Reynolds Community College

Adults with autism often face barriers to community access for work and leisure, yet few programs address transportation independence and safety. This study evaluated the Safe Rideshare Program (SRP), designed to teach autistic adults to use rideshare services. To assess acceptability, appropriateness, and the potential impact of the SRP and to evaluate changes in rideshare use for community access over a 2-mo follow-up period. A one-group, pretest-posttest study. Community. Thirteen autistic adults. The SRP consisted of five virtual training modules completed synchronously with project trainers via Zoom, followed by eight ride-along sessions using either Uber or Lyft rideshare services. Intervention acceptability was rated by participants using the Acceptability of Intervention Measure. Appropriateness of the intervention was assessed by trainers using the Intervention Appropriateness Measure. A 30-item Rideshare Independence Checklist was used to assess independence and safety using rideshare services. Of the 13 enrolled participants, 12 completed the program with strong acceptability and appropriateness ratings (≥75% threshold was met). Independence and safety significantly improved during the intervention, and at the 2-mo follow-up, 8 participants reported increased independent rides (p = .011). The SRP demonstrated preliminary acceptability and appropriateness, as well as the potential to improve transportation independence, safety, and community access for autistic adults. Plain-Language Summary: Many autistic adults face challenges accessing their communities for work, shopping, or social activities because of transportation barriers. Learning how to use rideshare services, such as Uber or Lyft, can help address this issue, but few programs are designed to teach these skills safely and effectively. To fill this gap, our team developed the Safe Rideshare Program (SRP) and tested its usefulness. Thirteen autistic adults, ages 18 to 24 yr, participated in this study. Most participants completed the entire program and gave it high ratings for being easy to follow and helpful. Trainers who worked with the participants also reported that the program was useful. By the end of the training, participants showed significant improvements in their ability to use rideshare services independently and safely. Two months after finishing the program, many participants continued to use rideshare services. On the basis of our preliminary findings, we believe that the SRP shows promise in helping autistic adults overcome transportation barriers and gain more independence. With improved access to transportation, participants were able to engage in more community activities, which can improve their quality of life and open up new opportunities for engagement.

The Internet of Things (IoT) is increasingly deployed at the edge under resource and environmental constraints, which limits the practicality of traditional intrusion detection systems (IDSs) on IoT hardware. This paper presents two IDS configurations. First, we develop a baseline IDS with fixed hyperparameters, achieving 99.20% accuracy and ~0.002 ms/sample inference latency on a desktop machine; this configuration is suitable for high-performance platforms but is not intended for constrained IoT deployment. Second, we propose a lightweight, edge-oriented IDS that applies ANOVA-based filter feature selection and uses a genetic algorithm (GA) for the bounded hyperparameter tuning of the classifier under stratified cross-validation, enabling efficient execution on Raspberry Pi-class devices. The lightweight IDS achieves 98.95% accuracy with ~4.3 ms/sample end-to-end inference latency on Raspberry Pi while detecting both low-volume and high-volume (DoS/DDoS) attacks. Experiments are conducted in a Raspberry Pi-based real lab using an up-to-date mixed-modal dataset combining system/network telemetry and heterogeneous physical sensors. Overall, the proposed framework demonstrates a practical, hardware-aware, and reproducible way to balance detection performance and edge-level latency using established techniques for real-world IoT IDS deployment.

Internet has revolutionized the technological era, which has a significant impact on us by making communication much better not only with the living beings but also with non-living things through the medium of internet of things (IoT). Thus, this topic highlights how internet of things can minimize user intervention in controlling home appliances and monitoring its setting. Integrating IoT with cloud computing and web service helps us in providing feasibility in accessing home appliances (i.e., monitoring appliances and measuring home condition). The whole process of integration aims to create an intelligent system. Thus, smart home is one of the application of IoT aimed at improving comfort, safety, and wellbeing within our homes.

In their introduction to Developing faculty learning communities at two-year colleges: Collaborative models to improve teaching and learning, Susan Sipple and Robin Lightner point to the findings o...

Struma ovarii, a rare germ cell tumor of the ovary composed of >50% thyroid tissue, is traditionally managed by gynecologic surgeons. Although struma ovarii is typically cured by simple excision, otolaryngology-head and neck surgeons may play a critical role in caring for these patients. In this article, we present two cases of struma ovarii and discuss the role of the otolaryngologist.

Through the stimulus of war and concerns about neuropsychiatric disability, the U.S. military developed methods to rapidly screen the mental health of World War I and II draftees. Intelligence testing and brief psychiatric screening expanded the accession physical examination and underwent revision to identify only gross mental health disability. Supplemental psychiatric evaluations and written psychological screening tools were abandoned after postwar assessments; they demonstrated poor predictive power in evaluating recruit service capacity for combat environments. Currently, only three mental health accession tools are used to screen applicants before their entrance into military service, namely, educational achievement, cognitive testing, and a cursory psychiatric evaluation. The Navy and Air Force use a fourth screening measure during entry-level training. Educational attainment with high school graduation has been the strongest predictor of finishing a service term. The purpose of this article is to provide both a historical review and a review of testing efforts.