Modelling of Supercapacitors: Factors Influencing Performance

The utilizable capacitance of Electrochemical Double Layer Capacitors (EDLCs) is a function of the frequency at which they are operated and this is strongly dependent on the construction and physical parameters of the device. We simulate the dynamic behavior of an EDLC using a spatially resolved model based on the porous electrode theory. The model of Verbrugge and Liu (J. Electrochem. Soc. 152, D79 (2005)) was extended with a dimension describing the transport into the carbon particle pores. Our results show a large influence of the electrode thickness (Le), separator thickness (Ls) and electrolyte conductivity (κ) on the performance of EDLCs. In agreement with experimental data, the time constant was an increasing function of Le and Ls and a decreasing function of κ. The main limitation was found to be on the scale of the whole cell, while transport into the particles became a limiting factor only if the particle size was unrealistically large. The results were generalized into a simplified relation allowing for a quick evaluation of performance for the design of new devices. This work provides an insight into the performance limitation of EDLCs and identifies the critical parameters to consider for both systems engineers and material scientists

Clustering Time Series from Mixture Polynomial Models with Discretised Data

Clustering time series is an active research area with applications in many fields. One common feature of time series is the likely presence of outliers. These uncharacteristic data can significantly effect the quality of clusters formed. This paper evaluates a method of over-coming the detrimental effects of outliers. We describe some of the alternative approaches to clustering time series, then specify a particular class of model for experimentation with k-means clustering and a correlation based distance metric. For data derived from this class of model we demonstrate that discretising the data into a binary series of above and below the median improves the clustering when the data has outliers. More specifically, we show that firstly discretisation does not significantly effect the accuracy of the clusters when there are no outliers and secondly it significantly increases the accuracy in the presence of outliers, even when the probability of outlier is very low

Combinatorial Bounds and Characterizations of Splitting Authentication Codes

We present several generalizations of results for splitting authentication codes by studying the aspect of multi-fold security. As the two primary results, we prove a combinatorial lower bound on the number of encoding rules and a combinatorial characterization of optimal splitting authentication codes that are multi-fold secure against spoofing attacks. The characterization is based on a new type of combinatorial designs, which we introduce and for which basic necessary conditions are given regarding their existence.Comment: 13 pages; to appear in "Cryptography and Communications

On the inverse Compton scattering model of radio pulsars

Some characteristics of the inverse Compton scattering (ICS) model are reviewed. At least the following properties of radio pulsars can be reproduced in the model: core or central emission beam, one or two hollow emission cones, different emission heights of these components, diverse pulse profiles at various frequencies, linear and circular polarization features of core and cones.Comment: 5 pages, no figures, LaTeX, a proceeding paper for Pacific Rim Conference on Stellar Astrophysics, Aug. 1999, HongKong, Chin

A Computation in a Cellular Automaton Collider Rule 110

A cellular automaton collider is a finite state machine build of rings of one-dimensional cellular automata. We show how a computation can be performed on the collider by exploiting interactions between gliders (particles, localisations). The constructions proposed are based on universality of elementary cellular automaton rule 110, cyclic tag systems, supercolliders, and computing on rings.Comment: 39 pages, 32 figures, 3 table

Learning Dilation Factors for Semantic Segmentation of Street Scenes

Contextual information is crucial for semantic segmentation. However, finding the optimal trade-off between keeping desired fine details and at the same time providing sufficiently large receptive fields is non trivial. This is even more so, when objects or classes present in an image significantly vary in size. Dilated convolutions have proven valuable for semantic segmentation, because they allow to increase the size of the receptive field without sacrificing image resolution. However, in current state-of-the-art methods, dilation parameters are hand-tuned and fixed. In this paper, we present an approach for learning dilation parameters adaptively per channel, consistently improving semantic segmentation results on street-scene datasets like Cityscapes and Camvid.Comment: GCPR201

Giant suppression of the Drude conductivity due to quantum interference in disordered two-dimensional systems

Temperature and magnetic field dependences of the conductivity in heavily doped, strongly disordered two-dimensional quantum well structures GaAs/In$_x$Ga$_{1-x}$As/GaAs are investigated within wide conductivity and temperature ranges. Role of the interference in the electron transport is studied in the regimes when the phase breaking length $L_\phi$ crosses over the localization length $\xi\sim l\exp{(\pi k_Fl/2)}$ with lowering temperature, where $k_F$ and $l$ are the Fermi quasimomentum and mean free path, respectively. It has been shown that all the experimental data can be understood within framework of simple model of the conductivity over delocalized states. This model differs from the conventional model of the weak localization developed for $k_Fl\gg 1$ and $L_\phi\ll\xi$ by one point: the value of the quantum interference contribution to the conductivity is restricted not only by the phase breaking length $L_\phi$ but by the localization length $\xi$ as well. We show that just the quantity $(\tau_\phi^\ast)^{-1}=\tau_\phi^{-1}+\tau_\xi^{-1}$ rather than $\tau_\phi^{-1}$, where $\tau_\phi\propto T^{-1}$ is the dephasing time and $\tau_\xi\sim\tau\exp(\pi k_F l)$, is responsible for the temperature and magnetic field dependences of the conductivity over the wide range of temperature and disorder strength down to the conductivity of order $10^{-2} e^2/h$.Comment: 11 pages, 15 figure