Ethernet Telemetry for Towed Arrays

The towed array electronics is essentially a multichannel real time data acquisition system. The major challenges involved in it are the simultaneous acquisition of data from multiple channels, telemetry of the data over tow cable (several kilometres in some systems) and synchronization with the onboard receiver for accurate reconstruction. A serial protocol is best suited to transmit the data to onboard electronics since number of wires inside the tow cable is limited. The best transmission medium for data over large distances is the optical fibre. In this a two step approach towards the realization of a reliable telemetry scheme for the sensor data using standard protocols is described. The two schemes are discussed in this paper. The first scheme is for conversion of parallel, time-multiplexed multi-sensor data to Ethernet. Existing towed arrays can be upgraded to ethernet using this scheme. Here the last lap of the transmission is by Ethernet over Fibre. For the next generation of towed arrays it is required to digitize and convert the data to ethernet close to the sensor. This is the second scheme. At the heart of this design is the Analog-to-Ethernet node. In addition to a more reliable interface, this helps in easier fault detection and firmware updates in the field for the towed arrays. The design challenges and considerations for incorporating a network of embedded devices within the array are highlighted

Multisensor Modeling Underwater with Uncertain Information

This thesis develops an approach to the construction of multidimensional stochastic models for intelligent systems exploring an underwater environment. It describes methods for building models by a three- dimensional spatial decomposition of stochastic, multisensor feature vectors. New sensor information is incrementally incorporated into the model by stochastic backprojection. Error and ambiguity are explicitly accounted for by blurring a spatial projection of remote sensor data before incorporation. The stochastic models can be used to derive surface maps or other representations of the environment. The methods are demonstrated on data sets from multibeam bathymetric surveying, towed sidescan bathymetry, towed sidescan acoustic imagery, and high-resolution scanning sonar aboard a remotely operated vehicle.

Pose Determination of a Grasped Object Using Limited Sensing

This report explores methods for determining the pose of a grasped object using only limited sensor information. The problem of pose determination is to find the position of an object relative to the hand. The information is useful when grasped objects are being manipulated. The problem is hard because of the large space of grasp configurations and the large amount of uncertainty inherent in dexterous hand control. By studying limited sensing approaches, the problem's inherent constraints can be better understood. This understanding helps to show how additional sensor data can be used to make recognition methods more effective and robust.

gvSIG Sensores

El protocolo SOS (Sensor Observation Service) es una especificación OGC dentro de la iniciativa Sensor Web Enablement (SWE), que permite acceder a las observaciones y datos de sensores heterogéneos de una manera estándar. En el proyecto gvSIG se ha abierto una línea de investigación entorno a la SWE, existiendo en la actualidad dos prototipos de clientes SOS para gvSIG y gvSIG Mobile. La especificación utilizada para describir las medidas proporcionadas por sensores es Observation & Measurement (O&M) y la descripción de los metadatos de los sensores (localización. ID, fenómenos medidos, procesamiento de los datos, etc) se obtiene a partir del esquema Sensor ML. Se ha implementado el siguiente conjunto de operaciones: GetCapabilities para la descripción del servicio; DescribeSensor para acceder a los metadatos del sensor y el GetObservation para recibir las observaciones. En el caso del prototipo para gvSIG escritorio se puede acceder a los datos procedentes de los distintos grupos de sensores “offerings” añadiéndolos en el mapa como nuevas capas. Los procedimientos o sensores que están incluidos en un “offering” son presentados como elementos de la capa que se pueden cartografiar en el mapa. Se puede acceder a las observaciones (GetObservation) de estos sensores filtrando los datos por intervalo de tiempo y propiedad del fenómeno observado. La información puede ser representada sobre el mapa mediante gráficas para una mejor comprensión con la posibilidad de comparar datos de distintos sensores. En el caso del prototipo para el cliente móvil gvSIG Mobile, se ha utilizado la misma filosofía que para el cliente de escritorio, siendo cada “offering” una nueva capa. Las observaciones de los sensores pueden ser visualizadas en la pantalla del dispositivo móvil y se pueden obtener mapas temáticos,con el objetivo de facilitar la interpretación de los datos

Comparison of balloon-carried atmospheric motion sensors with Doppler lidar turbulence measurements

Magnetic sensors have been added to a standard weather balloon radiosonde package to detect motion in turbulent air. These measure the terrestrial magnetic field and return data over the standard uhf radio telemetry. Variability in the magnetic sensor data is caused by motion of the instrument package. A series of radiosonde ascents carrying these sensors has been made near a Doppler lidar measuring atmospheric properties. Lidar-retrieved quantities include vertical velocity (w) profile and its standard deviation (w). w determined over 1 h is compared with the radiosonde motion variability at the same heights. Vertical motion in the radiosonde is found to be robustly increased when w>0.75 m s−1 and is linearly proportional to w. ©2009 American Institute of Physics

A mixture of experts network structure construction algorithm for modelling and control

This paper introduces a new fast, effective and practical model structure construction algorithm for a mixture of experts network system utilising only process data. The algorithm is based on a novel forward constrained regression procedure. Given a full set of the experts as potential model bases, the structure construction algorithm, formed on the forward constrained regression procedure, selects the most significant model base one by one so as to minimise the overall system approximation error at each iteration, while the gate parameters in the mixture of experts network system are accordingly adjusted so as to satisfy the convex constraints required in the derivation of the forward constrained regression procedure. The procedure continues until a proper system model is constructed that utilises some or all of the experts. A pruning algorithm of the consequent mixture of experts network system is also derived to generate an overall parsimonious construction algorithm. Numerical examples are provided to demonstrate the effectiveness of the new algorithms. The mixture of experts network framework can be applied to a wide variety of applications ranging from multiple model controller synthesis to multi-sensor data fusion.

Prosthesis grasp reflex via peripheral nerve control: an in vitro study

Here we present an economical and versatile platform for developing motor control and sensory feedback of a prosthetic hand via in vitro mammalian peripheral nerve activity. In this study, closed-loop control of the grasp function of the prosthetic hand was achieved by stimulation of a peripheral nerve preparation in response to slip sensor data from a robotic hand, forming a rudimentary reflex action. The single degree of freedom grasp was triggered by single unit activity from motor and sensory fibers as a result of stimulation. The work presented here provides a novel, reproducible, economic, and robust platform for experimenting with neural control of prosthetic devices before attempting in vivo implementation.

Cloud-assisted body area networks: state-of-the-art and future challenges

Body area networks (BANs) are emerging as enabling technology for many human-centered application domains such as health-care, sport, fitness, wellness, ergonomics, emergency, safety, security, and sociality. A BAN, which basically consists of wireless wearable sensor nodes usually coordinated by a static or mobile device, is mainly exploited to monitor single assisted livings. Data generated by a BAN can be processed in real-time by the BAN coordinator and/or transmitted to a server-side for online/offline processing and long-term storing. A network of BANs worn by a community of people produces large amount of contextual data that require a scalable and efficient approach for elaboration and storage. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of body sensor data streams. In this paper, we motivate the introduction of Cloud-assisted BANs along with the main challenges that need to be addressed for their development and management. The current state-of-the-art is overviewed and framed according to the main requirements for effective Cloud-assisted BAN architectures. Finally, relevant open research issues in terms of efficiency, scalability, security, interoperability, prototyping, dynamic deployment and management, are discussed.

Machine learning and small robot navigation

Developing successful navigation and mapping strategies is an essential part of autonomous robot research. However, hardware limitations often make for inaccurate systems. This project serves to investigate efficient alternatives to mapping an environment, by first creating a mobile robot, and then applying machine learning to the robot and controlling systems to increase the robustness of the robot system. My mapping system consists of a semi-autonomous robot drone in communication with a stationary Linux computer system. There are learning systems running on both the robot and the more powerful Linux system. The first stage of this project was devoted to designing and building an inexpensive robot. Utilizing my prior experience from independent studies in robotics, I designed a small mobile robot that was well suited for simple navigation and mapping research. When the major components of the robot base were designed, I began to implement my design. This involved physically constructing the base of the robot, as well as researching and acquiring components such as sensors. Implementing the more complex sensors became a time-consuming task, involving much research and assistance from a variety of sources. A concurrent stage of the project involved researching and experimenting with different types of machine learning systems. I finally settled on using neural networks as the machine learning system to incorporate into my project. Neural nets can be thought of as a structure of interconnected nodes, through which information filters. The type of neural net that I chose to use is a type that requires a known set of data that serves to train the net to produce the desired output. Neural nets are particularly well suited for use with robotic systems as they can handle cases that lie at the extreme edges of the training set, such as may be produced by "noisy" sensor data. Through experimenting with available neural net code, I became familiar with the code and its function, and modified it to be more generic and reusable for multiple applications of neural nets.

Evolução tectono-estrutural do Campo de Xaréu (Sub-bacia de Mundaú, Bacia do Ceará - NE do Brasil: abordagem multiescala e pluriferramental

The Xaréu Oil Field, located in the center-southern portion of the Mundaú Sub-Basin (eastern portion of the Ceará Basin), is characterized by a main Iramework of NW-trending and NE-dipping faults. The faults in the Xaréu Oil Field, among which the Xaréu Fautt stands out, are arranged according to an extensional-listriclan, rooted on a detachment surface corresponding to the Mundaú Fault, the border fautt of Mundaú Sub-Basin. During the tectonic-structural evolution of the Xaréu Oil Field and the Mundaú Sub-Basin, the Mundaú Fault played a crucial role on the control of the geometry of both compartments. The main carbonatic unit in the Xaréu Oil Field, named the Trairí Member(Paracuru Formation of Late Aptian to Early Albian age), contains the largest oil volume in the field, concentrated in structurally-controlled accumulations. The Trairí Member is composed by a variety of carbonatic rocks (massive, bedded or laminated calcilutites, ostracodites, calcarenites and carbonatic rudites, all of them presenting variable degrees of dolomitization). The carbonatic rocks are interbedded into thick packages of black shales and marls, besides local beds of siliciclastic conglomerates, sandstones, siltnes and argillites. From the spatial association and the genetic relationships between the carbonatic and siliciclastic units, it is possible to group them in three lithofacies associations (Marginal Plain, Ramp and Lacustrine Interior) that, together, were developed in a lacustrine system associated to a marginal sabkha. Structural studies based on drill coresthat sample the Trairí Member in the Xaréu Oil Field allowed to characterize two generations of meso- to microscale structures: the D1 group presents a typical hydroplastic character, being characterized by intra/interstratal to oblique-bedding shear zones. The hydroplastic character related to these structures allowed to infer their development at an early-lithilication stage of the Trairí Member, leading to infer an Early Cretaceous age to them. The second group of structures identified in the drill cores, nominated D2 and ascribed to a Neogene age, presents a strictly brttle character, being typilied by normal faults and slickenfibers of re-crystallized clayminerals, ali olthem displaying variable orientations. Although the present faults in the Xaréu Oil Field (and, consequently, in the Mundaú Sub-Basin) were classically relerred as struetures of essentially normal displacement, the kinematics analysis of the meso-to microscaie D1 struetures in the drill cores led to deline oblique displacements (normal with a clockwise strike-slip component) to these faults, indicating a main tectonic transport to ENE. These oblique movements would be responsible for the installation of a transtensive context in the Mundaú Sub-Basin, as part of the transcurrent to translormant opening of the Atlantic Equatorial Margin. The balancing of four struetural cross-sections ofthe Xaréu Oil Field indicates that the Mundaú Fault was responsible for more than 50% of the total stretching (ß factor) registered during the Early Aptian. At the initial stages of the "rifting", during Early Aptianuntil the Holocene, the Mundaú Sub-Basin (and consequently the Xaréu Oil Fleld) accumulated a total stretching between 1.21 and 1.23; in other words, the crust in this segment of the Atlantic Equatorial Margin was subjeeted to an elongation of about 20%. From estimates of oblique displacements related to the faults, it ws possible to construct diagrams that allow the determination of stretching factors related to these displacements. Using these diagrams and assuming the sense 01 dominant teetonictransport towards ENE, it was possible to calculate the real stretching lactors related to the oblique movement 0 of the faults in the Mundaú Sub-Basin. which reached actual values between 1.28 and 1.42. ln addnion to the tectonic-structural studies in the Xaréu Oil Field, the interpretation of remote sensing products, coupled wnh characterization of terrain analogues in seleeted areas along the northern Ceará State (continental margins of the Ceará and Potiguar basins), provided addnional data and constraints about the teetonic-structural evolution of the oil lield. The work at the analogue sites was particularly effective in the recognition and mapping, in semidetail scale, several generations of struetures originated under a brittle regime. Ali the obtained information (from the Xaréu Oil Field, the remote sensor data and the terrain analogues) were jointly interpreted, culminating with the proposnion of an evolutionary model lor this segment of the Atlantic Equatorial Margin; this model that can be applied to the whole Margin, as well. This segmentof the Atlantic Equatorial Margin was delormedin an early E-W (when considered lhe present-day position of the South American Plate) transcurrent to transform regime with dextral kinematics, started Irom, at least, the Early Aptian, which left its record in several outcrops along the continental margin of the Ceará State and specilically in the Xaréu off Field. The continuous operation of the regime, through the Albian and later periods, led to the definitive separation between the South American and African plates, with the formation of oceanic lithosphere between the two continental blocks, due to the emplacement off spreading centers. This process involved the subsequent transition of the transcurrent to a translorm dextral regime, creating lhe Equatorial Atlantic Oceano With the separation between the South American and African plates already completed and the increasing separation between lhe continental masses, other tecton ic mechanisms began to act during the Cenozoic (even though the Cretaceous tectonic regime lasted until the Neogene), like an E-W compressive stress líeld (related to the spreading olthe oceanic floor along lhe M id-Atlantic Ridge and to the compression of the Andean Chain) effective Irom the Late Cretaceous, and a state of general extension olthe horizontal surface (due to the thermal uplift ofthe central portion of Borborema Province), effective during the Neogene. The overlap of these mechanisms during the Cenozoic led to the imprint of a complex tectonic framework, which apparently influenced the migration and entrapment 01 hydrocarbon in the Ceará Basin

Intercontinental transport of nitrogen oxide pollution plumes

We describe the first satellite observation of intercontinental transport of nitrogen oxides emitted by power plants, verified by simulations with a particle tracer model. The analysis of such episodes shows that anthropogenic NOx plumes may influence the atmospheric chemistry thousands of kilometers away from its origin, as well as the ocean they traverse due to nitrogen fertilization. This kind of monitoring became possible by applying an improved algorithm to extract the tropospheric fraction of NO2 from the spectral data coming from the GOME instrument.As an example we show the observation of NO2 in the time period 4-14 May, 1998, from the South African Plateau to Australia which was possible due to favourable weather conditions during that time period which availed the satellite measurement. This episode was also simulated with the Lagrangian particle dispersion model FLEXPART which uses NOx emissions taken from an inventory for industrial emissions in South Africa and is driven with analyses from the European Centre for Medium-RangeWeather Forecasts. Additionally lightning emissions were taken into account by utilizing Lightning Imaging Sensor data. Lightning was found to contribute probably not more than 25% of the resulting concentrations. Both, the measured and simulated emission plume show matching patterns while traversing the Indian Ocean to Australia and show great resemblance to the aerosol and CO2 transport observed by Piketh et al. (2000).

Magnetic images of pharmaceutical dosage forms in the human gastrointestinal tract

Oral administration with solid dosage forms is a common route in the drug therapy widely used. The drug release by the disintegration process occurs in several gastrointestinal tract (GIT) regions. AC Biosusceptometry (ACB) was originally proposal to characterize the disintegration process of tablets in vitro and in the human stomach, through changes in magnetic signals. The aim of this work was to employ a multisensor ACB system to monitoring magnetic tablets and capsules in the human GIT and to obtain the magnetic images of the disintegration process. The ACB showed accuracy to quantify the gastric residence time, the intestinal transit time and the magnetic images allowed to visualize the disintegration of magnetic formulations in the GIT. The ACB is a non-invasive, radiation free technique, completely safe and harmless to the volunteers and had demonstrated potential to evaluate pharmaceutical dosage forms in the human gastrointestinal tract. © 2005 IEEE.

Characterization of the temperature, load and damage effects using piezoelectric transducer patches based on fuzzy clustering

Structural Health Monitoring (SHM) denotes a system with the ability to detect and interpret adverse changes in a structure. One of the critical challenges for practical implementation of SHM system is the ability to detect damage under changing environmental conditions. This paper aims to characterize the temperature, load and damage effects in the sensor measurements obtained with piezoelectric transducer (PZT) patches. Data sets are collected on thin aluminum specimens under different environmental conditions and artificially induced damage states. The fuzzy clustering algorithm is used to organize the sensor measurements into a set of clusters, which can attribute the variation in sensor data due to temperature, load or any induced damage.

Progetto di reti Sensori Wireless e tecniche di Fusione Sensoriale

Ambient Intelligence (AmI) envisions a world where smart, electronic environments are aware and responsive to their context. People moving into these settings engage many computational devices and systems simultaneously even if they are not aware of their presence. AmI stems from the convergence of three key technologies: ubiquitous computing, ubiquitous communication and natural interfaces. The dependence on a large amount of fixed and mobile sensors embedded into the environment makes of Wireless Sensor Networks one of the most relevant enabling technologies for AmI. WSN are complex systems made up of a number of sensor nodes, simple devices that typically embed a low power computational unit (microcontrollers, FPGAs etc.), a wireless communication unit, one or more sensors and a some form of energy supply (either batteries or energy scavenger modules). Low-cost, low-computational power, low energy consumption and small size are characteristics that must be taken into consideration when designing and dealing with WSNs. In order to handle the large amount of data generated by a WSN several multi sensor data fusion techniques have been developed. The aim of multisensor data fusion is to combine data to achieve better accuracy and inferences than could be achieved by the use of a single sensor alone. In this dissertation we present our results in building several AmI applications suitable for a WSN implementation. The work can be divided into two main areas: Multimodal Surveillance and Activity Recognition. Novel techniques to handle data from a network of low-cost, low-power Pyroelectric InfraRed (PIR) sensors are presented. Such techniques allow the detection of the number of people moving in the environment, their direction of movement and their position. We discuss how a mesh of PIR sensors can be integrated with a video surveillance system to increase its performance in people tracking. Furthermore we embed a PIR sensor within the design of a Wireless Video Sensor Node (WVSN) to extend its lifetime. Activity recognition is a fundamental block in natural interfaces. A challenging objective is to design an activity recognition system that is able to exploit a redundant but unreliable WSN. We present our activity in building a novel activity recognition architecture for such a dynamic system. The architecture has a hierarchical structure where simple nodes performs gesture classification and a high level meta classifiers fuses a changing number of classifier outputs. We demonstrate the benefit of such architecture in terms of increased recognition performance, and fault and noise robustness. Furthermore we show how we can extend network lifetime by performing a performance-power trade-off. Smart objects can enhance user experience within smart environments. We present our work in extending the capabilities of the Smart Micrel Cube (SMCube), a smart object used as tangible interface within a tangible computing framework, through the development of a gesture recognition algorithm suitable for this limited computational power device. Finally the development of activity recognition techniques can greatly benefit from the availability of shared dataset. We report our experience in building a dataset for activity recognition. Such dataset is freely available to the scientific community for research purposes and can be used as a testbench for developing, testing and comparing different activity recognition techniques.

Efficient subsequence alignment of time series

Zeitreihen sind allgegenwärtig. Die Erfassung und Verarbeitung kontinuierlich gemessener Daten ist in allen Bereichen der Naturwissenschaften, Medizin und Finanzwelt vertreten. Das enorme Anwachsen aufgezeichneter Datenmengen, sei es durch automatisierte Monitoring-Systeme oder integrierte Sensoren, bedarf außerordentlich schneller Algorithmen in Theorie und Praxis. Infolgedessen beschäftigt sich diese Arbeit mit der effizienten Berechnung von Teilsequenzalignments. Komplexe Algorithmen wie z.B. Anomaliedetektion, Motivfabfrage oder die unüberwachte Extraktion von prototypischen Bausteinen in Zeitreihen machen exzessiven Gebrauch von diesen Alignments. Darin begründet sich der Bedarf nach schnellen Implementierungen. Diese Arbeit untergliedert sich in drei Ansätze, die sich dieser Herausforderung widmen. Das umfasst vier Alignierungsalgorithmen und ihre Parallelisierung auf CUDA-fähiger Hardware, einen Algorithmus zur Segmentierung von Datenströmen und eine einheitliche Behandlung von Liegruppen-wertigen Zeitreihen.rnrnDer erste Beitrag ist eine vollständige CUDA-Portierung der UCR-Suite, die weltführende Implementierung von Teilsequenzalignierung. Das umfasst ein neues Berechnungsschema zur Ermittlung lokaler Alignierungsgüten unter Verwendung z-normierten euklidischen Abstands, welches auf jeder parallelen Hardware mit Unterstützung für schnelle Fouriertransformation einsetzbar ist. Des Weiteren geben wir eine SIMT-verträgliche Umsetzung der Lower-Bound-Kaskade der UCR-Suite zur effizienten Berechnung lokaler Alignierungsgüten unter Dynamic Time Warping an. Beide CUDA-Implementierungen ermöglichen eine um ein bis zwei Größenordnungen schnellere Berechnung als etablierte Methoden.rnrnAls zweites untersuchen wir zwei Linearzeit-Approximierungen für das elastische Alignment von Teilsequenzen. Auf der einen Seite behandeln wir ein SIMT-verträgliches Relaxierungschema für Greedy DTW und seine effiziente CUDA-Parallelisierung. Auf der anderen Seite führen wir ein neues lokales Abstandsmaß ein, den Gliding Elastic Match (GEM), welches mit der gleichen asymptotischen Zeitkomplexität wie Greedy DTW berechnet werden kann, jedoch eine vollständige Relaxierung der Penalty-Matrix bietet. Weitere Verbesserungen umfassen Invarianz gegen Trends auf der Messachse und uniforme Skalierung auf der Zeitachse. Des Weiteren wird eine Erweiterung von GEM zur Multi-Shape-Segmentierung diskutiert und auf Bewegungsdaten evaluiert. Beide CUDA-Parallelisierung verzeichnen Laufzeitverbesserungen um bis zu zwei Größenordnungen.rnrnDie Behandlung von Zeitreihen beschränkt sich in der Literatur in der Regel auf reellwertige Messdaten. Der dritte Beitrag umfasst eine einheitliche Methode zur Behandlung von Liegruppen-wertigen Zeitreihen. Darauf aufbauend werden Distanzmaße auf der Rotationsgruppe SO(3) und auf der euklidischen Gruppe SE(3) behandelt. Des Weiteren werden speichereffiziente Darstellungen und gruppenkompatible Erweiterungen elastischer Maße diskutiert.