Nonlinear Approximation for Natural Convection Flow Past A Vertical Moving Plate With Nonlinear Thermal Radiation Effect

This piece of work contains significant insight associated with the analysis of fluid transport in the vicinity of a constantly moving vertical plate with nonlinear thermal radiation. The heat transport at the wall surface is assumed to be influenced by convective boundary conditions. Furthermore, thermal transport is considered to be enhanced by nonlinear temperature variation with temperature (NDT). The boundary layer approximation equations are simplified through suitable alteration known as the similarity transformation. The resulting ODEs are translated into the IVP via shooting techniques and then integrated using the RKF45 algorithm in Maple. The impact of the dimensionless parameters dictating the fluid behaviour is demonstrated via graphs and tables. In the cause of the analysis, it is observed that the heat transfer enhances when the fluid flow in the direction +ve x-axis whereas the plate moves in the direction of the -ve x-axis but decreases when the plate and fluid move in the same direction. The skin friction coefficient decreases when the fluid flow is directed toward the +ve x-axis whereas the plate moves toward the -ve x-axis but is enhanced when the plate and the fluid move in the same orientation. The temperature and velocity profiles appreciate with the nonlinear thermal radiation when the motion of the plate and the fluid are on the same axis. The temperature gradient near the wall depreciated gradually due to nonlinear thermal radiation growth but appreciate in the free stream

Maximum Entropy Closure Relation for Higher Order Alignment and Orientation Tensors Compared to Quadratic and Hybrid Closure

A closure relation expresses the fourth order orientation tensor as a function of the second order one. Two well-known closure relations, the hybrid closure and the maximum entropy closure, are compared in the case of a rotation symmetric orientation distribution function. The maximum entropy closure predicts a positive fourth order parameter in the whole range of the second order parameter, whereas the hybrid closure results in negative fourth order parameters for small values of the second order one. For the maximum entropy closure quadratic fit polynomials are presented. For a general distribution without rotation symmetry, the expression for the entropy is exploited to derive an explicit form for the maximum entropy distribution. Lowest order approximation of this distribution function leads to simple closure forms for the fourth order alignment tensor and also for higher order alignment tensors

Computational Algorithm for Approximating Fractional Derivatives of Functions

This paper presents an algorithmic approach for numerically solving Caputo fractional differentiation. The trapezoidal rule was modified, the new modification was used to derive an algorithm to approximate fractional derivatives of order α > 0, the fractional derivative used was based on Caputo definition for a given function by a weighted sum of function and its ordinary derivatives values at specified points. The trapezoidal rule was used in conjunction with the finite difference scheme which is the forward, backward and central difference to derive the computational algorithm for the numerical approximation of Caputo fractional derivative for evaluating functions of fractional order. The study was conducted through some illustrative examples and analysis of error

Comparative Analysis of Rainfall-Runoff Modeling Using Support Vector Machines for Two Dams in Uttarakhand

The main objective of this study was to evaluate and compare the performances of rainfall-runoff models that were developed by using support vector machines (SVMs). Rainfall and runoff data of Haripura and Baur dams were adopted on daily basis from Irrigation Division Rudrapur in Uttarakhand. In this study, radial kernel function was used. As the values of Cost function (C),  and  varies, performances of the models can be altered. So, at optimum values of these variables, there exists a best correlation between rainfall and runoff. It can be inferred from the study that SVM models provide satisfactory results for both dams. These results can be used for runoff prediction for various purpose such as irrigation etc

Calibration Ratio Estimators of Population Mean Using Median of Auxiliary Variable

In this study we propose a calibration ratio estimator and a calibration separate ratio-product estimator of population mean of study variable under stratified sampling using the median of auxiliary variable. The calibration estimator used calibrated weight determined to minimize a chi-square distance measure subject to a set of constraint related to the auxiliary variable in other to increase precision of the estimators. The median of the auxiliary variable was used in defining the calibration constraints. The variances of the proposed estimators were also obtained. An empirical study to ascertain the performance of these estimators using simulated data under underlying distribution assumption of Student-T distribution, Cauchy distribution, Lognormal distribution, and Standard normal distribution with varying sample sizes of 10%, 20%, and 25% were carried out. The result of simulation reveals that when the underlying distribution is Student-T, at 10% sample size, the efficiency performance of the proposed calibration separate ratio-product estimator is better than other competing estimators. As the sample size is increased to 20% and 25%, the efficiency performance of the existing stratified ratio estimator and existing calibration ratio estimator respectively become better than the other estimators. Under the skewed distributions (Cauchy and Lognormal) and the standard normal distribution, it is observed that the proposed calibration ratio estimator is better than other competing estimators in terms of efficiency, consistency and reliability. The result also reveals that under the lognormal distribution, the conventional stratified ratio estimator and the conventional calibration ratio estimator give the same result

Development and Validation of a 3-Dimensional Flexible Laryngoscopy Training Simulator

The objective of this study was to validate the use of a 3-Dimensional Flexible Laryngoscopy Training Simulator. This is a simulation device development and validation study. Anonymized CT scan data from a head/neck CT of a patient with normal anatomy was imported and a head/neck digital model was created. A 3D simulation model was printed using a stiff (Stratasys Vero) and flexible (Stratasys Agilus) material combination with a ShoreA hardness value of 60. Novices and experts were instructed and provided 5 trials to pass the laryngoscope. The videos of the first and the last trial were recorded and evaluated by three different evaluators. Performances were measured by the amount of time spent and precision of the task. Repeated measures of ANOVA and generalized linear model with binomial proportion was used were utilized to analyze the data. The post training scores were statistically significantly higher than pre training scores (Mean: 15.57 vs. 13.01, p  <0.0001) controlling for trainee experience. The time taken to complete a successful pass post training was statistically significantly lesser than pre training (Mean: 62.55 secs vs. 36.36 secs, p-value = 0.0007) controlling for individual’s experience. The odds of becoming skilled at the task was 4 times higher post training in comparison to pre training, controlling for individual’s experience (OR: 4.05, p-value: 0.0026). The 3-Dimensional Flexible Laryngoscopy Training Simulator is a valid trainer for both novice and experienced individuals. The simulator can improve technical skill performance and is critical for medical training

Ground-state Shallow-donor Binding Energy in (In,Ga)N/GaN Double QWs Under Temperature, Size, and the Impurity Position Effects

In this paper, we study the hydrogen-like donor-impurity binding energy of the ground-state change as a function of the well width under the effect of temperature, size, and impurity position. Within the framework of the effective mass approximation, the Schrodinger-Poisson equation has been solved taken account an on-center hydrogen-like impurity in double QWs with rectangular finite confinement potential profile for 10% of indium concentration in the (well region). The eigenvalues and their correspondent eigenvectors have been obtained by the fined element method (FEM). The obtained results are in good agreement with the literature and show that the temperature, size, and the impurity position have a significant impact on the binding energy of a hydrogen-like impurity in symmetric double coupled quantum wells based on non-polar wurtzite (In,Ga) N/GaN core/Shell

Classification of Disaster Risks in the Philippines using Adaptive Boosting Algorithm with Decision Trees and Support Vector Machine as Based Estimators

This paper employed the intelligent approach based on machine learning categorized as base and ensemble methods in classifying the disaster risk in the Philippines. It focused on the Decision Trees, Support Vector Machine, Adaptive Boosting Algorithm with Decision Trees, and Support Vector Machine as base estimators. The research used the Exponential Regression for missing value imputation and converted the number of casualties, damaged houses, and properties into five (5) risk levels using Quantile Method. The 10-fold cross-validation was used to validate the proposed algorithms. The experiment shows that Decision Trees and Adaptive Decision Trees are the most suitable models for the disaster data with the score of more than 90%, more than 75%, more than  75%  in all the classification metrics (accuracy, precision, recall f1-score) when applied to classification risk levels of casualties, damaged houses and damaged properties respectively

Ground-state Shallow-donor Binding Energy in (In,Ga)N/GaN Double QWs Under Temperature, Size, and the Impurity Position Effects

In this paper, we study the hydrogen-like donor-impurity binding energy of the ground-state change as a function of the well width under the effect of temperature, size, and impurity position. Within the framework of the effective mass approximation, the Schrodinger-Poisson equation has been solved taken account an on-center hydrogen-like impurity in double QWs with rectangular finite confinement potential profile for 10% of indium concentration in the (well region). The eigenvalues and their correspondent eigenvectors have been obtained by the fined element method (FEM). The obtained results are in good agreement with the literature and show that the temperature, size, and the impurity position have a significant impact on the binding energy of a hydrogen-like impurity in symmetric double coupled quantum wells based on non-polar wurtzite (In,Ga) N/GaN core/Shell

Using Artificial Intelligence Techniques for Prediction and Estimation of Photovoltaic System Output Power

Two artificial intelligence methods, namely, support vector machines (SVM) and gene expression programming (GEP), were explored for prediction and estimation of the Photovoltaic (PV)output power. Measured values of temperature T (°C) and irradiance E (kWh/㎡) were used as inputs (independent variables) and PV output power P (Kw) was used as output (dependent variable). The statistical metrics were used to assess the predictive performances of the methods. The results of the two models were estimated and compared. The results showed that the two techniques performances are better and similar. Using GEP technique, the relationships between the two parameters and output power were established. Importance of each parameter as contributor to PV output power was also investigated. The results indicated that the SVM and GEP would become the powerful tools that could help estimate the PV output power capacity reserve