Obtenção e caracterização de um eco-compósito à base de látex e bainha da palha do coqueiro para isolamento térmico e acústico

With the emergence of new technologies, has grown the need to use new materials, and this has intensified research on the collection and use of materials from renewable sources, is to reduce production costs and / or environmental impact. In this context, it was found that the sheath coconut straw, can be utilized as raw material for the production of a eco-composite that can be used as a thermal and acoustic insulator. After selected from the coconut sheaths were subjected to treatment with aqueous 2 % sodium hydroxide (NaOH). The composite study was produced with the sheath and coconut natural latex, with coconut sheath percentage in the proportions 15%, 25% and 35% of the total compound volume. Physical, thermal and acoustic properties of the composites were analyzed in order to obtain data on the use of viability as thermoacoustic insulation. The CP15 composites, CP25 and CP35 showed thermal conductivity 0.188 W/m.K, 0.155 W/m.K and 0.150 W/m.K, respectively. It can be applied as thermal insulation in hot systems to 200 ° C. The CP35 composite was more efficient as a thermal and acoustic insulation, providing 20% noise reduction, 31% and 34% for frequencies of 1 kHz, 2 kHz and 4 kHz, respectively. The analyzes were based on ABNT, ASTM, UL. Based on these results, it can be concluded that the eco-composite produced the hem of coconut can be used as thermal and acoustic insulation. Thus, it gives a more noble end to this material, which most often is burned or disposed of improperly in the environment.

Obtenção e caracterização de um eco-compósito à base de látex e bainha da palha do coqueiro para isolamento térmico e acústico

With the emergence of new technologies, has grown the need to use new materials, and this has intensified research on the collection and use of materials from renewable sources, is to reduce production costs and / or environmental impact. In this context, it was found that the sheath coconut straw, can be utilized as raw material for the production of a eco-composite that can be used as a thermal and acoustic insulator. After selected from the coconut sheaths were subjected to treatment with aqueous 2 % sodium hydroxide (NaOH). The composite study was produced with the sheath and coconut natural latex, with coconut sheath percentage in the proportions 15%, 25% and 35% of the total compound volume. Physical, thermal and acoustic properties of the composites were analyzed in order to obtain data on the use of viability as thermoacoustic insulation. The CP15 composites, CP25 and CP35 showed thermal conductivity 0.188 W/m.K, 0.155 W/m.K and 0.150 W/m.K, respectively. It can be applied as thermal insulation in hot systems to 200 ° C. The CP35 composite was more efficient as a thermal and acoustic insulation, providing 20% noise reduction, 31% and 34% for frequencies of 1 kHz, 2 kHz and 4 kHz, respectively. The analyzes were based on ABNT, ASTM, UL. Based on these results, it can be concluded that the eco-composite produced the hem of coconut can be used as thermal and acoustic insulation. Thus, it gives a more noble end to this material, which most often is burned or disposed of improperly in the environment.

Uma interface para o controle de robôs móveis por intermédio de gestos

The main objective of this work was to enable the recognition of human gestures through the development of a computer program. The program created captures the gestures executed by the user through a camera attached to the computer and sends it to the robot command referring to the gesture. They were interpreted in total ve gestures made by human hand. The software (developed in C ++) widely used the computer vision concepts and open source library OpenCV that directly impact the overall e ciency of the control of mobile robots. The computer vision concepts take into account the use of lters to smooth/blur the image noise reduction, color space to better suit the developer's desktop as well as useful information for manipulating digital images. The OpenCV library was essential in creating the project because it was possible to use various functions/procedures for complete control lters, image borders, image area, the geometric center of borders, exchange of color spaces, convex hull and convexity defect, plus all the necessary means for the characterization of imaged features. During the development of the software was the appearance of several problems, as false positives (noise), underperforming the insertion of various lters with sizes oversized masks, as well as problems arising from the choice of color space for processing human skin tones. However, after the development of seven versions of the control software, it was possible to minimize the occurrence of false positives due to a better use of lters combined with a well-dimensioned mask size (tested at run time) all associated with a programming logic that has been perfected over the construction of the seven versions. After all the development is managed software that met the established requirements. After the completion of the control software, it was observed that the overall e ectiveness of the various programs, highlighting in particular the V programs: 84.75 %, with VI: 93.00 % and VII with: 94.67 % showed that the nal program performed well in interpreting gestures, proving that it was possible the mobile robot control through human gestures without the need for external accessories to give it a better mobility and cost savings for maintain such a system. The great merit of the program was to assist capacity in demystifying the man set/machine therefore uses an easy and intuitive interface for control of mobile robots. Another important feature observed is that to control the mobile robot is not necessary to be close to the same, as to control the equipment is necessary to receive only the address that the Robotino passes to the program via network or Wi-Fi.

Classificação de imagens de ambientes coralinos: uma abordagem empregando uma combinação de classificadores e máquina de vetor de suporte

The use of the maps obtained from remote sensing orbital images submitted to digital processing became fundamental to optimize conservation and monitoring actions of the coral reefs. However, the accuracy reached in the mapping of submerged areas is limited by variation of the water column that degrades the signal received by the orbital sensor and introduces errors in the final result of the classification. The limited capacity of the traditional methods based on conventional statistical techniques to solve the problems related to the inter-classes took the search of alternative strategies in the area of the Computational Intelligence. In this work an ensemble classifiers was built based on the combination of Support Vector Machines and Minimum Distance Classifier with the objective of classifying remotely sensed images of coral reefs ecosystem. The system is composed by three stages, through which the progressive refinement of the classification process happens. The patterns that received an ambiguous classification in a certain stage of the process were revalued in the subsequent stage. The prediction non ambiguous for all the data happened through the reduction or elimination of the false positive. The images were classified into five bottom-types: deep water; under-water corals; inter-tidal corals; algal and sandy bottom. The highest overall accuracy (89%) was obtained from SVM with polynomial kernel. The accuracy of the classified image was compared through the use of error matrix to the results obtained by the application of other classification methods based on a single classifier (neural network and the k-means algorithm). In the final, the comparison of results achieved demonstrated the potential of the ensemble classifiers as a tool of classification of images from submerged areas subject to the noise caused by atmospheric effects and the water column