31 resultados para Magellanic Clouds


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Despite the compelling case for moving towards cloud computing, the upstream oil & gas industry faces several technical challenges—most notably, a pronounced emphasis on data security, a reliance on extremely large data sets, and significant legacy investments in information technology infrastructure—that make a full migration to the public cloud difficult at present. Private and hybrid cloud solutions have consequently emerged within the industry to yield as much benefit from cloud-based technologies as possible while working within these constraints. This paper argues, however, that the move to private and hybrid clouds will very likely prove only to be a temporary stepping stone in the industry's technological evolution. By presenting evidence from other market sectors that have faced similar challenges in their journey to the cloud, we propose that enabling technologies and conditions will probably fall into place in a way that makes the public cloud a far more attractive option for the upstream oil & gas industry in the years ahead. The paper concludes with a discussion about the implications of this projected shift towards the public cloud, and calls for more of the industry's services to be offered through cloud-based “apps.”

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This paper presents a mapping and navigation system for a mobile robot, which uses vision as its sole sensor modality. The system enables the robot to navigate autonomously, plan paths and avoid obstacles using a vision based topometric map of its environment. The map consists of a globally-consistent pose-graph with a local 3D point cloud attached to each of its nodes. These point clouds are used for direction independent loop closure and to dynamically generate 2D metric maps for locally optimal path planning. Using this locally semi-continuous metric space, the robot performs shortest path planning instead of following the nodes of the graph --- as is done with most other vision-only navigation approaches. The system exploits the local accuracy of visual odometry in creating local metric maps, and uses pose graph SLAM, visual appearance-based place recognition and point clouds registration to create the topometric map. The ability of the framework to sustain vision-only navigation is validated experimentally, and the system is provided as open-source software.

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This paper presents the prototype of an information retrieval system for medical records that utilises visualisation techniques, namely word clouds and timelines. The system simplifies and assists information seeking tasks within the medical domain. Access to patient medical information can be time consuming as it requires practitioners to review a large number of electronic medical records to find relevant information. Presenting a summary of the content of a medical document by means of a word cloud may permit information seekers to decide upon the relevance of a document to their information need in a simple and time effective manner. We extend this intuition, by mapping word clouds of electronic medical records onto a timeline, to provide temporal information to the user. This allows exploring word clouds in the context of a patient’s medical history. To enhance the presentation of word clouds, we also provide the means for calculating aggregations and differences between patient’s word clouds.

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The ion (C6CH2)(.-) is formed in the gas phase by the process -C=C-C=C-C=CH2OEt --> (C6CH2)(.-) + EtO., and charge stripping of the product radical anion yields the carbenoid neutral C6CH2; this can be either a singlet (the ground state), which is best represented as the carbene :C=C=C=C=C=C=CH2, or a triplet; the adiabatic electron affinity and the dipole moment of the carbenoid neutral are calculated to be 2.82 eV and 7.33 D respectively.

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We describe a novel method of fabricating atom chips that are well suited to the production and manipulation of atomic Bose–Einstein condensates. Our chip was created using a silver foil and simple micro-cutting techniques without the need for photolithography. It can sustain larger currents than conventional chips, and is compatible with the patterning of complex trapping potentials. A near pure Bose–Einstein condensate of 4 × 104 87Rb atoms has been created in a magnetic microtrap formed by currents through wires on the chip. We have observed the fragmentation of atom clouds in close proximity to the silver conductors. The fragmentation has different characteristic features to those seen with copper conductors.

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The last few years have brought an increasing interest in the chemistry of rite interstellar and circumstellar environs. Many of the molecular species discovered in remote galactic regions have been dubbed 'non-terrestrial' because of their unique structures (Thaddeus et al, 1993). These findings have provided a challenge to chemists in many differing fields to attempt to generate these unusual species in the laboratory of particular recent interest have been the unsaturated hydrocarbon families, CnH and CnH2, which have been pursued by a number of diverse methodologies. A wine range of heterocumulenes, including CnO, HCnO, CnN, HCnN, CnS, HCnS, CnSi and HCnSi have also provided intriguing targets for laboratory experiments. Strictly the term cumulene refers to a class of compounds that possess a series of adjacent double bonds, with allene representing the simplest example (H2C=C=CH2). However for many of the non-terrestrial molecules presented here, the carbon chain cannot be described in terms of a single simple valence structure, and so we use the terms cumulene and heterocumulene in a more general sense: to describe molecular species that contain an unsaturated polycarbon chain. Mass spectrometry has proved an invaluable tool in the quest for interstellar cumulenes and heterocumulenes in the laboratory it has the ability in its many forms, to (i) generate charged analogs of these species in the gas phase, (ii) probe their connectivity, ion chemistry, and thermochemistry, and (iii) in some cases, elucidate the neutrals themselves. Here, we will discuss the progress of these studies to this time. (C) 1999 John Wiley & Sons, Inc.

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Theoretical calculations of the C3HO potential surface at the CCSD(T)/aug-cc-pVDu/B3LYP/6-31G* level indicate that the three radicals HCCCO, CCCHO, and (cyclo-C3H)=O are stable, with HCCCO being the most stable of the three. A fourth isomer, CCHCO, is unstable with respect to cyclization to (cyclo-C3H)=O. Two isomers have been prepared by neutralization of charged precursors, formed as follows: (i) HCCCO, by HC drop C-C(O)-O+(H)(Me) --> HC3O+ + MeOH, and (ii) C2CHO, by (a) Me3SiC drop C-CHO + HO- --> C- drop C-CHO + Me3SiOH and (b) C- drop C-CH(OH)-C drop CH --> C- drop C-CHO + C2H2. A comparison of the CR and -NR+ spectra of -C2CHO indicate that C2CHO is (partially) rearranging to an isomer that shows significant formation of CO.(+) in the -NR+ spectrum of the anion. Ab initio calculations indicate that HCCCO is the product of the isomerism and that a proportion of these isomerized neutrals dissociate to CO and C2H. The neutral HCCCO may be formed by (i) synchronous rearrangement of C2CHO and/or (ii) stepwise rearrangement of C2CHO through (cyclo-C3H)=O. The second of these processes should have the higher rate, as it has the lower barrier in the rate-determining step and the higher Arrhenius pre-exponential A factor.

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The ability to build high-fidelity 3D representations of the environment from sensor data is critical for autonomous robots. Multi-sensor data fusion allows for more complete and accurate representations. Furthermore, using distinct sensing modalities (i.e. sensors using a different physical process and/or operating at different electromagnetic frequencies) usually leads to more reliable perception, especially in challenging environments, as modalities may complement each other. However, they may react differently to certain materials or environmental conditions, leading to catastrophic fusion. In this paper, we propose a new method to reliably fuse data from multiple sensing modalities, including in situations where they detect different targets. We first compute distinct continuous surface representations for each sensing modality, with uncertainty, using Gaussian Process Implicit Surfaces (GPIS). Second, we perform a local consistency test between these representations, to separate consistent data (i.e. data corresponding to the detection of the same target by the sensors) from inconsistent data. The consistent data can then be fused together, using another GPIS process, and the rest of the data can be combined as appropriate. The approach is first validated using synthetic data. We then demonstrate its benefit using a mobile robot, equipped with a laser scanner and a radar, which operates in an outdoor environment in the presence of large clouds of airborne dust and smoke.

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This paper describes the results of experiments made in the vicinity of EHV overhead lines to investigate sources of clouds of charged particles using simultaneously-recording arrays of electric field meters to measure direct electric fields produced under ion clouds. E-field measurements, made at one metre above ground level, are correlated with wind speed and direction, and with measurements from ionisation counters and audible corona effects to identify possible positions of sources of corona on adjacent power lines. Measurements made in dry conditions on EHV lines in flat remote locations with no adjacent buildings or large vegetation indicate the presence of discrete ion sources associated with high stress points on some types of line hardware such as connectors and conductor spacers. Faulty line components such as insulators and line fittings are also found to be a possible source of ion clouds.

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A travel article about a visit to Klemtu and the Great Bear Rainforest, British Columbia. A LOW-TIDE mark of rocks coated in orange seaweed borders the islands of the Great Bear Rainforest. Our seaplane stays low under the clouds. As we approach the village of Klemtu, turning into Finlayson Channel, the trees beneath us thicken against the shoreline like a concert crowd being pushed from behind. There's no gap between the dark, still sea and the front row of soaring conifers, seemingly no entry point into one of the last great wilderness areas.

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Grateful Fateful Sunshine Rain is a permanent public artwork commissioned by Aria Property Group through a competitive process for the Austin apartment building in South Brisbane. Artist Statement: Residents of Brisbane have a complex relationship with weather. As the capital of the Sunshine State, weather is an integral part of the city’s cultural identity. Weather deeply affects the mood of the city – from the excitement of scantily clad partygoers on balmy December evenings and late February’s lethargy, to the deepening anxiety that emerges after 100 days of rain (or more commonly, 100 days without rain). With a brief nod to the city’s – now decommissioned – iconic MCL weather beacon, Grateful Fateful Sunshine Rain taps into this aspect of Brisbane’s psyche with poetic, illuminated visualisations of real-time weather forecasts issued by the Bureau of Meteorology. Each evening, the artwork downloads tomorrow’s forecast from the Bureau of Meteorology website. Data including, current local temperature, humidity, wind speed & direction, precipitation (rain, hail etc), are used to generate a lighting display that conveys how tomorrow will feel. The artwork’s background colour indicates the expected temperature – from cold blues through mild pastel pinks and blues to bright hot oranges and reds. White fluffy clouds roll across the artwork if cloud is predicted. The density of these clouds indicates the level of cover whilst movement indicates expected wind speed and direction. If rain is predicted, sparkles of white light will appear on top of whichever background colour is chosen for the next day’s temperature. Sparkles appear constantly before wet, drizzly days, and intermittently if scattered showers are predicted. Intermittent, but more intense sparkles appear before rain storms or thunderstorms. Research Contribution: The work has made contributions to the field in the way it rethinks approaches to the conceptualization, design and realization of illuminated urban media. This has led to new theorizations of urban media, which consider light and illumination can be used to convey meaningful data. The research has produced new methods for controlling illumination systems using tools and techniques typically employed in computation arts. It has also develop methods and processes for the design and production of illuminated urban media architectures that are connected to real time data sources, and do which not follow the assumed logics of screen based media and displays.

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Using cameras onboard a robot for detecting a coloured stationary target outdoors is a difficult task. Apart from the complexity of separating the target from the background scenery over different ranges, there are also the inconsistencies with direct and reflected illumination from the sun,clouds, moving and stationary objects. They can vary both the illumination on the target and its colour as perceived by the camera. In this paper, we analyse the effect of environment conditions, range to target, camera settings and image processing on the reported colours of various targets. The analysis indicates the colour space and camera configuration that provide the most consistent colour values over varying environment conditions and ranges. This information is used to develop a detection system that provides range and bearing to detected targets. The system is evaluated over various lighting conditions from bright sunlight, shadows and overcast days and demonstrates robust performance. The accuracy of the system is compared against a laser beacon detector with preliminary results indicating it to be a valuable asset for long-range coloured target detection.

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The climate in the Arctic is changing faster than anywhere else on earth. Poorly understood feedback processes relating to Arctic clouds and aerosol–cloud interactions contribute to a poor understanding of the present changes in the Arctic climate system, and also to a large spread in projections of future climate in the Arctic. The problem is exacerbated by the paucity of research-quality observations in the central Arctic. Improved formulations in climate models require such observations, which can only come from measurements in situ in this difficult-to-reach region with logistically demanding environmental conditions. The Arctic Summer Cloud Ocean Study (ASCOS) was the most extensive central Arctic Ocean expedition with an atmospheric focus during the International Polar Year (IPY) 2007–2008. ASCOS focused on the study of the formation and life cycle of low-level Arctic clouds. ASCOS departed from Longyearbyen on Svalbard on 2 August and returned on 9 September 2008. In transit into and out of the pack ice, four short research stations were undertaken in the Fram Strait: two in open water and two in the marginal ice zone. After traversing the pack ice northward, an ice camp was set up on 12 August at 87°21' N, 01°29' W and remained in operation through 1 September, drifting with the ice. During this time, extensive measurements were taken of atmospheric gas and particle chemistry and physics, mesoscale and boundary-layer meteorology, marine biology and chemistry, and upper ocean physics. ASCOS provides a unique interdisciplinary data set for development and testing of new hypotheses on cloud processes, their interactions with the sea ice and ocean and associated physical, chemical, and biological processes and interactions. For example, the first-ever quantitative observation of bubbles in Arctic leads, combined with the unique discovery of marine organic material, polymer gels with an origin in the ocean, inside cloud droplets suggests the possibility of primary marine organically derived cloud condensation nuclei in Arctic stratocumulus clouds. Direct observations of surface fluxes of aerosols could, however, not explain observed variability in aerosol concentrations, and the balance between local and remote aerosols sources remains open. Lack of cloud condensation nuclei (CCN) was at times a controlling factor in low-level cloud formation, and hence for the impact of clouds on the surface energy budget. ASCOS provided detailed measurements of the surface energy balance from late summer melt into the initial autumn freeze-up, and documented the effects of clouds and storms on the surface energy balance during this transition. In addition to such process-level studies, the unique, independent ASCOS data set can and is being used for validation of satellite retrievals, operational models, and reanalysis data sets.

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Adopting a multi-theoretical approach, I examine external auditors’ perceptions of the reasons why organizations do or do not adopt cloud computing. I interview forensic accountants and IT experts about the adoption, acceptance, institutional motives, and risks of cloud computing. Although the medium to large accounting firms where the external auditors worked almost exclusively used private clouds, both private and public cloud services were gaining a foothold among many of their clients. Despite the advantages of cloud computing, data confidentiality and the involvement of foreign jurisdictions remain a concern, particularly if the data are moved outside Australia. Additionally, some organizations seem to understand neither the technology itself nor their own requirements, which may lead to poorly negotiated contracts and service agreements. To minimize the risks associated with cloud computing, many organizations turn to hybrid solutions or private clouds that include national or dedicated data centers. To the best of my knowledge, this is the first empirical study that reports on cloud computing adoption from the perspectives of external auditors.

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This technical report describes a Light Detection and Ranging (LiDAR) augmented optimal path planning at low level flight methodology for remote sensing and sampling Unmanned Aerial Vehicles (UAV). The UAV is used to perform remote air sampling and data acquisition from a network of sensors on the ground. The data that contains information on the terrain is in the form of a 3D point clouds maps is processed by the algorithms to find an optimal path. The results show that the method and algorithm are able to use the LiDAR data to avoid obstacles when planning a path from a start to a target point. The report compares the performance of the method as the resolution of the LIDAR map is increased and when a Digital Elevation Model (DEM) is included. From a practical point of view, the optimal path plan is loaded and works seemingly with the UAV ground station and also shows the UAV ground station software augmented with more accurate LIDAR data.