Confidence Intervals for Comparison of the Squared Multiple Correlation Coefficients of Non-nested Models

Multiple linear regression analysis is used widely to evaluate how an outcome or responsevariable is related to a set of predictors. Once a final model is specified, the interpretation of predictors can be achieved by assessing the relative importance of predictors. A common approach to predictor importance is to compare the increase in squared multiple correlation for a given model when one predictor is added to the increase when another predictor is added to the same model. This thesis proposes asymmetric confidence-intervals for a difference between two correlated squared multiple correlation coefficients of non-nested models. These new proceduresare developed by recovering variance estimates needed for the difference from asymmetric confidence limits for single multiple correlation coefficients. Simulation resultsshow that the new procedure based on confidence limits obtained from the two-moment scaled central F approximation performs much better than the traditional Wald approach. Two examples are used to illustrate the methodology. The application of the procedure indominance analysis and commonality analysis is discussed

Stress-intensity factor calculations using the boundary force method

The Boundary Force Method (BFM) was formulated for the three fundamental problems of elasticity: the stress boundary value problem, the displacement boundary value problem, and the mixed boundary value problem. Because the BFM is a form of an indirect boundary element method, only the boundaries of the region of interest are modeled. The elasticity solution for the stress distribution due to concentrated forces and a moment applied at an arbitrary point in a cracked infinite plate is used as the fundamental solution. Thus, unlike other boundary element methods, here the crack face need not be modeled as part of the boundary. The formulation of the BFM is described and the accuracy of the method is established by analyzing a center-cracked specimen subjected to mixed boundary conditions and a three-hole cracked configuration subjected to traction boundary conditions. The results obtained are in good agreement with accepted numerical solutions. The method is then used to generate stress-intensity solutions for two common cracked configurations: an edge crack emanating from a semi-elliptical notch, and an edge crack emanating from a V-notch. The BFM is a versatile technique that can be used to obtain very accurate stress intensity factors for complex crack configurations subjected to stress, displacement, or mixed boundary conditions. The method requires a minimal amount of modeling effort

Boundary force method for analyzing two-dimensional cracked bodies

The Boundary Force Method (BFM) was formulated for the two-dimensional stress analysis of complex crack configurations. In this method, only the boundaries of the region of interest are modeled. The boundaries are divided into a finite number of straight-line segments, and at the center of each segment, concentrated forces and a moment are applied. This set of unknown forces and moments is calculated to satisfy the prescribed boundary conditions of the problem. The elasticity solution for the stress distribution due to concentrated forces and a moment applied at an arbitrary point in a cracked infinite plate are used as the fundamental solution. Thus, the crack need not be modeled as part of the boundary. The formulation of the BFM is described and the accuracy of the method is established by analyzing several crack configurations for which accepted stress-intensity factor solutions are known. The crack configurations investigated include mode I and mixed mode (mode I and II) problems. The results obtained are, in general, within + or - 0.5 percent of accurate numerical solutions. The versatility of the method is demonstrated through the analysis of complex crack configurations for which limited or no solutions are known

A re-evaluation of finite-element models and stress-intensity factors for surface cracks emanating from stress concentrations

A re-evaluation of the 3-D finite-element models and methods used to analyze surface crack at stress concentrations is presented. Previous finite-element models used by Raju and Newman for surface and corner cracks at holes were shown to have ill-shaped elements at the intersection of the hole and crack boundaries. These ill-shaped elements tended to make the model too stiff and, hence, gave lower stress-intensity factors near the hole-crack intersection than models without these elements. Improved models, without these ill-shaped elements, were developed for a surface crack at a circular hole and at a semi-circular edge notch. Stress-intensity factors were calculated by both the nodal-force and virtual-crack-closure methods. Both methods and different models gave essentially the same results. Comparisons made between the previously developed stress-intensity factor equations and the results from the improved models agreed well except for configurations with large notch-radii-to-plate-thickness ratios. Stress-intensity factors for a semi-elliptical surface crack located at the center of a semi-circular edge notch in a plate subjected to remote tensile loadings were calculated using the improved models. The ratio of crack depth to crack length ranged form 0.4 to 2; the ratio of crack depth to plate thickness ranged from 0.2 to 0.8; and the ratio of notch radius to the plate thickness ranged from 1 to 3. The models had about 15,000 degrees-of-freedom. Stress-intensity factors were calculated by using the nodal-force method

Non-stationary discrete convolution kernel for multimodal process monitoring

Data-driven process monitoring has benefited from the development and application of kernel transformations, especially when various types of nonlinearity exist in the data. However, when dealing with the multimodality behavior which is frequently observed in process operations, the most widely used Radial Basis Function kernel has limitations in describing process data collected from multiple normal operating modes. In this paper, we highlight this limitation via a synthesized example. In order to account for the multimodality behavior and improve fault detection performance accordingly, we propose a novel Non-stationary Discrete Convolution kernel, which derives from the convolution kernel structure, as an alternative to the RBF kernel. By assuming the training samples to be the support of the discrete convolution, this new kernel can properly address these training samples from different operating modes with diverse properties, and therefore can improve the data description and fault detection performance. Its performance is compared with RBF kernels under a standard kernel PCA framework and with other methods proposed for multimode process monitoring via numerical examples. Moreover, a benchmark data set collected from a pilot-scale multiphase flow facility is used to demonstrate the advantages of the new kernel when applied to an experimental data set

STUDENTS’ MATHEMATICS ATTITUDES AND METACOGNITIVE PROCESSES IN MATHEMATICAL PROBLEM SOLVING

Mathematical problem solving is considered as one of the many endpoints in teaching Mathematics to students. This study looked into the performance in mathematics problem solving among fourth year students of Central Mindanao University Laboratory High School and their relationship with students’ attitudes towards Mathematics. The attitudes measured were Attitude towards success in Math, Mother’s mathematics attitude, Father’s mathematics attitude, Motivation, Usefulness of Math, Teacher’s mathematics attitude, Confidence in learning math, and mathematics anxiety. It also investigated the metacognitive processes of students considering varying levels of their mathematics anxiety. It used the responses of 127 students. Of the 127, (nine) 9 were selected according to their mathematics anxiety levels to determine and compare their metacognitive processes. Results showed that students consider Mathematics as useful and they have a positive attitude towards success in Mathematics. The students’ fathers, mothers, and teachers also have positive attitudes towards their mathematics learning. However, overall, the students’ performance in mathematics problem solving is considered poor. Among the eight (8) mathematics attitudes only confidence in learning Math and mathematics anxiety were correlated with performance in mathematics problem solving. Confidence in learning Math was positively correlated, while mathematics anxiety was negatively correlated with performance in mathematics problem solving. Students with high mathematics anxiety tend to confirm their solutions with their classmates. Students with moderate anxiety are test-anxious and those with low anxiety are distracted by external factors, but can readily shift their focus back to problem solving. The three (3) cases showed that students with low, moderate, and high mathematics anxiety employed mostly orientation and execution procedures. There were only few instances of verification and lesser instances of organization procedures. Self-questioning was the most observed metacognitive skill. Furthermore, students from the three (3) cases were unable to correctly answer two (2) problems, both of which are non-routine due to unfamiliarity and “experiential interference”.  Article visualizations