Predicting Fine Spatial Scale Traffic Noise Using Mobile Measurements and Machine Learning

2020 ◽  
Vol 54 (20) ◽  
pp. 12860-12869
Author(s):  
Xiaozhe Yin ◽  
Masoud Fallah-Shorshani ◽  
Rob McConnell ◽  
Scott Fruin ◽  
Meredith Franklin
Keyword(s):  
Machine Learning ◽  
Spatial Scale ◽  
Traffic Noise ◽  
Fine Spatial Scale ◽  
Mobile Measurements

scholarly journals Application of Machine Learning to Include Honking Effect in Vehicular Traffic Noise Prediction

2021 ◽  
Vol 11 (13) ◽  
pp. 6030
Author(s):  
Daljeet Singh ◽  
Antonella B. Francavilla ◽  
Simona Mancini ◽  
Claudio Guarnaccia
Keyword(s):  
Machine Learning ◽  
Linear Models ◽  
Prediction Models ◽  
Road Traffic ◽  
Traffic Noise ◽  
Machine Learning Techniques ◽  
Coefficient Of Determination ◽  
Road Traffic Noise ◽  
Noise Prediction ◽  
Volume Percentage

A vehicular road traffic noise prediction methodology based on machine learning techniques has been presented. The road traffic parameters that have been considered are traffic volume, percentage of heavy vehicles, honking occurrences and the equivalent continuous sound pressure level. Leq A method to include the honking effect in the traffic noise prediction has been illustrated. The techniques that have been used for the prediction of traffic noise are decision trees, random forests, generalized linear models and artificial neural networks. The results obtained by using these methods have been compared on the basis of mean square error, correlation coefficient, coefficient of determination and accuracy. It has been observed that honking is an important parameter and contributes to the overall traffic noise, especially in congested Indian road traffic conditions. The effects of honking noise on the human health cannot be ignored and it should be included as a parameter in the future traffic noise prediction models.

Co-occurrence of tree species at fine spatial scale in a woodland cerrado, southeastern Brazil

Plant Ecology ◽  
2008 ◽  
Vol 200 (2) ◽  
pp. 277-286 ◽  
Author(s):  
Igor Aurélio Silva ◽  
Marco Antonio Batalha
Keyword(s):  
Spatial Scale ◽  
Tree Species ◽  
Southeastern Brazil ◽  
Fine Spatial Scale

scholarly journals The influence of roads on the fine-scale population genetic structure of the dengue vector Aedes aegypti (Linnaeus)

2021 ◽  
Vol 15 (2) ◽  
pp. e0009139
Author(s):  
Maria Angenica F. Regilme ◽  
Thaddeus M. Carvajal ◽  
Ann–Christin Honnen ◽  
Divina M. Amalin ◽  
Kozo Watanabe
Keyword(s):  
Gene Flow ◽  
Genetic Structure ◽  
Aedes Aegypti ◽  
Spatial Scale ◽  
Population Genetic Structure ◽  
Population Genetic ◽  
Mosquito Control ◽  
Genetic Admixture ◽  
Fine Spatial Scale ◽  
The Road

Dengue is endemic in tropical and subtropical countries and is transmitted mainly by Aedes aegypti. Mosquito movement can be affected by human-made structures such as roads that can act as a barrier. Roads can influence the population genetic structure of Ae. aegypti. We investigated the genetic structure and gene flow of Ae. aegypti as influenced by a primary road, España Boulevard (EB) with 2000-meter-long stretch and 24-meters-wide in a very fine spatial scale. We hypothesized that Ae. aegypti populations separated by EB will be different due to the limited gene flow as caused by the barrier effect of the road. A total of 359 adults and 17 larvae Ae. aegypti were collected from June to September 2017 in 13 sites across EB. North (N1-N8) and South (S1-S5) comprised of 211 and 165 individuals, respectively. All mosquitoes were genotyped at 11 microsatellite loci. AMOVA FST indicated significant genetic differentiation across the road. The constructed UPGMA dendrogram found 3 genetic groups revealing the clear separation between North and South sites across the road. On the other hand, Bayesian cluster analysis showed four genetic clusters (K = 4) wherein each individual samples have no distinct genetic cluster thus genetic admixture. Our results suggest that human-made landscape features such as primary roads are potential barriers to mosquito movement thereby limiting its gene flow across the road. This information is valuable in designing an effective mosquito control program in a very fine spatial scale.

Different Spatial Scales for Different Face Categorisations

Perception ◽  
1997 ◽  
Vol 26 (1_suppl) ◽  
pp. 295-295
Author(s):  
A Oliva ◽  
P G Schyns
Keyword(s):  
Spatial Scale ◽  
Spatial Scales ◽  
Visual Input ◽  
Perceptual Information ◽  
Fine Scale ◽  
Perceptual Cues ◽  
Fine Spatial Scale ◽  
Complex Stimuli ◽  
Face Stimuli ◽  
Opposite Gender

When people categorise complex stimuli such as faces, they might flexibly use the perceptual information available from the visual input. Three experiments were run to test this hypothesis with two different categorisations (gender and expression) of identical face stimuli. Stimuli were hybrids (Schyns and Oliva, 1994 Psychological Science5 195 – 200): they combined either a man or a woman with a particular expression at a coarse spatial scale with a face of the opposite gender with a different expression at the fine spatial scale. In experiment 1 we tested whether a gender vs an expression categorisation task tapped preferentially into a different spatial scale of the hybrids. Results showed that expression was biased to the fine scale, but that gender was not biased. In experiment 2 the same task was replicated, following a learning of the identity of the faces. It was then found that gender also became biased to the fine scale. In experiment 3 the expression task was changed to an identification of each expression to establish whether this could revert the scale biases observed in experiments 1 and 2. Results suggest that different categorisations of identical faces use different perceptual cues. This suggests that the nature of a task changes the representation of a stimulus.

scholarly journals Genetic analysis reveals efficient sexual spore dispersal at a fine spatial scale in Armillaria ostoyae, the causal agent of root-rot disease in conifers

2017 ◽  
Vol 121 (6-7) ◽  
pp. 550-560 ◽  
Author(s):  
Cyril Dutech ◽  
Frédéric Labbé ◽  
Xavier Capdevielle ◽  
Brigitte Lung-Escarmant
Keyword(s):  
Genetic Analysis ◽  
Spatial Scale ◽  
Root Rot ◽  
Causal Agent ◽  
Spore Dispersal ◽  
Fine Spatial Scale ◽  
Root Rot Disease ◽  
Armillaria Ostoyae ◽  
Rot Disease

scholarly journals Complementarity and discriminatory power of genotype and otolith shape in describing the fine-scale population structure of an exploited fish, the common sole of the Eastern English Channel

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0241429
Author(s):  
Marine Randon ◽  
Olivier Le Pape ◽  
Bruno Ernande ◽  
Kélig Mahé ◽  
Filip A. M. Volckaert ◽  
...  
Keyword(s):  
Population Structure ◽  
Spatial Scale ◽  
Discriminatory Power ◽  
Supervised Machine Learning ◽  
English Channel ◽  
Fine Spatial Scale ◽  
Otolith Shape ◽  
Marine Population ◽  
The Common ◽  
Common Sole

Marine organisms show population structure at a relatively fine spatial scale, even in open habitats. The tools commonly used to assess subtle patterns of connectivity have diverse levels of resolution and can complement each other to inform on population structure. We assessed and compared the discriminatory power of genetic markers and otolith shape to reveal the population structure on evolutionary and ecological time scales of the common sole (Solea solea), living in the Eastern English Channel (EEC) stock off France and the UK. First, we genotyped fish with Single Nucleotide Polymorphisms to assess population structure at an evolutionary scale. Then, we tested for spatial segregation of the subunits using otolith shape as an integrative tracer of life history. Finally, a supervised machine learning framework was applied to genotypes and otolith phenotypes to probabilistically assign adults to subunits and assess the discriminatory power of each approach. Low but significant genetic differentiation was found among subunits. Moreover, otolith shape appeared to vary spatially, suggesting spatial population structure at fine spatial scale. However, results of the supervised discriminant analyses failed to discriminate among subunits, especially for otolith shape. We suggest that the degree of population segregation may not be strong enough to allow for robust fish assignments. Finally, this study revealed a weak yet existing metapopulation structure of common sole at the fine spatial scale of the EEC based on genotypes and otolith shape, with one subunit being more isolated. Our study argues for the use of complementary tracers to investigate marine population structure.

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