963 resultados para automatic target detection
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Due to the imprecise nature of biological experiments, biological data is often characterized by the presence of redundant and noisy data. This may be due to errors that occurred during data collection, such as contaminations in laboratorial samples. It is the case of gene expression data, where the equipments and tools currently used frequently produce noisy biological data. Machine Learning algorithms have been successfully used in gene expression data analysis. Although many Machine Learning algorithms can deal with noise, detecting and removing noisy instances from the training data set can help the induction of the target hypothesis. This paper evaluates the use of distance-based pre-processing techniques for noise detection in gene expression data classification problems. This evaluation analyzes the effectiveness of the techniques investigated in removing noisy data, measured by the accuracy obtained by different Machine Learning classifiers over the pre-processed data.
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The aim of this study was to optimize a PCR assay that amplifies an 843 pb fragment from the p28 gene of Ehrlichia canis and compare it with two other PCR methods used to amplify portions of the 16S rRNA and dsb genes of Ehrlichia. Blood samples were collected from dogs suspected of having a positive diagnosis for canine ehrlichiosis. Amplification of the p28 gene by PCR produced an 843-bp fragment and this assay could detect DNA from one gene copy among 1 billion cells. All positive samples detected by the p28-based PCR were also positive by the 16S rRNA nested-PCR and also by the dsb-based PCR. Among the p28-based PCR negative samples, 55.3% were co-negatives, but 27.6% were positive in 16S rRNA and dsb based PCR assays. The p28-based PCR seems to be a useful test for the molecular detection of E. canis, however improvements in this PCR sensitivity are desired, so that it can become an important alternative in the diagnosis of canine ehrlichiosis.
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This study outlines the quantification of low levels of Alicyclobacillus acidoterrestris in pure cultures, since this bacterium is not inactivated by pasteurization and may remain in industrialized foods and beverages. Electroconductive polymer-modified fluorine tin oxide (FTO) electrodes and multiple nanoparticle labels were used for biosensing. The detection of A. acidoterrestris in pure cultures was performed by reverse transcription polymerase chain reaction (RT-PCR) and the sensitivity was further increased by asymmetric nested RT-PCR using electrochemical detection for quantification of the amplicon. The quantification of nested RT-PCR products by Ag/Au-based electrochemical detection was able to detect 2 colony forming units per mL (CFU mL(-1)) of spores in pure culture and low detection and quantification limits (7.07 and 23.6 nM, respectively) were obtained for the target A. acidoterrestris on the electrochemical detection bioassay.
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Prior experience with the elevated plus maze (EPM) increases the avoidance of rodents to the open arms and impairs the anxiolytic-like effects of benzodiazepines on the traditional behaviors evaluated upon re-exposure to the maze, a phenomenon known as one-trial tolerance. Risk assessment behaviors are also sensitive to benzodiazepines. During re-exposure to the maze, these behaviors reinstate the information-processing initiated during the first experience, and the detection of danger generates stronger open-arm avoidance. The present study investigated whether the benzodiazepine midazolam alters risk assessment behaviors and Fos protein distribution associated with test and retest sessions in the EPM. Naive or maze-experienced Wistar rats received either saline or midazolam (0.5 mg/kg i.p.) and were subjected to the EPM. Midazolam caused the usual effects on exploratory behavior, increasing exploratory activity of naive rats in the open arms and producing no effects on these conventional measures in rats re-exposed to the maze. Risk assessment behaviors, however, were sensitive to the benzodiazepine during both sessions, indicating anxiolytic-like effects of the drug in both conditions. Fos immunohistochemistry showed that midazolam injections were associated with a distinct pattern of action when administered before the test or retest session, and the anterior cingulate cortex, area 1 (Cg1), was the only structure targeted by the benzodiazepine in both situations. Bilateral infusions of midazolam into the Cg1 replicated the behavioral effects of the drug injected systemically, suggesting that this area is critically involved in the anxiolytic-like effects of benzodiazepines, although the behavioral strategy adopted by the animals appears to depend on the previous knowledge of the threatening environment. (C) 2009 IBRO. Published by Elsevier Ltd. All rights reserved.
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Objectives: Pneumothorax is a frequent complication during mechanical ventilation. Electrical impedance tomography (EIT) is a noninvasive tool that allows real-time imaging of regional ventilation. The purpose of this study was to 1) identify characteristic changes in the EIT signals associated with pneumothoraces; 2) develop and fine-tune an algorithm for their automatic detection; and 3) prospectively evaluate this algorithm for its sensitivity and specificity in detecting pneumothoraces in real time. Design: Prospective controlled laboratory animal investigation. Setting: Experimental Pulmonology Laboratory of the University of Sao Paulo. Subjects: Thirty-nine anesthetized mechanically ventilated supine pigs (31.0 +/- 3.2 kg, mean +/- SD). Interventions. In a first group of 18 animals monitored by EIT, we either injected progressive amounts of air (from 20 to 500 mL) through chest tubes or applied large positive end-expiratory pressure (PEEP) increments to simulate extreme lung overdistension. This first data set was used to calibrate an EIT-based pneumothorax detection algorithm. Subsequently, we evaluated the real-time performance of the detection algorithm in 21 additional animals (with normal or preinjured lungs), submitted to multiple ventilatory interventions or traumatic punctures of the lung. Measurements and Main Results: Primary EIT relative images were acquired online (50 images/sec) and processed according to a few imaging-analysis routines running automatically and in parallel. Pneumothoraces as small as 20 mL could be detected with a sensitivity of 100% and specificity 95% and could be easily distinguished from parenchymal overdistension induced by PEEP or recruiting maneuvers, Their location was correctly identified in all cases, with a total delay of only three respiratory cycles. Conclusions. We created an EIT-based algorithm capable of detecting early signs of pneumothoraces in high-risk situations, which also identifies its location. It requires that the pneumothorax occurs or enlarges at least minimally during the monitoring period. Such detection was operator-free and in quasi real-time, opening opportunities for improving patient safety during mechanical ventilation.
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The detection of acidophilic microorganisms from mining environments by culture methods is time consuming and unreliable. Several PCR approaches were developed to amplify small-subunit rRNA sequences from the DNA of six bacterial phylotypes associated with acidic mining environments, permitting the detection of the target DNA at concentrations as low as 10 fg.
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We have developed a sensitive resonant four-wave mixing technique based on two-photon parametric four-wave mixing with the addition of a phase matched ''seeder'' field. Generation of the seeder field via the same four-wave mixing process in a high pressure cell enables automatic phase matching to be achieved in a low pressure sample cell. This arrangement facilitates sensitive detection of complex molecular spectra by simply tuning the pump laser. We demonstrate the technique with the detection of nitric oxide down to concentrations more than 4 orders of magnitude below the capability of parametric four-wave mixing alone, with an estimated detection threshold of 10(12) molecules/cm(3).
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Introduction Reduction of automatic pressure support based on a target respiratory frequency or mandatory rate ventilation (MRV) is available in the Taema-Horus ventilator for the weaning process in the intensive care unit (ICU) setting. We hypothesised that MRV is as effective as manual weaning in post-operative ICU patients. Methods There were 106 patients selected in the postoperative period in a prospective, randomised, controlled protocol. When the patients arrived at the ICU after surgery, they were randomly assigned to either: traditional weaning, consisting of the manual reduction of pressure support every 30 minutes, keeping the respiratory rate/tidal volume (RR/TV) below 80 L until 5 to 7 cmH(2)O of pressure support ventilation (PSV); or automatic weaning, referring to MRV set with a respiratory frequency target of 15 breaths per minute (the ventilator automatically decreased the PSV level by 1 cmH(2)O every four respiratory cycles, if the patient`s RR was less than 15 per minute). The primary endpoint of the study was the duration of the weaning process. Secondary endpoints were levels of pressure support, RR, TV (mL), RR/TV, positive end expiratory pressure levels, FiO(2) and SpO(2) required during the weaning process, the need for reintubation and the need for non-invasive ventilation in the 48 hours after extubation. Results In the intention to treat analysis there were no statistically significant differences between the 53 patients selected for each group regarding gender (p = 0.541), age (p = 0.585) and type of surgery (p = 0.172). Nineteen patients presented complications during the trial (4 in the PSV manual group and 15 in the MRV automatic group, p < 0.05). Nine patients in the automatic group did not adapt to the MRV mode. The mean +/- sd (standard deviation) duration of the weaning process was 221 +/- 192 for the manual group, and 271 +/- 369 minutes for the automatic group (p = 0.375). PSV levels were significantly higher in MRV compared with that of the PSV manual reduction (p < 0.05). Reintubation was not required in either group. Non-invasive ventilation was necessary for two patients, in the manual group after cardiac surgery (p = 0.51). Conclusions The duration of the automatic reduction of pressure support was similar to the manual one in the postoperative period in the ICU, but presented more complications, especially no adaptation to the MRV algorithm. Trial Registration Trial registration number: ISRCTN37456640
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In this paper, methods are presented for automatic detection of the nipple and the pectoral muscle edge in mammograms via image processing in the Radon domain. Radon-domain information was used for the detection of straight-line candidates with high gradient. The longest straight-line candidate was used to identify the pectoral muscle edge. The nipple was detected as the convergence point of breast tissue components, indicated by the largest response in the Radon domain. Percentages of false-positive (FP) and false-negative (FN) areas were determined by comparing the areas of the pectoral muscle regions delimited manually by a radiologist and by the proposed method applied to 540 mediolateral-oblique (MLO) mammographic images. The average FP and FN were 8.99% and 9.13%, respectively. In the detection of the nipple, an average error of 7.4 mm was obtained with reference to the nipple as identified by a radiologist on 1,080 mammographic images (540 MLO and 540 craniocaudal views).
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The nature of the semantic memory deficit in dementia of the Alzheimer's type (DAT) was investigated in a semantic priming task which was designed to assess both automatic and attention-induced priming effects. Ten DAT patients and 10 age-matched control subjects completed a word naming semantic priming task in which both relatedness proportion (RP) and stimulus-onset asynchrony (SOA) were varied. A clear dissociation between automatic and attentional priming effects in both groups was demonstrated; however, the DAT subjects pattern of priming deviated significantly from that of the normal controls. The DAT patients failed to produce any priming under conditions which encouraged automatic semantic processing and produced facilitation only when the RP was high. In addition, the DAT group produced hyperpriming, with significantly larger facilitation effects than the control group. These results suggest an impairment of automatic spreading activation in DAT and have implications for theories of semantic memory impairment in DAT as well as models of normal priming. (C) 2001 Academic Press.
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Laboratory diagnosis of human respiratory syncytial virus (hRSV) infections has traditionally been performed by virus isolation in cell culture and the direct fluorescent-antibody assay (DFA). Reverse transcriptase PCR (RT-PCR) is now recognized as a sensitive and specific alternative for detection of hRSV in respiratory samples. Using the LightCycler instrument, we developed a rapid RT-PCR assay for the detection of hRSV (the LC-RT-PCR) with a pair of hybridization probes that target the hRSV L gene. In the present study, 190 nasopharyngeal aspirate samples from patients with clinically recognized respiratory tract infections were examined for hRSV. The results were then compared to the results obtained with a testing algorithm that combined DFA and a culture-augmented DFA (CA-DFA) assay developed in our laboratory. hRSV was detected in 77 (41%) specimens by LC-RT-PCR and in 75 (39%) specimens by the combination of DFA and CA-DFA. All specimens that were positive by the DFA and CA-DFA testing algorithm were positive by the LC-RT-PCR. The presence of hRSV RNA in the two additional LC-RT-PCR-positive specimens was confirmed by a conventional RT-PCR method that targets the hRSV N gene. The sensitivity of LC-RT-PCR was 50 PFU/ml; and this, together with its high specificity and rapid turnaround time, makes the LC-RT-PCR suitable for the detection of hRSV in clinical specimens.
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The current level of demand by customers in the electronics industry requires the production of parts with an extremely high level of reliability and quality to ensure complete confidence on the end customer. Automatic Optical Inspection (AOI) machines have an important role in the monitoring and detection of errors during the manufacturing process for printed circuit boards. These machines present images of products with probable assembly mistakes to an operator and him decide whether the product has a real defect or if in turn this was an automated false detection. Operator training is an important aspect for obtaining a lower rate of evaluation failure by the operator and consequently a lower rate of actual defects that slip through to the following processes. The Gage R&R methodology for attributes is part of a Six Sigma strategy to examine the repeatability and reproducibility of an evaluation system, thus giving important feedback on the suitability of each operator in classifying defects. This methodology was already applied in several industry sectors and services at different processes, with excellent results in the evaluation of subjective parameters. An application for training operators of AOI machines was developed, in order to be able to check their fitness and improve future evaluation performance. This application will provide a better understanding of the specific training needs for each operator, and also to accompany the evolution of the training program for new components which in turn present additional new difficulties for the operator evaluation. The use of this application will contribute to reduce the number of defects misclassified by the operators that are passed on to the following steps in the productive process. This defect reduction will also contribute to the continuous improvement of the operator evaluation performance, which is seen as a quality management goal.
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A deteção e seguimento de pessoas tem uma grande variedade de aplicações em visão computacional. Embora tenha sido alvo de anos de investigação, continua a ser um tópico em aberto, e ainda hoje, um grande desafio a obtenção de uma abordagem que inclua simultaneamente exibilidade e precisão. O trabalho apresentado nesta dissertação desenvolve um caso de estudo sobre deteção e seguimento automático de faces humanas, em ambiente de sala de reuniões, concretizado num sistema flexível de baixo custo. O sistema proposto é baseado no sistema operativo GNU's Not Unix (GNU) linux, e é dividido em quatro etapas, a aquisição de vídeo, a deteção da face, o tracking e reorientação da posição da câmara. A aquisição consiste na captura de frames de vídeo das três câmaras Internet Protocol (IP) Sony SNC-RZ25P, instaladas na sala, através de uma rede Local Area Network (LAN) também ele já existente. Esta etapa fornece os frames de vídeo para processamento à detecção e tracking. A deteção usa o algoritmo proposto por Viola e Jones, para a identificação de objetos, baseando-se nas suas principais características, que permite efetuar a deteção de qualquer tipo de objeto (neste caso faces humanas) de uma forma genérica e em tempo real. As saídas da deteção, quando é identificado com sucesso uma face, são as coordenadas do posicionamento da face, no frame de vídeo. As coordenadas da face detetada são usadas pelo algoritmo de tracking, para a partir desse ponto seguir a face pelos frames de vídeo subsequentes. A etapa de tracking implementa o algoritmo Continuously Adaptive Mean-SHIFT (Camshift) que baseia o seu funcionamento na pesquisa num mapa de densidade de probabilidade, do seu valor máximo, através de iterações sucessivas. O retorno do algoritmo são as coordenadas da posição e orientação da face. Estas coordenadas permitem orientar o posicionamento da câmara de forma que a face esteja sempre o mais próximo possível do centro do campo de visão da câmara. Os resultados obtidos mostraram que o sistema de tracking proposto é capaz de reconhecer e seguir faces em movimento em sequências de frames de vídeo, mostrando adequabilidade para aplicação de monotorização em tempo real.
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Recent studies of mobile Web trends show the continued explosion of mobile-friend content. However, the wide number and heterogeneity of mobile devices poses several challenges for Web programmers, who want automatic delivery of context and adaptation of the content to mobile devices. Hence, the device detection phase assumes an important role in this process. In this chapter, the authors compare the most used approaches for mobile device detection. Based on this study, they present an architecture for detecting and delivering uniform m-Learning content to students in a Higher School. The authors focus mainly on the XML device capabilities repository and on the REST API Web Service for dealing with device data. In the former, the authors detail the respective capabilities schema and present a new caching approach. In the latter, they present an extension of the current API for dealing with it. Finally, the authors validate their approach by presenting the overall data and statistics collected through the Google Analytics service, in order to better understand the adherence to the mobile Web interface, its evolution over time, and the main weaknesses.
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Dissertation presented to obtain the degree of Doctor of Philosophy in Electrical Engineering, speciality on Perceptional Systems, by the Universidade Nova de Lisboa, Faculty of Sciences and Technology