A unity-based framework for sound transmission and perception in video games

The ability for humans to hear, attend to, and understand incoming sounds is affected, at least, by environmental, morphological, and cognitive factors. Conversely, current implementations of audition in virtual characters often only consider as constraint to the auditory process the distance between the sound emitter and the sound receiver. To cope with this limitation, this paper presents ongoing work on a novel framework integrated in Unity, directed to game developers interested in implementing non-player characters with noisy, character-specific, and context-dependent auditory perception.info:eu-repo/semantics/acceptedVersio

Does exposure to televised debates change the weight of different criteria for candidate assessment? A quasi-experiment in the context of the 2014 Spitzenkandidaten debate

In this article, we show how exposure to debates primes specific candidate assessments as key factors of candidate appraisal. To fulfil this goal, we rely on quasi-experimental data collected in 24 European Union Member States and focus on a debate starred by largely unknown candidates (the 2014 European Spiztenkandidaten) engaged in a remarkably invisible campaign. Our results show that candidate perceptions become much more important factors of general candidate appraisal after the debate in the case of three out of the five lead candidates, namely those whose image benefitted from their participation in the debate. In several cases, personal likeability became more important in the general assessment of the Spitzenkandidaten, but there was also an increased relevance of the perceptions of leadership strength (Keller) and quality of the ideas to stimulate the European economy (Schulz and Tspiras). Moreover, in the cases of Schulz, Keller, and Tsipras, post-exposure candidate perceptions impacted more their general appraisal by participants without previous knowledge of them than by those who claimed to know them before the debate. Interestingly, leadership strength appraisal was more relevant for the former than for the latter participants. In short, by unveiling these patterns, this article not only provides evidence of the priming effects of debate exposure but also illustrates how such effects may vary according to citizens’ previous knowledge and the candidates’ general performance in the debate.info:eu-repo/semantics/publishedVersio

Analysis of Dominant Classes in Universal Adversarial Perturbations

The reasons why Deep Neural Networks are susceptible to being fooled by adversarial examples remains an open discussion. Indeed, many differ- ent strategies can be employed to efficiently generate adversarial attacks, some of them relying on different theoretical justifications. Among these strategies, universal (input-agnostic) perturbations are of particular inter- est, due to their capability to fool a network independently of the input in which the perturbation is applied. In this work, we investigate an in- triguing phenomenon of universal perturbations, which has been reported previously in the literature, yet without a proven justification: universal perturbations change the predicted classes for most inputs into one par- ticular (dominant) class, even if this behavior is not specified during the creation of the perturbation. In order to justify the cause of this phe- nomenon, we propose a number of hypotheses and experimentally test them using a speech command classification problem in the audio domain as a testbed. Our analyses reveal interesting properties of universal per- turbations, suggest new methods to generate such attacks and provide an explanation of dominant classes, under both a geometric and a data- feature perspective.IT1244-19 PRE_2019_1_0128 TIN2016-78365-R PID2019-104966GB-I00 FPU19/0323

Exploring Gaps in DeepFool inSearch of More Effective Adversarial Perturbations

Adversarial examples are inputs subtly perturbed to produce a wrong prediction in machine learning models, while remaining perceptually similar to the original input. To find adversarial examples, some attack strategies rely on linear approximations of different properties of the models. This opens a number of questions related to the accuracy of such approximations. In this paper we focus on DeepFool, a state-of-the-art attack algorithm, which is based on efficiently approximating the decision space of the target classifier to find the minimal perturbation needed to fool the model. The objective of this paper is to analyze the feasibility of finding inaccuracies in the linear approximation of DeepFool, with the aim of studying whether they can be used to increase the effectiveness of the attack. We introduce two strategies to efficiently explore gaps in the approximation of the decision boundaries, and evaluate our approach in a speech command classification task.IT1244-19 PRE_2019_1_0128 TIN2016-78365-R PID2019-104966GB-I00 FPU19/0323

Structure and Dynamics of the Globular Cluster Palomar 13

We present Keck/DEIMOS spectroscopy and Canada-France-Hawaii Telescope/MegaCam photometry for the Milky Way globular cluster Palomar 13. We triple the number of spectroscopically confirmed members, including many repeat velocity measurements. Palomar 13 is the only known globular cluster with possible evidence for dark matter, based on a Keck/High Resolution Echelle Spectrometer 21 star velocity dispersion of σ = 2.2 ± 0.4 km s^(–1). We reproduce this measurement, but demonstrate that it is inflated by unresolved binary stars. For our sample of 61 stars, the velocity dispersion is σ = 0.7^(+0.6)_(–0.5) km s^(–1). Combining our DEIMOS data with literature values, our final velocity dispersion is σ = 0.4^(+0.4)_( –0.3) km s^(–1). We determine a spectroscopic metallicity of [Fe/H] = –1.6 ± 0.1 dex, placing a 1σ upper limit of σ_([Fe/H]) ~ 0.2 dex on any internal metallicity spread. We determine Palomar 13's total luminosity to be M_V = –2.8 ± 0.4, making it among the least luminous known globular clusters. The photometric isophotes are regular out to the half-light radius and mildly irregular outside this radius. The outer surface brightness profile slope is shallower than typical globular clusters (Σ α r^η, η = –2.8 ± 0.3). Thus at large radius, tidal debris is likely affecting the appearance of Palomar 13. Combining our luminosity with the intrinsic velocity dispersion, we find a dynamical mass of M_(1/2) = 1.3^(+2:7)_(–1.3) × 10^3 M_☉ and a mass-to-light ratio of M/L_V = 2.4^(+5.0)_(–2.4) M_☉/L_☉. Within our measurement errors, the mass-to-light ratio agrees with the theoretical predictions for a single stellar population. We conclude that, while there is some evidence for tidal stripping at large radius, the dynamical mass of Palomar 13 is consistent with its stellar mass and neither significant dark matter, nor extreme tidal heating, is required to explain the cluster dynamics

Can cold weather be a cardiovascular determinant in warm countries?

In almost every temperate region of the world, the number of cardiovascular mortality increases significantly during winter months. This phenomenon has been considered as a public health issue in several countries as many of these deaths are considered to be avoidable. The cause for the excess of winter deaths can be attributed to a number of factors, such as diet, exercise and exposure to cold weather. Curiously, southern European countries, such as Portugal, seem to have the highest excess winter deaths that seem to be related to exposure of cold. However, very few studies have addressed this relationship in Portugal and no quantification of the role of cold weather on cardiovascular diseases has been published. The main goal of this study is to quantify the short effect of cold weather on the cardiovascular morbidity in Portugal Generalized additive Poisson regression models were used in order to obtain the influence of a thermal comfort index (PET) on daily hospitalizations for acute myocardial Infarction in the two most developed metropolitan areas of Portugal: Lisbon and Oporto. All models were adjusted for time and other environmental variables. Influenza was also considered as a confounder. The main results reveal an increase up to 2.2% (95% CI = 0,9%; 3,3%) of daily hospital admissions in winter per degree fall in PET. The increase in daily hospitalizations was greater for the entire population than when only the elderly (>65 years) were considered. View publicationinfo:eu-repo/semantics/publishedVersio

Sailing uncharted waters with old boats? COVID-19 and the digitalization and professionalization of presidential campaigns in Portugal

This article investigates the extent to which the COVID-19 pandemic fostered significant shifts in election campaigning. The argument is that COVID-19 might have had an impact on both digitalization and professionalization, which might have been regarded as necessary strategies to curb the difficulties brought about by the pandemic. We apply a most similar systems design with a threefold comparative scheme in order to capture and isolate such effects in the campaigns preceding the 2021 Portuguese presidential elections, using data from campaign spending, campaign activities, and social media activity and impact. Results show that the pandemic crisis has not, generally speaking, brought about a higher level of digitalization of electoral campaigns, in spite of online events having become more common. On the contrary, while there were signs of feebler patterns of normalization of online competition in 2021 vis-à-vis 2016, namely in terms of engagement, normalization was stronger after the lockdown than before. Lastly, relative investment in professionalization was similar in 2016 and 2021, and the difference between the budgeted and the actual investment in 2021 cannot be attributed to the worsening of the pandemic situation or to the lockdown. In sum, we depict a scenario of remarkable stability of the electoral campaigns put forward by presidential candidates in terms of digitalization and professionalization. Its possible causes and consequences are discussed.info:eu-repo/semantics/publishedVersio

perm mateda: A matlab toolbox of estimation of distribution algorithms for permutation-based combinatorial optimization problems

Permutation problems are combinatorial optimization problems whose solutions are naturally codified as permutations. Due to their complexity, motivated principally by the factorial cardinality of the search space of solutions, they have been a recurrent topic for the artificial intelligence and operations research community. Recently, among the vast number of metaheuristic algorithms, new advances on estimation of distribution algorithms (EDAs) have shown outstanding performance when solving some permutation problems. These novel EDAs implement distance-based exponential probability models such as the Mallows and Generalized Mallows models. In this paper, we present a Matlab package, perm mateda, for estimation of distribution algorithms on permutation problems, which has been implemented as an extension to the Mateda-2.0 toolbox of EDAs. Particularly, we provide implementations of the Mallows and Generalized Mallows EDAs under the Kendall’s-τ, Cayley, and Ulam distances. In addition, four classical permutation problems have been also implemented: Traveling Salesman Problem, Permutation Flowshop Scheduling Problem, Linear Ordering Problem, and Quadratic Assignment Problem