Experimento utilizando grãos para explorar a calibração em análises químicas

The conventional curriculum of Analytical Chemistry undergraduate courses emphasizes the introduction of techniques, methods and procedures used for instrumental analysis. All these concepts must be integrated into a sound conceptual framework to allow students to make appropriate decisions. Method calibration is one of the most critical parameters that has to be grasped since most analytical techniques depend on it for quantitative analysis. The conceptual understanding of calibration is not trivial for undergraduate students. External calibration is widely discussed during instrumental analysis courses. However, the understanding of the limitations of external calibration to correct some systematic errors is not directly derived from laboratory examples. The conceptual understanding of other calibration methods (standard addition, matrix matching, and internal standard) is imperative. The aim of this work is to present a simple experiment using grains (beans, corn and chickpeas) to explore different types of calibration methods.

Performance evaluation of 3D computer vision techniques

This work presents the implementation and comparison of three different techniques of three-dimensional computer vision as follows: • Stereo vision - correlation between two 2D images • Sensorial fusion - use of different sensors: camera 2D + ultrasound sensor (1D); • Structured light The computer vision techniques herein presented took into consideration the following characteristics: • Computational effort ( elapsed time for obtain the 3D information); • Influence of environmental conditions (noise due to a non uniform lighting, overlighting and shades); • The cost of the infrastructure for each technique; • Analysis of uncertainties, precision and accuracy. The option of using the Matlab software, version 5.1, for algorithm implementation of the three techniques was due to the simplicity of their commands, programming and debugging. Besides, this software is well known and used by the academic community, allowing the results of this work to be obtained and verified. Examples of three-dimensional vision applied to robotic assembling tasks ("pick-and-place") are presented.