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Integrity and Security in Cloud Computing Environment: A Review
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Cloud computing is a newly developed concept that aims to provide computing resources in the most effective and economical manner. The fundamental idea of cloud computing is to share computing resources among a user group. Cloud computing security is a collection of control-based techniques and strategies that intends to comply with regulatory compliance rules and protect cloud computing-related information, data apps, and infrastructure. On the other hand, data integrity is a guarantee that the digital data are not corrupted, and that only those authorized people can access or modify them (i.e., maintain data consistency, accuracy, and confidence). This review presents an overview of cloud computing concepts, its importance in many applications, and tools that can be used for providing the integrity and security to the data located in the cloud environment.

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Publication Date
Mon Mar 23 2020
Journal Name
Baghdad Science Journal
Surfactant Cloud Point Extraction as a Procedure of Preconcentrating for Metoclopramide Determination Using Spectro Analytical Technique
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In current article an easy and selective method is proposed for spectrophotometric estimation of metoclopramide (MCP) in pharmaceutical preparations using cloud point extraction (CPE) procedure. The method involved reaction between MCP with 1-Naphthol in alkali conditions using Triton X-114 to form a stable dark purple dye. The Beer’s law limit in the range 0.34-9 μg mL-1 of MCP with r =0.9959 (n=3) after optimization. The relative standard deviation (RSD) and percentage recoveries were 0.89 %, and (96.99–104.11%) respectively. As well, using surfactant cloud point extraction as a method to extract MCP was reinforced the extinction coefficient(ε) to 1.7333×105L/mol.cm in surfactant-rich phase. The small volume of organi

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Publication Date
Fri Nov 28 2025
Journal Name
Arabian Journal For Science And Engineering
Role of Artificial Intelligence in Enhancing Efficiency and Sustainability in Middle Eastern Oil and Gas: A Review
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This review examines how artificial intelligence (AI) including machine learning (ML), deep learning (DL), and the Internet of Things (IoT) is transforming operations across exploration, production, and refining in the Middle Eastern oil and gas sector. Using a systematic literature review approach, the study analyzes AI adoption in upstream, midstream, and downstream activities, with a focus on predictive maintenance, emission monitoring, and digital transformation. It identifies both opportunities and challenges in applying AI to achieve environmental and economic goals. Although adoption levels vary across the region, countries such as Saudi Arabia, the UAE, and Qatar are leading initiatives that align with global sustainability targets.

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Publication Date
Sun Mar 31 2024
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Using Solid Waste as A Substitute for Raw Materials in Construction: A Review.
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The main challenge is to protect the environment from future deterioration due to pollution and the lack of natural resources. Therefore, one of the most important things to pay attention to and get rid of its negative impact is solid waste. Solid waste is a double-edged sword according to the way it is dealt with, as neglecting it causes a serious environmental risk from water, air and soil pollution, while dealing with it in the right way makes it an important resource in preserving the environment. Accordingly, the proper management of solid waste and its reuse or recycling is the most important factor. Therefore, attention has been drawn to the use of solid waste in different ways, and the most common way is to use it as an alternative

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Publication Date
Thu Mar 02 2023
Journal Name
Applied Sciences
Machine Learning Techniques to Detect a DDoS Attack in SDN: A Systematic Review
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The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach

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Publication Date
Fri Mar 21 2025
Journal Name
Iklil For Human Studies
Review Article A Feminist Gothic in the American Literary Fiction
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Teresa Fitzpatrick presents a connection between oppressed women and the plant of Wisteria in gothic fiction in her article “Wisteria: A Female Eco-Gothic Metaphor in American Fiction Through the Ages.” The connection between women and nature is common in literature as women are usually compared to the beauty or ferocity of flowers, rivers, or natural phenomena in general. The connection extends to the architecture and sort of plants that appear in gothic literature. Gothic novels have routinely been connected to the secrets and life stories of women who cannot have the liberty to live or share them outside their homes. A fearful house with a prisoned person, ghost, or a secret is mostly normally found in gothic writing. Women have exce

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Publication Date
Fri Jun 20 2014
Journal Name
Jurnal Teknologi
A Review of Snake Models in Medical MR Image Segmentation
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Developing an efficient algorithm for automated Magnetic Resonance Imaging (MRI) segmentation to characterize tumor abnormalities in an accurate and reproducible manner is ever demanding. This paper presents an overview of the recent development and challenges of the energy minimizing active contour segmentation model called snake for the MRI. This model is successfully used in contour detection for object recognition, computer vision and graphics as well as biomedical image processing including X-ray, MRI and Ultrasound images. Snakes being deformable well-defined curves in the image domain can move under the influence of internal forces and external forces are subsequently derived from the image data. We underscore a critical appraisal

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Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes In Networks And Systems
Using Machine Learning to Control Congestion in SDN: A Review
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Publication Date
Tue Mar 15 2016
Journal Name
Asian Journal Of Applied Sciences
A Review: Training Requirement of Agriculture Extension Officers in Iraq
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Publication Date
Sat Dec 31 2022
Journal Name
Mathematical Modelling Of Engineering Problems
Investigation of Energy Efficient Clustering Algorithms in WSNs: A Review
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In recent years, Wireless Sensor Networks (WSNs) are attracting more attention in many fields as they are extensively used in a wide range of applications, such as environment monitoring, the Internet of Things, industrial operation control, electric distribution, and the oil industry. One of the major concerns in these networks is the limited energy sources. Clustering and routing algorithms represent one of the critical issues that directly contribute to power consumption in WSNs. Therefore, optimization techniques and routing protocols for such networks have to be studied and developed. This paper focuses on the most recent studies and algorithms that handle energy-efficiency clustering and routing in WSNs. In addition, the prime

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Publication Date
Tue Jan 01 2019
Journal Name
Iraqi Journal Of Agricultural Sciences
A review: Behavior of pitting corrosion in manufacturing food equipment
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