1,721,009 research outputs found
Design and implementation of machine learning techniques for modeling and managing battery energy storage systems
Full text linkThe fast technological evolution and industrialization that have interested the humankind since the fifties has caused a progressive and exponential increase of CO2 emissions and Earth temperature. Therefore, the research community and the political authorities have recognized the need of a deep technological revolution in both the transportation and the energy distribution systems to hinder climate changes. Thus, pure and hybrid electric powertrains, smart grids, and microgrids are key technologies for achieving the expected goals. Nevertheless, the development of the above mentioned technologies require very effective and performing Battery Energy Storage Systems (BESSs), and even more effective Battery Management Systems (BMSs).
Considering the above background, this Ph.D. thesis has focused on the development of an innovative and advanced BMS that involves the use of machine learning techniques for improving the BESS effectiveness and efficiency. Great attention has been paid to the State of Charge (SoC) estimation problem, aiming at investigating solutions for achieving more accurate and reliable estimations. To this aim, the main contribution has concerned the development of accurate and flexible models of electrochemical cells.
Three main modeling requirements have been pursued for ensuring accurate SoC estimations: insight on the cell physics, nonlinear approximation capability, and flexible system identification procedures. Thus, the research activity has aimed at fulfilling these requirements by developing and investigating three different modeling approaches, namely black, white, and gray box techniques.
Extreme Learning Machines, Radial Basis Function Neural Networks, and Wavelet Neural Networks were considered among the black box models, but none of them were able to achieve satisfactory SoC estimation performances. The white box Equivalent Circuit Models (ECMs) have achieved better results, proving the benefit that the insight on the cell physics provides to the SoC estimation task. Nevertheless, it has appeared clear that the linearity of ECMs has reduced their effectiveness in the SoC task. Thus, the gray box Neural Networks Ensemble (NNE) and the white box Equivalent Neural Networks Circuit (ENNC) models have been developed aiming at exploiting
the neural networks theory in order to achieve accurate models, ensuring at the same time very flexible system identification procedures together with nonlinear approximation capabilities.
The performances of NNE and ENNC have been compelling. In particular, the white box ENNC has reached the most effective performances, achieving accurate SoC estimations, together with a simple architecture and a flexible system identification procedure.
The outcome of this thesis makes it possible the development of an interesting scenario in which a suitable cloud framework provides remote assistance to several BMSs in order to adapt the managing algorithms to the aging of BESSs, even considering different and distinct applications
A LiDAR prototype with Silicon Photomultiplier and MEMS mirrors
No full textIn this paper, we present a low cost prototype of a Time-Of-Flight (TOF) LiDAR system, employing a SiPM as photodetector and MEMS mirrors in order to steer the nanosecond pulsed optical beam with a scanning angle of +/-6°. Preliminary TOF measurements have been performed both indoor and outdoor to test the limits of the system
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
A portable electronic system for non-invasive real-time acquisition of multiple physiological signals
No full textIn this work, we have designed and realised a portable and compact electronic system for the synchronous acquisition of multiple physiological signals. The system employs a Texas Instruments ADS1298 front-end with 24-bit resolution for data acquisition and supports up to 8 channels and 4 kHz sampling rate. The front-end communicates via SPI with a STM32 microcontroller which pre-processes the data and sends them through USB or Bluetooth to a suitable PC application. The system has been realized for the simultaneous acquisition of electrocardiographic (ECG) and photoplethysmographic (PPG) signals, but it can also be employed for acquiring other typologies of signals, e.g. breathing or electro-dermal activity, for a potential use in the automotive field to assess the driver’s health status in real-time or, in perspective, the stress level. PPG probes have also been realised, each one including dual wavelength LED (emitting at 735 and 850 nm), and a Silicon Photomultiplier (SiPM) detector (provided by STMicroelectronics) having high responsivity and gain [1]. The system integrates an I2C interface, 8-channel, 16-levels current LED driver for PPG probes and includes a Graphical User Interface (GUI) able, in real time, to (i) plot the signals, (ii) save the data, (iii) calculate and display main cardiovascular parameters (i.e., heart rate, breath rate, pulse arrival time, pulse transit time, pulse wave velocity). Both instantaneous or averaged values of heart rate are shown, also to display the time variation of the considered parameters and thus assess the so-called Heart Rate Variability [2]. Current version of the system is able to acquire up to 5 PPG waveforms and 3 ECG leads. Figure 1 shows a photo of the system, alongside with the PPG probes (on the right) and the standard ECG electrodes (on the left) which are used for signals acquisition. Figure 2 illustrates some screenshots of the developed GUI showing 2 ECG leads and 2 PPG waveforms. In detail, Fig. 2(a) depicts the windows displaying the waveforms, while, Fig. 2(b) exhibits the window dedicated to show in real-time the instantaneous and averaged values of the above-mentioned physiological parameters. Several measurement campaigns have been carried out on healthy volunteers of different ages to both test the correct functioning of the system, and also to compare the Pulse Arrival Time values computed between different body locations. In the future, by performing measurements on other typologies of subjects (e.g., hypertensive or diabetic patients), a statistical analysis of the collected data will be carried out, in order to evaluate the capability of using our system for distinguishing between different pathologies or for early disease detection, or even for assessing various stress levels.
This activity was supported by Advancing Smart Optical Imaging and Sensing for Health (ASTONISH) Project (Grant no. 692470), funded by H2020-EU.2.1.1.7.-ECSEL programme
Nonlinear brain-heart interactions in children with focal epilepsy assessed by mutual information of EEG and heart rate variability
No full textNetwork physiology is a recent approach describing the human body as an integrated network composed of several organ systems which continuously interact to produce healthy and diseased states. In this work, we apply the network physiology paradigm to study dynamical interactions between EEG activity and heart rate variability in children suffering from focal epilepsy. We aim to study the characteristics of brainheart coupling between, before, and after seizures to better understand the physiological mechanisms underlying seizure onset in the pre-ictal phase and the recovery of normal autonomic function in the post-ictal phase. In perspective, linking the dynamic information of brain-heart can provide useful information for a better seizure prediction. EEG and ECG data were recorded in 10 patients with focal epilepsy. After removal of baseline drift and muscle artifacts, the variability of heart rate and brain activity were measured extracting R-R intervals from the ECG and computing the spectral power of the EEG. 143 synchronous time series of 300 points were obtained in 4 different time windows (10 min and 10 sec before and after the seizure) and analyzed computing the cross-correlation coefficient (CC) and the mutual information (MI). A statistically significant increase of MI was observed just after seizure episodes (pvalue equal to 0.04, 10s before vs 10s after distributions, electrode O2), while a recovery of the baseline value was obtained 10 minutes after the episodes. This trend was found for several other EEG electrodes (Fp2, F3, F8, T3, C4, T4). On the contrary, CC did not change significantly across time windows. These results suggest that focal seizures are associated with an increased brain-heart coupling which is noticeable after seizure termination only in terms of mutual information. We conclude that focal epilepsy in childhood is associated with nonlinear brain-heart interaction mechanisms
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
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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