Two-dimensional gases of generalized statistics in a uniform magnetic field

We study the low temperature properties of two-dimensional ideal gases of generalized statistics in a uniform magnetic field. The generalized statistics considered here are the parafermion statistics and the exclusion statistics. Similarity in the behaviours of the parafermion gas of finite order $p$ and the gas with exclusion coefficient $g=1/p$ at very low temperatures is noted. These two systems become exactly equivalent at $T=0$. Qumtum Hall effect with these particles as charge carriers is briefly discussed.Comment: Latex file, 14 pages, 5 figures available on reques

Natural extensions and entropy of α\alpha-continued fractions

We construct a natural extension for each of Nakada's $\alpha$-continued fractions and show the continuity as a function of $\alpha$ of both the entropy and the measure of the natural extension domain with respect to the density function $(1+xy)^{-2}$. In particular, we show that, for all $0 < \alpha \le 1$, the product of the entropy with the measure of the domain equals $\pi^2/6$. As a key step, we give the explicit relationship between the $\alpha$-expansion of $\alpha-1$ and of $\alpha$

Measuring the energy intensity of domestic activities from smart meter data

Household electricity consumption can be broken down to appliance end-use through a variety of methods such as modelling, sub-metering, load disaggregation or non-intrusive appliance load monitoring (NILM). We advance and complement this important field of energy research through an innovative methodology that characterises the energy consumption of domestic life by making the linkages between appliance end-use and activities through an ontology built from qualitative data about the household and NILM data. We use activities as a descriptive term for the common ways households spend their time at home. These activities, such as cooking or laundering, are meaningful to households’ own lived experience. Thus, besides strictly technical algorithmic approaches for processing quantitative smart meter data, we also draw on social science time use approaches and interview and ethnography data. Our method disaggregates a households total electricity load down to appliance level and provides the start time, duration, and total electricity consumption for each occurrence of appliance usage. We then make inferences about activities occurring in the home by combining these disaggregated data with an ontology that formally specifies the relationships between electricity-using appliances and activities. We also propose two novel standardised metrics to enable easy quantifiable comparison within and across households of the energy intensity and routine of activities of interest. Finally, we demonstrate our results over a sample of ten households with an in-depth analysis of which activities can be inferred with the qualitative and quantitative data available for each household at any time, and the level of accuracy with which each activity can be inferred, unique to each household. This work has important applications from providing meaningful energy feedback to households to comparing the energy efficiency of households’ daily activities, and exploring the potential to shift the timing of activities for demand management

Scalable Mining of Common Routes in Mobile Communication Network Traffic Data

A probabilistic method for inferring common routes from mobile communication network traffic data is presented. Besides providing mobility information, valuable in a multitude of application areas, the method has the dual purpose of enabling efficient coarse-graining as well as anonymisation by mapping individual sequences onto common routes. The approach is to represent spatial trajectories by Cell ID sequences that are grouped into routes using locality-sensitive hashing and graph clustering. The method is demonstrated to be scalable, and to accurately group sequences using an evaluation set of GPS tagged data