Why Don't You Clean Your Glasses? Perception Attacks with Dynamic Optical Perturbations

Camera-based autonomous systems that emulate human perception are increasingly being integrated into safety-critical platforms. Consequently, an established body of literature has emerged that explores adversarial attacks targeting the underlying machine learning models. Adapting adversarial attacks to the physical world is desirable for the attacker, as this removes the need to compromise digital systems. However, the real world poses challenges related to the "survivability" of adversarial manipulations given environmental noise in perception pipelines and the dynamicity of autonomous systems. In this paper, we take a sensor-first approach. We present EvilEye, a man-in-the-middle perception attack that leverages transparent displays to generate dynamic physical adversarial examples. EvilEye exploits the camera's optics to induce misclassifications under a variety of illumination conditions. To generate dynamic perturbations, we formalize the projection of a digital attack into the physical domain by modeling the transformation function of the captured image through the optical pipeline. Our extensive experiments show that EvilEye's generated adversarial perturbations are much more robust across varying environmental light conditions relative to existing physical perturbation frameworks, achieving a high attack success rate (ASR) while bypassing state-of-the-art physical adversarial detection frameworks. We demonstrate that the dynamic nature of EvilEye enables attackers to adapt adversarial examples across a variety of objects with a significantly higher ASR compared to state-of-the-art physical world attack frameworks. Finally, we discuss mitigation strategies against the EvilEye attack.Comment: 15 pages, 11 figure

Decentralized Optimization of Electricity-Natural Gas Flow Considering Dynamic Characteristics of Networks

The interconnection of power and natural gas systems can improve the flexibility of system operation and the capacity of renewable energy consumption. It is necessary to consider the interaction between both, and carry out collaborative optimization of energy flow. For space-time related line packs, this paper studies the optimal multi-energy flow (OMEF) model of an integrated electricity-gas system, taking into account the dynamic characteristics of a natural gas system. Besides, in order to avoid the problem of large data collection in centralized algorithms and consider the characteristics of decentralized autonomous decision-making for each subsystem, this paper proposes a decentralized algorithm for the OMEF problem. This algorithm transforms the original non-convex OMEF problem into an iterative convex programming problem through penalty convex-concave procedure (PCCP), and then, uses the alternating direction method of multipliers (ADMM) algorithm at each iteration of PCCP to develop a decentralized collaborative optimization of power flow and natural gas flow. Finally, numerical simulations verify the effectiveness and accuracy of the algorithm proposed in this paper, and analyze the effects of dynamic characteristics of networks on system operation

Stair phase-coding fringe plus phase-shifting used in 3D measuring profilometry

As the number of codewords adopted in phase-coding fringes increases, the solution of fringe orders leads to many mistakes. Consequently, errors of the unwrapped phase occur. Thus, increasing the codeword approach in a phase-coding fringe remains a challenge. In this paper, a modified stair phase-coding fringe is designed, and a new phase unwrapping algorithm based on shifting fringe order is presented. The main idea of this method is that the width ratio between the sinusoidal fringe and each stair phase of phase-coding fringe is set to 1: n. The fringe order retrieved from the phase-coding fringe can be multiplied by the shift itself, thereby assisting phase unwrapping. This method adopts fewer codewords to replace the usual large number. As such, the approach gains two merits. One is that it guarantees a high measurement accuracy. The other is that it allows the measurement of isolated objects with complicated shapes. The experiments demonstrate that the proposed method is simple but effective

A Novel Method for Parameter Identification of Renewable Energy Resources based on Quantum Particle Swarm–Extreme Learning Machine

Accurately determining load model parameters is of the utmost importance for conducting power system simulation analysis and designing effective control strategies. Measurement-based approaches are commonly employed to identify load model parameters that closely reflect the actual operating conditions. However, these methods typically rely on iterative parameter search processes, which can be time-consuming, particularly when dealing with complex models. To address this challenge, this paper introduces a parameter identification method for the generalized synthetic load model (SLM) using the Extreme Learning Machine (ELM) technique, with the aim of enhancing computational efficiency. Furthermore, to achieve better alignment with load response curves, a Quantum Particle Swarm Optimization (QPSO) algorithm is adopted to train the ELM model. The proposed QPSO-ELM-based SLM parameter identification method is subsequently evaluated using a standard test system. To assess its effectiveness, parameter sensitivity analysis is performed, and simulation results are analyzed. The findings demonstrate that the proposed method yields favorable outcomes, offering improved computation efficiency in load model parameter identification tasks

Multi-Searcher Optimization for the Optimal Energy Dispatch of Combined Heat and Power-Thermal-Wind-Photovoltaic Systems

This paper proposes a novel multi-searcher optimization (MSO) algorithm for the optimal energy dispatch (OED) of combined heat and power-thermal-wind-photovoltaic systems. The available power of wind turbine (WT) units and photovoltaic (PV) units is approximated with the probability density functions of wind speed and solar irradiance, respectively. The chaos theory is used to implement a wide global search, which can effectively avoid a low-quality local optimum for OED. Besides, a double-layer searcher is designed to guarantee fast convergence to a high-quality optimal solution. Finally, three benchmark functions and an energy system with 27 units are used for testing the performance of the MSO compared with nine other frequently used heuristic algorithms. The simulation results demonstrate that the proposed technique not only can solve the highly nonlinear, non-smooth, and non-convex OED problem of an energy system, but can also achieve a superior performance for the convergence speed and the optimum quality

Coordinated Planning and Energy Conservation for Distribution Network with Renewable Energy: Standardized Information Model and Software

In recent years, energy conservation and environmental protection have attracted great attention by the state, and many efforts have been made from the policy and planning level. In view of the current distribution network planning requirements about energy-saving and environmental protection attributes such as loss reduction, carbon reduction, and environmental friendliness, this study proposes a set of energy-saving and environmental protection evaluation indicators for distribution network. Then, the CIM file library is constructed for typical equipment. Based on the CIM file, the digital planning technology for distribution network is designed. Besides, the feature library of energy conservation and environmental protection indicators, power flow calculation module, carbon flow calculation module, and renewable energy integration planning module are described

Energy Separation for Ranque-Hilsch Vortex Tube: A short review

© 2020 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/.In this article, the development of the energy separation for the vortex tube has been briefly reviewed. This review mainly focuses on three aspects, they are the energy separation principle, the design criteria of vortex tubes, and practical application. First, the research progress on the energy separation principle of the vortex tube from several aspects has been introduced, such as friction, pressure gradient, acoustic streaming, secondary circulation and multi-circulation theory. In addition, the control factors that affecting the performance of the vortex tube were summarized. Furthermore, due to its simple structure, safety and stability, the vortex tube is widely used in the field of refrigerating and heating, mixture separation. This survey, while extensive cannot cover all papers, some selection is necessary. The purpose of this review aims to summarize the important works of literature on the energy separation of vortex tube as well as identify limitations to existing studies and directions for future research.Peer reviewe