AIMC Topic: Cities

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Graph neural network-based surrogate modelling for real-time hydraulic prediction of urban drainage networks.

Water research
Physics-based models are computationally time-consuming and infeasible for real-time scenarios of urban drainage networks, and a surrogate model is needed to accelerate the online predictive modelling. Fully-connected neural networks (NNs) are potent...

Predicting Intimate Partner Violence Perpetration Among Young Adults Experiencing Homelessness in Seven U.S. Cities Using Interpretable Machine Learning.

Journal of interpersonal violence
Young adults experiencing homelessness (YAEH) are at higher risk for intimate partner violence (IPV) victimization than their housed peers. This is often due to their increased vulnerability to abuse and victimization before and during homelessness, ...

Machine learning-based analysis and prediction of meteorological factors and urban heatstroke diseases.

Frontiers in public health
INTRODUCTION: Heatstroke is a serious clinical condition caused by exposure to high temperature and high humidity environment, which leads to a rapid increase of the core temperature of the body to more than 40°C, accompanied by skin burning, conscio...

Segmentation of LiDAR point cloud data in urban areas using adaptive neighborhood selection technique.

PloS one
Semantic segmentation of urban areas using Light Detection and Ranging (LiDAR) point cloud data is challenging due to the complexity, outliers, and heterogeneous nature of the input point cloud data. The machine learning-based methods for segmenting ...

MSW-Net: A hierarchical stacking model for automated municipal solid waste classification.

Journal of the Air & Waste Management Association (1995)
Efficient solid waste management is crucial for urban health and welfare in the midst of fast industrialization and urbanization. In this changing environment, government authorities have a significant role in addressing and reducing the effects of s...

Integrating deep learning and regression models for accurate prediction of groundwater fluoride contamination in old city in Bitlis province, Eastern Anatolia Region, Türkiye.

Environmental science and pollution research international
Groundwater resources in Bitlis province and its surroundings in Türkiye's Eastern Anatolia Region are pivotal for drinking water, yet they face a significant threat from fluoride contamination, compounded by the region's volcanic rock structure. To ...

Designing energy-efficient buildings in urban centers through machine learning and enhanced clean water managements.

Environmental research
Rainwater Harvesting (RWH) is increasingly recognized as a vital sustainable practice in urban environments, aimed at enhancing water conservation and reducing energy consumption. This study introduces an innovative integration of nano-composite mate...

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, ...

Prediction of developmental toxic effects of fine particulate matter (PM) water-soluble components via machine learning through observation of PM from diverse urban areas.

The Science of the total environment
The global health implications of fine particulate matter (PM) underscore the imperative need for research into its toxicity and chemical composition. In this study, zebrafish embryos exposed to the water-soluble components of PM from two cities (Har...

Leveraging data science and machine learning for urban climate adaptation in two major African cities: a HEAT Center study protocol.

BMJ open
INTRODUCTION: African cities, particularly Abidjan and Johannesburg, face challenges of rapid urban growth, informality and strained health services, compounded by increasing temperatures due to climate change. This study aims to understand the compl...