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Effect of Size and Location of Square Web Openings on the Entire Behavior of Reinforced Concrete Deep Beams
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This paper presents an experimental and numerical study which was carried out to examine the influence of the size and the layout of the web openings on the load carrying capacity and the serviceability of reinforced concrete deep beams. Five full-scale simply supported reinforced concrete deep beams with two large web openings created in shear regions were tested up to failure. The shear span to overall depth ratio was (1.1). Square openings were located symmetrically relative to the midspan section either at the midpoint or at the interior boundaries of the shear span. Two different side dimensions for the square openings were considered, mainly, (200) mm and (230) mm. The strength results proved that the shear capacity of the deep beam is governed by the size and location of web openings. The experimental results indicated that the reduction of the shear capacity may reach (66%). ABAQUS finite element software program was used for simulation and analysis. Numerical analyses provided un-conservative estimates for deep beam load carrying capacity in the range between (5-21%). However, the maximum scatter of the finite element method predictions for first diagonal and first flexural cracking loads was not exceeding (17%). Also, at service load the numerical of midspan deflection was greater than the experimental values by (9-18%).

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Mining categorical Covid-19 data using chi-square and logistic regression algorithms
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Publication Date
Sun Nov 01 2015
Journal Name
Journal Of Engineering
Natural and Mixed Convection in Square Vented Enclosure Filled with Metal Foam
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Steady natural and mixed convection flow in a square vented enclosure filled with water-saturated aluminum metal foam is numerically investigated. The left vertical wall is kept at constant temperature and the remaining walls are thermally insulated. Forced convection is imposed by providing an inlet at cavity bottom surface, and a vent at the top surface. Natural convection takes place due to the temperature difference inside the enclosure. Darcy-Brinkman-Forchheimer model for fluid flow and the two-equation of the local thermal non-equilibrium model for heat flow was adopted to describe the flow characteristics within the porous cavity. Numerical results are obtained for a wide range of width of the inlet as a fraction

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Publication Date
Mon Jan 01 2018
Journal Name
Aip Conference Proceedings
The study of behavior titanium pure commercially coated with hydroxyapatite and zirconia
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Publication Date
Thu Nov 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
The Reflection of self competency of the managers in their behavior
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Abstract

      This research aims to measure the effect of Self competency of the Managers in their behavior from the view point of the working individual in the organization since the behavior of managers is considered to be one of the essential variables in the organization which can affect the performance and the commitment of the working individual. the questioners was used to gather the data and the Iraqi Rail Road co. was the field of the study . and a random sample of (36) individual of the subordinates of the managers society of the study and used the (SPSS) statistical program was used in the analysis of the data of the research . the findings refer to the existence of a

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Publication Date
Sat Dec 02 2023
Journal Name
Journal Of Engineering
Deep Learning of Diabetic Retinopathy Classification in Fundus Images
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Diabetic retinopathy is an eye disease in diabetic patients due to damage to the small blood vessels in the retina due to high and low blood sugar levels. Accurate detection and classification of Diabetic Retinopathy is an important task in computer-aided diagnosis, especially when planning for diabetic retinopathy surgery. Therefore, this study aims to design an automated model based on deep learning, which helps ophthalmologists detect and classify diabetic retinopathy severity through fundus images. In this work, a deep convolutional neural network (CNN) with transfer learning and fine tunes has been proposed by using pre-trained networks known as Residual Network-50 (ResNet-50). The overall framework of the proposed

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Publication Date
Sat Apr 11 2009
Journal Name
Journal Of Kerbala University
Evaluation The Behaviour of Reinforced Loose Sand under Inclined Loading
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Publication Date
Sun Apr 08 2018
Journal Name
Al-khwarizmi Engineering Journal
Evaluation the Mechanical Properties of Kaolin Particulate Reinforced Epoxy Composites
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Epoxy resin has many chemical features and mechanical properties, but it has a small elongation at break, low impact strength and crack propagation resistance, i.e. it exhibits a brittle behavior. In the current study, the influence of adding kaolin with variable particle size on the mechanical properties (flexural modulus E, toughness Gc, fracture toughness Kc, hardness HB, and Wear rate WR) of epoxy resin was evaluated. Composites of epoxy with varying concentrations (0, 10, 20, 30, 40 weights %) of kaolin were prepared by hand-out method. The composites showed improved (E, Gc, Kc, HB, and WR) properties with the addition of filler. Also, similar results were observed with the decrease in particle size. In addition, in this study, mult

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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
Thu Jan 04 2018
Journal Name
International Journal Of Science And Research (ijsr)
Effect of Doping on Properties of the Hall Effect and Electrical Conductivity for AgInTe2 Thin Films
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The effect of different doping ratio (0.3, 0.5, and 0.7) with thickness in the range 300nmand annealed at different temp.(Ta=RT, 473, 573, 673) K on the electrical conductivity and hall effect measurements of AgInTe2thin film have and been investigated AgAlxIn(1-x) Te2 (AAIT) at RT, using thermal evaporation technique all the films were prepared on glass substrates from the alloy of the compound. Electrical conductivity (σ), the activation energies (Ea1, Ea2), Hall mobility and the carrier concentration are investigated as a function of doping. All films consist of two types of transport mechanisms for free carriers. The activation energy (Ea) decreased whereas electrical conductivity increases with increased doping. Results of Hall Effect

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Publication Date
Mon Mar 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of bubble size in Bubble columns using Artificial Neural Network
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In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

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