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SIMULATION OF IDENTIFICATION AND CONTROL OF SCARA ROBOT USING MODIFIED RECURRENT NEURAL NETWORKS
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This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is better than RS and RW in identification the forward dynamics and provides good results in the Direct Inverse Neuro- Controller (DINC).

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
Strengthening and Closing Cracks for Existing Reinforced Concrete Girders Using Externally Post-Tensioned Tendons
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This research is devoted to study the strengthening technique for the existing reinforced concrete beams using external post-tensioning. An analytical methodology is proposed to predict the value of the effective prestress force for the external tendons required to close cracks in existing beams. The external prestressing force required to close cracks in existing members is only a part from the total strengthening force.
A computer program created by Oukaili (1997) and developed by Alhawwassi (2008) to evaluate curvature and deflection for reinforced concrete beams or internally prestressed concrete beams is modified to evaluate the deflection and the stress of the external tendons for the externally strengthened beams using Matlab

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Bayesian Tobit Quantile Regression Model Using Double Adaptive elastic net and Adaptive Ridge Regression
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     Recently Tobit  Quantile Regression(TQR) has emerged as an important tool in statistical analysis . in order to improve the parameter estimation in (TQR) we proposed Bayesian hierarchical model with double adaptive elastic net technique  and Bayesian hierarchical model with adaptive ridge regression technique .

 in double adaptive elastic net technique we assume  different penalization parameters  for penalization different regression coefficients in both parameters λ1and  λ, also in adaptive ridge regression technique we assume different  penalization parameters for penalization different regression coefficients i

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Publication Date
Tue Dec 12 2017
Journal Name
Al-khwarizmi Engineering Journal
Design a Vegetative Filter Strips Length Using VFSMOD_W Model for Reducing Sediments and Pesticides
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 Abstract 

The vegetative filter strips (VFS) are a useful tool used for reducing the movement of sediment and pesticide in therivers. The filter strip’s soil can help in reducing the runoff volume by infiltration. However, the characteristics of VFS (i.e., length) are not recently identified depending on the estimation of VFS modeling performance. The aim of this research is to study these characteristics and determine acorrelation between filter strip length and percent reduction (trapping efficiency) for sediment, water, and pesticide. Two proposed pesticides(one has organic carbon sorption coefficient, Koc, of 147 L/kg which is more moveable than XXXX, and another one

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Crossref
Publication Date
Wed Jan 28 2026
Journal Name
F1000research
Enhancing Solar Power Forecasting Accuracy Using HMPCS and Machine Learning Techniques: An Applied Study
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Background Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti

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Publication Date
Wed Dec 09 2020
Journal Name
Banks And Bank Systems
Cooperative decision-making on fiscal and monetary policy in Iraq using the prisoner’s dilemma
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This paper investigates the interaction between fiscal and monetary policy in Iraq after 2003 using the prisoner’s dilemma.The paper aims to determine the best form of coordination between these policies to achieve their goals; payoff matrix for both policies was constructed. To achieve the purpose, the quantitative approach was applied using several methods, including regression, building payoff matrices and decision analysis using a number of software.The results of the monetary policy payment function show that inflation rate has an inverse relationship with the auctions of selling foreign currency and a positive relationship with the government’s activity, while the fiscal policy function shows that real growth is positively

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
A study on predicting crime rates through machine learning and data mining using text
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Abstract<p>Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o</p> ... Show More
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Scopus (16)
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Publication Date
Fri Sep 01 2023
Journal Name
Al-khwarizmi Engineering Journal
A review on Activated Carbon Prepared from Agricultural Waste using Conventional and Microwave Activation
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In the recent years the research on the activated carbon preparation from agro-waste and byproducts have been increased due to their potency for agro-waste elimination. This paper presents a literature review on the synthesis of activated carbon from agro-waste using microwave irradiation method for heating. The applicable approach is highlighted, as well as the effects of activation conditions including carbonization temperature, retention period, and impregnation ratio. The review reveals that the agricultural wastes heated using a chemical process and microwave energy can produce activated carbon with a surface area that is significantly higher than that using the conventional heating method.

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Publication Date
Thu Jul 02 2026
Journal Name
Sciences Journal Of Physical Education
Using two types of electronic questions by applying the Quiz Creator program in the method of guided discovery and its effect on learning and maintaining a motor chain on the throat
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Publication Date
Fri May 30 2025
Journal Name
Journal Of Internet Services And Information Security
Enhancing Lung Cancer Classification using CT Images using Processing Techniques Employing U-Net Architecture
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Publication Date
Sat Apr 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Using PCR and Gel Electrophoresis Techniques to Molecular Confirm and Detection for Flowering Gene Presence in Maize Hybrids
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Abstract<p>The laboratory experiment was conducted in the laboratories of the Musayyib Bridge Company for Molecular Analyzes in the year 2021-2022 to study the molecular analysis of the inbreed lines and their hybrids F1 to estimate the genetic variation at the level of DNA shown by the selected pure inbreed lines and the resulting hybrids F1 of the flowering gene. Five pure inbreed lines of maize were selected (ZA17WR) Late, ZM74, Late, ZM19, Early ZM49WZ (Zi17WZ, Late, ZM49W3E) and their resulting hybrids, according to the study objective, from fifteen different inbreed lines with flowering time. The five inbreed lines were planted for four seasons (spring and fall 2019) and (spring and fall 2</p> ... Show More
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