Metal-oxide-metal point contact junction detectors

The detection mechanism(s) and design of a mechanically stable metal-oxide-metal point contact junction detector are considered. A prototype for a mechanically stable device has been constructed and tested. A technique has been developed which accurately predicts microwave video detector and heterodyne mixer SIM (semiconductor-insulator-metal) diode performance from low dc frequency volt-ampere curves. The difference in contact potential between the two metals and geometrically induced rectification constitute the detection mechanisms

#LTHEchat No 26 Learners’ Experiences of e-Learning with @ELESIG @rjsharpe and @leohavemann

Blog post and record (storified tweets) of tweet chat: #LTHEchat No 26 focusing on learners’ experiences of e-learning, with guest hosts Professor Rhona Sharpe (Oxford Brookes) and Leo Havemann (Birkbeck). #LTHEchat is the Learning and Teaching in Higher Education tweet chat - a conversation on Twitter using the #LTHEchat hashtag

Towards Developing AI Literacy: Three Student Provocations on AI in Higher Education

This article reports the reflections of the co-organisers on a recent AI in Higher Education event which was led by students from the University of Leeds and University College London. While academic communities and experts have contributed significantly to the discourse, students’ perspectives have so far been underrepresented. Three student provocations are shared which provided the focus of the discussions during the event. The student co-authors present future-gazing visions of the impact of AI in higher education and beyond. Our collaborative reflections highlight that whether we are seeking to bring about desirable, AI-empowered futures, or aspiring to evade undesirable consequences of these new technologies, it will be vital to develop and enhance the AI literacy of students and educators alike in order to make use of it ethically, creatively and critically

Identifying Overlapping and Hierarchical Thematic Structures in Networks of Scholarly Papers: A Comparison of Three Approaches

We implemented three recently proposed approaches to the identification of overlapping and hierarchical substructures in graphs and applied the corresponding algorithms to a network of 492 information-science papers coupled via their cited sources. The thematic substructures obtained and overlaps produced by the three hierarchical cluster algorithms were compared to a content-based categorisation, which we based on the interpretation of titles and keywords. We defined sets of papers dealing with three topics located on different levels of aggregation: h-index, webometrics, and bibliometrics. We identified these topics with branches in the dendrograms produced by the three cluster algorithms and compared the overlapping topics they detected with one another and with the three pre-defined paper sets. We discuss the advantages and drawbacks of applying the three approaches to paper networks in research fields.Comment: 18 pages, 9 figure

Local multiresolution order in community detection

Community detection algorithms attempt to find the best clusters of nodes in an arbitrary complex network. Multi-scale ("multiresolution") community detection extends the problem to identify the best network scale(s) for these clusters. The latter task is generally accomplished by analyzing community stability simultaneously for all clusters in the network. In the current work, we extend this general approach to define local multiresolution methods, which enable the extraction of well-defined local communities even if the global community structure is vaguely defined in an average sense. Toward this end, we propose measures analogous to variation of information and normalized mutual information that are used to quantitatively identify the best resolution(s) at the community level based on correlations between clusters in independently-solved systems. We demonstrate our method on two constructed networks as well as a real network and draw inferences about local community strength. Our approach is independent of the applied community detection algorithm save for the inherent requirement that the method be able to identify communities across different network scales, with appropriate changes to account for how different resolutions are evaluated or defined in a particular community detection method. It should, in principle, easily adapt to alternative community comparison measures.Comment: 19 pages, 11 figure

World citation and collaboration networks: uncovering the role of geography in science

Modern information and communication technologies, especially the Internet, have diminished the role of spatial distances and territorial boundaries on the access and transmissibility of information. This has enabled scientists for closer collaboration and internationalization. Nevertheless, geography remains an important factor affecting the dynamics of science. Here we present a systematic analysis of citation and collaboration networks between cities and countries, by assigning papers to the geographic locations of their authors' affiliations. The citation flows as well as the collaboration strengths between cities decrease with the distance between them and follow gravity laws. In addition, the total research impact of a country grows linearly with the amount of national funding for research & development. However, the average impact reveals a peculiar threshold effect: the scientific output of a country may reach an impact larger than the world average only if the country invests more than about 100,000 USD per researcher annually.Comment: Published version. 9 pages, 5 figures + Appendix, The world citation and collaboration networks at both city and country level are available at http://becs.aalto.fi/~rajkp/datasets.htm

Knowledge Integration and Diffusion: Measures and Mapping of Diversity and Coherence

I present a framework based on the concepts of diversity and coherence for the analysis of knowledge integration and diffusion. Visualisations that help understand insights gained are also introduced. The key novelty offered by this framework compared to previous approaches is the inclusion of cognitive distance (or proximity) between the categories that characterise the body of knowledge under study. I briefly discuss the different methods to map the cognitive dimension