Rutting has a significant impact on the pavements' performance. Rutting depth is often used as a parameter to assess the quality of pavements. The Asphalt Institute (AI) design method prescribes a maximum allowable rutting depth of 13mm, whereas the AASHTO design method stipulates a critical serviceability index of 2.5 which is equivalent to an average rutting depth of 15mm. In this research, static and repeated compression tests were performed to evaluate the permanent strain based on (1) the relationship between mix properties (asphalt content and type), and (2) testing temperature. The results indicated that the accumulated plastic strain was higher during the repeated load test than that during the static load tests. Notably, temperatur
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In this work, an experimental investigation has been done for heat transfer by natural-convection through a horizontal concentric annulus with porous media effects. The porous structure in gap spacing consists of a glass balls and replaced by plastic (PVC) balls with different sizes. The outer surface of outer tube is isothermally cooled while the outer surface of inner tube is heated with constant heat flux condition. The inner tube is heated with different supplied electrical power levels. Four different radius ratios of annulus are used. The effects of porous media material, particles size and annulus radius ratio on heat dissipation in terms of average Nusselt number have been analyzed. |
Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o
Objective (s): To determine proportion of anemia among sample of Pregnant women. To identify factors
associated with the anemia (Maternal age, maternal education, gestational age, parity, gravidity, birth
interval, smoking, taking iron supplements and dietary habits).
Methodology: A cross-sectional study conducted at Al- washash & Bab-almoadham primary health care
centers. The sample was selected by (non-probability convenient sampling) and sample size was (550).
The study started from 1st March 2011 to 30th of March 2012. The data was collected by direct interview
using special questionnaire to obtained socio-demographic information.
Results: the result shows that mean age of the subjects was 26.5± 7.5 years, 8
The energy requirements of corn silage harvesters and the application of precision agricultural techniques are essential for efficient and productive agricultural practices. The article aims to review previous studies on the energy requirements needed for different corn silage harvesting machines, and on the other hand, to present methods for measuring corn silage productivity directly in the field and monitoring it based on microcontrollers and artificial intelligence techniques. The process of making corn silage is done by cutting green fodder plants into small pieces, so special harvesters are used for this, called corn silage harvesters. The purpose of harvesting corn silage is to efficiently collect and store as many digestible nutrien
... Show Morethis paper contains preparation of Active carbon surface (AC) from pro so millet grain husks and Loading and activating by Iron oxide and hydrogen peroxide sequentially to obtain surface (ACIPE). The changes of previous processes on Active carbon surface were diagnosed by Fourier transform infrared spectroscopy (FTIR) and Scanning electron microscopy ( SEM ). These surfaces (AC and ACIPE ) were using as adsorbent for removing of congo red dye from aqueous solutions under certain conditions through batch system. More than one kinetic model was applied to congo red dye adsorption process and it was found that the most kinetic model applied to it is a model ( pseudo second order model).
This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.
Fuzzy logic is used to solve the load flow and contingency analysis problems, so decreasing computing time and its the best selection instead of the traditional methods. The proposed method is very accurate with outstanding computation time, which made the fuzzy load flow (FLF) suitable for real time application for small- as well as large-scale power systems. In addition that, the FLF efficiently able to solve load flow problem of ill-conditioned power systems and contingency analysis. The FLF method using Gaussian membership function requires less number of iterations and less computing time than that required in the FLF method using triangular membership function. Using sparsity technique for the input Ybus sparse matrix data gi
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