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Prediction of Shear Strength Parameters of Gypseous Soil using Artificial Neural Networks
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The shear strength of soil is one of the most important soil properties that should be identified before any foundation design. The presence of gypseous soil exacerbates foundation problems. In this research, an approach to forecasting shear strength parameters of gypseous soils based on basic soil properties was created using Artificial Neural Networks. Two models were built to forecast the cohesion and the angle of internal friction. Nine basic soil properties were used as inputs to both models for they were considered to have the most significant impact on soil shear strength, namely: depth, gypsum content, passing sieve no.200, liquid limit, plastic limit, plasticity index, water content, dry unit weight, and initial voids ratio. Multi-layer perceptron training by the backpropagation algorithm was used in creating the network. It was found that both models can predict shear strength parameters for gypseous soils with good reliability. Sensitivity analysis of the first model indicated that dry unit weight and plasticity index have the most significant effect on the predicted cohesion. While in the second model, the results indicated that the gypsum content and plasticity index have the most significant effect on the predicted angle of internal friction.

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Publication Date
Mon Oct 05 2026
Journal Name
Journal Of The College Of Basic Education
Rationing two test in strength endurance for young under the age of 16
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Publication Date
Sun Sep 01 2019
Journal Name
Pavement And Asset Management
Assessing the bond strength of two-layer Roller Compacted Concrete (RCC) for pavements
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Roller Compacted Concrete (RCC) is a mass concrete with zero slump consisting of well-graded aggregate, cementitious materials and water. RCC has many advantages over other pavement types, particularly cost and speed of construction. However, it also presents difficulties with high-speed applications related to surface texture and surface evenness. These difficulties have so far restricted the use of RCC to the lower layers of normal roads. This study investigates the possibility of expanding the application of RCC for normal roads and highways by using a two-layer system of roller compacted concrete. The suitability of RCC for such an application depends fundamentally on bond strength between the layers. The bond strength measured by shear

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Publication Date
Tue Jan 19 2021
Journal Name
Sn Applied Sciences
Post-fire serviceability and residual strength of composite post-tensioned concrete T-beams
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Abstract<p>In this study, the response of ten composite post-tensioned concrete beams topped by a reinforced concrete deck with adequate reinforcing shear connectors is investigated. Depending on the concrete compressive strength of the deck slab (20, 30, and 40 MPa), beams are grouped into three categories. Seven of these beams are exposed to a fire attack of 700 and 800 °C temperature simultaneously with or without the presence of a uniformly distributed sustained static loading. After cooling back to ambient temperature, these composite beams are loaded up to failure, using a force control module, by monotonic static loading in a four-point-bending setup with two symmetrical concentrated loads applied in </p> ... Show More
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Publication Date
Tue Jan 19 2021
Journal Name
Sn Applied Sciences
Post-fire serviceability and residual strength of composite post-tensioned concrete T-beams
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Abstract<p>In this study, the response of ten composite post-tensioned concrete beams topped by a reinforced concrete deck with adequate reinforcing shear connectors is investigated. Depending on the concrete compressive strength of the deck slab (20, 30, and 40 MPa), beams are grouped into three categories. Seven of these beams are exposed to a fire attack of 700 and 800 °C temperature simultaneously with or without the presence of a uniformly distributed sustained static loading. After cooling back to ambient temperature, these composite beams are loaded up to failure, using a force control module, by monotonic static loading in a four-point-bending setup with two symmetrical concentrated loads applied in </p> ... Show More
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Publication Date
Sat Jun 28 2014
Journal Name
Iraqi Postgraduate Medical Journal
Comparism Between Transvaginal Cervical Length Measurement and Digital Examination in Prediction of Imminent preterm Delivery
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BACKGROUND: Preterm labour is a major cause of perinatal morbidity and mortality, so it is important to predict preterm delivery using the clinical examination of the cervix and uterine contraction frequency. New markers for the prediction of preterm birth have been developed such as transvaginal ultrasound measurement of cervical length as this method is widely available. OBJECTIVE: To determine, whether transvaginal cervical length measurement predicts imminent preterm delivery better than digital cervical length measurement in women presented with preterm labour and intact membranes. PATIENTS AND METHODS: Two hundred women presented with preterm labour between 24 and 36+6 weeks of gestation were included in this study. All women subjecte

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Publication Date
Thu Dec 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Prediction of Performance Equations for Household Compressors Depending on Manufacturing Data for Refrigerators and Freezers
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Abstract

 A surface fitting model is developed based on calorimeter data for two famous brands of household compressors. Correlation equations of ten coefficient polynomials were found as a function of refrigerant saturating and evaporating temperatures in range of (-35℃ to -10℃) using Matlab software for cooling capacity, power consumption, and refrigerant mass flow rate.

Additional correlations equations for these variables as a quick choice selection for a proper compressor use at ASHRAE standard that cover a range of swept volume range (2.24-11.15) cm3.

The result indicated that these surface fitting models are accurate with in ± 15% for 72 compressors model of cooling cap

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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Publication Date
Thu Mar 10 2011
Journal Name
Tikrit Journal Of Agricultural Sciences
ESTIMATION OF GENE ACTION AND GENETIC PARAMETERS FOR SOME VEGETATIVE AND FLOWERY GROWTH CHARACTERS IN SUMMER SQUASH (Cucurbita pepo L.) BY USING MEAN GENERATION ANALYSIS
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An experiment was carried out in the vegetables field of Horticulture Department / College of Agriculture / Baghdad University , for the three seasons : spring and Autumn of 2005 , and spring of 2007 , to study the type of gene action in some traits of vegetative and flowery growth in summer squash crosses (4 x 3 = cross 1 , 3 x 7 = cross 2 , 3 x 4 = cross 3 , 3 x 5 = cross 4 , 5 x 1 = cross 5 , 5 x 2 = cross 6). The study followed generation mean analysis method which included to each cross (P1 , P2 , F1 , F2 , Bc1P1 , Bc1P2) , and those populations obtained by hybridization during the first and second seasons. Experimental comparison was performed in the second (Two crosses only) and third seasons , (four crosses) by using RCBD with three

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Publication Date
Wed Dec 25 2024
Journal Name
الذكوات البيض
Artificial Intelligence and its Impact on Education and Media
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Abstract Objectives: This research seeks to highlight one of the important topics artificial intelligence and its impact on education and media. This issue has received considerable attention from international institutions and organizations in order to keep pace with the world's current progress. The study provided an overview of the concept of artificial intelligence, its definitions, its importance and characteristics and its impact on education in general and on the student and teacher in particular, as well as linking the subject of education to the media because social media that is one of the media has a great impact on the academic community. Methods: This study relied on the analytical descriptive curriculum where one of the curr

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Publication Date
Sun Oct 15 2023
Journal Name
Journal Of Yarmouk
Artificial Intelligence Techniques for Colon Cancer Detection: A Review
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