title: Automatic species identification of live moths

authors: Mayo, Michael

subjects: computer science

abstract: A collection consisting of the images of 774 live moth individuals, each moth belonging to one of 35 different UK species, was analysed to determine if data mining techniques could be used effectively for automatic species identification. Feature vectors were extracted from each of the moth images and the machine learning toolkit WEKA was used to classify the moths by species using the feature vectors. Whereas a previous analysis of this image dataset reported in the literature [A. Watson, M. O'Neill, I. Kitching, Automated identification of live moths (Macrolepidoptera) using Digital Automated Identification System (DAISY), Systematics and Biodiversity 1 (3) (2004) 287-300.] required that each moth's least worn wing region be highlighted manually for each image, WEKA was able to achieve a greater level of accuracy (85%) using support vector machines without manual specification of a region of interest at all. This paper describes the features that were extracted from the images, and the various experiments using different classifiers and datasets that were performed. The results show that data mining can be usefully applied to the problem of automatic species identification of live specimens in the field.

text: Automatic species identification of live moths A collection consisting of the images of 774 live moth individuals, each moth belonging to one of 35 different UK species, was analysed to determine if data mining techniques could be used effectively for automatic species identification. Feature vectors were extracted from each of the moth images and the machine learning toolkit WEKA was used to classify the moths by species using the feature vectors. Whereas a previous analysis of this image dataset reported in the literature [A. Watson, M. O'Neill, I. Kitching, Automated identification of live moths (Macrolepidoptera) using Digital Automated Identification System (DAISY), Systematics and Biodiversity 1 (3) (2004) 287-300.] required that each moth's least worn wing region be highlighted manually for each image, WEKA was able to achieve a greater level of accuracy (85%) using support vector machines without manual specification of a region of interest at all. This paper describes the features that were extracted from the images, and the various experiments using different classifiers and datasets that were performed. The results show that data mining can be usefully applied to the problem of automatic species identification of live specimens in the field.

year: 2007

title: Not so scholarly but certainly on-message: the leadership BES and its significant silences

authors: Thrupp, Martin

subjects: New Zealand

abstract: This article suggests that the Leadership BES is intended to provide the intellectual underpinning for the Ministry of Education's preferred model of school leadership in New Zealand. Nevertheless, the instrumental 'what works' approach taken by the BES represents only a constrained and conservative research agenda which leaves out structural and political perspectives on school leadership. A number of points drawn from the introductory and main chapters of the BES are used to illustrate the problem. The article concludes by noting topics and authors which would have provided balance if included in the BES.

text: Not so scholarly but certainly on-message: the leadership BES and its significant silences This article suggests that the Leadership BES is intended to provide the intellectual underpinning for the Ministry of Education's preferred model of school leadership in New Zealand. Nevertheless, the instrumental 'what works' approach taken by the BES represents only a constrained and conservative research agenda which leaves out structural and political perspectives on school leadership. A number of points drawn from the introductory and main chapters of the BES are used to illustrate the problem. The article concludes by noting topics and authors which would have provided balance if included in the BES.

year: 2010

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