Image compression is one of the data compression types applied to digital images in order to reduce their high cost for storage and/or transmission. Image compression algorithms may take the benefit of visual sensitivity and statistical properties of image data to deliver superior results in comparison with generic data compression schemes, which are used for other digital data. In the first approach, the input image is divided into blocks, each of which is 16 x 16, 32 x 32, or 64 x 64 pixels. The blocks are converted first into a string; then, encoded by using a lossless and dictionary-based algorithm known as arithmetic coding. The more occurrence of the pixels values is codded in few bits compare with pixel values of less occurre

A substantial percentage of the world’s energy consumption (almost 40%) and carbon dioxide (CO2) emissions (around 37%) come from the construction industry, especially schools. This work presents a new hybrid artificial intelligence (AI) engineering model that aims to maximize energy performance on campuses in a holistic way. Modules for data-driven forecasting, metaheuristic optimization, and real-time adaptive control are all part of the concept. A thorough energy simulation of a university campus building is used in conjunction with the AI model to assess its performance through a co-simulation framework. Findings show that yearly peak electricity demand may be reduced by 18.7% and total site energy consumption by 22.4% when co

The Maxwell equations have been formulated for a composite slab waveguide at x-band wave propagation. The eigenvalues of the system equations are obtained by using MATLAB program. These eigenvalues are used to obtain the wave propagation constant and a number of modes inside the slabs. A good correspondence was seen between the number of modes and the cut off thickness. The parameter that affects the performance of waveguide is the slab thickness. The propagation constant is usually adopted to characterize this type of waveguide and show how the cutoff frequency of the mode in the slab is increased dramatically by decreasing the frequency.
Our study focused on lower modes, the results for the transmission coefficient are then used to

ولاء طارق حميد, Mustansiriyah Journal of Sports Science, 2021

In the present work, Uranium (²³⁸U), Thorium (²³²Th) and Potassium (⁴⁰K) specific activity concentration in (Bq/kg) was measured in five different types for wheat flours that are available in the Iraqi markets. The gamma spectrometry method with an NaI (Tl) detector has been used for radiometric measurements. Calculations of radium equivalent activity, annual effective dose equivalent, external hazard index (H_ex), internal hazard index (H_in), representing gamma index and gamma dose rate in all  flour samples were 17.98132 Bq/kg, 0.0100334, 0.04502, 0.04857, 0.06872, 0.125883 and 8.181244 respectively. It is found that the average of specific activity concentration of wheat flour sam

Background: tooth debonding was one of the major reasons for denture repair. With the use of recently introduced thermoplastic denture base materials the problem of tooth debonding increased due to the nature of the bond between these materials and the acrylic teeth. This study was aimed to assess the bond of the acrylic teeth to conventional heat cure acrylic resin and to thermoplastic resin denture base material and methods to enhance it. Materials and methods: acrylic resin teeth were bonded to heat cure acrylic resin with and without wetting the ridge laps of the teeth with monomer and acrylic teeth with prefabricated retentive holes, unmodified and modified, in their ridge laps were processed with Valplast thermoplastic resin denture b

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

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

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

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