999 resultados para Cloud discharge


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Post-discharge surgical wound infection surveillance is an important part of many infection control programs. It is frequently undertaken by patient self-assessment, prompted either by a telephone or postal questionnaire. To assess the reliability of this method, 290 patients were followed for six weeks postoperatively. Their wounds were photographed and also covertly assessed for signs of infection by two experienced infection control nurses (ICNs). Patients also responded to a postal questionnaire seeking evidence of infection at both week four and week six post-surgery. Correlation between the patient's assessment of their wound and the ICNs diagnosis was poor (r=0.37) with a low positive predictive value (28.7%), although negative predictive value was high (98.2%). Assessment of photos for signs of infection by two experienced clinicians also correlated poorly with the ICNs diagnosis of infection (r=0.54). The patient's recall of prescription of an antibiotic by their general practitioner (GP) for wound infection during the postoperative period correlated best with the ICNs diagnosis (r=0.76). This latter measure, particularly when confirmed by the GP in those patients reporting an infection, appears to provide the most valid and resource efficient marker of post-discharge surgical wound infection.

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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 (IT) 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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With the widespread application of healthcare Information and Communication Technology (ICT), constructing a stable and sustainable data sharing circumstance has attracted rapidly growing attention in both academic research area and healthcare industry. Cloud computing is one of long dreamed visions of Healthcare Cloud (HC), which matches the need of healthcare information sharing directly to various health providers over the Internet, regardless of their location and the amount of data. In this paper, we discuss important research tool related to health information sharing and integration in HC and investigate the arising challenges and issues. We describe many potential solutions to provide more opportunities to implement EHR cloud. As well, we introduce the development of a HC related collaborative healthcare research example, thus illustrating the prospective of applying Cloud Computing in the health information science research.

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The residence time distribution (RTD) is a crucial parameter when treating engine exhaust emissions with a Dielectric Barrier Discharge (DBD) reactor. In this paper, the residence time of such a reactor is investigated using a finite element based software: COMSOL Multiphysics 4.3. Non-thermal plasma (NTP) discharge is being introduced as a promising method for pollutant emission reduction. DBD is one of the most advantageous of NTP technologies. In a two cylinder co-axial DBD reactor, tubes are placed between two electrodes and flow passes through the annuals between these barrier tubes. If the mean residence time increases in a DBD reactor, there will be a corresponding increase in reaction time and consequently, the pollutant removal efficiency can increase. However, pollutant formation can occur during increased mean residence time and so the proportion of fluid that may remain for periods significantly longer than the mean residence time is of great importance. In this study, first, the residence time distribution is calculated based on the standard reactor used by the authors for ultrafine particle (10-500 nm) removal. Then, different geometrics and various inlet velocities are considered. Finally, for selected cases, some roughness elements added inside the reactor and the residence time is calculated. These results will form the basis for a COMSOL plasma and CFD module investigation.

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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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Background: Decreased ability to perform Activities of Daily Living (ADLs) during hospitalisation has negative consequences for patients and health service delivery. Objective: To develop an Index to stratify patients at lower and higher risk of a significant decline in ability to perform ADLs at discharge. Design: Prospective two cohort study comprising a derivation (n=389; mean age 82.3 years; SD� 7.1) and a validation cohort (n=153; mean age 81.5 years; SD� 6.1). Patients and setting: General medical patients aged = 70 years admitted to three university-affiliated acute care hospitals in Brisbane, Australia. Measurement and main results: The short ADL Scale was used to identify a significant decline in ability to perform ADLs from premorbid to discharge. In the derivation cohort, 77 patients (19.8%) experienced a significant decline. Four significant factors were identified for patients independent at baseline: 'requiring moderate assistance to being totally dependent on others with bathing'; 'difficulty understanding others (frequently or all the time)'; 'requiring moderate assistance to being totally dependent on others with performing housework'; a 'history of experiencing at least one fall in the previous 90 days prior to hospital admission' in addition to 'independent at baseline', which was protective against decline at discharge. 'Difficulty understanding others (frequently or all the time)' and 'requiring moderate assistance to being totally dependent on others with performing housework' were also predictors for patients dependent in ADLs at baseline. Sensitivity, specificity, Positive Predictive Value (PPV), and Negative Predictive Value (NPV) of the DADLD dichotomised risk scores were: 83.1% (95% CI 72.8; 90.7); 60.5% (95% CI 54.8; 65.9); 34.2% (95% CI 27.5; 41.5); 93.5% (95% CI 89.2; 96.5). In the validation cohort, 47 patients (30.7%) experienced a significant decline. Sensitivity, specificity, PPV and NPV of the DADLD were: 78.7% (95% CI 64.3; 89.3); 69.8% (95% CI 60.1, 78.3); 53.6% (95% CI 41.2; 65.7); 88.1% (95% CI 79.2; 94.1). Conclusions: The DADLD Index is a useful tool for identifying patients at higher risk of decline in ability to perform ADLs at discharge.

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Model calculations, which include the effects of turbulence during subsequent solar nebula evolution after the collapse of a cool interstellar cloud, can reconcile some of the apparent differences between physical parameters obtained from theory and the cosmochemical record. Two important aspects of turbulence in a protoplanetary cloud include the growth and transport of solid grains. While the physical effects of the process can be calculated and compared with the probable remains of the nebula formulation period, the more subtle effects on primitive grains and their survival in the cosmochemical record cannot be readily evaluated. The environment offered by the Space Station (or Space Shuttle) experimental facility can provide the vacuum and low gravity conditions for sufficiently long time periods required for experimental verification of these cosmochemical models.

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Normally, vehicles queued at an intersection reach maximum flow rate after the fourth vehicle and results in a start-up lost time. This research demonstrated that the Enlarged Stopping Distance (ESD) concept could assist in reducing the start-up time and therefore increase traffic flow capacity at signalised intersections. In essence ESD gives sufficient space for a queuing vehicle to accelerate simultaneously without having to wait for the front vehicle to depart, hence reducing start-up lost time. In practice, the ESD concept would be most effective when enlarged stopping distance between the first and second vehicle allowing faster clearance of the intersection.

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"The music industry is going through a period of immense change brought about in part by the digital revolution. What is the role of music in the age of computers and the internet? How has the music industry been transformed by the economic and technological upheavals of recent years, and how is it likely to change in the future? This is the first major study of the music industry in the new millennium. Wikström provides an international overview of the music industry and its future prospects in the world of global entertainment. He illuminates the workings of the music industry, and captures the dynamics at work in the production of musical culture between the transnational media conglomerates, the independent music companies and the public." -- back cover Table of Contents Introduction: Music in the Cloud Chapter 1: A Copyright Industry. Chapter 2: Inside the Music Industry Chapter 3: Music and the Media Chapter 4: Making Music - An Industrial or Creative Process Chapter 5: The Social and Creative Music Fan Chapter 6: Future Sounds

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Groundwater flow models are usually characterized as being either transient flow models or steady state flow models. Given that steady state groundwater flow conditions arise as a long time asymptotic limit of a particular transient response, it is natural for us to seek a finite estimate of the amount of time required for a particular transient flow problem to effectively reach steady state. Here, we introduce the concept of mean action time (MAT) to address a fundamental question: How long does it take for a groundwater recharge process or discharge processes to effectively reach steady state? This concept relies on identifying a cumulative distribution function, $F(t;x)$, which varies from $F(0;x)=0$ to $F(t;x) \to \infty$ as $t\to \infty$, thereby providing us with a measurement of the progress of the system towards steady state. The MAT corresponds to the mean of the associated probability density function $f(t;x) = \dfrac{dF}{dt}$, and we demonstrate that this framework provides useful analytical insight by explicitly showing how the MAT depends on the parameters in the model and the geometry of the problem. Additional theoretical results relating to the variance of $f(t;x)$, known as the variance of action time (VAT), are also presented. To test our theoretical predictions we include measurements from a laboratory–scale experiment describing flow through a homogeneous porous medium. The laboratory data confirms that the theoretical MAT predictions are in good agreement with measurements from the physical model.

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The main theme of this thesis is to allow the users of cloud services to outsource their data without the need to trust the cloud provider. The method is based on combining existing proof-of-storage schemes with distance-bounding protocols. Specifically, cloud customers will be able to verify the confidentiality, integrity, availability, fairness (or mutual non-repudiation), data freshness, geographic assurance and replication of their stored data directly, without having to rely on the word of the cloud provider.