This research develops a new method based on spectral indices and random forest classifier to detect paddy rice areas and then assess their distributions regarding to urban areas. The classification will be conducted on Landsat OLI images and Landsat OLI/Sentinel 1 SAR data. Consequently, developing a new spectral index by analyzing the relative importance of Landsat bands will be calculated by the random forest. The new spectral index has improved depending on the most three important bands, then two additional indices including the normalized difference vegetation index (NDVI), and standardized difference built-up index (NDBI) have been used to extract paddy rice fields from the data. Several experiments being conducted to analyze and understand the strengths and weakness of the proposed new method. This research shows that spectral indices are easy and accurate tool for rapid mapping of paddy rice fields in complicated environment where urban features are dominated. The outcomes of this research could help mapping and decision makers to progress their productivity and strategic plans for better management of rice fields.
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In this work, the effect of the addition of bright nickel plating and silver carried out by the electroplating method has been studied, on the coating of copper nanoparticles on the copper base metal via the process of thermal evaporation. The improvement of the solar absorber using CuNP in combination with the bright nickel and silver was obtained to be better than copper nanoparticles individually. A bright nickel enhanced the absorbed thermal stability. Also, other optical properties, absorptions, and emissivity slightly decreased from (93% to 87%), while the existence of silver had a slight impact on absorption of about (86.50%). On the other hand, thermal conductivity was evaluated using hot disk analyzer. The results showed a good
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In this work, chemical spray pyrolysis deposition (CSP) technique was used to prepare a mixed In2O3-CdO thin films with different CdO content (10, 30 and 50)%volume ratio on glass substrates at 150 ᵒC substrate temperature. The surface morphology and structural properties were measured to find the optimum conditions to improve thin films properties for using as photo detector. Current –Time, the sensitivity and response speed vary for each mixture. Samples with 10% vol. CdO content has square pulse response with average rise time nearly 1s and fall time 1s.
Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. One of the main advantages of using these techniques is that they require no knowledge or gradient information about the response surface. The poor behavior of genetic algorithms in some problems, sometimes attributed to design operators, has led to the development of other types of algorithms. One such class of these algorithms is compact Genetic Algorithm (cGA), it dramatically reduces the number of bits reqyuired to store the poulation and has a faster convergence speed. In this paper compact Genetic Algorithm is used to optimize the maximum likelihood estimator of the first order moving avergae model MA(1). Simulation results
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In this paper, we calculate and measure the SNR theoretically and experimental for digital full duplex optical communication systems for different ranges in free space, the system consists of transmitter and receiver in each side. The semiconductor laser (pointer) was used as a carrier wave in free space with the specification is 5mW power and 650nm wavelength. The type of optical detector was used a PIN with area 1mm2 and responsively 0.4A/W for this wavelength. The results show a high quality optical communication system for different range from (300-1300)m with different bit rat (60-140)kbit/sec is achieved with best values of the signal to noise ratio (SNR).
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of
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Computations of the relative permeability curves were made through their representation by two functions for wetting and nonwetting phases. Each function contains one parameter that controls the shape of the relative permeability curves. The values of these parameters are chosen to minimize an objective function, that is represented as a weighted sum of the squared differences between experimentally measured data and the corresponding data calculated by a mathematical model simulating the experiment. These data comprise the pressure drop across core samples and the recovery response of the displacing phase. Two mathematical models are constructed in this study to simulate incompressible, one-dimensional, two-phase flow. The first model d
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