Journal of University of Babylon

Due to increased maintenance and rehabilitation actions, significant volumes of Reclaimed Asphalt Pavement (RAP) are left in stockpiles. Replacing aggregate in Portland Cement Concrete (PCC) with additional RAP could help eliminate surplus RAP stockpiles and reduce PCC's natural aggregate consumption, positively impacting the environment and the economy. This paper is a state-of-the-art review of the literature on using RAP to Roller-compacted Concrete pavement (RCCP). The potential of RAP aggregates has been assessed based on their characteristics and the optimum moisture content (OMC), maximum dry density (MDD), compressive strength, splitting tensile strength, flexural strength, modulus of elasticity, abrasion resistance, shrinkage, porosity, water absorption, and freeze-thaw of RCCP. The literature study illustrated how a low-density, smooth-textured hydrophobic asphalt covering surrounds RAP aggregates. potentially reducing the maximum dry density (MDD) and optimum moisture content (OMC) of RCCP mixtures. This asphalt layer could reduce RAP's ability to bind with cement paste, reducing its strength properties. In addition, the hydrophobic nature of RAP may reduce porosity and water absorption. On the other hand, agglomerates and dust can have the reverse impact. Pavement application might be done with a lower replacement of RAP (less than 50%) without affecting the pavement's strength, porosity, or water absorption. However, Increasing the replacement of RAP aggregate may not be conducive to mechanical performance, but it has the potential to enhance the toughness and energy absorption capacity of pavements.

This paper introduces the turbine governor (TG) and automatic voltage regulator (AVR) and new Adaptive Neuro-Fuzzy Inference System (ANFIS) to search for improvement and the stability. MATLAB use on 3bus system and 3-phase faults between B1 and B2 systems with and without (TG), (AVR) and (ANFIS) at t_f = 5 sec. and t_c = 5.2 sec. From the results obtained from the simulations, conclude that the voltage is in a stable state whether the rotor angle is stable or unstable. (TG), (AVR) and (ANFIS) use in the grid have a role in the transient stability of the system and the voltage is improved.

Phenol is highly toxic even if it is present in very low concentrations. Industrial wastes from petroleum refineries generally contain phenol which must be treated. In situations when conventional techniques are unable to control phenol degradation, the electrochemical oxidation process has emerged as a solution to this problem. This study examines the effectiveness of a pilot electrochemical system that removes phenol from refinery wastewater using a rotating anode-induced basket electrochemical novel reactor technique. A rotary anode was used to increase the efficiency of the process and was also used (10%CuO/ γ- Al2O3) as a catalyst. The experimental results showed that by increasing the rotating speed and increasing the voltage of the power supply of the electrochemical reactor, the phenol removal increased. It was also found that when the concentration of phenol increased, the removal rate was decreased.

This paper looks for the possibility of using a seal, formed from an old truck’s tube, in self-drill bolt to mount sheets on solid frame. A general study of a seal’s strength in self-drill bolt is performed with Ansys workbench 2022R1, which is a finite element model software to analysis the stresses and deformations. Two types of rubber’s seal are used in the analysis, Neoprene and Elastomer, the elastomer is an equivalent rubber of tire’s tube. The metal washer, which is a part of self-drill bolt and located above the seal, is involved in all the simulations. Also, the shape of metal washer is considered in analysis for both rubber’s types. The shape used in the simulation are a semi conic and conic. Because there are several rubber’s types and metal washer’s shapes, five different modeling analyses are made with Workbench 2022R1. All dimensions and sizes of the parts in all modeling are taken from dimensions of the real parts available in local markets. The results show the tube’s rubber is a good replacement and has the best results with conic metal washer. In the case of not using tube’s rubber, a Neoprene seal bonded to conic metal washer is a second good choice. To make sure of the success of tube’s rubber, a simple experiment is made and its results approve, without debt, the possibility of using tube’s rubber as a seal.

Biaxially loaded reinforced concrete columns are structural components impacted by axial compression and bending forces in two directions. This study involves retrofitting of preloaded columns using ferrocement jacketing consists of high performance mortar and reinforced with geogrid mesh. Six reinforced concrete short columns (150*150*1700) mm are cast with concrete bracket at each end. Two of them served as control columns which are loaded till failure, while the other four columns are preloaded and then retrofitted. They are preloaded up to (65 & 85) % of the total failure loads of control specimens. The eccentricity value of loading changed between (30) mm and (70) mm for the both axes. The results proved that using this technique of retrofitting increases the ultimate carrying capacity of the preloaded columns up to (38.8) % comparing to the control specimens. It also improves their crack resistance and failure behavior. Finally, the experimental results are compared with the analytical results obtained from finite element analysis (FEA) using ABAQUS program.

Many cities in Iraq are currently exposed a rise in temperatures. Most of the urban forms observed in these cities are not suitable for such harsh conditions, as residential units, buildings and high-rise facilities have been planned and designed in a way that hinders the movement and transfer of air masses between different locations. In addition, the lack of vegetation cover, water bodies, and the use of building materials with high thermal retention capacity exacerbate the problem. In order to investigate one of the factors contributing to the aggravation of the urban heat island phenomenon, it is very necessary to study the role of vegetation cover. This element is of great importance due to its multifaceted benefits, including increasing oxygen levels in the atmosphere and its positive impacts on economic and recreational activities. To identify the most effective vegetation cover area to mitigate air temperature in urban areas, we conducted this study in Babil Governorate in Iraq. We used remote sensing applications to create thermal, vegetation, and image maps within the study area, where we identified several types of land cover, such as vegetation, barren lands, rural buildings, urban buildings, and streets. We excluded water bodies from our analysis because they can affect the relationship between vegetation cover and surface temperature. It is important to note that low vegetation usually leads to high surface temperature in dry areas, and on the other hand, low vegetation leads to low surface temperature of water bodies, which leads to a decrease in the correlation coefficient between vegetation index and surface temperature. A map of normalized difference vegetation index (NDVI) was created for a selected model within the geographical boundaries of Babylon Governorate. In addition, a map of surface temperature (LST) was created for the same area. A model consisting of (386) points was created by integrating heat maps and vegetation data. Then, a table was carefully prepared to include the above values, and correlations were created. Linear, logarithmic and polynomial regression models were evaluated, and the model with the highest correlation coefficient was chosen. We also found an approximate relationship between NDVI and the percentage of green areas, then the two relationships were linked by imposing the target temperature and extracting the approximate green area required to bring the surface temperature to the target level.

Facial expression recognition is an evolving field of research with various applications in system development. Recognizing facial expressions is particularly crucial in discourse construction. This study focuses on the design of a grammatical facial expressions (GFEs) recognition system that depended on extracted features from the estimation of head pose and detection of Action Units (AUs) in order to recognize grammatical expressions. The Facial Action Coding System (FACS) is utilized to depict AUs, which effectively capture and classify the intricate movements of facial muscles. Among the AUs, AUs 1 and 4 serve as potential indicators for recognizing grammatical expressions. The process of estimating head pose produces characteristics, including Euler angles (namely, pitch, roll, and yaw), as well as 3D coordinates, which signify the relative arrangements of facial landmarks in correspondence to the camera. The present study employs a dataset comprising video recordings obtained from a sample of 53 individuals whose ages range from 18 to 44 years. Two distinct classifications, namely Multilayer Perceptron (MLP) and K-Nearest Neighbor (KNN), are employed in the final stage of the proposed system. The experimental outcomes show that the KNN classifier attains better efficacy in contrast to the MLP classifier.

Heavy metals are currently recognized as one of the most serious environmental challenges, as well as one of the most dangerous environmental contaminants. Due to these metals' toxicity, inability to biodegrade, and tendency to accumulate in organisms and enter the human food chain, they are responsible for a wide range of diseases. Many techniques, including chemical precipitation, membrane filtration, coagulation and flocculation, flotation, electrochemical methods, adsorption, and ion exchange, can be used to remove heavy metal ions from wastewater. several key factors should be considered to ensure effective and efficient treatment methods such as effectiveness, cost, scalability, compatibility with wastewater characteristics, residual management, and environmental impact. A detailed explanation of the ion exchange method was provided because this technique shows great promise in terms of selectivity, availability, thermal stability, chemical compatibility, ionic capacity, and regeneration capability. This study will contribute to the field of sustainable materials science and environmental remediation.

Segmentation of Brain tumors refers to a crucial function in medical image processing. Despite a lot of main attempts and satisfactory results in such a field, appropriate classification and segmentation remain an important function. Segmentation of an image is a hard task in the processing of an image. In order to improve the efficiency of processing, analysis, and detection, hospitals have already begun to use machine learning (ML). To increase the speed of the recovery process started, doctors could get help with detection. In the last few years, techniques of machine learning have illustrated satisfactory performance in solving different issues of computer vision like semantic segmentation, image classification as well as object diagnosis. Several ML-based methods have been successfully applied to the problem of brain tumor segmentation. The present paper shows an overview of recent ML and deep learning techniques to diagnose and group brain illnesses from MRI images. More than 60 scientific studies are chosen and discussed here, covering technical features like network architecture design, and segmentation.

Motorcycles are one of the most widely used travel modes in many developing countries, and therefore motorcycle crashes are more dangerous than other vehicles, as for every mile traveled by vehicles, the rate of motorcycle crashes increases. Therefore, many factors contribute to increasing the rate of injuries, including not following safety rules, such as wearing a helmet, exceeding the permitted speed, using things that distract the leg, drinking alcohol, and other factors that help increase the rate of injuries. Motorcycle crashes remain a significant public health concern worldwide, with severe consequences for riders and other road users. Understanding the factors contributing to the severity of motorcycle crashes is crucial for developing effective interventions to reduce their impact. This study presents a scientometric analysis aimed at identifying and synthesizing the key factors associated with the severity of motorcycle crashes. Through a systematic review of the literature using scientometric techniques, including co-occurrence analysis and citation analysis, we examined trends, patterns, and relationships among factors influencing crash severity. Our analysis revealed several prominent factors contributing to the severity of motorcycle crashes, including rider characteristics (e.g., age, experience), environmental factors (e.g., road conditions, weather), vehicle-related factors (e.g., type of motorcycle, helmet use), and behavioral factors (e.g., speeding, alcohol impairment). Additionally, we identified emerging areas of research, such as the influence of advanced safety technologies and the impact of urbanization on motorcycle crash severity.

Communications systems based on fiber optics suffer from nonlinear effects. These nonlinear effects severely restrict wavelength division multiplexing (WDM) and thus impair the performance of the optical transmission system. A Polarization Combiner (PC) is one of the promising techniques that mitigates the nonlinear effects, especially interference. This work proposes a system that use PC with different modulation schemes including Return to Zero (RZ), Non-Return to Zero (NRZ), and Carrier-Suppressed Return-to-Zero (CSRZ) in a nonlinear optical fiber communication system. The performance of the proposed system was tested under different conditions, including changing the input power and at data transfer rates including (100 and 200) Gbps. It was shown from the results that the modulation form RZ provides the best performance, as nonlinear effects in optical fibers are decreased. Moreover, when the transmission distance is equal to 60 km, the RZ gives a Q-factor equal to 8.4. However, the Q-factors are equal to 1.44 and 6 when using NRZ and CSRZ respectively.

The one-dimensional model was selected to simulate the steam reforming to produce hydrogen in a fixed-bed reactor filled with catalyst particles. The model consists of mass balance of all stream components , heat balance on gas inside the reactor and tube wall reactor. This model was solved by using MATLAB/Simulink. The simulation results have been compared with actual data to validate the model. It was found the good agreement between the main exit molar rate and reformed gas temperature from the reforming reactor and the commercial reformer. Three different control methods were designed which are proportional-integral derivative, cascade and multi-loop to maintain the exit gas temperature. A comparison between these control methods have been made by using step change at different values of feed conditions. These results show that the multi-loop controller has rapidity, very good durability, more suitable, little offset, lower overshoot and less integral absolute error.