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.
New, simple and sensitive batch and reverse FIA spectrophotometric methods for the determination of doxycycline hyclate in pure form and in pharmaceutical preparations were proposed. These methods based on oxidative coupling reaction between doxycycline hyclate and 3-methylbenzothiazolinone-2-hydrazone hydrochloride (MBTH) in the presence ammonium ceric sulfate in acidic medium, to form green water-soluble dye that is stable and has a maximum absorbance at 626 nm. A calibration graph shows that a Beer's law is obeyed over the concentration range of 1-80 and 0.5-110 ?g.mL-1 of DCH for the batch and rFIA respectively with detection limit of 0.325 ?g.mL-1 of DCH for r-FIA methods. All different chemicals and physical experimental paramete
... Show MoreThe aim of the research is to design educational software based on Web Quests and to measure its effectiveness in developing information search skills of students at the Department of Educational and Psychological Sciences. The research is experimental in nature using pre-post measurement. The research sample consisted of (91) male and female students from the second grade in the Department of Educational and Psychological Sciences, they were divided into two equal groups; the experimental group consisted of (47) students who adopted the educational software as a studying method, and the control group consisted of (44) students who follow the traditional method. The researchers prepared a list of skills for searching information and they
... Show MoreFocusing of Gaussian laser beam through nonlinear media can induce spatial self- phase modulation which forms a far field intensity pattern of concentric rings. The nonlinear refractive index change of material depends on the number of pattern rings. In this paper, a formation of tunable nonlinear refractive index change of hybrid functionalized carbon nanotubes/silver nanoparticles acetone suspensions (F-MWCNTs/Ag-NPs) at weight mixing ratio of 1:3 and volume fraction of 6x10-6 , 9x10-6 , and 18x10-6 using laser beam at wavelength of 473nm was investigated experimentally. The results showed that tunable nonlinear refractive indices were obtained and increasing of incident laser power density led to increase the nonlinear refractive inde
... Show MoreIn the present study, a novel ligand (L) made of 2-hydroxynaphthaldehyde and 3-hydrazone-1,3-dihydro-indole-2-one(3-[(3-hydroxynaphthalen-2-yl-ethylidene)-hydrazono]-1,3-dihydro-indol-2-one). The ligand was characterized by FTIR, UV-vis, mass, 1H-NMR, 13C-NMR, and CHN elemental analysis. New complexes of this ligand were created by treating methanol and a drop of DMF solution of the produced ligand with the hydrated metal salts of Mn(II), Co(II), Ni(II), Cu(II), and Zn(II) in a molar ratio of 2:1 (L:M). As a result, complexes have been emerged and identified FTIR, UV-vis, C.H.N., chloride-containing, molar conductance, magnetic susceptibility, and atomic absorption. The characterization result for each complex indicated complexes wi
... Show MoreMany undergraduate learners at English departments who study English as a foreign language are unable to speak and use language correctly in their post -graduate careers. This problem can be attributed to certain difficulties, which they faced throughout their education years that hinder their endeavors to learn. Therefore, this study aims to discover the main difficulties faced by EFL students in language learning and test the difficulty variable according to gender and college variables then find suitable solutions for enhancing learning. A questionnaire with 15 items and 5 scales were used to help in discovering the difficulties. The questionnaire was distributed to the selected sample of study wh
... Show MoreBlogs have emerged as a powerful technology tool for English as a Foreign Language (EFL) classrooms. This literature review aims to provide an overview of the use of blogs as learning tools in EFL classrooms. The study examines the benefits and challenges of using blogs for language learning and the different types of blogs that can be used for language learning. It provides suggestions for teachers interested in using blogs as learning tools in their EFL classrooms. The findings suggest that blogs are a valuable and effective tool for language learning, particularly in promoting collaboration, communication, and motivation.
Witnessing human societies with the turn of the century atheist twenty huge revolution in information , the result of scientific and technological developments rapidly in space science and communications , and that made the whole world is like a small village not linked by road as it was in ancient times, through the rapid transportation as was the case a few years ago , thanks to the remote sensing devices that roam in space observant everything on the ground , that the information networks that overflowed the world a tremendous amount of information provided for each inhabitants of the earth , which made this information requirement for human life and human survival and well-being , as it has allowed that information to humans opportun
... Show MoreImitation learning is an effective method for training an autonomous agent to accomplish a task by imitating expert behaviors in their demonstrations. However, traditional imitation learning methods require a large number of expert demonstrations in order to learn a complex behavior. Such a disadvantage has limited the potential of imitation learning in complex tasks where the expert demonstrations are not sufficient. In order to address the problem, we propose a Generative Adversarial Network-based model which is designed to learn optimal policies using only a single demonstration. The proposed model is evaluated on two simulated tasks in comparison with other methods. The results show that our proposed model is capable of completing co
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