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International Conference on Computer engineering and Applications (ICCEA)

作者： Zhenwu Liu Zheng Zhang Hao Liu Bolin Ma State key Laboratory of Mathematical Engineering and Advanced Computing PLA Strategic Support Force Information Engineering University Zhengzhou China

ISBN: (数字)9781728159041

ISBN: (纸本)9781728159058

Aiming at the problems of limited number and diversity in existing web server software, an active defense mechanism for web services based on automated software diversity is proposed, and the system framework and implementation are introduced. The formula proves that the probability of an attack escape event is low. Security and performance experiments show that the active defense mechanism of web services based on automated software diversity can resist or detect memory error attacks with less overhead, indicating that automated software diversity can effectively improve the security of web services. This verifies its effectiveness and feasibility. Finally, the research prospects and improvement directions are given according to the implementation granularity of automated software diversity and the monitoring granularity of web services.

关键词： Security Web servers Hardware Layout Dynamic scheduling

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Unveiling the Precipitate Evolutions and Relationships between the Nano-Precipitates and Mechanical Properties in Ph13-8mo Stainless Steel

SSRN

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SSRN 2022年

作者： Cui, Puchang Yu, Shifan Zhou, Fei Wang, Hongli Bai, Qingqing Zhang, Zhihong Zheng, Huaibei Lai, Zhonghong Liu, Yong Zhu, Jingchuan School of Materials Science and Engineering Harbin Institute of Technology Harbin150001 China National Key Laboratory for Precision Hot Processing of Metals Harbin Institute of Technology Harbin150001 China Center for Analysis Measurement and Computing Harbin Institute of Technology Harbin150001 China State Key Laboratory for Environment-friendly Energy Materials School of Materials Science and Engineering Southwest University of Science and Technology Mianyang621010 China Chengdu Advanced Metal Materials Industrial Technology Institute Co. Ltd. Chengdu610300 China State Key Laboratory of Metal Material for Marine Equipment and Application Anshan114009 China

Precipitation hardening maraging steels possess of great importance with attractive properties in various industrial applications. However, a major confusion about the fine precipitate evolutions and the relationships between the strengthened particles and mechanical properties of PH13-8Mo steels under various heat treatment conditions remains to be further investigated. To shed light on the direct relationships between the fine nano-phase and mechanical properties, a combination of thermodynamics predictions and experimental measurements were carried out to model the issues. The investigation results reveal that the coherent NiAl nano-precipitates distributed on the lath-like martensite matrix firstly presented a steady growth and then a significant coarsening of approximately 9 nm at 593 °C for 5 h. The acicular or block-like diffusion-controlled reverted austenite enriched in Ni element with a tendency of growth was clarified, which maintains the K-S orientation relationship with martensite matrix after diverse aging treatments. The current studied PH13-8Mo steel displays comparable mechanical properties despite over-aging conditions, and the sharp drops in hardness and the steady increment in impact energy were systematically examined. The excellent work hardening behaviors of the present steel were modeled, which indicates that the modified Ludwik model displays significantly improved agreement with the experimental data than the widely accepted Hollomon model. The five strengthening mechanism models are discussed and the C-O-M model exhibits high consistency with the experimental data with a value of 652 MPa. The growth of nano-precipitates maybe prohibits the dislocations from cutting the particles, which promotes the hardening behaviors. This work offers a valuable reference for further quantitively experimental illustrates. © 2022, The Authors. All rights reserved.

关键词： Coarsening

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Adiabatic quantum algorithm for factorization with growing minimum energy gap

Quantum Engineering

引用

Quantum engineering 2021年第1期3卷

作者： Yan, Bao Jiang, Haocong Gao, Ming Duan, Qianheng Wang, Hong Ma, Zhi State Key Laboratory of Mathematical Engineering and Advanced Computing Science Road 62 ZhengzhouHenan China Zhengzhou Institute of Information Science and Technology Science Road 100 Zhengzhou China Institute of Information Technology Information Engineering University Zhengzhou China

We present a new quantum algorithm for factoring integers in the framework of adiabatic quantum computation. For an n bit integer with only one pair of equal bit factors we consider, the qubits needed in our algorithm is less than n, which makes it the most qubit-saving quantum factoring algorithm to our knowledge. Furthermore, we have numerically studied the scaling law for the minimum energy gap and entanglement entropy acrossing quantum phase transition. We have witnessed an increasing minimum gap scaling law which indicates the potential ability of an exponential quantum speedup with respect to the fastest classical factoring algorithm. In addition, the linear scaling law of the entanglement entropy provides the evidence that the system can provide large amount of entanglement which is the main resource for the quantum speedup. © 2021 John Wiley & Sons, Ltd.

关键词： Energy gap

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An Improved spectral graph partition intelligent clustering algorithm for low-power wireless networks

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Journal of Ambient Intelligence and Humanized computing 2019年 1-9页

作者： Chen, Ling Chen, Yan Wang, Yu Zhengzhou Science and Technology Institute Zhengzhou450002 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450002 China College of Computer Science Henan University of Engineering Zhengzhou451191 China

Aiming at the problem of energy imbalance and low-energy efficiency in wireless sensor network, a novel energy-balanced clustering routing algorithm based on spectral graph partition is proposed in this paper, which firstly calculates the optimum single-hop distance, balances the energy consumption of cluster heads, and avoids that the number of cluster heads is not fixed and cluster heads are clustered by using the traditional probability function. In addition, the transmission cost function is designed to construct the optimum transmission path to reduce energy consumption. The experimental results show that the network performance of our proposed algorithm is improved, which achieves on low-energy network for loss reduction and load balancing. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Cost functions

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Efficient Data Valuation Approximation in Federated Learning: A Sampling-based Approach

arXiv

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arXiv 2025年

作者： Wei, Shuyue Tong, Yongxin Zhou, Zimu He, Tianran Xu, Yi State Key Laboratory of Complex & Critical Software Environment Lab School of Computer Science and Engineering Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing Beihang University China City University of Hong Kong Hong Kong

Federated learning (FL) has emerged as a prominent distributed learning paradigm to utilize datasets across multiple data providers. In FL, cross-silo data providers often hesitate to share their high-quality dataset unless their data value can be fairly assessed. Shapley value (SV) has been advocated as the standard metric for data valuation in FL due to its desirable properties. However, the computational overhead of SV is prohibitive in practice, as it inherently requires training and evaluating an FL model across an exponential number of dataset combinations. Furthermore, existing solutions fail to achieve high accuracy and efficiency, making practical use of SV still out of reach, because they ignore choosing suitable computation scheme for approximation framework and overlook the property of utility function in FL. We first propose a unified stratified-sampling framework for two widely-used schemes. Then, we analyze and choose the more promising scheme under the FL linear regression assumption. After that, we identify a phenomenon termed key combinations, where only limited dataset combinations have a high-impact on final data value. Building on these insights, we propose a practical approximation algorithm, IPSS, which strategically selects high-impact dataset combinations rather than evaluating all possible combinations, thus substantially reducing time cost with minor approximation error. Furthermore, we conduct extensive evaluations on the FL benchmark datasets to demonstrate that our proposed algorithm outperforms a series of representative baselines in terms of efficiency and effectiveness. Copyright © 2025, The Authors. All rights reserved.

关键词： Federated learning

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Highly Stable Zinc Anodes Enabled by a Dual-Function Additive of In-Situ Film Formation and Electrostatic Shielding

SSRN

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SSRN 2024年

作者： Ji, Rui-Han Fu, Hao Wen, Qing Li, Pei-Yao Yang, Pei Chen, Yu-Jing Chen, He-Zhang Zhang, Jia-Feng Li, Ling-Jun Wang, Jie-Xi Wu, Qing Zhang, Xia-Hui Zheng, Jun-Chao Washington State University United States School of Metallurgy and Environment Central South University Hunan Changsha410083 China Engineering Research Center of the Ministry of Education for Advanced Battery Materials Central South University Hunan Changsha410083 China National Energy Metal Resources and New Materials Key Laboratory Central South University Hunan Changsha410083 China School of Chemistry and Chemical Engineering Hunan University of Science and Technology Hunan Xiangtan411201 China School of Materials Science and Engineering Changsha University of Science and Technology Changsha410114 China National Engineering Research Centre of Advanced Energy Storage Materials Changsha410205 China School of Information and Network Center Central South University Hunan Changsha410083 China Center for High-Performance Computing United States

The practical application of aqueous Zn-ion batteries (AZIBs) is significantly hindered by the short lifespan and low utilization of zinc metal anodes caused by the notorious hydrogen evolution reaction (HER), corrosion, and dendritic growth. The in-situ formation of a dense Zn-ion conducting solid electrolyte interphase (SEI) is an ideal approach to handle these problems. Herein, we present a twofold-protective strategy involving the dense in-situ SEI layer and the electrostatic shielding layer by incorporating 0.01 M yttrium nitrate (YN) additive into 2 M zinc sulfate electrolyte. The robust oxidizing characteristic of the nitrate induces rapid passivation on the surface of Zn anodes, by which these inevitable passivation byproducts are utilized for in-situ fabricating a dense SEI protection layer with excellent wettability. Besides, the infusion of high-valence rare-earth Y3+ forms a durable, dynamic electrostatic shielding layer around the growth tip of the protuberances. This can regulate Zn2+ deposition and aid in rectifying the irregular and sharp surface on zinc anodes. Benefiting from the synergistic effect of the static film protection and the dynamic electrostatic rectification, zinc anodes exhibit outstanding stability, as evidenced by remarkable cycling lifespan of exceeding 2000 h at 1 mAh cm-2 and 600 h at 10 mAh cm-2 in Zn symmetric cells and the preeminent CE of 99.83% with stably cycling over 2200 times in half-cells at 4 mA cm-2. This study reveals a straightforward yet pragmatic avenue of synergistic dual-protection effect to achieve anti-corrosion and dendrite-free Zn anodes. © 2024, The Authors. All rights reserved.

关键词： Passivation

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SpTFS: Sparse Tensor Format Selection for MTTKRP via Deep Learning 20

SpTFS: Sparse Tensor Format Selection for MTTKRP via Deep Le...

引用

Supercomputing Conference

作者： Qingxiao Sun Yi Liu Ming Dun Hailong Yang Zhongzhi Luan Lin Gan Guangwen Yang Depei Qian Beihang University China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China Tsinghua University China

ISBN: (数字)9781728199986

ISBN: (纸本)9781728199993

Canonical polyadic decomposition (CPD) is one of the most common tensor computations adopted in many scientific applications. The major bottleneck of CPD is matricized tensor times Khatri-Rao product (MTTKRP). To optimize the performance of MTTKRP, various sparse tensor formats have been proposed such as CSF and HiCOO. However, due to the spatial complexity of the tensors, no single format fits all tensors. To address this problem, we propose SpTFS, a framework that automatically predicts the optimal storage format for an input sparse tensor. Specifically, SpTFS leverages a set of sampling methods to lower the sparse tensor to fix-sized matrices and specific features. Then, TnsNet combines CNN and the feature layer to accurately predict the optimal format. The experimental results show that SpTFS achieves prediction accuracy of 92.7% and 96% on CPU and GPU respectively.

关键词： Tensors High performance computing Neural networks Graphics processing units Sampling methods Sparse matrices Matrix decomposition

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A Survey of Automatic Text Summarization Technology Based on Deep Learning

A Survey of Automatic Text Summarization Technology Based on...

引用

Artificial Intelligence and Computer engineering (ICAICE), International Conference on

作者： Mengli Zhang Gang Zhou Wanting Yu Wenfen Liu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Guilin University of Electronic Technology Guilin China

ISBN: (数字)9781728191461

ISBN: (纸本)9781728191478

With the rapid development of the Internet, the amount of network text data is increasing day by day. It is increasingly becoming a challenge to quickly mine useful information from massive amounts of text data. The emergence of automatic summarization technology provides new ideas and methods for solving this problem. Compared with extractive summarization model, abstractive summarization model more closely resembles the process of human summarization, giving it important research significance. In recent years, with the development of deep learning methods, text summarization technology based on deep learning has made unprecedented breakthroughs. Based on the current mainstream sequence-to- sequence framework, we summarize the state-of-the-art abstractive summarization models, compare the advantages of different models and applicable scenarios, and provide a clear context for researchers in related fields. Furthermore, we also make statistics on the Chinese and English datasets. Finally, we put forward some thoughts on the common problems in the field of automatic text summarization.

关键词： Deep learning Semantics Reinforcement learning Information retrieval Internet Task analysis Context modeling

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Design and implementation of a domain specific rule engine 1

引用

22nd Annual Conference on Computer engineering and Technology, NCCET 2018

作者： Chen, Mengdong Zhou, Xinjian Wu, Dong Xie, Xianghui State Key Laboratory of Mathematical Engineering and Advanced Computing Henghua Science and Technology Park WuxiJiangsu214125 China

ISBN: (数字)9789811359194

ISBN: (纸本)9789811359187

Security strings are often needed in identity authentication mechanism. Security strings recovery is a reverse process, which does much calculations on a large amount of possible strings to find the right one, so that we can recover lost or forgotten strings and regain access to valuable information. In this reverse process, we need first process basic strings based on transformation rules, so as to generate new ones quickly. Rule processing is complex, which has high requirements for computing power, processing time, especially system power consumption. In response to the above requirements, this work puts forward the idea of accelerating the processing of rules using hardware for the first time, and a domain specific rule engine is designed and implemented on the existing FPGA platform. The experimental results show that the performance of the rule engine on a single Xilinx Zynq 7z030 FPGA is better than that of CPU, its performance power ratio is 3 times higher than that of GPU, and 50 times higher than that of CPU. The speed and energy efficiency of the rule processing is improved effectively. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Engines

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An Efficient Rule Processing Architecture Based on Reconfigurable Hardware 1

引用

23rd Annual Conference on Computer engineering and Technology, NCCET 2019

作者： Chen, Mengdong Ren, Xiujiang Xie, Xianghui State Key Laboratory of Mathematical Engineering and Advanced Computing Henghua Science and Technology Park WuxiJiangsu214125 China

ISBN: (数字)9789811518508

ISBN: (纸本)9789811518492

In the recovery of security strings in identity authentication mechanism, the combination of dictionary and string transformation rules is an effective method. However, the processing of string transformation rules faces challenges such as performance and energy efficiency. The existing tools and researches are based on software. It’s difficult to meet the needs of actual recovery systems. In this paper, an efficient rule processing architecture based on reconfigurable hardware is proposed. The rules are processed using FPGA for the first time. A rule processor is designed and implemented on Xilinx Zynq XC7Z030 chip. The experimental results show that the performance of the rule processor is better than that of Intel i7-6700 CPU in typical cases. The performance power ratio of the rule processor is 1.4–2.1 times higher than that of NVIDIA GeForce GTX 1080 Ti GPU and 70 times higher than that of CPU, which effectively improves the speed and efficiency of rule processing. © 2019, Springer Nature Singapore Pte Ltd.

关键词： Reconfigurable hardware

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