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计算机教育 2018年第12期 131-135页

作者： Siyao Gong Dongming Chen Zhiliang Zhu software college Northeastern University

Under the influence of globalization, it's a trend to develop international education in universities around the world. China, as a giant education country, also takes part in the international education market, developing international education in universities, and recruiting international students to study in China. In this paper, it analyzes the rational reasons to develop international education in terms of globalization, nature of universities and consistent development. What's more, based on the experience of developing international education in software college, Northeastern University(NEU), China, it introduces three aspects of internationalization implemented in the college.

关键词： international education internationalization higher education globalization

Reform and Exploration of Bilingual Teaching in software college

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计算机教育 2018年第12期 103-107页

作者： Dongming Chen Yi Ma Beilei Wang software college Northeastern University

At present, many domestic colleges and universities have opened bilingual teaching, and achieved gratifying results, but bilingual teaching is still facing a lot of problems. Based on the concept and definition of bilingual teaching, this paper expounds the role and meaning of bilingual teaching, analyses the present situation and existing problems of bilingual teaching, and puts forward the effective way of bilingual teaching in colleges and universities.

关键词： bilingual teaching teaching reform teaching methods and measures

Multi-Agent Deep Reinforcement Learning for Efficient Computation Offloading in Mobile Edge Computing

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Computers, Materials & Continua 2023年第9期76卷 3585-3603页

作者： Tianzhe Jiao Xiaoyue Feng Chaopeng Guo Dongqi Wang Jie Song Department of software Engineering Software CollegeNortheastern UniversityShenyang110819China

Mobile-edge computing(MEC)is a promising technology for the fifth-generation(5G)and sixth-generation(6G)architectures,which provides resourceful computing capabilities for Internet of Things(IoT)devices,such as virtual reality,mobile devices,and smart cities.In general,these IoT applications always bring higher energy consumption than traditional applications,which are usually energy-constrained.To provide persistent energy,many references have studied the offloading problem to save energy consumption.However,the dynamic environment dramatically increases the optimization difficulty of the offloading decision.In this paper,we aim to minimize the energy consumption of the entireMECsystemunder the latency constraint by fully considering the dynamic environment.UnderMarkov games,we propose amulti-agent deep reinforcement learning approach based on the bi-level actorcritic learning structure to jointly optimize the offloading decision and resource allocation,which can solve the combinatorial optimization problem using an asymmetric method and compute the Stackelberg equilibrium as a better convergence point than Nash equilibrium in terms of Pareto superiority.Our method can better adapt to a dynamic environment during the data transmission than the single-agent strategy and can effectively tackle the coordination problem in the multi-agent environment.The simulation results show that the proposed method could decrease the total computational overhead by 17.8%compared to the actor-critic-based method and reduce the total computational overhead by 31.3%,36.5%,and 44.7%compared with randomoffloading,all local execution,and all offloading execution,respectively.

关键词： Computation offloading multi-agent deep reinforcement learning mobile-edge computing latency energy efficiency

Weakly Supervised Abstractive Summarization with Enhancing Factual Consistency for Chinese Complaint Reports

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Computers, Materials & Continua 2023年第6期75卷 6201-6217页

作者： Ren Tao Chen Shuang software college Northeastern UniversityShenyang110000China

A large variety of complaint reports reflect subjective information expressed by citizens.A key challenge of text summarization for complaint reports is to ensure the factual consistency of generated summary.Therefore,in this paper,a simple and weakly supervised framework considering factual consistency is proposed to generate a summary of city-based complaint reports without pre-labeled sentences/words.Furthermore,it considers the importance of entity in complaint reports to ensure factual consistency of summary.Experimental results on the customer review datasets(Yelp and Amazon)and complaint report dataset(complaint reports of Shenyang in China)show that the proposed framework outperforms state-of-the-art approaches in ROUGE scores and human evaluation.It unveils the effectiveness of our approach to helping in dealing with complaint reports.

关键词： Automatic summarization abstractive summarization weakly supervised training entity recognition

A Bit Level Encryption Scheme Based on Hyper-chaotic System Combing with the Ideology of Central Dogma

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Chinese Journal of Electronics 2018年第3期27卷 595-602页

作者： ZHANG Shun YANG Liang ZHANG Yuan GAO Tiegang College of Software Nankai University

An image encryption scheme based on confusion and diffusion is proposed. In the proposed scheme,original images are transformed into other forms, such as binary streams and ‘hyper-image’, firstly. Then the confusion process is achieved by permutation on the pixel level,the binary bit level, and the ‘hyper-image’ level respectively. Moreover, the diffusion process is operated on the‘hyper-image’ level by bitwise e Xclusive or(XOR) calculation with random sequence generated by a hyper-chaotic system. Furthermore, the central dogma in molecular biology is utilized in the construction of hyper-image, which demonstrates its superiority. Both the theoretical analysis and the experimental results have demonstrated the efficiency and validity of the proposed scheme, and images can be encrypted sufficiently through the three-time permutation and the chaotic substitution.

关键词： Image encryption Bit-level encryption Central dogma Hyper-chaos

Community Discovery Algorithm Based on Multi-Relationship Embedding

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Computer Systems Science & Engineering 2023年第9期46卷 2809-2820页

作者： Dongming Chen Mingshuo Nie Jie Wang Dongqi Wang software college Northeastern UniversityShenyang110169China

Complex systems in the real world often can be modeled as network structures,and community discovery algorithms for complex networks enable researchers to understand the internal structure and implicit information of networks.Existing community discovery algorithms are usually designed for single-layer networks or single-interaction relationships and do not consider the attribute information of nodes.However,many real-world networks consist of multiple types of nodes and edges,and there may be rich semantic information on nodes and edges.The methods for single-layer networks cannot effectively tackle multi-layer information,multi-relationship information,and attribute information.This paper proposes a community discovery algorithm based on multi-relationship embedding.The proposed algorithm first models the nodes in the network to obtain the embedding matrix for each node relationship type and generates the node embedding matrix for each specific relationship type in the network by node encoder.The node embedding matrix is provided as input for aggregating the node embedding matrix of each specific relationship type using a Graph Convolutional Network(GCN)to obtain the final node embedding matrix.This strategy allows capturing of rich structural and attributes information in multi-relational networks.Experiments were conducted on different datasets with baselines,and the results show that the proposed algorithm obtains significant performance improvement in community discovery,node clustering,and similarity search tasks,and compared to the baseline with the best performance,the proposed algorithm achieves an average improvement of 3.1%on Macro-F1 and 4.7%on Micro-F1,which proves the effectiveness of the proposed algorithm.

关键词： Network representation learning multi-relationship node encoder attribute information

A review of optimization methods for computation offloading in edge computing networks

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Digital Communications and Networks 2023年第2期9卷 450-461页

作者： Kuanishbay Sadatdiynov Laizhong Cui Lei Zhang Joshua Zhexue Huang Salman Salloum Mohammad Sultan Mahmud college of Computer Science and software Engineering Shenzhen UniversityShenzhen518061China

Handling the massive amount of data generated by Smart Mobile Devices(SMDs)is a challenging computational problem.Edge Computing is an emerging computation paradigm that is employed to conquer this problem.It can bring computation power closer to the end devices to reduce their computation latency and energy consumption.Therefore,this paradigm increases the computational ability of SMDs by collaboration with edge servers.This is achieved by computation offloading from the mobile devices to the edge nodes or servers.However,not all applications benefit from computation offloading,which is only suitable for certain types of tasks.Task properties,SMD capability,wireless channel state,and other factors must be counted when making computation offloading decisions.Hence,optimization methods are important tools in scheduling computation offloading tasks in Edge Computing networks.In this paper,we review six types of optimization methods-they are Lyapunov optimization,convex optimization,heuristic techniques,game theory,machine learning,and others.For each type,we focus on the objective functions,application areas,types of offloading methods,evaluation methods,as well as the time complexity of the proposed algorithms.We discuss a few research problems that are still open.Our purpose for this review is to provide a concise summary that can help new researchers get started with their computation offloading researches for Edge Computing networks.

关键词： Edge computing Computation offloading Latency and energy consumption minimization

Analysis of robustness of urban bus network

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Chinese Physics B 2016年第2期25卷 1-12页

作者：任涛王一帆刘苗苗徐艳杰 software college Northeastern University

In this paper, the invulnerability and cascade failures are discussed for the urban bus network. Firstly, three static models（bus stop network, bus transfer network, and bus line network） are used to analyse the structure and invulnerability of urban bus network in order to understand the features of bus network comprehensively. Secondly, a new way is proposed to study the invulnerability of urban bus network by modelling two layered networks, i.e., the bus stop-line network and the bus line-transfer network and then the interactions between different models are analysed. Finally, by modelling a new layered network which can reflect the dynamic passenger flows, the cascade failures are discussed. Then a new load redistribution method is proposed to study the robustness of dynamic traffic. In this paper, the bus network of Shenyang City which is one of the biggest cities in China, is taken as a simulation example. In addition, some suggestions are given to improve the urban bus network and provide emergency strategies when traffic congestion occurs according to the numerical simulation results.

关键词： complex network urban bus network layered network invulnerability cascade failures

Identity-based proxy re-encryption scheme from RLWE assumption with ciphertext evolution

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The Journal of China Universities of Posts and Telecommunications 2023年第5期30卷 51-60页

作者： Meng Hui Ren Lina Zhao Zongqu College of Software Henan Polytechnic UniversityJiaozuo 454000China

Proxy re-encryption(PRE)allows users to transfer decryption rights to the data requester via proxy.Due to the current PRE schemes from lattice(LPRE)cannot fulfill chosen-ciphertext attack(CCA)security,an identity-based PRE(IB-PRE)scheme from learning with errors over ring(RLWE)assumption with ciphertext evolution(IB-LPRE-CE)was proposed.IB-LPRE-CE generates the private key using the preimage sampling algorithm(SamplePre)and completes the ciphertext delegation using the re-encryption algorithm.In addition,for the problem of ciphertext delegation change caused by the long-term secret key update,the idea of PRE is used to complete ciphertext evolution and the modification of ciphertext delegation,which improves the efficiency of secure data sharing.In terms of security,IB-LPRE-CE is CCA security based on RLWE assumption.Compared with the current LPRE schemes,IB-LPRE-CE offers greater security and improves the computational efficiency of the encryption algorithm.

关键词： proxy re-encryption(PRE) learning with errors over ring(RLWE) chosen-ciphertext attack(CCA) ciphertext delegation ciphertext evolution

Devising optimal integration test orders using cost-benefit analysis

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Frontiers of Information Technology & Electronic Engineering 2022年第5期23卷 692-714页

作者： Fanyi MENG Ying WANG Hai YU Zhiliang ZHU software college Northeastern UniversityShenyang 110169China State Key Lab for Novel software Technology Nanjing UniversityNanjing 210023China

Integration testing is an integral part of software testing.Prior studies have focused on reducing test cost in integration test order generation.However,there are no studies concerning the testing priorities of critical classes when generating integration test orders.Such priorities greatly affect testing efficiency.In this study,we propose an effective strategy that considers both test cost and efficiency when generating test orders.According to a series of dynamic execution scenarios,the software is mapped into a multi-layer dynamic execution network(MDEN)model.By analyzing the dynamic structural complexity,an evaluation scheme is proposed to quantify the class testing priority with the defined class risk index.Cost–benefit analysis is used to perform cycle-breaking operations,satisfying two principles:assigning higher priorities to higher-risk classes and minimizing the total complexity of test stubs.We also present a strategy to evaluate the effectiveness of integration test order algorithms by calculating the reduction of software risk during their testing process.Experiment results show that our approach performs better across software of different scales,in comparison with the existing algorithms that aim only to minimize test cost.Finally,we implement a tool,ITOsolution,to help practitioners automatically generate test orders.

关键词： Integration test order Cost–benefit analysis Probabilistic risk analysis Complex network