Delinquency prevention procedures of Massachusetts police

Thesis (M.S.)--Boston Universit

Learning Deep Neural Networks for Enhanced Prostate Histological Image Analysis

In recent years, deep convolutional neural networks (CNNs) have shown promise for improving prostate cancer diagnosis by enabling quantitative histopathology through digital pathology. However, there are a number of factors that limit the widespread adoption and clinical utility of deep learning for digital pathology. One of these limitations is the requirement for large labelled training datasets which are expensive to construct due to limited availability of the requisite expertise. Additionally, digital pathology applications typically require the digitisation of histological slides at high magnifications. This process can be challenging especially when digitising large histological slides such as prostatectomies. This work studies and addresses these issues in two important applications of digital pathology: prostate nuclei detection and cell type classification. We study the performance of CNNs at different magnifications and demonstrate that it is possible to perform nuclei detection in low magnification prostate histopathology using CNNs with minimal loss in accuracy. We then study the training of prostate nuclei detectors in the small data setting and demonstrate that although it is possible to train nuclei detectors with minimal data, the models will be sensitive to hyperparameter choice and therefore may not generalise well. Instead, we show that pre-training the CNNs with colon histology data makes them more robust to hyperparameter choice. We then study the CNN performance for prostate cell type classification using supervised, transfer and semi-supervised learning in the small data setting. Our results show that transfer learning can be detrimental to performance but semi-supervised learning is able to provide significant improvements to the learning curve, allowing the training of neural networks with modest amounts of labelled data. We then propose a novel semi-supervised learning method called Deeply-supervised Exemplar CNNs and demonstrate their ability to improve the cell type classifier learning curves at a much better rate than previous semi-supervised neural network methods

Antarctic Ocean polynyas

The spatial and temporal variability of sea ice concentrations derived from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) brightness temperatures are presented. Emphasis is on the continental shelf region of the Ross Sea during 1984, when supporting data were obtained from oceanographic stations and moored instruments. The effects of the large spring polynya in the Ross Sea on summer insolation, surface heat layer storage, and late autumn ice formation are described

Policies to create and destroy human capital in Europe

Trends in skill bias and greater turbulence in modern labor markets put wages and employment prospects of unskilled workers under pressure. Weak incentives to utilize and maintain skills over the life-cycle become manifest with the ageing of the population. Reinvention of human capital policies is required to avoid increasing welfare state dependency among the unskilled and to reduce inefficiencies in human capital formation. Policy makers should acknowledge strong dynamic complementarities in skill formation. Investments in the human capital of children should expand relative to investment in older workers. There is no trade-off between equity and efficiency at early ages of human development but there is a substantial trade-off at later ages. Later remediation of skill deficits acquired in early years is often ineffective. Active labor market and training policies should therefore be reformulated. Skill formation is impaired when the returns to skill formation are low due to low skill use and insufficient skill maintenance later on in life. High marginal tax rates and generous benefit systems reduce labor force participation rates and hours worked and thereby lower the utilization rate of human capital. Tax-benefit systems should be reconsidered as they increasingly redistribute resources from outsiders to insiders in labor markets which is both distortionary and inequitable. Early retirement and pension schemes should be made actuarially fairer as they entail strong incentives to retire early and human capital is thus written off too quickly

I Want You, Dearie

https://digitalcommons.library.umaine.edu/mmb-vp/4717/thumbnail.jp