Showing papers by "University of Piraeus published in 2022"

Roadmap on signal processing for next generation measurement systems

Abstract: Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative forms of signals that can be enhanced and analysed for information extraction and quantification. The recent advances in artificial intelligence and machine learning are shifting the research attention towards intelligent, data-driven, signal processing. This roadmap presents a critical overview of the state-of-the-art methods and applications aiming to highlight future challenges and research opportunities towards next generation measurement systems. It covers a broad spectrum of topics ranging from basic to industrial research, organized in concise thematic sections that reflect the trends and the impacts of current and future developments per research field. Furthermore, it offers guidance to researchers and funding agencies in identifying new prospects.

Promoting smart tourism personalised services via a combination of deep learning techniques

Abstract: Coronavirus has radically changed the world and our lives in many and various ways. During this crisis, the tourism sector was severely damaged globally, as, within some weeks, popular touristic places worldwide changed from over-tourism to non-tourism destinations. In order to address new challenges in this sector, a novel cloud-based framework is proposed that exploits image labelling through Deep Learning and Neural Network-based Collaborative Filtering models in order to generate personalised recommendations in the context of smart tourism. At the same time, this paper also aims at offering valuable insights regarding Artificial Neural Networks and Matrix Factorisation Neural Networks. Moreover, in this research, the authors demonstrate the architecture/topology of ANN models used to generate predictions regarding tourists’ preferences, along with experimental results produced during model evaluation and the configuration that resulted in the highest accuracy in predictions.

The “Right to Be Forgotten” in the GDPR: Implementation Challenges and Potential Solutions

Abstract: The GDPR, being a legal document, follows a technology-agnostic approach so as not to bind the provisions of the law with current trends and state-of-the-art technologies in computer science and information technology. Yet, the technical challenges of aligning modern systems and processes with the GDPR provisions, and mainly with the Right to be Forgotten (RtbF), are numerous and in most cases insurmountable. To this end, in this Chapter we discuss the challenges of implementing the RtbF on contemporary information systems, and we assess technical methods, architectures, and frameworks—existing either in corporate or academic environments—in terms of fulfilling the technical practicalities for effectively integrating the new forgetting requirements into current computing infrastructures. We also discuss the GDPR forgetting requirements in respect to their impact on the backup and archiving procedures stipulated by the modern security standards. In this context, we examine the implications of erasure requests on current IT backup systems, and we highlight a number of envisaged organizational, business and technical challenges pertained to the widely known backup standards, data retention policies, backup mediums, search services, and ERP (Enterprise Resource Planning) systems.

Fair efficiency decomposition in network DEA: A compromise programming approach

Abstract: We introduce in this paper a novel network DEA approach to determine a single and fair efficiency decomposition for series multi-stage processes. We provide direct comparisons with the bargaining approach of Zhou et al. (2013) [1]. First, we prove the equivalence of the proposed approach with the bargaining approach for series two-stage processes in which only the intermediate products are the outputs of the first stage and the inputs to the second one. Next, we reveal the inadequacy of the bargaining approach to be applied in series processes with more than two stages, as it yields multiple non-extreme efficiency decompositions instead of one. On the contrary, we show that our approach provides a single non-extreme efficiency decomposition. In addition to these contributions, our approach is novel in the sense that the obtained efficiency decomposition represents a fair compromise between the stages, as it is as close as possible to the maximum efficiency score and as far away as possible to the minimum efficiency score attained by each stage. To reach such a fair compromise among the stages we employ the weighted min-max method in a multi-objective programming framework, and we guide the search direction on the line that connects the ideal point with the nadir point. We provide graphical illustrations and comparisons based on data drawn from the literature as well as on synthetic data.

Analysis of Planar Random Arrays With Stochastic Geometry Tools

Abstract: The performance of 2-D random arrays is analyzed using the distance distributions of an isotropic homogeneous binomial point process. The array factor is expressed as the superposition of the patterns of equal-amplitude isotropic elements uniformly randomly distributed in a disk area. The distribution of the distance to the $k$ th nearest element from the center of the disk is utilized in the summation, providing a novel representation of the array factor in terms of ordered distances. Furthermore, an alternative distribution is examined by setting a constraint to the distance of the farthest element from the origin. The mean range of the elements in the disk and a numerical calculation of the mean interelement distance is provided. The statistical average and the variance of the array factor as well as the average power pattern are derived and compared to previous results. The 3 dB beamwidth, directivity, nulls, and sidelobe peaks are discussed in terms of the number of elements and the array density. Simulation results for various random arrays and comparison of ensemble-averaged parameters with those of deterministic and sparse arrays from the literature are provided. The results are applicable to collaborative beamforming for distributed wireless ad hoc networks.

Some Characterizations of Mixed Renewal Processes

Abstract: Abstract Some characterizations of mixed renewal processes in terms of exchangeability and of different types of regular conditional probabilities are given. As a consequence, an existence result for mixed renewal processes, providing also a new construction for them, is obtained. As an application, some concrete examples of constructing such processes are presented and the corresponding regular conditional probabilities are explicitly computed.

Optimal Testing Strategies for Infectious Diseases

Abstract: 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.

Collaborative Practice-Based Learning Methods in Architectural Design and Building Technology Education in a Cross-Cultural, Cross-Geographical Environment

Abstract: Design-build workshops and the proliferation of internet technologies fuel the exploration of alternative methods in international architectural education. Taking the example of a student team entry in an international construction workshop, this paper explores the possibilities and the effectiveness of alternative collaborative learning methods through practical application and the use of digital technologies in an intercultural environment. Τhis research focuses on the integration of building technology in the design through different learning environments in a design-built project. Using online questionnaires and interviews, students' learning background and their exposure to different learning styles is analyzed, both before and during the workshop. The findings of the research suggest that many students consider conventional design studio disconnected with reality and that learning with practical application helps their deeper understanding of the building processes. Most of them believe that the virtual studio environment encourages collaboration in the class and in a cross-cultural environment. A balanced combination of the three learning environments best suits contemporary learning and the needs of a globalized industry.

Enabling Speech Emotional Intelligence as a Service in Homecare Platforms

Abstract: During the last years, the field of affective computing that deals with identification, recording, interpreting, and processing of emotion and affective state of an individual has won ground in the scientific community. Thus, the incorporation of affective computing and the corresponding emotional intelligence in homecare services, which entail the social and healthcare delivery at the home of the patient via the utilization of information and communication technology, seems quite important. Among the available means of expression, speech constitutes one of the most natural mechanisms, providing adequate information for recognizing emotion. In this paper, we describe the design and implementation of an affective recognition service integrated in a holistic electronic homecare management system, covering the entire lifecycle of doctor-patient interaction, incorporating speech emotion recognition (SER)-oriented methods. Within this context, we evaluate the performance of several SER techniques deployed in the homecare system, from well-established machine learning algorithms to Deep Learning architectures and we report the corresponding results.

Coordinates Distributions in Finite Uniformly Random Networks

Abstract: This work introduces the concept of angular distance distributions of the nodes in a Binomial point process-based model for wireless networks. The need for the derivation of these distributions is motivated by the use of high-frequency bands in the mmWave or even in the sub-THz bands. These frequencies are closely related to the beamforming capabilities of the transceivers in wireless networks. Therefore, the directional characteristics of the beams utilized by the communicating nodes, along with the random location of the latter, lead to an increasing demand for the distributions derived in this paper. A direct consequence of the Binomial process utilized to model the random location of a fixed number of nodes in a ball, is that the extracted distributions are based on the generalized beta distribution. The presented results are applicable to two- and three-dimensional networks and can be used to study various network characteristics among which are the interference, and the beam management.

Is mandatory vaccination in population over 60 adequate to control the COVID-19 pandemic in E.U.?

Abstract: Vaccine hesitancy, which potentially leads to refusal or delayed acceptance of COVID-19 vaccines, is considered a key driver for the increasing death toll from the pandemic in the E.U.. European Commission and several member states’ governments are either planning or have already directly or indirectly announced mandatory vaccination for individuals aged over 60, the group repeatedly proved to be the most vulnerable. In this paper, an assessment of this strategy benefits is attempted. This is done by examining the reduction of Standard Expected Years of Life Lost (SEYLL) per person of the EU population over 60 as a function of their vaccination percentage. Publicly available data and some first results of the second iteration of the SHARE COVID-19 survey conducted during the summer of 2021 on acceptance of COVID-19 vaccines are used as input.

The Emerging Era of Human-AI Interaction: Keynote Address

Abstract: At present, a major paradigm shift is taking place where computers are no longer solely executing human instructions but rather, they become agents with decision making capabilities through their AI empowered software. This leads to a whole emerging era of Human-AI Interaction which is increasingly affecting working and everyday lives of all people. The promise of AI is big in assisting humans through all sorts of interactive applications including smartphones, wearables, self-driving cars, smart homes, and offices, virtual assistants as well as contributing to the advancements of human achievements in science and arts. AI alleviates human cognitive overload both on the use of complex software and in difficult problem-solving situations, it provides orientation in the vast cyberspace navigation, it offers enlightening visions in huge accumulated human knowledge all through deep learning, machine learning, decision making methods, cognitive theories, fuzzy logic and more but with a degree of uncertainty and possible consequent errors in results. However, in this new kind of interaction, the human nature, capabilities, understanding, feelings, and needs remain unchanged and constitute the most important issue in the two-part dialogue, urging for more research on trustworthy and explainable AI.This paper aims to highlight important advantages and gains and discuss consequent challenges of the emerging human-AI interaction by presenting a critical overview of the state-of-the-art as well as the author’s personal point of view as to how this dialogue can acquire more explainability and trustworthiness while preserving usability.

Human–Machine Requirements’ Convergence for the Design of Assistive Navigation Software: Τhe Case of Blind or Visually Impaired People

Abstract: Autonomous navigation is a desirable capability for various types of “smart” devices or vehicles. The development of software designed for this purpose has become a central research field for major companies, as well as in academia. This trend is accompanied by a tendency to equip moving devices with artificial intelligence (AI) features. Interestingly, however, the most (and not artificially) intelligent unit which may require assistance from digital applications in order to achieve autonomous navigation is a blind or a visually impaired person (BVI). It is argued that as the capabilities of AI are being enhanced, convergence will occur among a significant subset of the requirements concerning assistive navigation software for the BVI and AI-equipped moving devices, respectively. The corresponding requirements which have been elicited through interviews with BVI people are presented. A subset of these requirements, which exhibit direct or prospective convergence with the corresponding requirements of AI devices is then outlined, with emphasis on possible opportunities for interaction between the two research topics.

SoK: cross-border criminal investigations and digital evidence

Abstract: Abstract Digital evidence underpin the majority of crimes as their analysis is an integral part of almost every criminal investigation. Even if we temporarily disregard the numerous challenges in the collection and analysis of digital evidence, the exchange of the evidence among the different stakeholders has many thorny issues. Of specific interest are cross-border criminal investigations as the complexity is significantly high due to the heterogeneity of legal frameworks, which beyond time bottlenecks can also become prohibiting. The aim of this article is to analyse the current state of practice of cross-border investigations considering the efficacy of current collaboration protocols along with the challenges and drawbacks to be overcome. Further to performing a legally oriented research treatise, we recall all the challenges raised in the literature and discuss them from a more practical yet global perspective. Thus, this article paves the way to enabling practitioners and stakeholders to leverage horizontal strategies to fill in the identified gaps timely and accurately.

Exploiting WiFi usability features for association attacks in IEEE 802.11: Attack analysis and mitigation controls1

Abstract: Association attacks aim to manipulate WiFi clients into associating with a malicious access point, by exploiting protocol vulnerabilities and usability features implemented on the network managers of modern operating systems. In this paper we classify association attacks based on the network manager features that each attack exploits. To validate their current validity status, we implement and test all known association attacks against the network managers of popular operating systems, by using our Wifiphisher tool. We analyze various strategies that may be implemented by an adversary in order to increase the success rate of association attacks. Furthermore, we examine the behavior of association attacks against upcoming security protocols and certifications for IEEE 802.11, such as WPA3, Wi-Fi Enhanced Open and Easy Connect. Our results show that even though the network managers have hampered the effectiveness of some known attacks (e.g. KARMA), other techniques (e.g. Known Beacons) are still active threats. More importantly, our results show that even the newer security protocols leave room for association attacks. Finally, we describe novel detection and prevention techniques for association attacks, as well as security controls based on user awareness.

Smart traffic lights for people with visual impairments: A literature overview and a proposed implementation

Abstract: Attempting to establish aids for individuals who are visually impaired has urged many cities to seek solutions for improving their quality of life. Namely, cities have installed sound-emitting devices into traffic lights as well as sidewalks that assist their navigation. Moreover, as cities are always striving to move forward and achieve innovations concerning navigation for disabled individuals, smart traffic lights, capable of synchronizing in real-time according to traffic and individual mobility conditions, are already being installed around the world. This is in line with the adoption of the smart city concept, which involves a set of methodologies and indicators that regulate how cities perform regarding the promotion of citizens’ quality of life. Another important principle is the techno-economic aspect indicating the need for low-cost careful planning to produce cost-efficient solutions, while additional important issues are maintenance, power efficiency, and the means to coordinate numerous devices to facilitate operation in a timely and reliable manner. In this article, we present an overview of the existing solutions for the navigation of people who are blind and visually impaired along with a requirement analysis performed on the feedback received from interviews with members of the Lighthouse for the Blind of Greece both of which lead to the proposal of a new implementation that pushes the state of the art.