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Density distributions, form factors and reaction cross sections for exotic 11Be and 15C nuclei
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The ground state proton, neutron and matter densities of exotic 11Be and 15C nuclei are studied by means of the TFSM and BCM. In TFSM, the calculations are based on using different model spaces for the core and the valence (halo) neutron. Besides single particle harmonic oscillator wave functions are employed with two different size parameters  Bc and Bv.  In BCM, the halo nucleus is considered as a composite projectile consisting of core and valence clusters bounded in a state of relative motion. The internal densities of the clusters are described by single particle Gaussian wave functions.

 Elastic electron scattering proton form factors for these exotic nuclei are analyzed via the plane wave born approximation (PWBA). As the calculations in the BCM do not distinguish between protons and neutrons, the calculations of the proton form factors are restricted only by the TFSM.

The reaction cross sections for these exotic nuclei are studied by means of the Glauber model with an optical limit approximation using the ground state densities of the projectile and target, where these densities are described by single Gaussian functions. The calculated reaction cross sections at high energy are in agreement with the experimental data.

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Publication Date
Wed Oct 12 2022
Journal Name
Axioms
Razy: A String Matching Algorithm for Automatic Analysis of Pathological Reports
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Pathology reports are necessary for specialists to make an appropriate diagnosis of diseases in general and blood diseases in particular. Therefore, specialists check blood cells and other blood details. Thus, to diagnose a disease, specialists must analyze the factors of the patient’s blood and medical history. Generally, doctors have tended to use intelligent agents to help them with CBC analysis. However, these agents need analytical tools to extract the parameters (CBC parameters) employed in the prediction of the development of life-threatening bacteremia and offer prognostic data. Therefore, this paper proposes an enhancement to the Rabin–Karp algorithm and then mixes it with the fuzzy ratio to make this algorithm suitable

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Publication Date
Sat Jan 01 2022
Journal Name
Proceeding Of The 1st International Conference On Advanced Research In Pure And Applied Science (icarpas2021): Third Annual Conference Of Al-muthanna University/college Of Science
Efficient approach for solving high order (2+1)D-differential equation
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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Perceptually Important Points-Based Data Aggregation Method for Wireless Sensor Networks
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The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the

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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
An Effective Hybrid Deep Neural Network for Arabic Fake News Detection
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Recently, the phenomenon of the spread of fake news or misinformation in most fields has taken on a wide resonance in societies. Combating this phenomenon and detecting misleading information manually is rather boring, takes a long time, and impractical. It is therefore necessary to rely on the fields of artificial intelligence to solve this problem. As such, this study aims to use deep learning techniques to detect Arabic fake news based on Arabic dataset called the AraNews dataset. This dataset contains news articles covering multiple fields such as politics, economy, culture, sports and others. A Hybrid Deep Neural Network has been proposed to improve accuracy. This network focuses on the properties of both the Text-Convolution Neural

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Publication Date
Fri May 03 2024
Journal Name
Journal Of Optics
Transmission Of 10 Gb/s For Underwater Optical Wireless Communication System
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Publication Date
Mon Jan 01 2024
Journal Name
Recent Research On Geotechnical Engineering, Remote Sensing, Geophysics And Earthquake Seismology
Evaluating the Accuracy of iPhone Lidar Sensor for Building Façades Conservation
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Publication Date
Mon Jul 15 2019
Journal Name
Iet Microwaves, Antennas & Propagation
Hilbert metamaterial printed antenna based on organic substrates for energy harvesting
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Abstract In this study, an investigation is conducted to realise the possibility of organic materials use in radio frequency (RF) electronics for RF-energy harvesting. Iraqi palm tree remnants mixed with nickel oxide nanoparticles hosted in polyethylene, INP substrates, is proposed for this study. Moreover, a metamaterial (MTM) antenna is printed on the created INP substrate of 0.8 mm thickness using silver nanoparticles conductive ink. The fabricated antenna performances are instigated numerically than validated experimentally in terms of S11 spectra and radiation patterns. It is found that the proposed antenna shows an ultra-wide band matching bandwidth to cover the frequencies from 2.4 to 10 GHz with bore-sight gain variation from 2.2 to

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet-Based Feature Extraction for Cassava Classification: A Machine Learning Approach
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Cassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has

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Publication Date
Tue Dec 11 2018
Journal Name
Baghdad Science Journal
Study of Cytotoxic Effect of Aqueous Extract Fenugreek(Trigonella Foenum Graecum L.S) Seeds and The New Complexes of Rh (?) and Pd (?) on Cancer Cell Lines
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The effect of the aqueous extract of fenugreek seeds (Trigonella Foenum Graecum L.), Rhodium complex (?) with formula [RhL2CLH2O].1 1/2 ETOH and palladium (?) [pdl2].2ETOH,where L=2-hydroxy phenyl piperonalidine was studied on two cancer cell lines. The first cell line was intestine cancer of female albino mice (L20B), the second one was Rhabdomysarcomas (RD)cell line in human. The activity of the new complexes and the aqueous extract was compared to the well-known anticancer drug (cis-platin) by utilizing the in vitro system. The cell lines were treated with four concentrations of cis-platin 31.25,62.5,125 and 250 ?g/ml for 72 hour exposure time. The same concentrations were used with extract and the new complexes. This study showed that t

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Publication Date
Mon Aug 25 2014
Journal Name
Biology
Vesicular Trafficking Defects, Developmental Abnormalities, and Alterations in the Cellular Death Process Occur in Cell Lines that Over-Express Dictyostelium GTPase, Rab2, and Rab2 Mutants
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