Long term vacuum storage test and vibration effects evaluation on multi-layer super insulation blankets. Supplement to Voyager thermal insulation systems. Phase 2 - Summary report

Long term vacuum storage test and vibration effects analysis of multilayer super insulation blanket

Planetary vehicle thermal insulation systems, phase I Summary report

Tests and analyses to select materials and techniques for thermal insulation of planetary spacecraf

Planetary vehicle thermal insulation systems Final report

Goldized Mylar or Kapton and other materials for planetary vehicle thermal insulation system

Improved CTA Coronary Segmentation with a Volume-Specific Intensity Threshold

State-of-the-art CTA imaging equipment has increased increased clinician's ability to make non-invasive diagnoses of coronary heart disease; however, an effective interpretation of the cardiac CTA becomes cumbersome due to large amount of imaged data. Intensity based background suppression is often used to enhance the coronary vasculature but setting a fixed threshold to discriminate coronaries from fatty muscles could be misleading due to non-homogeneous response of contrast medium in CTA volumes. In this work, we propose a volumespecific model of the contrast medium in the coronary segmentation process to improve the segmentation accuracy. The influence of the contrast medium in a CTA volume was modelled by approximating the intensity histogram of the descending aorta with Gaussian approximation. It should be noted that a significant variation in Gaussian mean for 12 CTA volumes validates the need of volume-wise exclusive intensity threshold for accurate coronary segmentation. Moreover, the effectiveness of the adaptive intensity threshold is illustrated with the help of qualitative and quantitative results

End-to-End Trainable Deep Active Contour Models for Automated Image Segmentation: Delineating Buildings in Aerial Imagery

The automated segmentation of buildings in remote sensing imagery is a challenging task that requires the accurate delineation of multiple building instances over typically large image areas. Manual methods are often laborious and current deep-learning-based approaches fail to delineate all building instances and do so with adequate accuracy. As a solution, we present Trainable Deep Active Contours (TDACs), an automatic image segmentation framework that intimately unites Convolutional Neural Networks (CNNs) and Active Contour Models (ACMs). The Eulerian energy functional of the ACM component includes per-pixel parameter maps that are predicted by the backbone CNN, which also initializes the ACM. Importantly, both the ACM and CNN components are fully implemented in TensorFlow and the entire TDAC architecture is end-to-end automatically differentiable and backpropagation trainable without user intervention. TDAC yields fast, accurate, and fully automatic simultaneous delineation of arbitrarily many buildings in the image. We validate the model on two publicly available aerial image datasets for building segmentation, and our results demonstrate that TDAC establishes a new state-of-the-art performance.Comment: Accepted to European Conference on Computer Vision (ECCV) 202

Not just for romance: applications of speed dating in social work education

In this article we address how a contemporary adaptation of the \u27speed dating\u27 model was used for educational purposes with two cohorts of social work students. We outline the dimensions of \u27speed dating\u27 as a contemporary social phenomenon, then address how this model relates specifically to groupwork process, and can be used to facilitate social work student learning. The curriculum for two classroom group activities using the \u27speed dating\u27 model are outlined, the first to develop university level study skills, the second for debriefing field placement learning experiences. Finally we examine why the \u27speed dating\u27 metaphor was successful in provoking a playful yet constructively creative space for students to engage in groupwork process.<br /

Automatic segmentation of myocardium from black-blood MR images using entropy and local neighborhood information.

By using entropy and local neighborhood information, we present in this study a robust adaptive Gaussian regularizing Chan-Vese (CV) model to segment the myocardium from magnetic resonance images with intensity inhomogeneity. By utilizing the circular Hough transformation (CHT) our model is able to detect epicardial and endocardial contours of the left ventricle (LV) as circles automatically, and the circles are used as the initialization. In the cost functional of our model, the interior and exterior energies are weighted by the entropy to improve the robustness of the evolving curve. Local neighborhood information is used to evolve the level set function to reduce the impact of the heterogeneity inside the regions and to improve the segmentation accuracy. An adaptive window is utilized to reduce the sensitivity to initialization. The Gaussian kernel is used to regularize the level set function, which can not only ensure the smoothness and stability of the level set function, but also eliminate the traditional Euclidean length term and re-initialization. Extensive validation of the proposed method on patient data demonstrates its superior performance over other state-of-the-art methods

Late Byzantine Mineral Soda High Alumina Glasses from Asia Minor: A New Primary Glass Production Group

The chemical characterisation of archaeological glass allows the discrimination between different glass groups and the identification of raw materials and technological traditions of their production. Several lines of evidence point towards the large-scale production of first millennium CE glass in a limited number of glass making factories from a mixture of Egyptian mineral soda and a locally available silica source. Fundamental changes in the manufacturing processes occurred from the eight/ninth century CE onwards, when Egyptian mineral soda was gradually replaced by soda-rich plant ash in Egypt as well as the Islamic Middle East. In order to elucidate the supply and consumption of glass during this transitional period, 31 glass samples from the assemblage found at Pergamon (Turkey) that date to the fourth to fourteenth centuries CE were analysed by electron microprobe analysis (EPMA) and by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS). The statistical evaluation of the data revealed that the Byzantine glasses from Pergamon represent at least three different glass production technologies, one of which had not previously been recognised in the glass making traditions of the Mediterranean. While the chemical characteristics of the late antique and early medieval fragments confirm the current model of glass production and distribution at the time, the elemental make-up of the majority of the eighth- to fourteenth-century glasses from Pergamon indicate the existence of a late Byzantine glass type that is characterised by high alumina levels. Judging from the trace element patterns and elevated boron and lithium concentrations, these glasses were produced with a mineral soda different to the Egyptian natron from the Wadi Natrun, suggesting a possible regional Byzantine primary glass production in Asia Minor