Ball-Scale Based Hierarchical Multi-Object Recognition in 3D Medical Images

This paper investigates, using prior shape models and the concept of ball scale (b-scale), ways of automatically recognizing objects in 3D images without performing elaborate searches or optimization. That is, the goal is to place the model in a single shot close to the right pose (position, orientation, and scale) in a given image so that the model boundaries fall in the close vicinity of object boundaries in the image. This is achieved via the following set of key ideas: (a) A semi-automatic way of constructing a multi-object shape model assembly. (b) A novel strategy of encoding, via b-scale, the pose relationship between objects in the training images and their intensity patterns captured in b-scale images. (c) A hierarchical mechanism of positioning the model, in a one-shot way, in a given image from a knowledge of the learnt pose relationship and the b-scale image of the given image to be segmented. The evaluation results on a set of 20 routine clinical abdominal female and male CT data sets indicate the following: (1) Incorporating a large number of objects improves the recognition accuracy dramatically. (2) The recognition algorithm can be thought as a hierarchical framework such that quick replacement of the model assembly is defined as coarse recognition and delineation itself is known as finest recognition. (3) Scale yields useful information about the relationship between the model assembly and any given image such that the recognition results in a placement of the model close to the actual pose without doing any elaborate searches or optimization. (4) Effective object recognition can make delineation most accurate.Comment: This paper was published and presented in SPIE Medical Imaging 201

Efficacy of Surrogate Measures in Performance-Based Design of Water Distribution Networks

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Raman and photoluminescence studies on thermally annealed porous silicon

We report Raman and Photoluminescence (PL) studies of porous silicon (PS) as a function of isochronal thermal annealing from room temperature to 900°C. The PL peak position and intensity show nonmonotonic variation with increasing temperature. The PL intensity first increases upto 100°C, then decreases till 550°C and recovers its intensity at 700 °C before it completely disappears at 800 °C. The red shifted asymmetric Raman line shape can be fitted by phonon confinement model along with the disordered silicon component. Our results clearly indicate that the origin of visible PL can be better explained by a new hybrid model which incorporates both nanostructures for quantum confinement and silicon complexes (such as SiHx and siloxene) and defects at Si/SiO2 interfaces as luminescent centres

Origin of visible photoluminescence from porous silicon as studied by Raman spectroscopy

In this paper we discuss the different models proposed to explain the visible luminescence in porous silicon (PS). We review our recent photoluminescence and Raman studies on PS as a function of different preparation conditions and isochronal thermal annealing. Our results can be explained by a hybrid model which incorporates both nanostructures for quantum confinement and silicon complexes (such as SiHx and siloxene) and defects at Si/SiO2 interfaces as luminescent centres

Unimpeded permeation of water through helium-leak-tight graphene-based membranes

Permeation through nanometer pores is important in the design of materials for filtration and separation techniques and because of unusual fundamental behavior arising at the molecular scale. We found that submicron-thick membranes made from graphene oxide can be completely impermeable to liquids, vapors and gases, including helium, but allow unimpeded permeation of water (H2O permeates through the membranes at least 10^10 times faster than He). We attribute these seemingly incompatible observations to a low-friction flow of a monolayer of water through two dimensional capillaries formed by closely spaced graphene sheets. Diffusion of other molecules is blocked by reversible narrowing of the capillaries in low humidity and/or by their clogging with water

The Making of Cloud Applications An Empirical Study on Software Development for the Cloud

Cloud computing is gaining more and more traction as a deployment and provisioning model for software. While a large body of research already covers how to optimally operate a cloud system, we still lack insights into how professional software engineers actually use clouds, and how the cloud impacts development practices. This paper reports on the first systematic study on how software developers build applications in the cloud. We conducted a mixed-method study, consisting of qualitative interviews of 25 professional developers and a quantitative survey with 294 responses. Our results show that adopting the cloud has a profound impact throughout the software development process, as well as on how developers utilize tools and data in their daily work. Among other things, we found that (1) developers need better means to anticipate runtime problems and rigorously define metrics for improved fault localization and (2) the cloud offers an abundance of operational data, however, developers still often rely on their experience and intuition rather than utilizing metrics. From our findings, we extracted a set of guidelines for cloud development and identified challenges for researchers and tool vendors