978 resultados para Operational Adaptive Diagnostic Scale - EDAO
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RTUWO Advances in Wireless and Optical Communications 2015 (RTUWO 2015). 5-6 Nov Riga, Latvia.
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Neuroschistosomiasis (NS) is the second most common form of presentation of infection by the trematode, Schistosoma mansoni. Granulomatous inflammatory reaction occurs as a result of schistosome eggs being transmitted to spinal cord or brain via the vascular system, or by inadvertent adult worm migration to these organs. The two main clinical syndromes are spinal cord neuroschistosomiasis (acute or subacute myelopathy) and localized cerebral or cerebellar neuroschistosomiasis (focal CNS impairment, seizures, increased intracranial pressure). Presumptive diagnosis of NS requires confirming the presence of S. mansoni infection by stool microscopy or rectal biopsy for trematode eggs, and serologic testing of blood and spinal fluid. The localized lesions are identified by signs and symptoms, and confirmed by imaging techniques (contrast myelography, CT and MRI). Algorithms are presented to allow a stepwise approach to diagnosis.
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A novel control technique is investigated in the adaptive control of a typical paradigm, an approximately and partially modeled cart plus double pendulum system. In contrast to the traditional approaches that try to build up ”complete” and ”permanent” system models it develops ”temporal” and ”partial” ones that are valid only in the actual dynamic environment of the system, that is only within some ”spatio-temporal vicinity” of the actual observations. This technique was investigated for various physical systems via ”preliminary” simulations integrating by the simplest 1st order finite element approach for the time domain. In 2004 INRIA issued its SCILAB 3.0 and its improved numerical simulation tool ”Scicos” making it possible to generate ”professional”, ”convenient”, and accurate simulations. The basic principles of the adaptive control, the typical tools available in Scicos, and others developed by the authors, as well as the improved simulation results and conclusions are presented in the contribution.
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Canadian Journal of Civil Engineering 36(10) 1605–16
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In this study, energy production for autonomous underwater vehicles is investigated. This project is part of a bigger project called TURTLE. The autonomous vehicles perform oceanic researches at seabed for which they are intended to be kept operational underwater for several months. In order to ful l a long-term underwater condition, powerful batteries are combined with \micro- scale" energy production on the spot. This work tends to develop a system that generates power up to a maximum of 30 W. Latter energy harvesting structure consists basically of a turbine combined with a generator and low-power electronics to adjust the achieved voltage to a required battery charger voltage. Every component is examined separately hence an optimum can be de ned for all, and subsequently also an overall optimum. Di erent design parameters as e.g. number of blades, solidity ratio and cross-section area are compared for di erent turbines, in order to see what is the most feasible type. Further, a generator is chosen by studying how ux distributions might be adjusted to low velocities, and how cogging torque can be excluded by adapted designs. Low-power electronics are con gured in order to convert and stabilize heavily varying three-phase voltages to a constant, recti ed voltage which is usable for battery storage. Clearly, di erent component parameters as maximum power and torque are matched here to increase the overall power generation. Furthermore an overall maximum power is set up for achieving a maximum power ow at load side. Due to among others typical low velocities of about 0.1 to 0.5 m/s, and constructing limits of the prototype, the vast range of components is restricted to only a few that could be used. Hence, a helical turbine is combined in a direct drive mode to a coreless-stator axial- ux permanent-magnet generator, from which the output voltage is adjusted subsequently by a recti er, impedance matching unit, upconverter circuit and an overall control unit to regulate di erent component parameters. All these electronics are combined in a closed-loop design to involve positive feedback signals. Furthermore a theoretical con guration for the TURTLE vehicle is described in this work and a solution is proposed that might be implemented, for which several design tests are performable in a future study.
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This paper presents the design of low cost, small autonomous surface vehicle for missions in the coastal waters and specifically for the challenging surf zone. The main objective of the vehicle design described in this paper is to address both the capability of operation at sea in relative challenging conditions and maintain a very low set of operational requirements (ease of deployment). This vehicle provides a first step towards being able to perform general purpose missions (such as data gathering or patrolling) and to at least in a relatively short distances to be able to be used in rescue operations (with very low handling requirements) such as carrying support to humans on the water. The USV is based on a commercially available fiber glass hull, it uses a directional waterjet powered by an electrical brushless motor for propulsion, thus without any protruding propeller reducing danger in rescue operations. Its small dimensions (1.5 m length) and weight allow versatility and ease of deployment. The vehicle design is described in this paper both from a hardware and software point of view. A characterization of the vehicle in terms of energy consumption and performance is provided both from test tank and operational scenario tests. An example application in search and rescue is also presented and discussed with the integration of this vehicle in the European ICARUS (7th framework) research project addressing the development and integration of robotic tools for large scale search and rescue operations.
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This paper presents a decision support methodology for electricity market players’ bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method’s adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts’ negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems’ technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players’ decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operator—MIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts’ negotiations.
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A significant number of Brazilian gestational-age women are still not tested for HIV, representing a high risk of transmission to their newborns. The current study sought to identify the number of pregnant women with no previous testing or undocumented for HIV referred to the Gynecology and Obstetrics Department of a Regional Teaching Hospital and included diagnosis of HIV infection determined by a rapid test and perinatal transmission in pregnancy. Medical records of all pregnant women admitted to hospital from January 2001 to December 2005 were reviewed. Pregnant women without HIV results were submitted to a rapid HIV test. Those who tested positive were further tested by ELISA and confirmed by indirect immunofluorescence assay (IIA) or Western blot (WB). The viral load from babies born to HIV-infected mothers was assessed by bDNA. Of the 16,424 pregnant women analyzed (6.6%), 1,089 were undocumented for HIV. Eleven women were positive in rapid testing and 10 were confirmed by ELISA, IIA or WB, with 0.9% seropositivity. Mother/infant pairs received zidovudine monotherapy prophylaxis and infant viral load was lower than 50 copies/mL. A higher number of pregnant women previously tested for HIV during antenatal care was verified, compared to that obtained nationwide.
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Toxoplasma gondii causes severe fetal disease during acute infection in pregnant women, thus demanding early diagnosis for effective treatment and fetus preservation. Fetal tests are inefficient and risky, and diagnosis is based on maternal IgM serology, which had weak screening ability due to increased sensitivity, with alternative IgG avidity tests. Here, we performed ELISA and avidity assays using a recombinant T. gondii antigen, rROP2, in samples from 160 pregnant women screened from a large public hospital who were referred due to positive IgM assays. IgG serology and avidity assays were compared using whole T. gondii extract or rROP2. ELISA IgG detection with rROP2 showed good agreement with assays performed with T. gondii extract, but rROP2 IgG avidity assays were unrelated to whole extract antigen IgG avidity, regardless of the chaotrope used. These data show that avidity maturation is specific to individual antigen prevalence and immune response during infection. ELISA rROP2 IgG assays may be an alternative serological test for the diagnosis of toxoplasmosis during pregnancy, although our data do not support their use in avidity assays.
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Background Musicians are frequently affected by playing-related musculoskeletal disorders (PRMD). Common solutions used by Western medicine to treat musculoskeletal pain include rehabilitation programs and drugs, but their results are sometimes disappointing. Objective To study the effects of self-administered exercises based on Tuina techniques on the pain intensity caused by PRMD of professional orchestra musicians, using numeric visual scale (NVS). Design, setting, participants and interventions We performed a prospective, controlled, single-blinded, randomized study with musicians suffering from PRMD. Participating musicians were randomly distributed into the experimental (n = 39) and the control (n = 30) groups. After an individual diagnostic assessment, specific Tuina self-administered exercises were developed and taught to the participants. Musicians were instructed to repeat the exercises every day for 3 weeks. Main outcome measures Pain intensity was measured by NVS before the intervention and after 1, 3, 5, 10, 15 and 20 d of treatment. The procedure was the same for the control group, however the Tuina exercises were executed in points away from the commonly-used acupuncture points. Results In the treatment group, but not the control group, pain intensity was significantly reduced on days 1, 3, 5, 10, 15 and 20. Conclusion The results obtained are consistent with the hypothesis that self-administered exercises based on Tuina techniques could help professional musicians controlling the pain caused by PRMD. Although our results are very promising, further studies are needed employing a larger sample size and double blinding designs.
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Optimization methods have been used in many areas of knowledge, such as Engineering, Statistics, Chemistry, among others, to solve optimization problems. In many cases it is not possible to use derivative methods, due to the characteristics of the problem to be solved and/or its constraints, for example if the involved functions are non-smooth and/or their derivatives are not know. To solve this type of problems a Java based API has been implemented, which includes only derivative-free optimization methods, and that can be used to solve both constrained and unconstrained problems. For solving constrained problems, the classic Penalty and Barrier functions were included in the API. In this paper a new approach to Penalty and Barrier functions, based on Fuzzy Logic, is proposed. Two penalty functions, that impose a progressive penalization to solutions that violate the constraints, are discussed. The implemented functions impose a low penalization when the violation of the constraints is low and a heavy penalty when the violation is high. Numerical results, obtained using twenty-eight test problems, comparing the proposed Fuzzy Logic based functions to six of the classic Penalty and Barrier functions are presented. Considering the achieved results, it can be concluded that the proposed penalty functions besides being very robust also have a very good performance.