oalib

Publish in OALib Journal

ISSN: 2333-9721

APC: Only $99

Submit

Any time

2019 ( 1 )

2018 ( 10 )

2017 ( 9 )

2016 ( 8 )

Custom range...

Search Results: 1 - 10 of 4503 matches for " Neil Reid "
All listed articles are free for downloading (OA Articles)
Page 1 /4503
Display every page Item
Diffusion in Networks With Overlapping Community Structure
Fergal Reid,Neil Hurley
Computer Science , 2011,
Abstract: In this work we study diffusion in networks with community structure. We first replicate and extend work on networks with non-overlapping community structure. We then study diffusion on network models that have overlapping community structure. We study contagions in the standard SIR model, and complex contagions thought to be better models of some social diffusion processes. Finally, we investigate diffusion on empirical networks with known overlapping community structure, by analysing the structure of such networks, and by simulating contagion on them. We find that simple and complex contagions can spread fast in networks with overlapping community structure. We also find that short paths exist through overlapping community structure on empirical networks.
Collaboration in Local Economic Development: The Case of Toledo
Neil Reid,Bruce W. Smith
Urbani Izziv , 2012,
Abstract: Many American communities place a high priority on retaining and attracting innovative industries. However, in most American metropolitan areas, the responsibility for local economic development is fragmented along jurisdictional and institutional lines. The result of this fragmentation is that local economic development is often chaotic with no one individual, agency, or jurisdiction in control, which may inhibit the effectiveness of local economic development efforts. To address these challenges and more effectively utilize resources, there has been greater emphasis recently on regional collaboration in local economic development. The purpose of this paper is to measure the extent of collaboration among local economic development professionals in the Toledo, Ohio Metropolitan Statistical Area and to identify the extent to which these interactions constitute a social network. We believe that the existence of a strong social network among economic development professionals is critical to overcome some of the negative effects of jurisdictional and institutional fragmentation. While there is a core network of relatively dense collaboration in northwest Ohio, that network does not span the entire metropolitan area. A high level of local interactions occurs, but there are few “global pipelines” outside the region. A potential challenge for economic development in the region is to avoid “lock in”, which will make it more difficult to attract innovative industries or diversify the economy in order to decrease the traditional dependence on the auto industry.
Automatic Reasoning about Causal Events in Surveillance Video
Neil M. Robertson,Ian D. Reid
EURASIP Journal on Image and Video Processing , 2011, DOI: 10.1155/2011/530325
Abstract:
Partitioning Breaks Communities
Fergal Reid,Aaron McDaid,Neil Hurley
Computer Science , 2011,
Abstract: Considering a clique as a conservative definition of community structure, we examine how graph partitioning algorithms interact with cliques. Many popular community-finding algorithms partition the entire graph into non-overlapping communities. We show that on a wide range of empirical networks, from different domains, significant numbers of cliques are split across the separate partitions produced by these algorithms. We then examine the largest connected component of the subgraph formed by retaining only edges in cliques, and apply partitioning strategies that explicitly minimise the number of cliques split. We further examine several modern overlapping community finding algorithms, in terms of the interaction between cliques and the communities they find, and in terms of the global overlap of the sets of communities they find. We conclude that, due to the connectedness of many networks, any community finding algorithm that produces partitions must fail to find at least some significant structures. Moreover, contrary to traditional intuition, in some empirical networks, strong ties and cliques frequently do cross community boundaries; much community structure is fundamentally overlapping and unpartitionable in nature.
Percolation Computation in Complex Networks
Fergal Reid,Aaron McDaid,Neil Hurley
Computer Science , 2012,
Abstract: K-clique percolation is an overlapping community finding algorithm which extracts particular structures, comprised of overlapping cliques, from complex networks. While it is conceptually straightforward, and can be elegantly expressed using clique graphs, certain aspects of k-clique percolation are computationally challenging in practice. In this paper we investigate aspects of empirical social networks, such as the large numbers of overlapping maximal cliques contained within them, that make clique percolation, and clique graph representations, computationally expensive. We motivate a simple algorithm to conduct clique percolation, and investigate its performance compared to current best-in-class algorithms. We present improvements to this algorithm, which allow us to perform k-clique percolation on much larger empirical datasets. Our approaches perform much better than existing algorithms on networks exhibiting pervasively overlapping community structure, especially for higher values of k. However, clique percolation remains a hard computational problem; current algorithms still scale worse than some other overlapping community finding algorithms.
Determining Glomerular Filtration Rate in Homozygous Sickle Cell Disease: Utility of Serum Creatinine Based Estimating Equations
Monika R. Asnani, O’Neil Lynch, Marvin E. Reid
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0069922
Abstract: Background Various estimating equations have been developed to estimate glomerular filtration rate (GFR) for use in clinical practice. However, the unique renal physiological and pathological processes that occur in sickle cell disease (SCD) may invalidate these estimates in this patient population. This study aims to compare GFR estimated using common existing GFR predictive equations to actual measured GFR in persons with homozygous SCD. If the existing equations perform poorly, we propose to develop a new estimating equation for use in persons with SCD. Methods 98 patients with the homozygous SS disease (55 females: 43 males; mean age 34±2.3 years) had serum measurements of creatinine, as well as had GFR measured using 99mTc-DTPA nuclear renal scan. GFR was estimated using the Modification of Diet in Renal Disease (MDRD), Cockcroft-Gault (CG), and the serum creatinine based CKD-EPI equations. The Bland-Altman limit of agreement method was used to determine agreement between measured and estimated GFR values. A SCD-specific estimating equation for GFR (JSCCS-GFR equation) was generated by means of multiple regression via backward elimination. Results The mean measured GFR±SD was 94.9±27.4 mls/min/1.73 m2 BSA, with a range of 6.4–159.0 mls/min/1.73 m2. The MDRD and CG equations both overestimated GFR, with the agreement worsening with higher GFR values. The serum creatinine based CKD-EPI equation performed relatively well, but with a systematic bias of about 45 mls/min. The new equation developed resulted in a better fit to our sickle cell disease data than the MDRD equation. Conclusion Current estimating equations, other than the CKD-EPI equation, do not perform very accurately in persons with homozygous SS disease. A fairly accurate estimating equation, suitable for persons with GFR >60 mls/min/1.73 m2 has been developed from our dataset and validated within a simulated dataset.
Detecting highly overlapping community structure by greedy clique expansion
Conrad Lee,Fergal Reid,Aaron McDaid,Neil Hurley
Physics , 2010,
Abstract: In complex networks it is common for each node to belong to several communities, implying a highly overlapping community structure. Recent advances in benchmarking indicate that existing community assignment algorithms that are capable of detecting overlapping communities perform well only when the extent of community overlap is kept to modest levels. To overcome this limitation, we introduce a new community assignment algorithm called Greedy Clique Expansion (GCE). The algorithm identifies distinct cliques as seeds and expands these seeds by greedily optimizing a local fitness function. We perform extensive benchmarks on synthetic data to demonstrate that GCE's good performance is robust across diverse graph topologies. Significantly, GCE is the only algorithm to perform well on these synthetic graphs, in which every node belongs to multiple communities. Furthermore, when put to the task of identifying functional modules in protein interaction data, and college dorm assignments in Facebook friendship data, we find that GCE performs competitively.
Seeding for pervasively overlapping communities
Conrad Lee,Fergal Reid,Aaron McDaid,Neil Hurley
Computer Science , 2011, DOI: 10.1103/PhysRevE.83.066107
Abstract: In some social and biological networks, the majority of nodes belong to multiple communities. It has recently been shown that a number of the algorithms that are designed to detect overlapping communities do not perform well in such highly overlapping settings. Here, we consider one class of these algorithms, those which optimize a local fitness measure, typically by using a greedy heuristic to expand a seed into a community. We perform synthetic benchmarks which indicate that an appropriate seeding strategy becomes increasingly important as the extent of community overlap increases. We find that distinct cliques provide the best seeds. We find further support for this seeding strategy with benchmarks on a Facebook network and the yeast interactome.
Key health promotion factors among male members of staff at a higher educational institution: A cross-sectional postal survey
Alena Vasianovich, Edwin R van Teijlingen, Garth Reid, Neil W Scott
BMC Public Health , 2008, DOI: 10.1186/1471-2458-8-58
Abstract: A descriptive cross-sectional survey was conducted among all male staff employed by a Higher Education institute in Scotland using a postal self-completed questionnaire. A total of 1,335 questionnaires were distributed and 501 were returned completed (38% return rate). The data were analysed using SPSS 13.0 for Windows.Less than 10% currently smoked and almost 44% of these smokers were light smokers. Marital status, job title, consumption of alcohol and physical activity level were the major factors associated with smoking behaviour. Men in manual jobs were far more likely to smoke. Nearly all (90%) consumed alcohol, and almost 37% had more than recommended eight units of alcohol per day at least once a week and 16% had more than 21 units weekly. Younger men reported higher amount of units of alcohol on their heaviest day and per week. Approximately 80% were physically active, but less than 40% met the current Government guidelines for moderate physical activity. Most men wanted to increase their activity level.There are areas of health-related behaviour, which should be addressed in populations of this kind. Needs assessment could indicate which public health interventions would be most appropriately aimed at this target group. However, the low response rate calls for some caution in interpreting our findings.Men's health is poor compared to women's according to a range of measures and varies across ethnicity and socio-economic class [1]. In 2003–05 the average life expectancy at birth of females born in the UK was 80 years compared to about 76 years for males [2]. Men are more likely than women to be mentally ill and they are in greater risk of heart disease and stroke; men in routine and manual jobs are more likely to smoke and have chronic health problems than other men; diagnoses of both prostate and testicular cancer have increased since the early 1990s [1]. The suicide rate amongst young men has increased by 250% over the past two decades [1]. Slightly more t
The Queen and I: Neural Correlates of Altered Self-Related Cognitions in Major Depressive Episode
May Sarsam, Laura M. Parkes, Neil Roberts, Graeme S. Reid, Peter Kinderman
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0078844
Abstract: Background Pervasive negative thoughts about the self are central to the experience of depression. Brain imaging studies in the general population have localised self-related cognitive processing to areas of the medial pre-frontal cortex. Aims To use fMRI to compare the neural correlates of self-referential processing in depressed and non-depressed participants. Method Cross-sectional comparison of regional activation using Blood Oxygen Level Dependent (BOLD) fMRI in 13 non-medicated participants with major depressive episode and 14 comparison participants, whilst carrying out a self-referential cognitive task. Results Both groups showed significant activation of the dorsomedial pre-frontal cortex and posterior cingulate cortex in the ‘self-referent’ condition. The depressed group showed significantly greater activation in the medial superior frontal cortex during the self-referent task. No difference was observed between groups in the ‘other-referent’ condition. Conclusions Major depressive episode is associated with specific neurofunctional changes related to self-referential processing.
Page 1 /4503
Display every page Item


Home
Copyright © 2008-2017 Open Access Library. All rights reserved.