This paper presents an event-driven cloud-based serverless architecture for a remote patient monitoring system. The architecture is designed to be scalable, resilient, and cost-effective, and leverages managed cloud s...
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ISBN:
(数字)9798331533366
ISBN:
(纸本)9798331533373
This paper presents an event-driven cloud-based serverless architecture for a remote patient monitoring system. The architecture is designed to be scalable, resilient, and cost-effective, and leverages managed cloud services to handle load variations and service faults. To evaluate the architecture, we conducted comprehensive capacity, scalability, and resilience tests. The test results show that the architecture can meet the performance, scalability, and reliability requirements of a remote patient monitoring system. Additionally, a detailed analysis of operational costs in the cloud confirms the cost-effectiveness of the solution and highlights practical opportunities for improvements.
The recent integration of visual capabilities into Large Language Models (LLMs) has the potential to play a pivotal role in science and technology education, where visual elements such as diagrams, charts, and tables ...
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Microservice application developers try to mitigate the impact of partial outages typically by implementing service-to-service interactions that use well-known resiliency patterns, such as Retry, Fail Fast, and Circui...
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ISBN:
(数字)9781728146591
ISBN:
(纸本)9781728146607
Microservice application developers try to mitigate the impact of partial outages typically by implementing service-to-service interactions that use well-known resiliency patterns, such as Retry, Fail Fast, and Circuit Breaker. However, those resiliency patterns-as well as their available open-source implementations-are often documented informally, leaving it up to application developers to figure out when and how to use those patterns in the context of a particular microservice application. In this paper, we take a first step towards improving on this situation by introducing a model checking-based approach in which we use the PRISM probabilistic model checker to analyze the behavior of the Retry and Circuit Breaker resiliency patterns as continuous-time Markov chains (CTMC). This approach has enabled us to quantify the impact of applying each resiliency pattern on multiple quality attributes, as well as to determine how to best tune their parameters to deal with varying service availability conditions, in the context of a simple client-service interaction scenario.
A self-adaptive system can dynamically monitor and adapt its behavior to preserve or enhance its quality attributes under uncertain operating conditions. This article identifies key challenges for the development of m...
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Background: The three-item Sexual Distress Scale (SDS-3) has been frequently used to assess distress related to sexuality in public health surveys and research on sexual wellbeing. However, its psychometric properties...
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Background: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalen...
Background: Experimental and epidemiological studies indicate an association between exposure to particulate matter (PM) air pollution and increased risk of type 2 diabetes. In view of the high and increasing prevalence of diabetes, we aimed to quantify the burden of type 2 diabetes attributable to PM2·5 originating from ambient and household air pollution. Methods: We systematically compiled all relevant cohort and case-control studies assessing the effect of exposure to household and ambient fine particulate matter (PM2·5) air pollution on type 2 diabetes incidence and mortality. We derived an exposure–response curve from the extracted relative risk estimates using the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. The estimated curve was linked to ambient and household PM2·5 exposures from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019, and estimates of the attributable burden (population attributable fractions and rates per 100 000 population of deaths and disability-adjusted life-years) for 204 countries from 1990 to 2019 were calculated. We also assessed the role of changes in exposure, population size, age, and type 2 diabetes incidence in the observed trend in PM2·5-attributable type 2 diabetes burden. All estimates are presented with 95% uncertainty intervals. Findings: In 2019, approximately a fifth of the global burden of type 2 diabetes was attributable to PM2·5 exposure, with an estimated 3·78 (95% uncertainty interval 2·68–4·83) deaths per 100 000 population and 167 (117–223) disability-adjusted life-years (DALYs) per 100 000 population. Approximately 13·4% (9·49–17·5) of deaths and 13·6% (9·73–17·9) of DALYs due to type 2 diabetes were contributed by ambient PM2·5, and 6·50% (4·22–9·53) of deaths and 5·92% (3·81–8·64) of DALYs by household air pollution. High burdens, in terms of numbers as well as rates, were estimated in Asia, sub-Saharan Africa, and South Am
Hospital El Salvador: a novel paradigm of intensive care in response to COVID-19 in central America. Lancet Glob Health 2021;9: e241?42?In this Comment, the conflict of interest statement should have included the foll...
Hospital El Salvador: a novel paradigm of intensive care in response to COVID-19 in central America. Lancet Glob Health 2021;9: e241?42?In this Comment, the conflict of interest statement should have included the following: ?By virtue of their roles within a public hospital or the Ministry of Health, MB, LC, WH, and XS are government employees. The findings and conclusions in the Comment are only those of the authors.? This correction has been made as of Feb 26, 2021.
Background: High-resolution estimates of HIV burden across space and time provide an important tool for tracking and monitoring the progress of prevention and control efforts and assist with improving the precision an...
Background: High-resolution estimates of HIV burden across space and time provide an important tool for tracking and monitoring the progress of prevention and control efforts and assist with improving the precision and efficiency of targeting efforts. We aimed to assess HIV incidence and HIV mortality for all second-level administrative units across sub-Saharan Africa. Methods: In this modelling study, we developed a framework that used the geographically specific HIV prevalence data collected in seroprevalence surveys and antenatal care clinics to train a model that estimates HIV incidence and mortality among individuals aged 15–49 years. We used a model-based geostatistical framework to estimate HIV prevalence at the second administrative level in 44 countries in sub-Saharan Africa for 2000–18 and sought data on the number of individuals on antiretroviral therapy (ART) by second-level administrative unit. We then modified the Estimation and Projection Package (EPP) to use these HIV prevalence and treatment estimates to estimate HIV incidence and mortality by second-level administrative unit. Findings: The estimates suggest substantial variation in HIV incidence and mortality rates both between and within countries in sub-Saharan Africa, with 15 countries having a ten-times or greater difference in estimated HIV incidence between the second-level administrative units with the lowest and highest estimated incidence levels. Across all 44 countries in 2018, HIV incidence ranged from 2·8 (95% uncertainty interval 2·1–3·8) in Mauritania to 1585·9 (1369·4–1824·8) cases per 100 000 people in Lesotho and HIV mortality ranged from 0·8 (0·7–0·9) in Mauritania to 676·5 (513·6–888·0) deaths per 100 000 people in Lesotho. Variation in both incidence and mortality was substantially greater at the subnational level than at the national level and the highest estimated rates were accordingly higher. Among second-level administrative units, Guijá District, Gaza Province, Mozambique,
In this paper we address the task of hierarchical bird species identification from audio recordings. We evaluate three types of approaches to deal with hierarchical classification problems: the flat classification app...
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ISBN:
(纸本)9781479906505
In this paper we address the task of hierarchical bird species identification from audio recordings. We evaluate three types of approaches to deal with hierarchical classification problems: the flat classification approach, the local-model per parent node classifier approach and the global-model hierarchical-classification approach. For the flat and local-model classification approach we employ the classic Naive Bayes algorithm. For the global-model approach we use the Global Model Naive Bayes (GMNB) algorithm. As in the classical Naive Bayes, the algorithm computes prior probabilities and likelihoods, but these computations take into account the hierarchical classification scenario: it assumes that any example which belongs to a given class will also belong to all its ancestor classes. In the current application, the employed class hierarchy is the standard scientific taxonomy of birds used in Biology. In order to deal with the bird songs we obtain features by computing several acoustic quantities from intervals of the audio signal. We conduct three experiments in order to compare the three different approaches to the hierarchical bird species identification problem. Our experimental results show that the use of the GMNB hierarchical classification algorithm outperforms both the flat and local-model approaches (Using the Hierarchical F-measure metric);hence the use of a global-model approach (such as the GMNB) can be a feasible way to improve the classification performance for problems with a large number of classes.
Eliciting and re-using knowledge within an organization requires a very structured communication process among its employees in order to avoid misunderstanding and confusion. The transfer of knowledge among actors can...
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