For more than a decade, externally bonded carbon fiber reinforced polymer (CFRP) composites successfully utilized in retrofitting reinforced concrete structural elements. The function of CFRP reinforcement in increasing the ductility of reinforced concrete (RC) beam is essential in such members. Flexural and shear behaviors, ductility, and confinement were the main studied properties that used the CFRP as a strengthening material. However, limited attention has been paid to investigate the energy absorption of torsion strengthening of concrete members, especially two-span concrete beams. Hence, the target of this work is to investigate the effectiveness of CFRP-strengthening technique with regard to energy absorption of two-span RC

Classical cryptography systems exhibit major vulnerabilities because of the rapid development of quan tum computing algorithms and devices. These vulnerabilities were mitigated utilizing quantum key distribution (QKD), which is based on a quantum no-cloning algorithm that assures the safe generation and transmission of the encryption keys. A quantum computing platform, named Qiskit, was utilized by many recent researchers to analyze the security of several QKD protocols, such as BB84 and B92. In this paper, we demonstrate the simulation and implementation of a modified multistage QKD protocol by Qiskit. The simulation and implementation studies were based on the “local_qasm” simulator and the “FakeVigo” backend, respectively. T

The university course timetable problem (UCTP) is typically a combinatorial optimization problem. Manually achieving a useful timetable requires many days of effort, and the results are still unsatisfactory. unsatisfactory. Various states of art methods (heuristic, meta-heuristic) are used to satisfactorily solve UCTP. However, these approaches typically represent the instance-specific solutions. The hyper-heuristic framework adequately addresses this complex problem. This research proposed Particle Swarm Optimizer-based Hyper Heuristic (HH PSO) to solve UCTP efficiently. PSO is used as a higher-level method that selects low-level heuristics (LLH) sequence which further generates an optimal solution. The proposed a

Precise and interpretable classification of autism-related behaviors is important for initial diagnosis, personalized intervention, and support arrangements. This study proposes an interpretable machine learning (ML) model using Light Gradient Boosting Machine (LightGBM) and Categorical Boosting (CatBoost) to classify behavioral patterns into four categories (normal, mild, moderate, and severe) associated with Autism Spectrum Disorder (ASD) based on a custom 377-instance survey dataset from Iraqi parents and teachers of children aged 6-12. The model observes 16 key features across communication and social interaction, repetitive behaviors, language, and adaptive skills, preprocessed via interquartile range (IQR) outlier removal, me

Summary The paper proposes a small custom CNN for classifying solid waste into four classes: aluminum, cardboard, plastic, and glass. It is designed for real-time use on limited hardware such as a Raspberry Pi or Jetson.

This work is concerned with the synthesis of two types of composites thin films (Sb2O3:WO3 and (Sb2O3:In2O3) with different concentrations (0.0,0.05,0.1, and 0.15). The prepared thin films are characterized with the use of the X-ray diffraction atomic force microscope AFM and UV-Vis–infrared spectrophotometer. The structural examination shows that both composite's thin films were polycrystalline with nano size with cubic phase as majority and orthorhombic phase as minority phase. The crystal size decreases from 34.6 to 24.7 and 21.7 nm for (Sb2O3:WO3) and (Sb2O3:In2O3) thin films, respectively. The average roughness shows non-regular growth by increasing the concentration of both oxides. The optical energy band gap shows a red shi

      Compounds from tin oxide doped with gallium oxide and cerium oxide were synthesized. Thin films from (SnO2:Ga2O3,CeO2) with different doping ratios were prepared on glass and single crystal silicon as substrates with the use of the pulsed laser deposition technique. The results of FTIR spectrums analysis was presented. Varies heterojunctions were fabricated from (SnO2:Ga2O3,CeO2 /Cu2S/c-pSi) heterojunctions solar cell which are formed from two layers: the first was Cu2S and the second was layer from tin oxide doped with two oxides named gallium oxide and cerium oxide with different doping ratios (0, 0.03, 0.05, and 0.07). The heterojuntion (SnO2:5%Ga2O3 /Cu2S/c-pSi photovoltaic structure exhibits open circuit voltage (Voc

The present research investigates hydrodesulfurization (HDS) and hydrodearomatization (HAD) of raw kerosene with 0.364 wt. % sulfur and 16.498 wt. % aromatics supplied from Al-Dura Refinery. Hydrotreating reactions were carried out in one stage reactor over high metal  Ni W/γ-Al2O3 prepared catalyst at different temperatures 275-350oC, pressures 32-62 bar, LHSV 1-4 hr-1, and H2/HC ratios 200-500. The prepared catalyst was pre-sulfided remarkably at low temperature and high pressure to avoid risky of sintering associated with gaining the active sulfide phase at high temperatures.  Results showed an obvious differences between HDS and HAD rates due to difficulty of polyaromatics saturation compared with desulfurization. Sulfur and

This work studied the facilitation of the transportation of Sharqi Baghdad heavy crude oil characterized with high viscosity 51.6 cSt at 40 °C, low API 18.8, and high asphaltenes content 7.1 wt.%, by reducing its viscosity from break down asphaltene agglomerates using different types of hydrocarbon and oxygenated polar solvents such as toluene, methanol, mix xylenes, and reformate. The best results are obtained by using methanol because it owns a high efficiency to reduce viscosity of crude oil to 21.1 cSt at 40 °C. Toluene, xylenes and reformate decreased viscosity to 25.3, 27.5 and 28,4 cSt at 40 °C, respectively. Asphaltenes content decreased to 4.2 wt. % by using toluene at 110 °C. And best improvement in API of the heavy cr