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

The study presents the performance of flexural strengthening of concrete members exposed to partially unbonded prestressing with a particular emphasis on the amount (0, 14.2, and 28.5%) of cut strands-symmetrical and asymmetrical damage. In addition to examining the influence of cut strands on the remaining capacity of post-tensioned unbonded members and the effectiveness of carbon fiber reinforced polymer laminates restoration, The investigated results on rectangular members subjected to a four-point static bending load based on the composition of the laminate affected the stress of the CFRP, the failure mode, and flexural strength and deflection are covered in this study. The experimental results revealed that the usage of CFRP la

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

The study included isolate and diagnose fungus Fusarium solani of the local soil and purified and development in the PDB medium and the filtrate extracted using a solvent (Ethyl acetate) to obtain the fungal secondary metabolites extract. This extract has shown bioactivity against both reference isolates (E.coli (ATCC25922) and S.aureus(NCTC6571)) and pathogenic isolates S.pyogenes, K. pneumonia and S.typhimurium using agar disk diffusion technique , The diameters of the inhibition zones of fungal secondary metabolites24.0 mm against E.coli and 31.5 mm against S.aureus,and 34.0 mm against K.pneumoniae and 18.0 mm against S.pyogenes and 33.5mm against S.typhimurium. The test revealed the minimum inhibitory concentration (MIC) of the fungal

This study presents, for the first time, an innovative Jet Plasma-assisted technique for the green synthesis of TiO₂@Ag core–shell nanoparticles using chard leaf extract as a natural reducing and stabilizing agent. The Jet Plasma provides a highly energetic environment that accelerates nucleation and core–shell formation at low temperatures without toxic precursors. The synthesized nanoparticles exhibited uniform and stable structures, as confirmed by comprehensive characterization techniques including X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), ultraviolet–visible (UV–Vis) spectroscopy, transmission electron microscopy (TEM), and zeta potential analysis. XRD patterns confirmed the crystalline anatase

Background: Stroke defined by diminished cerebral blood flow, results in brain damage and neurological impairments. It often leads to considerable difficulties, such as limited mobility and compromised hand function, usually manifesting as a weakening in the ability to open and shut the hand. Objective: The study evaluates the differences between opening and closing hands when utilizing a soft robot. Methods: The study was conducted in the Mosul Specialist Rehabilitation Center which involved 68 participants, all over 20 years old, with visual impairments. The Iranian Clinical Trials Registry and Ministry of Planning approved the study, The Fugl-Meyer Assessment for Upper Extremity Action Research Arm Test, and Arm Motor Ability Test were

The melting duration in the photovoltaic/phase-change material (PV/PCM) system is a crucial parameter for thermal energy management such that its improvement can realize better energy management in respect to thermal storage capabilities, thermal conditions, and the lifespan of PV modules. An innovative and efficient technique for improving the melting duration is the inclusion of an exterior metal foam layer in the PV/PCM system. For detailed investigations of utilizing different metal foam configurations in terms of their convective heat transfer coefficients, the present paper proposes a newly developed mathematical model for the PV/PCM–metal foam assembly that can readily be implemented with a wide range of operating condition