title: Approximation of invariant measures for a class of maps with indifferent fixed points

authors: Murray, Rua

subjects: mathematics

abstract: Certain dynamical systems on the interval with neutrally stable repelling points admit invariant probability measures which are absolutely continuous with respect to Lebesgue measure. These maps are often used as a model of intermittent dynamics, since they exhibit polynomial rather than exponential decay of correlations (due to the absence of a spectral gap in the underlying transfer operator). This paper presents a class of these maps which are expanding (with convex branches) for which the invariant probability measures can be rigorously approximated by Ulam’s method (a sequence of finite rank approximations to the transfer operator). L1–convergence of the scheme is proved, and some numerical experiments are reported.

text: Approximation of invariant measures for a class of maps with indifferent fixed points Certain dynamical systems on the interval with neutrally stable repelling points admit invariant probability measures which are absolutely continuous with respect to Lebesgue measure. These maps are often used as a model of intermittent dynamics, since they exhibit polynomial rather than exponential decay of correlations (due to the absence of a spectral gap in the underlying transfer operator). This paper presents a class of these maps which are expanding (with convex branches) for which the invariant probability measures can be rigorously approximated by Ulam’s method (a sequence of finite rank approximations to the transfer operator). L1–convergence of the scheme is proved, and some numerical experiments are reported.

year: 2005

title: Difference in details: transfer learning case study of "cryptic" plants and moths

authors: Vetrova, Varvara

subjects: Machine learning

abstract: Can we classify species of very similar looking organisms quickly and accurately using only out of the box feature transfer? What if we only have small number of images? This experimental paper is part of on-going project on species recognition research and evaluates transfer learning and fine-tuning approaches on two highly specialized fine-grained datasets. The two fine-grained datasets were specifically assembled for the purpose of this research. These datasets consist of images of New Zealand native species of moths and ”cryptic” plants of Genus Corposma found also in New Zealand. We compare results from finetuning experiments with performance of transfer learning without fine-tuning. The latter results are based on features extracted from various levels of depth in the InceptionV3 network, including fully connected layers. The extracted features serve as inputs to a number of classification algorithms. We observe contrasting results for the two datasets. For the dataset of moths, the method based on features extracted from deep levels of the InceptionV3 network outperforms fine-tuning in accuracy (90.09% versus 87.18%). This is not the case for the dataset of cryptic plants (60.46% versus 74.37%). Despite both datasets being fine-grained in nature, these experimental differences could be attributed to intrinsically different morphology of organisms and warrant further investigation.

text: Difference in details: transfer learning case study of "cryptic" plants and moths Can we classify species of very similar looking organisms quickly and accurately using only out of the box feature transfer? What if we only have small number of images? This experimental paper is part of on-going project on species recognition research and evaluates transfer learning and fine-tuning approaches on two highly specialized fine-grained datasets. The two fine-grained datasets were specifically assembled for the purpose of this research. These datasets consist of images of New Zealand native species of moths and ”cryptic” plants of Genus Corposma found also in New Zealand. We compare results from finetuning experiments with performance of transfer learning without fine-tuning. The latter results are based on features extracted from various levels of depth in the InceptionV3 network, including fully connected layers. The extracted features serve as inputs to a number of classification algorithms. We observe contrasting results for the two datasets. For the dataset of moths, the method based on features extracted from deep levels of the InceptionV3 network outperforms fine-tuning in accuracy (90.09% versus 87.18%). This is not the case for the dataset of cryptic plants (60.46% versus 74.37%). Despite both datasets being fine-grained in nature, these experimental differences could be attributed to intrinsically different morphology of organisms and warrant further investigation.

year: 2018

title: Health equity and wellbeing among older people's caregivers in New Zealand during COVID-19: Protocol for a qualitative study.

authors: Burholt, Vanessa

subjects: Aged

abstract: BACKGROUND: Knowledge of the challenges unpaid caregivers faced providing care to older people during the COVID-19 pandemic is limited. Challenges may be especially pronounced for those experiencing inequitable access to health and social care. This participatory action research study, located in New Zealand, has four main objectives, (i) to understand the challenges and rewards associated with caregiving to older care recipients during the COVID-19 pandemic restrictions; (ii) to map and collate resources developed (or mobilised) by organisations during the pandemic; (iii) to co-produce policy recommendations, identify useful caregiver resources and practices, prioritise unmet needs (challenges); and, (iv) to use project results in knowledge translation, in order to improve caregivers access to resources, and raise the profile and recognition of caregivers contribution to society. METHODS AND ANALYSIS: Māori, Pacific and rural-dwelling caregivers to 30 older care-recipients, and 30 representatives from organisations supporting caregivers in New Zealand will be interviewed. Combining data from the interviews and caregivers letters (from an archive of older people's pandemic experiences), framework analysis will be used to examine the interrelated systems of the human ecological model and the impact on caregiving experiences during the pandemic. Resources that service providers had created or used for caregivers and older people will be collated and categorised. Through co-production with caregivers and community partners we will produce three short films describing caregivers' pandemic experiences; identify a suite of resources for caregivers to use in future events requiring self-isolation, and in everyday life; and generate ideas to address unresolved issues.

text: Health equity and wellbeing among older people's caregivers in New Zealand during COVID-19: Protocol for a qualitative study. BACKGROUND: Knowledge of the challenges unpaid caregivers faced providing care to older people during the COVID-19 pandemic is limited. Challenges may be especially pronounced for those experiencing inequitable access to health and social care. This participatory action research study, located in New Zealand, has four main objectives, (i) to understand the challenges and rewards associated with caregiving to older care recipients during the COVID-19 pandemic restrictions; (ii) to map and collate resources developed (or mobilised) by organisations during the pandemic; (iii) to co-produce policy recommendations, identify useful caregiver resources and practices, prioritise unmet needs (challenges); and, (iv) to use project results in knowledge translation, in order to improve caregivers access to resources, and raise the profile and recognition of caregivers contribution to society. METHODS AND ANALYSIS: Māori, Pacific and rural-dwelling caregivers to 30 older care-recipients, and 30 representatives from organisations supporting caregivers in New Zealand will be interviewed. Combining data from the interviews and caregivers letters (from an archive of older people's pandemic experiences), framework analysis will be used to examine the interrelated systems of the human ecological model and the impact on caregiving experiences during the pandemic. Resources that service providers had created or used for caregivers and older people will be collated and categorised. Through co-production with caregivers and community partners we will produce three short films describing caregivers' pandemic experiences; identify a suite of resources for caregivers to use in future events requiring self-isolation, and in everyday life; and generate ideas to address unresolved issues.

year: 2022