Publications
2022
Conference Papers
Dimitrios Kavelidis Frantzis, Emmanouil Tsardoulias, Thomas Karanikiotis, Eleni Poptsi, Magda Tsolaki and Andreas Symeonidis
National Conference ACOUSTICS 2022, 2022 Oct
![]() ![]() In this study, the validity of a Machine Learning multiclass classification process is examined, as to classify a speaker in a cognitive decline stage, aiming to develop a simple screening test. The target classes comprise Cognitively Healthy controls, Subjective Cognitive Decline and Early & Late Mild Cognitive Impairment. Speech data was collected from structured interviews on 84 people, split in stages of increasing required levels of cognitive difficulty. Audio features were extracted based on Silence, Prosody and Zero-Crossings, as well as on the feature vectors’ differences between stages, and were evaluated with the Random Forest, Extra-Trees and Support Vector Machines classifiers. The best classification was achieved using models trained with stage differences features (on SVM), resulting in a mean accuracy of 80.99±3.29%. @conference{2022kavAlzSpeech, | |
Eleni Poptsi, Despoina Moraitou, Emmanouil Tsardoulias, Andreas Symeonidis and Magda Tsolaki
"Υποκειμενική νοητική εξασθένιση: Κομμάτι της υγιούς γήρανσης ή έναρξη νευροεκφύλισης; Νεότερα δεδομένα της συστοιχίας R4Alz"
8ο Παγκρήτιο Διεπιστημονικό Συνέδριο Νόσου Alzheimer και Συναφών Διαταραχών και 4ο Πανελλήνιο Συνέδριο στην ενεργό και υγιή γήρανση, Σεπτεμβρίος 2022, Εμπορικό και Βιομηχανικό Επιμελητήριο Ηρακλείου, 2022 Sep
![]() @conference{2022Kretepub1, | |
Evangelos Papathomas, Themistoklis Diamantopoulos and Andreas Symeonidis
"Semantic Code Search in Software Repositories using Neural Machine Translation"
Fundamental Approaches to Software Engineering, pp. 225-244, Springer International Publishing, Cham, 2022 Apr
![]() ![]() ![]() Nowadays, software development is accelerated through the reuse of code snippets found online in question-answering platforms and software repositories. In order to be efficient, this process requires forming an appropriate query and identifying the most suitable code snippet, which can sometimes be challenging and particularly time-consuming. Over the last years, several code recommendation systems have been developed to offer a solution to this problem. Nevertheless, most of them recommend API calls or sequences instead of reusable code snippets. Furthermore, they do not employ architectures advanced enough to exploit the semantics of natural language and code in order to form the optimal query from the question posed. To overcome these issues, we propose CodeTransformer, a code recommendation system that provides useful, reusable code snippets extracted from open-source GitHub repositories. By employing a neural network architecture that comprises advanced attention mechanisms, our system effectively understands and models natural language queries and code snippets in a joint vector space. Upon evaluating CodeTransformer quantitatively against a similar system and qualitatively using a dataset from Stack Overflow, we conclude that our approach can recommend useful and reusable snippets to developers. @conference{FASE2022, | |
Andreas Goulas, Nikolaos Malamas and Andreas L. Symeonidis
"A Methodology for Enabling NLP Capabilities on Edge and Low-Resource Devices"
Natural Language Processing and Information Systems, pp. 197--208, Springer International Publishing, Cham, 2022 Jun
![]() ![]() ![]() Conversational assistants with increasing NLP capabilities are becoming commodity functionality for most new devices. However, the underlying language models responsible for language-related intelligence are typically characterized by a large number of parameters and high demand for memory and resources. This makes them a no-go for edge and low-resource devices, forcing them to be cloud-hosted, hence experiencing delays. To this end, we design a systematic language-agnostic methodology to develop powerful lightweight NLP models using knowledge distillation techniques, this way building models suitable for such low resource devices. We follow the steps of the proposed approach for the Greek language and build the first - to the best of our knowledge - lightweight Greek language model, which we make publicly available. We train and evaluate GloVe word embeddings in Greek and efficiently distill Greek-BERT into various BiLSTM models, without considerable loss in performance. Experiments indicate that knowledge distillation and data augmentation can improve the performance of simple BiLSTM models for two NLP tasks in Modern Greek, i.e., Topic Classification and Natural Language Inference, making them suitable candidates for low-resource devices. @inproceedings{goulas-et-al, | |
Argyrios Papoudakis, Thomas Karanikiotis and Andreas Symeonidis
"A Mechanism for Automatically Extracting Reusable and Maintainable Code Idioms from Software Repositories"
Proceedings of the 17th International Conference on Software Technologies - ICSOFT, pp. 79-90, SciTePress, 2022 Jul
![]() ![]() ![]() The importance of correct, qualitative and evolvable code is non-negotiable, when considering the maintainability potential of software. At the same time, the deluge of software residing in code hosting platforms has led to a new component-based software development paradigm, where reuse of suitable software components/ snippets is important for software projects to be implemented as fast as possible. However, ensuring acceptable quality that will guarantee basic maintainability is also required. A condition for acceptable software reusability and maintainability is the use of idiomatic code, based on syntactic fragments that recur frequently across software projects and are characterized by high quality. In this work, we present a mechanism that employs the top repositories from GitHub in order to automatically identify reusable and maintainable code idioms. By extracting the Abstract Syntax Tree representation of each project we group code snippets that appear to have similar struc tural and semantic information. Preliminary evaluation of our methodology indicates that our approach can identify commonly used, reusable and maintainable code idioms that can be effectively given as actionable recommendations to the developers. @conference{icsoft22karanikiotis, | |
Georgios Kalantzis, Gerasimos Papakostas, Thomas Karanikiotis, Michail Papamichail and Andreas Symeonidis
"A Heuristic Approach towards Continuous Implicit Authentication"
2022 IEEE International Joint Conference on Biometrics (IJCB), pp. 1-7, IEEE, 2022 Oct
![]() ![]() ![]() Smartphones nowadays handle large amounts of sensitive user information, since users exchange undisclosed information on an everyday basis. This generates the need for more effective authentication mechanisms, deviating from the traditional ones. In this direction, many research approaches are targeted towards continuous implicit authentication, on the basis of modelling the constant interaction of the user with the device. These approaches yield promising results, however certain improvements can be made by exploiting the sequential order of the predictions and the known performance metrics. In this work, we propose a heuristics algorithm, which, given a series of predictions from any continuous implicit authentication model, can ex-ploit the sequential order in order to fix any false predictions and improve the accuracy of the smartphone security system. Preliminary evaluation on several axes indicates that our approach can effectively improve any CIA model and achieve significantly better results. @conference{ijcb2022karanikiotis, | |
Eleni Poptsi, Despoina Moraitou, Emmanouil Tsardoulias, Andreas Symeonidis and Magda Tsolaki
"Νευροψυχολογική συστοιχία REMEDES for Alzheimer (R4Alz): Παρουσίαση ενός εργαλείου πρώιμης διάγνωσης των νευροεκφυλιστικών νοσημάτων"
8ο Παγκρήτιο Διεπιστημονικό Συνέδριο Νόσου Alzheimer και Συναφών Διαταραχών και 4ο Πανελλήνιο Συνέδριο στην ενεργό και υγιή γήρανση, Σεπτεμβρίος 2022, Εμπορικό και Βιομηχανικό Επιμελητήριο Ηρακλείου, 2022 Sep
![]() @conference{Kreteconf2_2022, | |
Emmanouil Tsardoulias, Eleni Poptsi, Dimitrios F. Kavelidis, Thomas Karanikiotis, Magda Tsolaki, Despoina Moraitou and Andreas L. Symeonidis
"Early detection of neurocognitive decline using Cyber Physical Systems and Artificial Intelligence"
9th Technology Forum, Thessaloniki, 2022 Sep
![]() ![]() @conference{tf20221, | |
Theodoros Papafotiou, Efthymia Amarantidou, Efseveia Nestoropoulou and Emmanouil Tsardoulias
"Autonomous Driving Vehicle in 1:10 scaled environment"
9th Technology Forum, Thessaloniki, 2022 Sep
![]() ![]() @conference{tf20222, | |
Konstantinos Panayiotou, Emmanouil Tsardoulias and Andreas Symeonidis
"Low-code development & verification of Cyber-Physical Systems"
9th Technology Forum, Thessaloniki, 2022 Sep
![]() ![]() @conference{tf20223, |
2021
Conference Papers
2020
Conference Papers
2019
Conference Papers
Kyriakos C Chatzidimitriou, Michail D Papamichail, Napoleon-Christos I Oikonomou, Dimitrios Lampoudis and Andreas L Symeonidis
"Cenote: A Big Data Management and Analytics Infrastructure for the Web of Things"
IEEE/WIC/ACM International Conference on Web Intelligence, pp. 282-285, ACM, 2019 Oct
![]() ![]() ![]() In the era of Big Data, Cloud Computing and Internet of Things, most of the existing, integrated solutions that attempt to solve their challenges are either proprietary, limit functionality to a predefined set of requirements, or hide the way data are stored and accessed. In this work we propose Cenote, an open source Big Data management and analytics infrastructure for the Web of Things that overcomes the above limitations. Cenote is built on component-based software engineering principles and provides an all-inclusive solution based on components that work well individually. @inproceedings{Chatzidimitriou:2019:CBD:3350546.3352531, | |
Themistoklis Diamantopoulos, Maria-Ioanna Sifaki and Andreas L. Symeonidis
"Towards Mining Answer Edits to Extract Evolution Patterns in Stack Overflow"
16th International Conference on Mining Software Repositories, 2019 Mar
![]() ![]() ![]() Thecurrentstateofpracticedictatesthatinorderto solve a problem encountered when building software, developers ask for help in online platforms, such as Stack Overflow. In this context of collaboration, answers to question posts often undergo several edits to provide the best solution to the problem stated. In this work, we explore the potential of mining Stack Overflow answer edits to extract common patterns when answering a post. In particular, we design a similarity scheme that takes into account the text and code of answer edits and cluster edits according to their semantics. Upon applying our methodology, we provide frequent edit patterns and indicate how they could be used to answer future research questions. Our evaluation indicates that our approach can be effective for identifying commonly applied edits, thus illustrating the transformation path from the initial answer to the optimal solution. @conference{Diamantopoulos2019, | |
Tsardoulias Emmanouil, Panayiotou Konstantinos, Symeonidis Andreas and Petrou Loukas
"REMEDES: Τεχνικά χαρακτηριστικά και προδιαγραφές συστήματος αποτίμησης κιναισθησίας προς διάγνωση της νόσου Alzheimer"
11th Panhellenic Conference on Alzheimer's Disease & 3rd Mediterranean Conference on Neurodegenerative Diseases PICAD & MeCoND, Thessaloniki, Greece, 2019 Feb
![]() ![]() Το REMEDES αποτελεί ένα σύστημα προσανατολισμένο στην μέτρηση και καταγραφή αντανακλαστικών και αντίδρασης με υψηλή ακρίβεια, κάνοντας χρήση οπτικών ή/και ακουστικών ερεθισμάτων. Το σύστημα είναι κατάλληλο για την ποσοτικοποίηση της ιδιοδεκτικότητας/κιναισθησίας, καθώς στηρίζεται στο βασικό πεδίο της ανθρώπινης δράσης/αντίδρασης, έχοντας ως είσοδο την όραση ή την ακοή και έξοδο το μυοσκελετικό σύστημα. Ως σύστημα, το REMEDES αποτελείται από έναν αριθμό ασύρματων φορητών συσκευών (Pads), οι οποίες μπορούν να τοποθετηθούν στον χώρο και να “προγραμματιστούν” ανάλογα, υλοποιώντας έτσι διάφορους τύπους ασκήσεων. Μέσω του κατάλληλου λογισμικού, για κάθε άσκηση γίνεται ανάλυση αποτελεσμάτων, ενώ παρέχονται στοιχεία επίδοσης χρήστη. Το σύστημα δίνει την δυνατότητα σύγκρισης των επιδόσεων ανάμεσα σε άλλους χρήστες ή ομάδες χρηστών. Κάθε REMEDES Pad ενεργοποιείται, παράγοντας φως συγκεκριμένου χρώματος/φωτεινότητας ή ήχο συγκεκριμένης έντασης/συχνότητας. Στη συνέχεια, ο εκάστοτε χρήστης καλείται να το “απενεργοποιήσει”, περνώντας το χέρι (ή άλλο μέλος του σώματος ανάλογα με την άσκηση) μπροστά από το εμπρόσθιο μέρος της συσκευής, οπότε και καταγράφεται με ακρίβεια ο χρόνος που πέρασε από την ενεργοποίηση έως την απενεργοποίηση του Pad. Κάθε άσκηση αποτελείται από έναν αριθμό τέτοιων ενεργοποιήσεων/απενεργοποιήσεων. Συνεπώς συνδυάζοντας διαφορετικές τοπολογίες και διαφορετικά ερεθίσματα (χρώματα, φωτεινότητες, ήχο), μπορεί να δημιουργηθεί ένα μεγάλο εύρος ασκήσεων διαφορετικής πολυπλοκότητας και δυσκολίας. Το σύστημα καταμετρά τις έγκυρες, άκυρες και εσφαλμένες απενεργοποιήσεις, όπως και όλους τους χρόνους απόκρισης, και παρουσιάζει τα αποτελέσματα σε γραφική κι επεξεργάσιμη μορφή. Ένα από τα ανταγωνιστικά πλεονεκτήματα του συστήματος REMEDES σε σχέση με άλλα, παρόμοια, συστήματα είναι ότι υποστηρίζει μέσα από τη διαδικτυακή γραφική του διεπαφή τη δημιουργία και εκτέλεση ασκήσεων τυχαίας ενεργοποίησης (όπου το σύστημα αποφασίζει ποιες συσκευές θα ενεργοποιηθούν ανάλογα με παραμέτρους εισόδου), ασκήσεις προκαθορισμένων βημάτων, όπως και ασκήσεις ελέγχου μνήμης. Στη συγκεκριμένη ομιλία θα παρουσιαστούν ο τρόπος λειτουργίας του συστήματος, οι οθόνες διεπαφής όπου εμφανίζονται τα αποτελέσματα και μία μικρή επίδειξη ενδεικτικών ασκήσεων. @conference{EmmanouilPICAD2019, | |
Konstantinos Panayiotou, Emmanouil Tsardoulias, Christopher Zolotas, Iason Paraskevopoulos, Alexandra Chatzicharistou, Alexandros Sahinis, Stathis Dimitriadis, Dimitra Ntzioni, Christopher Mpekos, Giannis Manousaridis, Aris Georgoulas and Andreas Symeonidis
"Ms Pacman and the Robotic Ghost: A Modern Cyber-Physical Remake of the Famous Pacman Game"
2019 Sixth International Conference on Internet of Things: Systems, Management and Security (IOTSMS), 2019 Oct
![]() ![]() ![]() Robotics and Internet of Things (IoT) are two of the most blooming scientific areas during the last years. Robotics has gained a lot of attention in the last decades and includes several disciplines (mapping, localization, planning, control etc.), while IoT is a quite new and exciting area, where seamless data aggregation and resource utilization from heterogeneous physical objects (e.g. devices, sensor networks and robots) is defined via multi-layer architectures. Moreover, Cyber-Physical systems (CPS) share similar concepts and principles with the IoT, focused on interconnecting physical and computational resources via multi-layer architectures. The current paper joins the Robotics and CPS disciplines via an architecture where heterogeneous physical and computational elements exist (robots, web app, message broker etc.), so as to implement a cyber-physical port of the famous Pacman game, called RoboPacman. @conference{etsardouPacman2019, | |
Anastasios Tzitzis, Spyros Megalou, Stavroula Siachalou, Emmanouil Tsardoulias, Traianos Yioultsis and Antonis G. Dimitriou
"3D Localization of RFID Tags with a Single Antenna by a Moving Robot and ”Phase ReLock”"
2019 IEEE International Conference on RFID Technology and Applications (RFID-TA), 2019 Sep
![]() ![]() ![]() In this paper, we propose a novel method for the three dimensional (3D) localization of RFID tags, by deploying a single RFID antenna on a robotic platform. The constructed robot is capable of performing Simultaneous Localization (of its own position) and Mapping (SLAM) of the environment and then locating the tags around its path. The proposed method exploits the unwrapped measured phase of the backscattered signal, in such manner that the localization problem can be solved rapidly by standard optimization methods. Three dimensional solution is accomplished with a single antenna on top of the robot, by forcing the robot to traverse non-straight paths (e.g. s-shaped) along the environment. It is proven theoretically and experimentally that any non-straight path reduces the locus of possible solutions to only two points along the 3D space, instead of the circle that represents the corresponding locus for typical straight robot trajectories. As a consequence, by applying our proposed method ”Phase Relock” along the known half-plane of the search-space, the unique solution is rapidly found. We experimentally compare our method against the ”holographic” method, which represents the accuracy benchmark in priorart, deploying commercial off-the-shelf (COTS) equipment. Both algorithms find the unique solution, as expected. Furthermore, ”Phase ReLock” overcomes the calculations-grid constraints of the latter. Thus, better accuracy is achieved, while, more importantly, Phase-Relock is orders of magnitude faster, allowing for the applicability of the method in real-time inventorying and localization. @conference{etsardouRfid12019, | |
Stavroula Siachalou, Spyros Megalou, Anastasios Tzitzis, Emmanouil Tsardoulias, John Sahalos, Traianos Yioultsis and Antonis G. Dimitriou
"Robotic Inventorying and Localization of RFID Tags, Exploiting Phase-Fingerprinting"
2019 IEEE International Conference on RFID Technology and Applications (RFID-TA), 2019 Sep
![]() ![]() ![]() In this paper we investigate the performance of phase-based fingerprinting for the localization of RFID-tagged items in warehouses and large retail stores, by deploying ground and aerial RFID-equipped robots. The measured phases of the target RFID tags, collected along a given robot's trajectory, are compared to the corresponding phase-measurements of reference RFID tags; i.e. tags placed at known locations. The advantage of the method is that it doesn't need to estimate the robot's trajectory, since estimation is carried out by comparing phase measurements collected at neighboring time-intervals. This is of paramount importance for an RFID equipped drone, destined to fly indoors, since its weight should be kept as low as possible, in order to constrain its diameter correspondingly small. The phase measurements are initially unwrapped and then fingerprinting is applied. We compare the phase-fingerprinting with RSSI based fingerprinting. Phase-fingerprinting is significantly more accurate, because of the shape of the phase-function, which is typically U-shaped, with its minimum, measured at the point of the trajectory, when the robot-tag distance is minimised. Experimental accuracy of 15cm is typically achieved, depending on the density of the reference tags' grid. @conference{etsardouRfid22019, | |
Michail D. Papamichail, Themistoklis Diamantopoulos, Vasileios Matsoukas, Christos Athanasiadis and Andreas L. Symeonidis
"Towards Extracting the Role and Behavior of Contributors in Open-source Projects"
Proceedings of the 14th International Conference on Software Technologies - Volume 1: ICSOFT, pp. 536-543, SciTePress, 2019 Jul
![]() ![]() ![]() Lately, the popular open source paradigm and the adoption of agile methodologies have changed the way soft-ware is developed. Effective collaboration within software teams has become crucial for building successful products. In this context, harnessing the data available in online code hosting facilities can help towards understanding how teams work and optimizing the development process. Although there are several approaches that mine contributions’ data, they usually view contributors as a uniform body of engineers, and focus mainlyon the aspect of productivity while neglecting the quality of the work performed. In this work, we design a methodology for identifying engineer roles in development teams and determine the behaviors that prevail for each role. Using a dataset of GitHub projects, we perform clustering against the DevOps axis, thus identifying three roles: developers that are mainly preoccupied with code commits, operations engineers that focus on task assignment and acceptance testing, and the lately popular role of DevOps engineers that are a mix of both.Our analysis further extracts behavioral patterns for each role, this way assisting team leaders in knowing their team and effectively directing responsibilities to achieve optimal workload balancing and task allocati @inproceedings{icsoft19devops, | |
Kyriakos C. Chatzidimitriou, Michail D. Papamichail, Themistoklis Diamantopoulos, Napoleon-Christos Oikonomou and Andreas L. Symeonidis
"npm Packages as Ingredients: A Recipe-based Approach - Volume 1: ICSOFT"
Proceedings of the 14th International Conference on Software Technologies, pp. 544-551, SciTePress, 2019 Jul
![]() ![]() ![]() The sharing and growth of open source software packages in the npm JavaScript (JS) ecosystem has beenexponential, not only in numbers but also in terms of interconnectivity, to the extend that often the size of de-pendencies has become more than the size of the written code. This reuse-oriented paradigm, often attributedto the lack of a standard library in node and/or in the micropackaging culture of the ecosystem, yields interest-ing insights on the way developers build their packages. In this work we view the dependency network of thenpm ecosystem from a “culinary” perspective. We assume that dependencies are the ingredients in a recipe,which corresponds to the produced software package. We employ network analysis and information retrievaltechniques in order to capture the dependencies that tend to co-occur in the development of npm packages andidentify the communities that have been evolved as the main drivers for npm’s exponential grow. @inproceedings{icsoft19npm, | |
Maria Kotouza, Fotis Psomopoulos and Periklis A. Mitkas
New Trends in Databases and Information Systems, pp. 564-569, Springer International Publishing, Cham, 2019 Sep
![]() ![]() Nowadays, a wide range of sciences are moving towards the Big Data era, producing large volumes of data that require processing for new knowledge extraction. Scientific workflows are often the key tools for solving problems characterized by computational complexity and data diversity, whereas cloud computing can effectively facilitate their efficient execution. In this paper, we present a generative big data analysis workflow that can provide analytics, clustering, prediction and visualization services to datasets coming from various scientific fields, by transforming input data into strings. The workflow consists of novel algorithms for data processing and relationship discovery, that are scalable and suitable for cloud infrastructures. Domain experts can interact with the workflow components, set their parameters, run personalized pipelines and have support for decision-making processes. As case studies in this paper, two datasets consisting of (i) Documents and (ii) Gene sequence data are used, showing promising results in terms of efficiency and performance. @inproceedings{Kotouza19NTDIS, | |
Ιoannis Maniadis, Konstantinos N. Vavliakis and Andreas L. Symeonidis
"Banner Personalization for e-Commerce"
AIAI 2019: Artificial Intelligence Applications and Innovations, pp. 635-646, 2019 May
![]() @inproceedings{kvavAIAI2019, | |
Spyros Megalou, Anastasios Tzitzis, Stavroula Siachalou, Traianos Yioultsis, John Sahalos, Emmanouil Tsardoulias, Alexandros Filotheou, Andreas Symeonidis, Loukas Petrou and Antonis G. Dimitriou
"Fingerprinting Localization of RFID tags with Real-Time Performance-Assessment, using a Moving Robot"
13th European Conference of Antennas and Propagation, Krakow, Poland, 2019 Jan
![]() @conference{Megalou2019, | |
Konstantinos Panayiotou, Emmanouil Tsardoulias, Christopher Zolotas, Iason Paraskevopoulos, Alexandra Chatzicharistou, Alexandros Sahinis, Stathis Dimitriadis, Dimitra Ntzioni, Christopher Mpekos, Giannis Manousaridis, Aris Georgoulas and Andreas L. Symeonidis
"Ms Pacman and the Robotic Ghost: A Modern Cyber-Physical Remake of the Famous Pacman Game"
2019 Sixth International Conference on Internet of Things: Systems, Management and Security (IOTSMS), pp. 147-154, 2019 Oct
![]() ![]() @inproceedings{panayiotou2019ms, | |
Eleni Poptsi, Despoina Moraitou, Tsardoulias Emmanouil, Panayiotou Konstantinos, Symeonidis Andreas, Petrou Loukas and Magda Tsolaki
"Συστοιχία REMEDES: Ένα νέο ηλεκτρονικό εργαλείο αξιολόγησης ικανοτήτων νοητικού ελέγχου στη γήρανση"
11th Panhellenic Conference on Alzheimer's Disease & 3rd Mediterranean Conference on Neurodegenerative Diseases PICAD & MeCoND, Thessaloniki, Greece, 2019 Feb
![]() ![]() Στις μέρες μας, υπάρχουν αρκετά νευροψυχολογικά εργαλεία που έχουν χρησιμοποιηθεί για τον διαχωρισμό των νοητικά υγιών ατόμων άνω των 65 ετών, από τα άτομα με Υποκειμενική Νοητική Δυσλειτουργία (ΥΝΔ), με Ήπια Νοητική Δυσλειτουργία (ΗΝΔ) και άνοια. Με βάση την υπάρχουσα βιβλιογραφία, οι ικανότητες νοητικού ελέγχου όπως η αναστολή και η εργαζόμενη μνήμη έχουν συσχετιστεί με νοητική έκπτωση και άνοια. Ωστόσο, οι δοκιμασίες που χρησιμοποιούνται έως σήμερα τείνουν να επηρεάζονται είτε από το εκπαιδευτικό επίπεδο του εξεταζόμενου, είτε από αντίστοιχες γλωσσικές μειονεξίες. Γι’ αυτό το λόγο τα υπάρχοντα εργαλεία φαίνεται να μην είναι ιδιαίτερα ευαίσθητα στη διαφορική διάγνωση μεταξύ των παραπάνω ομάδων. Κατά συνέπεια, η σχεδίαση κατάλληλων συστοιχιών/εργαλείων που μπορούν να εκτιμήσουν της ικανότητες νοητικού ελέγχου, χωρίς να απαιτούν γλωσσικές ικανότητες (μειώνοντας έτσι την επίδραση του εκπαιδευτικού επιπέδου των συμμετεχόντων) παραμένει ένα θέμα ιδιαίτερα επίκαιρο. Για το σκοπό αυτό δημιουργήθηκε μια συστοιχία αξιολόγησης του νοητικού ελέγχου προσαρμόζοντας το σύστημα “REMEDES1”, ένα σύστημα μέτρησης αντανακλαστικών/αντίδρασης. Η συστοιχία αυτή επικεντρώνεται σε τρεις διαφορετικές πτυχές του νοητικού ελέγχου (εργαζόμενη μνήμη, προσοχή κι εκτελεστική λειτουργία). Η πρώτη δοκιμασία εξετάζει ικανότητες εργαζόμενης μνήμης, ενώ η επόμενη εκτιμά ικανότητες εποπτικού συστήματος προσοχής. Οι τελευταία δοκιμασία διερευνά τον ανασταλτικό έλεγχο και την εναλλαγή κανόνων/έργων. Η συστοιχία δοκιμασιών REMEDES4Alzheimer θα εφαρμοστεί σε 150 συμμετέχοντες (n=150), οι οποίοι θα χωριστούν σε τέσσερις ομάδες: α) υγιείς ηλικιωμένοι, β) ηλικιωμένοι με Υποκειμενική Νοητική Διαταραχή (ΥNΔ), γ) διαγνωσθέντες με Ήπια Νοητική Διαταραχή (ΗNΔ) και δ) διαγνωσθέντες με ήπια άνοια. Στη συγκεκριμένη ομιλία θα παρουσιαστεί η φιλοσοφία και η δομή της συστοιχίας, τα πλεονεκτήματά της σε σχέση με τις υπόλοιπες συστοιχίες νοητικού ελέγχου που υπάρχουν, καθώς και τα πρώτα αποτελέσματα από το πιλοτικό στάδιο της μελέτης. @conference{PoptsiMeCoND2019, | |
Eleni Poptsi, Despoina Moraitou, Tsardoulias Emmanouil, Panayiotou Konstantinos, Symeonidis Andreas, Petrou Loukas and Magda Tsolaki
"Αξιολόγηση του νοητικού ελέγχου στη γήρανση με τη χρήση ηλεκτρονικών εργαλείων μέσω του συστήματος αντανακλαστικών/αντίδρασης REMEDES4Alzheimer"
11th Panhellenic Conference on Alzheimer's Disease & 3rd Mediterranean Conference on Neurodegenerative Diseases PICAD & MeCoND, Thessaloniki, Greece, 2019 Feb
![]() ![]() Η συστοιχία REMEDES4Alzheimer είναι ένα νέο ηλεκτρονικό εργαλείο που στοχεύει στην αξιολόγηση ικανοτήτων νοητικού ελέγχου και απευθύνεται σε ηλικιωμένους με νοητικά ελλείμματα. Η συστοιχία αυτή αποτελεί προσαρμογή του ήδη υπάρχοντος συστήματος αντανακλαστικών/αντίδρασης REMEDES. Στόχος της παρούσας συστοιχίας είναι η διαφορική διάγνωση μεταξύ ήπιων και μείζονων νοητικών διαταραχών από το φυσιολογικό γήρας και από το φυσιολογικό γήρας με ήπια νοητικά παράπονα. Το σύστημα αποτελείται από 7 φορητές συσκευές (REMEDES pads), οι οποίες είναι προγραμματισμένες να ενεργοποιούνται, δηλαδή να παράγουν χρώμα ή/και ήχο ανάλογα με τις απαιτήσεις της εκάστοτε υποδοκιμασίας. Για τις ανάγκες της αξιολόγησης του νοητικού ελέγχου στη γήρανση έχουν προσαρτηθεί στα REMEDES pads γραφικές αναπαραστάσεις ζώων, οι οποίες συνδυάζονται με τις αντίστοιχες ηχητικές αναπαραστάσεις. Ο εξεταζόμενος καλείται να απενεργοποιήσει τα REMEDES pads, περνώντας το χέρι του πάνω από κάθε ένα, ανάλογα με τις οδηγίες της κάθε υπο-δοκιμασίας. Κατά τη διάρκεια της εκτέλεσης της συστοιχίας δοκιμασιών, οι οδηγίες που αναφέρονται στα έργα δίνονται τόσο λεκτικά όσο και μη λεκτικά (μέσω εικονικών αναπαραστάσεων-σκίτσων). Η συστοιχία περιλαμβάνει δοκιμασίες οι οποίες αξιολογούν τρεις βασικές πλευρές των ικανοτήτων νοητικού ελέγχου. Η πρώτη δοκιμασία αξιολογεί ικανότητες εργαζόμενης μνήμης και συγκεκριμένα ικανότητες αποθήκευσης, επεξεργασίας και ενημέρωσης της εργαζόμενης μνήμης. Η δεύτερη δοκιμασία αξιολογεί το εποπτικό σύστημα προσοχής και συγκεκριμένα την οπτική και ακουστική επιλεκτική προσοχή, την συντηρούμενη και διαμοιραζόμενη προσοχή. Η τρίτη και τελευταία δοκιμασία αξιολογεί εκτελεστικές ικανότητες και συγκεκριμένα τον ανασταλτικό έλεγχο, την εναλλαγή των κανόνων/έργων και τη νοητική ευελιξία. Στη συγκεκριμένη ομιλία θα παρουσιαστεί η δομή και το περιεχόμενο της κάθε δοκιμασίας, ο τρόπος βαθμολόγησης της συστοιχίας καθώς και οι δυνατότητες που δίνει το γραφικό περιβάλλον του συστήματος. @conference{PoptsiPICAD2019, | |
Christos Psarras, Themistoklis Diamantopoulos and Andreas Symeonidis
"A Mechanism for Automatically Summarizing Software Functionality from Source Code"
Proceedings of the 2019 IEEE International Conference on Software Quality, Reliability and Security (QRS), pp. 121-130, IEEE, Sofia, Bulgaria, 2019 Jul
![]() ![]() ![]() When developers search online to find software components to reuse, they usually first need to understand the container projects/libraries, and subsequently identify the required functionality. Several approaches identify and summarize the offerings of projects from their source code, however they often require that the developer has knowledge of the underlying topic modeling techniques; they do not provide a mechanism for tuning the number of topics, and they offer no control over the top terms for each topic. In this work, we use a vectorizer to extract information from variable/method names and comments, and apply Latent Dirichlet Allocation to cluster the source code files of a project into different semantic topics.The number of topics is optimized based on their purity with respect to project packages, while topic categories are constructed to provide further intuition and Stack Exchange tags are used to express the topics in more abstract terms @inproceedings{QRS2019, | |
Stavroula Siachalou, Spyros Megalou, Anastasios Tzitzis, Emmanouil Tsardoulias, John Sahalos, Traianos Yioultsis and Antonis Dimitriou
"Robotic Inventorying and Localization of RFID Tags"
2019 IEEE International Conference on RFID Technology and Applications (RFID-TA), pp. 362-367, IEEE, 2019 Sep
![]() ![]() ![]() In this paper we investigate the performance of phase-based fingerprinting for the localization of RFID-tagged items in warehouses and large retail stores, by deploying ground and aerial RFID-equipped robots. The measured phases of the target RFID tags, collected along a given robot’s trajectory, are compared to the corresponding phase-measurements of reference RFID tags; i.e. tags placed at known locations. The advantage of the method is that it doesn’t need to estimate the robot’s trajectory, since estimation is carried out by comparing phase measurements collected at neighboring time-intervals. This is of paramount importance for an RFID equipped drone, destined to fly indoors, since its weight should be kept as low as possible, in order to constrain its diameter correspondingly small. The phase measurements are initially unwrapped and then fingerprinting is applied. We compare the phase-fingerprinting with RSSI based fingerprinting. Phase-fingerprinting is significantly more accurate, because of the shape of the phase-function, which is typically U-shaped, with its minimum, measured at the point of the trajectory, when the robot-tag distance is minimised. Experimental accuracy of 15cm is typically achieved, depending on the density of the reference tags’ grid. @inproceedings{siachalou2019robotic, | |
Anastasios Tzitzis, Spyros Megalou, Stavroula Siachalou, Traianos Yioultsis, John Sahalos, Emmanouil Tsardoulias, Alexandros Filotheou, Andreas Symeonidis, Loukas Petrou and Antonis G. Dimitriou
"Phase ReLock - Localization of RFID Tags by a Moving Robot"
13th European Conference of Antennas and Propagation, Krakow, Poland, 2019 Jan
![]() @conference{Tzitzis2019, | |
Anastasios Tzitzis, Spyros Megalou, Stavroula Siachalou, Emmanouil Tsardoulias, Traianos Yioultsis and Antonis Dimitriou
"3D Localization of RFID Tags with a Single Antenna by a Moving Robot and” Phase ReLock”"
2019 IEEE International Conference on RFID Technology and Applications (RFID-TA), pp. 273-278, IEEE, 2019 Sep
![]() ![]() ![]() In this paper, we propose a novel method for the three dimensional (3D) localization of RFID tags, by deploying a single RFID antenna on a robotic platform. The constructed robot is capable of performing Simultaneous Localization (of its own position) and Mapping (SLAM) of the environment and then locating the tags around its path. The proposed method exploits the unwrapped measured phase of the backscattered signal, in such manner that the localization problem can be solved rapidly by standard optimization methods. Three dimensional solution is accomplished with a single antenna on top of the robot, by forcing the robot to traverse non-straight paths (e.g. s-shaped) along the environment. It is proven theoretically and experimentally that any non-straight path reduces the locus of possible solutions to only two points along the 3D space, instead of the circle that represents the corresponding locus for typical straight robot trajectories. As a consequence, by applying our proposed method ”Phase Relock” along the known half-plane of the search-space, the unique solution is rapidly found. We experimentally compare our method against the ”holographic” method, which represents the accuracy benchmark in priorart, deploying commercial off-the-shelf (COTS) equipment. Both algorithms find the unique solution, as expected. Furthermore, ”Phase ReLock” overcomes the calculations-grid constraints of the latter. Thus, better accuracy is achieved, while, more importantly, Phase-Relock is orders of magnitude faster, allowing for the applicability of the method in real-time inventorying and localization. @inproceedings{tzitzis20193d, | |
Konstantinos N. Vavliakis, George Katsikopoulos and Andreas L. Symeonidis
"E-commerce Personalization with Elasticsearch"
International Workshop on Web Search and Data Mining in conjunction with The 10th International Conference on Ambient Systems, Networks and Technologies (ANT 2019), Leuven, Belgium, 2019 Apr
![]() ![]() ![]() Personalization techniques are constantly gaining traction among e-commerce retailers, since major advancements have been made at research level and the benefits are clear and pertinent. However, effectively applying personalization in real life is a challenging task, since the proper mixture of technology, data and content is complex and differs between organizations. In fact, personalization applications such as personalized search remain largely unfulfilled, especially by small and medium sized retailers, due to time and space limitations. In this paper we propose a novel approach for near real-time personalized e-commerce search that provides improved personalized results within the limited accepted time frames required for online browsing. We propose combining features such as product popularity, user interests, and query-product relevance with collaborative filtering, and implement our solution in Elasticsearch in order to achieve acceptable execution timings. We evaluate our approach against a publicly available dataset, as well as a running e-commerce store. @inproceedings{VavliakisWSDM2018, |
2018
Conference Papers
Eleni Nisioti, Kyriakos C. Chatzidimitriou and Andreas L. Symeonidis
"ICML 2018 AutoML WorkshopPredicting hyperparameters from meta-features in binary classification problems"
AutoML, http://assets.ctfassets.net/c5lel8y1n83c/5uAPDjSvcseoko2cCcQcEi/8bd1d8e3630e246946feac86271fe03b/PPC17-automl2018.pdf, Stockholm, Sweden, 2018 Jul
![]() ![]() The presence of computationally demanding problems and the current inability to auto-matically transfer experience from the application of past experiments to new ones delaysthe evolution of knowledge itself. In this paper we present the Automated Data Scientist1,a system that employs meta-learning for hyperparameter selection and builds a rich ensem-ble of models through forward model selection in order to automate binary classificationtasks. Preliminary evaluation shows that the system is capable of coping with classificationproblems of medium complexity. @conference{2018Nisioti, | |
Sotirios-Filippos Tsarouchis, Maria Th. Kotouza, Fotis E. Psomopoulos and Pericles A. Mitkas
"A Multi-metric Algorithm for Hierarchical Clustering of Same-Length Protein Sequences"
IFIP International Conference on Artificial Intelligence Applications and Innovations, pp. 189-199, Springer, Cham, 2018 May
![]() ![]() The identification of meaningful groups of proteins has always been a major area of interest for structural and functional genomics. Successful protein clustering can lead to significant insight, assisting in both tracing the evolutionary history of the respective molecules as well as in identifying potential functions and interactions of novel sequences. Here we propose a clustering algorithm for same-length sequences, which allows the construction of subset hierarchy and facilitates the identification of the underlying patterns for any given subset. The proposed method utilizes the metrics of sequence identity and amino-acid similarity simultaneously as direct measures. The algorithm was applied on a real-world dataset consisting of clonotypic immunoglobulin (IG) sequences from Chronic lymphocytic leukemia (CLL) patients, showing promising results. @inproceedings{2018Tsarouchis, | |
Kyriakos C. Chatzidimitriou, Michail Papamichail, Themistoklis Diamantopoulos, Michail Tsapanos and Andreas L. Symeonidis
"npm-miner: An Infrastructure for Measuring the Quality of the npm Registry"
MSR ’18: 15th International Conference on Mining Software Repositories, pp. 4, ACM, Gothenburg, Sweden, 2018 May
![]() ![]() ![]() As the popularity of the JavaScript language is constantly increasing, one of the most important challenges today is to assess the quality of JavaScript packages. Developers often employ tools for code linting and for the extraction of static analysis metrics in order to assess and/or improve their code. In this context, we have developed npn-miner, a platform that crawls the npm registry and analyzes the packages using static analysis tools in order to extract detailed quality metrics as well as high-level quality attributes, such as maintainability and security. Our infrastructure includes an index that is accessible through a web interface, while we have also constructed a dataset with the results of a detailed analysis for 2000 popular npm packages. @inproceedings{Chatzidimitriou2018MSR, | |
Themistoklis Diamantopoulos, Georgios Karagiannopoulos and Andreas Symeonidis
"CodeCatch: Extracting Source Code Snippets from Online Sources"
IEEE/ACM 6th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering (RAISE), pp. 21-27, https://dl.acm.org/ft_gateway.cfm?id=3194107&ftid=1982571&dwn=1&CFID=87644405&CFTOKEN=833260e7cb501a7d-48967D35-AFC5-4678-82812B13D64D3DD3, 2018 May
![]() ![]() ![]() https://dl.acm.org/ft_gateway.cfm?id=3194107&ftid=1982571&dwn=1&CFID=87644405&CFTOKEN=833260e7cb501a7d-48967D35-AFC5-4678-82812B13D64D3DD3 @inproceedings{Diamantopoulos2018, | |
Anastasios Dimanidis, Kyriakos C. Chatzidimitriou and Andreas L. Symeonidis
"A Natural Language Driven Approach for Automated Web API Development: Gherkin2OAS"
WWW ’18 Companion: The 2018 Web Conference Companion, pp. 6, Lyon, France, 2018 Apr
![]() ![]() ![]() Speeding up the development process of Web Services, while adhering to high quality software standards is a typical requirement in the software industry. This is why industry specialists usually suggest \\"driven by\\" development approaches to tackle this problem. In this paper, we propose such a methodology that employs Specification Driven Development and Behavior Driven Development in order to facilitate the phases of Web Service requirements elicitation and specification. Furthermore, we introduce gherkin2OAS, a software tool that aspires to bridge the aforementioned development approaches. Through the suggested methodology and tool, one may design and build RESTful services fast, while ensuring proper functionality. @inproceedings{Dimanidis2018, | |
Maria Th. Kotouza, Konstantinos N. Vavliakis, Fotis E. Psomopoulos and Pericles A. Mitkas
"A Hierarchical Multi-Metric Framework for Item Clustering"
5th International Conference on Big Data Computing Applications and Technologies, pp. 191-197, IEEE/ACM, Zurich, Switzerland, 2018 Dec
![]() ![]() ![]() Item clustering is commonly used for dimensionality reduction, uncovering item similarities and connections, gaining insights of the market structure and recommendations. Hierarchical clustering methods produce a hierarchy structure along with the clusters that can be useful for managing item categories and sub-categories, dealing with indirect competition and new item categorization as well. Nevertheless, baseline hierarchical clustering algorithms have high computational cost and memory usage. In this paper we propose an innovative scalable hierarchical clustering framework, which overcomes these limitations. Our work consists of a binary tree construction algorithm that creates a hierarchy of the items using three metrics, a) Identity, b) Similarity and c) Entropy, as well as a branch breaking algorithm which composes the final clusters by applying thresholds to each branch of the tree. ?he proposed framework is evaluated on the popular MovieLens 20M dataset achieving significant reduction in both memory consumption and computational time over a baseline hierarchical clustering algorithm. @inproceedings{KotouzaVPM18, | |
Panagiotis G. Mousouliotis, Konstantinos L. Panayiotou, Emmanouil G. Tsardoulias, Loukas P. Petrou and Andreas L. Symeonidis
"Expanding a robots life: Low power object recognition via FPGA-based DCNN deployment"
MOCAST, https://arxiv.org/abs/1804.00512, 2018 Mar
![]() ![]() FPGAs are commonly used to accelerate domain-specific algorithmic implementations, as they can achieve impressive performance boosts, are reprogrammable and exhibit minimal power consumption. In this work, the SqueezeNet DCNN is accelerated using an SoC FPGA in order for the offered object recognition resource to be employed in a robotic application. Experiments are conducted to investigate the performance and power consumption of the implementation in comparison to deployment on other widely-used computational systems. thanks you! @conference{Mousouliotis2018, | |
Michail Papamichail, Themistoklis Diamantopoulos, Ilias Chrysovergis, Philippos Samlidis and Andreas Symeonidis
Proceedings of the 2018 Workshop on Machine Learning Techniques for Software Quality Evaluation (MaLTeSQuE), https://www.researchgate.net/publication/324106989_User-Perceived_Reusability_Estimation_based_on_Analysis_of_Software_Repositories, 2018 Mar
![]() ![]() ![]() The popularity of open-source software repositories has led to a new reuse paradigm, where online resources can be thoroughly analyzed to identify reusable software components. Obviously, assessing the quality and specifically the reusability potential of source code residing in open software repositories poses a major challenge for the research community. Although several systems have been designed towards this direction, most of them do not focus on reusability. In this paper, we define and formulate a reusability score by employing information from GitHub stars and forks, which indicate the extent to which software components are adopted/accepted by developers. Our methodology involves applying and assessing different state-of-the-practice machine learning algorithms, in order to construct models for reusability estimation at both class and package levels. Preliminary evaluation of our methodology indicates that our approach can successfully assess reusability, as perceived by developers. @inproceedings{Papamichail2018MaLTeSQuE, | |
Emmanouil G. Tsardoulias, Konstantinos L. Panayiotou, Christoforos Zolotas, Alexandros Philotheou, Anreas L. Symeonidis and Loukas Petrou
"From classical to cloud robotics: Challenges and potential"
3rd International Workshop on Microsystems, Sindos Campus, ATEI Thessaloniki, Greece, 2018 Dec
![]() ![]() ![]() Nowadays, a rapid transition from the classical robotic systems to more modern concepts like Cloud or IoT robotics is being experienced. The current paper briefly overviews the benefits robots can have, as parts of the increasingly interconnected world. @conference{TsardouliasMicrosystems2018, | |
Konstantinos N. Vavliakis, Maria Th. Kotouza, Andreas L. Symeonidis and Pericles A. Mitkas
"Recommendation Systems in a Conversational Web"
Proceedings of the 14th International Conference on Web Information Systems and Technologies - Volume 1: WEBIST,, pp. 68-77, SciTePress, 2018 Jan
![]() ![]() ![]() In this paper we redefine the concept of Conversation Web in the context of hyper-personalization. We argue that hyper-personalization in the WWW is only possible within a conversational web where websites and users continuously “discuss” (interact in any way). We present a modular system architecture for the conversational WWW, given that adapting to various user profiles and multivariate websites in terms of size and user traffic is necessary, especially in e-commerce. Obviously there cannot be a unique fit-to-all algorithm, but numerous complementary personalization algorithms and techniques are needed. In this context, we propose PRCW, a novel hybrid approach combining offline and online recommendations using RFMG, an extension of RFM modeling. We evaluate our approach against the results of a deep neural network in two datasets coming from different online retailers. Our evaluation indicates that a) the proposed approach outperforms current state-of-art methods in small-medium datasets and can improve performance in large datasets when combined with other methods, b) results can greatly vary in different datasets, depending on size and characteristics, thus locating the proper method for each dataset can be a rather complex task, and c) offline algorithms should be combined with online methods in order to get optimal results since offline algorithms tend to offer better performance but online algorithms are necessary for exploiting new users and trends that turn up. @conference{webist18, |