Flexible pipes, such as GRP pipes, serve as effective underground infrastructure especially as sewer pipeline. This study is an attempt for understanding the effects of bedding types on the behavior of large diameter GRP flexible sewer pipes using three dimensional finite element approaches. Theoretical and numerical analyses were performed using both BS EN 1295-1 approach and finite element method (ABAQUS software). The effects of different parameters are studied such as, depth of backfill, bedding compaction, and backfill compaction. Due to compaction, an increase in the bedding compaction modulus (E’₁) results in a reduction of both stresses and displacements of the pipe, especially, for well compacted ba

The research is based on the basic idea that companies today are moving towards a new trend towards protecting the environment coupled with the increasing wareness of the pollution damage caused by these companies due to their operations and activities in the environment. The two main reasons that led the researchers to choose this subject is the need to adapt the companies themselves in response to successive developments, The great development was that companies moved from the sole economic responsibility of the business to social responsibility by emphasizing socially responsible profit. The problem of research is the knowledge of the availability of the dimensions of the green processing series in Kirkuk Cement Factory The re

Table tennis is considered one of the fast base sports that the player needs to have the speed of performance and awareness, especially in straight forward and back strikes, which is an important offensive skills, and the player success depends on his perception speed to the point of the fall of the ball in the arena of his competitor. But there is no way to measure cognitive processing speed. Therefore, the researchers sought to design a test that measures this ability to ensure its scientific evaluation, and then establish standard scores for this test for the players of the specialized school of table tennis, to help evaluate them objectively and move away from subjective estimates when evaluating and developing measuring instruments in

A new scheme of plasma-mediated thermal coupling has been implemented which yields the temporal distributions of the thermal flux which reaches the metal surface, from which the spatial and temporal temperature profiles can be calculated. The model has shown that the temperature of evaporating surface is determined by the balance between the absorbed power and the rate of energy loss due to evaporation. When the laser power intensity range is 107 to108 W/cm2 the temperature of vapor could increase beyond the critical temperature of plasma ignition, i.e. plasma will be ignited above the metal surface. The plasma density has been analyzed at different values of vapor temperature and pressure using Boltzmann’s code for calculation of elec

The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

The effect of using three different interpolation methods (nearest neighbour, linear and non-linear) on a 3D sinogram to restore the missing data due to using angular difference greater than 1° (considered as optimum 3D sinogram) is presented. Two reconstruction methods are adopted in this study, the back-projection method and Fourier slice theorem method, from the results the second reconstruction proven to be a promising reconstruction with the linear interpolation method when the angular difference is less than 20°.

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

     The searching process using a binary codebook of combined Block Truncation Coding (BTC) method and Vector Quantization (VQ), i.e. a full codebook search for each input image vector to find the best matched code word in the codebook, requires a long time.   Therefore, in this paper, after designing a small binary codebook, we adopted a new method by rotating each binary code word in this codebook into 900 to 2700 step 900 directions. Then, we systematized each code word depending on its angle  to involve four types of binary code books (i.e. Pour when , Flat when  , Vertical when, or Zigzag). The proposed scheme was used for decreasing the time of the coding procedure, with very small distortion per block, by designing s

Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s