1,720,963 research outputs found
Multi-Sensor System for Detection and Classification of Human Activities
No full textThis paper describes a novel system for detecting and classifying human activities based on a multi-sensor approach. The aim of this research is to create a loosely structured environment, where activity is constantly monitored and automatically classified, transparently to the subjects who are observed. The system uses four calibrated cameras installed in the room which is being monitored and a body-mounted wireless accelerometer on each person, exploiting the features of different sensors to maximize recognition accuracy, improve scalability and reliability. The algorithms on which the system is based, as well as its structure, are aimed at analyzing and classifying complex movements (like walking, sitting, jumping, running, falling, etc.) of potentially multiple people at the same time. Here, we describe a preliminary application, in which action classification is mostly aimed at detecting falls. Several instances of a hybrid classifier based on Support Vector Machines and Hierarchical Temporal Memories, a recent bio-inspired computational paradigm, are used to detect potentially dangerous activities of each person in the environment. If such an activity is detected and if the person “in danger” is wearing the accelerometer, the system localizes and activates it to receive data and then performs a more reliable fall detection using a specifically trained classifier. The opportunity to turn on the accelerometer on-demand makes it possible to extend its battery life. Besides and beyond surveillance, this system could also be used for the assessment of the degree of independence of elderly people or, in rehabilitation, to assist patients during recovery
Classifying Human Body Acceleration Patterns Using a Hierarchical Temporal Memory.
No full textThis paper introduces a novel approach to the detection of human body movements during daily life. With the sole use of one wearable wireless triaxial accelerometer attached to one's chest, this approach aims at classifying raw acceleration data robustly, to detect many common human behaviors without requiring any specific a-priori knowledge about movements. The proposed approach consists of feeding sensory data into a specifically trained Hierarchical Temporal Memory (HTM) to extract invariant spatial-temporal patterns that characterize different body movements. The HTM output is then classified using a Support Vector Machine (SVM) into different categories. The performance of this new HTM+SVM combination is compared with a single SVM using realword data corresponding to movements like "standing", "walking", "jumping" and "falling", acquired from a group of different people. Experimental results show that the HTM+SVM approach can detect behaviors with very high accuracy and is more robust, with respect to noise, than a classifier based solely on SVMs
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
Sensor Fusion-oriented Fall Detection for Assistive Technologies Applications
No full textA new trend in modern Assistive Technologies implies making extensive use of ICT to develop efficient and reliable "Ambient Intelligence'' applications dedicated to disabled, elderly or frail people.
In this paper we describe two fall detectors, based on bio-inspired algorithms. Such devices can either operate independently or be part of a modular and easily extensible architecture, able to manage different areas of an intelligent environment. In this case, effective data fusion can be achieved, thanks to the complementary nature of the sensors on which the detectors are based.
One device is based on vision and can be implemented on a standard FPGA programmable logic. It relies on a simplified version of the Particle Swarm Optimization algorithm. The other device under consideration is a wearable accelerometer-based fall detector, which relies on a recent soft-computing paradigm called Hierarchical Temporal Memories (HTMs)
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe 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
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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