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Development of Robust and Efficient Symmetric Random Keys Model based on the Latin Square Matrix
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Symmetric cryptography forms the backbone of secure data communication and storage by relying on the strength and randomness of cryptographic keys. This increases complexity, enhances cryptographic systems' overall robustness, and is immune to various attacks. The present work proposes a hybrid model based on the Latin square matrix (LSM) and subtractive random number generator (SRNG) algorithms for producing random keys. The hybrid model enhances the security of the cipher key against different attacks and increases the degree of diffusion. Different key lengths can also be generated based on the algorithm without compromising security. It comprises two phases. The first phase generates a seed value that depends on producing a randomly predefined set of key numbers of size n via the Donald E. Knuths SRNG algorithm (subtractive method). The second phase uses the output key (or seed value) from the previous phase as input to the Latin square matrix (LSM) to formulate a new key randomly. To increase the complexity of the generated key, another new random key of the same length that fulfills Shannon’s principle of confusion and diffusion properties is XORed. Four test keys for each 128, 192,256,512, and 1024–bit length are used to evaluate the strength of the proposed model. The experimental results and security analyses revealed that all test keys met the statistical National Institute of Standards (NIST) standards and had high values for entropy values exceeding 0.98. The key length of the proposed model for n bits is 25*n, which is large enough to overcome brute-force attacks. Moreover, the generated keys are very sensitive to initial values, which increases the complexity against different attacks.

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Publication Date
Tue Apr 02 2019
Journal Name
Artificial Intelligence Research
A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder
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A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

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Publication Date
Tue Sep 01 2020
Journal Name
Journal Of Engineering
An Adaptive Digital Neural Network-Like-PID Control Law Design for Fuel Cell System Based on FPGA Technique
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This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH2) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue

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Publication Date
Sat Apr 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
The Effect of Vitamin B9 and E on the Yield and Its Components of the Wheat Crop
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Abstract<p>During the 2016–2017 and 2017–2018 winter semesters, researchers from the College of Agricultural Engineering Sciences at the University of Baghdad conducted a field experiment at the university’s research station. This inquiry set out to examine how spraying wheat plants with vitamins B9 (Folic acid) and E (Tocopherol) affected certain yield characteristics (Al-Fourat variety). The studies were set up as three repetitions of a factorial experiment using a Randomized Full Block Design. Vitamin E was sprayed at 0, 1, and 2 ml.L<sup>-1</sup>, while vitamin B9 was sprayed at 0, 1, and 3 ml.L<sup>-1</sup> (0, 250, and 500 mg. L<sup>-1</sup>). While the </p> ... Show More
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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Joint audit and its impact on the market value of firms listed on the Iraq Stock Exchange
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The research aims to investigate the possibility of joint auditing in improving the market value of Iraqi companies listed on the Iraq Stock Exchange. The sample was represented by 10 Iraqi companies listed in the Iraq market for the period from 2014-2017 (2 years before implementation and 2 years after implementation) and the research was based on the idea that joint auditing enhances investor confidence and raises their level of security as a result of providing quality and reliable reports, and thus This indicates good news in the market that reflects on the performance of stocks and the market value of companies that adopt joint auditing. The results of the analysis indicate an improvement in the market value, but this improv

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Publication Date
Sun Sep 06 2020
Journal Name
European Journal Of Dental Education
Evaluation of technology‐based learning by dental students during the pandemic outbreak of coronavirus disease 2019
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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Improvement of the Fault Tolerance in IoT Based Positioning Systems by Applying for Redundancy in the Controller Layer
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In recent years, the positioning applications of Internet-of-Things (IoT) based systems have grown increasingly popular, and are found to be useful in tracking the daily activities of children, the elderly and vehicle tracking. It can be argued that the data obtained from GPS based systems may contain error, hence taking these factors into account, the proposed method for this study is based on the application of IoT-based positioning and the replacement of using IoT instead of GPS.  This cannot, however, be a reason for not using the GPS, and in order to enhance the reliability, a parallel combination of the modern system and traditional methods simultaneously can be applied. Although GPS signals can only be accessed in open spaces, GP

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Publication Date
Sun Mar 30 2025
Journal Name
Wasit Journal For Pure Sciences
Histological study of testis of golden hamster (Mesocricetus auratus) in different ages during   postnatal development
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The present study aimed to investigate the histology of the testis in golden hamster during 1, 28 and 60 day of old. Tissue  samples  were  processed,  sectioned  and  subjected  to  specific  stains  to  reveal histological  details. Observation of one day old showed the testicle enclosed by undifferentiated thin layer of testicle capsule which consisted of undifferentiated myoblasts and fibroblasts small size seminiferous tubules appeared, one layer of spermatogonium cells (Type-A) which revealed mitotic figures, at 28 day old the capsule was consisted of thick outer fibromuscular layer and thick inner vascular layer that revealed encouraged blood vessels and cells, Spermatogonial cells type-A & B appeared as large

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Biological versus Topological Domains in Improving the Reliability of Evolutionary-Based Protein Complex Detection Algorithms
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     By definition, the detection of protein complexes that form protein-protein interaction networks (PPINs) is an NP-hard problem. Evolutionary algorithms (EAs), as global search methods, are proven in the literature to be more successful than greedy methods in detecting protein complexes. However, the design of most of these EA-based approaches relies on the topological information of the proteins in the PPIN. Biological information, as a key resource for molecular profiles, on the other hand, acquired a little interest in the design of the components in these EA-based methods. The main aim of this paper is to redesign two operators in the EA based on the functional domain rather than the graph topological domain. The perturb

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Publication Date
Thu Nov 02 2023
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Appraising the Role of Pharmacists in Medication Reconciliation at Hospital Discharge: A Field-Based Study
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Objective: To measure the effect of the pharmacist-led medication reconciliation service before hospital discharge on preventing potential medication errors. Methods: This behavioral interventional study took place in a public teaching hospital in Iraq between December 2022 and January 2023. It included inpatients who were taking four or more medications upon discharge from the internal medicine ward and the cardiac care unit. The researcher provided the patients with a medication reconciliation form and reconciliation form (including medication regimen and pharmacist instructions) before discharging them home. Any discrepancies between the patients’ understanding and the actual medication recommendations prescribed by the physici

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Publication Date
Sat Jun 01 2024
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
A novel fusion-based approach for the classification of packets in wireless body area networks
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This abstract focuses on the significance of wireless body area networks (WBANs) as a cutting-edge and self-governing technology, which has garnered substantial attention from researchers. The central challenge faced by WBANs revolves around upholding quality of service (QoS) within rapidly evolving sectors like healthcare. The intricate task of managing diverse traffic types with limited resources further compounds this challenge. Particularly in medical WBANs, the prioritization of vital data is crucial to ensure prompt delivery of critical information. Given the stringent requirements of these systems, any data loss or delays are untenable, necessitating the implementation of intelligent algorithms. These algorithms play a pivota

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