Search results for "DISTANCE"

Hyperspectral detection of citrus damage with Mahalanobis kernel classifier

2007

Presented is a full computer vision system for the identification of post-harvest damage in citrus packing houses. The method is based on the combined use of hyperspectral images and the Mahalanobis kernel classifier. More accurate and reliable results compared to other methods are obtained in several scenarios and acquired images.

Clustering-Based Protocol Classification via Dimensionality Reduction

2015

We propose a unique framework that is based upon diffusion processes and other methodologies for finding meaningful geometric descriptions in high-dimensional datasets. We will show that the eigenfunctions of the generated underlying Markov matrices can be used to construct diffusion processes that generate efficient representations of complex geometric structures for high-dimensional data analysis. This is done by non-linear transformations that identify geometric patterns in these huge datasets that find the connections among them while projecting them onto low dimensional spaces. Our methods automatically classify and recognize network protocols. The main core of the proposed methodology…

Accelerated Proximal Gradient Descent in Metric Learning for Kernel Regression

2018

The purpose of this paper is to learn a specific distance function for the Nadayara Watson estimator to be applied as a non-linear classifier. The idea of transforming the predictor variables and learning a kernel function based on Mahalanobis pseudo distance througth an low rank structure in the distance function will help us to lead the development of this problem. In context of metric learning for kernel regression, we introduce an Accelerated Proximal Gradient to solve the non-convex optimization problem with better convergence rate than gradient descent. An extensive experiment and the corresponding discussion tries to show that our strategie its a competitive solution in relation to p…

Use of QSAR methods for predicting the chemiluminescent behaviour of organic compounds upon reaction with potassium permanganate in an acid medium

2009

In previous work, molecular connectivity computations were successfully used to predict the chemiluminescent behaviour of organic compounds upon reaction with common strong oxidants and the native fluorescence too; both of them in a liquid phase. The obtained results were used to develop new analytical procedures to the given compounds. For the first time, connectivity methods were used for a purely analytical purpose. In this work, we went deeper into the knowledge of direct chemiluminescence processes by using molecular connectivity in the form of QSAR methods to predict the chemiluminescence intensity produced by reactions between organic compounds (pharmaceuticals mainly) and potassium …

2014

Large data sets classification is widely used in many industrial applications. It is a challenging task to classify large data sets efficiently, accurately, and robustly, as large data sets always contain numerous instances with high dimensional feature space. In order to deal with this problem, in this paper we present an online Logdet divergence based metric learning (LDML) model by making use of the powerfulness of metric learning. We firstly generate a Mahalanobis matrix via learning the training data with LDML model. Meanwhile, we propose a compressed representation for high dimensional Mahalanobis matrix to reduce the computation complexity in each iteration. The final Mahalanobis mat…

The fundamental theory of optimal "Anti-Bayesian" parametric pattern classification using order statistics criteria

2013

Author's version of an article in the journal: Pattern Recognition. Also available from the publisher at: http://dx.doi.org/10.1016/j.patcog.2012.07.004 The gold standard for a classifier is the condition of optimality attained by the Bayesian classifier. Within a Bayesian paradigm, if we are allowed to compare the testing sample with only a single point in the feature space from each class, the optimal Bayesian strategy would be to achieve this based on the (Mahalanobis) distance from the corresponding means. The reader should observe that, in this context, the mean, in one sense, is the most central point in the respective distribution. In this paper, we shall show that we can obtain opti…

A field test of behavioural flexibility in Zenaida doves (Zenaida aurita).

2010

7 pages; International audience; Animals' ability to adjust their behaviour when environmental conditions change can increase their likelihood of survival. Although such behavioural flexibility is regularly observed in the field, it has proven difficult to systematically quantify and predict inter-individual differences in free-living animals. We presented 24 Zenaida doves (Zenaida aurita) on 12 territories with two learning tests in their natural habitat in Barbados. The dove pairs showed high site fidelity and territoriality, allowing us to test individuals repeatedly while accounting for the effects of territorial chases and pair bonds on our learning measures. We used a foraging apparat…

Get some respect – buy organic foods! When everyday consumer choices serve as prosocial status signaling

2020

Status considerations have recently been linked to prosocial behaviors. This research shows that even everyday consumer behaviors such as favoring organic foods serve as prosocial status signaling. Key ideas from the continuum model of consumer impression formation and the theories of costly signaling and symbolic consumption are synthetized to make sense of this phenomenon. Two web-surveys (Ns = 187, 259) and a field study (N = 336) following experimental designs are conducted. This approach allows the analysis of both the more and less conscious reactions of consumers. Study 1 shows that the image of consumers favoring organic product versions is marked by characteristics consistent with …

Evaluation of HIV-1 integrase resistance emergence and evolution in patients treated with integrase inhibitors

2020

Abstract Objectives This study evaluated the emergence of mutations associated with integrase strand transfer inhibitors (INSTI) resistance (INSTI-RMs) and the integrase evolution in human immunodeficiency virus type 1 (HIV-1) infected patients treated with this drug class. Methods The emergence of INSTI-RMs and integrase evolution (estimated as genetic distance between integrase sequences under INSTI treatment and before INSTI treatment) were evaluated in 107 INSTI-naive patients (19 drug-naive and 88 drug-experienced) with two plasma genotypic resistance tests: one before INSTI treatment and one under INSTI treatment. A logistic regression analysis was performed to evaluate factors associ…

Effects of target distance on select biomechanical parameters in taekwondo roundhouse kick.

2013

The aim of this study was to investigate the effects of target distance on temporal and impact force parameters that are important performance factors in taekwondo kicks. Forty-nine taekwondo athletes (age = 24.5 +/- 5.9 years; mass = 79.9 +/- 10.8 kg) were recruited: 13 male experts, 21 male novices, 8 female experts, and 6 female novices. Impact force, reaction time, and execution time were computed. Three-way repeated measure ANOVAs revealed significant 'distance' effect on impact force, reaction time, and execution time (p = 0.001). Comparisons between distance conditions revealed that taekwondo athletes kicked with higher impact force from short distance (17.6 +/- 7.5 N/kg) than from l…