Building occupancy modelling at the district level: A combined copula-nested hazard-based approach

Planning and managing an energy system in a district require a comprehensive understanding and accurate modelling of people's occupancy and circulation among multiple buildings. Due to the lack of occupancy modelling tools for district scale analysis, energy models still use simplified occupancy patterns provided in building codes and standards. However, the simplified information restricts the reflection of complex occupancy patterns driven by urban heterogeneity. This paper fills this research gap and presents a hazard-based model combined with nested copula dependence to describe the complex occupants' interactions between buildings in a district, enabling the characterisation of irregular occupancy patterns in special cases. The proposed model is calibrated using Wi-Fi authentication data from the Imperial College London (UK) South Kensington campus and is validated using the following days of the same data by evaluating the performance of predicted occupancy patterns both on average and day by day. The validation results demonstrate that the model can accurately capture the effects of the urban environment on occupancy duration and choice of transition within a district. Mean Absolute Percentage Errors (MAPEs) of average-pattern predictions are between 7% and 16% for most buildings, though a bit lower in accuracy for the Library and Food Hall predictions with MAPEs of 32%–36%. We also discuss the contributions of the proposed occupancy model to potential future applications, including efficient building space use, local energy planning and management

An approach for building occupancy modelling considering the urban context

Building occupancy, which reflects occupant presence, movements and activities within the building space, is a key factor to consider in building energy modelling and simulation. Characterising complex occupant behaviours and their determinants poses challenges from the sensing, modelling, interpretation and prediction perspectives. Past studies typically applied time-dependent models to predict regular occupancy patterns for commercial buildings. However, this prevalent reliance on purely time-of-day effects is typically not sufficient to accurately characterise the complex occupancy patterns as they may vary with building’s surrounding conditions, i.e. the urban environment. Therefore, this research proposes a conceptual framework to incorporate the interactions between urban systems and building occupancy. Under the framework, we propose a novel modelling methodology relying on competing risk hazard formulation to analyse the occupancy of a case study building in London, UK. The occupancy profiles were inferred from the Wi-Fi connection logs extracted from the existing Wi-Fi infrastructure. When compared with the conventional discrete-time Markov Chain Model (MCM), the hazard-based modelling approach was able to better capture the duration dependent nature of the transition probabilities as well as incorporate and quantify the influence of the local environment on occupancy transitions. The work has demonstrated that this approach enables a convenient and flexible incorporation of urban dependencies leading to accurate occupancy predictions whilst providing the ability to interpret the impacts of urban systems on building occupancy. Keywords: Urban system; Competing risk hazard model; Building occupancy simulation; Wi4 Fi connection dat

The Hudson Bay Lithospheric Experiment (HuBLE) : Insights into Precambrian Plate Tectonics and the Development of Mantle Keels

The UK component of HuBLE was supported by Natural Environment Research Council (NERC) grant NE/F007337/1, with financial and logistical support from the Geological Survey of Canada, Canada–Nunavut Geoscience Office, SEIS-UK (the seismic node of NERC), and First Nations communities of Nunavut. J. Beauchesne and J. Kendall provided invaluable assistance in the field. Discussions with M. St-Onge, T. Skulski, D. Corrigan and M. Sanborne-Barrie were helpful for interpretation of the data. D. Eaton and F. A. Darbyshire acknowledge the Natural Sciences and Engineering Research Council. Four stations on the Belcher Islands and northern Quebec were installed by the University of Western Ontario and funded through a grant to D. Eaton (UWO Academic Development Fund). I. Bastow is funded by the Leverhulme Trust. This is Natural Resources Canada Contribution 20130084 to its Geomapping for Energy and Minerals Program. This work has received funding from the European Research Council under the European Unions Seventh Framework Programme (FP7/2007-2013)/ERC Grant agreement no. 240473 ‘CoMITAC’.Peer reviewedPublisher PD

A realistic vascular model for BOLD signal up to 16.4 T

The blood oxygenation level-dependent (BOLD) signal using functional magnetic resonance imaging (fMRI) is currently the most popular imaging method to study brain function non-invasively. The sensitivity of the BOLD signal to different types of MRI sequences and vessel sizes is currently under investigation [1]. Gradient echo (GRE) sequences are known to be sensitive to larger vessels (venules and veins), whereas spin-echo (SE) sequences are generally more sensitive to smaller vessels (venules and capillaries), especially at high magnetic field strength [2, 3]. However, the widely used single vessel model is only an approximation to the realistic vascular distribution. Realistic vascular models have been proposed by Marques and Bowtell [4] and, recently, by Chen et al.[5]. We herein present a realistic vascular model (RVM) where diffusion is accounted for by a Monte-Carlo random walk

Autonomous clustering using rough set theory

This paper proposes a clustering technique that minimises the need for subjective human intervention and is based on elements of rough set theory. The proposed algorithm is unified in its approach to clustering and makes use of both local and global data properties to obtain clustering solutions. It handles single-type and mixed attribute data sets with ease and results from three data sets of single and mixed attribute types are used to illustrate the technique and establish its efficiency

Geometrical Magnetic Frustration in Rare Earth Chalcogenide Spinels

We have characterized the magnetic and structural properties of the CdLn2Se4 (Ln = Dy, Ho), and CdLn2S4 (Ln = Ho, Er, Tm, Yb) spinels. We observe all compounds to be normal spinels, possessing a geometrically frustrated sublattice of lanthanide atoms with no observable structural disorder. Fits to the high temperature magnetic susceptibilities indicate these materials to have effective antiferromagnetic interactions, with Curie-Weiss temperatures theta ~ -10 K, except CdYb2S4 for which theta ~ -40 K. The absence of magnetic long range order or glassiness above T = 1.8 K strongly suggests that these materials are a new venue in which to study the effects of strong geometrical frustration, potentially as rich in new physical phenomena as that of the pyrochlore oxides.Comment: 17 pages, 5 figures, submitted to Phys Rev B; added acknowledgement

Random walks - a sequential approach

In this paper sequential monitoring schemes to detect nonparametric drifts are studied for the random walk case. The procedure is based on a kernel smoother. As a by-product we obtain the asymptotics of the Nadaraya-Watson estimator and its as- sociated sequential partial sum process under non-standard sampling. The asymptotic behavior differs substantially from the stationary situation, if there is a unit root (random walk component). To obtain meaningful asymptotic results we consider local nonpara- metric alternatives for the drift component. It turns out that the rate of convergence at which the drift vanishes determines whether the asymptotic properties of the monitoring procedure are determined by a deterministic or random function. Further, we provide a theoretical result about the optimal kernel for a given alternative