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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Ziogas, Ioannis Hadjileontiadis, Leontios J. Khandoker, Ahsan H. Al Shehhi, Aamna Dpt. of Biomedical Eng. and Biotechnology Khalifa University of Science and Technology Abu Dhabi United Arab Emirates Dpt. of Electrical and Computer Eng. Aristotle University of Thessaloniki Thessaloniki Greece

ISBN: (纸本)9798350368741

Wearable and smartphone-based emotion recognition (WER) remains a challenging setting in affective computing, due to the notorious difficulty and bias associated with in-the-wild label collection. The high inter-and intra-subject emotional variability motivates us to explore WER modeling through graph node classification in a limited resources learning scheme powered by Self-Supervised Learning (SSL) graph masking augmentation tasks. We employ a subgraph sampling approach during training, utilizing labeled and unlabeled data, along with supervised, semi-supervised, and SSL mechanisms in a multi-task inductive graph neural network architecture. Our evaluations on K-EmoPhone through leave-one-group-out cross-validation in the binary arousal and valence tasks yield average accuracy gains of 4.3% and 7.8%, compared to the full resource setting, utilizing only 20% and 25% of the labels, respectively. Our model analysis sheds light on the relation of SSL graph augmentations to emotional arousal and valence and justifies the approach of SSL-driven subgraph training for in-the-wild WER. © 2025 IEEE.

关键词： Graph Masking Graph Neural Networks Self-Supervised Learning Wearable Emotion Recognition

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Self-Supervised Graph Representation Learning for In-The-Wild Wearable and Smartphone based Emotion Recognition

Self-Supervised Graph Representation Learning for In-The-Wil...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Ioannis Ziogas Leontios J. Hadjileontiadis Ahsan H. Khandoker Aamna Al Shehhi Dpt. of Biomedical Eng. and Biotechnology Khalifa University of Science and Technology Abu Dhabi UAE Dpt. of Electrical and Computer Eng Aristotle University of Thessaloniki Thessaloniki Greece

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Wearable and smartphone-based emotion recognition (WER) remains a challenging setting in affective computing, due to the notorious difficulty and bias associated with in-thewild label collection. The high inter-and intra-subject emotional variability motivates us to explore WER modeling through graph node classification in a limited resources learning scheme powered by Self-Supervised Learning (SSL) graph masking augmentation tasks. We employ a subgraph sampling approach during training, utilizing labeled and unlabeled data, along with supervised, semi-supervised, and SSL mechanisms in a multi-task inductive graph neural network architecture. Our evaluations on K-EmoPhone through leave-one-group-out cross-validation in the binary arousal and valence tasks yield average accuracy gains of 4.3% and 7.8%, compared to the full resource setting, utilizing only 20% and 25% of the labels, respectively. Our model analysis sheds light on the relation of SSL graph augmentations to emotional arousal and valence and justifies the approach of SSL-driven subgraph training for in-the-wild WER.

关键词： Training Representation learning Emotion recognition Time series analysis Speech recognition Self-supervised learning Signal processing biomedical monitoring Wearable devices Speech processing

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An efficient heuristic for geometric analysis of cell deformations

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computers in Biology and Medicine 2025年 186卷 109709-109709页

作者： Soto, Yaima Paz Garcia, Silena Herold Gual-Arnau, Ximo Jaume-i-Capó, Antoni González-Hidalgo, Manuel Department of Informatics University of Guantánamo Guantánamo Cuba Department of Computer Science University of Oriente Santiago de Cuba Cuba Departament de Matemàtiques Institute of New Imaging Technologies Universitat Jaume I Castelló Spain UGiVIA Research Group University of the Balearic Islands Dpt. of Mathematics and Computer Science Crta. Valldemossa Km 7.5 PalmaE-07122 Spain SCOPIA Research Group University of the Balearic Islands Dpt. of Mathematics and Computer Science Crta. Valldemossa Km 7.5 PalmaE-07122 Spain PalmaE-07122 Spain PalmaE-07122 Spain PalmaE-07122 Spain

Sickle cell disease causes erythrocytes to become sickle-shaped, affecting their movement in the bloodstream and reducing oxygen delivery. It has a high global prevalence and places a significant burden on healthcare systems, especially in resource-limited regions. Automated classification of sickle cells in blood images is crucial, allowing the specialist to reduce the effort required and avoid errors when quantifying the deformed cells and assessing the severity of a crisis. Recent studies have proposed various erythrocyte representation and classification methods (Jennifer et al., 2023 [1]). Since classification depends solely on cell shape, a suitable approach models erythrocytes as closed planar curves in shape space (Epifanio et al., 2020). This approach employs elastic distances between shapes, which are invariant under rotations, translations, scaling, and reparameterizations, ensuring consistent distance measurements regardless of the curves’ position, starting point, or traversal speed. While previous methods exploiting shape space distances had achieved high accuracy, we refined the model by considering the geometric characteristics of healthy and sickled erythrocytes. Our method proposes (1) to employ a fixed parameterization based on the major axis of each cell to compute distances and (2) to align each cell with two templates using this parameterization before computing distances. Aligning shapes to templates before distance computation, a concept successfully applied in areas such as molecular dynamics (Richmond et al., 2004 [2]), and using a fixed parameterization, instead of minimizing distances across all possible parameterizations, simplifies calculations. This strategy achieves 96.03% accuracy rate in both supervised classification and unsupervised clustering. Our method ensures efficient erythrocyte classification, maintaining or improving accuracy over shape space models while significantly reducing computational costs. © 2025 Elsevier Ltd

关键词： Template matching

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Smart Delivery for Goods Exploiting ML Algorithms 26

Smart Delivery for Goods Exploiting ML Algorithms

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26th Pan-Hellenic Conference on informatics, PCI 2022

作者： Boumpa, Eleni Tsoukas, Vasileios Chioktour, Vasileios Kalafati, Maria Spathoulas, Georgios Kakarountas, Athanasios Dpt. of Computer Science and Biomedical Informatics University of Thessaly Lamia Greece

ISBN: (纸本)9781450398541

This paper presents the work conducted on providing an efficient solution to the Vehicle Routing Problem considering all stages of a delivery process. The results are promising when compared to real-life data and depict the benefits of the application of ML algorithms in all stages of the process. A platform capable to monitor the various stages of the process was developed, and a number of ML models were incorporated to provide the best solution to a multiobjective problem. The results indicate on average a maximum of 25% distance saving, and a maximum of 14% regarding the total delivery time. © 2022 ACM.

关键词： Fleet operations

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Wearable panic attack detection system 2017

Wearable panic attack detection system

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21st Pan-Hellenic Conference on informatics, PCI 2017

作者： Sapounaki, Maria Polychronou, Ioanna Gkonta, Maria Vogiatzoglou, Angeliki Kakarountas, Athanasios University of Thessaly Dpt. of Computer Science and Biomedical Informatics Lamia Greece

ISBN: (纸本)9781450353557

The paper proposes a wearable system for panic attack detection, constructed by COTS products. It is the first open hardware/open software prototype of its kind to the best of the authors knowledge. In this paper, the requirements of the system are presented, as well as the development of the system using open hardware and open software. All the components are described and the system is detailed in order to be repeated for use as a reference system forpanic attack detection. © 2017 Association for Computing Machinery.

关键词： Software prototyping

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Prototype Haptic Feedback Device for Robot-Assisted Minimally Invasive Surgery 6

Prototype Haptic Feedback Device for Robot-Assisted Minimall...

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6th South-East Europe Design Automation, computer Engineering, computer Networks and Social Media Conference, SEEDA-CECNSM 2021

作者： Zagori, Sofia I. Kakarountas, Athanasios P. Dpt. of Computer Science and Biomedical Informatics University of Thessaly Lamia Greece

ISBN: (纸本)9781665427425

Robot-Assisted Minimally Invasive Surgery (RAMIS) is an innovation that has benefited hundreds of thousands of patients to date. However, despite their many advantages, those robots are not as popular as expected. Many health professionals are hesitant to use them since they don't provide as much feedback as to their human senses. Haptic feedback is crucial for the smooth conduction of the operation. Our goal was to develop a low-cost sensing system for surgical robots, which will add to their attraction and make them more appealing to surgeons and patients. © 2021 IEEE

关键词： Feedback

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A Reward Modulated Spiked Timing Depended Plasticity inspired algorithm applied on a MultiLayer Perceptron 27

A Reward Modulated Spiked Timing Depended Plasticity inspire...

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27th Pan-Hellenic Conference on Progress in Computing and informatics with International Participation, PCI 2023

作者： Giannakas, Georgios Sapounaki, Maria Tsoukas, Vasileios Kakarountas, Athanasios Dpt. of Computer Science and Biomedical Informatics University of Thessaly Lamia Greece

ISBN: (纸本)9798400716263

The creation of a framework in which traditional Machine Learning and neuromorphic algorithms compete to solve a shared Reinforcement Learning environment is presented in this work. In addition, this configuration allows the exploitation of modern and widely-used Machine Learning libraries. The PyTorch framework is used to investigate the expanded capabilities and potential of training an action-critic network pair comprised of specialised units using a custom learning algorithm. The policy and value networks utilised in this context are fully interconnected MultiLayer Perceptrons. The training procedure employs two distinct algorithms: an algorithm inspired by Reward Modulated Spiked Timing Dependent Plasticity and the conventional Back Propagation technique. A comparative evaluation and analysis of the findings is performed. © 2023 Owner/Author.

关键词： Reinforcement learning

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Systolic binary counter using a cellular automaton-based prescaler 2017

Systolic binary counter using a cellular automaton-based pre...

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21st Pan-Hellenic Conference on informatics, PCI 2017

作者： Chioktour, Vasileios Spathoulas, Georgios Kakarountas, Athanasios University of Thessaly Dpt. of Computer Science and Biomedical Informatics Lamia Greece

ISBN: (纸本)9781450353557

Counters are among the fundamental digital circuits in every computing system. For this reason, counter design is of great interest in the design of computers and embedded systems, in terms of area requirements,power dissipation and performance. Many techniques have been proposed in the past specifically to increase the counter's speed without increasing design complexity. Traditionally, it is of great concern to make a fast counter suitable for many applications, without adding to the critical path and keeping speed independent of its size. In this work, a binary counter is proposed, based on 1D Cellular Automata (CA), which is used as a prescaler in a systolic structure, that offers constant delay for counters of various bit-widths. © 2017 Association for Computing Machinery.

关键词： Cellular automata

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A Review of Homomorphic Encryption and its Contribution to the Sector of Health Services 27

A Review of Homomorphic Encryption and its Contribution to t...

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27th Pan-Hellenic Conference on Progress in Computing and informatics with International Participation, PCI 2023

作者： Roumpies, Fotios Kakarountas, Athanasios Dpt. of Computer Science and Biomedical Informatics University of Thessaly Lamia Greece

ISBN: (纸本)9798400716263

Homomorphic encryption is a groundbreaking cryptographic method that has made giant contributions to healthcare by addressing the urgent need for steady and privacy-keeping information analysis and sharing. This encryption approach permits information to be processed while nonetheless in its encrypted form, permitting healthcare businesses to perform complex computations on confidential patient information without compromising character privacy or data protection. It paved the way for secure cloud-based facts storage, sharing, and collaborative healthcare research, facilitating advancements in fact-driven selection-making, customized medicinal drugs, and remote affected person tracking. Homomorphic encryption has emerged as a vital enabler of innovation by maintaining the confidentiality of affected personal information while enabling meaningful analysis. © 2023 Owner/Author.

关键词： Data privacy

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Home assistive system for dementia 2017

Home assistive system for dementia

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21st Pan-Hellenic Conference on informatics, PCI 2017

作者： Boumpa, Eleni Charalampou, Ioanna Gkogkidis, Anargyros Kakarountas, Athanasios University of Thessaly Dpt. of Computer Science and Biomedical Informatics Lamia Greece

ISBN: (纸本)9781450353557

This work proposes an innovative home assisted system, based on the interaction of the stimulus earpiece. It addresses a need of people suffering from dementia as well as their familiars to be recognized by them and have better interaction and collaboration. The project aims not only to people already suffering from dementia at early stages but also people with genetic predisposition who may be trained appropriately to discover and create acoustical stimuli associated to their familiars. The system offers an ubiquitous recognition system, without the need for extensive training of the patient, based on the principles of music therapy and the features of wireless communication. To the best of the authors knowledge, this is the first system of its kind ever reported in the literature.

关键词： Ubiquitous computing

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