This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduce

Background:Parkinson’disease(PD) is a neurodegenerative disorder of the central nervous system characterized by resting tremor, bradykinesia, cogwheel rigidity, and impairment of postural reflexes; the frequency of PD increases with aging.Clinically Parkinson's disease characterized by two groups of symptoms: motor and non-motor symptoms.Non-motor symptoms can be categorized as autonomic, cognitive/psychiatric (may include depression, dementia, anxiety, hallucinations), sensory and rapid eye movements (REM) sleep behavior disorder (RBD).

Objectives:The objectives of this study are to find out the frequency of the non-motor symptoms of idiopathic Parkinson disease in a group of patients in Baghd

Porosity is important because it reflects the presence of oil reserves. Hence, the number of underground reserves and a direct influence on the essential petrophysical parameters, such as permeability and saturation, are related to connected pores. Also, the selection of perforation interval and recommended drilling additional infill wells. For the estimation two distinct methods are used to obtain the results: the first method is based on conventional equations that utilize porosity logs. In contrast, the second approach relies on statistical methods based on making matrices dependent on rock and fluid composition and solving the equations (matrices) instantaneously. In which records have entered as equations, and the matrix is sol

Anabolic androgenic steroids (AAS) are man-made derivatives of the male sex hormone testosterone, originally designed for therapeutic uses to provide higher anabolic potency with lower androgenic effects. Increasing numbers of young athletes are using these agents illicitly to enhance physical fitness, appearance, and performance despite their numerous side effects and worldwide banning.  Today, their use remains one of the main health problems in sports because of their availability and low price.  The present study focuses on investigating the adverse effects of anabolic androgenic steroid abuse on sex hormones, liver and renal function tests, fasting glucose levels and lipid metabolism in Iraqi male recreational bodybuilders

The precise classification of DNA sequences is pivotal in genomics, holding significant implications for personalized medicine. The stakes are particularly high when classifying key genetic markers such as BRAC, related to breast cancer susceptibility; BRAF, associated with various malignancies; and KRAS, a recognized oncogene. Conventional machine learning techniques often necessitate intricate feature engineering and may not capture the full spectrum of sequence dependencies. To ameliorate these limitations, this study employs an adapted UNet architecture, originally designed for biomedical image segmentation, to classify DNA sequences.The attention mechanism was also tested LONG WITH u-Net architecture to precisely classify DNA sequences

Abstract

This research presents a on-line cognitive tuning control algorithm for the nonlinear controller of path-tracking for dynamic wheeled mobile robot to stabilize and follow a continuous reference path with minimum tracking pose error. The goal of the proposed structure of a hybrid (Bees-PSO) algorithm is to find and tune the values of the control gains of the nonlinear (neural and back-stepping method) controllers as a simple on-line with fast tuning techniques in order to obtain the best torques actions of the wheels for the cart mobile robot from the proposed two controllers. Simulation results (Matlab Package 2012a) show that the nonlinear neural controller with hybrid Bees-PSO cognitive algorithm is m