scholarly journals Spacial and Frequency Domain Calculation of Terrain Roughness Metric Root-Mean-Square (RMS)

2014 ◽  
Author(s):  
Wesley Bylsma
Keyword(s):  
Frequency Domain ◽  
Root Mean Square ◽  
Mean Square ◽  
Terrain Roughness

scholarly journals A Feasible Approach to Detect Pesticides in Food Samples Using THz-FDS and Chemometrics

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Qian Chen ◽  
Shengyao Jia ◽  
Jianyuan Qin ◽  
Yong Du ◽  
Zongshan Zhao
Keyword(s):  
Root Mean Square Error ◽  
Frequency Domain ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Density Functional ◽  
Food Samples ◽  
High Spectral Resolution ◽  
Quantitative Detection ◽  
Mean Square ◽  
Terahertz Frequency

The use of pesticides will have an impact on food, organisms, and environment. Specifically, pesticide residues in food will damage human health. Because of its high permeability, low energy, high spectral resolution, and fingerprint characteristics, terahertz frequency-domain spectroscopy has been introduced into the determination of pesticides (imidacloprid, acetamiprid, and triadimefon) residues in food samples (glutinous rice flour, wheat flour, and corn flour) in our present study. These three pesticides exhibit their own absorption peaks in the region of 0.4–1.7 THz. For understanding the origins of these peaks, the experimental data are interpreted by using density functional theory calculations at the level of B3LYP/6-31G (d). It is found that these absorption peaks come from the intramolecular and intermolecular interactions. The absorption peaks of pesticides are still detectable in a mixture of pesticides and food samples when they reach a certain concentration. The results from chemometrics analysis show that quantitative detection of pesticides in food samples is feasible. The partial least squares regression models have high correlation coefficient (>0.99), low root-mean-square error of calibration (<1.5%), low root-mean-square error of cross-validation (<2.4%), and low root-mean-square error of prediction (<2.3%), indicating good quality of prediction for pesticides concentration. Our results prove that the terahertz frequency-domain spectrum combined with chemometrics can be used for the detection of pesticides in food samples.

Analysis of vibrations in a diesel engine produced by Jatropha biodiesel using heterogeneous catalyst

2022 ◽  
pp. 0958305X2110639
Author(s):  
Aparna Singh ◽  
Akhilesh Kumar Choudhary ◽  
Shailendra Sinha ◽  
Hitesh Panchal ◽  
Kishor Kumar Sadasivuni
Keyword(s):  
Diesel Engine ◽  
Frequency Domain ◽  
Heterogeneous Catalyst ◽  
Root Mean Square ◽  
Compression Ratio ◽  
Optimization Technique ◽  
Molar Ratio ◽  
P Value ◽  
Mean Square ◽  
Input Parameters

Extensive consumption of fossil fuel has contributed to the worldwide decline of its reserves and detrimental effect on the environment. Therefore, it is essential to explore alternative option of fuel for diesel engine. The main objective of this research article is to optimize vibrations in a single-cylinder variable compression ratio diesel engine driven by Jatropha biodiesel blend. The heterogeneous catalyst (calcium oxide) is used to manufacture of biodiesel from Jatropha curcas oil by a process of transesterification. The optimization technique (Response Surface Methodology) has been employed to optimize root mean square acceleration of vibration by taking load, compression ratio (CR), and fuel injection pressure (FIP) as engine input parameters. Experiments were designed according to central composite design. The amplitude of the frequency domain signals is determined using Fast Fourier Transform and the influence of input parameters has been investigated in the frequency domain analysis of the vibration signatures. The adequacy and significance of the models have been checked by p-value and F value tests. Regression coefficients Adj. R2, R2, Pred. R2 were also found in acceptable range. The experimental outcome reveals that biodiesel yield of 81.6% was obtained at methanol-to-oil molar ratio of 12:1, reaction temperature of 65°C, reaction time of 3 h, and catalyst concentration of 5 wt%. Simultaneously, the model obtained a series of solutions based on the desirability criteria and proposed optimum setting of engine input parameters at a load of 2.59 kg, 17.94 CR, and 268.76 bar FIP for B30 blend. B30 blend generated root mean square acceleration of 4.46 m/s2 at above optimized conditions. A validation trial was conducted and the percentage of error for root mean square acceleration was found to be 2.3356% and 1.3039%, respectively, for B0 and B30 blend.

scholarly journals Characterization of Wavelet Decomposition Strain Signal Using the K-Mean Clustering Method

2018 ◽  
Vol 7 (3.17) ◽  
pp. 158
Author(s):  
A A. Rahim ◽  
C H. Chin ◽  
S Abdullah ◽  
S S. K. Singh ◽  
M Z. Nuawi ◽  
...  
Keyword(s):  
Fatigue Life ◽  
Frequency Domain ◽  
Root Mean Square ◽  
Time Domain ◽  
Average Distance ◽  
Industrial Area ◽  
Discrete Wavelet ◽  
Mean Square ◽  
Time Frequency ◽  
Strain Signal

This paper aims to study the characterisation of time-frequency domain to analyse the fatigue strain signal due to weaknesses in time domain and frequency domain approaches. The objectives were to determine the behaviour of strain signal, characterise the fatigue life of strain signal and validate the fatigue life in time-frequency domain. The strain signal was obtained using data acquisition devices and strain gauges on two types of road condition including highway and industrial area. The acquired signals were analysed with time domain, frequency domain and time-frequency domain approaches. In time-frequency domain, the signals were decomposed using 4th Daubechies discrete wavelet transform. To validate the effectiveness of time-frequency approach in characterising vibration fatigue signal, fatigue data was clustered by mapping of the data based on the spectrum energy, root-mean-square and fatigue life obtained. The clustering was performed by comparing the centroid values which both data had five clusters as the optimum data clustering with 0.836 average distance to centroid. From this, the relationship between fatigue life, root-mean-square and spectrum energy can be determined and thus a new fatigue life criterion was developed. 

The Relationship of Root Mean Square Value of Electromyography and Isometric Torque of Quadriceps in Normal Subjects

2016 ◽  
Vol 26 (1) ◽  
pp. 58
Author(s):  
Qiurong XIE ◽  
Zheng JIANG ◽  
Qinglu LUO ◽  
Jie LIANG ◽  
Xiaoling WANG ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Normal Subjects ◽  
Mean Square ◽  
Isometric Torque ◽  
Relationship Of ◽  
The Relationship

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 Histamine Control in Raw and Processed Tuna: A Rapid Tool Based on NIR Spectroscopy

Foods ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 885
Author(s):  
Sergio Ghidini ◽  
Luca Maria Chiesa ◽  
Sara Panseri ◽  
Maria Olga Varrà ◽  
Adriana Ianieri ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Partial Least Square ◽  
Least Square ◽  
Partial Least Square Regression ◽  
Coefficient Of Determination ◽  
Mean Square ◽  
Tuna Fish ◽  
Mean Square Errors

The present study was designed to investigate whether near infrared (NIR) spectroscopy with minimal sample processing could be a suitable technique to rapidly measure histamine levels in raw and processed tuna fish. Calibration models based on orthogonal partial least square regression (OPLSR) were built to predict histamine in the range 10–1000 mg kg−1 using the 1000–2500 nm NIR spectra of artificially-contaminated fish. The two models were then validated using a new set of naturally contaminated samples in which histamine content was determined by conventional high-performance liquid chromatography (HPLC) analysis. As for calibration results, coefficient of determination (r2) > 0.98, root mean square of estimation (RMSEE) ≤ 5 mg kg−1 and root mean square of cross-validation (RMSECV) ≤ 6 mg kg−1 were achieved. Both models were optimal also in the validation stage, showing r2 values > 0.97, root mean square errors of prediction (RMSEP) ≤ 10 mg kg−1 and relative range error (RER) ≥ 25, with better results showed by the model for processed fish. The promising results achieved suggest NIR spectroscopy as an implemental analytical solution in fish industries and markets to effectively determine histamine amounts.

Intersession reliability of GPS-based and accelerometer-based physical variables in small-sided games with and without the offside rule

2021 ◽  
pp. 175433712098764
Author(s):  
Igor Junio de Oliveira Custódio ◽  
Gibson Moreira Praça ◽  
Leandro Vinhas de Paula ◽  
Sarah da Glória Teles Bredt ◽  
Fabio Yuzo Nakamura ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Global Positioning System ◽  
Intraclass Correlation ◽  
Correlation Coefficients ◽  
Mean Square ◽  
Physical Demands ◽  
Intraclass Correlation Coefficients ◽  
Total Distance ◽  
Global Positioning ◽  
High Level

This study aimed to analyze the intersession reliability of global positioning system (GPS-based) distances and accelerometer-based (acceleration) variables in small-sided soccer games (SSG) with and without the offside rule, as well as compare variables between the tasks. Twenty-four high-level U-17 soccer athletes played 3 versus 3 (plus goalkeepers) SSG in two formats (with and without the offside rule). SSG were performed on eight consecutive weeks (4 weeks for each group), twice a week. The physical demands were recorded using a GPS with an embedded triaxial accelerometer. GPS-based variables (total distance, average speed, and distances covered at different speeds) and accelerometer-based variables (Player Load™, root mean square of the acceleration recorded in each movement axis, and the root mean square of resultant acceleration) were calculated. Results showed that the inclusion of the offside rule reduced the total distance covered (large effect) and the distances covered at moderate speed zones (7–12.9 km/h – moderate effect; 13–17.9 km/h – large effect). In both SSG formats, GPS-based variables presented good to excellent reliability (intraclass correlation coefficients – ICC > 0.62) and accelerometer-based variables presented excellent reliability (ICC values > 0.89). Based on the results of this study, the offside rule decreases the physical demand of 3 versus 3 SSG and the physical demands required in these SSG present high intersession reliability.

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