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Generation of True Random TTL Signals for Quantum Key-Distribution Systems Based on True Random Binary Sequences
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A true random TTL pulse generator was implemented and investigated for quantum key distribution systems. The random TTL signals are generated by low cost components available in the local markets. The TTL signals are obtained by using true random binary sequences based on registering photon arrival time difference registered in coincidence windows between two single – photon detectors. The true random TTL pulse generator performance was tested by using time to digital converters which gives accurate readings for photon arrival time. The proposed true random pulse TTL generator can be used in any quantum -key distribution system for random operation of the transmitters for these systems

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Publication Date
Sat Nov 05 2022
Journal Name
Sensors
Enhancement of the CAST Block Algorithm Based on Novel S-Box for Image Encryption
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Background and Aim: due to the rapid growth of data communication and multimedia system applications, security becomes a critical issue in the communication and storage of images. This study aims to improve encryption and decryption for various types of images by decreasing time consumption and strengthening security. Methodology: An algorithm is proposed for encrypting images based on the Carlisle Adams and Stafford Tavares CAST block cipher algorithm with 3D and 2D logistic maps. A chaotic function that increases the randomness in the encrypted data and images, thereby breaking the relation sequence through the encryption procedure, is introduced. The time is decreased by using three secure and private S-Boxes rather than using si

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Hybrid CNN-based Recommendation System
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Recommendation systems are now being used to address the problem of excess information in several sectors such as entertainment, social networking, and e-commerce. Although conventional methods to recommendation systems have achieved significant success in providing item suggestions, they still face many challenges, including the cold start problem and data sparsity. Numerous recommendation models have been created in order to address these difficulties. Nevertheless, including user or item-specific information has the potential to enhance the performance of recommendations. The ConvFM model is a novel convolutional neural network architecture that combines the capabilities of deep learning for feature extraction with the effectiveness o

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
MAGNETO HYDRODYNAMIC NATURAL CONVECTION FLOW ON A VERTICAL CYLINDER WITH A PRESENCE OF HEAT GENERATION AND RADIATION
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The present work investigates the effect of magneto – hydrodynamic (MHD) laminar natural convection flow on a vertical cylinder in presence of heat generation and radiation. The governing equations which used are Continuity, Momentum and Energy equations. These equations are transformed to dimensionless equations using Vorticity-Stream Function method and the resulting nonlinear system
of partial differential equations are then solved numerically using finite difference approximation. A thermal boundary condition of a constant wall temperature is considered. A computer program (Fortran 90) was built to calculate the rate of heat transfer in terms of local Nusselt number, total mean Nusselt number, velocity distribution as well as te

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Cost technique based on ABCII specifications and its effect in the Implementation of contracting contracts: Applied research in Al-Mansour general company for construction contracting
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The problem of research was to identify after the use of cost technology based on specifications in the validity of determining and measuring the costs of the implementation of contracting, by applying to al-Mansour General Construction Contracting Company as an appropriate alternative to the traditional costing system currently adopted, which is characterized by many shortcomings and weaknesses Which has been reflected in the validity and integrity of the calculations. To solve this problem, the research was based on the premise that: (The application of cost technology based on specifications will result in calculating the cost of the product according to the specification required by the customer, to meet his wishes properly and witho

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Publication Date
Mon Dec 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
The Effect of importance in the Intellectual Capital On Internal control Systems Analytical Research in A sample of general inspectors’ offices in Iraq
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The research aims to know the influence of the intellectual capital on the internal control system in a sample of General Inspection Offices in Iraq. The research includes a sample of individuals who are working in these offices total sample (46) individuals distributed according to functional levels (General Inspector, Deputy Inspector General, and Director) , The data and information were collected by using questionnaire, which is done for this purpose, as well as personal interviews in order to reach to the results that achieve the aim of this research , Two hypotheses were formed , the first hypothesis consists of (4) secondary hypothesis , All these hypotheses were tested by using statistical tools such as (percentages, freq

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Estimation of Reliability through the Wiener Degradation Process Based on the Genetic Algorithm to Estimating Parameters
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      In this paper, the researcher suggested using the Genetic algorithm method to estimate the parameters of the Wiener degradation process,  where it is based on the Wiener process in order to estimate the reliability of high-efficiency products, due to the difficulty of estimating the reliability of them using traditional techniques that depend only on the failure times of products. Monte Carlo simulation has been applied for the purpose of proving the efficiency of the proposed method in estimating parameters; it was compared with the method of the maximum likelihood estimation. The results were that the Genetic algorithm method is the best based on the AMSE comparison criterion, then the reliab

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Publication Date
Tue Dec 02 2014
Journal Name
International Journal Of Innovative Science, Engineering & Technology
Structural and Optical Properties of Synthesized Manganese doped ZnS Quantum Dots
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ZnS:MnP2+P nanoparticles were prepared by a simple microwave irradiation method under mild condition. The starting materials for the synthesis of ZnS:MnP 2+P quantum dots were zinc acetate as zinc source, thioacetamide as a sulfur source, manganese chloride as manganese source (R & M Chemical) and ethylene glycol as a solvent. All chemicals were analytical grade products and used without further purification. The quantum dots of ZnS:MnP 2+P with cubic structure were characterized by X-ray powder diffraction (XRD), the morphology of the film is seen by scanning electron microscopy (SEM) also by field effect scanning electron microscopy (FESEM). The composition of the samples is analysed by EDS. UV-Visible absorption spectroscopy analysis

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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
Quantum Theory of Atom in Molecules Investigation Trinuclear Ruthenium: DFT Approach
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The topological indices of the "[(µ3-2, 5-dioxyocyclohexylidene)-bis ((2-hydrido)-nonacarbonyltriruthenium]” were studied within the quantum theory of atoms in the molecule (QTAIM), clusters are
analyzed using the density functional theory (DFT). The estimated topological variables accord with prior
descriptions of comparable transition metal complexes. The Quantum Theory of Atom, in molecules
investigation of the bridging core component, Ru3H2, revealed critical binding points (chemical bonding)
between Ru (1) and Ru (2) and Ru (3). Consequently, delocalization index for this non-bonding interaction
was calculated in the core of Ru3H2, the interaction is of the (5centre–5electron) class.

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Publication Date
Fri Sep 09 2022
Journal Name
Journal Of Ovonic Research
Confinement factor and carrier recombination of InGaAsP/InP quantum well lasers
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Low-dimensional materials have attracted significant attention in developing and enhancing the performance of quantum well lasers due to their extraordinary unique properties. The optical confinement factor is one of the most effective parameters for evaluating the optimal performance of a semiconductor laser diode when used to measure the optical gain and current threshold. The optical confinement factor and the radiative recombination of single quantum wells (SQW) and multi-quantum wells (MQW) for InGaAsP/InP have been theoretically studied using both radiative and Auger coefficients. Quantum well width, barrier width, and number of quantum wells were all looked at to see how these things changed the optical confinement factor and

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