Identification, 3D-Reconstruction, and Classification of Dangerous Road Cracks.

Advances in semiconductor technology and wireless sensor networks have permitted the development of automated inspection at diverse scales (machine, human, infrastructure, environment, etc.). However, automated identification of road cracks is still in its early stages. This is largely owing to the difficulty obtaining pavement photographs and the tiny size of flaws (cracks). The existence of pavement cracks and potholes reduces the value of the infrastructure, thus the severity of the fracture must be estimated. Annually, operators in many nations must audit thousands of kilometers of road to locate this degradation. This procedure is costly, sluggish, and produces fairly subjective results. The goal of this work is to create an efficient automated system for crack identification, extraction, and 3D reconstruction. The creation of crack-free roads is critical to preventing traffic deaths and saving lives. The proposed method consists of five major stages: detection of flaws after processing the input picture with the Gaussian filter, contrast adjustment, and ultimately, threshold-based segmentation. We created a database of road cracks to assess the efficacy of our proposed method. The result obtained are commendable and outperform previous state-of-the-art studies.

Development of an intelligent system based on metaverse learning for students with disabilities.

Due to the coronavirus-2019 pandemic, people have had to work and study using the Internet such that the strengthened metaverse has become a part of the lives of people worldwide. The advent of technology linking the real and virtual worlds has facilitated the transmission of spatial audio and haptics to allow the metaverse to offer multisensory experiences in diverse fields, especially in teaching. The main idea of the proposed project is the development of a simple intelligent system for meta-learning. The suggested system should be self-configurable according to the different users of the metaverse. We aimed to design and create a virtual learning environment using Open Simulator based on a 3D virtual environment and simulation of the real-world environment. We then connected this environment to a learning management system (Moodle) through technology for 3D virtual environments (Sloodle) to allow the management of students, especially those with different abilities, and followed up on their activities, tests, and exams. This environment also has the advantage of storing educational content. We evaluated the performance of the Open Simulator in both standalone and grid modes based on the login times. The result showed times the standalone and grid modes of 12 s and 16 s, which demonstrated the robustness of the proposed platform. We also tested the system on 50 disabled learners, according to the t-test of independent samples. A test was conducted in the mathematics course, in which the students were divided into two equal groups (n = 25 each) to take the test traditionally and using the chair test tool, which is one of the most important tools of the Sloodle technology. According to the results, the null hypothesis was rejected, and we accepted the alternative hypothesis that demonstrated a difference in achievement between the two groups.

Implication of organic acids in the long-distance transport and the accumulation of lead in Sesuvium portulacastrum and Brassica juncea.

The implication of organic acids in Pb translocation was studied in two species varying in shoot lead accumulation, Sesuvium portulacastrum and Brassica juncea. Citric, fumaric, malic and α-cetoglutaric acids were separated and determined by HPLC technique in shoots, roots and xylem saps of the both species grown in nutrient solutions added with 200 and 400 µM of Pb(II). The lead content of the xylem saps was determined by ICP-MS. Results showed that S. portulacastrum is more tolerant to Pb than B. juncea. Lead concentration in xylem sap of the S. portulacastrum was significantly greater than in that of B. juncea. For both species, a positive correlation was established between lead and citrate concentrations in xylem sap. However minor relationship was observed for fumaric, malic and α-cetoglutaric acids. In the shoots lead treatment also induced a significant increase in citric acid concentration. Both observations suggest the implication of citric acid in lead translocation and shoot accumulation in S. portulacastrum and B. juncea. The relatively high accumulation of citric acid in xylem sap and shoot of S. portulacastrum could explain its high potential to translocate and accumulate this metal in shoot suggesting their possible use to remediate Pb polluted soils.