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

Background Due to the intermittent, nonlinear, and uncertain behavior of renewable energy sources (res) such as solar and wind, grid stability and reliability require very high forecasting and optimization skills as widely reported in the literature. Traditional optimization methods work very well in small or static systems but are suffer difficulty on large-scale, dynamic and stochastic renewable environment due to their NP-hard nature. Methods The framework introduces the concept of a Machine Learning-Assisted Hybrid Cuckoo Search (ML-HCS) that combines CS with a hybrid metaheuristic and integrates Long Short-Term Memory (LSTM) networks for forecasting based on both regression models of LSTMs and hybrid optimization algorithm

For the duration of the last few many years many improvement in computer technology, software program programming and application production had been followed with the aid of diverse engineering disciplines. Those trends are on the whole focusing on synthetic intelligence strategies. Therefore, a number of definitions are supplied, which recognition at the concept of artificial intelligence from exclusive viewpoints. This paper shows current applications of artificial intelligence (AI) that facilitate cost management in civil engineering tasks. An evaluation of the artificial intelligence in its precise partial branches is supplied. These branches or strategies contributed to the creation of a sizable group of fashions s

The presented work shows a preliminary analytic method for estimation of load and pressure distributions on low speed wings with flow separation and wake rollup phenomena’s. A higher order vortex panel method is coupled with the numerical lifting line theory by means of iterative procedure including models of separation and wake rollup. The computer programs are written in FORTRAN which are stable and efficient.

      The capability of the present method is investigated through a number of test cases with different types of wing sections (NACA 0012 and GA(W)-1) for different aspect ratios and angles of attack, the results include the lift and drag curves, lift and pressure distributions along the wing s

Today the NOMA has exponential growth in the use of Optical Visible Light Communication (OVLC) due to good features such as high spectral efficiency, low BER, and flexibility. Moreover, it creates a huge demand for electronic devices with high-speed processing and data rates, which leads to more FPGA power consumption. Therefore; it is a big challenge for scientists and researchers today to recover this problem by reducing the FPGA power and size of the devices. The subject matter of this article is producing an algorithm model to reduce the power consumption of (Field Programmable Gate Array) FPGA used in the design of the Non-Orthogonal Multiple Access (NOMA) techniques applied in (OVLC) systems combined with a blue laser. However, The po

The Taylor series is defined by the f and g series. The solution to the satellite's equation of motion is expanding to generate Taylor series through the coefficients f and g. In this study, the orbit equation in a perifocal system is solved using the Taylor series, which is based on time changing. A program in matlab is designed to apply the results for a geocentric satellite in low orbit (height from perigee, hp= 622 km). The input parameters were the initial distance from perigee, the initial time, eccentricity, true anomaly, position, and finally the velocity. The output parameters were the final distance from perigee and the final time values. The results of radial distance as opposed to time were plotted for dissimilar times in

   The Sadi reservoir is one of the largest and most important unconventional tight oil reservoirs in southern Iraq. However, it suffers from low production rates, necessitating many development strategies that require a correct and reliable characterization of reservoir fluid properties. Whilst these properties are originally obtained from laboratory experiments, measurement errors often occur despite rigorous workflows, which negatively affect the calculation of reservoir fluid properties. This study utilizes the fluid thermodynamics characterization program (PVTp) to generate a reliable model for determining the oil properties of Sadi reservoir. A methodology was developed to simulate fluid thermodynamic tests, including Differ

The problem of the study was to identify the possibility of benefiting from the application of the target cost system as a modern cost system to activate the environmental cost management instead of the traditional systems used in the company due to the great transformations witnessed by the business environment in all fields, which have resulted in the search for modern systems to provide more accurate and more appropriate information to reduce Costs, because accurate information makes the company have a complete vision to achieve the company’s goals. To solve this problem, the research was based on the following hypothesis (that the role of the target cost system leads to the activation of environmental cost management). Target c