Virtual reality (VR) has recently emerged as a potentially effective way to provide general and specialty health care services, and appears poised to enter mainstream psychotherapy delivery. Because VR could be part of the future of clinical psychology, it is critical to all psychotherapists that it be defined broadly. To ensure appropriate development of VR applications, clinicians must have a clear understanding of the opportunities and challenges it will provide in professional practice. This review outlines the current state of clinical research relevant to the development of virtual environments for use in psychotherapy. In particular, the paper focuses its analysis on both actual applications of VR in clinical psychology and how different clinical perspectives can use this approach to improve the process of therapeutic change.

/pdf/virtual-reality-in-psychotherapy-review-1gn0qnf6n2.pdf

Army Science Conference

Virtual reality in psychotherapy: review.

Evolutionary network analysis has found an increasing interest in the literature because of the importance of different kinds of dynamic social networks, email networks, biological networks, and social streams. When a network evolves, the results of data mining algorithms such as community detection need to be correspondingly updated. Furthermore, the specific kinds of changes to the structure of the network, such as the impact on community structure or the impact on network structural parameters, such as node degrees, also needs to be analyzed. Some dynamic networks have a much faster rate of edge arrival and are referred to as network streams or graph streams. The analysis of such networks is especially challenging, because it needs to be performed with an online approach, under the one-pass constraint of data streams. The incorporation of content can add further complexity to the evolution analysis process. This survey provides an overview of the vast literature on graph evolution analysis and the numerous applications that arise in different contexts.

/pdf/evolutionary-network-analysis-a-survey-3lijh6h2nx.pdf

Evolutionary Network Analysis: A Survey

https://deepblue.lib.umich.edu/bitstream/handle/2027.42/31738/0000677.pdf;sequence=1

On the shear behavior of engineered cementitious composites

This report reviews existing fatigue detection and prediction technologies. Data regarding the different technologies available were collected from a variety of worldwide sources. The first half of this report summarises the current state of research and development of the technologies and summarises the status of the technologies with respect to the key issues of sensitivity, reliability, validity and acceptability. The second half evaluates the role of the technologies in transportation, and comments on the place of the technologies vis-a-vis other enforcement and regulatory frameworks, especially in Australia and New Zealand. The report authors conclude that the hardware technologies should never be used as the company fatigue management system. Hardware technologies only have the potential to be a last ditch safety device. Nevertheless, the output of hardware technologies could usefully feed into company fatigue management systems to provide real time risk assessment. However, hardware technology output should never be the only input into a management system. Other inputs should at least come from validated software technologies, mutual assessment of fitness for duty and other risk assessments of work load, schedules and rosters. (a)

/pdf/review-of-fatigue-detection-and-prediction-technologies-1p1v6g2eab.pdf

Army Science Conference

Citations

Virtual reality in psychotherapy: review.

Evolutionary Network Analysis: A Survey

On the shear behavior of engineered cementitious composites

Review of fatigue detection and prediction technologies

Compression testing of metallic glass at small length scales: Effects on deformation mode and stability

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