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This research work intends to enhance the stepped double-slope solar still performance through an experimental assessment of combining linen wicks and cobalt oxide nanoparticles to the stepped double-slope solar still to improve the water evaporation and water production. The results illustrated that the cotton wicks and cobalt oxide (Co3O4) nanofluid with 1wt% increased the hourly freshwater output (HP) and instantaneous thermal efficiency (ITE). On the other hand, this study compares four machine learning methods to create a prediction model of tubular solar still performance. The methods developed and compared are support vector regressor (SVR), decision tree regressor, neural network, and deep neural network based on experimental data. This problem is a multi-output prediction problem which is HP and ITE. The prediction performance for the SVR was the lowest, with 70 (ml/m2 h) mean absolute error (MAE) for HP and 4.5% for ITE. Decision tree regressor has a better prediction for HP with 33 (ml/m2 h) MAE and almost the same MAE for ITE. Neural network has a better prediction for HP with 28 (ml/m2 h) MAE and a bit worse prediction for ITE with 5.7%. The best model used the deep neural network with 1.94 (ml/m2 h) MAE for HP and 0.67% MAE for ITE.

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Collision avoidance and autonomous control of vehicles have become essential needs for providing a high-quality and safe life. This paper introduces a new generic scheme for a virtual antenna array (VAA) and its application in a train collision-avoidance system (TCAS). The proposed TCAS shall have the capability of identifying the range and angle of an object in front of a moving train and provide the required alerts. Thereby, a new virtual array distribution for both the transmitting and the receiving antenna arrays is introduced to get a long-range object detection and high-resolution multi-input multi-output (MIMO) system. This can be accomplished because the VAA radiation pattern is the multiplication of the radiation patterns for both the transmitting and receiving antenna arrays, which is different than each one of them alone. In this work, the VAA is utilized in radar systems in which the radar range depends on the multiplication of the gain of the transmitting and receiving antennas. So, we introduce a new scheme for the general design of VAA-based radars. A prototype for the antenna system was fixed on a of Texas Instruments platform for the cascading radar. One of the main problems of the VAA is the loss of radiated power in undesired directions, which affects the maximum detection range in beamforming systems and degrades the diversity gain in MIMO applications. These issues have been solved by the introduction of the practical implementation of a proposed high-gain, low side lobe level VAA system for automotive radar that is based on the integration of four AWR1243 RF chips operating in a frequency range of 76 GHz to 81 GHz. It was implemented using low-power 45 nm (TI) RFCMOS technology. The measured gain of the realized VAA was 47.2 dBi, which was 1.815 times higher than that of the Texas instrumentation linear frequency modulated continuous wave (TI' LFMCW) radar, which was 26 dBi. The proposed VAA saved 45% of the required implementation area compared to the TI' LFMCW antenna array. The VAA system was fabricated and tested in an anechoic chamber, and it was found that the simulated and measured patterns of the proposed VAA were highly matched in terms of half-power beamwidth and side lobe level.

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Solar photovoltaic panels are increasingly being used throughout the world, particularly in Egypt, where a station has been constructed in the city of Aswan with a capacity of 1480 MW, and is classified as one of the largest photovoltaic plants in the Middle East country, where photovoltaic systems are characterized as environmentally friendly and do not produce any pollutants, and photovoltaic systems have the ability to operate with diffuse radiation. It is therefore very important to understand how photovoltaic panels respond to changing weather conditions and how climate conditions affect the performance of photovoltaic cells, as only 15-20% of solar radiation can be converted to electricity, while the rest is wasted as thermal heat. There are two very important factors influencing the efficiency of the photovoltaic cells: the cell temperature and the solar radiation intensity on the photovoltaic cells. Cooling of the optical surfaces is one of the main factors that must be considered in order to achieve the highest efficiency when operating the solar PV systems. By using the appropriate cooling technology for the photovoltaic cells, the electrical efficiency is improved, and the cell degradation rate is decreased over time, which increases the life span of the PV panels. In some applications, such as industrial and domestic applications, excess energy removed with cooling technology could be used. The cooling mediums used to cool the PV panels are water, air, PCM, and nanofluid. Also, the spectral splitting utilization represents a good solution for hybrid solar photovoltaic-thermal applications to obtain higher performance of the photovoltaic. This paper gives a brief analysis of technologies used to improve PV systems efficiency in terms of the nature of cooling media, spectral splitting, and reflectors. Moreover, the economic study of these techniques is presented to demonstrate their economic feasibility. The aims of the present review paper are to provide good knowledge and understanding of all technologies used to improve the performance of PV systems and demonstrate the economic feasibility of these technologies.

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