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Prediction of Ultimate Soil Bearing Capacity for Shallow Strip Foundation on Sandy Soils by Using (ANN) Techniqu
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Bearing capacity of soil is an important factor in designing shallow foundations. It is directly related to foundation dimensions and consequently its performance. The calculations for obtaining the bearing capacity of a soil needs many varying parameters, for example soil type, depth of foundation, unit weight of soil, etc. which makes these calculation very variable–parameter dependent. This paper presents the results of comparison between the theoretical equation stated by Terzaghi and the Artificial Neural Networks (ANN) technique to estimate the ultimate bearing capacity of the strip shallow footing on sandy soils. The results show a very good agreement between the theoretical solution and the ANN technique. Results revealed that using ANN gave a very high correlation factor associated with the results obtained from Terzagih’s equation, besides little computation time needed compared with computation time needed when applying Terzagih’s equation.

Publication Date
Fri Aug 15 2025
Journal Name
Modern Sport
Time out in basketball and it effect on playing for excellent degrees in Iraq
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The value of time out as a time not count of official time form the game like four periods and extra time also it considered a great interest if used well thru the game , the importance of this problem is not using well the time out and when the coach ask for time out and how to invest this time legally to make good results also there is no observing system as the researcher see gives the reality image that the coach is successful lead the game when he takes time out . The goals of research that knowing on numbers of time out for excellent teams in Iraq (first &second) stages and putting special inventory reverse reality of asking time out (positive &negative) on playing basketball , the hypothesis of research that tell the time out effect

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Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Microgrid Integration Based on Deep Learning NARMA-L2 Controller for Maximum Power Point Tracking
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This paper presents a hybrid energy resources (HER) system consisting of solar PV, storage, and utility grid. It is a challenge in real time to extract maximum power point (MPP) from the PV solar under variations of the irradiance strength.  This work addresses challenges in identifying global MPP, dynamic algorithm behavior, tracking speed, adaptability to changing conditions, and accuracy. Shallow Neural Networks using the deep learning NARMA-L2 controller have been proposed. It is modeled to predict the reference voltage under different irradiance. The dynamic PV solar and nonlinearity have been trained to track the maximum power drawn from the PV solar systems in real time.

Moreover, the proposed controller i

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Physics: Conference Series
Gamma Irradiation Effects on Energy Transfer Parameters for Acrvlaven – Rhodamine19 Binary Laser Dye Mixtures
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Publication Date
Sun Dec 30 2012
Journal Name
Journal Of Kufa For Mathematics And Computer
On Jeffery Prior Distribution in Modified Double Stage Shrinkage-Bayesian Estimator for Exponential Mean
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Publication Date
Wed Mar 16 2022
Journal Name
International Journal Of Recent Contributions From Engineering, Science & It
Smart Learning based on Moodle E-learning Platform and Digital Skills for University Students
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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Physics: Conference Series
Gamma Irradiation Effects on Energy Transfer Parameters for Acrvlaven – Rhodamine19 Binary Laser Dye Mixtures
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Publication Date
Fri Jul 19 2024
Journal Name
An International Journal Of Optimization And Control: Theories & Applications (ijocta)
Design optimal neural network based on new LM training algorithm for solving 3D - PDEs
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In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

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Publication Date
Fri Dec 01 2023
Journal Name
Iraqi Journal Of Physics
Gas Sensor for Hazardous Nitrogen Dioxide Based on TiO2 Nanotube Synthesis via Electrochemical Method
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Because of the quick growth of electrical instruments used in noxious gas detection, the importance of gas sensors has increased. X-ray diffraction (XRD) can be used to examine the crystal phase structure of sensing materials, which affects the properties of gas sensing. This contributes to the study of the effect of electrochemical synthesis of titanium dioxide (TiO2) materials with various crystal phase shapes, such as rutile TiO2 (R-TiO2NTs) and anatase TiO2 (A-TiO2NTs). In this work, we have studied the effect of voltage on preparing TiO2 nanotube arrays via the anodization technique for gas sensor applications. The results acquired from XRD, energy dispersion spectro

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Publication Date
Fri Sep 01 2023
Journal Name
Al-khwarizmi Engineering Journal
High Transaction Rates Performance Evaluation for Secure E-government Based on Private Blockchain Scheme
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The implementation of technology in the provision of public services and communication to citizens, which is commonly referred to as e-government, has brought multitude of benefits, including enhanced efficiency, accessibility, and transparency. Nevertheless, this approach also presents particular security concerns, such as cyber threats, data breaches, and access control. One technology that can aid in mitigating the effects of security vulnerabilities within e-government is permissioned blockchain. This work examines the performance of the hyperledger fabric private blockchain under high transaction loads by analyzing two scenarios that involve six organizations as case studies. Several parameters, such as transaction send ra

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Publication Date
Mon Jan 01 2024
Journal Name
Applied And Computational Mathematics
Reliable computational methods for solving Jeffery-Hamel flow problem based on polynomial function spaces
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In this paper reliable computational methods (RCMs) based on the monomial stan-dard polynomials have been executed to solve the problem of Jeffery-Hamel flow (JHF). In addition, convenient base functions, namely Bernoulli, Euler and Laguerre polynomials, have been used to enhance the reliability of the computational methods. Using such functions turns the problem into a set of solvable nonlinear algebraic system that MathematicaⓇ12 can solve. The JHF problem has been solved with the help of Improved Reliable Computational Methods (I-RCMs), and a review of the methods has been given. Also, published facts are used to make comparisons. As further evidence of the accuracy and dependability of the proposed methods, the maximum error remainder

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