It is known that energy is essential to life and economic growth. Energy is a foundation stone of the modern industrial economy. Energy provides an essential ingredient for almost all human activities, for example, without water, life as we know it would not be possible. Clean water or fresh water is rare in many low-density locations, and most of the time, there is no electrical grid connection or other energy source available, except renewable energy sources, which mostly pertain to solar radiation. Because desalination may turn salty water into a potable supply, it is a feasible solution to the issue of water shortage. Desalination is a reasonable answer for these areas' demands. Desalination systems and energy conversion are two distinct and independent technologies used in RE desalination. The actual issue with these technologies is determining the best economic layout and assessment of the integrated plants to make them profitable for isolated or desert areas. The conversion of renewable energy sources, such as solar, necessitates significant financial outlays, and despite extensive research and development, the technology is not yet sufficiently advanced to be used on a broad scale. With a focus on solar energy applications, this article provides an overview of the most significant advancements in the field of desalination using renewable energies, as well as the highlights that have been made in recent years.

Machine learning (ML) has become a crucial tool in analyzing big data within the healthcare domain, offering predictive capabilities, personalized treatments, and enhanced decision-making processes. This review systematically examines the latest ML techniques applied to big data analysis in healthcare, including supervised and unsupervised learning, deep learning, and ensemble methods. We analyze the advantages and limitations of these approaches and their effectiveness in improving patient outcomes, diagnosing diseases, and optimizing resource allocation. Furthermore, we highlight key challenges such as data privacy, model interpretability, and computational efficiency. This paper provides a comparative assessment of ML-based healthcare solutions, offering insights into future research directions and best practices for integrating ML in real-world medical applications.

One of the most urgent environmental issues is groundwater pollution, especially in relation to nitrate removal, which presents significant dangers to human health and the environment. In order to address nitrate contamination in groundwater, this review examines creative and sustainable methods that make use of waste materials, specifically recycled rubber from discarded tires. Based on experimental and field performance, the article covers many approaches that have been developed employing recycled rubber as an adsorbent for nitrate and evaluates their efficacy. It also emphasizes the chemical and physical characteristics of recycled rubber, such as particle size, surface changes, and interaction parameters, that improve its effectiveness in removing nitrate. With the help of this thorough analysis, the study offers recommendations for improving recycled rubber's performance as a long-term and practical remedy for nitrate contamination. It also calls for more investigation and development to increase the system's effectiveness in a range of groundwater conditions.

Thermosiphon flow of flat plate solar collector (FPC) is one of the economic strategies of renewable energy. The aim of this study is to reduce the exergy destruction and improve energy efficiency of FPC under climatic conditions of Iraq. The CuO nanoparticles suspended in pure water has been utilized due to high thermal properties with 0.1%, 0.5% and 1% volume concentrations. Results show that the outlet temperature is increased with increasing solar radiation earlier then decreased after 12 P.M. similar behavior of solar radiation. The thermal efficiency is increased as solar radiation increased then decreased after 12 P.M. as the solar radiation behavior. It was noticed that the efficiency of using nanofluids has the same behavior as using purified water with deviation 15%. The amount of 1.0 vol% of nanofluid with pure water as the working fluid reaches the greatest thermal efficiency which is 69.06%. The 1% nanofluids concentration has better efficiency. The results show up the nanofluids was better than pure water due to their dispersion and thermophysical property predictions.

Single slope solar still is one of the most popular water purifiers. This paper investigated heat transfer processes that occur inside the solar still numerically and experimentally In addition, attempts to improve productivity have been studied. Comsol Multiphysics software (v5.5) was used to develop a 3D mathematical model to examine the considered developments. Four different heating tank designs (sphere, half sphere, con, and rectangular) were compared as an optimization step. The studies have also considered the volume of the tank to choose to best one among the proposed volumes. The experimental study included the manufacturing of a water heating tank and its integration with a solar still. An improvement of (35%) was obtained when designing a halfsphere tank with a volume of 2.5 times that of a conventional solar still (CSS).

Detecting direction of arrival (DoA) using array antenna is considered as common challenge in different typeS of applications, such as sonar, radar, wireless communications. DoA estimation plays an important role in direction finding applications. Further, effective DoA estimation technique is the primary requirements for smart antenna system to realize beam forming technique. Multiple signal classification (MUSIC) and Estimation of Signal Parameters via Rotational Invariance (ESPRIT) algorithms have been widely studied, and they are considered as fundamental for the majority of the DoA methods in literature. In this paper, the principal of DoA estimations is presented. The main focus of the current paper is on the classical methods (Bartletts and MVDR), MUSIC and ESPRIT algorithms. Review of various efforts that have been made to enhance the performance of these algorithms was acheived. Then compared their performances using simulation results. Further, applying MUSIC algorithm to estimate the frequency of the multiple incident signals. The results show that MUSIC algorithm has higher resolution compared to other presented techniques. It is also shown that the accuracy of ESPRIT method is mainly rely on the number of antenna elements. Finally, the principle of Eigenvalues-based method was proposed. It is shown that this method has good resolution with very low complexity as it does not need decomposition of covariance matrix.

In the recent years, researchers have been interested in planning of layout of projects´ site since it is a basic factor for a successful project undertaking. Projects´ sites comprise temporary facilities and heavy construction equipment that share the same space or may require the same area of construction site, therefore, construction site should be organized well, so that construction activity will be in its full swing. The site layout planning process includes identifying the needed temporary facilities for supporting operations of construction, specifying their shapes and sizes, and optimizing their positions within the boundaries of sites. In this review, a number of methods and techniques used for construction site layout planning are reviewed and discussed, the frequent problems at construction sites are included, the ways of improving the efficiency of planning of sites layout are listed and discussed. The advantages of good planning of sites layout and the effects of neglecting sites layout planning are reviewed.