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9th IEEE Smart World Congress, SWC 2023

作者： Rodriguez-Arozamena, Mario Aranguren-Mendieta, Inigo Perez, Joshue Zubizarreta, Asier Tecnalia Basque Research and Technology Alliance Bilbao Derio Spain Basque Research and Technology Alliance Industry and Mobility Unit Tecnalia Derio Spain Dept. of Automatic Control and Systems Engineering Bilbao Spain

ISBN: (纸本)9798350319804

Precise localization is essential for the operation of Connected and Automated Vehicles (CAVs) in urban scenarios. Camera and LiDAR-based solutions are currently used in some of the CAVs around the world, but they entail an expensive performance in terms of computational time and economic cost. Due to this, Global Navigation Satellite System (GNSS) based solutions remains the preferred solution for positioning Automated Vehicles in different Operational Design Domains (ODDs). Although several improvements in system reliability have been made recently, in case of positioning failures most of the architectures rely on system redundancy or automation disengagements to achieve minimal risk conditions. This paper presents a fail-safe decision architecture for mitigating positioning failures of automated vehicles in urban scenarios. The proposed architecture utilizes a combination of sensor fusion localization and decision-making modules to ensure the safe and efficient operation of the vehicle in the event of a positioning failure. The proposed approach is evaluated through simulation in a representative urban scenario and is shown to effectively handle positioning failures, improving the localization accuracy provided by each information source. © 2023 IEEE.

关键词： automated driving fail-safe operation fallback strategy positioning failure safe state

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BIOPHYSICAL SIGNAL PROCESSING FOR automatic ANXIETY CLASSIFICATION IN A VIRTUAL REALITY EXPOSURE THERAPY SYSTEM

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and computer Science 2024年第2期86卷 73-84页

作者： Jinga, Nicolae Petrescu, Cătălin-Dumitru Mitruț, Oana Moldoveanu, Alin Moldoveanu, Florica Petrescu, Livia Dept. of Computer Science National University of Science and Technology POLITEHNICA Bucharest Romania Dept. of Automatic Control and Systems Engineering National University of Science and Technology POLITEHNICA Bucharest Romania Faculty of Biology University of Bucharest Romania

This paper presents a signal processing framework for automatic anxiety level classification in a virtual reality exposure therapy system. Two types of biophysical data (heart rate and electrodermal activity) were recorded, pre-processed and passed through a feature extraction procedure that provided input for the real-time anxiety level classification algorithm. We showcase the mathematical and engineering techniques behind the procedures and conclude with the challenges encountered in our research and future development ideas. The proposed method provides a good estimate of the level of anxiety while having at the same time a reduced level of complexity, allowing implementation on equipment with limited computing resources. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Classification (of information)

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Efficient Deep Learning Models Based on Tension Techniques for Sign Language Recognition

SSRN

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SSRN 2023年

作者： Attia, Nehal F. Faheem Said Ahmed, Mohamed T. Alshewimy, Mahmoud A.M. Computer and Automatic Control Dept. Faculty of Engineering Tanta University Tanta Egypt

Among the various ways of self-expression and communication between people, communication by speaking prevails. Speech presents a significant challenge for some disabled people, such as the deaf, hearing impaired, wordless, and dumb persons. Therefore, these people rely on the use of sign language to interact with others. Sign language is a system of movements and visual messages that ensure the integration of these individuals into groups that communicate vocally. On the other side, it is necessary to understand the gestures and linguistic semantics of these individuals. The main objective of this study is to establish a new model that enhances the performance of the existing paradigms in use for the recognition of American Sign Language (ASL). Therefore, three enhanced deep-learning models of YOLOv5 for recognizing the alphabetic and numeric information conveyed by hand motions are presented in this paper. These models depend on using different attention approaches. The suggested models were evaluated using the MU HandImages ASL dataset. The proposed models yielded superior results compared to those achieved by the initial version of YOLOv5. The modified models have reached their maximum accuracy of 98.9%, maximum recall of 97.5%, maximum mAP 0.5 of 99.2%, and maximum mAP 0.5:0.95 of 98.9%. © 2023, The Authors. All rights reserved.

关键词： computer vision

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Deep Learning-Based Retinal Blood Vessel Segmentation Using U-Net Architecture

Deep Learning-Based Retinal Blood Vessel Segmentation Using ...

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E-Health and Bioengineering Conference (EHB)

作者： Ligia-Gabriela Boazu Marian-Alexandru Petraru Otilia Zvorișteanu Dept. of Computer Science and Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iași Iași Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Retinal blood vessel segmentation is an essential component in the diagnosis and monitoring of various ophthalmological conditions, such as diabetic retinopathy, glaucoma or macular degeneration, providing valuable information about the state of blood vessels and ocular blood circulation. Traditional methods for segmenting blood vessels from retinal images present certain limitations in terms of accuracy and robustness, especially under variable lighting conditions, the presence of artifacts or low-quality images. However, current techniques based on convolutional neural networks have demonstrated the ability to achieve precise and robust segmentations in a variety of conditions, outperforming traditional methods. Nevertheless, neural networks face challenges regarding the limited availability of retinal image datasets necessary for training and evaluating these solutions. In this paper we describe a solution for retinal blood vessel segmentation using the U-Net architecture. This neural network achieves impressive results even with very small datasets, demonstrating the efficiency and robustness of the U-Net architecture for retinal blood vessel segmentation.

关键词： Training Macular degeneration Image segmentation Neural networks Blood vessels Network architecture Retina Robustness Monitoring Biomedical imaging

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Enhancing Learning and Therapy for Children with Autism: Innovative Activities with the NAO Robot

Enhancing Learning and Therapy for Children with Autism: Inn...

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E-Health and Bioengineering Conference (EHB)

作者： Iustina-Bianca Bulai Otilia Zvorişteanu Dept. of Computer Science and Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iaşi Iaşi Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Worldwide, autism affects 1 in 100 children, with diagnoses steadily rising since the 2000s. Romania lacks official statistics on autism prevalence, but global estimates suggest similarity. Children with autism struggle with social interactions and verbal communication, prompting interest in social robots for therapy and education. Tailored robot-assisted sessions offer potential for cognitive development, vocabulary enhancement, social interaction, and behavioral stimulation like concentration and attention. The NAO robot's user-friendly design, technical capabilities, and integrated features make it well-suited for these purposes. This paper presents activities that exemplify the concept of “learning through play,” allowing children to engage in exploration, experimentation, and effective learning in an enjoyable manner.

关键词： Autism Vocabulary Hospitals Social robots Education Biomedical engineering

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Features of Space Vector Pulse Width Modulation in 5-phases Cascaded High Voltage Converters 5

Features of Space Vector Pulse Width Modulation in 5-phases ...

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5th IEEE KhPI Week on Advanced Technology, KhPIWeek 2024

作者： Busher, Victor Chornyi, Oleksii Tytiuk, Valerii Glazeva, Oksana Kuznetsov, Vitaliy Dept. of Electrical Engineering and Electronics National University "Odessa Maritime Academy" Odessa Ukraine Institute of Electromechanics Energy Saving and Automatic Control Systems Kremenchuk Mykhailo Ostrohradskyi National University Kremenchuk Ukraine Kryvyi Rih National University Kryvyi Rih Ukraine Dept. of the electrical engineering Ukrainian State University of Science and Technologies Dnipro Ukraine

ISBN: (纸本)9798350384499

The purpose of this work is to analyze the capabilities of space-vector pulse-width modulation when controlling a 5-phase high-voltage cascade frequency converter in normal mode and several types of emergency situations. Taking into account the large number of controlled power transistors, an asynchronous modulation method is proposed, based on calculating the amplitude values of individual phases at each time based on the duty cycle of space vectors, which allows the control system to use independent switching in each phase. In emergency modes, when individual H-bridges are damaged, it is proposed to use the balanced space vectors method, which ensures the symmetry of the electromagnetic field in the event of a short circuit of both individual cascades and one or two phases of the inverter. Methodology. We use a mathematical and geometric interpretation of variable amplitude space vectors when projecting voltages onto a symmetrical 5-phase load. Results. Analysis of the 1st harmonic of phase voltages showed that the use of the space vector modulation method in the normal operating mode of a 5-phase converter makes it possible to increase the utilization factor of DC voltage sources by 23.1% (instead of 15.6% for a 3-phase converter). If individual H-bridges fail and the voltages in the load phases are balanced, the utilization factor may decrease, but in any case it will remain greater than 1. In this case, the higher harmonics, despite significant distortions in the shape of the phase voltages, are mutually compensated in the electromagnetic field of the load, as evidenced by absence of pulsations and shocks on the graphs of transient processes of the electromagnetic torque of the engine. Balancing of the electromagnetic field in the load is maintained even if one or two phases of the inverter are short-circuited. This significantly increases the survivability of the electric drive, which is especially important in critical mechanisms and technological processes,

关键词： Electric motors

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Ontological Analysis of the Digital Crime Conceptual Model 18

Ontological Analysis of the Digital Crime Conceptual Model

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18th IEEE International Conference on computer Science and Information Technologies, CSIT 2023

作者： Vlasenko, Lidiia Lutska, Nataliia Zaiets, Nataliia Lysenko, Vitaliy State University of Trade and Economics dept. of Software Engineering and Cyber Security Kyiv Ukraine National University of Food Technologies dept. of Automation and Computer Technologies of Control Systems Kyiv Ukraine National University of Life and Environmental Sciences of Ukraine dept. of Automation and Robotic Systems Kyiv Ukraine

ISBN: (纸本)9798350360462

A conceptual ontological model of Digital Crime has been developed, consisting of five non-empty classes. Identification and classification were carried out according to the experience of domestic and foreign experts. The central place of the model is occupied by objects of the Digital Crime class, which have their own attributes and are connected by various links with other objects. Objects of some classes are filled in by users, others are formed by knowledge engineers. Based on the ontological analysis, SWRL-rules are constructed that automatically form links between objects of the custom classes Digital crime and Digital evidence with objects of the Type of crime and Criminal Liability classes. The last class contains articles of the Criminal Code of Ukraine on criminal liability for digital crimes. The ontological model is developed taking into account possible requests to it. Such queries can be formed on the basis of direct relationships between human and automatic concepts. And also contain logical chains to concepts that do not contain an explicit link in the ontology. It is assumed that the model can be expanded and supplemented. The ontological model of Digital Crime can be used to share information, develop new systems and applications, improve information retrieval and ensure its accordance. © 2023 IEEE.

关键词： Ontology

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Process-Model-Free Design of MPC via a Reference-Model-Based PI controller for the Gas Turbine 9

Process-Model-Free Design of MPC via a Reference-Model-Based...

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9th International Conference on Electrical engineering, control and Robotics, EECR 2023

作者： Shi, Gengjin Dai, Chengbo Ma, Miaomiao Li, Donghai Ding, Yanjun Tsinghua University State Key Lab of Power Systems Dept. of Energy & Power Engineering Beijing China North China Electric Power University School of Control & Computer Engineering Beijing China

ISBN: (纸本)9781665491204

Model predictive control (MPC) is a modern advanced control strategy which has great reputation because of its excellent reference tracking performance and the ability to deal with process constraints, time delay and multivariable problems. However, the gas turbine is difficult to model accurately and unmeasurable disturbances are unavoidable, which limits the application of MPC to the gas turbine. To solve these problems, a process-model-free design method for MPC via a reference-model (RM)-based proportional-integral (PI) controller-desired dynamic equational (DDE)-PI controller (MPC-DDE) is proposed in this paper. The DDE-PI provides the design model for the MPC and handle with unmeasurable disturbances while MPC provides a rolling optimized set point for DDE-PI. Simulation results illustrate the superiorities of the proposed hierarchical control strategy in reference tracking, disturbance rejection and robustness, which indicates the promising prospect of practical application of MPC-DDE to the gas turbine. © 2023 IEEE.

关键词： Model predictive control

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Data-driven modeling of heat pumps and thermal storage units for MPC

Data-driven modeling of heat pumps and thermal storage units...

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2023 International Conference on the Built Environment in Transition, CISBAT 2023

作者： Brandes, M. Cai, H. Vivian, J. Croci, L. Heer, P. Smith, R. Urban Energy Systems Laboratory Empa Dübendorf Switzerland Dept. of Industrial Engineering University of Padova Padua Italy Dept. of Power System Development Ricerca Sistema Energetico SpA Milan Italy Automatic Control Laboratory Department of Electrical Engineering and Information Technology ETH Zurich Switzerland

Heat pumps can play a crucial role in the European energy strategy 2050, which aims to achieve net-zero greenhouse gas emissions. When coupled with thermal energy storage and integrated with advanced control strategies, heat pump operation can be optimized to reduce carbon footprint and respond to the needs of system operators. However, to scale in a multitude of buildings, the transferability of the modeling into heterogeneous systems is crucial. In this paper, two different interpretable linear models, a hybrid (grey-box) and a fully data-driven (black-box) model are investigated. Specifically, two regression-based identification methods (SINDYc and DMDc) are used for dynamic models and the LASSO regression is used for static models. The transferability of the approach is evaluated using two real-world facilities with heterogeneous sizing and configuration. The results show a similar simulation performance for both cases with a maximum normalized RMSE of 0.41 and 0.60, respectively. This confirms the transferability of the approach that is necessary for large-scale implementation. © 2023 Institute of Physics Publishing. All rights reserved.

关键词： Carbon footprint

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Forecasting of Monkeypox Cases Using Optimized SARIMAX Based Model 3

Forecasting of Monkeypox Cases Using Optimized SARIMAX Based...

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3rd IEEE International Conference on Electronic engineering, ICEEM 2023

作者： Elshabrawy, Mahmoud Eid, Marwa M. Abdelhamid, Abdelaziz A. El-Kenawy, El-Sayed M. Ibrahim, Abdelhameed Delta Higher Institute of Engineering and Technology Dept. of Communications & Electronics Mansoura Egypt Delta University for Science and Technology Faculty of Artificial Intelligence Mansoura35111 Egypt Ain Shams University Faculty of Computer and Information Sciences Dep. of Computer Science Cairo Egypt University Mansoura Faculty of Engineering Computer Engineering and Control Systems Dept. Egypt

ISBN: (纸本)9798350323511

This study presents a dipper-throated-based ant colony optimization (DTACO) with the Seasonal Auto-Regressive Integrated Moving Average with eXogenous factor (SARIMAX) model (DTACO+SARIMAX) to forecast monkeypox cases. The work optimizes the SARIMAX model using grid search cross-validation and fine-tunes its hyperparameters using DTACO to improve prediction accuracy. The suggested model's consistency and accuracy are considerable compared to previous studies. Comparisons with state-of-the-art models validate the proposed model's predictions. DTACO+SARIMAX can be used to control disease and monitor monkeypox. Healthcare organizations and governments can better manage and track the pandemic's course by offering accurate predictions, reducing public panic, and enabling effective pandemic planning. The Analysis of Variance (ANOVA) and Wilcoxon signed-rank tests are conducted on the proposed DTACO-SARIMAX model and compared models. © 2023 IEEE.

关键词： Ant colony optimization

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