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A Modified Symmetric Key Fully Homomorphic Encryption Scheme Based on Read-Muller Code
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Homomorphic encryption became popular and powerful cryptographic primitive for various cloud computing applications. In the recent decades several developments has been made. Few schemes based on coding theory have been proposed but none of them support unlimited operations with security.   We propose a modified Reed-Muller Code based symmetric key fully homomorphic encryption to improve its security by using message expansion technique. Message expansion with prepended random fixed length string provides one-to-many mapping between message and codeword, thus one-to many mapping between plaintext and ciphertext. The proposed scheme supports both (MOD 2) additive and multiplication operations unlimitedly.   We make an effort to prove the security of the scheme under indistinguishability under chosen-plaintext attack (IND-CPA) through a game-based security proof. The security proof gives a mathematical analysis and its complexity of hardness. Also, it presents security analysis against all the known attacks with respect to the message expansion and homomorphic operations.

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Publication Date
Tue Mar 01 2016
Journal Name
Journal Of Engineering
The Catalytic Activity of Modified Zeolite Lanthanum on the Catalytic Cracking of Al-Duara Atmospheric Distillation Residue.
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Atmospheric residue fluid catalytic cracking was selected as a probe reaction to test the catalytic performance of modified NaY zeolites and prepared NaY zeolites. Modified NaY zeolites have been synthesized by simple ion exchange methods. Three samples of modified zeolite Y have been obtained by replacing the sodium ions in the original sample with lanthanum and the weight percent added are 0.28, 0.53, and 1.02 respectively. The effects of addition of lanthanum to zeolite Y in different weight percent on the cracking catalysts were investigated using an experimental laboratory plant scale of fluidized bed reactor.

The experiments have been performed with weight hourly space velocity (WHSV) range of 6 to 24 h

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Publication Date
Thu Jun 02 2011
Journal Name
Ibn Al-haithem Journal For Pure And Applied Sciences
On modified pr-test double stage shrinkage estimators for estimate the parameters of simple linear regression model
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Publication Date
Fri Mar 01 2024
Journal Name
Construction And Building Materials
Uni- and tri-axial tests and property characterization for thermomechanical effect on hydrated lime modified asphalt concrete
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Permanent deformation, fatigue and thermal cracking are the three typical distresses of flexible pavement. Using hydrated lime (HL) into the conventional limestone mineral additive has been widely practiced, including in Europe, to improve the mechanical properties of hot mix asphalt (HMA) concrete and as the result the durability of the constructed pavement. Large number of experimental studies have been reported to find the optimum addition of HL for the improvement on HMA concrete mechanical properties, moisture susceptibility and fatigue resistance. Pavement in service is under complex thermomechanical stress-strain conditions due to coupled atmospheric and surrounding environment temperature variation and the traffic loading. To predic

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Publication Date
Sat Jun 01 2019
Journal Name
2019 International Symposium On Networks, Computers And Communications (isncc)
An Interference Mitigation Scheme for Millimetre Wave Heterogeneous Cloud Radio Access Network with Dynamic RRH Clustering
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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
Dual-Layer Compressive Sensing Scheme Incorporating Adaptive Cross Approximation Algorithm for Solving Monostatic Electromagnetic Scattering Problems
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Publication Date
Sun Jan 20 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Text Classification Based on Weighted Extreme Learning Machine
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The huge amount of documents in the internet led to the rapid need of text classification (TC). TC is used to organize these text documents. In this research paper, a new model is based on Extreme Machine learning (EML) is used. The proposed model consists of many phases including: preprocessing, feature extraction, Multiple Linear Regression (MLR) and ELM. The basic idea of the proposed model is built upon the calculation of feature weights by using MLR. These feature weights with the extracted features introduced as an input to the ELM that produced weighted Extreme Learning Machine (WELM). The results showed   a great competence of the proposed WELM compared to the ELM. 

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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Engineering
GNSS Baseline Configuration Based on First Order Design
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The quality of Global Navigation Satellite Systems (GNSS) networks are considerably influenced by the configuration of the observed baselines. Where, this study aims to find an optimal configuration for GNSS baselines in terms of the number and distribution  of baselines to improve the quality criteria of the GNSS networks. First order design problem (FOD) was applied in this research to optimize GNSS network baselines configuration, and based on sequential adjustment method to solve its objective functions.

FOD for optimum precision (FOD-p) was the proposed model which based on the design criteria of A-optimality and E-optimality. These design criteria were selected as objective functions of precision, whic

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Publication Date
Sat Jun 26 2021
Journal Name
2021 Ieee International Conference On Automatic Control & Intelligent Systems (i2cacis)
Vulnerability Assessment on Ethereum Based Smart Contract Applications
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Publication Date
Thu Aug 01 2019
Journal Name
2019 2nd International Conference On Engineering Technology And Its Applications (iiceta)
Human Gait Identification System Based on Average Silhouette
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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Physics: Conference Series
Improve topic modeling algorithms based on Twitter hashtags
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Abstract<p>Today with increase using social media, a lot of researchers have interested in topic extraction from Twitter. Twitter is an unstructured short text and messy that it is critical to find topics from tweets. While topic modeling algorithms such as Latent Semantic Analysis (LSA) and Latent Dirichlet Allocation (LDA) are originally designed to derive topics from large documents such as articles, and books. They are often less efficient when applied to short text content like Twitter. Luckily, Twitter has many features that represent the interaction between users. Tweets have rich user-generated hashtags as keywords. In this paper, we exploit the hashtags feature to improve topics learned</p> ... Show More
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