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23rd International Conference on Machine Learning and Cybernetics, ICMLC 2024

作者： Simpson, Lachlan Costanza, Federico Millar, Kyle Cheng, Adriel Lim, Cheng-Chew Chew, Hong Gunn School of Computer and Mathematical Sciences The University of Adelaide Australia School of Electrical and Mechanical Engineering The University of Adelaide Australia Defence Science & Technology Group Information Sciences Division Australia

ISBN: (纸本)9798331528041

Adversarial attacks on explainability models have drastic consequences when explanations are used to understand the reasoning of neural networks in safety critical systems. Path methods are one such class of attribution methods susceptible to adversarial attacks. Adversarial learning is typically phrased as a constrained optimisation problem. In this work, we propose algebraic adversarial examples and study the conditions under which one can generate adversarial examples for integrated gradients. Algebraic adversarial examples provide a mathematically tractable approach to adversarial examples. © 2024 IEEE.

关键词： Adversarial machine learning

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Efficient Steady-State Tissue Simulation for Surgical Robotics: A First-Order Position-Based Method

Efficient Steady-State Tissue Simulation for Surgical Roboti...

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International Symposium on Medical Robotics (ISMR)

作者： Samuel Tobin Yufei Wu Fei Liu Caleb Rucker Department of Mechanical Aerospace & Biomedical Engineering University of Tennessee Knoxville TN USA Department of Electrical Engineering & Computer Science University of Tennessee Knoxville TN USA

ISBN: (数字)9798331599003

ISBN: (纸本)9798331599010

Soft tissue simulation can play an essential role in the automation of robotic surgery by providing contextual information during surgery and generating datasets for training. Any time tissue deformations are simulated, computational speed, accuracy, and stability are key concerns. State-of-theart tissue simulation resolves inertial dynamics solutions using position-based computational methods. However, existing methods fail to efficiently resolve steady-state solutions at surgical size scales because of transient inertial dynamics and the small time step required for stability at such size scales. We propose a position-based tissue simulation framework which is based on large-deformation Neo-Hookean elasticity and enables fast resolution to steady-state for efficient simulation. Our method replaces the inertial terms in the model with a virtual viscous damping term. This enables realistic tissue motion while eliminating the transient vibrations that require more computation. It also enables smooth and stable dynamic transitions between disparate static states. We detail the selection of parameters and step sizes for efficient steady-state simulation. We further compare our approach to a state-of-the-art position-based method and show significant improvements in stability and realtime performance at surgical size scales.

关键词： Vibrations Training Medical robotics Deformation Dynamics Surgery Elasticity Stability analysis Steady-state Transient analysis

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WAVEFIELD CHARACTERIZATION OF LAMB WAVE PROPAGATION IN COMPOSITE PLATES BASED ON GUIDED WAVE OMNIDIRECTIONAL WAVENUMBER SIMULATION 18

WAVEFIELD CHARACTERIZATION OF LAMB WAVE PROPAGATION IN COMPO...

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18th Symposium on Piezoelectricity, Acoustic Waves, and Device Applications, SPAWDA 2024

作者： Wang, Lei Liu, Hongye Sun, Maoxun Chen, Xiaorong Shen, Liang Qiu, Chongpeng Tian, Zhenhua School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China Department of Mechanical Engineering Virginia Polytechnic Institute State University 1145 Perry Street BlacksburgVA24061 United States

ISBN: (纸本)9798331523732

With the growing application of composite materials in sectors such as aerospace, automotive, and wind energy, accurately assessing their mechanical properties is critical for effective non-destructive testing (NDT) and structural health monitoring (SHM). In this paper, a three-dimensional finite element model was developed to generate the fundamental A0 Lamb wave mode within an 8-layer orthotropic laminate, addressing the complexities associated with the anisotropic behavior of composites. Utilizing the Legendre Orthogonal Polynomial Expansion (LOPE) method, we characterized the wave number profile, revealing significant directional dependence in wave propagation across multilayer laminates. The results demonstrated strong agreement between the analytical predictions from the LOPE method and the finite element simulations, confirming the robustness of our modeling approach. Additionally, we introduced an innovative omnidirectional wavefield representation method, effectively mitigating the influence of phase and group velocity steering angles. These findings enhance our understanding of guided wave dynamics in composite materials, offering valuable insights for the development of more effective detection strategies and assessments of structural integrity in complex composite systems. © 2024 IEEE.

关键词： Gravity waves

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Fatigue crack propagation across grain boundary of Al-Cu-Mg bicrystal based on crystal plasticity XFEM and cohesive zone model

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Journal of Materials science & Technology 2022年第31期126卷 275-287页

作者： Qi Zhao Magd Abdel Wahab Yong Ling Zhiyi Liu School of Materials Science and Engineering Hubei University of Automotive TechnologyShiyan 442002China Faculty of Mechanical-Electrical and Computer Engineering School of Engineering and TechnologyVan Lang UniversityHo Chi Minh CityVietnam Soete Laboratory Faculty of Engineering and ArchitectureGhent UniversityTechnologiepark Zwijnaarde 903B-9052 ZwijnaardeBelgium School of Materials Science and Engineering Central South UniversityChangsha 410083China

In this paper,a methodology integrating crystal plasticity(CP),the eXtended finite element method(XFEM)and the cohesive zone model(CZM)is developed for an Al-Cu-Mg alloy to predict fatigue crack propagation(FCP)across grain boundary(GB)of Al-Cu-Mg alloy during stageІІ.One GB model is incor-porated into FCP constitutive law to describe grain interaction at GB.A bicrystal containing GB is built up to simulate FCP behavior through L participated *** features including GB characteristic,cumulative plastic strain(CPS)distribution and crystal slipping evidence can be *** numer-ical results are compared with published experimental data to check the accuracy of *** work demonstrates that the combination of CP containing GB constitutive laws,XFEM and CZM is a promising methodology in predicting twist angle-controlled crack deflection through GBs.

关键词： Grain boundary Twist angle Crystal plasticity Extended finite element method Fatigue crack propagation Cumulative plastic strain

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Style-constrained Takagi-Sugeno-Kang Fuzzy Classifier

Style-constrained Takagi-Sugeno-Kang Fuzzy Classifier

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2023 IEEE International Conference on Control, Electronics and computer Technology, ICCECT 2023

作者： Gu, Suhang Shi, Hangming Zhou, Jie Jiang, Zhibin Lu, Mingli Zhu, Peiyi Changzhou University School of Mechanical Engineering and Rail Transit Changzhou China Shaoxing University Department of Computer Science and Engineering Shaoxing China Changshu Institue of Technology School of Electrical Engineering and Automation Suzhou China

ISBN: (纸本)9798350399028

Due to the excellent interpretability and classification performance, the Takagi-Sugeno-Kang fuzzy classifier (TSK-FC) has drawn great attention. However, different patterns own their respective homogeneities, and the samples from different groups present explicitly or implicitly homogenous styles, which are significantly different from the assumption that all samples from different groups are identically and independently distributed (i.i.d.). In this paper, a style-constrained Takagi-Sugeno-Kang fuzzy classifier called SC-TSK-FC is proposed by breaking the i.i.d. assumption. To explore the styles of data, a series of style matrices are embedded into the objective function of the TSK-FC. Besides, with the introduction of the regularization term corresponding to each style matrix, the nuances between different styles of data can be captured, which can help improve the classification performance of SC-TSK-FC. Particularly, five fixed fuzzy partitions with interpretable linguistic terms are adopted to along each input feature, and SC-TSK-FC outperforms TSKFC by using less fuzzy rules. These guarantee the interpretability of SC-TSK-FC. Experimental results on some benchmark datasets demonstrate the effectiveness of the proposed SC-TSK-FC. © 2023 IEEE.

关键词： Matrix algebra

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Measurement-Device-Independent Deterministic Quantum Key Distribution 9

Measurement-Device-Independent Deterministic Quantum Key Dis...

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9th Annual International Conference on Network and Information Systems for computers, ICNISC 2023

作者： Zhang, Ting Liu, Jie Kang, Guodong Jishou University School of Physics and Mechanical and Electrical Engineering Jishou China Jishou University School of Computer Science and Engineering School of Physics and Mechanical and Electrical Engineering Jishou China Hunan Normal University Key Laboratory of Low Dimensional Quantum Structures and Quantum Control Ministry of Education College of Physics and Electronic Science Changsha China

ISBN: (纸本)9798350306682

Improve the secure key rate and the limited communication distance is the main goal in the field of quantum key distribution. Measurement-device-independent quantum key distribution, not only removes all detector side channel attacks, but also doubles the secure transmission distance. However, most of measurement-device -independent quantum key distribution protocols are non-deterministic. In this paper, we propose a measurement-device-independent deterministic quantum key distribution protocol that doubles the secure distance and amends the non-deterministic factor of current measurement-device -independent quantum key distribution. And with imperfect devices model assumption, we derived the formula of the performances for it and find that the limited distance can be extended over 200km with relatively high secure key rate by employing parameters of current technologies. © 2023 IEEE.

关键词： Quantum cryptography

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AI-Driven Personalization of E-Therapy Interventions for Anxiety, Stress, and Depression 18

AI-Driven Personalization of E-Therapy Interventions for Anx...

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18th International Conference on Open Source Systems and Technologies, ICOSST 2024

作者： Ramzan, Hafiz Arslan Abdulah, Fatima Ahmad, Muddaber Ramzan, Sadia Ashraf, Munazza School of Electrical Engineering and Computer Science National University of Sciences and Technology Islamabad Pakistan School of Mechanical and Manufacturing Engineering National University of Sciences and Technology Islamabad Pakistan National University of Computer and Emerging Sciences Department of Computer Science Chiniot Faisalabad Pakistan GIFT University Department of Humanities and Social Sciences Gujranwala Pakistan

ISBN: (纸本)9798331508692

This study explores the use of artificial intelligence (AI) to personalize e-therapy interventions for anxiety, stress, and depression. Leveraging machine learning models, including K-Nearest Neighbors (KNN), Support Vector Machines (SVM), and Decision Trees, we analyze a dataset of depression, anxiety, and stress scales responses to develop predictive models that tailor therapeutic interventions. The accuracy and efficacy of proposed models vary, indicating that AI has the potential to improve the level of personalization of mental health therapies. The results indicate that AI-driven techniques can significantly improve the effectiveness and efficiency of e-therapy platforms. © 2024 IEEE.

关键词： Adversarial machine learning

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Design and Implementation of Renewable Energy Applications Based Bi-Directional Buck-Boost Converter 3

Design and Implementation of Renewable Energy Applications B...

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3rd International Conference on Innovative Practices in Technology and Management, ICIPTM 2023

作者： Ramana, K. Venkata Arulkumar, S. Marathe, Asmita Beshir, Kedir Jaiganesh, V. Tamilselvi, K. Sudhakar, M. Vnr Vignana Jyothi Institute of Engineering & Technology Department of Computer Scinece and Engineering Hyderabad India Wachemo University Centre for Energy Studies Department of Electrical and Computer Engineering Ethiopia Savitribai Phule Pune University Department of Technology Pune India Wachemo University Department of Electrical and Computer Engineering 667 Ethiopia Bharath Institute of Higher Education and Research Department of Mechanical Engineering Tamil Nadu Chennai India Panimalar Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Sri Sai Ram Engineering College Department of Mechanical Engineering Chennai India

ISBN: (纸本)9798350336238

Our main focus was on creating a Two directional power converter for a standalone photo-voltaic energy-generating technology as well as technology energy control when a lead-acid energy storage device is used to control the energy supply. We utilized a light bulb as the load to evaluate the effectiveness of the directional power converter developed as part of our project as well as the functionality of energy control technologies. The suggested technology was composed of an energy control technology, a lead-acid battery, a bulb, a two-directional buck-boost converter, an utmost power point tracking controller, and these components. An energy control technique was developed to grow the rate at which the Photo-voltaic power producing technology consumed energy. The circuits are intended to charge the battery between upper and lower voltage limits, as well as to continuously check the battery's state of charge and add or release current as necessary. The bidirectional buck-boost converter's ability to function as a charge controller on its own, along with the use of particular BUCK and BOOST converter properties to optimize the home application, is the primary distinction between the method used in the proposed technology and other techniques used in the past. The battery is charged and discharged using a bidirectional dc-dc converter. Measurement data are employed to support the viability of a photovoltaic air conditioning technology. © 2023 IEEE.

关键词： Buck-Boost converter

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Sparse Dynamic Network Reconstruction Through L1-regularization of a Lyapunov Equation 63

Sparse Dynamic Network Reconstruction Through L1-regularizat...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Belaustegui, Ian Xul Arango, Marcela Ordorica Rossi-Pool, Roman Leonard, Naomi Ehrich Franci, Alessio Princeton University Department of Mechanical and Aerospace Engineering United States Universidad Nacional Autónoma de México Instituto de Fisiología Celular - Neurociencias and Centro de Ciencias de la Complejidad Mexico University of Liege Wel Research Institute Department of Electrical Engineering and Computer Science Wavre Belgium

ISBN: (纸本)9798350316339

An important problem in many areas of science is that of recovering interaction networks from high-dimensional time-series of many interacting dynamical processes. A common approach is to use the elements of the correlation matrix or its inverse as proxies of the interaction strengths, but the reconstructed networks are necessarily undirected. Transfer entropy methods have been proposed to reconstruct directed networks, but the reconstructed network lacks information about interaction strengths. We propose a network reconstruction method that inherits the best of the two approaches by reconstructing a directed weighted network from noisy data under the assumption that the network is sparse and the dynamics are governed by a linear (or weakly-nonlinear) stochastic dynamical system. The two steps of our method are i) constructing an (infinite) family of candidate networks by solving the covariance matrix Lyapunov equation for the state matrix and ii) using L1-regularization to select a sparse solution. We further show how to use prior information on the (non)existence of a few directed edges to dramatically improve the quality of the reconstruction. © 2024 IEEE.

关键词： Stochastic systems

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Implementing a Robust and Scalable Detect-and-Avoid Algorithm for UAV Navigation in ROS 15

Implementing a Robust and Scalable Detect-and-Avoid Algorith...

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15th International Conference on Information, Intelligence, Systems and Applications, IISA 2024

作者： Meimetis, Dimitrios Daramouskas, Ioannis Lappas, Vaios Perikos, Isidoros Kapoulas, Vaggelis Paraskevas, Michael Nkua Department of Aerospace Science & Technology Athens Greece Computer Technology Institute and Press 'Diophantus' Patras Greece UoP Applied Mechanics Lab Patras Greece UoP Computer Engineering and Informatics Department Patras Greece Computer Technology Institute and Press 'Diophantus' University of Peloponnese Electrical and Computer Engineering Dept. Patras Greece

ISBN: (纸本)9798350368833

Unmanned aerial vehicles (UAVs) have garnered significant attention from the research community during the last decade, due to their diverse capabilities and potential applications. One of the most critical functions that drones must execute efficiently is navigation in real-world environments. This paper presents a decentralized approach for enabling unmanned aerial vehicles (UAVs) to navigate safely in unknown environments and avoid obstacles. Leveraging the Optimal Reciprocal Collision Avoidance (ORCA) algorithm, implemented in the Robot Operating System (ROS), our method facilitates conflict detection and resolution in 2D environments. Through simulations using ROS, Gazebo, and Iris drones, we validate the effectiveness of our approach in scenarios with initial trajectory conflicts. Our work addresses the pressing need for UAVs to autonomously plan and execute safe flights, laying the groundwork for enhanced UAV capabilities in various real-world applications. The simulation results demonstrate the efficiency and robustness of our approach. © 2024 IEEE.

关键词： Drones

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