2,381 Works

A typed, algebraic approach to parsing

Neel Krishnaswami & Jeremy Yallop
In this paper, we recall the definition of the context-free expressions (or µ-regular expressions), an algebraic presentation of the context-free languages. Then, we define a core type system for the context-free expressions which gives a compositional criterion for identifying those context-free expressions which can be parsed unambiguously by predictive algorithms in the style of recursive descent or LL(1). Next, we show how these typed grammar expressions can be used to derive a parser combinator library...

Large Eddy Simulation of Bluff Body Stabilised Premixed Flames Using Flamelets

James Massey, Ivan Langella & Nedunchezhian Swaminathan
Large Eddy Simulations of an unconfined turbulent lean practical flame stabilised behind a bluff body burner are computed using structured and unstructured numerical solvers. Unstrained flamelets are used as the sub-grid scale combustion closure using constant and dynamic formulations to model the flame curvature parameter βc. The model uses a presumed probability density function to calculate the filtered reaction rate. The aim of this study is to determine the numerical set-up that provides the most...

Modelling of thermal energy storage systems for bulk electricity storage

Pau Farres Antunez
This report was submitted for the First Year Assessment of the PhD course in Engineering at Cambridge University Engineering Department. ABSTRACT Growing concerns about climate change and energy security are increasing worldwide efforts to decarbonize the electrical grids, pushing governments and international institutions to promote the use of Renewable Energies (RE). However, two major RE sources -wind and solar energy- present natural fluctuations, and any grid containing big portions of such sources faces the major...

Structure and Torsional Dynamics of the Water Octamer

David Wales, William Cole, James Farrell & Ricjard Saykally
Clusters of eight water molecules play an important role in theoretical analysis of aqueousstructure and dynamics but have proven to be challenging experimental targets. Herewe report the high-resolution spectroscopic characterization of the water octamer.Terahertz (THz) vibration-rotation-tunneling (VRT) spectroscopy resolved 99 transitionswith 1 part per million precision in a narrow range near 46.5 wave numbers, which wereassigned to the h16octamer via detailed isotope dilution experiments. Fitting to a semi-rigid symmetric top model supports predictions of two...

The potential harms of online targeting

Karina Vold, Jessica Whittlestone & Anna Alexandrova
Despite increasing attention being paid to the potential harms of online targeting over the last year, there is still a lack of clarity over what precisely those harms are. To help address this lack of clarity, this submission focuses on question 1: What evidence is there about the harms and benefits of online targeting? This question was discussed at a workshop we held on “The Methodology and Ethics of Targeting” at the Leverhulme Centre for...

Digital manufacturing on a shoestring: Low cost digital solutions for SMEs

D McFarlane, S Ratchev, A Thorne, Ajith Parlikad, Lavindra De Silva, B Schönfuß, Gregory Hawkridge, G Terrazas & Yedige Tlegenov
One of the key findings in a number of recent studies has been that small and medium sized manufacturers (SMEs) have been slow in adopting digital solutions within their organisations. Cost is understood to be one of the key barriers to adoption. Digital Manufacturing on a Shoestring is an approach to increasing the digital capabilities of SMEs via a series of low cost solutions. The programme proposes using off-the-shelf, (possibly non-industrial) components and software to...

Prioritising low cost digital solutions required by manufacturing SMEs: A shoestring approach

B Schönfuß, D McFarlane, N Athanassopoulou, L Salter, Lavindra De Silva & S Ratchev
This paper establishes a reference set of those low cost digital solutions needed by small and medium sized manufacturers – SMEs – and proposes a method for determining development priorities using input from reference groups of SMEs. The paper describes the approach taken to identifying and classifying common digital solutions used in manufacturing and the results from a series of workshops in which company representatives prioritise different solution types to help guide developments.


M Harkey, J Davis, B Lu, L Price, C Eaton, G Lo, M Barbe, R Ward, M Zhang, S-H Liu, KL Lapane, James MacKay, TE McAlindon & JB Driban

Using computing models from particle physics to investigate dose-toxicity correlations in cancer radiotherapy

A Drew, PJ Elwood, K Harrison, Michael Parker, HL Pullen, M Romanchikova, E Silvester, AD Sultana, Michael Sutcliffe, SJ Thomas & PL Yeap
© Published under licence by IOP Publishing Ltd. A system has been developed to provide flexible, efficient and robust processing of radiotherapy planning and treatment data collected in the VoxTox project, which investigates differences between planned and delivered dose, and dose-toxicity correlations. This paper outlines the system requirements and implementation, highlighting the use made of software tools and computing models developed for experiments at the Large Hadron Collider. Experience with VoxTox data processing is summarised.

Research Data Management Newsletter - August 2017

Office Of Scholarly Communication
The Research Data Management newsletter from the Office of Scholarly Communication. The RDM letter covers new research data services from the University of Cambridge, training and events, policy, the research funder landscape and job opportunities. Sign up here: http://www.data.cam.ac.uk/datanews

Axioms for Modelling Cubical Type Theory in a Topos

Ian Orton & Andrew Pitts
The homotopical approach to intensional type theory views proofs of equality as paths. We explore what is required of an interval-like object I in a topos to give a model of type theory in which elements of identity types are functions with domain I. Cohen, Coquand, Huber and Mörtberg give such a model using a particular category of presheaves. We investigate the extent to which their model construction can be expressed in the internal type...

Next generation doctoral training for future infrastructure and built environment

Niamh Gibbons, Janet Lees & Abir Al-Tabbaa
Urbanisation, population growth, scarcity of resources, climatic change, rapid technological development, and the globalisation of both construction and engineering design are driving the pace of change within the construction industry. There is a clear need for engineering education to evolve alongside these changes. Specific challenges facing the construction industry include the delivery of large complex construction projects, creating complex underground spaces and the ramifications of extreme environments. At a doctoral level, there is a need...

Lock-Free algorithms under stochastic schedulers

D Alistarh, Thomas Sauerwald & M Vojnovíc

A case for efficient accelerator design space exploration via Bayesian optimization

B Reagen, JM Hernandez-Lobato, R Adolf, M Gelbart, P Whatmough, GY Wei & D Brooks
In this paper we propose using machine learning to improve the design of deep neural network hardware accelerators. We show how to adapt multi-objective Bayesian optimization to overcome a challenging design problem: Optimizing deep neural network hardware accelerators for both accuracy and energy efficiency. DNN accelerators exhibit all aspects of a challenging optimization space: The landscape is rough, evaluating designs is expensive, the objectives compete with each other, and both design spaces (algorithmic and microarchitectural)...

Student-teacher training with diverse decision tree ensembles

Jeremy Wong & Mark Gales
Student-teacher training allows a large teacher model or ensemble of teachers to be compressed into a single student model, for the purpose of efficient decoding. However, current approaches in automatic speech recognition assume that the state clusters, often defined by Phonetic Decision Trees (PDT), are the same across all models. This limits the diversity that can be captured within the ensemble, and also the flexibility when selecting the complexity of the student model output. This...

Personal data management with the databox: What's inside the box?

Richard Mortier, J Zhao, Jonathon Crowcroft, L Wang, Q Li, H Haddadi, Y Amar, A Crabtree, J Colley, T Lodge, A Brown, D McAuley & C Greenhalgh

Zero reverse recovery in SiC and GaN Schottky diodes: A comparison

L Efthymiou, Giorgia Longobardi, Florin Udrea, E Lin, T Chien & M Chen
© 2016 IEEE. Similarly to the unipolar SiC Schottky diodes, AlGaN/GaN Schottky devices have been suggested to have a negligible reverse recovery current during turn-off and can therefore be switched at very high frequencies with low power losses [1-2]. This study aims to investigate this claim by comparing the reverse recovery characteristic of an AlGaN/GaN diode with that of a SiC diode and a fast recovery Si P-N diode for the same current (4 A)...

Ultra-fast load balancing on scale-free networks

K Bringmann, T Friedrich, M Hoefer, R Rothenberger & Thomas Sauerwald

Joint estimation of linear and non-linear signal-to-noise ratio based on Neural Networks

Francisco Javier Vaquero Caballero, David Ives, Q Zhuge, M O'Sullivan & Sebastian Savory
A novel technique estimating ASE and non-linear SNR is presented. Our method is evaluated by simulations obtaining a std error of 0.23 dB for both ASE and non-linear SNR.

Semantic Localisation via Globally Unique Instance Segmentation

Ignas Budvytis, Patrick Sauer & Roberto Cipolla
In this work we propose a novel approach to semantic localisation. Our work is motivated by the need for environment perception techniques which not only perform self-localisation within a map but also simultaneously recognise surrounding objects. Such capabilities are crucial for computer vision applications which interact with the environment: autonomous driving, augmented reality or robotics. In order to achieve this goal we propose a solution which consists of three key steps. Firstly, a database of...

Psychometric scaling of TID2013 dataset

Aliaksei Mikhailiuk, M Perez-Ortiz & Rafal Mantiuk
TID2013 is a subjective image quality assessment dataset with a wide range of distortion types and over 3000 images. The dataset has proven to be a challenging test for objective quality metrics. The dataset mean opinion scores were obtained by collecting pairwise comparison judgments using the Swiss tournament system, and averaging votes of observers. However, this approach differs from the usual analysis of multiple pairwise comparisons, which involves psychometric scaling of the comparison data using...

The relation between MOS and pairwise comparisons and the importance of cross-content comparisons

E Zerman, V Hulusic, G Valenzise, Rafal Mantiuk & F Dufaux
© 2018, Society for Imaging Science and Technology. Subjective quality assessment is considered a reliable method for quality assessment of distorted stimuli for several multimedia applications. The experimental methods can be broadly categorized into those that rate and rank stimuli. Although ranking directly provides an order of stimuli rather than a continuous measure of quality, the experimental data can be converted using scaling methods into an interval scale, similar to that provided by rating methods....

Ethical issues in research using datasets of illicit origin

Daniel Thomas, Sergio Pastrana Portillo, Alice Hutchings, Richard Clayton & Alastair Beresford
We evaluate the use of data obtained by illicit means against a broad set of ethical and legal issues. Our analysis covers both the direct collection, and secondary uses of, data obtained via illicit means such as exploiting a vulnerability, or unauthorized disclosure. We extract ethical principles from existing advice and guidance and analyse how they have been applied within more than 20 recent peer reviewed papers that deal with illicitly obtained datasets. We find...

Registration Year

  • 2016
  • 2017
  • 2018
  • 2019

Resource Types

  • Collection

Data Centers

  • University of Cambridge