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16th IEEE AFRICON, AFRICON 2023

作者： Skrjanc, Igor University of Ljubljana Laboratory of Control Systems and Cybernetics Faculty of Electrical Engineering Ljubljana Slovenia

ISBN: (纸本)9798350336214

This article proposes a novel approach to clustering called eCauchy, which is based on the Cauchy density function. This method is similar to the well-known possibilistic c-means clustering (PCM), which was developed to address the limitations of fuzzy c-means algorithms (FCM). Density-based clustering is particularly useful when dealing with noisy data and frequent outliers. The recursive measure of density can be adapted for various data mining tasks, including regression and classification. The eCauchy algorithm is simple to use and can handle big-data problems. It evolves dynamically by adding and removing clusters based on a few initial parameters, such as maximum and minimum density. This allows for the identification of clusters with different shapes and sizes and is robust to outliers and high levels of noise. The paper demonstrates the universality of this algorithm and its modifications through several simple examples that can also be found in more complex forms in real-world applications. © 2023 IEEE.

关键词： Big data

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Training an EOG-Based Wordometer Without Reading – A Simple HCI Application to Quantify Reading Metrics 1

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25th International Conference on Human-Computer Interaction , HCII 2023

作者： Mifsud, Matthew Camilleri, Tracey A. Camilleri, Kenneth P. Centre for Biomedical Cybernetics University of Malta Msida Malta Department of Systems and Control Engineering University of Malta Msida Malta

ISBN: (数字)9783031359897

ISBN: (纸本)9783031359880

Reading is the activity through which humans decipher written symbols in an effort to extract information from written text. Whether written on paper, or displayed on a screen, literacy can be considered as a valuable tool to one’s social and educational development. Through the use of electrooculography (EOG), as a means of tracking one’s eye movements, this work presents the development of a novel Wordometer application, capable of measuring the quantity of reading. Through the incorporation of a novel light-weight cue-based training protocol, this application obtained an average word estimation error of 8.23 % when tested across five human subjects using EOG data. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Eye tracking

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A switched system for modeling the +-inal dilation exercises 12

A switched system for modeling the +-inal dilation exercises

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12th IFAC Symposium on Biological and Medical Systems, BMS 2024

作者： Jackson, Roxanne R. Varagnolo, Damiano Dewitte, Marieke Knorn, Steffi Department of Control Engineering Technische Universität Berlin Germany Department of Engineering Cybernetics Norwegian University of Science and Technology Norway Department of Experimental Health Psychology Maastricht University Netherlands

Genito-pelvic pain/penetration disorders, i.e., painful experiences during penetrative sexual intercourse, affect an estimated 30-40% of people with vaginas at some point in their lives. Treatments for Genito-pelvic pain/penetration disorders vary depending on the main cause of the condition but may include the use of vaginal trainers/dilators which are used to stretch the vaginal duct and relax the Pelvic floor muscles. As a step towards understanding how patients respond to vaginal trainers, we investigate the interaction of pain and pleasure characteristics during treatments. In this paper, we adapt an existing qualitative model into a switched system where switches are determined by a patient's subjective level of pleasure. A qualitative model of the pain and fear characteristics is derived for each switched state. Due to sparsity in the experimental data, we adopt a weighted least squares approach for parameter identification using online (constant sampling period) and offline data (sparse and inconsistent sampling). The results indicate that it is a promising method compared to the grey-box model without considering pleasure levels but there is an obvious and variable delay in the reporting of a patient's pleasure levels which affects the overall performance of the switched system. © 2024 The Authors. This is an open access article under the CC BY-NC-ND license.

关键词： Decision support systems

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Design of unbiased reduced order filter for stochastic systems with sampled measurements 12

Design of unbiased reduced order filter for stochastic syste...

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12th International Conference on Mathematical Modeling in Physical Sciences, IC-MSQUARE 2023

作者： Kamenshchikov, Mikhail Lomonosov Moscow State University Faculty of Computational Mathematics and Cybernetics Department of Nonlinear Dynamical Systems and Control Processes Moscow119991 Russia V. A. Trapeznikov Institute of Control Sciences Russian Academy of Sciences Laboratory of Terminal Control Systems Moscow117997 Russia National University of Science and Technology "MISiS" Department of Engineering Cybernetics Moscow119049 Russia

The problem of synthesizing reduced order filter, that forms an unbiased estimate of linear functional from an unknown phase vector of a continuous time stochastic system with sampled measurements and additive noises, is considered in this work. The H2 norm of the weighted transfer function from input noises to estimation error is used as a performance criterion. The method for reduced order filter design is based on the expression of the explicit dependence of performance criterion on unknown parameters in the canonical basis and the application of the non-convex optimization technique. Numerical simulations are performed to illustrate the proposed approach. © 2024 Institute of Physics Publishing. All rights reserved.

关键词： Stochastic systems

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Modelling information warfare dynamics to counter propaganda using a nonlinear differential equation with a PINN-based learning approach

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International Journal of Information Technology (Singapore) 2024年第3期16卷 1527-1538页

作者： Pandey, Rashmikiran Pandey, Mrinal Nazarov, Alexey Nikolaevich Department of Radio Engineering and Cybernetics Moscow Institute of Physics and Technology Moscow Russian Federation Federal Research Center Computer Science and Control Russian Academy of Science Moscow Russian Federation

The widespread dissemination of misinformation and propaganda has become a crucial issue in societal conversations. This study presents an innovative framework to counter propaganda within information warfare using a modified logistic differential equation integrated with a Physics-Informed Neural Network (PINN). Employing the LIAR dataset, which reflects real-world political discourse, our model captures the intricate dynamics of propaganda. The novel approach effectively estimates underlying dynamics and unknown parameters, yielding superior accuracy (97.32%) compared to benchmark models. A parameter sensitivity analysis reveals the significant impact of the spread rate parameter, shedding light on aggressive propaganda dissemination. This research paves the way for robust methods in combating propaganda, demonstrating the effectiveness and superiority of the proposed PINN-based model over established benchmark models. © 2023, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of Computer Applications and Management.

关键词： Information warfare Nonlinear differential equations PINN Propaganda Random forest classifier TF-IDF

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Detection of Electric Motor Damage Through Analysis of Sound Signals Using Bayesian Neural Networks 50

Detection of Electric Motor Damage Through Analysis of Sound...

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50th Annual Conference of the IEEE Industrial Electronics Society, IECON 2024

作者： Bauer, Waldemar Zagórowska, Marta Baranowski, Jerzy Dept. of Automatic Control & Robotics AGH University of Krakow Krakow Poland Dept. of Engineering Cybernetics Norwegian University of Science and Technology Trondheim Norway

ISBN: (纸本)9781665464543

Fault monitoring and diagnostics are important to ensure reliability of electric motors. Efficient algorithms for fault detection improve reliability, yet development of cost-effective and reliable classifiers for diagnostics of equipment is challenging, in particular due to unavailability of well-balanced datasets, with signals from properly functioning equipment and those from faulty equipment. Thus, we propose to use a Bayesian neural network to detect and classify faults in electric motors, given its efficacy with imbalanced training data. The performance of the proposed network is demonstrated on real life signals, and a robustness analysis of the proposed solution is provided. © 2024 IEEE.

关键词： Damage detection

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Parameter Adjustments in POMDP-Based Trajectory Planning for Unsignalized Intersections 10

Parameter Adjustments in POMDP-Based Trajectory Planning for...

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10th International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2024

作者： Kollarčík, Adam Hanzálek, Zdeněk Dept. of Control Engineering Faculty of Electrical Engineering Czech Technical University Prague Czech Republic Czech Institute of Informatics Robotics and Cybernetics Czech Technical University Prague Czech Republic

ISBN: (纸本)9789897587030

This paper investigates the problem of trajectory planning for autonomous vehicles at unsignalized intersections, specifically focusing on scenarios where the vehicle lacks the right of way and yet must cross safely. To address this issue, we have employed a method based on the Partially Observable Markov Decision Processes (POMDPs) framework designed for planning under uncertainty. The method utilizes the Adaptive Belief Tree (ABT) algorithm as an approximate solver for the POMDPs. We outline the POMDP formulation, beginning with discretizing the intersection's topology. Additionally, we present a dynamics model for the prediction of the evolving states of vehicles, such as their position and velocity. Using an observation model, we also describe the connection of those states with the imperfect (noisy) available measurements. Our results confirmed that the method is able to plan collision-free trajectories in a series of simulations utilizing real-world traffic data from aerial footage of two distinct intersections. Furthermore, we studied the impact of parameter adjustments of the ABT algorithm on the method's performance. This provides guidance in determining reasonable parameter settings, which is valuable for future method applications. Copyright © 2024 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Vehicles

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Advancing Network Anomaly Detection: Comparative Analysis of Machine Learning Models

Advancing Network Anomaly Detection: Comparative Analysis of...

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International Conference on. Cryptology and Network Security with Machine Learning, ICCNSML 2023

作者： Pandey, Rashmikiran Pandey, Mrinal Nazarov, Alexey Department of Radio Engineering and Cybernetics Moscow Institute of Physics and Technology Moscow Russia Federal Research Center Computer Science and Control Russian Academy of Science Moscow Russia

ISBN: (纸本)9789819706402

In the rapidly evolving realm of cyber-security, the detection of network anomalies serves as a pivotal line of defense against a myriad of malicious activities and cyberthreats. This research undertakes the task of enhancing the accuracy and efficacy of network anomaly detection by employing a comparative analysis of various individual machine learning models. The study delves into the performance of distinct models, including Random Forest, Gradient Boosting, AdaBoost, neural networks, and SVM, meticulously scrutinizing their capabilities in detecting network anomalies. The crux of this study lies in its meticulous evaluation of each individual model on the revered NSL-KDD dataset—an established benchmark within the field of network intrusion detection. Through a systematic blend of rigorous mathematical frameworks, precise model implementations, and comprehensive experimental assessments, this research offers a deep understanding of the inner workings of each algorithm. The pivotal aspect of this study revolves around the comprehensive comparative analysis of these standalone models. Going beyond the mere quantifica-tion of accuracy, the exploration delves into aspects of precision, recall, F1-score, and more, shedding light on their diverse facets of performance. With achieved accuracies of 99.2419% for Random Forest, 99.5197% for Gradient Boosting, 86.6044% for AdaBoost, 84.00% for neural networks, and 87.00% for SVM, this research underlines the distinctive attributes and potential of each model in the context of network anomaly detection. As the study unravels the distinct strengths and limitations of each model, it contributes to the broader landscape of cyber-security by providing insights into the efficacy of individual machine learning approaches. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Support vector machines

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Dynamic Multihead Attention for Enhancing Neural Machine Translation Performance 5th

Dynamic Multihead Attention for Enhancing Neural Machine Tra...

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5th International Conference on Trends in Computational and Cognitive engineering, TCCE 2023

作者： Pandey, Mrinal Pandey, Rashmikiran Nazarov, Alexey Department of Radio Engineering and Cybernetics Moscow Institute of Physics and Technology Moscow Russia Federal Research Center Computer Science and Control Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9789819719228

The research paper delves into the realm of "Attention-Based Neural Machine Translation for Multilingual Communication", focusing on the revolutionary impact of attention mechanisms in enhancing cross-language understanding. Through dynamic allocation of focus to pertinent segments of source sequences, attention mechanisms have significantly improved the precision and coherence of translations, playing a pivotal role in multilingual communication. The paper underscores the importance of this technology in addressing the complexities of aligning words across diverse languages and maintaining grammatical accuracy, crucial for effective cross-lingual interactions. The study also presents a visual flowchart outlining the core components of attention-based NMT, encompassing the encoder, decoder, and attention context. Moreover, the paper extrapolates the future trajectory of attention-based NMT, identifying areas for continued exploration and innovation. Researchers are urged to refine attention models to cater to intricate linguistic structures, potentially unveiling novel mechanisms that strike a balance between capturing long-range dependencies and computational efficiency. Furthermore, the paper anticipates the integration of attention-based NMT with multimodal inputs, unlocking the potential for comprehensive communication by incorporating visual and auditory cues. These advancements hold the promise of revolutionising multilingual communication, shaping a future where language barriers are transcended in various domains, from global diplomacy to education and beyond. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Neural machine translation

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Dwell-Free Typing Using an EOG Based Virtual Keyboard 24th

Dwell-Free Typing Using an EOG Based Virtual Keyboard

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24th International Conference on Human-Computer Interaction, HCI International, HCII 2022

作者： Mifsud, Matthew Camilleri, Tracey A. Camilleri, Kenneth P. Department of Systems and Control Engineering University of Malta Msida Malta Centre for Biomedical Cybernetics Department of Systems and Control Engineering University of Malta Msida Malta

ISBN: (纸本)9783031063879

This work presents the development of an asynchronous dwell-free virtual keyboard application which can be operated using electrooculographic (EOG) data. Unlike other EOG based eye typing applications, the developed system avoids the use of dwell-times and relieves the user from the need to perform repetitive and unnatural eye movements to move a cursor towards the desired letter or the need to perform voluntary blinks to interact with the application. Instead, the proposed application requires the user to simply glance through the vicinity of the desired letters, as one would swipe through letters when typing on a touchscreen device, after which a set of word predictions are displayed for the user to select. The proposed application obtained a top five rate of 76.00 ± 12.61% using EOG data which is comparable to the top five rate of 79.00 ± 13.37% obtained when operating the application using a vision-based eye gaze tracker. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Eye movements

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