Misan Journal of Engineering Sciences

This study investigates the torsional strength of beams made of a reactive powder concrete mix containing fine recycled aggregate. It also studies the mechanical properties of reactive powder concrete (RPC) in its fresh and hard state and the impacts of replacing it with recycled aggregate in different grading sizes. Seven RPC beams were examined and divided into two groups: the first group (control 0%, 20%, 40%, and 60%) of replacement with natural fine aggregate (600μm) and the second group at constant replacement 40% with different grading maximum sizes (1.18 mm, 2.36 mm, and 4.75 mm). The results indicate that reactive powder concrete at 40% replacement and particle size 2.36 mm of recycled aggregate gives the highest result regarding torsion behavior strength.

Millimeter wave (mmWave) is a crucial frequency range for fifth-generation (5G) mobile communication, characterized by wide bandwidth and higher data rates. Antenna components will be small, wideband, and high-gain for use in 5G systems. This study presents the design and simulation of an ultra-wideband rectangular antenna with T-shaped slots, developed using an evolutionary-oriented method for 5G mmWave applications. The antenna dimensions are tiny, with a width of 17 mm and a length of 16 mm. The suggested antenna is constructed utilizing a Rogers RT5580 substrate with a thickness of 0.254 mm. The operating bandwidth of the antenna element is between 25.45 GHz and 44.25 GHz, including 5G frequency ranges. The results show a steady end-fire radiation pattern with a gain of more than 9.5 dBi across the whole frequency range. The suggested antenna's improvements and benefits for 5G specs, bandwidth, and small size are supported by the most recent study in the field. The suggested antenna element works well with large radio communities and 5G multi-input multi-output (MIMO) applications.

Fiber Reinforced Polymer (FRP) reinforcement bars have been increasingly utilized in reinforced concrete structures over the last two decades, substituting conventional steel reinforcement, particularly in places facing challenging environmental circumstances. A literature review is presented in this article, with the primary focus being on the bond performance of FRP bars to concrete. The purpose of this study is to cover all of the useful contributions that have been made on the bond performance in earlier research. This work is based on results from the collection of experimental data from a total of 1784 pullout tests in the existing literature. The bonding performance of FRP bars with concrete represents an extremely essential characteristic for assembling the FRP bars into corrosion-free reinforced concrete structures. FRP materials, contrary to steel reinforcements, possess non-homogeneous, anisotropic, and elastically linear features, thus resulting in a distinct force transfer mechanism between concrete and reinforcement. The most significant parameters influencing the bonding of FRP bars to concrete were outlined in this paper. The information gathered through the investigation indicated that FRP bars behave effectively as reinforcement components in reinforced concrete structures.

This paper presents an innovative concept to improve the load carrying capacity, settlement, and the lateral deformation characteristics of the granular-pile by incorporating biopolymer as a binder to the fill materials of the granu-lar pile. This natural biopolymer is sustainable and eco-friendly substitute binder to the conventional binder ( cement, lime), which have sever impacts on the environment. A series of loading tests using large scale models was performed considering different biopolymer contents, various ratio of footing diameter to pile diameter df/Dp, and fiber content. Results revealed that the incorporating biopolymerresulted in stiffening granular pile and eliminate the common bulging failure. Therefore, load carrying capacityincreased significantly, corresponding with clear restraint against the lateral deformation. For ground reinforced with ordinary granular pile considering df/Dp of 1.5, 1.25, 1.0, 0.75 and 0.5, the bearing pressure increased from 60 kN/m2 for the native ground to 65, 110, 157, 185 and 230 kN/m2 respectively. Compared with 230 kN/m2 for the ordinary granular pile with df/Dp = 0.5, bearing pressure increased to 245, 304, 525, 638 and 649 kN/m2 when 1, 2, 4, 6 and 8% of biopolymer was incorporated with the granular material of the pile, respectively. However, with increasing df/Dp to 1.5, the capacity increased from 65 kN/m2 for the ordinary granular pile to 74, 107, 144, 442, and 495 kN/m2 for biopolymer-granular pile considering the aforementioned contents of the biopolymer respectively.

The ionosphere's condition affects how HF radio waves propagate, which changes over time of day, season, and Solar activity conditions. These waves, when propagating through ions, are affected by several factors, including refraction, reflection, and absorption. To reduce these effects, ray tracing is an important tool that depends on atmospheric communication, relying on the IRI model to describe the ionosphere's parameters. This paper is an overview of the ionosphere and reviews the IRI model and ray tracing technique. IRI is acknowledged as the ionosphere's official standard by the organization for international standards, International Radio Science Union, Europe's collaboration with the Space Research Committee to promote space. According to these organizations, the IRI is a pilot (data-based) model that represents the basic parameters of the ionosphere based on the ion cover data record.

In the majority of hospitals and clinics, doctors currently employ medical images, including brain MRIs, ultrasounds, and X-ray images, to diagnose a variety of severe diseases. Image encryption is critical for safeguarding data confidentiality from fraudulent use and illegal access in eHealth applications. Chaos is an exceptionally powerful cryptographic resource since its inception in image-encryption methods. This work offers a comprehensive overview of the evolution of algorithms for image encryption based on chaos theory, including both symmetric and asymmetric approaches. This research is distinguished from previous review research, which addressed many varied methods of chaos-based image encryption and focused on theoretical aspects only; these techniques could be used in digital medical records of hospital patients and telemedicine communication. This analysis revealed that the most favorable outcomes were presented in the method using the Blum-Goldwasser Cryptosystem (BGC) and Elliptic Curve Cryptography (ECC) with NPCR of 99.6901% and UACI of 33.694%. The review demonstrated that these algorithms offer robust security and intricacy regarding keys. However, certain studies have identified challenges associated with the complexity of keys and the time required for implementation in real-time. The paper suggests that the efficacy of algorithms should be enhanced and evaluated on a broader scale than image types. It begins with a comprehensive introduction to image encryption, which addresses the fundamental concepts. Then, it conducts a thorough examination of chaos-based image encryption, that encompasses a variety of methods and approaches within this field.

Fiber meshes are used in concrete slabs to strengthen the concrete and slow the spread of cracks, which raises the concrete modulus of elasticity and plasticity. This paper presents the experimental study conducted on six concrete slabs resting on the Winkler support with square dimensions of (800×800) mm and a thickness of (100) mm, with a fabricated steel mesh (∅4mm@150mm) located near the center section of the slab, and strengthened with different types which of fiber meshes are fiberglass, polypropylene, carbon, geogrid and waste rubber fibers, located in the tension and compression zones. The Winkler foundation is used to represent the ground soil in the study of concrete slabs on the ground in terms of toughness, stiffness, and ductility index. Twelve rubber supports with a stiffness of (7500) kN/m are used, and they are supported by a steel plate that is (800×800) mm in size and has a thickness of (10) mm. According to the testing results, all of the specimens strengthened with fiber meshes have shown a considerable improvement in toughness and ductility index, especially the specimen that strengthened two-layer carbon fiber meshes, where the increases were 331.8% and 4.76 respectively, and a large improvement in the stiffness was in the specimen that strengthens two-layer glass fibers by 44.2%. The slab-strengthened polypropylene has the lowest percentage increase in toughness (22.1%), while the slab-strengthened geogrid and waste rubber has the lowest percentage increases in stiffness (37.2%) and lowest improvement in the plasticity index was in slab-strengthened two-layer from polypropylene fiber by (1.90). Early cracking appeared in the slab-strengthened polypropylene, which had less load capacity than the other specimens, and the maximum ultimate load was (45.5) kN/mm, which is near the maximum ultimate load of the control slab.

Early identification of Autism Spectrum Disorder (ASD) in school-aged children is critical, as timely intervention has been shown to markedly enhance developmental trajectories. This study investigates the feasibility of facial image analysis for ASD screening by leveraging four pre-trained convolutional neural network (CNN) architectures—VGG-16, InceptionV3, EfficientNet-B0, and EfficientNet-B7—applied to a balanced dataset comprising 2,540 labeled facial images (1,327 autistic and 1,327 non-autistic), curated from a publicly available Kaggle repository. VGG-16 yielded the highest classification accuracy at 84.33%, followed closely by EfficientNet-B0 (83.67%), InceptionV3 (81.00%), and EfficientNet-B7 (80.00%). To assess the robustness of these findings, we conducted five independent training runs per model, followed by statistical significance testing using one-sample t-tests and one-way ANOVA. All models significantly outperformed the chance baseline (p < 0.05), though pairwise differences in accuracy did not reach statistical significance at the α = 0.05 level. Unlike many prior studies that employed limited or imbalanced datasets, or assessed only a single architecture, this work offers a systematic comparative evaluation under uniform training conditions with a specific focus on school-aged populations. The results suggest that CNN-based facial analysis holds promise as a non-invasive, scalable adjunct screening method, particularly suited for deployment in educational contexts where clinical resources may be constrained.

The co-polymer surfactant, 2-(4-(Methoxy carbonyl)-2,4-dimethyl hexanamido)-2-methyl propane-1-sulfonic acid (M1) at diffident concentrations (250,500,750 & 1000) ppm, was produced and studied structurally by Fourier-transform infrared (FTIR) spectroscopy, 1H NMR, 13C NMR, and elemental analysis. The corrosion inhibition efficacy of M1 on mild steel in 1 M HCl solution was assessed via Potentiodynamic polarization. The results indicated a notable reduction in corrosion rates with different concentrations of M1 at 25°C. M1 attained a corrosion inhibition efficacy of 77.528% at an optimal concentration of 1000 ppm. Tafel polarization investigations indicated that M1 functions as a mixed-type inhibitor, inhibiting both cathodic and anodic processes. The adsorption characteristics of M1 on the mild steel surface were optimally represented by the Langmuir adsorption isotherm, signifying a blend of physical and chemical adsorption mechanisms.

The deterioration of reinforced concrete structures due to exposure to fire and high temperatures remains a major challenge in structural engineering. High temperatures negatively affect the mechanical properties of concrete, particularly its load-bearing capacity, which can lead to premature structural failure before the designed service life. In this experimental study, five reinforced concrete slab specimens, each measuring 1000 × 400 mm, were prepared and tested. The concrete was poured with varying reinforcement ratios ranging from 0.0037, 0.009, 0.012, 0.0075, and 0.007, while the slab thicknesses ranged from 50 mm to 80 mm. The specimens were subjected to various thermal exposure conditions to evaluate the effects of fire-induced deterioration on their structural behavior. All specimens were then tested under a single-point central load at mid-span until structural failure occurred. The results indicated a significant decrease in the compressive strength and load-bearing capacity of concrete between (25-75%) at elevated temperatures.

The high operating temperature of photovoltaic (PV) modules significantly reduces their electrical efficiency and hinders the advancement of PV applications. Although various cooling techniques have been proposed, many exhibit limited effectiveness due to inadequate heat transfer rate between the cooling medium and the PV module surface. In this study, a PV/T system incorporating a serpentine cooling channel was designed to enhance the thermal and electrical performance of PV/T systems. Water was used as the cooling fluid due to its favorable thermal properties and availability. The system's performance was evaluated experimentally at Misan University, located in southern Iraq, during the months of August and September, when solar radiation is typically high. The results demonstrated that the average electrical efficiency of the PV module improved by 3%, increasing from 7.5% to 10.5% when Reynolds number (Re) rose from 750 to 1250. Moreover, the average cell temperature in the proposed serpentine channel design was reduced by 6°C compared to conventional PV modules. The findings also indicated that the new cooling configuration performed more effectively under high solar radiation conditions, highlighting its potential for improving PV module efficiency.

It is necessary to observe that the technologies used in the field of radio transmission and wireless communications determine the features and efficiency of networks. Given the ever-increasing need for high-speed wireless communication, Millimeter-wave (mmWave) and sub-6 GHz technologies have been developed and integrated into current communication systems. This article summaries the comparison between these two different frequency bands regarding their unique advantages, disadvantages, and their uses, while emphasizing more in their advantages. We consider hybrid integration solutions capitalizing on complementary characteristics of both frequency bands in order to achieve improved performance in 5G and beyond networks. mmWave frequencies offer high data rates and large bandwidth that is required by applications requiring extremely fast connectivity. Due to the limited range and sensitivity to obstructions, sub-6 GHz frequencies are required; however, the coverage and penetration through the obstructions are higher. By combining these technologies, hybrid systems can ensure smooth communication, increase dependability, and improve the spectrum utilization. As it considers the technical challenges, possible solutions, and performance gain of hybrid mmWave and sub-6 GHz integration, this article points out the role of increasingly sophisticated antenna designs, beamforming methods and smart spectrum control array This research gives insight into the future of wireless communication by analyzing through simulation experiments and thorough analysis of the essential elements whose successful deployment is needed in order to utilize the benefits of hybrid systems.

Understanding the mechanical behaviour of confined cylindrical shells is essential for the long-term stability of geotechnical structures such as buried pipelines and well casings. These structures often experience lateral loading when embedded in granular materials or rock, resulting in complex solid-to-solid interactions. This study investigates the stability of a metallic tube confined within such media through a combination of experimental and numerical approaches. A laboratory-scale test setup was developed to conduct controlled experiments on instrumented metallic tubes. The setup enabled the determination of the critical buckling pressure, identification of post-buckling stability loss, and monitoring of local deformations leading to failure. The study revealed that both nature (homogeneous vs. bi-material) and the stiffness of the confining medium significantly influence the critical buckling pressure and the angular extension of the single-lobe deformation pattern. Complementary finite element simulations were performed to interpret the experimental findings. The numerical results showed excellent agreement with the experimental data, validating the modelling approach. Simulations further provided detailed insights into the initiation and evolution of buckling prior to structural instability under increasing lateral confinement. These findings contribute to a deeper understanding of confined shell behaviour and have practical implications for the design and assessment of underground tubular structures.

Effective transient power sharing is critical for the stable and reliable operation of microgrids. This paper investigates the enhancement of Proportional-Integral-Derivative (PID) controller performance for a grid-forming inverter system utilizing Particle Swarm Optimization (PSO) for optimal parameter tuning. The performance of a PSO-optimized PID (PSO-PID) controller is rigorously compared against a traditionally tuned PID controller under varying reference power commands and external disturbances. Key performance aspects including time-domain response (overshoot, settling time, tracking accuracy), control effort, frequency-domain characteristics of the tracking error and phase-plane stability are meticulously. Analyzed results demonstrate that the PSO-PID controller significantly outperforms the traditional PID exhibiting substantially reduced overshoot lower error integrals (IAE and ITAE) and a more stable less aggressive control signal that remains within saturation limits.

Separating three high-purity products from a mixture of three components requires a series of columns for distillation and separation. This process results in significant operational and capital costs, as well as a substantial footprint within the plant. To address these issues, a type of distillation column referred to as a Divided Wall Distillation Column (DWDC) has been recently designed. This design incorporates a wall within the conventional distillation column, effectively partitioning the column into four distinct sections: Top, Bottom, Main fractionation, and Prefractionation. This distillation column effectively separates three components, and in some instances, four components, within a single unit. This design minimizes total costs, reduces operating expenses, and occupies less space within the facility. However, this type of distillation column (DWDC) is not represented in any of the simulation software utilized for distillation column simulations, including gPROMS ®, ASPEN Pulse ®, and HYSYS ®, among others. In this research, we developed several models that simulate the operation of (DWDC), achieving favorable verification results between the practical values and the simulation values

Internet of things (IoT) and DoS attacks are two of the modern subjects currently being discussed and studied. In this paper, An approach the defense algorithm of IDS for IoT networks’ security development contrary to attacks of DoS applying unusual ML and diagnosis has been presented. An anomaly detection is used in the provided IDS to control network traffic in an ongoing way for deviations from usual profiles. Four observed classifier algorithms have been applied: k-Nearest Neighbor (kNN), Support Vector Machine (SVM), Random Forest (RF), and Decision Tree (DT). Two feature selection mechanisms, which are Particle Swarm Optimization Algorithm (PSO) and Correlation-based Feature Selection Recursive Feature Elimination (RFE) have been used to compare their performances. The dataset of IoTID20 has been used, one of the most currently used to diagnose anomalous tasks in IoT networks, for checking our model. The best results were obtained using RF and kNN classifiers that were trained with features selected by RFE. kNN benefits from the smaller feature space since it focuses on distance measures, which are more successful with a refined set of features. RF improves decision-making by focusing on the most informative features, resulting in better overall performance. RFE notably improved kNN and DT accuracy, while SVM showed consistent results regardless of the feature of selection. These results highlight the importance of feature selection in optimizing classifiers for IoT intrusion detection , and achieved perfect scores (1,00) across all metrics.The aim from this paper is to enhance intrusion detection in iot networks by designing adual stage feature selection method based on RFE and PSO.

This study shows the possibility of predicting specific characteristicsof kerosene and gas oil using experimental measurements as inputs. Variables for programming (ANN) of artificial neuron networks. This study examines fuels from Dora refinery and investigates the relationship between fuel density and various properties such as volume, viscosity, and temperature. The correlation equation was determined by several linear regression analyses, and the coefficient (R2) showed some measurements in a strong achieved:R = 0.99986 for keosene, R= 0.99886 for gas oil.

Strong columns and weak beams (SCWB)" is a structural engineering principle that suggests a building's columns must be stronger than its beams. The beams should be flexible enough to deflect and absorb stresses, while the columns should be strong enough to support the load. It is intended to prevent the building as a whole from collapsing. When the column is stronger than the beams in a moment, the plastic hinges will move to the beam and prevent widespread damage. In this scenario, the only visible indicator of beam damage would be flexure, and people would have enough time to leave before the beams failed above them. This work is divided into nine main sections.