The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

Water supply networks are marred by serious risks of imperceptible pipeline leakage, posing ‎sustainability ‎and ‎performance ‎threats.  This article highlights the use of vibratory signal features to get around the drawbacks of traditional methods in a highly detailed framework for leak detection based on CatBoost. demonstrated excellent diagnostic performance and carried out a thorough test performance evaluation on five leakage configurations  . The expected system achieved an accuracy of 98.1% (variance (well within x/3% of expected):, beating traditional competitors such as Random Forest (97.3%) and Support Vector Machine (93.8%). ‎For example, the area under the receiver-operating characteristic curve was 0.995, in

In this study, the potential of adsorption of amoxicillin antibiotic (AMOX) from aqueous solutions using prepared activated carbon (AC) was studied. The used AC was prepared from an inexpensive and available precursor (sunflower seed hulls (SSH)) and activated by potassium hydroxide (KOH). The prepared AC was examined for its ability to remove AMOX from aqueous contaminated solutions and characterized with the aid of N2 -adsorption/desorption isotherm Brunauer–Emmett– Teller, scanning electron microscopy, energy-dispersive X-ray spectroscopy and Fourier-transform infrared. Zeta potential of the prepared activated carbon from sunflower seed hulls (SSHAC) were studied in relation to AMOX adsorption. The physical and chemical propert

Hepatitis is one of the diseases that has become more developed in recent years in terms of the high number of infections. Hepatitis causes inflammation that destroys liver cells, and it occurs as a result of viruses, bacteria, blood transfusions, and others. There are five types of hepatitis viruses, which are (A, B, C, D, E) according to their severity. The disease varies by type. Accurate and early diagnosis is the best way to prevent disease, as it allows infected people to take preventive steps so that they do not transmit the difference to other people, and diagnosis using artificial intelligence gives an accurate and rapid diagnostic result. Where the analytical method of the data relied on the radial basis network to diagnose the

This study focuses on how tax administrations in Iraq use Artificial Intelligence (AI) techniques to monitor tax evasion for individuals and companies to achieve Tax Compliance (TC). AI was measured through four dimensions: Advanced Data Analytics Techniques (ADAT), Explainable AI (EAI), Machine learning (ML), and Robotic Process Automation (RPA). At the same time, TC was measured through registration, accounting, and tax payment stages. We relied on the questionnaire form to measure the variables. A sample of employees in the General Tax Authority in Iraq was selected, and a questionnaire was distributed to 132 people. The results indicated that the dimensions of AI affect achieving TC at all stages. This study provides evidence of using A

Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization

This study aimed to investigate the effect of water treated with a magnetic field with different induction on the histological structure of the kidney and testicular tissue of albino rats. For this purpose, fifty albino rats were divided into five equal groups, the first of which was used as a control group, drank clean tap water for four weeks, the other groups were given daily water treated with a magnetic field with an induction of 500, 1000, 1500 and 2000 gauss. Then the animals were sacrificed and histological changes in the kidneys and testicles were examined. Histopathological examination of the kidneys of animals that were given water treated with a magnetic field with an induction of 500, 1000 and 1500 gauss revealed n

Background: Dental calculus is mineralized dental plaque formed on teeth and dental prosthesis surfaces in the oral cavity. Urinary stone is a crystal aggregation formed in urinary system due to minerals saturation present in urine. The structure of dental calculus is similar to that of urinary stone. Objective: To assess oral hygiene and gingival status in patients with urinary stone. And compared with healthy subjects. Patients and Methods: Sixty participants, 25-40 years, were involved in this study who were divided into study and control group. The study group involved patients with urinary stone while the control group involved healthy subjects. Clinical parameters including plaque, calculus and gingival indices were recorded for al