7,989 research outputs found
A highly scalable Met Office NERC Cloud model
Large Eddy Simulation is a critical modelling tool for scien- tists investigating atmospheric flows, turbulence and cloud microphysics. Within the UK, the principal LES model used by the atmospheric research community is the Met Office Large Eddy Model (LEM). The LEM was originally devel- oped in the late 1980s using computational techniques and assumptions of the time, which means that the it does not scale beyond 512 cores. In this paper we present the Met Office NERC Cloud model, MONC, which is a re-write of the existing LEM. We discuss the software engineering and architectural decisions made in order to develop a flexible, extensible model which the community can easily customise for their own needs. The scalability of MONC is evaluated, along with numerous additional customisations made to fur- ther improve performance at large core counts. The result of this work is a model which delivers to the community signifi- cant new scientific modelling capability that takes advantage of the current and future generation HPC machine
Maintaining credibility when communicating uncertainty: The role of communication format
Research into risk communication has commonly highlighted
the disparity between the meaning intended by the
communicator and what is understood by the recipient. Such
miscommunications will have implications for perceived trust
and expertise of the communicator, but it is not known whether
this differs according to the communication format. We
examined the effect of using verbal, numerical and mixed
communication formats on perceptions of credibility and
correctness, as well as whether they influenced a decision to
evacuate, both before and after an âerroneousâ prediction (i.e.
an âunlikelyâ event occurs, or a âlikelyâ event does not occur).
We observed no effect of communication format on any of the
measures pre-outcome, but found the numerical format was
perceived as less incorrect, as well as more credible than the
other formats after an âerroneousâ prediction, but only when
low probability expressions were used. Our findings suggest
numbers should be used in consequential risk communications
Communicating Uncertainty: The Role of Communication Format in Maximising Understanding and Maintaining Credibility
This thesis investigates the effect of communication format on the understanding of uncertainty communications and considers the implications of these findings for a communicatorâs perceived credibility. The research compares five formats: verbal probability expressions (VPEs; e.g., âunlikelyâ); numerical expressions â point (e.g., â20% likelihoodâ) and range estimates (e.g., â10â30% likelihoodâ); and mixed expressions in two orders (verbal-numerical, e.g., âunlikely [20% likelihood]â and numerical-verbal format, e.g., â20% likelihood [unlikely]â). Using the âwhich-outcomeâ methodology, we observe that when participants are asked to estimate the probability of the outcome of a natural hazard that is described as âunlikelyâ, the majority indicate outcomes with a value exceeding the maximum value shown, equivalent to a 0% probability. Extending this work to numerical and mixed formats, we find that 0% interpretations are also given to communications using a verbal-numerical format (Chapter 2). If âunlikelyâ is interpreted as referring to events which will never occur, there could be implications for a communicatorâs perceived credibility should an âunlikelyâ event actually occur. In the low probability domain, we find a communicator who uses a verbal format in their prediction is perceived as less credible and less correct than one who uses a numerical format. However, in the high probability domain (where a âlikelyâ event does not occur) such an effect of format is not consistently observed (Chapter 3). We suggest âdirectionalityâoutcome congruenceâ can explain these findings. For example, the negatively directional term âunlikelyâ led to harsher ratings because the outcome was counter to the original focus of the prediction (i.e., on its non-occurrence). Comparing communications featuring positively and negatively directional VPEs, we find that communicators are perceived as less credible and less correct given directionalityâoutcome incongruence (Chapter 4). Our findings demonstrate the influence of pragmatics on (a) the understanding of uncertainty communications and (b) perceived communicator credibility
Stochastic rounding and reduced-precision fixed-point arithmetic for solving neural ordinary differential equations
Although double-precision floating-point arithmetic currently dominates
high-performance computing, there is increasing interest in smaller and simpler
arithmetic types. The main reasons are potential improvements in energy
efficiency and memory footprint and bandwidth. However, simply switching to
lower-precision types typically results in increased numerical errors. We
investigate approaches to improving the accuracy of reduced-precision
fixed-point arithmetic types, using examples in an important domain for
numerical computation in neuroscience: the solution of Ordinary Differential
Equations (ODEs). The Izhikevich neuron model is used to demonstrate that
rounding has an important role in producing accurate spike timings from
explicit ODE solution algorithms. In particular, fixed-point arithmetic with
stochastic rounding consistently results in smaller errors compared to single
precision floating-point and fixed-point arithmetic with round-to-nearest
across a range of neuron behaviours and ODE solvers. A computationally much
cheaper alternative is also investigated, inspired by the concept of dither
that is a widely understood mechanism for providing resolution below the least
significant bit (LSB) in digital signal processing. These results will have
implications for the solution of ODEs in other subject areas, and should also
be directly relevant to the huge range of practical problems that are
represented by Partial Differential Equations (PDEs).Comment: Submitted to Philosophical Transactions of the Royal Society
On the role of pre and post-processing in environmental data mining
The quality of discovered knowledge is highly depending on data quality. Unfortunately real data use to contain noise, uncertainty, errors, redundancies or even irrelevant information. The more complex is the reality to be analyzed, the higher the risk of getting low quality data. Knowledge Discovery from Databases (KDD) offers a global framework to prepare data in the right form to perform correct analyses. On the other hand, the quality of decisions taken upon KDD results, depend not only on the quality of the results themselves, but on the capacity of the system to communicate those results in an understandable form. Environmental systems are particularly complex and environmental users particularly require clarity in their results. In this paper some details about how this can be achieved are provided. The role of the pre and post processing in the whole process of Knowledge Discovery in environmental systems is discussed
The doctoral research abstracts. Vol:7 2015 / Institute of Graduate Studies, UiTM
Foreword:
The Seventh Issue of The Doctoral Research Abstracts captures the novelty of
65 doctorates receiving their scrolls in UiTMâs 82nd Convocation in the field of
Science and Technology, Business and Administration, and Social Science and
Humanities. To the recipients I would like to say that you have most certainly
done UiTM proud by journeying through the scholastic path with its endless
challenges and impediments, and persevering right till the very end.
This convocation should not be regarded as the end of your highest scholarly
achievement and contribution to the body of knowledge but rather as the
beginning of embarking into high impact innovative research for the
community and country from knowledge gained during this academic
journey.
As alumni of UiTM, we will always hold you dear to our hearts. A new
âhandshakeâ is about to take place between you and UiTM as joint
collaborators in future research undertakings. I envisioned a strong
research pact between you as our alumni and UiTM in breaking the
frontier of knowledge through research.
I wish you all the best in your endeavour and may I offer my
congratulations to all the graduands. âUiTM sentiasa dihati kuâ /
Tan Sri Datoâ Sri Prof Ir Dr Sahol Hamid Abu Bakar , FASc, PEng
Vice Chancellor
Universiti Teknologi MAR
Recommended from our members
Communicative Information Visualizations: How to make data more understandable by the general public
Although data visualizations have been around for centuries and are encountered frequently by the general public, existing evidence suggests that a significant portion of people have difficulty understanding and interpreting them. It might not seem like a big problem when a reader misreads a weather map and finds themselves without an umbrella in a rainstorm, but for those who lack the means, experience, or ability to make sense of data, misreading a data visualization concerning public health and safety could be a matter of life and death. However, figuring out how to make visualizations truly usable for a diverse audience remains difficult. In my thesis, I examined three areas where altering current practices may help make data visualizations more understandable and impactful in the future
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