Finding structures in information networks using the affinity network

This thesis proposes a novel graphical model for inference called the Affinity Network,which displays the closeness between pairs of variables and is an alternative to Bayesian Networks and Dependency Networks. The Affinity Network shares some similarities with Bayesian Networks and Dependency Networks but avoids their heuristic and stochastic graph construction algorithms by using a message passing scheme. A comparison with the above two instances of graphical models is given for sparse discrete and continuous medical data and data taken from the UCI machine learning repository. The experimental study reveals that the Affinity Network graphs tend to be more accurate on the basis of an exhaustive search with the small datasets. Moreover, the graph construction algorithm is faster than the other two methods with huge datasets. The Affinity Network is also applied to data produced by a synchronised system. A detailed analysis and numerical investigation into this dynamical system is provided and it is shown that the Affinity Network can be used to characterise its emergent behaviour even in the presence of noise.

New developments in library orientation and information literacy:regenerating library services for new students

Over the last six years, Aston University Library & Information Services Induction Team have worked on the Welcome experience for new and returning students to the Library.  The article provides an overview of the Induction programme and how it has evolved to engage students pre and post arrival to the University. 

Stepping Stones to Information Literacy: a PebblePad case study

Aston University has recently made PebblePad, an e-portfolio or personal learning system, available to all students within the University. The customisable Profiles within PebblePad allow students to self-declare their skills in particular areas, attaching evidence of their skills or an action plan for improvement to each statement. Formal Information Literacy (IL) teaching within Aston University is currently limited to Library & Information Services (LIS) Information Specialists delivering a maximum of one session to each student during each level of their degree. However, many of the skills are continually developed by students during the course of their academic studies. For this project, an IL skills profile was created within PebblePad, which was then promoted to groups of staff and students to complete during the academic session 2009-10. Functionality within PebblePad allowed students to share their IL skills profile, evidence, action plans or any other items they felt were appropriate with an LIS Information Specialist who was able to add comments and offer suggestions for activities to help the student to develop further. Activities were closely related to students’ coursework where possible: suggesting a student kept a short reflective log of their information searching and evaluating process for an upcoming essay, for example. Feedback on the usefulness of the IL Profile will be sought from students through focus groups and the communication tools in PebblePad. In this way, we hope to make students more aware of their IL skills and to offer IL skills support over a longer period of time than a single session can provide. We will present preliminary conclusions about the practicalities and benefits of a self-declaration approach to developing IL skills in students at Aston University.

Equilibration through local information exchange in networks

We study the equilibrium states of energy functions involving a large set of real variables, defined on the links of sparsely connected networks, and interacting at the network nodes, using the cavity and replica methods. When applied to the representative problem of network resource allocation, an efficient distributed algorithm is devised, with simulations showing full agreement with theory. Scaling properties with the network connectivity and the resource availability are found. © 2006 The American Physical Society.

Investigating the supply and demand relationship in a profession: the English and Welsh schools of librarianship and information Studies and the Higher Education Library and Information Services employment sector in England and Wales.

Concern has been expressed in the professional literature - borne out by professional experience and observation - that the supply and demand relationship existing between the 13 English and Welsh Library and Information Studies (LIS) Schools (as providers of `First Professional' staff) and the Higher Education Library and Information Services (HE LIS) sector of England and Wales (as one group of employers of such staff) is unsatisfactory and needs attention. An appropriate methodology to investigate this problem was devised. A basic content analysis of Schools' curricular and recruitment material intended for public consumption was undertaken to establish an overview of the LIS initial professional education system in England and Wales, and to identify and analyse any covert messages imparted to readers. This was followed by a mix of Main Questionnaires and Semi-Structured Interviews with appropriate populations. The investigation revealed some serious areas of dissatisfaction by the HE LIS Chiefs with the role and function of the Schools. Considerable divergence of views emerged on the state of the working relationships between the two sectors and on the Schools' successes in meeting the needs of the HE LIS sector and on CPD provision. There were, however, areas of substantial and consistent agreement between the two sectors. The main implications of the findings were that those areas encompassing divergence of views were worrying and needed addressing by both sides. Possible ways forward included recommendations on improving the image of the profession purveyed by the Schools; the forming of closer and more effective inter-sectoral relationships; recognising fully the importance of `practicum' and increasing and sustaining the network of `practicum' providers.

Combining temporal and spectral information with spatial mapping to identify differences between phonological and semantic networks:a magnetoencephalographic approach

Early, lesion-based models of language processing suggested that semantic and phonological processes are associated with distinct temporal and parietal regions respectively, with frontal areas more indirectly involved. Contemporary spatial brain mapping techniques have not supported such clear-cut segregation, with strong evidence of activation in left temporal areas by both processes and disputed evidence of involvement of frontal areas in both processes. We suggest that combining spatial information with temporal and spectral data may allow a closer scrutiny of the differential involvement of closely overlapping cortical areas in language processing. Using beamforming techniques to analyze magnetoencephalography data, we localized the neuronal substrates underlying primed responses to nouns requiring either phonological or semantic processing, and examined the associated measures of time and frequency in those areas where activation was common to both tasks. Power changes in the beta (14-30 Hz) and gamma (30-50 Hz) frequency bandswere analyzed in pre-selected time windows of 350-550 and 500-700ms In left temporal regions, both tasks elicited power changes in the same time window (350-550 ms), but with different spectral characteristics, low beta (14-20 Hz) for the phonological task and high beta (20-30 Hz) for the semantic task. In frontal areas (BA10), both tasks elicited power changes in the gamma band (30-50 Hz), but in different time windows, 500-700ms for the phonological task and 350-550ms for the semantic task. In the left inferior parietal area (BA40), both tasks elicited changes in the 20-30 Hz beta frequency band but in different time windows, 350-550ms for the phonological task and 500-700ms for the semantic task. Our findings suggest that, where spatial measures may indicate overlapping areas of involvement, additional beamforming techniques can demonstrate differential activation in time and frequency domains. © 2012 McNab, Hillebrand, Swithenby and Rippon.

Understanding supply chain disruption risk with the aid of social networks and information flows analysis

Supply Chain Risk Management (SCRM) has become a popular area of research and study in recent years. This can be highlighted by the number of peer reviewed articles that have appeared in academic literature. This coupled with the realisation by companies that SCRM strategies are required to mitigate the risks that they face, makes for challenging research questions in the field of risk management. The challenge that companies face today is not only to identify the types of risks that they face, but also to assess the indicators of risk that face them. This will allow them to mitigate that risk before any disruption to the supply chain occurs. The use of social network theory can aid in the identification of disruption risk. This thesis proposes the combination of social networks, behavioural risk indicators and information management, to uniquely identify disruption risk. The propositions that were developed from the literature review and exploratory case study in the aerospace OEM, in this thesis are:- By improving information flows, through the use of social networks, we can identify supply chain disruption risk. - The management of information to identify supply chain disruption risk can be explored using push and pull concepts. The propositions were further explored through four focus group sessions, two within the OEM and two within an academic setting. The literature review conducted by the researcher did not find any studies that have evaluated supply chain disruption risk management in terms of social network analysis or information management studies. The evaluation of SCRM using these methods is thought to be a unique way of understanding the issues in SCRM that practitioners face today in the aerospace industry.

Survival data analysis using neural networks

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The opportunity recognition process:the mechanisms by which entrepreneurial opportunities are recognised and the role played by social networks in this process

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Innovation and policy networks:the social shaping of BSE-related technologies and the inadequate assessmant of related risks

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Combining deformable templates and neural networks for HCR

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Neural networks for modelling wind vectors

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Neural networks applied to ignition timing calibration

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Pulse coupled neural networks:an exploration of parameterisation methods

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