The current Iraqi standard specifications for roads and bridges allowed the prepared Job-Mix Formula for asphalt mixtures to witness some tolerances with regard to the following: coarse aggregate gradation by ± 6.0 %, fine aggregate gradation by ± 4.0 %, filler gradation by ± 2.0 %, asphalt cement content by ± 0.3 % and mixing temperature by ± 15 oC. The objective of this work is to evaluate the behavior of asphalt mixtures prepared by different aggregates gradations (12.5 mm nominal maximum size) that fabricated by several asphalt contents (40-50 grade) and various mixing temperature. All the tolerances specified in the specifications are taken into account, furthermore, the zones beyond these tolerances
... Show MoreTensile strength is a critical property of Hot Mix Asphalt (HMA) pavements and is closely related to distresses such as fatigue cracking. This study aims to evaluate methods for assessing fatigue cracking in Asphalt Concrete (AC) mixes. In order to achieve optimum density at different binder contents, the mixes were compressed using a gyratory compactor. Tensile strength was assessed using the Indirect Tensile (IDT) and Semi-Circular Bend (SCB) tests. The results showed that the tensile strength measured by the SCB test was consistently higher than that measured by the IDT test at 25 °C. In addition, the SCB test showed a stronger correlation between increasing binder content and tensile strength. For binder contents ranging from 4
... Show MoreCoronavirus: (COVID-19) is a recently discovered viral disease caused by a new strain of coronavirus.
The majority of patients with corona-virus infections will have a mild-moderate respiratory disease that recovers without special care. Most often, the elderly, and others with chronic medical conditions such as asthma, coronary disease, respiratory illness, and malignancy are seriously ill.
COVID-19 is spread mostly by salivary droplets or nasal secretions when an infected person coughs or sneezes.
COVID-19 causes severe acute respiratory illness (SARS-COV-2). The first incidence was recorded in Wuhan, China, in 2019. Since then it spreads leading to a pandemic.
... Show MoreKE Sharquie, AA Noaimi, BO Saleh, ZN Anbar…, Saudi Med J, 2009 - Cited by 13
Fractal geometry is receiving increase attention as a quantitative and qualitative model for natural phenomena description, which can establish an active classification technique when applied on satellite images. In this paper, a satellite image is used which was taken by Quick Bird that contains different visible classes. After pre-processing, this image passes through two stages: segmentation and classification. The segmentation carried out by hybrid two methods used to produce effective results; the two methods are Quadtree method that operated inside Horizontal-Vertical method. The hybrid method is segmented the image into two rectangular blocks, either horizontally or vertically depending on spectral uniformity crit
... Show More<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c
... Show MoreSupport vector machine (SVM) is a popular supervised learning algorithm based on margin maximization. It has a high training cost and does not scale well to a large number of data points. We propose a multiresolution algorithm MRH-SVM that trains SVM on a hierarchical data aggregation structure, which also serves as a common data input to other learning algorithms. The proposed algorithm learns SVM models using high-level data aggregates and only visits data aggregates at more detailed levels where support vectors reside. In addition to performance improvements, the algorithm has advantages such as the ability to handle data streams and datasets with imbalanced classes. Experimental results show significant performance improvements in compa
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