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9th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2020

作者： Zhang, Gaofei Zhang, Zheng Wang, Jiang Ji, Xinsheng State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Information Engineering University Zhengzhou China

With the rapid development of the information society, there are corresponding tool solutions for various daily problems. Aiming at the complex generation process and inconvenient operation of heterogeneous components in a security defense system constructed with dissimilar redundancy, in this paper, we propose a practical basic software application isomerization tool chain, which integrates a series of key technologies of heterogeneous structures. At the same time, corresponding automated tests are provided for users to conduct comprehensive evaluation. Experimental evaluation shows that the tool chain will be able to provide heterogeneous component support for security defense technologies based on dissimilarity redundancy construction and improve the security of software systems. © 2020 IEEE.

关键词： Application programs

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MXenes@Te as a composite material for high-performance aluminum batteries

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Science China Materials 2022年第1期65卷 85-94页

作者： Xiaogeng Huo Xiaoxu Wang Jianling Li Bao Zhang Yu Zhang Te Qin Feiyu Kang State Key Laboratory of Advanced Metallurgy School of Metallurgical and Ecological EngineeringUniversity of Science and Technology BeijingBeijing 100083China Beijing computing center Beijing Academy of Science and TechnologyBeijing 100094China Laboratory of Advanced Materials School of Materials Science and EngineeringTsinghua UniversityBeijing 100084China

The emerging two-dimensional(2D)materials,MXenes,play an important role in various fields of energy storage and exhibit excellent electrochemical ***,we prepared few-layered MXenes(F-Ti_(3)C_(2)T_(x))and loaded Te on the surface of F-Ti_(3)C_(2)T_(x) by using a simple hightemperature evaporation *** addition,the electrochemical performance of the aluminum battery with F-Ti_(3)C_(2)T_(x) as support material was *** initial charge/discharge specific capacities are 987/1096mAh g^(-1)at 0.2Ag^(-1).An obvious discharge voltage plateau of about 1.3V appears at various current *** specific capacity is about 258mAh g^(-1)with MXenes@Te as the active material in the aluminum battery,which benefits from the excellent electronic conductivity of the MXenes and their 2D layered *** functional theory calculations were carried out to explore the ***_(3)C_(2)O_(2)@Te is more inclined to adsorb[AlCl_(4)]^(-) than Ti_(3)C_(2)O_(2).Furthermore,the valence change behavior of element Te was studied by using thermodynamic calculation(FactSage 7.1).X-ray photoelectron spectroscopy results show that when the battery is fully charged to 2.4V element Te and Ti ions(Ti^(3+),Ti^(2+))are oxidized to Te^(4+)and Ti^(4+).In contrast to the charging process,the high-valence Te^(4+)and Ti^(4+)are reduced again during *** Te is reduced to lower-valence Te^(2-)when the discharge voltage is lower than 0.6 V,and a higher charge voltage(2.56 V)is required for Te to be oxidized to Te^(6+).

关键词： MXenes@Te aluminum batteries specific capacity density functional theory

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A novel hyperchaotic multistable heterogeneous neural network with hidden attractors and its application in image encryption

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Chinese Journal of Physics 2025年 96卷 851-874页

作者： Zhi Huang Zhen Li Qiao Wang Weijie Tan Xianming Wu College of Big Data and Information Engineering Guizhou University Guiyang 550025 China State Key Laboratory of Public Big Data Guizhou University Guiyang 550025 China Guizhou Key Laboratory of Artificial Intelligence and Brain-inspired Computing College of Mathematics and Big Data Guizhou Education University Guiyang 550018 China State Key Laboratory of Public Big Data Key Laboratory of Advanced Manufacturing Technology of Ministry of Education Guizhou University Guiyang 550025 China School of Mechanical and Electrical Engineering Guizhou Normal University Guiyang 550025 China

By simulating the unique properties of different types of neurons and their interconnecting patterns, heterogeneous neural networks can more accurately reflect the structural and functional characteristics of biological neural systems. Therefore, a novel hyperbolic non-volatile locally active memristor is proposed, enabling the construction of a heterogeneous Hindmarsh–Rose neuron memristive synapse-coupled Hopfield neural network (HR-M-HNN) via synaptic characteristic emulation. Dynamic analysis reveals that the HR-M-HNN exhibits hidden attractor characteristics due to the absence of equilibrium points and can generate complex dynamics behaviors, including hyperchaos, chaos, periodic and quasi-periodic, and multistability. Further research reveals a strong correlation between the chaotic state of HR-M-HNN and the locally active control parameter of the memristor. To verify the accuracy of the dynamic analysis, the corresponding analog circuit is designed. Furthermore, based on the HR-M-HNN hyperchaotic system, a novel image encryption scheme is proposed, which utilizes the position index of the Latin square to perform synchronous permutation and diffusion on the plain image, reducing redundant operations and effectively enhancing the encryption speed. Security analyses demonstrate that the proposed image encryption scheme offers excellent performance and robustness.

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Neural Manifold Learning Based on 40 nm Dual-Mode PCM Compute-in-Memory Chip with Hardware Adaptive Drift Compensation

Neural Manifold Learning Based on 40 nm Dual-Mode PCM Comput...

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2024 IEEE International Electron Devices Meeting, IEDM 2024

作者： Yan, Longhao Li, Yuqi Li, Xi Pan, Zelun Wang, Zeyu Wang, Xile Wang, Bowen Zhan, Zhe Tang, Xiyuan Tao, Yaoyu Ge, Woo-Ping Song, Zhitang Huang, Ru Yang, Yuchao Beijing Advanced Innovation Center for Integrated Circuits School of Integrate Circuits Peking University Beijing China Beijing China Center for Brain Inspired Chips Institute for Artificial Intelligence Peking University Beijing China Guangdong Provincial Key Laboratory of In-Memory Computing Chips School of Electronic and Computer Engineering Peking University Shenzhen China State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences China

ISBN: (纸本)9798350365429

Neural manifold learning (NML), as a significant research topic in the field of neuroscience, plays a vital role in the realization of intelligent brain-computer interface (BCI) at the edge. However, traditional edge computing platforms fall short in meeting the demands for the huge computing power needed to process massive neural data. Here, we design a 288Kb dual-mode phase change memory (PCM) compute-in-memory chip in 40nm technology and utilize its two cores for two fundamental kernels in NML, vector matrix multiplication (VMM) and true random number generation, and develop a PCM-based NML system for the first time. In particular, in order to mitigate the performance degradation caused by PCM conductance drift, we propose a novel adaptive-PCM-drift-compensation scheme that significantly improves the accuracy of VMM results. Compared with CPU platforms running the same tasks, the resulting chip improves the computing energy efficiency and throughput by 476× and 264×, respectively. © 2024 IEEE.

关键词： Random number generation

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Integrating Artificial Intelligence into Operating Systems: A Comprehensive Survey on Techniques, Applications, and Future Directions

arXiv

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arXiv 2024年

作者： Zhang, Yifan Zhao, Xinkui Li, Ziying Yin, Jianwei Zhang, Lufei Chen, Zuoning School of Software Technology Zhejiang University Zhejiang Ningbo315048 China College of Computer Science and Technology Zhejiang University Zhejiang Hangzhou310058 China State Key Laboratory of Mathematical Engineering and Advanced Computing Jiangsu Wuxi214125 China Chinese Academy of Engineering Beijing100088 China

In the era of the Internet of Everything, operating systems (OSs) face unprecedented challenges posed by an evolving application landscape and increasingly heterogeneous hardware ecosystems. This shift toward increasingly dynamic and unpredictable operational contexts presents significant challenges for both OS developers and users. Against this backdrop, the fusion of Artificial Intelligence (AI) with Operating Systems emerges as a critical frontier for innovation. This survey delves into the intricate interplay between AI and OSs, illustrating how existing OS mechanisms combined with AI significantly elevate the performance, security, and efficiency of modern operating systems. We investigate a range of AI methodologies applied to optimize core OS functionalities and clarify the correlation to related studies. Our analysis touches on the existing hurdles and prospective avenues in this interdisciplinary domain, underscoring the imperative for robust and seamless integration of AI capabilities into OS architectures. Through an examination of illustrative case studies and cutting-edge developments, we offer a thorough review of the current status of AI-OS integration, accentuating its pivotal role in steering the evolution of advanced computing paradigms. We also envision the promising prospects of Intelligent Operating Systems, debating how groundbreaking OS designs will usher in novel possibilities and highlight the central role that AI will assume in propelling these next-generation systems forward. This forward-thinking outlook illuminates the profound influence of AI on the foundational elements of computing, heralding the advent of a new epoch characterized by intelligent, self-adapting, and highly adaptive software ecosystems. Copyright © 2024, The Authors. All rights reserved.

关键词： Artificial intelligence

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A riemannian exponential augmented lagrangian method for computing the projection robust Wasserstein distance 23

A riemannian exponential augmented lagrangian method for com...

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Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Bo Jiang Ya-Feng Liu Ministry of Education Key Laboratory of NSLSCS School of Mathematical Sciences Nanjing Normal University Nanjing China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China

Projection robust Wasserstein (PRW) distance is recently proposed to efficiently mitigate the curse of dimensionality in the classical Wasserstein distance. In this paper, by equivalently reformulating the computation of the PRW distance as an optimization problem over the Cartesian product of the Stiefel manifold and the Euclidean space with additional nonlinear inequality constraints, we propose a Riemannian exponential augmented Lagrangian method (REALM) for solving this problem. Compared with the existing Riemannian exponential penalty-based approaches, REALM can potentially avoid too small penalty parameters and exhibit more stable numerical performance. To solve the subproblems in REALM efficiently, we design an inexact Riemannian Barzilai-Borwein method with Sinkhorn iteration (iRBBS), which selects the stepsizes adaptively rather than tuning the step-sizes in efforts as done in the existing methods. We show that iRBBS can return an ε-stationary point of the original PRW distance problem within O(ε-3) iterations, which matches the best known iteration complexity result. Extensive numerical results demonstrate that our proposed methods outperform the state-of-the-art solvers for computing the PRW distance.

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mathematical modeling of intelligent RGV simulation scheduling system based on simulated annealing algorithm

Mathematical modeling of intelligent RGV simulation scheduli...

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International Symposium on Computational Intelligence and Design, ISCID

作者： Benchao Yang Hongchuan Zhou Jiaqi Liu State Key Laboratory of Mathematical Engineering and advanced computing Information Engineering University Zhengzhou China

ISBN: (纸本)9781665438575

By establishing a mathematical model, the intelligent RGV scheduling scheme is optimized to design an efficient and stable intelligent RGV simulation scheduling system. This paper studies two different situations, including whether there is a fault in a process. Using the combination of high response ratio priority scheduling algorithm and simulated annealing algorithm, the process conditions including two or more process package faults are established, an intelligent RGV simulation scheduling algorithm based on simulated annealing is proposed, and the general intelligent RGV simulation scheduling system model is established. At the end of the paper, the failure of the two processes is also analyzed, and similar solutions can be given on the basis of this paper.

关键词： Annealing Scheduling algorithms Memory management Loading Simulated annealing Scheduling mathematical models

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单原子在铝合金中的扩散迁移行为:可解释机器学习加速第一原理计算方法

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Science China Materials 2024年第4期67卷 1140-1149页

作者：黄敬涛薛景腾李明伟程源来忠红胡津周飞曲囡刘勇朱景川 School of Materials Science and Engineering Harbin Institute of TechnologyHarbin 150001China National Key Laboratory for Precision Hot Processing of Metals Harbin Institute of TechnologyHarbin 150001China National Key Laboratory of Science and Technology on Advanced Composites in SpecialEnvironments Harbin Institute of TechnologyHarbin 150001 China Center for Analysis Measurement and ComputingHarbin Institute of TechnologyHarbin 150001China State Key Laboratory for Environment-friendly Energy Materials School of Materials Science and EngineringSouthwest University of Science and TechnologyMianyang 621010China

本文采用机器学习加速第一原理计算的方法,研究了铝基体中单原子的扩散迁移行为.建立铝基体中三十多种单原子扩散迁移行为的小样本数据集,以原子半径、离子半径和第一电离能等固有参数作为输入特征值,合金原子与空位之间的相互作用能以... 详细信息

本文采用机器学习加速第一原理计算的方法,研究了铝基体中单原子的扩散迁移行为.建立铝基体中三十多种单原子扩散迁移行为的小样本数据集,以原子半径、离子半径和第一电离能等固有参数作为输入特征值,合金原子与空位之间的相互作用能以及合金原子在铝基体中的扩散势垒作为输出参数.通过相关性分析初步确定描述符与预测目标之间的关系,并利用递归特征消除法确定不同目标的输入特征和描述符数量.通过交叉验证证明所选模型的先进性,并进行微调以优化其性能.为了验证其效率和准确性,CatBoost模型经过了传统算法的严格测试.利用训练有素的模型预测周期表中其他单原子在铝基体中的扩散迁移行为.机器学习加速第一原理计算的结果可为进一步开发新型铝合金提供理论依据.

关键词：机器学习扩散迁移交叉验证输出参数单原子第一原理计算原子半径小样本数据

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Path planning of UAV base station based on deep reinforcement learning

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Procedia Computer Science 2022年 202卷 89-104页

作者： Siming Yang Zheng Shan Jiang Cao Yuan Gao Yang Guo Ping Wang Xiaonan Wang Jing Wang Tingting Zhang Jiayu Guo State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Henan 450001 China Academy of Military Science of the PLA Beijing 100091 China Network Technology Research Center of the PLA Beijing 100090 China

UAV base station platform has become the current research hotspot of assisting ground base station for wireless *** present, the most important issue is how to make path planning to provide the stable communication guarantee for multiple mobile users. In this article, we model the air-to-ground channel to describe the path loss between the UAV platform and the user and build a simulation environment for training based on the OpenAI-GYM architecture. In addition, this paper proposes a reinforcement learning algorithm based on intrinsic rewards, which uses the mean square error of the state prediction results to quantify the novelty of the state. Algorithms enable agents to efficiently carry out strategy iterations. Experiments results showed that our algorithm has a higher score and takes less time.

关键词： UAV path planning Wireless communication coverage Deep learning Deep reinforcement learning

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THE Furnace temperature curve based on one-dimensional unsteady heat conduction model

THE Furnace temperature curve based on one-dimensional unste...

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International Symposium on Computational Intelligence and Design, ISCID

作者： Jiaqi Liu Hongchuan Zhou Benchao Yang State Key Laboratory of Mathematical Engineering and advanced computing Information Engineering University Zhengzhou China

ISBN: (纸本)9781665438575

This paper mainly studies the change rule of center temperature of welding zone in backwelding furnace under different set temperature and transfer rate conditions, and searches for appropriate temperature and rate to obtain the optimal furnace temperature curve. Different infinite length plate models were established for the small temperature region and interval respectively, and the heat transfer of each part was considered according to Fourier heat law and Newton cooling law, and the equation about the temperature change with time was constructed based on the law of energy conservation.

关键词： Heating systems Semiconductor device modeling Temperature Cooling Furnaces Computational modeling Welding

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