Optimal Wideband LPDA Design for Efficient Multimedia Content Delivery over Emerging Mobile Computing Systems

An optimal synthesis of a wideband Log-Periodic Dipole Array (LPDA) is introduced in the present study. The LPDA optimization is performed under several requirements concerning the standing wave ratio, the forward gain, the gain flatness, the front-to-back ratio and the side lobe level, over a wide frequency range. The LPDA geometry that complies with the above requirements is suitable for efficient multimedia content delivery. The optimization process is accomplished by applying a recently introduced method called Invasive Weed Optimization (IWO). The method has already been compared to other evolutionary methods and has shown superiority in solving complex non-linear problems in telecommunications and electromagnetics. In the present study, the IWO method has been chosen to optimize an LPDA for operation in the frequency range 800-3300 MHz. Due to its excellent performance, the LPDA can effectively be used for multimedia content reception over future mobile computing systems

Exponential Log-Periodic Antenna Design Using Improved Particle Swarm Optimization with Velocity Mutation

An improved particle swarm optimization (PSO) method applied to the design of a new wideband log-periodic antenna (LPA) geometry is introduced. This new PSO variant, called PSO with velocity mutation (PSOvm), induces mutation on the velocities of those particles that cannot improve their position. The proposed LPA consists of wire dipoles with lengths and distances varied according to an exponential rule, which is defined by two specific parameters called length factor and spacing factor. The LPA is optimized for operation in 790-6000MHz frequency range, in order to cover the most usual wireless services in practice, and also to provide in this range the highest possible forward gain, gain flatness below 2dB, secondary lobe level below –20dB with respect to the main lobe peak, and standing wave ratio below 2. To demonstrate its superiority in terms of performance, PSOvm is compared to well-known optimization methods. The comparison is performed by applying all the methods on several test functions and also on the LPA optimization problem defined by the above-mentioned requirements. Furthermore, the radiation characteristics of the PSOvm-based LPA give prominence to the effectiveness of the proposed exponential geometry compared to the traditional Carrel’s geometry

Wavelet analysis applied on temporal data sets in order to reveal possible pre-seismic radio anomalies and comparison with the trend of the raw data

Since 2009, several radio receivers have been installed throughout Europe in order to realize the INFREP European radio network for studying the VLF (10-50 kHz) and LF (150-300 kHz) radio precursors of earthquakes. Precursors can be related to “anomalies” in the night-time behavior of VLF signals. A suitable method of analysis is the use of the Wavelet spectra. Using the “Morlet function”, the Wavelet transform of a time signal is a complex series that can be usefully represented by its square amplitude, i.e. considering the so-called Wavelet power spectrum. The power spectrum is a 2D diagram that, once properly normalized with respect to the power of the white noise, gives information on the strength and precise time of occurrence of the various Fourier components, which are present in the original time series. The main difference between the Wavelet power spectra and the Fourier power spectra for the time series is that the former identifies the frequency content along the operational time, which cannot be done with the latter. Anomalies are identified as regions of the Wavelet spectrogram characterized by a sudden increase in the power strength. On January 30, 2020 an earthquake with Mw= 6.0 occurred in Dodecanese Islands. The results of the Wavelet analysis carried out on data collected some INFREP receivers is compared with the trends of the raw data. The time series from January 24, 2020 till January 31, 2000 was analyzed. The Wavelet spectrogram shows a peak corresponding to a period of 1 day on the days before January 30. This anomaly was found for signals transmitted at the frequencies 19,58 kHz, 20, 27 kHz, 23,40 kHz with an energy in the peak increasing from 19,58 kHz to 23,40 kHz. In particular, the signal at the frequency 19,58 kHz, shows a peak on January 29, while the frequencies 20,27 kHz and 23,40 kHz are characterized by a peak starting on January 28 and continuing to January 29. The results presented in this work shows the perspective use of the Wavelet spectrum analysis as an operational tool for the detection of anomalies in VLF and LF signal potentially related to EQ precursors

Study of VLF/LF wave propagations above seismic areas

Abstract: We report on radio transmitter signals recorded in Europe by INFREP network which is mainly devoted to search for earthquakes electromagnetic precursors (Biagi et al., 2011). We consider in this analysis the detection of transmitter signals recorded by INFREP receivers located in different regions of Europe, i.e. Romania, Italy, Greece and Austria. The aim is the investigation of the electromagnetic environment above earthquakes regions. We selected seismic events which occurred in the year 2016 and characterized by a moment magnitude (Mw) above 5.0 and a depth of less than 50 km. A common method is applied to all events and which involves the analysis of the VLF/LF signal detection taking into consideration the following parameters: (a) the distance transmitters-receivers, (b) the signal to noise ratio during the diurnal and night observations, (c) the daily and night averaged amplitude and (d) the sunset and sunrise termination times. This leads us to specify the key factors which can be considered as criteria to distinguish and to identify earthquakes precursors. We discuss in this contribution the radio wave propagation in the D- and E-layers and their impacts on the VLF/LF amplitude signal. We show that the 'seismic anomaly' requests a more precise analysis of the 'quiet' and 'disturbed' ionospheric conditions and their corresponding spectral traces on the VLF/LF transmitter signals

Μελέτη κατώτερης ιονόσφαιρας και της αλληλεπίδρασης με σεισμική δραστηριότητα με την χρήση δικτύου δεκτών ραδιοκυμάτων

This work investigates the application of Digital Signal Processing methods, including the application of neural networks, in the study of lower ionosphere, and the seismic interactions before, during and after an earthquake. An introduction and analysis of the building blocks of the interactions from a geophysical perspective, and the different elements that make up the Lithosphere-Atmosphere-Ionosphere Connection (LAIC) mechanism, is presented. This mechanism describes the interactions during the preparation and occurrence of an earthquake, and the ionosphere. The International Network for Frontier Research on Earthquake Precursors (INFREP), a radio receiver network that has been used and expanded during this study is presented, along with the framework of other similar networks. For this study, the application of the Hilbert Huang Transformation (HHT) and the Zhao-Atlas-Marks Distribution (ZAMD), are presented, evaluated and compared to more traditional methods like the Wavelet Transformation (WT), and are found to be complementary for a full picture of the phenomenon. In addition, the next step of analysis, with the inclusion of Differential Analysis (DA), is presented, leveraging multiple receivers and transmitter pairs, for a detailed analysis. The application of Neural Networks, using Predictive Modular Neural Network (PREMONN) architecture, and Self-Organizing Maps (SOM) is demonstrated. As a final step, the complete process is presented, using different examples of significant earthquake events in the region of the receivers, and the repeatability of the process is validated, using two similar events, that occurred at different times, in the same area. From the above process, it is shown, that the methods presented, provide the capability to detect a pattern of disturbances with unique behavior, in multiple configurations of receivers and transmitters and with the analysis of these patterns, it is providing the capability to analyze in depth the interaction of precursors of seismic event, as they are detected in the lower ionosphere.Στην παρούσα εργασία μελετήθηκε η ανάπτυξη και εφαρμογή τεχνικών και μεθόδων Ψηφιακής Επεξεργασίας Σήματος και Νευρωνικών δικτύων για την μελέτη των αλληλεπιδράσεων μεταξύ κατώτερης ιονόσφαιρας και σεισμικής δραστηριότητας, πριν, κατά την διάρκεια και μετά από έναν σεισμό. Οι βασικοί γεωφυσικοί μηχανισμοί των αλληλεπιδράσεων αυτών παρουσιάστηκαν και περιγράφηκαν. Στη διαδικασία της έρευνας, που οδήγησε την παρούσα μελέτη, χρησιμοποιήθηκε και επεκτάθηκε ένα διεθνές δίκτυο δεκτών ραδιοκυμάτων VLF και LF, και παρουσιάστηκε η χρήση του δικτύου δεκτών στην λήψη σημάτων από ένα δίκτυο πομπών διεθνούς εμβέλειας. Στη συνέχεια, στην παρούσα μελέτη, παρουσιάστηκαν τα δεδομένα αυτού του δικτύου, και οι μέθοδοι οι οποίες εξελίχθηκαν για την μελέτη αυτών των δεδομένων. Τα αποτελέσματα αυτών των μεθόδων έδειξαν την μεγάλη χρησιμότητα αυτού του δικτύου. Η μεθοδολογία που αναπτύχθηκε περιγράφεται σε κάθε στάδιό της στην παρούσα εργασία, και για κάθε στάδιο, παρουσιάζονται αναλυτικά τα αποτελέσματα που εξάγονται. Περιληπτικά, η διαδικασία αποτελείται από την αρχική διαδικασία κανονικοποίησης των δεδομένων του δικτύου, ώστε να απορριφθούν οι διαφοροποιήσεις που μπορεί να οφείλονται στα ιδιαίτερα χαρακτηριστικά των διαφορετικών ζευγών πομπών-δεκτών που χρησιμοποιούνται. Εν συνεχεία, τα δεδομένα υπόκεινται σε μια δεύτερη επεξεργασία, χρησιμοποιώντας μία παραλλαγή του μετασχηματισμού Hilbert Huang (HHT) σε σχέση με τον αρχικό μετασχηματισμό HHT. Με την εφαρμογή της ανάλυσης αυτής εξάγεται το φασματικό περιεχόμενο των σημάτων και επιλέγεται ο θόρυβος που βρίσκεται στις υψηλότερες συχνότητες, διαλέγοντας για την μελέτη τις πρώτες δύο ενδογενείς συναρτήσεις ρυθμού (Intrinsic Mode Functions – IMF). Το αποτέλεσμα αυτής της διαδικασίας συγκρίνεται επίσης με τον μετασχηματισμό Zhao-Atlas-Marks (ZAMD). Στην διαδικασία παρουσίασης των τεχνικών, φάνηκε καθαρά το γεγονός ότι ο HHT και ο ZAM αλληλοσυμπληρώνονται στην ανάλυση των δεδομένων, και το ότι η χρήση και των δύο μεθόδων δίνει πληρέστερη εικόνα. Παρουσιάστηκε επίσης η χρήση Νευρωνικών Δικτύων, με την εφαρμογή των Predictive Modular Neural Network (PREMONN) , και Self-Organizing Maps (SOM) και τα αποτελέσματα που δείχνουν ότι δίνεται η δυνατότητα της αυτόματης επεξεργασίας των διαθέσιμων δεδομένων, και της αυτόματης επισήμανσης σημείων ενδιαφέροντος. Η πλήρης εφαρμογή της διαδικασίας που αναπτύχθηκε, δίνει μια ολοκληρωμένη επισκόπηση των δεδομένων, και τα αποτελέσματα αυτής παρουσιάστηκαν εκτενώς στην παρούσα εργασία. Στην συνέχεια, χρησιμοποιώντας ως βάση την δομής του δικτύου με πολλαπλούς δέκτες, και με την ανάπτυξη νέων μεθόδων ανάλυσης των δεδομένων βασισμένων στη χρήση διαφορικής ανάλυσης (DA), αλλά και εφαρμόζοντας όλη την προηγούμενη διαδικασία που έχει αναπτυχθεί, παρουσιάστηκε η βελτίωση των δυνατοτήτων του δικτύου, που μπορεί να δώσει πληρέστερη επισκόπηση ενός σεισμικού φαινομένου. Σε κάθε βήμα παρουσίασης της πλήρους μεθόδου παρουσιάστηκαν ανάλογα παραδείγματα σεισμών, με τα πραγματικά τους δεδομένα, δίνοντας λεπτομερή ανάλυση για 12 σεισμικά φαινόμενα, των τελευταίων 6 ετών, παρουσιάζοντας με παραδείγματα την σημασία κάθε βήματος και την σχέση του με τα προηγούμενα. Το σύνολο των μεθόδων ανάλυσης πρόδρομων σεισμικών φαινομένων που αναπτύχθηκε, παρέχει μια ολοκληρωμένη και ευσύνοπτη παρουσίαση νέων δεδομένων, επεκτείνοντας τις δυνατότητες του δικτύου των δεκτών που έχουν εγκατασταθεί και μπορεί να αποτελέσει ένα εργαλείο πρόγνωσης σεισμικής δραστηριότητας, και πιθανότατα να είναι κομμάτι ενός ολοκληρωμένου συστήματος προειδοποίησης για την αποφυγή υλικών ζημιών αλλά σημαντικότερα την αποφυγή απώλειας ανθρωπίνων ζωών

Application of empirical mode decomposition to very low frequency signals for identification of seismic-ionospheric precursor phenomena

<p>This study investigates the application of empirical mode decomposition to signals from very low frequency transmitters in Europe that were received in Thessaloniki, Greece, to provide a method for depicting seismic-ionospheric precursor phenomena that occur prior to an earthquake. The basis for ionosphere interactions with seismic phenomena has been well documented in past studies, and the depiction of disturbances applied from the earthionosphere waveguide on the received signals was the purpose of this study. Empirical mode decomposition is a method for processing of nonlinear and nonstationary signals, to decompose them into their functional components, known as intrinsic mode functions. This method can provide high pass filtering to signals, thus depicting a clearer image of any abnormal disturbances in the signals that are not part of the normal noise content. Observations of such precursor phenomena are presented and correlated to earthquakes, to demonstrate the effectiveness of this method.</p><p class="western" lang="en-US"><span style="font-family: Arial, sans-serif; font-size: xx-small;"><br /></span></p&gt

Variation of some planetary seismic hazard indices on the occasion of Lefkada, Greece, earthquake of 17 November, 2015

In this paper we investigate the variation of the tidal triggering effect efficiency, by means of the tidal seismicity compliance parameter p, and the lower Ionosphere variations, by means of the variation of the High-Frequency limit, fo, of the ionospheric turbulence content with the time and space proximity to the site of the earthquake occurrence as well as by the intensity variations of VLF signals transmitted over the seismic area. It is shown that the “Earth tides-seismicity compliance parameter” p may be used as a medium time earthquake warning while the frequency content of the ionospheric turbulence over the earthquake epicenter, deduced directly from GPS network TEC observations or indirectly through the VLF transmission network, may be used for the short time earthquake forecasting, deserving the special attention of the authorities, the scientists and the society

Ionospheric turbulence from TEC variations and VLF/LF transmitter signal observations before and during the destructive seismic activity of August and October 2016 in Central Italy

In this paper we investigate the ionospheric turbulence from observations of TEC variations as well as from VLF/LF transmitter signal observations before and during the disastrous seismic activity of August and October 2016 in Central Italy. The Total Electron Content (TEC) data of 8 Global Positioning System (GPS) stations of the EUREF network, which are being provided by IONOLAB (Turkey), were analysed using Discrete Fourier Analysis in order to investigate the TEC variations. The data acquired for VLF/LF signal observations are from the receiver of Thessaloniki (40.59N, 22,78E), Greece, which monitor the VLF/LF transmitters of the International Network for Frontier Research on Earthquake Precursors (INFREP). A method of normalization according to the distance between the receiver and the transmitter is applied on the above data and then they are processed by the Hilbert Huang Transform (HHT) to produce the corresponding spectra for visual analysis. The results of both methods indicate that the High- Frequency limit fo, of the ionospheric turbulence content, increases as the site and the moment of the earthquake occurrence is approaching, pointing to the earthquake locus