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 postponement of delay of interim payments is at the forefront of delay factors caused by the employer’s decision. Even the least one is to leave the job site caused by the contractor’s second part of the contract, the repeated unjustified stopping of the work at the site, without permission or notice from the client’s representatives. The developed model was applied to about 97 projects and used as a prediction model. The decision tree model shows higher accuracy in the prediction.
In this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.
In this paper, the delay integral equations in population growth will be described,discussed , studied and transfered this model to integro-differential equation. At last,we will solve this problem by using variational approach.
Abstract\
In this research, estimated the reliability of water system network in Baghdad was done. to assess its performance during a specific period. a fault tree through static and dynamic gates was belt and these gates represent logical relationships between the main events in the network and analyzed using dynamic Bayesian networks . As it has been applied Dynamic Bayesian networks estimate reliability by translating dynamic fault tree to Dynamic Bayesian networks and reliability of the system appreciated. As was the potential for the expense of each phase of the network for each gate . Because there are two parts to the Dynamic Bayesian networks and two part of gate (AND), which includes the three basic units of the
... Show MoreIn this paper, we investigate the connection between the hierarchical models and the power prior distribution in quantile regression (QReg). Under specific quantile, we develop an expression for the power parameter ( ) to calibrate the power prior distribution for quantile regression to a corresponding hierarchical model. In addition, we estimate the relation between the and the quantile level via hierarchical model. Our proposed methodology is illustrated with real data example.
Iraq suffers from serious pollution with harmful particles that have important direct and indirect effects on human activities and human health. In this research, a system for detecting pollutants in the air was designed and manufactured using infrared laser technology. This system was used to detect the presence of pollutants in the dust storms that swept the city of Baghdad which could have a negative impact on human health and living organisms.
The designed detection system based on the use of infrared laser (IR) with a wavelength of 1064 nm was used for the purposes of detecting pollutants based on the scattering of the laser beam from these pollutants. The system was aligned to obtain the best signal for the scattered rays, w
... Show MoreBackground Direct-acting antivirals (DAAs) combination therapies from various mechanisms of action and families have been revolutionized the management landscape of chronic hepatitis C virus (HCV). Ombitasvir, paritaprevir with ritonavir (OBV/PTV/r) ± ribavirin (RBV) is approved to treat HCV genotype 4 (GT4) infection. Here, our objective was to delineate the efficacy and safety of OBV/PTV/r plus RBV in treating of Egyptian naïve patients infected with HCV GT4.
Methods a cohort of 100 Egyptian patients infected with HCV GT4 was allocated and administered orally OBV/PTV/r with RBV. The primary endpoint of our study was a sustained virological response (HCV RNA < 12 IU/mL) 12 weeks after the c
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