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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
Sat Mar 30 2024
Journal Name
مجلة نسق
Education Skills and Their Role in the Health and Psychological Development of the Child An Anthropological Study
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The study highlighted the transformation of value systems and educational patterns between past and present, especially with the introduction of modern variables and means, such as mobile phones, the internet, social media, and others. These factors have contributed both positively and negatively to the study. The study highlights the integral role of the school in collaboration with the family in guiding and educating children. It also emphasizes the active role of the school in developing students' abilities and skills, either attracting them to school or vice versa. This includes an examination of the essential skills required in education and their role in achieving a state of psychological well-being and systematically developing child

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Publication Date
Wed Apr 01 2020
Journal Name
Biochemical And Cellular Archives
POSSIBLE ROLE OF HCMV INFECTION ON THE DEVELOPMENT OF HPV POSITIVE CERVICAL CARCINOMA IN A GROUP OF IRAQI WOMEN
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The cervical cancer considered as the fourth female prevalent disease worldwide, it was once the most extensively recognized female cancer two in many low-income countries. Human Cytomegalovirus (HCMV) exhibits broader tropism and can cause infection in most of the human body organs. Although, human cytomegalovirus HCMV is not yet considered an oncogenic virus, there is increased evidences of HCMV infection implication in malignant diseases of different cancer types. The present study aims to evaluate the effect of CMV infection on the development of HPV16 positive cervical cancinoma. The current retrospective study enrolled a number of paraffinized cervical cancer tissues .included 30 cervical carcinomatous tissues and 10 biopsies from an

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Publication Date
Thu Nov 21 2019
Journal Name
Journal Of Engineering
A Neural Networks based Predictive Voltage-Tracking Controller Design for Proton Exchange Membrane Fuel Cell Model
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In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

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Publication Date
Sat Aug 08 2026
Journal Name
Scientific Reports
Enhancement of selecting the cluster head based on the voting mechanism and Elliptic Curve Cryptography for Wireless Sensor Networks (ECHVM)
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Abstract<p> The Wireless Sensor Networks (WSNs), which are deployed in harsh environments, are extremely susceptible to localized battery exhaustion as well as intelligent inside routing threats, especially sinkhole and data falsification attacks. In this paper, we present ECHVM (Enhanced Cluster Head selection by Voting and an ECC-based Blockchain Mechanism), a novel, secure, and energy-efficient routing framework to achieve an optimal trade-off between network security and hardware resource efficiency. We present the ECHVM protocol that combines Elliptic Curve Cryptography (ECC) with a lightweight, local distributed ledger to mitigate risks of centralized authority by tr</p> ... Show More
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Publication Date
Mon Sep 01 2014
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Suggested Model for accounting disclosure proactive and reflect on the decisions of investors: Applied research in a sample of industrial companies listed on the Iraq Stock Exchange
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Often requires the investor to know the result of the company's activity contribute to the investor or by wanting to invest in them because profit or loss of the company affect positively or negatively in the price of shares of the company and with the end of the fiscal year delayed companies often to issue its financial statements after it is approved and audited by an observer External Auditor, From here came the idea of ​​research that appears to stakeholders of financial statements proactive appear, including actual figures for earlier stages have been prepared lists about lists and planned by the administration reflect the results of its phase remainder of the year as if they are (half a year or season or month) to offer At the

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
A Comprehensive Review on Medical Image Steganography Based on LSB Technique and Potential Challenges
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The rapid development of telemedicine services and the requirements for exchanging medical information between physicians, consultants, and health institutions have made the protection of patients’ information an important priority for any future e-health system. The protection of medical information, including the cover (i.e. medical image), has a specificity that slightly differs from the requirements for protecting other information. It is necessary to preserve the cover greatly due to its importance on the reception side as medical staff use this information to provide a diagnosis to save a patient's life. If the cover is tampered with, this leads to failure in achieving the goal of telemedicine. Therefore, this work provides an in

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Publication Date
Tue Jan 31 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
Survey on intrusion detection system based on analysis concept drift: Status and future directions
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Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor

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Publication Date
Fri Oct 02 2026
Journal Name
Journal Of Physical Education
The Effect of Taking Amino Acids Associated with Muscle Strength Training On the Development of Some Physiological Indicators In Badminton Players
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The aim of the research was designing a nutritional program with amino acids well as designing exercises for muscular strength training for youth female badminton players. In addition to that the researcher aimed at identifying the effect of amino acid accompanied with muscular training on some physiological indicators in youth female badminton players. The researcher used the experimental method. The subjects were (7) youth female badminton players from the Armenian badminton club. Many physiological tests were conducted including PWC170 and Vo2Max. The data was collected and treated using proper statistical operations to conclude that amino acid accompanied with muscular ability training have a positive effect on some physiological indica

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Publication Date
Sun Apr 23 2017
Journal Name
International Conference Of Reliable Information And Communication Technology
Classification of Arabic Writer Based on Clustering Techniques
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Arabic text categorization for pattern recognitions is challenging. We propose for the first time a novel holistic method based on clustering for classifying Arabic writer. The categorization is accomplished stage-wise. Firstly, these document images are sectioned into lines, words, and characters. Secondly, their structural and statistical features are obtained from sectioned portions. Thirdly, F-Measure is used to evaluate the performance of the extracted features and their combination in different linkage methods for each distance measures and different numbers of groups. Finally, experiments are conducted on the standard KHATT dataset of Arabic handwritten text comprised of varying samples from 1000 writers. The results in the generatio

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Scopus
Publication Date
Sun Jun 01 2014
Journal Name
Baghdad Science Journal
Classification of fetal abnormalities based on CTG signal
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The fetal heart rate (FHR) signal processing based on Artificial Neural Networks (ANN),Fuzzy Logic (FL) and frequency domain Discrete Wavelet Transform(DWT) were analysis in order to perform automatic analysis using personal computers. Cardiotocography (CTG) is a primary biophysical method of fetal monitoring. The assessment of the printed CTG traces was based on the visual analysis of patterns that describing the variability of fetal heart rate signal. Fetal heart rate data of pregnant women with pregnancy between 38 and 40 weeks of gestation were studied. The first stage in the system was to convert the cardiotocograghy (CTG) tracing in to digital series so that the system can be analyzed ,while the second stage ,the FHR time series was t

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