Deep Learning Architectures for time of arrival detection in Acoustic Emissions Monitoring

Acoustic Emission (AE) monitoring can be used to detect the presence of damage as well as determine its location in Structural Health Monitoring (SHM) applications. Information on the time difference of the signal generated by the damage event arriving at different sensors is essential in performing localization. This makes the time of arrival (ToA) an important piece of information to retrieve from the AE signal. Generally, this is determined using statistical methods such as the Akaike Information Criterion (AIC) which is particularly prone to errors in the presence of noise. And given that the structures of interest are surrounded with harsh environments, a way to accurately estimate the arrival time in such noisy scenarios is of particular interest. In this work, two new methods are presented to estimate the arrival times of AE signals which are based on Machine Learning. Inspired by great results in the field, two models are presented which are Deep Learning models - a subset of machine learning. They are based on Convolutional Neural Network (CNN) and Capsule Neural Network (CapsNet). The primary advantage of such models is that they do not require the user to pre-define selected features but only require raw data to be given and the models establish non-linear relationships between the inputs and outputs. The performance of the models is evaluated using AE signals generated by a custom ray-tracing algorithm by propagating them on an aluminium plate and compared to AIC. It was found that the relative error in estimation on the test set was < 5% for the models compared to around 45% of AIC. The testing process was further continued by preparing an experimental setup and acquiring real AE signals to test on. Similar performances were observed where the two models not only outperform AIC by more than a magnitude in their average errors but also they were shown to be a lot more robust as compared to AIC which fails in the presence of noise.

Exploiting the environment for structural health monitoring: Strategies, algorithms, and technologies

A densely built environment is a complex system of infrastructure, nature, and people closely interconnected and interacting. Vehicles, public transport, weather action, and sports activities constitute a manifold set of excitation and degradation sources for civil structures. In this context, operators should consider different factors in a holistic approach for assessing the structural health state. Vibration-based structural health monitoring (SHM) has demonstrated great potential as a decision-supporting tool to schedule maintenance interventions. However, most excitation sources are considered an issue for practical SHM applications since traditional methods are typically based on strict assumptions on input stationarity. Last-generation low-cost sensors present limitations related to a modest sensitivity and high noise floor compared to traditional instrumentation. If these devices are used for SHM in urban scenarios, short vibration recordings collected during high-intensity events and vehicle passage may be the only available datasets with a sufficient signal-to-noise ratio. While researchers have spent efforts to mitigate the effects of short-term phenomena in vibration-based SHM, the ultimate goal of this thesis is to exploit them and obtain valuable information on the structural health state. First, this thesis proposes strategies and algorithms for smart sensors operating individually or in a distributed computing framework to identify damage-sensitive features based on instantaneous modal parameters and influence lines. Ordinary traffic and people activities become essential sources of excitation, while human-powered vehicles, instrumented with smartphones, take the role of roving sensors in crowdsourced monitoring strategies. The technical and computational apparatus is optimized using in-memory computing technologies. Moreover, identifying additional local features can be particularly useful to support the damage assessment of complex structures. Thereby, smart coatings are studied to enable the self-sensing properties of ordinary structural elements. In this context, a machine-learning-aided tomography method is proposed to interpret the data provided by a nanocomposite paint interrogated electrically.

Sensitivity and specificity of machine learning classifiers for glaucoma diagnosis using Spectral Domain OCT and standard automated perimetry

PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.

Monitoramento de parâmetros imunológicos em atletas adolescentes de basquetebol durante e após a temporada esportiva= : Monitoring of immunological parameters in adolescent basketball athletes during and after a sports season

Universidade Estadual de Campinas . Faculdade de Educação Física

A feasibility study of cell phone and landline phone interviews for monitoring of risk and protection factors for chronic diseases in Brazil

The study objective was to evaluate the feasibility of interviews by cell phone as a complement to interviews by landline to estimate risk and protection factors for chronic non-communicable diseases. Adult cell phone users were evaluated by random digit dialing. Questions asked were: age, sex, education, race, marital status, ownership of landline and cell phones, health condition, weight and height, medical diagnosis of hypertension and diabetes, physical activity, diet, binge drinking and smoking. The estimates were calculated using post-stratification weights. The cell phone interview system showed a reduced capacity to reach elderly and low educated populations. The estimates of the risk and protection factors for chronic non-communicable diseases in cell phone interviews were equal to the estimates obtained by landline phone. Eligibility, success and refusal rates using the cell phone system were lower than those of the landline system, but loss and cost were much higher, suggesting it is unsatisfactory as a complementary method in such a context.

Monitoring Millennium Development Goals in Brazilian municipalities: challenges to be met in facing up to iniquities

The Healthy Cities and Agenda 21 programs improve living and health conditions and affect social and economic determinants of health. The Millennium Development Goals (MDG) indicators can be used to assess the impact of social agendas. A data search was carried out for the period 1997 to 2006 to obtain 48 indicators proposed by the United Nations and a further 74 proposed by the technical group for the MDGin Brazil. There is a scarcity of studies concerned with assessing the MDG at the municipal level. Data from Brazilian health information systems are not always consistent or accurate for municipalities. The lack of availability and reliable data led to the substitution of some indicators. The information systems did not always provide annual data; national household surveys could not be disaggregated at the municipal level and there were also modifications on conceptual definitions over time. As a result, the project created an alternative list with 29 indicators. MDG monitoring at the local community can be important to measure the performance of actions toward improvements in quality of life and social iniquities.

Classification of breast masses using a committee machine of artificial neural networks

This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.

The Borg Scale as an Important Tool of Self-Monitoring and Self-Regulation of Exercise Prescription in Heart Failure Patients During Hydrotherapy - A Randomized Blinded Controlled Trial

Background: The Borg Scale may be a useful tool for heart failure patients to self-monitor and self-regulate exercise on land or in water (hydrotherapy) by maintaining the heart rate (HR) between the anaerobic threshold and respiratory compensation point. Methods and Results: Patients performed a cardiopulmonary exercise test to determine their anaerobic threshold/respiratory compensation points. The percentage of the mean HR during the exercise session in relation to the anaerobic threshold HR (%EHR-AT), in relation to the respiratory compensation point (%EHR-RCP), in relation to the peak HR by the exercise test (%EHR-Peak) and in relation to the maximum predicted HR (%EHR-Predicted) was calculated. Next, patients were randomized into the land or water exercise group. One blinded investigator instructed the patients in each group to exercise at a level between ""relatively easy and slightly tiring"". The mean HR throughout the 30-min exercise session was recorded. The %EHR-AT and %EHR-Predicted did not differ between the land and water exercisegroups, but they differed in the %EHR-RCP (95 +/- 7 to 86 +/- 7. P<0.001) and in the %EHR-Peak (85 +/- 8 to 78 +/- 9, P=0.007). Conclusions: Exercise guided by the Borg scale maintains the patient's HR between the anaerobic threshold and respiratory compensation point (ie, in the exercise training zone). (Circ J 2009; 73: 1871-1876)

Cyclic variability of the circumstellar disk of the Be star zeta Tauri I. Long-term monitoring observations

Context. Emission lines formed in decretion disks of Be stars often undergo long-term cyclic variations, especially in the violet-to-red (V/R) ratio of their primary components. The underlying structural and dynamical variations of the disks are only partly understood. From observations of the bright Be-shell star. Tau, the possibly broadest and longest data set illustrating the prototype of this behaviour was compiled from our own and archival observations. It comprises optical and infrared spectra, broad-band polarimetry, and interferometric observations. Aims. The dense, long-time monitoring permits a better separation of repetitive and ephemeral variations. The broad wavelength coverage includes lines formed under different physical conditions, i.e. different locations in the disk, so that the dynamics can be probed throughout much of the disk. Polarimetry and interferometry constrain the spatial structure. All together, the objective is a better understand the dynamics and life cycle of decretion disks. Methods. Standard methods of data acquisition, reduction, and analysis were applied. Results. From 3 V/R cycles between 1997 and 2008, a mean cycle length in Ha of 1400-1430 days was derived. After each minimum in V/R, the shell absorption weakens and splits into two components, leading to 3 emission peaks. This phase may make the strongest contribution to the variability in cycle length. There is no obvious connection between the V/R cycle and the 133-day orbital period of the not otherwise detected companion. V/R curves of different lines are shifted in phase. Lines formed on average closer to the central star are ahead of the others. The shell absorption lines fall into 2 categories differing in line width, ionization/excitation potential, and variability of the equivalent width. They seem to form in separate regions of the disk, probably crossing the line of sight at different times. The interferometry has resolved the continuum and the line emission in Br gamma and HeI 2.06. The phasing of the Br gamma emission shows that the photocenter of the line-emitting region lies within the plane of the disk but is offset from the continuum source. The plane of the disk is constant throughout the observed V/R cycles. The observations lay the foundation for the fully self-consistent, one-armed, disk-oscillation model developed in Paper II.

Development of a DNA-dosimeter system for monitoring the effects of solar-ultraviolet radiation

Solar radiation sustains and affects all life forms on Earth. In recent years, the increase in environmental levels of solar-UV radiation due to depletion of the stratospheric ozone layer, as a result of anthropogenic emission of destructive chemicals, has highlighted serious issues of social concern. This becomes still more dramatic in tropical and subtropical regions, where the intensity of solar radiation is higher. To better understand the impact of the harmful effects of solar-UV radiation on the DNA molecule, we developed a reliable biological monitoring system based on the exposure of plasmid DNA to artificial UV lamps and sunlight. The determination and quanti. cation of different types of UV photoproducts were performed through the use of specific DNA repair enzymes and antibodies. As expected, a significant number of CPDs and 6-4PPs was observed when the DNA-dosimeter system was exposed to increasing doses of UVB radiation. Moreover, CPDs could also be clearly detected in plasmid DNA when this system was exposed to either UVA or directly to sunlight. Interestingly, although less abundant, 6-4PPs and oxidative DNA damage were also generated after exposure to both UVA and sunlight. These results confirm the genotoxic potential of sunlight, reveal that UVA may also produce CPDs and 6-4PPs directly in naked DNA and demonstrate the applicability of a DNA-dosimeter system for monitoring the biological effects of solar-UV radiation.

Continuous monitoring of ascorbate transport through neuroblastoma cells with a ruthenium oxide hexacyanoferrate modified microelectrode

The uptake of ascorbate by neuroblastoma cells using a ruthenium oxide hexacyanoferrate (RuOHCF)-modified carbon fiber disc (CFD) microelectrode (r = 14.5 mu m) was investigated. By use of the proposed electrochemical sensor the amperometric determination of ascorbate was performed at 0.0 V in minimum essential medium (MEM, pH = 7.2) with a limit of detection of 25 mu mol L(-1). Under the optimum experimental conditions, no interference from MEM constituents and reduced glutathione (used to prevent the oxidation of ascorbate during the experiments) was noticed. The stability of the RuOHCF-modified electrode response was studied by measuring the sensitivity over an extended period of time (120 h), a decrease of around 10% being noticed at the end of the experiment. The rate of ascorbate uptake by control human neuroblastoma SH-SY5Y cells, and cells transfected with wild-type Cu,Zn-superoxide dismutase (SOD WT) or with a mutant typical of familial amyotrophic lateral sclerosis (SOD G93A), was in agreement with the level of oxidative stress in these cells. The usefulness of the RuOHCF-modified microelectrode for in vivo monitoring of ascorbate inside neuroblastoma cells was also demonstrated.

Single reaction interface flow system for chemiluminescent monitoring of mannitol based on its hydroxyl radical scavenger activity

A single reaction interface flow analysis (SIFA) system for the monitoring of mannitol in pharmaceutical formulations and human urine is presented. The developed approach takes advantage of the mannitol scavenger aptitude to inhibit the chemiluminescent reaction between luminol and myoglobin in the absence of H(2)O(2). The SIFA system facilitated the fully automation of the developed methodology, allowing the in-line reproducible handling of chemical species with a very short lifetime as is the case of the hydroxyl radical generated in the abovementioned luminol/myoglobin reaction. The proposed methodology allowed the determination of mannitol concentrations between 25 mmol L(-1) and 1 mol L(-1), with good precision (R.S.D. < 4.7%, n = 3) and a sampling frequency of about 60 h(-1). The procedure was applied to the determination of mannitol in pharmaceuticals and in human urine samples Without any pretreatment process. The results obtained for pharmaceutical formulations were statistically comparable to those provided by the reference method (R.D. < 4.6%); recoveries values obtained in the analysis of spiked urine samples (between 94.9 and 105.3% of the added amount) were also satisfactory. (C) 2008 Elsevier B.V. All rights reserved.

A new monitor for routine thermal and epithermal neutron fluence rate monitoring in k(0) INAA

The Zr-Au set for monitoring the thermal and epithermal neutron fluence rate and the epithermal spectrum parameter a is not always practicable for routine application of INAA in well-thermalized facilities. An alternative set consisting of Cr, Au and Mo provides values for the thermal neutron fluence rate, f and alpha that are not significantly different from those found via the Zr-Au method and the Cd-covered Zr-method. The IRMM standard SMELS-II was analyzed using the (Au-Cr-Mo) monitor and a good agreement was obtained. (C) 2008 Elsevier Ltd. All rights reserved.

Monitoring stress tolerance and occurrences of upper respiratory illness in basketball players by means of psychometric tools and salivary biomarkers

The aim of the study was to evaluate the possible relationships between stress tolerance, training load, banal infections and salivary parameters during 4 weeks of regular training in fifteen basketball players. The Daily Analysis of Life Demands for Athletes` questionnaire (sources and symptoms of stress) and the Wisconsin Upper Respiratory Symptom Survey were used on a weekly basis. Salivary cortisol and salivary immunoglobulin A (SIgA) were collected at the beginning (before) and after the study, and measured by enzyme-linked immunosorbent assay (ELISA). Ratings of perceived exertion (training load) were also obtained. The results from ANOVA with repeated measures showed greater training loads, number of upper respiratory tract infection episodes and negative sensation to both symptoms and sources of stress, at week 2 (p < 0.05). Significant increases in cortisol levels and decreases in SIgA secretion rate were noted (before to after). Negative sensations to symptoms of stress at week 4 were inversely and significantly correlated with SIgA secretion rate. A positive and significant relationship between sources and symptoms of stress at week 4 and cortisol levels were verified. In summary, an approach incorporating in conjunction psychometric tools and salivary biomarkers could be an efficient means of monitoring reaction to stress in sport. Copyright (C) 2010 John Wiley & Sons, Ltd.