Three-dimensional printed models versus conventional stone models: an accuracy analysis

Aim: To compare the accuracy (trueness and precision) of cost-accessible three-dimensional (3D) printed models. Methods: A maxillary typodont (MM) was scanned and printed 10 times in polylactic acid, resulting in 10 digital models (DMs). Polyvinylsiloxane impressions were made to obtain 10 conventional stone models (SMs). All models were scanned and imported to CloudCompare software. The total area and three locations of interest were evaluated (zenith to incisal [Z-I], canine to canine [C-C], and first molar to canine [1M-C] distances). Total area evaluations were performed by aligning the MM and experimental models using the best-fit algorithm and were compared using the Haussdorf distance. The distances between points of interest were measured using the point-picking tool at the same 3D coordinates. The mean volumetric deviations were considered for trueness analysis. Precision was set as the standard deviation. Statistical differences were evaluated using the Student's t-test. Results:Total area volumetric comparisons showed that DMs showed superior trueness and precision (-0.02 ± 0.03) compared to the SMs (0.37 ± 0.29) (P < 0.001). No differences between the models were observed for Z-I (P = .155); however, SMs showed fewer deviations for C-C (P = .035) and 1M-C (P = .001) than DMs. Conclusions: The DMs presented superior trueness and precision for total area compared to the SMs; however, the SMs were more accurate when points of interest were evaluated

Embedded system in Arduino platform with Fuzzy control to support the grain aeration decision / Sistema embarcado em plataforma Arduino, com controle Fuzzy para suporte a decisão de aeração de grãos

ABSTRACT: Aeration is currently the most commonly used technique to improve the drying and storage of grain, depending on temperature and water content of the grain, as of the temperature and relative humidity of the outside air. In order to monitor temperature and humidity of the grain mass, it is possible to have a network of sensors in the cells of both internal and external storage. Use of artificial intelligence through Fuzzy theory, has been used since the 60s and enables their application on various forms. Thus, it is observed that the aeration of grain in function of representing a system of controlled environment can be studied in relation to the application of this theory. Therefore, the aim of this paper is to present an embedded Fuzzy control system based on the mathematical model of CRUZ et al. (2002) and applied to the Arduino platform, for decision support in aeration of grain. For this, an embedded Arduino system was developed, which received the environmental values of temperature and humidity to then be processed in a Fuzzy controller and return the output as a recommendation to control the aeration process rationally. Comparing the results obtained from the graph presented by LASSERAN (1981) it was observed that the system is effective.

RESUMO: A aeração é a técnica mais utilizada para melhorar a secagem e as condições de armazenamento de grãos, dependendo da temperatura e teor de água do grão, e da temperatura e da umidade relativa do ar externo. O controle da aeração depende do monitoramento da temperatura e da umidade da massa de grãos, podendo-se utilizar uma rede de sensores nas células de armazenamento tanto interna como externamente. A utilização de inteligência artificial pela aplicação da teoria Fuzzy vem sendo utilizada desde a década de 60 e pode ser usada em diversos meios. Assim, observa-se que a aeração de grãos, por ser um sistema de ambiência controlada, pode ser objeto de estudo na aplicação dessa teoria. Diante disso, objetiva-se com este trabalho apresentar um sistema embarcado de controle Fuzzy, baseado no modelo matemático de CRUZ et al. (2002) e aplicados em plataforma Arduino, para suporte a decisão na aeração de grãos. Para tanto, foi desenvolvido um sistema embarcado em Arduino, o qual recebe os valores ambientais: temperatura e umidade para então processar em um controlador Fuzzy e retornar como saída uma recomendação de aeração para controlar o processo de forma racional. Comparando-se os resultados obtidos com o gráfico apresentado por LASSERAN (1981), observasse que o sistema é eficaz.