910 resultados para Structural damage detection


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The analysis of system calls is one method employed by anomaly detection systems to recognise malicious code execution. Similarities can be drawn between this process and the behaviour of certain cells belonging to the human immune system, and can be applied to construct an artificial immune system. A recently developed hypothesis in immunology, the Danger Theory, states that our immune system responds to the presence of intruders through sensing molecules belonging to those invaders, plus signals generated by the host indicating danger and damage. We propose the incorporation of this concept into a responsive intrusion detection system, where behavioural information of the system and running processes is combined with information regarding individual system calls.

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Poultry colibacillosis due to Avian Pathogenic Escherichia coli (APEC) is responsible for several extra-intestinal pathological conditions, leading to serious economic damage in poultry production. The most commonly associated pathologies are airsacculitis, colisepticemia, and cellulitis in broiler chickens, and salpingitis and peritonitis in broiler breeders. In this work a total of 66 strains isolated from dead broiler breeders affected with colibacillosis and 61 strains from healthy broilers were studied. Strains from broiler breeders were typified with serogroups O2, O18, and O78, which are mainly associated with disease. The serogroup O78 was the most prevalent (58%). All the strains were checked for the presence of 11 virulence genes: 1) arginine succinyltransferase A (astA); ii) E. coli hemeutilization protein A (chuA); iii) colicin V A/B (cvaA/B); iv) fimbriae mannose-binding type 1 (fimC); v) ferric yersiniabactin uptake A (fyuA); vi) iron-repressible high-molecular-weight proteins 2 (irp2); vii) increased serum survival (iss); viii) iron-uptake systems of E. coli D (iucD); ix) pielonefritis associated to pili C (papC); x) temperature sensitive haemaglutinin (tsh), and xi) vacuolating autotransporter toxin (vat), by Multiplex-PCR. The results showed that all genes are present in both commensal and pathogenic E. coli strains. The iron uptake-related genes and the serum survival gene were more prevalent among APEC. The adhesin genes, except tsh, and the toxin genes, except astA, were also more prevalent among APEC isolates. Except for astA and tsh, APEC strains harbored the majority of the virulence-associated genes studied and fimC was the most prevalent gene, detected in 96.97 and 88.52% of APEC and AFEC strains, respectively. Possession of more than one iron transport system seems to play an important role on APEC survival.

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Chemical pollution by pesticides has been identified as a possible contributing factor to the massive mortality outbreaks observed in Crassostrea gigas for several years. A previous study demonstrated the vertical transmission of DNA damage by subjecting oyster genitors to the herbicide diuron at environmental concentrations during gametogenesis. This trans-generational effect occurs through damage to genitor-exposed gametes, as measured by the comet-assay. The presence of DNA damage in gametes could be linked to the formation of DNA damage in other germ cells. In order to explore this question, the levels and cell distribution of the oxidized base lesion 8-oxodGuo were studied in the gonads of exposed genitors. High-performance liquid chromatography coupled with UV and electrochemical detection analysis showed an increase in 8-oxodGuo levels in both male and female gonads after exposure to diuron. Immunohistochemistry analysis showed the presence of 8-oxodGuo at all stages of male germ cells, from early to mature stages. Conversely, the oxidized base was only present in early germ cell stages in female gonads. These results indicate that male and female genitors underwent oxidative stress following exposure to diuron, resulting in DNA oxidation in both early germ cells and gametes, such as spermatozoa, which could explain the transmission of diuron-induced DNA damage to offspring. Furthermore, immunostaining of early germ cells seems indicates that damages caused by exposure to diuron on germ line not only affect the current sexual cycle but also could affect future gametogenesis.

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The analysis of system calls is one method employed by anomaly detection systems to recognise malicious code execution. Similarities can be drawn between this process and the behaviour of certain cells belonging to the human immune system, and can be applied to construct an artificial immune system. A recently developed hypothesis in immunology, the Danger Theory, states that our immune system responds to the presence of intruders through sensing molecules belonging to those invaders, plus signals generated by the host indicating danger and damage. We propose the incorporation of this concept into a responsive intrusion detection system, where behavioural information of the system and running processes is combined with information regarding individual system calls.

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Fiber reinforced composite tanks provide a promising method of storage for liquid oxygen and hydrogen for aerospace applications. The inherent thermal fatigue of these vessels leads to the formation of microcracks, which allow gas phase leakage across the tank walls. In this dissertation, self-healing functionality is imparted to a structural composite to effectively seal microcracks induced by both mechanical and thermal loading cycles. Two different microencapsulated healing chemistries are investigated in woven glass fiber/epoxy and uni-weave carbon fiber/epoxy composites. Self-healing of mechanically induced damage was first studied in a room temperature cured plain weave E-glass/epoxy composite with encapsulated dicyclopentadiene (DCPD) monomer and wax protected Grubbs' catalyst healing components. A controlled amount of microcracking was introduced through cyclic indentation of opposing surfaces of the composite. The resulting damage zone was proportional to the indentation load. Healing was assessed through the use of a pressure cell apparatus to detect nitrogen flow through the thickness direction of the damaged composite. Successful healing resulted in a perfect seal, with no measurable gas flow. The effect of DCPD microcapsule size (51 um and 18 um) and concentration (0 - 12.2 wt%) on the self-sealing ability was investigated. Composite specimens with 6.5 wt% 51 um capsules sealed 67% of the time, compared to 13% for the control panels without healing components. A thermally stable, dual microcapsule healing chemistry comprised of silanol terminated poly(dimethyl siloxane) plus a crosslinking agent and a tin catalyst was employed to allow higher composite processing temperatures. The microcapsules were incorporated into a satin weave E-glass fiber/epoxy composite processed at 120C to yield a glass transition temperature of 127C. Self-sealing ability after mechanical damage was assessed for different microcapsule sizes (25 um and 42 um) and concentrations (0 - 11 vol%). Incorporating 9 vol% 42 um capsules or 11 vol% 25 um capsules into the composite matrix leads to 100% of the samples sealing. The effect of microcapsule concentration on the short beam strength, storage modulus, and glass transition temperature of the composite specimens was also investigated. The thermally stable tin catalyzed poly(dimethyl siloxane) healing chemistry was then integrated into a [0/90]s uniweave carbon fiber/epoxy composite. Thermal cycling (-196C to 35C) of these specimens lead to the formation of microcracks, over time, formed a percolating crack network from one side of the composite to the other, resulting in a gas permeable specimen. Crack damage accumulation and sample permeability was monitored with number of cycles for both self-healing and traditional non-healing composites. Crack accumulation occurred at a similar rate for all sample types tested. A 63% increase in lifetime extension was achieved for the self-healing specimens over traditional non-healing composites.

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Tese (doutorado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Civil e Ambiental, 2015.

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We evaluate the effectiveness of the Colombian Central Bank´s interventions in the foreign exchange market during the period 2000 to 2014 -- We examine the stochastic process that describes the exchange rate, with a focus on the detection of structural breaks or unit roots in the data to determine whether the Central Bank´s interventions were effective -- We find that the exchange rate can be described either by a random walk or by a trend-stationary model with multiple breaks -- In neither cases do we find any evidence that the exchange rate was affected by the Central Bank interventions

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Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

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Abstract: We present an optical sensing methodology to estimate the fatigue damage stateof structures made of carbon fiber reinforced polymer (CFRP), by measuring variations on the surface roughness. Variable amplitude loads (VAL), which represent realistic loads during aeronautical missions of fighter aircraft (FALSTAFF) have been applied to coupons until failure. Stiffness degradation and surface roughness variations have been measured during the life of the coupons obtaining a Pearson correlation of 0.75 between both variables. The data were compared with a previous study for Constant Amplitude Load (CAL) obtaining similar results. Conclusions suggest that the surface roughness measured in strategic zones is a useful technique for structural health monitoring of CFRP structures, and that it is independent of the type of load applied. Surface roughness can be measured in the field by optical techniques such as speckle, confocal perfilometers and interferometry, among others.

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This thesis is concerned with change point analysis for time series, i.e. with detection of structural breaks in time-ordered, random data. This long-standing research field regained popularity over the last few years and is still undergoing, as statistical analysis in general, a transformation to high-dimensional problems. We focus on the fundamental »change in the mean« problem and provide extensions of the classical non-parametric Darling-Erdős-type cumulative sum (CUSUM) testing and estimation theory within highdimensional Hilbert space settings. In the first part we contribute to (long run) principal component based testing methods for Hilbert space valued time series under a rather broad (abrupt, epidemic, gradual, multiple) change setting and under dependence. For the dependence structure we consider either traditional m-dependence assumptions or more recently developed m-approximability conditions which cover, e.g., MA, AR and ARCH models. We derive Gumbel and Brownian bridge type approximations of the distribution of the test statistic under the null hypothesis of no change and consistency conditions under the alternative. A new formulation of the test statistic using projections on subspaces allows us to simplify the standard proof techniques and to weaken common assumptions on the covariance structure. Furthermore, we propose to adjust the principal components by an implicit estimation of a (possible) change direction. This approach adds flexibility to projection based methods, weakens typical technical conditions and provides better consistency properties under the alternative. In the second part we contribute to estimation methods for common changes in the means of panels of Hilbert space valued time series. We analyze weighted CUSUM estimates within a recently proposed »high-dimensional low sample size (HDLSS)« framework, where the sample size is fixed but the number of panels increases. We derive sharp conditions on »pointwise asymptotic accuracy« or »uniform asymptotic accuracy« of those estimates in terms of the weighting function. Particularly, we prove that a covariance-based correction of Darling-Erdős-type CUSUM estimates is required to guarantee uniform asymptotic accuracy under moderate dependence conditions within panels and that these conditions are fulfilled, e.g., by any MA(1) time series. As a counterexample we show that for AR(1) time series, close to the non-stationary case, the dependence is too strong and uniform asymptotic accuracy cannot be ensured. Finally, we conduct simulations to demonstrate that our results are practically applicable and that our methodological suggestions are advantageous.