Coefficient of Determination Research Papers (original) (raw)

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- Mathematics, Biomedical Engineering, Biosystems engineering, Moisture Content
- by Vitezslav Otruba
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- Titanium, Physical sciences, CHEMICAL SCIENCES, Tungsten Carbide

J Nondestruct Eval (2010) 29: 3842 DOI 10.1007/s10921-010-0063-7 Acoustic Properties of Selected Tropical Wood Species Yahya Sedik · Sinin Hamdan · Ismail Jusoh · Mahbub Hasan Published online: 12 February 2010 © Springer... more

- by Dalbir Sogi
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- Chemistry, Food Science, Medicine, Food Science and Technology
- by Johnson Fasinmirin
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- Soil moisture, Evapotranspiration, Growth and development, Water balance

For centuries, land degradation triggered by deforestation has occurred in Ethiopia, in particular in the northern regional state Tigray, the area under study. In order to change this situation, the local government started to establish enclosures. In these sites, grazing is no longer permitted so that forest can naturally regenerate. In order to develop sustainable yield planning for forest rehabilitation

- by Christoph Kleinn
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- Case Study, Local governance, Natural Regeneration, Prediction Model
- by Michael Binford
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- Human Geography, Null Model, Landscape Pattern, Coefficient of Determination
- by Chris Rogers
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- Mathematics, Birth Weight, Goodness of Fit, Animal Feed
- by Mohammad Hossein Keshavarz
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- Engineering, Prediction, Safety, Correlation
- by M. Azzi and +1
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- Air Quality, Seasonality, Atmospheric sciences, Carbon Monoxide
- by mahfuz rahman
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- Mathematics, Flow measurement, Pipe Flow, Agriculture and Rural Development
- by Roxana Lopez-Cruz
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- Microbiology, Geography, Epidemiology, Biomathematics
- by Luiz Pinto
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- Food Engineering, Particle Size, Food Sciences, Coefficient of Determination
- by Chong-Yu Xu
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- Climate variability, Seasonality, Atmospheric sciences, Model Selection

Artificial Neural Network (ANN) and regression models were developed using watershed-scale geomorphologic parameters to predict surface runoff and sediment losses of the St. Esprit watershed, Quebec, Canada. Ge o- morphological parameters describing the land surface drainage characteristics and surface water flow behav- iour were empirically associated with measured rainfall and runoff data and used as input to a three-layered back-propagation

- by Kendall Swanson
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- Mathematics, Ultrasound, Animal Production, Body Composition
- by Carlos Valdes
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- Earth Sciences, Arid environments, Invasive Species, Soil Salinity

Sorption isotherms were determined for salted alligator's meat at four different temperatures (10°C, 15°C, 25°C and 35°C), using a standard gravimetric method. The goodness of fit of five sorption models to experimental data was determined. Five models, namely the GAB, the BET, the Halsey, the Henderson and the Hailwood and Horrobin, were evaluated to determine the best fit for the experimental data. The GAB was the best fitted model for the data of salted alligator's meat with an average error less than 10% for temperature of 10°C and less than 5% for the others temperatures. The coefficients of determination (r2) were 0.99 for all temperatures considered. The monolayer values decreased as temperature increased. The other four models were not appropriated to fit the data because of the high error values, although the r2 were also similar to the GAB model. The net isosteric heat of sorption was estimated from equilibrium sorption data, using the Clausis–Clapeyron equation. Isosteric heats of sorption were found to increase with increasing temperature and could be well adjusted by an exponential relationship.

- by Silvia Barboza
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- Food Engineering, Food, Goodness of Fit, Moisture Content
- by Andrej Kielbassa
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- Engineering, Dental Materials, Porosity, Sliding wear

- by Lola Suárez
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- Remote Sensing, Time Series, Water Stress, Statistical Significance
- by Romdhane Rekaya
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- Genetics, Animal Production, Parameter estimation, Data Structure
- by Siham Lahsasni
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- Food Engineering, Air flow, Air Conditioning, Relative Humidity
- by Mauricio Acuna
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- Near Infrared, Multivariate Analysis, Near Infrared Spectroscopy, Real Time
- by mauro moresi
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- Food Engineering, Stress relaxation, Work Stress, Spectrum
- by Tore Solheim
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- Forensic Science, Principal Component Analysis, Multidisciplinary, Humans
- by sadia sherazi
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- Analytical Chemistry, FTIR spectroscopy, Fatty acids, Calibration
- by Jon Vik
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- Ecology, Population ecology, Density dependence, Snowshoe Hare
- by Simeon Jekayinfa
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- Mechanical Engineering, Quality, Business and Management, Regression Analysis

Quality characteristics of wheat are determined by different physiochemical and rheological analysis by using different AACC methods. AACC methods are expensive, time consuming and cause destruction of samples. Fourier transforms infrared (FTIR) spectroscopy is one of the most important and emerging tool used for analyzing wheat for different quality parameters. This technique is rapid and sensitive with a great variety of sampling techniques. In the present study different wheat varieties were analyzed for quality assessment and were also characterized by using AACC methods and FTIR technique. The straight grade flour was analyzed for physical, chemical and rheological properties by standard methods and results were obtained. FTIR works on the basis of functional groups and provide information in the form of peaks. On basis of peaks the value of moisture, protein, fat, ash, carbohydrates and hardness of grain were determined. Peaks for water were observed in the range 1,640 cm−1 and 3,300 cm−1 on the basis of functional group H and OH. Protein was observed in the range from 1,600 cm−1 to 1,700 cm−1 and 1,550 cm−1 to 1,570 cm−1 on the basis of bond amide I and amide II respectively. Fat was also observed within these ranges but on the basis of C-H bond and also starch was observed in the range from 2,800 and 3,000 cm−1 (C-H stretch region) and in the range 3,000 and 3,600 cm−1 (O-H stretch region). As FTIR is a fast tool it can be easily emplyed for wheat varieties identification according to a set criterion.

- by Imran Pasha
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- Mechanical Engineering, Analytical Chemistry, Principal Component Analysis, Biomass
- by Faisal Afzal Siddiqui
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- Conjoint Analysis, Mobile phone, IT Value, Coefficient of Determination
- by Judith Singer
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- Statistics, Regression Analysis, Regression Model, Coefficient of Determination
- by Mojtaba Ahmadi
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- Engineering, Response Surface Methodology, Wastewater Treatment, Water Pollution
- by E. Auclair
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- Biomass, Multidisciplinary, Adsorption, Saccharomyces cerevisiae

This paper examined the effect of coarse aggregate sizes on the compressive strength of concrete using response surface methodology. It has become imperative to carry out this study to ascertain which aggregate size, will produce the optimum compressive strength, which may guide engineers when using it in the construction industry. Regression equations relating the compressive strength of concrete using various aggregate sizes with both the curing duration, fine aggregate, cement and water/cement ratios were developed. The adequacy of the model was checked using the coefficient of determination (R 2). The results showed that the 9.5 mm aggregate sized concrete had 35 N/mm 2 as compressive strength for 28 days curing duration, while the 12.5 mm aggregate sized concrete had 24 N/mm 2 as compressive strength for 28 days curing duration and the 19 mm aggregate sized concrete's compressive strength was 23 N/mm 2 when cured for 28 days. The compressive strength of 9.5 mm aggregate sized concrete had an increase of 1.46% and 1.52% over the 12.5 mm and 19 mm aggregate sized concrete's compressive strength. The low coefficient of determination (R 2) of 0.1270 for 9.5 mm aggregate sized concrete, R 2 of 0.1322 for 12.5 mm aggregate sized concrete and R 2 of 0.1243 for 19 mm aggregate sized concrete shows that the linear model could not predict the compressive strengths of the different aggregate sized concrete efficiently.

- by NIPES JOURNALS
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- Compressive Strength, Regression, Coefficient of Determination, Aggregate Sizes

This paper proposes a framework for the training of learning systems for regression when (i) the number of examples is small and contains interdependencies, and (ii) each sample consists of large quantities of discrete data that are functional in nature. The objective is to achieve robust yet nonlinear relations between inputs and outputs. In this study, laser scans of the

- by Janet Ronsky
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- Engineering, Principal Component Analysis, Functional data analysis, X Rays
- by Albrecht Claessens
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- Anthropometry, Adolescent, Humans, Child
- by ibrahim alp
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- Mechanical Engineering, Chemical Engineering, Design, Mathematical Programming
- by saleh arekhi
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- Geology, Case Study, Crop management, Coefficient of Determination

Research on more productive and sustainable sugarcane production systems would be aided by a comprehensive simulator of the sugarcane crop that is cognisant of a broader crop-soil-management system. A sugarcane crop model is described that can be deployed in the APSIM framework for agricultural systems simulation. The model operates on a daily time step, grows a leaf canopy, uses intercepted radiation to produce assimilate, and partitions this assimilate into leaf, structural stalk and sugar. The crop physiological processes represented in the model respond to the radiation and temperature environment and are sensitive to water and nitrogen supply. The model simulates growth, water use, N accumulation, sugar dry weight and fresh cane yield for plant and ratoon crops in response to climate, soil, management and genotypic factors. The model was developed on 35 datasets from Australia, Hawaii, South Africa and Swaziland, covering a wide range of crop classes, latitudes, water regimes and nitrogen supply conditions. Coefficients of determination for model predictions compared to observed data included 0.79 for LAI, 0.93 for crop biomass, 0.83 for stalk sucrose and 0.86 for N accumulation in above ground tissues. The particular strengths of this model are discussed in the context of agricultural systems simulation.

- by Chep Chuot
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- South Africa, Field Crops, Nitrogen, System Simulation