Girder Load Share for the Curved I-Girder Bridge Subjected to the Point Load
Publication Date
Mon Aug 01 2022
Journal Name
International Journal Of Hydrogen Energy
Exploring the application of AlN graphyne in calcium ion batteries
Destiny functional theory (DFT) calculations are undertaken in order to scrutinize the electrochemical and calcium (Ca) storage characteristics of a graphyne-like aluminum nitride monolayer (G-AlNyen) as an electrode material for Ca-ion batteries (CIBs). The results show that the change in internal energy as well as the cell voltage values for the CIB with the G-AlNyen anode are comparable to others with two-dimensional 2D nano-materials. It is shown that Ca is adsorbed primarily onto the center of a hexagonal and triangular ring of G-AlNyen with absorption energies of −2.06 and −0.42 eV. After increasing the concentration of Ca atoms on G-AlNyen, the adsorption energy as well as the cell voltage decreases. Lower values of 0.15–0.32 e
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Publication Date
Mon Aug 01 2011
Journal Name
Journal Of Engineering
EXPERIMENTAL OBSERVATIONS ON THE BEHAVIOR OF A PILED RAFT FOUNDATION
The piled raft is a geotechnical composite construction consisting of three elements: piles, raft and soil.
In the design of piled rafts, the load shared between the piles and the raft, and the piles are used up to a
load level that can be of the same order of magnitude as the bearing capacity of a comparable single
pile or even greater. Therefore, the piled raft foundation allows reduction of settlements in a very
economic way as compared to traditional foundation concepts.
This paper presents experimental study to investigate the behavior of piled raft system in sandy
soil. A small scale “prototype” model was tested in a sand box with load applied to the system through
a compression machine. The settlement was
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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The Prediction of COVID 19 Disease Using Feature Selection Techniques
Abstract<p>COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in </p>
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Feature selection
COVID 19
Recursive Feature Elimination
Extra Tree Classifier
Restricted Boltzmann Machine
Naïve Bayesian
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Publication Date
Wed Mar 01 2017
Journal Name
Neural Computing And Applications
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Publication Date
Tue Jul 01 2014
Journal Name
Bulletin Of The Iraq Natural History Museum
Publication Date
Fri Jul 01 2022
Journal Name
Iop Conference Series: Earth And Environmental Science
A study Some Technical Indicators of the Local Designed Machine
Abstract<p>The effect of compound machine on wheat/ AlNoor cultivar was studied based on some technical indicators. were tested under three speeds ( 2.541, 3.433 and 4.091km.hr<sup>-1</sup>) and three tillage depths (14, 16 and 18cm). The experiments were conducted in a factorial experiment under complete randomized design with three replications. The results showed that the 2.541km.hr<sup>-1</sup> practical speed was significantly better than other two speed in all studied conditions. Except for the FC, which achieved the best results with the third speed 4.091 km.hr<sup>-1</sup>. mechanical parameters, plant growth parameters and yield and growth parameters. The 1</p>
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Publication Date
Sat Jan 01 2022
Journal Name
3rd International Scientific Conference Of Alkafeel University (iscku 2021)
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Publication Date
Wed Mar 12 2025
Journal Name
Imam Ja'afar Al-sadiq University Journal Of Legal Studies
Publication Date
Thu Dec 23 2010
Journal Name
Arabian Journal Of Geosciences
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Publication Date
Sun Jan 10 2016
Journal Name
British Journal Of Applied Science & Technology
The Effect of Classification Methods on Facial Emotion Recognition Accuracy
Facial emotions
feature selection
data clustering
modified K-Means clustering algorithm
LDA algorithm
Statistical classifier
Neural Network
Support Vector Machine (SVM)
The interests toward developing accurate automatic face emotion recognition methodologies are growing vastly, and it is still one of an ever growing research field in the region of computer vision, artificial intelligent and automation. However, there is a challenge to build an automated system which equals human ability to recognize facial emotion because of the lack of an effective facial feature descriptor and the difficulty of choosing proper classification method. In this paper, a geometric based feature vector has been proposed. For the classification purpose, three different types of classification methods are tested: statistical, artificial neural network (NN) and Support Vector Machine (SVM). A modified K-Means clustering algorithm
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