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.
The study involved the synthesis of new complexes with tetradentate ligand (LH). The general formula of complexes was [M(LH)(H2O)2] with M of Ni2+, Co2+, Cu2+, and Zn+. The ligand was synthesized by treating the 2-hydroxybenzohydrazide with salicylaldehyde. The structural characteristics of ligands and complexes were analyzed using various techniques, including elemental analyses, magnetic susceptibility, molar conductivity, infrared, ultraviolet absorption, mass, and NMR spectroscopy studies. The physical measurements indicated that the prepared complexes are non-electrolyte and showed that the ligand is tetradentate when coordinated with metal ions through the nitrogen of azomethine (–C=N–), two oxygen atoms of O–H phenolic,
... Show MoreIn the geotechnical and terramechanical engineering applications, precise understandings are yet to be established on the off-road structures interacting with complex soil profiles. Several theoretical and experimental approaches have been used to measure the ultimate bearing capacity of the layered soil, but with a significant level of differences depending on the failure mechanisms assumed. Furthermore, local displacement fields in layered soils are not yet studied well. Here, the bearing capacity of a dense sand layer overlying loose sand beneath a rigid beam is studied under the plain-strain condition. The study employs using digital particle image velocimetry (DPIV) and finite element method (FEM) simulations. In the FEM, an experiment
... Show More<span lang="EN-US">The fundamental of a downlink massive multiple-input multiple-output (MIMO) energy- issue efficiency strategy is known as minimum mean squared error (MMSE) implementation degrades the performance of a downlink massive MIMO energy-efficiency scheme, so some improvements are adding for this precoding scheme to improve its workthat is called our proposal solution as a proposed improved MMSE precoder (PIMP). The energy efficiency (EE) study has also taken into mind drastically lowering radiated power while maintaining high throughput and minimizing interference issues. We further find the tradeoff between spectral efficiency (SE) and EE although they coincide at the beginning but later their interests become con
... Show MoreBackground: This in vitro study compares a novel calcium-phosphate etchant paste to conventional 37% phosphoric acid gel for bonding metal and ceramic brackets by evaluating the shear bond strength, remnant adhesive and enamel damage following water storage, acid challenge and fatigue loading. Material and Methods: Metal and ceramic brackets were bonded to 240 extracted human premolars using two enamel conditioning protocols: conventional 37% phosphoric acid (PA) gel (control), and an acidic calcium-phosphate (CaP) paste. The CaP paste was prepared from β-tricalcium phosphate and monocalcium phosphate monohydrate powders mixed with 37% phosphoric acid solution, and the resulting phase was confirmed using FTIR. The bonded premolars were exp
... Show MoreCombination of natural poly-phenolic compounds with chemotherapeutic agents is recently being a novel strategy in cancer therapy researches owing to their potential antioxidant and anti-inflammatory properties that modulate several intracellular signaling pathways.
Resveratrol and Baicalein are well known poly-phenolic compounds that belong to stilbene and flavone subclasses, respectively.
This study aims to investigate the possible enhancement effect of resveratrol and Baicalein when combined with doxorubicin using a different combination ratio and applied on two cancer cell lines: HCT116 (colorectal cancer cells) and HepG2 (hepatocellular cancer cells). It also investigates the possibility of such natural compounds to p
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