91 research outputs found
To Olga : an appreciation in verse.
No full textPoetic appreciation of Mrs. Olga Hunter, wife of the author. Bound in cream card covers with applied cover label
Supports and Barriers to Effective Job Matching for Persons With Intellectual Disabilities
No full textAbstract
Date Presented 3/31/2017
Several practices act as barriers, as supports, or as both to the job-matching process. Future research should focus on integrating these factors into a systematic procedure for matching persons with disabilities to long-term, competitive community employment.
Primary Author and Speaker: Andrew Persch
Additional Authors and Speakers: Beth Pfeiffer, Rebecca Weisshaar, Amy Darragh, Dennis Cleary</jats:p
Home-Based Intervention for Chemotherapy-Induced Peripheral Neuropathy
No full textAbstract
Date Presented 3/31/2017
Peripheral neuropathy is a side effect of neurotoxic chemotherapy, resulting in pain and declines in function and quality of life. This pilot study assessed effects of a sensorimotor intervention on pain, function, and quality of life in individuals with breast cancer.
Primary Author and Speaker: Amy Darragh
Additional Authors and Speakers: Karli Vicary
Contributing Authors: Karen Hock, LeAnn Gaerke, Sharon Flinn</jats:p
Development of a time-synchronised multi-input computer vision system for structural monitioring utilising deep learning for vehicle identification
No full textUse of a roving computer vision system to compare anomaly detection techniques for health monitoring of bridges
Full text linkDisplacement measurements can provide valuable insights into structural conditions and in-service behaviour of bridges under operational and environmental loadings. Computer vision systems have been validated as a means of displacement estimation; the research developed here is intended to form the basis of a real-time damage detection system. This paper demonstrates a solution for detecting damage to a bridge from displacement measurements using a roving vision sensor-based approach. Displacements are measured using a synchronised multi-camera vision-based measurement system. The performance of the system is evaluated in a series of controlled laboratory tests. For damage detection, five unsupervised anomaly detection techniques: Autoencoder, K-Nearest Neighbours, Kernel Density, Local Outlier Factor and Isolation Forest, are compared. The results obtained for damage detection and localisation are promising, with an f1-Score of 0.96–0.97 obtained across various analysis scenarios. The approaches proposed in this research provide a means of detecting changes to bridges using low-cost technologies requiring minimal sensor installation and reducing sources of error and allowing for rating of bridge structures
Use of A Roving Vision Sensor Setup to Train an Autoencoder for Damage Detection of Bridge Structures
No full textThis paper will demonstrate a solution for detecting damage to a bridge structure from measured displacements gathered using a roving vision sensor based approach. The measurement of displacement was accomplished using a synchronised multi-camera contactless vision based multiple point displacement measurement system using wireless action cameras. Displacement measurements can provide a valuable insight into the structural condition and service behaviour of bridges under live loading. Computer Vision systems have been validated as a means of displacement calculation, the research developed here is intended to form the basis of a real time damage detection system. This is done through the use of unsupervised deep learning methods for anomaly detection which could form the basis of a low cost durable alternative which is rapidly deployable in the field. The performance of the system was evaluated in a series of controlled laboratory tests. This research provides a means of detecting changes to a bridge structure through use of minimal sensor installation, reducing potential sources of error and allowing for potential live rating of bridge structures
A review of Vision based Methods for Pothole Detection and Road Profile Analysis
No full textThis paper is an overview of the development and application of Computer Vision for the detection of pothole, pavement distress and road profile analysis and categorisation. A brief explanation of the traditional methods for determining these factors is given, followed by a chronological description of the evolution and the challenges of using Computer Vision (CV) approaches to determine these conditions. The paper is separated into sections aligned to image capture and analysis methodologies. Qualitative evaluations and comparison of these methods have been provided along with the proposal of guidelines for new computer vision-based road analysis systems
Development and Laboratory Testing of a Multipoint Displacement Monitoring System
No full textThis paper develops a synchronised multi-camera contactless vision based multiple point displacement measurement system using wireless action cameras. Displacement measurements can provide a valuable insight into the structural condition and service behaviour of bridges under live loading. However conventional displacement gauges or GPS based systems have limitations in terms of access and accuracy. Computer Vision systems have been validated as a means of displacement calculation, however existing systems in use are limited in scope by their inability to reliably track multiple points on a long span bridge structure. The system introduced in this paper provides a low cost durable alternative which is rapidly deployable. Commercial action cameras were paired with an industrially validated solution for synchronisation to provide multiple point displacement readings. The performance of the system was evaluated in a series of controlled laboratory tests. This included the development of robust displacement identification algorithms which were tested and validated against displacement measurements obtained using a fibre optic displacement gauge. This research will significantly advance current vision based Structural health monitoring (SHM) systems which can be cost prohibitive and provides rapid method of obtaining data which accurately relates to measured bridge deflections
Development and Laboratory Testing of a Multipoint Displacement Monitoring System
No full textThis paper develops a synchronised multi-camera contactless vision based multiple point displacement measurement system using wireless action cameras. Displacement measurements can provide a valuable insight into the structural condition and service behaviour of bridges under live loading. However conventional displacement gauges or GPS based systems have limitations in terms of access and accuracy. Computer Vision systems have been validated as a means of displacement calculation, however existing systems in use are limited in scope by their inability to reliably track multiple points on a long span bridge structure. The system introduced in this paper provides a low cost durable alternative which is rapidly deployable. Commercial action cameras were paired with an industrially validated solution for synchronisation to provide multiple point displacement readings. The performance of the system was evaluated in a series of controlled laboratory tests. This included the development of robust displacement identification algorithms which were tested and validated against displacement measurements obtained using a fibre optic displacement gauge. This research will significantly advance current vision based Structural health monitoring (SHM) systems which can be cost prohibitive and provides rapid method of obtaining data which accurately relates to measured bridge deflections
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