Use Of Linear Regression Techniques Research Articles

Output Error Methods for Robot Identification

Abstract Industrial robot identification is usually based on the inverse dynamic identification model (IDIM) that comes from Newton's laws and has the advantage of being linear with respect to the parameters. Building the IDIM from the measurement signals allows the use of linear regression techniques like the least-squares (LS) or the instrumental variable (IV) for instance. Nonetheless, this involves a careful preprocessing to deal with sensor noise. An alternative in system identification is to consider an output error approach where the model's parameters are iteratively tuned in order to match the simulated model's output and the measured system's output. This paper proposes an extensive comparison of three different output error approaches in the context of robot identification. One of the main outcomes of this work is to show that choosing the input torque as target identification signal instead of the output position may lead to a gain in robustness versus modeling errors and noise and in computational time. Theoretical developments are illustrated on a six degrees-of-freedom rigid robot.

Winter Season Analysis of Global Warming Impact on Sivas Province

The climate has undergone various levels of change since the existence of the Earth. With the industrial Resolution, humankind has begun to be influential in climate change. Industrial revolution lead to unsteady greenhouse gases emissions that led to the global warming and consequent climate change impacts at different scales in various regions of the world. Accordingly, the seasonal periods started to change especially for seasons of Spring and Fall and consequently undesirable changes in the natural events started to occur such as excessive rain, outdoor temperatures above seasonal normal levels. Nowadays, global climate change is one of the most significant problems that mankind has to front with respect to its results. Due to global warming the Turkish province of Sivas is in a sensitive position because of its location. In this study, Sivas province is studied in terms of monthly and seasonal temperature trends. The temperature trends are analyzed by the use of linear regression techniques and the results indicate a significant rise in temperature trends.

Modeling the leadership – project performance relation: radial basis function, Gaussian and Kriging methods as alternatives to linear regression

The purpose of this paper is to analyze alternative forecasting methods that produce results at least similar to or better than linear regression (MLR) that can be used in the modeling of social systems. While organizations may be considered as typically non-linear systems, the common feature of most models found in literature continues to be the use of linear regression techniques. From a case study, advanced statistical methods of Gaussian and Kriging are evaluated, as well as an artificial intelligence (AI) tool, the radial basis function (RBF). The results show the best performance of the suggested methods compared to MLR, especially RBF, because of its uniform prediction behavior throughout all ranges of evaluation. These techniques, although somewhat unconventional in social systems modeling, present a potential contribution in increasing the accuracy and precision of the predictions allowing a more accurate assessment of the impact of certain strategies on the project performance to be made before the allocation of material, human and financial resources.

Ball-Sport Endurance and Sprint Test (BEAST90): Validity and Reliability of a 90-Minute Soccer Performance Test

The aim of this study was to determine the validity and reliability of a 90-minute soccer performance test: Ball-sport Endurance and Sprint Test (BEAST90). Fifteen healthy male amateur soccer players participated and attended 5 testing sessions over a 10-day period to perform physiologic and soccer-specific assessments. This included familiarization sessions and 2 full trials of the BEAST90, separated by 7 days. The total 90-minute distance, mean percent peak heart rate (HRpeak), and estimated percent peak oxygen uptake of the BEAST90 were 8,097 ± 458 m, 85 ± 5% and 82 ± 14%, respectively. Measures obtained from trial 1 and trial 2 were not significantly different (p > 0.05). Reliability of measures over 90 minutes ranged from 0.9-25.5% (% typical error). The BEAST90 protocol replicated soccer match play in terms of time, movement patterns, physical demands (volume and intensity), distances, and mean and HRpeak values, as well as having an aerobic load similar to that observed during a soccer match. Reproducibility of key physical measures during the BEAST90 were mostly high, suggesting good reliability. The BEAST90 could be used in studies that wish to determine the effects of training or nutritional interventions on prolonged intermittent physical performance.

Investigações psicológicas no ciberespaço: desenvolvendo modelos preditivos sobre a adesão às crenças ufológicas

O objetivo do presente artigo procura é desenvolver, mediante o uso da regressão linear, modelos estatísticos capazes de isolar e avaliar o impacto de uma série de variáveis independentes – interesse pelo assunto, filiação a grupos ufológicos e grau de conhecimento – sobre o grau de adesão às crenças ufológicas e, em seguida, partir da modelagem de equação estrutural, elaborar modelos explicativos capazes de se ajustar aos dados obtidos em uma pesquisa empírica sobre as crenças ufológicas e os extraterrestres. Os resultados obtidos pela regressão linear indicaram que os modelos elaborados possuem um poder preditivo relativamente alto e uma qualidade bastante aceitável, a se considerar os índices de ajustamento da equação estrutural, que apresentaram valores bastante toleráveis para estudos conduzidos nos domínios das ciências comportamentais. Finalmente, foram apresentadas algumas implicações destes modelos para a pesquisa psicossocial sobre as crenças, em especial sobre as crenças ufológicas.Palavras-chave: crenças; crenças compartilhadas; ufologia.

Sequential V(A)/Q distributions in the normal rabbit by micropore membrane inlet mass spectrometry.

We developed micropore membrane inlet mass spectrometer (MMIMS) probes to rapidly measure inert-gas partial pressures in small blood samples. The mass spectrometer output was linearly related to inert-gas partial pressure (r(2) of 0.996-1.000) and was nearly independent of large variations in inert-gas solubility in liquid samples. We infused six inert gases into five pentobarbital-anesthetized New Zealand rabbits and used the MMIMS system to measure inert-gas partial pressures in systemic and pulmonary arterial blood and in mixed expired gas samples. The retention and excretion data were transformed into distributions of ventilation-to-perfusion ratios (V(A)/Q) with the use of linear regression techniques. Distributions of V(A)/Q were unimodal and broad, consistent with prior reports in the normal rabbit. Total blood sample volume for each VA/Q distribution was 4 ml, and analysis time was 8 min. MMIMS provides a convenient method to perform the multiple inert-gas elimination technique rapidly and with small blood sample volumes.

About the use of rank transformation in sensitivity analysis of model output

Rank transformations are frequently employed in numerical experiments involving a computational model, especially in the context of sensitivity and uncertainty analyses. Response surface replacement and parameter screening are tasks which may benefit from a rank transformation. Ranks can cope with nonlinear (albeit monotonic) input-output distributions, allowing the use of linear regression techniques. Rank transformed statistics are more robust, and provide a useful solution in the presence of long tailed input and output distributions. As is known to practitioners, care must be employed when interpreting the results of such analyses, as any conclusion drawn using ranks does not translate easily to the original model. In the present note an heuristic approach is taken, to explore, by way of practical examples, the effect of a rank transformation on the outcome of a sensitivity analysis. An attempt is made to identify trends, and to correlate these effects to a model taxonomy. Employing sensitivity indices, whereby the total variance of the model output is decomposed into a sum of terms of increasing dimensionality, we show that the main effect of the rank transformation is to increase the relative weight of the first order terms (the ‘main effects’), at the expense of the ‘interactions’ and ‘higher order interactions’. As a result the influence of those parameters which influence the output mostly by way of interactions may be overlooked in an analysis based on the ranks. This difficulty increases with the dimensionality of the problem, and may lead to the failure of a rank based sensitivity analysis. We suggest that the models can be ranked, with respect to the complexity of their input-output relationship, by mean of an ‘Association’ index I y. I y may complement the usual model coefficient of determination R y 2 as a measure of model complexity for the purpose of uncertainty and sensitivity analysis.

Relations between the prevailing visibility, nephelometer scattering coefficient and sunphotometer turbidity coefficient

Empirical relations between the visibility, nephelometer scattering coefficient and turbidity coefficients were obtained from nephelometer and sunphotometer measurements taken at the Research Triangle Park, North Carolina and the Raleigh-Durham Airport hourly prevailing visibility observations. The data spanned the period between 1972 and 1976. Using graphical techniques, the relation between the visibility V and the nephelometer scattering coefficient b was determined to be V = Ab −1 with acceptable values of A ranging between 1.5 and 2.3. Various formulae relating the visibility V and the decadic turbidity coefficient B( λ) for wavelengths λ of 380 and 500 nm to the nephelometer scattering coefficient b were obtained by the use of linear regression techniques. Averaging the set of b −1 observed for each V, a correlation coefficient of essentially unity was obtained for each year. A relation between V and b −1, for the same period as the above graphical relation, was determined to be V = 1.7 b −1. A correlation coefficient of approximately 0.8 was obtained for B( λ) and the nephelometer aerosol scattering coefficient b' (nephelometer scattering coefficient minus Rayleigh scattering coefficient). For the total time period, the relations B( λ) = gs( λ) + β( λ) b' where σ(500) = 0.054; β(500) = 1.1 km and σ(380) = 0.064; β(380) = 1.6 km were obtained.