Search results for " observation"
showing 10 items of 441 documents
Evaluating the citywide Edinburgh 20mph speed limit intervention effects on traffic speed and volume: A pre-post observational evaluation.
2021
Objectives Traffic speed is important to public health as it is a major contributory factor to collision risk and casualty severity. 20mph (32km/h) speed limit interventions are an increasingly common approach to address this transport and health challenge, but a more developed evidence base is needed to understand their effects. This study describes the changes in traffic speed and traffic volume in the City of Edinburgh, pre- and 12 months post-implementation of phased city-wide 20mph speed limits from 2016–2018. Methods The City of Edinburgh Council collected speed and volume data across one full week (24 hours a day) pre- and post-20mph speed limits for 66 streets. The pre- and post-sp…
Effects of Age and Playing Tactics on the Individual Tactical Behavior in U10 and U12 Elite Spanish Soccer Players
2022
The aim of this paper was to explore the effects of age and playing tactics on the individual tactical behavior and performance in young soccer players. A total of 1247 individual possessions during 16 knockout matches from LaLiga Promises U12 tournament (n = 621) and LaLiga U10 Iscar Cup (n = 626) were analyzed by observational methodology. Multilevel and multivariate logistic regression models were created to explain the interdependent effects of age category and playing tactics on the individual tactical behavior and performance. Youth players performed most of their actions against defensive pressure (72.5%), during offensive support (91.3%) and receiving the ball facing forward (62.6%)…
Learning main drivers of crop progress and failure in Europe with interpretable machine learning
2021
Abstract A wide variety of methods exist nowadays to address the important problem of estimating crop yields from available remote sensing and climate data. Among the different approaches, machine learning (ML) techniques are being increasingly adopted, since they allow exploiting all the information on crop progress and environmental conditions and their relations with crop yield, achieving reliable and accurate estimations. However, interpreting the relationships learned by the ML models, and hence getting insights about the problem, remains a complex and usually unexplored task. Without accountability, confidence and trust in the ML models can be compromised. Here, we develop interpretab…
Ecological Sampling Methods for Studying Everyday Situations
2017
This chapter reviews existing and emerging methodologies for the ambulatory assessment of real-world situations. It distinguishes between first-person/subjective and third-person/objective approaches and provides research examples for each reviewed ecological assessment method. The chapter opens with a discussion of why it is important to assess situations directly in daily life. The following two main sections review approaches for (a) the first-person assessment of real-world situation experiences and perceptions, such as experience sampling and daily diary approaches, and (b) the third-person assessment of objective real-world situation cues, such as naturalistic observation and mobile s…
Splitting of surface-related phonons in Raman spectra of self-assembled GaN nanowires
2012
cited By 2; International audience; Micro Raman spectroscopy studies have been performed on GaN nanowires grown by Plasma-Assisted Molecular Beam Epitaxy on Silicon (111) substrate. From the analysis of experimental data, the emergence of a two peaks band located near 700 cm-1 has been attributed to the Raman scattering by surface-related phonons. We have analyzed the surface character of these two modes by changing the dielectric constant of the exterior medium and some experimental parameters. Furthermore, a theoretical model describing the nanowires ensemble by means of an effective dielectric function has been used to interpret the Raman scattering results. Those numerical simulations a…
Cómo se calma al primo en la ESO : la externalización a PCPI y la subjetivación de la selección escolar
2020
This paper deals with the process of externalization of pupils from compulsory lower secondary education to external programs (PCPI). It describes the negotiations, interactions and strategies deployed in the process, as well as the actors involved and the subjective effects it has on the students. The paper is based on ethnographic fieldwork conducted in a state secondary school in Madrid, and draws on document analysis, participant observation and interviews with students and the school personnel. The proposal of referral to basic vocational training programs external to compulsory education constitutes a status degradation for the students, which are defined as unable to complete compuls…
Flood Detection On Low Cost Orbital Hardware
2019
Satellite imaging is a critical technology for monitoring and responding to natural disasters such as flooding. Despite the capabilities of modern satellites, there is still much to be desired from the perspective of first response organisations like UNICEF. Two main challenges are rapid access to data, and the ability to automatically identify flooded regions in images. We describe a prototypical flood segmentation system, identifying cloud, water and land, that could be deployed on a constellation of small satellites, performing processing on board to reduce downlink bandwidth by 2 orders of magnitude. We target PhiSat-1, part of the FSSCAT mission, which is planned to be launched by the …
Integrating Domain Knowledge in Data-Driven Earth Observation With Process Convolutions
2022
The modelling of Earth observation data is a challenging problem, typically approached by either purely mechanistic or purely data-driven methods. Mechanistic models encode the domain knowledge and physical rules governing the system. Such models, however, need the correct specification of all interactions between variables in the problem and the appropriate parameterization is a challenge in itself. On the other hand, machine learning approaches are flexible data-driven tools, able to approximate arbitrarily complex functions, but lack interpretability and struggle when data is scarce or in extrapolation regimes. In this paper, we argue that hybrid learning schemes that combine both approa…
A perspective on Gaussian processes for Earth observation
2019
Earth observation (EO) by airborne and satellite remote sensing and in-situ observations play a fundamental role in monitoring our planet. In the last decade, machine learning and Gaussian processes (GPs) in particular has attained outstanding results in the estimation of bio-geo-physical variables from the acquired images at local and global scales in a time-resolved manner. GPs provide not only accurate estimates but also principled uncertainty estimates for the predictions, can easily accommodate multimodal data coming from different sensors and from multitemporal acquisitions, allow the introduction of physical knowledge, and a formal treatment of uncertainty quantification and error pr…
Learning Structures in Earth Observation Data with Gaussian Processes
2020
Gaussian Processes (GPs) has experienced tremendous success in geoscience in general and for bio-geophysical parameter retrieval in the last years. GPs constitute a solid Bayesian framework to formulate many function approximation problems consistently. This paper reviews the main theoretical GP developments in the field. We review new algorithms that respect the signal and noise characteristics, that provide feature rankings automatically, and that allow applicability of associated uncertainty intervals to transport GP models in space and time. All these developments are illustrated in the field of geoscience and remote sensing at a local and global scales through a set of illustrative exa…