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IEEE Workshop on Evolving and Adaptive Intelligent Systems (EAIS)

作者： Morsinaldo Medeiros Thommas Flores Marianne Silva Ivanovitch Silva Postgraduate Program in Electrical and Computer Engineering (PPgEEC) Federal University of Rio Grande do Norte Natal Brazil Federal University of Alagoas Penedo Brazil

ISBN: (数字)9798350366235

ISBN: (纸本)9798350366242

The rapid increase in vehicular sensor data and advances in Internet of Things (IoT) technologies pose a dual challenge and opportunity for real-time traffic management and driver behavior analysis in the domain of Intelligent Transportation Systems (ITS). The current gap lies in effectively processing this data at the network edge, which is critical for timely and efficient decision-making in ITS. Our study proposes a novel, multi-layered, stream-oriented data processing methodology specifically designed for edge computing environments to address this challenge. This approach integrates soft sensors, the Typicality and Eccentricity Data Analytics (TEDA) framework, and an incremental clustering algorithm to detect and classify driver behavior patterns. The emphasis on using low-energy hardware and TinyML techniques is crucial, aiming to optimize processing efficiency while minimizing the environmental impact. To substantiate the efficacy of our methodology, we conducted a practical case study in Natal-RN, Brazil, utilizing the Freematics One + OBD-II microcontroller device for real-world application and validation. This involved two participants and focused on real-time data analysis for driver profile detection. The preliminary results demonstrate a significant potential of our approach in accurately classifying driving behaviors and patterns, offering insights for enhancing vehicle efficiency and reducing fuel consumption. This study fills a critical gap in ITS. It sets the stage for future research in sustainable and adaptive transportation systems, leveraging the power of edge computing and incremental algorithms in real-time data stream processing.

关键词： Data analysis Soft sensors Image edge detection Heuristic algorithms Clustering algorithms Real-time systems Classification algorithms

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Intelligent Behavior Simulation Module for Software Process Elements

Intelligent Behavior Simulation Module for Software Process ...

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Brazilian Symposium on Games and Digital Entertainment (SBGAMES)

作者： Rafael O. Chaves Walter A. Da L. Lobato Emanuel M. Da C. Tavares Sandro R. B. Oliveira Tales C. Miranda Eloi L. Favero Postgraduate Program in Electrical Engineering Instituto de Tecnologia Universidade Federal do Paraná Belem Brazil Postgraduate Program in Computer Science Instituto de Ciências Exatas e Naturais Universidade Federal do Paraná Belem Brazil

Componentization is a Software engineering (SE) strategy successfull in the development of new projects. Mainstream games use components that handle a set of functions elevant to a common aspect of a genre (e.g. real time strategy, first person shooter). However, Artificial Intelligence (AI) components, in spite of their great game play weight in current games, few has been researched and published about. This scenario gets worse when it comes to specific components for SE simulation games. This paper shows the results of the development of an AI component called Intelligent Behavior Simulation Module for Software Process Elements (MSCI-ep) for software process simulators. MSCI-ep objectives are to support and encourage development of this genre of educational games.

关键词： Software Games Artificial intelligence Productivity Computational modeling Mathematical model Mood

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An impedance control modification guaranteeing compliance strictly within preselected spatial limits

An impedance control modification guaranteeing compliance st...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： A. Theodorakopoulos G. A. Rovithakis Z. Doulgeri IKY Fellowships of Excellence for Postgraduate Studies in Greece - Siemens Program Greek State Scholarships Foundation Dept. of Electrical & Computer Engineering Aristotle University of Thessaloniki Greece

In this work a modification of a Cartesian impedance controller is presented. The proposed controller guarantees compliance of the operated manipulator strictly within preselected spatial limits. Specifically, by introducing a nonlinear stiffness term into the control design, the manipulator is prevented from colliding with an explicitly defined hard boundary, like a human being or a fragile object. When operating in spatial regions sufficiently away from the boundary the manipulator behaves as if it were operated via a linear stiffness impedance controller, thus preserving in these regions its compliance and convergence characteristics. A comparative simulation with a linear stiffness impedance controller is performed to verify and clarify the proposed approach.

关键词： Impedance Manipulator dynamics Robot kinematics Force Aerospace electronics

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A Voice-Assisted Approach for Vehicular Data Querying from Automotive IoT-Based Databases

A Voice-Assisted Approach for Vehicular Data Querying from A...

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International Workshop on Secure Internet of Things (SIoT)

作者： Matheus Andrade Esther Wanderley Mariana Azevedo Thaís Medeiros Marianne Silva Ivanovitch Silva Daniel G. Costa Postgraduate Program in Electrical and Computer Engineering (PPgEEC) Federal University of Rio Grande do Norte - Natal Brazil INEGI Faculty of Enzineering University of Porto Porto Portugal

The automotive industry's transformative conver-gence of cutting-edge technologies, such as the Internet of Things (loT), electronic voice assistants, and custom APls, have paved the way for a remarkable array of opportunities to enhance vehicle security while revolutionizing user-car interactions. Actually, when leveraging loT sensors of multiple types and configurations, their produced, collected, and stored real-time data may offer in-depth and comprehensive insights into vehicle information, opening many possibilities when loT-generated databases are created. In this context, the primary goal of this paper is to create a new approach based on the popular Amazon Alexa voice assistant, which would allow facilitated queries of vehicular data from cloud-based databases. For that, a new Alexa service (skill) is created, as well as a custom API, allowing easy access to different types of data previously retrieved from vehicular sensors and properly stored. Doing so, the implemented skill indirectly processes data from loT sensors through the custom API, enabling users to access vital vehicular information using intuitive voice commands, remotely. A case study in a real scenario is conducted to validate and confirm the feasibility of real-time vehicle information access, showcasing the benefits of the proposed approach when combined with other solutions in a macro vehicular-centric loT ecosystem.

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A Framework for Efficient Communication in IoT Applications in the Automotive Industry with OBD-II Edge

A Framework for Efficient Communication in IoT Applications ...

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International Workshop on Secure Internet of Things (SIoT)

作者： Morsinaldo Medeiros Mariana Azevedo Miguel Amaral Carlos M. D. Viegas Marianne Silva Ivanovitch Silva Daniel G. Costa Postgraduate Program in Electrical and Computer Engineering (PPgEEC) Federal University of Rio Grande do Norte - Natal Brazil INEGI Faculty of Enzineering University of Porto Porto Portugal

Driven by the Internet of Things (IoT) revolution, the automotive industry is transforming itself significantly. Ve-hicles, once merely transportation machines, have now evolved into complex networks of sensors and actuators. This evolution heralds an era of intelligent and connected vehicles that collect and analyze real-time data, benefiting various sectors. In response to this scenario, this paper introduces a framework for collecting and processing vehicular information, leveraging the capabilities of Edge Computing. The framework integrates the OBD-II Edge (Freematics ONE+) technology for efficient data acquisition, harnessing the power of Edge Computing to enable real-time data processing and immediate response at the network's edge. Additionally, Node-RED and Kafka technologies are utilized for efficient data handling and routing, while the Timescale database ensures optimized storage of time-series data. Finally, the Streamlit tool provides an intuitive data visualization interface, enhancing data analysis and decision-making processes. Evaluated through a real-case scenario study, this proposal has proven viable and effective, providing analyses that directly contribute to vehicular safety and preventive maintenance, while also enhancing logistical operations in the field.

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Evaluating the Influence of Phase-Locked Loops on the Response of Grid-Following Inverter-Based Resources to Interconnection Transmission Line Faults

Evaluating the Influence of Phase-Locked Loops on the Respon...

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Workshop on Communication Networks and Power Systems (WCNPS)

作者： Pedro Henrique de Morais Martins Luciano Sales Barros Felipe Vigolvino Lopes Postgraduate Program in Renewable Energies Federal University of Paraíba Department of Computer Systems Federal University of Paraíba Department of Electrical Engineering Federal University of Paraíba

ISBN: (数字)9798331507152

ISBN: (纸本)9798331507169

In this paper, the influence of different Phase-Locked Loops (PLLs) on the fault response of a grid-following (GFL) Inverter-Based Resource (IBR) is evaluated. The analyzed IBR represents a wind power plant with rated power equal to 100 MVA, being composed of 50 turbines with 2 MVA each, whose controls follow the Brazilian grid code. Two PLL models are taken into account to conduct the proposed studies, which include the analysis of voltage and frequency estimated by each PLL, and currents injected into the IBR interconnection transmission line. The Synchronous Reference Frame (SRF) PLL and the Quadrature Signal Generator-based Second-Order Generalized Integrator (QSG-SOGI) PLL are considered, assessing their influence under different transmission line fault scenarios. The obtained results indicate that the PLL can present severe instabilities during faults, which can be more or less critical depending on the fault type and on the PLL type. Indeed, the results reveal that different PLLs can result in distinct behaviors of currents injected into the interconnection line, raising the importance of knowing the PLL structures when studies on IBR fault responses are of interest.

关键词： Power transmission lines Grid following Conferences Voltage Wind power generation Power system stability Frequency estimation Phase locked loops Inverter-based resource Turbines

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N-Sequence RSNS Redundancy Analysis

N-Sequence RSNS Redundancy Analysis

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IEEE International Symposium on Information Theory

作者： Brian L. Luke Phillip. E. Pace Program Development Team Navy Information Operations Command Suitland Fort Meade MD USA Department of Electrical and Computer Engineering Naval Postgraduate School Monterrey CA USA

ISBN: (纸本)142440505X

Without dispute, symmetrical folding waveforms are the most common type of waveform in engineering science (e.g., cosine, sine). symmetrical number systems (SNS) have been formed to extract the maximum amount of information from symmetrically folded waveforms. The robust symmetrical number system (RSNS) is formed using N ges 2 sequences and ensures that two successive RSNS vectors differ by only one digit. This Gray-code property reduces the possibility of encoding errors and makes the RSNS useful in applications such as folding analog-to-digital converters, direction finding antenna architectures and photonic processors. This paper determines the length of combined sequences that contain no ambiguities (Mcirc) which we call the RSNS dynamic range. The position of M is also derived. We first extend our two-sequence results to develop Mcirc for a three-sequence RSNS with moduli of the form 2 r - 1, 2 r , 2 r + 1. We then extend the results to solving the N-channel RSNS redundancy locations in general

关键词： Dynamic range Redundancy Information analysis Military computing Data mining Robustness Encoding Analog-digital conversion Directive antennas Reflective binary codes

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Shoulder Flexion Pre-Movement Recognition Through Subject-Specific Brain Regions to Command an Upper Limb Exoskeleton

Shoulder Flexion Pre-Movement Recognition Through Subject-Sp...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Yunier Prieur-Coloma Denis Delisle-Rodríguez Leondry Mayeta-Revilla Dharmendra Gurve Ramón A. Reinoso-Leblanch Alberto López-Delis Teodiano Bastos Sri Krishnan Adson F. da Rocha Center of Medical Biophysics University of Oriente Cuba Postgraduate Program in Electrical Engineering Federal University of Espirito Santo Brazil Department of Biomedical Engineering University of Oriente Cuba Department of Electrical Computer and Biomedical Engineering Ryerson University Toronto Canada Department of Electrical Engineering University of Brasilia Brasilia Brasil

ISBN: (数字)9781728119908

ISBN: (纸本)9781728119915

This work presents two brain-computer interfaces (BCIs) for shoulder pre-movement recognition using: 1) manual strategy for Electroencephalography (EEG) channels selection, and 2) subject-specific channels selection by applying non-negative factorization matrix (NMF). Besides, the proposed BCIs compute spatial features extracted from filtered EEG signals through Riemannian covariance matrices and a linear discriminant analysis (LDA) to discriminate both shoulder pre-movement and rest states. We studied on twenty-one healthy subjects different frequency ranges looking the best frequency band for shoulder pre-movement recognition. As a result, our BCI located automatically EEG channels on the contralateral moved limb, and enhancing the pre-movement recognition (ACC = 71.39 ± 12.68%, κ = 0.43 ± 0.25%). The ability of the proposed BCIs to select specific EEG locations more cortically related to the moved limb could benefit the neuro-rehabilitation process.

关键词： Electroencephalography Manuals Covariance matrices Shoulder Frequency measurement Exoskeletons Brain-computer interfaces

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Delay tolerant transport protocol - DTTP

Delay tolerant transport protocol - DTTP

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International Global Information Infrastructure Symposium (GIIS)

作者： Fabio Luiz P. Albini Anelise Munaretto Mauro Fonseca Graduate School of Electrical Engineering and Computer Science (CPGEI) Federal Technological University of Parana (UTFPR) Curitiba Brazil Postgraduate Program in Computer Science (PPGIa) Pontifical Catholic University of Parana (PUCPR) Curitiba Brazil

This paper consists in a novel transport protocol description for Delay-Tolerant Networks and Disruption Tolerant Networks (both DTN). This protocol was designed to offer a better information delivery rate in DTNs scenarios. Fountain codes techniques are used to achieve our needs. The performance results were tested taking into account the hosts buffer size, the TTL (Time To Live) of the messages and the amount of redundant information generated into the network. A better delivery rate and performance were achieved using the proposed protocol.

关键词： Transport protocols Data models Delay Error correction codes Educational institutions Process control

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A Novel Ensemble XGBoost and Deep Q-Network for Pregnancy Risk Prediction on Multi-Class Imbalanced Datasets

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ICT Express 2025年

作者： Kurnianingsih Sou Nobukawa Melyana Nurul Widyawati Cipta Pramana Nurseno Bayu Aji Afandi Nur Aziz Thohari Dwiana Hendrawati Eri Sato-Shimokawara Naoyuki Kubota Department of Electrical Engineering Politeknik Negeri Semarang H. Soedarto Tembalang Semarang 50275 Central Java Indonesia Department of Computer Science Chiba Institute of Technology 2-17-1 Tsudanuma Narashino 275-0016 Chiba Japan Department of Postgraduate Program Poltekkes Kemenkes Semarang Jl. Tirto Agung Pedalangan Kecamatan Banyumanik Semarang 50268 Central Java Indonesia Department of Obstetrics and Gynecology KRMT Wongsonegoro Hospital Jl. Tembalang Semarang 50272 Central Java Indonesia Department of Mechanical Engineering Politeknik Negeri Semarang H. Soedarto Tembalang Semarang 50275 Central Java Indonesia Faculty of Systems Design Tokyo Metropolitan University Tokyo 1910065 Japan

Addressing imbalanced data is essential for accurate prediction. We propose a novel ensemble method of XGBoost and deep Q-learning networks (DQN) for pregnancy risk prediction. First, we train the majority class utilizing XGBoost. We subsequently utilize DQN to train the minority class into binary classifications. Finally, we use the trained models from DQN and XGBoost in ensemble learning to generate the final classification results. The XGBoost-DQN model achieves high performance with 0.9819 in precision, recall, F1-score, and accuracy, outperforming several baseline classifiers on private data from 5,313 pregnant women in Indonesia and showing superior results on public datasets.

关键词： Imbalanced dataset ensemble learning XGBoost Tree Deep Q-Network pregnancy risk

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