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Implementation of new Secure Mechanism for Data Deduplication in Hybrid Cloud
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Cloud computing provides huge amount of area for storage of the data, but with an increase of number of users and size of their data, cloud storage environment faces earnest problem such as saving storage space, managing this large data, security and privacy of data. To save space in cloud storage one of the important methods is data deduplication, it is one of the compression technique that allows only one copy of the data to be saved and eliminate the extra copies. To offer security and privacy of the sensitive data while supporting the deduplication, In this work attacks that exploit the hybrid cloud deduplication have been identified, allowing an attacker to gain access to the files of other users based on very small hash signatures of these files. More specifically, an attacker who knows the hash signature of a file can convince the storage service that he/she owns that file, hence the server lets the attacker to download the entire file. To overcome such attacks,the hash signature is encrypted with the user password. As a proof of concept a prototype of the proposed authorized deduplicate is implemented and conducted the test bed experiments using the prototype. Performance measurements indicate that the proposed Deduplication system incurs minimal overhead in the context of uploading, bandwidth compared to native deduplication.

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Advanced Intelligent Data Hiding Using Video Stego and Convolutional Neural Networks
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Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,

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Publication Date
Wed Jan 01 2014
Journal Name
Proceedings Of The Aintec 2014 On Asian Internet Engineering Conference - Aintec '14
LTE Peak Data Rate Estimation Using Modified alpha-Shannon Capacity Formula
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Publication Date
Sat Mar 01 2008
Journal Name
Iraqi Journal Of Physics
Comparison between Different Data Image Compression Techniques Applied on SAR Images
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In this paper, image compression technique is presented based on the Zonal transform method. The DCT, Walsh, and Hadamard transform techniques are also implements. These different transforms are applied on SAR images using Different block size. The effects of implementing these different transforms are investigated. The main shortcoming associated with this radar imagery system is the presence of the speckle noise, which affected the compression results.

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Publication Date
Sun Jan 06 2013
Journal Name
Chemical And Process Engineering Research
Milled Iraqi phoenix dactylifera data palm pruning woods lignin qualitative determination
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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
A multivariate Bayesian model using Gibbs sampler with real data application
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In many scientific fields, Bayesian models are commonly used in recent research. This research presents a new Bayesian model for estimating parameters and forecasting using the Gibbs sampler algorithm. Posterior distributions are generated using the inverse gamma distribution and the multivariate normal distribution as prior distributions. The new method was used to investigate and summaries Bayesian statistics' posterior distribution. The theory and derivation of the posterior distribution are explained in detail in this paper. The proposed approach is applied to three simulation datasets of 100, 300, and 500 sample sizes. Also, the procedure was extended to the real dataset called the rock intensity dataset. The actual dataset is collecte

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Publication Date
Tue Mar 01 2022
Journal Name
Asian Journal Of Applied Sciences
Comparison between Expert Systems, Machine Learning, and Big Data: An Overview
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Today, the science of artificial intelligence has become one of the most important sciences in creating intelligent computer programs that simulate the human mind. The goal of artificial intelligence in the medical field is to assist doctors and health care workers in diagnosing diseases and clinical treatment, reducing the rate of medical error, and saving lives of citizens. The main and widely used technologies are expert systems, machine learning and big data. In the article, a brief overview of the three mentioned techniques will be provided to make it easier for readers to understand these techniques and their importance.

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Pharmaceutical Research
Synthesis, characterization and bioactivity study of mixed-lig and complexes with some metal ions for new dithiocarbamate,3-aminophenol
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Publication Date
Fri Nov 11 2011
Journal Name
Thesis
Performance Analysis of a New Compact Magneto-Rheological Proportional Control Valve for Hydraulic Actuation Using FEM and Experimental Approach
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One of the main parts in hydraulic system is directional control valve, which is needed in order to operate hydraulic actuator. Practically, a conventional directional control valve has complex construction and moving parts, such as spool. Alternatively, a proposed Magneto-rheological (MR) directional control valve can offer a better solution without any moving parts by means of MR fluid. MR fluid consists of stable suspension of micro-sized magnetic particles dispersed in carrier medium like hydrocarbon oil. The main objectives of this present research are to design a MR directional control valve using MR fluid, to analyse its magnetic circuit using FEMM software, and to study and simulate the performance of this valve. In this research, a

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Publication Date
Mon Dec 24 2018
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
FAUNISTIC REVIEW OF THE GENUS CHAITOPHORUS KOCH, 1854 (APHIDIDAE, CHAITOPHORINAE, CHAITOPHORINI) WITH NEW RECORD SPECIES FOR IRAQ APHID FAUNA
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    A faunistic review of the genus Chaitophorus Koch, 1854, including four species in Iraq is given; the distribution data of each species and their hosts have been recorded. In this investigation the poplar leaf aphid Ch. populialbae (Boyer de Fonscolombe, 1841) is recorded here for the first time in Iraq on popular trees Populus euphratica Oliv. during the period from November 2016 to April 2017 in Baghdad province.

 

    A brief description for apterous viviparous female of this species is given; and a  key to the species of the genus Chaitophorus is constricted.

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Publication Date
Fri Jun 01 2018
Journal Name
Nano Hybrids And Composites
OLED Hybrid Light Emitting Devices with ZnS QDs, TPBi and Alq3 Electron Transport Layers
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Semiconductor quantum dots (QDs) have attracted tremendous attentions for their unique characteristics for solid-state lighting and thin-film display applications. A simple chemical method was used to synthesis quantum dots (QDs) of zinc sulfide (ZnS) with low cost. The XRD) shows cubic phase of the prepared ZnS with an average particles size of (3-29) nm. In UV-Vis. spectra observed a large blue shift over 38 nm. The band gaps energy (Eg) was 3.8 eV and 3.37eV from the absorption and photoluminescence (PL) respectively which larger than the Eg for bulk. QDs-LED hybrid devices were fabricated using ITO/ PEDOT: PSS/ Poly-TPD/ ZnS-QDs/ with different electron transport layers and cathode of LiF/Al layers. The EL spectrum reveals a bro

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