Browsing by Issue Date, starting with "2019-09-06"
Now showing 1 - 5 of 5
Results Per Page
Sort Options
- O papel da inteligência emocional na relação entre a satisfação pós-compra por impulso e tendência para a compra no comportamento do consumidorPublication . Pataliy, Lyubov; Lopez, AníbalO presente trabalho pretende estudar o efeito da satisfação pós-compra por impulso no comportamento do consumidor. Mais especificamente, este estudo analisa o efeito da satisfação pós-compra por impulso (Tempo 1) na tendência para comprar por impulso, e os seus efeitos na repetição e recomendação da compra (Tempo 2). Mais ainda, testámos o efeito moderador da inteligência emocional. Usámos um estudo de painel, com uma amostra de 259 indivíduos, e com dois momentos de recolha de dados, para testar as nossas hipóteses. Os resultados obtidos demonstraram que a tendência para comprar por impulso medeia a relação entre a satisfação pós-compra e o comportamento do consumidor (i.e., repetição e recomendação). Adicionalmente, a inteligência emocional moderou a relação entre a satisfação pós-compra e a tendência para a compra por impulso. Implicações teóricas e práticas são discutidas.
- Analysis of Open Government Data initiatives in BrazilPublication . Bittencourt, Cinthya Alcantara; Estima, JacintoThe Open Data movement has been growing worldwide over the last decade following the crescent data production and technological evolution. This movement use Information and Communication Technologies to provide data in an available, interoperable, license-free, reusable and accessible way to everyone. The Open Data applied to government data relates to a subset called Open Government Data and has the potential to support better decisions and make governments more transparent, efficient, and accountable. Among some of the identified benefits that can be reached through Open Government Data are generate economic growth, motivate innovations, trigger social changes, stimulate citizen participation, thus promoting more democratic societies. The present study selected a set of Open Data requirements from the literature and characterized a collection of datasets from the main Brazilian Open Data government portals regarding their compliance with those requirements. The results showed that the analyzed datasets meet more than half of the requirements but are far from being fully compliant. These results can support government bodies in the identification of the gaps that need to be addressed to make Open Government Data initiatives more effective and harnessed to their full potential.
- Combined measurements of Higgs boson production and decay using up to $80$ fb$^{-1}$ of proton-proton collision data at $\sqrt{s}=$ 13 TeV collected with the ATLAS experimentPublication . ATLAS CollaborationCombined measurements of Higgs boson production cross sections and branching fractions are presented. The combination is based on the analyses of the Higgs boson decay modes $H \to \gamma\gamma$, $ZZ^\ast$, $WW^\ast$, $\tau\tau$, $b\bar{b}$, $\mu\mu$, searches for decays into invisible final states, and on measurements of off-shell Higgs boson production. Up to $79.8$ fb$^{-1}$ of proton-proton collision data collected at $\sqrt{s}=$ 13 TeV with the ATLAS detector are used. Results are presented for the gluon-gluon fusion and vector-boson fusion processes, and for associated production with vector bosons or top-quarks. The global signal strength is determined to be $\mu = 1.11^{+0.09}_{-0.08}$. The combined measurement yields an observed (expected) significance for the vector-boson fusion production process of $6.5\sigma$ ($5.3\sigma$). Measurements in kinematic regions defined within the simplified template cross section framework are also shown. The results are interpreted in terms of modifiers applied to the Standard Model couplings of the Higgs boson to other particles, and are used to set exclusion limits on parameters in two-Higgs-doublet models and in the simplified Minimal Supersymmetric Standard Model. No significant deviations from Standard Model predictions are observed.
- O Turismo e o Terrorismo: entre definições e consequênciasPublication . Caixinha, Francisco Batista Vicente Romão; Cadavez, Maria Cândida PachecoTurismo e terrorismo são dois termos que raramente aparecem associados um ao outro. No entanto, com o crescimento da importância do turismo a nível global, diversas organizações terroristas começaram a olhar para esta área como potencial alvo, uma vez que o turismo engloba muitos mercados e é um ponto de contacto entre vários agentes a nível mundial, assim sendo a possibilidade de desestabilização torna-se bastante maior. É importante analisar e compreender de que forma estes atentados são levados a cabo, as suas origens mais abrangentes e as suas consequências imediatas ou a longo prazo no setor turístico. O que é o turismo? O que é o terrorismo? Por que se procura atacar alvos turísticos? São perguntas às quais se tentará dar resposta neste trabalho.
- Sibilant consonants classification with deep neural networksPublication . Anjos, Ivo; Marques, Nuno; Grilo, Ana Margarida; Guimarães, Isabel; Magalhães, João; Cavaco, SofiaAbstract. Many children su ering from speech sound disorders cannot pronounce the sibilant consonants correctly. We have developed a serious game that is controlled by the children's voices in real time and that allows children to practice the European Portuguese sibilant consonants. For this, the game uses a sibilant consonant classi er. Since the game does not require any type of adult supervision, children can practice the production of these sounds more often, which may lead to faster improvements of their speech. Recently, the use of deep neural networks has given considerable improvements in classi cation for a variety of use cases, from image classication to speech and language processing. Here we propose to use deep convolutional neural networks to classify sibilant phonemes of European Portuguese in our serious game for speech and language therapy. We compared the performance of several diferent arti cial neural networks that used Mel frequency cepstral coefcients or log Mel lterbanks. Our best deep learning model achieves classi cation scores of 95:48% using a 2D convolutional model with log Mel lterbanks as input features.