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arXiv 2025年

作者： Guo, keying He, Ruisi Yang, Mi Zhang, Yuxin Ai, Bo Zhang, Haoxiang Han, Jiahui Chen, Ruifeng School of Electronics and Information Engineering Beijing Jiaotong University Beijing100044 China State Key Laboratory of Advanced Rail Autonomous Operation Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing100044 China China Academy of Industrial Internet Ministry of Industry and Information Technology Beijing China Institute of Computing Technology China Academy of Railway Sciences Corporation Limited Beijing100081 China

Time-varying non-stationary channels, with complex dynamic variations and temporal evolution characteristics, have significant challenges in channel modeling and communication system performance evaluation. Most existing methods of time-varying channel modeling focus on predicting channel state at a given moment or simulating short-term channel fluctuations, which are unable to capture the long-term evolution of the channel. This paper emphasizes the generation of long-term dynamic channel to fully capture evolution of non-stationary channel properties. The generated channel not only reflects temporal dynamics but also ensures consistent stationarity. We propose a hybrid deep learning framework that combines conditional generative adversarial networks (CGAN) with long short-term memory (LSTM) networks. A stationarity-constrained approach is designed to ensure temporal correlation of the generated time-series channel. This method can generate channel with required temporal non-stationarity. The model is validated by comparing channel statistical features, and the results show that the generated channel is in good agreement with raw channel and provides good performance in terms of non-stationarity. Copyright © 2025, The Authors. All rights reserved.

关键词： Long Term Evolution (LTE)

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A new static vulnerabilities analysis algorithm for PHP codes 3

A new static vulnerabilities analysis algorithm for PHP code...

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3rd Annual International Conference on Network and Information Systems for Computers, ICNISC 2017

作者： Yan, Xue-Xiong Ma, Heng-Tai Institute of Software Chinese Academy of Sciences Beijing China State Key Laboratory of Mathematical Engineering and Advanced Computing Beijing China

ISBN: (纸本)9781538616185

as for detecting taint-style vulnerabilities in PHP codes, this paper introduces function calling control vulnerability, which is a new kind of taint-style vulnerabilities in PHP codes without sensitive function, and enriches classical update rules for taint analysis with a new transfer function definition, which is used to deal with statements with a single function call. The new static vulnerabilities analysis algorithm is implemented in a tool named POSE, and the experiment results of the POSE show that the new algorithm is valid for detecting more type of taint-style vulnerabilities in PHP codes. © 2019 IEEE.

关键词： Codes (symbols)

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Ultraclean Surface of Garnet-Type Electrolyte Enables Low Interfacial Resistance in Solid-state Lithium Batteries

SSRN

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SSRN 2022年

作者： Qin, Zhiwei Xie, Yuming Meng, Xiangchen Qian, Delai Shan, Cheng Mao, Dongxin He, Gang Zheng, Zhen Wan, Long Huang, Yongxian X. State Key Laboratory of Advanced Welding and Joining Harbin Institute of Technology Harbin150001 China School of Materials Science and Engineering Harbin Institute of Technology Harbin150001 China Center for Analysis Measurement and Computing Harbin Institute of Technology Harbin150001 China

Solid-state lithium batteries (SSLBs) with garnet-type Li6.5La3Zr1.5Ta 0.5O12 (LLZTO) are one of the most promising candidates for next-generation energy storage system due to their high safety and high stability against Li metal. However, the poor interfacial contact of Li/LLZTO interface induced by Li2CO3 surface impurity hinders its practical application. Herein, we propose an environmental friendliness and convenient high-speed mechanical polishing (HMP) method to remove impurities on porous LLZTO surface and retrieve its lithiophilicity. The strong centrifugal force provided by the high rotation speed promotes the complete removal of Li2CO3 impurity and accelerates the Li-ion transport at Li/LLZTO interface, reducing the interfacial resistance to 28.15 Ω·cm 2 under ultraclean interface, which is comparable to the state-of-the-art surface treatments. Symmetric Li cells assembled with high-speed (5000 rpm) polished LLZTO exhibit a critical current density of 1.91 mA·cm-2 and excellent cycling stability for 1200 h at 0.1 mA·cm-2. SSLBs with LiFePO 4 cathode achieve a superior stable cycling performance with a high discharge capacity of 138.6 mA·h·g-1 and a capacity retention of 89.5% after 500 cycles (0.2 C). This work guides a new understanding for obtaining lithiophilic Li/LLZTO interface through a simple, low-cost and high-efficient polishing strategy, which is potentially utilized for large-scale industrial production of SSLBs. © 2022, The Authors. All rights reserved.

关键词： Solid electrolytes

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Retraction Note: A robust image steganography based on the concatenated error correction encoder and discrete cosine transform coefficients

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Journal of Ambient Intelligence and Humanized computing 2024年第1期15卷 245-245页

作者： Bao, Zhenkun Guo, Yanqing Li, Xiaolong Zhang, Yi Xu, Meng Luo, Xiangyang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Zhengzhou Science and Technology Institute Zhengzhou China School of Information and Communication Engineering Dalian University of Technology Dalian China Institute of Information Science Beijing Jiaotong University Beijing China

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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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International Electron Devices Meeting (IEDM)

作者： Longhao Yan Yuqi Li Xi Li Zelun Pan Zeyu Wang Xile Wang Bowen Wang Zhe Zhan Xiyuan Tang Yaoyu Tao Woo-Ping Ge Zhitang Song Ru Huang Yuchao Yang Beijing Advanced Innovation Center for Integrated Circuits School of Integrate Circuits Peking University Beijing China State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Center for Brain Inspired Intelligence Chinese Institute for Brain Research (CIBR) 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

ISBN: (数字)9798350365429

ISBN: (纸本)9798350365436

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 $476\times$ and $264\times$ , respectively.

关键词： Phase change materials Virtual machine monitors In-memory computing Throughput Hardware Energy efficiency Common Information Model (computing) Vectors Manifold learning System-on-chip

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Interface engineering for Garnet-Type Electrolyte Enables Low Interfacial Resistance in Solid-state Lithium Batteries

SSRN

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SSRN 2022年

作者： Qin, Zhiwei Xie, Yuming Meng, Xiangchen Qian, Delai Shan, Cheng Mao, Dongxin He, Gang Zheng, Zhen Wan, Long Huang, Yongxian State Key Laboratory of Advanced Welding and Joining Harbin Institute of Technology Harbin150001 China School of Materials Science and Engineering Harbin Institute of Technology Harbin150001 China Center for Analysis Measurement and Computing Harbin Institute of Technology Harbin150001 China

Solid-state lithium batteries (SSLBs) with garnet-type Li6.5La3Zr1.5Ta0.5O12 (LLZTO) are one of the most promising candidates for next-generation energy storage system due to their high safety and high stability against Li metal. However, the poor interfacial contact of Li/LLZTO interface induced by Li2CO3 surface impurity hinders its practical application. Herein, interface engineering enabled by high-speed mechanical polishing (HMP) method is proposed to remove impurities on porous LLZTO surface and retrieve its lithiophilicity. The strong centrifugal force provided by the high rotation speed promotes the complete removal of Li2CO3 impurity and accelerates the Li-ion transport at Li/LLZTO interface, reducing the interfacial resistance to 28.15 Ω·cm2 under ultraclean interface, which is comparable to the state-of-the-art surface treatments. Symmetric Li cells assembled with high-speed (5000 rpm) polished LLZTO exhibit a critical current density of 1.91 mA·cm-2 and excellent cycling stability for 1200 h at 0.1 mA·cm-2. SSLBs with LiFePO4 cathode achieve a superior stable cycling performance with a high discharge capacity of 138.6 mA·h·g-1 and a capacity retention of 89.5% after 500 cycles (0.2 C). This work guides a new understanding for obtaining lithiophilic Li/LLZTO interface through a simple, low-cost and high-efficient polishing strategy, which is potentially utilized for large-scale industrial production of SSLBs. © 2022, The Authors. All rights reserved.

关键词： Solid electrolytes

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High-capacity and Robust Image Watermarking Algorithm

Research Square

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Research Square 2021年

作者： Liu, Zheng Li, Xi-Yan Zhou, Qing-Lei Sun, Hanqing Lian, Weimin Wang, Guizhi School of Information Engineering Henan University of Animal Husbandry and Economy Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China School of Information Science and Technology HaiNan Normal University Haikou China School of Information Engineering Zhengzhou University Zhengzhou China

With the development of internet, digital media can be manipulated, reproduced, and distributed conveniently over networks. However, illegal copy, transmission and distribution of digital media become an important security issue. In this paper, we propose a high-capacity and robustness method based on discrete wavelet transforms(DWT) and optimal discrete cosine transforms(DCT). We present two approaches, they are: DWT-ODCT(high-capacity and robust image watermarking algorithm based on DWT and optimal DCT), and(P-DWT-ODCT) high-capacity and robust image watermarking algorithm based on DWT and optimal DCT by watermark preprocessing. The watermark image is preprocessed by halftone and quad tree techniques, and the position information about the content is extracted as the actual embedded value. The cover image is transformed by DWT and optimal DCT, which provides high imperceptibility and the least image distortion. Watermark bits are not directly inserted into the frequency coefficient, but embedded by modifying the coefficient according to some rules. With this method, regardless of the approach used, our study are higher capacity and robustness than the existing schemes. The watermark extraction produces high image quality after a variety of attacks. © 2021, CC BY.

关键词： Discrete wavelet transforms

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Stabilization of Continuous-Time Markov/Semi-Markov Jump Linear Systems Via Finite Data-Rate Feedback

SSRN

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SSRN 2022年

作者： Wang, Jingyi Feng, Jianwen Xu, Chen Wu, Xiaoqun Lü, Jinhu College of Mathematics and Statistics Shenzhen University Shenzhen518060 China School of Mathematics and Statistics Hubei Key Laboratory of Computational Science Wuhan University Wuhan China State Key Laboratory of Software Development Environment School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China

This letter investigates almost sure exponential stabilization of continuous-time Markov jump linear systems (MJLSs) under communication data-rate constraints by introducing sampling and quantization into the feedback control. Different from previous works, the sampling times and the jump times are independent of each other in this letter. The quantization is recursively adjusted on the sampling time, and its updating strategy does not depend on the switching in a sampling interval. In other words, the explicit value of the switching signal in a sampling interval is not necessary. The numerically testable condition is developed to ensure almost sure exponential stabilization of MJLSs under the proposed communication and control protocols. We also drop the assumption of stabilizability of all individual modes required in previous works about the switched systems. Moreover, we extend the result to the case of continuous-time semi-Markov jump linear systems (semi-MJLSs) via the semi-Markov kernel approach. Finally, some numerical examples are presented to illustrate the effectiveness on stabilization of the proposed communication and control protocols. © 2022, The Authors. All rights reserved.

关键词： Markov processes

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A survey of coverage-guided greybox fuzzing with deep neural models

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Information and Software Technology 2025年 186卷

作者： Junyang Qiu Yupeng Jiang Yuantian Miao Wei Luo Lei Pan Xi Zheng State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214123 China School of Computing Macquarie University Sydney 2109 NSW Australia School of Information and Physical Sciences University of Newcastle Newcastle 2308 NSW Australia School of Information Technology Deakin University Melbourne 3125 VIC Australia

Coverage-guided greybox fuzzing (CGF) has emerged as a powerful technique for software vulnerability detection, yet traditional techniques often struggle with the increasing complexity of modern software systems and the vastness of input spaces. Deep neural networks (DNNs) have begun to fundamentally transform CGF by addressing these limitations through automated feature extraction, adaptive input generation, and intelligent path prioritization. However, despite these advancements, critical gaps persist in understanding the state-of-the-art landscape. Existing studies often lack rigorous benchmarks to evaluate scalability and generalizability, fail to address the interpretability of neural-guided decisions, and overlook the integration of emerging paradigms such as large language models (LLMs) and neurosymbolic reasoning. This survey systematically bridges these gaps by providing a comprehensive taxonomy of DNN-driven CGF techniques, analyzing their strengths and limitations across key fuzzing stages—seed generation, selection, and mutation. We find that although DNNs have significantly improved fuzzing efficiency, challenges such as semantically invalid seeds, high computational overhead, and limited cross-domain adaptability remain unresolved. Most importantly, we identify two transformative directions with the potential to redefine CGF: (1) LLM-powered fuzzing , which combines generative AI with domain-specific fine-tuning to produce context-aware inputs; and (2) neurosymbolic integration , which merges the precision of symbolic execution with the scalability of neural networks to tackle path explosion. By synthesizing these insights, this survey not only clarifies the state-of-the-art but also outlines a roadmap for developing robust, explainable, and widely applicable intelligent fuzzers. The future of CGF lies in hybrid models that integrate data-driven learning with formal methods, paving the way for autonomous vulnerability discovery in an era of increasingl

关键词： Greybox fuzzing Software vulnerability Code coverage Deep learning Large language models

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Multi-Variant Execution Research of Software Diversity

Multi-Variant Execution Research of Software Diversity

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2019 International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2019

作者： Liu, Zhenwu Zhang, Zheng Zhang, Jiexin Liu, Hao State Key Laboratory of Mathematical Engineering and Advanced Computing PLA Strategic Support Force Information Engineering University ZhengZhou HeNan450001 China

As more and more software products are threatened by malicious reverse analysis, along with software products are pirated, tampered with and so on, it is of great significance to study software security protection technology in depth. As a software security protection technology, software diversification introduces uncertainty into the target program and provides probabilistic protection for the target program. Multi-Variant Execution (MVE) are fine-grained implementation of software diversification that produces functionally identical variants at the system call level. This article first introduces the related concepts of multi-variant execution. Secondly, it expounds the key technologies of multi-variant execution implementation-variant generation, variant monitor, input/output and synchronization, monitor-variant communication. Security of monitors and different variant communication technologies are analyzed and compared, their advantages and defects are pointed out respectively. Several implementation methods of multi-variant execution design are summarized. Finally, the reasons for the false negatives and false positives of attack events are analyzed, and the prospects and challenges of using multi-variant execution techniques to implement security systems are summarized. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Artificial intelligence

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