• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.908-918
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• 2023

The Saudi National Atomic Energy project aims to adopt peaceful nuclear technologies and be part of the country's energy mix. As emerging nuclear energy, it is essential to understand public concerns and acceptability of nuclear energy, as well as the factors influencing acceptance to develop nuclear energy policy and implement nuclear energy programs. The purpose of this study is to analyze the public attitudes and acceptance of nuclear energy among Saudi Arabian citizens by utilizing protection motivation theory and theory of planned behavior. A total of 1,404 participants answered a questionnaire which was distribute by convenience sampling approach. A Structural Equation Modeling framework was constructed and analyzed to understand public behavior toward building the country's first Nuclear Power Plant (NPP). Before analyzing the data, the model was validated. The research concluded that the benefits of nuclear power plants were essential in determining people's acceptance of NPPs. Surprisingly, the effect of the perceived benefits was found higher than the effect of the perceived risks to the acceptance. Furthermore, the public's participation in this study revealed that the NPPs location has a significant impact on their acceptance. Based on the finding, several policy implementations were suggested. Finally, the study's model results would benefit scholars, government agencies, and the business sector in Saudi Arabia and worldwide.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.113-124
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• 2024

One of the goals of the Saudi Arabia 2030 vision is to ensure full employment of its citizens. Recruitment of graduates depends on the quality of skills that they may have gained during their study. Hence, the quality of education and ensuring that graduates have sufficient knowledge about the in-demand skills of the market are necessary. However, IT graduates are usually not aware of whether they are suitable for recruitment or not. This study builds a prediction model that can be deployed on the web, where users can input variables to generate predictions. Furthermore, it provides data-driven recommendations of the in-demand skills in the Saudi IT labor market to overcome the unemployment problem. Data were collected from two online job portals: LinkedIn and Bayt.com. Three machine learning algorithms, namely, Support Vector Machine, k-Nearest Neighbor, and Naïve Bayes were used to build the model. Furthermore, descriptive and data analysis methods were employed herein to evaluate the existing gap. Results showed that there existed a gap between labor market employers' expectations of Saudi workers and the skills that the workers were equipped with from their educational institutions. Planned collaboration between industry and education providers is required to narrow down this gap.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.677-682
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• 2020

To investigate the nexus between urban population, gross capital formation, and economic growth in the Kingdom of Saudi Arabia, yearly data was collected from the World Bank for the period 1974- 2018. Basic statistics test and correlation matrix was used to investigate the causal effect among the tested parameters, followed by Augmented Dickey-Fuller (ADF) stationary test, co-integration analysis by Johansen test after that Vector Auto-Correction Model for both short-run and long-run and finally the Granger-Causality tests. Result of unit root test analysis shows that the urban population became stationary at I (0) level while economic growth and gross capital formation became stationary at I (1). Johansen co-integration analysis indicates that there is presence of both long-run and short-run relationship between the three variables in the Kingdom of Saudi Arabia. The result of the VECM Model reflects that both economic growth and gross capital formation have a negative impact on urban population in the short run. According to the Granger-Causality tests, there is unidirectional causality with the urban population by both gross capital formation and economic growth. Also, the result of the Granger Causality tests show that there is unidirectional causality between economic growth and gross capital formations.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.5
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• pp.2723-2726
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• 2016

Cancer represent one of the most serious health problems and major causes of death around the world. Many anticancer drugs in clinical use today are natural products or derived from natural sources. Withania somnifera (L.) Dunal is a small shrub widely distributed in many parts of the world including Saudi Arabia. The antiproliferative activities of the methanolic extract of W. somnifera leaves collected from Faifa mountains, southwest Saudi Arabia against MCF-7, HCT116 and HepH2 cell lines were investigated. The extract showed a strong antiproliferative activity against all cell lines with $IC_{50}$ values of 3.35, 2.19 and $1.89{\mu}g/ml$, respectively. Flow cytometry results showed that the extract arrested the cell cycle at S phase, and the increase in the caspase 3 activity suggested that the extract could induce cell apoptosis by a caspase mediated pathway. These results demonstrated that the methanolic extract of W. somnifera leaves collected from Faifa mountains has comparable strong antiproliferative activities to samples collected from different locations.

• Environmental Engineering Research
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• v.23 no.1
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• pp.84-91
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• 2018

The present study deals with the management of groundwater resources of an important agriculture track of north-western part of Saudi Arabia. Due to strategic importance of the area efforts have been made to estimate aquifer proneness to attenuate contamination. This includes determining hydrodynamic behavior of the groundwater system. The important parameters of any vulnerability model are geological formations in the region, depth to water levels, soil, rainfall, topography, vadose zone, the drainage network and hydraulic conductivity, land use, hydrochemical data, water discharge, etc. All these parameters have greater control and helps determining response of groundwater system to a possible contaminant threat. A widely used DRASTIC model helps integrate these data layers to estimate vulnerability indices using GIS environment. DRASTIC parameters were assigned appropriate ratings depending upon existing data range and a constant weight factor. Further, land-use pattern map of study area was integrated with vulnerability map to produce pollution risk map. A comparison of DRASTIC model was done with GOD and AVI vulnerability models. Model validation was done with $NO_3$, $SO_4$ and Cl concentrations. These maps help to assess the zones of potential risk of contamination to the groundwater resources.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.16
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• pp.6477-6483
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• 2014

Background: Shammah is a traditional form of chewing tobacco [smokeless tobacco, (ST)] that is commonly used in the Middle East especially in Saudi Arabia (KSA), Yemen and Sudan. The Substance Abuse Research Centre (SARC) at Jazan University noted that no adequate research and information on the prevalence of shammah use in the province of Jazan, and KSA as well, has been provided in the scientific literature. Materials and Methods: An intensive systematic review of online databases was performed, including AMED (The Allied and Complementary Medicine Database), Biological Abstracts, Cochrane Collection Plus, Dentistry and Oral Sciences Source, E-Journals Database, EBSCO Discovery Service, MEDLINE, PEMSoft, PEP Archive, PsycARTICLES, scopus, Sciencedirect and Google Scholar. Results: Shammah is a mixture of powdered tobacco, lime, ash, black pepper, oils and flavorings. ST in KSA is placed in the buccal or lower labial vestibule of the mouth. The user (or dipper) spits out insoluble debris. The importation of ST products is prohibited in KSA. Accessible information on legislative action to control the use of ST in KSA appeared in 1990. The actual percentage use may be higher, than reported since shammah is illegal in KSA and there may be some reluctance to admit to its use. Conclusions: This review paper is an initial step in a funded research project by SARC to understand the pattern of use of shammah and provide adequate epidemiological data. One goal of this review is to generate further data for public health education.

• Parasites, Hosts and Diseases
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• v.58 no.2
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• pp.129-134
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• 2020

In most developing countries, Dientamoeba fragilis infection is an obscure protozoan infection. We aimed to determine a frequency and clinical importance of D. fragilis infection in Taif, Saudi Arabia. A 1-year case control study included patients with gastrointestinal (cases, n=114) or non-gastrointestinal symptoms (controls, n=90). The fecal samples were examined with the classical parasitological methods for intestinal protozoa, and by real time PCR for D. fragilis. The infection by D. fragilis was detected in 5.8% by PCR and in 4.4% patients by microscopy. The infection was identified more in control group (n=9) than in cases (n=3); a sole infection in 11 patients and mixed with Giardia in 1 patient. The other enteric parasites detected were Blastocystis sp. (8.3%), Giardia sp. (5.3%), Cryptosporidium sp. (2.9%), Entamoeba histolytica (1.4%), Entamoeba coli (0.9%) and Hymenolepis nana (0.4%). Our results tend to reinforce the need to increase awareness of D. fragilis infection in Saudi Arabia.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.212-222
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• 2021

Multiple waves of COVID-19 highlighted one crucial aspect of this pandemic worldwide that factors affecting the spread of COVID-19 infection are evolving based on various regional and local practices and events. The introduction of vaccines since early 2021 is expected to significantly control and reduce the cases. However, virus mutations and its new variant has challenged these expectations. Several countries, which contained the COVID-19 pandemic successfully in the first wave, failed to repeat the same in the second and third waves. This work focuses on COVID-19 pandemic control and management in Saudi Arabia. This work aims to predict new cases using deep learning using various important factors. The proposed method is called Deep Learning and Dynamic Weighing-based (DLDW) COVID-19 cases prediction method. Special consideration has been given to the evolving factors that are responsible for recent surges in the pandemic. For this purpose, two weights are assigned to data instance which are based on feature importance and dynamic weight-based time. Older data is given fewer weights and vice-versa. Feature selection identifies the factors affecting the rate of new cases evolved over the period. The DLDW method produced 80.39% prediction accuracy, 6.54%, 9.15%, and 7.19% higher than the three other classifiers, Deep learning (DL), Random Forest (RF), and Gradient Boosting Machine (GBM). Further in Saudi Arabia, our study implicitly concluded that lockdowns, vaccination, and self-aware restricted mobility of residents are effective tools in controlling and managing the COVID-19 pandemic.

• International Journal of Computer Science & Network Security
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• v.21 no.12
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• pp.101-109
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• 2021

Cybercrimes are the biggest threat that can influence the future of e-commerce, particularly in difficult times such as the COVID-19 pandemic. This pandemic has resulted in noticeable changes in e-customer behaviour represented in three types: spending rates, types of goods bought, and the number of purchasing times. Moreover, the percentage of cybercrime in many countries, including Saudi Arabia, has increased during the pandemic. The increase in the number of cybercrimes during the COVID-19 crisis and the changes in consumer behaviour shows that there is an urgent need to conduct research on the factors that have led to this. This study will explore the most significant factors that have an effect on the unexpected change of customer behaviour and cybercrime perceived risk during the COVID-19 pandemic in Saudi Arabia. The finding of the study will hopefully contribute to attempts in finding safer methods for shopping online during COVID-19 and similar crisis.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.201-210
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• 2021

COVID-19 presented the world with a severe loss of life and impact, which has no geographical bounds or expected time to when its effects will subside. It has affected countries across the globe, disrupting economic levels and businesses in every industry while also altering individuals' everyday lives. The current research aims to examine the impact of coronavirus pandemic on entrepreneur's business activities and their perceptions on the difference in consumer behavior during this time. The findings reveal the pandemic negatively impacted business productivity and profits, forcing many businesses to physically close permanently. Surprisingly, female entrepreneurs do not perceive a change in consumer behavior compared to pre-COVID-19 times. Interestingly, the results indicate there is a negative impact on employees' efficiency to conduct work in which almost no research has conveyed such a finding. For this purpose, a survey was conducted with 445 responses from male and female entrepreneurs in the capital city of Riyadh, Saudi Arabia, using a simple random sample over the period of four months. Ultimately, this research will help entrepreneurs gain more knowledge and a deeper understanding of this new environment necessary to undertaking certain measures and adaptability in order to sustain their businesses during unprecedented times.