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Remote Data Auditing in a Cloud Computing Environment
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In the current paradigms of information technology, cloud computing is the most essential kind of computer service. It satisfies the need for high-volume customers, flexible computing capabilities for a range of applications like as database archiving and business analytics, and the requirement for extra computer resources to provide a financial value for cloud providers. The purpose of this investigation is to assess the viability of doing data audits remotely inside a cloud computing setting. There includes discussion of the theory behind cloud computing and distributed storage systems, as well as the method of remote data auditing. In this research, it is mentioned to safeguard the data that is outsourced and stored in cloud servers. There are four different techniques of remote data auditing procedures that are presented here for distributed cloud services. There are several difficulties associated with data audit methods; however, these difficulties may be overcome by using a variety of techniques, such as the Boneh-Lynn-Shacham signature or the automated blocker protocol. In addition to that, other difficulties associated with distributed-based remote data auditing solutions are discussed. In addition, a variety of approaches might be researched further for further examination in order to find answers to these impending problems.

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Publication Date
Wed Dec 15 2021
Journal Name
Journal Of Baghdad College Of Dentistry
Odontogenic Cysts and Tumors of Maxilla and Maxillary Sinus (A Clinicopathological Analysis)
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Background: Knowledge about the prevalence and distribution of pathologies in a particular location is important when a differential diagnosis is being formulated. The aim of this study was to describe the prevalence and the clinicopathological features of odontogenic cysts and tumors affecting the maxilla and to discuss the unusual presentation of those lesions within maxillary sinus.

Materials and Methods: A multicenter retrospective analysis was performed on pathology archives of patients who were diagnosed with maxillary odontogenic cysts and tumors from 2010 to 2020. Data were collected with respect to age, gender and location.

Result: A total of 384 cases was identified, 320 (83.3%) cases were diagnosed as odontogenic

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Publication Date
Mon Jun 09 2025
Journal Name
Journal Of Discrete Mathematical Sciences And Cryptography
A novel improvement of skew tent map for generating Pseudo random numbers
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An encryption system needs unpredictability and randomness property to maintain information security during transmission and storage. Although chaotic maps have this property, they have limitations such as low Lyapunov exponents, low sensitivity and limited chaotic regions. The paper presents a new improved skewed tent map to address these problems. The improved skew tent map (ISTM) increases the sensitivity to initial conditions and control parameters. It has uniform distribution of output sequences. The programs for ISTM chaotic behavior were implemented in MATLAB R2023b. The novel ISTM produces a binary sequence, with high degree of complexity and good randomness properties. The performance of the ISTM generator shows effective s

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Publication Date
Fri Mar 31 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Formulation of Alpha Tocopherol Acetate as a Powder Dosage Form by Adsorption
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Alpha-tocopherol acetate is one of the most important vitamin E derivatives,that were used  as antioxidants. Adsorbents like kaolin, magnesium carbonate, and microcrystalline cellulose were used successfully to incorporate oily alpha-tocopherol acetate into an acceptable powder dosage form. The results revealed that microcrystalline cellulose as an adsorbents gave the best results with 50% loading capacity at time, 8 minutes before and after incubation period (3 months at 30C°), while kaolin and magnesium carbonate have been shown a significant difference before and after incubation. Addition of 1% w/w magnesium carbonate to the kaolin enhanced the loading capacity by decreasing the time of adsorption from 20 to 6 minutes and 47

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Publication Date
Mon Jan 01 2024
Journal Name
Route Educational And Social Science Journal
SCAPEGOATS OF THE MARSH: A POLITICAL READING OF SEAMUS HEANEY’S BOG POEMS
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Publication Date
Wed Jan 01 2020
Journal Name
Indian Journal Of Forensic Medicine And Toxicology
Color stability of different aesthetic resin composite materials: A digital image analysis
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Publication Date
Wed Sep 01 2021
Journal Name
Expert Systems With Applications
A long short-term recurrent spatial-temporal fusion for myoelectric pattern recognition
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Publication Date
Mon Oct 30 2023
Journal Name
Traitement Du Signal
A Comprehensive Review on Machine Learning Approaches for Enhancing Human Speech Recognition
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Publication Date
Sun Mar 31 2024
Journal Name
Iraqi Geological Journal
Exploring the Impact of Petrophysical Uncertainties on Recoverable Reserves: A Case Study
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Reliable estimation of critical parameters such as hydrocarbon pore volume, water saturation, and recovery factor are essential for accurate reserve assessment. The inherent uncertainties associated with these parameters encompass a reasonable range of estimated recoverable volumes for single accumulations or projects. Incorporating this uncertainty range allows for a comprehensive understanding of potential outcomes and associated risks. In this study, we focus on the oil field located in the northern part of Iraq and employ a Monte Carlo based petrophysical uncertainty modeling approach. This method systematically considers various sources of error and utilizes effective interpretation techniques. Leveraging the current state of a

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Publication Date
Wed May 10 2023
Journal Name
Diagnostics
A Deep Feature Fusion of Improved Suspected Keratoconus Detection with Deep Learning
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Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

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Publication Date
Thu Sep 30 2004
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
A Simple Method for Studying Crushability and Grindability of Rocks and Minerals
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