Search results for "Recognition"
showing 10 items of 3607 documents
Ion-Pairing Effects in the Self-Assembly of a Fluorescent Pseudorotaxane
2006
Herein we report on the self-assembly, in a low polarity solvent, of a pseudorotaxane species comprising binaphthyl-26-crown-8 (BN26C8) as the macrocyclic host and anthracenyl-benzylammonium as the threadlike positively charged guest (ABH+). Absorption and luminescence data reveal a very efficient energy transfer process occurring from the binaphthyl to the anthracene singlet excited states. The self-assembly is highly dependent on the nature of the counteranion confirming the crucial role played by it in the competition between the self-assembly process and the formation of ion pairs (ABH+X-). This behavior can be readily evidenced in dilute solutions from the analysis of the luminescence …
The cryogenic anticoincidence detector for ATHENA-XMS: preliminary results from the new prototype
2012
ATHENA has been the re-scoped IXO mission, and one of the foreseen focal plane instrument was the X-ray Microcalorimeter Spectrometer (XMS) working in the energy range 0.3-10 keV, which was a kilo-pixel array based on TES (Transition Edge Sensor) detectors. The need of an anticoincidence (AC) detector is legitimated by the results performed with GEANT4 simulations about the impact of the non x-ray background onto XMS at L2 orbit (REQ. < 0.02 cts/cm2/s/keV). Our consortium has both developed and tested several samples, with increasing area, in order to match the large area of the XMS (64 mm2). Here we show the preliminary results from the last prototype. The results achieved in this work off…
The importance of pattern similarity between Müllerian mimics in predator avoidance learning
2004
Müllerian mimicry, where unpalatable prey share common warning patterns, has long fascinated evolutionary biologists. It is commonly assumed that Müllerian mimics benefit by sharing the costs of predator education, thus reducing per capita mortality, although there has been no direct test of this assumption. Here, we specifically measure the selection pressure exerted by avian predators on unpalatable prey with different degrees of visual similarity in their warning patterns. Using wild-caught birds foraging on novel patterned prey in the laboratory, we unexpectedly found that pattern similarity did not increase the speed of avoidance learning, and even dissimilar mimics shared the educatio…
Comparison and multiresolution analysis of irregular meshes with appearance attributes
2004
We present in this dissertation a method to compare and to analyse irregular meshes with appearance attributes. First, we propose a mesh comparison method using a new attribute deviation metric. Considered meshes contain geometric and appearance attributes (e.g. color, texture,temperature). The proposed deviation assessment allows the computation of local attribute differences between two meshes. We present an application of this method to mesh simplification algorithm quality assessment.Then we propose two multiresolution analysis schemes for irregular meshes with appearance attributes. First, a mesh is decomposed in a discret number of levels of detail. We introduce a surface geometry rel…
A Hardware and Secure Pseudorandom Generator for Constrained Devices
2018
Hardware security for an Internet of Things or cyber physical system drives the need for ubiquitous cryptography to different sensing infrastructures in these fields. In particular, generating strong cryptographic keys on such resource-constrained device depends on a lightweight and cryptographically secure random number generator. In this research work, we have introduced a new hardware chaos-based pseudorandom number generator, which is mainly based on the deletion of an Hamilton cycle within the $N$ -cube (or on the vectorial negation), plus one single permutation. We have rigorously proven the chaotic behavior and cryptographically secure property of the whole proposal: the mid-term eff…
Localisation visuelle basée sur la reconnaissance du lieu dans les environnements changeants
2017
In many applications, it is crucial that a robot or vehicle localizes itself within the world especially for autonomous navigation and driving. The goal of this thesis is to improve place recognition performance for visual localization in changing environment. The approach is as follows: in off-line phase, geo-referenced images of each location are acquired, features are extracted and saved. While in the on-line phase, the vehicle localizes itself by identifying a previously-visited location through image or sequence retrieving. However, visual localization is challenging due to drastic appearance and illumination changes caused by weather conditions or seasonal changing. This thesis addres…
On spline methods of approximation under L-fuzzy information
2011
This work is closely related to our previous papers on algorithms of approximation under L-fuzzy information. In the classical theory of approximation central algorithms were worked out on the basis of usual, that is crisp splines. We describe central methods for solution of linear problems with balanced L-fuzzy information and develop the concept of L-fuzzy splines.
Reliable polygonal approximations of imaged real objects through dominant point detection
1998
Abstract The problem of dominant point detection is posed, taking into account what usually happens in practice. The algorithms found in the literature often prove their performance with laboratory contours, but the shapes in real images present noise, quantization, and high inter and intra-shape variability. These effects are analyzed and solutions to them are proposed. We will also focus on the conditions for an efficient (few points) and precise (low error) dominant point extraction that preserves the original shape. A measurement of the committed error (optimization error, E 0 ) that takes into account both aspects is defined for studying this feature.
Sequential Mining Classification
2017
Sequential pattern mining is a data mining technique that aims to extract and analyze frequent subsequences from sequences of events or items with time constraint. Sequence data mining was introduced in 1995 with the well-known Apriori algorithm. The algorithm studied the transactions through time, in order to extract frequent patterns from the sequences of products related to a customer. Later, this technique became useful in many applications: DNA researches, medical diagnosis and prevention, telecommunications, etc. GSP, SPAM, SPADE, PrefixSPan and other advanced algorithms followed. View the evolution of data mining techniques based on sequential data, this paper discusses the multiple …
Hop: Histogram of patterns for human action representation
2017
This paper presents a novel method for representing actions in terms of multinomial distributions of frequent sequential patterns of different length. Frequent sequential patterns are series of data descriptors that occur many times in the data. This paper proposes to learn a codebook of frequent sequential patterns by means of an apriori-like algorithm, and to represent an action with a Bag-of-Frequent-Sequential-Patterns approach. Preliminary experiments of the proposed method have been conducted for action classification on skeletal data. The method achieves state-of-the-art accuracy value in cross-subject validation.