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14th International Conference on Information, Intelligence, Systems and Applications, IISA 2023

作者： Deligiannidou, Aikaterini Rapti, Aggeliki Ioannou, Zafeiria-Marina Viennas, Emmanouil Papaloukopoulos, Christos Paschou, Mersini University of Patras Computer Engineering and Informatics Dpt Patras Greece University of Patras Computer Engineering and Informatics Dpt Greece Intraway Ltd Patras Greece Devout L.P. Patras Greece

ISBN: (纸本)9798350318067

The present work aims at the development of smart tools and techniques for the interoperability of information sources and the identification, timely detection, and suppression of forms of fraud with the assurance of data protection. The main goal is the research of smart techniques that will allow direct access to properly encoded and anonymized personal data. The innovation is in the ability to perform comparisons and actions that will allow all the necessary controls to address and prevent fraud, identifying the people that are involved in it, but not revealing personal information for other people recorded in files and registers. This is a novel approach to upgrade the operational action of public bodies and authorities and to give the possibility of dealing with fraud, and applying control to business groups and SMEs. In this work, the classification of users in terms of software use cases, the architecture of the approach and an integrated system of interoperability of information sources process is proposed. All technological developments were taken into account and the appropriate technological choices were made so that the implementing team is able to proceed with the implementation of the functional parts of the system software. Initial results are reported for a privacy-preserving process while cross-referencing files and information. © 2023 IEEE.

关键词： Interoperability

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Question Answering Chatbots for Biomedical Research Using Transformers

Question Answering Chatbots for Biomedical Research Using Tr...

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International Conference on Artificial Intelligence in Information and Communication (ICAIIC)

作者： Evdokia Xygi Andreas D. Andriopoulos Dimitrios A. Koutsomitropoulos Computer Engineering and Informatics Dpt. University of Patras Patras Greece

Professionals as well as the general public need effective help to access, understand and consume complex biomedical concepts. The existence of an interaction environment capable of automatically processing such information - thus replacing human intervention - such as chatbots, is however challenging. In this paper we propose a method of utilizing chatbots in the domain of biomedicine. In the implementation we choose to incorporate the BERT algorithm, so as to adopt a modern technique for natural language processing tasks. We use several pre-trained models (RoBERTa, XLM-R, BERT Large, and BioBert) in order to evaluate their ability to back the chatbot infrastructure. The data is retrieved from the PubMed repository, with the final set being formed into full sentences or potential chatbot responses, thus preserving their conceptual meaning. Response selection is performed using similarity metrics and F-score. The results create a ranking of the models placing related ones closely, recognizing the ability to always answer each question and highlighting the importance of the training previously applied to them. These are compared to the Count Vectorizer technique, which appears to perform better, but with several weaknesses, as many questions could not be answered.

关键词： Training Measurement Biological system modeling Bit error rate Chatbots Transformers Question answering (information retrieval)

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SECURITY SYSTEMS IN GREEK HEALTH CARE INSTITUTIONS: A SCOPING REVIEW TOWARDS AN EFFECTIVE BENCHMARKING APPROACH 22

SECURITY SYSTEMS IN GREEK HEALTH CARE INSTITUTIONS: A SCOPIN...

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22nd International Conference on e-Society 2024, ES 2024 and 20th International Conference on Mobile Learning 2024, ML 2024

作者： Mariettou, Savina Koutsojannis, Constantinos Triantafyllou, Vassilis University of Peloponnese Electrical and Computer Engineering Department Patras Greece Health Physics & Computational Intelligence Laboratory Physiotherapy Department School of Health Rehabilitation Sciences University of Patras Patras Greece Network Technologies and Digital Transformation lab Electrical and Computer Engineering Dpt. University of Peloponnese Patras Greece

Healthcare has undoubtedly brought many advancements through information technology. Specifically, healthcare informatics involves the use of various technologies, data management and communication systems to collect, store, analyze and effectively disseminate information. Therefore, the above serves to improve care as well as patient outcomes, improve efficiency, promote innovation and data analysis, as digitization has become an integral part of our daily lives in today's world. However, with the increased use of interconnected systems and electronic health records, hospitals have become prime targets for cyber-attacks. In this article we will delve into the critical topic of cybersecurity in hospitals as well as nursing facilities. The deepening of this issue was carried out with extensive analysis of the security systems of Greek hospitals. We investigated all their web sites and the security systems already in place on those sites. By checking we found a number vulnerabilities and potential risks. The most important weakness is the lack of legal as well as technical information for all interested citizens and patients. More organizational as well as technical work concerning internal architecture of information systems is needed, towards the improvement of security. In conclusion, we present our proposals on strategies to strengthen healthcare facilities against cyber threats. © 2024 International Conferences e-Society 2024 and Mobile Learning 2024. All rights reserved.

关键词： Cybersecurity Digitization Healthcare Information Patients Systems

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Optimizing Federated Learning through Lightweight and Scalable Blockchain

Optimizing Federated Learning through Lightweight and Scalab...

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International Conference on Distributed Computing in Sensor Systems (DCOSS)

作者： Georgios Andronikidis George Niotis Charis Eleftheriadis Konstantinos Kyranou Sotiris Nikoletseas Panagiotis Sarigiannidis Sidroco Holdings Ltd Nicosia Cyprus Dpt. of Computer Engineering & Informatics University of Patras Patras Greece Dpt. of Electrical & Computer Engineering University of Western Macedonia Kozani Greece

ISBN: (数字)9798350369441

ISBN: (纸本)9798350369458

In recent years, the increased focus on preserving data privacy, the advancements in machine learning, and the ongoing innovations in blockchain technology have sparked significant interest in implementing blockchain-based federated learning frameworks. Proposed solutions primarily focus on addressing the growing size of the blockchain in relation to machine learning algorithms, particularly the number of parameters involved in federated learning. However, the expanding blockchain scale results in increased time requirements, making many solutions impractical. In light of these issues, our research introduces a proof-of-concept for a lightweight, scalable, and modular blockchain network using Hyperledger Fabric to enhance federated learning. Performance evaluations using Hyperledger Caliper show that the proposed blockchain network effectively improves federated learning without compromising latency and throughput. Experimental results affirm blockchain’s proficiency in managing substantial transaction payloads from federated learning clients, especially with resource-intensive machine learning algorithms during training.

关键词： Training Machine learning algorithms Federated learning Distributed ledger computer architecture Throughput Fabrics

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FraMark: A Blockchain Marketplace for a 5G Network Management using Fractional NFTs 7

FraMark: A Blockchain Marketplace for a 5G Network Managemen...

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7th World Symposium on Communication engineering, WSCE 2024

作者： Michoulis, George Tsourdinis, Kyros Niotis, George Kyranou, Konstantinos Fountoukidis, Eleutherios Lagkas, Thomas Argyriou, Vasileios Sarigiannidis, Panagiotis Psannis, Konstantinos E. Goudos, Sotirios K. Sidroco Holdings Ltd R&D Dpt. Thessaloniki Greece Sidroco Holdings Ltd R&D Dpt. Nicosia Cyprus Democritus University of Thrace Dpt. of Computer Science Kavala Greece University of Western Macedonia Dpt. of Electrical & Computer Engineering Kozani Greece Kingston University London Kingston Upon Thames Dpt. of Networks and Digital Media Surrey United Kingdom University of Macedonia Department of Applied Informatics Thessaloniki Greece ELEDIA@AUTH School of Physics Aristotle University of Thessaloniki Thessaloniki Greece

ISBN: (纸本)9798331542825

This paper presents FraMark, a blockchain-based framework for 5G network management that utilizes Hyperledger Fabric and fractional Non-Fungible Tokens (NFTs) to optimize resource allocation. We introduce a comprehensive system that fractionalizes digital assets to represent 5G network resources, enhancing efficiency and allocation flexibility. Our framework addresses the challenges of 5G network management by ensuring low latency, high transaction throughput, and secure resource trading. We conduct experiments to evaluate the performance of our approach, including CPU and memory utilization, latency analysis, and block size assessment. The results demonstrate the effectiveness of FraMark in improving network resource utilization and transaction efficiency, validating our framework's claims. By leveraging blockchain technology and innovative resource slicing techniques, FraMark paves the way for dynamic and efficient 5G network management. © 2024 IEEE.

关键词： 5G mobile communication systems

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Validating Ontology-based Annotations of Biomedical Resources using Zero-shot Learning 2021

Validating Ontology-based Annotations of Biomedical Resource...

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12th International Conference on Computational Systems-Biology and Bioinformatics, CSBio 2021

作者： Koutsomitropoulos, Dimitrios Computer Engineering and Informatics Dpt. University of Patras Patras26500 Greece

ISBN: (纸本)9781450385107

Authoritative thesauri in the form of web ontologies offer a sound representation of domain knowledge and can act as a reference point for automated semantic tagging. On the other hand, current language models achieve to capture contextualized semantics of text corpora and can be leveraged towards this goal. We present an approach for injecting subject annotations using query term expansion against such ontologies in the biomedical domain. For the user to have an indication of the usefulness of these suggestions we further propose an online method for validating the quality of annotations using NLI models such as BART and XLM-R. To circumvent training barriers posed by very large label sets and scarcity of data we rely on zero-shot classification and show that semantic matching can contribute above-average thematic annotations. Also, a web-based validation service can be attractive for human curators vs. the overhead of pretraining large, domain-tailored classification models. © 2021 ACM.

关键词： Thesauri

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Interoperability of Information Sources for Identification With Privacy Preservation and Early Fraud Detection

Interoperability of Information Sources for Identification W...

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International Conference on Information, Intelligence, Systems and Applications (IISA)

作者： Aikaterini Deligiannidou Aggeliki Rapti Zafeiria-Marina Ioannou Emmanouil Viennas Christos Papaloukopoulos Mersini Paschou Computer Engineering and Informatics Dpt University of Patras Patras Greece Computer Engineering and Informatics Dpt University of Patras Intraway LTD Patras Greece DEVOUT L.P. Patras Greece

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When Circular Economy Meets the Smart City Ecosystem: Defining the Smart and Circular City

When Circular Economy Meets the Smart City Ecosystem: Defini...

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IEEE International Smart Cities Conference (ISC2)

作者： Georgios Mylonas Athanasios Kalogeras Sobah Abbas Petersen Luis Muñoz Ioannis Chatzigiannakis Industrial Systems Institute Athena Research Center Patras Greece Dpt. of Computer Science Norwegian University of Science and Technology Trondheim Norway Dpt. of Communications Engineering Universidad de Cantabria Santander Spain Dpt. of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9798350364316

ISBN: (纸本)9798350364323

Smart cities have been a very active research area in the past 20 years, while continuously adapting to new technological advancements and keeping up with the times regarding sustainability and climate change. In this context, there have been numerous proposals to expand the scope of smart cities, focusing on resilience and sustainability, among other aspects, resulting in terms like smart sustainable cities. At the same time, there is an ongoing discussion regarding the degree in which smart cities put people at their centre. In this work, we argue toward expanding the current smart city definition by integrating the circular economy as one of its central pillars and adopting the term smart (and) circular city. We discuss the ways a smart and circular city encompasses both sustainability and smartness in an integral manner, while also being well-positioned to foster novel business activity and models and helping to place citizens at the heart of the smart city. In this sense, we also argue that previous research in smart cities and technologies, such as those related to Industry 4.0, can serve as a cornerstone to implement circular economy activities within cities, at a scale that exceeds current activities that are based on more conventional approaches. We also outline current open challenges in this domain and research questions that still need to be addressed.

关键词： Heart Climate change Smart cities Ecosystems Focusing Fourth Industrial Revolution Proposals Sustainable development Resilience Business

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When Circular Economy Meets the Smart City Ecosystem: Defining the Smart and Circular City

arXiv

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arXiv 2024年

作者： Mylonas, Georgios Kalogeras, Athanasios Petersen, Sobah Abbas Muñoz, Luis Chatzigiannakis, Ioannis Industrial Systems Institute Athena Research Center Patras Greece Dpt. of Computer Science Norwegian University of Science and Technology Trondheim Norway Dpt. of Communications Engineering Universidad de Cantabria Santander Spain Dpt. of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

关键词： Circular economy

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A Multispectral Dataset for the Detection of Tutaabsoluta and Leveillula Taurica in Tomato Plants

SSRN

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SSRN 2022年

作者： Georgantopoulos, Panagiotis S. Papadimitriou, Dimitris Constantinopoulos, Constantinos Manios, Thrasyvoulos Daliakopoulos, Ioannis N. Kosmopoulos, Dimitrios Computer Engineering & Informatics Dpt. University of Patras Rio26504 Greece Dpt. of Agriculture Hellenic Mediterranean University Heraklion71410 Greece

Tomato (Solanum lycopersicum) is one of the most importantvegetables for human nutrition and its cultivation employs amounts of resourcesworldwide. However, tomato cultivation is plagued by several diseases and peststhat increase the production cost and introduce additional environmental andhealth risks due to pesticide use. Timely disease and pest detection is of highimportance for tomato crop production and the environment, as plant protec-tion input can be optimized. Here, we present a dataset of multispectral images(RGB and NIR) of tomato plants, at various stages of infection with Tuta ab-soluta and Leveillula taurica, which to our knowledge is unique. The datasetcomprised of 263 images collected from a real greenhouse. Additionally, weapplied a baseline Faster-RCNN object detector for the localization and classi-fication of lesions. Our experiments include (i) a version for the RGB channelsand (ii) a custom backbone architecture version for feature fusion using thesame Faster-RCNN head. Results of mAP 18.5% and mAP 20.2% respectively,highlight the added value of NIR spectral bands for detecting these diseases. © 2022, The Authors. All rights reserved.

关键词： Cultivation

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