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Exploiting Trust for Resilient Hypothesis Testing with Malicious Robots (evolved version)

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arXiv 2023年

作者： Cavorsi, Matthew Akgün, Orhan Eren Yemini, Michal Goldsmith, Andrea Gil, Stephanie The School of Engineering and Applied Sciences Harvard University United States The Faculty of Engineering Bar-Ilan University Israel The Department of Electrical and Computer Engineering Princeton University United States

We develop a resilient binary hypothesis testing framework for decision making in adversarial multi-robot crowdsensing tasks. This framework exploits stochastic trust observations between robots to arrive at tractable, resilient decision making at a centralized Fusion Center (FC) even when i) there exist malicious robots in the network and their number may be larger than the number of legitimate robots, and ii) the FC uses one-shot noisy measurements from all robots. We derive two algorithms to achieve this. The first is the Two Stage Approach (2SA) that estimates the legitimacy of robots based on received trust observations, and provably minimizes the probability of detection error in the worst-case malicious attack. Here, the proportion of malicious robots is known but arbitrary. For the case of an unknown proportion of malicious robots, we develop the Adversarial Generalized Likelihood Ratio Test (A-GLRT) that uses both the reported robot measurements and trust observations to estimate the trustworthiness of robots, their reporting strategy, and the correct hypothesis simultaneously. We exploit special problem structure to show that this approach remains computationally tractable despite several unknown problem parameters. We deploy both algorithms in a hardware experiment where a group of robots conducts crowdsensing of traffic conditions on a mock-up road network similar in spirit to Google Maps, subject to a Sybil attack. We extract the trust observations for each robot from actual communication signals which provide statistical information on the uniqueness of the sender. We show that even when the malicious robots are in the majority, the FC can reduce the probability of detection error to 30.5% and 29% for the 2SA and the A-GLRT respectively. Copyright © 2023, The Authors. All rights reserved.

关键词： Robots

Optimizing energy payment, user satisfaction, and self-sufficiency in flexibility-constrained smart home energy management: A multi-objective optimization approach

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e-Prime - Advances in electrical engineering, Electronics and Energy 2023年 6卷

作者： Dorahaki, Sobhan MollahassaniPour, Mojgan Rashidinejad, Masoud Department of Electrical Engineering Shahid Bahonar University of Kerman Kerman Iran Faculty of Electrical and Computer Engineering University of Sistan and Baluchestan Zahedan Iran

Smart homes have assumed a pivotal role within energy communities, offering sophisticated home energy management systems tailored to end-users preferences across technical, economic, social, and environmental facets. Amid the proliferation of smart appliances and advanced communication infrastructure, these domiciles play a crucial part in optimizing energy utilization and fostering sustainable practices. Notably, they create an enabling environment for the integration of renewable energy resources, but their widespread adoption may potentially challenge the flexibility of the overarching energy system. In this paper, a novel flexibility-constrained smart home energy management framework is proposed aiming at optimizing energy payment, end-user satisfaction, and end-user self-sufficiency preferences. Diverse technologies including Combined Heat and power (CHP) units, PhotoVoltaic (PV) generation units, electrical energy storage systems, and electric vehicles are considered in the smart home where the PV unit uncertainty is modeled by a scenario-based approach. The lexicographic technique as a Multi-Criteria Decision Making (MCDM) approach is utilized to find an appropriate compromise among different targets. The proposed model is structured as a Mixed-Integer Linear Programming (MILP) problem that is solved by the CPLEX solver in the GAMS environment. The results reveal a significant disparity in energy payments when the flexibility limit falls below 40 % of the predefined amount. The results demonstrate that altering the priority order of the objective functions has led to significant changes in energy payment, end-user satisfaction, and end-user self-sufficiency, with variations of 27.4 %, 100 %, and 56.64 %, respectively. © 2023 The Author(s)

关键词： End-User Satisfaction Flexibility Home Energy Management Lexicographic Multi-Objective Optimization Self-sufficiency

A Novel Terahertz Metamaterial Absorber Based on Split-Relief Design for the Application of Refractive Index Sensing

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SSRN

SSRN 2023年

作者： Abdulkarim, Yadgar I. Muhammadsharif, Fahmi F. Appasani, Bhargav Bakır, Mehmet Karaaslan, Muharrem Rezaei, Pejman Khatami, Seyed Amin Daraei, Omid Mohsen Zamzam, Pouria Dong, Jian School of Computer Science and Engineering Central South University Changsha410075 China Physics Department College of Science Charmo University Chamchamal Sulaimania46023 Iraq Department of Physics Faculty of Science and Health Koya University KOY45 Koya Iraq School of Electronics Engineering KIIT University Odisha Bhubaneswar India Department of Computer Engineering Bozok University Yozgat66200 Turkey Department of Electrical-Electronics Engineering Iskenderun Technical University Hatay 31200 Turkey Electrical and Computer Engineering Faculty Semnan University Semnan Iran Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran

THz metamaterial absorbers are a subclass of metamaterial-based structures that can absorb THz electromagnetic radiations in the THz range. In this paper, four different designs of THz metamaterial absorbers are proposed which are based on split-relief (SR) design. They consist of sun-shaped, SR sun-shaped, star-shaped and SR star-shaped resonators coated on top of a dielectric substrate. The resonance frequencies of the designs were found to be at 0.70, 1.04, 0.41 and 0.60 THz, respectively. Results showed that the resonance frequency was independent on the incident and polarization angles. The proposed absorbers were used to detect the thickness and refractive index of the analyte. The thickness of the analyte can be detected with a sensitivity of 73 GHz/µm for the Sun design, 238 GHz/µm for the SRSun design, 45.2 GHz/µm for the Star design, and 133.4 GHz/µm for the SRStar design. Similarly, the refractive index of the analyte can be measured with a sensitivity of 1.581 THz/RIU for the Sun design, 4.053 THz/RIU for the SRSun design, 1.077 THz/RIU for the Star design, and 2.067 THz/RIU for the SRStar design when the analyte thickness was fixed at 3 μm. The resonance mechanism was explained considering electric and magnetic field distributions. © 2023, The Authors. All rights reserved.

关键词： Refractive index

The Effect of Mismatch between SPECT and CT Images on Deep Learning-based Attenuation Correction for Myocardial Perfusion SPECT

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The Effect of Mismatch between SPECT and CT Images on Deep L...

2022 IEEE Nuclear Science Symposium, Medical Imaging Conference, and Room Temperature Semiconductor Detector Conference, IEEE NSS MIC RTSD 2022

作者： Du, Yu Shang, Jingjie Sun, Jingzhang Wang, Lu Xu, Hao Mok, Greta S. P. University of Macau Faculty of Science and Technology Department of Electrical and Computer Engineering China The First Affiliated Hospital of Jinan University Department of Nuclear Medicine PET/CT-MRI Centre Guangdong Guangzhou China

ISBN: (纸本)9781665488723

Attenuation correction (AC) using deep learning (DL)-based methods improves image quality and quantitative accuracy in myocardial perfusion (MP) SPECT when CT-based AC (CT-AC) is not feasible. However, potential misalignments between SPECT and CT may affect the DL-based AC performance. This study aims to evaluate this effect based on real patient data. Fifity-eight stress/rest99mTc-sestamibi scans from 34 patients were retrospectively analyzed. Thirty-six projections, acquired from RAO to LPO in 11 min, were reconstructed by OS-EM algorithm, with and without CT-AC. A 3D conditional generative adversarial network was implemented and optimized for the DL-ACµ and DL-AC, while 43, 5 and 10 datasets were used for training, validation and testing with a 6-fold cross-validation. SPECT and CT mismatch was modeled by randomly shifting the CT images in 3 dimensions (8.6±3.8 mm) with respective to their corresponding SPECT images based on a clinical reference. Mismatched SPECT and CT images were also used to train the network separately, i.e., mDL-AC and mDL-ACµ. NMSE, SSIM, joint correlation histogram and linear regression on a 3D cardiac VOI were compared for all cases, with matched CT-AC as the reference. NMSE and SSIM show significantly degraded performance on mDL-ACµ and mDL-AC as compared to DL-ACµ and DL-AC, respectively. mDL-ACµ is consistently better than mDL-AC. The joint correlation histogram and linear regression result is consistent. We conclude that though SPECT and CT mismatch significantly degrades DL-based AC performance, mDL-ACµ is more robust to mDL-AC for MP SPECT and shows improved results as compared to NAC. © 2022 IEEE.

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Can Copyright be Reduced to Privacy?

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arXiv 2023年

作者： Elkin-Koren, Niva Hacohen, Uri Livni, Roi Moran, Shay Faculty of Law Tel Aviv University Department of Electrical Engineering Tel Aviv University Department of Mathematics and Computer Science Technion

There is a growing concern that generative AI models will generate outputs closely resembling the copyrighted materials for which they are trained. This worry has intensified as the quality and complexity of generative models have immensely improved, and the availability of extensive datasets containing copyrighted material has expanded. Researchers are actively exploring strategies to mitigate the risk of generating infringing samples, with a recent line of work suggesting to employ techniques such as differential privacy and other forms of algorithmic stability to provide guarantees on the lack of infringing copying. In this work, we examine whether such algorithmic stability techniques are suitable to ensure the responsible use of generative models without inadvertently violating copyright laws. We argue that while these techniques aim to verify the presence of identifiable information in datasets, thus being privacy-oriented, copyright law aims to promote the use of original works for the benefit of society as a whole, provided that no unlicensed use of protected expression occurred. These fundamental differences between privacy and copyright must not be overlooked. In particular, we demonstrate that while algorithmic stability may be perceived as a practical tool to detect copying, such copying does not necessarily constitute copyright infringement. Therefore, if adopted as a standard for detecting an establishing copyright infringement, algorithmic stability may undermine the intended objectives of copyright law. © 2023, CC BY-SA.

关键词： Stability

Reinforcement Learning-Based Fault-Tolerant Control of Uncertain Strict-Feedback Nonlinear Systems With Intermittent Actuator Faults

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IEEE Transactions on Neural Networks and Learning Systems 2025年第6期36卷 10464-10478页

作者： Qinmin Yang Huaying Li Zhengwei Ruan Bo Fan Shuzhi Sam Ge State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China Hangzhou Huawei Communication Technology Company Ltd. Hangzhou China School of Automation Science and Engineering Xi’an Jiaotong University Xi’an China Department of Electrical and Computer Engineering Institute for Functional Intelligent Materials National University of Singapore Queenstown Singapore

In this work, a novel reinforcement learning-based adaptive fault-tolerant control (FTC) scheme with actuator redundancy is presented for a nonlinear strict-feedback system with nonlinear dynamics and uncertainties. A learning-based switching function technique is established to steer different groups of actuators automatically and successively to mitigate the impact of faulty actuators by observing a switching performance index. The optimal tracking control problem (OTCP) of strict-feedback nonlinear systems is transformed into an equivalent optimal regulation problem of each affine subsystem via adaptive feedforward controllers. Subsequently, the designed objective functions associated with Hamilton–Jacobi–Bellman (HJB) estimate errors caused by neural network (NN) approximations can be minimized by the reinforcement learning algorithm without value or policy iterations. It is proved that the tracking objective can be achieved and all signals in the closed-loop system can be guaranteed to be bounded, as long as the minimum time interval between two successive failures is bounded. Theoretical results are verified by simulations.

关键词： Actuators Switches Fault tolerant systems Control systems Optimal control Redundancy Nonlinear dynamical systems Adaptive control Regulation Industrial control

PAS-SLAM: A Visual SLAM System for Planar Ambiguous Scenes

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arXiv 2024年

作者： Hu, Xinggang Wu, Yanmin Zhao, Mingyuan Yang, Linghao Zhang, Xiangkui Ji, Xiangyang School of Electronic Information and Electrical Engineering Dalian University of Technology Dalian China School of Electronic and Computer Engineering Peking University Shenzhen China Department of Automation Tsinghua University Beijing China College of Information Science and Engineering Northeastern University Shenyang China

Visual SLAM (Simultaneous Localization and Mapping) based on planar features has found widespread applications in fields such as environmental structure perception and augmented reality. However, current research faces challenges in accurately localizing and mapping in planar ambiguous scenes, primarily due to the poor accuracy of the employed planar features and data association methods. In this paper, we propose a visual SLAM system based on planar features designed for planar ambiguous scenes, encompassing planar processing, data association, and multi-constraint factor graph optimization. We introduce a planar processing strategy that integrates semantic information with planar features, extracting the edges and vertices of planes to be utilized in tasks such as plane selection, data association, and pose optimization. Next, we present an integrated data association strategy that combines plane parameters, semantic information, projection IoU (Intersection over Union), and non-parametric tests, achieving accurate and robust plane data association in planar ambiguous scenes. Finally, we design a set of multi-constraint factor graphs for camera pose optimization. Qualitative and quantitative experiments conducted on publicly available datasets demonstrate that our proposed system competes effectively in both accuracy and robustness in terms of map construction and camera localization compared to state-of-the-art methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Augmented reality

Kalman Filter for tracking a noisy cosinusoidal signal with constant amplitude

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Kalman Filter for tracking a noisy cosinusoidal signal with ...

International Conference on computer and Communication engineering, ICCCE

作者： Prima Wijaya Kusuma Mohamed Hadi Habaebi Galang P. N. Hakim Rachmat Muwardi Md. Rafiqul Islam Department of Electrical Engineering Faculty of Engineering Universitas Mercu Buana Jakarta Indonesia Department of Electrical and Computer Engineering Kulliyyah of Engineering (KOE) International Islamic University Malaysia (IIUM) Selangor Malaysia School of Optics and Photonics Beijing Institute of Technology Beijing China

This paper presents a Kalman filter based approach in order to solve the problem of tracking a noisy cosinusoidal signal with constant amplitude in the presence of noise. The objective is to estimate the state of the signal accurately, considering the inherent challenges posed by noise corruption. The Kalman filter is utilized as the core algorithm for state estimation, leveraging its ability to combine noisy measurements and a dynamic model to provide optimal estimates. The filter is initialized with zero states and covariance, and the state and covariance estimates are iteratively updated using time updates and measurement update equations. Through extensive simulations, the performance of the proposed Kalman filter-based algorithm is evaluated. The results demonstrate its effectiveness in accurately tracking cosinusoidal signals and mitigating the impact of noise. the Kalman Filter algorithm in this system produces low MSE at about 0.021 and MAE at about 0.111. The metrics results signify the algorithm’s ability to filter noise and estimate the actual state of the system, reflecting its robust tracking performance. The simulation results validate the effectiveness of the proposed approach and highlight its potential to enhance signal tracking accuracy in the presence of noise. Further research can explore the algorithm’s performance in various scenarios and investigate additional modifications to increase its robustness in challenging environments.

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An Overview of Recent Developments in ‘Big’ Boolean Equations

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arXiv 2023年

作者： Ali Rushdi, Ali Muhammad Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University P. O. Box 80200 Jeddah21589 Saudi Arabia

A task frequently encountered in digital circuit design is the solution of a two-valued Boolean equation of the form ℎ(X, Y, Z) = 1, where ℎ: B2κ+m+n → B2 and X, Y, and Z are binary vectors of lengths κ, m, and n, representing inputs, intermediary values, and outputs, respectively. The resultant of the suppression of the variables Y from this equation could be written in the form g(X, Z) = 1 where g: B2κ+n → B2. Typically, one needs to solve for Z in terms of X, and hence it is unavoidable to resort to ‘big’ Boolean algebras which are finite (atomic) Boolean algebras larger than the two-valued Boolean algebra. Other situations which necessitate ‘big’ Boolean-equation-solving are the so-called ‘elementary problems of digital circuit design,’ which entail five vector-Boolean quantities X, Y, Z, s and t that belong to B2κ, B2m, B2n, B2l , and B2l , respectively. Consider a ‘parent’ combinational network C of two (vectorial) inputs X and Y and a vectorial output t(X, Y), and assume that network C consists of two subnetworks A and B, where subnetwork A has the single (vectorial) input X and the (vectorial) output Z(X), while network B has the two vectorial inputs Z(X) and Y and the (vectorial) output s(Z, Y), which is exactly the same as the (vectorial) output t(X, Y) of network C. The above arrangement involves three vectorial Boolean functions, namely Z(X), s(Z, Y) and t(X, Y). Three problems arise when one utilizes the information that s(Z(X), Y) and t(X, Y) are equal, together with knowledge of two of the three functions X(X), s(Z, Y) and t(X, Y) in order to deduce the third function. Two of these problems are natural examples why ‘big’ Boolean-equation-solving is warranted. Methods of solving ‘big’ Boolean equations can be broadly classified as algebraic, tabular, numerical and map methods. The most prominent among these classes are the algebraic and map methods. This paper surveys and compares these two types of methods as regards simplicity, efficiency, and usabil

关键词： Integrated circuit manufacture