Coping with Loss

No community is immune from tragedy, as Furman has discovered all too often in recent years

The generalized Fenyes-Nelson model for free scalar field theory

The generalized Fenyes--Nelson model of quantum mechanics is applied to the free scalar field. The resulting Markov field is equivalent to the Euclidean Markov field with the times scaled by a common factor which depends on the diffusion parameter. This result is consistent between Guerra's earlier work on stochastic quantization of scalar fields. It suggests a deep connection between Euclidean field theory and the stochastic interpretation of quantum mechanics. The question of Lorentz covariance is also discussed.Comment: 6 page

BIO-INSPIRED COVERAGE OF INVISIBLE HAZARDOUS SUBSTANCES IN THE ENVIRONMENT

Inspired by the simplicity of how nature solves its problems, a controller based upon the bacteria chemotaxis behavior and flocking of starlings in nature is developed and presented. It would enable the localization and subsequent mapping of pollutants in the environment. The pollutants could range from chemical leaks to invisible air borne hazardous materials. Simulation is used to explore the feasibility of the proposed controller and then a brief discussion on how to implement it onto a real robotic platform is presented. By using the advantages offered by swarm robotics, it is possible to achieve a collective mapping of an invisible pollutant spread over a large area. The approach presented is very simple, computational efficient, easily tuned and yet highly effective (desirable characteristics of biological systems) in generating a representation of an invisible pollutant. </jats:p

MANTIS: System support for MultimodAl NeTworks of In-situ Sensors

The MANTIS MultimodAl system for NeTworks of In-situ wireless Sensors provides a new multithreaded embedded operating system integrated with a general-purpose single-board hardware platform to enable flexible and rapid prototyping of wireless sensor networks. The key design goals of MANTIS are ease of use, i.e. a small learning curve that encourages novice programmers to rapidly prototype novel sensor networking applications in software and hardware, as well as flexibility, so that expert researchers can leverage or develop advanced software features and hardware extensions to suit the needs of advanced research in wireless sensor networks. Categories and Subject Descriptor

Tracking and sensor coverage of spatio-temporal quantities using a swarm of artificial foraging agents

Using a network of mobile sensors to track and map a dynamic spatio-temporal process in the environment is one of the current challenges in multi-agent systems. In this work, a distributed probabilistic multi-agent algorithm inspired by the bacterium foraging behavior is presented. The novelty of the algorithm lies in being capable of tracking and mapping a spatio-temporal quantity without the need of machine learning, estimation algorithms or future planning. This is unlike most current techniques that rely heavily on machine learning to estimate the distribution as well as the profile of spatio-temporal quantities. The experimental studies carried out in this work show that the algorithm works well by following the concentration gradient of a dynamic plume created under diffusive conditions. Furthermore, the algorithm is inherently capable of finding the source of a diffusive spatio-temporal quantity as well as performing environmental exploration. It is computationally tractable for simple agents, shown to adapt to its environment and can deal successfully with noise in sensor readings as well as in robot dynamics