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Enhancing the Delta Training Rule for a Single Layer Feedforward Heteroassociative Memory Neural Network
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In this paper, an algorithm is suggested to train a single layer feedforward neural network to function as a heteroassociative memory. This algorithm enhances the ability of the memory to recall the stored patterns when partially described noisy inputs patterns are presented. The algorithm relies on adapting the standard delta rule by introducing new terms, first order term and second order term to it. Results show that the heteroassociative neural network trained with this algorithm perfectly recalls the desired stored pattern when 1.6% and 3.2% special partially described noisy inputs patterns are presented.

Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Using Pomegranate Peel Extract to Change the Adverse Effect of Ethephon by Enhancing its Antioxidant, Anti-inflammatory, and Anti-apoptotic Effects in Rats
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Organophosphorus insecticide and growth regulator namely Ethephon (2-chloroethylphosphonic acid) are widely used as a ripening process accelerator and a cultivation duration inhibitor. Pomegranate extract (PPE) has recently been taken into consideration due to its pharmacological effects especially those associated with renal diseases. Thus, this study aims to investigate the possible protective effect of PPE against ethephon-induced nephrotoxicity in rats. In this study four groups of adult male rats were divided into control group, PPE 400 mg/kg group, Ethephon 250 mg/kg group, and finally, PPE + Ethephon group (treated with the same dose of PPE group and Ethephon group). In the current study, kidney function parameters (KIM-1, creatin

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Publication Date
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

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Publication Date
Tue Jan 01 2019
Journal Name
Mustansiriyah Journal Of Sports Science
The use of training methods in accordance with special exercises to develop flexibility and perform the skills of shooting from above the chest (abduction) to wrestlers ages (14-15)"
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Evolution has become a feature of this era because of the speed that makes it open multiple horizons and many to identify everything that is new in different areas and also characterized by the competitive position of emotional attitudes changing depending on the positions of winning and defeat, and the use of training methods are the most important pillars of the game of wrestling, The methods contribute to raising the level of the wrestler and refining his physical and skill potential. The problem of the research is that the shooting exercises from above the chest are very important in Roman wrestling and can be terminated by the player. Through very personal interviews for coaches and concluded that there is a weakness in the level of fl

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Publication Date
Sun Mar 31 2013
Journal Name
Inventi Impact: Artificial Intelligence
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 bett

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Recognizing Different Foot Deformities Using FSR Sensors by Static Classification of Neural Networks
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Sensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar

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Publication Date
Wed Dec 27 2017
Journal Name
Al-khwarizmi Engineering Journal
Human Face Recognition Using GABOR Filter And Different Self Organizing Maps Neural Networks
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This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

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Publication Date
Sun Jan 01 2023
Journal Name
The Egyptian Journal Of Hospital Medicine
Training of Skilled Force with The Different Medical Ball and Their Effect on Developing Some Special Physical Abilities and the Accuracy of Long Shooting Performance in Handball
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Publication Date
Mon Aug 27 2018
Journal Name
International Research Journal Of Pharmacy
PRELIMINARY PHYTOCHEMICAL SCREENIG AND HIGH PERFORMANCE THIN LAYER CHROMATOGRAPHY[HPTLC] DETECTION OF PHENOLIC ACIDS IN LANATA CAMARA LEAVES CULTIVATED IN IRAQ
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Publication Date
Wed Dec 27 2023
Journal Name
Optical And Quantum Electronics
Synthesis and study of photoelectrochromic and photocatalytic behavior of double-layer N-doped TiO2/Co3O4 configuration via DC reactive magnetron sputtering
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This work introduces the synthesis and the characterization of N-doped TiO2 and Co3O4 thin films prepared via DC reactive magnetron sputtering technique. N-doped TiO2 thin films was deposited on indium-tin oxide (ITO) conducting substrate at different nitrogen ratios, then the Co3O4 thin film was deposited onto the N-doped TiO2 layer to synthesize a double-layer TiO2-N/Co3O4 Photoelectrochromic device. Several techniques were used to characterize the produces which are x-ray diffraction (XRD), field emission-scanning electron microscopy (FE-SEM), Fourier-transform infrared (FTIR) spectroscopy and UV–Vis spectroscopy. The Photoelectrochromic device was characterized by UV–Vis spectroscopy and the results show that the double-layer N-dope

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Publication Date
Wed May 17 2023
Journal Name
Journal Of Engineering
A Simulation of Core Displacement Experiments for the Determination of the Relative Permeability
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Computations of the relative permeability curves were made through their representation by two functions for wetting and nonwetting phases. Each function contains one parameter that controls the shape of the relative permeability curves. The values of these parameters are chosen to minimize an objective function, that is represented as a weighted sum of the squared differences between experimentally measured data and the corresponding data calculated by a mathematical model simulating the experiment. These data comprise the pressure drop across core samples and the recovery response of the displacing phase. Two mathematical models are constructed in this study to simulate incompressible, one-dimensional, two-phase flow. The first model d

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