1,720,965 research outputs found
eSysId: Embedded System Identification for Vibration Monitoring at the Extreme Edge
Full text linkEnabling extreme edge processing functionalities will lead
a breakthrough in the development of the next generation of Structural
Health Monitoring (SHM) systems, thanks to the adoption of sensor–near
data analtycs which will make the structural inference process faster and
more advantageous in terms of power consumption and data volume.
In this work, we specifically endorse this paradigm in the context of
vibration–based diagnostics by proposing a novel, intelligent accelerom-
eter sensor combining, in an embedded device, advanced edge data ana-
lytics implementing System Identification algorithms, and energy–aware
custom hardware supporting it. The effect of the bit–depth quantization
of the collected signal on the quality of the retrieved structural param-
eters is assessed; moreover, a cost–benefit analysis is also encompassed,
showing how the developed solution might be globally more advanta-
geous from an energy point of view, reaching up to 10x power saving if
compared with standard alternatives
Compression-Accuracy Co-optimization Through Hardware-aware Neural Architecture Search for Vibration Damage Detection
Full text linkInternet-of-Things (IoT) is a key enabler for the transition to the Automatic Structural Health Monitoring (ASHM) of technical facilities, thanks to the seamless flow of data from a multitude of always connected devices. Current IoT-ASHM installations, however, face the double challenge to ensure high accuracy while meeting the requirement of minimal energy consumption. The paper tackles these issues from a deep-learning perspective, and describes an IoT-enabled monitoring approach based on a distributed end-to-end deep neural network (DNN). The architecture supports both data compression and damage detection. A low-end microcontroller hosts a specific local DNN; a hardware-aware neural-architecture search strategy rules network optimization, in order to satisfy the resource constraints set by low-end computing devices. The features extracted from data feed an aggregating unit, which includes a stacked global classification layer for full-scale damage detection. After proper quantization, the designed models are eventually deployed on a wireless accelerometer sensor. Finally, a cost-benefit analysis evaluates the system’s impact on the sensor energy autonomy. Experiments on a well-known dataset proved that the proposed solution could achieve state-of-the-art classification scores (all metrics above 98.4%) with a minimal transmission cost (less than 53 B on average); as compared with conventional approaches, the described strategy yielded a reduction of three orders of magnitude in energy consumption
Spiking Neural Networks for Energy-efficient Acoustic Emission-Based Monitoring
Full text linkAcoustic Emission (AE) is one of the most effective Nondestructive Testing (NDT) techniques for the identification and characterization of stress waves originated at the uprising of acoustic-related defects (e.g., cracks). To this end, the estimation of the Time of Arrival (ToA) is crucial. In this work, a novel processing flow which shifts the identification process from the time to the timefrequency domain via Wavelet Transform (WT) is proposed, allowing to better capture transient behaviours typical of the originated AE signals. More specifically, both the Continuous and the Discrete WT alternatives have been explored to find the best compromise between time-frequency resolution and computational complexity in view of extreme edge deployments. Furthermore, the event-driven capabilities of neuromorphic architectures (and Spiking Neural Networks in particular) in processing spiky and sparse temporal information are exploited to retrieve ToA in a beyond state-of-the-art power efficient manner and negligible loss of performance with respect to standard models. Therefrom, we aim at combining the superior performances in ToA identification enabled by the WT operator with the unique energy saving disclosed by spiking hardware and software. Experimental tests executed on a metallic plate structure demonstrated that WT combined with SNN can achieve high precision (median values less than 5 cm) in ToA estimation and AE source localization even in presence of relevant noise (SNR down to 2 dB), while its deployment on dedicated neuromorphic architectures can reduce by six orders of magnitude the power expenditure per inference when compared to standard convolutional architectures
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
Low-Power MIMO Guided-Wave Communication
Full text linkThis article demonstrates the use of guided elastic waves (GEW) for multiple-in and multiple-out (MIMO) data communication in the framework of a structural health monitoring (SHM) system. Therefore, miniaturized low-voltage communication nodes have been developed. They are arranged in a spatially distributed and permanently installed network. Wireless exchange of encoded information across a metallic plate and a stiffened carbon-fiber reinforced plastics (CFRP) structure is investigated. A combination of square-wave excitation sequences and frequency-division multiplexing (FDM) is explored for parallel communication with multiple nodes. Moreover, the impact of the excitation-sequence length on the reliability of information transmission is studied in view of future energy-aware application scenarios. The presented system achieves in both studied structures error-free transmission at a data rate of 0.17 kbps (per carrier frequency) with a power consumption of 224 mW
VERSATILE SENSOR NODE WITH ACOUSTIC DATA COMMUNICATION CAPABILITIES FOR FSAT NETWORKS IN GUIDED WAVE-BASED STRUCTURAL HEALTH MONITORING APPLICATIONS
No full textDispelling 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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