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This paper discusses an all-encompassing approach to increase the number of students in engineering through innovative outreach, recruiting, and retention programs. Prior to adopting these programs, the School of Electrical and Computer Engineering (ECE) at the University of Oklahoma (OU), Norman, experienced a reduction in engineering enrollment similar to the trend that has occurred across the U.S. over the last few years. As a result, the school investigated the key factors that influence selection of engineering as a career path and initiated a corrective program to reverse this trend. The program involves focusing on the present through retention, on the immediate future through recruiting, and on the distant future through outreach. The focus of all of these programs is to mobilize the OU-ECE faculty and student body to present advanced engineering technologies, innovative demonstrations, and hands-on activities at a level that the individual student can understand and appreciate. Student surveys and interviews are used to assess the program qualitatively, and OU-ECE enrollment numbers are used as a quantitative assessment. [ABSTRACT FROM PUBLISHER]

Hardware platforms for socially interactive robotics can be limited by cost or lack of functionality. This article presents the overall system—design, hardware, and software—for Quori, a novel, affordable, socially interactive humanoid robot platform for facilitating noncontact human–robot interaction (HRI) research. The design of the system is motivated by feedback sampled from the HRI research community. The overall design maintains a balance of affordability and functionality. Initial Quori testing and a six-month deployment are presented. Ten Quori platforms have been awarded to a diverse group of researchers from across the United States to facilitate HRI research to build a community database from a common platform. [ABSTRACT FROM AUTHOR]

Autism Spectrum Disorder (ASD) affects 1 in 54 children in the United States. A core social communication skill negatively impacted by ASD is joint attention (JA), which influences the development of language, cognitive, and social skills from infancy onward. Although several technology-based JA studies have shown potential, they primarily focus on response to joint attention (RJA). The other important component of JA, the initiation of joint attention (IJA), has received less attention from a technology-based intervention perspective. In this work, we present an immersive Computer-mediated Caregiver-Child Interaction (C3I) system to help children with ASD practice IJA skills. C3I is a novel computerized intervention system that integrates a caregiver in the teaching loop, thereby preserving the advantages of both human and computer-administered intervention. A feasibility study with 6 dyads (caregiver-child with ASD) was conducted. A near significant increase with medium effect size on IJA performance was observed. Meanwhile, physiology-based stress analysis showed that C3I did not increase stress of the caregivers over the course of the study. To the best of our knowledge, this is the first autonomous system designed for teaching IJA skills to children with ASD incorporating caregivers within the loop to enhance the potential for generalization in real-world. [ABSTRACT FROM AUTHOR]

Agent-based models have long been used to generate states of variables at individual and aggregate levels. More recently, robotic and computer agents are being given forms in which internal dispositions such as cognitive reasoning, emotions, and preferences are represented. We note limitations in most common representations of preferences in these applications and propose conditions for dynamic forms of the variable. A consequence of the dynamics we propose is that preferences exhibit continuous variation in restricted intervals while maintaining characteristic differences between entities and over time. After giving a form to preferences in a situated application to a consumption system, analytical and computational methods are used to establish that dynamics in the system have properties we describe. We then derive dependencies of the restricted intervals in which preferences typically vary. Estimation of these intervals is exemplified in data on the U.S. economy. The system is then embodied in a network form in which cycle and randomness from environments and their interactions are represented. A demonstration of stochastic resonance in the networked system supports the imputed dynamics. The network model is also used to indicate network dependencies of the bounds of the interval in which preferences vary. Finally, the relevance of the dynamics that are proposed in preferences to other internal dispositions that include emotion in agent-based models is discussed. [ABSTRACT FROM AUTHOR]

Reacting to the turbulent events of the last decade or so, the U.S. government has focused much attention on developing strategies to curtail the misuse of technology, especially biological agents. In principle, any technology can be exploited and used to achieve malicious ends. This is an especially poignant issue now that we have reached the digital age and that an individual person?s actions can have an impact that spans across the globe. One way in which a malicious actor could cause serious harm is by manipulating how a robot functions. [ABSTRACT FROM AUTHOR]

Presents a study which investigated the interactions between humans and robots during the robot-assisted Urban Search and Rescue (USAR) response at the World Trade Center in New York City after the September 11, 2001 terrorist attacks. Examination of related work on USAR as a robotic domain, hardware and software development; Discussion of the robot-assisted response in terms of environment and conditions, agents and skills; Results from the post-hoc data analysis.