5,381 research outputs found
Metrics for Graph Comparison: A Practitioner's Guide
Comparison of graph structure is a ubiquitous task in data analysis and
machine learning, with diverse applications in fields such as neuroscience,
cyber security, social network analysis, and bioinformatics, among others.
Discovery and comparison of structures such as modular communities, rich clubs,
hubs, and trees in data in these fields yields insight into the generative
mechanisms and functional properties of the graph.
Often, two graphs are compared via a pairwise distance measure, with a small
distance indicating structural similarity and vice versa. Common choices
include spectral distances (also known as distances) and distances
based on node affinities. However, there has of yet been no comparative study
of the efficacy of these distance measures in discerning between common graph
topologies and different structural scales.
In this work, we compare commonly used graph metrics and distance measures,
and demonstrate their ability to discern between common topological features
found in both random graph models and empirical datasets. We put forward a
multi-scale picture of graph structure, in which the effect of global and local
structure upon the distance measures is considered. We make recommendations on
the applicability of different distance measures to empirical graph data
problem based on this multi-scale view. Finally, we introduce the Python
library NetComp which implements the graph distances used in this work
On the construction of probabilistic Newton-type algorithms
It has recently been shown that many of the existing quasi-Newton algorithms
can be formulated as learning algorithms, capable of learning local models of
the cost functions. Importantly, this understanding allows us to safely start
assembling probabilistic Newton-type algorithms, applicable in situations where
we only have access to noisy observations of the cost function and its
derivatives. This is where our interest lies.
We make contributions to the use of the non-parametric and probabilistic
Gaussian process models in solving these stochastic optimisation problems.
Specifically, we present a new algorithm that unites these approximations
together with recent probabilistic line search routines to deliver a
probabilistic quasi-Newton approach.
We also show that the probabilistic optimisation algorithms deliver promising
results on challenging nonlinear system identification problems where the very
nature of the problem is such that we can only access the cost function and its
derivative via noisy observations, since there are no closed-form expressions
available
Towards business integration as a service 2.0 (BIaaS 2.0)
Cloud Computing Business Framework (CCBF) is a framework for designing and implementation of Could Computing solutions. This proposal focuses on how CCBF can help to address linkage in Cloud Computing implementations. This leads to the development of Business Integration as a Service 1.0 (BIaaS 1.0) allowing different services, roles and functionalities to work together in a linkage-oriented framework where the outcome of one service can be input to another, without the need to translate between domains or languages. BIaaS 2.0 aims to allow automation, enhanced security, advanced risk modelling and improved collaboration between processes in BIaaS 1.0. The benefits from adopting BIaaS 1.0 and developing BIaaS 2.0 are illustrated using a case study from the University of Southampton and several collaborators including IBM US. BIaaS 2.0 can work with mainstream technologies such as scientific workflows, and the proposal and demonstration of BIaaS 2.0 will be aimed to certainly benefit industry and academia. © 2011 IEEE
Inelastic neutron scattering studies of the quantum frustrated magnet clinoatacamite, -Cu2(OD)3Cl, a proposed valence bond solid (VBS)
The frustrated magnet clinoatacamite, -Cu(OH)Cl, is
attracting a lot of interest after suggestions that at low temperature it forms
an exotic quantum state termed a Valence Bond Solid (VBS) made from dimerised
Cu () spins.\cite{Lee_clinoatacamite} Key to the arguments
surrounding this proposal were suggestions that the kagom\'e planes in the
magnetic pyrochlore lattice of clinoatacamite are only weakly coupled, causing
the system to behave as a quasi-2-dimensional magnet. This was reasoned from
the near 95 angles made at the bridging oxygens that mediate exchange
between the Cu ions that link the kagom\'e planes.
Recent work pointed out that this exchange model is inappropriate for
-Cu(OH)Cl, where the oxygen is present as a
-OH.\cite{Wills_JPC} Further, it used symmetry calculations and neutron
powder diffraction to show that the low temperature magnetic structure (
K) was canted and involved significant spin ordering on all the Cu
spins, which is incompatible with the interpretation of simultaneous VBS and
N\'eel ordering. Correspondingly, clinoatacamite is best considered a distorted
pyrochlore magnet. In this report we show detailed inelastic neutron scattering
spectra and revisit the responses of this frustrated quantum magnet.Comment: Proceedings of The International Conference on Highly Frustrated
Magnetism 2008 (HFM2008
Providing value to a business using a lightweight design system to support knowledge reuse by designers
This paper describes an alternative approach to knowledge based systems in engineering than traditional geometry or explicit knowledge focused systems. Past systems have supported product optimisation rather than creative solutions and provide little benefit to businesses for bespoke and low volume products or products which do not benefit from optimisation. The approach here addresses this by supporting the creativity of designers through codified tacit knowledge and encouraging knowledge reuse for bespoke product development, in particular for small to medium sized enterprises. The implementation and evaluation of the approach is described within a company producing bespoke fixtures and tooling in shorter than average lead times. The active support of knowledge management in the company is intended to add value to the business by further reducing the lead times of the designs and creating a positive impact to business processes. The evaluation demonstrates a viable alternative framework to the traditional management of knowledge in engineering, which could be implemented by other small to medium enterprises
Pseudo-half-metalicity in the double perovskite SrCrReO from density-functional calculations
The electronic structure of the spintronic material SrCrReO is
studied by means of full-potential linear muffin-tin orbital method. Scalar
relativistic calculations predict SrCrReO to be half-metallic with a
magnetic moment of 1 . When spin-orbit coupling is included, the
half-metallic gap closes into a pseudo-gap, and an unquenched rhenium orbital
moment appears, resulting in a significant increase of the total magnetic
moment to 1.28 . This moment is significantly larger than the
experimental moment of 0.9 . A possible explanation of this discrepancy
is that the anti-site disorder in SrCrReO is significantly larger than
hitherto assumed.Comment: 3 Pages, 1 figure, 1 Tabl
Expert Finding by Capturing Organisational Knowledge from Legacy Documents
Organisations capitalise on their best knowledge through the improvement of shared expertise which leads to a higher level of productivity and competency. The recognition of the need to foster the sharing of expertise has led to the development of expert finder systems that hold pointers to experts who posses specific knowledge in organisations. This paper discusses an approach to locating an expert through the application of information retrieval and analysis processes to an organization’s existing information resources, with specific reference to the engineering design domain. The approach taken was realised through an expert finder system framework. It enables the relationships of heterogeneous information sources with experts to be factored in modelling individuals’ expertise. These valuable relationships are typically ignored by existing expert finder systems, which only focus on how documents relate to their content. The developed framework also provides an architecture that can be easily adapted to different organisational environments. In addition, it also allows users to access the expertise recognition logic, giving them greater trust in the systems implemented using this framework. The framework were applied to real world application and evaluated within a major engineering company
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