The primary objective of this study is to manage price market items in the construction of walls for affordable structures with load-bearing hollow masonry units using the ACI 211.1 blend design with a slump range of 25-50 mm that follows the specification limits of IQS 1077. It was difficult to reach a suitable cement weight to minimum content (economic and environmental goal), so many trail mixtures were cast. A portion (10-20%) of the coarse aggregates was replaced with concrete, tile, and clay-brick waste. Finally, two curing methods were used: immersion under water as normal curing, and water spraying as it is closer to the field conditions. The recommendation in IQS 1077 to increase the curing period from 14 to 28 days was taken into account. The results proved that the compressive strength of the blocks of cured immersion under water increased by 2.63%-0.63% and 5.12%-7.88% for 10% and 20% concrete waste aggregates, decreased by 0,3.84% and 4.22%,6.41% for 10% and 20% tile waste aggregates, and decrease by 5.71%-6.10% and 12.1%-11.4% for 10% and 20% brick waste aggregates, respectively at 14 and 28 days, and beams that were cured by spraying performed a little worse than those immersed under water.
he assignment model represents a mathematical model that aims at expressing an important problem facing enterprises and companies in the public and private sectors, which are characterized by ensuring their activities, in order to take the appropriate decision to get the best allocation of tasks for machines or jobs or workers on the machines that he owns in order to increase profits or reduce costs and time As this model is called multi-objective assignment because it takes into account the factors of time and cost together and hence we have two goals for the assignment problem, so it is not possible to solve by the usual methods and has been resorted to the use of multiple programming The objectives were to solve the problem of
... Show MoreIn this paper, the method of estimating the variation of Zenith Path Delay (ZPD) estimation method will be illustrate and evaluate using Real Time Kinematic Differential Global Positioning System (RTK-DGPS). The GPS provides a relative method to remotely sense atmospheric water vapor in any weather condition. The GPS signal delay in the atmosphere can be expressed as ZPD. In order to evaluate the results, four points had been chosen in the university of Baghdad campus to be rover ones, with a fixed Base point. For each rover position a 155 day of coordinates measurements was collected to overcome the results. Many models and mathematic calculations were used to extract the ZPD using the Matlab environment. The result shows that the ZPD valu
... Show MoreSemi-parametric regression models have been studied in a variety of applications and scientific fields due to their high flexibility in dealing with data that has problems, as they are characterized by the ease of interpretation of the parameter part while retaining the flexibility of the non-parametric part. The response variable or explanatory variables can have outliers, and the OLS approach have the sensitivity to outliers. To address this issue, robust (resistance) methods were used, which are less sensitive in the presence of outlier values in the data. This study aims to estimate the partial regression model using the robust estimation method with the wavel
... Show MoreCOVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in
The Mishrif Formation is one of the most important geological formations in Iraq consisting of limestone, marl, and shale layers since it is one of the main oil producing reservoirs in the country, which contain a significant portion of Iraq's oil reserves. The formation has been extensively explored and developed by the Iraqi government and international oil companies, with many oil fields being developed within it. The accurate evaluation of the Mishrif formation is key to the successful exploitation of this field. However, its geological complexity poses significant challenges for oil production, requiring advanced techniques to accurately evaluate its petrophysical properties.
This study used advanced well-logging analysi
... Show MoreST Alawi, NA Mustafa, Al-Mustansiriyah Journal of Science, 2013
Abstract: Stars whose initial masses are between (0.89 - 8.0) M☉ go through an Asymptotic Giant Branch (AGB) phase at the end of their life. Which have been evolved from the main sequence phase through Asymptotic Giant Branch (AGB). The calculations were done by adopted Synthetic Model showed the following results: 1- Mass loss on the AGB phase consists of two phases for period (P <500) days and for (P>500) days; 2- the mass loss rate exponentially increases with the pulsation periods; 3- The expansion velocity VAGB for our stars are calculated according to the three assumptions; 4- the terminal velocity depends on several factors likes metallicity and luminosity. The calculations indicated that a super wind phase (S.W) developed on the A
... Show MoreThe research aims to determine the mix of production optimization in the case of several conflicting objectives to be achieved at the same time, therefore, discussions dealt with the concept of programming goals and entrances to be resolved and dealt with the general formula for the programming model the goals and finally determine the mix of production optimization using a programming model targets to the default case.
Projects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postpo