1,721,063 research outputs found
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
An End to End Indoor Air Monitoring System Based on Machine Learning and SENSIPLUS Platform
Full text linkIn the framework of indoor air monitoring, this paper proposes an Internet of Things ready solution to detect and classify contaminants. It is based on a compact and low-power integrated system including both sensing and processing capabilities. The sensing is composed of a sensor array on which electrical impedance measurements are performed through a microchip, named SENSIPLUS, while the processing phase is mainly based on Machine Learning techniques, embedded in a low power and low resources micro controller unit, for classification purposes. An extensive experimental campaign on different contaminants has been carried out and raw sensor data have been processed through a lightweight Multi Layer Perceptron for embedded implementation. More complex and computationally costly Deep Learning techniques, as Convolutional Neural Network and Long Short Term Memory, have been adopted as a reference for the validation of Multi Layer Perceptron performance. Results prove good classification capabilities, obtaining an accuracy greater than 75% in average. The obtained results, jointly with the reduced computational costs of the solution, highlight that this proposal is a proof of concept for a pervasive IoT air monitoring system
Performance comparison in Ultra Wide Band positioning in sensor networks: least square minimization versus grid search approach
No full textThe localization task in sensor networks is partic-ularly critical whenever the sensor measurements are position-related, as in case of thermal and electromagnetic quantities. The deployment of a sensor network often requires the usage of low-cost devices able to achieve acceptable measurement accuracy and having the need to retrieve fast and accurate positioning information. In such networks, the localization task is generally performed by a special node coordinating the network. Nevertheless, its computing power is often limited. To this aim, in this paper we compare two different positioning techniques (least square minimization, grid search), to be applied in Ultra- Wide-Band positioning scheme, from the accuracy point of view and computing time required for accomplishing the task. They differ in working principle, needed a priori information, localization resolution and time to completion parameter. According to the available resources, the adoption of one of them should be prefer-able to the other one. Obtained results prove the goodness of both methods, specifically ranking them by application purposes. The paper is intended to give the designers an extensive analysis to evaluate pros and cons to adopt a completely blind positioning technique, namely the least square minimization, versus a more informed and constrained system, as the grid search case
A multi-frequency approach to mitigate the performance degradation of a magnetic positioning system under CW disturbance conditions
No full textMagnetic localization in 3D space is a challenging but promising task in those indoor applications where low costs and limited range are key requirements as in industrial and in some medical clinics’ frameworks. In such cases, the localization system generally operates in disturbed environments where, in the worst case, continuous-wave disturbances could permanently affect the system performance. Therefore, the evaluation of its susceptibility to external disturbances is an issue to be assessed, before deploying the most suitable solution. Therefore, it is important to accomplish for two tasks: (i) to quantify the disturbance effect on the system performance and (ii) to propose robustness solutions to minimize the disturbance effect, thus allowing the system to behave as in regular mode. In this paper, concerning with continuous wave conducted disturbances, which act as the most impacting external disturbing sources, both the tasks are addressed by considering both analytical modeling and experimental validations
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
Metrological characterization of a novel microsensor platform for activated carbon filters monitoring
No full textNowadays, an increasing concern about people and environmental health and safety is spreading all over the world, and technologies such as efficient monitoring systems are furthered. In the field of air quality, filtering systems, especially based on activated carbons (ACs), are commonly used. In most cases, their state of health is not monitored, and their time of life is based on statistical and a priori evaluations. This paper proposes a novel microsensor platform for the real-time monitoring of AC filters based on the impedance measurements during gas exposition. A metrological characterization of the novel proposed instrument is provided in this paper, by comparing its output to a reference RLC meter. A calibration and adjustment procedure is developed in order to analyze the device measurement capabilities and obtain correction coefficients. Experiments with different gas typologies are presented, and the analysis of filters impedance dynamics is provided
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
Optimization and experimental characterization of novel measurement methods for wide-band spectrum sensing in cognitive radio applications
No full textSpectrum sensing is a fundamental task in the complex field of cognitive radio systems. It allows a cognitive terminal to scan a frequency span of interest and sense the presence of other users transmitting over it. Many spectrum sensing methods are present in literature and many interesting algorithms have been proposed. Unfortunately, very few methods allow to know the exact boundaries of the user signal, without knowing any channelization of the spectrum of interest. In this context, the paper proposes two novel algorithms, whose purpose is twofold: to keep a low computational burden and to provide information at the most detailed level with respect to the category the algorithms belong to. Tests, executed on simulated and emulated signals, have demonstrated that both algorithms allow reaching a detection probability greater then 95% and a false alarm probability lower then 5% even in scenarios characterized by SNR as low as −10 d
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
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