Search results for "pattern"
showing 10 items of 4203 documents
OMICfpp: a fuzzy approach for paired RNA-Seq counts
2019
© The Author(s) 2019.
Wind effects on the migration routes of trans-Saharan soaring raptors: geographical, seasonal, and interspecific variation
2016
Wind is among the most important environmental factors shaping birds’ migration patterns. Birds must deal with the displacement caused by crosswinds and their behavior can vary according to different factors such as flight mode, migratory season, experience, and distance to goal areas. Here we analyze the relationship between wind and migratory movements of three raptor species which migrate by soaring–gliding flight: Egyptian vulture Neophron percnopterus, booted eagle Aquila pennata, and short-toed snake eagle Circaetus gallicus. We analyzed daily migratory segments (i.e., the path joining consecutive roosting locations) using data recorded by GPS satellite telemetry. Daily movements of E…
Why aren't warning signals everywhere? : On the prevalence of aposematism and mimicry in communities
2021
Warning signals are a striking example of natural selection present in almost every ecological community - from Nordic meadows to tropical rainforests, defended prey species and their mimics ward off potential predators before they attack. Yet despite the wide distribution of warning signals, they are relatively scarce as a proportion of the total prey available, and more so in some biomes than others. Classically, warning signals are thought to be governed by positive density-dependent selection, i.e. they succeed better when they are more common. Therefore, after surmounting this initial barrier to their evolution, it is puzzling that they remain uncommon on the scale of the community. He…
A segmentation algorithm for noisy images
2005
International audience; This paper presents a segmentation algorithm for gray-level images and addresses issues related to its performance on noisy images. It formulates an image segmentation problem as a partition of a weighted image neighborhood hypergraph. To overcome the computational difficulty of directly solving this problem, a multilevel hypergraph partitioning has been used. To evaluate the algorithm, we have studied how noise affects the performance of the algorithm. The alpha-stable noise is considered and its effects on the algorithm are studied. Key words : graph, hypergraph, neighborhood hypergraph, multilevel hypergraph partitioning, image segmentation and noise removal.
Hybrid Deep Shallow Network for Assessment of Depression Using Electroencephalogram Signals
2020
Depression is a mental health disorder characterised by persistently depressed mood or loss of interest in activities resulting impairment in daily life significantly. Electroencephalography (EEG) can assist with the accurate diagnosis of depression. In this paper, we present two different hybrid deep learning models for classification and assessment of patient suffering with depression. We have combined convolutional neural network with Gated recurrent units (RGUs), thus the proposed network is shallow and much smaller in size in comparison to its counter LSTM network. In addition to this, proposed approach is less sensitive to parameter settings. Extensive experiments on EEG dataset shows…
Flow measurement using circular portable flume
2018
Abstract The circular portable flume is a simple device to measure discharge in circular drainage networks. Since the unit can be easily installed and removed, it is helpful in water distribution measurement and management. First in this paper the available studies are reviewed for highlighting the effect of both the contraction ratio and the flume slope on the stage-discharge relationship. Then the Buckingham's Theorem of the dimensional analysis and the self-similarity theory are used to deduce the stage-discharge curve of the circular flume. The new theoretical stage-discharge equation is calibrated by the literature available experimental data and those obtained in this experimental inv…
Analytical approach extending the Granier method to radial sap flow patterns
2020
Abstract The Granier thermal dissipation (TD) method is probably the most applied method to compute the transpiration flux of trees, due to its simplicity and effective compromise between theory and data availability. Starting from the heat transfer equations at the basis of Granier’s method, the objective of this paper is to derive an analytical solution for the transpiration flux to extend the sap flow equations to the radial domain. We adopted a flexible approach to cope with the differences in radial sapflow density (SFD) profile shapes that are known to occur in relation to wood anatomy (diffuse porous vs. ring- or non-porous xylem). With this purpose, we investigated the robustness of…
LMI-based 2D-3D Registration: from Uncalibrated Images to Euclidean Scene
2015
International audience; This paper investigates the problem of registering a scanned scene, represented by 3D Euclidean point coordinates , and two or more uncalibrated cameras. An unknown subset of the scanned points have their image projections detected and matched across images. The proposed approach assumes the cameras only known in some arbitrary projective frame and no calibration or autocalibration is required. The devised solution is based on a Linear Matrix Inequality (LMI) framework that allows simultaneously estimating the projective transformation relating the cameras to the scene and establishing 2D-3D correspondences without triangulating image points. The proposed LMI framewo…
Ant Colony Optimisation-Based Classification Using Two-Dimensional Polygons
2016
The application of Ant Colony Optimization to the field of classification has mostly been limited to hybrid approaches which attempt at boosting the performance of existing classifiers (such as Decision Trees and Support Vector Machines (SVM)) — often through guided feature reductions or parameter optimizations.
Accelerated bearing life-Time test rig development for low speed data acquisition
2017
Condition monitoring plays an important role in rotating machinery to ensure reliability of the equipment, and to detect fault conditions at an early stage. Although health monitoring methodologies have been thoroughly developed for rotating machinery, low-speed conditions often pose a challenge due to the low signal-to-noise ratio. To this aim, sophisticated algorithms that reduce noise and highlight the bearing faults are necessary to accurately diagnose machines undergoing this condition. In the development phase, sensor data from a healthy and damaged bearing rotating at low-speed is required to verify the performance of such algorithms. A test rig for performing accelerated life-time t…