2,153 Works

Model Guided Application for Investigating Particle Number (PN) Emissions in GDI Spark Ignition Engines

KF Lee, N Eaves, Sebastian Mosbach, D Ooi, J Lai, A Bhave, A Manz, JN Geiler, JA Noble, D Duca & C Focsa
© 2019 SAE International. All Rights Reserved. Model guided application (MGA) combining physico-chemical internal combustion engine simulation with advanced analytics offers a robust framework to develop and test particle number (PN) emissions reduction strategies. The digital engineering workflow presented in this paper integrates the kinetics & SRM Engine Suite with parameter estimation techniques applicable to the simulation of particle formation and dynamics in gasoline direct injection (GDI) spark ignition (SI) engines. The evolution of the...

Real-time noise-aware tone-mapping and its use in luminance retargeting

G Eilertsen, RK Mantiuk & J Unger
With the aid of tone-mapping operators, high dynamic range images can be mapped for reproduction on standard displays. However, for large restrictions in terms of display dynamic range and peak luminance, limitations of the human visual system have significant impact on the visual appearance. In this paper, we use components from the real-time noise-aware tone-mapping to complement an existing method for perceptual matching of image appearance under different luminance levels. The refined luminance retargeting method...

Development of Pore Pressure and Shear Strain in Clean Hostun Sands Under Multi-directional Loading Paths

Mengchen Sun & Giovanna Biscontin
A series of undrained multi-directional direct simple shear tests with circular paths were conducted to investigate the excess pore pressure generation and shear strain development in clean Hostun sands under multi-directional loading condition. The results of an example test are shown. The excess pore pressure accumulation and shear strain development under multi-directional loading condition exhibits evidently different characteristics compared with that under uni-directional loading condition. Excess pore pressure accumulates generally with the circular stress path...

Pro-Diluvian: Understanding scoped-flooding for content discovery in information-centric networking

L Wang, S Bayhan, J Ott, J Kangasharju, A Sathiaseelan & Jonathon Crowcroft

A Comparison of Impairment Abstractions by Multiple Users of an Installed Fiber Infrastructure

David Ives, S Yan, L Galdino, DJ Elson, FJ Vaquero-Caballero, G Saavedrar, R Wang, D Lavery, R Nejabati, P Bayvel, D Simeonidou & SJ Savory

Polos opostos? Um estudo comparativo das políticas de habitação em Portugal e na Dinamarca

Sonia Nunes Alves
Entre as políticas de habitação e os regimes de propriedade dominantes em diversos países observam-se diferenças notáveis. Até que ponto estas diferenças são ditadas por grandes interesses económicos e explicadas pela ideologia prevalecente no contexto das circunstâncias políticas de cada país? Partindo do princípio que a comparação entre os países do norte e do sul da Europa tem sido vastamente negligenciada pelos estudos comparados de políticas de habitação, ao usar os casos português e dinamarquês,...

Toward industry 4.0: Efficient and sustainable manufacturing leveraging MAESTRI total efficiency framework

E Ferrera, R Rossini, AJ Baptista, Stephen Evans, GG Hovest, Maria Holgado, E Lezak, EJ Lourenço, Z Masluszczak, A Schneider, EJ Silva, O Werner-Kytölä & MA Estrela
© Springer International Publishing AG 2017.This paper presents an overview of the work under development within MAESTRI EU-funded collaborative project. The MAESTRI Total Efficiency Framework (MTEF) aims to advance the sustainability of manufacturing and process industries by providing a management system in the form of a flexible and scalable platform and methodology. The MTEF is based on four pillars: (a) an effective management system targeted at process continuous improvement; (b) Efficiency assessment tools to support...

Topic-Enhanced Memory Networks for Personalised Point-of-Interest Recommendation

Xiao Zhou, Cecilia Mascolo & Zhongxiang Zhao
Point-of-Interest (POI) recommender systems play a vital role in people’s lives by recommending unexplored POIs to users and have drawn extensive attention from both academia and industry. De- spite their value, however, they still su er from the challenges of capturing complicated user preferences and ne-grained user-POI relationship for spatio-temporal sensitive POI recommendation. Existing recommendation algorithms, including both shallow and deep approaches, usually embed the visiting records of a user into a single latent vector...

A Machine Learning Tool for Interpreting Differences in Cognition Using Brain Features

Tiago Azevedo, Luca Passamonti, Pietro Lió & Nicola Toschi
Predicting variability in cognition traits is an attractive and challenging area of research, where different approaches and datasets have been implemented with mixed results. Some powerful Machine Learning algorithms employed before are difficult to interpret, while other algorithms are easy to interpret but might not be as powerful. To improve understanding of individual cognitive differences in humans, we make use of the most recent developments in Machine Learning in which powerful prediction models can be...

Distractor Suppression in Visual Search

Alexander Muhl-Richardson, Sergio A Recio & Gregory Davis

CMOS technology platform for ubiquitous microsensors

Florin Udrea & Andrea De Luca

On the reproducibility of CMOS plasmonic mid-IR thermal emitters

Andrea De Luca, SZ Ali & Florin Udrea

An Operational Semantics for C/C++11 Concurrency

Kyndylan Nienhuis, Kayvan Memarian & Peter Sewell
The C/C++11 concurrency model balances two goals: it is relaxed enough to be efficiently implementable and (leaving aside the "thin-air" problem) it is strong enough to give useful guarantees to programmers. It is mathematically precise and has been used in verification research and compiler testing. However, the model is expressed in an axiomatic style, as predicates on complete candidate executions. This suffices for computing the set of allowed executions of a small litmus test, but...

Sequence Multi-task Learning to Forecast Mental Wellbeing from Sparse Self-reported Data

Dimitrios Spathis, Sandra Servia-Rodriguez, Katayoun Farrahi, Cecilia Mascolo & Jason Rentfrow
Smartphones have started to be used as self reporting tools for mental health state as they accompany individuals during their days and can therefore gather temporally fine grained data. However, the analysis of self reported mood data offers challenges related to non-homogeneity of mood assessment among individuals due to the complexity of the feeling and the reporting scales, as well as the noise and sparseness of the reports when collected in the wild. In this...

Passive mobile sensing and psychological traits for large scale mood prediction

Dimitrios Spathis, Sandra Servia-Rodriguez, Katayoun Farrahi, Cecilia Mascolo & Jason Rentfrow
Experience sampling has long been the established method to sample people’s mood in order to assess their mental state. Smartphones have started to be used as experience sampling tools for mental health state as they accompany individuals during their day and can therefore gather in-the-moment data. However, the granularity of the data needs to be traded off with the level of interruption these tools introduce on users’ activities. As a consequence the data collected with...

PREDICTING THE OPERABILITY OF DAMAGED COMPRESSORS USING MACHINE LEARNING

James Taylor, Bryce Conduit, Anthony Dickens, Chris Hall, Malcolm Hillel & Rob Miller
The application of machine learning to aerospace problems faces a particular challenge. For successful learning a large amount of good quality training data is required, typically tens of thousands of cases. However, due to the time and cost of experimental aerospace testing, this data is scarce. This paper shows that successful learning is possible with two novel techniques: The first technique is rapid testing. Over the last five years the Whittle Laboratory has developed a...

High-Bandwidth Low-Cost High-Speed Optical Fiber Links using Organic Light Emitting Diodes

Priyanka De Souza, Nikolaos Bamiedakis, K Yoshida, PP Manousiadis, GA Turnbull, IDW Samuel, Richard Penty & Ian White
Record-high 200 Mbps transmission using an OLED with a 31 MHz 3 dB bandwidth using a 3-tap feedforward equaliser is achieved, demonstrating the potential of such devices for use in low-cost polymer optical fiber links.

Phase-tuned entangled state generation between distant spin qubits

R Stockill, M Stanley, L Huthmacher, CL Gall, A Miller, E Clarke, M Hugues, C Matthiesen & M Atatu¨Re

Learning an appearance-based gaze estimator from one million synthesised images

E Wood, T Baltrušaitis, LP Morency, Peter Robinson & A Bulling

Filterless non-dispersive infra-red gas detection: A proof of concept

Andrea De Luca, SZ Ali, RH Hopper, S Boual, JW Gardner & Florin Udrea

Designing autonomy in cars: A survey and two focus groups on driving habits of an inclusive user group, and group attitudes towards autonomous cars

Ioannis Politis, Patrick Langdon, Michael Bradley, Lee Skrypchuk, A Mouzakitis & Peter Clarkson

Multi-task Adversarial Network for Disentangled Feature Learning

Yang Liu, Z Wang, H Jin & Ian Wassell
We address the problem of image feature learning for the applications where multiple factors exist in the image gen- eration process and only some factors are of our interest. We present a novel multi-task adversarial network based on an encoder-discriminator-generator architecture. The en- coder extracts a disentangled feature representation for the factors of interest. The discriminators classify each of the factors as individual tasks. The encoder and the discrimina- tors are trained cooperatively on factors...

ECF: An MPTCP path scheduler to manage heterogeneous paths

YS Lim, EM Nahum, D Towsley & Richard Gibbens
© 2017 ACM. Multi-Path TCP (MPTCP) is a new standardized transport protocol that enables devices to utilize multiple network interfaces. The default MPTCP path scheduler prioritizes paths with the smallest round trip time (RTT). In this work, we examine whether the default MPTCP path scheduler can provide applications the ideal aggregate bandwidth, i.e., the sum of available bandwidths of all paths. Our experimental results show that heterogeneous paths cause under-utilization of the fast path, resulting...

ECF: An MPTCP path scheduler to manage heterogeneous paths

YS Lim, D Towsley, EM Nahum & Richard Gibbens
© 2017 Association for Computing Machinery. Multi-Path TCP (MPTCP) is a new standardized transport protocol that enables devices to utilize multiple network interfaces. The default MPTCP path scheduler prioritizes paths with the smallest round trip time (RTT).In this work, we examine whether the default MPTCP path scheduler can provide applications the ideal aggregate bandwidth, i.e., the sum of available bandwidths of every paths. Our experimental results show that heterogeneous paths cause underutilization of the fast...

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