title: Pumped storage for reduced emissions?

authors: Bardsley, W. Earl

abstract: As part of a recent report on transitioning to a lower emissions economy (Productivity Commission, 2018), a case was made for electricity from expanded renewable sources to replace fossil fuel usage in industry, with concurrent adoption of electric vehicles (EVs).

text: Pumped storage for reduced emissions? As part of a recent report on transitioning to a lower emissions economy (Productivity Commission, 2018), a case was made for electricity from expanded renewable sources to replace fossil fuel usage in industry, with concurrent adoption of electric vehicles (EVs).

year: 2018

title: The positive effects of negative information: Extending one-class classification models in binary proteomic sequence classification

authors: Mutter, Stefan

subjects: computer science

abstract: Profile Hidden Markov Models (PHMMs) have been widely used as models for Multiple Sequence Alignments. By their nature, they are generative one-class classifiers trained only on sequences belonging to the target class they represent. Nevertheless, they are often used to discriminate between classes. In this paper, we investigate the beneficial effects of information from non-target classes in discriminative tasks. Firstly, the traditional PHMM is extended to a new binary classifier. Secondly, we propose propositional representations of the original PHMM that capture information from target and non-target sequences and can be used with standard binary classifiers. Since PHMM training is time intensive, we investigate whether our approach allows the training of the PHMM to stop, before it is fully converged, without loss of predictive power.

text: The positive effects of negative information: Extending one-class classification models in binary proteomic sequence classification Profile Hidden Markov Models (PHMMs) have been widely used as models for Multiple Sequence Alignments. By their nature, they are generative one-class classifiers trained only on sequences belonging to the target class they represent. Nevertheless, they are often used to discriminate between classes. In this paper, we investigate the beneficial effects of information from non-target classes in discriminative tasks. Firstly, the traditional PHMM is extended to a new binary classifier. Secondly, we propose propositional representations of the original PHMM that capture information from target and non-target sequences and can be used with standard binary classifiers. Since PHMM training is time intensive, we investigate whether our approach allows the training of the PHMM to stop, before it is fully converged, without loss of predictive power.

year: 2009

title: “If it don’t talk, it's not whakapapa data”: Conceptualising whakapapa data in a digital age

authors: Pēpi Tarapa‐Dewes, Ella

subjects: data protection

abstract: In Te Ao Māori, whakapapa is a sacred framework that connects all aspects of existence. Whakapapa is highly sensitive information and a taonga that requires active protection. But what can be considered whakapapa data in a digital age where data linkage is ubiquitous and the boundaries between personal and collective information are increasingly blurred? We explore this question through a case study with Ngāti Tiipa, a hapū that is actively engaged in its own data sovereignty research. Reflexive thematic analysis of whānau kōrero identified three types of whakapapa data, each denoting a specific kind of connection: 1) between relatives, both living and deceased; 2) between people and places of cultural significance; and 3) between people and the spiritual realm. Whānau concepts of whakapapa data tend to be context‐specific, suggesting that it is more useful to think of whakapapa data as dynamic and relational rather than a fixed, inherent attribute.

text: “If it don’t talk, it's not whakapapa data”: Conceptualising whakapapa data in a digital age In Te Ao Māori, whakapapa is a sacred framework that connects all aspects of existence. Whakapapa is highly sensitive information and a taonga that requires active protection. But what can be considered whakapapa data in a digital age where data linkage is ubiquitous and the boundaries between personal and collective information are increasingly blurred? We explore this question through a case study with Ngāti Tiipa, a hapū that is actively engaged in its own data sovereignty research. Reflexive thematic analysis of whānau kōrero identified three types of whakapapa data, each denoting a specific kind of connection: 1) between relatives, both living and deceased; 2) between people and places of cultural significance; and 3) between people and the spiritual realm. Whānau concepts of whakapapa data tend to be context‐specific, suggesting that it is more useful to think of whakapapa data as dynamic and relational rather than a fixed, inherent attribute.

year: 2026-02