965 resultados para Underwater bio-acoustic event detection
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This paper makes a comparative analysis of results produced by the application of two techniques for the detection and segmentation of bodies in motion captured in images sequence, namely: 1) technique based on the temporal average of the values of each pixel recorded in N consecutive image frames and, 2) technique based on historical values associated with pixels recorded in different frames of an image sequence.
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An ability to detect and quantify protein molecules, harbingers of specific pathologies, potentially underpins both early disease diagnosis and an assessment of treatment efficacy. However, the specific detection of a particular protein biomarker in a complex environment is by no means an easy task and requires a progressive improvement in sensor technology. The high surface area, volume, electrical conductance, atomic level thickness and apparent biocompatibility of graphene makes it potentially an exceedingly powerful transducer of biorecognition events; the demands of its application in biosensing, and progress to date are reviewed herein.
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In water distribution systems, old metallic pipes have been replaced by plastic pipes due to their deterioration over time. Although acoustic methods are effective in finding leaks in metallic pipes, they have been found to be problematic when applied to plastic pipes due to the high damping within the pipe wall and the surrounding medium. This is responsible for the leak signal not traveling long distances. Moreover, the leak energy in plastic pipes is generally located at a narrow frequency range located at low frequencies. However, the presence of resonances can narrow even more this frequency range. In order to minimise the influence of background noise and resonances on the calculation of the time delay estimate, band-pass filters are often used to supress undesirable frequency components of the noise. The objective of this paper is to investigate the influence of resonances in the pipe system (pipe, valves, connections and hydrants), on the time delay estimate calculated using acoustic signals. Analytical models and actual leak data collected in a bespoke rig located in the United Kingdom are used to investigate this feature.
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Walking on irregular surfaces and in the presence of unexpected events is a challenging problem for bipedal machines. Up to date, their ability to cope with gait disturbances is far less successful than humans': Neither trajectory controlled robots, nor dynamic walking machines (Limit CycleWalkers) are able to handle them satisfactorily. On the contrary, humans reject gait perturbations naturally and efficiently relying on their sensory organs that, if needed, elicit a recovery action. A similar approach may be envisioned for bipedal robots and exoskeletons: An algorithm continuously observes the state of the walker and, if an unexpected event happens, triggers an adequate reaction. This paper presents a monitoring algorithm that provides immediate detection of any type of perturbation based solely on a phase representation of the normal walking of the robot. The proposed method was evaluated in a Limit Cycle Walker prototype that suffered push and trip perturbations at different moments of the gait cycle, providing 100% successful detections for the current experimental apparatus and adequately tuned parameters, with no false positives when the robot is walking unperturbed.
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[ES] La Planificación de Rutas o Caminos es un disciplina de Robótica que trata la búsqueda de caminos factibles u óptimos. Para la mayoría de vehículos y entornos, no es un problema trivial y por tanto nos encontramos con un gran diversidad de algoritmos para resolverlo, no sólo en Robótica e Inteligencia Artificial, sino también como parte de la literatura de Optimización, con Métodos Numéricos y Algoritmos Bio-inspirados, como Algoritmos Genéticos y el Algoritmo de la Colonia de Hormigas. El caso particular de escenarios de costes variables es considerablemente difícil de abordar porque el entorno en el que se mueve el vehículo cambia con el tiempo. El presente trabajo de tesis estudia este problema y propone varias soluciones prácticas para aplicaciones de Robótica Submarina.
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Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)
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[ES]El proyecto contiene módulos de simulación, procesado de datos, mapeo y localización, desarrollados en C++ utilizando ROS (Robot Operating System) y PCL (Point Cloud Library). Ha sido desarrollado bajo el proyecto de robótica submarina AVORA.Se han caracterizado el vehículo y el sensor, y se han analizado diferentes tecnologías de sensores y mapeo. Los datos pasan por tres etapas: Conversión a nube de puntos, filtrado por umbral, eliminación de puntos espureos y, opcionalmente, detección de formas. Estos datos son utilizados para construir un mapa de superficie multinivel. La otra herramienta desarrollada es un algoritmo de Punto más Cercano Iterativo (ICP) modificado, que tiene en cuenta el modo de funcionamiento del sonar de imagen utilizado.
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This study provides a comprehensive genetic overview on the endangered Italian wolf population. In particular, it focuses on two research lines. On one hand, we focalised on melanism in wolf in order to isolate a mutation related with black coat colour in canids. With several reported black individuals (an exception at European level), the Italian wolf population constituted a challenging research field posing many unanswered questions. As found in North American wolf, we reported that melanism in the Italian population is caused by a different melanocortin pathway component, the K locus, in which a beta-defensin protein acts as an alternative ligand for the Mc1r. This research project was conducted in collaboration with Prof. Gregory Barsh, Department of Genetics and Paediatrics, Stanford University. On the other hand, we performed analysis on a high number of SNPs thanks to a customized Canine microarray useful to integrate or substitute the STR markers for genotyping individuals and detecting wolf-dog hybrids. Thanks to DNA microchip technology, we obtained an impressive amount of genetic data which provides a solid base for future functional genomic studies. This study was undertaken in collaboration with Prof. Robert K. Wayne, Department of Ecology and Evolutionary Biology, University of California, Los Angeles (UCLA).
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Während in den letzten Jahren zahlreiche Biosensoren zum spezifischen Nachweis von DNA entwickelt wurden, ist die Anwendung oberflächen-sensitiver Methoden auf enzymatische Reaktionen ein vergleichsweise neues Forschungsgebiet. Trotz der hohen Empfindlichkeit und der Möglichkeit zur Echtzeit-Beobachtung molekularer Prozesse, ist die Anwendung dieser Methoden nicht etabliert, da die Enzymaktivität durch die Nähe zur Oberfläche beeinträchtigt sein kann. Im Rahmen dieser Arbeit wurde die enzymatische Verlängerung immobilisierter DNA durch eine DNA Polymerase mit Hilfe von Oberflächenplasmonen-Fluoreszenzspektroskopie (SPFS) und einer Quarzkristall-Mikrowaage (QCM) untersucht. Die Synthese von DNA wurde im Fall der QCM als Massenzuwachs detektiert, der sich im Abfall der Resonanzfrequenz des Schwingquarzes und einem Anstieg seiner Dissipationsenergie ausdrückte. Die viskoelastischen Eigenschaften der DNA-Schichten wurden bestimmt, indem die erhaltenen Daten mit einem auf Voigt basierenden Modell ausgewertet wurden. SPFS nutzt das evaneszente elektromagnetische Feld, das mit Oberflächenplasmonen einhergeht, zur oberflächen-sensitiven Anregung von Chromophoren. Auf diese Weise wurde der Einbau von Farbstoff-markierten Nukleotiden in die entstehende DNA-Sequenz als Indikator für das Voranschreiten der Reaktion ausgenutzt. Beide Meßtechniken konnten erfolgreich zum Nachweis der DNA-Synthese herangezogen werden, wobei die katalytische Aktivität des Enzyms vergleichbar zu der in Lösung gemessenen war.
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The surface electrocardiogram (ECG) is an established diagnostic tool for the detection of abnormalities in the electrical activity of the heart. The interest of the ECG, however, extends beyond the diagnostic purpose. In recent years, studies in cognitive psychophysiology have related heart rate variability (HRV) to memory performance and mental workload. The aim of this thesis was to analyze the variability of surface ECG derived rhythms, at two different time scales: the discrete-event time scale, typical of beat-related features (Objective I), and the “continuous” time scale of separated sources in the ECG (Objective II), in selected scenarios relevant to psychophysiological and clinical research, respectively. Objective I) Joint time-frequency and non-linear analysis of HRV was carried out, with the goal of assessing psychophysiological workload (PPW) in response to working memory engaging tasks. Results from fourteen healthy young subjects suggest the potential use of the proposed indices in discriminating PPW levels in response to varying memory-search task difficulty. Objective II) A novel source-cancellation method based on morphology clustering was proposed for the estimation of the atrial wavefront in atrial fibrillation (AF) from body surface potential maps. Strong direct correlation between spectral concentration (SC) of atrial wavefront and temporal variability of the spectral distribution was shown in persistent AF patients, suggesting that with higher SC, shorter observation time is required to collect spectral distribution, from which the fibrillatory rate is estimated. This could be time and cost effective in clinical decision-making. The results held for reduced leads sets, suggesting that a simplified setup could also be considered, further reducing the costs. In designing the methods of this thesis, an online signal processing approach was kept, with the goal of contributing to real-world applicability. An algorithm for automatic assessment of ambulatory ECG quality, and an automatic ECG delineation algorithm were designed and validated.
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The improvement of devices provided by Nanotechnology has put forward new classes of sensors, called bio-nanosensors, which are very promising for the detection of biochemical molecules in a large variety of applications. Their use in lab-on-a-chip could gives rise to new opportunities in many fields, from health-care and bio-warfare to environmental and high-throughput screening for pharmaceutical industry. Bio-nanosensors have great advantages in terms of cost, performance, and parallelization. Indeed, they require very low quantities of reagents and improve the overall signal-to-noise-ratio due to increase of binding signal variations vs. area and reduction of stray capacitances. Additionally, they give rise to new challenges, such as the need to design high-performance low-noise integrated electronic interfaces. This thesis is related to the design of high-performance advanced CMOS interfaces for electrochemical bio-nanosensors. The main focus of the thesis is: 1) critical analysis of noise in sensing interfaces, 2) devising new techniques for noise reduction in discrete-time approaches, 3) developing new architectures for low-noise, low-power sensing interfaces. The manuscript reports a multi-project activity focusing on low-noise design and presents two developed integrated circuits (ICs) as examples of advanced CMOS interfaces for bio-nanosensors. The first project concerns low-noise current-sensing interface for DC and transient measurements of electrophysiological signals. The focus of this research activity is on the noise optimization of the electronic interface. A new noise reduction technique has been developed so as to realize an integrated CMOS interfaces with performance comparable with state-of-the-art instrumentations. The second project intends to realize a stand-alone, high-accuracy electrochemical impedance spectroscopy interface. The system is tailored for conductivity-temperature-depth sensors in environmental applications, as well as for bio-nanosensors. It is based on a band-pass delta-sigma technique and combines low-noise performance with low-power requirements.
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Electrochemical biosensors provide an attractive means to analyze the content of a biological sample due to the direct conversion of a biological event to an electronic signal, enabling the development of cheap, small, portable and simple devices, that allow multiplex and real-time detection. At the same time nanobiotechnology is drastically revolutionizing the biosensors development and different transduction strategies exploit concepts developed in these field to simplify the analysis operations for operators and end users, offering higher specificity, higher sensitivity, higher operational stability, integrated sample treatments and shorter analysis time. The aim of this PhD work has been the application of nanobiotechnological strategies to electrochemical biosensors for the detection of biological macromolecules. Specifically, one project was focused on the application of a DNA nanotechnology called hybridization chain reaction (HCR), to amplify the hybridization signal in an electrochemical DNA biosensor. Another project on which the research activity was focused concerns the development of an electrochemical biosensor based on a biological model membrane anchored to a solid surface (tBLM), for the recognition of interactions between the lipid membrane and different types of target molecules.
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The promising development in the routine nanofabrication and the increasing knowledge of the working principles of new classes of highly sensitive, label-free and possibly cost-effective bio-nanosensors for the detection of molecules in liquid environment, has rapidly increased the possibility to develop portable sensor devices that could have a great impact on many application fields, such as health-care, environment and food production, thanks to the intrinsic ability of these biosensors to detect, monitor and study events at the nanoscale. Moreover, there is a growing demand for low-cost, compact readout structures able to perform accurate preliminary tests on biosensors and/or to perform routine tests with respect to experimental conditions avoiding skilled personnel and bulky laboratory instruments. This thesis focuses on analysing, designing and testing novel implementation of bio-nanosensors in layered hybrid systems where microfluidic devices and microelectronic systems are fused in compact printed circuit board (PCB) technology. In particular the manuscript presents hybrid systems in two validating cases using nanopore and nanowire technology, demonstrating new features not covered by state of the art technologies and based on the use of two custom integrated circuits (ICs). As far as the nanopores interface system is concerned, an automatic setup has been developed for the concurrent formation of bilayer lipid membranes combined with a custom parallel readout electronic system creating a complete portable platform for nanopores or ion channels studies. On the other hand, referring to the nanowire readout hybrid interface, two systems enabling to perform parallel, real-time, complex impedance measurements based on lock-in technique, as well as impedance spectroscopy measurements have been developed. This feature enable to experimentally investigate the possibility to enrich informations on the bio-nanosensors concurrently acquiring impedance magnitude and phase thus investigating capacitive contributions of bioanalytical interactions on biosensor surface.
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Sensors are devices that have shown widespread use, from the detection of gas molecules to the tracking of chemical signals in biological cells. Single walled carbon nanotube (SWCNT) and graphene based electrodes have demonstrated to be an excellent material for the development of electrochemical biosensors as they display remarkable electronic properties and the ability to act as individual nanoelectrodes, display an excellent low-dimensional charge carrier transport, and promote surface electrocatalysis. The present work aims at the preparation and investigation of electrochemically modified SWCNT and graphene-based electrodes for applications in the field of biosensors. We initially studied SWCNT films and focused on their topography and surface composition, electrical and optical properties. Parallel to SWCNTs, graphene films were investigated. Higher resistance values were obtained in comparison with nanotubes films. The electrochemical surface modification of both electrodes was investigated following two routes (i) the electrografting of aryl diazonium salts, and (ii) the electrophylic addition of 1, 3-benzodithiolylium tetrafluoroborate (BDYT). Both the qualitative and quantitative characteristics of the modified electrode surfaces were studied such as the degree of functionalization and their surface composition. The combination of Raman, X-ray photoelectron spectroscopy, atomic force microscopy, electrochemistry and other techniques, has demonstrated that selected precursors could be covalently anchored to the nanotubes and graphene-based electrode surfaces through novel carbon-carbon formation.
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Autism Spectrum Disorders (ASDs) describe a set of neurodevelopmental disorders. ASD represents a significant public health problem. Currently, ASDs are not diagnosed before the 2nd year of life but an early identification of ASDs would be crucial as interventions are much more effective than specific therapies starting in later childhood. To this aim, cheap an contact-less automatic approaches recently aroused great clinical interest. Among them, the cry and the movements of the newborn, both involving the central nervous system, are proposed as possible indicators of neurological disorders. This PhD work is a first step towards solving this challenging problem. An integrated system is presented enabling the recording of audio (crying) and video (movements) data of the newborn, their automatic analysis with innovative techniques for the extraction of clinically relevant parameters and their classification with data mining techniques. New robust algorithms were developed for the selection of the voiced parts of the cry signal, the estimation of acoustic parameters based on the wavelet transform and the analysis of the infant’s general movements (GMs) through a new body model for segmentation and 2D reconstruction. In addition to a thorough literature review this thesis presents the state of the art on these topics that shows that no studies exist concerning normative ranges for newborn infant cry in the first 6 months of life nor the correlation between cry and movements. Through the new automatic methods a population of control infants (“low-risk”, LR) was compared to a group of “high-risk” (HR) infants, i.e. siblings of children already diagnosed with ASD. A subset of LR infants clinically diagnosed as newborns with Typical Development (TD) and one affected by ASD were compared. The results show that the selected acoustic parameters allow good differentiation between the two groups. This result provides new perspectives both diagnostic and therapeutic.