1,720,972 research outputs found
Network-Level Power-Performance Trade-Off in Wearable Activity Recognition: A Dynamic Sensor Selection Approach
No full textWearable gesture recognition enables context aware applications and unobtrusive HCI. It is realized by
applying machine learning techniques to data from on-body sensor nodes. We present an gesture recognition
system minimizing power while maintaining a run-time application defined performance target through
dynamic sensor selection.
Compared to the non managed approach optimized for recognition accuracy (95% accuracy), our technique
can extend network lifetime by 4 times with accuracy >90% and by 9 times with accuracy >70%. We
characterize the approach and outline its applicability to other scenarios
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Activity recognition from on-body sensors by classifier fusion: sensor scalability and robustness
No full textDispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Activity recognition from on-body sensors: accuracy-power trade-off by dynamic sensor selection
No full textActivity recognition from an on-body sensor network enables
context-aware applications in wearable computing. A guaranteed classification
accuracy is desirable while optimizing power consumption to ensure
the system’s wearability. In this paper, we investigate the benefits
of dynamic sensor selection in order to use efficiently available energy
while achieving a desired activity recognition accuracy. For this purpose
we introduce and characterize an activity recognition method with
an underlying run-time sensor selection scheme. The system relies on a
meta-classifier that fuses the information of classifiers operating on individual
sensors. Sensors are selected according to their contribution to
classification accuracy as assessed during system training. We test this
system by recognizing manipulative activities of assembly-line workers
in a car production environment. Results show that the system’s lifetime
can be significantly extended while keeping high recognition accuracies.
We discuss how this approach can be implemented in a dynamic sensor
network by using the context-recognition framework Titan that we are
developing for dynamic and heterogeneous sensor networks
Service discovery and composition in body area networks
No full textIn pervasive environments, Body Area Networks (BANs) are characterized by the mobility of their users. BANs can continuously interact with each other, thus enabling the provision of new applications and services at runtime. New complex services can be provided by composing simpler services available on neighbouring network nodes. However, since the topology of BANs is continuously changing due to users' movements, it is unfeasible to specify a-priori all possible configurations under which a given complex service can be composed. In order to address this issue, we introduce a two--layered service discovery and composition architecture, that proactively notifies a distributed service directory with changes in service availability. In order to cope with the network mobility and intermittent connectivity, our approach is to cluster nodes in the sensor network based on their connectivity patterns. We use a multi--agent state machine to recognize the availability of complex services and to provide them. Our solution is validated by a prototype implementation of our architecture, by the study of the statistical model of complex services, and by experimental evaluations
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