Climate change in recent years has greatly affected the distribution of ground covers. Monitoring these changes has become very easy due to the development of remote sensitivity science and the use of satellites to monitor these changes. The aim of this research is to monitor changes in the spectral reflectivity of the Baghdad governorate center for the month (March, June, September, December) of the year 2021 using remote sensing and satellite images Sentinel 2 and knowing the climate imact on them. Fifty-one samples were selected for four types of ground cover (agricultural land, water, buildings and open space) and their spectral reflectivity was calculated using satellite images. Sentinel 2, where it was processed and analyzed, and then the spectral reflectivity values were calculated using the ArcGIS program. The effect of climate on the spectral reflectivity comes through its impact on the ground covers and thus changing the spectral signature of them. The relationship between temperature, spectral reflectivity, humidity, spectral reflectivity, and knowledge of the type of the relationship between them by means of mathematical equations. The results showed that the spectral reflection of the plant at the near-infrared beam has the most change than the rest of the ground covers.
Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with
... Show MoreIn this work, the photocatalytic degradation of indigo carmine (IC) using zinc oxide suspension was studied. The effect of influential parameters such as initial indigo carmine concentration and catalyst loading were studied with the effect of Vis irradiation in the presence of reused ZnO was also investigated. The increased in initial dye concentration decreased the photodegradation and the increased catalyst loading increased the degradation percentage and the reused-ZnO exhibits lower photocatalytic activity than the ZnO catalyst. It has been found that the photocatalytic degradation of indigo carmine obeyed the pseudo-first-order kinetic reaction in presence of zinc oxide. This was found from plotting the relationship between ln
... Show MoreTo demonstrate the effect of changing cavity length for FM mode locked on pulse parameters and make comparison for both dispersion regime , a plot for each pulse parameter as Lr function are presented for normal and anomalous dispersion regimes . The analysis is based on the theoretical study and the results of numerical simulation using MATLAB. The effect of both normal and anomalous dispersion regimes on output pulses is investigate Fiber length effects on pulse parameters are investigated by driving the modulator into different values. A numerical solution for model equations using fourth-fifth order, Runge-Kutta method is performed through MATLAB 7.0 program. Fiber length effect on pulse parameters is investigated by driving th
... Show MoreThe aim of this study was to increasing natural carotenoides production by a locally isolate Rodotorula mucilagenosa M. by determination of the optimal conditions for growth and production of this agents, for encouragest to use it in food application permute artificial pigments which harmfull for consumer health and envieronmental. The optimal condition of carotenoides production from Rhodotorula mucilaginosa M were studied. The results shows the best carbon and nitrogen source were glucose and yeast extract. The carotenoids a mount production was 47430 microgram ̸ litter and 47460 microgram ̸ litter, respectively, and the optimum temperature was 30°C, PH 6, that the carotenoides a mount was 47470 microgram ̸ litter and 47670 microgr
... Show MoreThe pumping station became widely used in many fields. Free surface vortices at intakes of pumps are not favorable. It may cause noise, excessive vibration, damage to the pumping structure, reduction in efficiency and flow for hydro-turbines, etc. One of the important problems encountered during the pump intake design is the depth of submergence and other design parameters to avoid strong free-surface vortices formation. This study aims to compute the critical submergence depth with some geometrical and hydraulic limitations by using Computational Fluid Dynamic (CFD) package. The mathematical model was validated with a laboratory model that had been conducted. The model of three intake pipes was investigated under five d
... Show MoreColorectal cancer (CRC) is the most common gastrointestinal malignancy and one of the top ten common cancers worldwide with approximately 2 million cases. There are multiple risk factors that could lead to CRC emergence; of which are genetic polymorphisms. Excision repair cross-complementing group 2 (ERCC2) gene encodes for ERCC2 enzyme which plays a crucial role in maintaining genomic integrity by removing DNA adducts. Several studies suggested that there could be a link between genetic polymorphisms of ERCC2 gene and the risk of CRC development. Hence the present study aims to validate the relationship between the following ERCC2 single nucleotide polymorphisms (rs13181, rs149943175, rs530662943, and rs1799790) and CRC susceptibility. A t
... Show MoreThe issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p
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