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2021国际计算机前沿大会

作者： Ke Tang Fudong Liu Zheng Shan Chunyan Zhang State Key Laboratory of Mathematical Engineering and Advanced Computing

Information technology facilitates people's lives greatly,while it also brings many security issues,such as code plagiarism,software in-fringement,and malicious *** order to solve the problems,reverse engineering is applied to analyze abundant binary code manually,which costs a lot of ***,due to the maturity of different obfuscation techniques,the disassembly code generated from the same function differs greatly in the opcode and control flow graph through different obfuscation *** paper propose a method inspired by natural language processing,to realize the semantic similarity matching of binary code in basic block granularity and function *** the similarity matching task of binary code obtained by different obfuscation options of LLVM,the indicator reaches 99%,which is better than the existing technologies.

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High-throughput studies and machine learning for design of β titanium alloys with optimum properties

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Transactions of Nonferrous Metals Society of China 2024年第10期34卷 3194-3207页

作者： Wei-min CHEN Jin-feng LING Kewu BAI Kai-hong ZHENG Fu-xing YIN Li-jun ZHANG Yong DU Guangdong Provincial Key Laboratory of Metal Toughening Technology and Application National Engineering Research Center of Powder Metallurgy of Titanium&Rare MetalsInstitute of New MaterialsGuangdong Academy of SciencesGuangzhou 510650China Institute of Advanced Wear&Corrosion Resistant and Functional Materials Jinan UniversityGuangzhou 510632China Institute of High Performance Computing Agency for ScienceTechnology and Research138632Singapore State Key Laboratory of Powder Metallurgy Central South UniversityChangsha 410083China

Based on experimental data,machine learning(ML) models for Young's modulus,hardness,and hot-working ability of Ti-based alloys were *** the models,the interdiffusion and mechanical property data were high-throughput re-evaluated from composition variations and nanoindentation data of diffusion ***,the Ti-(22±0.5)at.%Nb-(30±0.5)at.%Zr-(4±0.5)at.%Cr(TNZC) alloy with a single body-centered cubic(BCC) phase was screened in an interactive *** experimental results exhibited a relatively low Young's modulus of(58±4) GPa,high nanohardness of(3.4±0.2) GPa,high microhardness of HV(520±5),high compressive yield strength of(1220±18) MPa,large plastic strain greater than 30%,and superior dry-and wet-wear *** work demonstrates that ML combined with high-throughput analytic approaches can offer a powerful tool to accelerate the design of multicomponent Ti alloys with desired ***,it is indicated that TNZC alloy is an attractive candidate for biomedical applications.

关键词： high-throughput machine learning Ti-based alloys diffusion couple mechanical properties wear behavior

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Dual-axial self-attention network for text classification

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Science China(Information Sciences) 2021年第12期64卷 80-90页

作者： Xiaochuan ZHANG Xipeng QIU Jianmin PANG Fudong LIU Xingwei LI State Key Laboratory of Mathematical Engineering and Advanced Computing Shanghai Key Laboratory of Intelligent Information Processing Fudan University School of Computer Science Fudan University

Text classification is an important task in natural language processing and numerous studies aim to improve the accuracy and efficiency of text classification models. In this study, we propose an effective and efficient text classification model which is based on self-attention solely. The recently proposed multidimensional self-attention significantly improved the performance of self-attention. However, existing models suffer from two major limitations:(1) the previous multi-dimensional self-attention models are quite timeconsuming;(2) the dependencies of elements along the feature axis are not taken into account. To overcome these problems, in this paper, a much more computational efficient multi-dimensional self-attention model is proposed, and two parallel self-attention modules, called dual-axial self-attention, are applied to capture rich dependencies along the feature axis as well as the text axis. A text classification model is then *** experimental results on eight representative datasets show that the proposed text classification model can obtain state-of-the-art results and the proposed self-attention outperforms conventional self-attention models.

关键词： text classification dual-axial self-attention feature-axial dependency

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A new method for solving the linear recurrence relation with nonhomogeneous constant coefficients in some cases 4

A new method for solving the linear recurrence relation with...

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2021 4th International Conference on Mechatronics and Computer Technology engineering, MCTE 2021

作者： Yang, Ben-Chao Han, Xue-Feng State Key Laboratory of Mathematical Engineering and Advanced Computing Henan Zhengzhou China School of Mathematics and Information Science Henan Polytechnic University Henan Jiaozuo China

Recursive relation mainly describes the unique law satisfied by a sequence, so it plays an important role in almost all branches of mathematics. It is also one of the main algorithms commonly used in computer programming. This paper first introduces the concept of recursive relation and two common basic forms, then starts with the solution of linear recursive relation with non-homogeneous constant coefficients, gives a new solution idea, and gives a general proof. Finally, through an example, the general method and the new method given in this paper are compared and verified. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Computer programming

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Embedding Attribute and Relation Information for Person Entity Alignment 6

Embedding Attribute and Relation Information for Person Enti...

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6th International Conference on Big Data and Information Analytics, BigDIA 2020

作者： Wang, Can Liu, Xiaonan Yin, Meijuan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

Person entity alignment is to distinguish whether the person entity information extracted from different data sources refer to the same entity. Existing methods mainly use attribute and relation information of entity to solve entity alignment problem. Most of them are based on common information of entity, while ignore some non-common but semantically similar attribute information and they only consider the relation between first-order adjacent entity, which makes it difficult to accurately align entity in the case of scarcity of common information. so we propose a person entity alignment method based on joint embedding of attribute and relation information, which makes full use of non-common but related information of entity to align them and improves the Hit@k of alignment results when common information is sparse. In the method, the representation vector of attribute information and the representation vector of relation information are obtained by embedding. During embedding, we consider the identification of different attributes and the second-order relation between entities to improve the role of feature attributes and the second-order relation in entity alignment. When calculating the similarity of entities, binary linear regression model is used to fit the weight of attribute information and relation information similarity, so as to adapt to the different characteristics of the entity data under different circumstances. The experimental results show that, compared with the related methods, the Hit@1 value and Hit@10 value of the proposed method increased by more than 8.4% and more than 9.1% respectively. © 2020 IEEE.

关键词： Embeddings

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A BOW-Based Sentence Embedding Method for Chinese Event Identification 4

A BOW-Based Sentence Embedding Method for Chinese Event Iden...

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2019 4th International Seminar on Computer Technology, Mechanical and Electrical engineering, ISCME 2019

作者： Gao, Lizheng Zhou, Gang Luo, Junyong State Key of Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

Event extraction is an important branch of information extraction. It involves two challenging issues: event identification and argument identification. Most approaches of event identification are trigger-based, which suffer a lot from sample imbalance, word ambiguity, low scalability, etc. To solve these problems, we attempt to explore sentence-based event identification, whose main issue is sentence representation. With the success of word embedding, it has attracted much attention to generate semantic embeddings of sentences. In this paper, we propose a simple BOW-based sentence embedding method to represent event sentences for Chinese event identification. We compute embeddings on the dependency tree and map different relations to simple arithmetic operations. We evaluate our method with a dataset of Chinese event identification and compare the result with other BOW-based methods. The results show that our approach significantly outperforms other BOW-based methods. © Published under licence by IOP Publishing Ltd.

关键词： Embeddings

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An Efficient Sieve Algorithm with Evolutionary Technique 20

An Efficient Sieve Algorithm with Evolutionary Technique

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20th IEEE International Conference on Communication Technology, ICCT 2020

作者： Sun, Zedong Gu, Chunxiang Zheng, Yonghui State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781728181417

Sieve algorithm plays an important role in solving the shortest vector problem, which is one of the most representative hard lattice problems. In this paper, we propose an efficient sieve algorithm with evolutionary techniques. By combining Gauss Sieve algorithm with global selection, we propose an efficient sieve algorithm. Experimental results show that our algorithm performs better than FPLLL's Gauss Sieve algorithm in solving the shortest vector problem. Furthermore, we explore how mutation behaves in accelerating sieve algorithm. © 2020 IEEE.

关键词： Evolutionary algorithms

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Research on Cascading Failures of Power Grid

Research on Cascading Failures of Power Grid

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作者： Hongmin WANG Qiang WEI Yaobin XIE State Key Laboratory of Mathematical Engineering and Advanced Computing

The safe and stable operation of power system is related to the national economy and people's livelihood of the whole *** are almost always caused by cascading *** paper first analyzes the global blackouts in the past 20 years,and points out that the scale and probability distribution of blackouts obey the power-law ***,it is concluded that transmission line fault,bus fault,large-scale power flow transfer and relay protection device misoperation are the main factors causing cascading ***,the five stages of cascading failure evolution are analyzed,which are slow successive interruption process,fast successive interruption process,transient oscillation,avalanche blackout and long ***,the research results of cascading failure at home and abroad in recent years are analyzed from three research points:small world network,topological network and two-layer coupling network.

关键词： Cascading failure Cyber-physical system Small world network Two-layer coupling network

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Stability Analysis of a Rumor Propagation Model in Complex Networks with Holling II Type Functional Response 6

Stability Analysis of a Rumor Propagation Model in Complex N...

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6th International Conference on Big Data and Information Analytics, BigDIA 2020

作者： Yu, Ze Zhou, Gang Luo, Junyong Zhang, Mengli Huang, Ningbo State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

In this paper, we propose a SH2I2 rumor propagation model considering self-learning mechanism and echo chamber situation with Holling type II functional response in homogeneous and heterogeneous networks. Firstly, we obtain the basic reproduction number through Jacobian Matrix method and calculate the equilibrium points. Secondly, we prove the existence of rumor-prevailing equilibrium point as well as the local and globally stabilities by Routh-Huiwitz judgment and Lyapunov function. Finally, we use theoretical analysis and numerical simulations to investigate the effect of parameters for suppressing the prevalence of rumors. © 2020 IEEE.

关键词： Heterogeneous networks

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Memory Error Detection Based on Dynamic Binary Translation 20

Memory Error Detection Based on Dynamic Binary Translation

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20th IEEE International Conference on Communication Technology, ICCT 2020

作者： Xu, Hang Ren, Wei Liu, Zimian Chen, Jiajun Zhu, Junhu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781728181417

Dynamic memory error detection technology is widely utilized in locating and mitigating memory-corruption vulnerabilities. High false negative in existing technologies impairs the effectiveness of detection, especially when the detector has no source code. We proposed a dynamic memory error detection method based on dynamic binary translation. It realized the detection by combining a call stack tracing method and an IR language level memory error detection method. Experiments show that the detection success rate of this method in the heap and stack memory destruction is more than 80%. © 2020 IEEE.

关键词： Error detection

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