Classification Performance of Multilayer Perceptrons with Different Risk Functionals

In the present paper we assess the performance of information-theoretic inspired risks functionals in multilayer perceptrons with reference to the two most popular ones, Mean Square Error and Cross-Entropy. The information-theoretic inspired risks, recently proposed, are: HS and HR2 are, respectively, the Shannon and quadratic Rényi entropies of the error; ZED is a risk reflecting the error density at zero errors; EXP is a generalized exponential risk, able to mimic a wide variety of risk functionals, including the information-thoeretic ones. The experiments were carried out with multilayer perceptrons on 35 public real-world datasets. All experiments were performed according to the same protocol. The statistical tests applied to the experimental results showed that the ubiquitous mean square error was the less interesting risk functional to be used by multilayer perceptrons. Namely, mean square error never achieved a significantly better classification performance than competing risks. Cross-entropy and EXP were the risks found by several tests to be significantly better than their competitors. Counts of significantly better and worse risks have also shown the usefulness of HS and HR2 for some datasets.

Gender differences in internet usage habits: a case study in higher education

The usage of information and communication technologies has been growing among students and teachers. In order to improve the use of the Internet as a tool to support teaching and learning it is necessary to understand the Internet usage habits of students. Thus, a study was conducted with 1397 students from five schools of the Polytechnic of Porto. The data was collected through an online questionnaire abd was analized by age range, gender and scientific field. In this paper,gender differences are analyzed and presented in 3 dimensions: type of Internet usage, communication tools and the role of the Internet tools in education.

On the Sensor Classification Scheme of Robotic Manipulators

This paper analyzes the signals captured during impacts and vibrations of a mechanical manipulator. The Fourier Transform of eighteen different signals are calculated and approximated by trendlines based on a power law formula. A sensor classification scheme based on the frequency spectrum behavior is presented.

Towards a classification scheme for musical sounds

Signal Processing: Algorithms, Architectures, Arrangements, and Applications (SPA), 2013

How does gender affect visiting a world heritage site?

To date few studies have been undertaken in Portugal dealing with the attitudes, motivations, and profile of tourists who visit World Heritage Sites. Also, few studies have dealt with destination image (e.g., Agapito, Mendes & Valle, 2010; Lopes, 2011). As far as it is known, none have approached the issue of gender differences in the choice of a Portuguese heritage destination. Since cultural tourism destinations need to differentiate themselves from each other, appropriate market segmentation must be based on a deep understanding of the customers’ motivations and preferences. Keeping in mind results from empirical literature (e.g., Silberberg, 1995; Beerli & Martin, 2004; Richards, 2004; Pérez, 2009; Sheng, Shen, & Chen, 2008), gender seems to be a possible approach to market segmentation, whether for Guimarães or for other cultural tourism destinations around the world. Located in the north-western region of Portugal, Guimarães is a city of strong symbolic and cultural significance, and the nomination of its historical centre as a World Heritage Site in 2001 enhanced its tourism potential. This study analyses the possible relation between gender and attitudes and motivations towards a World Heritage Site, such as Guimarães. Additionally, the empirical approach used in the study tries to capture differences in the perceived attributes of the city. Commonalities and distinctions within and between groups of tourists, by focusing on the specific characteristic of gender, were analysed. The study addressed two main questions: first, whether males and females have similar or different preferences in choosing the city as their destination; and, second, whether there are gender differences in the perception of the attributes of Guimarães. A better understanding of the gendered nature of the destination is a valuable cue for shaping products and services according to visitors’ preferences.

An automatic voice pleasantness classification system based on prosodic and acoustic patterns of voice preference

In the last few years the number of systems and devices that use voice based interaction has grown significantly. For a continued use of these systems the interface must be reliable and pleasant in order to provide an optimal user experience. However there are currently very few studies that try to evaluate how good is a voice when the application is a speech based interface. In this paper we present a new automatic voice pleasantness classification system based on prosodic and acoustic patterns of voice preference. Our study is based on a multi-language database composed by female voices. In the objective performance evaluation the system achieved a 7.3% error rate.