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14th IEEE International Conference on Cognitive Infocommunications, CogInfoCom 2023

作者： Tóth, Bálint Torma, Szabolcs Nagy, Ákos Szegletes, Luca Department of Measurement and Information Systems Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary

ISBN: (纸本)9798350325652

Blood pressure is one of the most vital signals characterizing the health status of the human body. Based on this physiological data, many current and future diseases can be detected. Therefore, having a device that can continuously measure blood pressure without a cuff or medical intervention would be highly beneficial. This study aims to investigate noninvasive blood pressure measurement with the help of a low-power microcontroller, namely STM32F446RE. These measuring methods are based on deep neural networks and utilize externally measured photoplethysmography (PPG) and electrocardiogram (ECG) signals. The performance of the proposed models is compared to similar solutions from the literature and inspected for memory usage and runtime. The results of this work show that a convolutional layer-based model can be used for proper blood pressure estimation in such an energy-efficient device. © 2023 IEEE.

关键词： Blood pressure

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Comparison of optimization algorithms for installation error calibration of accelerometer arrays 23

Comparison of optimization algorithms for installation error...

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23rd IEEE International Symposium on Computational Intelligence and informatics, CINTI 2023

作者： Pesti, Richard Sarcevic, Peter Csik, Dominik Nagy, Istvan Odry, Akos Óbuda University Doctoral School of Applied Informatics and Applied Mathematics Budapest Hungary University of Szeged Department of Mechatronics and Automation Szeged Hungary Óbuda University Bánki Donát Faculty of Mechanical and Safety Engineering Budapest Hungary

ISBN: (纸本)9798350342949

Accelerometers play a crucial role in localization problems, but their accuracy depends on the precision of the calibration process. In this paper, a comparison of optimization algorithms is presented within the scope of between sensor error calibration. The Particle Swarm optimization (PSO) and Genetic Algorithm (GA) are proposed for the problem, and tested in three different setups. Moreover, the MATLAB built-in fmincon minimization algorithm is also evaluated for calibration parameter estimation. A custom fitness function is proposed to obtain the between sensor misalignment and bias errors, for two accelerometers. The analysis highlights that the algorithms can successfully determine the between sensor error parameters. The conducted comparison shows that fmincon reached an outstanding speed in terms of convergency, but in overall PSO has produced better results compared to GA and fmincon. PSO is more suitable for the calibration problem because of its robustness and stability characteristics. © 2023 IEEE.

关键词： Calibration

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Peak Current Mode control for Grid-Connected Energy Storage Inverters

Renewable Energy and Power Quality Journal

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Renewable Energy and Power Quality Journal 2024年第3期22卷 132-136页

作者： Stranyóczky, László Futó, András Veréb, Szabolcs Varjasi, István Sütő, Zoltán Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3 BudapestH-1111 Hungary

Nowadays, three-phase inverters are playing an increasingly important role in various applications, such as drives, solar systems, energy storage systems. The commonly used PI current control method in the d-q coordinate system satisfies the requirements of most of the cases. However, in some specific applications, such as a grid-connected inverter for an energy storage system, the PI controller response time may not be sufficient to meet the criteria. This paper describes the application of the PCMC (Peak Current Mode control) control technique, which is commonly used for DC-DC converters, and applies it to the case of three-phase two-level inverters. Advantages and disadvantages of PCMC compared to a conventional PI control solution are presented, and the performance of the two control techniques is compared for a grid connected energy storage inverter. © 2024, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

关键词： Energy storage

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Assessing Temperature Sensitivity and Ring Oscillator Count Impact on Configurable Ring Oscillator PUF Performance

Assessing Temperature Sensitivity and Ring Oscillator Count ...

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Mediterranean Conference on Embedded Computing (MECO)

作者： Husam Kareem Oliver Krammer Dmitriy Dunaev Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary Department of Electronics Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary

ISBN: (数字)9798350387568

ISBN: (纸本)9798350387575

Physically Unclonable Functions (PUFs) have been introduced as highly promising hardware primitives for key-based security applications. A PUF can be thought of as a hardware fingerprint that is able to produce a device-specific key for utilization in applications involving device identification and cryptographic key-based security. Among various PUF approaches, the ring oscillator (RO) PUF stands out as the most common PUF design due to its simple implementation and high-performance features. However, RO-PUFs are often classified as weak PUFs due to their limited input-output combinations, commonly referred to as challenge-response pairs within the scope of PUFs. Increasing the CRPs size of traditional RO-PUF results in a proportional growth in the hardware requirements for the RO-PUF design. This correlation arises from the linear relationship between the CRPs size and the hardware resources necessary for the RO-PUF design. Configurable RO-PUF emerged as a solution that expands the CRPs size without a substantial hardware increase. This study evaluates the performance reliability of CRO-PUF across various temperatures. Additionally, we explore the impact of altering the ring oscillators count on the CRO-PUF's performance.

关键词： Ring oscillators Temperature sensors Embedded computing Sensitivity Fingerprint recognition Reliability engineering Physical unclonable function

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Unleashing the Full Potential: Increasing the Bit Configuration Options in Configurable Ring Oscillator PUF

Unleashing the Full Potential: Increasing the Bit Configurat...

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Mediterranean Electrotechnical Conference (MELECON)

ISBN: (数字)9798350387025

ISBN: (纸本)9798350387032

Physically unclonable functions (PUFs) are essential primitives for enhancing hardware security, leveraging the variations in physical characteristics of integrated circuits (ICs) that happen during the manufacturing process. Among various PUF designs, the Ring Oscillator (RO) PUF offers design simplicity and high performance. However, RO-PUFs have been limited in their input-output combinations or what is referred to as challenge-response pairs (CRPs) within the scope of PUFs, classifying them as weak PUFs. Consequently, increasing the CRPs size of the RO-PUF will result in an enhancement of the PUF's overall security attributes. Increasing the CRPs size of a RO-PUF can be achieved through two main methods. Firstly, by increasing the number of ring oscillators in the design which leads to greater hardware demands. Secondly, configurability can be introduced into the individual ring oscillators of the RO-PUF without imposing a substantial demand on hardware resources. Therefore, this paper utilizes the configurability approach to maximize the size of the CRPs set. The evaluation process conducted in this study demonstrates that the proposed design provides excellent results across several performance metrics.

关键词： Ring oscillators Measurement Integrated circuits Electric potential Manufacturing processes Hardware security Artificial neural networks

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Real-time Pricing Mechanism for V2G Using Distributed Bilevel Optimization 63

Real-time Pricing Mechanism for V2G Using Distributed Bileve...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： You, Jiawei Dai, Xinliang Jiang, Yuning Yin, Haoyu Shi, Yuanming Jones, Colin N. ShanghaiTech University School of Information Science and Technology China Epfl Switzerland Karlsruhe Institute of Technology Institute for Automation and Applied Informatics Germany Epfl Automatic Control Laboratory Switzerland Washington University in St. Louis Department of Electrical and Systems Engineering United States

ISBN: (纸本)9798350316339

This paper explores the impact of the burgeoning electric vehicle (EV) presence on distribution grid operations, highlighting the challenges they present to conventional pricing strategies due to their dual role as power consumers and suppliers, coupled with their energy storage capabilities. We propose an advanced real-time pricing model for the electricity market, employing a novel distributed bilevel optimization framework. This framework distinguishes between the distribution system operator (DSO) at the upper level and the EVs at the lower level, each aiming to optimize profit margins. The optimization includes power flow constraints at the upper level to ensure efficient operation within safe system limits, while model predictive control (MPC) is used to optimize lower-level EV responses. Additionally, we provide a rigorous convergence analysis of the proposed bilevel optimization method. Detailed convergence studies and simulation results demonstrate the effectiveness and superiority of the proposed algorithm. © 2024 IEEE.

关键词： Predictive control systems

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Ripple current control for single phase-shift dual active bridge converters

Renewable Energy and Power Quality Journal

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Renewable Energy and Power Quality Journal 2024年第3期22卷 76-84页

作者： Veréb, Sz. Stranyóczky, L. Sütő, Z. Balogh, A. Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Műegyetem rkp. 3. BudapestH-1111 Hungary

Nowadays, the need for isolated bidirectional DC/DC converters is growing. In these types of equipment, the dual active bridge topology is widespread, where mostly the transformer leakage inductance value determines its dynamic behavior. Voltage imbalance between the primary and secondary side results in unwanted excessive transformer peak current if the leakage inductance is low, thus limiting the load transient response of the converter. In this paper, a ripple current control method is pre-sented, which reduces the transformer peak current to its minimal level, furthermore, allows the magnetizing current components to be distributed between the primary and secondary sides in an ar-bitrary proportion. The proposed control was tested in HIL simulation and on a real 360kW dual active bridge converter. Based on the results the current stress on semiconductors and DC capac-itors were reduced while the utilization and the efficiency of the converter were increased. © 2024, European Association for the Development of Renewable Energy, Environment and Power Quality (EA4EPQ). All rights reserved.

关键词： Capacitor bank

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Expression recognition based on convolutional difference contextual feature fusion

Expression recognition based on convolutional difference con...

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2022 International Conference on Electronic Information engineering and Computer Science, EIECS 2022

作者： Lu, Shengfu Yang, Chuang Li, Mi Kang, Jiaming Faculty of Information Technology Beijing University of Technology Beijing International Collaboration Base on Brain Informatics and Wisdom Services Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing China Department of Automation Faculty of Information Technology Beijing University of Technology Beijing China Department of Automation Faculty of Information Technology Beijing China

ISBN: (纸本)9781510663312

Facial expression recognition has always been a focus of study in emotion computing. With the aim of solving the problem that previous facial expression recognition studies are susceptible to individual differences and background noise, as well as the loss of facial expression features in deep networks of deep convolutional networks, we propose a facial expression method based on convolutional difference contextual feature fusion. The convolutional difference module can carry out difference operation between emotional image and neutral image in the input image, eliminate individual difference and background noise in expression features and improve the accuracy and generalization of the network. Finally, convolutional difference and contextual features are combined to improve the accuracy of the network further. Experiment results of 4 public facial expression datasets illustrate that compared with the existing facial expression recognition methods, this method has higher accuracy, can extract facial expression features more effectively, and has a better generalization ability. © 2023 SPIE.

关键词： Convolutional neural networks

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Diffusion Probabilistic Model Based Face Anonymization in Embedded Environments

Diffusion Probabilistic Model Based Face Anonymization in Em...

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International Conference on Cognitive Infocommunications (CogInfoCom)

作者： Balázs Tibor Morvay Bálint Béres Szabolcs Torma Luca Szegletes Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economic Budapest Hungary

Computer vision systems depend on vast and diverse datasets to achieve optimal performance. However, in scenarios where data collection involves personal identifiable information, privacy-protecting legislation can impede the acquisition process. To address this challenge, we present a novel face anonymization pipeline capable of running on embedded platforms. The proposed methodology combines denoising diffusion probabilistic models (DDPMs) and advanced image super-resolution techniques, such as DFDNet and ESPCN, to achieve high-quality anonymized facial images while preserving crucial facial keypoint locations. We conduct a comprehensive evaluation of the pipeline's performance, encompassing image quality, keypoint precision, and efficiency on two popular single-board computers, namely the Nvidia Jetson Nano and the Raspberry Pi 4B. The source code is available at https://***/balazsmorv/facediffusion.

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Machine Learning Vulnerability Assessment of Ring Oscillator Physical Unclonable Functions

Machine Learning Vulnerability Assessment of Ring Oscillator...

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International Conference on control, automation and Diagnosis (ICCAD)

作者： Husam Kareem Dmitriy Dunaev Department of Automation and Applied Informatics Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary

Devices authentication and cryptographic keys production techniques are implemented in various security applications. Because of its ability to generate unique, unclonable, and unpredictable cryptographic keys, physically unclonable functions (PUFs) have been utilized in various hardware security applications. However, PUFs can be vulnerable to adversary attacks like machine learning (ML)-based modeling attacks. Input-output combinations of PUFs are called challenge-response pairs (CRPs). This article provides a vulnerability assessment of three recent Ring Oscillator (RO) PUFs approaches against ML modeling attacks. Assuming that adversary obtains part of the RO-PUF CRPs, and they can be used to predict the unrevealed CRPs. The article has a secondary objective to assess the impact of aging on the tested RO-PUF approaches in regenerating the same response.

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