Object recognition is the technique of specifying the location of various objects in images or videos. There exist numerous algorithms for the recognition of objects such as R-CNN, Fast R-CNN, Faster R-CNN, HOG, R-FCN, SSD, SSP-net, SVM, CNN, YOLO, etc., based on the techniques of machine learning and deep learning. Although these models have been employed for various types of object detection applications, however, tiny object detection faces the challenge of low precision. It is essential to develop a lightweight and robust model for object detection that can detect tiny objects with high precision. In this study, we suggest an enhanced YOLOv2 (You Only Look Once version 2) algorithm for object detection, i.e., vehicle detection and recognition in surveillance videos. We modified the base network of the YOLOv2 by reducing the number of parameters and replacing it with DenseNet. We employed the DenseNet-201 technique for feature extraction in our improved model that extracts the most representative features from the images. Moreover, our proposed model is more compact due to the dense architecture of the base network. We utilized DenseNet-201 as a base network due to the direct connection among all layers, which helps to extract a valuable information from the very first layer and pass it to the final layer. The dataset gathered from the Kaggle and KITTI was used for the training of the proposed model, and we cross-validated the performance using MS COCO and Pascal VOC datasets. To assess the efficacy of the proposed model, we utilized extensive experimentation, which demonstrates that our algorithm beats existing vehicle detection approaches, with an average precision of 97.51%.

The purpose of this paper is to develop fragility curves for bridges in Korea. Fragility curves are needed for assessing the vulnerability of bridges to unscheduled events and for setting retrofit and/or repair priorities. Research results show that individual bridges suffer different levels of damage, depending not only on the magnitude of earthquake and distance from the epicenter, but also on the structural characteristics of the bridge and the soil type on which it is built. For the construction of bridge fragility curves for Korea, we used data from 1008 expressway bridges and a statistical regression method. The relationships between peak ground accelerations and vulnerabilities were modeled with logistic curve equations using the bridge classification and models by Hwang, Jernigan and Lin. The primary contribution of this research is that this study is the first of its kind that develops fragility curves for bridges in Korea, which can now be used for various applications that analyze the socio-economic impacts of network vulnerability caused by natural and man-made disasters. Finding a logical and rational basis for transforming the structural disruption ratio of a bridge directly to its functional disruption ratio is left for a future study.

According to the Global Status Report on Road Safety in 2015 from the World Health Organization (WHO), road traffic injuries claim more than 1.25 million lives each year, and they are the leading cause of death among young people aged between 15 and 29 years old. Road traffic fatalities in the Kingdom of Saudi Arabia (KSA) account for 4.7% of all mortalities and have plateaued over the last decade at 22–25 per 100,000 people. According to the Ministry of Interior (MOI) and Police department, 460,488 traffic accidents occurring on the roads in the KSA leading to 7489 deaths and 33,139 injuries, have recorded during 2017 (1438 H) The improvement of drivers’ behavior through education, training, appropriate driver licensing and enforcement is recognized as a kernel in enhancing traffic and transport safety in the National Transportation Strategy. Moreover, it is accepted as an urgent issue to implement and strengthen institutional frameworks and capacities as well as targeted activities in the area of enforcement, engineering, education and emergency response on the national level. However, it is difficult to find any well-organized school traffic safety education material in KSA. For this reason, the objective of this paper was to propose a new traffic safety education material for children (under 13 years old) in KSA. Firstly, traffic safety regulations, policies and traffic safety education programs were reviewed and examined in the school of the United States, the United Kingdom, Germany, Korea, Japan, and Sweden. Then the topics of the new traffic safety education material needed for children who will be the protagonists in KSA were chosen. In this new traffic safety education material, the utilization of various visual aids has been emphasized on for children’s better understanding such as cartoons, graphics, and pictures in the Arabic Language. Finally, questionnaire surveys were conducted to verify the effectiveness of the new material. It is expected that this research became an ignition in the KSA to respond to the global trend of intensive attention to traffic safety. The new material is expected to be actively used mainly in schools and at homes to correct the misbehaviors of road users, to decrease the mortality and morbidity from road traffic accidents, and ultimately to cut off both direct and indirect social costs caused by road traffic accidents in the KSA.

The efficiency of grid-connected photovoltaic (PV) systems can be improved using a suitable maximum power point tracking (MPPT) control. Many MPPT techniques have been developed. However, when atmospheric conditions change rapidly, the PV modules respond nonlinearly and the performance of these methods especially the conventional ones is significantly reduced. Therefore, to successfully pursue the maximum power point (MPP) in PV systems, a robust MPPT integrated with sliding mode control (SMC) is employed. This paper proposes a circle search algorithm based super twisting SMC (CSA-STSMC) for tracking the MPP for 100-kW of different commercial grid-connected PV modules coupled with an energy storage system that used to smooth their output fluctuations. Moreover, the STSMC and PI controllers’ gains are optimized using the CSA and Grey Wolf Optimizer (GWO) methods and the performance of proposed method is demonstrated through comparisons with CSA based Proportional-Integral controller (CSA-PI), GWO-STSMC, and Incremental Conductance based PI controller (InC-PI) methods. The optimization and simulation analysis are executed in A MATLAB/Simulink environment. It is observed that the proposed method outperforms the considered methods in terms of robustness, tracking speed, best convergence to the minimum error’s value and better tracking efficiency in the maximizing the extracted power from the introduced PV systems.

Epoxy-based vitrimers represent a paradigm shift in material science, offering an unprecedented combination of mechanical robustness, environmental sustainability, and reconfigurability. These dynamic polymer systems utilize associative dynamic covalent bonds (DCBs) such as transesterification to blend the structural integrity of thermosets with the recyclability and self-healing properties of thermoplastics. This unique combination makes vitrimers ideal candidates for high-performance applications in industries such as civil engineering, where material durability, repairability, and environmental compatibility are critical. Epoxy-based vitrimers, in particular, exhibit exceptional self-healing capabilities, allowing them to autonomously repair microcracks and damage, restoring mechanical properties under appropriate stimuli such as heat or light. Their recyclability further aligns with global sustainability goals by reducing material waste and lifecycle costs. Recent advancements have also integrated bio-based feedstocks and scalable manufacturing methods, enhancing the feasibility of these materials for industrial applications. This review explores the underlying self-healing mechanisms, dynamic recycling processes, and the emerging role of epoxy-based vitrimers in civil engineering. Challenges related to scalability, mechanical optimization, and regulatory acceptance are also discussed, with a focus on their potential to drive sustainable innovation in infrastructure materials.