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Implementation of a modified noise-free and noisy multistage quantum cryptography protocol using QISKIT
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Classical cryptography systems exhibit major vulnerabilities because of the rapid development of quan tum computing algorithms and devices. These vulnerabilities were mitigated utilizing quantum key distribution (QKD), which is based on a quantum no-cloning algorithm that assures the safe generation and transmission of the encryption keys. A quantum computing platform, named Qiskit, was utilized by many recent researchers to analyze the security of several QKD protocols, such as BB84 and B92. In this paper, we demonstrate the simulation and implementation of a modified multistage QKD protocol by Qiskit. The simulation and implementation studies were based on the “local_qasm” simulator and the “FakeVigo” backend, respectively. The suggested multistage QKD applies different random commutative sets of Euler’s angles to the transmitted qubits. If Eve successfully hacked the Euler’s angles of a transmitted qubit, Bob will predict the hacking event because other bits apply different Euler’s angles. The commutative sets of Euler’s angles should be selected by a prior agreement between Alice and Bob. Our approach provides additional security proof for the multistage QKD protocol enabling safe public sharing of a sifted key between the sender and receiver

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Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for</p> ... Show More
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Publication Date
Mon Oct 01 2018
Journal Name
Ieee Transactions On Network Science And Engineering
A Resource Allocation Mechanism for Cloud Radio Access Network Based on Cell Differentiation and Integration Concept
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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Proposal of Using Principle of Maximizing Entropy of Generalized Gamma Distribution to Estimate the Survival probabilities of the
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Abstract

In this research we been estimated the survival function for data suffer from the disturbances and confusion of  Iraq Household Socio-Economic Survey: IHSES II 2012 , to data from a five-year age groups follow the distribution of the Generalized Gamma: GG. It had been used two methods for the purposes of estimating and fitting which is the way the Principle of Maximizing Entropy: POME, and method of booting to nonparametric smoothing function for Kernel, to overcome the mathematical problems plaguing integrals contained in this distribution in particular of the integration of the incomplete gamma function, along with the use of traditional way in which is the Maximum Likelihood: ML. Where the comparison on t

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Publication Date
Sun May 01 2022
Journal Name
Journal Of Engineering
Parametric Study of a Two-Phase Closed Thermosyphon Loop
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A theoretical and experimental investigation was carried out to study the behavior of a two-phase closed thermosyphon loop (TPCTL) during steady-state operation using different working fluids. Three working fluids were investigated, i.e., distilled water, methanol, and ethanol. The TPCTL was constructed from an evaporator, condenser, and two pipelines (riser and downcomer). The driving force is the difference in pressure between the evaporator and condenser sections and the fluid returns to the heating section by gravity. In this study, the significant parameters used in the experiments were filling ratios (FR%) of 50%, 75%, and 100% and heat-input range at the evaporator section of 215-860.2 W. When the loop reached to

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Publication Date
Tue Jun 01 2010
Journal Name
Journal Of Economics And Administrative Sciences
Bayes Estimator as a Function of Some Classical Estimator
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Maximum likelihood estimation method, uniformly minimum variance unbiased estimation method and minimum mean square error estimation, as classical estimation procedures, are frequently used for parameter estimation in statistics, which assuming the parameter is constant , while Bayes method assuming the parameter is random variable and hence the Bayes estimator is an estimator which minimize the Bayes risk for each value the random observable and for square error lose function the Bayes estimator is the posterior mean. It is well known that the Bayesian estimation is hardly used as a parameter estimation technique due to some difficulties to finding a prior distribution.

The interest of this paper is that

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Publication Date
Mon Jan 01 2024
Journal Name
Tropical Journal Of Natural Product Research
Cytotoxic Potential of Neem (Azadirachta indica A. Juss) Oil
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An increasing interest is emerging in identifying natural products to overcome drug resistance in cancer patients. In this context, the present study was conducted to investigate the cytotoxic effects of neem plant (Azadirachta indica) oil in three different biological models (breast cancer cell lines, Allium cepa root tip, and mice vital organs). The cytotoxic potential of the neem oil was evaluated with two human cell lines (MCF7 and MDA-MB231) and an Allum cepa root tip bioassay. Histopathological analysis was conducted on the neem oil-treated and untreated control mice. The results revealed an anti-proliferative effect for neem oil on both estrogen receptor-positive (MCF7) and estrogen receptor-negative (MDA-MB231) breast cancer cell li

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Publication Date
Tue Mar 01 2022
Journal Name
Bulletin Of The Australian Mathematical Society
A DYNAMICAL STUDY OF SALINE PLUMES IN DESALINATION OUTFALLS
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Publication Date
Sun Jul 01 2001
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
HAEMATOZO`A OF THE AVIAN FAMILY PHASIANIDAE IN IRAQ
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A collection of 118 specimens of Iraqi phasianid birds belong to four species was examined
for haematozoa. Results show that 21.2% of them were infected with one or more of four
species of blood parasites; Haemoproteus danilewskyi, H. santosdiasi, Plasmodium sp. and
microfilaria. Haemoproteus danilewskyi is reported here for the first time in Iraq.

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Publication Date
Sat Oct 27 2018
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
A NEW SPECIES OF CARABIDAE (NSECTA: COLEOPTERA) FROM IRAQ
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Aniera desert/cola was found new to science and to the Iraqi fauna. The description was
mainly based on external features and male genit

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Publication Date
Fri Jul 25 2025
Journal Name
Alustath Journal For Human And Social Sciences
Efforts of Modern Arabs in Neurolinguistics, a cognitive approach
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Neurolinguistics is a new science, which studies the close relationship between language and neuroscience, and this new interdisciplinary field confirms the functional integration between language and the nervous system, that is, the movement of linguistic information in the brain in receiving, acquiring and producing to achieve linguistic communication; Because language is in fact a mental process that takes place only through the nervous system, and this research shows the benefit of each of these two fields to the other, and this science includes important topics, including: language acquisition, the linguistic abilities of the two hemispheres of the brain, the linguistic responsibility of the brain centers, and the time limit for langua

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