PM(10) remote sensing from geostationary SEVIRI and polar-orbiting MODIS sensors over the complex terrain of the European Alpine region

The subject of this study is to investigate the capability of spaceborne remote sensing data to predict ground concentrations of PM10 over the European Alpine region using satellite derived Aerosol Optical Depth (AOD) from the geostationary Spinning Enhanced Visible and InfraRed Imager (SEVIRI) and the polar-orbiting MODerate resolution Imaging Spectroradiometer (MODIS). The spatial and temporal resolutions of these aerosol products (10 km and 2 measurements per day for MODIS, ∼ 25 km and observation intervals of 15 min for SEVIRI) permit an evaluation of PM estimation from space at different spatial and temporal scales. Different empirical linear relationships between coincident AOD and PM10 observations are evaluated at 13 ground-based PM measurement sites, with the assumption that aerosols are vertically homogeneously distributed below the planetary Boundary Layer Height (BLH). The BLH and Relative Humidity (RH) variability are assessed, as well as their impact on the parameterization. The BLH has a strong influence on the correlation of daily and hourly time series, whilst RH effects are less clear and smaller in magnitude. Despite its lower spatial resolution and AOD accuracy, SEVIRI shows higher correlations than MODIS (rSEV∼ 0.7, rMOD∼ 0.6) with regard to daily averaged PM10. Advantages from MODIS arise only at hourly time scales in mountainous locations but lower correlations were found for both sensors at this time scale (r∼ 0.45). Moreover, the fraction of days in 2008 with at least one satellite observation was 27% for SEVIRI and 17% for MODIS. These results suggest that the frequency of observations plays an important role in PM monitoring, while higher spatial resolution does not generally improve the PM estimation. Ground-based Sun Photometer (SP) measurements are used to validate the satellite-based AOD in the study region and to discuss the impact of aerosols' micro-physical properties in the empirical models. A lower error limit of 30 to 60% in the PM10 assessment from space is estimated in the study area as a result of AOD uncertainties, variability of aerosols properties and the heterogeneity of ground measurement sites. It is concluded that SEVIRI has a similar capacity to map PM as sensors on board polar-orbiting platforms, with the advantage of a higher number of observations. However, the accuracy represents a serious limitation to the applicability of satellites for ground PM mapping, especially in mountainous areas.

Full correction for spatially distributed speed-of-sound in echo ultrasound based on measuring aberration delays via transmit beam steering

Aberrations of the acoustic wave front, caused by spatial variations of the speed-of-sound, are a main limiting factor to the diagnostic power of medical ultrasound imaging. If not accounted for, aberrations result in low resolution and increased side lobe level, over all reducing contrast in deep tissue imaging. Various techniques have been proposed for quantifying aberrations by analysing the arrival time of coherent echoes from so-called guide stars or beacons. In situations where a guide star is missing, aperture-based techniques may give ambiguous results. Moreover, they are conceptually focused on aberrators that can be approximated as a phase screen in front of the probe. We propose a novel technique, where the effect of aberration is detected in the reconstructed image as opposed to the aperture data. The varying local echo phase when changing the transmit beam steering angle directly reflects the varying arrival time of the transmit wave front. This allows sensing the angle-dependent aberration delay in a spatially resolved way, and thus aberration correction for a spatially distributed volume aberrator. In phantoms containing a cylindrical aberrator, we achieved location-independent diffraction-limited resolution as well as accurate display of echo location based on reconstructing the speed-of-sound spatially resolved. First successful volunteer results confirm the clinical potential of the proposed technique.

Distributed transpressive continental deformation: The Varto Fault Zone, eastern Turkey

The convergence between the Eurasian and Arabian plates has created a complicated structural setting in the Eastern Turkish high plateau (ETHP), particularly around the Karlıova Triple Junction (KTJ) where the Eurasian, Arabian, and Anatolian plates intersect. This region of interest includes the junction of the North Anatolian Shear Zone (NASZ) and the East Anatolian Shear Zone (EASZ), which forms the northern border of the westwardly extruding Anatolian Scholle and the western boundary of the ETHP, respectively. In this study, we focused on a poorly studied component of the KTJ, the Varto Fault Zone (VFZ), and the adjacent secondary structures, which have complex structural settings. Through integrated analyses of remote sensing and field observations, we identified a widely distributed transpressional zone where the Varto segment of the VFZ forms the most northern boundary. The other segments, namely, the Leylekdağ and Çayçatı segments, are oblique-reverse faults that are significantly defined by uplifted topography along their strikes. The measured 515 and 265 m of cumulative uplifts for Mt. Leylek and Mt. Dodan, respectively, yield a minimum uplift rate of 0.35 mm/a for the last 2.2 Ma. The multi-oriented secondary structures were mostly correlated with “the distributed strike-slip” and “the distributed transpressional” in analogue experiments. The misfits in strike of some of secondary faults between our observations and the experimental results were justified by about 20° to 25° clockwise restoration of all relevant structures that were palaeomagnetically measured to have happened since ~ 2.8 Ma ago. Our detected fault patterns and their true nature are well aligned as being part of a transpressional tectonic setting that supports previously suggested stationary triple junction models.

Application of active heat pulse method with fiber optic temperature sensing for estimation of wetting bulbs and water distribution in drip emitters.

Through the use of the Distributed Fiber Optic Temperature Measurement (DFOT) method, it is possible to measure the temperature in small intervals (on the order of centimeters) for long distances (on the order of kilometers) with a high temporal frequency and great accuracy. The heat pulse method consists of applying a known amount of heat to the soil and monitoring the temperature evolution, which is primarily dependent on the soil moisture content. The use of both methods, which is called the active heat pulse method with fiber optic temperature sensing (AHFO), allows accurate soil moisture content measurements. In order to experimentally study the wetting patterns, i.e. shape, size, and the water distribution, from a drip irrigation emitter, a soil column of 0.5 m of diameter and 0.6 m high was built. Inside the column, a fiber optic cable with a stainless steel sheath was placed forming three concentric helixes of diameters 0.2 m, 0.4 m and 0.6 m, leading to a 148 measurement point network. Before, during, and after the irrigation event, heat pulses were performed supplying electrical power of 20 W/m to the steel. The soil moisture content was measured with a capacitive sensor in one location at depths of 0.1 m, 0.2 m, 0.3 m and 0.4 m during the irrigation. It was also determined by the gravimetric method in several locations and depths before and right after the irrigation. The emitter bulb dimensions and shape evolution was satisfactorily measured during infiltration. Furthermore, some bulb's characteristics difficult to predict (e.g. preferential flow) were detected. The results point out that the AHFO is a useful tool to estimate the wetting pattern of drip irrigation emitters in soil columns and show a high potential for its use in the field.

Vertical-cavity semiconductor optical amplifiers (VCSOAs) as optical sensing elements

Semiconductor Optical Amplifiers (SOAs) have mainly found application in optical telecommunication networks for optical signal regeneration, wavelength switching or wavelength conversion. The objective of this paper is to report the use of semiconductor optical amplifiers for optical sensing taking into account their optical bistable properties. As it was previously reported, some semiconductor optical amplifiers, including Fabry-Perot and Distributed-Feedback Semiconductor Optical Amplifiers (FPSOAs and DFBSOAs), may exhibit optical bistability. The characteristics of the attained optical bistability in this kind of devices are strongly dependent on different parameters including wavelength, temperature or applied bias current and small variations lead to a change on their bistable properties. As in previous analyses for Fabry-Perot and DFB SOAs, the variations of these parameters and their possible application for optical sensing are reported in this paper for the case of the Vertical-Cavity Semiconductor Optical Amplifier (VCSOA). When using a VCSOA, the input power needed for the appearance of optical bistability is one order of magnitude lower than that needed in edge-emitting devices. This feature, added to the low manufacturing costs of VCSOAs and the ease to integrate them in 2-D arrays, makes the VCSOA a very promising device for its potential use in optical sensing applications.

Cooperative Multi-robot Patrolling: A study of distributed approaches based on mathematical models of game theory to protect infrastructures

El principio de Teoría de Juegos permite desarrollar modelos estocásticos de patrullaje multi-robot para proteger infraestructuras criticas. La protección de infraestructuras criticas representa un gran reto para los países al rededor del mundo, principalmente después de los ataques terroristas llevados a cabo la década pasada. En este documento el termino infraestructura hace referencia a aeropuertos, plantas nucleares u otros instalaciones. El problema de patrullaje se define como la actividad de patrullar un entorno determinado para monitorear cualquier actividad o sensar algunas variables ambientales. En esta actividad, un grupo de robots debe visitar un conjunto de puntos de interés definidos en un entorno en intervalos de tiempo irregulares con propósitos de seguridad. Los modelos de partullaje multi-robot son utilizados para resolver este problema. Hasta el momento existen trabajos que resuelven este problema utilizando diversos principios matemáticos. Los modelos de patrullaje multi-robot desarrollados en esos trabajos representan un gran avance en este campo de investigación. Sin embargo, los modelos con los mejores resultados no son viables para aplicaciones de seguridad debido a su naturaleza centralizada y determinista. Esta tesis presenta cinco modelos de patrullaje multi-robot distribuidos e impredecibles basados en modelos matemáticos de aprendizaje de Teoría de Juegos. El objetivo del desarrollo de estos modelos está en resolver los inconvenientes presentes en trabajos preliminares. Con esta finalidad, el problema de patrullaje multi-robot se formuló utilizando conceptos de Teoría de Grafos, en la cual se definieron varios juegos en cada vértice de un grafo. Los modelos de patrullaje multi-robot desarrollados en este trabajo de investigación se han validado y comparado con los mejores modelos disponibles en la literatura. Para llevar a cabo tanto la validación como la comparación se ha utilizado un simulador de patrullaje y un grupo de robots reales. Los resultados experimentales muestran que los modelos de patrullaje desarrollados en este trabajo de investigación trabajan mejor que modelos de trabajos previos en el 80% de 150 casos de estudio. Además de esto, estos modelos cuentan con varias características importantes tales como distribución, robustez, escalabilidad y dinamismo. Los avances logrados con este trabajo de investigación dan evidencia del potencial de Teoría de Juegos para desarrollar modelos de patrullaje útiles para proteger infraestructuras. ABSTRACT Game theory principle allows to developing stochastic multi-robot patrolling models to protect critical infrastructures. Critical infrastructures protection is a great concern for countries around the world, mainly due to terrorist attacks in the last decade. In this document, the term infrastructures includes airports, nuclear power plants, and many other facilities. The patrolling problem is defined as the activity of traversing a given environment to monitoring any activity or sensing some environmental variables If this activity were performed by a fleet of robots, they would have to visit some places of interest of an environment at irregular intervals of time for security purposes. This problem is solved using multi-robot patrolling models. To date, literature works have been solved this problem applying various mathematical principles.The multi-robot patrolling models developed in those works represent great advances in this field. However, the models that obtain the best results are unfeasible for security applications due to their centralized and predictable nature. This thesis presents five distributed and unpredictable multi-robot patrolling models based on mathematical learning models derived from Game Theory. These multi-robot patrolling models aim at overcoming the disadvantages of previous work. To this end, the multi-robot patrolling problem was formulated using concepts of Graph Theory to represent the environment. Several normal-form games were defined at each vertex of a graph in this formulation. The multi-robot patrolling models developed in this research work have been validated and compared with best ranked multi-robot patrolling models in the literature. Both validation and comparison were preformed by using both a patrolling simulator and real robots. Experimental results show that the multirobot patrolling models developed in this research work improve previous ones in as many as 80% of 150 cases of study. Moreover, these multi-robot patrolling models rely on several features to highlight in security applications such as distribution, robustness, scalability, and dynamism. The achievements obtained in this research work validate the potential of Game Theory to develop patrolling models to protect infrastructures.

Pseudo-random single photon counting for space-borne atmospheric sensing applications

The ability to accurately observe the Earth's carbon cycles from space gives scientists an important tool to analyze climate change. Current space-borne Integrated-Path Differential Absorption (IPDA) Iidar concepts have the potential to meet this need. They are mainly based on the pulsed time-offlight principle, in which two high energy pulses of different wavelengths interrogate the atmosphere for its transmission properties and are backscattered by the ground. In this paper, feasibility study results of a Pseudo-Random Single Photon Counting (PRSPC) IPDA lidar are reported. The proposed approach replaces the high energy pulsed source (e.g. a solidstate laser), with a semiconductor laser in CW operation with a similar average power of a few Watts, benefiting from better efficiency and reliability. The auto-correlation property of Pseudo-Random Binary Sequence (PRBS) and temporal shifting of the codes can be utilized to transmit both wavelengths simultaneously, avoiding the beam misalignment problem experienced by pulsed techniques. The envelope signal to noise ratio has been analyzed, and various system parameters have been selected. By restricting the telescopes field-of-view, the dominant noise source of ambient light can be suppressed, and in addition with a low noise single photon counting detector, a retrieval precision of 1.5 ppm over 50 km along-track averaging could be attained. We also describe preliminary experimental results involving a negative feedback Indium Gallium Arsenide (InGaAs) single photon avalanche photodiode and a low power Distributed Feedback laser diode modulated with PRBS driven acoustic optical modulator. The results demonstrate that higher detector saturation count rates will be needed for use in future spacebourne missions but measurement linearity and precision should meet the stringent requirements set out by future Earthobserving missions.

Self-sensing properties of alkali activated blast furnace slag (BFS) composites reinforced with carbon fibers

In recent years, several researchers have shown the good performance of alkali activated slag cement and concretes. Besides their good mechanical properties and durability, this type of cement is a good alternative to Portland cements if sustainability is considered. Moreover, multifunctional cement composites have been developed in the last decades for their functional applications (self-sensing, EMI shielding, self-heating, etc.). In this study, the strain and damage sensing possible application of carbon fiber reinforced alkali activated slag pastes has been evaluated. Cement pastes with 0, 0.29 and 0.58 vol % carbon fiber addition were prepared. Both carbon fiber dosages showed sensing properties. For strain sensing, function gage factors of up to 661 were calculated for compressive cycles. Furthermore, all composites with carbon fibers suffered a sudden increase in their resistivity when internal damages began, prior to any external signal of damage. Hence, this material may be suitable as strain or damage sensor.

3D visual sensing of human hand for remote operation of a robotic hand

New low cost sensors and open free libraries for 3D image processing are making important advances in robot vision applications possible, such as three-dimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a novel method for recognizing and tracking the fingers of a human hand is presented. This method is based on point clouds from range images captured by a RGBD sensor. It works in real time and it does not require visual marks, camera calibration or previous knowledge of the environment. Moreover, it works successfully even when multiple objects appear in the scene or when the ambient light is changed. Furthermore, this method was designed to develop a human interface to control domestic or industrial devices, remotely. In this paper, the method was tested by operating a robotic hand. Firstly, the human hand was recognized and the fingers were detected. Secondly, the movement of the fingers was analysed and mapped to be imitated by a robotic hand.

S. 2297, the Land Remote Sensing Policy Act of 1992 : hearing before the Subcommittee on Science, Technology, and Space of the Committee on Commerce, Science, and Transportation, United States Senate, One Hundred Second Congress, second session, May 6, 1992.

Shipping list no.: 93-0028-P.

Combining spatially distributed predictions from neural networks

In this report we discuss the problem of combining spatially-distributed predictions from neural networks. An example of this problem is the prediction of a wind vector-field from remote-sensing data by combining bottom-up predictions (wind vector predictions on a pixel-by-pixel basis) with prior knowledge about wind-field configurations. This task can be achieved using the scaled-likelihood method, which has been used by Morgan and Bourlard (1995) and Smyth (1994), in the context of Hidden Markov modelling

Recent advances in fibre grating devices and their sensing applications

Over the last twenty years, we have been continuously seeing R&D efforts and activities in developing optical fibre grating devices and technologies and exploring their applications for telecommunications, optical signal processing and smart sensing, and recently for medical care and biophotonics. In addition, we have also witnessed successful commercialisation of these R&Ds, especially in the area of fibre Bragg grating (FBG) based distributed sensor network systems and technologies for engineering structure monitoring in industrial sectors such as oil, energy and civil engineering. Despite countless published reports and papers and commercial realisation, we are still seeing significant and novel research activities in this area. This invited paper will give an overview on recent advances in fibre grating devices and their sensing applications with a focus on novel fibre gratings and their functions and grating structures in speciality fibres. The most recent developments in (i) femtosecond inscription for microfluidic/grating devices, (2) tilted grating based novel polarisation devices and (3) dual-peak long-period grating based DNA hybridisation sensors will be discussed.

Distributed temperature sensor based on Brillouin loss in an optical fibre for transient threshold monitoring

A distributed temperature sensor for transient threshold monitoring with a 22 km sensing length, based on the Brillouin loss in standard communications fibre, is demonstrated. The system can be used for real-time monitoring of a preset temperature threshold. Good S/N ratios were achieved with only 8–16 sample averages giving a response time of 2 to 4 s with a temperature uncertainty of ±1 °C.

22km distributed strain sensor using Brillouin loss in an optical fibre

A novel distributed strain sensor is presented utilizing the strain dependence of the frequency at which the Brillouin loss is maximized in the interaction between a cw laser and a pulsed laser. A strain resolution of 20 µ with a spatial resolution of 5 m has been achieved with a 22 km sensing length.

Combined distributed temperature and strain sensor based on Brillouin loss in an optical fiber

We present a novel distributed sensor that utilizes the temperature and strain dependence of the frequency at which the Brillouin loss is maximized in the interaction between a cw laser and a pulsed laser. With a 22-km sensing length, a strain resolution of 20 µ? and a temperature resolution of 2°C have been achieved with a spatial resolution of 5 m.