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Composites with natural lignocellulosic fillers are being cited as a viable and sustainable alternative to conventional materials, as they combine lower costs with lower weight. In many tropical countries, such as Brazil, there is a considerable amount of lignocellulosic waste that is improperly discarded, which causes pollution of the environment. The Amazon region has huge deposits of clay silicate materials in the Negro River basin, such as kaolin, which can be used as fillers in polymeric composite materials. This work investigates a new composite material (ETK) made of epoxy resin (ER), powdered tucumã endocarp (PTE), and kaolin (K), without coupling agents, with the aim of producing a composite with lower environmental impact. The ETK samples, totaling 25 different compositions, were prepared by cold molding. Characterizations of the samples were performed using a scanning electron microscope (SEM) and a Fourier-transform infrared spectrometer (FTIR). In addition, the mechanical properties were determined via tensile, compressive, three-point flexural and impact tests. The FTIR and SEM results showed an interaction between ER, PTE, and K, and the incorporation of PTE and K reduced the mechanical properties of the ETK samples. Nonetheless, these composites can be considered potential materials to be used for sustainable engineering applications in which high mechanical strength is not a main requirement of the material.

Human vision plays a very important role in the perception of the environment, communication and interaction between individuals. Machine vision is increasingly being embedded in electronic devices, as cameras are used with the function of perceiving the environment and identifying the elements inserted in a scene. Real-time image processing and pattern recognition are processing intensive tasks, even with the technology of today. This chapter proposes a vision system that recognizes hand gestures combining motion detection techniques, detection of skin tones, and classification using a model based on the Haar Cascade and CamShift algorithms. The new algorithm presented is 29 % faster than its competitors.

Detecting the age of a document is an important subject for forensic purposes. As the paper ages, its color changes depending on a number of factors such as its original color, storage conditions, environment temperature, humidity, etc. In Brazil, documents such and birth and wedding certificates during the second half of the 20th century used standardized preprinted forms. This paper proposes a model for determining the age of such documents based on the color components of the background of its scanned image.

Very often interested readers highlight documents with felt pens. Such marking may be seen as personal view of the most important aspects of the document, which are used to instantly draw the readers' attention at. This article addresses ways of using the highlighting made by the reader of a book or a paper documents to automatically generate its text summary.