title: Memento Mori : Memento Maori – moko and memory

authors: Te Awekotuku, Ngahuia

subjects: tangi

abstract: Moko patterns, mau moko, “wearing ink” is often explained as an act of remembrance, a symbol of honour or success, of grieving or loss. Memento mori, remembering the dead and remembrance of death, pervades the Maori world, and is profoundly expressed in customary practice – haehae, upoko tuhi, and ta moko. These embodied and visceral experiences are described in waiata tangi, in whai korero, in moteatea, in the traditional context, and graphically recorded on the living flesh in our contemporary world. Mau moko celebrates identity, so modern memorial ornamentation mourns and reflects on this in ‘memento mori’; and also reinforces and engages reality in the correspondent notion of ‘memento Maori’; an assertion that claims dominion and understanding across generations, across time, across space.

text: Memento Mori : Memento Maori – moko and memory Moko patterns, mau moko, “wearing ink” is often explained as an act of remembrance, a symbol of honour or success, of grieving or loss. Memento mori, remembering the dead and remembrance of death, pervades the Maori world, and is profoundly expressed in customary practice – haehae, upoko tuhi, and ta moko. These embodied and visceral experiences are described in waiata tangi, in whai korero, in moteatea, in the traditional context, and graphically recorded on the living flesh in our contemporary world. Mau moko celebrates identity, so modern memorial ornamentation mourns and reflects on this in ‘memento mori’; and also reinforces and engages reality in the correspondent notion of ‘memento Maori’; an assertion that claims dominion and understanding across generations, across time, across space.

year: 2009-11

title: One hundred years of Sylvia Ashton-Warner: An introduction.

authors: Middleton, Sue

subjects: Sylvia Ashton-Warner

abstract: A biography of Sylvia Ashton-Warner is presented. She was born on 17 December 1908 in New Zealand. She studied at the Auckland Teachers' Training College and taught in several native schools including Horoera Native School and Pipiriki Native School. Later she started writing, starting with "Teacher," a book about teaching schemes and followed by "Incense to Idols," "Bell Call," and "Greenstone." Also, her travels to various places are mentioned.

text: One hundred years of Sylvia Ashton-Warner: An introduction. A biography of Sylvia Ashton-Warner is presented. She was born on 17 December 1908 in New Zealand. She studied at the Auckland Teachers' Training College and taught in several native schools including Horoera Native School and Pipiriki Native School. Later she started writing, starting with "Teacher," a book about teaching schemes and followed by "Incense to Idols," "Bell Call," and "Greenstone." Also, her travels to various places are mentioned.

year: 2008

title: Discriminating Against New Classes: One-class versus Multi-class Classification

authors: Hempstalk, Kathryn

subjects: computer science

abstract: Many applications require the ability to identify data that is anomalous with respect to a target group of observations, in the sense of belonging to a new, previously unseen ‘attacker’ class. One possible approach to this kind of verification problem is one-class classification, learning a description of the target class concerned based solely on data from this class. However, if known non-target classes are available at training time, it is also possible to use standard multi-class or two-class classification, exploiting the negative data to infer a description of the target class. In this paper we assume that this scenario holds and investigate under what conditions multi-class and two-class Naïve Bayes classifiers are preferable to the corresponding one-class model when the aim is to identify examples from a new ‘attacker’ class. To this end we first identify a way of performing a fair comparison between the techniques concerned and present an adaptation of standard cross-validation. This is one of the main contributions of the paper. Based on the experimental results obtained, we then show under what conditions which group of techniques is likely to be preferable. Our main finding is that multi-class and two-class classification becomes preferable to one-class classification when a sufficiently large number of non-target classes is available.

text: Discriminating Against New Classes: One-class versus Multi-class Classification Many applications require the ability to identify data that is anomalous with respect to a target group of observations, in the sense of belonging to a new, previously unseen ‘attacker’ class. One possible approach to this kind of verification problem is one-class classification, learning a description of the target class concerned based solely on data from this class. However, if known non-target classes are available at training time, it is also possible to use standard multi-class or two-class classification, exploiting the negative data to infer a description of the target class. In this paper we assume that this scenario holds and investigate under what conditions multi-class and two-class Naïve Bayes classifiers are preferable to the corresponding one-class model when the aim is to identify examples from a new ‘attacker’ class. To this end we first identify a way of performing a fair comparison between the techniques concerned and present an adaptation of standard cross-validation. This is one of the main contributions of the paper. Based on the experimental results obtained, we then show under what conditions which group of techniques is likely to be preferable. Our main finding is that multi-class and two-class classification becomes preferable to one-class classification when a sufficiently large number of non-target classes is available.

year: 2008