Intelligent waste sorting for urban sustainability using deep learning. [PDF]
Ahmad G +9 more
europepmc +1 more source
Glenoid Augmentation With Humeral Head Autograft in Reverse Shoulder Arthroplasty: A Retrospective Study of an Innovative Technique. [PDF]
Pennock H +5 more
europepmc +1 more source
Bioconversion of lignin and food waste into vanillin and biohydrogen by Escherichia coli MC3: a novel dual-functional bacteria. [PDF]
Chuancheng D +6 more
europepmc +1 more source
The Use of Industry 4.0 and 5.0 Technologies in the Transformation of Food Services: An Integrative Review. [PDF]
Cantarelli da Silva R +3 more
europepmc +1 more source
The FOod Commodity composition for Waste qUantification and valorization opportunitieS (FOWCUS) Dataset. [PDF]
Coudard A +4 more
europepmc +1 more source
BIM-integrated life cycle assessment of decentralized cement-based waste recycling in renovation projects. [PDF]
Younes A +5 more
europepmc +1 more source
Related searches:
IoT-based waste management: hybrid optimal routing and waste classification model
Environmental Science and Pollution ResearchInternet of Things (IoT) makes connectivity between physical devices which are embedded with sensors, software, and connectivity that let them to communicate and transfer data. This technology makes it possible to collect and transfer data from a vast network device, opening the door to the development of automatic and more efficiency systems. The term
Sunilkumar Ketineni +5 more
openaire +3 more sources
Classification of dimension stone wastes
Environmental Science and Pollution Research, 2012For countries in which the stone industry is well developed, opposition to quarry and plant waste is gradually increasing. The primary step for waste control and environmental management is to define the problem of concern. In this study, natural building stone wastes were classified for the first time in the literature.Following on-site physical ...
Karaca, Zeki +2 more
openaire +5 more sources
Classification of Hazardous Wastes
Journal of the Environmental Engineering Division, 1980The multivariate statistical techniques of linear discriminant analysis and cluster analysis were applied to the classification of hazardous wastes. Linear discriminate analysis was used to classify a sample of waste streams from the metal smelting and refining industries, with a resultant classification accuracy of 83%.
Albert J. Klee, Michael U. Flanders
openaire +1 more source
In recent years, waste segregation, treatment, and recycling have become critical global issues, drawing significant attention worldwide. However, the efficiency of recycling processes can be influenced by numerous factors.
Zhitong Lee, Y. Wu, Xukang Wang
semanticscholar +1 more source

