Search results for " Selection"
showing 10 items of 1271 documents
Out in the open : behavior’s effect on predation risk and thermoregulation by aposematic caterpillars
2020
Abstract Warning coloration should be under strong stabilizing selection but often displays considerable intraspecific variation. Opposing selection on color by predators and temperature is one potential explanation for this seeming paradox. Despite the importance of behavior for both predator avoidance and thermoregulation, its role in mediating selection by predators and temperature on warning coloration has received little attention. Wood tiger moth caterpillars, Arctia plantaginis, have aposematic coloration, an orange patch on the black body. The size of the orange patch varies considerably: individuals with larger patches are safer from predators, but having a small patch is beneficia…
Settlement dynamics and recruitment responses of Mediterranean gorgonians larvae to different crustose coralline algae species
2020
International audience; Sessile marine species such as Anthozoans act as ecosystem engineers due to their three-dimensional structure. Gorgonians, in particular, can form dense underwater forests that give shelter to other species increasing local biodiversity. In the last decades, several Mediterranean gorgonian populations have been affected by natural and anthropogenic impacts which drastically reduced their size. However, some species showed unexpected resilience, mainly due to the supply of new individuals. To understand the mechanisms underlying recovery processes, studies on the first life history stages (i.e. larval dispersal, settlement and recruitment) are needed. In tropical cora…
Species interactions, environmental gradients and body size shape population niche width
2021
1. Competition for shared resources is commonly assumed to restrict population-level niche width of coexisting species. However, the identity and abundance of coexisting species, the prevailing environmental conditions, and the individual body size may shape the effects of interspecific interactions on species’ niche width. 2. Here we study the effects of interspecific and intraspecific interactions, lake area and altitude, and fish body size on the trophic niche width and resource use of a generalist predator, the littoral-dwelling large, sparsely rakered morph of European whitefish (Coregonus lavaretus; hereafter LSR whitefish). We use stable isotope, diet and survey fishing data from 14 …
Optimization of photovoltaic solar power plant locations in northern Chile
2017
The optimization of photovoltaic solar power plants location in Atacama Desert, Chile, is presented in this study. The study considers three objectives: (1) Find sites with the highest solar energy potential, (2) determine sites with the least impact on the environment, and (3) locate the areas which produce small social impact. To solve this task, multi-criteria decision analyses (MCDAs) such as analytical hierarchy process and ordered weighted averaging were applied in a GIS environment. In addition, survey results of social impacts were analyzed and included into the decision-making process, including landscape values. The most suitable sites for solar energy projects were found near roa…
Extreme minimal learning machine: Ridge regression with distance-based basis
2019
The extreme learning machine (ELM) and the minimal learning machine (MLM) are nonlinear and scalable machine learning techniques with a randomly generated basis. Both techniques start with a step in which a matrix of weights for the linear combination of the basis is recovered. In the MLM, the feature mapping in this step corresponds to distance calculations between the training data and a set of reference points, whereas in the ELM, a transformation using a radial or sigmoidal activation function is commonly used. Computation of the model output, for prediction or classification purposes, is straightforward with the ELM after the first step. In the original MLM, one needs to solve an addit…
Selective visual odometry for accurate AUV localization
2015
In this paper we present a stereo visual odometry system developed for autonomous underwater vehicle localization tasks. The main idea is to make use of only highly reliable data in the estimation process, employing a robust keypoint tracking approach and an effective keyframe selection strategy, so that camera movements are estimated with high accuracy even for long paths. Furthermore, in order to limit the drift error, camera pose estimation is referred to the last keyframe, selected by analyzing the feature temporal flow. The proposed system was tested on the KITTI evaluation framework and on the New Tsukuba stereo dataset to assess its effectiveness on long tracks and different illumina…
Accurate keyframe selection and keypoint tracking for robust visual odometry
2016
This paper presents a novel stereo visual odometry (VO) framework based on structure from motion, where a robust keypoint tracking and matching is combined with an effective keyframe selection strategy. In order to track and find correct feature correspondences a robust loop chain matching scheme on two consecutive stereo pairs is introduced. Keyframe selection is based on the proportion of features with high temporal disparity. This criterion relies on the observation that the error in the pose estimation propagates from the uncertainty of 3D points—higher for distant points, that have low 2D motion. Comparative results based on three VO datasets show that the proposed solution is remarkab…
VARIABLE SELECTION FOR NOISY DATA APPLIED IN PROTEOMICS
2014
International audience; The paper proposes a variable selection method for pro-teomics. It aims at selecting, among a set of proteins, those (named biomarkers) which enable to discriminate between two groups of individuals (healthy and pathological). To this end, data is available for a cohort of individuals: the biological state and a measurement of concentrations for a list of proteins. The proposed approach is based on a Bayesian hierarchical model for the dependencies between biological and instrumental variables. The optimal selection function minimizes the Bayesian risk, that is to say the selected set of variables maximizes the posterior probability. The two main contributions are: (…
Input Selection Methods for Soft Sensor Design: A Survey
2020
Soft Sensors (SSs) are inferential models used in many industrial fields. They allow for real-time estimation of hard-to-measure variables as a function of available data obtained from online sensors. SSs are generally built using industries historical databases through data-driven approaches. A critical issue in SS design concerns the selection of input variables, among those available in a candidate dataset. In the case of industrial processes, candidate inputs can reach great numbers, making the design computationally demanding and leading to poorly performing models. An input selection procedure is then necessary. Most used input selection approaches for SS design are addressed in this …
Grading investment diversification options in presence of non-historical financial information
2021
Modern portfolio theory deals with the problem of selecting a portfolio of financial assets such that the expected return is maximized for a given level of risk. The forecast of the expected individual assets’ returns and risk is usually based on their historical returns. In this work, we consider a situation in which the investor has non-historical additional information that is used for the forecast of the expected returns. This implies that there is no obvious statistical risk measure any more, and it poses the problem of selecting an adequate set of diversification constraints to mitigate the risk of the selected portfolio without losing the value of the non-statistical information owne…