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CPSS Transactions on Power Electronics and Applications 2021年第3期6卷 227-234页

作者： Gong, Cheng Sou, Wai-Kit Lam, Chi-Seng State Key Laboratory of Analog and Mixed-Signal VLSI University of Macau Macao 999078 China also with the Institute of Microelectronics University of Macau Macao 999078 China and also with the Department of Electrical and Computer Engineering Faculty of Science and Technology University of Macau Macao 999078 China

Compared with the conventional active power filter (APF), the static var compensator coupling hybrid active power filter (SVC-HAPF) has distinct characteristics of low DC-link operating voltage, which can lower the system and operational costs. It also has a wider operational range than the conventional hybrid active power filter (HAPF). In this paper, a harmonic state-space (HSS) modeling is firstly proposed to address the nonlinearity issue of the SVC-HAPF. The HSS based SVC-HAPF model is linear time-invariant (LTI), which enables the optimal control techniques. Then, the linear matrix inequality (LMI) based H∞ optimal control design is proposed, which finds the optimal controller parameters via convex optimization algorithm. The proposed controller for the SVC-HAPF achieves high steady-state accuracy, fast transient response, and fixed switching frequency simultaneously. Finally, simulation and experimental results are also provided to verify the effectiveness and performance of the optimal controller for the SVC-HAPF in comparison with the recent developed state-of-the-art multi-quasi-proportional-resonant (MQPR) controller, which shows superior control performances. © 2017 CPSS.

关键词： State space methods

Addressing the regulatory gap: moving towards an EU AI audit ecosystem beyond the AI Act by including civil society

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AI and Ethics 2024年 1-22页

作者： Hartmann, David de Pereira, José Renato Laranjeira Streitbörger, Chiara Berendt, Bettina Faculty of Electrical Engineering and Computer Science TU Berlin Berlin Germany Weizenbaum Institute for the Networked Society Berlin Germany LAPIN - Laboratory of Public Policy and Internet Public Policy Division Brasília Brazil Bonn Sustainable AI Lab University of Bonn Bonn Germany Kammergericht Berlin Berlin Germany Department of Computer Science KU Leuven Leuven Belgium

The European legislature has proposed the Digital Services Act (DSA) and Artificial Intelligence Act (AIA) to regulate platforms and Artificial Intelligence (AI) products. We review to what extent third-party audits are part of both laws and how is access to information on models and the data provided. By considering the value of third-party audits and third-party data access in an audit ecosystem, we identify a regulatory gap in that the AIA does not provide access to data for researchers and civil society. Our contributions to the literature include: (1) Defining an AI audit ecosystem incorporating compliance and oversight. (2) Highlighting a regulatory gap within the DSA and AIA regulatory framework, preventing the establishment of an AI audit ecosystem that has effective oversight by civil society and academia. (3) Emphasizing that third-party audits by research and civil society must be part of that ecosystem, we call for AIA amendments and delegated acts to include data and model access for certain AI products. Furthermore, we call for the DSA to provide NGOs and investigative journalists with data access to platforms by delegated acts and for adaptions and amendments of the AIA to provide third-party audits and data and model access, at least for high-risk systems. Regulations modeled after EU AI regulations should enable data access and third-party audits, fostering an AI audit ecosystem that promotes compliance and oversight mechanisms.

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A Monotone Circuit Construction for Individually-Secure Multi-Secret Sharing

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arXiv 2024年

作者： Bass, Cailyn Cohen, Alejandro D'Oliveira, Rafael G.L. Médard, Muriel School of Mathematical and Statistical Sciences Clemson University ClemsonSC United States Faculty of Electrical and Computer Engineering Technion-Institute of Technology Haifa Israel Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA United States

In this work, we introduce a new technique for taking a single-secret sharing scheme with a general access structure and transforming it into an individually secure multisecret sharing scheme where every secret has the same general access structure. To increase the information rate, we consider Individual Security which guarantees zero mutual information with each secret individually, for any unauthorized subsets. Our approach involves identifying which shares of the single-secret sharing scheme can be replaced by linear combinations of messages. When m- 1 shares are replaced, our scheme obtains an information rate of m/|S|, where S is the set of shares. This provides an improvement over the information rate of 1/|S| in the original single-secret sharing scheme. Copyright © 2024, The Authors. All rights reserved.

关键词： Timing circuits

Fake the Real: Backdoor Attack on Deep Speech Classification via Voice Conversion

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arXiv 2023年

作者： Ye, Zhe Mao, Terui Dong, Li Yan, Diqun Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China Zhejiang Key Laboratory of Mobile Network Application Technology China Ningbo City College of Vocational Technology Ningbo China

Deep speech classification has achieved tremendous success and greatly promoted the emergence of many real-world applications. However, backdoor attacks present a new security threat to it, particularly with untrustworthy third-party platforms, as pre-defined triggers set by the attacker can activate the backdoor. Most of the triggers in existing speech backdoor attacks are sample-agnostic, and even if the triggers are designed to be unnoticeable, they can still be audible. This work explores a backdoor attack that utilizes sample-specific triggers based on voice conversion. Specifically, we adopt a pre-trained voice conversion model to generate the trigger, ensuring that the poisoned samples does not introduce any additional audible noise. Extensive experiments on two speech classification tasks demonstrate the effectiveness of our attack. Furthermore, we analyzed the specific scenarios that activated the proposed backdoor and verified its resistance against fine-tuning. Copyright © 2023, The Authors. All rights reserved.

关键词： Speech recognition

Shannon capacity, Lovász theta number and the Mycielski construction1

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arXiv 2023年

作者： Csonka, Bence Simonyi, Gábor Department of Computer Science and Information Theory Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics MTA-BME Lendület Hungary Arithmetic Combinatorics Research Group MKH Budapest Hungary Artificial Intelligence National Laboratory of Hungary Hungary Budapest Hungary Department of Computer Science and Information Theory Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Hungary

We investigate the effect of the well-known Mycielski construction on the Shannon capacity of graphs and on one of its most prominent upper bounds, the (complementary) Lovász theta number. We prove that if the Shannon capacity of a graph, the distinguishability graph of a noisy channel, is attained by some finite power, then its Mycielskian has strictly larger Shannon capacity than the graph itself. For the complementary Lovász theta function we show that its value on the Mycielskian of a graph is completely determined by its value on the original graph, a phenomenon similar to the one discovered for the fractional chromatic number by Larsen, Propp and Ullman. We also consider the possibility of generalizing our results on the Sperner capacity of directed graphs and on the generalized Mycielsky construction. Possible connections with what Zuiddam calls the asymptotic spectrum of graphs are discussed as *** Codes 05C76, 94A24, 05C15, 05C50 Copyright © 2023, The Authors. All rights reserved.

关键词： Directed graphs

Automatic Sitting Posture Recognition in Wheelchair Users: An AI-driven Pilot Study

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Automatic Sitting Posture Recognition in Wheelchair Users: A...

International Conference on Frontiers of Signal Processing (ICFSP)

作者： Fouzi Harrou Abdelhakim Dorbane Ying Sun Electrical and Mathematical Sciences and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Computer Thuwal Saudi Arabia Smart Structures Laboratory (SSL) Faculty of Science and Technology University of Ain Temouchent Ain Temouchent Algeria

ISBN: (数字)9798350353235

ISBN: (纸本)9798350353242

Automated recognition of sitting postures in wheelchair users is crucial for preventing pressure ulcers and improving overall comfort and health. This pilot study explores using XGBoost for automatic sitting posture recognition in wheelchair users. XGBoost was chosen for its robustness, ability to handle imbalanced datasets, and its strategy of combining multiple weak learners to create a strong learner, thereby enhancing model accuracy and robustness. The proposed approach is evaluated using a publicly available dataset. Pressure sensors on the seat and an ultrasonic sensor on the backrest were utilized to classify four sitting postures: normal sitting, higher pressure on the right side, higher pressure on the left side, and higher forward pressure. XGBoost demonstrated superior performance with perfect accuracy and F1-score, outperforming Support Vector Machines (SVM) and Naive Bayes classifiers. Additionally, SHAP (SHapley Additive exPlanations) analysis is employed to model explainability and identify the most significant variables for detecting abnormal postures. While results are promising, the limited dataset suggests that further research with more extensive data and additional sensors could enhance accuracy.

关键词： Support vector machines Pressure sensors Analytical models Accuracy Wheelchairs Signal processing Robustness Acoustics Naive Bayes methods Ensemble learning

Integrated sensing and full-duplex communication: Joint transceiver beamforming and power allocation

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arXiv 2023年

作者： He, Zhenyao Xu, Wei Shen, Hong Ng, Derrick Wing Kwan Eldar, Yonina C. You, Xiaohu National Mobile Communications Research Laboratory Southeast University Bangladesh School of Electrical Engineering and Telecommunications University of New South Wales Australia Faculty of Mathematics and Computer Science Weizmann Institute of Science

Beamforming design has been widely investigated for integrated sensing and communication (ISAC) systems with full-duplex (FD) sensing and half-duplex (HD) communication. To achieve higher spectral efficiency, in this paper, we extend existing ISAC beamforming design by considering the FD capability for both radar and communication. Specifically, we consider an ISAC system, where the base station (BS) performs target detection and communicates with multiple downlink users and uplink users reusing the same time and frequency resources. We jointly optimize the downlink dual-functional transmit signal and the uplink receive beamformers at the BS and the transmit power at the uplink users. The problem is formulated to minimize the total transmit power of the system while guaranteeing the communication and sensing requirements. The downlink and uplink transmissions are tightly coupled, making the joint optimization challenging. To handle this issue, we first determine the receive beamformers in closed forms with respect to the BS transmit beamforming and the user transmit power and then suggest an iterative solution to the remaining problem. We demonstrate via numerical results that the optimized FD communication-based ISAC leads to power efficiency improvement compared to conventional ISAC with HD communication. Copyright © 2023, The Authors. All rights reserved.

关键词： Beamforming

Enhancing photovoltaic system performance using advanced gradient boosting methods

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Enhancing photovoltaic system performance using advanced gra...

International Conference on Control, Automation and Diagnosis (ICCAD)

ISBN: (数字)9798350361025

ISBN: (纸本)9798350361032

Photovoltaic (PV) systems are indispensable elements in clean energy production. Predicting PV power is crucial for optimizing system performance and ensuring grid stability. This paper investigates the performance of gradient boosting approaches, XGBoost and Catboost, in predicting PV power. Datasets recorded each minute, including weather data and power output from two distinct PV systems in Brisbane, Australia, are used in this study for evaluation. Results show that the XGBoost slightly outperformed Catboost and achieved good prediction performance. Also, the XGBoost output was interpreted using the Shapley additive interpretation (SHAP) method to identify the important factor impacting PV power prediction. Results confirm that solar radiation is the most important factor influencing the performance of photovoltaic systems, and the other weather variables have a weaker impact. These findings contribute valuable insights for enhancing the efficiency and reliability of PV systems in renewable energy applications.

关键词： Photovoltaic systems Accuracy System performance Noise reduction Noise Predictive models Boosting

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arXiv 2025年

作者： Fidêncio, Aline Xavier Grün, Felix Klaes, Christian Iossifidis, Ioannis Robotics and BCI Laboratory Institute of Computer Science Ruhr West University of Applied Sciences Mülheim an der Ruhr Germany Faculty of Electrical Engineering and Information Technology Ruhr University Bochum Bochum Germany KlaesLab Department of Neurosurgery University Hospital Knappschaftskrankenhaus Ruhr University Bochum Bochum Germany Faculty of Computer Science Ruhr University Bochum Bochum Germany

Brain-computer interfaces (BCIs) are developed for individuals with motor disabilities to offer alternative methods of communication, such as controlling and interacting with external devices. These systems are designed to improve quality of life, particularly for those with limited mobility. BCIs that rely on non-invasive recordings, such as electroencephalography (EEG), have been developed for a wide range of scenarios due to their practicality and safety. However, BCI performance is often limited by non-stationarities in the EEG data, which can arise from changes in the subject’s mental state or device characteristics, such as electrode impedance. These challenges motivate ongoing research into the development of adaptive BCIs capable of handling such variations. Over the past years, the interest in using the so-called error-related potentials (ErrPs) to improve BCI performance has increased. This is because ErrPs represent the neural response to both self-made and external errors and can be measured using non-invasive techniques. These signals have been combined with different BCI paradigms and used in different works to improve BCI performance via error correction or adaptation. In this work we introduce and explore a new approach for creating an adaptive ErrP-based BCI by evaluating the use of reinforcement learning (RL). This study demonstrates the feasibility of a RL-driven adaptive brain-computer interface (BCI) framework that integrates error-related potentials (ErrPs) and motor imagery. By employing two RL agents to dynamically adapt to EEG non-stationarities, we validate the framework on both a publicly available motor imagery dataset and using a novel experimental protocol involving a fast-paced game designed to enhance user engagement. Results highlight the framework’s potential: RL agents successfully learned control policies from user interactions, achieving robust performance across datasets. However, a critical finding emerged from the game-based p

关键词： Reinforcement learning

Highly Sensitive Humidity Sensor Based on Strontium-Doped Lanthanum Ferrite Nanofibers

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SSRN

SSRN 2023年

作者： Zhang, Ziyi Li, Fangxin Zheng, Yangong Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China Key Laboratory of Microelectronic Devices & Integrated Technology Institute of Microelectronics Chinese Academy of Sciences Beijing100029 China

Humidity sensors are the most widely applied sensors. Although some highly sensitive humidity sensors have been explored, devices that can accurately detect low humidity are still required. Improving the adsorption of water molecules by surface regulation is an effective way to enhance humidity sensitivity. In this study, electrospinning prepared a series of lanthanum ferrite samples doped with different concentrations of strontium. For the sample with a surface atomic ratio between strontium and lanthanum was approximately 0.2, there was a 6×104 times change in the resistance of the sensor to 90% relative humidity, and the response was 6.76 for 4% relative humidity. Negligible hysteresis, and excellent stability demonstrate the advantages of the strontium-doped lanthanum ferrite nanofibers. The sensing mechanism was discussed by measuring the change of band gap and work function of samples with different concentrations of strontium doping. Furthermore, suitable doping also decreased the adsorption energy and increased the charge transfer during the adsorption of water molecules on the surface of lanthanum ferrite based on the calculations. This study provides a new perspective for enhancing the sensitivity of humidity sensors via surface regulation. © 2023, The Authors. All rights reserved.

关键词： Electrospinning