Abstract. Many people in the Kingdom of Saudi Arabia, KSA are suffering because of road accidents in spite of huge efforts to reduce fatalities.  A recent study revealed that the most prominent factors leading to road accidents were incorrect behavior by the vehicle driver, failure to follow the regulations and continuous violations. Excessive speed ranks second in the causes of fatal traffic accidents, while crossing a red signal is the third factor. This paper presents the results of an evaluation and analysis of speed at different selected locations in Eastern Province, Kingdom of Saudi Arabia. The study was carried out along two major corridors in Eastern province: GCC and King Fahd highways. 88 site locations were studied thoroughly. The results showed that speed problems exist in some locations. The 85th percentile speeds were used to assess the drivers complains with posted speed. It was found that the percentage of drivers exceeding the posted speed varied according to the location. In some locations it exceeded 20% on average. The results showed that, based on the limited collected data, the posted speed in some locations may not be appropriate. The GIS analysis revealed that in the locations of high speed there is a high percentage of accidents.

Abstract. A customer enters a store, buys something, and leaves without realising that the customer has been charged. This trend is significantly growing due to the increasing availability of NFC, Bluetooth, and/or Internet of Things (IoT) enabled devices for payment. IoT-based mobile payment solutions have significant potential to address increased consumers’ desire for convenience and improve efficiency. Nevertheless, the adoption of IoT mobile payment systems is still in its infancy. Hence, this study examines the factors driving consumers’ behavioural intention to use IoT mobile payment by employing the theoretical lens of the unified theory of adoption and use of technology (UTAUT) and trust-based acceptance models. This research applies a structural equation modelling (SEM) analysis and the PLSpredict algorithm to validate the model.  Based on data collected from university students and faculty members due to their high probability of using IoT mobile payment systems, this work reveals an excellent tendency to adopt online and mobile payment. The findings highlight the three most influential factors (i) performance expectancy, (ii) effort expectancy, and (iii) trust. Moreover, this study discloses a high correlation between cognitive and emotional trust and trust within the trust-based acceptance model. However, the result reveals insufficient statistical evidence to support the positive impact of social influence, facilitating condition, and price value on consumers’ behavioural intention to use IoT mobile payment. Finally, this study offers practical and theoretical implications in the IoT and mobile payment literature.

ABSTRACT. Agriculture is one of the main sources of income for the government of Saudi Arabia. It is included in one of the twelve pillars of the 2030 vision. The Public Investment Fund which is also known as PIF has launched its strategic plan for 2021-2025 to thrive the economy for diversity. This strategic plan consists of numerous key initiatives and one of them is food and agriculture. It focuses on enabling the growth of food and agriculture inside Saudi Arabia to reach the sustainability level of domestic food production, ensuring food strength and flexibility and having a diversity food supply sources from outside the country. Hence, having disease-free plants is a must for this initiative. In this paper, proposing an algorithm to detect diseases in plants is presented. It works based on combining the K-means and Convolutional Neural Networks (CNNs) approaches. The obtained results show that this method achieves more than 95% of accuracy. The simulation experiments are conducted using MATLAB as a simulation tool. Finally, an assessment between the proposed algorithm and some state-of-the-art works from the literature is presented. This evaluation shows that the implemented method outperforms other works in terms on accuracy, precision, and recall respectively.

Abstract: For the buildings of importance, it is essential to focus attention on knowing the behavior of these buildings towards resisting wind loads and seismic loads and finding the stresses resulting from this resistance to make a reliable design that guarantees the safety of these buildings. In this paper, a "conference building" located at Islamic University in Madinah region has been studied under the impact of seismic load. It has been analyzed to ensure its ability to resist seismic load stably. Al-Madinah region is located between two seismic zones (0 and 1) as stated in the Saudi Arabia zonation map which has factors of 0.05g and 0.075g respectively. According to that, the structure was checked for a higher seismic zone (zone 2A) of a Peak Ground-Acceleration (PGA) of 0.15g and this was done according to Eurocode-8 (EC8) requirements and the analysis was carried out manually and by using SAP2000. According to the results obtained using the shear wall system, the building had exhibited very high stability against seismic load by more than three times against sliding and 24 times against overturning. The building’s elements were designed and the selected sections have been found suitable for exerting good performance.