2,449 research outputs found
A semi-supervised approach to visualizing and manipulating overlapping communities
When evaluating a network topology, occasionally data structures cannot be segmented into absolute, heterogeneous groups. There may be a spectrum to the dataset that does not allow for this hard clustering approach and may need to segment using fuzzy/overlapping communities or cliques. Even to this degree, when group members can belong to multiple cliques, there leaves an ever present layer of doubt, noise, and outliers caused by the overlapping clustering algorithms. These imperfections can either be corrected by an expert user to enhance the clustering algorithm or to preserve their own mental models of the communities. Presented is a visualization that models overlapping community membership and provides an interactive interface to facilitate a quick and efficient means of both sorting through large network topologies and preserving the user's mental model of the structure. © 2013 IEEE
Adaptive visualization of research communities
Adaptive visualization approaches attempt to tune the content and the topology of information visualization to various user characteristics. While adapting visualization to user cognitive traits, goals, or knowledge has been relatively well explored, some other user characteristics have received no attention. This paper presents a methodology to adapt a traditional cluster-based visualization of communities to user individual model of community organization. This class of user-adapted visualization is not only achievable, but expected due to real world situation where users cannot be segmented into heterogeneous communities since many users have affinity to more than one group. An interactive clustering and visualization approach presented in the paper allows the user communicate their personal mental models of overlapping communities to the clustering algorithm itself and obtain a community visualization image that more realistically fits their prospects
Students’ perceptions of online reading behaviour at an institution of higher learning in South Africa: A pilot project
Technological advances and the internet have altered the way people engage with reading material. Students’ reading preferences are increasingly screen-based as most students prefer and are required to use online reading in higher education institutions. The research explored the perceived impact of online reading on students’ reading comprehension and academic performance.
A non-experimental research design was utilised for this survey, typically including the quantitative domain and, to a lesser extent, the qualitative domain.
Seventy-one students who were available and consented completed the survey and included 20 first year, 19 second year, 22 third year and ten fourth year students.
The results from a pilot study conducted on first to final year students at a department from a Health Care Sciences University indicated mostly positive feedback regarding the perceived effect of online reading on reading comprehension and academic performance. Most students prefer online reading as it is easily accessible, visually interactive and provides unlimited access to information. The results showed correlations and contradictions to the findings presented in the literature.
Conclusions, recommendations and implications are made based on the findings of the study. The findings indicate that students, especially first-year entering students, should be prepared for online reading and be made aware of online reading techniques to support them in attaining academic literacy. These reading techniques could improve the throughput rate and lower the dropout rate in higher institutions in South Africa
Superparamagnetic behaviour of antiferromagnetic DyPO4 nanoparticles
We report on the low-temperature magnetic ac-susceptibility of
antiferromagnetic DyPO4 nanoparticles with a very high surface to volume ratio.
The results are interpreted in terms of superparamagnetic relaxation of the
Neel vector arising from a relatively large number approx 0.2 Na of
uncompensated spins probably existing on the surface of the nanoparticles. The
activation energy of the relaxation process is found to be Ea / kB = (2.6+-0.1)
K within a model taking into account the magnetic interaction between
nanoparticles.Comment: 3 pages, 1 figure, Espcrc2, ICM0
Using appreciative inquiry to develop a research capacity development programme
With academics struggling to find the balance between research and teaching, there is a
need to identify strategies that would assist academics in making the necessary changes
to manage their time. Appreciative Inquiry (AI) is a strength-based change process
based on the premise that academics are change agents who possess knowledge and
experience that can make a difference. This article proposes an AI methodological
framework for an academic development strategy focussing on integrating research into
teaching. Currently, few measures exist that focus on assisting academics in incorporating
research into their teaching and learning practices. The article aims to describe the
strategies used to initiate a process that builds on the positive experiences of academics
in teaching in an environment where academics may become overwhelmed when
focussing only on barriers. The process described focuses on the aims of the academic
development programme at each stage as well as the roles of the participants. The AI
approach is a novel framework that can be used to initiate research capacity building
among academics.Department of HE and Training approved lis
Superconductivity in a Molecular Metal Cluster Compound
Compelling evidence for band-type conductivity and even bulk
superconductivity below K has been found in
Ga-NMR experiments in crystalline ordered, giant Ga
cluster-compounds. This material appears to represent the first realization of
a theoretical model proposed by Friedel in 1992 for superconductivity in
ordered arrays of weakly coupled, identical metal nanoparticles.Comment: 5 pages, 4 figure
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