C2MS: Dynamic Monitoring and Management of Cloud Infrastructures

Server clustering is a common design principle employed by many organisations who require high availability, scalability and easier management of their infrastructure. Servers are typically clustered according to the service they provide whether it be the application(s) installed, the role of the server or server accessibility for example. In order to optimize performance, manage load and maintain availability, servers may migrate from one cluster group to another making it difficult for server monitoring tools to continuously monitor these dynamically changing groups. Server monitoring tools are usually statically configured and with any change of group membership requires manual reconfiguration; an unreasonable task to undertake on large-scale cloud infrastructures. In this paper we present the Cloudlet Control and Management System (C2MS); a system for monitoring and controlling dynamic groups of physical or virtual servers within cloud infrastructures. The C2MS extends Ganglia - an open source scalable system performance monitoring tool - by allowing system administrators to define, monitor and modify server groups without the need for server reconfiguration. In turn administrators can easily monitor group and individual server metrics on large-scale dynamic cloud infrastructures where roles of servers may change frequently. Furthermore, we complement group monitoring with a control element allowing administrator-specified actions to be performed over servers within service groups as well as introduce further customized monitoring metrics. This paper outlines the design, implementation and evaluation of the C2MS.Comment: Proceedings of the The 5th IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2013), 8 page

A efficient and practical 3D face scanner using near infrared and visible photometric stereo

AbstractThis paper is concerned with the acquisition of model data for automatic 3D face recognition applications. As 3D methods become progressively more popular in face recognition research, the need for fast and accurate data capture has become crucial. This paper is motivated by this need and offers three primary contributions. Firstly, the paper demonstrates that four-source photometric stereo offers a potential means for data capture that is computationally nd financially viable and easily deployable in commercial settings. We have shown that both visible light and less ntrusive near infrared light is suitable for facial illumination. The second contribution is a detailed set of experimental esults that compare the accuracy of the device to ground truth, which was captured using a commercial projected pattern range finder. Importantly, we show that not only is near infrared light a valid alternative to the more commonly xploited visible light, but that it actually gives more accurate reconstructions. Finally, we assess the validity of the Lambertian assumption on skin reflectance data and show that better results may be obtained by incorporating more dvanced reflectance functions, such as the Oren–Nayar model

Vanishing point detection for visual surveillance systems in railway platform environments

© 2018 Elsevier B.V. Visual surveillance is of paramount importance in public spaces and especially in train and metro platforms which are particularly susceptible to many types of crime from petty theft to terrorist activity. Image resolution of visual surveillance systems is limited by a trade-off between several requirements such as sensor and lens cost, transmission bandwidth and storage space. When image quality cannot be improved using high-resolution sensors, high-end lenses or IR illumination, the visual surveillance system may need to increase the resolving power of the images by software to provide accurate outputs such as, in our case, vanishing points (VPs). Despite having numerous applications in camera calibration, 3D reconstruction and threat detection, a general method for VP detection has remained elusive. Rather than attempting the infeasible task of VP detection in general scenes, this paper presents a novel method that is fine-tuned to work for railway station environments and is shown to outperform the state-of-the-art for that particular case. In this paper, we propose a three-stage approach to accurately detect the main lines and vanishing points in low-resolution images acquired by visual surveillance systems in indoor and outdoor railway platform environments. First, several frames are used to increase the resolving power through a multi-frame image enhancer. Second, an adaptive edge detection is performed and a novel line clustering algorithm is then applied to determine the parameters of the lines that converge at VPs; this is based on statistics of the detected lines and heuristics about the type of scene. Finally, vanishing points are computed via a voting system to optimize detection in an attempt to omit spurious lines. The proposed approach is very robust since it is not affected by ever-changing illumination and weather conditions of the scene, and it is immune to vibrations. Accurate and reliable vanishing point detection provides very valuable information, which can be used to aid camera calibration, automatic scene understanding, scene segmentation, semantic classification or augmented reality in platform environments

A new paradigm for space astrophysics mission design

Pursuing ground breaking science in a highly cost-constrained environment presents new challenges to the development of future space astrophysics missions. Within the conventional cost models for large observatories, executing a flagship “mission after next” appears to be unstainable. To achieve our nation’s science ambitions requires a new paradigm of system design, development and manufacture. This paper explores the nature of the current paradigm and proposes a series of steps to guide the entire community to a sustainable future

A real-time PCR-based assay for detection of Wuchereria bancrofti DNA in blood and mosquitoes

We developed and evaluated real-time polymerase chain reaction (PCR) assays for detecting Wuchereria bancrofti DNA in human blood and in mosquitoes. An assay based on detection of the W. bancrofti “LDR” repeat DNA sequence was more sensitive than an assay for Wolbachia 16S rDNA. The LDR-based assay was sensitive for detecting microfilarial DNA on dried membrane filters or on filter paper. We also compared real-time PCR with conventional PCR (C-PCR) for detecting W. bancrofti DNA in mosquito samples collected in endemic areas in Egypt and Papua New Guinea. Although the two methods had comparable sensitivity for detecting filarial DNA in reference samples, real-time PCR was more sensitive than C-PCR in practice with field samples. Other advantages of real-time PCR include its high-throughput capacity and decreased risk of cross-contamination between test samples. We believe that real-time PCR has great potential as a tool for monitoring progress in large-scale filariasis elimination programs

Does Income Mobility Equalize Longer-term Incomes? New Measures of an Old Concept

This paper develops a new class of measures of mobility as an equalizer of longer-term incomes – a concept different from other notions such as mobility as time-independence, positional movement, share movement, income flux, and directional income movement. A number of properties are specified leading to a class of indices, one easily-implementable member of which is applied to data for the United States and France. Using this index, income mobility is found to have equalized longer-term earnings among U.S. men in the 1970s but not in the 1980s or 1990s. In France, though, income mobility was equalizing throughout, and it has attained its maximum in the most recent period

Enhanced Usability of Managing Workflows in an Industrial Data Gateway

The Grid and Cloud User Support Environment (gUSE) enables users convenient and easy access to grid and cloud infrastructures by providing a general purpose, workflow-oriented graphical user interface to create and run workflows on various Distributed Computing Infrastructures (DCIs). Its arrangements for creating and modifying existing workflows are, however, non-intuitive and cumbersome due to the technologies and architecture employed by gUSE. In this paper, we outline the first integrated web-based workflow editor for gUSE with the aim of improving the user experience for those with industrial data workflows and the wider gUSE community. We report initial assessments of the editor's utility based on users' feedback. We argue that combining access to diverse scalable resources with improved workflow creation tools is important for all big data applications and research infrastructures

Comparison of Lidar Backscatter with Particle Distribution and GOES-7 Data in Hurricane Juliette

Measurements of calibrated backscatter, using two continuous wave Doppler lidars operating at wavelengths 9.1 and 10.6 micrometers were obtained along with cloud particle size distributions in Hurricane Juliette on 21 September 1995 at altitude approximately 11.7 km. Agreement between backscatter from the two lidars and with the cloud particle size distribution is excellent. Features in backscatter and particle number density compare well with concurrent GOES-7 infrared images

Traffic-related pollution and asthma prevalence in children. Quantification of associations with nitrogen dioxide.

Ambient nitrogen dioxide is a widely available measure of traffic-related air pollution and is inconsistently associated with the prevalence of asthma symptoms in children. The use of this relationship to evaluate the health impact of policies affecting traffic management and traffic emissions is limited by the lack of a concentration-response function based on systematic review and meta-analysis of relevant studies. Using systematic methods, we identified papers containing quantitative estimates for nitrogen dioxide and the 12 month period prevalence of asthma symptoms in children in which the exposure contrast was within-community and dominated by traffic pollution. One estimate was selected from each study according to an a priori algorithm. Odds ratios were standardised to 10 μg/m(3) and summary estimates were obtained using random- and fixed-effects estimates. Eighteen studies were identified. Concentrations of nitrogen dioxide were estimated for the home address (12) and/or school (8) using a range of methods; land use regression (6), study monitors (6), dispersion modelling (4) and interpolation (2). Fourteen studies showed positive associations but only two associations were statistically significant at the 5 % level. There was moderate heterogeneity (I(2) = 32.8 %) and the random-effects estimate for the odds ratio was 1.06 (95 % CI 1.00 to 1.11). There was no evidence of small study bias. Individual studies tended to have only weak positive associations between nitrogen dioxide and asthma prevalence but the summary estimate bordered on statistical significance at the 5 % level. Although small, the potential impact on asthma prevalence could be considerable because of the high level of baseline prevalence in many cities. Whether the association is causal or indicates the effects of a correlated pollutant or other confounders, the estimate obtained by the meta-analysis would be appropriate for estimating impacts of traffic pollution on asthma prevalence