Classificação automática de estilos de videoaulas

Although video lessons are often used in diverse areas that cover a wide range of studies and applications, the lack of a common approach to defining and classifying their styles results in the use of many different models for these purposes. There are different proposals for classifying these styles, but with differences between them. Consolidating production styles makes it possible to understand the possibilities of producing materials and facilitates communication between researchers or content producers. To develop this common approach, there is a need to build a framework through which these styles can be defined and classified. In addition, much has been done to investigate the effects of these styles on student engagement and learning outcome. These studies suggest that video lessons styles affect academic performance and that students learn better through a certain video lesson style compared to others. Based on this, the objectives of this work are to propose a unified model for classifying styles of video lessons based on the nomenclatures and definitions used in the literature also, to propose an approach for automatic classification of 4 video lesson styles (Talking Head, Voice Over Slides, Presentation Style and Khan-Style) using visual characteristics of these styles. The proposed classification model allows classifying video styles based on 2 visual dimensions which are human embedding and instructional media. It is believed that this model will make possible the correct characterization and formation of a common understanding of definitions of video lessons styles based on existing scientific studies. The automatic classification of styles can be used by recommendation systems to suggest styles that are more consistent with student preferences and the intended learning outcome. The approach presented for the automatic classification shows that the features extracted from the videos are capable of accurately classifying the set of styles presented in this study and this classification is carried out through simple and easy-to-extract features.Embora as videoaulas sejam frequentemente utilizadas em diversas áreas que abrangem uma ampla gama de estudos e aplicações, a falta de uma abordagem comum para a definição e classificação de seus estilos resulta na utilização de vários modelos diferentes para esses fins. Existem diferentes propostas de classificação desses estilos mas com divergências entre si. Consolidar os estilos de produção permitiria entender as possibilidades de produção de materiais e facilitaria a comunicação entre pesquisadores ou produtores de conteúdo. Para desenvolver essa abordagem comum, existe a necessidade de construir uma estrutura através da qual esses estilos possam ser definidos e classificados. Além disso, muito tem sido feito para investigar os efeitos desses estilos no envolvimento do aluno e no resultado de aprendizagem. Esses estudos sugerem que os estilos de videoaula afetam o desempenho acadêmico e que os alunos aprendam melhor através de um determinado estilo de videoaula em comparação com outros. Com base nisso, os objetivos deste trabalho são propor um modelo unificado para classificação de estilos de videoaulas com base nas nomenclaturas e definições usadas na literatura e propor uma abordagem para classificação automática de 4 estilos de videoaula (Talking Head, Voice Over Slides, Presentation Style e Khan-Style), utilizando características visuais desses estilos. O modelo de classificação proposto permite classificar os estilos de vídeo com base em 2 dimensões visuais, incorporação humana e mídia instrucional. Acreditase que com esse modelo tornará possível a correta caracterização e formação de um entendimento comum de definições de estilos de videoaulas com base em estudos científicos existentes. Já a classificação automática dos estilos poderá ser utilizada por sistemas de recomendação para sugestão de estilos mais aderentes a preferências dos alunos e ao resultado de aprendizagem pretendido. A abordagem apresentada para a classificação automática mostra que as features extraídas dos vídeos são capazes de classificar de forma acurada o conjunto de estilos apresentados neste estudo, sendo essa classificação realizada por meio de features simples e fáceis de serem extraídas

Effect of lung recruitment and titrated Positive End-Expiratory Pressure (PEEP) vs low PEEP on mortality in patients with acute respiratory distress syndrome - A randomized clinical trial

IMPORTANCE: The effects of recruitment maneuvers and positive end-expiratory pressure (PEEP) titration on clinical outcomes in patients with acute respiratory distress syndrome (ARDS) remain uncertain. OBJECTIVE: To determine if lung recruitment associated with PEEP titration according to the best respiratory-system compliance decreases 28-day mortality of patients with moderate to severe ARDS compared with a conventional low-PEEP strategy. DESIGN, SETTING, AND PARTICIPANTS: Multicenter, randomized trial conducted at 120 intensive care units (ICUs) from 9 countries from November 17, 2011, through April 25, 2017, enrolling adults with moderate to severe ARDS. INTERVENTIONS: An experimental strategy with a lung recruitment maneuver and PEEP titration according to the best respiratory-system compliance (n = 501; experimental group) or a control strategy of low PEEP (n = 509). All patients received volume-assist control mode until weaning. MAIN OUTCOMES AND MEASURES: The primary outcome was all-cause mortality until 28 days. Secondary outcomes were length of ICU and hospital stay; ventilator-free days through day 28; pneumothorax requiring drainage within 7 days; barotrauma within 7 days; and ICU, in-hospital, and 6-month mortality. RESULTS: A total of 1010 patients (37.5% female; mean [SD] age, 50.9 [17.4] years) were enrolled and followed up. At 28 days, 277 of 501 patients (55.3%) in the experimental group and 251 of 509 patients (49.3%) in the control group had died (hazard ratio [HR], 1.20; 95% CI, 1.01 to 1.42; P = .041). Compared with the control group, the experimental group strategy increased 6-month mortality (65.3% vs 59.9%; HR, 1.18; 95% CI, 1.01 to 1.38; P = .04), decreased the number of mean ventilator-free days (5.3 vs 6.4; difference, −1.1; 95% CI, −2.1 to −0.1; P = .03), increased the risk of pneumothorax requiring drainage (3.2% vs 1.2%; difference, 2.0%; 95% CI, 0.0% to 4.0%; P = .03), and the risk of barotrauma (5.6% vs 1.6%; difference, 4.0%; 95% CI, 1.5% to 6.5%; P = .001). There were no significant differences in the length of ICU stay, length of hospital stay, ICU mortality, and in-hospital mortality. CONCLUSIONS AND RELEVANCE: In patients with moderate to severe ARDS, a strategy with lung recruitment and titrated PEEP compared with low PEEP increased 28-day all-cause mortality. These findings do not support the routine use of lung recruitment maneuver and PEEP titration in these patients. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT01374022