Recent Submissions

  • Digital Twin Integration for Hydrogen Leakage Modeling and Analysis

    El-Amin, Mohamed F.; No Collaboration; Energy Lab; 0; 0; NSMTU; 0; El-Amin, Mohamed F. (IEEE, 2024-03-01)
    Digital twin technology is revolutionizing the modeling and simulation of complex systems, such as hydrogen leakage. This paper focuses on integrating digital twin components, starting with experimental measurements. The collected data is then used to calibrate the corresponding physics-based model, improving the accuracy of predictions. A numerical simulator is developed to enable virtual experiments and performance analysis. Comprehensive datasets are generated from real and virtual experiments, enhancing the capabilities of the twin by providing diverse training data. Machine learning prediction utilizes real and artificial datasets to gain insights into system behavior. The bidirectional relationship between the numerical simulator and machine learning prediction enhances accuracy and enriches the overall process. Viewed through the lens of science fiction, the case study on hydrogen leakage can be sculpted into a compelling narrative intertwining advanced technology, human resilience, and the ever-present challenge of harnessing and managing powerful, futuristic energy sources deep within planets.
  • The Generalized Average Entropy with Applications to some Satellite Image Thresholding

    O, Kittaneh; No Collaboration; Artificial Intelligence & Cyber Security Lab; 0; 0; NSMTU; 0; O, Kittaneh (IEEE, 2023-04-11)
    This paper suggests a generalization to the average entropy that was introduced by Kittaneh et. al. [The American Statistician 70 (2016) 1]. Some properties of this generalization are studied and a new fully automated entropy-based multi-level image thresholding method with a solid theoretical background is proposed. The method is applied to several real satellite images and compared with the so-called Otsu’s method. The comparative study shows that the proposed method is comparable to Otsu’s method.
  • Mapping the Research Landscape of Social and Cultural Impacts on Smart Cities

    Ibrahim, Asmaa; Brahimi, Tayeb; College collaboration; NA; NA; NA; NSMTU; NA; Asmaa Ibrahim (Springer Proceedings in Complexity, 2024-01-01)
    The integration of digital technology and innovation in the creation of smart cities has significantly improved the quality of life for citizens. However, while there have been extensive studies on the technological capabilities of smart cities, there is a notable gap in research concerning their cultural and social aspects. To address this concern, this study aims to comprehensively examine the social and cultural impacts of smart cities through bibliometric analysis. By analyzing 1160 published articles from the Scopus database, the study highlights the importance of prioritizing the creation of inclusive, safe, resilient, and sustainable cities, aligning with the United Nations Sustainable Development Goal 11. The study identifies China, the United States, Italy, India, and the United Kingdom as the top contributing countries, with the Norwegian University of Science and Technology being the most active institution in this area. Moreover, this research explores the intersection of social and cultural impacts within the broader context of Innovation 5.0 and Industry 5.0, providing valuable insights for future researchers and practitioners. Nevertheless, it is crucial to acknowledge certain limitations, such as the reliance on Scopus data, which may exclude relevant publications from other sources. Additionally, the analysis based on bibliometric data may not capture the full extent of social and cultural impacts associated with smart cities.
  • Detection of Hydrogen Leakage Using Different Machine Learning Techniques

    El-Amin, Mohamed F.; No Collaboration; Energy Lab; 0; 0; NSMTU; 0; El-Amin, Mohamed F. (IEEE, 2023-04-11)
    When employing pure hydrogen, its leakage poses a serious safety risk since it can cause fire or explode if it comes into contact with the air. In this study, hydrogen leakage in a form of a buoyant jet is investigated using machine learning approaches. As the experiments used to explore hydrogen leaks are extremely dangerous, and there is a limitation of data, we instead construct an artificial dataset using a traditional numerical model. The dataset was produced using a combined empirical-analytical-numerical model. Investigations into dataset preparation, feature significance, correlation, and hyperparameter adjustment are conducted. Artificial neural networks, random forests, gradient boosting regression, and decision trees are the machine-learning approaches that have been used to forecast the distribution of hydrogen leaks in the atmosphere. Different error metrics and R 2 correlation have been used to assess the prediction accuracy. The RF method was found to be the most effective approach for forecasting the dispersion of hydrogen leaking into the air.
  • Machine Learning Prediction for Nanoparticles Behavior in Hydrocarbon Reservoirs

    El-Amin, Mohamed F.; Al Wateed, Mohamed F.; No Collaboration; Energy Lab; 0; Budoor Alwated; NSMTU; 0; El-Amin, Mohamed F. (IEEE, 2023-04-11)
    The use of machine learning to forecast how nanoparticles would migrate through porous material is covered in this research. We employed the random forest, decision tree, artificial neural network, and gradient boosting regression machine learning techniques. Since there are not many experimental datasets available, it is easier to create artificial datasets using verified numerical simulators. Additionally, covered in the paper are data preprocessing, correlations, the importance of features, and hyperparameter adjustment. Moreover, different error metrics and R 2 -correlation are used to gauge how well the predictive models perform. Finally, examples of the findings are presented. The decision tree model is determined to have the highest accuracy, the best performance, and the lowest root mean squared error.
  • Data Mining and Visualization of Space Technology Research Trends in the Arab World

    Brahimi, Tayeb; No Collaboration; Energy Lab; NSMTU; Brahimi, Tayeb (IEEE, 2023-04-11)
    Space exploration has become a crucial field in recent years, with many countries investing heavily in research and development to enhance their capabilities. Nevertheless, there has been a lack of research on the trends and advancements in aerospace research in the Arab world. This study aims to address this gap by conducting a bibliometric analysis of scientific publications using the Scopus database. The analyzed data covers the period from 1980 to 2022 and focuses on identifying the historical foundations, evolution, and emergence of space programs through citation, occurrence, collaboration, and clustering. The United Arab Emirates is found to be the most active country in terms of publications, followed by Saudi Arabia and Egypt. The results indicate that the majority of the publications are centered on remote sensing and the use of optical systems in space exploration. This study provides valuable insights into technological innovation in the aerospace sector in the Arab world and highlights potential research directions for future studies.
  • Mapping the Scientific Landscape of Metaverse Using VOSviewer and Bibliometrix

    Brahimi, Tayeb; Haneya, Hala; Department Collaboration; Energy Lab; 1; 1; NSMTU; Brahimi, Tayeb (IEEE, 2023-04-11)
    The concept of the Metaverse has gained increasing attention as advances in virtual and augmented reality (AR) technologies have enabled the creation of immersive and interactive virtual environments. However, most of these studies remain independent and only a few studies attempted to investigate their relationships. To analyze key trends in Metaverse research and conduct a thorough bibliometric analysis, we used VOSviewer and Bibliometrix, R-tool package on the Scopus database. Our co-occurrence analysis revealed that the hot topics are related to virtual reality, augmented reality, the Internet of Things, and blockchain, and there are potential areas for future research, such as privacy, security, and education in the Metaverse. In addition, our analysis identified the most active countries and institutions in the field, the top subject areas, as well as potential gaps in the literature that could be explored in future research. This study provides valuable insights into Metaverse research and can help guide future research in this field.
  • Design and Simulation of a Standalone PV System for a Mosque in NEOM City

    Alzharani, Amani; Brahimi, Tayeb; Rajeh, Mashael; Banjar, Shaima; No Collaboration; Energy Lab; NSMTU; 3; Alzharani, Amani (2021-03-07)
    The current state and the future potentials of renewable energy have increased widely globally to reduce the usage of other resources such as fossil fuel, which affect the environment. NEOM city in the Kingdom of Saudi Arabia (KSA) is a case where renewable energy will count for 100% of its energy consumption. Solar energy will play a prominent role in NEOM city. This project aims to present a design and simulation of a standalone photovoltaic (PV) system for a mosque located in NEOM city to meet the people's need for electricity. The system harvests solar energy and converts it into electrical energy to cover the electrical power needed for a typical mosque in NEOM. The design and simulation have been implemented using PVsyst software, powerful software for designing, simulating and generating PV systems reports. The designed standalone PV system could produce yearly electrical energy of 300 MWh. This study's significance relies on initiating research and development of building PV systems to harvest solar energy in NEOM city.
  • Wind Energy in Saudi Arabia Opportunities and Challenges

    Alkinani, Sadeem; Alghazi, Omnia; Asfour, Rawan; Brahimi, Tayeb; Department Collaboration; Energy Lab; NSMTU; 3; Alkinani, Sadeem (IEOM, 2022-04-05)
    Wind energy has been recognized as one of the fastest-growing energy sources in world and as a key role in reducing greenhouse gas emissions, reducing dependence on oil, diversifying energy supply, and providing electricity at a low cost. In its 2030 Vision, the Kingdom of Saudi Arabia has recently set ambitious targets to move away from oil dependency and redirect the efforts towards more higher-value exploitation of oil and gas, mainly meeting 10 percent of its energy demand through renewable energy sources. This paper attempts to explore the feasibility of using wind turbine machines for energy generation in Saudi Arabia by presenting a study of the opportunities and challenges that can arise while installing these machines. The paper also highlights several technical challenges and gaps that have been anticipated for this design motivation. Observations and upcoming trends show that by 2030 renewable energy, including solar and wind, will provide up to 50% of electricity production in the Kingdom.
  • A Bibliometric of Sentiment Analysis in Tourism Industry during COVID-19 Pandemic

    Yaqub, Asra; Huda, Talib; Brahimi, Tayeb; Sarirete, Akila; Department Collaboration; Energy Lab; 2; Master of Science in Urban Design; Asra, Yaqub (IEOM, 2022-03-07)
    The purpose of this paper is to explore, visualize, and analyze the state-of-the-art research of sentiment analysis in the tourism industry during COVID-19 using bibliometrics. The information source is obtained from the Scopus database from January 1, 2020, to November 27, 2021. A sample of 1690 documents was obtained within this period. Topic areas with titles, keywords, and abstract criteria in sentiment analysis and travel and tourism were used as a reference for extracting results. There was a significant increase in papers published in 2020 and 2021 related to COVID-19 and sentiment analysis. The top five most active countries were the United States (310 documents and 1799 citations), followed by the United Kingdom (170 documents and 12674 citations), China (240 documents and 1297 citations), Australia (120 documents and 430 citations), and Germany (44 documents and 172 citations). The maximum number of occurrences was "social media (401)" followed by "sentiment analysis (149)", "tourism (116)", "Covid-19 (131)", and "Twitter (77)". This study provides an overview of sentiment analysis and shows the trends in the research and publication with the tourism industry.
  • A Data Mining Analysis of Cognitive Science and Artificial Intelligence

    Brahimi, Tayeb; Haneya, Hala; Yaqub, Asra; Al Salem, Fatmah; Bathallath, Joudi; No Collaboration; Energy Lab; 4; NSMTU; Brahimi, Tayeb (IEEE, 2023-01-13)
    Cognitive science borrows from fields such as Artificial Intelligence (AI) which helps in simulating and modeling the human brain. Recently, there has been an increase in the number of research and applications involving cognitive science and AI cooperation. Based on data extracted from the Scopus database. This paper uses the Visualization Of Similarities Method (VOS) between objects in VOSviewer 1.6.18 to look at, evaluate, and find relevant literature, trends, and the scope of research in the fields of cognitive science and AI. The results showed that the USA, the UK, China, Germany, and Canada are the top 5 most active countries in terms of publications. The University of Calgary came out on top of the active institution while the top funding source came from the National Science Foundation in the USA. The study's results will serve as a road map for future academics and researchers developing theory and practice in artificial intelligence and cognitive science.
  • The Practicality of the Internet of Underwater Things: MATLAB & Simulink AUV Application IoT

    Al Talib, Rabab; Rabih Fatayerji, Hala; Alqurashi, Asmaa; Brahimi, Tayeb; No Collaboration; Energy Lab; 3; NSMTU; Al Talib, Rabab (IEOM, 2022-06-12)
    As Oceans cover approximately 72% of the Earth's surface, it is imperative to extend the Internet of Things (IoT) principles to the existing bodies, paving the way for a new digital trend: the Internet of Underwater Things (IoUT). The IoUT refers to the worldwide network of smart interconnected underwater objects, which enhances monitoring unexplored and vast water areas. It enables various applications like environmental monitoring, disaster prevention, and underground exploration. The Internet of Underground things with such applications is among the leading applied technologies in smart cities. This paper aims to focus specifically on determining the potential applications of the IoUT applications, which can help in examining the challenges that are and will be faced during its modeling and implementation. The study aims to investigate the challenges of designing and implementing such a network. The research includes communication networks and MATLAB & Simulink simulation. Based on previous reviews, an optimal network of IoUT enhances the development and integration of various systems for the robust evaluation of water ecosystems. The study's outcomes include a tested AUV simulation model, which is a crucial part of an IoUT system that can be adjusted to suit local water conditions. The idea of IoUT should be embraced due to its positive impact on social and economic factors.
  • Modeling and Numerical Analysis of Harvesting Atmospheric Water Using Copper Chloride

    Brahimi, Tayeb; El-Amin, Mohamed; Alkinani, Sadeem; Department Collaboration; Energy Lab; NSMTU; 1; Alkinan, Sadeem (IEEE, 2022-06-13)
    Access to freshwater is becoming increasingly difficult due to a lack of sources, such as lakes, rivers, and groundwater. To resolve water scarcity, Harvesting Atmospheric Water (HAW) has emerged as a promising alternative water source, particularly for arid areas. However, the efficiency of an atmospheric water harvesting system depends on relative humidity, temperature, water sorption capacity based on the adsorption phenomenon, and other factors. This paper aims to develop a mathematical model to simulate and analyze atmospheric water harvesting using copper chloride. The simulation results show that the proposed mathematical modeling predicts well the water content. The water content reaches saturation at different times, depending on the depth. More work is underway to simulate and analyze atmospheric water harvesting using other types of salts, for example, magnesium sulfate and copper sulfate and compare the results with experimental data, as well as conducting sensitivity analysis to explore how depths, porosities, hydraulic conductivities, temperatures, and relative humidity affect moisture absorption.
  • An Outlook to Childhood Obesity in Saudi Arabia using VOSviewer

    Haneya, Hala; Balbaid, Hanin; Ranjha, Hafsa; Brahimi, Tayeb; Khateeb, Kholoud; Department Collaboration; Energy Lab; 3; NSMTU; Brahimi, Tayeb (IEOM, 2022-03-07)
    Childhood Obesity (CHO) is a global epidemic that has increased in recent years. According to the World Health Organization (WHO), 39 million children under five will be overweight or obese in 2020. In Saudi Arabia, the prevalence of obesity reached its peak at 35.5%. WHO also anticipated that by 2030, 30% of all deaths worldwide would be caused by lifestyle diseases. Extensive studies have been published on the fundamental causes of obesity, its treatment, and its prevention. As a result of the efforts and resources invested in childhood obesity research, control, and prevention, it is necessary to assess and analyze these studies and provide valuable insights to public health officials and healthcare institutions. Using the Scopus database, this paper uses bibliometric analysis to evaluate and identify trends and studies in childhood obesity in Saudi Arabia based on VOSviewer. Results revealed that the top 5 active affiliations in childhood obesity are King Saud University (165 documents), King Abdulaziz University (139), King Saud University for Health Sciences (47), Imam Abdulrahman Bin Faisal University(42), and Princess Nourah Bint Abdulrahman University (39). King Saud University sponsored the highest number of published documents. Out of 643 documents retrieved from the Scopus database, 42.5% were in Medicine and 11.8% in biochemistry. Understanding state-of-the-art childhood obesity is critical in planning future measures to control and prevent highrisk children early and future obesity complications. This study aims to provide insight for Saudi Arabian authorities to consider boosting health measures to reduce the incidence and prevalence of CHO.
  • Research and Trends in COVID-19 Vaccines Using VOSviewer

    Brahimi, Tayeb; Abbas, Hagar; No Collaboration; Energy Lab; 1; NSMTU; Brahimi, Tayeb (Springer, 2022-02-18)
    The World Health Organization (WHO) classified the latest coronavirus (COVID-19) as a pandemic on March 11, 2020. As a result, the pandemic has spread to practically every country on the planet. WHO’s major goals for 2021 are to fight COVID-19, strengthen current health systems, increase access to COVID-19 treatment, and provide equitable and safe vaccines for all. As the number of scientific publications continues to expand, there is an increasing need to analyze factors and characteristics that contribute to highly published documents and highly cited articles. This study evaluates and identifies trends and studies in COVID-19 vaccines using the SCOPUS database and VOSviewer. The top five active countries on COVID-19 vaccines publication are the United States with 4168 documents, China with 2245 documents, Italy with 1512 documents, the United Kingdom with 1370 documents, and Spain with 663 documents. Results of network visualizations indicate that understanding the state-of-the-art COVID-19 pandemic is essential in planning future measures to fight COVID-19 and improve vaccination uptake
  • Wind Farm Layout: Modeling and Optimization Using Genetic Algorithm

    Brahimi, Tayeb; El-Amin, Mohamed; Asfour, Rawan; Department Collaboration; Energy Lab; NSMTU; 1; Asfour, Rawan (IOP Publishing Ltd, 2022-01-08)
    . Wind Farm Layout Optimization (WFLO) is a complex multidisciplinary topic that requires a lot of expertise and is becoming an essential part of today's wind farm planning. Yet, selecting optimum wind farm locations is complex, time-consuming, and influenced by environmental factors and upstream turbines inflow wind. The present study attempts to develop an optimization approach based on the Genetic Approach (GA) to determine the most suitable wind turbine locations that maximize the net energy production while minimizing the Cost of Energy (COE) ($/kWh). The WFLO for the optimized objective function was performed for 500, 1000, and 1500 iterations. The best output was obtained for 1500 iterations with the lowest value for the objective function.