914 resultados para MULTIMEDIA INTERACTIVA


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The purpose of this study was to investigate the effect of multimedia instruction on achievement of college students in AMR 2010 from exploration and discovery to 1865. A non-equivalent control group design was used. The dependent variable was achievement. The independent variables were learning styles, method of instruction, and visual clarifiers (notes). The study was conducted using two history sections from Palm Beach Community College, in Boca Raton, Florida, between August and December, 1998. Data were obtained by means of placement scores, posttests, the Productivity Environmental Preference Survey (PEPS), and a researcher-developed student survey. Statistical analysis of the data was done using SPSS statistical software. Demographic variables were compared using Chi square. T tests were run on the posttests to determine the equality of variances. The posttest scores of the groups were compared using the analysis of covariance (ANCOVA) at the .05 level of significance. The first hypothesis there is a significant difference in students' learning of U.S. History when students receive multimedia instruction was supported, F (1, 52) = 16.88, p < .0005, and F = (1, 53) = 8.52, p < .005 for Tests 2 and 3, respectively. The second hypothesis there is a significant difference on the effectiveness of multimedia instruction based on students' various learning preferences was not supported. The last hypotheses there is a significant difference on students' learning of U.S. History when students whose first language is other than English and students who need remediation receive visual clarifiers were not supported. Analysis of covariance (ANCOVA) indicated no difference between the groups on Test 1, Test 2, or Test 3: F (1, 45) = .01, p < .940, F (1, 52) = .77, p < .385, and F (1, 53) =.17, p < .678, respectively, for language. Analysis of covariance (ANCOVA) indicated no significant difference on Test 1, Test 2, or Test 3, between the groups on the variable remediation: F (1, 45) = .31, p < .580, F (1, 52) = 1.44, p < .236, and F (1, 53) = .21, p < .645, respectively. ^

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The main challenges of multimedia data retrieval lie in the effective mapping between low-level features and high-level concepts, and in the individual users' subjective perceptions of multimedia content. ^ The objectives of this dissertation are to develop an integrated multimedia indexing and retrieval framework with the aim to bridge the gap between semantic concepts and low-level features. To achieve this goal, a set of core techniques have been developed, including image segmentation, content-based image retrieval, object tracking, video indexing, and video event detection. These core techniques are integrated in a systematic way to enable the semantic search for images/videos, and can be tailored to solve the problems in other multimedia related domains. In image retrieval, two new methods of bridging the semantic gap are proposed: (1) for general content-based image retrieval, a stochastic mechanism is utilized to enable the long-term learning of high-level concepts from a set of training data, such as user access frequencies and access patterns of images. (2) In addition to whole-image retrieval, a novel multiple instance learning framework is proposed for object-based image retrieval, by which a user is allowed to more effectively search for images that contain multiple objects of interest. An enhanced image segmentation algorithm is developed to extract the object information from images. This segmentation algorithm is further used in video indexing and retrieval, by which a robust video shot/scene segmentation method is developed based on low-level visual feature comparison, object tracking, and audio analysis. Based on shot boundaries, a novel data mining framework is further proposed to detect events in soccer videos, while fully utilizing the multi-modality features and object information obtained through video shot/scene detection. ^ Another contribution of this dissertation is the potential of the above techniques to be tailored and applied to other multimedia applications. This is demonstrated by their utilization in traffic video surveillance applications. The enhanced image segmentation algorithm, coupled with an adaptive background learning algorithm, improves the performance of vehicle identification. A sophisticated object tracking algorithm is proposed to track individual vehicles, while the spatial and temporal relationships of vehicle objects are modeled by an abstract semantic model. ^

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With the proliferation of multimedia data and ever-growing requests for multimedia applications, there is an increasing need for efficient and effective indexing, storage and retrieval of multimedia data, such as graphics, images, animation, video, audio and text. Due to the special characteristics of the multimedia data, the Multimedia Database management Systems (MMDBMSs) have emerged and attracted great research attention in recent years. Though much research effort has been devoted to this area, it is still far from maturity and there exist many open issues. In this dissertation, with the focus of addressing three of the essential challenges in developing the MMDBMS, namely, semantic gap, perception subjectivity and data organization, a systematic and integrated framework is proposed with video database and image database serving as the testbed. In particular, the framework addresses these challenges separately yet coherently from three main aspects of a MMDBMS: multimedia data representation, indexing and retrieval. In terms of multimedia data representation, the key to address the semantic gap issue is to intelligently and automatically model the mid-level representation and/or semi-semantic descriptors besides the extraction of the low-level media features. The data organization challenge is mainly addressed by the aspect of media indexing where various levels of indexing are required to support the diverse query requirements. In particular, the focus of this study is to facilitate the high-level video indexing by proposing a multimodal event mining framework associated with temporal knowledge discovery approaches. With respect to the perception subjectivity issue, advanced techniques are proposed to support users' interaction and to effectively model users' perception from the feedback at both the image-level and object-level.

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With the recent explosion in the complexity and amount of digital multimedia data, there has been a huge impact on the operations of various organizations in distinct areas, such as government services, education, medical care, business, entertainment, etc. To satisfy the growing demand of multimedia data management systems, an integrated framework called DIMUSE is proposed and deployed for distributed multimedia applications to offer a full scope of multimedia related tools and provide appealing experiences for the users. This research mainly focuses on video database modeling and retrieval by addressing a set of core challenges. First, a comprehensive multimedia database modeling mechanism called Hierarchical Markov Model Mediator (HMMM) is proposed to model high dimensional media data including video objects, low-level visual/audio features, as well as historical access patterns and frequencies. The associated retrieval and ranking algorithms are designed to support not only the general queries, but also the complicated temporal event pattern queries. Second, system training and learning methodologies are incorporated such that user interests are mined efficiently to improve the retrieval performance. Third, video clustering techniques are proposed to continuously increase the searching speed and accuracy by architecting a more efficient multimedia database structure. A distributed video management and retrieval system is designed and implemented to demonstrate the overall performance. The proposed approach is further customized for a mobile-based video retrieval system to solve the perception subjectivity issue by considering individual user's profile. Moreover, to deal with security and privacy issues and concerns in distributed multimedia applications, DIMUSE also incorporates a practical framework called SMARXO, which supports multilevel multimedia security control. SMARXO efficiently combines role-based access control (RBAC), XML and object-relational database management system (ORDBMS) to achieve the target of proficient security control. A distributed multimedia management system named DMMManager (Distributed MultiMedia Manager) is developed with the proposed framework DEMUR; to support multimedia capturing, analysis, retrieval, authoring and presentation in one single framework.

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Since multimedia data, such as images and videos, are way more expressive and informative than ordinary text-based data, people find it more attractive to communicate and express with them. Additionally, with the rising popularity of social networking tools such as Facebook and Twitter, multimedia information retrieval can no longer be considered a solitary task. Rather, people constantly collaborate with one another while searching and retrieving information. But the very cause of the popularity of multimedia data, the huge and different types of information a single data object can carry, makes their management a challenging task. Multimedia data is commonly represented as multidimensional feature vectors and carry high-level semantic information. These two characteristics make them very different from traditional alpha-numeric data. Thus, to try to manage them with frameworks and rationales designed for primitive alpha-numeric data, will be inefficient. An index structure is the backbone of any database management system. It has been seen that index structures present in existing relational database management frameworks cannot handle multimedia data effectively. Thus, in this dissertation, a generalized multidimensional index structure is proposed which accommodates the atypical multidimensional representation and the semantic information carried by different multimedia data seamlessly from within one single framework. Additionally, the dissertation investigates the evolving relationships among multimedia data in a collaborative environment and how such information can help to customize the design of the proposed index structure, when it is used to manage multimedia data in a shared environment. Extensive experiments were conducted to present the usability and better performance of the proposed framework over current state-of-art approaches.

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Forms of interactive multimedia, including CD-ROM, DV-I, Laserdisc, and virtual reality, have given a new perspective to training in many industries. As the hospitality industry and other service industries continue to grow, these forms of technology are becoming of increasing interest as organizations strive to deliver more efficient and effective services to customers and employees

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The advent of smart TVs has reshaped the TV-consumer interaction by combining TVs with mobile-like applications and access to the Internet. However, consumers are still unable to seamlessly interact with the contents being streamed. An example of such limitation is TV shopping, in which a consumer makes a purchase of a product or item displayed in the current TV show. Currently, consumers can only stop the current show and attempt to find a similar item in the Web or an actual store. It would be more convenient if the consumer could interact with the TV to purchase interesting items. ^ Towards the realization of TV shopping, this dissertation proposes a scalable multimedia content processing framework. Two main challenges in TV shopping are addressed: the efficient detection of products in the content stream, and the retrieval of similar products given a consumer-selected product. The proposed framework consists of three components. The first component performs computational and temporal aware multimedia abstraction to select a reduced number of frames that summarize the important information in the video stream. By both reducing the number of frames and taking into account the computational cost of the subsequent detection phase, this component component allows the efficient detection of products in the stream. The second component realizes the detection phase. It executes scalable product detection using multi-cue optimization. Additional information cues are formulated into an optimization problem that allows the detection of complex products, i.e., those that do not have a rigid form and can appear in various poses. After the second component identifies products in the video stream, the consumer can select an interesting one for which similar ones must be located in a product database. To this end, the third component of the framework consists of an efficient, multi-dimensional, tree-based indexing method for multimedia databases. The proposed index mechanism serves as the backbone of the search. Moreover, it is able to efficiently bridge the semantic gap and perception subjectivity issues during the retrieval process to provide more relevant results.^

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The purpose of this study was to investigate the effect of multimedia instruction on achievement of college students in AMH 2010 from exploration and discovery to1865. A non-equivalent control group design was used. The dependent variable was achievement. The independent variables were learning styles method of instruction, and visual clarifiers (notes). The study was conducted using two history sections from Palm Beach Community College, in Boca Raton, Florida, between August and December, 1998. Data were obtained by means of placement scores, posttests, the Productivity Environmental Preference Survey (PEPS), and a researcher-developed student survey. Statistical analysis of the data was done using SPSS statistical software. Demographic variables were compared using Chi square. T tests were run on the posttests to determine the equality of variances. The posttest scores of the groups were compared using the analysis of covariance (ANCOVA) at the .05 level of significance. The first hypothesis there is a significant difference in students' learning of U.S. History when students receive multimedia instruction was supported, F = (1, 52)= 688, p < .0005, and F = (1, 53) = 8.52, p < .005for Tests 2 and 3, respectively. The second hypothesis there is a significant difference on the effectiveness of multimedia instruction based on students' various learning preferences was not supported. The last hypotheses there is a significant difference on students' learning of U.S. History when students whose first language is other than English and students who need remediation receive visual clarifiers were not supported. Analysis of covariance (ANCOVA) indicated no difference between the groups on Test 1, Test 2, or Test 3: F (1, 4 5)= .01, p < .940, F (l, 52) = .77, p < .385, and F (1,53) =.17, p > .678, respectively, for language. Analysis of covariance (ANCOVA) indicated no significant difference on Test 1, Test 2, or Test 3, between the groups on the variable remediation: F (1, 45) = .31, p < .580, F (1, 52) = 1.44, p < .236, and F (1, 53) = .21, p < .645, respectively.

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Este trabalho propõe o estudo comparativo do uso de infográficos multimídia pelos sites Clarín.com, da Argentina e Folha.com, do Brasil. A pesquisa tem como objetivo verificar e analisar como esses dois importantes veículos de comunicação online da América Latina têm utilizado a tecnologia HTML5 para avançar nas possibilidades interativas do gênero jornalístico. Para tanto, a análise comparada trata da infografia multimídia, que tem passado por profundas mudanças tecnológicas, alterando o formato e o conteúdo da notícia. Além da conceituação teórica e revisão de literatura sobre infografia, newsgame, narrativa transmídia, jornalismo online, interatividade e as linguagens de programação voltadas para a produção de infografia multimídia, o trabalho realizou análise comparativa das seções Infográficos, veiculada pela Folha.com, e Especiales Multimedia, do Clarín.com. O estudo, quantitativo e qualitativo, verificou os recursos narrativos e informativos, ferramentas e tecnologias de linguagem de programação para Internet que são empregadas pelos dois meios de comunicação, com base no modelo de análise proposto por Alberto Cairo em Infografia 2.0 – visualización interactiva de información en prensa. A pesquisa demonstrou que ainda que o Clarín.com tenha utilizado a tecnologia Flash na maioria dos infográficos multimídia analisados, os resultados da análise comparada mostram que os infográficos do jornal online argentino possibilitaram níveis mais elevados de interatividade do que os infográficos multimídia da Folha.com, desenvolvidos majoritariamente em HTML5.

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El Servicio de Documentación Multimedia (MULTIDOC 3.0) dependiente de la Sección Departamental/Departamento de Biblioteconomía y Documentación de la Universidad Complutense de Madrid (http://www.multidoc.es) fue creado en junio de 1993. Con patente número M 2202582 registrada con fecha 20.5.1999 en el Boletín Oficial de la Propiedad Industrial (BOPI, 1.7.1999), no ha dejado de desarrollar actividades académico-investigadoras de forma ininterrumpida hasta la actualidad: proyectos de investigación, publicaciones electrónicas, revistas, portales, canales, blogs, presencia en redes sociales generales y especializadas; con actuaciones en todos estos años en el ámbito de la formación, congresos, asociaciones, producción multimedia propia, difusión informativa, gozando de un buen posicionamiento.

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BIBLIORed3.0 es una web universitaria administrada y mantenida en la Universidad Complutense (Servicio Documentación Multimedia del Dpto. Biblioteconomía y Documentación) dedicada a proporcionar información y documentación multimedia en y sobre cine, periodismo, publicidad, radio, televisión, internet-web social y gestión de información en medios de comunicación (documentación informativa) en el ámbito fundamentalmente de archivos, bibliotecas, centros-servicios de documentación y servicios especializados universitarios, en acceso abierto y proyección iberoamericana, en la idea de convertirse en una red social propia. BIBLIORed3.0 dispone de dominio propio en Internet e ISSN 2386-8880 (asignado por BNE-Biblioteca Nacional de España, 26.01.2015).

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La información sobre conceptos de innovación educomunicativa en la web, sobre todo los relacionados con las TIC, suele ser confusa y presentarse de una forma divulgativa inexacta o de una manera científica compleja en artículos largos. Además, suelen utilizarse términos en inglés o en extrañas hibridaciones. Las y los estudiantes –y cualquier persona- que buscan estos términos suelen recurrir a la divulgación inexacta, lo que hace que no comprendan el término en toda su extensión y, por tanto, que los desarrollos que se realizan, tanto teóricos como prácticos, se alejen de la excelencia ya desde su inicio. Conceptos como Branding, Big Data, Force Touch, Gamificación, Geocaching, InRead video, Inroll Video, Interfaz Social, Mobile First, Mooc, Neurocomunicación, Responsive Web Design, Transmedia, Walking Cinema, Walking Documentary, Wayfinding… o no se comprenden o se comprenden sin los matices imprescindibles para un buen desarrollo académico y profesional. Los investigadores del grupo “Museum I+D+C. Laboratorio de cultura digital y museografía hipermedia” de la Universidad Complutense de Madrid, pertenecientes a distintas universidades de Argentina, Brasil, España, México, Colombia, Chile, Ecuador y Reino Unido, coinciden en la necesidad de intentar clarificar esos términos. Queremos animar a cualquier persona que lea estas líneas a participar en el proyecto, bien proponiendo mejoras o aportando nuevos términos.

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Desarrollo de una guía interactiva donde se muestran los ciclos biológicos,imágenes y dibujos de los estadios evolutivos de los principales géneros y especies de parásitos protozoos relevantes en al ámbito veterinario.

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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.