In this article, Convolution Neural Network (CNN) is used to detect damage and no damage images form satellite imagery using different classifiers. These classifiers are well-known models that are used with CNN to detect and classify images using a specific dataset. The dataset used belongs to the Huston hurricane that caused several damages in the nearby areas. In addition, a transfer learning property is used to store the knowledge (weights) and reuse it in the next task. Moreover, each applied classifier is used to detect the images from the dataset after it is split into training, testing and validation. Keras library is used to apply the CNN algorithm with each selected classifier to detect the images. Furthermore, the performance measures are used as a criterion to decide which classifier is the best one to detect the images with high accuracy. Eventually, the simulation results show that each classifier detect the damage/no damage image with different performance measures and then makes it easy to select the best one.
Zinc is one of the essential trace elements, it plays a key role in many biochemical and functional processes. It is less harmful than many other minerals, in the case of exposure to high doses of zinc, poisoning occurs, and this poisoning may mostly result from the accidental ingestion of household products containing zinc or nutritional supplements, this study was conducted to find out the effects of zinc on the concentration of amino acid. A total of 30 adult white mouse males were taken and divided into three groups; the first group (control) of 10 mice taken with distilled water for 30 days, the second group includes 10 mice that were dose with Zn drug concentration of 50 mg/kg/day for 30 days, the third group includes 10 mice that wer
... Show MoreHeavy metal ion removal from industrial wastewater treatment systems is still difficult because it contains organic contaminants. In this study, functional composite hydrogels with photo Fenton reaction activity were used to decompose organic contaminants. Fe3O4 Nanoparticle, chitosan (CS), and other materials make up the hydrogel. There are different factors that affected Photo-Fenton activity including (pH, H2O2 conc., temp., and exposure period). Atomic force microscopy was used to examine the morphology of the composite and its average diameter (AFM). After 60 minutes of exposure to UV radiation, CS/ Fe3O4 hydrogel composite had degraded methylene blue (M.B.)
... Show MoreThis study included the isolation and identification of Aspergillus flavus isolates associated with imported American rice grains and local corn grains which collected from local markets, using UV light with 365 nm wave length and different media (PDA, YEA, COA, and CDA ). One hundred and seven fungal isolates were identified in rice and 147 isolates in corn.4 genera and 7 species were associated with grains, the genera were Aspergillus ,Fusarium ,Neurospora ,Penicillium . Aspergillus was dominant with occurrence of 0.47% and frequency of 11.75% in rice grains whereas in corn grains the genus Neurospora was dominant with occurrence of 1.09% and frequency 27.25% ,results revealed that 20 isolates out of 50 A. flavus isolates were able
... Show MoreA factorial experiment (2× 3) in randomized complete block design (RCBD) with three replications was conducted to examine the effect of honeycomb selection method using three interplant distances on the vegetative growth, flowering, and fruit set of two cultivars of bean, Bronco and Strike. Interplant distances used were 75× 65 cm, 90× 78 cm, and 105× 91 cm (row× plant) represent short (high plant density), intermediate (intermediate plant density), and wide (low plant density) distance, respectively. Parameters used for selection were number of days from planting to the initiation of first flower, number of nodes formed prior to the onset of first flower, and number of main branches. Results showed significant superiority of the Strik
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