61 research outputs found
Self-Supervised Representation Learning for Online Handwriting Text Classification
Self-supervised learning offers an efficient way of extracting rich
representations from various types of unlabeled data while avoiding the cost of
annotating large-scale datasets. This is achievable by designing a pretext task
to form pseudo labels with respect to the modality and domain of the data.
Given the evolving applications of online handwritten texts, in this study, we
propose the novel Part of Stroke Masking (POSM) as a pretext task for
pretraining models to extract informative representations from the online
handwriting of individuals in English and Chinese languages, along with two
suggested pipelines for fine-tuning the pretrained models. To evaluate the
quality of the extracted representations, we use both intrinsic and extrinsic
evaluation methods. The pretrained models are fine-tuned to achieve
state-of-the-art results in tasks such as writer identification, gender
classification, and handedness classification, also highlighting the
superiority of utilizing the pretrained models over the models trained from
scratch
Improving Access and Mental Health for Youth Through Virtual Models of Care
The overall objective of this research is to evaluate the use of a mobile health smartphone application (app) to improve the mental health of youth between the ages of 14–25 years, with symptoms of anxiety/depression. This project includes 115 youth who are accessing outpatient mental health services at one of three hospitals and two community agencies. The youth and care providers are using eHealth technology to enhance care. The technology uses mobile questionnaires to help promote self-assessment and track changes to support the plan of care. The technology also allows secure virtual treatment visits that youth can participate in through mobile devices. This longitudinal study uses participatory action research with mixed methods. The majority of participants identified themselves as Caucasian (66.9%). Expectedly, the demographics revealed that Anxiety Disorders and Mood Disorders were highly prevalent within the sample (71.9% and 67.5% respectively). Findings from the qualitative summary established that both staff and youth found the software and platform beneficial
The Impact of Digital Technologies on Public Health in Developed and Developing Countries
This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic
The Impact of Digital Technologies on Public Health in Developed and Developing Countries
This open access book constitutes the refereed proceedings of the 18th International Conference on String Processing and Information Retrieval, ICOST 2020, held in Hammamet, Tunisia, in June 2020.* The 17 full papers and 23 short papers presented in this volume were carefully reviewed and selected from 49 submissions. They cover topics such as: IoT and AI solutions for e-health; biomedical and health informatics; behavior and activity monitoring; behavior and activity monitoring; and wellbeing technology. *This conference was held virtually due to the COVID-19 pandemic
Undergraduate and Graduate Course Descriptions, 2021 Fall
Wright State University undergraduate and graduate course descriptions from Fall 2021
Undergraduate and Graduate Course Descriptions, 2021 Fall
Wright State University undergraduate and graduate course descriptions from Fall 2021
Undergraduate and Graduate Course Descriptions, 2020 Fall
Wright State University undergraduate and graduate course descriptions from Fall 2020
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