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On the k-error linear complexity of 2p~2-periodic binary sequences

science China(Information sciences) 2020年第9期63卷 263-276页

作者： Zhihua NIU Can YUAN Zhixiong CHEN Xiaoni DU Tao ZHANG School of Computer Engineering and Science Shanghai University College of Mathematics and Statistics Northwest Normal University Provincial Key Laboratory of Applied Mathematics Putian University

Dear editor,Pseudorandom sequences play an important role in cryptography. In particular in symmetric cryptography they serve as the secret key. So the designs of pseudorandom sequences and cryptographic indicators ar...

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Explainable-AI-based two-stage solution for WSN object localization using zero-touch mobile transceivers

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science China(Information sciences) 2024年第7期67卷 27-45页

作者： Kai FANG Junxin CHEN Han ZHU Thippa Reddy GADEKALLU Xiaoping WU Wei WANG School of Mathematics and Computer Science Zhejiang A&F University School of Software Dalian University of Technology Faculty of Applied Sciences Macao Polytechnic University Department of Electrical and Computer Engineering Lebanese American University School of Information Engineering Huzhou University Guangdong-Hong Kong-Macao Joint Laboratory for Emotional Intelligence and Pervasive Computing Artificial Intelligence Research Institute Shenzhen MSU-BIT University

Artificial intelligence technology is widely used in the field of wireless sensor networks(WSN).Due to its inexplicability, the interference factors in the process of WSN object localization cannot be effectively eliminated. In this paper, an explainable-AI-based two-stage solution is proposed for WSN object localization. In this solution, mobile transceivers are used to enlarge the positioning range and eliminate the blind area for object localization. The motion parameters of transceivers are considered to be unavailable,and the localization problem is highly nonlinear with respect to the unknown parameters. To address this,an explainable AI model is proposed to solve the localization problem. Since the relationship among the variables is difficult to fully include in the first-stage traditional model, we develop a two-stage explainable AI solution for this localization problem. The two-stage solution is actually a comprehensive consideration of the relationship between variables. The solution can continue to use the constraints unused in the firststage during the second-stage, thereby improving the performance of the solution. Therefore, the two-stage solution has stronger robustness compared to the closed-form solution. Experimental results show that the performance of both the two-stage solution and the traditional solution will be affected by numerical changes in unknown parameters. However, the two-stage solution performs better than the traditional solution, especially with a small number of mobile transceivers and sensors or in the presence of high noise. Furthermore,we have also verified the feasibility of the proposed explainable-AI-based two-stage solution.

关键词： explainable AI object localization semidefinite relaxation mobile transceiver two-stage solution closed-form solution

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Recent advances in particle swarm optimization analysis and understanding 2021 21

Recent advances in particle swarm optimization analysis and ...

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2021 Genetic and Evolutionary Computation Conference, GECCO 2021

作者： Engelbrecht, A P Cleghorn, C W Stellenbosch University Department of Industrial Engineering South Africa Division of Computer Science Stellenbosch University South Africa University of the Witwatersrand School of Computer Science and Applied Mathematics South Africa

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On a Cyclometric Modification of the Chua System 6

On a Cyclometric Modification of the Chua System

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6th IEEE International Conference and Workshop Obuda on Electrical and Power engineering, CANDO-EPE 2023

作者： Nagy, Balint Joos, Antal Kovari, Attila Institute of Computer Engineering University of Dunaujvaros Department of Mathematics Dunaujvaros Hungary Institute of Electrophysics Obuda University Kandó Kálmán Faculty of Electrical Engineering Department of Natural Sciences Budapest Hungary Budapest Business University Faculty of Finance and Accountancy Department of Applied Quantitative Methods Budapest Hungary Institute of Digital Technology Eszterházy Károly Catholic University Faculty of Computer Science Eger Hungary Institute of Engineering University of Dunaújváros Department of Natural Sciences Dunaujvaros Hungary John von Neumann University Gamf Faculty of Engineering and Computer Science Kecskemét Hungary

ISBN: (纸本)9798350328752

Chaos is not only a unique chapter in the theory of dynamical systems but also a useful one with many applications in the field of communications. In this work a cyclometric modification of the well-known example of chaotic systems, the modified differential equations describing the behavior of the Chua-circuit is investigated. The results obtained can be applied in the encryption methods of the implementation of different communication channels like machine-machine or cognitive one. © 2023 IEEE.

关键词： Chaotic systems

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Multi-objective VNF Placement Optimization with NSGA-III 1st

Multi-objective VNF Placement Optimization with NSGA-III

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1st International Conference on Advances in Computing Research, ACR’23

作者： Bekhit, Mahmoud Fathalla, Ahmed Eldesouky, Esraa Salah, Ahmad Faculty of Engineering and Information Technology University of Technology Sydney Sydney Australia Kent Institute Australia Melbourne Australia Department of Mathematics Faculty of Science Suez Canal University Ismailia Egypt Department of Computer Science College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz University Al-Kharj Saudi Arabia College of Computers and Informatics Zagazig University Zagazig Egypt College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Oman

ISBN: (纸本)9783031337420

With the rising acceptance of virtual network functions (VNFs) as a replacement for traditional network functions, the optimal placement of VNFs has become a crucial task for ensuring constant performance within constrained resources. This research investigates the challenge of mapping and scheduling VNFs as a multi-objective optimization problem. The state-of-the-art methods have focused on optimizing the mapping or scheduling of VNFs while considering one or two objectives continuously. In this study, we aim to optimize two objectives: minimizing the link capacity cost and maximizing the average resource utilization of each virtual machine. To address this problem, an adaptation of the NSGA-III optimization algorithm is proposed and thoroughly evaluated through a set of experiments. In terms of objective values, the results outlined that the proposed method outperformed the other methods of comparison by a significant margin. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Mapping

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Efficient Privacy-Preserving ML for IoT: Cluster-Based Split Federated Learning Scheme for Non-IID Data 7

Efficient Privacy-Preserving ML for IoT: Cluster-Based Split...

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7th Cyber Security in Networking Conference, CSNet 2023

作者： Arafeh, Mohamad Wazzeh, Mohamad Ould-Slimane, Hakima Talhi, Chamseddine Mourad, Azzam Otrok, Hadi Department of Software and It Engineering Montreal Canada Department of Mathematics and Computer Science Canada New York University Division of Science Abu Dhabi United Arab Emirates Cyber Security Systems and Applied Ai Research Center Lebanese American University Department of Csm Beirut Lebanon Khalifa University Department of Eecs Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350342871

This paper proposes a scheme addressing the challenges of integrating privacy-preserving distributed machine learning in the Internet of Things (IoT) context while improving the efficiency of the learning process and accelerating the convergence of the model. Specifically, it addresses the presence of non-independent and identically distributed (Non-IID) data and device heterogeneity, which occurs during parallel training and are common characteristics of IoT environments. In this context, SplitFed is a privacy-preserving technique that combines Federated Learning (FL) and Split Learning (SL) to enable fast and privacy-preserving model training on IoT devices. Through parallelism, FL allows fast and parallel model training. Furthermore, SL enables weak devices to train models through model splitting. However, SplitFed suffers from the increasing convergence time due to the FL parallelism introducing Non-IID and stragglers issues. In this paper, we aim to address the aforementioned problems by proposing a clustering parallelization scheme. As such, similar clients are combined based on their weight divergence and considered a single FL unit addressing the Non-IID problem. Moreover, to improve time efficiency and overcome the stragglers' presence, we offer a second clustering stage that separates clients by efficiency and uses FedAsync for model aggregation. © 2023 IEEE.

关键词： Internet of things

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Invisible Servoing: a Visual Servoing Approach with Return-Conditioned Latent Diffusion

arXiv

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arXiv 2024年

作者： Gerges, Bishoy Bazzana, Barbara Botteghi, Nicolò Aboudorra, Youssef Franchi, Antonio Robotics and Mechatronics Group Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede7500AE Netherlands Department of Applied Mathematics University of Twente Enschede7500AE Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome00185 Italy

In this paper, we present a novel visual servoing (VS) approach based on latent Denoising Diffusion Probabilistic Models (DDPMs). Opposite to classical VS methods, the proposed approach allows reaching the desired target view, even when the target is initially not visible. This is possible thanks to the learning of a latent representation that the DDPM uses for planning and a dataset of trajectories encompassing target-invisible initial views. The latent representation is learned using a Cross-Modal Variational Autoencoder, and used to estimate the return for conditioning the trajectory generation of the DDPM. Given the current image, the DDPM generates trajectories in the latent space driving the robotic platform to the desired visual target. The approach is applicable to any velocity-based controlled platform. We test our method with simulated and real-world experiments using generic multi-rotor Uncrewed Aerial Vehicles (UAVs). A video of our experiments can be found at https://***/yu-aTxqceOA. Copyright © 2024, The Authors. All rights reserved.

关键词： Trajectories

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Modeling and numerical analysis of nanoliquid (titanium oxide, graphene oxide) flow viscous fluid with second order velocity slip and entropy generation

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Chinese Journal of Chemical engineering 2021年第3期34卷 17-25页

作者： M.Ijaz Khan Seifedine Kadry Yuming Chu M.Waqas Department of Mathematics Riphah International UniversityFaisalabad CampusFaisalabad 38000Pakistan Department of Mathematics and Computer Science Beirut Arab UniversityBeirutLebanon Department of Mathematics Huzhou UniversityHuzhou 313000China Hunan Provincial Key Laboratory of Mathematical Modeling and Analysis in Engineering Changsha University of Science&TechnologyChangsha 410114China NUTECH School of Applied Sciences and Humanities National University of TechnologyIslamabad 44000Pakistan

The prime objective of the present communication is to examine the entropy-optimized second order velocity slip Darcy–Forchheimer hybrid nanofluid flow of viscous material between two rotating *** conducting flow is considered and saturated through Darcy–Forchheimer *** the disks are rotating with different angular frequencies and stretches with different *** graphene oxide and titanium dioxide are considered for hybrid nanoparticles and water as a continuous phase *** heating,heat generation/absorption and viscous dissipation effects are incorporated in the mathematical modeling of energy ***,binary chemical reaction with activation energy is *** total entropy rate is calculated in the presence of heat transfer irreversibility,fluid friction irreversibility,Joule heating irreversibility,porosity irreversibility and chemical reaction irreversibility through thermodynamics second *** nonlinear governing equations are first converted into ordinary differential equations through implementation of appropriate similarity transformations and then numerical solutions are calculated through Built-in-Shooting *** of sundry flow variables on the entropy generation rate,velocity,concentration,Bejan number,temperature are discussed graphically for both graphene oxide and titanium dioxide hybrid *** engineering interest like skin friction coefficient and Nusselt number are computed numerically and presented through *** is noticed from the obtained results that entropy generation rate and Bejan number have similar effects versus diffusion *** entropy generation rate is more against the higher Brinkman number.

关键词： Darcy-Forchheimer porous medium Titanium dioxide and graphene oxide nanoparticles Second order velocity slip Convective boundary condition Activation energy Heat generation/absorption

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Critical nonlinear aspects of hopping transport for reconfigurable logic in disordered dopant networks

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Physical Review applied 2024年第2期22卷 024063页

作者： Henri Tertilt Jonas Mensing Marlon Becker Wilfred G. van der Wiel Peter A. Bobbert Andreas Heuer Institute for Physical Chemistry Department of Physics NanoElectronics Group Faculty of Electrical Engineering Mathematics and Computer Science MESA+ Institute for Nanotechnology and Center for Brain-Inspired Nano Systems (BRAINS) Department of Applied Physics Center for Computational Energy Research (CCER)

Nonlinear behavior in the hopping transport of interacting charges enables reconfigurable logic in disordered dopant network devices, where voltages applied at control electrodes tune the relation between voltages applied at input electrodes and the current measured at an output electrode. From kinetic Monte Carlo simulations we analyze the critical nonlinear aspects of variable-range hopping transport for realizing Boolean logic gates in these devices on three levels. First, we quantify the occurrence of individual gates for random choices of control voltages. We find that linearly inseparable gates such as the xor gate are less likely to occur than linearly separable gates such as the and gate, despite the fact that the number of different regions in the multidimensional control voltage space for which and or xor gates occur is comparable. Second, we use principal-component analysis to characterize the distribution of the output current vectors for the (00,10,01,11) logic input combinations in terms of eigenvectors and eigenvalues of the output covariance matrix. This allows a simple and direct comparison of the behavior of different simulated devices and a comparison to experimental devices. Third, we quantify the nonlinearity in the distribution of the output current vectors necessary for realizing Boolean functionality by introducing three nonlinearity indicators. The analysis provides a physical interpretation of the effects of changing the hopping distance and temperature and is used in a comparison with data generated by a deep neural network trained on a physical device.

关键词： Carrier dynamics Dynamics of networks Electrical conductivity Fitness Hopping transport Network optimization Optimization problems Temperature

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IT-Security Risk Based Approach for Secure Operation of Distributed Data Platforms in Supply Chains

IT-Security Risk Based Approach for Secure Operation of Dist...

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IEEE International Conference on Industrial engineering and engineering Management

作者： Marvin Voß Jonas Kallisch Maxim Runge Tobias Theus Karl-Heinz Niemann Christoph Wunck Faculty I - Electrical Engineering and Information Technology University of Applied Sciences and Arts Hannover Germany Department of Engineering Section Electrical Engineering and Computer Science University of Applied Sciences Emden/Leer Germany Faculty of Mathematics Informatics and Statistics Ludwig Maximilian University Munich Germany

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

This paper presents the development of a secure data platform designed to enhance operational efficiency and to facilitate cross-company collaboration within the manufacturing supply chain. The platform is designed to ease secure information exchange while maintaining the sovereignty of each participant, leveraging standardized security features and advanced technologies such as federated learning. Security measures are based on a comprehensive risk analysis, which methodically identifies, assesses, and mitigates potential threats. Moreover, federated learning models that are not transparent are utilized. This allows data owners to maintain control over sensitive information within the consortium. The described approach markedly enhances both security and operational collaboration across the industry, representing a crucial stride towards more integrated and efficient supply chain management in manufacturing.

关键词： Industries Supply chain management Federated learning Supply chains Collaboration Particle measurements Manufacturing Security Risk analysis Information exchange

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