تحليل الشراكات التجارية للعراق 2003-2013

This study aims to enhance the RC5 algorithm to improve encryption and decryption speeds in devices with limited power and memory resources. These resource-constrained applications, which range in size from wearables and smart cards to microscopic sensors, frequently function in settings where traditional cryptographic techniques because of their high computational overhead and memory requirements are impracticable. The Enhanced RC5 (ERC5) algorithm integrates the PKCS#7 padding method to effectively adapt to various data sizes. Empirical investigation reveals significant improvements in encryption speed with ERC5, ranging from 50.90% to 64.18% for audio files and 46.97% to 56.84% for image files, depending on file size. A substanti

The mechanical design of elevator elements is always performed by international standards. The engineer selects the appropriate elements of elevator according to catalogues without knowing scientific details. Therefore, a theoretical analysis is achieved at two operating conditions for guide rails (1) safety gear operation, and (2) running condition with the loads unevenly distributed on the elevator car. The guide rail is considered a continuous beam with variable supports. Then the British code is listed showing the equations used in it.

The theoretical equations showed that guide rails are never subjected to stress in simultaneous combined buckling and bending in the plane, where the bending moment is exerted. It is always a c

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

Objectives: Semen analysis is the cornerstone for the valuation of the male partner in the infertile couples. This test has been standardized throughout the world through the World Health Organization (WHO) since the1970s by producing, editing, updating, and disseminating a semen analysis manual and guidelines. A retrospective study to give an insight about  male infertility. Methods: This retrospective study assessed the semen findings of 1000 men evaluated at the  Department of Urology, Al-Kindy Teaching Hospital in Baghdad-Iraq  between January 2016 and May 2019. Semen analysis were done for them. Results: According to WHO standard for semen normality, 1000 samples that were analyzed, normospermia was shown in 835 (83.5%)males

A frequently used approach for denoising is the shrinkage of coefficients of the noisy signal representation in a transform domain. This paper proposes an algorithm based on hybrid transform (stationary wavelet transform proceeding by slantlet transform); The slantlet transform is applied to the approximation subband of the stationary wavelet transform. BlockShrink thresholding technique is applied to the hybrid transform coefficients. This technique can decide the optimal block size and thresholding for every wavelet subband by risk estimate (SURE). The proposed algorithm was executed by using MATLAB R2010aminimizing Stein’s unbiased with natural images contaminated by white Gaussian noise. Numerical results show that our algorithm co

Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither non-brain tissues nor

   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

Cognitive stylistics is one discipline of applied linguistics that relies on the reader’s interpretation and inference of the meaning of the text depending on his background knowledge. It studies how the reader understands the text and mapping it with his real experiences (Jeffries and McIntyre,2010). The present study is a cognitive stylistic analysis of digital stories. Digital stories are short narratives made by a combination of different sorts of digital media such as pictures, audios and videos. These digital media are employed to tell stories about oneself, famous people, and important events. The analyzed stories are selected from “Daily Yahoo Stories” and are analyzed according to Lakoff (1993) approach, The analysis investig