1,721,245 research outputs found
Being ‘International’: The Opportunities and Challenges of Studying Education as an International Student
Full text linkAlthough still in a minority, there has been an increase in numbers of international students joining undergraduate education studies degrees in the UK in recent years. This chapter, co-authored by current and recent international education students, explores the many reasons why this group elect to study in the UK. Reasons include perceived prestige and quality of the higher education system, prior familiarity with English language and culture, and links with institutions in their home countries. Drawing on literature pertaining to the UK education studies context the chapter notes that, whilst international students typically enjoy and value the transition to UK study, there can be many personal, linguistic, social, cultural and academic challenges. International students bring distinct perspectives to the study of education which are of great value to home students and staff, but can also find engaging with the complexities of UK education policy and culture difficult at times. The chapter concludes with a range of practical suggestions for how international students can be supported within the undergraduate subject of education, and how staff and home students can contribute to a learning environment which benefits and includes everyone
Urban traffic event detection using Twitter data
Full text linkUnderstanding traffic events is important for urban policy making and transport management. Traffic events could be related to traffic congestion, transportation infrastructure issues, parking issues, to name a few. Currently, traffic events are monitored through static sensors e.g., CCTV camera, loop detectors which have limited spatial coverage and high main- tenance cost. Thus, we attempt to use the concept of citizens as sensors and develop a cost-effective model to understand urban traffic events from unstructured and informal tweets. So far existing works attempted to classify tweets either in traffic or non-traffic categorization [1], [3], [4]. Most of the state-of- the-art have used geotagged tweets for identifying traffic events [2], which accounted for only 1%-3% total tweet population, and thus lots of useful information in the ungeotagged tweets may be lost. Some other works explored a number of abstract topics related to urban transportation and environment, however without retrieving any spatial information from the tweet [5], [6].
The main contribution of this work is, in contrast to the earlier works, this research explores ungeotagged tweets to detect traffic events and developed a novel framework (Fig. 1, 2) that does not only categorize traffic related tweets but also retrieve locations of the traffic events from the tweet content. The model has been tested in the city of Mumbai in India where people use different local place names which are often informal and hard to detect using a traditional named entity recognition systems. To detect the locations of the traffic events we developed a hybrid georeferencing model that consists of a supervised model and a number of spatial rules that can handle informal place names and vernacular geographical aspects.
For tweet categorization we used a binary classifier based on Decision Tree (DT) with 0.65 precision and 0.57 recall. The tweets are manually labelled into either traffic or non-traffic. Then the classifier is trained using a bag-of-words model. In the next phase, a hybrid georeferencing model is developed. The proposed georeferencing model consists of a pre-trained StanfordNER on the top tier and two spatial rule-based layers in the subsequent tiers (Fig. 3). The rules are based on spatial prepositions, object types and vernacular place names in India. Out of 1143 annotated place names the model can correctly retrieve 691 place names. To disambiguate and geocode the place names, OpenStreetMap has been used. This work shows Twitter can be useful for detecting urban events in Mumbai. One of the challenges in georeferencing the traffic event location lies in the way people mention the place names. The same place name may be mentioned differently by different people or it may not be present in the gazetteer, e.g., OpenStreetMap, which causes difficulty in toponym recognition and disambiguation. In this work the toponyms (retrieved from tweet content) are mapped to precise geo-coordinates to indicate traffic locations. However, traffic events can stretch along a street segment or over a region. Future work will look into understanding the spatial extent of the affected area from other contextual cues and spatial relationships retrieved from the tweet content
Eliciting concepts of place for text-based image retrieval
No full textThis paper describes research being employed in the Tripod project to improve the retrieval of photographs through a comprehensive knowledge of where they were taken. The methods described here attempt to elicit semantics, and thus terms for use in indexing, related to the idea of place from theoretical geography. Three approaches are outlined: literature-based, empirical experiments, and data mining
Gazetteer matching for natural features in Switzerland
No full textWe investigate gazetteer matching between natural features in Switzerland. We produce a gold standard dataset for a subset of features from 8 natural feature types in GeoNames aligned with their corresponding match(es) in SwissNames3D, an authoritative gazetteer. Based on this dataset, we comment on feature type alignments between the two resources and on type-specific differences to take into consideration for the matching task. We present preliminary results of rule-based matching and plans for future work
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment
Full text linkConservation and monitoring of forest biodiversity requires reliable information about forest structure and composition at multiple spatial scales. However, detailed data about forest habitat characteristics across large areas are often incomplete due to difficulties associated with field sampling methods. To overcome this limitation we employed a nationally available light detection and ranging (LiDAR) remote sensing dataset to develop variables describing forest landscape structure across a large environmental gradient in Switzerland. Using a model species indicative of structurally rich mountain forests (hazel grouse Bonasa bonasia), we tested the potential of such variables to predict species occurrence and evaluated the additional benefit of LiDAR data when used in combination with traditional, sample plot-based field variables. We calibrated boosted regression trees (BRT) models for both variable sets separately and in combination, and compared the models’ accuracies. While both field-based and LiDAR models performed well, combining the two data sources improved the accuracy of the species’ habitat model. The variables retained from the two datasets held different types of information: field variables mostly quantified food resources and cover in the field and shrub layer, LiDAR variables characterized heterogeneity of vegetation structure which correlated with field variables describing the understory and ground vegetation. When combined with data on forest vegetation composition from field surveys, LiDAR provides valuable complementary information for encompassing species niches more comprehensively. Thus, LiDAR bridges the gap between precise, locally restricted field-data and coarse digital land cover information by reliably identifying habitat structure and quality across large areas
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