998 resultados para Diagnostic Algorithms


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Networks are evolving toward a ubiquitous model in which heterogeneousdevices are interconnected. Cryptographic algorithms are required for developing securitysolutions that protect network activity. However, the computational and energy limitationsof network devices jeopardize the actual implementation of such mechanisms. In thispaper, we perform a wide analysis on the expenses of launching symmetric and asymmetriccryptographic algorithms, hash chain functions, elliptic curves cryptography and pairingbased cryptography on personal agendas, and compare them with the costs of basic operatingsystem functions. Results show that although cryptographic power costs are high and suchoperations shall be restricted in time, they are not the main limiting factor of the autonomyof a device.

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The paper presents some contemporary approaches to spatial environmental data analysis. The main topics are concentrated on the decision-oriented problems of environmental spatial data mining and modeling: valorization and representativity of data with the help of exploratory data analysis, spatial predictions, probabilistic and risk mapping, development and application of conditional stochastic simulation models. The innovative part of the paper presents integrated/hybrid model-machine learning (ML) residuals sequential simulations-MLRSS. The models are based on multilayer perceptron and support vector regression ML algorithms used for modeling long-range spatial trends and sequential simulations of the residuals. NIL algorithms deliver non-linear solution for the spatial non-stationary problems, which are difficult for geostatistical approach. Geostatistical tools (variography) are used to characterize performance of ML algorithms, by analyzing quality and quantity of the spatially structured information extracted from data with ML algorithms. Sequential simulations provide efficient assessment of uncertainty and spatial variability. Case study from the Chernobyl fallouts illustrates the performance of the proposed model. It is shown that probability mapping, provided by the combination of ML data driven and geostatistical model based approaches, can be efficiently used in decision-making process. (C) 2003 Elsevier Ltd. All rights reserved.

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This paper presents a Bayesian approach to the design of transmit prefiltering matrices in closed-loop schemes robust to channel estimation errors. The algorithms are derived for a multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) system. Two different optimizationcriteria are analyzed: the minimization of the mean square error and the minimization of the bit error rate. In both cases, the transmitter design is based on the singular value decomposition (SVD) of the conditional mean of the channel response, given the channel estimate. The performance of the proposed algorithms is analyzed,and their relationship with existing algorithms is indicated. As withother previously proposed solutions, the minimum bit error rate algorithmconverges to the open-loop transmission scheme for very poor CSI estimates.

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Many engineering problems that can be formulatedas constrained optimization problems result in solutionsgiven by a waterfilling structure; the classical example is thecapacity-achieving solution for a frequency-selective channel.For simple waterfilling solutions with a single waterlevel and asingle constraint (typically, a power constraint), some algorithmshave been proposed in the literature to compute the solutionsnumerically. However, some other optimization problems result insignificantly more complicated waterfilling solutions that includemultiple waterlevels and multiple constraints. For such cases, itmay still be possible to obtain practical algorithms to evaluate thesolutions numerically but only after a painstaking inspection ofthe specific waterfilling structure. In addition, a unified view ofthe different types of waterfilling solutions and the correspondingpractical algorithms is missing.The purpose of this paper is twofold. On the one hand, itoverviews the waterfilling results existing in the literature from aunified viewpoint. On the other hand, it bridges the gap betweena wide family of waterfilling solutions and their efficient implementationin practice; to be more precise, it provides a practicalalgorithm to evaluate numerically a general waterfilling solution,which includes the currently existing waterfilling solutions andothers that may possibly appear in future problems.

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In this paper, two probabilistic adaptive algorithmsfor jointly detecting active users in a DS-CDMA system arereported. The first one, which is based on the theory of hiddenMarkov models (HMM’s) and the Baum–Wech (BW) algorithm,is proposed within the CDMA scenario and compared withthe second one, which is a previously developed Viterbi-basedalgorithm. Both techniques are completely blind in the sense thatno knowledge of the signatures, channel state information, ortraining sequences is required for any user. Once convergencehas been achieved, an estimate of the signature of each userconvolved with its physical channel response (CR) and estimateddata sequences are provided. This CR estimate can be used toswitch to any decision-directed (DD) adaptation scheme. Performanceof the algorithms is verified via simulations as well as onexperimental data obtained in an underwater acoustics (UWA)environment. In both cases, performance is found to be highlysatisfactory, showing the near–far resistance of the analyzed algorithms.

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To evaluate the impact of noninvasive ventilation (NIV) algorithms available on intensive care unit ventilators on the incidence of patient-ventilator asynchrony in patients receiving NIV for acute respiratory failure. Prospective multicenter randomized cross-over study. Intensive care units in three university hospitals. Patients consecutively admitted to the ICU and treated by NIV with an ICU ventilator were included. Airway pressure, flow and surface diaphragmatic electromyography were recorded continuously during two 30-min periods, with the NIV (NIV+) or without the NIV algorithm (NIV0). Asynchrony events, the asynchrony index (AI) and a specific asynchrony index influenced by leaks (AIleaks) were determined from tracing analysis. Sixty-five patients were included. With and without the NIV algorithm, respectively, auto-triggering was present in 14 (22%) and 10 (15%) patients, ineffective breaths in 15 (23%) and 5 (8%) (p = 0.004), late cycling in 11 (17%) and 5 (8%) (p = 0.003), premature cycling in 22 (34%) and 21 (32%), and double triggering in 3 (5%) and 6 (9%). The mean number of asynchronies influenced by leaks was significantly reduced by the NIV algorithm (p < 0.05). A significant correlation was found between the magnitude of leaks and AIleaks when the NIV algorithm was not activated (p = 0.03). The global AI remained unchanged, mainly because on some ventilators with the NIV algorithm premature cycling occurs. In acute respiratory failure, NIV algorithms provided by ICU ventilators can reduce the incidence of asynchronies because of leaks, thus confirming bench test results, but some of these algorithms can generate premature cycling.

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Remote diagnostics has become very popular in marine industry. Diagnostic systems are improved all the time and the newest monitoring systems are constantly taken into operation. Most vessels are, however, rigged up by outmoded facilities, which should be updated. In this work the principles of operating of such a remote diagnostic system as the ABB's third generation remote diagnostic system (RDS) and the newest Propulsion Condition Management System (PCMS) are studied. As a result of the thesis the ways of upgrading the old systems of RDS are presented. Specifically, the work focuses on the establishment of the connection between Advant controller AC-110 from the old system and PCMS server, and in other words how to get Modbus data by OPC server.

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Electrical Impedance Tomography (EIT) is an imaging method which enables a volume conductivity map of a subject to be produced from multiple impedance measurements. It has the potential to become a portable non-invasive imaging technique of particular use in imaging brain function. Accurate numerical forward models may be used to improve image reconstruction but, until now, have employed an assumption of isotropic tissue conductivity. This may be expected to introduce inaccuracy, as body tissues, especially those such as white matter and the skull in head imaging, are highly anisotropic. The purpose of this study was, for the first time, to develop a method for incorporating anisotropy in a forward numerical model for EIT of the head and assess the resulting improvement in image quality in the case of linear reconstruction of one example of the human head. A realistic Finite Element Model (FEM) of an adult human head with segments for the scalp, skull, CSF, and brain was produced from a structural MRI. Anisotropy of the brain was estimated from a diffusion tensor-MRI of the same subject and anisotropy of the skull was approximated from the structural information. A method for incorporation of anisotropy in the forward model and its use in image reconstruction was produced. The improvement in reconstructed image quality was assessed in computer simulation by producing forward data, and then linear reconstruction using a sensitivity matrix approach. The mean boundary data difference between anisotropic and isotropic forward models for a reference conductivity was 50%. Use of the correct anisotropic FEM in image reconstruction, as opposed to an isotropic one, corrected an error of 24 mm in imaging a 10% conductivity decrease located in the hippocampus, improved localisation for conductivity changes deep in the brain and due to epilepsy by 4-17 mm, and, overall, led to a substantial improvement on image quality. This suggests that incorporation of anisotropy in numerical models used for image reconstruction is likely to improve EIT image quality.

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Miliary tuberculosis is a rare disease that is difficult to diagnose because of its non-specific presentation. It should be suspected in elderly patients who complaint of failure to thrive, unexplained fatigue and weight loss. Using a clinical situation where the diagnosis was made only at autopsy, we briefly review the epidemiology of miliary tuberculosis and propose recommendations for the diagnosis and the prophylaxis of latent tuberculosis. Finally, we discuss criteria to perform epidemiological investigations among close contacts in this situation.

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Given the low sensitivity of amoebal coculture, we developed a specific real-time PCR for the detection of Parachlamydia. The analytical sensitivity was high, and the inter- and intrarun variabilities were low. When the PCR was applied to nasopharyngeal aspirates, it was positive for six patients with bronchiolitis. Future studies should assess the role of Parachlamydia in bronchiolitis.

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The impact of depressed neonatal cerebral oxidative phosphorylation for diagnosing the severity of perinatal asphyxia was estimated by correlating the concentrations of phosphocreatine (PCr) and ATP as determined by magnetic resonance spectroscopy with the degree of hypoxic-ischemic encephalopathy (HIE) in 23 asphyxiated term neonates. Ten healthy age-matched neonates served as controls. In patients, the mean concentrations +/- SD of PCr and ATP were 0.99 +/- 0.46 mmol/L (1.6 +/- 0.2 mmol/L) and 0.99 +/- 0.35 mmol/L (1.7 +/- 0.2 mmol/L), respectively (normal values in parentheses). [PCr] and [ATP] correlated significantly with the severity of HIE (r = 0.85 and 0.9, respectively, p < 0.001), indicating that the neonatal encephalopathy is the clinical manifestation of a marred brain energy metabolism. Neurodevelopmental outcome was evaluated in 21 children at 3, 9, and 18 mo. Seven infants had multiple impairments, five were moderately handicapped, five had only mild symptoms, and four were normal. There was a significant correlation between the cerebral concentrations of PCr or ATP at birth and outcome (r = 0.8, p < 0.001) and between the degree of neonatal neurologic depression and outcome (r = 0.7). More important, the outcome of neonates with moderate HIE could better be predicted with information from quantitative 31P magnetic resonance spectroscopy than from neurologic examinations. In general, the accuracy of outcome predictability could significantly be increased by adding results from 31P magnetic resonance spectroscopy to the neonatal neurologic score, but not vice versa. No correlation with outcome was found for other perinatal risk factors, including Apgar score.

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Objective: to assess the diagnostic accuracy of different anthropometric markers in defining low aerobic fitness among adolescents. Methods: cross-sectional study on 2,331 boys and 2,366 girls aged 10 - 18 years. Body mass index (BMI) was measured using standardized methods; body fat (BF) was assessed by bioelectrical impedance. Low aerobic fitness was assessed by the 20-meter shuttle run using the FITNESSGRAMR criteria. Waist was measured in a subsample of 1,933 boys and 1,897 girls. Overweight, obesity and excess fat were defined according to the International Obesity Task Force (IOTF) or FITNESSGRAMR criteria. Results: 38.5% of boys and 46.5% of girls were considered as unfit according to the FITNESSGRAMR criteria. In boys, the area under the ROC curve (AUC) and 95% confidence interval were 66.7 (64.1 - 69.3), 67.1 (64.5 - 69.6) and 64.6 (61.9 - 67.2) for BMI, BF and waist, respectively (P<0.02). In girls, the values were 68.3 (65.9 - 70.8), 63.8 (61.3 - 66.3) and 65.9 (63.4 - 68.4), respectively (P<0.001). In boys, the sensitivity and specificity to diagnose low fitness were 13% and 99% for obesity (IOTF); 38% and 86% for overweight + obesity (IOTF); 28% and 94% for obesity (FITNESSGRAMR) and 42% and 81% for excess fat (FITNESSGRAMR). For girls, the values were 9% and 99% for obesity (IOTF); 33% and 82% for overweight + obesity (IOTF); 22% and 94% for obesity (FITNESSGRAMR) and 26% and 90% for excess fat (FITNESSGRAMR). Conclusions: BMI, not body fat or waist, should be used to define low aerobic fitness. The IOTF BMI cut-points to define obesity have a very low screening capacity and should not be used.

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Personal results are presented to illustrate the development of immunoscintigraphy for the detection of cancer over the last 12 years, from the early experimental results in nude mice grafted with human colon carcinoma to the most modern form of immunoscintigraphy applied to patients, using I123 labeled Fab fragments from monoclonal anti-CEA antibodies detected by single photon emission computerized tomography (SPECT). The first generation of immunoscintigraphy used I131 labeled, immunoadsorbent purified, polyclonal anti-CEA antibodies and planar scintigraphy, as the detection system. The second generation used I131 labeled monoclonal anti-CEA antibodies and SPECT, while the third generation employed I123 labeled fragments of monoclonal antibodies and SPECT. The improvement in the precision of tumor images with the most recent forms of immunoscintigraphy is obvious. However, we think the usefulness of immunoscintigraphy for routine cancer management has not yet been entirely demonstrated. Further prospective trials are still necessary to determine the precise clinical role of immunoscintigraphy. A case report is presented on a patient with two liver metastases from a sigmoid carcinoma, who received through the hepatic artery a therapeutic dose (100 mCi) of I131 coupled to 40 mg of a mixture of two high affinity anti-CEA monoclonal antibodies. Excellent localisation in the metastases of the I131 labeled antibodies was demonstrated by SPECT and the treatment was well tolerated. The irradiation dose to the tumor, however, was too low at 4300 rads (with 1075 rads to the normal liver and 88 rads to the bone marrow), and no evidence of tumor regression was obtained. Different approaches for increasing the irradiation dose delivered to the tumor by the antibodies are considered.