Computational Approaches to Assistive Technologies for People with Disabilities
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Assistive technologies have become increasingly important for people with disabilities in recent years. This book is the result of over a decade of research into computational approaches to assistive technology. Its chapters are based on a number of graduate theses, successfully completed over the past dozen or so years under the supervision of Kanlaya Naruedomkul of Mahidol University in Bangkok, Thailand and Nick Cercone of York University, Toronto, Canada. Some applications in the chapters use Thai language examples, but the techniques employed are not restricted to any single language. Each chapter is based on the Ph.D. work of a former or current student, suitably updated and presented for interested readers. The book is divided into four sections. Following an introduction, which includes a review of assistive technology products, part two covers applications, and includes chapters on alternative sign text MT for language learning, lexical simplification using word sense disambiguation and detecting and rating dementia through lexical analysis of spontaneous speech. Part three deals with theories and systems, and includes: granules for learning behavior, rough sets methods and applications for medical data and multimedia support systems as assistive technology for hearing impaired students. Part four presents a conclusion which includes a look into the future. Although this book is not a comprehensive treatise on assistive technology, it nevertheless provides a fascinating look at recent research, and will be of interest to all those whose work involves the application of assistive technologies for people with disabilities.IOS Press is an international science, technical and medical publisher of high-quality books for academics, scientists, and professionals in all fields. Some of the areas we publish in: -Biomedicine -Oncology -Artificial intelligence -Databases and information systems -Maritime engineering -Nanotechnology -Geoengineering -All aspects of physics -E-governance -E-commerce -The knowledge economy -Urban studies -Arms control -Understanding and responding to terrorism -Medical informatics -Computer Sciences
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it