Search results for "PROB"

A principled approach to network-based classification and data representation

2013

Measures of similarity are fundamental in pattern recognition and data mining. Typically the Euclidean metric is used in this context, weighting all variables equally and therefore assuming equal relevance, which is very rare in real applications. In contrast, given an estimate of a conditional density function, the Fisher information calculated in primary data space implicitly measures the relevance of variables in a principled way by reference to auxiliary data such as class labels. This paper proposes a framework that uses a distance metric based on Fisher information to construct similarity networks that achieve a more informative and principled representation of data. The framework ena…

Automating statistical diagrammatic representations with data characterization

2017

The search for an efficient method to enhance data cognition is especially important when managing data from multidimensional databases. Open data policies have dramatically increased not only the volume of data available to the public, but also the need to automate the translation of data into efficient graphical representations. Graphic automation involves producing an algorithm that necessarily contains inputs derived from the type of data. A set of rules are then applied to combine the input variables and produce a graphical representation. Automated systems, however, fail to provide an efficient graphical representation because they only consider either a one-dimensional characterizat…

Gui-driven intelligent tutoring system with affective support to help learning the algebraic method

2017

Despite many research efforts focused on the development of algebraic reasoning and the resolution of story problems, several investigations have reported that relatively advanced students experience serious difficulties in symbolizing certain meaningful relations by using algebraic equations. In this paper, we describe and justify the Graphical User Interface of an Intelligent Tutoring System that allows learning and practising the procedural aspects involved in translating the information contained in a story problem into a symbolic representation. The application design has been driven by cognitive findings from several previous investigations. First, the process of translating a word pr…

Simulation of laser-generated ultrasonic wave propagation in solid media and air with application to NDE

2009

Ultrasonic methods are well known as powerful and reliable tool for defect detection. In the previous decades focus and interest have been directed to non-contact sensors and methods, showing many advantages over contact techniques where inspection depends on contact conditions (pressure, coupling medium, contact area). The non-contact hybrid ultrasonic method described here is of interest for many applications, requiring periodic inspection in service or after manufacturing. Despite the potential impact of laser-generated ultrasound in many areas of industry, robust tools for studying the phenomenon are lacking and thus limit the design and optimization of non-destructive testing and evalu…

A Survey of Bayesian Techniques in Computer Vision

2010

The Bayesian approach to classification is intended to solve questions concerning how to assign a class to an observed pattern using probability estimations. Red, green and blue (RGB) or hue, saturation and lightness (HSL) values of pixels in digital colour images can be considered as feature vectors to be classified, thus leading to Bayesian colour image segmentation. Bayesian classifiers are also used to sort objects but, in this case, reduction of the dimensionality of the feature vector is often required prior to the analysis. This chapter shows some applications of Bayesian learning techniques in computer vision in the agriculture and agri-food sectors. Inspection and classification of…

Text Classification Using Novel “Anti-Bayesian” Techniques

2015

This paper presents a non-traditional “Anti-Bayesian” solution for the traditional Text Classification (TC) problem. Historically, all the recorded TC schemes work using the fundamental paradigm that once the statistical features are inferred from the syntactic/semantic indicators, the classifiers themselves are the well-established statistical ones. In this paper, we shall demonstrate that by virtue of the skewed distributions of the features, one could advantageously work with information latent in certain “non-central” quantiles (i.e., those distant from the mean) of the distributions. We, indeed, demonstrate that such classifiers exist and are attainable, and show that the design and im…

Predictive and Contextual Feature Separation for Bayesian Metanetworks

2007

Bayesian Networks are proven to be a comprehensive model to describe causal relationships among domain attributes with probabilistic measure of conditional dependency. However, depending on a context, many attributes of the model might not be relevant. If a Bayesian Network has been learned across multiple contexts then all uncovered conditional dependencies are averaged over all contexts and cannot guarantee high predictive accuracy when applied to a concrete case. We are considering a context as a set of contextual attributes, which are not directly effect probability distribution of the target attributes, but they effect on "relevance" of the predictive attributes towards target attribut…

Capturing methodological trends in mobile communication studies

2013

This study investigates methodological trends in mobile communication studies. The articles published over the past 20 years in five journals (Communication Research, Journal of Communication, Journal of Computer-Mediated Communication, New Media & Society, and Information, Communication & Society) are analysed. The results show that the quantitative and qualitative studies have increased while theoretical accounts have remained few. The quantitative approach is the most applied. The studied articles reflect a structural problem of science communication that stems from the lack of cumulativity of scientific results and cross-national analyses and from the standard length of articles that po…

Assessment of qualitative judgements for conditional events in expert systems

1991

Capacity studies of spatially correlated MIMO Rice channels

2010

In this paper, we have studied the statistical properties of the capacity of spatially correlated multiple-input multiple-output (MIMO) Rice channels. We have derived an exact closed-form expression for the probability density function (PDF) and an exact expression for the cumulative distribution function (CDF) of the channel capacity for single-input multiple-output (SIMO) and multiple-input single-output (MISO) systems. Furthermore, an accurate closed-form expression has been derived for the level-crossing rate (LCR) and an accurate expression has been obtained for the average duration of fades (ADF) of the SIMO and MISO channel capacities. For the MIMO case, we have investigated the PDF,…