Search results for "Linear"
showing 10 items of 7165 documents
Bayesian Methodology in Statistics
2009
Bayesian methods provide a complete paradigm for statistical inference under uncertainty. These may be derived from an axiomatic system and provide a coherent methodology which makes it possible to incorporate relevant initial information, and which solves many of the difficulties that frequentist methods are known to face. If no prior information is to be assumed, the more frequent situation met in scientific reporting, a formal initial prior function, the reference prior, mathematically derived from the assumed model, is used; this leads to objective Bayesian methods, objective in the precise sense that their results, like frequentist results, only depend on the assumed model and the data…
Experimental observations of upstream overdeepening
2005
The issue of morphodynamic influence in meandering streams is investigated through a series of laboratory experiments on curved and straight flumes. Both qualitative and quantitative observations confirm the suitability of the recent theoretical developments (Zolezzi & Seminara 2001) that indicate the occurrence of two distinct regimes of morphodynamic influence, depending on the value of the width ratio of the channel β. The threshold value βR separating the upstream from the downstream influence regimes coincides with the resonant value discovered by Blondeaux & Seminara (1985). Indeed it is observed that upstream influence may occur only in relatively wide channels, while narrower stream…
3/4-efficient Bell measurement with passive linear optics and unentangled ancillae
2014
It is well known that an unambiguous discrimination of the four optically encoded Bell states is possible with a probability of $50\%$ at best, when using static, passive linear optics and arbitrarily many vacuum mode ancillae. By adding unentangled single-photon ancillae, we are able to surpass this limit and reach a success probability of at least $75\%$. We discuss the error robustness of the proposed scheme and a generalization to reach a success probability arbitrarily close to $100\%$.
RISQUE ASSOCIE A L'UTILISATION DE LA LOI DE BENFORD POUR DETECTER DES VENTES FRAUDULEUSES DE BIENS INNOVANTS A LA MODE
2010
Benford's law has been promoted as providing the auditors with a turnkey solution for fraud detection. The purpose of this paper is to show it is not always possible to detect fraudulent sales with that law. We use sales in volume of game consoles in Japan (since 1989), in United-States, in France, in Germany and in United-Kingdom (since 2000). After reviewing briefly the literature and our study design, the chi-square test and the bias analysis were used to measure the goodness-of-fit to Benford's law. Despite the absence of actual fraud, these sale series of fashion goods are not significantly in conformity with Benford's law. Thus, for the detection of fraudulent sales in this sector, th…
Protective role of mindfulness, self-compassion and psychological flexibility on the burnout subtypes among psychology and nursing undergraduate stud…
2021
Abstract To explore the relationship between mindfulness, self-compassion and psychological flexibility, and the burnout subtypes in university students of the Psychology and Nursing degrees, and to analyse possible risk factors for developing burnout among socio-demographic and studies-related characteristics. Design Cross-sectional study conducted on a sample of 644 undergraduate students of Nursing and Psychology from two Spanish universities. Methods The study was conducted between December 2015 and May 2016. Bivariate Pearson's correlations were computed to analyse the association between mindfulness facets, self-compassion and psychological flexibility, and levels of burnout. Multivar…
Phase separation of symmetrical polymer mixtures in thin-film geometry
1995
Monte Carlo simulations of the bond fluctuation model of symmetrical polymer blends confined between two “neutral” repulsive walls are presented for chain lengthNA=NB=32 and a wide range of film thicknessD (fromD=8 toD=48 in units of the lattice spacing). The critical temperaturesTc(D) of unmixing are located by finite-size scaling methods, and it is shown that\(T_c (\infty ) - T_c (D) \propto D^{ - {1 \mathord{\left/ {\vphantom {1 {v_3 }}} \right. \kern-\nulldelimiterspace} {v_3 }}} \), wherev3≈0.63 is the correlation length exponent of the three-dimensional Ising model universality class. Contrary to this result, it is argued that the critical behavior of the films is ruled by two-dimensi…
Sparse Manifold Clustering and Embedding to discriminate gene expression profiles of glioblastoma and meningioma tumors.
2013
Sparse Manifold Clustering and Embedding (SMCE) algorithm has been recently proposed for simultaneous clustering and dimensionality reduction of data on nonlinear manifolds using sparse representation techniques. In this work, SMCE algorithm is applied to the differential discrimination of Glioblastoma and Meningioma Tumors by means of their Gene Expression Profiles. Our purpose was to evaluate the robustness of this nonlinear manifold to classify gene expression profiles, characterized by the high-dimensionality of their representations and the low discrimination power of most of the genes. For this objective, we used SMCE to reduce the dimensionality of a preprocessed dataset of 35 single…
Reproducing kernel hilbert spaces regression methods for genomic assisted prediction of quantitative traits.
2008
Abstract Reproducing kernel Hilbert spaces regression procedures for prediction of total genetic value for quantitative traits, which make use of phenotypic and genomic data simultaneously, are discussed from a theoretical perspective. It is argued that a nonparametric treatment may be needed for capturing the multiple and complex interactions potentially arising in whole-genome models, i.e., those based on thousands of single-nucleotide polymorphism (SNP) markers. After a review of reproducing kernel Hilbert spaces regression, it is shown that the statistical specification admits a standard mixed-effects linear model representation, with smoothing parameters treated as variance components.…
Monitoring barley and corn growth from remote sensing data at field scale
2004
Vegetation indices have been used for operational quantitative monitoring of vegetation. Here, corn and barley cultures have been used to relate meaningful biophysical parameters such as dry biomass and Crop Growth Rate (CGR) to the well-established Normalized Difference Vegetation Index (NDVI). We explain these relationships by means of the use of the Light Use Efficiency (LUE) models, based on the positive relation between primary production and Absorbed Photosynthetically Active Radiation (APAR). In these models we introduce NDVI as a linear estimator of f APAR. Experimental data over corn and barley show that dry biomass is linearly related to the Time-Integrated Value of the NDVI (TIND…
The Application of Machine Learning Algorithms to the Analysis of Electromyographic Patterns From Arthritic Patients
2009
The main aim of our study was to investigate the possibility of applying machine learning techniques to the analysis of electromyographic patterns (EMG) collected from arthritic patients during gait. The EMG recordings were collected from the lower limbs of patients with arthritis and compared with those of healthy subjects (CO) with no musculoskeletal disorder. The study involved subjects suffering from two forms of arthritis, viz, rheumatoid arthritis (RA) and hip osteoarthritis (OA). The analysis of the data was plagued by two problems which frequently render the analysis of this type of data extremely difficult. One was the small number of human subjects that could be included in the in…