AI Medical Compendium Journal:
Waste management (New York, N.Y.)

Showing 31 to 40 of 68 articles

Exploring artificial intelligence role in improving service building engagement in sorting.

Waste management (New York, N.Y.)
Waste management researchers have identified that the correct disposal of solid waste is better addressed upstream, where people properly sort their solid waste. Sorting solid waste is a practice that requires a behaviour friendly to sorting and will...

Machine learning modeling of thermally assisted biodrying process for municipal sludge.

Waste management (New York, N.Y.)
Preparation of activated carbons is an important way to utilize municipal sludge (MS) resources, while drying is a pretreatment method for making activated carbons from MS. In this study, machine learning techniques were used to develop moisture rati...

Improved medical waste plasma gasification modelling based on implicit knowledge-guided interpretable machine learning.

Waste management (New York, N.Y.)
Ensuring the interpretability of machine learning models in chemical engineering remains challenging due to inherent limitations and data quality issues, hindering their reliable application. In this study, a qualitatively implicit knowledge-guided m...

Machine learning-aided unveiling the relationship between chemical pretreatment and methane production of lignocellulosic waste.

Waste management (New York, N.Y.)
Chemical pretreatment is a common method to enhance the cumulative methane yield (CMY) of lignocellulosic waste (LW) but its effectiveness is subject to various factors, and accurate estimation of methane production of pretreated LW remains a challen...

Quantification of litter in cities using a smartphone application and citizen science in conjunction with deep learning-based image processing.

Waste management (New York, N.Y.)
Cities are a major source of litter pollution. Determination of the abundance and composition of plastic litter in cities is imperative for effective pollution management, environmental protection, and sustainable urban development. Therefore, here, ...

Higher heating value estimation of wastes and fuels from ultimate and proximate analysis by using artificial neural networks.

Waste management (New York, N.Y.)
Higher heating value (HHV) is one of the most important parameters in determining the quality of the fuels. In this study, comparatively large datasets of ultimate and proximate analysis are constructed to be used in HHV estimation of several classes...

Artificial Intelligence in enhancing sustainable practices for infectious municipal waste classification.

Waste management (New York, N.Y.)
This research paper focuses on effective infectious municipal waste management in urban settings, highlighting a dearth of dedicated research in this domain. Unlike general or specific waste types, infectious waste poses distinct health and environme...

Multi-objective location-routing optimization based on machine learning for green municipal waste management.

Waste management (New York, N.Y.)
Most of the existing municipal waste management (MWM) systems focus on the optimization of the waste disposal center locations and waste collection paths, which can be modeled based on the location-routing problem (LRP). This study models a green MWM...

Machine-learning intervention progress in the field of organic waste composting: Simulation, prediction, optimization, and challenges.

Waste management (New York, N.Y.)
Aerobic composting stands as a widely-adopted method for treating organic solid waste (OSW), simultaneously producing organic fertilizers and soil amendments. This biologically-driven biochemical reaction process, however, presents challenges due to ...

Multi-modal deep learning networks for RGB-D pavement waste detection and recognition.

Waste management (New York, N.Y.)
To create a clean living environment, governments around the world have hired a large number of workers to clean up waste on pavements, which is inefficient for waste management. To better alleviate this problem, relevant scholars have proposed sever...