AIMC Topic: Geography

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Scaling Laws in City Growth: Setting Limitations with Self-Organizing Maps.

PloS one
Do scaling relations always provide the means to anticipate the relationships between the size of cities, costs of maintenance, and the socio-economic benefits resulting from their growth? Scaling laws are considered a universal principle that descri...

Predicting and communicating flood risk of transport infrastructure based on watershed characteristics.

Journal of environmental management
This research aims to identify and communicate water-related vulnerabilities in transport infrastructure, specifically flood risk of road/rail-stream intersections, based on watershed characteristics. This was done using flooding in Värmland and Väst...

Artificial Intelligence Procedures for Tree Taper Estimation within a Complex Vegetation Mosaic in Brazil.

PloS one
Tree stem form in native tropical forests is very irregular, posing a challenge to establishing taper equations that can accurately predict the diameter at any height along the stem and subsequently merchantable volume. Artificial intelligence approa...

A Natural Language Interface Concordant with a Knowledge Base.

Computational intelligence and neuroscience
The discordance between expressions interpretable by a natural language interface (NLI) system and those answerable by a knowledge base is a critical problem in the field of NLIs. In order to solve this discordance problem, this paper proposes a meth...

Evidence of Water Quality Degradation in Lower Mekong Basin Revealed by Self-Organizing Map.

PloS one
To reach a better understanding of the spatial variability of water quality in the Lower Mekong Basin (LMB), the Self-Organizing Map (SOM) was used to classify 117 monitoring sites and hotspots of pollution within the basin identified according to wa...

Machine Learning Based Classification of Microsatellite Variation: An Effective Approach for Phylogeographic Characterization of Olive Populations.

PloS one
Finding efficient analytical techniques is overwhelmingly turning into a bottleneck for the effectiveness of large biological data. Machine learning offers a novel and powerful tool to advance classification and modeling solutions in molecular biolog...

Exploring supervised neighborhood preserving embedding (SNPE) as a nonlinear feature extraction method for vibrational spectroscopic discrimination of agricultural samples according to geographical origins.

Talanta
Supervised neighborhood preserving embedding (SNPE), a nonlinear dimensionality reduction method, was employed to represent near-infrared (NIR) and Raman spectral features of agricultural samples (Angelica gigas, sesame, and red pepper), and the newl...

The relationship between left ventricle myocardial performance index of healthy women and geographical factors.

International journal of biometeorology
The study focused on the relationship between geographical factors and left ventricular myocardial performance index (MPI)reference value, analyed the different distribution of MPI, and then provided a scientific basis for clinical examination. This ...

Recent advances of machine learning in the geographical origin traceability of food and agro-products: A review.

Comprehensive reviews in food science and food safety
The geographical origin traceability of food and agro-products has been attracted worldwide. Especially with the rise of machine learning (ML) technology, it provides cutting-edge solutions to erstwhile intractable issues to identify the origin of fo...

Robotics at the Service of Wheelchair Mobility for People with Disabilities: Story of a Clinical-Scientific Partnership.

Studies in health technology and informatics
The mobility of people with motor disabilities combined with sensory or cognitive disabilities, sometimes leads to safety issues that make independent travel impossible. In this context, teams based in Rennes in the west of France have been working t...