Component Skills of Reading Among Learners of Chinese as a Second Language.

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2018

Principal Component Analysis

This book is aimed at raising awareness of researchers, scientists and engineers on the benefits of Principal Component Analysis (PCA) in data analysis. In this book, the reader will find the applications of PCA in fields such as taxonomy, biology, pharmacy,finance, agriculture, ecology, health and architecture

Automatic Seizure Detection Based on Star Graph Topological Indices

[Abstract] The recognition of seizures is very important for the diagnosis of patients with epilepsy. The seizure is a process of rhythmic discharge in brain and occurs rarely and unpredictably. This behavior generates a need of an automatic detection of seizures by using the signals of long-term electroencephalography (EEG) recordings. Due to the non-stationary character of EEG signals, the conventional methods of frequency analysis are not the best alternative to obtain good results in diagnostic purpose. The present work proposes a method of EEG signal analysis based on star graph topological indices (SGTIs) for the first time. The signal information, such as amplitude and time occurrence, is codified into invariant SGTIs which are the basis for the classification models that can discriminate the epileptic EEG records from the non-epileptic ones. The method with SGTIs and the simplest linear discriminant methods provide similar results to those previously published, which are based on the time-frequency analysis and artificial neural networks. Thus, this work proposes a simpler and faster alternative for automatic detection of seizures from the EEG recordings.Xunta de Galicia; 2007/127Xunta de Galicia; 2007/144Instituto de Salud Carlos III; PIO52048Instituto de Salud Carlos III; RD07/0067/0005Ministerio de Ciencia e Innovación; TIN2009—07707

Bright or dark, or virtues and vices? A reexamination of the big five and job performance

Personality research in industrial/organizational psychology has been dominated by the description of personality traits and outcomes as either bright or dark. Unfortunately, research has shown that bright traits have dark outcomes and vice versa, suggesting that a paradox is plaguing the literature. To resolve this paradox, I propose that a different heuristic stemming from positive psychology be utilized: virtues and vices. Virtues refer to exercises of human excellence while vices refer to actions of human failure. Drawing on the virtue ethics concept of the Aristotelian mean, dark traits are viewed as extreme or elevated levels of bright personality traits, allowing both to be described by a common set of dimensions. Further, I posit that under certain circumstances, even extreme trait standings might result in acts of human excellence. Importantly, this resolution implies that nonlinear relationships may accurately describe the functional form of relationships linking personality dimensions to valued outcomes. To test this model, I applied the virtues and vices heuristic to five basic personality dimensions (the Big Five) described by the Five-Factor Model (FFM) of personality in order to construct a measurement model that views extreme levels of these dimensions as dark. To develop this measurement model, trained item writers generated nine hundred fifty-eight items according to these specifications (approximately 30 items per each of the 30 narrow traits of the FFM). Two subject-matter experts rated these items on extremity for the purposes of reducing this initial item pool to a smaller set of usable resulted in a set of three hundred items that were administered to a sample of 728 working employees obtained through Amazon\u27s Mechanical Turk along with self-descriptions of task performance, organizational citizenship, and deviant work behavior (outcomes widely accepted as either virtuous or vice-like). Ideal-point item-response theory was used to estimate person parameters for the five personality dimensions. Small nonlinear effects were detected linking several traits and outcomes. Small-n employee selection scenarios were simulated to demonstrate the practical importance of these small effects. Implications for theory and practice are discussed

Abstracts of Papers, 79th Annual Meeting of the Virginia Academy of Science, May 22-25, 2001, James Madison University, Harrisonburg, Virginia

Abstracts of papers that were presented at the 79th Annual Meeting of the Virginia Academy of Science, May 22-25, 2001, James Madison University, Harrisonburg, Virginia