses the freely available GPS service to determine the position of the moving objects. The tests of the implemented system in different regions and conditions show that the maximum uncertainty in the obtained positions is a circle with radius of about 16 m, which is an acceptable result for tracking the movement of objects in wide and open environments.