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Deep Bayesian for Opinion-target identification
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The use of deep learning.

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Publication Date
Sun Jun 06 2021
Journal Name
Materials
Strengthening of Continuous Reinforced Concrete Deep Beams with Large Openings Using CFRP Strips
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To accommodate utilities in buildings, different sizes of openings are provided in the web of reinforced concrete deep beams, which cause reductions in the beam strength and stiffness. This paper aims to investigate experimentally and numerically the effectiveness of using carbon fiber reinforced polymer (CFRP) strips, as a strengthening technique, to externally strengthen reinforced concrete continuous deep beams (RCCDBs) with large openings. The experimental work included testing three RCCDBs under five-point bending. A reference specimen was prepared without openings to explore the reductions in strength and stiffness after providing large openings. Openings were created symmetrically at the center of spans of the other specimens

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Behavior of Reinforced Concrete Deep Beams Strengthened with Carbon Fiber Reinforced Polymer Strips
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This research is concerned to investigate the behavior of reinforced concrete (RC) deep beams strengthened with carbon fiber reinforced polymer (CFRP) strips. The experimental part of this research is carried out by testing seven RC deep beams having the same dimensions and steel reinforcement which have been divided into two groups according to the strengthening schemes. Group one was consisted of three deep beams strengthened with vertical U-wrapped CFRP strips. While, Group two was consisted of three deep beams strengthened with inclined CFRP strips oriented by 45o with the longitudinal axis of the beam. The remaining beam is kept unstrengthening as a reference beam. For each group, the variable considered

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Publication Date
Wed Mar 08 2023
Journal Name
Sensors
A Critical Review of Remote Sensing Approaches and Deep Learning Techniques in Archaeology
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To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip

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Scopus (20)
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Publication Date
Mon Sep 30 2024
Journal Name
Medical Journal Of Babylon
Effectiveness of Deep Breathing Technique on Pain Level of School Children during Catheterization
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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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Scopus (39)
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Publication Date
Sun Jan 01 2017
Journal Name
World Journal Of Pharmaceutical Research
IDENTIFICATION OF SOME SPECIES OF WIREWORM AGRIOTES SPP. (COLEOPTERA: ELATERIDAE) IN BAGHDAD
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Publication Date
Mon Dec 13 2010
Journal Name
المجلة البيطرية العراقية
The isolation and identification of the important pathogenic bacteria from fresh meat
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This study was aimed to investigate the load of bacterial contaminant in fresh meat with different types of bacteria.One handered and seven samples were collected from different regions of Baghdad . These samples included 37 of fresh beef 70 of fresh sheep meat. All samples were cultured on different selective media to identitfy of contaminated bacteria .The result revealed that The percentage of bacterial isolate from raw sheep meat were, % 23.8of StreptococcusgroupD,29.4 % of Staphylococcus aureus ,14.7 % of E.coli , %4.9of Salmonella spp, ,%3.5 of pseudomonas aeruginosa, %14.7.%14.7 of Proteus spp.% 2.1 of Listeria spp while the raw beef meat content %5.55 of Staphylococcus aureus, %8.14 of streptococcus group D , %5.18 %1.85 of E.coli,

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Publication Date
Tue Sep 21 2021
Journal Name
Journal Of Healthcare Engineering
Complexity and Entropy Analysis to Improve Gender Identification from Emotional-Based EEGs
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Investigating gender differences based on emotional changes becomes essential to understand various human behaviors in our daily life. Ten students from the University of Vienna have been recruited by recording the electroencephalogram (EEG) dataset while watching four short emotional video clips (anger, happiness, sadness, and neutral) of audiovisual stimuli. In this study, conventional filter and wavelet (WT) denoising techniques were applied as a preprocessing stage and Hurst exponent

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Scopus (10)
Crossref (7)
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Publication Date
Wed Mar 16 2016
Journal Name
World Journal Of Pharmaceutical Research
Identification of some species of wireworm Agriotes spp.(Coleoptera: Elateridae) in Baghdad
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Publication Date
Sat May 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Isolation and Identification of Alkaline Protease Producing Aspergills niger from Iraqi Soils
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Abstract<p>Twenty purified isolates were obtained by using different soil sources, only twelve isolates belonging to Aspergillus genera depending on cultural and morphological characterization. The isolates were used as alkaline protease producer. The highest proteolytic, enzymatic activity (95.83U/ml) was obtained from <italic>Aspergillus</italic> sp. ZE isolate. This isolate was identified by 5.8 rRNA gene sequencing as <italic>Aspergills niger</italic> (accuracy of 99%), which was matched with the sequence of <italic>Aspergills niger</italic> strain GM775228 recorded in Gene bank under the ID: GM 775228.1.</p>
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