O controle de perdas em sistemas de distribuição de água para abastecimento é uma preocupação constante, e uma tarefa fundamental para a solução do problema é a detecção rápida e confiável dos vazamentos que frequentemente iniciam em qualquer ponto da rede. Uma abordagem promissória é a detecção de vazamentos baseada na análise de sinais adquiridos pelo monitoramento das redes durante sua operação, e dentro dela se enquadra este trabalho. É desenvolvido um sistema de reconhecimento de padrões para análise de sinais de pressão e vazão que permite identificar se durante a aquisição do sinal aconteceu um vazamento ou não. Para a conformação desse sistema diversas técnicas são exploradas, incluindo a extração de características no domínio do tempo (energia, entropia, número de cruzamentos por zero) e na decomposição wavelet (distribuição da energia nas componentes). Também é explorado o uso de algoritmos para classificação de diferentes tipos (vizinhos mais próximos, árvore de decisão, regra de decisão, Naive Bayes, máquina de vetor suporte e rede neural artificial com funções de base radial). Sinais são adquiridos junto ao circuito hidráulico experimental, que permitiu a simulação da ocorrência de um vazamento na rede...

In this paper it is presented recent developments in the heterodyne detection holographic techniques for studding photosensitive materials. The actual state of the technique allows simultaneous and independent measurement of the refractive index and of the absorption coefficient changes in photosensitive materials and their use to self-stabilize the fringe pattern. The modeling of the measured signal together with the fringe stabilization allow the long term-fitting of the optical properties and the study the photosensitive materials close to the saturation.

Nowadays there is great interest in structural damage detection in systems using nondestructive tests. Once the failure is detected, as for instance a crack, it is possible to take providences. There are several different approaches that can be used to obtain information about the existence, location and extension of the fault in the system by non-destructive tests. Among these methodologies, one can mention different optimization techniques, as for instance classical methods, genetic algorithms, neural networks, etc. Most of these techniques, which are based on element-byelement adjustments of a finite element (FE) model, take advantage of the dynamic behavior of the model. However, in practical situations, usually, is almost impossible to obtain an accuracy model. In this paper, it is proposed an experimental technique for damage location. This technique is based on H: norm to obtain the damage location. The dynamic properties of the structure were identified using experimental data by eigensystem realization algorithm (ERA). The experimental test was carried out in a beam structure through varying the mass of an element. For the output signal was used a piezoelectric sensor. The signal of input of sine form was generated through SignalCalc® software.

INTRODUCTION: The detection of the somatosensory response (SR) is an important tool for the neurophysiological evaluation in the intra and post-operative period of some vascular and spine surgeries. Particularly, the SR identification with a maximum false positive ratio by means of Objective Response Detection (ORD) techniques could lead to a less subjective procedure. In this work a novel ORD, the Rice Detector (RD), is presented and its theoretical critical value is obtained. METHODS: The probability of detection (PD) of RD is assessed for different numbers of eletroencephalographic (EEG) signal epochs (M = 30, 60, 120, 240) and signal-to-noise ratios (-20 to 10 dB, in steps of 1 dB) by means of simulation. The simulated PD curves (PDc) are compared with the theoretical ones and with the PDc of the Magnitude-Squared Coherence (MSC), a well-known ORD technique. The performance of RD and MSC are also compared for real EEG data. The comparison is based on the DP for estimates calculated with M = 30, 60, 120 and 240 epochs. RESULTS: The results showed that the simulated PDc follow the theoretical ones and both the MSC and RD present similar performance, with slight advantage for this latter at low M-values. However, for real data, no statistical significant difference (proportion test with alpha=0.05) was found between MSC and RD. CONCLUSION: Both techniques presented mean detection rates varying from 70% to 90%...

Microscopic calcium (Ca2+) events (such as Ca2+ sparks) are an important area for study, as they help clarify the mechanism(s) underlying intracellular signaling. In the heart, Ca2+ sparks occur as a result of Ca2+ release from the sarcoendoplasmic reticulum, via ryanodine receptor channels. Measurement of Ca2+ spark properties can provide valuable information about the control of ryanodine receptor channel gating in situ, but requires high spatiotemporal resolution imaging, which produces noisy datasets that are problematic for spark detection. Automated detection algorithms may overcome visual detection bias, but missed and false-positive events can distort the distribution of measured Ca2+ spark properties. We present a sensitive and reliable method for the automated detection of Ca2+ sparks in datasets obtained using confocal line-scanning or total internal reflection fluorescence microscopy. This matched-filter detection algorithm (MFDA) employs a user-defined object, chosen to mimic Ca2+ spark properties, and the experimental dataset is searched for instances of the object. Detection certainty is provided by nonparametric statistical testing. The supplied codes can also refine the search object on the basis of those detected to further increase detection sensitivity. In comparison to a commonly used...

Psychophysical forward masking is an increase in threshold of detection of a sound (probe) when it is preceded by another sound (masker). This is reminiscent of the reduction in neuronal responses to a sound following prior stimulation. Studies in the auditory nerve and cochlear nucleus using signal detection theory techniques to derive neuronal thresholds showed that in centrally projecting neurons, increases in masked thresholds were significantly smaller than the changes measured psychophysically. Larger threshold shifts have been reported in the inferior colliculus of awake marmoset. The present study investigated the magnitude of forward masking in primary auditory cortical neurons of anaesthetised guinea-pigs. Responses of cortical neurons to unmasked and forward masked tones were measured and probe detection thresholds estimated using signal detection theory methods. Threshold shifts were larger than in the auditory nerve, cochlear nucleus and inferior colliculus. The larger threshold shifts suggest that central, and probably cortical, processes contribute to forward masking. However, although methodological differences make comparisons difficult, the threshold shifts in cortical neurons were, in contrast to subcortical nuclei...

Fetal electrocardiogram (FECG) signal contains potentially precise information that could assist clinicians in making more appropriate and timely decisions during labor. The ultimate reason for the interest in FECG signal analysis is in clinical diagnosis and biomedical applications. The extraction and detection of the FECG signal from composite abdominal signals with powerful and advance methodologies are becoming very important requirements in fetal monitoring. The purpose of this review paper is to illustrate the various methodologies and developed algorithms on FECG signal detection and analysis to provide efficient and effective ways of understanding the FECG signal and its nature for fetal monitoring. A comparative study has been carried out to show the performance and accuracy of various methods of FECG signal analysis for fetal monitoring. Finally, this paper further focused some of the hardware implementations using electrical signals for monitoring the fetal heart rate. This paper opens up a passage for researchers, physicians, and end users to advocate an excellent understanding of FECG signal and its analysis procedures for fetal heart rate monitoring system.

Optical approaches for tracking neural dynamics are of widespread interest, but a theoretical framework quantifying the physical limits of these techniques has been lacking. We formulate such a framework by using signal detection and estimation theory to obtain physical bounds on the detection of neural spikes and the estimation of their occurrence times as set by photon counting statistics (shot noise). These bounds are succinctly expressed via a discriminability index that depends on the kinetics of the optical indicator and the relative fluxes of signal and background photons. This approach facilitates quantitative evaluations of different indicators, detector technologies, and data analyses. Our treatment also provides optimal filtering techniques for optical detection of spikes. We compare various types of Ca2+ indicators and show that background photons are a chief impediment to voltage sensing. Thus, voltage indicators that change color in response to membrane depolarization may offer a key advantage over those that change intensity. We also examine fluorescence resonance energy transfer indicators and identify the regimes in which the widely used ratiometric analysis of signals is substantially suboptimal. Overall, by showing how different optical factors interact to affect signal quality...

Post-marketing detection and surveillance of potential safety hazards are crucial tasks in pharmacovigilance. To uncover such safety risks, a wide set of techniques has been developed for spontaneous reporting data and, more recently, for longitudinal data. This paper gives a broad overview of the signal detection process and introduces some types of data sources typically used. The most commonly applied signal detection algorithms are presented, covering simple frequentistic methods like the proportional reporting rate or the reporting odds ratio, more advanced Bayesian techniques for spontaneous and longitudinal data, e.g., the Bayesian Confidence Propagation Neural Network or the Multi-item Gamma-Poisson Shrinker and methods developed for longitudinal data only, like the IC temporal pattern detection. Additionally, the problem of adjustment for underlying confounding is discussed and the most common strategies to automatically identify false-positive signals are addressed. A drug monitoring technique based on Wald’s sequential probability ratio test is presented. For each method, a real-life application is given, and a wide set of literature for further reading is referenced.

Le méthotrexate (MTX), un agent anti-cancéreux fréquemment utilisé en chimiothérapie, requiert généralement un suivi thérapeutique de la médication (Therapeutic Drug Monitoring, TDM) pour surveiller son niveau sanguin chez le patient afin de maximiser son efficacité tout en limitant ses effets secondaires. Malgré la fenêtre thérapeutique étroite entre l’efficacité et la toxicité, le MTX reste, à ce jour, un des agents anti-cancéreux les plus utilisés au monde. Les techniques analytiques existantes pour le TDM du MTX sont coûteuses, requièrent temps et efforts, sans nécessairement fournir promptement les résultats dans le délai requis. Afin d’accélérer le processus de dosage du MTX en TDM, une stratégie a été proposée basée sur un essai compétitif caractérisé principalement par le couplage plasmonique d’une surface métallique et de nanoparticules d’or. Plus précisément, l’essai quantitatif exploite la réaction de compétition entre le MTX et une nanoparticule d’or fonctionnalisée avec l’acide folique (FA-AuNP) ayant une affinité pour un récepteur moléculaire, la réductase humaine de dihydrofolate (hDHFR), une enzyme associée aux maladies prolifératives. Le MTX libre mixé avec les FA-AuNP...

Induction motors are reliable and widely used in industrialised nations. However induction motors, like any other machine, will eventually fail. If the failure is not anticipated, it can result in a significant revenue loss. Therefore, there is a strong need to develop an efficient maintenance program. The most cost-effective solution is condition-based maintenance. An effective condition-based maintenance program requires an on-line condition monitoring system that can diagnose the condition of an induction motor in order to determine the types of faults and their severity while the motor is under a normal operating condition. The work in this thesis investigates the detection of stator and rotor faults (i.e. shorted turn faults, eccentricity faults, and broken rotor bar faults) using three types of sensor signals (i.e. current, leakage flux, and vibration) under different loading conditions. The work is based on an extensive series of sensor measurements taken using a number of nominally identical healthy machines (2.2 kW) and custom-modified machines (2.2 kW) with configurable stator and rotor fault settings. The thesis starts by investigating the estimation of rotor speed and rotor slot number. These two parameters are important in determining the fault frequency components that are used for detecting the stator and rotor faults. The rotor speed investigation compares four different estimation methods from the three different sensor signal types. It is found that the speed estimation techniques based on the eccentricity harmonics and the rotor frequency in the stator current...

Lamb wave based detection techniques have received a lot of attention over the past twenty years. Many of these techniques utilise a baseline data subtraction method to evaluate the presence of mechanical damage in plate and shell components. In this subtraction method, the baseline signal previously recorded for a defect-free structure is compared or subtracted with the signal during damage inspections. A significant difference between these signals, which depends on the particular application, is treated as the presence of critical damage. However, the accuracy of this method can be significantly compromised by various changes in Lamb wave propagation characteristics, which can be associated with temperature variations, degradation of material, PZT and adhesive properties. In the proposed technique, 3D Laser Vibrometery (3D LV), in conjunction with explicit FE modelling of guided waves, are utilised to compensate all variations and degradation effects, and to produce the baseline signal for the current conditions. The paper describes a virtual implementation of this technique for a simple beam structure and 1D wave propagation. Future work will be directed to implement this technology to 2D and 3D structures as well as practical case studies.; Pouria Aryan...

The recently introduced theory of Compressive Sensing (CS) enables a new method for signal recovery from incomplete information (a reduced set of “compressive” linear measurements), based on the assumption that the signal is sparse in some dictionary. Such compressive measurement schemes are desirable in practice for reducing the costs of signal acquisition, storage, and processing. However, the current CS framework considers only a certain task (signal recovery) and only in a certain model setting (sparsity). We show that compressive measurements are in fact information scalable, allowing one to answer a broad spectrum of questions about a signal when provided only with a reduced set of compressive measurements. These questions range from complete signal recovery at one extreme down to a simple binary detection decision at the other. (Questions in between include, for example, estimation and classification.) We provide techniques such as a “compressive matched filter” for answering several of these questions given the available measurements, often without needing to first reconstruct the signal. In many cases, these techniques can succeed with far fewer measurements than would be required for full signal recovery, and such techniques can also be computationally more efficient. Based on additional mathematical insight...

La concentration locale des messagers chimiques sécrétés par les cellules peut être mesurée afin de mieux comprendre les mécanismes moléculaires liés à diverses maladies, dont les métastases du cancer. De nouvelles techniques analytiques sont requises pour effectuer ces mesures locales de marqueurs biologiques à proximité des cellules. Ce mémoire présentera le développement d’une nouvelle technique basée sur la réponse plasmonique sur des leviers AFM, permettant d’étudier les réactions chimiques et biologiques à la surface des leviers grâce au phénomène de résonance des plasmons de surface (SPR), ainsi qu’à la diffusion Raman exaltée par effet de pointe (TERS). En effet, il est possible de localiser l’amplification du signal Raman à la pointe d’un levier AFM, tout comme le principe de la diffusion Raman exaltée par effet de surface (SERS) basée sur la diffusion de la lumière par des nanoparticules métalliques, et permettant une large amplification du signal Raman. La surface du levier est recouverte d’une nano-couche métallique d’or, suivi par des réactions biologiques pour l’immobilisation d’un récepteur moléculaire, créant ainsi un biocapteur sur la pointe du levier. Une détection secondaire utilisant des nanoparticules d’or conjuguées à un anticorps secondaire permet également une amplification du signal SPR et Raman lors de la détection d’antigène. Ce mémoire démontrera le développement et la validation de la détection de l’immunoglobuline G (IgG) sur la pointe du levier AFM.Dans des projets futurs...

L’amélioration de la disponibilité et de la fiabilité des éoliennes offshores et des systèmes de récupération de l’énergie des courants marins implique la nécessité de minimiser et de prévoir les opérations de maintenance. En fonctionnement à vitesse variable ou en régime transitoire, des techniques de traitement du signal avancées sont requises pour réaliser la détection et le diagnostic des défaillances à partir des courants statoriques. Dans ce contexte, plusieurs études récentes ont proposées l’utilisation de techniques temps-fréquence et temps-échelle pour le diagnostic. Les techniques les plus utilisées sont : Le spectrogramme, la transformée en ondelettes, la représentation de Wigner-Ville et la transformée de Hilbert-Huang. Cet article propose alors une étude comparative et une analyse de ces techniques pour la détection des défauts qui surviennent dans une génératrice asynchrone connectée à un réseau triphasé fonctionnant en régime nominal.; Ce travail est soutenu par Brest Métropole Océan (BMO).

One of the main objectives in pharmacovigilance is the detection of adverse drug events (ADEs) through mining of healthcare databases, such as electronic health records or administrative claims data. Although different approaches have been shown to be of great value, research is still focusing on the enhancement of signal detection to gain efficiency in further assessment and follow-up. We applied similarity-based modeling techniques, using 2D and 3D molecular structure, ADE, target, and ATC (anatomical therapeutic chemical) similarity measures, to the candidate associations selected previously in a medication-wide association study for four ADE outcomes. Our results showed an improvement in the precision when we ranked the subset of ADE candidates using similarity scorings. This method is simple, useful to strengthen or prioritize signals generated from healthcare databases, and facilitates ADE detection through the identification of the most similar drugs for which ADE information is available.

The four-planet system around GJ 581 has received attention because it has been claimed that there are possibly two additional low-mass companions as well - one of them being a planet in the middle of the stellar habitable zone. We re-analyse the available HARPS and HIRES Doppler data in an attempt to determine the false positive rate of our Bayesian data analysis techniques and to count the number of Keplerian signals in the GJ 581 data. We apply the common Lomb-Scargle periodograms and posterior sampling techniques in the Bayesian framework to estimate the number of signals in the radial velocities. We also analyse the HARPS velocities sequentially after each full observing period to compare the sensitivities and false positive rates of the two signal detection techniques. By relaxing the assumption that the radial velocity noise is white, we also demonstrate the consequences that noise correlations have on the obtained results and the significances of the signals. According to our analyses, the number of Keplerian signals favoured by the publicly available HARPS and HIRES radial velocity data of GJ 581 is four. This result relies on the sensitivity of the Bayesian statistical analysis techniques but also depends on the assumed noise model. We also show that the radial velocity noise is actually not white and that this feature has to be accounted for when analysing radial velocities in a search for low-amplitude signals corresponding to low-mass planets. ...; Comment: 11 Pages...

The study and application of signal detection techniques based on cross-correlation method for acoustic transient signals in noisy and reverberant environments are presented. These techniques are shown to provide high signal to noise ratio, good signal discernment from very close echoes and accurate detection of signal arrival time. The proposed methodology has been tested on real data collected in environments and conditions where its benefits can be shown. This work focuses on the acoustic detection applied to tasks of positioning in underwater structures and calibration such those as ANTARES and KM3NeT deep-sea neutrino telescopes, as well as, in particle detection through acoustic events for the COUPP/PICO detectors. Moreover, a method for obtaining the real amplitude of the signal in time (voltage) by using cross correlation has been developed and tested and is described in this work.; Comment: 11 pages, 11 figures. MARSS 2014

The purpose of this work is to investigate optimal methods for the detection of short duration (burst) PN-spread PSK waveforms in HF atmospheric noise. As has been shown, the optimal detector for any waveform in Gaussian background noise is a matched filter. However, HF atmospheric noise is non-Gaussian, necessitating alternate detector designs. A theoretical approach to an alternate detector design is taken, based on radar clutter modeling techniques and concepts from detection theory. The industry standard model for HF atmospheric noise is contained in COR Report 322-3 (1986). The CCLR 322 noise model is a graphical, empirical model based on observations of HF atmospheric noise taken over the course of many years at numerous worldwide receive sites. In this work, it is shown that the CQR 322 noise model may be approximated by a random process which is a member of the class of non-Gaussian random processes known as spherically-invariant random processes (SIRPs). This analytical, empirical SIRP representation is then shewn to be identical to the Hall model of impulsive phenomena (1966). In a departure from Flail (who uses his analytical representation to derive an optimal, parametric, coherent detector), the locally optimal, parametric...

In this paper, we develop a new soft-in soft-out (SISO) multiple-input multiple-output (MIMO) detection algorithm using the Markov chain Monte Carlo (MCMC) simulation techniques and study its performance when applied to a MIMO communication system. Comparison with the best MIMO detection algorithm in the current literature, the sphere decoding, show that the proposed detection algorithm can improve the gap between the present results and the capacity by as much as 2 dB.