Harris Georgiou | National & Kapodistrian University of Athens (original) (raw)

Papers by Harris Georgiou

fMRI-Sparse toolbox is a minimalistic collection of low-level data h... more fMRI-Sparse toolbox is a minimalistic collection of low-level data handling (matrix) functions for fMRI processing, block-based & event-based test pattern series, as well as "realistic" simulated fMRI data series for algorithm benchmarking, template scripts for various fMRI decomposition methods (GLM, PCA, ICA, BP, CCA, KSVD), analysis of components & activation maps, etc. Since the toolbox can be used as a benchmarking suite, several data generators are included for creating fully-identifiable fMRI-like data series.

viXra, Jun 1, 2015

Game Theory is one of the most challenging and controversial fields of applied Mathematics. Based... more Game Theory is one of the most challenging and controversial fields of applied Mathematics. Based on a robust theoretical framework, its applications range from analyzing simple board games and conflict situations to modeling complex systems and evolutionary dynamics. This book is a short collection of introductory papers in the field, aimed primarily as reading material for graduate-and postgraduate-level lectures in Game Theory and/or Machine Learning. The four papers included here are all original works already published as open-access or conference publications, spanning a timeframe of several years apart and a wide range of topics. Hence, each paper is self-contained and can be studied on its own, without any prerequisite knowledge from the previous ones. However, their presentation order is consistent with going from the most elementary issues to the more advanced and experiment-rigorous topics. The first paper presents an overview of Game Theory in general, its core issues and building blocks, game analysis and methods for identifying Minimax solutions and Nash equilibria, as well as a brief introduction to coalitional gaming and collective efficiency. There is also a short summary of other important elements like signaling, credibility, threats/promises, etc. The second paper extends some of the topics from coalitional gaming, focusing more on collective efficiency, optimal voting mechanisms and weighted voting, as well as a brief proposal for applying this gametheoretic framework to optimal combination of experts. The third paper builds upon this proposed framework and employs it in Pattern Recognition (Machine Learning) within the context of combining pattern classifiers. A "static" model for weighted majority voting with an analytical model for the voting weights is experimentally tested against other similar models. Finally, the forth paper presents an extension of this game-theoretic approach for classifier combination, employing "adaptive" voting weights via local accuracy estimates; in other words, the ensemble of classifiers is adapted to local efficiency priors (instead of static globals) but keeping the same analytical model for the voting weights, i.e., without the need to acquire them via training. This new approach is experimentally validated against state-of-the-art combination methods for pattern classifiers and it is proven highly competitive with much lower complexity overhead.

This package contains a set of data regarding daily refugee arrivals at the Greek islands of firs... more This package contains a set of data regarding daily refugee arrivals at the Greek islands of first-reception in teh Aegean Sea, for the most intense period of influx waves, from the beginning of October 2015 until the mid-January of 2016. The sources of the data are: 1) For daily arrivals: UNHCR Refugees/Migrants Emergency Response (Data mashups) http://data.unhcr.org/mediterranean/country.php?id=83 2) For weather: Searchable Weather Database - National Observatory (Greece) http://meteosearch.meteo.gr/ The datasets from (1) have already been used in various publications describing such predictive analytics models. Detailed description and related conclusions can be found at: * Harris V. Georgiou, "Identification of refugee influx patterns in Greece via model-theoretic analysis of daily arrivals" (9-May-2016), https://arxiv.org/abs/1605.02784 _______________________________________________ AVAILABLE FILE FORMATS The datasets are available in the following formats (included): *.xlsx : MS-Excel/LibreOffice native spreadsheets *.csv : comma-separated plaintext spreadsheets *arff : WEKA native data source (plaintext) These data formats are equivalent, i.e., they contain the exact same sets of data. Normally, at least one of them should be compatible with any major programming platform (e.g. Matlab, Octave, R) or any native programming language for arbitrary handling (e.g. C, Java).

Quality assurance and resulting image quality in modern mammography are known to be directly rela... more Quality assurance and resulting image quality in modern mammography are known to be directly related to X-ray exposure parameters. Current state-ofthe-art detector technologies and architectures, even in the case of digital mammography, suffer from various non-trivial quality deterioration factors, including spatial resolution, contrast and noise. Although proper selection of the exposure parameters by an expert radiologist can minimize these problems, automatic control can greatly increase the quality and the reliability of the system. Current automatic exposure control techniques like automatic exposure control (AEC) and automatic brightness control (ABC) can only be employed in the context of automatic timers, while still associated with typical global image quality measurements. A new innovative approach is proposed in this report, including a content-oriented quantitative feature analysis of tissue-related discriminative information in the case of digital mammographic images. The final processing module is to be used as an intelligent controller in future radiographic systems, effectively improving the quality of the resulting image via accurate and content-related automatic image quality evaluation, while at the same time optimizing the exposure parameters versus minimum radiation dose and extending the adaptability of the system to case-specific patient attributes.

WP3: issues related to D.8 and D.9 material WP3: issues related to D.8 and D.9 material Overview ... more WP3: issues related to D.8 and D.9 material WP3: issues related to D.8 and D.9 material Overview of image pre Overview of image pre-and post and post-filtering filtering Enhancements to image restoration options Enhancements to image restoration options Preface to x Preface to x-ray camera geometry (WP8) ray camera geometry (WP8) Implementation & calibration issues Implementation & calibration issues Aspects relative to Aspects relative to " "Exploitation & Dissemination Exploitation & Dissemination" " 2 2-17 17 WP3: Issues related to D.8 and D.9 material WP3: Issues related to D.8 and D.9 material

Zenodo (CERN European Organization for Nuclear Research), Apr 15, 2020

Springer eBooks, 2021

Visual analytics science develops principles and methods for efficient human-computer collaborati... more Visual analytics science develops principles and methods for efficient human-computer collaboration in solving complex problems. Visual and interactive techniques are used to create conditions in which human analysts can effectively utilize their unique capabilities: the power of seeing, interpreting, linking, and reasoning. Visual analytics research deals with various types of data and analysis tasks from numerous application domains. A prominent research topic is analysis of spatiotemporal data, which may describe events occurring at different spatial locations, changes of attribute values associated with places or spatial objects, or movements of people, vehicles, or other objects. Such kinds of data are abundant in urban applications. Movement data are a quintessential type of spatiotemporal data because they can be considered from multiple perspectives as trajectories, as spatial events, and as changes of space-related attribute values. By example of movement data, we demonstrate the utilization of visual analytics techniques and approaches in data exploration and analysis.

arXiv (Cornell University), Jun 16, 2015

In this paper, a gentle introduction to Game Theory is presented in the form of basic concepts an... more In this paper, a gentle introduction to Game Theory is presented in the form of basic concepts and examples. Minimax and Nash's theorem are introduced as the formal definitions for optimal strategies and equilibria in zero-sum and nonzero-sum games. Several elements of cooperative gaming, coalitions, voting ensembles, voting power and collective efficiency are described in brief. Analytical (matrix) and extended (treegraph) forms of game representation is illustrated as the basic tools for identifying optimal strategies and "solutions" in games of any kind. Next, a typology of four standard nonzero-sum games is investigated, analyzing the Nash equilibria and the optimal strategies in each case. Signaling, stance and third-party intermediates are described as very important properties when analyzing strategic moves, while credibility and reputation is described as crucial factors when signaling promises or threats. Utility is introduced as a generalization of typical cost/gain functions and it is used to explain the incentives of irrational players under the scope of "rational irrationality". Finally, a brief reference is presented for several other more advanced concepts of gaming, including emergence of cooperation, evolutionary stable strategies, two-level games, metagames, hypergames and the Harsanyi transformation.

viXra, Jun 1, 2015

In this paper, a gentle introduction to Game Theory is presented in the form of basic concepts an... more In this paper, a gentle introduction to Game Theory is presented in the form of basic concepts and examples. Minimax and Nash's theorem are introduced as the formal definitions for optimal strategies and equilibria in zero-sum and nonzero-sum games. Several elements of cooperaive gaming, coalitions, voting ensembles, voting power and collective efficiency are described in brief. Analytical (matrix) and extended (tree-graph) forms of game representation is illustrated as the basic tools for identifying optimal strategies and "solutions" in games of any kind. Next, a typology of four standard nonzero-sum games is investigated, analyzing the Nash equilibria and the optimal strategies in each case. Signaling, stance and third-party intermediates are described as very important properties when analyzing strategic moves, while credibility and reputation is described as crucial factors when signaling promises or threats. Utility is introduced as a generalization of typical cost/gain functions and it is used to explain the incentives of irrational players under the scope of "rational irrationality". Finally, a brief reference is presented for several other more advanced concepts of gaming, including emergence of cooperation, evolutionary stable strategies, two-level games, metagames, hypergames and the Harsanyi transformation.

Innovative technologies can enhance operational capabilities of First Responders (FRs) during Sea... more Innovative technologies can enhance operational capabilities of First Responders (FRs) during Search & Rescue (SAR) operations, while at the same time increasing safety levels. The INGENIOUS project (EU Horizon 2020) aims at developing, integrating, testing and validating a next generation SAR toolkit for collaborative response, which ensures high level of protection and augmented operational capacity in disaster situations. In this paper, a subset of components of the toolkit mostly focused on increasing situational awareness and safety are described: the Fusion Engine (FE), which receives data from multiple sources, stores and analyzes them for integration purposes regarding situational awareness and sends them to the Common Operational Picture (COP) as well as the mobile FR terminals; the Smart Boots (SB), which collect data of individual FRs and provide information regarding their health status and alerts; the Modular Airborne Camera System (MACS); the Multi-purpose Autonomous eXploring (MAX) drone for indoor/outdoor mapping and assessment of unknown environments; and the Micro INdoor drones (MINs) used for FRs indoor localization. The functionalities of these components, as well as the first prototypes developed and currently under lab and field test, are presented in this paper. This work is supported by the projects INGENIOUS, which has received funding from the European Union's Horizon 2020 (H2020) programme under grant agreement No:833435.

2022 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS)

Global NEST International Conference on Environmental Science & Technology

Water resource management is one the most urgent aspects of environmental protection and sustaina... more Water resource management is one the most urgent aspects of environmental protection and sustainability policies world-wide. Accurate, real-time remote sensing of the status of underground reservoirs is required for proper regional planning, prevention of droughts, optimized farming etc. ‘Water Underground’ is a low-cost solution, based on a combination of Internet of Things (IoT) local sensing, Edge computing, Cloud storage, web services and Machine Learning (ML) and predictive analytics, continuously monitoring the level of underground water and its quality. Specifically, water level is monitored via an IoT apparatus providing the Static (SWL) and Pumping Water Level (PWL). Moreover, the quality of water is tracked via measuring the Total Dissolved Solids (TDS), Oxidation-Reduction Potential (ORP), temperature, pH, electrical-conductivity, etc. Local processing in the IoT device includes measurements’ transformations and robust adaptive control for the device’s actuators. The rese...

arXiv (Cornell University), Oct 15, 2022

Efficient and quick remote communication in search and rescue operations can be life-saving for t... more Efficient and quick remote communication in search and rescue operations can be life-saving for the first responders. However, while operating on the field means of communication based on text, image and audio are not suitable for several disaster scenarios. In this paper, we present a smartwatchbased application, which utilizes a Deep Learning (DL) model, to recognize a set of predefined arm gestures, maps them into Morse code via vibrations enabling remote communication amongst first responders. The model performance was evaluated by training it using 4,200 gestures performed by 7 subjects (cross-validation) wearing a smartwatch on their dominant arm. Our DL model relies on convolutional pooling and surpasses the performance of existing DL approaches and common machine learning classifiers, obtaining gesture recognition accuracy above 95%. We conclude by discussing the results and providing future directions.

Zenodo (CERN European Organization for Nuclear Research), Oct 7, 2022

On September 29th, 2021 a field testing activity for the INGENIOUS project took place at HRTA's t... more On September 29th, 2021 a field testing activity for the INGENIOUS project took place at HRTA's training facilities in Afidnes (ATC), Attica region of Greece. The INGENIOUS project is about ensuring a high level of protection and augmented operational capacity for First Responders (FR) working inside the disaster area. The main objectives of these two Small Scale Field Tests included the integration of the specific components of the INGENIOUS Toolkit in real-life conditions, in order to provide testing, assessment, validation and improvements for further development steps. FRs have a significant role as they are the end-users that in future will depend on technologies like these, while robustness, accuracy and reliability of the components are crucial acceptance factors. Hence, this work presents these field tests, their outcomes and the assessment of their results from the FR perspective for realworld Search and Rescue (SAR) operations.

During the last two years, hundreds of thousands of refugees have traveled across the Mediterrane... more During the last two years, hundreds of thousands of refugees have traveled across the Mediterranean Sea, in perilous conditions and unsafe boats, resulting in thousands of dead and missing, despite the best rescue eorts from both sides. Data analysis and statistics may have an answer for the challenging task of predicting the ows of incoming boats and assisting in the prompt allocation of Search & Rescue (SAR) resources at the frontlines.

viXra, Jun 1, 2015

Zenodo (CERN European Organization for Nuclear Research), Apr 15, 2020

Springer eBooks, 2021

arXiv (Cornell University), Jun 16, 2015

viXra, Jun 1, 2015

In this paper, a gentle introduction to Game Theory is presented in the form of basic concepts an... more In this paper, a gentle introduction to Game Theory is presented in the form of basic concepts and examples. Minimax and Nash's theorem are introduced as the formal definitions for optimal strategies and equilibria in zero-sum and nonzero-sum games. Several elements of cooperaive gaming, coalitions, voting ensembles, voting power and collective efficiency are described in brief. Analytical (matrix) and extended (tree-graph) forms of game representation is illustrated as the basic tools for identifying optimal strategies and "solutions" in games of any kind. Next, a typology of four standard nonzero-sum games is investigated, analyzing the Nash equilibria and the optimal strategies in each case. Signaling, stance and third-party intermediates are described as very important properties when analyzing strategic moves, while credibility and reputation is described as crucial factors when signaling promises or threats. Utility is introduced as a generalization of typical cost/gain functions and it is used to explain the incentives of irrational players under the scope of "rational irrationality". Finally, a brief reference is presented for several other more advanced concepts of gaming, including emergence of cooperation, evolutionary stable strategies, two-level games, metagames, hypergames and the Harsanyi transformation.

2022 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS)

Global NEST International Conference on Environmental Science & Technology

arXiv (Cornell University), Oct 15, 2022

Zenodo (CERN European Organization for Nuclear Research), Oct 7, 2022

The Science behind the COVID Pandemic and Healthcare Technology Solutions , 2022

This work is focused on multi-aspect analytics of epidemic data, using Greece as the use case for... more This work is focused on multi-aspect analytics of epidemic data, using Greece as the use case for assessing the national outbreak and estimating the general trends and outlook of it since the beginning of the pandemic in early 2020 up to the end of 2020. Using methodologies from compartmentalized epidemic modelling, data analytics and machine learning, several insights are presented with regard to early tracking of the evolving outbreak, despite having to deal with data scarcity, inconsistencies and quality issues. It is intended to be used as a guideline for data-related challenges on producing actionable information to decisionmakers during an active epidemic. Keywords: COVID-19 • SARS-CoV-2 • Greece • data analytics • SEIR • predictive modelling • data restoration • computational epidemics • epidemic tracking.

The Science behind the COVID Pandemic and Healthcare Technology Solutions , 2022

Screening tests for infectious diseases is a problem typically addressed in the field of Medicine... more Screening tests for infectious diseases is a problem typically addressed in the field of Medicine and Epidemics. However, as the SARS-CoV-2 pandemic emerged, it became clear that there is no globally accepted strategy for optimizing such procedures, e.g. in international transportation and border checks, which policy makers can employ. In this study, the general problem of developing optimal testing strategies for infectious diseases is explored under the scope of Game Theory, sampling and estimation methods from classic Statistics, as well as Bayesian methods for the proper treatment of posterior updates, leading to the benefits of employing Machine Learning for data-driven structural risk minimization. Six main guidelines are established by this work, dictating estimated variance of prevalence and associated risk as the main minimization target, in terms of both a criterion for inflow quotas allocation between population groups, as well as optimal posterior updates via classic confidence intervals and Bayesian methods. As a result, it is established that minimum infection risk, not optimal resource allocation, is the real challenge and top priority in formalizing optimal screening strategies for such risk mitigation policies. Keywords: Epidemics • SARS-CoV-2 • screening methods • testing strategies • Game Theory • Machine Learning • Bayesian methods.

The book is the second part of a two-volume work on all the intermediate processing levels in Com... more The book is the second part of a two-volume work on all the intermediate processing levels in Computer Aided Diagnosis (CAD) or Automated Computer Diagnosis (ACD), focused primarily on the theoretical aspects of related algorithms and methodologies. It includes an extensive list of more than 860 relevant bibliographic references, a very useful textbook for academics and researchers.
Arnaoutis Publ., Oct-2012, ISBN: 978-9609764100.

The book is the first part of a two-volume work on all the intermediate processing levels in Comp... more The book is the first part of a two-volume work on all the intermediate processing levels in Computer Aided Diagnosis (CAD) or Automated Computer Diagnosis (ACD), focused primarily on the programming and development of relevant applications. It is accompanied by full source code (ANSI C/C++) of more than 12.000 lines and complete description of the implemented full applications that are presented therein. Arnaoutis Publ., Oct-2012, ISBN: 978-9609764094.