Understanding Park Support: Philanthropy and Other Support for Yellowstone National Park

This report was conducted as one piece of a larger project on visitor support for Yellowstone National Park. Twenty-eight interviews were conducted with park non-profit supporters and repeat visitors to determine how these participants support the park and the reasons behind doing so. Additionally, other causes supported by participants were examined to place park support in a broader philanthropic context. Results revealed that beyond monetary support, activities such as sharing experiences, introducing newcomers to Yellowstone, and educating others about Yellowstone were common support activities utilized by all three groups. Repeat visitors were less likely to give monetary contributions, but otherwise equally active in other arenas of support. Reasons for providing these actions varied, but centered on aspects of Yellowstone that visitors valued, altruism, tangible benefits derived for support, and the efficacy of support actions. Participants were also actively involved in the larger field of philanthropy, supporting both other environmental causes as well as other typical non-profits

Light Field Compression by Residual CNN Assisted JPEG

Light field (LF) imaging has gained significant attention due to its recent success in 3-dimensional (3D) displaying and rendering as well as augmented and virtual reality usage. Nonetheless, because of the two extra dimensions, LFs are much larger than conventional images. We develop a JPEG-assisted learning-based technique to reconstruct an LF from a JPEG bitstream with a bit per pixel ratio of 0.0047 on average. For compression, we keep the LF's center view and use JPEG compression with 50% quality. Our reconstruction pipeline consists of a small JPEG enhancement network (JPEG-Hance), a depth estimation network (Depth-Net), followed by view synthesizing by warping the enhanced center view. Our pipeline is significantly faster than using video compression on pseudo-sequences extracted from an LF, both in compression and decompression, while maintaining effective performance. We show that with a 1% compression time cost and 18x speedup for decompression, our methods reconstructed LFs have better structural similarity index metric (SSIM) and comparable peak signal-to-noise ratio (PSNR) compared to the state-of-the-art video compression techniques used to compress LFs

Evidential Communities for Complex Networks

Community detection is of great importance for understand-ing graph structure in social networks. The communities in real-world networks are often overlapped, i.e. some nodes may be a member of multiple clusters. How to uncover the overlapping communities/clusters in a complex network is a general problem in data mining of network data sets. In this paper, a novel algorithm to identify overlapping communi-ties in complex networks by a combination of an evidential modularity function, a spectral mapping method and evidential c-means clustering is devised. Experimental results indicate that this detection approach can take advantage of the theory of belief functions, and preforms good both at detecting community structure and determining the appropri-ate number of clusters. Moreover, the credal partition obtained by the proposed method could give us a deeper insight into the graph structure

Customized Blister Packaging for Patients Living with HIV: Assessment of Patient Attitudes and Satisfaction

Adherence to antiretroviral medication results in reduced HIV transmission and improved health outcomes, yet challenges with medication adherence remain. A Collaborative Care Program was developed with a community pharmacy integrating a multi-dose adherence packaging service. We surveyed program participants to assess their satisfaction with this program and found an overall positive sentiment toward the program, that the program helped with reducing missed doses, and all patients would recommend the program to others