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2023 IEEE International Conference on Electro Information Technology, eIT 2023

作者： Chen, Yang Chen, Jun Liu, Chenang Liu, Guodong Ferrari, Maximiliano Sundararajan, Aditya Department of Industrial and Systems Engineering North Carolina Agricultural and Technical State University Greensboro United States Department of Electrical and Computer Engineering Oakland University RochesterMI48309 United States School of Industrial Engineeering and Management Oklahoma State University Stillwater United States Electrification and Energy Infrastructures Division Oak Ridge National Laboratory Oak RidgeTN37831 United States

ISBN: (纸本)9781665493765

Focusing on remote, isolated, and underserved communities, a multi-energy system is designed in this research which is capable of utilizing different energy sources in a more coordinated and energy-efficient way to support various demands, such as fresh water, electricity, hydrogen, thermal demand, etc. The energy sources considered are renewables (wind, solar, marine) and natural gas. The energy conversion process includes water desalination, gas combustion, water electrolyzation, and different types of storage (hydrogen tank, electricity, thermal, etc.) are designed to serve as buffers in supply-demand balancing. Sets of experiments are designed to demonstrate the effectiveness of the proposed operating model and investigate the impact of uncertainties from renewable generations and demands. © 2023 IEEE.

关键词： Desalination

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Gradient Descent with Low-Rank Objective Functions

Gradient Descent with Low-Rank Objective Functions

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IEEE Conference on Decision and Control

作者： Romain Cosson Ali Jadbabaie Anuran Makur Amirhossein Reisizadeh Devavrat Shah Inria Paris France Laboratory for Information & Decision Systems MIT Cambridge MA USA Department of Computer Science School of Electrical & Computer Engineering Purdue University West Lafayette IN USA

Several recent empirical studies demonstrate that important machine learning tasks, e.g., training deep neural networks, exhibit low-rank structure, where the loss function varies significantly in only a few directions of the input space. In this paper, we leverage such low-rank structure to reduce the high computational cost of canonical gradient-based methods such as gradient descent (GD). Our proposed Low-Rank Gradient Descent (LRGD) algorithm finds an $\epsilon$ -minimizer of a p-dimensional function by first identifying $r\leq p$ significant directions, and then estimating the true p-dimensional gradient at every iteration by computing directional derivatives only along those $r$ directions. We establish that the “directional oracle complexity” of LRGD for strongly convex objective functions is $\mathrm{O}(r\log(1/\epsilon)+rp)$ . Therefore, when $r\ll p$ , LRGD provides significant improvement over the known complexity of $\mathcal{O}(p\log(1/\epsilon))$ of GD in the strongly convex setting. Furthermore, using real and synthetic data, we empirically find that LRGD provides significant gains over GD when the data has low-rank structure, and in the absence of such structure, LRGD does not degrade performance compared to GD.

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Matrix Factorization for Inferring Associations and Missing Links

arXiv

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arXiv 2025年

作者： Barron, Ryan Eren, Maksim E. Truong, Duc P. Matuszek, Cynthia Wendelberger, James Dorn, Mary F. Alexandrov, Boian Theoretical Division Los Alamos National Laboratory United States Information Systems and Modeling Los Alamos National Laboratory United States Department of Computer Science and Electrical Engineering University of Maryland Baltimore County United States Computer Computational and Statistical Sciences Los Alamos National Laboratory United States

Missing link prediction is a method for network analysis, with applications in recommender systems, biology, social sciences, cybersecurity, information retrieval, and Artificial Intelligence (AI) reasoning in Knowledge Graphs. Missing link prediction identifies unseen but potentially existing connections in a network by analyzing the observed patterns and relationships. In proliferation detection, this supports efforts to identify and characterize attempts by state and non-state actors to acquire nuclear weapons or associated technology - a notoriously challenging but vital mission for global security. Dimensionality reduction techniques like Non-Negative Matrix Factorization (NMF) and Logistic Matrix Factorization (LMF) are effective but require selection of the matrix rank parameter, that is, of the number of hidden features, k, to avoid over/under-fitting. We introduce novel Weighted (WNMFk), Boolean (BNMFk), and Recommender (RNMFk) matrix factorization methods, along with ensemble variants incorporating logistic factorization, for link prediction. Our methods integrate automatic model determination for rank estimation by evaluating stability and accuracy using a modified bootstrap methodology and uncertainty quantification (UQ), assessing prediction reliability under random perturbations. Additionally, we incorporate Otsu threshold selection and k-means clustering for Boolean matrix factorization, comparing them to coordinate descent-based Boolean thresholding. Our experiments highlight the impact of rank k selection, evaluate model performance under varying test-set sizes, and demonstrate the benefits of UQ for reliable predictions using abstention. We validate our methods on three synthetic datasets (Boolean and Gaussian distributed) and benchmark them against LMF and symmetric LMF (symLMF) on five real-world protein-protein interaction networks, showcasing an improved prediction performance. Copyright © 2025, The Authors. All rights reserved.

关键词： Non-negative matrix factorization

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Worst-Case Integrity Attacks and Resilient State Estimation With Partially Secured Measurements

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IEEE Transactions on Control of Network systems 2025年

作者： Zhou, Jing Shang, Jun Chen, Tongwen University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Tongji University Department of Control Science and Engineering Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Shanghai200092 China

This paper examines the problem of optimal deception attacks against state estimation with partially secured measurements, where smart sensors transmit innovation sequences to the remote end for information fusion. Due to resource limitations or defensive countermeasures, the adversary can only modify data packets transmitted through unreliable channels. Meanwhile, the attack should be synthesized with sophistication to deceive an anomaly detector. To investigate the vulnerabilities of such estimation systems without feedback links and enhance security performance, the optimal attack policy is derived by formulating and explicitly solving a convex optimization problem, with the goal of maximizing the sum of estimation errors. Subsequently, a novel attack detection and resilient state estimation algorithm is proposed to ensure an acceptable level of estimation accuracy. The theoretical performance metrics, including false alarm rates for the proposed detector, are provided. Finally, the effectiveness of the results is confirmed through numerical examples. © 2014 IEEE.

关键词： Optimal detection

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Exploration of the Role of Cryptoprocessors in Advancing IoT Security

Exploration of the Role of Cryptoprocessors in Advancing IoT...

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International Conference on Distributed Computing in Sensor systems (DCOSS)

作者： Elena Kakoulli Eleftherios Zacharioudakis Department of Computer Science Intelligent Systems Laboratory Neapolis University Pafos Pafos Cyprus Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus Igor Sikorsky Kyiv Polytechnic Institute National Technical University of Ukraine Kyiv Ukraine

ISBN: (数字)9798350369441

ISBN: (纸本)9798350369458

This paper presents a thorough exploration of Cryptoprocessors in the context of the Internet of Things (IoT). The focus is on hardware support, cryptographic processors, and energy-efficient designs to fortify the security of IoT ecosystems. Leveraging insights from recent research papers, the survey examines various aspects of Cryptoprocessor implementations, ranging from lightweight countermeasures to advanced lattice-based post-quantum cryptography. The proposed paper amalgamates findings from studies on hardware architectures, energy-efficient designs, and innovative cryptographic algorithms to provide a holistic overview of state-of-the-art advancements in IoT security. The synthesis of this survey’s exploration aims to contribute to the ongoing discourse on securing IoT devices through robust hardware-backed cryptographic solutions.

关键词： Surveys Industries Technological innovation Program processors Ecosystems Hardware Energy efficiency

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Output Feedback Position Tracking Control of Marine Vessels Subject to Periodic Disturbances

Output Feedback Position Tracking Control of Marine Vessels ...

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American Control Conference (ACC)

作者： Deniz Kurtoglu Enver Tatlicioglu Erkan Zergeroglu Department of Mechanical Engineering Laboratory for Autonomy Control Information and Systems (LACIS) University of South Florida Tampa FL United States of America Department of Electrical Electronics Engineering Ege University Izmir Turkey Department of Computer Engineering Gebze Technical University Gebze Kocaeli Turkey

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This work deals with the design and implementation of a novel output feedback position tracking controller for marine vessels subject to uncertainties in their dynamical parameters and periodic external disturbance. Specifically, an adaptive controller that does not make use of velocity measurements has been presented which can compensate for uncertainties in the system's dynamical parameters and periodic external disturbance. A filtered based velocity surrogate formulation in conjunction with a periodic noise estimator and a desired model compensation based adaptive parameter estimator have been utilized to tackle the problem. Boundedness of the closed loop system and convergence of the position tracking error to the origin are proven via Lyapunov-type arguments. Comparative numerical simulations are presented to illustrate the effectiveness of the proposed controller.

关键词： Uncertain systems Uncertainty Noise Estimation Numerical simulation Filtering theory Numerical models

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Robust characterization of photonic integrated circuits

arXiv

引用

arXiv 2024年

作者： Wang, Jiajia Xu, Xingyuan Zhang, Haoran Zeng, Xuecheng Bai, Yunping Lowery, Arthur J. Xu, Kun State Key Laboratory of Information Photonics and Optical Communications Beijing University of Posts and Telecommunications Beijing100876 China Electro-Photonics Laboratory Department of Electrical and Computer Systems Engineering Monash University ClaytonVIC3800 Australia

Photonic integrated circuits (PICs) offer ultra-broad optical bandwidths that enable unprecedented data throughputs for signal processing applications. Dynamic reconfigurability enables compensation of fabrication flaws and fluctuating external environments, tuning for adaptive equalization and training of optical neural networks. The initial step in PIC reconfiguration entails measuring its dynamic performance, often described by its frequency response. While measuring the amplitude response is straightforward, e.g. using a tunable laser and optical power meter, measuring the phase response presents challenges due to various factors, including phase variations in test connections and instrumentation limitations. To address these challenges, a universal and robust characterization technique is proposed, which uses an on-chip reference path coupled to the signal processing core (SPC), with a delay larger or smaller than the total delay across the signal processing paths. A Fourier transform of the chip's power response reveals the SPC's impulse response. The method is more robust against low reference-path power and imprecise delays. Experiments using a finite-impulse-response (FIR) structure demonstrate rapid SPC training, overcoming thermal crosstalk and device imperfections. This approach offers a promising solution for PIC characterization, facilitating expedited physical parameter training for advanced applications in communications and optical neural networks. Copyright © 2024, The Authors. All rights reserved.

关键词： Photonic integrated circuits

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Graph-Based Visual-Kinematic Fusion and Monte Carlo Initialization for Fast-Deployable Cable-Driven Robots

Graph-Based Visual-Kinematic Fusion and Monte Carlo Initiali...

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IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： R. Khorrambakht H. Damirchi M.R. Dindarloo A. Saki S.A. Khalilpour Hamid D. Taghirad Stephan Weiss Electrical & Computer Engineering Department Control/Robotics Research Laboratory Tandon School of Engineering New York University Brooklyn NY School of Computer Science University of Adelaide Australia Faculty of Electrical Engineering University of Technology Tehran Iran Department of Smart Systems Technologies University of Klagenfurt Austria

Ease of calibration and high-accuracy task-space state-estimation purely based on onboard sensors is a key requirement for enabling easily deployable cable robots in real-world applications. In this work, we incorporate the onboard camera and kinematic sensors to drive a statistical fusion framework that presents a unified localization and calibration system which requires no initial values for the kinematic parameters. This is achieved by formulating a Monte-Carlo algorithm that initializes a factor-graph representation of the calibration and localization problem. With this, we are able to jointly identify both the kinematic parameters and the visual odometry scale alongside their corresponding uncertainties. We demonstrate the practical applicability of the framework using our state-estimation dataset recorded with the ARAS-CAM suspended cable driven parallel robot, and published as part of this manuscript.

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Mechanical Design with Experimental Verification of a Lightweight Exoskeleton Chair

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Journal of Bionic engineering 2021年第2期18卷 319-332页

作者： Zihao Du Zefeng Yan Tiantian Huang Ou Bai Qin Huang Bin Han State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Human Cyber-Physical Systems Laboratory Department of Electrical and Computer EngineeringFlorida International UniversityMiami 33174USA Department of Rehabilitation Medicine Union HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430022China

In this study,a human-chair model was developed as the basis for a wearable-chair design.A prototype chair,HUST-EC,based on the model was fabricated and *** the optimization under the golden divisional method,an optimized simulation of the operating mode with the lowest chair height was implemented.A novel multi-link support structure has been established with parameters optimized using Matlab *** stress analysis of the solid models was conducted to ensure the adequate support from the designed chair for the *** subjects participated in the evaluation experiment,who performed both static tasks and dynamic *** experimental results consisted of subjective evaluation and objective *** experimental data demonstrate that(1)the HUST-EC can effectively reduce the activation level of related muscles at a variety of tasks;(2)the plantar pressure was reduced by 54%–67%;(3)the angle between the upper body and the vertical axis was reduced by 59%–77%;(4)the subjective scores for chair comfortability,portability,and stability were all higher than *** results further revealed that the designed chair can reduce the musculoskeletal burden and may improve work efficiency.

关键词： exoskeleton wearable chair bionic robot mechanism design ergonomics

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Convex Ternary Quartics Are SOS-Convex

arXiv

引用

arXiv 2024年

作者： Ahmadi, Amir Ali Blekherman, Grigoriy Parrilo, Pablo A. The Department of Operations Research and Financial Engineering Princeton University United States The School of Mathematics The Georgia Institute of Technology United States The Laboratory for Information and Decision Systems The Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology United States

We show that if a ternary quartic form is convex, then it must be sos-convex;i.e, if the Hessian H(x) of a ternary quartic form is positive semidefinite for all x, then the biquadratic form yT H(x)y in the variables x:= (x1, x2, x3)T and y:= (y1, y2, y3)T must be a sum of squares. This result is in a meaningful sense the "convex analogue" of Hilbert’s celebrated theorem on ternary quartics. We show that exploiting the structure of the Hessian matrix is crucial in any possible proof of this result by presenting an explicit example of a biquadratic form b(x, y) that is symmetric in x and y, nonnegative, but not a sum of squares. © 2024, CC BY.

关键词： Matrix algebra

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