title: Mid-Holocene Aboriginal occupation of offshore islands in northern Australia? A reassessment of Wurdukanhan, Mornington Island, southern Gulf of Carpentaria, Australia

authors: Rosendahl, Daniel

subjects: Science & Technology

abstract: Claims for mid-Holocene Aboriginal occupation at the shell matrix site of Wurdukanhan, Mornington Island, Gulf of Carpentaria, Australia, are reassessed through an analysis of the excavated assemblage coupled with new surveys and an extensive dating program. Memmott et al. (2006, pp. 38, 39) reported basal ages of c.5000–5500 years from Wurdukanhan as ‘the oldest date yet obtained for any archaeological site on the coast of the southern Gulf of Carpentaria’ and used these dates to argue for ‘a relatively lengthy occupation since at least the mid-Holocene’. If substantiated, with the exception of western Torres Strait, these claims make Mornington Island the only offshore island used across northern Australia in the mid-Holocene where it is conventionally thought that Aboriginal people only (re)colonised islands after sea-level maximum was achieved after the mid-Holocene. Our analysis of Wurdukanhan demonstrates high shellfish taxa diversity, high rates of natural shell predation and high densities of foraminifera throughout the deposit demonstrating a natural origin for the assemblage. Results are considered in the context of other dated shell matrix sites in the area and a geomorphological model for landscape development of the Sandalwood River catchment.

text: Mid-Holocene Aboriginal occupation of offshore islands in northern Australia? A reassessment of Wurdukanhan, Mornington Island, southern Gulf of Carpentaria, Australia Claims for mid-Holocene Aboriginal occupation at the shell matrix site of Wurdukanhan, Mornington Island, Gulf of Carpentaria, Australia, are reassessed through an analysis of the excavated assemblage coupled with new surveys and an extensive dating program. Memmott et al. (2006, pp. 38, 39) reported basal ages of c.5000–5500 years from Wurdukanhan as ‘the oldest date yet obtained for any archaeological site on the coast of the southern Gulf of Carpentaria’ and used these dates to argue for ‘a relatively lengthy occupation since at least the mid-Holocene’. If substantiated, with the exception of western Torres Strait, these claims make Mornington Island the only offshore island used across northern Australia in the mid-Holocene where it is conventionally thought that Aboriginal people only (re)colonised islands after sea-level maximum was achieved after the mid-Holocene. Our analysis of Wurdukanhan demonstrates high shellfish taxa diversity, high rates of natural shell predation and high densities of foraminifera throughout the deposit demonstrating a natural origin for the assemblage. Results are considered in the context of other dated shell matrix sites in the area and a geomorphological model for landscape development of the Sandalwood River catchment.

year: 2015

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: Creating an environment to inform, build, and sustain a Māori health research workforce

authors: Barrett, Nikki Maree

subjects: Kaupapa Māori

abstract: Ensuring the growth and development of the Māori health research workforce is key to achieving health equity for Māori and enabling positive change for all New Zealanders. The purpose of this study was to identify enablers and barriers to research for Māori staff in a large health organisation, and to understand how research is developed and undertaken. A Kaupapa Māori mixed-methods study was undertaken, using an electronic survey comprised of quantitative data and open-ended responses delivered to all Māori staff at the Waikato District Health Board. Following the survey were 10 one on one interviews. Survey data were analysed using descriptive statistics and open-ended responses summarised. A descriptive thematic analysis was undertaken of the interview data. Each of the interview responses was coded and five themes emerged. Frontline Māori staff affirmed their desire to conduct, design, and undertake health research. Challenges to staff included a lack of information on research opportunities, unclear processes for initiating research, and lack of support and resource. The evidence from participants provides insights into Māori health research priorities, considerations for those wanting to undertake research, and solutions for informing, building, and sustaining the Māori health research workforce.

text: Creating an environment to inform, build, and sustain a Māori health research workforce Ensuring the growth and development of the Māori health research workforce is key to achieving health equity for Māori and enabling positive change for all New Zealanders. The purpose of this study was to identify enablers and barriers to research for Māori staff in a large health organisation, and to understand how research is developed and undertaken. A Kaupapa Māori mixed-methods study was undertaken, using an electronic survey comprised of quantitative data and open-ended responses delivered to all Māori staff at the Waikato District Health Board. Following the survey were 10 one on one interviews. Survey data were analysed using descriptive statistics and open-ended responses summarised. A descriptive thematic analysis was undertaken of the interview data. Each of the interview responses was coded and five themes emerged. Frontline Māori staff affirmed their desire to conduct, design, and undertake health research. Challenges to staff included a lack of information on research opportunities, unclear processes for initiating research, and lack of support and resource. The evidence from participants provides insights into Māori health research priorities, considerations for those wanting to undertake research, and solutions for informing, building, and sustaining the Māori health research workforce.

year: 2023