62021 research outputs found
Sort by
Crowd Scene Anomaly Detection in Online Videos
Get PDFThe prevalence of surveillance cameras in public places has led to an extremely pressing need for effective position and crowd monitoring, as well as anomaly detection. This paper tends to exhibit an incorporated approach that combines state-of-the-art computer vision techniques for comprehensive crowd surveillance. The main features of this novel approach are summarized into four steps: (a) Object detection and tracking; (b) Geometric rectification for positioning; (c) Motion extraction; and (d) Anomaly detection. First, this uses YOLOv5's Convolutional Neural Network (CNN) model in making efficient detection of objects, focusing on spotting individuals within crowded scenes. After detection, a strong mechanism for tracking is established with the help of the DeepSORT algorithm, which can track the person across frames. It has to gain the people's position in the video frame and analyze motion data with the guarantee of capture of camera-scene geometry. Each frame thus gets converted from the 3D perspective to a 2D bird's eye view within the surveillance video, giving a guarantee of capture of the geometry of a camera scene. Motion anomaly detection is addressed through statistical methods, with Kernel Density Estimation (KDE) being employed to identify deviations from normal motion patterns. Extensive experiments conducted on different online crowd scene video datasets validate the effectiveness of the proposed anomaly detection mechanism. Overall, this integrated approach proposes a promising solution to crowd surveillance, further development of object detection, tracking, and anomaly analysis for monitoring public spaces.No embargoAcademic Major: Computer Science and Engineerin
The Moritz Briefing (October/November 2024)
No full textAn occasional newsletter highlighting recent activities and achievements of the Moritz Faculty
Support Beyond the Studio: Feminist Praxis and the Art Librarian
Get PDFPublisher allows immediate open acces
Parts of a Whole: Tutor Perceptions of Online Writing Tutoring Platforms
Get PDFDespite the breadth of research available on online writing instruction (OWI) in writing centers, there is very little exploration regarding the technology operated in online writing tutoring due to the fast-changing evolution of online platforms and the Internet. Though the dynamic nature of technologies can be intimidating, this gap in writing center research invites the opportunity to research the practical improvement of the components of online writing instruction. This study uses an online survey method to collect data on writing tutor perceptions of online platforms, gaining an understanding of how current writing center technologies are operating in online synchronous tutorials. Qualitative analysis through thematic coding of survey responses shows that many of the current platforms and features used by writing centers to conduct online synchronous sessions possess a variety of deficits, particularly in the pedagogical affordances they offer for tutors and the accessibility of their interfaces for writers. Results also demonstrate how tutors interact with the writer and their texts through implementing both external and internal feedback, fostering collaboration, and incorporating writer preference into their usage of features and platforms. These findings contribute to an empirical body of data to inform tutor training for online writing instruction, and indicate that writing centers must consider evaluating their online platform choices to strike a balance between what works for administrators, tutors, and writers. This study also illustrates how, as we begin to understand how tutors are using the parts and features of online platforms, the whole of online writing instruction can begin to be recognized as a separate tutoring practice with its own unique affordances, as opposed to an approximation of face-to-face writing tutoring.Ohio State University Department of EnglishNo embargoAcademic Major: Englis
The Combined Effect of Anxiety and Substance Use on Quality of Life in Traumatic Brain Injury Patients
Get PDFBackground: Behavioral health disorders are common in traumatic brain injury (TBI) populations, with anxiety and substance use disorders being among the most common. Treatment research that investigates interventions that target, in tandem, anxiety and substance use are promising for populations without traumatic brain injury.
Objective: To determine if quality of life at two years post-injury is predicted by anxiety and problematic use of substances at one-year post-TBI, separately and in combination. The study is being conducted to better inform treatment research for TBI populations as to whether anxiety and problematic use of substances should be more closely examined and treated together in TBI patients.
Measures: Problem Substance Use (based on TBI Model Systems questions on substance use), GAD-7, SF-12
Participants: Two hundred and one participants with complete data drawn from the Traumatic Brain Injury Model Systems (TBIMS) study.
Design: Regression analysis
Results: The results of our regression analysis revealed that there was not a significant association between the combination of moderate-severe anxiety symptoms (GAD-7) and Problem Substance Use, and SF-12 Mental and Physical Component scores (MCS, PCS). However, moderate-severe anxiety symptoms alone were a significant predictor for the SF-12 mental component score. Age was a significant predictor of the MCS, and sex as well as FIM cognitive predicted PCS.
Discussion: These findings support the idea that anxiety is an important consideration in the treatment and rehabilitation of persons with TBI, as well as their sex, age, and independent functioning. Further research into treatments that predominantly consider these variables is recommended to give patients the best quality of life outcomes as possible.No embargoAcademic Major: Psycholog
Economic Analysis of ODRC Solar Field Construction
Get PDFCourse Code: AEDECON 4567This report details research and comparative economic analysis on constructing a photovoltaic solar field at Ohio Department of Rehabilitation and Correctional (ODRC) facilities. The report contains a detailed preliminary screening process to establish which facilities are feasible for solar field implementation and construction. This includes the determination of investment tax credit eligibility, electricity consumption analysis, the use and results of photovoltaic modeling software, the use of Geographic Information Systems data to determine land availability and detailed research on current net metering regulations in Ohio. A financial model was developed to determine the capital and annual costs of photovoltaics to estimate the projected future cash flows at each facility. Net present value analysis was conducted to analyze the future cash flows of each facility to determine the ideal fit for a commercial-scale solar field.Ohio Department of Rehabilitation and CorrectionAcademic Major: Environment, Economy, Development, and SustainabilityAcademic Major: Frenc
