A study of publish/subscribe systems for real-time grid monitoring

Monitoring and controlling a large number of geographically distributed scientific instruments is a challenging task. Some operations on these instruments require real-time (or quasi real-time) response which make it even more difficult. In this paper, we describe the requirements of distributed monitoring for a possible future electrical power grid based on real-time extensions to grid computing. We examine several standards and publish/subscribe middleware candidates, some of which were specially designed and developed for grid monitoring. We analyze their architecture and functionality, and discuss the advantages and disadvantages. We report on a series of tests to measure their real-time performance and scalability

Mosaicking with cosmic microwave background interferometers

Measurements of cosmic microwave background (CMB) anisotropies by interferometers offer several advantages over single-dish observations. The formalism for analyzing interferometer CMB data is well developed in the flat-sky approximation, valid for small fields of view. As the area of sky is increased to obtain finer spectral resolution, this approximation needs to be relaxed. We extend the formalism for CMB interferometry, including both temperature and polarization, to mosaics of observations covering arbitrarily large areas of the sky, with each individual pointing lying within the flat-sky approximation. We present a method for computing the correlation between visibilities with arbitrary pointing centers and baselines and illustrate the effects of sky curvature on the l-space resolution that can be obtained from a mosaic.Comment: 9 pages; submitted to Ap

Towards Expressive and Versatile Visualization-as-a-Service (VaaS)

The rapid growth of data in scientific visualization has posed significant challenges to the scalability and availability of interactive visualization tools. These challenges can be largely attributed to the limitations of traditional monolithic applications in handling large datasets and accommodating multiple users or devices. To address these issues, the Visualization-as-a-Service (VaaS) architecture has emerged as a promising solution. VaaS leverages cloud-based visualization capabilities to provide on-demand and cost-effective interactive visualization. Existing VaaS has been simplistic by design with focuses on task-parallelism with single-user-per-device tasks for predetermined visualizations. This dissertation aims to extend the capabilities of VaaS by exploring data-parallel visualization services with multi-device support and hypothesis-driven explorations. By incorporating stateful information and enabling dynamic computation, VaaS\u27 performance and flexibility for various real-world applications is improved. This dissertation explores the history of monolithic and VaaS architectures, the design and implementations of 3 new VaaS applications, and a final exploration of the future of VaaS. This research contributes to the advancement of interactive scientific visualization, addressing the challenges posed by large datasets and remote collaboration scenarios

Systematic Errors in Cosmic Microwave Background Interferometry

Cosmic microwave background (CMB) polarization observations will require superb control of systematic errors in order to achieve their full scientific potential, particularly in the case of attempts to detect the B modes that may provide a window on inflation. Interferometry may be a promising way to achieve these goals. This paper presents a formalism for characterizing the effects of a variety of systematic errors on interferometric CMB polarization observations, with particular emphasis on estimates of the B-mode power spectrum. The most severe errors are those that couple the temperature anisotropy signal to polarization; such errors include cross-talk within detectors, misalignment of polarizers, and cross-polarization. In a B mode experiment, the next most serious category of errors are those that mix E and B modes, such as gain fluctuations, pointing errors, and beam shape errors. The paper also indicates which sources of error may cause circular polarization (e.g., from foregrounds) to contaminate the cosmologically interesting linear polarization channels, and conversely whether monitoring of the circular polarization channels may yield useful information about the errors themselves. For all the sources of error considered, estimates of the level of control that will be required for both E and B mode experiments are provided. Both experiments that interfere linear polarizations and those that interfere circular polarizations are considered. The fact that circular experiments simultaneously measure both linear polarization Stokes parameters in each baseline mitigates some sources of error.Comment: 19 pages, 9 figures, submitted to Phys. Rev.

Distributed monitoring and control of future power systems via grid computing

It is now widely accepted within the electrical power supply industry that future power systems operates with significantly larger numbers of small-scale highly dispersed generation units that use renewable energy sources and also reduce carbon dioxide emissions. In order to operate such future power systems securely and efficiently it will be necessary to monitor and control output levels and scheduling when connecting such generation to a power system especially when it is typically embedded at the distribution level. Traditional monitoring and control technology that is currently employed at the transmission level is highly centralized and not scalable to include such significant increases in distributed and embedded generation. However, this paper proposes and demonstrates the adoption of a relatively new technology 'grid computing' that can provide both a scalable and universally adoptable solution to the problems associated with the distributed monitoring and control of future power systems

A Bayesian approach to discrete object detection in astronomical datasets

A Bayesian approach is presented for detecting and characterising the signal from discrete objects embedded in a diffuse background. The approach centres around the evaluation of the posterior distribution for the parameters of the discrete objects, given the observed data, and defines the theoretically-optimal procedure for parametrised object detection. Two alternative strategies are investigated: the simultaneous detection of all the discrete objects in the dataset, and the iterative detection of objects. In both cases, the parameter space characterising the object(s) is explored using Markov-Chain Monte-Carlo sampling. For the iterative detection of objects, another approach is to locate the global maximum of the posterior at each iteration using a simulated annealing downhill simplex algorithm. The techniques are applied to a two-dimensional toy problem consisting of Gaussian objects embedded in uncorrelated pixel noise. A cosmological illustration of the iterative approach is also presented, in which the thermal and kinetic Sunyaev-Zel'dovich effects from clusters of galaxies are detected in microwave maps dominated by emission from primordial cosmic microwave background anisotropies.Comment: 20 pages, 12 figures, accepted by MNRAS; contains some additional material in response to referee's comment

Automatic Classification of Human Epithelial Type 2 Cell Indirect Immunofluorescence Images using Cell Pyramid Matching

This paper describes a novel system for automatic classification of images obtained from Anti-Nuclear Antibody (ANA) pathology tests on Human Epithelial type 2 (HEp-2) cells using the Indirect Immunofluorescence (IIF) protocol. The IIF protocol on HEp-2 cells has been the hallmark method to identify the presence of ANAs, due to its high sensitivity and the large range of antigens that can be detected. However, it suffers from numerous shortcomings, such as being subjective as well as time and labour intensive. Computer Aided Diagnostic (CAD) systems have been developed to address these problems, which automatically classify a HEp-2 cell image into one of its known patterns (eg. speckled, homogeneous). Most of the existing CAD systems use handpicked features to represent a HEp-2 cell image, which may only work in limited scenarios. We propose a novel automatic cell image classification method termed Cell Pyramid Matching (CPM), which is comprised of regional histograms of visual words coupled with the Multiple Kernel Learning framework. We present a study of several variations of generating histograms and show the efficacy of the system on two publicly available datasets: the ICPR HEp-2 cell classification contest dataset and the SNPHEp-2 dataset.Comment: arXiv admin note: substantial text overlap with arXiv:1304.126

Sensitivity of a Bolometric Interferometer to the CMB power spectrum

Context. The search for B-mode polarization fluctuations in the Cosmic Microwave Background is one of the main challenges of modern cosmology. The expected level of the B-mode signal is very low and therefore requires the development of highly sensitive instruments with low systematic errors. An appealing possibility is bolometric interferometry. Aims. We compare in this article the sensitivity on the CMB angular power spectrum achieved with direct imaging, heterodyne and bolometric interferometry. Methods. Using a simple power spectrum estimator, we calculate its variance leading to the counterpart for bolometric interferometry of the well known Knox formula for direct imaging. Results. We find that bolometric interferometry is less sensitive than direct imaging. However, as expected, it is finally more sensitive than heterodyne interferometry due to the low noise of the bolometers. It therefore appears as an alternative to direct imagers with different and possibly lower systematic errors, mainly due to the absence of an optical setup in front of the horns.Comment: 5 pages, 3 figures. This last version matches the published version (Astronomy and Astrophysics 491 3 (2008) 923-927). Sensitivity of Heterodyne Interferometers modified by a factor of tw