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Other Forestry and Forest Sciences Commons™
Open Access. Powered by Scholars. Published by Universities.®
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- Aerobiological index (1)
- Cancer driver mutations (1)
- Convolutional neural networks (1)
- Deep learning (1)
- Drug discovery (1)
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- Ensemble-based machine learning features (1)
- Environmental health -- South Africa (1)
- Forests and forestry -- Health aspects (1)
- Healthy urban itineraries (1)
- Kriging (1)
- LiDAR (1)
- Machine learning classifiers (1)
- Plane trees and allergies (1)
- Random forest (1)
- University of Cape Town. National Income Dynamics Study (1)
- Urban forestry -- Effect on mental health (1)
- Urban planning (1)
Articles 1 - 3 of 3
Full-Text Articles in Other Forestry and Forest Sciences
Forests And Mental Health In South Africa: Panel Data Evidence, Dambala Gelo
Forests And Mental Health In South Africa: Panel Data Evidence, Dambala Gelo
Forest Collaborative Research
Slides from a presentation that examines the linkages between the green environment (urban forests, green open urban space) and mental health in South Africa. The author used representative panel data from the National Income Dynamics Survey, including the Center for Epidemiological Studies Short Depression Scale, to uncover these links.
Integration Of Random Forest Classifiers And Deep Convolutional Neural Networks For Classification And Biomolecular Modeling Of Cancer Driver Mutations, Steve Agajanian, Odeyemi Oluyemi, Gennady M. Verkhivker
Integration Of Random Forest Classifiers And Deep Convolutional Neural Networks For Classification And Biomolecular Modeling Of Cancer Driver Mutations, Steve Agajanian, Odeyemi Oluyemi, Gennady M. Verkhivker
Mathematics, Physics, and Computer Science Faculty Articles and Research
Development of machine learning solutions for prediction of functional and clinical significance of cancer driver genes and mutations are paramount in modern biomedical research and have gained a significant momentum in a recent decade. In this work, we integrate different machine learning approaches, including tree based methods, random forest and gradient boosted tree (GBT) classifiers along with deep convolutional neural networks (CNN) for prediction of cancer driver mutations in the genomic datasets. The feasibility of CNN in using raw nucleotide sequences for classification of cancer driver mutations was initially explored by employing label encoding, one hot encoding, and embedding to …
Urban Aerobiological Risk Mapping Of Ornamental Trees Using A New Index Based On Lidar And Kriging: A Case Study Of Plane Trees, Raúl Pecero-Casimiro, Santiago Fernández-Rodríguez, Rafael Tormo-Molina, Alejandro Monroy-Colín, Inmaculada Silva-Palacios, Juan Pedro Cortés-Pérez, Ángela Gonzalo-Garijo, J. M. Maya-Manzano
Urban Aerobiological Risk Mapping Of Ornamental Trees Using A New Index Based On Lidar And Kriging: A Case Study Of Plane Trees, Raúl Pecero-Casimiro, Santiago Fernández-Rodríguez, Rafael Tormo-Molina, Alejandro Monroy-Colín, Inmaculada Silva-Palacios, Juan Pedro Cortés-Pérez, Ángela Gonzalo-Garijo, J. M. Maya-Manzano
Articles
Ornamental trees bring benefits for human health, including reducing urban pollution. However, some species, such as plane trees (Platanus sp.), produce allergenic pollen. Consequently, urban maps are a valuable tool for allergic patients and allergists, but they often fail to include variables that contribute to the “building downwash effect”, such as the width and shape of streets and the height of buildings. Other factors that directly influence pollen dispersion (slopes and other geographical features) also have not traditionally been discussed. The LiDAR (Laser Imaging Detection and Ranging) technique enables one to consider these variables with high accuracy. This work proposes …