Search results for "Pattern"
showing 10 items of 4203 documents
Microarray Funzionali attraverso metodologie da Inkjet Printing: dalla biosensoristica allo screening farmacologico
2009
Self-selected running gait modifications reduce acute impact loading, awkwardness, and effort
2021
Impact loading has been associated with running-related injuries, and gait retraining has been suggested as a means of reducing impact loading and lowering the risk of injury. However, gait retraining can lead to increased perceived awkwardness and effort. The influence of specifically trained and self-selected running gait modifications on acute impact loading, perceived awkwardness and effort is currently unclear. Sixteen habitual rearfoot/midfoot runners performed forefoot strike pattern, increased step rate, anterior trunk lean and self-selected running gait modifications on an instrumented treadmill based on real-time biofeedback. Impact loading, perceived awkwardness and effort scores…
Factors related to excessive patellofemoral loading in rearfoot running
2015
Running is recognized as one of the most popular exercise methods. Furthermore, running related injuries have been under the scope for the last few decades. Synchronous function between the segments of the lower limbs is necessary for efficient locomotion. Patellofemoral pain syndrome is a common exercise related syndrome and multifactorial in nature. The purpose of this study was to measure contact forces and frontal plane moments to detect the factors that are associated with atypically high patellofemoral joint loading in rearfoot striking (RFS) running pattern, and moreover, which could possibly contribute to development of the patellofemoral pain syndrome. 39 team sport female athletes…
Convergence Analysis of Distributed Set-Valued Information Systems
2016
This paper focuses on the convergence of information in distributed systems of agents communicating over a network. The information on which the convergence is sought is not rep- resented by real numbers, as often in the literature, rather by sets. The dynamics of the evolution of information across the net- work is accordingly described by set-valued iterative maps. While the study of convergence of set-valued iterative maps is highly complex in general, this paper focuses on Boolean maps, which are comprised of arbitrary combinations of unions, intersections, and complements of sets. For these important class of systems, we provide tools to study both global and local convergence. A distr…
Learning-based multiresolution transforms with application to image compression
2013
In Harten's framework, multiresolution transforms are defined by predicting finer resolution levels of information from coarser ones using an operator, called prediction operator, and defining details (or wavelet coefficients) that are the difference between the exact and predicted values. In this paper we use tools of statistical learning in order to design a more accurate prediction operator in this framework based on a training sample, resulting in multiresolution decompositions with enhanced sparsity. In the case of images, we incorporate edge detection techniques in the design of the prediction operator in order to avoid Gibbs phenomenon. Numerical tests are presented showing that the …
Predicting perceptual distortion sensitivity with gain control models of LGN
2017
Optical sensor for remote estimation of alcohol concentration in blood stream
2013
Abstract The purpose of this manuscript is to validate our recently developed novel optical approach for extraction of remote vibration sources as a successful technique to estimate the alcohol concentration in blood stream. This technique is based on the tracking of temporal changes of reflected secondary speckle patterns produced in human skin when being illuminated by a laser beam. Since the skin’s vibrations profile is changed due to the alcohol in the blood stream, the extraction of the vibration profile can be translated into the corresponding alcohol concentration values by means of defining several parameters acting as indicators for the presence of alcohol in the blood stream. We h…
Classification of persimmon fruit origin by near infrared spectrometry and least squares-support vector machines
2014
Abstract The main objective of this work has been the authentication by Fourier transform near infrared (FT-NIR) spectrometry of the origin of persimmon fruits cultivated in different regions of Spain. In order to achieve this goal, 166 persimmon samples from 7 different regions of Spain were analyzed by FT-NIR spectrometry. By splitting the spectral data in training and independent test sets, a classification model was built using least squares support vector machines chemometric technique. Orthogonal signal correction and principal component analysis were performed prior to conduct the classification strategy. The verified model was applied for the prediction of the origin of 50 samples f…
Alternative method for binary shape alignment of non-symmetrical shapes based on minimal enclosing box
2012
Proposed is a novel method based on the minimal enclosing box (MEB) to determine the canonical orientation associated with a three-dimensional binary shape. It is suggested that, when the shape has no clear distinctive features and two or more of the eigenvalues are similar, this method is more suitable than the commonly used method based on principal component analysis (PCA). An experiment is performed with shapes of human livers by measuring the degree on which a prototypical image (atlas) matches to a new shape after alignment by PCA, minimal area projection (MAP), and MEB showing that in this case MEB outperforms the usual PCA-based alignment method and also the MAP method.
Ensemble feature selection with the simple Bayesian classification
2003
Abstract A popular method for creating an accurate classifier from a set of training data is to build several classifiers, and then to combine their predictions. The ensembles of simple Bayesian classifiers have traditionally not been a focus of research. One way to generate an ensemble of accurate and diverse simple Bayesian classifiers is to use different feature subsets generated with the random subspace method. In this case, the ensemble consists of multiple classifiers constructed by randomly selecting feature subsets, that is, classifiers constructed in randomly chosen subspaces. In this paper, we present an algorithm for building ensembles of simple Bayesian classifiers in random sub…