scholarly journals The Effects of Visual Feedback on Performance in Heart Rate- and Power-Based-Tasks during a Constant Load Cycling Test

2021 ◽  
pp. 49-57
Author(s):  
Martin Dobiasch ◽  
Björn Krenn ◽  
Robert P. Lamberts ◽  
Arnold Baca
Keyword(s):  
Heart Rate ◽  
Root Mean Square Error ◽  
Performance Feedback ◽  
Constant Load ◽  
Performance Tests ◽  
The Novel ◽  
Mean Square ◽  
Novel Variants ◽  
Load Cycling ◽  
Lower Root

Performance feedback can be essential for cyclists to help with pacing their efforts during competitions and also during standardized performance tests. However, the choice of feedback options on modern bike computers is limited. Moreover, little research on the effectiveness of the currently used feedback methods is available. In this study, two novel feedback variants using a bar or a tacho to visualize targets and deviation from targets were compared to a classic design using only numbers. Participants (6 female and 25 male trained to well-trained athletes) completed a protocol consisting of three heart rate-based tasks and one power-based task. The displays were compared with respect to their ability to guide athletes during their trials. Results showed lower root mean square error (RMSE) of the novel variants, but no significant effect of feedback variant on RMSE was found for both tasks (p > 0.05). However, when comparing the feedback variants on a person to person basis, significant differences were found for all investigated scenarios (p < 0.001). This leads to the conclusion that novel feedback variants can improve athletes’ ability to follow heart rate-based and power-based protocols, but even better results might be achieved by individualizing the feedback.

The Results of the Sub-Pixel Efficacy Region Based Bivariate Linear Interpolation Function

2009 ◽  
pp. 72-170
Author(s):  
Carlo Ciulla
Keyword(s):  
Root Mean Square Error ◽  
Coordinate System ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Linear Interpolation ◽  
Sampling Location ◽  
The Novel ◽  
Interpolation Function ◽  
Mean Square ◽  
Lower Root

This is the first of the chapters of the book that present results obtained processing the MRI database with both classic and SRE-based interpolation paradigms. The focus of this chapter is on the bivariate linear interpolation function. An overview on the validation paradigm is given along with an explanation of the simulations that were conducted in order to validate the SRE-based bivariate liner interpolation function. Subsequently, results with real MRI are shown quantitatively through plots of the metric called RMSE Ratio which was employed to assess which one between classic and SRE-based interpolation furnishes lower root-mean-square-error (RMSE). Qualitative demonstration of the results with MRI is also given. The chapter also discusses and evaluates the case of interpolation error improvement when the novel re-sampling location within the pixel is placed on the x axis of the coordinate system (i.e. yr0 = 0) and consistently, both quantitative and qualitative results are presented through plots of the RSME Ratio and figures respectively.

scholarly journals Relationships between Thoroughbreds’ Contribution in the Pedigree and the Level of Fearfulness and Performance in Warmblood Stallions

2018 ◽  
Vol 68 (3) ◽  
pp. 288-300 ◽  
Author(s):  
Budzyńska Monika ◽  
Kamieniak Jarosław ◽  
Marciniak Beata ◽  
Sołtys Leszek
Keyword(s):  
Heart Rate ◽  
Performance Tests ◽  
The Novel ◽  
Novel Object ◽  
Percentage Contribution ◽  
Object Based ◽  
Novel Objects ◽  
Potential Factor ◽  
And Performance ◽  
Fear Reactivity

Abstract The aim of this study was to test the hypothesis that Thoroughbred (TB) ancestors blood percentage in a pedigree is a potential factor differentiating the level of fearfulness (based on behavior and heart rate (HR)) and performance scores in warmblood stallions. A total of 267 three-year-old warmblood stallions were subjected to the novel-object based test during their participation in the performance tests’ program. The effect of ancestors percentage contribution in the pedigree was analyzed by taking into account horses of four TB (<25.01, 25.01-50.00, 50.01-75.00, >75.00%) ancestor groups. It was found that the stallions with a higher proportion (>75.00%) of TB blood revealed higher values of HR measured at the riding hall just before the start of the fearfulness test. The results showed that the higher proportions of TB ancestors blood in the stallions’ pedigree were correlated with the higher values for total time to pass novel objects when led by a handler during the fearfulness test. Negative correlations were found between the TB percentage and the scores for character and trot evaluated by the trainer as well as rideability evaluated by the test rider. The fi ndings imply that a high proportion of Thoroughbreds in the pedigree may negatively infl uence some performance traits and increase fear reactivity in warmblood stallions.

Quantitative Analysis of Mixtures Using Terahertz Time-Domain Spectroscopy and Different PLS Algorithms

2013 ◽  
Vol 804 ◽  
pp. 23-28 ◽  
Author(s):  
Tao Chen ◽  
Zhi Li ◽  
Fang Rong Hu ◽  
Wei Mo
Keyword(s):  
Quantitative Analysis ◽  
Root Mean Square Error ◽  
Mean Square Error ◽  
Time Domain ◽  
Ternary Mixtures ◽  
Mean Square ◽  
Multicomponent Mixtures ◽  
Terahertz Time Domain Spectroscopy ◽  
Lower Root ◽  
Anhydrous Theophylline

This paper attempted the feasibility to determine component concentrations in multicomponent mixtures with terahertz time-domain spectroscopy (THz-TDS) combined with different partial least-squares regression (PLS) algorithms. First, THz absorbance spectra for 75 ternary mixtures of anhydrous theophylline, lactose monohydrate and magnesium stearate were investigated using THz-TDS in the frequency range from 0.1 to 3.0 THz, then four different PLS methods, including interval PLS (iPLS), backward interval PLS (biPLS), synergy interval PLS (siPLS) and moving window PLS (mwPLS), were employed to perform quantitative analysis of anhydrous theophylline concentrations in ternary mixtures. The performance of mwPLS model is the best in contrast to other PLS models and full spectrum PLS. The optimal model was achieved with higher correlation coefficient for calibration (RC) of 0.9842, higher correlation coefficient for prediction (RP) of 0.9851, lower root mean square error of cross-validation (RMSECV) of 3.8241, and lower root mean square error of prediction (RMSEP) of 4.1540. Experimental results demonstrate that THz spectroscopy combined with PLS algorithms could be successfully applied as an effective nondestructive tool for the quantitative analysis of component concentrations in multicomponent mixtures, and mwPLS is an ideal method for reducing the complexity and improving the performance of the model.

scholarly journals Estimation of Apple Flowering Frost Loss for Fruit Yield Based on Gridded Meteorological and Remote Sensing Data in Luochuan, Shaanxi Province, China

2021 ◽  
Vol 13 (9) ◽  
pp. 1630
Author(s):  
Yaohui Zhu ◽  
Guijun Yang ◽  
Hao Yang ◽  
Fa Zhao ◽  
Shaoyu Han ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Minimum Temperature ◽  
Price Regulation ◽  
Flowering Period ◽  
Mean Square ◽  
Prevention Measures ◽  
Agricultural Insurance

With the increase in the frequency of extreme weather events in recent years, apple growing areas in the Loess Plateau frequently encounter frost during flowering. Accurately assessing the frost loss in orchards during the flowering period is of great significance for optimizing disaster prevention measures, market apple price regulation, agricultural insurance, and government subsidy programs. The previous research on orchard frost disasters is mainly focused on early risk warning. Therefore, to effectively quantify orchard frost loss, this paper proposes a frost loss assessment model constructed using meteorological and remote sensing information and applies this model to the regional-scale assessment of orchard fruit loss after frost. As an example, this article examines a frost event that occurred during the apple flowering period in Luochuan County, Northwestern China, on 17 April 2020. A multivariable linear regression (MLR) model was constructed based on the orchard planting years, the number of flowering days, and the chill accumulation before frost, as well as the minimum temperature and daily temperature difference on the day of frost. Then, the model simulation accuracy was verified using the leave-one-out cross-validation (LOOCV) method, and the coefficient of determination (R2), the root mean square error (RMSE), and the normalized root mean square error (NRMSE) were 0.69, 18.76%, and 18.76%, respectively. Additionally, the extended Fourier amplitude sensitivity test (EFAST) method was used for the sensitivity analysis of the model parameters. The results show that the simulated apple orchard fruit number reduction ratio is highly sensitive to the minimum temperature on the day of frost, and the chill accumulation and planting years before the frost, with sensitivity values of ≥0.74, ≥0.25, and ≥0.15, respectively. This research can not only assist governments in optimizing traditional orchard frost prevention measures and market price regulation but can also provide a reference for agricultural insurance companies to formulate plans for compensation after frost.

scholarly journals Whole-Genome Sequence Analysis of Pseudorabies Virus Clinical Isolates from Pigs in China between 2012 and 2017 in China

Viruses ◽  
2021 ◽  
Vol 13 (7) ◽  
pp. 1322
Author(s):  
Ruiming Hu ◽  
Leyi Wang ◽  
Qingyun Liu ◽  
Lin Hua ◽  
Xi Huang ◽  
...  
Keyword(s):  
Selection Pressure ◽  
Pseudorabies Virus ◽  
Viral Evolution ◽  
Infectious Agent ◽  
Genomic Diversity ◽  
Whole Genome Sequence ◽  
Evolutionary Constraint ◽  
The Novel ◽  
Novel Variants ◽  
Pressure Analysis

Pseudorabies virus (PRV) is an economically significant swine infectious agent. A PRV outbreak took place in China in 2011 with novel virulent variants. Although the association of viral genomic variability with pathogenicity is not fully confirmed, the knowledge concerning PRV genomic diversity and evolution is still limited. Here, we sequenced 54 genomes of novel PRV variants isolated in China from 2012 to 2017. Phylogenetic analysis revealed that China strains and US/Europe strains were classified into two separate genotypes. PRV strains isolated from 2012 to 2017 in China are highly related to each other and genetically close to classic China strains such as Ea, Fa, and SC. RDP analysis revealed 23 recombination events within novel PRV variants, indicating that recombination contributes significantly to the viral evolution. The selection pressure analysis indicated that most ORFs were under evolutionary constraint, and 19 amino acid residue sites in 15 ORFs were identified under positive selection. Additionally, 37 unique mutations were identified in 19 ORFs, which distinguish the novel variants from classic strains. Overall, our study suggested that novel PRV variants might evolve from classical PRV strains through point mutation and recombination mechanisms.

scholarly journals Low Cost Automatic Reconstruction of Tree Structure by AdQSM with Terrestrial Close-Range Photogrammetry

Forests ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1020
Author(s):  
Yanqi Dong ◽  
Guangpeng Fan ◽  
Zhiwu Zhou ◽  
Jincheng Liu ◽  
Yongguo Wang ◽  
...  
Keyword(s):  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Low Cost ◽  
Reference Value ◽  
Tree Height ◽  
Point Clouds ◽  
Tree Structure ◽  
Mean Square ◽  
Tree Model

The quantitative structure model (QSM) contains the branch geometry and attributes of the tree. AdQSM is a new, accurate, and detailed tree QSM. In this paper, an automatic modeling method based on AdQSM is developed, and a low-cost technical scheme of tree structure modeling is provided, so that AdQSM can be freely used by more people. First, we used two digital cameras to collect two-dimensional (2D) photos of trees and generated three-dimensional (3D) point clouds of plot and segmented individual tree from the plot point clouds. Then a new QSM-AdQSM was used to construct tree model from point clouds of 44 trees. Finally, to verify the effectiveness of our method, the diameter at breast height (DBH), tree height, and trunk volume were derived from the reconstructed tree model. These parameters extracted from AdQSM were compared with the reference values from forest inventory. For the DBH, the relative bias (rBias), root mean square error (RMSE), and coefficient of variation of root mean square error (rRMSE) were 4.26%, 1.93 cm, and 6.60%. For the tree height, the rBias, RMSE, and rRMSE were—10.86%, 1.67 m, and 12.34%. The determination coefficient (R2) of DBH and tree height estimated by AdQSM and the reference value were 0.94 and 0.86. We used the trunk volume calculated by the allometric equation as a reference value to test the accuracy of AdQSM. The trunk volume was estimated based on AdQSM, and its bias was 0.07066 m3, rBias was 18.73%, RMSE was 0.12369 m3, rRMSE was 32.78%. To better evaluate the accuracy of QSM’s reconstruction of the trunk volume, we compared AdQSM and TreeQSM in the same dataset. The bias of the trunk volume estimated based on TreeQSM was −0.05071 m3, and the rBias was −13.44%, RMSE was 0.13267 m3, rRMSE was 35.16%. At 95% confidence interval level, the concordance correlation coefficient (CCC = 0.77) of the agreement between the estimated tree trunk volume of AdQSM and the reference value was greater than that of TreeQSM (CCC = 0.60). The significance of this research is as follows: (1) The automatic modeling method based on AdQSM is developed, which expands the application scope of AdQSM; (2) provide low-cost photogrammetric point cloud as the input data of AdQSM; (3) explore the potential of AdQSM to reconstruct forest terrestrial photogrammetric point clouds.

scholarly journals Rapid Biochemical Methane Potential Evaluation of Anaerobic Co-Digestion Feedstocks Based on Near Infrared Spectroscopy and Chemometrics

Energies ◽  
2021 ◽  
Vol 14 (5) ◽  
pp. 1460
Author(s):  
Jinming Liu ◽  
Changhao Zeng ◽  
Na Wang ◽  
Jianfei Shi ◽  
Bo Zhang ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Variable Selection ◽  
Root Mean Square Error ◽  
Least Squares ◽  
Mean Square Error ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Mean Square ◽  
Biochemical Methane Potential ◽  
Methane Potential

Biochemical methane potential (BMP) of anaerobic co-digestion (co-AD) feedstocks is an essential basis for optimizing ratios of materials. Given the time-consuming shortage of conventional BMP tests, a rapid estimated method was proposed for BMP of co-AD—with straw and feces as feedstocks—based on near infrared spectroscopy (NIRS) combined with chemometrics. Partial least squares with several variable selection algorithms were used for establishing calibration models. Variable selection methods were constructed by the genetic simulated annealing algorithm (GSA) combined with interval partial least squares (iPLS), synergy iPLS, backward iPLS, and competitive adaptive reweighted sampling (CARS), respectively. By comparing the modeling performances of characteristic wavelengths selected by different algorithms, it was found that the model constructed using 57 characteristic wavelengths selected by CARS-GSA had the best prediction accuracy. For the validation set, the determination coefficient, root mean square error and relative root mean square error of the CARS-GSA model were 0.984, 6.293 and 2.600, respectively. The result shows that the NIRS regression model—constructed with characteristic wavelengths, selected by CARS-GSA—can meet actual detection requirements. Based on a large number of samples collected, the method proposed in this study can realize the rapid and accurate determination of the BMP for co-AD raw materials in biogas engineering.

scholarly journals A Trigonometric Projection Method for Overcoming High Intensity Heart Rate Caused Waveform Deformation in Electrocardiogram Biometrics

2021 ◽  
Author(s):  
Tsu-Wang Shen ◽  
Shan-Chun Chang
Keyword(s):  
Heart Rate ◽  
High Intensity ◽  
Correlation Coefficients ◽  
Calibration Method ◽  
Mean Square ◽  
Biometric Technology ◽  
Overall Performance ◽  
Electrocardiogram Signal ◽  
Mean Square Difference ◽  
Electrocardiogram Ecg

Abstract Purpose Although electrocardiogram (ECG) has been proven as a biometric for human identification, applying biometric technology remains challenging with diverse heart rate circumstances in which high intensity heart rate caused waveform deformation may not be known in advance when ECG templates are registered. Methods A calibration method that calculates the ratio of the length of an unidentified electrocardiogram signal to the length of an electrocardiogram template is proposed in this paper. Next, the R peak is used as an axis anchor point of a trigonometric projection (TP) to attain the displacement value. Finally, the unidentified ECG signal is calibrated according to the generated trigonometric value, which corresponds to the trigonometric projection degree of the ratio and the attained displacement measurement. Results The results reveal that the proposed method provides superior overall performance compared with that of the conventional downsampling method, based on the percentage root mean square difference (PRD), correlation coefficients, and mean square error (MSE). Conclusion The curve fitting equation directly maps from the heart rate levels to the TP degree without prior registration information. The proposed ECG calibration method offers a more robust system against heart rate interference when conducting ECG identification.

scholarly journals Quality of wood in the stands of poplar clones

2008 ◽  
Vol 54 (No. 1) ◽  
pp. 9-16
Author(s):  
R. Petráš ◽  
J. Mecko ◽  
V. Nociar
Keyword(s):  
Root Mean Square Error ◽  
Systematic Error ◽  
Mean Square Error ◽  
Statistical Tests ◽  
Mean Square ◽  
Poplar Clones ◽  
Mean Diameter ◽  
Empirical Material ◽  
Relative Root

The results obtained in research on the quality of raw timber by means of the structure of assortments for the stands of poplar clones Robusta and I-214 are presented in the paper. Models for an estimation of the structure of basic assortments of poplar stands were constructed separately for each clone in dependence on mean diameter, quality of stems, and damage to stems in the stand. The clone Robusta has higher proportions of higher-quality assortments than the clone I-214. The accuracy of models was determined on empirical material. It was confirmed by statistical tests that the models did not have a systematic error. The relative root mean-square error for main assortments of the clone I-214 is 15–27% and Robusta 13–24%.

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