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Lactic acid-based deep eutectic solvents and activated carbon for soap removal from crude biodiesel
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Publication Date
Thu Dec 01 2022
Journal Name
Iaes International Journal Of Artificial Intelligence
Reduced hardware requirements of deep neural network for breast cancer diagnosis
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Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

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Publication Date
Wed Mar 15 2023
Journal Name
International Journal Of Advances In Intelligent Informatics
An automatic lip reading for short sentences using deep learning nets
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One study whose importance has significantly grown in recent years is lip-reading, particularly with the widespread of using deep learning techniques. Lip reading is essential for speech recognition in noisy environments or for those with hearing impairments. It refers to recognizing spoken sentences using visual information acquired from lip movements. Also, the lip area, especially for males, suffers from several problems, such as the mouth area containing the mustache and beard, which may cover the lip area. This paper proposes an automatic lip-reading system to recognize and classify short English sentences spoken by speakers using deep learning networks. The input video extracts frames and each frame is passed to the Viola-Jone

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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
Mon Jan 01 2024
Journal Name
Fusion: Practice And Applications
Proposed Framework for Semantic Segmentation of Aerial Hyperspectral Images Using Deep Learning and SVM Approach
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Publication Date
Wed Apr 12 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Science
Synthesis and Characterization New Schiff Bases, Pyrazole and Pyrazoline Compounds Derived From Acid Hydrazide Containing Isoxazoline Ring
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The work involves synthesis of new Schiff bases ([V] a, b and [VI] a, b), pyrazoles [VII] a, b and pyrazolines [VIII] a, b derivatives containing isoxazoline unit starting with chalcones. 4-bromoacetophenone was reacted with 4-hydroxybenzaldehyde or 4-hydroxyacetophenone was reacted with 4-bromobenzaldehyde in basic medium to give chalcone by Claisen-Schemidt reaction. The chalcons [I] a, b was reacted with hydroxylamine hydrochloride to form isoxazolines [II] a, b. which were reacted with ethyl chloro acetate in basic medium to get ester compounds [III] a, b. The condensation new ester [III] a, b with hydrazine hydrate80% yieldedacid hydrazide [IV] a, b. The later compound refluxing with 4-substituted benzaldehyde in dry benzene to give Sc

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Publication Date
Sat Jul 01 2023
Journal Name
Aip Conf. Proc. 2290
Synthesis, characterization and antimicrobial studies of mixed ligand from phthalic acid and 1,10-phenanthroline with their complexes
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In the present work, the phthalic acid (phthH2) and 1.10 phenonthroline (phen), and their complexes were synthesized and isolated as [M(phth)(phen)2], Mn(II), Fe(II), Co(II), Ni(II) Cu(II), Zn(II), and Cd(II) ions. These complexes were characterized by elemental analysis, melting point, conductivity, percentage metal, UV–Vis, FT-IR, and magnetic moment measurements. The molar conductance indicates that all the metal complexes in DMSO are nonelectrolytic. phthalic acid (phtha), and 1,10-Phenanthroline (phen), behaved as bidentate, coordinating to the metal ion through their two oxygen and two pyridinyl nitrogen atoms respectively, as corroborated by. Electronic spectra, FTIR, spectroscopy amusement indicated that all the metal complexes ad

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Publication Date
Wed Sep 01 2021
Journal Name
Iraqi Journal Of Physics
Enhancement of Photoconductive Detector Based on Carbon Nanotubes Decorated with Silver Nanoparticles by Adding Conductive Polymer
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In this work, wide band range photo detector operating in UV, Visible and IR was fabricated using carbon nanotubes (MWCNTs, SWCNTs) decorated with silver nanoparticles (Ag NPs). Silicon was used as a substrate to deposited CNTs/Ag NPs by the drop casting technique. Polyamide nylon polymer was used to coat CNTs/Ag NPs to enhance the photo-response of the detector. The electro-exploding wire technology was used to synthesize Ag NPs. Good dispersion of silver NPs achieved by a simple chemistry process on the surface of CNTs. The optical, structure and electrical characteristic of CNTs decorated with Ag NPs were characterized by X-Ray diffraction and Field Emission Scanning Electron Microscopy.  X-ray diffra

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Publication Date
Tue Jan 01 2019
Journal Name
Desalination And Water Treatment
Xylenol orange removal from aqueous solution by natural bauxite (BXT) and BXT-HDTMA: kinetic, thermodynamic and isotherm modeling
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Publication Date
Tue Jan 01 2019
Journal Name
Desalination And Water Treatment
Xylenol orange removal from aqueous solution by natural bauxite (BXT) and BXT-HDTMA: kinetic, thermodynamic and isotherm modeling
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Publication Date
Fri Mar 08 2019
Journal Name
Desalination And Water Treatment
Xylenol orange removal from aqueous solution by natural bauxite (BXT) and BXT-HDTMA: kinetic, thermodynamic and isotherm modeling
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Sorption is a key factor in removal of organic and inorganic contaminants from their aqueous solutions. In this study, we investigated the removal of Xylenol Orange tetrasodium salt (XOTS) from its aqueous solution by Bauxite (BXT) and cationic surfactant hexadecyltrimethyl ammonium bromide modified Bauxite (BXT-HDTMA) in batch experiments. The BXT and BXT-HDTMA were characterized using FTIR, and SEM techniques. Adsorption studies were performed at various parameters i.e. temperature, contact time, adsorbent weight, and pH. The modified BXT showed better maximum removal efficiency (98.6% at pH = 9.03) compared to natural Bauxite (75% at pH 2.27), suggesting that BXT-HDTMA is an excellent adsorbent for the removal of XOTS from water. The equ

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