988 resultados para visual tools


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This article argues that an indigenous approach to communication research allows us to re-think academic approaches of engaging in and evaluating participatory communication research. It takes as its case study the Komuniti Tok Piksa project undertaken in the Highlands of Papua New Guinea. The project explores ways in which visual methods when paired with a community action approach embedded within an indigenous framework can be used to facilitate social change through meaningful participation. It involves communities to narrate their experiences in regard to HIV and AIDS and assists them in designing and recording their own messages. Local researchers are trained in using visual tools to facilitate this engagement with the communities.

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Synchronous generators are essential components of electric power systems. They are present both in hydro and thermal power plants, performing the function of converting mechanical into electrical energy. This paper presents a visual approach to manipulate parameters that affect operation limits of synchronous generators, using a specifically designed software. The operating characteristics of synchronous generators, for all possible modes of operation, are revised in order to link the concepts to the graphic objects. The approach matches the distance learning tool requirements and also enriches the learning process by developing student trust and understanding of the concepts involved in building synchronous machine capability curves. © 2012 IEEE.

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Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

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Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

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International exhibitions were greatly responsible for the modernization of western society. The motive for these events was based on the possibility of enhancing the country’s international status abroad. The genesis of world exhibitions came from the conviction that humanity as a whole would improve the continual flow of new practical applications, the development of modern communication techniques and the social need for a medium that could acquaint the general public with changes in technology, economy and society .
Since the first national industrial exhibitions in Paris during the eighteenth century and especially starting from the first Great Exhibition in London’s Hyde Park in 1851 these international events spread steadily all over Europe and the United States, to reach Latin America in the beginnings of the twentieth century . The work of professionals such as Daniel Burnham, Werner Hegemann and Elbert Peets made the relation between exhibitions and urban transformation a much more connected one, setting a precedent for subsequent exhibitions.
In Buenos Aires, the celebration of the centennial of independence from Spain in 1910 had many meanings and repercussions. A series of factors allowed for a moment of change in the city. Official optimism, economical progress, inequality and social conflict made of this a suitable time for transformation. With the organization of the Exposición Internacional the government had, among others, one specific aim: to achieve a network of visual tools to set the feeling of belonging and provide an identity for the mixture of cultures that populated the city of Buenos Aires at the time. Another important objective of the government was to put Buenos Aires at the level of European cities.
Foreign professionals had a great influence in the conceptual and factual shaping of the exhibition and in the subsequent changes caused in the urban condition. The exhibition had an important role in the ways of thinking the city and in the leisure ideas it introduced. The exhibition, as a didactic tool, worked as a precedent for conceiving leisure spaces in the future. Urban and landscape planners such as Joseph Bouvard and Charles Thays were instrumental in great part of the design of the Exhibition, but it was not only the architects and designers who shaped the identity of the fair. Other visitors such as Jules Huret or Georges Clemenceau were responsible for giving the city an international image it did not previously have.
This paper will explore on the one hand the significance of the exhibition of 1910 for the shaping of the city and its image; and on the other hand, the role of foreign professionals and the reach these influences had.

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This article considers how visual practices are used to manage knowledge in project-based work. It compares project-based work in a capital goods manufacturer and an architectural firm. Visual representations are used extensively in both cases, but the nature of visual practice differs significantly between the two. The research explores the kinds of knowledge that are (and aren't) developed and made visible in strategizing and planning activities. For example, whereas the emphasis of project-based work in the former firm is on exploitation of knowledge and it visualizes its project context largely in commercial and processual terms, the emphasis in the latter is on exploration and it uses a wide range of visual materials to understand physical interdependencies across the project boundary. We contend particular kinds of visual tools can help project teams step between exploration and exploitation within a project, and articulate the types of representations, foci of attention and patterns of interaction involved. The findings suggest that business managers can make more deliberate choices about how knowledge is made visible, and can change visual practice to align the project with exploring and exploiting opportunities. It raises the question: What don't you see within your organization? The work contributes to academic debates about managing through projects, strategising and organizing, while the focus on visual representation disrupts the tacit-codified dichotomy in the broad debate on knowledge and learning, and highlights the craft skills central to strategizing and organizing.

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Scientists use a range of visual forms to imagine new relations, test ideas and elaborate knowledge, with digital technologies increasingly used to construct elaborate maps, 3D simulations, graphs or enhanced photographs. These visual tools are not simply passive communication devices but actively shape how we build knowledge in science.

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Abstract Background Facilitating the provision of appropriate health care for immigrant and Aboriginal populations in Canada is critical for maximizing health potential and well-being. Numerous reports describe heightened risks of poor maternal and birth outcomes for immigrant and Aboriginal women. Many of these outcomes may relate to food consumption/practices and thus may be obviated through provision of resources which suit the women's ethnocultural preferences. This project aims to understand ethnocultural food and health practices of Aboriginal and immigrant women, and how these intersect with respect to the legacy of Aboriginal colonialism and to the social contexts of cultural adaptation and adjustment of immigrants. The findings will inform the development of visual tools for health promotion by practitioners. Methods/Design This four-phase study employs a case study design allowing for multiple means of data collection and different units of analysis. Phase 1 consists of a scoping review of the literature. Phases 2 and 3 incorporate pictorial representations of food choices (photovoice in Phase 2) with semi-structured photo-elicited interviews (in Phase 3). The findings from Phases 1-3 and consultations with key stakeholders will generate key understandings for Phase 4, the production of culturally appropriate visual tools. For the scoping review, an emerging methodological framework will be utilized in addition to systematic review guidelines. A research librarian will assist with the search strategy and retrieval of literature. For Phases 2 and 3, recruitment of 20-24 women will be facilitated by team member affiliations at perinatal clinics in one of the city's most diverse neighbourhoods. The interviews will reveal culturally normative practices surrounding maternal food choices and consumption, including how women negotiate these practices within their own worldview and experiences. A structured and comprehensive integrated knowledge translation plan has been formulated. Discussion The findings of this study will provide practitioners with an understanding of the cultural differences that affect women's dietary choices during maternity. We expect that the developed resources will be of immediate use within the women's units and will enhance counseling efforts. Wide dissemination of outputs may have a greater long term impact in the primary and secondary prevention of these high risk conditions.

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As ferramentas visuais tem se mostrado eficazes no ensino de química. Essas ferramentas apresentam bases efetivas para a compreensão da química em seus três modos de representação (macroscópico, submicroscópico e simbólico). Apesar da importância da utilização destas ferramentas, muitos professores não estão preparados para sua utilização em sala de aula. Diante disso, surge a necessidade de formar professores com capacidades para criar metodologias que abordem as ferramentas visuais, pois estas podem facilitar o desenvolvimento da habilidade de interpretação de representações pelos estudantes. Esta pesquisa possui o objetivo de investigar se os bolsistas PIBID de química da USP, após atividades formativas, apresentaram em suas produções didáticas atividades que possuam indícios dos fatores que remetem ao desenvolvimento da habilidade representacional e se estas produções apresentam uma elevada exigência conceitual. A coleta de dados foi realizada por um acompanhamento da formação inicial a qual os bolsistas PIBID participaram. Após a formação os bolsistas acompanharam as aulas de química de uma escola da cidade de São Paulo. Durante este período os bolsistas planejaram aulas a serem aplicadas na escola. Ao final de todo o processo, os bolsistas PIBID redigiram um relatório contendo o que foi abordado, suas observações e avaliações das aulas. A análise do desenvolvimento da habilidade de interpretação de representações foi realizada através de uma metodologia qualitativa, na qual foram utilizados trechos dos relatórios que se enquadrassem ao modelo CRM, adaptado de Schonborn e Anderson (2009). Como foi observado que os bolsistas PIBID utilizaram diversos dos fatores do modelo CRM em suas produções didáticas, foi realizada uma análise para averiguar se estas produções também continham elevada exigência conceitual. O cálculo do nível de exigência conceitual foi realizado abordando uma metodologia mista, que envolve o método quantitativo e qualitativo. O cálculo mostrou que os relatórios apresentaram satisfatório nível de exigência conceitual. Com a análise foi possível concluir que esta pesquisa pode contribuir para a reflexão sobre a importância da formação de professores para o ensino de química/ciências, e ainda traz um modelo que pode servir como embasamento para que professores planejem suas aulas do modo a abordar a habilidade de interpretação de representações, que é fundamental para compreensão da química pelos estudantes.

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This exhibition was a research presentation of works made at Center for Land Use Interpretation [CLUI]base in Wendover, Utah, USA between 2008-2010. The project was commissioned by the Centre For Land Interpretation in USA and funded by The Henry Moore Foundation in the UK. Documentation of research conducted in the field as made available as video and installation. An experimental discourse on the preservation of land art was put with GPS drawings and research information displayed as maps and documents. In examining physical sites in Utah, USA, the project connected to contemporary discourse centred on archives in relation to land art and land use. Using experimental processes conceived in relation to key concepts such as event structures and entropy, conceptual frameworks developed by Robert Smithson (USA) and John Latham (UK), the 'death drive' of the archive was examined in the context of a cultural impulse to preserve iconic works. The work took items from Lathams archive and placed them at the canonical 'Spiral Jetty', Smithson land art work at Rozel Point north of Salt Lake City. This became a focus for the project that also highlighted the role of the Getty Foundation in documenting major public artworks and CLUI in creating an American Land Museum. Work was created in the field at extreme remote locations using GPS technologies and visual tools were developed to articulate the concepts of the artists discussed, to engage the exhibition audience in ideas of transformation and entropy in art. Audiences were encouraged to sign a petition to be used in future preservation of spiral jetty currently facing development challenges.

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Domain-specific visual languages support high-level modeling for a wide range of application domains. However, building tools to support such languages is very challenging. We describe a set of key conceptual requirements for such tools and our approach to addressing these requirements, a set of visual language-based metatools. These support definition of metamodels, visual notations, views, modeling behaviors, design critics, and model transformations and provide a platform to realize target visual modeling tools. Extensions support collaborative work, human-centric tool interaction, and multiplatform deployment. We illustrate application of the metatoolset on tools developed with our approach. We describe tool developer and cognitive evaluations of our platform and our exemplar tools, and summarize key future research directions.

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Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A < AV > V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis.