In this paper, two new simple, fast and efficient block matching algorithms are introduced, both methods begins blocks matching process from the image center block and moves across the blocks toward image boundaries. With each block, its motion vector is initialized using linear prediction that depending on the motion vectors of its neighbor blocks that are already scanned and their motion vectors are assessed. Also, a hybrid mechanism is introduced, it depends on mixing the proposed two predictive mechanisms with Exhaustive Search (ES) mechanism in order to gain matching accuracy near or similar to ES but with Search Time ST less than 80% of the ES. Also, it offers more control capability to reduce the search errors. The experimental tests

Nowadays, still images are used everywhere in the digital world. The shortages of storage capacity and transmission bandwidth make efficient compression solutions essential. A revolutionary mathematics tool, wavelet transform, has already shown its power in image processing. The major topic of this paper, is improve the compresses of still images by Multiwavelet based on estimation the high Multiwavelet coefficients in high frequencies sub band  by interpolation instead of sending all Multiwavelet coefficients. When comparing the proposed approach with other compression methods Good result obtained

Nanomaterials have an excellent potential for improving the rheological and tribological properties of lubricating oil. In this study, oleic acid was used to surface-modify nanoparticles to enhance the dispersion and stability of Nanofluid. The surface modification was conducted for inorganic nanoparticles (NPs) TiO₂ and CuO with oleic acid (OA) surfactant, where oleic acid could render the surface of TiO₂-CuO hydrophobic. Fourier transform infrared spectroscopy (FTIR), and Scanning electron microscopy (SEM) were used to characterize the surface modification of NPs. The main objective of this study was to investigate the influence of adding modified TiO₂-CuO NPs with weight ratio 1:1 on thermal-physical propertie

In cognitive radio system, the spectrum sensing has a major challenge in needing a sensing method, which has a high detection capability with reduced complexity. In this paper, a low-cost hybrid spectrum sensing method with an optimized detection performance based on energy and cyclostationary detectors is proposed. The method is designed such that at high signal-to-noise ratio SNR values, energy detector is used alone to perform the detection. At low SNR values, cyclostationary detector with reduced complexity may be employed to support the accurate detection. The complexity reduction is done in two ways: through reducing the number of sensing samples used in the autocorrelation process in the time domain and through using the Slid

Numeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a

Image quality plays a vital role in improving and assessing image compression performance. Image compression represents big image data to a new image with a smaller size suitable for storage and transmission. This paper aims to evaluate the implementation of the hybrid techniques-based tensor product mixed transform. Compression and quality metrics such as compression-ratio (CR), rate-distortion (RD), peak signal-to-noise ratio (PSNR), and Structural Content (SC) are utilized for evaluating the hybrid techniques. Then, a comparison between techniques is achieved according to these metrics to estimate the best technique. The main contribution is to improve the hybrid techniques. The proposed hybrid techniques are consisting of discrete wavel

Green synthesis is depending on preparation of nano composited SiO₂/V₂O₅ by using the modified sol-gel method depending on rice husk ash as a source for the extraction of silica gel and the product powder of nano composited SiO₂/V₂O₅ characterization by many techniques such as X-ray diffraction spectroscopy (XRD), field emission scanning electron microscopy (FESEM), and N₂ adsorptions/desorption isotherms (BET). This study also includs the biological effectiveness of SiO₂/V₂O₅ and its effect on inhibiting bacterial growth after the prepared nanomaterial was applied to wound dressings, which gave a promising result for its use as

        Urban land price is the primary indicator of land development in urban areas. Land prices in holly cities have rapidly increased due to tourism and religious activities. Public agencies are usually facing challenges in managing land prices in religious areas. Therefore, they require developed models or tools to understand land prices within religious cities. Predicting land prices can efficiently retain future management and develop urban lands within religious cities. This study proposed a new methodology to predict urban land prices within holy cities. The methodology is based on two models, Linear Regression (LR) and Support Vector Regression (SVR), and nine variables (land price, land area,