HF Radar observations of the Dardanelles outflow current in North Eastern Aegean using validated WERA HF radar data

A two-site WERA HF radar station was installed in November 2009 at the eastern coast of Lemnos Island in North Aegean Sea, aiming to monitor the surface inflow of Black Sea waters exiting from the Dardanelles Strait, as well as to constitute a coastal management tool for incidents of oil-pollution or save-and-rescue operations. Strong interference by foreign transmissions is a source of noise deteriorating the quality of the backscattered signal, thus significantly reducing the HF radar’s effective data return rate. In order to ameliorate this problem, further quality-control and data gap interpolating procedures have been developed and applied, to be used in addition to the procedures incorporated and used by the manufacturer’s signal processing software. The second-level processing involves traditional despiking in the temporal domain, preceding Empirical Orthogonal Function analysis. The latter is used not only to filter high-frequency noise but also to fill data gaps in time and space. The data reconstruction procedure has been assessed via comparison of (a) HF radial with CODE-type drifter radial velocities as well as (b) HF-derived virtual drifter tracks with actual drifter tracks. The main circulation features and their variability, as revealed by the reconstructed fields, are presented

Autonomous Drones for Trail Navigation using DNNs

Στην παρούσα διπλωματική εργασία, προτείνεται ο σχεδιασμός και η υλοποίηση ενός πρότυπου drone που έχει τη δυνατότητα αυτόνομης πλοήγησης σε δασικό μονοπάτι χωρίς πρότερη γνώση του περιβάλλοντα χώρου. Χρησιμοποιεί σύστημα τεχνητής όρασης τριών επιπέδων: (i) ένα νευρωνικό δίκτυο βάθους (DNN) για εκτίμηση πλευρικής μετατόπισης και προσανατολισμού ως προς το κέντρο του μονοπατιού, (ii) ένα DNN για αναγνώριση αντικειμένων, και (iii) ένα σύστημα αποφυγής εμποδίων. Η σύνθεση του μικρού εναέριου σκάφους (MAV) έγινε από διαθέσιμα εξαρτήματα (hardware) του εργαστηρίου. Για τον αλγόριθμο ακολουθίας δασικών μονοπατιών, ως βάση νευρωνικού δικτύου χρησιμοποιήθηκε το TrailNet. Στη συνέχεια επανεκπαιδεύτηκε και εμπλουτίστηκε με σύνολο δεδομένων που δημιουργήθηκε από την δασική περιοχή της Πανεπιστημιούπολης Ιλισίων, προσαρμόζοντάς το στην τοπική βλάστηση. Για την επιλογή των βέλτιστων αλγορίθμων αναγνώρισης αντικειμένων, έγινε δοκιμή και αξιολόγηση από αντίστοιχους της τελευταίας γενιάς στην πλακέτα επεξεργασίας Jetson TX2 της NVIDIA. Τέλος δίνεται πρόταση πειραματικής πτήσης με συγκεκριμένες παραμέτρους για την αξιολόγηση της ορθής λειτουργίας.This thesis proposes the design and implementation of a prototype drone stack that is able to autonomously navigate through a forest trail path without having prior knowledge of the surrounding area. It uses a 3 level vision system: (i) a deep neural network (DNN) for estimating the view orientation and lateral offset of the vehicle with respect to the trail center, (ii) a DNN for object detection and (iii) a Guidance system for obstacle avoidance. Hardware synthesis of the Micro Aerial Vehicle (MAV) was built upon hardware parts, available from the lab. Trail following algorithm makes use of TrailNet’s neural network. It was also retrained and enriched by a newly created dataset, formed with footage from the nearby forest canopy of Ilisia Univesity Campus. This also made the model more adaptive to local vegetation characteristics. For object detection service, a comparison between well-known algorithms was made and an evaluation was done in terms of accuracy and efficiency. These were tested on NVIDIA’s Jetson TX2 Dev Kit board. At last, a suggestion of an experimental flight is given with particular parameters, for the evaluation of the proper operation

Facilitating the Exploitation of Linked Open Statistical Data: JSON-QB API Requirements and Design Criteria

Recently, many organizations have opened up their data for others to reuse. A major part of these data concern statistics such as demographic and social indicators. Linked Data is a promising paradigm for opening data because it facilitates data integration on the Web. Re- cently, a growing number of organizations adopted linked data paradigm and provided Linked Open Statistical Data (LOSD). These data can be exploited to create added value services and applications that require integrated data from multiple sources. In this paper, we suggest that in order to unleash the full potential of LOSD we need to facilitate the interaction with LOSD and hide most of the complexity. Moreover, we describe the requirements and design criteria of a JSON-QB API that (i) facilitates the development of LOSD tools through a style of interaction familiar to web developers and (ii) offers a uniform way to access LOSD. A proof of concept implementation of the JSON-QB API demonstrates part of the proposed functionality

Statistical Mechanical Approach to Human Language

We use the formulation of equilibrium statistical mechanics in order to study some important characteristics of language. Using a simple expression for the Hamiltonian of a language system, which is directly implied by the Zipf law, we are able to explain several characteristic features of human language that seem completely unrelated, such as the universality of the Zipf exponent, the vocabulary size of children, the reduced communication abilities of people suffering from schizophrenia, etc. While several explanations are necessarily only qualitative at this stage, we have, nevertheless, been able to derive a formula for the vocabulary size of children as a function of age, which agrees rather well with experimental data.Comment: 20 pages,4 figures, Accepted in Physica

e-COVID: Ένα διαδραστικό διαδικτυακό Σ.Γ.Π. για τη μοντελοποίηση μεταβλητών του κορωνοϊού

Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) “Γεωπληροφορική

Dissecting the Butterfly: Representation of Disciplines Publishing at the Web Science Conference Series

International audienceWeb Science is an interdisciplinary arena. Motivated by the unforeseen scale and impact of the web, it addresses web-related research questions in a holistic manner, incorporating perspectives from a broad set of disciplines. There has been ongoing discussion about which disciplines are more or less present in the community, and about defining Web Science itself: there is, however, a dearth of empirical work in this area. This research note presents an early analysis of the presence of different disciplines in the Web Science community. To gain insight into this area, we applied Natural Language Processing and topic extraction to Web Science papers from 2009 to 2011. We compare the results to two current representations of Web Science: the 'Web Science butterfly' diagram and the Web Science Subject Categorization. We discuss the benefits of such an exploratory analysis, our early results, and steps for producing more robust results

Evolution of Vocabulary on Scale-free and Random Networks

We examine the evolution of the vocabulary of a group of individuals (linguistic agents) on a scale-free network, using Monte Carlo simulations and assumptions from evolutionary game theory. It is known that when the agents are arranged in a two-dimensional lattice structure and interact by diffusion and encounter, then their final vocabulary size is the maximum possible. Knowing all available words is essential in order to increase the probability to ``survive'' by effective reproduction. On scale-free networks we find a different result. It is not necessary to learn the entire vocabulary available. Survival chances are increased by using the vocabulary of the ``hubs'' (nodes with high degree). The existence of the ``hubs'' in a scale-free network is the source of an additional important fitness generating mechanism.Comment: 10 pages, 3 Figures, accepted in Physica

Language Time Series Analysis

We use the Detrended Fluctuation Analysis (DFA) and the Grassberger-Proccacia analysis (GP) methods in order to study language characteristics. Despite that we construct our signals using only word lengths or word frequencies, excluding in this way huge amount of information from language, the application of Grassberger- Proccacia (GP) analysis indicates that linguistic signals may be considered as the manifestation of a complex system of high dimensionality, different from random signals or systems of low dimensionality such as the earth climate. The DFA method is additionally able to distinguish a natural language signal from a computer code signal. This last result may be useful in the field of cryptography.Comment: 21 pages, 5 figures, accepted in Physica