Search results for "Bust"
showing 10 items of 1000 documents
TAKEOFF AND LANDING ROBUST CONTROL SYSTEM FOR A TANDEM CANARD UAV
2005
In spite of modern wide improvements in UAV’s technologies, a few number of such a vehicles is fully autonomous from takeoff to landing . So, either autonomous operation or operation with minimal human intervention is, actually, the primary design goal for the UAV’s researchers. The core of the problem is the design of the landing and takeoff control system. The objective of this paper is to design a control system in which the same state variables are controlled during both the descending/ascending path and the flare, tacking into account the actual ground effect. Robust control techniques are employed with the aim to cope with atmospheric turbulence, measurement noise, parameter variation…
How Universal Is the Relationship between Remotely Sensed Vegetation Indices and Crop Leaf Area Index? A Global Assessment
2016
This study aims to assess the relationship between Leaf Area Index (LAI) and remotely sensed Vegetation Indices (VIs) for major crops, based on a globally explicit dataset of in situ LAI measurements over a significant set of locations. We used a total of 1394 LAI measurements from 29 sites spanning 4 continents and covering 15 crop types with corresponding Landsat satellite images. Best-fit functions for the LAI-VI relationships were generated and assessed in terms of crop type, vegetation index, level of radiometric/atmospheric processing, method of LAI measurement, as well as the time difference between LAI measurements and satellite overpass. These global LAI-VI relationships were evalu…
Spectroscopic Detection and Structure of Hydroxidooxidosulfur (HOSO) Radical, An Important Intermediate in the Chemistry of Sulfur-Bearing Compounds
2013
The rotational spectrum of hydroxidooxidosulfur, HOSO, an intermediate of particular interest in the combustion of sulfur-rich fuels, has been determined to high accuracy from gas-phase measurements. Detection of specific isotopic species using isotopically enriched gases suggests that HOSO is formed in our discharge nozzle via the reaction H + SO2 (+M) → HOSO (+M). A precise experimental r0 geometry has also been derived from the isotopic analysis; HOSO has a cis configuration, but the subtle structural question of its planarity remains unresolved. From the derived spectroscopic constants, in situ and remote sensing for this fundamental radical can now be undertaken in a variety of environ…
Chaotic dynamics and partial hyperbolicity
2017
The dynamics of hyperbolic systems is considered well understood from topological point of view as well as from stochastic point of view. S. Smale and R. Abraham gave an example showing that, in general, the hyperbolic systems are not dense among all differentiable systems. In 1970s, M. Brin and Y. Pesin proposed a new notion: partial hyperbolicity to release the notion of hyperbolicity. One aim of this thesis is to understand the dynamics of certain partially hyperbolic systems from stochastic point of view as well as from topological point of view. From stochastic point of view, we prove the following results: — There exists an open and dense subset U of robustly transitive nonhyperbolic …
Atom, atom-type and total molecular linear indices as a promising approach for bioorganic and medicinal chemistry: theoretical and experimental asses…
2004
Abstract Helminth infections are a medical problem in the world nowadays. In this paper a novel atom-level chemical descriptor has been applied to estimate the anthelmintic activity. Total and local linear indices and linear discriminant analysis were used to obtain a quantitative model that discriminates between anthelmintic and non-anthelmintic drug-like compounds. The discriminant model has an accuracy of 90.11% in the training set, with a high Matthews’ correlation coefficient (MCC = 0.80). To assess the robustness and predictive power of the obtained model, internal (leave-n-out) and external validation process was performed. The QSAR model correctly classified 88.55% of compounds in t…
Using machine learning to disentangle LHC signatures of Dark Matter candidates
2019
We study the prospects of characterising Dark Matter at colliders using Machine Learning (ML) techniques. We focus on the monojet and missing transverse energy (MET) channel and propose a set of benchmark models for the study: a typical WIMP Dark Matter candidate in the form of a SUSY neutralino, a pseudo-Goldstone impostor in the shape of an Axion-Like Particle, and a light Dark Matter impostor whose interactions are mediated by a heavy particle. All these benchmarks are tensioned against each other, and against the main SM background ($Z$+jets). Our analysis uses both the leading-order kinematic features as well as the information of an additional hard jet. We explore different representa…
<title>Real-time face tracking and recognition for video conferencing</title>
2001
This paper describes a system of vision in real time, allowing to detect automatically the faces presence, to localize and to follow them in video sequences. We verify also the faces identities. These processes are based by combining technique of image processing and methods of neural networks. The tracking is realized with a strategy of prediction-verification using the dynamic information of the detection. The system has been evaluated quantitatively on 8 video sequences. The robustness of the method has been tested on various lightings images. We present also the analysis of complexity of this algorithm in order to realize an implementation in real time on a FPGA based architecture.
Automatic Identification of Watermarks and Watermarking Robustness Using Machine Learning Techniques
2021
The goal of this article is to propose a framework for automatic identification of watermarks from modified host images. The framework can be used with any watermark embedding/extraction system and is based on models built using machine learning (ML) techniques. Any supervised ML approach can be theoretically chosen. An important part of our framework consists in building a stand-alone module, independent of the watermarking system, for generating two types of watermarks datasets. The first type of datasets, that we will name artificially datasets, is generated from the original images by adding noise with an imposed maximum level of noise. The second type contains altered watermarked image…
Regularized RBF Networks for Hyperspectral Data Classification
2004
In this paper, we analyze several regularized types of Radial Basis Function (RBF) Networks for crop classification using hyperspectral images. We compare the regularized RBF neural network with Support Vector Machines (SVM) using the RBF kernel, and AdaBoost Regularized (ABR) algorithm using RBF bases, in terms of accuracy and robustness. Several scenarios of increasing input space dimensionality are tested for six images containing six crop classes. Also, regularization, sparseness, and knowledge extraction are paid attention.
Atmospheric aging of small-scale wood combustion emissions (model MECHA 1.0) – is it possible to distinguish causal effects from non-causal ass…
2020
Abstract. Primary emissions of wood combustion are complex mixtures of hundreds or even over a thousand compounds, which pass through a series of chemical reactions and physical transformation processes in the atmosphere (aging). This aging process depends on atmospheric conditions, such as concentration of atmospheric oxidizing agents (OH radical, ozone and nitrate radicals), humidity and solar radiation, and is known to strongly affect the characteristics of atmospheric aerosols. However, there are only few models that are able to represent the aging of emissions during its lifetime in the atmosphere. In this work, we implemented a model (Model for aging of Emissions in environmental CHAm…