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The major problem in Thailand related to parking is time violation. Vehicles are not allowed to park for more than a specified amount of time. Implementation of closed-circuit television (CCTV) surveillance cameras along with human labor is the present remedy. However, this paper presents an approach that can introduce a low-cost time violation tracking system using CCTV, Deep Learning models, and object tracking algorithms. This approach is fairly new because of its appliance of the SOTA detection technique, object tracking approach, and time boundary implementations. YOLOv8, along with the DeepSORT/OC-SORT algorithm, is utilized for the detection and tracking that allows us to set a timer and track the time violation. Using the same apparatus along with Deep Learning models and algorithms has produced a better system with better performance. The performance of both tracking algorithms was well depicted in the results, obtaining MOTA scores of (1.0, 1.0, 0.96, 0.90) and (1, 0.76, 0.90, 0.83) in four different surveillance data for DeepSORT and OC-SORT, respectively. [ABSTRACT FROM AUTHOR]

Introduce a new dynamic classifying algorithm in this paper to recognize and monitor fish activity to simultaneously better comprehend their synapomorphies. The pre-trained Mask Regional Convolutional Neural Network (Mask-R-CNN) is trained using a set of test models extracted from recorded video recording. The approach suggested subsequently yields well-enhanced feature vectors. The system's automatic fish detection and tracking capabilities are improved, enhancing underwater investigation for supervising ecological biodiversity. The publicly accessible field-truth dataset assesses recall, F1-score, and classification and tracking precision. Utilizing current tracking R-CNN algorithms like Lowest Output Sum of Siamese Mask (SiamMask), Sequential Non-Maximum Suppression (Seq-NMS), and Squared Errors (MOSSE), comparative performance testing is conducted. In comparison to Siam-Mask (84%), Seq-NMS (78%) and MOSSE (75%), more than 120 of 170 specific bream were detected using the pre-trained Mask-R-CNN of the proposed algorithm (87%). This pre-trained Mask R-CNN system was used in the evaluation, and it was discovered that detection and tracking accuracy had increased significantly. This suggests that the ocean ecosystem could benefit from applying the proposed approach for management of ecology. [ABSTRACT FROM AUTHOR]

Diaspora researchers work in one country but have ancestral origins in another, either through moves during a research career (mobile diaspora researchers) or by starting research in the target country (embedded diaspora researchers). Whilst mobile researchers might be tracked through affiliation changes in bibliometric databases, embedded researchers cannot. This article reports an evidence-based discussion of which countries' diaspora researchers can be partially tracked using first or last names, addressing this limitation. A frequency analysis of first and last names of authors of all Scopus journal articles 2001-2021 for 200 countries or regions. There are great variations in the extent to which first or last names are uniquely national, from Monserrat (no unique first names) to Thailand (81% unique last names). Nevertheless, most countries have a subset of first or last names that are relatively unique. For the 50 countries with the most researchers, authors with relatively national names are always more likely to research their name-associated country, suggesting a continued national association. Lists of researchers' first and last name frequencies and proportions are provided for 200 countries/regions. Only one period is tracked (2001-2021) and no attempt was made to validate the ancestral origins of any researcher. Simple name heuristics can be used to identify the international spread of a sample of most countries' diaspora researchers, but some manual checks of individual names are needed to weed out false matches. This can supplement mobile researcher data from bibliometric databases. This is the first attempt to list name associations for the authors of all countries and large regions, and to identify the countries for which diaspora researchers could be tracked by name. [ABSTRACT FROM AUTHOR]