Towards condition-invariant, top-down visual place recognition

In this paper we present a novel place recognition algorithm inspired by recent discoveries in human visual neuroscience. The algorithm combines intolerant but fast low resolution whole image matching with highly tolerant, sub-image patch matching processes. The approach does not require prior training and works on single images (although we use a cohort normalization score to exploit temporal frame information), alleviating the need for either a velocity signal or image sequence, differentiating it from current state of the art methods. We demonstrate the algorithm on the challenging Alderley sunny day – rainy night dataset, which has only been previously solved by integrating over 320 frame long image sequences. The system is able to achieve 21.24% recall at 100% precision, matching drastically different day and night-time images of places while successfully rejecting match hypotheses between highly aliased images of different places. The results provide a new benchmark for single image, condition-invariant place recognition.

Vision-based simultaneous localization and mapping in changing outdoor environments

For robots operating in outdoor environments, a number of factors, including weather, time of day, rough terrain, high speeds, and hardware limitations, make performing vision-based simultaneous localization and mapping with current techniques infeasible due to factors such as image blur and/or underexposure, especially on smaller platforms and low-cost hardware. In this paper, we present novel visual place-recognition and odometry techniques that address the challenges posed by low lighting, perceptual change, and low-cost cameras. Our primary contribution is a novel two-step algorithm that combines fast low-resolution whole image matching with a higher-resolution patch-verification step, as well as image saliency methods that simultaneously improve performance and decrease computing time. The algorithms are demonstrated using consumer cameras mounted on a small vehicle in a mixed urban and vegetated environment and a car traversing highway and suburban streets, at different times of day and night and in various weather conditions. The algorithms achieve reliable mapping over the course of a day, both when incrementally incorporating new visual scenes from different times of day into an existing map, and when using a static map comprising visual scenes captured at only one point in time. Using the two-step place-recognition process, we demonstrate for the first time single-image, error-free place recognition at recall rates above 50% across a day-night dataset without prior training or utilization of image sequences. This place-recognition performance enables topologically correct mapping across day-night cycles.

Visualization of predictive distributions for discrete spatial-temporal log Cox processes approximated with MCMC

An important aspect of decision support systems involves applying sophisticated and flexible statistical models to real datasets and communicating these results to decision makers in interpretable ways. An important class of problem is the modelling of incidence such as fire, disease etc. Models of incidence known as point processes or Cox processes are particularly challenging as they are ‘doubly stochastic’ i.e. obtaining the probability mass function of incidents requires two integrals to be evaluated. Existing approaches to the problem either use simple models that obtain predictions using plug-in point estimates and do not distinguish between Cox processes and density estimation but do use sophisticated 3D visualization for interpretation. Alternatively other work employs sophisticated non-parametric Bayesian Cox process models, but do not use visualization to render interpretable complex spatial temporal forecasts. The contribution here is to fill this gap by inferring predictive distributions of Gaussian-log Cox processes and rendering them using state of the art 3D visualization techniques. This requires performing inference on an approximation of the model on a discretized grid of large scale and adapting an existing spatial-diurnal kernel to the log Gaussian Cox process context.

The politics of literacy in David Almond and Dave McKean’s "The Savage" (2008)

Competency in language and literacy are central to contemporary debates about education in Anglophone nations around the world. This paper suggests that such debates are informing not just educational policy but children’s literature itself as can be seen in Almond and McKean’s The Savage. This hybrid text combines prose and graphic narrative and narration in order to tell the story of Blue, a young British boy negotiating his identity in the aftermath of his father's death. While foregrounding a narrative of ideal masculinity, The Savage enacts and privileges a formal and thematic ideal of literacy as index of individual agency and development. Almond and McKean produce a politicised understanding of language and literacy that simultaneously positions The Savage in a textual tradition of socio-culturally disenfranchised youth, and intervenes in that tradition to (perhaps ironically) affirm the very conditions previously critiqued by that very tradition. Where earlier authors such as Barry Hines sought to challenge normative accounts of language and literacy in order to indict educational policy and praxes, Almond and McKean work to naturalise the very logics of education and agency by which their protagonist has been disenfranchised. In doing so, The Savage exemplifies current approaches to education which claim to value social and cultural diversity while imposing national standardised testing predicated on assumptions about the legitimacy of uniform standards and definitions of literacy.

David Hicks and Cathie Holden (eds.) (2007). Teaching The Global Dimension. London: Routledge, Taylor & Francis Group, 212 pages.

Teaching The Global Dimension (2007) is intended for primary and secondary teachers, pre-service teachers and educators interested in fostering global concerns in the education system. It aims at linking theory and practice and is structured as follows. Part 1, the global dimension, proposes an educational framework for understanding global concerns. Individual chapters in this section deal with some educational responses to global issues and the ways in which young people might become, in Hick’s terms, more “world-minded”. In the first two chapters, Hicks presents first, some educational responses to global issues that have emerged in recent decades, and second, an outline of the evolution of global education as a specific field. As with all the chapters in this book, most of the examples are drawn from the United Kingdom. Young people’s concerns, student teachers’ views and the teaching of controversial issues, comprise the other chapters in this section. Taken collectively, the chapters in Part 2 articulate the conceptual framework for developing, teaching and evaluating a global dimension across the curriculum. Individual chapters in this section, written by a range of authors, explore eight key concepts considered necessary to underpin appropriate learning experiences in the classroom. These are conflict, social justice, values and perceptions, sustainability, interdependence, human rights, diversity and citizenship. These chapters are engaging and well structured. Their common format consists of a succinct introduction, reference to positive action for change, and examples of recent effective classroom practice. Two chapters comprise the final section of this book and suggest different ways in which the global dimension can be achieved in the primary and the secondary classroom.

An interview with Professor David Held : exploring the concepts of cosmopolitanism and democracy

David Held is the Graham Wallace Chair in Political Science, and co-director of LSE Global Governance, at the London School of Economics. He is the author of many works, such as Cosmopolitanism: Ideals and Realities (2010); The Cosmopolitanism Reader (2010), with Garrett Brown; Globalisation/AntiGlobalisation (2007), Models of Democracy (2006), Global Covenant (2004) and Global Transformations: Politics, Economics and Culture (1999). Professor Held is also the co-founder, alongside Lord Professor Anthony Giddens, of Polity Press. Professor Held is widely known for his work concerning cosmopolitan theory, democracy, and social, political and economic global improvement. His Global Policy Journal endeavours to marry academic developments with practitioner realities, and contributes to the understanding and improvement of our governing systems.

David F. Treagust : congenial soul, science educator, and international research leader

For almost a half century David F. Treafust has been an exemplary science educator who has contributed through his dedication and commitments to students, curriculum development and collaboration with teachers, and cutting edge research in science education that has impacted the field globally, nationally and locally. A hallmark of his outstanding career is his collaborative style that inspires others to produce their best work.

'In the hands of the Receivers': The Politics of Literacy in The Savage by David Almond and Dave McKean

David Almond and Dave McKean's The Savage is a hybrid prose and graphic novel which tells the story of one young man’s maturation through literacy. The protagonist learns to deal with the death of his father and his own 'savage' self by writing a graphic novel. This article reads The Savage in the context of earlier, 'Northern' literacy narrative - particularly Tony Harrison's poem "Them & [uz]" and Barry Hines' Kes — through the discourse of neoliberalism and the notion of the reluctant boy reader. It is suggested that Almond and McKean are influenced by currently dominant ideologies of gender and literacy.

Sympathy for the devil [Book reviewed : "Tasmanian Devil: A Unique and Threatened Animal" by David Owen and David Pemberton]

Two representations have dominated public perceptions of the largest living marsupial carnivore, the Tasmanian devil. One is the voracious, hurricane-like innocent savage Taz of Looney Tunes cartoon fame. The other, familiar in nineteenth- and twentieth-century rural Tasmania, is the ferocious predator and scavenger that wantonly kills livestock — and perhaps even people, should they become immobilized in the wilderness at night. Devils can take prey nearly three times their size and eat more than a third of their body weight in a sitting. Even so, it is hard to imagine how this species, being only slightly larger than a fox terrier, could be so maligned in name and image...

FGFR2 point mutations in 466 Endometrioid Endometrial Tumors : relationship with MSI, KRAS, PIK3CA, CTNNB1 mutations and Clinicopathological features

Mutations in multiple oncogenes including KRAS, CTNNB1, PIK3CA and FGFR2 have been identified in endometrial cancer. The aim of this study was to provide insight into the clinicopathological features associated with patterns of mutation in these genes, a necessary step in planning targeted therapies for endometrial cancer. 466 endometrioid endometrial tumors were tested for mutations in FGFR2, KRAS, CTNNB1, and PIK3CA. The relationships between mutation status, tumor microsatellite instability (MSI) and clinicopathological features including overall survival (OS) and disease-free survival (DFS) were evaluated using Kaplan-Meier survival analysis and Cox proportional hazard models. Mutations were identified in FGFR2 (48/466); KRAS (87/464); CTNNB1 (88/454) and PIK3CA (104/464). KRAS and FGFR2 mutations were significantly more common, and CTNNB1 mutations less common, in MSI positive tumors. KRAS and FGFR2 occurred in a near mutually exclusive pattern (p = 0.05) and, surprisingly, mutations in KRAS and CTNNB1 also occurred in a near mutually exclusive pattern (p = 0.0002). Multivariate analysis revealed that mutation in KRAS and FGFR2 showed a trend (p = 0.06) towards longer and shorter DFS, respectively. In the 386 patients with early stage disease (stage I and II), FGFR2 mutation was significantly associated with shorter DFS (HR = 3.24; 95% confidence interval, CI, 1.35-7.77; p = 0.008) and OS (HR = 2.00; 95% CI 1.09-3.65; p = 0.025) and KRAS was associated with longer DFS (HR = 0.23; 95% CI 0.05-0.97; p = 0.045). In conclusion, although KRAS and FGFR2 mutations share similar activation of the MAPK pathway, our data suggest very different roles in tumor biology. This has implications for the implementation of anti-FGFR or anti-MEK biologic therapies.

Personalization in tag ontology learning for recommendation making

Due to the explosive growth of the Web, the domain of Web personalization has gained great momentum both in the research and commercial areas. One of the most popular web personalization systems is recommender systems. In recommender systems choosing user information that can be used to profile users is very crucial for user profiling. In Web 2.0, one facility that can help users organize Web resources of their interest is user tagging systems. Exploring user tagging behavior provides a promising way for understanding users’ information needs since tags are given directly by users. However, free and relatively uncontrolled vocabulary makes the user self-defined tags lack of standardization and semantic ambiguity. Also, the relationships among tags need to be explored since there are rich relationships among tags which could provide valuable information for us to better understand users. In this paper, we propose a novel approach for learning tag ontology based on the widely used lexical database WordNet for capturing the semantics and the structural relationships of tags. We present personalization strategies to disambiguate the semantics of tags by combining the opinion of WordNet lexicographers and users’ tagging behavior together. To personalize further, clustering of users is performed to generate a more accurate ontology for a particular group of users. In order to evaluate the usefulness of the tag ontology, we use the tag ontology in a pilot tag recommendation experiment for improving the recommendation performance by exploiting the semantic information in the tag ontology. The initial result shows that the personalized information has improved the accuracy of the tag recommendation.