954 resultados para Medical informatics applications


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Dissertação para obtenção do Grau de Mestre em Energias Renováveis – Conversão Eléctrica e Utilização Sustentáveis

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Currently, a learning management system (LMS) plays a central role in any e-learning environment. These environments include systems to handle the pedagogic aspects of the teaching–learning process (e.g. specialized tutors, simulation games) and the academic aspects (e.g. academic management systems). Thus, the potential for interoperability is an important, although over looked, aspect of an LMS. In this paper, we make a comparative study of the interoperability level of the most relevant LMS. We start by defining an application and a specification model. For the application model, we create a basic application that acts as a tool provider for LMS integration. The specification model acts as the API that the LMS should implement to communicate with the tool provider. Based on researches, we select the Learning Tools Interoperability (LTI) from IMS. Finally, we compare the LMS interoperability level defined as the effort made to integrate the application on the study LMS.

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The robotics community is concerned with the ability to infer and compare the results from researchers in areas such as vision perception and multi-robot cooperative behavior. To accomplish that task, this paper proposes a real-time indoor visual ground truth system capable of providing accuracy with at least more magnitude than the precision of the algorithm to be evaluated. A multi-camera architecture is proposed under the ROS (Robot Operating System) framework to estimate the 3D position of objects and the implementation and results were contextualized to the Robocup Middle Size League scenario.

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Intense environmental impacts, causing alterations of the natural habitats of fauna, including those of sandfly disease vectors are observed in Mato Grosso State, Central Brazil. Entomologic survey of phlebotomines was based on light trap and was carried out by entomological nucleus of the FUNASA and SES in the period between 1996 and 2001. Eighty eight species were identified, including the following sandflies with medical importance to leishmaniasis: Lutzomyia amazonensis, L. anduzei, L. antunesi, L. ayrozai, L. carrerai carrerai, L. complexa, L. cruzi, L. flaviscutellata, L. intermedia, L. longipalpis, L. migonei, L. paraensis, L. ubiquitalis, L. whitmani and L. yuilli yuilli. Most sandflies of medical importance occurred in the Amazon forest and savannah. L. longipalpis and L. cruzi had high densities in the savannah region. L. flaviscutellata is predominating in both the Amazon forest and the savannah region. L. whitmani and L. antunesi were sampled in the Amazon forest, savannah and marsh land.

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Presented at INForum - Simpósio de Informática (INFORUM 2015). 7 to 8, Sep, 2015. Portugal.

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EMC2 finds solutions for dynamic adaptability in open systems. It provides handling of mixed criticality multicore applications in r eal-time conditions, withscalability and utmost flexibility, full-scale deployment and management of integrated tool chains, through the entire lifecycle.

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Postsurgical acute suppurative parotitis is a bacterial gland infection that occurs from a few days up to some weeks after abdominal surgical procedures. In this study, the authors analyze the prevalence of this complication in Hospital das Clínicas/São Paulo University Medical School by prospectively reviewing the charts of patients who underwent surgeries performed by the gastroenterological and general surgery staff from 1980 to 2005. Diagnosis of parotitis or sialoadenitis was analyzed. Sialolithiasis and chronic parotitis previous to hospitalization were exclusion criteria. In a total of 100,679 surgeries, 256 patients were diagnosed with parotitis or sialoadenitis. Nevertheless, only three cases of acute postsurgical suppurative parotitis associated with the surgery were identified giving an incidence of 0.0028%. All patients presented with risk factors such as malnutrition, immunosuppression, prolonged immobilization and dehydration. In the past, acute postsurgical suppurative parotitis was a relatively common complication after major abdominal surgeries. Its incidence decreased as a consequence of the improvement of perioperative antibiotic therapy and postoperative support. In spite of the current low incidence, we believe it is important to identify risks and diagnose as quick as possible, in order to introduce prompt and appropriate therapeutic measures and avoid potentially fatal complications with the evolution of the disease.

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Real-time monitoring applications may be used in a wireless sensor network (WSN) and may generate packet flows with strict quality of service requirements in terms of delay, jitter, or packet loss. When strict delays are imposed from source to destination, the packets must be delivered at the destination within an end-to-end delay (EED) hard limit in order to be considered useful. Since the WSN nodes are scarce both in processing and energy resources, it is desirable that they only transport useful data, as this contributes to enhance the overall network performance and to improve energy efficiency. In this paper, we propose a novel cross-layer admission control (CLAC) mechanism to enhance the network performance and increase energy efficiency of a WSN, by avoiding the transmission of potentially useless packets. The CLAC mechanism uses an estimation technique to preview packets EED, and decides to forward a packet only if it is expected to meet the EED deadline defined by the application, dropping it otherwise. The results obtained show that CLAC enhances the network performance by increasing the useful packet delivery ratio in high network loads and improves the energy efficiency in every network load.

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Dissertação para obtenção do Grau de Mestre em Engenharia Informática

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Dissertação para obtenção do Grau de Doutor em Bioengenharia

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This paper suggests that a convenient score test against non-nested alternatives can be constructed from the linear combination of the likelihood functions of the competing models. It is shown that this procedure is essentially a test for the correct specification of the conditional distribution of the variable of interest.

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The complexity of systems is considered an obstacle to the progress of the IT industry. Autonomic computing is presented as the alternative to cope with the growing complexity. It is a holistic approach, in which the systems are able to configure, heal, optimize, and protect by themselves. Web-based applications are an example of systems where the complexity is high. The number of components, their interoperability, and workload variations are factors that may lead to performance failures or unavailability scenarios. The occurrence of these scenarios affects the revenue and reputation of businesses that rely on these types of applications. In this article, we present a self-healing framework for Web-based applications (SHõWA). SHõWA is composed by several modules, which monitor the application, analyze the data to detect and pinpoint anomalies, and execute recovery actions autonomously. The monitoring is done by a small aspect-oriented programming agent. This agent does not require changes to the application source code and includes adaptive and selective algorithms to regulate the level of monitoring. The anomalies are detected and pinpointed by means of statistical correlation. The data analysis detects changes in the server response time and analyzes if those changes are correlated with the workload or are due to a performance anomaly. In the presence of per- formance anomalies, the data analysis pinpoints the anomaly. Upon the pinpointing of anomalies, SHõWA executes a recovery procedure. We also present a study about the detection and localization of anomalies, the accuracy of the data analysis, and the performance impact induced by SHõWA. Two benchmarking applications, exercised through dynamic workloads, and different types of anomaly were considered in the study. The results reveal that (1) the capacity of SHõWA to detect and pinpoint anomalies while the number of end users affected is low; (2) SHõWA was able to detect anomalies without raising any false alarm; and (3) SHõWA does not induce a significant performance overhead (throughput was affected in less than 1%, and the response time delay was no more than 2 milliseconds).