scholarly journals Mathematical models for metric features extraction from RGB-D sensor

2021 ◽  
Vol 14 (11) ◽  
Author(s):  
Elton Fernandes Dos Santos ◽  
Laurimar Gonçalves Vendrusculo ◽  
Luciano Bastos Lopes ◽  
Scheila Geiele Kamchen ◽  
Isabella C. F. S. Condotta
Keyword(s):  
Regression Models ◽  
Flat Surface ◽  
Average Distance ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Target Area ◽  
Depth Images ◽  
White Cardboard ◽  
Set Up

The use of the RGB-D camera has been applied in several fields of science. That popularization is due to the emergence of technologies such as the Intel® RealSense™ D400 series. However, despite the actual demand from some potential users, few studies concern the characterization of these sensors for object measurements. Our study sought to estimate models dealing with calculating the area and length between targets or points within RGB and depth images.  An experiment was set up with white cardboard fixed on a flat surface with colored pins. We measured the distance between the camera and cardboard by calculating the average distance from the pixels belonging to the target area. The Information Criterion AIC and BIC associated with R2 were performed to select the best models. Polynomial and power regression models reached the highest coefficient of determination and smallest values of AIC and BIC.

scholarly journals A NON-DESTRUCTIVE METHOD FOR ESTIMATING LEAF AREA OF Ceiba glaziovii (Kuntze) K. Schum.

FLORESTA ◽  
2019 ◽  
Vol 50 (1) ◽  
pp. 1063
Author(s):  
João Everthon da Silva Ribeiro ◽  
Francisco Romário Andrade Figueiredo ◽  
Ester Dos Santos Coêlho ◽  
Walter Esfrain Pereira ◽  
Manoel Bandeira de Albuquerque
Keyword(s):  
Leaf Area ◽  
Regression Models ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Linear Measurements ◽  
Maximum Width ◽  
Bias Index ◽  
Different Shapes ◽  
Non Destructive

The determination of leaf area is of fundamental importance in studies involving ecological and ecophysiological aspects of forest species. The objective of this research was to adjust an equation to determine the leaf area of Ceiba glaziovii as a function of linear measurements of leaves. Six hundred healthy leaf limbs were collected in different matrices, with different shapes and sizes, in the Mata do Pau-Ferro State Park, Areia, Paraíba state, Northeast Brazil. The maximum length (L), maximum width (W), product between length and width (L.W), and leaf area of the leaf limbs were calculated. The regression models used to construct equations were: linear, linear without intercept, quadratic, cubic, power and exponential. The criteria for choosing the best equation were based on the coefficient of determination (R²), Akaike information criterion (AIC), root mean square error (RMSE), Willmott concordance index (d) and BIAS index. All the proposed equations satisfactorily estimate the leaf area of C. glaziovii, due to their high determination coefficients (R² ≥ 0.851). The linear model without intercept, using the product between length and width (L.W), presented the best criteria to estimate the leaf area of the species, using the equation 0.4549*LW.

Optimizing age at first use of semen for higher fertilityin Sahiwal breeding bulls

2016 ◽  
Author(s):  
B. C. Naha ◽  
A. K. Chakravarty ◽  
M. A. Mir ◽  
M. Bhakat
Keyword(s):  
Comparative Evaluation ◽  
Regression Models ◽  
Information Criterion ◽  
Conception Rate ◽  
Coefficient Of Determination ◽  
Progeny Testing ◽  
Testing Programme ◽  
Multiple Regression Models ◽  
Improvement Programme ◽  
Selection Of

The objective of the study was to optimise the age at first use (AAFU) of semen in Sahiwal breeding bulls which will help in early selection of bulls under progeny testing programme. The data on AAFU, conception rate based on first A.I. (CRFAI), overall conception rate (OCR) and birth weight (B.WT) of 43 Sahiwal bulls during 1987 to 2013 at NDRI centre pertaining to 8 sets of Sahiwal improvement programme at ICAR-NDRI, Karnal, India were adjusted for significant environmental influences and subsequently analyzed. Simple and multiple regression models were used for prediction of CRFAI and OCR of Sahiwal bulls. Comparative evaluation of three developed models (I to III) have showed that Model III, having AAFU and B.WT which fulfill the accuracy of model as revealed by high coefficient of determination, low mean sum of square to due error, low conceptual predictive value and low Bayesian information criterion . The results showed that average predicted CRFAI was highest (49.34%) at less than 5 years and lowest (44.79%) at > 6 years of age at first A.I. /use. Similarly average predicted OCR was highest (48.50%) at less than 5 years and lowest (44.56%) at >6 years of age at first A.I. / use of Sahiwal bulls. In organized herd under progeny testing programme, Sahiwal bulls should be used prior to 5 years which is expected to result in 4.45% better CRFAI and 3.94% better OCR in comparison to Sahiwal bulls used after 6 years of age.

Optimum age at first semen freezing in relation to fertility of Sahiwal breeding bulls

2018 ◽  
Author(s):  
B. C. Naha ◽  
A. K. Chakravarty ◽  
M. A. Mir ◽  
M. Bhakat ◽  
Ramendra Das ◽  
...  
Keyword(s):  
Birth Weight ◽  
Regression Models ◽  
Dairy Herd ◽  
Information Criterion ◽  
Conception Rate ◽  
Coefficient Of Determination ◽  
National Dairy Research Institute ◽  
Multiple Regression Models ◽  
Improvement Programme ◽  
Selection Of

Early selection of bulls having optimum age at first semen freezing play an important role in improving reproductive performance in a dairy herd. Twenty seven years data (1987-2013) on age at first semen freezing (AAFSF), conception rate based on first A.I. (CRFAI) , overall conception rate (OCR) and birth weight (B.WT) of 41 Sahiwal bulls belonging to 8 sets of Sahiwal improvement programme at ICAR-National Dairy Research Institute, Karnal, Haryana, India; were adjusted against environmental effects and subsequently analysed. Simple and multiple regression models were used for prediction of CRFAI and OCR of Sahiwal bulls. Among the three developed models (I to III), it was observed that Model III having age at first semen freezing and birth weight fulfil the accuracy of model i.e.; having high coefficient of determination (R2) value (CRFAI = 67% and OCR= 69%), low mean error sum of square (MSSe), low conceptual predictive value (CP value) and low Bayesian information criterion (BIC). The results revealed that optimum age at first semen freezing of Sahiwal bulls should be 2.5 - 3.0 years for 3.10% higher conception rate based on first A.I. (48.86%) and 4.39% higher overall conception rate (48.78%) in comparison to Sahiwal bulls with more than 3.5 years of age (CRFAI :- 45.76% and OCR :- 44.39%).

scholarly journals Adjusting weight growth curve of male quails Coturnix japonica reared in the semi-arid region of the State of Pernambuco

2018 ◽  
Vol 41 (1) ◽  
pp. 42563 ◽  
Author(s):  
Leandro Ricardo Rodrigues de Lucena ◽  
Marco Aurélio Carneiro de Holanda ◽  
Mônica Calixto Ribeiro de Holanda ◽  
Marcelo Lopes dos Anjos
Keyword(s):  
Growth Curve ◽  
Regression Models ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Normal Regression ◽  
Weight Growth ◽  
Semi Arid Region ◽  
Log Normal ◽  
Squared Residuals

This study adjusted different regression models to describe the growth pattern of meat quails from birth to 42 days of age. Data of 300 male quails were used. Weight and height information of all quails were collected weekly from the 1st to the 42nd day of age. Body weight of poultry was subjected to the polynomial, logistic, Gompertz, Weibull, and log-normal regression models. The criteria used to choose the best model to explain the growth curve of quails were the coefficient of determination of the model, Akaike’s information criterion, sum of squared residuals and Willmott’s index. For all the models used, the variables age and height were significant to explain the weight of quails. The polynomial (R² = 99.99%, AIC = 24.68, SSR = 27.5, d = 0.9999) and log-normal (R² = 99.60%, AIC = -17.5, SSR = 107.15, d = 0.9989) models presented the best fit criteria and were recommended to explain the growth of quails.

Rapid, Refined, and Robust Method for Expression, Purification, and Characterization of Recombinant Human Amyloid-beta M1-42

2019 ◽  
Author(s):  
Priya Prakash ◽  
Travis Lantz ◽  
Krupal P. Jethava ◽  
Gaurav Chopra
Keyword(s):  
Amyloid Beta ◽  
Western Blots ◽  
Force Microscopy ◽  
E Coli ◽  
Atomic Force ◽  
Set Up ◽  
Short Time

Amyloid plaques found in the brains of Alzheimer’s disease (AD) patients primarily consists of amyloid beta 1-42 (Ab42). Commercially, Ab42 is synthetized using peptide synthesizers. We describe a robust methodology for expression of recombinant human Ab(M1-42) in Rosetta(DE3)pLysS and BL21(DE3)pLysS competent E. coli with refined and rapid analytical purification techniques. The peptide is isolated and purified from the transformed cells using an optimized set-up for reverse-phase HPLC protocol, using commonly available C18 columns, yielding high amounts of peptide (~15-20 mg per 1 L culture) in a short time. The recombinant Ab(M1-42) forms characteristic aggregates similar to synthetic Ab42 aggregates as verified by western blots and atomic force microscopy to warrant future biological use. Our rapid, refined, and robust technique to purify human Ab(M1-42) can be used to synthesize chemical probes for several downstream in vitro and in vivo assays to facilitate AD research.

Isolation and characterization of oleochemical compounds from watermelon seed

2020 ◽  
Vol 10 (4) ◽  
pp. 79-82
Author(s):  
Madhubhushan M ◽  
Seshaiah S ◽  
Chandrudu J ◽  
Sagar R ◽  
Akila CR
Keyword(s):  
Cutting Tool ◽  
Citrullus Lanatus ◽  
Fatty Esters ◽  
Mineral Oils ◽  
Light Yellow ◽  
Isolation And Characterization ◽  
The Common ◽  
Set Up ◽  
Natural Gradation

The common watermelon item (Citrullus lanatus) seeds were gained from castoffs verdant nourishments for use by decorating, sun ventilation and pulverizing. Light yellow-toned oil was gotten by dissolvable withdrawal using oil atmosphere and the going with traits were gotten using oil ether: pH, refractive rundown, thickness, dissolvable miscibility, coagulating temperature, fire nature, express gravity, streak point and warmth of consuming. With a shallow level of unsaturation, stepped level of smoothness, and proximity of raised degree of the sensible proportion of free unsaturated fats. The low assessment of the solidifying temperature of the oil offered a hint that the oil can be managed in various areas paying little heed to the qualification in temperature. The following level of linoleic destructive of the oil offers a hint of natural gradation of solidarity. Fatty esters are increasing expanding significance as a biodegradable swap for mineral oils. In some request regions, for example, cutting tool oil, gearbox, pressure-driven oils, and greases for raw petroleum creation, the oleochemical items are set up. Nonetheless, certain particular wellsprings of fatty esters are hitherto to be abused for this comparative reason. This exploration subsequently tests into one of the less used wellsprings of fatty esters in watermelon. The oil from the kernels demonstrations a top-notch yield presents significant utilitarian gatherings for change and thus was utilized to set up an assortment of oleochemicals which demonstrated excellence materials in contrast with the routinely utilized oils feed frameworks for oleochemicals after portrayal. The photopolymers acquired indicated piercing vinyl protons for consistent polymerize.

scholarly journals Modeling of Lake Malombe Annual Fish Landings and Catch per Unit Effort (CPUE)

Forecasting ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 39-55
Author(s):  
Rodgers Makwinja ◽  
Seyoum Mengistou ◽  
Emmanuel Kaunda ◽  
Tena Alemiew ◽  
Titus Bandulo Phiri ◽  
...  
Keyword(s):  
Time Series ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Efficiency Coefficient ◽  
Arima Models ◽  
Catch Per Unit Effort ◽  
Annual Fish ◽  
Unit Effort ◽  
The Mean

Forecasting, using time series data, has become the most relevant and effective tool for fisheries stock assessment. Autoregressive integrated moving average (ARIMA) modeling has been commonly used to predict the general trend for fish landings with increased reliability and precision. In this paper, ARIMA models were applied to predict Lake Malombe annual fish landings and catch per unit effort (CPUE). The annual fish landings and CPUE trends were first observed and both were non-stationary. The first-order differencing was applied to transform the non-stationary data into stationary. Autocorrelation functions (AC), partial autocorrelation function (PAC), Akaike information criterion (AIC), Bayesian information criterion (BIC), square root of the mean square error (RMSE), the mean absolute error (MAE), percentage standard error of prediction (SEP), average relative variance (ARV), Gaussian maximum likelihood estimation (GMLE) algorithm, efficiency coefficient (E2), coefficient of determination (R2), and persistent index (PI) were estimated, which led to the identification and construction of ARIMA models, suitable in explaining the time series and forecasting. According to the measures of forecasting accuracy, the best forecasting models for fish landings and CPUE were ARIMA (0,1,1) and ARIMA (0,1,0). These models had the lowest values AIC, BIC, RMSE, MAE, SEP, ARV. The models further displayed the highest values of GMLE, PI, R2, and E2. The “auto. arima ()” command in R version 3.6.3 further displayed ARIMA (0,1,1) and ARIMA (0,1,0) as the best. The selected models satisfactorily forecasted the fish landings of 2725.243 metric tons and CPUE of 0.097 kg/h by 2024.

scholarly journals Characterization of Ultra-Thin Diamond-Like Carbon Films by SEM/EDX

Coatings ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 729
Author(s):  
Chanida Puttichaem ◽  
Guilherme P. Souza ◽  
Kurt C. Ruthe ◽  
Kittipong Chainok
Keyword(s):  
Regression Models ◽  
Hard Disk Drives ◽  
Carbon Films ◽  
Diamond Like Carbon ◽  
Disk Drives ◽  
Cross Sectional ◽  
Protective Films ◽  
High Throughput Method ◽  
Multiple Regression Models

A novel, high throughput method to characterize the chemistry of ultra-thin diamond-like carbon films is discussed. The method uses surface sensitive SEM/EDX to provide substrate-specific, semi-quantitative silicon nitride/DLC stack composition of protective films extensively used in the hard disk drives industry and at Angstrom-level. SEM/EDX output is correlated to TEM to provide direct, gauge-capable film thickness information using multiple regression models that make predictions based on film constituents. The best model uses the N/Si ratio in the films, instead of separate Si and N contributions. Topography of substrate/film after undergoing wear is correlatively and compositionally described based on chemical changes detected via the SEM/EDX method without the need for tedious cross-sectional workflows. Wear track regions of the substrate have a film depleted of carbon, as well as Si and N in the most severe cases, also revealing iron oxide formation. Analysis of film composition variations around industry-level thicknesses reveals a complex interplay between oxygen, silicon and nitrogen, which has been reflected mathematically in the regression models, as well as used to provide valuable insights into the as-deposited physics of the film.

scholarly journals Diurnal Variation of the Diffuse Attenuation Coefficient for Downwelling Irradiance at 490 nm in Coastal East China Sea

2021 ◽  
Vol 13 (9) ◽  
pp. 1676
Author(s):  
Yu Zhang ◽  
Zhantang Xu ◽  
Yuezhong Yang ◽  
Guifen Wang ◽  
Wen Zhou ◽  
...  
Keyword(s):  
Diurnal Variation ◽  
Attenuation Coefficient ◽  
East China Sea ◽  
East China ◽  
Coefficient Of Determination ◽  
Target Area ◽  
Diffuse Attenuation Coefficient ◽  
China Sea ◽  
Mean Square Errors ◽  
Downwelling Irradiance

The diurnal variation of the diffuse attenuation coefficient for downwelling irradiance at 490 nm (Kd(490)) has complex characteristics in the coastal regions. However, owing to the scarcity of in situ data, our knowledge on the diurnal variation is inadequate. In this study, an optical-buoy dataset was used to investigate the diurnal variation of Kd(490) in the coastal East China Sea, and to evaluate the Kd(490) L2 products of geostationary ocean color imager (GOCI), as well as the performance of six empirical algorithms for Kd(490) estimation in the Case-2 water. The results of validation show that there was high uncertainty in GOCI L2 Kd(490), with mean absolute percentage errors (MAPEs) of 69.57% and 68.86% and root mean square errors (RMSEs) of 0.70 and 0.71 m−1 compared to buoy-measured Kd12(490) and Kd13(490), respectively. Meanwhile, with the coefficient of determination (R2) of 0.71, as well as the lowest MAPE of 27.31% and RMSE of 0.29 m−1, the new dual ratio algorithm (NDRA) performed the best in estimating Kd(490) in the target area, among the six algorithms. Further, four main types of Kd(490) diurnal variation were found from buoy data, showing different variabilities compared to the area closer to the shore. One typical diurnal variation pattern showed that Kd(490) decreased at flood tide and increased at ebb tide, which was confirmed by GOCI images through the use of NDRA. Hydrometeorological factors influencing the diurnal variations of Kd(490) were also studied. In addition to verifying the predominant impact of tide, we found that the dominant effect of tide and wind on the water column is intensifying sediment resuspension, and the change of sediment transport produced by them are secondary to it.

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