5 resultados para Audio-visual materials

em Universidad de Alicante


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This thesis explores the role of multimodality in language learners’ comprehension, and more specifically, the effects on students’ audio-visual comprehension when different orchestrations of modes appear in the visualization of vodcasts. Firstly, I describe the state of the art of its three main areas of concern, namely the evolution of meaning-making, Information and Communication Technology (ICT), and audio-visual comprehension. One of the most important contributions in the theoretical overview is the suggested integrative model of audio-visual comprehension, which attempts to explain how students process information received from different inputs. Secondly, I present a study based on the following research questions: ‘Which modes are orchestrated throughout the vodcasts?’, ‘Are there any multimodal ensembles that are more beneficial for students’ audio-visual comprehension?’, and ‘What are the students’ attitudes towards audio-visual (e.g., vodcasts) compared to traditional audio (e.g., audio tracks) comprehension activities?’. Along with these research questions, I have formulated two hypotheses: Audio-visual comprehension improves when there is a greater number of orchestrated modes, and students have a more positive attitude towards vodcasts than traditional audios when carrying out comprehension activities. The study includes a multimodal discourse analysis, audio-visual comprehension tests, and students’ questionnaires. The multimodal discourse analysis of two British Council’s language learning vodcasts, entitled English is GREAT and Camden Fashion, using ELAN as the multimodal annotation tool, shows that there are a variety of multimodal ensembles of two, three and four modes. The audio-visual comprehension tests were given to 40 Spanish students, learning English as a foreign language, after the visualization of vodcasts. These comprehension tests contain questions related to specific orchestrations of modes appearing in the vodcasts. The statistical analysis of the test results, using repeated-measures ANOVA, reveal that students obtain better audio-visual comprehension results when the multimodal ensembles are constituted by a greater number of orchestrated modes. Finally, the data compiled from the questionnaires, conclude that students have a more positive attitude towards vodcasts in comparison to traditional audio listenings. Results from the audio-visual comprehension tests and questionnaires prove the two hypotheses of this study.

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Las teorías cognitivas han demostrado que el pensamiento humano se encuentra corporeizado; es decir, que accedemos a la realidad mediante nuestros sentidos y no podemos huir de ellos. Para entender y manejar conceptos abstractos utilizamos proyecciones metafóricas basadas en sensaciones corporales. De ahí la ubicuidad de la metáfora en el lenguaje cotidiano. Aunque esta afirmación ha sido ampliamente probada con el análisis del corpus verbal en distintas lenguas, apenas existen investigaciones en el corpus audiovisual. Si las metáforas primarias forman parte de nuestro inconsciente cognitivo, son inherentes al ser humano y consecuencia de la naturaleza del cerebro, deben generar también metáforas visuales. En este artículo, se analizan y discuten una serie de ejemplos para comprobarlo.

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From a gender perspective, protection and advertising political actions about work-family should promote sharing responsibilities between sexes. Next to political action and specific measures, the project of equal opportunities needs a long-term strategy based on the education on equality. This article proposes the methodologic exposition of a study based on these premises. It facilitates and explains the protocol used for the analysis of the audio-visual advertising campaigns on conciliation emitted by the Woman’s Institute. The evaluation of the actions is focused on the effectiveness from the point of view of mass media. It provides some data that illustrates the proposed study. Finally, it considers the difficulties of the available sources of information.

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This paper illustrates how to design a visual experiment to measure color differences in gonioapparent materials and how to assess the merits of different advanced color-difference formulas trying to predict the results of such experiment. Successful color-difference formulas are necessary for industrial quality control and artificial color-vision applications. A color- difference formula must be accurate under a wide variety of experimental conditions including the use of challenging materials like, for example, gonioapparent samples. Improving the experimental design in a previous paper [Melgosaet al., Optics Express 22, 3458-3467 (2014)], we have tested 11 advanced color-difference formulas from visual assessments performed by a panel of 11 observers with normal colorvision using a set of 56 nearly achromatic colorpairs of automotive gonioapparent samples. Best predictions of our experimental results were found for the AUDI2000 color-difference formula, followed by color-difference formulas based on the color appearance model CIECAM02. Parameters in the original weighting function for lightness in the AUDI2000 formula were optimized obtaining small improvements. However, a power function from results provided by the AUDI2000 formula considerably improved results, producing values close to the inter-observer variability in our visual experiment. Additional research is required to obtain a modified AUDI2000 color-difference formula significantly better than the current one.

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Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object’s surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand’s fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments.