title: Experiments with multi-view multi-instance learning for supervised image classification

authors: Mayo, Michael

subjects: computer science

abstract: In this paper we empirically investigate the benefits of multi-view multi-instance (MVMI) learning for supervised image classification. In multi-instance learning, examples for learning contain bags of feature vectors and thus data from different views cannot simply be concatenated as in the single-instance case. Hence, multi-view learning, where one classifier is built per view, is particularly attractive when applying multi-instance learning to image classification. We take several diverse image data sets—ranging from person detection to astronomical object classification to species recognition—and derive a set of multiple instance views from each of them. We then show via an extensive set of 10_10 stratified cross-validation experiments that MVMI, based on averaging predicted confidence scores, generally exceeds the performance of traditional single-view multi-instance learning, when using support vector machines and boosting as the underlying learning algorithms.

text: Experiments with multi-view multi-instance learning for supervised image classification In this paper we empirically investigate the benefits of multi-view multi-instance (MVMI) learning for supervised image classification. In multi-instance learning, examples for learning contain bags of feature vectors and thus data from different views cannot simply be concatenated as in the single-instance case. Hence, multi-view learning, where one classifier is built per view, is particularly attractive when applying multi-instance learning to image classification. We take several diverse image data sets—ranging from person detection to astronomical object classification to species recognition—and derive a set of multiple instance views from each of them. We then show via an extensive set of 10_10 stratified cross-validation experiments that MVMI, based on averaging predicted confidence scores, generally exceeds the performance of traditional single-view multi-instance learning, when using support vector machines and boosting as the underlying learning algorithms.

year: 2011

title: Monitoring pre-hospital transport of severely injured patients in the Midland Region of New Zealand.

authors: Whitehead, Jesse

subjects: Humans

abstract: AIM: Pre-hospital triage strategies aim to identify the type and extent of patient injuries and ensure that they are transferred to the most appropriate trauma centres. Despite the importance of appropriate pre-hospital transport, there is little evidence base to assist medical staff on optimal destination policy for emergent pre-hospital transport. This paper explores the spatial relationship of patient transfers prior to the implementation of the Midland Pre-Hospital Trauma Destination Matrix in New Zealand, and is a retrospective view of practice against a destination policy that was applied after the study period. METHODS: We use data obtained from the Midland Trauma Registry merged with Global Positioning System (GPS) data from St John and Land Information New Zealand Data Service on major trauma occurring in 2014 and 2015. Using ArcGIS, data were analysed for spatial relationships between factors associated with major trauma events and pre-hospital transportation. RESULTS: In the retrospective analysis of 162 major trauma patients, 107 (66%) were transported to a hospital that matched the destination specified in the Matrix, and 55 (34%) were transported to a non-Matrix designated hospital. CONCLUSION: Approximately one-third of patients were not directly transported to the preferred definitive care hospital subsequently defined in the Midland Pre-Hospital Trauma Destination Matrix. Ongoing monitoring of the pre-hospital transportation system and the implementation of a formal pre-hospital transport policy may improve the efficiency of the Midland Trauma System. Future studies should examine the possible reasons for variations in triage decisions across the Midland Region.

text: Monitoring pre-hospital transport of severely injured patients in the Midland Region of New Zealand. AIM: Pre-hospital triage strategies aim to identify the type and extent of patient injuries and ensure that they are transferred to the most appropriate trauma centres. Despite the importance of appropriate pre-hospital transport, there is little evidence base to assist medical staff on optimal destination policy for emergent pre-hospital transport. This paper explores the spatial relationship of patient transfers prior to the implementation of the Midland Pre-Hospital Trauma Destination Matrix in New Zealand, and is a retrospective view of practice against a destination policy that was applied after the study period. METHODS: We use data obtained from the Midland Trauma Registry merged with Global Positioning System (GPS) data from St John and Land Information New Zealand Data Service on major trauma occurring in 2014 and 2015. Using ArcGIS, data were analysed for spatial relationships between factors associated with major trauma events and pre-hospital transportation. RESULTS: In the retrospective analysis of 162 major trauma patients, 107 (66%) were transported to a hospital that matched the destination specified in the Matrix, and 55 (34%) were transported to a non-Matrix designated hospital. CONCLUSION: Approximately one-third of patients were not directly transported to the preferred definitive care hospital subsequently defined in the Midland Pre-Hospital Trauma Destination Matrix. Ongoing monitoring of the pre-hospital transportation system and the implementation of a formal pre-hospital transport policy may improve the efficiency of the Midland Trauma System. Future studies should examine the possible reasons for variations in triage decisions across the Midland Region.

year: 2018

title: Donna Awatere’s Māori Sovereignty: Reflections on White Supremacy and the Racialization of Crime Control and Surveillance in Aotearoa New Zealand

authors: Dawson, Brian

abstract: Donna Awatere’s examination of whiteness within the Aotearoa New Zealand context, specifically white cultural imperialism, has largely been ignored in academic scholarship. For her, white culture, and its articulation through governance and policy, is the starting point and lens to understanding and addressing historical and contemporary Māori dispossession and ensuing strategies of racialized surveillance, control, and containment. In this essay, we argue that Awatere’s attention to past forms of genocide – mapping them to emerging forms of state confinement of Māori, which engender genocidal characteristics, and problematizing “whiteness” – situates the book Māori Sovereignty as an important text in the field of criminal justice, especially that which manifests in settler-colonial contexts.

text: Donna Awatere’s Māori Sovereignty: Reflections on White Supremacy and the Racialization of Crime Control and Surveillance in Aotearoa New Zealand Donna Awatere’s examination of whiteness within the Aotearoa New Zealand context, specifically white cultural imperialism, has largely been ignored in academic scholarship. For her, white culture, and its articulation through governance and policy, is the starting point and lens to understanding and addressing historical and contemporary Māori dispossession and ensuing strategies of racialized surveillance, control, and containment. In this essay, we argue that Awatere’s attention to past forms of genocide – mapping them to emerging forms of state confinement of Māori, which engender genocidal characteristics, and problematizing “whiteness” – situates the book Māori Sovereignty as an important text in the field of criminal justice, especially that which manifests in settler-colonial contexts.

year: 2023-07-27