867 resultados para Intrusion Detection System (IDS)


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The electromechanical impedance (EMI) technique has been successfully used in structural health monitoring (SHM) systems on a wide variety of structures. The basic concept of this technique is to monitor the structural integrity by exciting and sensing a piezoelectric transducer, usually a lead zirconate titanate (PZT) wafer bonded to the structure to be monitored and excited in a suitable frequency range. Because of the piezoelectric effect, there is a relationship between the mechanical impedance of the host structure, which is directly related to its integrity, and the electrical impedance of the PZT transducer, obtained by a ratio between the excitation and the sensing signals.This work presents a study on damage (leaks) detection using EMI based method. Tests were carried out in a rig water system built in a Hydraulic Laboratory for different leaks conditions in a metallic pipeline. Also, it was evaluated the influence of the PZT position bonded to the pipeline. The results show that leaks can effectively be detected using common metrics for damage detection such as RMSD and CCDM. Further, it was observed that the position of the PZT bonded to the pipes is an important variable and has to be controlled.

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Acoustic techniques have been used for many years to find and locate leaks in buried water distribution systems. Hydrophones and accelerometers are typically used as sensors. Although geophones could be used as well, they are not generally used for leak detection. A simple acoustic model of the pipe and the sensors has been proposed previously by some of the authors of this paper, and their model was used to explain some of the features observed in measurements. However, simultaneous measurements of a leak using all three sensor-types in controlled conditions for plastic pipes has not been reported to-date and hence they have not yet been compared directly. This paper fills that gap in knowledge. A set of measurements was made on a bespoke buried plastic water distribution pipe test rig to validate the previously reported analytical model. There is qualitative agreement between the experimental results and the model predictions in terms of the differing filtering properties of the pipe-sensor systems. A quality measure for the data is also presented, which is the ratio of the bandwidth over which the analysis is carried out divided by the centre frequency of this bandwidth. Based on this metric, the accelerometer was found to be the best sensor to use for the test rig described in this paper. However, for a system in which the distance between the sensors is large or the attenuation factor of the system is high, then it would be advantageous to use hydrophones, even though they are invasive sensors.

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This paper presents a Computer Aided Diagnosis (CAD) system that automatically classifies microcalcifications detected on digital mammograms into one of the five types proposed by Michele Le Gal, a classification scheme that allows radiologists to determine whether a breast tumor is malignant or not without the need for surgeries. The developed system uses a combination of wavelets and Artificial Neural Networks (ANN) and is executed on an Altera DE2-115 Development Kit, a kit containing a Field-Programmable Gate Array (FPGA) that allows the system to be smaller, cheaper and more energy efficient. Results have shown that the system was able to correctly classify 96.67% of test samples, which can be used as a second opinion by radiologists in breast cancer early diagnosis. (C) 2013 The Authors. Published by Elsevier B.V.

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Techniques based on signal analysis for leak detection in water supply systems typically use long pressure and/or flow data series of variable length. This paper presents the feature extraction from pressure signals and their application to the identification of changes related to the onset of a leak. Example signals were acquired from an experimental laboratory circuit, and features were extracted from temporal domain and from transformed signals. Statistical analysis of features values and a classification method were applied. It was verified the feasibility of using feature vectors for distinguish data acquired in the absence or presence of a leak.

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Interest in the electronic properties of carbon nanotubes has increased in recent years. These materials can be used in the development of electrochemical sensors for the measurement and monitoring of analytes of environmental interest, such as pharmaceuticals, dyes, and pesticides. This work describes the use of homemade screen-printed electrodes modified with multi-walled carbon nanotubes (MWCNT) for the electrochemical detection of the fungicide thiram. The electrochemical characteristics of the proposed system were evaluated using cyclic voltammetry, with investigation of the electrochemical behavior of the sensor in the presence of the analyte, and estimation of electrochemical parameters including the diffusion coefficient, electron transfer coefficient (α), and number of electrons transferred in the catalytic electro-oxidation. The sensor response was optimized using amperometry. The best sensor performance was obtained in 0.1 mol L-1 phosphate buffer solution at pH 8.0, where a detection limit of 7.9 x 10-6 mol L-1 was achieved. Finally, in order to improve the sensitivity of the sensor, square wave voltammetry (SWV) was used for thiram quantification, instead of amperometry. Using SWV, a response range for thiram from 9.9 x 10-6 to 9.1 x 10-5 mol L-1 was obtained, with a sensitivity of 30948 µA mol L-1, and limits of detection and quantification of 1.6 x 10-6 and 5.4 x 10-6 mol L-1, respectively. The applicability of this efficient new alternative methodology for thiram detection was demonstrated using analyses of enriched soil samples.

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To evaluate the influence of examiner's clinical experience on detection and treatment decision of caries lesions in primary molars. Design Three experienced dentists (Group A) and three undergraduate students (Group B) used the International Caries Detection and Assessment System (ICDAS) criteria and bitewing radiographs (BW) to perform examinations twice in 77 primary molars that presented a sound or carious occlusal surface. For the treatment decision (TD), the examiners attributed scores, analyzing the teeth in conjunction with the radiographs. The presence and the depth of lesion were validated histologically, and reproducibility was evaluated. The sensitivity, specificity, accuracy, and area under the ROC curve values were calculated for ICDAS and BW. The associations between ICDAS, BW, and TD were analyzed by means of contingency tables. Results Interexaminer agreement for ICDAS, BW, and TD were excellent for Group B and moderate for Group A. The two groups presented similar and satisfactory performance for caries lesion detection using ICDAS and BW. In the treatment decision, Group A was shown to have a less invasive approach than Group B. Conclusion The examiner's experience was not determinant for the clinical and radiographic detection of occlusal lesions in primary teeth but influenced the treatment decision of initial lesions.

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