In this study, the response and behavior of machine foundations resting on dry and saturated sand was investigated experimentally. In order to investigate the response of soil and footing to steady state dynamic loading, a physical model was manufactured. The manufactured physical model could be used to simulate steady state harmonic load at different operating frequencies. Total of (84) physical models were performed. The parameters that were taken into considerations include loading frequency, size of footing and different soil conditions. The footing parameters were related to the size of the rectangular footing and depth of embedment. Two sizes of rectangular steel model footing were used (100 200 12.5 mm) and (200 400 5.0 mm).

The free zone or the free economy cities are cities with classification and functional specificity, although the history of  the concept of these areas has been It dates back to distant eras, but the intellectual and philosophical construction with the support of intellectual approaches, the most important of which is globalization contributed to its rapid spread globally and taking a variety of forms and models. With the diversity of its formulas and objectives countries have competed in adopting the establishment of these areas, meanwhile The influence of related trends affected the contemporary formation of these sites. Therefore ,the research was directed focus on the importance of adopting a set of common indicators (collection

Background Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti

Machine learning is considered a powerful technique in many applications such as classification, clustering, recognition and prediction. Deep learning is a modern, vital and superior machine learning that gives stunning performance, especially with huge data. Stock market price prediction is the process of determining the future value of a prospect of a financial instrument traded in the market, to gain a great profit a successful prediction must be conducted, in order to achieve that machine learning is used, in this article, two approaches are proposed to predict the stock market prices and movement using two datasets, the first approach employs two machine learning models (J48 & logistic regression) while the second approach based on rec

A characteristic study of a passively Q-switched diode pumped solid state laser system is presented in this work. For laser a comparison study for the theoretically calculated results with a simulation results using a software which calculates the Q-switched solid state laser parameters was such as energy, peak power and pulse width were performed. There was a good agreement between our theoretical calculations and the simulation values.

A substantial percentage of the world’s energy consumption (almost 40%) and carbon dioxide (CO2) emissions (around 37%) come from the construction industry, especially schools. This work presents a new hybrid artificial intelligence (AI) engineering model that aims to maximize energy performance on campuses in a holistic way. Modules for data-driven forecasting, metaheuristic optimization, and real-time adaptive control are all part of the concept. A thorough energy simulation of a university campus building is used in conjunction with the AI model to assess its performance through a co-simulation framework. Findings show that yearly peak electricity demand may be reduced by 18.7% and total site energy consumption by 22.4% when co

Orthogonal Frequency Division Multiplexing (OFDM) is an efficient multi-carrier technique.The core operation in the OFDM systems is the FFT/IFFT unit that requires a large amount of hardware resources and processing delay. The developments in implementation techniques likes Field Programmable Gate Array (FPGA) technologies have made OFDM a feasible option. The goal of this paper is to design and implement an OFDM transmitter based on Altera FPGA using Quartus software. The proposed transmitter is carried out to simplify the Fourier transform calculation by using decoder instead of multipliers. After programming ALTERA DE2 FPGA kit with implemented project, several practical tests have been done starting from monitoring all the results of

Positron annihilation lifetime has been utilized for the first time to investigate the free - volume hole properties in thermolumenscent dosimeter ( TLD ) as a function of gamma-dosc . The hole volume, free volume fraction determined form orthopsitronium lifetime are found to be ?lamatically increase to large values , and then to minimum values as a function ofgamma-dose . The free - volume holes size is found to be 0.163nm’ and to have maximum of 0.166nm^ at the gamma-dose of 0.1 and 0.8 Gy, respectively-