Features and neural net recognition strategies for hand printed digits

The thesis goal is to develop a computer system for hand printed digit recognition based on an investigation into various feature extractors and neural network strategies. Features such as subwindow pixel summation, moments, and orientation vectors will be among those investigated. Morphological thinning of characters prior to feature extraction will be used to assess the impact on network training and testing. Different strategies for implementing a multilayer perceptron neural network will be investigated. A high-level language called MatLab will be used for neural network algorithm development and quick prototyping. The feature extractors will be developed to operate on small (less than or equal to 256 bits) binary hand printed digits (0, 1, 2, 3, 4, 5, 6, 7, 8, 9)

Plastic possibilities: Contrasting the uses of plastic ‘waste’ in India

This is the final version. Available on open access from Wiley via the DOI in this recordThis article draws on examples of inventive plastic reuse from India and personal anecdotes of elders as an anthropological reflection on possible plastic futures. It sketches the large-scale governmental reforms in the domain of municipal solid waste management, or MSWM (which, by legal definition in India, includes plastic waste). In this regard, it draws out some of the problematic socio-political and environmental implications of Prime Minister Narendra Modi's ‘Clean India’ campaign, whose technocratic policy orientations towards standardized centralized MSWM echo his cultural nationalist agenda. These reforms contrast with home-based re-engineering methods and the redeploying of plastic discards (thereby making them notuner moton (‘like new again’), and their localized circulation through relatively local but uneven reputational and economic networks. Clean India sequesters and processes vast quantities of plastics through the wide-ranging adoption of a waste-to-energy techno-fix (in which plastics are incinerated). In contrast, the authors illustrate routine practices and relations whereby people reuse, repurpose and recycle plastics. While Clean India can detract from and disrupt these mundane practices and everyday relations, these are suggestive of alternative plastic futures – both socio-material and environmental

Phase-specific and lifetime costs of cancer care in Ontario, Canada

BACKGROUND: Cancer is a major public health issue and represents a significant economic burden to health care systems worldwide. The objective of this analysis was to estimate phase-specific, 5-year and lifetime net costs for the 21 most prevalent cancer sites, and remaining tumour sites combined, in Ontario, Canada. METHODS: We selected all adult patients diagnosed with a primary cancer between 1997 and 2007, with valid ICD-O site and histology codes, and who survived 30 days or more after diagnosis, from the Ontario Cancer Registry (N = 394,092). Patients were linked to treatment data from Cancer Care Ontario and administrative health care databases at the Institute for Clinical and Evaluative Sciences. Net costs (i.e., cost difference between patients and matched non-cancer control subjects) were estimated by phase of care and sex, and used to estimate 5-year and lifetime costs. RESULTS: Mean net costs of care (2009 CAD) were highest in the initial (6 months post-diagnosis) and terminal (12 months pre-death) phases, and lowest in the (3 months) pre-diagnosis and continuing phases of care. Phase-specific net costs were generally lowest for melanoma and highest for brain cancer. Mean 5-year net costs varied from less than $25,000 for melanoma, thyroid and testicular cancers to more than$60,000 for multiple myeloma and leukemia. Lifetime costs ranged from less than $55,000 for lung and liver cancers to over$110,000 for leukemia, multiple myeloma, lymphoma and breast cancer. CONCLUSIONS: Costs of cancer care are substantial and vary by cancer site, phase of care and time horizon analyzed. These cost estimates are valuable to decision makers to understand the economic burden of cancer care and may be useful inputs to researchers undertaking cancer-related economic evaluations