In this study, the results of the uranium concentrations and specific activity in 10 rice samples are described using a solid-state track detector (CR-39). Samples were collected from various local Iraqi markets with different origins (Iraq, India, America, and Thailand). Our findings found that the results of uranium concentration in all studied samples are ranging from (0.55 ± 0.28 to 1.74 ± 0.31) ppm with a weighted average of (1.24 ± 0.99) ppm. Also, results demonstrate that the specific activity values of the studied samples swing between values of (6.88 ± 3.52 and 21.49 ± 3.85) Bq/Kg. The obtained results of the studied rice samples are indicated that it is less than the acceptable limit of those studies established by ma

The present study aimed to identify the therapeutic evaluation of chitosan extracted from the fungus cushroom and pure chitosan on glucose and lipid profile in the blood of 35 male rabbits with hyperlipidemia induced experimentally by cholesterol. The tests included estimation of glucose levels, total cholesterol, triglycerides, high-density lipoproteins, low-density lipoproteins, and very low-density lipoproteins. hyperlipidemia was induced in the male rabbits used in the study which was administered orally with cholesterol 150mg/kg body weight for a week. rabbits were divided into seven groups: control, cholesterol, pure chitosan, mushroom chitosan, cholesterol and pure chitosan, cholesterol and mushroom chitosan and cholestero

The implementation of technology in the provision of public services and communication to citizens, which is commonly referred to as e-government, has brought multitude of benefits, including enhanced efficiency, accessibility, and transparency. Nevertheless, this approach also presents particular security concerns, such as cyber threats, data breaches, and access control. One technology that can aid in mitigating the effects of security vulnerabilities within e-government is permissioned blockchain. This work examines the performance of the hyperledger fabric private blockchain under high transaction loads by analyzing two scenarios that involve six organizations as case studies. Several parameters, such as transaction send ra

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

The Supreme Judicial Council decided on July 3, 2003, to set up a court to deal with the issues of publication and media. This court tries to solve the problems of media and publishing in both its civil and penal aspects. The decision of establishing the court represents a new and important step to be taken by the Iraqi Judicial Council for the tremendous development witnessed by media sector in general and press in particular especially after 2003.
This study includes two main axes: the first one deals with the most important crimes of publication in the Iraqi legislations such as the crimes of defamation, libel, insult, indecency, and incitement; the second deals with an analytical survey of the completed cases i.e. the issues tha

Deep Learning Techniques For Skull Stripping of Brain MR Images

    In this article, the research presents a general overview of deep learning-based AVSS (audio-visual source separation) systems. AVSS has achieved exceptional results in a number of areas, including decreasing noise levels, boosting speech recognition, and improving audio quality. The advantages and disadvantages of each deep learning model are discussed throughout the research as it reviews various current experiments on AVSS. The TCD TIMIT dataset (which contains top-notch audio and video recordings created especially for speech recognition tasks) and the Voxceleb dataset (a sizable collection of brief audio-visual clips with human speech) are just a couple of the useful datasets summarized in the paper that can be used to test A

One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p