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Leopoldo Angrisani

Bio: Leopoldo Angrisani is an academic researcher from University of Naples Federico II. The author has contributed to research in topics: Digital signal processing & Signal processing. The author has an hindex of 30, co-authored 262 publications receiving 3473 citations. Previous affiliations of Leopoldo Angrisani include University of Salerno & Information Technology University.


Papers
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Journal ArticleDOI
TL;DR: In this article, a measurement method for power quality analysis in electrical power systems is presented, which is the evolution of an iterative procedure already set up by the authors and allows the most relevant disturbances in electrical Power systems to be detected, localized and estimated automatically.
Abstract: The paper presents a measurement method for power quality analysis in electrical power systems. The method is the evolution of an iterative procedure already set up by the authors and allows the most relevant disturbances in electrical power systems to be detected, localized and estimated automatically. The detection of the disturbance and its duration are attained by a proper application, on the sampled signal, of the continuous wavelet transform (CWT). Disturbance amplitude is estimated by decomposing, in an optimized way, the signal in frequency subbands by means of the discrete time wavelet transform (DTWT). The proposed method is characterized by high rejection to noise, introduced by both measurement chain and system under test, and it is designed for an agile disturbance classification. Moreover, it is also conceived for future implementation both in a real-time measurement equipment and in an off-line analysis tool. In the paper firstly the theoretical background is reported and briefly discussed. Then, the proposed method is described in detail. Finally, some case-studies are examined in order to highlight the performance of the method.

303 citations

Journal ArticleDOI
TL;DR: The purpose of this paper is to gain helpful information and hints to efficiently face coexistence problems between such networks and optimize their setup in some real-life conditions.
Abstract: Coexistence issues between IEEE 802.11b wireless communication networks and IEEE 802.15.4 wireless sensor networks, operating over the 2.4-GHz industrial, scientific, and medical band, are assessed. In particular, meaningful experiments that are performed through a suitable testbed are presented. Such experiments involve both the physical layer, through measurements of channel power and the SIR, and the network/transport layer, by means of packet loss ratio estimations. Different configurations of the testbed are considered; major characteristics, such as the packet rate, the packet size, the SIR, and the network topology, are varied. The purpose of this paper is to gain helpful information and hints to efficiently face coexistence problems between such networks and optimize their setup in some real-life conditions. Details concerning the testbed, the measurement procedure, and the performed experiments are provided.

183 citations

Journal ArticleDOI
TL;DR: The method succeeds in enhancing the classification performance with respect to other available solutions by exploiting the modularity as well as original strategies concerning wavelet network implementation and training.
Abstract: A methodology is presented for developing a digital signal-processing architecture capable of simultaneous and automated detection and classification of transient signals. The basic unit of the aforementioned architecture is the wavelet network, which combines the ability of the wavelet transform of analyzing nonstationary signals with the classification capability of artificial neural networks. By exploiting the modularity as well as original strategies concerning wavelet network implementation and training, the method succeeds in enhancing the classification performance with respect to other available solutions.

105 citations

Journal ArticleDOI
TL;DR: The proposed measurement procedure for choosing the optimal values of the parameters of the transform according to the local features of the analyzed signal is described, and the results of several experimental tests conducted both on monocomponent and multicomponent signals are presented; advantages over other solutions are also highlighted.
Abstract: A measurement method for instantaneous frequency estimation is presented in this paper. The method is based on the use of the chirplet transform, a linear time-frequency representation (TFR) allowing additional modifications of each cell on the time-frequency plane with respect to other TFRs. In particular, a modified version of this transform is proposed here; a bending effect can be further imposed on the cells. Thanks both to this feature and a suitable measurement procedure, properly set up by the authors, the method assures a satisfying accuracy in reconstructing the instantaneous frequency trajectory of monocomponent signals as well as a good resolving capability in the analysis of multicomponent signals whose instantaneous frequency trajectories are strongly nonlinear and very close to one another. Theoretical details concerning the chirplet transform and its modified version are first given. Then, the proposed measurement procedure for choosing the optimal values of the parameters of the transform according to the local features of the analyzed signal is described. At the end, the results of several experimental tests conducted both on monocomponent and multicomponent signals are presented; advantages over other solutions are also highlighted.

77 citations

Journal ArticleDOI
TL;DR: This paper proposes a wearable monitoring system for inspection in the framework of Industry 4.0 that integrates augmented reality glasses with a noninvasive single-channel brain–computer interface (BCI), which replaces the classical input interface of AR platforms.
Abstract: This paper proposes a wearable monitoring system for inspection in the framework of Industry 4.0. The instrument integrates augmented reality (AR) glasses with a noninvasive single-channel brain–computer interface (BCI), which replaces the classical input interface of AR platforms. Steady-state visually evoked potentials (SSVEP) are measured by a single-channel electroencephalography (EEG) and simple power spectral density analysis. The visual stimuli for SSVEP elicitation are provided by AR glasses while displaying the inspection information. The real-time metrological performance of the BCI is assessed by the receiver operating characteristic curve on the experimental data from 20 subjects. The characterization was carried out by considering stimulation times from 10.0 down to 2.0 s. The thresholds for the classification were found to be dependent on the subject and the obtained average accuracy goes from 98.9% at 10.0 s to 81.1% at 2.0 s. An inspection case study of the integrated AR-BCI device shows encouraging accuracy of about 80% of lab values.

75 citations


Cited by
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Journal Article
TL;DR: This book by a teacher of statistics (as well as a consultant for "experimenters") is a comprehensive study of the philosophical background for the statistical design of experiment.
Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

13,333 citations

Journal Article
TL;DR: This study reviews several of the most commonly used inductive teaching methods, including inquiry learning, problem-based learning, project-basedLearning, case-based teaching, discovery learning, and just-in-time teaching, and defines each method, highlights commonalities and specific differences, and reviews research on the effectiveness.
Abstract: Traditional engineering instruction is deductive, beginning with theories and progressing to the applications of those theories Alternative teaching approaches are more inductive Topics are introduced by presenting specific observations, case studies or problems, and theories are taught or the students are helped to discover them only after the need to know them has been established This study reviews several of the most commonly used inductive teaching methods, including inquiry learning, problem-based learning, project-based learning, case-based teaching, discovery learning, and just-in-time teaching The paper defines each method, highlights commonalities and specific differences, and reviews research on the effectiveness of the methods While the strength of the evidence varies from one method to another, inductive methods are consistently found to be at least equal to, and in general more effective than, traditional deductive methods for achieving a broad range of learning outcomes

1,673 citations

01 Jan 2007
TL;DR: In this paper, the authors provide updates to IEEE 802.16's MIB for the MAC, PHY and asso-ciated management procedures in order to accommodate recent extensions to the standard.
Abstract: This document provides updates to IEEE Std 802.16's MIB for the MAC, PHY and asso- ciated management procedures in order to accommodate recent extensions to the standard.

1,481 citations

Journal ArticleDOI
TL;DR: A comprehensive experimental study on the statistical characterization of the wireless channel in different electric-power-system environments, including a 500-kV substation, an industrial power control room, and an underground network transformer vault is presented.
Abstract: The collaborative and low-cost nature of wireless sensor networks (WSNs) brings significant advantages over traditional communication technologies used in today's electric power systems. Recently, WSNs have been widely recognized as a promising technology that can enhance various aspects of today's electric power systems, including generation, delivery, and utilization, making them a vital component of the next-generation electric power system, the smart grid. However, harsh and complex electric-power-system environments pose great challenges in the reliability of WSN communications in smart-grid applications. This paper starts with an overview of the application of WSNs for electric power systems along with their opportunities and challenges and opens up future work in many unexploited research areas in diverse smart-grid applications. Then, it presents a comprehensive experimental study on the statistical characterization of the wireless channel in different electric-power-system environments, including a 500-kV substation, an industrial power control room, and an underground network transformer vault. Field tests have been performed on IEEE 802.15.4-compliant wireless sensor nodes in real-world power delivery and distribution systems to measure background noise, channel characteristics, and attenuation in the 2.4-GHz frequency band. Overall, the empirical measurements and experimental results provide valuable insights about IEEE 802.15.4-compliant sensor network platforms and guide design decisions and tradeoffs for WSN-based smart-grid applications.

1,255 citations

Proceedings ArticleDOI
17 Aug 2015
TL;DR: SpotFi only uses information that is already exposed by WiFi chips and does not require any hardware or firmware changes, yet achieves the same accuracy as state-of-the-art localization systems.
Abstract: This paper presents the design and implementation of SpotFi, an accurate indoor localization system that can be deployed on commodity WiFi infrastructure. SpotFi only uses information that is already exposed by WiFi chips and does not require any hardware or firmware changes, yet achieves the same accuracy as state-of-the-art localization systems. SpotFi makes two key technical contributions. First, SpotFi incorporates super-resolution algorithms that can accurately compute the angle of arrival (AoA) of multipath components even when the access point (AP) has only three antennas. Second, it incorporates novel filtering and estimation techniques to identify AoA of direct path between the localization target and AP by assigning values for each path depending on how likely the particular path is the direct path. Our experiments in a multipath rich indoor environment show that SpotFi achieves a median accuracy of 40 cm and is robust to indoor hindrances such as obstacles and multipath.

1,159 citations