This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

Background/Objectives: The purpose of current research aims to a modified image representation framework for Content-Based Image Retrieval (CBIR) through gray scale input image, Zernike Moments (ZMs) properties, Local Binary Pattern (LBP), Y Color Space, Slantlet Transform (SLT), and Discrete Wavelet Transform (DWT). Methods/Statistical analysis: This study surveyed and analysed three standard datasets WANG V1.0, WANG V2.0, and Caltech 101. The features an image of objects in this sets that belong to 101 classes-with approximately 40-800 images for every category. The suggested infrastructure within the study seeks to present a description and operationalization of the CBIR system through automated attribute extraction system premised on CN

Improved Merging Multi Convolutional Neural Networks Framework of Image Indexing and Retrieval

Physical measurements are one of the basic factors that affect the performance of the goalkeeper, especially when confronting fixed kicks that require special skills such as the reaction and accuracy in concentration, and with technological development artificial intelligence has become an effective tool for analyzing mathematical data that is difficult to discover in traditional methods The study aims to employ techniques Artificial intelligence to study the relationship between physical measurements and the accuracy of confronting the fixed kicks of goalkeepers in football. This study will contribute to providing a deeper understanding of physical factors that affect the performance of goalkeepers, in addition to designing dedicat

Abstract This study explores the extent to which public relations (PR) departments within Traqj governmental institutions are integrating artificial intelligence (AI) applications into their communication activities. The research adresses the growing importanc of AI in enhancing administrative efficieney, communication transparency, and stakeholder engagement. Adopting a descriptive research design, the study relied on an electtonic questionnaire distributed to PR profesionals across various ministries and government bodies, collecting 100 valid responses. The indings reveal that while younger PR practitioners are actively embracing AI, older employees show limited engagement. Most participants acquired AI-related skills through self- learn

When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat

The present study aimed to determine the serum sex hormone levels among Benign Prostatic Hyperplasia (BPH) patients before and after 3 months of oral administration of 5-α reductase inhibitor(finasteride). Forty BPH patients and 40 healthy men from Amara city were involved in this study, their ages were between 40-59 year. They were all subjected  to direct estimation of hormones by MinVidas method including Testosterone (T), Estradiol (E2), Follicle Stimulating Hormone (FSH), Luteinizing Hormone (LH), Prolactin (PRL), and Dihydrotestosterone (DHT) before and after 3 months of treatment with 5α-reductase inhibitor (finasteride) (the healthy individuals didn’t take finasteride).The results showed that T level was significantly lo

The purpose of this subject is to identify what is being studied in the article, which is the involvement of human Metapneumovirus in children with respiratory illnesses. During the period November 2020 to February 2021, 100 patients with respiratory tract infections were admitted to Al Zahra Teaching Hospital and AL-Forat AL-Awsat Teaching Hospital in Najaf Governorate. Nasopharyngeal swabs were collected from patients for molecular diagnosis of human metapneumovirus using Real-Time-PCR. The patients were distributed based on age into five groups as follows (Less than one, 1-2, 2-3, 3-4, and 4-5 years), and twenty samples of healthy individuals were approved as a control group without any clinical signs of infection. the children of age gr

              The current paper proposes a new estimator for the linear regression model parameters under Big Data circumstances.  From the diversity of Big Data variables comes many challenges that  can be interesting to the  researchers who try their best to find new and novel methods to estimate the parameters of linear regression model. Data has been collected by Central Statistical Organization IRAQ, and the child labor in Iraq has been chosen as data. Child labor is the most vital phenomena that both society and education are suffering from and it affects the future of our next generation. Two methods have been selected to estimate the parameter