Search results for "RECOGNITION"
showing 10 items of 3607 documents
A Viscoelastic Model for the Long-Term Deflection of Segmental Prestressed Box Girders
2017
Most of segmental prestressed concrete box girders exhibit excessive multidecade deflections unforeseeable by past and current design codes. To investigate such a behavior, mainly caused by creep and shrinkage phenomena, an effective finite element (FE) formulation is presented in this article. This formulation is developed by invoking the stationarity of an energetic principle for linear viscoelastic problems and relies on the Bazant creep constitutive law. A case study representative of segmental prestressed concrete box girders susceptible to creep is also analyzed in the article, that is, the Colle Isarco viaduct. Its FE model, based on the aforementioned energetic formulation, was succ…
The Legend of Excellent Businessman. A Neuroethical Perspective
2019
If the question about the causes of the crises has generated a good deal of literature in Spain, the key issue in recent times has been how to create that tangible and intangible wealth that only companies can give. One of the proposals that specialists agree upon is to revitalise the business entrepreneurial spirit, presenting the entrepreneurs’ way of life as an attractive option, due to the good they produce and the social recognition they enjoy. Accepting the suggestions of the so-called “narrative turn”, the article analyses the virtualities of business narratives in order to enhance the role of entrepreneurs. To this end, the article aims to cover three stages: (1) narratives are nece…
Neural Networks in ECG Classification
2011
In this chapter, we review the vast field of application of artificial neural networks in cardiac pathology discrimination based on electrocardiographic signals. We discuss advantages and drawbacks of neural and adaptive systems in cardiovascular medicine and catch a glimpse of forthcoming developments in machine learning models for the real clinical environment. Some problems are identified in the learning tasks of beat detection, feature selection/extraction, and classification, and some proposals and suggestions are given to alleviate the problems of interpretability, overfitting, and adaptation. These have become important problems in recent years and will surely constitute the basis of…
Apodization of imaging systems by means of a random spatially nonstationary absorbing screen
1992
The amplitude impulse response (AIR) of coherent imaging systems with random binary apodizers is analyzed. Formulas for the mean value and the variance of the AIR are derived for two statistical one-dimensional models of apodizers: (1) nonuniform low-density shot noise and (2) a nonuniform unipolar synchronous random process. We show that for both models a high signal-to-noise ratio is achieved within the central peak and the low-order sidelobes of the AIR. Apodizers based on the second model permit higher values of the signal-to-noise ratio than those based on the first one.
Host–Guest Interactions of Sodiumsulfonatomethyleneresorcinarene and Quaternary Ammonium Halides: An Experimental–Computational Analysis of the Guest…
2020
The molecular recognition of nine quaternary alkyl- and aryl-ammonium halides (Bn) by two different receptors, Calkyl-tetrasodiumsulfonatomethyleneresorcinarene (An), were studied in solution using...
Spatial noise-aware temperature retrieval from infrared sounder data
2020
In this paper we present a combined strategy for the retrieval of atmospheric profiles from infrared sounders. The approach considers the spatial information and a noise-dependent dimensionality reduction approach. The extracted features are fed into a canonical linear regression. We compare Principal Component Analysis (PCA) and Minimum Noise Fraction (MNF) for dimensionality reduction, and study the compactness and information content of the extracted features. Assessment of the results is done on a big dataset covering many spatial and temporal situations. PCA is widely used for these purposes but our analysis shows that one can gain significant improvements of the error rates when using…
Mast cells as rapid innate sensors of cytomegalovirus by TLR3/TRIF signaling-dependent and -independent mechanisms
2014
The succinct metaphor, ‘the immune system's loaded gun', has been used to describe the role of mast cells (MCs) due to their storage of a wide range of potent pro-inflammatory and antimicrobial mediators in secretory granules that can be released almost instantly on demand to fight invaders. Located at host–environment boundaries and equipped with an arsenal of pattern recognition receptors, MCs are destined to be rapid innate sensors of pathogens penetrating endothelial and epithelial surfaces. Although the importance of MCs in antimicrobial and antiparasitic defense has long been appreciated, their role in raising the alarm against viral infections has been noted only recently. Work on cy…
Solution and solid-state studies on the halide binding affinity of perfluorophenyl-armed uranyl–salophen receptors enhanced by anion–π Interactions
2016
The enhancement of the binding between halide anions and a Lewis acidic uranyl-salophen receptor has been achieved by the introduction of pendant electron- deficient arene units into the receptor skeleton. The association and the occurrence of the elusive anion-p interaction with halide anions (as tetrabutylammonium salts) have been demonstrated in solution and in the solid state, providing unambiguous evidence on the interplay of the concerted interactions responsible for the anion binding.
Two-view “cylindrical decomposition” of binary images
2001
This paper describes the discrete cylindrical algebraic decomposition (DCAD) construction along two orthogonal views of binary images. The combination of two information is used to avoid ambiguities for image recognition purposes. This algorithm associates an object connectivity graph to each connected component, allowing a complete description of the structuring information. Moreover, an easy and compact representation of the scene is achieved by using strings in a five letter alphabet. Examples on complex digital images are also provided. © 2001 Elsevier Science Inc.
Wi-Dia: Data-Driven Wireless Diagnostic Using Context Recognition
2018
The recent densification of Wi-Fi networks is exacerbating the effects of well-known pathologies including hidden nodes and flow starvation. This paper provides an automatic diagnostic tool for detecting the source roots of performance impairments by recognizing the wireless operating context. Our tool for Wi-Fi diagnostic, named Wi-Dia, exploits machine learning methods and uses features related to network topology and channel utilization, without impact on regular network operations and working in real-time. Real-time per-link Wi-Fi diagnosis enables recovering actions for context-specific treatments. Wi-Dia classifier recognizes different classes of interference; it is jointly trained us…