The application of surface second harmonic sensor to probe laser induced modification of titanium dioxide

The effects of high power pulsed laser light on a TiO2 photocatalyst have been investigated using a surface second harmonic generation (SSHG) sensor. When TiO2 is irradiated with a laser at 355mm a visible change in colour from white to dark blue crystals was observed. X-ray diffraction studies indicate that the crystal structure of the TiO2 developed a more rutile form following laser exposure.

A methodology for sensor modeling and placement optimization to support temperature monitoring

This paper presents a modeling and optimization approach for sensor placement in a building zone that supports reliable environment monitoring. © 2012 ACM.

A Soft Sensor for Viscosity Control of Polymer Extrusion

Viscosity represents a key indicator of product quality in polymer extrusion but has traditionally been difficult to measure in-process in real-time. An innovative, yet simple, solution to this problem is proposed by a Prediction-Feedback observer mechanism. A `Prediction' model based on the operating conditions generates an open-loop estimate of the melt viscosity; this estimate is used as an input to a second, `Feedback' model to predict the pressure of the system. The pressure value is compared to the actual measured melt pressure and the error used to correct the viscosity estimate. The Prediction model captures the relationship between the operating conditions and the resulting melt viscosity and as such describes the specific material behavior. The Feedback model on the other hand describes the fundamental physical relationship between viscosity and extruder pressure and is a function of the machine geometry. The resulting system yields viscosity estimates within 1% error, shows excellent disturbance rejection properties and can be directly applied to model-based control. This is of major significance to achieving higher quality and reducing waste and set-up times in the polymer extrusion industry.

A hydrogel based zinc(ii) sensor for use in fluorescent multi-well plate analysis

A polymeric hydrogel containing a photoinduced electron transfer (PET) based probe for Zn(ii) has been formulated into the wells of a 96-well plate. Upon addition of Zn(ii) ions to selected wells, the fluorescence of the gel was observed to increase in a concentration dependent manner in the 0.25-1.75 mM range. The millimolar binding constant observed for this probe is higher than that reported for other Zn(ii) probes in the literature and offers the possibility to determine the concentration of this ion in environments where the Zn(ii) concentration is high. The combination of the multi-well plate set-up with fluorescence detection offers the possibility of high-throughput screening using low sample volumes in a timely manner. To the best of our knowledge, this is the first reported example of a polymeric hydrogel sensor for zinc with capability for use in fluorescence multi-well plate assay.

Fusion of Static and Temporal Information for Threat Evaluation in Sensor Networks

In many CCTV and sensor network based intelligent surveillance systems, a number of attributes or criteria are used to individually evaluate the degree of potential threat of a suspect. The outcomes for these attributes are in general from analytical algorithms where data are often pervaded with uncertainty and incompleteness. As a result, such individual threat evaluations are often inconsistent, and individual evaluations can change as time elapses. Therefore, integrating heterogeneous threat evaluations with temporal influence to obtain a better overall evaluation is a challenging issue. So far, this issue has rarely be considered by existing event reasoning frameworks under uncertainty in sensor network based surveillance. In this paper, we first propose a weighted aggregation operator based on a set of principles that constraints the fusion of individual threat evaluations. Then, we propose a method to integrate the temporal influence on threat evaluation changes. Finally, we demonstrate the usefulness of our system with a decision support event modeling framework using an airport security surveillance scenario.

Kinetics of methylene blue (MB) photocatalyzed reduction and dark regeneration in a colorimetric oxygen sensor

Performance data for a dye based, regenerable oxygen sensor (Mills and Lawrie [1], Mills et al. [2]) are analyzed to develop useful kinetic models for sensor photoactivation (dye reduction) and dark, oxygen detection (dye oxidation). The titania loaded, thin film sensor exhibits an apparent first order photoactivation of the dye, which we demonstrate (Section 3.2 and Fig. 4) is due to a kinetic disguise of a zero order photoreaction occurring through a non-uniformly illuminated sensor film. The observed zero order, slow recovery due to dye oxidation by dioxygen (O2 detection) appears best rationalized by a model assuming a near O2-impermeable skin developing on the sensor surface as solvent is evaporatively removed following sensor film casting and curing.

Context-dependent Combination of Sensor Information in Dempster-Shafer Theory for BDI

There has been much interest in the belief–desire–intention (BDI) agent-based model for developing scalable intelligent systems, e.g. using the AgentSpeak framework. However, reasoning from sensor information in these large-scale systems remains a significant challenge. For example, agents may be faced with information from heterogeneous sources which is uncertain and incomplete, while the sources themselves may be unreliable or conflicting. In order to derive meaningful conclusions, it is important that such information be correctly modelled and combined. In this paper, we choose to model uncertain sensor information in Dempster–Shafer (DS) theory. Unfortunately, as in other uncertainty theories, simple combination strategies in DS theory are often too restrictive (losing valuable information) or too permissive (resulting in ignorance). For this reason, we investigate how a context-dependent strategy originally defined for possibility theory can be adapted to DS theory. In particular, we use the notion of largely partially maximal consistent subsets (LPMCSes) to characterise the context for when to use Dempster’s original rule of combination and for when to resort to an alternative. To guide this process, we identify existing measures of similarity and conflict for finding LPMCSes along with quality of information heuristics to ensure that LPMCSes are formed around high-quality information. We then propose an intelligent sensor model for integrating this information into the AgentSpeak framework which is responsible for applying evidence propagation to construct compatible information, for performing context-dependent combination and for deriving beliefs for revising an agent’s belief base. Finally, we present a power grid scenario inspired by a real-world case study to demonstrate our work.

Kinect and Episodic Reasoning for Human Action Recognition

This paper presents a method for rational behaviour recognition that combines vision-based pose estimation with knowledge modeling and reasoning. The proposed method consists of two stages. First, RGB-D images are used in the estimation of the body postures. Then, estimated actions are evaluated to verify that they make sense. This method requires rational behaviour to be exhibited. To comply with this requirement, this work proposes a rational RGB-D dataset with two types of sequences, some for training and some for testing. Preliminary results show the addition of knowledge modeling and reasoning leads to a significant increase of recognition accuracy when compared to a system based only on computer vision.

Levantamiento de una base de datos para el diagnóstico de fallas en motores de combustión interna ciclo Otto con sistema MPFI mediante el análisis del sensor MAP

En el presente documento se presenta el desarrollo de la creación de una base de datos para el diagnóstico de fallas en los motores de combustión interna MPFI mediante el análisis del sensor MAP (Manifold Absolute Pressure), a través del cual se puede determinar y diagnosticar fallas en sensores, actuadores y sistemas auxiliares.

Transient transpiration radiometer : development of a heat flux sensor for high aggressivity environments

The development of a new instrument for the measurement of convective and radiative is proposed, based on the transient operation of a transpiration radiometer. Current transpiration radiometers rely on steady state temperature measurements in a porous element crossed by a know gas mass flow. As a consequence of the porous sensing element’s intrinsically high thermal inertia, the instrument’s time constant is in the order of several seconds. The proposed instrument preserves established advantages of transpiration radiometers while incorporating additional features that broaden its applicability range. The most important developments are a significant reduction of the instrument’s response time and the possibility of separating and measuring the convective and radiative components of the heat flux. These objectives are achieved through the analysis of the instrument’s transient response, a pulsed gas flow being used to induce the transient behavior.

Estimating bottom properties with a vector sensor array during MakaiEx 2005

Nowadays, vector sensors which measure both acoustic pressure and particle velocity begin to be available in underwater acoustic systems, normally configured as vector sensor arrays (VSA). The spatial filtering capabilities of a VSA can be used, with advantage over traditional pressure only hydrophone arrays, for estimating acoustic field directionality as well as arrival times and spectral content, which could open up the possibility for its use in bottom properties' estimation. An additional motivation for this work is to test the possibility of using high frequency probe signals (say above 2 kHz) for reducing size and cost of actual sub bottom profilers and current geoacoustic inversion methods. This work studies the bottom related structure of the VSA acquired signals, regarding the emitted signal waveform, frequency band and source-receiver geometry in order to estimate bottom properties, specially bottom reflection coefficient characteristics. Such a system was used during the Makai 2005 experiment, off Kauai I., Hawai (USA) to receive precoded signals in a broad frequency band from 8 up to 14 kHz. The agreement between the observed and the modelled acoustic data is discussed and preliminary results on the bottom reflection estimation are presented.