153 resultados para COMPUTER-AIDED DIAGNOSIS


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Power distribution automation and control are import-ant tools in the current restructured electricity markets. Unfortunately, due to its stochastic nature, distribution systems faults are hardly avoidable. This paper proposes a novel fault diagnosis scheme for power distribution systems, composed by three different processes: fault detection and classification, fault location, and fault section determination. The fault detection and classification technique is wavelet based. The fault-location technique is impedance based and uses local voltage and current fundamental phasors. The fault section determination method is artificial neural network based and uses the local current and voltage signals to estimate the faulted section. The proposed hybrid scheme was validated through Alternate Transient Program/Electromagentic Transients Program simulations and was implemented as embedded software. It is currently used as a fault diagnosis tool in a Southern Brazilian power distribution company.

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An efficient expert system for the power transformer condition assessment is presented in this paper. Through the application of Duval`s triangle and the method of the gas ratios a first assessment of the transformer condition is obtained in the form of a dissolved gas analysis (DGA) diagnosis according IEC 60599. As a second step, a knowledge mining procedure is performed, by conducting surveys whose results are fed into a first Type-2 Fuzzy Logic System (T2-FLS), in order to initially evaluate the condition of the equipment taking only the results of dissolved gas analysis into account. The output of this first T2-FLS is used as the input of a second T2-FLS, which additionally weighs up the condition of the paper-oil system. The output of this last T2-FLS is given in terms of words easily understandable by the maintenance personnel. The proposed assessing methodology has been validated for several cases of transformers in service. (C) 2010 Elsevier Ltd. All rights reserved.

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A two-dimensional numeric simulator is developed to predict the nonlinear, convective-reactive, oxygen mass exchange in a cross-flow hollow fiber blood oxygenator. The numeric simulator also calculates the carbon dioxide mass exchange, as hemoglobin affinity to oxygen is affected by the local pH value, which depends mostly on the local carbon dioxide content in blood. Blood pH calculation inside the oxygenator is made by the simultaneous solution of an equation that takes into account the blood buffering capacity and the classical Henderson-Hasselbach equation. The modeling of the mass transfer conductance in the blood comprises a global factor, which is a function of the Reynolds number, and a local factor, which takes into account the amount of oxygen reacted to hemoglobin. The simulator is calibrated against experimental data for an in-line fiber bundle. The results are: (i) the calibration process allows the precise determination of the mass transfer conductance for both oxygen and carbon dioxide; (ii) very alkaline pH values occur in the blood path at the gas inlet side of the fiber bundle; (iii) the parametric analysis of the effect of the blood base excess (BE) shows that V(CO2) is similar in the case of blood metabolic alkalosis, metabolic acidosis, or normal BE, for a similar blood inlet P(CO2), although the condition of metabolic alkalosis is the worst case, as the pH in the vicinity of the gas inlet is the most alkaline; (iv) the parametric analysis of the effect of the gas flow to blood flow ratio (Q(G)/Q(B)) shows that V(CO2) variation with the gas flow is almost linear up to Q(G)/Q(B) = 2.0. V(O2) is not affected by the gas flow as it was observed that by increasing the gas flow up to eight times, the V(O2) grows only 1%. The mass exchange of carbon dioxide uses the full length of the hollow-fiber only if Q(G)/Q(B) > 2.0, as it was observed that only in this condition does the local variation of pH and blood P(CO2) comprise the whole fiber bundle.

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Safety Instrumented Systems (SIS) are designed to prevent and / or mitigate accidents, avoiding undesirable high potential risk scenarios, assuring protection of people`s health, protecting the environment and saving costs of industrial equipment. The design of these systems require formal methods for ensuring the safety requirements, but according material published in this area, has not identified a consolidated procedure to match the task. This sense, this article introduces a formal method for diagnosis and treatment of critical faults based on Bayesian network (BN) and Petri net (PN). This approach considers diagnosis and treatment for each safety instrumented function (SIF) including hazard and operability (HAZOP) study in the equipment or system under control. It also uses BN and Behavioral Petri net (BPN) for diagnoses and decision-making and the PN for the synthesis, modeling and control to be implemented by Safety Programmable Logic Controller (PLC). An application example considering the diagnosis and treatment of critical faults is presented and illustrates the methodology proposed.

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The TCP/IP architecture was consolidated as a standard to the distributed systems. However, there are several researches and discussions about alternatives to the evolution of this architecture and, in this study area, this work presents the Title Model to contribute with the application needs support by the cross layer ontology use and the horizontal addressing, in a next generation Internet. For a practical viewpoint, is showed the network cost reduction for the distributed programming example, in networks with layer 2 connectivity. To prove the title model enhancement, it is presented the network analysis performed for the message passing interface, sending a vector of integers and returning its sum. By this analysis, it is confirmed that the current proposal allows, in this environment, a reduction of 15,23% over the total network traffic, in bytes.

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The increasing adoption of information systems in healthcare has led to a scenario where patient information security is more and more being regarded as a critical issue. Allowing patient information to be in jeopardy may lead to irreparable damage, physically, morally, and socially to the patient, potentially shaking the credibility of the healthcare institution. Medical images play a crucial role in such context, given their importance in diagnosis, treatment, and research. Therefore, it is vital to take measures in order to prevent tampering and determine their provenance. This demands adoption of security mechanisms to assure information integrity and authenticity. There are a number of works done in this field, based on two major approaches: use of metadata and use of watermarking. However, there still are limitations for both approaches that must be properly addressed. This paper presents a new method using cryptographic means to improve trustworthiness of medical images, providing a stronger link between the image and the information on its integrity and authenticity, without compromising image quality to the end user. Use of Digital Imaging and Communications in Medicine structures is also an advantage for ease of development and deployment.

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SKAN: Skin Scanner - System for Skin Cancer Detection Using Adaptive Techniques - combines computer engineering concepts with areas like dermatology and oncology. Its objective is to discern images of skin cancer, specifically melanoma, from others that show only common spots or other types of skin diseases, using image recognition. This work makes use of the ABCDE visual rule, which is often used by dermatologists for melanoma identification, to define which characteristics are analyzed by the software. It then applies various algorithms and techniques, including an ellipse-fitting algorithm, to extract and measure these characteristics and decide whether the spot is a melanoma or not. The achieved results are presented with special focus on the adaptive decision-making and its effect on the diagnosis. Finally, other applications of the software and its algorithms are presented.

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Since the computer viruses pose a serious problem to individual and corporative computer systems, a lot of effort has been dedicated to study how to avoid their deleterious actions, trying to create anti-virus programs acting as vaccines in personal computers or in strategic network nodes. Another way to combat viruses propagation is to establish preventive policies based on the whole operation of a system that can be modeled with population models, similar to those that are used in epidemiological studies. Here, a modified version of the SIR (Susceptible-Infected-Removed) model is presented and how its parameters are related to network characteristics is explained. Then, disease-free and endemic equilibrium points are calculated, stability and bifurcation conditions are derived and some numerical simulations are shown. The relations among the model parameters in the several bifurcation conditions allow a network design minimizing viruses risks. (C) 2009 Elsevier Inc. All rights reserved.

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A thermodynamic information system for diagnosis and prognosis of an existing power plant was developed. The system is based on an analytic approach that informs the current thermodynamic condition of all cycle components, as well as the improvement that can be obtained in the cycle performance by the elimination of the discovered anomalies. The effects induced by components anomalies and repairs in other components efficiency, which have proven to be one of the main drawbacks in the diagnosis and prognosis analyses, are taken into consideration owing to the use of performance curves and corrected performance curves together with the thermodynamic data collected from the distributed control system. The approach used to develop the system is explained, the system implementation in a real gas turbine cogeneration combined cycle is described and the results are discussed. (C) 2011 Elsevier Ltd. All rights reserved.

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Computer viruses are an important risk to computational systems endangering either corporations of all sizes or personal computers used for domestic applications. Here, classical epidemiological models for disease propagation are adapted to computer networks and, by using simple systems identification techniques a model called SAIC (Susceptible, Antidotal, Infectious, Contaminated) is developed. Real data about computer viruses are used to validate the model. (c) 2008 Elsevier Ltd. All rights reserved.

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We standardized serodiagnosis of dogs infected with Trypanosoma cruzi using TESA (trypomastigote excreted-secreted antigen)-blot developed for human Chagas disease. TESA-blot showed 100% sensitivity and specificity. In contrast, ELISA using TESA (TESA-ELISA) or epimastigotes (epi-ELISA) as antigen yielded 100% sensitivity but specificity of 94.1% and 49.4%, respectively. When used in field studies in an endemic region for Chagas disease, visceral leishmaniasis and Trypanosoma evansi (Mato Grosso do Sul state, Central Brazil), positivities were 9.3% for TESA-blot, 10.7% for TESA-ELISA and 32% for epi-ELISA. Dogs from a non-endemic region for these infections (Rondonia state, western Amazonia) where T cruzi is enzootic showed positivity of 4.5% for TESA-blot and epi-ELISA and 6.8% for TESA-ELISA. Sera from urban dogs from Santos, Sao Paulo, where these diseases are absent, yielded negative results. TESA-blot was the only method that distinguished dogs infected with T cruzi from those infected with Leishmania chagasi and/or Trypanosoma evansi. (C) 2009 Published by Elsevier B.V.

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Symptoms resembling giant calyx, a graft-transmissible disease, were observed on 1-5% of eggplant (aubergine; Solanum melongena L.) plants in production fields in Sao Paulo state, Brazil. Phytoplasmas were detected in 1 2 of 1 2 samples from symptomatic plants that were analysed by a nested PCR assay employing 16S rRNA gene primers R16mF2/R16mR1 followed by R16F2n/R16R2. RFLP analysis of the resulting rRNA gene products (1.2 kb) indicated that all plants contained similar phytoplasmas, each closely resembling strains previously classified as members of RFLP group 16SrIII (X-disease group). Virtual RFLP and phylogenetic analyses of sequences derived from PCR products identified phytoplasmas infecting eggplant crops grown in Piracicaba as a lineage of the subgroup 16SrIII-J, whereas phytoplasmas detected in plants grown in Braganca Paulista were tentatively classified as members of a novel subgroup 16SrIII-U. These findings confirm eggplant as a new host of group 16SrIII-J phytoplasmas and extend the known diversity of strains belonging to this group in Brazil.

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Rare HFE variants have been shown to be associated with hereditary hemochromatosis (HH), an iron overload disease. The low frequency of the HFE p.C282Y mutation in HH-affected Brazilian patients may suggest that other HFE-related mutations may also be implicated in the pathogenesis of HH in this population. The main aim was to screen for new HFE mutations in Brazilian individuals with primary iron overload and to investigate their relationship with HH. Fifty Brazilian patients with primary iron overload (transferrin saturation >50% in females and 60% in males) were selected. Subsequent bidirectional sequencing for each HFE exon was performed. The effect of HFE mutations on protein structure were analyzed by molecular dynamics simulation and free binding energy calculations. p.C282Y in homozygosis or in heterozygosis with p.H63D were the most frequent genotypic combinations associated with HH in our sample population (present in 17 individuals, 34%). Thirty-six (72.0%) out of the 50 individuals presented at least one HFE mutation. The most frequent genotype associated with HH was the homozygous p.C282Y mutation (n = 11, 22.0%). One novel mutation (p.V256I) was indentified in heterozygosis with the p.H63D mutation. In silico modeling analysis of protein behavior indicated that the p.V256I mutation does not reduce the binding affinity between HFE and beta 2-microglobulin ((beta 2M) in the same way the p.C282Y mutation does compared with the native HFE protein. In conclusion, screening of HFE through direct sequencing, as compared to p.C282Y/p.H63D genotyping, was not able to increase the molecular diagnosis yield of HH. The novel p.V256I mutation could not be implicated in the molecular basis of the HH phenotype, although its role cannot be completely excluded in HH-phenotype development. Our molecular modeling analysis can help in the analysis of novel, previously undescribed, HFE mutations. (C) 2010 Elsevier Inc. All rights reserved.

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In this study, 20 Brazilian public schools have been assessed regarding good manufacturing practices and standard sanitation operating procedures implementation. We used a checklist comprised of 10 parts ( facilities and installations, water supply, equipments and tools, pest control, waste management, personal hygiene, sanitation, storage, documentation, and training), making a total of 69 questions. The implementing modification cost to the found nonconformities was also determined so that it could work with technical data as a based decision-making prioritization. The average nonconformity percentage at schools concerning to prerequisite program was 36%, from which 66% of them own inadequate installations, 65% waste management, 44% regarding documentation, and 35% water supply and sanitation. The initial estimated cost for changing has been U.S.$24,438 and monthly investments of 1.55% on the currently needed invested values. This would result in U.S.$0.015 increase on each served meal cost over the investment replacement within a year. Thus, we have concluded that such modifications are economically feasible and will be considered on technical requirements when prerequisite program implementation priorities are established.

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In the protein folding problem, solvent-mediated forces are commonly represented by intra-chain pairwise contact energy. Although this approximation has proven to be useful in several circumstances, it is limited in some other aspects of the problem. Here we show that it is possible to achieve two models to represent the chain-solvent system. one of them with implicit and other with explicit solvent, such that both reproduce the same thermodynamic results. Firstly, lattice models treated by analytical methods, were used to show that the implicit and explicitly representation of solvent effects can be energetically equivalent only if local solvent properties are time and spatially invariant. Following, applying the same reasoning Used for the lattice models, two inter-consistent Monte Carlo off-lattice models for implicit and explicit solvent are constructed, being that now in the latter the solvent properties are allowed to fluctuate. Then, it is shown that the chain configurational evolution as well as the globule equilibrium conformation are significantly distinct for implicit and explicit solvent systems. Actually, strongly contrasting with the implicit solvent version, the explicit solvent model predicts: (i) a malleable globule, in agreement with the estimated large protein-volume fluctuations; (ii) thermal conformational stability, resembling the conformational hear resistance of globular proteins, in which radii of gyration are practically insensitive to thermal effects over a relatively wide range of temperatures; and (iii) smaller radii of gyration at higher temperatures, indicating that the chain conformational entropy in the unfolded state is significantly smaller than that estimated from random coil configurations. Finally, we comment on the meaning of these results with respect to the understanding of the folding process. (C) 2009 Elsevier B.V. All rights reserved.