Accelerometers can measure total and activity-specific energy expenditures in free-ranging marine mammals only if linked to time-activity budgets

Peer reviewedPostprin

Effects of pitch size and skill level on tactical behaviours of Association Football players during small-sided and conditioned games

In Association Football, the study of variability in players' movement trajectories during performance can provide insights on tactical behaviours. This study aimed to analyse the movement variability present in: i) the players' actions zones and ii), distances travelled over time, considered as a player's positional spatial reference. Additionally, we investigated whether the movement variability characteristics of players from different skill levels varied. Two groups of U-17 yrs players of different performance levels (national and regional) performed in three small-sided games with varying pitch dimensions (small, intermediate and large). Linear and non-linear analyses were used to capture the magnitude and structure of their movement variability. Results showed that increases in pitch size resulted in more restricted action zones and higher distance values from personal spatial positional references for both groups. National-level players were more sensitive to pitch modifications and displayed more variability than regional-level players in the small and intermediate pitches. These findings advance understanding about individual tactical behaviours in Association Football and have implications for training design, using pitch size manipulation

The evolution of language: a comparative review

For many years the evolution of language has been seen as a disreputable topic, mired in fanciful "just so stories" about language origins. However, in the last decade a new synthesis of modern linguistics, cognitive neuroscience and neo-Darwinian evolutionary theory has begun to make important contributions to our understanding of the biology and evolution of language. I review some of this recent progress, focusing on the value of the comparative method, which uses data from animal species to draw inferences about language evolution. Discussing speech first, I show how data concerning a wide variety of species, from monkeys to birds, can increase our understanding of the anatomical and neural mechanisms underlying human spoken language, and how bird and whale song provide insights into the ultimate evolutionary function of language. I discuss the ‘‘descended larynx’ ’ of humans, a peculiar adaptation for speech that has received much attention in the past, which despite earlier claims is not uniquely human. Then I will turn to the neural mechanisms underlying spoken language, pointing out the difficulties animals apparently experience in perceiving hierarchical structure in sounds, and stressing the importance of vocal imitation in the evolution of a spoken language. Turning to ultimate function, I suggest that communication among kin (especially between parents and offspring) played a crucial but neglected role in driving language evolution. Finally, I briefly discuss phylogeny, discussing hypotheses that offer plausible routes to human language from a non-linguistic chimp-like ancestor. I conclude that comparative data from living animals will be key to developing a richer, more interdisciplinary understanding of our most distinctively human trait: language

Geolocation with subsampled microblog social media

The article of record as published may be found at http://dx.doi.org/10.1145/2733373.2806357.We propose a data-driven geolocation method on microblog text. Key idea underlying our approach is sparse coding, an unsupervised learning algorithm. Unlike conventional positioning algorithms, we geolocate a user by identifying features extracted from her social media text. We also present an enhancement robust to erasure of words in the text and report our experimental results with uniformly or randomly subsampled microblog text. Our solution features a novel two-step procedure consisting of upconversion and iterative refinement by joint sparse coding. As a result, we can reduce the amount of input data required by geolocation while preserving good prediction accuracy. In the light of information preservation and privacy, we remark potential applications of these results.Funded by Naval Postgraduate School (Naval Supply Systems Command award)National Science Foundation Graduate Research FellowshipGrant No. DGE1144152 (NSF)Agreement No. DGE1144152 (NPS

A C-DBSCAN algorithm for determining bus-stop locations based on taxi GPS data

Determining suitable bus-stop locations is critical in improving the quality of bus services. Previous studies on selecting bus stop locations mainly consider environmental factors such as population density and traffic conditions, seldom of them consider the travel patterns of people, which is a key factor for determining bus-stop locations. In order to draw people’s travel patterns, this paper improves the density-based spatial clustering of applications with noise (DBSCAN) algorithm to find hot pick-up and drop-off locations based on taxi GPS data. The discovered density-based hot locations could be regarded as the candidate for bus-stop locations. This paper further utilizes the improved DBSCAN algorithm, namely as C-DBSCAN in this paper, to discover candidate bus-stop locations to Capital International Airport in Beijing based on taxi GPS data in November 2012. Finally, this paper discusses the effects of key parameters in C-DBSCAN algorithm on the clustering results. Keywords Bus-stop locations, Public transport service, Taxi GPS data, Centralize density-based spatial clustering of applications with noise

The ranking based constrained document clustering method and its application to social event detection

With the growing size and variety of social media files on the web, it’s becoming critical to efficiently organize them into clusters for further processing. This paper presents a novel scalable constrained document clustering method that harnesses the power of search engines capable of dealing with large text data. Instead of calculating distance between the documents and all of the clusters’ centroids, a neighborhood of best cluster candidates is chosen using a document ranking scheme. To make the method faster and less memory dependable, the in-memory and in-database processing are combined in a semi-incremental manner. This method has been extensively tested in the social event detection application. Empirical analysis shows that the proposed method is efficient both in computation and memory usage while producing notable accuracy

Multi-source Toponym Data Integration and Mediation for a Meta-Gazetteer Service

Abstract. A variety of gazetteers exist based on administrative or user contributed data. Each of these data sources has benefits for particular geographical analysis and information retrieval tasks but none is a one fit all solution. We present a mediation framework to access and integrate distributed gazetteer resources to build a meta-gazetteer that generates augmented versions of place name information. The approach combines different aspects of place name data from multiple gazetteer sources that refer to the same geographic place and employs several similarity metrics to identify equivalent toponyms.