This paper proposes a hybrid artificial intelligence (AI) model that combines an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) to predict the Quality of Service (QoS) in 5G networks. The model utilizes radio channel indicators such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), Received Signal Strength Indicator (RSSI), and Channel Quality Indicator (CQI) to forecast throughput and latency levels. These indicators are critical factors affecting network performance; however, the nonlinear relationship among them makes traditional analytical models inadequate for accurate QoS prediction. The importance of the current study lies in estimating QoS in 5G networks by combining

Polymer electrolyte films composed of PVP and PVP/glycerin with varying concentrations of CuCl2 (10, 20, and 30 wt.%) were synthesized using the solution casting method. The synthesized electrolyte films were characterized using FTIR, XRD, UV-Vis, DSC, and TGA techniques. FTIR spectroscopy revealed an O-H stretching vibration of PVP around 3300 cm(-1), which experienced broadening and a reduction in intensity upon the introduction of glycerin and CuCl2. XRD analysis displayed a characteristic peak at 2 theta similar to 20 degrees, with the peak shifting towards higher angles and a slight decrease in intensity as the CuCl2 concentration increased, indicating a disruption of the crystalline structure of the host matrix. UV-Vis analysis reveal

Background/Objectives: Early and accurate discrimination of neurological conditions, dementia, stroke and healthy aging, remains a critical clinical challenge. Electroencephalography (EEG) is a non-invasive measure of brain dynamics and entropy-based features obtained from multichannel EEG have shown strong discriminative ability. However, existing deep learning approaches do not sufficiently address the combined challenges of small clinical cohorts and high-dimensional entropy feature spaces. In this study, a novel architecture is proposed for multi-class neurological EEG classification under extreme small-sample conditions. Methods: A novel dual-branch Channel-wise Transformer and Attention-Branch Network (EEG-ChTABNet) are pr to

Accelerates operating managements in the facilities contemporary business environment toward redefining processes and strategies that you need to perform tasks of guaranteeing them continue in an environment performance dominated by economic globalization and the circumstances of uncertainty attempt the creation of a new structure through multiple pages seek to improve profitability and sustainable growth in performance in a climatefocuses on the development of institutional processes, reduce costs and achieve customer satisfaction to meet their demands and expectations are constantly changing. The research was presented structural matrix performance combines methodology Alsigma in order to improve customer satisfaction significantly bet

The objective of the study was to identify the effect of the use of the Colb model for the students of the third stage in the College of Physical Education and Sports Sciences, University of Baghdad,As well as to identify the differences between the research groups in the remote tests in learning skills using the model Colb.The researcher used the experimental method and included the sample of the research on the students of the third stage in the College of Physical Education and Sports Science / University of Baghdad by drawing lots, the third division (j) was chosen to represent the experimental group,And the third division (c) to represent the control groupafter the distribution of the sample splitting measure according to the Colb mode

Rehabilitation robots are widely recognized as vital for restoring motor function in patients with lower-limb impairments. A Modified Fractional-Order Proportional-Integral-Derivative (MFOPID) controller is proposed to improve trajectory tracking of a 2-DoF Lower Limb Rehabilitation Exoskeleton Robot (LLRER). The classical FOPID is augmented with a modified control formulation by which steady-state error is reduced and the transient response is sharpened. Controller gains and fractional orders were tuned offline using a hybrid metaheuristic Improved Elk Herd Optimization hybridized with Grey Wolf and Multi-Verse Optimization algorithms (IElk-GM) so that exploration and exploitation are balanced. Superiority over the classical FOPID

The study aimed at recognizing the availability of the cultural intelligence dimensions in social studies book at the high school in the kingdom of Saudi Arabia (curricula system- joint program). The study used the descriptive approach and content analysis method. As tools of the study, the study adopted a list of cultural list of indicators and dimensions that suits the secondary stage social curricula. It further adopted a content analysis form designed to analyze the social studies book in the secondary school in the kingdom of Saudi Arabia. The study has reached several results, the most significant results were: There is a difference in including the cultural intelligence dimensions in social studies book at high school in the kingd