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Prestressing Effects on Full Scale Deep Beams with Large Web Openings¨: An Experimental and Numerical Study
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Most studies on deep beams have been made with reinforced concrete deep beams, only a few studies investigate the response of prestressed deep beams, while, to the best of our knowledge, there is not a study that investigates the response of full scale (T-section) prestressed deep beams with large web openings. An experimental and numerical study was conducted in order to investigate the shear strength of ordinary reinforced and partially prestressed full scale (T-section) deep beams that contain large web openings in order to investigate the prestressing existence effects on the deep beam responses and to better understand the effects of prestressing locations and opening depth to beam depth ratio on the deep beam performance and behavior. A total of seven deep beam specimens with identical shear span-to-depth ratio, compressive strength of concrete, and amount of horizontal and vertical web reinforcement ratios have been tested under mid-span concentrated load applied monotonically until failure. The main variables studied were the effects of depth of the web openings and the prestressing location on deep beam performance. The test results showed that the enlargement in the size of web openings substantially reduces the element’s shear capacities while prestressing strands location above the web openings has more effect at increasing the element’s shear capacities. The numerical study considered three-dimensional finite element models that have been developed in Abaqus software to simulate and predict the performance of prestressed deep beams. The results of numerical simulations were in good agreement with the experimental ones.

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Publication Date
Fri Oct 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Reflection the organizational Ambidexterity on organizational excellence An exploratory study at the Iraqi Cotton Industries Company
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Organizations of various activities strive to excel and continue in light of the challenges they face, so they seek to have leaders and workers in them for the ingenuity that is reflected in their excellence in work and achievement that is achieved through the adoption of the best modern technological technologies to reach Organizations to the best levels and thus achieve their goals easily and successfully.  The research aims are to know the correlation and impact between organizational proficiency and the dimensions of Organizations excellence (leadership excellence, and distinguish subordinates and excellence in organizational structure) at the Cotton Industries Company through the adoption of a unit of measurement which

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Measuring the impact of the financial value of human resources on investor decisions: (An Empirical Study)
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The aim of the research is to clarify the measurement of the impact regarding financial value of human resources on investors' decisions by considering that the human element is one of the assets of the company. Therefore, a set of criteria must be available to determine the applicability of these standards in the human resource because it has an effective role in the success for the company. Is to measure the value of human resources in a financial format according to the first two methods depends on the value and the second depends on the cost.

In order to achieve the objectives of the study, a questionnaire was designed to survey the views of a number of employees of the General Company for Leather Industries in order to arriv

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Publication Date
Tue May 30 2017
Journal Name
Environmental Earth Sciences
Purification of aqueous solutions from Pb(II) by natural bentonite: an empirical study on chemical adsorption
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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
An Environmental Study of Epiphytic Algae on Ceratophyllum demersum in Tigris River within Baghdad City, Iraq
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The present study was conducted in the Tigris River within Baghdad (University of Baghdad campus). The study included some physicochemical parameters and qualitative of epiphytic algae on the host plant (Ceratophyllum demersum) during summer season 2013. The results revealed that the study area was alkaline, hard and oxygenated water. A total of 105 taxa of epiphytic algae was identified. Bacillariophyceae diatoms composed 44.7% of the total and were represented by 42.4% of the order Pennales and 1.9 %of the order Centrales. Chlorophyceae composed 32.3%, followed by Cyanophyceae composed 22.8 % of the total. The total number of epiphytic algae was fluctuated among the study period. Most of the identified algae were benthos type and a few

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Publication Date
Thu Dec 28 2023
Journal Name
Al–bahith Al–a'alami
Contents of the photo coverage of the Gulf Cup Championship on the pages of photojournalists on Instagram: An analytical study
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This study intends to examine the content of photo coverage related to the Gulf Cup (Gulf 25) as presented by Iraqi photojournalists on Instagram between 02/01/2023 and 27/01/2023. Utilizing content analysis, the two researchers employed the survey method to evaluate 674 digital photos posted by seven photojournalists specializing in this sporting event, which concluded with the Iraqi team's victory in the city of Basra.
Key findings from the study include:
1. The Category "Photos from the Gulf Cup matches" predominated, accounting for 291 instances or 42.794% of the total.
2. Photojournalists exhibited a keen interest in capturing images of attending fans and documenting celebrations surrounding th

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Publication Date
Sat Oct 30 2021
Journal Name
Iraqi Journal Of Science
The Effects of Conductance on Metastable Switches in Memristive Devices Based on Anti-Hebbian and Hebbian (AHaH) Learning Rules
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     In the last few years, the literature conferred a great interest in studying the feasibility of using memristive devices for computing. Memristive devices are important in structure, dynamics, as well as functionalities of artificial neural networks (ANNs) because of their resemblance to biological learning in synapses and neurons regarding switching characteristics of their resistance. Memristive architecture consists of a number of metastable switches (MSSs). Although the literature covered a variety of memristive applications for general purpose computations, the effect of low or high conductance of each MSS was unclear. This paper focuses on finding a potential criterion to calculate the conductance of each MMS rather t

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Face Recognition and Emotion Recognition from Facial Expression Using Deep Learning Neural Network
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Abstract<p>Face recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.</p>
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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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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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Publication Date
Fri Oct 14 2022
Journal Name
المجلة العراقية لعلوم التربة
REVIEW: USING MACHINE VISION AND DEEP LEARINING IN AUTOMATED SORTING OF LOCAL LEMONS
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Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.