Intelligent Computing for Sustainable Energy and Environment (ICSEE 2012)

No Abstract available

Herschel key program HERITAGE:A far-infrared source catalog for the Magellanic Clouds

Observations from the HERschel Inventory of the Agents of Galaxy Evolution (HERITAGE ) have been used to identify dusty populations of sources in the Large and Small Magellanic Clouds (LMC and SMC). We conducted the study using the HERITAGE catalogs of point sources available from the Herschel Science Center from both the Photodetector Array Camera and Spectrometer (PACS; 100 and 160 μm) and Spectral and Photometric Imaging Receiver (SPIRE; 250, 350, and 500 μm) cameras. These catalogs are matched to each other to create a Herschel band-merged catalog and then further matched to archival Spitzer IRAC and MIPS catalogs from the Spitzer Surveying the Agents of Galaxy Evolution (SAGE) and SAGE-SMC surveys to create single mid- to far-infrared (far-IR) point source catalogs that span the wavelength range from 3.6 to 500 μm. There are 35,322 unique sources in the LMC and 7503 in the SMC. To be bright in the FIR, a source must be very dusty, and so the sources in the HERITAGE catalogs represent the dustiest populations of sources. The brightest HERITAGE sources are dominated by young stellar objects (YSOs), and the dimmest by background galaxies. We identify the sources most likely to be background galaxies by first considering their morphology (distant galaxies are point-like at the resolution of Herschel) and then comparing the flux distribution to that of the Herschel Astrophysical Terahertz Large Area Survey (ATLAS ) survey of galaxies. We find a total of 9745 background galaxy candidates in the LMC HERITAGE images and 5111 in the SMC images, in agreement with the number predicted by extrapolating from the ATLAS flux distribution. The majority of the Magellanic Cloud-residing sources are either very young, embedded forming stars or dusty clumps of the interstellar medium. Using the presence of 24 μm emission as a tracer of star formation, we identify 3518 YSO candidates in the LMC and 663 in the SMC. There are far fewer far-IR bright YSOs in the SMC than the LMC due to both the SMC's smaller size and its lower dust content. The YSO candidate lists may be contaminated at low flux levels by background galaxies, and so we differentiate between sources with a high ("probable") and moderate ("possible ") likelihood of being a YSO. There are 2493/425 probable YSO candidates in the LMC/SMC. Approximately 73% of the Herschel YSO candidates are newly identified in the LMC, and 35% in the SMC. We further identify a small population of dusty objects in the late stages of stellar evolution including extreme and post-asymptotic giant branch, planetary nebulae, and supernova remnants. These populations are identified by matching the HERITAGE catalogs to lists of previously identified objects in the literature. Approximately half of the LMC sources and one quarter of the SMC sources are too faint to obtain accurate ample FIR photometry and are unclassified.

Development tools for opportunistic pervasive computing

The goal of the POBICOS project is a platform that facilitates the development and deployment of pervasive computing applications destined for networked, cooperating objects. POBICOS object communities are heterogeneous in terms of the sensing, actuating, and computing resources contributed by each object. Moreover, it is assumed that an object community is formed without any master plan; for example, it may emerge as a by-product of acquiring everyday, POBICOS-enabled objects by a household. As a result, the target object community is, at least partially, unknown to the application programmer, and so a POBICOS application should be able to deliver its functionality on top of diverse object communities (we call this opportunistic computing). The POBICOS platform includes a middleware offering a programming model for opportunistic computing, as well as development and monitoring tools. This paper briefly describes the tools produced in the first phase of the project. Also, the stakeholders using these tools are identified, and a development process for both the middleware and applications is presented. © 2009 IEEE.

Tangible applications for regular objects:An end-user model for pervasive computing at home

This paper describes an end-user model for a domestic pervasive computing platform formed by regular home objects. The platform does not rely on pre-planned infrastructure; instead, it exploits objects that are already available in the home and exposes their joint sensing, actuating and computing capabilities to home automation applications. We advocate an incremental process of the platform formation and introduce tangible, object-like artifacts for representing important platform functions. One of those artifacts, the application pill, is a tiny object with a minimal user interface, used to carry the application, as well as to start and stop its execution and provide hints about its operational status. We also emphasize streamlining the user's interaction with the platform. The user engages any UI-capable object of his choice to configure applications, while applications issue notifications and alerts exploiting whichever available objects can be used for that purpose. Finally, the paper briefly describes an actual implementation of the presented end-user model. © (2010) by International Academy, Research, and Industry Association (IARIA).

A Significance-Driven Programming Framework for Energy-Constrained Approximate Computing

Approximate execution is a viable technique for energy-con\-strained environments, provided that applications have the mechanisms to produce outputs of the highest possible quality within the given energy budget.
We introduce a framework for energy-constrained execution with controlled and graceful quality loss. A simple programming model allows users to express the relative importance of computations for the quality of the end result, as well as minimum quality requirements. The significance-aware runtime system uses an application-specific analytical energy model to identify the degree of concurrency and approximation that maximizes quality while meeting user-specified energy constraints. Evaluation on a dual-socket 8-core server shows that the proposed
framework predicts the optimal configuration with high accuracy, enabling energy-constrained executions that result in significantly higher quality compared to loop perforation, a compiler approximation technique.

A Programming Model and Runtime System for Significance-Aware Energy-Efficient Computing.

We introduce a task-based programming model and runtime system that exploit the observation that not all parts of a program are equally significant for the accuracy of the end-result, in order to trade off the quality of program outputs for increased energy-efficiency. This is done in a structured and flexible way, allowing for easy exploitation of different points in the quality/energy space, without adversely affecting application performance. The runtime system can apply a number of different policies to decide whether it will execute less-significant tasks accurately or approximately.

The experimental evaluation indicates that our system can achieve an energy reduction of up to 83% compared with a fully accurate execution and up to 35% compared with an approximate version employing loop perforation. At the same time, our approach always results in graceful quality degradation.

Computing lower and upper expectations under epistemic independence

This paper investigates the computation of lower/upper expectations that must cohere with a collection of probabilistic assessments and a collection of judgements of epistemic independence. New algorithms, based on multilinear programming, are presented, both for independence among events and among random variables. Separation properties of graphical models are also investigated.

Pool Evolution: A Parallel Pattern for Evolutionary and Symbolic Computing

We introduce a new parallel pattern derived from a specific application domain and show how it turns out to have application beyond its domain of origin. The pool evolution pattern models the parallel evolution of a population subject to mutations and evolving in such a way that a given fitness function is optimized. The pattern has been demonstrated to be suitable for capturing and modeling the parallel patterns underpinning various evolutionary algorithms, as well as other parallel patterns typical of symbolic computation. In this paper we introduce the pattern, we discuss its implementation on modern multi/many core architectures and finally present experimental results obtained with FastFlow and Erlang implementations to assess its feasibility and scalability.

Approximate Computing with Unreliable Dynamic Memories

Embedded memories account for a large fraction of the overall silicon area and power consumption in modern SoC(s). While embedded memories are typically realized with SRAM, alternative solutions, such as embedded dynamic memories (eDRAM), can provide higher density and/or reduced power consumption. One major challenge that impedes the widespread adoption of eDRAM is that they require frequent refreshes potentially reducing the availability of the memory in periods of high activity and also consuming significant amount of power due to such frequent refreshes. Reducing the refresh rate while on one hand can reduce the power overhead, if not performed in a timely manner, can cause some cells to lose their content potentially resulting in memory errors. In this paper, we consider extending the refresh period of gain-cell based dynamic memories beyond the worst-case point of failure, assuming that the resulting errors can be tolerated when the use-cases are in the domain of inherently error-resilient applications. For example, we observe that for various data mining applications, a large number of memory failures can be accepted with tolerable imprecision in output quality. In particular, our results indicate that by allowing as many as 177 errors in a 16 kB memory, the maximum loss in output quality is 11%. We use this failure limit to study the impact of relaxing reliability constraints on memory availability and retention power for different technologies.

Expanded iron uta spectra - Probing the thermal stability limits in AGN clouds

The Fe unresolved transition arrays (UTAs) produce prominent features in the 15-17 Å wavelength range in the spectra of active galactic nuclei (AGNs). Here, we present new calculations of the energies and oscillator strengths of inner-shell lines from Fe XIV, Fe XV, and Fe XVI. These are crucial ions since they are dominant at inflection points in the gas thermal stability curve, and UTA excitation followed by autoionization is an important ionization mechanism for these species. We incorporate these, and data reported in previous papers, into the plasma simulation code Cloudy. This updated physics is subsequently employed to reconsider the thermally stable phases in absorbing media in AGNs. We show how the absorption profile of the Fe XIV UTA depends on density, due to the changing populations of levels within the ground configuration. © 2013. The American Astronomical Society. All rights reserved.

Large- and small-scale structure of the intermediate- and high-velocity clouds towards the LMC and SMC.

We employ Ca II K and Na I D interstellar absorption-line spectroscopy of early-type stars in the Large and Small Magellanic Clouds (LMC, SMC) to investigate the large- and small-scale structure in foreground intermediate- and high-velocity clouds (I/HVCs). Data include FLAMES-GIRAFFE Ca II K observations of 403 stars in four open clusters, plus FEROS or UVES spectra of 156 stars in the LMC and SMC. The FLAMES observations are amongst the most extensive probes to date of Ca II structures on ∼20 arcsec scales in Magellanic I/HVCs. From the FLAMES data within a 0 ∘.∘.∘.5 field of view, the Ca II K equivalent width in the I/HVC components towards three clusters varies by factors of ≥10. There are no detections of molecular gas in absorption at intermediate or high velocities, although molecular absorption is present at LMC and Galactic velocities towards some sightlines. The FEROS/UVES data show Ca II K I/HVC absorption in ∼60 per cent of sightlines. The range in the Ca II/Na I ratio in I/HVCs is from –0.45 to +1.5 dex, similar to previous measurements for I/HVCs. In 10 sightlines we find Ca II/O I ratios in I/HVC gas ranging from 0.2 to 1.5 dex below the solar value, indicating either dust or ionization effects. In nine sightlines I/HVC gas is detected in both H I and Ca II at similar velocities, implying that the two elements form part of the same structure.

Are Computer Scientists Geeks? Gender Differences In Attitudes And Experiences Related To Computing Among Secondary Education Students In Northern Ireland.

The worldwide scarcity of women studying or employed in ICT, or in computing related disciplines, continues to be a topic of concern for industry, the education sector and governments. Within Europe while females make up 46% of the workforce only 17% of IT staff are female. A similar gender divide trend is repeated worldwide, with top technology employers in Silicon Valley, including Facebook, Google, Twitter and Apple reporting that only 30% of the workforce is female (Larson 2014). Previous research into this gender divide suggests that young women in Secondary Education display a more negative attitude towards computing than their male counterparts. It would appear that the negative female perception of computing has led to representatively low numbers of women studying ICT at a tertiary level and consequently an under representation of females within the ICT industry. The aim of this study is to 1) establish a baseline understanding of the attitudes and perceptions of Secondary Education pupils in regard to computing and 2) statistically establish if young females in Secondary Education really do have a more negative attitude towards computing.