This study aims to estimate the accuracy of digital elevation models (DEM) which are created with exploitation of open source Google Earth data and comparing with the widely available DEM datasets, Shuttle Radar Topography Mission (SRTM), version 3, and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), version 2. The GPS technique is used in this study to produce digital elevation raster with a high level of accuracy, as reference raster, compared to the DEM datasets. Baghdad University, Al Jadriya campus, is selected as a study area. Besides, 151 reference points were created within the study area to evaluate the results based on the values of RMS.Furthermore, th

Flexible pavements are considered an essential element of transportation infrastructure. So, evaluations of flexible pavement performance are necessary for the proper management of transportation infrastructure. Pavement condition index (PCI) and international roughness index (IRI) are common indices applied to evaluate pavement surface conditions. However, the pavement condition surveys to calculate PCI are costly and time-consuming as compared to IRI. This article focuses on developing regression models that predict PCI from IRI. Eighty-three flexible pavement sections, with section length equal to 250 m, were selected in Al-Diwaniyah, Iraq, to develop PCI-IRI relationships. In terms of the quantity and severity of eac

The presence of heavy metals in the environment is major concern due to their toxicity. In the present study a strong acid cation exchange resin, Amberlite IR 120 was used for the removal of lead, zinc and copper from simulated wastewater. The optimum conditions were determined in a batch system of concentration 100 mg/L, pH range between 1 and 8, contact time between 5 and 120 minutes, and amount of adsorbent was from 0.05 to 0.45 g/100 ml. A constant stirring speed, 180 rpm, was chosen during all of the experiments. The optimum conditions were found to be pH of 4 for copper and lead and pH 6 for zinc, contact time of 60 min and 0.35 g of adsorbent. Three different temperatures (25, 40 and 60°C) were selected to investigate the effect

Early detection of eye diseases can forestall visual deficiency and vision loss. There are several types of human eye diseases, for example, diabetic retinopathy, glaucoma, arteriosclerosis, and hypertension. Diabetic retinopathy (DR) which is brought about by diabetes causes the retinal vessels harmed and blood leakage in the retina. Retinal blood vessels have a huge job in the detection and treatment of different retinal diseases. Thus, retinal vasculature extraction is significant to help experts for the finding and treatment of systematic diseases. Accordingly, early detection and consequent treatment are fundamental for influenced patients to protect their vision. The aim of this paper is to detect blood vessels from

In this study, a new class of polymeric nanocomposites was synthesized and characterized.  One mole of dimethyl adipate and two moles of thiosemicarbazide in ethanol first reacted to form the compound [C1]. Compound [C1] then reacted with sodium hydroxide to produce compounds [C2]. Hydrazine hydrate reacted with compound [C2] to generate compound [C3]. Compound [C4] was synthesized from compound [C3] and maleic anhydride. A polymer [C5] is formed by the reaction of the compound [C4] with ammonium persulfate as an initiator. This polymer was then combined with nano: ZnNPs, AgNPs, SiNPs, or IONPs using a hotplate stirrer for 3 hours to produce nanocomposites [C6-C9]. FTIR, 1H-NMR, and Field Emission Scanning Electron Microscope (FESEM) were

Copper oxide (CuO) nanoparticles were synthesized through the thermal decomposition of a copper(II) Schiff-base complex. The complex was formed by reacting cupric acetate with a Schiff base in a 2:1 metal-to-ligand ratio. The Schiff base itself was synthesized via the condensation of benzidine and 2-hydroxybenzaldehyde in the presence of glacial acetic acid. This newly synthesized symmetric Schiff base served as the ligand for the Cu(II) metal ion complex. The ligand and its complex were characterized using several spectroscopic methods, including FTIR, UV-vis, 1H-NMR, 13C-NMR, CHNS, and AAS, along with TGA, molar conductivity and magnetic susceptibility measurements. The CuO nanoparticles were produced by thermally decomposing the