Redox Chemiluminescence and the Problem of Self-supporting Cold Light Sources

By generating the redox species at potentials corresponding to the foot of polarographic waves, the conversion of electrical energy into light at efficiencies greater than 100°/o is shown to be thermodynamically permitted. It is also shown that criteria for this are not met by presently available redox chemiluminescent systems, and the ionquenching efficiency of the electrode is quantitatively evaluated as a function of redox annihilation rate constant, luminescor parent compound concentration, molecular 1size, and applied potential

Redox Chemiluminescence and the Problem of Self-supporting Cold Light Sources

By generating the redox species at potentials corresponding to the foot of polarographic waves, the conversion of electrical energy into light at efficiencies greater than 100°/o is shown to be thermodynamically permitted. It is also shown that criteria for this are not met by presently available redox chemiluminescent systems, and the ionquenching efficiency of the electrode is quantitatively evaluated as a function of redox annihilation rate constant, luminescor parent compound concentration, molecular 1size, and applied potential

Enhancing particle filters using local likelihood sampling

Particle filters provide a means to track the state of an object even when the dynamics and the observations are non-linear/non-Gaussian. However, they can be very inefficient when the observation noise is low as compared to the system noise, as it is often the case in visual tracking applications. In this paper we propose a new two-stage sampling procedure to boost the performance of particle filters under this condition. We provide conditions under which the new procedure is proven to reduce the variance of the weights. Synthetic and real-world visual tracking experiments are used to confirm the validity of the theoretical analysis

Sequential importance sampling for visual tracking reconsidered

we consider the task of filtering dynamical systems observed in noise by incails of sequential importance sampling when the proposal is restricted to the innovation components of the state. It is argued that the unmodified sequential importance sampling/resampling (SIR) algorithm may yield high variance estimates of the posterior in this case, resulting in poor performance when e.g. in visual tracking one tries to build a SIR algorithm on the top of the output of a color blob detector. A new method that associates the innovations sampled from the proposal and the particles in a separate computational step is proposed. The method is shown to outperform the unmodified SIR algorithm in a series of vision based object tracking experiments, both in terms of accuracy and robustness

A Rewriting-Logic-Based Technique for Modeling Thermal Systems

This paper presents a rewriting-logic-based modeling and analysis technique for physical systems, with focus on thermal systems. The contributions of this paper can be summarized as follows: (i) providing a framework for modeling and executing physical systems, where both the physical components and their physical interactions are treated as first-class citizens; (ii) showing how heat transfer problems in thermal systems can be modeled in Real-Time Maude; (iii) giving the implementation in Real-Time Maude of a basic numerical technique for executing continuous behaviors in object-oriented hybrid systems; and (iv) illustrating these techniques with a set of incremental case studies using realistic physical parameters, with examples of simulation and model checking analyses.Comment: In Proceedings RTRTS 2010, arXiv:1009.398