Mapeamento digital de áreas suscetíveis a escorregamento na parte continental do município de Angra dos Reis, RJ.

O presente trabalho tem como objetivo analisar a classificação resultante do emprego da Avaliação de Multicritérios, utilizando a técnica AHP (Analytic Hierarchy Process), em ambiente SIG, para o mapeamento de áreas suscetíveis à escorregamento no município de Angra dos Reis. O estudo exigiu duas imagens Landsat 7 TM, obtidas respectivamente em 14/08/2006 e 17/06/2005. O produto gerado será comparado com os dados já existentes disponibilizados pela Defesa Civil do município, servindo de auxílio às ações no processo de gestão territorial, dando suporte ao planejamento e execução de projetos ambientais e de engenharia e apoio a tomadas de decisões governamentais, evitando novos desastres como os ocorridos em 31/12/2009 e 01/01/2010.

Tudo isso é inovação: mediação e criatividade no encontro entre o designer e as artesãs

O objetivo deste trabalho trata-se de explorar o papel do designer quando em relação à contextos de produção artesanal, partindo de pesquisa etnográfica realizada em uma oficina de design, conduzida por Lars Diederichsen, para as artesãs da Cooperativa Lã Pura. Inserida no programa Talentos do Brasil, do Ministério do Desenvolvimento Agrário, a oficina de design tem como propósito a geração de novos produtos para a cooperativa e configura-se como a visita de um designer ao grupo. As bases teóricas para a análise das relações entre o designer e artesãs estão amparadas no conceito de mediação (Velho, 2001; 2003). Ao relacionarem-se esses sujeitos negociam seus projetos, transitam entre diversos domínios e reconstroem as suas realidades e a si mesmos, criando e recriando as suas identidades como mulheres artesãs e como designer, contribuindo para a conceituação do que significa ser mulher artesã e ser designer. Ao mesmo tempo, a ideia de criatividade permeia todo o processo da oficina de design, tendo sido problematizada a partir de Ingold e Hallam (2007) que sugerem os conceitos de inovação e improvisação.

USE OF TSIM IN DIGITAL SIMULATION.

In this paper we shall discuss the use of the TSIM simulation software for modelling large-scale industrial processes. The discussion draws on our recent experience of modelling a large plant in the food-processing industry. We shall focus on those features of software organization and software engineering which proved to be particularly necessary for the execution of this project, and illustrate the extent to which the use of TISM facilitated the implementation of these features. We shall also make some general remarks about the 'life-cycle' of models resulting from projects of this kind.

Identification of Materials from Construction Site Images Using Content Based Image Retrieval Techniques

The capability to automatically identify shapes, objects and materials from the image content through direct and indirect methodologies has enabled the development of several civil engineering related applications that assist in the design, construction and maintenance of construction projects. Examples include surface cracks detection, assessment of fire-damaged mortar, fatigue evaluation of asphalt mixes, aggregate shape measurements, velocimentry, vehicles detection, pore size distribution in geotextiles, damage detection and others. This capability is a product of the technological breakthroughs in the area of Image and Video Processing that has allowed for the development of a large number of digital imaging applications in all industries ranging from the well established medical diagnostic tools (magnetic resonance imaging, spectroscopy and nuclear medical imaging) to image searching mechanisms (image matching, content based image retrieval). Content based image retrieval techniques can also assist in the automated recognition of materials in construction site images and thus enable the development of reliable methods for image classification and retrieval. The amount of original imaging information produced yearly in the construction industry during the last decade has experienced a tremendous growth. Digital cameras and image databases are gradually replacing traditional photography while owners demand complete site photograph logs and engineers store thousands of images for each project to use in a number of construction management tasks. However, construction companies tend to store images without following any standardized indexing protocols, thus making the manual searching and retrieval a tedious and time-consuming effort. Alternatively, material and object identification techniques can be used for the development of automated, content based, construction site image retrieval methodology. These methods can utilize automatic material or object based indexing to remove the user from the time-consuming and tedious manual classification process. In this paper, a novel material identification methodology is presented. This method utilizes content based image retrieval concepts to match known material samples with material clusters within the image content. The results demonstrate the suitability of this methodology for construction site image retrieval purposes and reveal the capability of existing image processing technologies to accurately identify a wealth of materials from construction site images.

Shape Recognition of Linear Construction Entities from Construction Site Images

The capability to automatically identify shapes, objects and materials from the image content through direct and indirect methodologies has enabled the development of several civil engineering related applications that assist in the design, construction and maintenance of construction projects. This capability is a product of the technological breakthroughs in the area of Image Processing that has allowed for the development of a large number of digital imaging applications in all industries. In this paper, an automated and content based shape recognition model is presented. This model was devised to enhance the recognition capabilities of our existing material based image retrieval model. The shape recognition model is based on clustering techniques, and specifically those related with material and object segmentation. The model detects the borders of each previously detected material depicted in the image, examines its linearity (length/width ratio) and detects its orientation (horizontal/vertical). The results emonstrate the suitability of this model for construction site image retrieval purposes and reveal the capability of existing clustering technologies to accurately identify the shape of a wealth of materials from construction site images.