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EDSA-Ensemble: an Event Detection Sentiment Analysis Ensemble Architecture

IEEE Transactions on Affective Computing 2024年第02期16卷 1-18页

作者： PETRESCU, Alexandru TRUICA, Ciprian-Octavian APOSTOL, Elena-Simona PASCHKE, Adrian Computer Science and Engineering Department Faculty of Automatic Control and Computers National University of Science and Technology Politehnica Bucharest Bucharest Romania Fraunhofer Institute for Open Communication Systems Berlin Germany

As global digitization continues to grow, technology becomes more affordable and easier to use, and social media platforms thrive, becoming the new means of spreading information and news. Communities are built around sharing and discussing current events. Within these communities, users are enabled to share their opinions about each event. Using Sentiment Analysis to understand the polarity of each message belonging to an event, as well as the entire event, can help to better understand the general and individual feelings of significant trends and the dynamics on online social networks. In this context, we propose a new ensemble architecture, EDSAEnsemble (Event Detection Sentiment Analysis Ensemble), that uses Event Detection and Sentiment Analysis to improve the detection of the polarity for current events from Social Media. For Event Detection, we use techniques based on Information Diffusion taking into account both the time span and the topics. To detect the polarity of each event, we preprocess the text and employ several Machine and Deep Learning models to create an ensemble model. The preprocessing step includes several word representation models: raw frequency, TFIDF, Word2Vec, and Transformers. The proposed EDSA-Ensemble architecture improves the event sentiment classification over the individual Machine and Deep Learning models. Authors

关键词： Sentiment analysis

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Voltage and power control for distributed generation units in islanded microgrids 6th

Voltage and power control for distributed generation units i...

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6th International Conference on Renewable Energies Offshore, RENEW 2024

作者： Rouch, T. Bagheri M’zoughi, F. Aboutalebi, P. Ahmad, I. Garrido, A.J. Garrido, I. Institute of Research and Development of Processes—IIDP Department of Automatic Control and Systems Engineering Faculty of Engineering of Bilbao University of the Basque Country Bilbao Spain

ISBN: (纸本)9781032905570

This article presents an optimized control strategy tailored for DC islanded microgrids, featuring a voltage controller based on mixed H2/H∞ state feedback using linear matrix inequalities (LMIs) and a power controller guided by droop characteristics. A polytopic modeling approach addresses system uncertainties and nonlinearities. The controller aims to stabilize the system, reject disturbances, equitably distribute power among distributed generation units (DGUs), and minimize energy consumption. Regional pole placement ensures welldamped transient responses. Simulation results demonstrate effective management of load perturbations and DGU disconnections, with a comparative analysis against an H∞ controller offering additional insights into performance. © 2025 The Author(s).

关键词： Microgrids

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Improving Common Spatial Patterns in Brain-Computer Interface Using Dynamic Time Warping and EEG Normalization 2

Improving Common Spatial Patterns in Brain-Computer Interfac...

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2nd Edition IEEE International Conference on Metrology for eXtended Reality, Artificial Intelligence and Neural engineering, MetroXRAINE 2023

作者： Mohamed, Mohamed A.A. Mansour, Salem Soulatiantork, Payam Ang, Kai Keng Soon, Phua Kok Arvaneh, Mahnaz University of Sheffield Automatic Control and Systems Engineering Department Sheffield United Kingdom Singapore

ISBN: (纸本)9798350300802

Common spatial patterns (CSP) is widely employed for spatial filtering and feature extraction in electroencephalogram (EEG)-based brain-computer interfaces (BCIs), However, the non-stationary nature of EEG signals can lead to poor estimation of CSP. To address this drawback, this paper proposes a novel algorithm called scaled and warped CSP (SW-CSP). The proposed algorithm enhances the classical CSP by reducing within EEG class non-stationarity across both time and amplitude domains, followed by automatically selecting the most discriminative features. First, the maximum-minimum scaling is applied to align amplitude of each EEG trial to its class average. Next, dynamic time warping (DTW) temporally aligns each scaled EEG trial to its class average. Thereafter, the scaled and warped EEG trials are used to compute the CSP covariance matrices. Finally, the proposed Fisher's score is used to select most discriminative SW-CSP filters. The proposed SW-CSP algorithm is evaluated using two datasets, and compared with the CSP algorithm and the previously proposed DTW-CSP. The results showed that the SW-CSP significantly outperformed both CSP and DTW-CSP (p © 2023 IEEE.

关键词： brain-computer interface common spatial patterns dynamic time warping EEG Fisher's score non-stationarity

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Hybrid offshore wind turbines: control-oriented modeling approaches 6th

Hybrid offshore wind turbines: Control-oriented modeling app...

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6th International Conference on Renewable Energies Offshore, RENEW 2024

作者： Ahmad, I. M’zoughi, F. Aboutalebi, P. Garrido, I. Garrido, A.J. Automatic Control Group—ACG Institute of Research and Development of Processes—IIDP Department of Automatic Control and Systems Engineering Engineering School of Bilbao—EIB/BIE Faculty of Engineering of Bilbao—EIB/BIE University of the Basque Country—UPV/EHU Bilbao Spain

ISBN: (纸本)9781032905570

In the pursuit of sustainable electricity generation from offshore wind and wave energy, the combination of Floating Offshore Wind Turbines (FOWTs) and Oscillating Water Columns (OWCs) has emerged as a promising solution to enhance the working lifespan of this kind of systems. This study introduces a control-focused modeling approach, using empirical data collected from the widely accepted FAST environment, to implement advanced control laws for these integrated platforms. Leveraging Long Short-Term Memory (LSTM) and Artificial Neural Networks (ANN), the research yields predictive models that effectively capture the platform pitch dynamics so as to optimize control strategies. By integrating advanced machine learning techniques, these approaches address the challenges of modeling floating offshore structures in dynamic environments. In this sense, the neuro-estimators developed in this study closely match the original plant results, offering researchers a straightforward way to implement complex control schemes that could hardly be implemented over the original non-linear system. © 2025 The Author(s).

关键词： Offshore wind turbines

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Real-time Tiredness Detection System using Nvidia Jetson Nano and OpenCV 11

Real-time Tiredness Detection System using Nvidia Jetson Nan...

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11th International Conference on Information Technology and Quantitative Management, ITQM 2024

作者： Florian, Nicolae Popescu, Dumitru Hossu, Andrei Department of Automatic Control and Systems Engineering University Politehnica Bucuresti Bucharest060042 Romania Academy of Romanian Scientists Romania

In this paper, we explore how to use a Nvidia Jetson Nano and Python to create a system that detects weariness in a person's face using computer vision and machine learning techniques. The system captures the person's face in real time, preprocesses the picture to cut noise, then detects the face using Haar cascades. Next, using computer vision algorithms, characteristics associated with weariness, such as the eyes, are retrieved. These characteristics are then used to build a machine learning model that can predict weariness in the live stream feed. Lastly, using a graphical user interface, the findings are shown, and the system may be fine-tuned to increase accuracy. This device might be used in applications such as driver monitoring and traffic safety. © 2024 The Authors.

关键词： Graphical user interfaces

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A Predictive control based Scheme for Maximum Power Extraction of PMSG based Wind Turbine systems 32

A Predictive Control based Scheme for Maximum Power Extracti...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Shiravani, Fahimeh Cortajarena, Jose Antonio Alkorta, Patxi Perez, Mikel Gonzalez Barambones, Oscar Basque Country University School of Engineering of Gipuzkoa - EIG/Eibar Department of Automatic Control and Systems Engineering Spain Basque Country University School of Engineering of Gipuzko- EIG/Eibar Department of Electronic Technology Spain Basque Country University School of Engineering of Gipuzkoa-EIG/Eibar Department of Automatic Control and Systems Engineering Spain Basque Country University School of Engineering of Vitoria Department of Automatic Control and Systems Engineering Spain

ISBN: (纸本)9798350399714

In this proposal, a predictive control scheme is considered for PMSG based wind turbine system in order to maximize power extraction. The main goal is to maintain the turbine tip-speed ratio (and consequently the power coefficient) at its optimal point and regulate the PMSG rotor speed in reaction to the variation of wind speed. The control of generator speed is done by employing a generalized predictive controller. This regulator by taking advantage of the predictive feature can prepare the generator to react to the upcoming wind in advance and consequently increases the efficiency of the turbine. Also, it has been demonstrated that this controller enhances the transient response of the system compared to the conventional methods. The proposed controller has been validated through Matlab/Simulink and an experimental test bench. © 2023 IEEE.

关键词： controllers

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Unsupervised Learning-Based Methodology for Detection of Postural Anomalies in Wheelchair Users

Unsupervised Learning-Based Methodology for Detection of Pos...

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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Vermander, Patrick Mancisidor, Aitziber Fortino, Giancarlo Cabanes, Itziar Gravina, Raffaele Department of Automatic Control and System Engineering Bilbao Spain Department of Informatics Modeling Electronics and Systems Engineering Rende Italy

ISBN: (纸本)9798350337020

Postural monitoring in wheelchair users is a topic of growing interest. The detection of changes in the sitting patterns of these patients may serve to detect changes in their functional status and be able to adapt rehabilitation early. For this reason, this paper presents a methodology for the detection of specific postural anomalies that, unlike previous works, adopts unsupervised learning. The proposed methodology involves data dimensionality reduction using Principal Component Analysis, and the application of K-means clustering to group different normal posture states. The anomalies are detected using a threshold approach, where data points that fall outside a certain threshold are considered as anomalies. The results show that the methodology is effective in identifying anomalies with a high degree of accuracy (around 90%). © 2023 IEEE.

关键词： Anomaly detection Kmeans PCA Postural monitoring Wheelchair

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Study of Discrete Analog Filters with Pole Frequency Adjustment Using General Feedback Resistors 26

Study of Discrete Analog Filters with Pole Frequency Adjustm...

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26th International Conference on Digital Signal Processing and its Applications, DSPA 2024

作者： Denisenko, Darya Prokopenko, Nikolay Butyrlagin, Nikolay Ivanov, Yuri Don State Technical University Southern Federal University Department of Scientific Research Department of Automatic Control Systems Rostov-on-Don Russia Don State Technical University Department of Information Systems and Radio Engineering Rostov-on-Don Russia Southern Federal University Department of Automatic Control Systems Rostov-on-Don Russia

ISBN: (纸本)9798350361728

Three new modifications of second-order low-frequency discrete analog filters (DAFs) based on switched capacitors have been developed and studied. A distinctive feature of the DAFs under consideration is the presence of two resistors in the general feedback circuit. This allows, at constant values of the capacitances of the frequency-setting capacitors and a fixed switching frequency of electronic switches, to control the frequency of the DAF pole by changing the resistance ratio of these resistors. The basic equations for the low-pass filter gain at zero frequency, the low-pass filter gain at the pole frequency, as well as formulas for calculating the pole frequency and pole attenuation are given. In the Micro-Cap environment, computer simulation of the proposed modifications of the DAF was performed, which shows that the considered circuit solutions perform the functions of a low-pass filter. © 2024 IEEE.

关键词： Operational amplifiers

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Management of the Traffic Networks Transportation in Supplier-Customers Services by Strategic Games 11

Management of the Traffic Networks Transportation in Supplie...

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11th International Conference on Information Technology and Quantitative Management, ITQM 2024

作者： Bîlbîie, Radu Popescu, Dumitru Dimon, Catalin Department of Automatic Control and Systems Engineering UPB Bucharest Romania Academy of Romanian Scientists Ilfov 3 Bucharest050044 Romania

This paper presents an innovative approach to optimize traffic networks in a supplier-customer system based on specific strategies of game theory. The traffic network is represented as a routing configuration in which the arcs represent various possible roads between supplier and customer entities, each route having an associated transport cost for the product unit. The game structure is defined by a matrix of transport costs between the players, supplier and customer, with their corresponding strategies. Based on these costs, the game matrix is built to which the existing quantities in warehouses are added, respectively the quantities requested by the final customers. By solving the game associated to the transportation traffic network, the different strategies are proposed for choosing the optimal solution. The simulation results confirm the effectiveness of the proposed approach and recommend some performant procedures for solving the game, such as Hurwicz, Laplace and Savage, close to optimal solution. This research opens new directions for management optimization in other domains such as comunication, electrical and administrativ networks. © 2024 The Authors.

关键词： Sales

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CDQKL: Consensus-Based Distributed Quantum Kernel Learning 1

CDQKL: Consensus-Based Distributed Quantum Kernel Learning

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1st International Conference on Quantum Communications, Networking, and Computing, QCNC 2024

作者： Ma, Wenxuan Liu, Mengxiang Deng, Ruilong State Key Laboratory of Industrial Control Technology The College of Control Science and Engineering Zhejiang University Hangzhou310027 China University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (纸本)9798350366778

The field of quantum computing has developed rapidly in recent years due to its promising trend of surpassing traditional machine learning in terms of speed and effectiveness. Quantum kernel learning is one of the paradigms of quantum machine learning, but the training of quantum kernel is time consuming. Therefore, this work makes the first attempt to introduce a consensus-based distributed approach to quantum kernel learning - named CDQKL - that only requires to exchange model parameter information between adjacent nodes while avoiding the need of sharing local training data. Through comparative experimental studies, the advantages of CDQKL in classification accuracy and convergence speed are verified. Considering the popularization of quantum computing cloud service and miniaturization of quantum terminals, the CDQKL adapting to this trend is able to play a vital role in data security, which implies the far-reaching significance of this work. Our code is available at https://***/Leisurivan/CDOKL. © 2024 IEEE.

关键词： Quantum computers

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