The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

There many methods for estimation of permeability. In this Paper, permeability has been estimated by two methods. The conventional and modified methods are used to calculate flow zone indicator (FZI). The hydraulic flow unit (HU) was identified by FZI technique. This technique is effective in predicting the permeability in un-cored intervals/wells. HU is related with FZI and rock quality index (RQI). All available cores from 7 wells (Su -4, Su -5, Su -7, Su -8, Su -9, Su -12, and Su -14) were used to be database for HU classification. The plot of probability cumulative of FZI is used. The plot of core-derived probability FZI for both modified and conventional method which indicates 4 Hu (A, B, C and D) for Nahr Umr forma

Georeferencing process is one of the most important prerequisites for various geomatics applications; for example, photogrammetry, laser scan analysis, remotely sensing, spatial and descriptive data collection, and others. Georeferencing mostly involves the transformation of coordinates obtained from images that are inhomogeneous due to accuracy differences. The georeferencing depends on image resolution and accuracy level of measurements of reference points ground coordinates.  Accordingly, this study discusses the subject of coordinate’s transformation from the image to the global coordinates system (WGS84) to find a suitable method that provides more accurate results. In this study, the Artificial Neural Network (ANN) method wa

The main objective of this study is to develop predictive models using SPSS software (version 18) for Marshall Test results of asphalt mixtures compacted by Hammer, Gyratory, and Roller compaction. Bulk density of (2.351) gm/cc, at OAC of (4.7) % was obtained as a benchmark after using Marshall Compactor as laboratory compactive effort with 75-blows. Same density was achieved by Roller and Gyratory Compactors using its mix designed methods.

A total of (75) specimens, for Marshall, Gyratory, and Roller Compactors have been prepared, based on OAC of (4.7) % with an additional asphalt contents of more and less than (0.5) % from the optimum value. All specimens have been subjected to Marshall Test. Mathematical model

Frequently, load associated mode of failure, rutting and fatigue, are the main failure types found in some newly constructed roads within Baghdad, the capital of Iraq, and some suburban areas. The use of excessive amount of natural sand in asphalt concrete mixes which is attractive to local contractors could be one of the possible causes to the lack of strength properties of the mixes resulting in frustration in the pavement performance. In this study, the performance properties of asphalt concrete mixes with two natural sand types, desert and river sands, were evaluated. Moreover, five replacement rates of 0, 25, 50, 75, and 100% by weight of the fine aggregate finer than 4.75 were used. The performance properties including moisture susc

The presented research aims to manipulate and improve the aging behaviors of concrete composite systems by employing ecologically safe date palm (seeds and husks) waste as a filler. In addition, optimized workability, durability, and erosion resistance properties for the new material were investigated.
The experimental work included the application of different mixing ratios (50/50, 30/70, and 70/30) of husk date/ date seeds to study the enhanced physicochemical behaviors and erosion resistant of bio-waste-concrete composite system exposed to severe temperature conditions (50 ºC) for a time period of 25 days. Optimum results were observed for samples reinforced with the natural filler with a ratio of 50/50 in comparison to the base

The studies on unbonded post-tensioned concrete members strengthened with Carbon Fiber Reinforced Polymers (CFRPs) are limited and the effect of strengthening on the strain of unbonded pre-stressed steel is not well characterized. Estimating the flexural capacity of unbound post-tensioned members using the design methodology specified in the design guidelines for FRP strengthening techniques of bonded post-tensioned members does not provide a reliable evaluation. This study investigates the behavior of unbonded post-tensioned concrete members with partial strand damage (14.3% and 28.6% damage) and strengthened with CFRP laminates using a near-surface mounted technique with and without U-wrap anchorages. The experimental results show

This study was conducted to determining the variable effects on water quality of Greater Zab River in Erbil province, Iraq, using multivariate statistical analysis. Seventeen variables were monitored in four sampling sites during one year (from May 2012 to April 2013). The dataset were treated using principal component analysis (PCA)/ factor analysis (FA), cluster analysis (CA) to the most important factors affecting water quality, sources of pollution and suitability of water for drinking consumption and irrigation. Six factors were identified as responsible for the data structure explaining 73.5% of the total variance in the dataset and are conditionally named, hydrochemical from weathering, mineral salts and domestic wastes. CA showed