953 resultados para approach-oriented coping
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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
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ABSTRACT OBJECTIVE To identify individual and hospital characteristics associated with the risk of readmission in older inpatients for proximal femoral fracture in the period of 90 days after discharge. METHODS Deaths and readmissions were obtained by a linkage of databases of the Hospital Information System of the Unified Health System and the System of Information on Mortality of the city of Rio de Janeiro from 2008 to 2011. The population of 3,405 individuals aged 60 or older, with non-elective hospitalization for proximal femoral fracture was followed for 90 days after discharge. Cox multilevel model was used for discharge time until readmission, and the characteristics of the patients were used on the first level and the characteristics of the hospitals on the second level. RESULTS The risk of readmission was higher for men (hazard ratio [HR] = 1.37; 95%CI 1.08–1.73), individuals more than 79 years old (HR = 1.45; 95%CI 1.06–1.98), patients who were hospitalized for more than two weeks (HR = 1.33; 95%CI 1.06-1.67), and for those who underwent arthroplasty when compared with the ones who underwent osteosynthesis (HR = 0.57; 95%CI 0.41–0.79). Besides, patients admitted to state hospitals had lower risk for readmission when compared with inpatients in municipal (HR = 1.71; 95%CI 1.09–2.68) and federal hospitals (HR = 1.81; 95%CI 1.00–3.27). The random effect of the hospitals in the adjusted model remained statistically significant (p < 0.05). CONCLUSIONS Hospitals have complex structures that reflect in the quality of care. Thus, we propose that future studies may include these complexities and the severity of the patients in the analysis of the data, also considering the correlation between readmission and mortality to reduce biases.
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Dissertação de Mestrado em Engenharia Informática
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Many learning problems require handling high dimensional datasets with a relatively small number of instances. Learning algorithms are thus confronted with the curse of dimensionality, and need to address it in order to be effective. Examples of these types of data include the bag-of-words representation in text classification problems and gene expression data for tumor detection/classification. Usually, among the high number of features characterizing the instances, many may be irrelevant (or even detrimental) for the learning tasks. It is thus clear that there is a need for adequate techniques for feature representation, reduction, and selection, to improve both the classification accuracy and the memory requirements. In this paper, we propose combined unsupervised feature discretization and feature selection techniques, suitable for medium and high-dimensional datasets. The experimental results on several standard datasets, with both sparse and dense features, show the efficiency of the proposed techniques as well as improvements over previous related techniques.
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Behavioral biometrics is one of the areas with growing interest within the biosignal research community. A recent trend in the field is ECG-based biometrics, where electrocardiographic (ECG) signals are used as input to the biometric system. Previous work has shown this to be a promising trait, with the potential to serve as a good complement to other existing, and already more established modalities, due to its intrinsic characteristics. In this paper, we propose a system for ECG biometrics centered on signals acquired at the subject's hand. Our work is based on a previously developed custom, non-intrusive sensing apparatus for data acquisition at the hands, and involved the pre-processing of the ECG signals, and evaluation of two classification approaches targeted at real-time or near real-time applications. Preliminary results show that this system leads to competitive results both for authentication and identification, and further validate the potential of ECG signals as a complementary modality in the toolbox of the biometric system designer.
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One fundamental idea of service-oriented computing is that applications should be developed by composing already available services. Due to the long running nature of service interactions, a main challenge in service composition is ensuring correctness of transaction recovery. In this paper, we use a process calculus suitable for modelling long running transactions with a recovery mechanism based on compensations. Within this setting, we discuss and formally state correctness criteria for compensable processes compositions, assuming that each process is correct with respect to transaction recovery. Under our theory, we formally interpret self-healing compositions, that can detect and recover from faults, as correct compositions of compensable processes. Moreover, we develop an automated verification approach and we apply it to an illustrative case study.
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Remote Laboratories or WebLabs constitute a first-order didactic resource in engineering faculties. However, in many cases, they lack a proper software design, both in the client and server side, which degrades their quality and academic usefulness. This paper presents the main characteristics of a Remote Laboratory, analyzes the software technologies to implement the client and server sides in a WebLab, and correlates these technologies with the characteristics to facilitate the selection of a technology to implement a WebLab. The results obtained suggest the adoption of a Service Oriented Laboratory Architecture-based approach for the design of future Remote Laboratories so that client-agnostic Remote Laboratories and Remote Laboratory composition are enabled. The experience with the real Remote Laboratory, WebLab-Deusto, is also presented.
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Dissertation submitted for a PhD degree in Electrical Engineering, speciality of Robotics and Integrated Manufacturing from the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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Dissertação apresentada para obtenção do Grau de Doutor em Conservação e Restauro, especialidade Teoria, História e Técnicas, pela Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia
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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do Grau de Mestre em Engenharia Informática.
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Tese de Mestrado em Engenharia Informática
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A dynamical approach to study the behaviour of generalized populational growth models from Bets(p, 2) densities, with strong Allee effect, is presented. The dynamical analysis of the respective unimodal maps is performed using symbolic dynamics techniques. The complexity of the correspondent discrete dynamical systems is measured in terms of topological entropy. Different populational dynamics regimes are obtained when the intrinsic growth rates are modified: extinction, bistability, chaotic semistability and essential extinction.
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The study of transient dynamical phenomena near bifurcation thresholds has attracted the interest of many researchers due to the relevance of bifurcations in different physical or biological systems. In the context of saddle-node bifurcations, where two or more fixed points collide annihilating each other, it is known that the dynamics can suffer the so-called delayed transition. This phenomenon emerges when the system spends a lot of time before reaching the remaining stable equilibrium, found after the bifurcation, because of the presence of a saddle-remnant in phase space. Some works have analytically tackled this phenomenon, especially in time-continuous dynamical systems, showing that the time delay, tau, scales according to an inverse square-root power law, tau similar to (mu-mu (c) )(-1/2), as the bifurcation parameter mu, is driven further away from its critical value, mu (c) . In this work, we first characterize analytically this scaling law using complex variable techniques for a family of one-dimensional maps, called the normal form for the saddle-node bifurcation. We then apply our general analytic results to a single-species ecological model with harvesting given by a unimodal map, characterizing the delayed transition and the scaling law arising due to the constant of harvesting. For both analyzed systems, we show that the numerical results are in perfect agreement with the analytical solutions we are providing. The procedure presented in this work can be used to characterize the scaling laws of one-dimensional discrete dynamical systems with saddle-node bifurcations.
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Signal Processing, vol. 86, nº 10