888 resultados para Grid computing environment
Resumo:
Internet of Things systems are pervasive systems evolved from cyber-physical to large-scale systems. Due to the number of technologies involved, software development involves several integration challenges. Among them, the ones preventing proper integration are those related to the system heterogeneity, and thus addressing interoperability issues. From a software engineering perspective, developers mostly experience the lack of interoperability in the two phases of software development: programming and deployment. On the one hand, modern software tends to be distributed in several components, each adopting its most-appropriate technology stack, pushing programmers to code in a protocol- and data-agnostic way. On the other hand, each software component should run in the most appropriate execution environment and, as a result, system architects strive to automate the deployment in distributed infrastructures. This dissertation aims to improve the development process by introducing proper tools to handle certain aspects of the system heterogeneity. Our effort focuses on three of these aspects and, for each one of those, we propose a tool addressing the underlying challenge. The first tool aims to handle heterogeneity at the transport and application protocol level, the second to manage different data formats, while the third to obtain optimal deployment. To realize the tools, we adopted a linguistic approach, i.e.\ we provided specific linguistic abstractions that help developers to increase the expressive power of the programming language they use, writing better solutions in more straightforward ways. To validate the approach, we implemented use cases to show that the tools can be used in practice and that they help to achieve the expected level of interoperability. In conclusion, to move a step towards the realization of an integrated Internet of Things ecosystem, we target programmers and architects and propose them to use the presented tools to ease the software development process.
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Early definitions of Smart Building focused almost entirely on the technology aspect and did not suggest user interaction at all. Indeed, today we would attribute it more to the concept of the automated building. In this sense, control of comfort conditions inside buildings is a problem that is being well investigated, since it has a direct effect on users’ productivity and an indirect effect on energy saving. Therefore, from the users’ perspective, a typical environment can be considered comfortable, if it’s capable of providing adequate thermal comfort, visual comfort and indoor air quality conditions and acoustic comfort. In the last years, the scientific community has dealt with many challenges, especially from a technological point of view. For instance, smart sensing devices, the internet, and communication technologies have enabled a new paradigm called Edge computing that brings computation and data storage closer to the location where it is needed, to improve response times and save bandwidth. This has allowed us to improve services, sustainability and decision making. Many solutions have been implemented such as smart classrooms, controlling the thermal condition of the building, monitoring HVAC data for energy-efficient of the campus and so forth. Though these projects provide to the realization of smart campus, a framework for smart campus is yet to be determined. These new technologies have also introduced new research challenges: within this thesis work, some of the principal open challenges will be faced, proposing a new conceptual framework, technologies and tools to move forward the actual implementation of smart campuses. Keeping in mind, several problems known in the literature have been investigated: the occupancy detection, noise monitoring for acoustic comfort, context awareness inside the building, wayfinding indoor, strategic deployment for air quality and books preserving.
Resumo:
Since the end of the long winter of virtual reality (VR) at the beginning of the 2010 decade, many improvements have been made in terms of hardware technologies and software platforms performances and costs. Many expect such trend will continue, pushing the penetration rate of virtual reality headsets to skyrocket at some point in the future, just as mobile platforms did before. In the meantime, virtual reality is slowly transitioning from a specialized laboratory-only technology, to a consumer electronics appliance, opening interesting opportunities and challenges. In this transition, two interesting research questions amount to how 2D-based content and applications may benefit (or be hurt) by the adoption of 3D-based immersive environments and to how to proficiently support such integration. Acknowledging the relevance of the former, we here consider the latter question, focusing our attention on the diversified family of PC-based simulation tools and platforms. VR-based visualization is, in fact, widely understood and appreciated in the simulation arena, but mainly confined to high performance computing laboratories. Our contribution here aims at characterizing the simulation tools which could benefit from immersive interfaces, along with a general framework and a preliminary implementation which may be put to good use to support their transition from uniquely 2D to blended 2D/3D environments.
Resumo:
Modern scientific discoveries are driven by an unsatisfiable demand for computational resources. High-Performance Computing (HPC) systems are an aggregation of computing power to deliver considerably higher performance than one typical desktop computer can provide, to solve large problems in science, engineering, or business. An HPC room in the datacenter is a complex controlled environment that hosts thousands of computing nodes that consume electrical power in the range of megawatts, which gets completely transformed into heat. Although a datacenter contains sophisticated cooling systems, our studies indicate quantitative evidence of thermal bottlenecks in real-life production workload, showing the presence of significant spatial and temporal thermal and power heterogeneity. Therefore minor thermal issues/anomalies can potentially start a chain of events that leads to an unbalance between the amount of heat generated by the computing nodes and the heat removed by the cooling system originating thermal hazards. Although thermal anomalies are rare events, anomaly detection/prediction in time is vital to avoid IT and facility equipment damage and outage of the datacenter, with severe societal and business losses. For this reason, automated approaches to detect thermal anomalies in datacenters have considerable potential. This thesis analyzed and characterized the power and thermal characteristics of a Tier0 datacenter (CINECA) during production and under abnormal thermal conditions. Then, a Deep Learning (DL)-powered thermal hazard prediction framework is proposed. The proposed models are validated against real thermal hazard events reported for the studied HPC cluster while in production. This thesis is the first empirical study of thermal anomaly detection and prediction techniques of a real large-scale HPC system to the best of my knowledge. For this thesis, I used a large-scale dataset, monitoring data of tens of thousands of sensors for around 24 months with a data collection rate of around 20 seconds.
Resumo:
A densely built environment is a complex system of infrastructure, nature, and people closely interconnected and interacting. Vehicles, public transport, weather action, and sports activities constitute a manifold set of excitation and degradation sources for civil structures. In this context, operators should consider different factors in a holistic approach for assessing the structural health state. Vibration-based structural health monitoring (SHM) has demonstrated great potential as a decision-supporting tool to schedule maintenance interventions. However, most excitation sources are considered an issue for practical SHM applications since traditional methods are typically based on strict assumptions on input stationarity. Last-generation low-cost sensors present limitations related to a modest sensitivity and high noise floor compared to traditional instrumentation. If these devices are used for SHM in urban scenarios, short vibration recordings collected during high-intensity events and vehicle passage may be the only available datasets with a sufficient signal-to-noise ratio. While researchers have spent efforts to mitigate the effects of short-term phenomena in vibration-based SHM, the ultimate goal of this thesis is to exploit them and obtain valuable information on the structural health state. First, this thesis proposes strategies and algorithms for smart sensors operating individually or in a distributed computing framework to identify damage-sensitive features based on instantaneous modal parameters and influence lines. Ordinary traffic and people activities become essential sources of excitation, while human-powered vehicles, instrumented with smartphones, take the role of roving sensors in crowdsourced monitoring strategies. The technical and computational apparatus is optimized using in-memory computing technologies. Moreover, identifying additional local features can be particularly useful to support the damage assessment of complex structures. Thereby, smart coatings are studied to enable the self-sensing properties of ordinary structural elements. In this context, a machine-learning-aided tomography method is proposed to interpret the data provided by a nanocomposite paint interrogated electrically.
Resumo:
The coastal ocean is a complex environment with extremely dynamic processes that require a high-resolution and cross-scale modeling approach in which all hydrodynamic fields and scales are considered integral parts of the overall system. In the last decade, unstructured-grid models have been used to advance in seamless modeling between scales. On the other hand, the data assimilation methodologies to improve the unstructured-grid models in the coastal seas have been developed only recently and need significant advancements. Here, we link the unstructured-grid ocean modeling to the variational data assimilation methods. In particular, we show results from the modeling system SANIFS based on SHYFEM fully-baroclinic unstructured-grid model interfaced with OceanVar, a state-of-art variational data assimilation scheme adopted for several systems based on a structured grid. OceanVar implements a 3DVar DA scheme. The combination of three linear operators models the background error covariance matrix. The vertical part is represented using multivariate EOFs for temperature, salinity, and sea level anomaly. The horizontal part is assumed to be Gaussian isotropic and is modeled using a first-order recursive filter algorithm designed for structured and regular grids. Here we introduced a novel recursive filter algorithm for unstructured grids. A local hydrostatic adjustment scheme models the rapidly evolving part of the background error covariance. We designed two data assimilation experiments using SANIFS implementation interfaced with OceanVar over the period 2017-2018, one with only temperature and salinity assimilation by Argo profiles and the second also including sea level anomaly. The results showed a successful implementation of the approach and the added value of the assimilation for the active tracer fields. While looking at the broad basin, no significant improvements are highlighted for the sea level, requiring future investigations. Furthermore, a Machine Learning methodology based on an LSTM network has been used to predict the model SST increments.
Resumo:
Industry 4.0 refers to the 4th industrial revolution and at its bases, we can see the digitalization and the automation of the assembly line. The whole production process has improved and evolved thanks to the advances made in networking, and AI studies, which include of course machine learning, cloud computing, IoT, and other technologies that are finally being implemented into the industrial scenario. All these technologies have in common a need for faster, more secure, robust, and reliable communication. One of the many solutions for these demands is the use of mobile communication technologies in the industrial environment, but which technology is better suited for these demands? Of course, the answer isn’t as simple as it seems. The 4th industrial revolution has a never seen incomparable potential with respect to the previous ones, every factory, enterprise, or company have different network demands, and even in each of these infrastructures, the demands may diversify by sector, or by application. For example, in the health care industry, there may be e a need for increased bandwidth for the analysis of high-definition videos or, faster speeds in order to have analytics occur in real-time, and again another application might be higher security and reliability to protect patients’ data. As seen above, choosing the right technology for the right environment and application, considers many things, and the ones just stated are but a speck of dust with respect to the overall picture. In this thesis, we will investigate a comparison between the use of two of the available technologies in use for the industrial environment: Wi-Fi 6 and 5G Private Networks in the specific case of a steel factory.
Resumo:
Most epidemiological studies concerning differentiated thyroid cancers (DTC) indicate an increasing incidence over the last two decades. This increase might be partially explained by the better access to health services worldwide, but clinicopathological analyses do not fully support this hypothesis, indicating that there are carcinogenetic factors behind this noticeable increasing incidence. Although we have undoubtedly understood the biology and molecular pathways underlying thyroid carcinogenesis in a better way, we have made very little progresses in identifying a risk profile for DTC, and our knowledge of risk factors is very similar to what we knew 30-40 years ago. In addition to ionizing radiation exposure, the most documented and established risk factor for DTC, we also investigated the role of other factors, including eating habits, tobacco smoking, living in a volcanic area, xenobiotics, and viruses, which could be involved in thyroid carcinogenesis, thus, contributing to the increase in DTC incidence rates observed.
Resumo:
This study compares the impact of obesogenic environment (OE) in six different periods of development on sperm parameters and the testicular structure of adult rats and their correlations with sex steroid and metabolic scenario. Wistar rats were exposed to OE during gestation (O1), during gestation/lactation (O2), from weaning to adulthood (O3), from lactation to adulthood (O4), from gestation to sexual maturity (O5), and after sexual maturation (O6). OE was induced by a 20% fat diet, and control groups were fed a balanced diet (4% fat). Serum leptin levels and adiposity index indicate that all groups were obese, except for O1. Three progressive levels of impaired metabolic status were observed: O1 presented insulin resistance, O2 were insulin resistant and obese, and groups O3, O4, and O5 were insulin resistant, obese, and diabetic. These three levels of metabolic damage were proportional to the increase of leptin and decreased circulating testosterone. The impairment in the daily sperm production (DSP) paralleled these three levels of metabolic and hormonal damage being marginal in O1, increasing in O2, and being higher in groups O3, O4, O5, and O6. None of the OE periods affected the sperm transit time in the epididymis, and the lower sperm reserves were caused mainly by impaired DSP. In conclusion, OE during sexual maturation markedly reduces the DSP at adulthood in the rat. A severe reduction in the DSP also occurs in OE exposure during gestation/lactation but not in gestation, indicating that breast-feeding is a critical period for spermatogenic impairment under obesogenic conditions.
Resumo:
to assess how nurses perceive autonomy, control over the environment, the professional relationship between nurses and physicians and the organizational support and correlate them with burnout, satisfaction at work, quality of work and the intention to quit work in primary healthcare. cross-sectional and correlation study, using a sample of 198 nurses. The tools used were the Nursing Work Index Revised, Maslach Burnout Inventory and a form to characterize the nurses. To analyze the data, descriptive statistics were applied and Spearman's correlation coefficient was used. the nurses assessed that the environment is partially favorable for: autonomy, professional relationship and organizational support and that the control over this environment is limited. Significant correlations were evidenced between the Nursing Work Index Revised, Maslach Burnout Inventory and the variables: satisfaction at work, quality of care and the intent to quit the job. the nurses' perceptions regarding the environment of practice are correlated with burnout, satisfaction at work, quality of care and the intent to quit the job. This study provides support for the restructuring of work processes in the primary health care environment and for communication among the health service management, human resources and occupational health areas.
Resumo:
Seasonally dry tropical plant formations (SDTF) are likely to exhibit phylogenetic clustering owing to niche conservatism driven by a strong environmental filter (water stress), but heterogeneous edaphic environments and life histories may result in heterogeneity in degree of phylogenetic clustering. We investigated phylogenetic patterns across ecological gradients related to water availability (edaphic environment and climate) in the Caatinga, a SDTF in Brazil. Caatinga is characterized by semiarid climate and three distinct edaphic environments - sedimentary, crystalline, and inselberg -representing a decreasing gradient in soil water availability. We used two measures of phylogenetic diversity: Net Relatedness Index based on the entire phylogeny among species present in a site, reflecting long-term diversification; and Nearest Taxon Index based on the tips of the phylogeny, reflecting more recent diversification. We also evaluated woody species in contrast to herbaceous species. The main climatic variable influencing phylogenetic pattern was precipitation in the driest quarter, particularly for herbaceous species, suggesting that environmental filtering related to minimal periods of precipitation is an important driver of Caatinga biodiversity, as one might expect for a SDTF. Woody species tended to show phylogenetic clustering whereas herbaceous species tended towards phylogenetic overdispersion. We also found phylogenetic clustering in two edaphic environments (sedimentary and crystalline) in contrast to phylogenetic overdispersion in the third (inselberg). We conclude that while niche conservatism is evident in phylogenetic clustering in the Caatinga, this is not a universal pattern likely due to heterogeneity in the degree of realized environmental filtering across edaphic environments. Thus, SDTF, in spite of a strong shared environmental filter, are potentially heterogeneous in phylogenetic structuring. Our results support the need for scientifically informed conservation strategies in the Caatinga and other SDTF regions that have not previously been prioritized for conservation in order to take into account this heterogeneity.
Resumo:
The Cananéia-Iguape system, SE Brazil, consists of a complex of lagoonal channels, located in a United Nations Educational, Scientific and Cultural Organization (UNESCO) Biosphere Reserve. Nevertheless, important environmental changes have occurred in approximately the last 150 yrs due to the opening of an artificial channel, the Valo Grande, connecting the Ribeira de Iguape River to the lagoonal system. Our objective is to assess the historical record of the uppermost layers of the sedimentary column of the lagoonal system in order to determine the history of environmental changes caused by the opening of the artificial channel. In this sense, an integrated geochemical-faunal approach is used. The environmental changes led significant modifications in salinity, in changes of the depositional patterns of sediments and foraminiferal assemblages (including periods of defaunation), and, more drastically, in the input of heavy metals to the coastal environment. The concentrations Pb in the core analyzed here were up to two times higher than the values measured in contaminated sediments from the Santos estuary, the most industrialized coastal zone in Brazil.
The bubbles or the boiling pot?: an ecosystemic approach to culture, environment and quality of life
Resumo:
For the diagnosis and prognosis of the problems of quality of life, a multidisciplinary ecosystemic approach encompasses four dimensions of being-in-the-world, as donors and recipients: intimate, interactive, social and biophysical. Social, cultural and environmental vulnerabilities are understood and dealt with, in different circumstances of space and time, as the conjugated effect of all dimensions of being-in-the-world, as they induce the events (deficits and assets), cope with consequences (desired or undesired) and contribute for change. Instead of fragmented and reduced representations of reality, diagnosis and prognosis of cultural, educational, environmental and health problems considers the connections (assets) and ruptures (deficits) between the different dimensions, providing a planning model to develop and evaluate research, teaching programmes, public policies and field projects. The methodology is participatory, experiential and reflexive; heuristic-hermeneutic processes unveil cultural and epistemic paradigms that orient subject-object relationships; giving people the opportunity to reflect on their own realities, engage in new experiences and find new ways to live better in a better world. The proposal is a creative model for thought and practice, providing many opportunities for discussion, debate and development of holistic projects integrating different scientific domains (social sciences, psychology, education, philosophy, etc.)
Resumo:
Background: The aim of this study was analyze associations between the practice of walking and environmental perception among elderly Brazilians in a region of low socioeconomic level. Methods: A cross-sectional study was conducted among 385 elderly people aged 60 years and over. To evaluate walking, the International Physical Activity Questionnaire (IPAQ), long version (leisure and transport modules) was used. The environment was evaluated by means of the Neighborhood Environmental Walkability Scale (NEWS) (adapted Brazilian version). For the statistical analysis, multiple logistic regression models were created separately for men and women. The practice of at least 150 minutes a week of walking was the dependent variable, and the variables of environmental perception were the independent variables. All the models were controlled for schooling level and age. Results: The proportion of elderly people active in walking was 56.9% for the men and 26.4% for the women. The perception of the presence of soccer fields (OR = 4.12) and their proximity, within ten minutes' walk from home (OR = 3.43), were associated with the practice of walking among the men. The perception of the presence of public squares (OR = 4.70) and the proximity of primary healthcare units, within ten minutes' walk from home (OR = 3.71), were associated with the practice of walking among the women. An association with adequate perception of vehicle traffic remained at the threshold of significance for the women. Conclusion: Accessibility of leisure structures such as football fields and public squares and of health services such as primary healthcare units were important environmental variables associated with the practice of walking among elderly people living in a region of low socioeconomic level in Brazil. These variables need to be taken into consideration when aiming to promote the practice of walking among elderly people living in similar regions.
Resumo:
Background: The purpose of this study was to analyze the relationship between adolescents' physical activity practice and their perception about the environment of urban parks. Methods: A school-based representative sample (n = 1,718; boys = 40.4%) of teenagers of Curitiba, Southern region of Brazil. A questionnaire was employed to identify perceived parks environmental features as well as physical activity practice in the parks (PAP), habitual physical activity (HPA) and demographics. The relationship between PAP and parks environments was analyzed through multivariate logistic regression controlling for age and socioeconomic status, HPA and parks distance. Results: After controlling for confounders PAP was associated with lack of space to be physically active, activities to choose from and equipments for both boys and girls, (odds ratio (OR)-ranging from 1.5 to 1.8). Among boys, having people of same age (OR = 1.5) and accessibility (OR = 2.0) showed association with PAP only in crude analysis. However, among girls, to be bulled or teased (OR = 1.4) and accessibility (OR = 1.7) were associated with PAP after confounding control. Conclusions: The results showed that specific attributes in parks may be considered and offered to increase the likelihood of physical activity practice among adolescents in such locations.