Self-Reported Changes in Organizational Commitment : The Relationship between Present Organizational Commitment and its Perceived Changes over Time

A sample of 188 university employees was surveyed about present levels of organizational commitment and beliefs about changes in commitment over time. Both present levels of commitment and self-reported increases in each of the three forms of commitment (i.e., affective, continuance, and normative) were negatively associated with turnover intention, with present levels of commitment producing correlations of a significantly greater magnitude. In a simplified model, all present forms of commitment combined with age were found to be significant predictors. A moderation effect was found for continuance commitment, in that as magnitude of beliefs about continuance commitment increasing over time grew, so did the negative relationship of continuance commitment to turnover intention. This effect was only found at low levels of present continuance commitment. Sequential polynomial regression revealed nonlinear relationships of tenure with each form of commitment. Cubic models were adopted for both affective and normative commitment while a quadratic model was adopted for continuance commitment.  M.A

Enabling Machine Science through Distributed Human Computing

Distributed human computing techniques have been shown to be effective ways of accessing the problem-solving capabilities of a large group of anonymous individuals over the World Wide Web. They have been successfully applied to such diverse domains as computer security, biology and astronomy. The success of distributed human computing in various domains suggests that it can be utilized for complex collaborative problem solving. Thus it could be used for machine science : utilizing machines to facilitate the vetting of disparate human hypotheses for solving scientific and engineering problems. In this thesis, we show that machine science is possible through distributed human computing methods for some tasks. By enabling anonymous individuals to collaborate in a way that parallels the scientific method -- suggesting hypotheses, testing and then communicating them for vetting by other participants -- we demonstrate that a crowd can together define robot control strategies, design robot morphologies capable of fast-forward locomotion and contribute features to machine learning models for residential electric energy usage. We also introduce a new methodology for empowering a fully automated robot design system by seeding it with intuitions distilled from the crowd. Our findings suggest that increasingly large, diverse and complex collaborations that combine people and machines in the right way may enable problem solving in a wide range of fields

Efficient Training Set Use For Blood Pressure Prediction in a Large Scale Learning Classifier System

ABSTRACT We define a machine learning problem to forecast arterial blood pressure. Our goal is to solve this problem with a large scale learning classifier system. Because learning classifiers systems are extremely computationally intensive and this problem's eventually large training set will be very costly to execute, we address how to use less of the training set while not negatively impacting learning accuracy. Our approach is to allow competition among solutions which have not been evaluated on the entire training set. The best of these solutions are then evaluated on more of the training set while their offspring start off being evaluated on less of the training set. To keep selection fair, we divide competing solutions according to how many training examples they have been tested on

Toward energy Autonomy in heterogeneous Modular Plant-Inspired Robots through Artificial evolution

Contemporary robots perform energy intensive tasks—e.g., manipulation and locomotion—making the development of energy autonomous robots challenging. Since plants are primary energy producers in natural ecosystems, we took plants as a source of inspiration for designing our robotics platform. This led us to investigate energy autonomy in robots through employing solar panels. As plants move slowly compared to other large terrestrial organisms, it is expected that plant-inspired robots can enable robotic applications, such as long-term monitoring and exploration, where energy consumption could be minimized. Since it is difficult to manually design robotic systems that adhere to full energy autonomy, we utilize evolutionary algorithms to automate the design and evaluation of energy harvesting robots. We demonstrate how artificial evolution can lead to the design and control of a modular plant-like robot. Robotic phenotypes were acquired through implementing an evolutionary algorithm, a generative encoding and modular building blocks in a simulation environment. The generative encoding is based on a context sensitive Lindenmayer-System (L-System) and the evolutionary algorithm is used to optimize compositions of heterogeneous modular building blocks in the simulation environment. Phenotypes that evolved from the simulation environment are in turn transferred to a physical robot platform. The robotics platform consists of five different types of modules: (1) a base module, (2) a cube module, (3) servo modules, and (4,5) two types of solar panel modules that are used to harvest energy. The control system for the platform is initially evolved in the simulation environment and afterward transferred to an actual physical robot. A few experiments were done showing the relationship between energy cost and the amount of light tracking that evolved in the simulation. The reconfigurable modular robots are eventually used to harvest light with the possibility to be reconfigured based on the needs of the designer, the type of usable modules, and/or the optimal configuration derived from the simulation environment. Long-term energy autonomy has not been tested in this robotics platform. However, we think our robotics platform can serve as a stepping stone toward full energy autonomy in modular robots

Review of \u3ci\u3eTwentieth-Century Texas: A Social and Cultural History.\u3c/i\u3e Edited by John W. Storey and Mary L. Kelley

Given such a large body of scholarship, editors John W. Storey and Mary L. Kelley admit, another study of Texas seems hardly necessary. Nevertheless, they contend, Twentieth Century Texas: A Social and Cultural History (a collection of fifteen essays) fills a weakness in the Lone Star State\u27s history bibliography, arguing that social and cultural subjects have received short shrift in survey texts. Moreover, Storey and Kelly justify their volume because it focuses solely on the past century, bringing the story up-to-date. All students of Texas\u27s past will enjoy this collection. Summary histories of Mexican Texans, blacks, women, literature, education, and cinema are worthwhile for those beginning their study of twentieth-century Texas. For more knowledgeable students, the collection introduces topics they can pursue in articles or books by the same authors. For example, Kelley ( Private Wealth, Public Good: Texans and Philanthropy ) and Ralph A. Wooster ( Over Here: Texans on the Home Front ) have written books on these themes. Teachers will find Twentieth-Century Texas useful as a source of information and a stimulus for new classroom topics. Perhaps the most beneficial article for lecture details is Storey\u27s compilation of data on Texans\u27 religious diversity in Pagodas amid the Steeples: The Changing Religious Landscape. Michael R. Grauer\u27s Wider Than the Limits of Our State: Texas Art in the Twentieth Century synthesizes the essentials on an understudied subject. Gary Hartman\u27s From Yellow Roses to Dixie Chicks: Women and Gender in Texas Music History suggests an entertaining and informative lesson (just add music). On the other hand, the book\u27s bulk (480 pages) means Twentieth Century Texas is not a narrow reader helpful as a supplement to a textbook

Governor Leroy Collins of Florida and the Selma Crisis of 1965

On Tuesday, March 9, 1965, a bright sun shone on Selma, Alabama, replacing the gray, gloomy weather which had blanketed the city for days. Despite the sixty degree temperature, the air held a winter crispness. Most of the people gathered at Brown’s Chapel wore heavy overcoats and gloves. The nervous conversations grew into an expectant murmur and then applause as a young black man came into view. He walked among the crowd, touched the extended hands, and moved to the church steps to speak. He was their leader. Arguments about whether or not to march ended. They would abide by his decision. The deep, resonant voice of the Reverend Martin Luther King, Jr., boomed out across the churchyard proclaiming, “I have no alternative but to lead a march from this spot to carry our grievances to the seat of government. I have made my choice. I have got to march.