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Trina Myers

Researcher at James Cook University

Publications -  62
Citations -  372

Trina Myers is an academic researcher from James Cook University. The author has contributed to research in topics: Knowledge extraction & Wireless sensor network. The author has an hindex of 10, co-authored 58 publications receiving 312 citations. Previous affiliations of Trina Myers include Queensland University of Technology.

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SEMAT — The Next Generation of Inexpensive Marine Environmental Monitoring and Measurement Systems

TL;DR: SEMAT is a “smart” wireless sensor network that uses a commodity-based approach for selecting technologies most appropriate to the scientifically driven marine research and monitoring domain/field that allows for significantly cheaper environmental observation systems that cover a larger geographical area and can therefore collect more representative data.
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A Meta-Synthesis of Behavioral Outcomes from Telemedicine Clinical Trials for Type 2 Diabetes and the Clinical User-Experience Evaluation (CUE)

TL;DR: Results show that technology-intervened treatments provide positive behavior changes among patients and are potentially highly beneficial for chronic illness management such as type 2 diabetes.
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Cultivating ICT students' interpersonal soft skills in online learning environments using traditional active learning techniques

TL;DR: In this paper, the authors present a discussion of preliminary findings from a pilot study to determine best practices for developing interpersonal skills for students while working in virtual groups using synchronous and asynchronous online technologies.
Proceedings ArticleDOI

Sensor networks in workplaces: Correlating comfort and productivity

TL;DR: The preliminary results indicate that despite climate controlled conditions (i.e., a sealed air conditioned building), natural variance and sub-optimal conditions directly affected reported productivity.
Proceedings ArticleDOI

Geological Visualisation with Augmented Reality

TL;DR: A new method that applies Augmented Reality (AR) with generic smart phones and tablets to view existing geological data sets to avoid the need to understand mapping techniques when referencing three-dimensional (3D) models to the above ground terrain.