Saudi Cultural Missions Theses & Dissertations
Permanent URI for this communityhttps://drepo.sdl.edu.sa/handle/20.500.14154/10
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Item Restricted Food Safety in UK Households: The Influence of Concerns Regarding Food Poisoning and Demographics on Compliance with Meat and Poultry Handling Guidelines(The university of Leeds, 2024-08-30) Alsufyani, Nuha Hameed; Ensaff, HannahThis study investigated whether concern about food poisoning (e.g., Salmonella and E. coli) influences household compliance with hygiene guidelines for handling raw meat and poultry at home, and how demographic factors affect this compliance. A secondary analysis of the data from the “Food and You 2” survey (wave 6) by the Food Standards Agency, involving 4,893 respondents from England, Wales, and Northern Ireland, was conducted. Descriptive statistics, Chi-Square tests, and logistic regression were used to explore relationships between variables. Results showed that 53% of respondents exhibited high compliance with hygiene guidelines. Concern about food poisoning was significantly associated with higher compliance (57% vs. 48%, p<0.001). The logistic regression showed that concerned individuals were 48% more likely to report high compliance. Additionally, age, sex, employment, and being the main food provider were significantly associated with compliance, while marital status and income were not significant predictors. Specifically, increasing the age predicts higher compliance with 18% for each decade, females were 19% more likely to comply than males, employed individuals had 37% higher odds of compliance compared to unemployed, and main food providers were over 2 times as likely to comply as non-regular cooks. The study concludes that food poisoning concerns and demographic factors, particularly age and being the main food providers, play significant roles in predicting compliance with hygiene guidelines. These findings can inform targeted public health interventions to enhance food safety practices, especially among younger populations and less frequent cooks.21 0Item Restricted Understanding the Influence of Cultural Factors on Process Safety Behaviours in the Saudi Arabian Oil and Gas Industry(The University of Sheffield, 2024-09-02) Algarni, Abdulrahman; Hoseyni, SeyedThe study proposed seeks to investigate the main cultural factors that can impact process safety behaviours with focus on risk perception within the Saudi Arabian oil and gas industry. The project, through the collected data seeks to suggest recommendations which can improve safety culture and reduce its impacts on process safety behaviours. The study is based on a mixed-methods approach which combines quantitative questionnaires with qualitative case study analysis. Tow quantitative questionnaires where designed and directed to selected managers and workers operating in the Saudi oil and gas industry. These two questionnaires investigated many cultural dimensions which can impact risk perception among participants. The case study provided by Alshahrani et al (n.d.) investigated the impact of national culture on safety behaviour among Saudi and non-Saudi employees operating in the petrochemical industry as part of the oil and gas industry. The main findings of this research proved that some cultural factors in the Saudi oil and gas industry are determinant in shaping the effectiveness of risk perception the process safety behaviour in general terms. There are clear indications from the questionnaires basically and the case study that cultural factors such as traditional and religious values, masculinity as related to risk taking behaviours, fatalistic attitudes, low perception of risk tolerance and risky optimism are currently impacting the level of risk perception in the Saudi oil and gas sector having as such a direct impact on process safety behaviours10 0Item Restricted Predicting Pedestrian Crossing Intention(Saudi Digital Library, 2024) Alofi, Afnan; Trivedi, MohanAutonomous vehicles face significant challenges in understanding pedestrian behavior, particularly in urban environments. The system must recognize pedestrians’ intentions and anticipate their actions to achieve intelligent driving. This paper focuses on predicting pedestrian crossings, aiming to enable oncoming vehicles to react in a timely manner. We investigate the effectiveness of various input modalities for pedestrian crossing prediction, including human poses, bounding boxes and ego vehicle speed features. We propose a novel lightweight architec- ture based on LSTM and attention to accurately identifying crossing pedestrians. Our methods evaluated on two widely used public datasets for pedestrian behavior, PIE and JAAD datasets, and our algorithm achieved a state-of-the-art performance in both datasets34 0