Models and algorithms for detection and tracking of coordinated groups

In this paper, we describe models and algorithms for detection and tracking of group and individual targets. We develop two novel group dynamical models, within a continuous time setting, that aim to mimic behavioural properties of groups. We also describe two possible ways of modeling interactions between closely using Markov Random Field (MRF) and repulsive forces. These can be combined together with a group structure transition model to create realistic evolving group models. We use a Markov Chain Monte Carlo (MCMC)-Particles Algorithm to perform sequential inference. Computer simulations demonstrate the ability of the algorithm to detect and track targets within groups, as well as infer the correct group structure over time. ©2008 IEEE.

Video tracking using dual-treewavelet polar matching and particle filtering

In this paper, we describe a video tracking application using the dual-tree polar matching algorithm. The models are specified in a probabilistic setting, and a particle ilter is used to perform the sequential inference. Computer simulations demonstrate the ability of the algorithm to track a simulated video moving target in an urban environment with complete and partial occlusions. © The Institution of Engineering and Technology.

Differential Dynamic Microscopy: a High-Throughput Method for Characterizing the Motility of Microorganism

We present a fast, high-throughput method for characterizing the motility of microorganisms in 3D based on standard imaging microscopy. Instead of tracking individual cells, we analyse the spatio-temporal fluctuations of the intensity in the sample from time-lapse images and obtain the intermediate scattering function (ISF) of the system. We demonstrate our method on two different types of microorganisms: bacteria, both smooth swimming (run only) and wild type (run and tumble) Escherichia coli, and the bi-flagellate alga Chlamydomonas reinhardtii. We validate the methodology using computer simulations and particle tracking. From the ISF, we are able to extract (i) for E. coli: the swimming speed distribution, the fraction of motile cells and the diffusivity, and (ii) for C. reinhardtii: the swimming speed distribution, the amplitude and frequency of the oscillatory dynamics. In both cases, the motility parameters are averaged over \approx 10^4 cells and obtained in a few minutes.

Design and simulations of SOI CMOS micro-hotplate gas sensors

This paper describes a new generation of integrated solid-state gas-sensors embedded in SOI micro-hotplates. The micro-hotplates lie on a SOI membrane and consist of MOSFET heaters that elevate the operating temperature, through self-heating, of a gas sensitive material. These sensors are fully compatible with SOI CMOS or BiCMOS technologies, offer ultra-low power consumption (under 100 mW), high sensitivity, low noise, low unit cost, reproducibility and reliability through the use of on-chip integration. In addition, the new integrated sensors offer a nearly uniform temperature distribution over the active area at its operating temperatures at up to about 300-350°C. This makes SOI-based gas-sensing devices particularly attractive for use in handheld battery-operated gas monitors. This paper reports on the design of a chemo-resistive gas sensor and proposes for the first time an intelligent SOI membrane microcalorimeter using active micro-FET heaters and temperature sensors. A comprehensive set of numerical and analogue simulations is also presented including complex 2D and 3D electro-thermal numerical analyses. © 2001 Elsevier Science B.V. All rights reserved.

Multi-field simulations and characterization of CMOS-MEMS high-temperature smart gas sensors based on SOI technology

This paper describes multiple field-coupled simulations and device characterization of fully CMOS-MEMS-compatible smart gas sensors. The sensor structure is designated for gas/vapour detection at high temperatures (>300 °C) with low power consumption, high sensitivity and competent mechanic robustness employing the silicon-on-insulator (SOI) wafer technology, CMOS process and micromachining techniques. The smart gas sensor features micro-heaters using p-type MOSFETs or polysilicon resistors and differentially transducing circuits for in situ temperature measurement. Physical models and 3D electro-thermo-mechanical simulations of the SOI micro-hotplate induced by Joule, self-heating, mechanic stress and piezoresistive effects are provided. The electro-thermal effect initiates and thus affects electronic and mechanical characteristics of the sensor devices at high temperatures. Experiments on variation and characterization of micro-heater resistance, power consumption, thermal imaging, deformation interferometry and dynamic thermal response of the SOI micro-hotplate have been presented and discussed. The full integration of the smart gas sensor with automatically temperature-reading ICs demonstrates the lowest power consumption of 57 mW at 300 °C and fast thermal response of 10 ms. © 2008 IOP Publishing Ltd.

Simulations of thermal upgrading methods for oil shale reservoirs

This paper analyzes reaction and thermal front development in porous reservoirs with reacting flows, such as those encountered in shale oil extraction. A set of dimensionless parameters and a 3D code are developed in order to investigate the important physical and chemical variables of such reservoirs when heated by in situ methods. This contribution builds on a 1D model developed for the precursor study to this work. Theory necessary for this study is presented, namely shale decomposition chemical mechanisms, governing equations for multiphase flow in porous media and necessary closure models. Plotting the ratio of the thermal wave speed to the fluid speed allows one to infer that the reaction wave front ends where this ratio is at a minimum. The reaction front follows the thermal front closely, thus allowing assumptions to be made about the extent of decomposition solely by looking at thermal wave progression. Furthermore, this sensitivity analysis showed that a certain minimum permeability is required in order to ensure the formation of a traveling thermal wave. It was found that by studying the non-dimensional governing parameters of the system one can ascribe characteristic values for these parameters for given initial and boundary conditions. This allows one to roughly predict the performance of a particular method on a particular reservoir given approximate values for initial and boundary conditions. Channelling and flow blockage due to carbon residue buildup impeded each method's performance. Blockage was found to be a result of imbalanced heating. Copyright 2012, Society of Petroleum Engineers.