Intelligent computer-aided training authoring environment

Although there has been much research into intelligent tutoring systems (ITS), there are few authoring systems available that support ITS metaphors. Instructional developers are generally obliged to use tools designed for creating on-line books. We are currently developing an authoring environment derived from NASA's research on intelligent computer-aided training (ICAT). The ICAT metaphor, currently in use at NASA has proven effective in disciplines from satellite deployment to high school physics. This technique provides a personal trainer (PT) who instructs the student using a simulated work environment (SWE). The PT acts as a tutor, providing individualized instruction and assistance to each student. Teaching in an SWE allows the student to learn tasks by doing them, rather than by reading about them. This authoring environment will expedite ICAT development by providing a tool set that guides the trainer modeling process. Additionally, this environment provides a vehicle for distributing NASA's ICAT technology to the private sector

Can Self-Organizing Maps accurately predict photometric redshifts?

We present an unsupervised machine learning approach that can be employed for estimating photometric redshifts. The proposed method is based on a vector quantization approach called Self--Organizing Mapping (SOM). A variety of photometrically derived input values were utilized from the Sloan Digital Sky Survey's Main Galaxy Sample, Luminous Red Galaxy, and Quasar samples along with the PHAT0 data set from the PHoto-z Accuracy Testing project. Regression results obtained with this new approach were evaluated in terms of root mean square error (RMSE) to estimate the accuracy of the photometric redshift estimates. The results demonstrate competitive RMSE and outlier percentages when compared with several other popular approaches such as Artificial Neural Networks and Gaussian Process Regression. SOM RMSE--results (using $\Delta$z=z$_{phot}$--z$_{spec}$) for the Main Galaxy Sample are 0.023, for the Luminous Red Galaxy sample 0.027, Quasars are 0.418, and PHAT0 synthetic data are 0.022. The results demonstrate that there are non--unique solutions for estimating SOM RMSEs. Further research is needed in order to find more robust estimation techniques using SOMs, but the results herein are a positive indication of their capabilities when compared with other well-known methods.Comment: 5 pages, 3 figures, submitted to PAS

Spread in flat rolling

A velocity field was derived for a flat workpiece undergoing plastic deformation between cylindrical rolls in a rolling mill. Using the velocity field, an expression was written for the total power input required for the rolling process in terms of the process parameters: roll diameter, thickness reduction, workpiece geometry, surface friction, and spread. The Upper Bound Theorem was applied to the power expression to establish an upper limit on it. This limit was minimized with respect to spread to determine the value of spread requiring the least amount of input power

Using O*NET to Develop a Framework of Job Characteristics to Potentially Improve the Predictive Validity of Personality Measures

It has long been theorized that we can improve prediction of job-related behavior from measures of personality by identifying job characteristics that allow for the expression of individual differences (e.g., Mischel, 1968). Using O*NET data, the current paper develops a framework for job characteristics that could improve the extent to which we can predict behavior from personality. More specifically, it investigates relationships between Work Styles, Generalized Work Activities, and Work Context variables. Job characteristics varied in importance as a function of four Work Styles composites: achievement, people orientation, stability, and attention to detail, and the relationships were largely consistent with the tenants of Trait Activation Theory (Tett & Burnett, 2003). In addition to limitations and future directions, the discussion section contains implications of the current study for practitioners, including implications for hiring practices and job placement

The Mediating Role of Sleep in the Associations of Adult Attachment and Self Disclosure in Romantic Relationships

Research has shown that adult attachment style predicts self disclosure in relationships (Chen, Hi, Shi, & Chen, 2019 as cited in Collins and Allard, 2007). Previous research has also pointed to a positive relationship between healthy attachment and well-being, as well as sleep quality (Escolas, Hildebrandt, Maiers, Baker, & Mason, 2013 via Verdecia, Jean-Louis, Zizi, Casimir, & Browne, 2009). The purpose of this study was to examine sleep as a possible mediator between attachment styles and self disclosure. The current sample consisted of 202 participants recruited from Amazon Mechanical Turk (MTurk). Results indicated that sleep quality (indicated by sleepiness and insomnia) mediated the relationship between attachment and self disclosure. Future research may explore the potential benefits of high sleep quality to those who demonstrate avoidant or anxious attachment styles, as it could increase self disclosure in relationships