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Progress in Applied Electrical Engineering (PAEE)

作者： Patryk Mendoń Mariusz Pelc Aleksandra Kawala-Sterniuk Mariusz Gola Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole Poland Faculty of Mathematics Physics and Computer Science University of Opole Opole Poland

ISBN: (数字)9798331527563

ISBN: (纸本)9798331527570

In this paper the authors propose a system architecture which allows product scoring based on sentiment analysis and utilising Machine Learning (ML) and Expert systems technologies. This solution presented in this paper allows decoupling the AI-based part, which is very capable in sentiment analysis but is lacking some flexibility to actually put the sentiment analysis results in a wider context to make a better sense as to what the results actually mean. This task in our solution is performed by the Expert system where the expert may provide some decision making rules in order to determine the final system *** results confirm discrepancy between reviews and star ratings.

关键词： Knowledge engineering Fuzzy logic Sentiment analysis Reviews Systems architecture Stars Machine learning Cognition Expert systems System analysis and design

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Adversarial Capsule Networks for Romanian Satire Detection and Sentiment Analysis

arXiv

引用

arXiv 2023年

作者： Echim, Sebastian-Vasile Smădu, Răzvan-Alexandru Avram, Andrei-Marius Cercel, Dumitru-Clementin Pop, Florin Faculty of Automatic Control and Computers University Politehnica of Bucharest Romania National Institute for Research and Development in Informatics - ICI Bucharest Romania

Satire detection and sentiment analysis are intensively explored natural language processing (NLP) tasks that study the identification of the satirical tone from texts and extracting sentiments in relationship with their targets. In languages with fewer research resources, an alternative is to produce artificial examples based on character-level adversarial processes to overcome dataset size limitations. Such samples are proven to act as a regularization method, thus improving the robustness of models. In this work, we improve the well-known NLP models (i.e., Convolutional Neural Networks, Long Short-Term Memory (LSTM), Bidirectional LSTM, Gated Recurrent Units (GRUs), and Bidirectional GRUs) with adversarial training and capsule networks. The fine-tuned models are used for satire detection and sentiment analysis tasks in the Romanian language. The proposed framework outperforms the existing methods for the two tasks, achieving up to 99.08% accuracy, thus confirming the improvements added by the capsule layers and the adversarial training in NLP approaches. © 2023, CC BY-NC-SA.

关键词： Sentiment analysis

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RoBERTweet: A BERT Language Model for Romanian Tweets

arXiv

引用

arXiv 2023年

作者： Tăiatu, Iulian-Marius Avram, Andrei-Marius Cercel, Dumitru-Clementin Pop, Florin Faculty of Automatic Control and Computers University Politehnica of Bucharest Romania National Institute for Research and Development in Informatics - ICI Bucharest Romania

Developing natural language processing (NLP) systems for social media analysis remains an important topic in artificial intelligence research. This article introduces RoBERTweet, the first Transformer architecture trained on Romanian tweets. Our RoBERTweet comes in two versions, following the base and large architectures of BERT. The corpus used for pre-training the models represents a novelty for the Romanian NLP community and consists of all tweets collected from 2008 to 2022. Experiments show that RoBERTweet models outperform the previous general-domain Romanian and multilingual language models on three NLP tasks with tweet inputs: emotion detection, sexist language identification, and named entity recognition. We make our models and the newly created corpus of Romanian tweets freely available. © 2023, CC BY-SA.

关键词： Computational linguistics

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Machine Learning Detects Anomalies in OPS-SAT Telemetry 23rd

Machine Learning Detects Anomalies in OPS-SAT Telemetry

引用

23rd International Conference on Computational Science, ICCS 2023

作者： Ruszczak, Bogdan Kotowski, Krzysztof Andrzejewski, Jacek Musial, Alicja Evans, David Zelenevskiy, Vladimir Bammens, Sam Laurinovics, Rodrigo Nalepa, Jakub Faculty of Electrical Engineering Automatic Control and Informatics Department of Informatics Opole University of Technology Prószkowska 76 Opole45-758 Poland Faculty of Automatic Control Electronics and Computer Science Department of Algorithmics and Software Silesian University of Technology Akademicka 16 Gliwice44-100 Poland KP Labs Konarskiego 18C Gliwice44-100 Poland European Space Agency/ESOC Robert-Bosch-Str. 5 Darmstadt64293 Germany Telespazio Germany GmbH Europaplatz 5 Darmstadt64293 Germany IrbGS ltd "Viraki" Ance Parish IrbeneLV-3601 Latvia

ISBN: (纸本)9783031359941

Detecting anomalies in satellite telemetry data is pivotal in ensuring its safe operations. Although there exist various data-driven techniques for the task of determining abnormal parts of the signal, they are virtually never validated over real telemetries. Analyzing such data is challenging due to its intrinsic characteristics, as telemetry may be noisy and affected by incorrect acquisition, resulting in missing parts of the signal. In this paper, we tackle this issue and propose a machine learning approach for detecting anomalies in single-channel satellite telemetry. To validate its capabilities in a practical scenario, we build a dataset capturing the nominal and anomalous telemetry data captured on board OPS-SAT—a nanosatellite launched and operated by the European Space Agency. Our extensive experimental study showed that the proposed algorithm offers high-quality anomaly detection in real-life satellite telemetry, reaching 98.4% accuracy over the unseen test set. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Machine learning

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Non-Invasive Device for Hearing Rehabilitation

Non-Invasive Device for Hearing Rehabilitation

引用

E-Health and Bioengineering Conference (EHB)

作者： Daniela Goldan Mihai Aron Teofil Ilie Ursache Gladiola Petroiu Cristian Rotariu Dept. of Biomedical Sciences Faculty of Medical Bioengineering Grigore T. Popa University of Medicine and Pharmacy of Iasi Iași Romania Dept. of Automatic Control and Applied Informatics Faculty of Automatic Control and Computer Engineering Gheorghe Asachi Technical University Iași Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Hearing loss impacts over 5% of the world's population, a percent rising due to aging populations, noise exposure, and chronic health conditions. To address this, we developed a non-invasive hearing device designed for individuals with hearing challenges that limit the use of hearing aids. The proposed device integrates a set of Bluetooth headphones with a smartphone, that process the ambient sound in real time through a software application and delivers to the hear impaired patient via bone conduction, bypassing traditional auditory pathways. Laboratory tests confirmed that the proposed device effectively replicates auditory perception. The developed device offers an accessible and user-friendly alternative to patients who cannot use traditional hearing aids.

关键词： Irrigation Noise Auditory system Ear Receivers Hearing aids Propagation losses Real-time systems Software Testing

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SkinDistilViT: Lightweight Vision Transformer for Skin Lesion Classification

arXiv

引用

arXiv 2023年

作者： Lungu-Stan, Vlad-Constantin Cercel, Dumitru-Clementin Pop, Florin Faculty of Automatic Control and Computers University Politehnica of Bucharest Romania National Institute for Research and Development in Informatics - ICI Bucharest Romania

Skin cancer is a treatable disease if discovered early. We provide a production-specific solution to the skin cancer classification problem that matches human performance in melanoma identification by training a vision transformer on melanoma medical images annotated by experts. Since inference cost, both time and memory wise is important in practice, we employ knowledge distillation to obtain a model that retains 98.33% of the teacher’s balanced multi-class accuracy, at a fraction of the cost. Memory-wise, our model is 49.60% smaller than the teacher. Time-wise, our solution is 69.25% faster on GPU and 97.96% faster on CPU. By adding classification heads at each level of the transformer and employing a cascading distillation process, we improve the balanced multi-class accuracy of the base model by 2.1%, while creating a range of models of various sizes but comparable performance. We provide the code at https://***/Longman-Stan/SkinDistilVit. © 2023, CC BY-NC-ND.

关键词： Distillation

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Advanced Signal Processing and Classification of EEG Patterns in Neurointerface Systems 3

Advanced Signal Processing and Classification of EEG Pattern...

引用

3rd International Workshop on Information Technologies: Theoretical and Applied Problems, ITTAP 2023

作者： Lupenko, Serhii Butsiy, Roman Volyanyk, Oleksandr Stadnyk, Nataliia Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Opole45-758 Poland Institute of Telecommunications and Global Information Space National Academy of Sciences of Ukraine Kyiv02000 Ukraine Ternopil Ivan Puluj National Technical University Ternopil46001 Ukraine

This study provides a comprehensive assessment of an extended set of modern classifiers designed for electroencephalography signal analysis in brain-computer interface systems. Using the modern model of the vector of cyclic rhythmically connected random processes for estimating signal characteristics, the classifiers compared encompass k-NN, Linear SVM, Decision Tree, Random Forest, Multilayer Perceptron, AdaBoost, and Naive Bayes. By decomposing signals into Fourier series, the optimal number of coefficients is investigated to both reduce computational complexity and increase accuracy. To facilitate a transparent and decisive comparison among the classifiers, the Confusion Matrix methodology is used. Results suggest that among the diverse range evaluated, Linear SVM, Naive Bayes, and Multilayer Perceptron classifiers showcased superior accuracy. © 2023 CEUR-WS. All rights reserved.

关键词： Brain computer interface

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Cardiac Condition Detection Model Using Alexnet and Time-Frequency Representation of ECG Signals

Cardiac Condition Detection Model Using Alexnet and Time-Fre...

引用

E-Health and Bioengineering Conference (EHB)

作者： Mihai Aron Teofil Ilie Ursache Gladiola Petroiu Cristian Rotariu Dept. of Biomedical Sciences Grigore T. Popa University of Medicine and Pharmacy of Iasi Faculty of Medical Bioengineering Iaşi Romania Dept. of Automatic Control and Applied Informatics Gheorghe Asachi Technical University Faculty of Automatic Control and Computer Engineering Iaşi Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Cardiac conditions are one of the leading causes of death worldwide. To address this, we designed a model that can detect cardiac conditions from a patient's electrocardiogram (ECG). This will convert the 1D ECG signal into a 2D scalogram using wavelet transforms with Morlet wavelets. With the help of a network based on the AlexNet convolutional neural network, it distinguishes between a normal ECG signal and one indicative of arrhythmia or congestive heart failure. The resulting model performs well, achieving a classification accuracy of 92.20% and providing a robust approach for detecting cardiac conditions.

关键词： Wavelet transforms Training Time-frequency analysis Accuracy Biological system modeling Electrocardiography Predictive models Congestive heart failure Convolutional neural networks Biomedical engineering

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Evaluating the usage of Text to3D scene generation methods in Game-Based Learning

Evaluating the usage of Text to3D scene generation methods i...

引用

International Conference on control Systems and Computer Science (CSCS)

作者： Alexandru Gradinaru Mihnea Vrejoiu Florica Moldoveanu Maria-Anca Balutoiu Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Bucharest Romania National Institute for Research and Development in Informatics Bucharest Romania

Computer games as an educational tool significantly improved information retention, student involvement, and motivation. Despite the growing popularity and the demonstrated positive impact, little progress is made to let educators create games without learning game programming or investing massive amounts of time, money, and human resources. This paper considers the usage of procedural content generation in simplifying the generation of game environments. Given that most educational material is in text format, we evaluate the possibility of generating 3D scenes starting from natural language text. A comprehensive survey of the current methods is presented, analyzing whether they can be successfully used in game-based learning. The study discusses several current limitations and possible improvements, highlighting a need for better progress in the domain.

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Managing Notifications and Alerts Generated by an IoMT-based Health Monitoring System for Older People 10

Managing Notifications and Alerts Generated by an IoMT-based...

引用

10th E-Health and Bioengineering Conference, EHB 2022

作者： Alexandru, Adriana Tîrziu, Eugenia Tudora, Eleonora Nicolau, Dragoș National Institute for Research and Development in Informatics Bucharest Romania University Valahia of Târgoviște Târgoviște Romania Doctoral School of Automatic Control and Computers University Politehnica of Bucharest Bucharest Romania

ISBN: (纸本)9781665485579

Internet of Medical Things (IoMT) has already proved to support a proper evaluation of the medical status and living conditions of a patient by gathering a large variety of data. For a personalized health management of an older patient, IoMT provides the capacity for sustaining the transformation the patient-physician relationship by enabling a real-time and continuous remote monitoring of the health status, activities and well-being of the senior, especially in a residential environment. Thus, a new collaborative solution between the patient and the physician and the enhancement of their involvement and shared decision-making are provided. Health remote monitoring systems in smart environments are able to be a viable alternative to traditional healthcare solutions. The ongoing "Non-invasive monitoring and health assessment of the elderly in a smart environment (RO-SmartAgeing)" project aims to a complete and accurate solution for assessing the health condition of the seniors, improving their wellbeing and quality of life. The continuous monitoring of patient’s health status together of the provision of notifications and alerts related to problems in her/his health condition can allow the physician to provide health services at a higher level of efficiency and to offer a more comprehensive perspective of proactive and preventive medical acts. © 2022 IEEE.

关键词： Decision making

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