ABSTRACT
Many applications requiring both spectral and spatial information at high resolution benefit from spectral imaging. Although different technical methods have been developed and commercially available, computational spectral cameras represent a compact, lightweight, and inexpensive solution. However, the tradeoff between spatial and spectral resolutions, dominated by the limited data volume and environmental noise, limits the potential of these cameras. In this study, we developed a deeply learned broadband encoding stochastic hyperspectral camera. In particular, using advanced artificial intelligence in filter design and spectrum reconstruction, we achieved 7000-11,000 times faster signal processing and ~10 times improvement regarding noise tolerance. These improvements enabled us to precisely and dynamically reconstruct the spectra of the entire field of view, previously unreachable with compact computational spectral cameras.
ABSTRACT
In using a laser light source, it becomes possible to realize an ultra-wide display gamut that approaches the human color vision limit. This paper introduces a method for extremely large gamut optimization for different primary numbers, and it offers a primary set that produces a nearly ultimate gamut. Considering display lightness, we calculated wavelength selection and lightness design of a display with 3-9 primaries in the CIELAB uniform color space (UCS) by optimizing the coverage of the optimal color gamut. Theoretically the maximum gamut area of a laser display with 3-12 primaries in the CIE xy and CIE u'v' chromaticity diagrams is also calculated for comparison. We recommend 6 primaries as a reasonable choice, since the coverage reaches 97.6% of the optimal color. Taking into account the luminance efficacy of radiation (LER) and feasible laser wavelengths in practice, we get a practical design of wavelengths and power for a laser projection display with 6 primaries, which covers 96.6% of the optimal color gamut.
ABSTRACT
PURPOSE: Models of health influence providers' practice and delivery of health care. This study surveyed a random sample of providers to determine if health care providers from mainstream medicine (MM), integrative medicine (IM), and complementary and alternative medicine (CAM) hold mutually exclusive models of health or combine notions from models thought to be contradictory. METHODS: A survey was created through qualitative research, piloted, and mailed to a wide variety of MM, IM, and CAM health care professionals. RESULTS: All providers combined various models and definitions of health. Most utilized the biomedical approach to some extent. Balance (holistic model) and functioning in daily life were essential to most respondents' models of health, disease, and healing. Close communication between MM and CAM systems was preferred over complete separation or a single system. CONCLUSIONS: Many providers of all types combine widely disparate components in their definitions of health, providing keys for improving communication.
