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Recent statistics indicate that as of 2023, the global renewable energy capacity has reached new heights, with Saudi Arabia significantly contributing to this growth through its strategic initiatives. The kingdom is particularly focusing on harnessing solar power, given its abundant sunlight, and is also exploring wind energy, leveraging its vast desert landscapes. These efforts are part of Saudi Arabia's broader strategy to become a global leader in renewable energy. This paper provides a detailed exploration of Saudi Arabia's ambitious journey from a fossil-fuel-dominated energy sector to a more sustainable, renewable-energy-driven future. Anchored in the broader context of global energy trends, the study emphasizes the critical shift toward renewable resources, with a particular focus on Saudi Arabia's unique position in this global movement. Key to this transition is Saudi Arabia's Vision 2030, a strategic framework that guides the country's renewable energy policies and initiatives. A comprehensive review of these policies, including other governmental and international collaborations that support renewable energy development, is offered. The current state of renewable energy in Saudi Arabia is assessed, including an overview of existing projects and production statistics. The paper also explores emerging technologies such as energy storage systems and smart grid solutions, emphasizing their role in Saudi Arabia's energy transition. An impact assessment is conducted to understand the environmental, economic, and social effects of this energy shift. The paper also includes a comparative analysis of other countries' renewable energy transitions, extracting lessons and best practices applicable to the Saudi context. Strategic recommendations and reflections on Saudi Arabia's future role in the global energy landscape are provided for stakeholders in energy policy, environmental planning, and sustainable development. [ABSTRACT FROM AUTHOR]

Sign language is an essential means of communication for individuals with hearing disabilities. However, there is a significant shortage of sign language interpreters in some languages, especially in Saudi Arabia. This shortage results in a large proportion of the hearing-impaired population being deprived of services, especially in public places. This paper aims to address this gap in accessibility by leveraging technology to develop systems capable of recognizing Arabic Sign Language (ArSL) using deep learning techniques. In this paper, we propose a hybrid model to capture the spatio-temporal aspects of sign language (i.e., letters and words). The hybrid model consists of a Convolutional Neural Network (CNN) classifier to extract spatial features from sign language data and a Long Short-Term Memory (LSTM) classifier to extract spatial and temporal characteristics to handle sequential data (i.e., hand movements). To demonstrate the feasibility of our proposed hybrid model, we created a dataset of 20 different words, resulting in 4000 images for ArSL: 10 static gesture words and 500 videos for 10 dynamic gesture words. Our proposed hybrid model demonstrates promising performance, with the CNN and LSTM classifiers achieving accuracy rates of 94.40% and 82.70%, respectively. These results indicate that our approach can significantly enhance communication accessibility for the hearing-impaired community in Saudi Arabia. Thus, this paper represents a major step toward promoting inclusivity and improving the quality of life for the hearing impaired. [ABSTRACT FROM AUTHOR]

This research paper presents a comprehensive study on the implementation of photovoltaic (PV) energy systems at Al-Abrar Mosque in Saudi Arabia. The primary objective was to explore optimal regional solar power strategies. By synergistically integrating technical evaluations of the PV system with economic analyses, including the payback period and levelized cost of energy (LCOE), alongside an investigation of net metering and net billing scenarios, we delineated a pathway toward achieving net zero billing for the mosque's energy requirements. This study examined two scenarios: Scenario I involved net metering, while Scenario II explored net billing. Our theoretical and simulation results, derived from detailed analyses conducted using PVsyst software, unequivocally demonstrated the superiority of net metering for this specific application. With net metering, the mosque's energy needs can be efficiently met using minimal infrastructure—comprising only 34 photovoltaic modules and a single inverter. In contrast, net billing requires significantly higher resource demands, underscoring the economic and spatial advantages of net metering. Additionally, the payback period for Scenario I is 7.9 years, while for Scenario II, it extends to 87 years. Through rigorous simulations, this study reaffirmed the practicality and feasibility of the net metering approach within the context of Saudi Arabia. Furthermore, our research provides actionable insights for implementing sustainable solutions at specific sites, such as the Al-Abrar Mosque, and contributes to advancing renewable energy knowledge in the region. [ABSTRACT FROM AUTHOR]

Deaf and hard-of-hearing people mainly communicate using sign language, which is a set of signs made using hand gestures combined with facial expressions to make meaningful and complete sentences. The problem that faces deaf and hard-of-hearing people is the lack of automatic tools that translate sign languages into written or spoken text, which has led to a communication gap between them and their communities. Most state-of-the-art vision-based sign language recognition approaches focus on translating non-Arabic sign languages, with few targeting the Arabic Sign Language (ArSL) and even fewer targeting the Saudi Sign Language (SSL). This paper proposes a mobile application that helps deaf and hard-of-hearing people in Saudi Arabia to communicate efficiently with their communities. The prototype is an Android-based mobile application that applies deep learning techniques to translate isolated SSL to text and audio and includes unique features that are not available in other related applications targeting ArSL. The proposed approach, when evaluated on a comprehensive dataset, has demonstrated its effectiveness by outperforming several state-of-the-art approaches and producing results that are comparable to these approaches. Moreover, testing the prototype on several deaf and hard-of-hearing users, in addition to hearing users, proved its usefulness. In the future, we aim to improve the accuracy of the model and enrich the application with more features. [ABSTRACT FROM AUTHOR]

Several research papers have attempted to describe the dynamics of COVID-19 based on systems of differential equations. These systems have taken into account quarantined or isolated cases, vaccinations, control measures, and demographic parameters, presenting propositions regarding theoretical results that often investigate the asymptotic behavior of the system. In this paper, we discuss issues that concern the theoretical results proposed in the paper "An Extended SEIR Model with Vaccination for Forecasting the COVID-19 Pandemic in Saudi Arabia Using an Ensemble Kalman Filter". We propose detailed explanations regarding the resolution of these issues. Additionally, this paper focuses on extending the local stability analysis of the disease-free equilibrium, as presented in the aforementioned paper, while emphasizing the derivation of theorems that validate the global stability of both epidemic equilibria. Emphasis is placed on the basic reproduction number R 0 , which determines the asymptotic behavior of the system. This index represents the expected number of secondary infections that are generated from an already infected case in a population where almost all individuals are susceptible. The derived propositions can inform health authorities about the long-term behavior of the phenomenon, potentially leading to more precise and efficient public measures. Finally, it is worth noting that the examined paper still presents an interesting epidemiological scheme, and the utilization of the Kalman filtering approach remains one of the state-of-the-art methods for modeling epidemic phenomena. [ABSTRACT FROM AUTHOR]

Utilizing renewable energy (RE) sources can provide a realistic answer to the problem of many nations' energy needs. This paper reviews the current status of using RE to produce electricity in the Kingdom of Saudi Arabia (KSA). The primary aim of the review is to identify and analyze the solar- and wind-energy utilization, problems, and future trends in KSA while taking into account all relevant aspects, associated development hurdles, and suggested solutions. All involved parties will receive useful results and conclusions from a thorough examination and analysis of the pertinent literature that can assist them in understanding the potential of solar and wind energy, considering all the linked issues. [ABSTRACT FROM AUTHOR]

Background: Oral potentially malignant disorders (OPMDs) are a group of chronic oral mucosal diseases associated with an increased risk of malignant transformation. Multiple studies have investigated the prevalence of these conditions in multiple regions; however, there are limited data about the prevalence of OPMDs in the Kingdom of Saudi Arabia (KSA). This paper aims to review the prevalence of OPMDs in the KSA, to ensure better understanding of the population risk and propose a more standardised approach to the diagnosis and management of this group across the KSA. In addition, this review will discuss the prevalence of oral cancer in the KSA, considering independent risk factors for oral cancer development. Methods: Electronic databases including PubMed, Medline, Medscape, ScienceDirect, StatPearls, BMC Oral Health and the Cochrane Library were searched with the keywords "Oral Potentially Malignant Disorders"; "Saudi Arabia"; and "Oral Cancer". Identified articles were reviewed independently by 2 reviewers against defined inclusion and exclusion criteria. Results: 16 studies were included in this review. The prevalence of OPMDs in KSA varies significantly depending on age, gender, social habits, background disease and dental status. Conclusions: This review highlights the need for up-to-date data on the prevalence, distribution, and characteristics of OPMDs in KSA. The diverse prevalence rates and distinct characteristics of various OPMDs emphasise the necessity for targeted preventive measures. As the data on OPMDs in KSA remains limited, future research efforts should prioritise the establishment of comprehensive epidemiological studies to inform effective public health interventions in this region. [ABSTRACT FROM AUTHOR]

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for coronavirus disease-19 (COVID-19). This virus has caused a global pandemic, marked by several mutations leading to multiple waves of infection. This paper proposes a comprehensive and integrative mathematical approach to the third wave of COVID-19 (Omicron) in the Kingdom of Saudi Arabia (KSA) for the period between 16 December 2022 and 8 February 2023. It may help to implement a better response in the next waves. For this purpose, in this article, we generate a new mathematical transmission model for coronavirus, particularly during the third wave in the KSA caused by the Omicron variant, factoring in the impact of vaccination. We developed this model using a fractal-fractional derivative approach. It categorizes the total population into six segments: susceptible, vaccinated, exposed, asymptomatic infected, symptomatic infected, and recovered individuals. The conventional least-squares method is used for estimating the model parameters. The Perov fixed point theorem is utilized to demonstrate the solution's uniqueness and existence. Moreover, we investigate the Ulam–Hyers stability of this fractal–fractional model. Our numerical approach involves a two-step Newton polynomial approximation. We present simulation results that vary according to the fractional orders (γ) and fractal dimensions (θ), providing detailed analysis and discussion. Our graphical analysis shows that the fractal-fractional derivative model offers more biologically realistic results than traditional integer-order and other fractional models. [ABSTRACT FROM AUTHOR]

Integrating renewable energy sources (RES), such as photovoltaic (PV) systems, into power system networks increases uncertainty, leading to practical challenges. Therefore, an accurate photovoltaic (PV) power prediction model is required to provide essential data that supports smooth power system operation. Hence, the work presented in this paper compares and discusses the results of different machine learning (ML) techniques in predicting the power produced by the 300 MW Sakaka PV Power Plant in the north of Saudi Arabia. The validation of the presented work is performed using real-world operational data obtained from the specified solar farm. Several performance measures, including accuracy, precision, recall, F1 Score, and mean square error (MSE), are used in this work to evaluate the performance of the different ML approaches and determine the most precise prediction model. The obtained results show that the Support Vector Machine (SVM) with a Radial basis function (RBF) is the most effective approach for optimizing solar power prediction in large-scale solar farms. [ABSTRACT FROM AUTHOR]

This paper is devoted to the analysis of air temperature and humidity changes during the two solar eclipses of 26 December 2019 and 21 June 2020 in Saudi Arabia based on data we collected from two different sites. We highlight the complexity of humidity's response to a solar eclipse, which is quite different from temperature's response. During the December event, the Sun rose already partially eclipsed, while for the June eclipse, it was only partial at Riyadh. This difference apparently affected the observed response on the recorded variables: temperature, relative humidity (RH), and vapor pressure (VP) in the two events. Changes in these variables went unnoticed for the first eclipse since they were within the natural variability of the day; yet for the other, they showed evident alterations in the slopes of the major parameters, which we analyze and discuss. A decrease in temperature of 3.2 °C was detected in Riyadh. However, RH and VP showed an oscillation that we explain taking into account a similar effect reported in other eclipses. We measured a time lag of about 15 min from the eclipse central phase in the city. Related fluctuations and dynamics from the computed rates of the temporal variation of temperature and RH are scrutinized. Furthermore, an overdue significant review of terrestrial atmospheric parameters is also offered in the context of the eclipse meteorology, particularly related to desert atmospheres. We also try to identify the influence of solar eclipses in similar environments doing a broad inter-comparison with other observations of these variables in the Near East, northern Africa, and in the United States. These inter-comparisons reveal how complex and dissimilar the response of the lower atmosphere to a solar eclipse can be within a desert environment and other similar environments. [ABSTRACT FROM AUTHOR]

The Kingdom of Saudi Arabia is experiencing a surge in electricity demand, with power generation increasing 4 times in 25 years from 1990 to 2014. Despite the abundant primary renewable energy sources, the country has overlooked them in the past in national energy policies. However, in recent years, renewable energy has become a part of the Kingdom of Saudi Arabia's energy conservation policy due to climate changes, technological progress, economies of scale, and increased competitiveness in supply chains. The Saudi government has created the King Abdullah City for Atomic and Renewable Energy (KACARE) to develop national strategies for effectively utilizing renewable and nuclear energy. This paper reviews the current state of the art of the renewable energy technologies available on the market and evaluates the installation of renewable energy plants near Saudi Arabia's East Coast for a new town, focusing on technical rather than economic aspects. The paper provides a wide review of the possible technical solutions to exploit the producibility of different renewable sources, considering the challenging climate conditions typical of desert areas. The analysis of a real case study shows a high availability of wind and solar irradiance that allow a net energy production of 354 and 129 GWh, respectively. In addition, the comparison between a typical ground-mounted photovoltaic (PV) system and an emerging floating PV reveals that for the same installed power, occupied area, and environmental conditions, the latter has a 4% greater performance ratio due to the cooling effect of water. [ABSTRACT FROM AUTHOR]