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.

Calculation of breed direct and maternal genetic fractions and breed specific direct and maternal heterozygosity for crossbreeding data

Teaching, research, and herd breeding applications may require calculation of breed additive contributions for direct and maternal genetic effects and fractions of heterozygosity associated with breed specific direct and maternal heterosis effects. These coefficients can be obtained from the first NB rows of a pseudo numerator relationship matrix where the first NB rows represent fractional contributions by breed to each animal or group representing a specific breed cross. The table begins with an NB x NB identity matrix representing pure breeds. Initial animals or representative crosses must be purebreds or two-breed crosses. Parents of initial purebreds are represented by the corresponding column and initial two-breed cross progeny by the two corresponding columns of the identity matrix. After that, usual rules are used to calculate the NB column entries corresponding to breeds for each animal. The NB entries are fractions of genes expected to be contributed by each of the pure breeds and correspond to the breed additive direct fractions. Entries in the column corresponding to the dam represent breed additive maternal fractions. Breed specific direct heterozygosity coefficients are entries of an NB x NB matrix formed by the outer product of the two NB by 1 columns associated with sire and dam of the animal. One minus sum of the diagonals represents total direct heterozygosity. Similarly, the NB x NB matrix formed by the outer product of columns associated with sire of dam and dam of dam contains breed specific maternal heterozygosity coefficients. These steps can be programmed to create covariates to merge with data. If X represents these coefficients for all unique breed crosses, then the reduced row echelon form function of MATLAB or SAS can be used on X to determine estimable functions of additive breed direct and maternal effects and breed specific direct and maternal heterosis effects

A semi-automatic computerized method to measure baroreflex-mediated heart rate responses that reduces interobserver variability

Arterial baroreflex sensitivity estimated by pharmacological impulse stimuli depends on intrinsic signal variability and usually a subjective choice of blood pressure (BP) and heart rate (HR) values. We propose a semi-automatic method to estimate cardiovascular reflex sensitivity to bolus infusions of phenylephrine and nitroprusside. Beat-to-beat BP and HR time series for male Wistar rats (N = 13) were obtained from the digitized signal (sample frequency = 2 kHz) and analyzed by the proposed method (PRM) developed in Matlab language. In the PRM, time series were low-pass filtered with zero-phase distortion (3rd order Butterworth used in the forward and reverse direction) and presented graphically, and parameters were selected interactively. Differences between basal mean values and peak BP (deltaBP) and HR (deltaHR) values after drug infusions were used to calculate baroreflex sensitivity indexes, defined as the deltaHR/deltaBP ratio. The PRM was compared to the method traditionally (TDM) employed by seven independent observers using files for reflex bradycardia (N = 43) and tachycardia (N = 61). Agreement was assessed by Bland and Altman plots. Dispersion among users, measured as the standard deviation, was higher for TDM for reflex bradycardia (0.60 ± 0.46 vs 0.21 ± 0.26 bpm/mmHg for PRM, P < 0.001) and tachycardia (0.83 ± 0.62 vs 0.28 ± 0.28 bpm/mmHg for PRM, P < 0.001). The advantage of the present method is related to its objectivity, since the routine automatically calculates the desired parameters according to previous software instructions. This is an objective, robust and easy-to-use tool for cardiovascular reflex studies.