title: Regression modelling of spectroscopic data using lazy learning and deep neural networks

authors: Fraser, Huon

subjects: Regression

abstract: Neural networks show promise in modelling infrared (IR) spectroscopic data, but many of the proposed solutions in the literature are either Multilayer Perceptrons with a single hidden layer or are adapted from successful solutions in other domains such as convolutional networks from image processing.

This thesis investigates the use of Monte Carlo search to build candidate deep neural networks from scratch. As the prediction targets are real numbers and the modelling is prone to error from outliers, lazy, locally weighted methods are also investigated. 

Predictions from the network are compared to predictions made from locally weighting the features extracted from the same network. To measure progress, these results are compared to classical statistical methods commonly used to model spectroscopic data, such as partial least squares (PLS) regression.

Results suggest that deep networks trained via Monte-Carlo search outperform classical approaches. They also show that PLS dimension reduction as a preprocessing technique can improve the quality of search at little cost in predictive ability. Encouraging results using this approach are obtained on the publicly available Mangoes dataset. Finally, a streaming regression solution is investigated in which selected deep neural network models perform well. In this setting, however, locally weighted regression can result in sporadic outlier predictions, so an ensemble solution is proposed as a remedy.

text: Regression modelling of spectroscopic data using lazy learning and deep neural networks Neural networks show promise in modelling infrared (IR) spectroscopic data, but many of the proposed solutions in the literature are either Multilayer Perceptrons with a single hidden layer or are adapted from successful solutions in other domains such as convolutional networks from image processing.

This thesis investigates the use of Monte Carlo search to build candidate deep neural networks from scratch. As the prediction targets are real numbers and the modelling is prone to error from outliers, lazy, locally weighted methods are also investigated. 

Predictions from the network are compared to predictions made from locally weighting the features extracted from the same network. To measure progress, these results are compared to classical statistical methods commonly used to model spectroscopic data, such as partial least squares (PLS) regression.

Results suggest that deep networks trained via Monte-Carlo search outperform classical approaches. They also show that PLS dimension reduction as a preprocessing technique can improve the quality of search at little cost in predictive ability. Encouraging results using this approach are obtained on the publicly available Mangoes dataset. Finally, a streaming regression solution is investigated in which selected deep neural network models perform well. In this setting, however, locally weighted regression can result in sporadic outlier predictions, so an ensemble solution is proposed as a remedy.

year: 2022

title: Peat humification records from Restionaceae bogs in northern New Zealand as potential indicators of Holocene precipitation, seasonality, and ENSO

authors: Newnham, Rewi M.

subjects: Science & Technology

abstract: In comparison with temperature reconstructions, New Zealand proxy records for paleo-precipitation are rare, despite the importance of precipitation in contemporary climate variability and for projected climate impacts. In this study, records of mid-late Holocene palaeomoisture variation were derived for two hydrologically separate ombrotrophic Restionaceae bogs in northern New Zealand, based on peat humification analysis. At each site, three cores were analysed for peat humification, facilitating both intra- and inter-site comparisons. Age models for the six sequences were developed using radiocarbon dating and tephrochronology. Twelve tephras (including six cryptotephras) were recognised, four of which were used to precisely link the two sites and to define start and end points for the records at 7027 ± 170 (Tuhua tephra) and 1718 ± 10 cal yr BP (Taupo tephra) (2σ-age ranges), respectively. We find individual differences between the six peat humification records at short-term timescales that are presumably due to local site factors, in particular changing vegetation and microtopography, or to changes in the composition of the material analysed. Stronger longer-term coherence is observed between all six records but is attributed to slow anaerobic decay over time because the implied trend towards wetter summers in the late Holocene cannot be corroborated by independent climate proxies. Despite these confounding factors, centennial scale shifts in bog surface wetness are a pervasive feature of all six records with varying degrees of overlap in time that show strong correspondence with El Niño-Southern Oscillation reconstructions from the eastern equatorial Pacific. These results indicate the potential for peat humification records from New Zealand's ombrotrophic bogs to elucidate past climate variability and also demonstrate the importance of developing multiple well-dated profiles from more than one site.

text: Peat humification records from Restionaceae bogs in northern New Zealand as potential indicators of Holocene precipitation, seasonality, and ENSO In comparison with temperature reconstructions, New Zealand proxy records for paleo-precipitation are rare, despite the importance of precipitation in contemporary climate variability and for projected climate impacts. In this study, records of mid-late Holocene palaeomoisture variation were derived for two hydrologically separate ombrotrophic Restionaceae bogs in northern New Zealand, based on peat humification analysis. At each site, three cores were analysed for peat humification, facilitating both intra- and inter-site comparisons. Age models for the six sequences were developed using radiocarbon dating and tephrochronology. Twelve tephras (including six cryptotephras) were recognised, four of which were used to precisely link the two sites and to define start and end points for the records at 7027 ± 170 (Tuhua tephra) and 1718 ± 10 cal yr BP (Taupo tephra) (2σ-age ranges), respectively. We find individual differences between the six peat humification records at short-term timescales that are presumably due to local site factors, in particular changing vegetation and microtopography, or to changes in the composition of the material analysed. Stronger longer-term coherence is observed between all six records but is attributed to slow anaerobic decay over time because the implied trend towards wetter summers in the late Holocene cannot be corroborated by independent climate proxies. Despite these confounding factors, centennial scale shifts in bog surface wetness are a pervasive feature of all six records with varying degrees of overlap in time that show strong correspondence with El Niño-Southern Oscillation reconstructions from the eastern equatorial Pacific. These results indicate the potential for peat humification records from New Zealand's ombrotrophic bogs to elucidate past climate variability and also demonstrate the importance of developing multiple well-dated profiles from more than one site.

year: 2019

title: Research support in New Zealand University Libraries

authors: Howie, Jess

abstract: Researcher-facing librarians in New Zealand are providing guidance across more of the research lifecycle than ever before in response to an increasingly complex scholarly ecosystem. This research explored the development of research support through survey responses from all eight New Zealand University Libraries. From the responses it was possible to ascertain the level of services offered or planned in the four key areas of research impact, Research Data Management, scholarly communication and Kaupapa Māori research. Skills gaps and barriers to service development were also identified. Comparison with an earlier study revealed that research impact and Research Data Management services have developed well over the last 6 years. A good level of maturity was identified in scholarly communication services but support for Kaupapa Māori research was identified as an area for development. Barriers to service development included lack of resourcing and low recognition of library value from the wider institution.

text: Research support in New Zealand University Libraries Researcher-facing librarians in New Zealand are providing guidance across more of the research lifecycle than ever before in response to an increasingly complex scholarly ecosystem. This research explored the development of research support through survey responses from all eight New Zealand University Libraries. From the responses it was possible to ascertain the level of services offered or planned in the four key areas of research impact, Research Data Management, scholarly communication and Kaupapa Māori research. Skills gaps and barriers to service development were also identified. Comparison with an earlier study revealed that research impact and Research Data Management services have developed well over the last 6 years. A good level of maturity was identified in scholarly communication services but support for Kaupapa Māori research was identified as an area for development. Barriers to service development included lack of resourcing and low recognition of library value from the wider institution.

year: 2019-01-01