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L1 -norm Based Nonlinear Reconstruction Improves Quantitative Accuracy of Spectral Diffuse Optical Tomography
No full textSpectrally constrained diffuse optical tomography (SCDOT) is known to improve reconstruction in diffuse optical imaging: constraining the reconstruction by coupling the optical
properties across multiple wavelengths and suppressing artefacts in the resulting reconstructed images. In other work, L1-norm regularization has been shown to be able to improve certain types of image reconstruction problem as its sparsity-promoting properties render it robust against
noise and enable preservation of edges in images, but because the L1-norm is non-differentiable, it is not always simple to implement. In this work, we show how to incorporate L1 regularization into SCDOT. Three popular algorithms for L1 regularization are assessed for application in SCDOT: iteratively reweighted least square algorithm (IRLS), alternating directional method of
multipliers (ADMM) and fast iterative shrinkage-thresholding algorithm (FISTA). We introduce an objective procedure for determining the regularization parameter in these algorithms and compare their performance in two-dimensional and three-dimensional simulated experiments. Our results show that L1 regularization consistently outperforms Tikhonov regularization in this application, particularly in the presence of noise
Everyday Decisions Findings Summary: Easyread
Get PDFAn easyread summary of the findings from the Everyday Decisions research projec
Heritages of Migration: Moving Stories, Objects and Home, Conference Proceedings
Get PDFOfficial Conference Proceedings for the international conference Heritages of Migration: Moving Stories, Objects and Home, Conference Proceedings (6-10 April 2017, Buenos Aires, Argentina) Organised by the Ironbridge International Institute for Cultural Heritage, University of Birmingham, Collaborative for Cultural Heritage Management and Policy (CHAMP), University of Illinois, Universidad Nacional de Tres de Febrero (UNTREF), UNESCO Chair of Cultural Tourism, Argentina
Investigation into the Effect of Sulfate and Borate Incorporation on the Structure and Properties of SrFeO3-δ
No full textFamily Impact of Meningitis dataset
No full textThis dataset contain questionnaire survey data collected in 2012 and 2013 from 1627 family members of individuals who contracted (and survived) meningitis. The survey data include:
(i) living arrangements; (ii) health status of survivors and any subsequent after-effects of meningitis; (iii) informal care tasks and caring experience; (iv) socio-demographic information about the family member; (v)health status and quality of life of family member
Transport Infrastructure Interdependencies with Energy, Water, Waste and Communication Infrastructure in the United Kingdom
Get PDFThe role of infrastructure interdependencies is challenging due to the complexity and dynamic
environment of all infrastructures and vital for critical infrastructure systems. There is an ongoing
debate about the value of the benefits of the five national infrastructure sectors (energy, water,
transport, waste and communication) in the UK and how they interact in terms of social, economic
and environmental wellbeing (Hall et al., 2016, p.10; iBUILD, 2015; Liveable Cities, 2015; National
Infrastructure Plan, 2013). This study focuses only on one of the three aforementioned values, the
economic value. The hypothesis tested is whether the transport sector is economically
complemented by the energy, water and waste sectors and economically substituted by the
communication sector. The authors use the process analysis “networks and cohorts”, an analysis
that uses tables, diagrams, models and networks of interactions along with organizational linkages
(Hill, 1993). Of interest for this study in particular is the grand total of all revenues (capital value)
which create incomes into other sectors and creates dependencies. This, by definition, is the Gross
Value Added. The last five symmetric (product by product) Input-Output tables of gross value added
are used: 2010, 2005, 1995, 1990 and 1984 (Office for National Statistics, 2015). The theory
underpinning the hypothesis was verified and one mathematical equation was developed based on
the historical data of the gross value added by the value created in millions of pounds (£m) from the
other critical sectors to transport
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