3 research outputs found
Design and analysis of a concrete modular housing system constructed with 3D panels
Full text linkThesis (S.B.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2004.Includes bibliographical references (p. 68-69).An innovative modular house system design utilizing an alternative concrete residential building system called 3D panels is presented along with an overview of 3D panels as well as relevant methods and markets. The proposed design is an integrated approach to residential construction with unique provisions for structural elements and utilities. The design is hexagonally modular and may be scaled freely with a low number of unique components. An analysis of the house design in terms of labor requirements, construction process, cost, and structural feasibility is also presented.by Sam Rhea Sarcia.S.B
Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based Approaches
Full text linkImaging spectrometers measure electromagnetic energy scattered in their instantaneous field view in hundreds or thousands of spectral channels with higher spectral resolution than multispectral cameras. Imaging spectrometers are therefore often referred to as hyperspectral cameras (HSCs). Higher spectral resolution enables material identification via spectroscopic analysis, which facilitates countless applications that require identifying materials in scenarios unsuitable for classical spectroscopic analysis. Due to low spatial resolution of HSCs, microscopic material mixing, and multiple scattering, spectra measured by HSCs are mixtures of spectra of materials in a scene. Thus, accurate estimation requires unmixing. Pixels are assumed to be mixtures of a few materials, called endmembers. Unmixing involves estimating all or some of: the number of endmembers, their spectral signatures, and their abundances at each pixel. Unmixing is a challenging, ill-posed inverse problem because of model inaccuracies, observation noise, environmental conditions, endmember variability, and data set size. Researchers have devised and investigated many models searching for robust, stable, tractable, and accurate unmixing algorithms. This paper presents an overview of unmixing methods from the time of Keshava and Mustard's unmixing tutorial [1] to the present. Mixing models are first discussed. Signal-subspace, geometrical, statistical, sparsity-based, and spatial-contextual unmixing algorithms are described. Mathematical problems and potential solutions are described. Algorithm characteristics are illustrated experimentally
Understanding national trends in COVID‐19 vaccine hesitancy in Canada – April 2020 to March 2021
No full textObjective: Key to reducing COVID‐19 morbidity and mortality and reducing the need for further lockdown measures in Canada and worldwide is widespread acceptance of COVID‐19 vaccines. Vaccine hesitancy has emerged as a key barrier to achieving optimal vaccination rates, for which there is little data among Canadians. This study examined rates of vaccine hesitancy and their correlates among Canadian adults. Methods: This study analyzed data from five age, sex and province‐weighted population‐based samples to describe rates of hesitancy between April 2020 and March 2021 among Canadians who completed online surveys as part of the iCARE Study, and various sociodemographic, clinical and psychological correlates. Vaccine hesitancy was assessed by asking: “If a vaccine for COVID‐19 were available today, what is the likelihood that you would get vaccinated?” Responses were dichotomized into ‘very likely’, ‘unlikely’, ‘somewhat unlikely’ (reflecting some degree of vaccine hesitancy) vs ‘extremely likely’ to get the vaccine, which was the comparator. Results: Overall, 15,019 respondents participated in the study. A total of 42.2% of respondents reported vaccine hesitancy over the course of the study, which was lowest during surveys 1 (April 2020) and 5 (March 2021) and highest during survey 3 (November 2020). Fully adjusted multivariate logistic regression analyses revealed that women, those aged 50 and younger, non‐Whites, those with high school education or less, and those with annual household incomes below the poverty line in Canada (i.e., $60,000) were significantly more likely to report being vaccine hesitant over the study period, as were essential and healthcare workers, parents of children under the age of 18, and those who do not get regular flu vaccines. Believing engaging in infection prevention behaviours (like vaccination) is important for reducing virus transmission and high COVID‐19 health concerns (being infected and infecting others) were associated with 77% and 54% reduction in vaccine hesitancy, respectively, and having high personal financial concerns (worried about job or income loss) was associated with 1.33 times increased odds of vaccine hesitancy. Conclusion: Results point to the importance of targeting vaccine efforts to women, younger people and socioeconomically disadvantaged groups, and that vaccine messaging should emphasize the benefits of getting vaccinated, and how the benefits (particularly to health) far outweigh the risks. Future research is needed to monitor ongoing changes in vaccine intentions and behaviour, as well as to better understand motivators and facilitators of vaccine acceptance, particularly among vulnerable groups. The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license
