This research presents an ontology-based approach to infer incomplete mobile vehicle trajectories, enhancing urban traffic analysis by transforming raw spatio-temporal data into semantic locations and leveraging knowledge-driven inference methods. The approach aims to improve the accuracy and interpretability of mobility pattern analysis in smart city applications.
In the context of applying machine learning to solve problems for risk prediction, disease detection, and treatment evaluation, EHR pose many challenges– they do not have a consistent, standardized format across institutions particularly in US, can contain human errors and introduce collection biases. In addition, some institutions or geographic regions do not have access to the technology or financial resources necessary to implement EHR, thus resulting in vulnerable and disadvantaged communities not being electronically visible.
A roadmap for health care leaders to execute intrinsic agency toward equity, supporting SDGs 3 and 10.
Digital health programs are urgently needed to accelerate the adoption of Artificial Intelligence and Clinical Decision Support Systems (AI-CDSS) in clinical settings. However, such programs are still lacking for undergraduate medical students, and new approaches are required to prepare them for the arrival of new and unknown technologies.
The study discusses the fundamental concepts of blockchain technology, including cryptography, hash functions, digital signatures, and Merkle trees. Providing an in-depth presentation of the mechanism for reaching consensus.
This study supports SDG's 9 and 13 through its discussion of the effects of optimizing Municipal Solid Waste management systems by increasing waste collection coverage and implementing diverse streams of waste valorization, causing a decrease of atmospheric pollution.
Studies on the distribution of microplastics in aquatic environments are summarized and environmental and anthropogenic factors affecting microplastic toxicity are reviewed
This paper sought to explore similarities, variations and determinants of sustainable plastics consumption behavior within a sample of approximately 7600 respondents from eight European countries. We find that most consumers engage in sustainable plastics behavior during the usage phase, by reusing plastic containers and refilling water bottles. The regression analysis suggests that personal responsibility, having high values for nature, being a member of a nature organization and feeling knowledgeable about plastic pollution are important predictors of sustainable plastics consumption.
Celebrated annually on 8 March, International Women's Day is a global day to recognize the social, economic, cultural, and political achievements of women. The theme for this International Women’s
Elsevier,
Measurement: Journal of the International Measurement Confederation, Volume 209, 15 March 2023
The research aims to assess the environmental sustainability of measurements, and the investigation is conducted through two case studies within the information and communication technology sector. The authors put forward recommendations for increasing a measurement's environmental sustainability.
