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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

A Survey of the Application of English Vocabulary software in college Students' English Learning

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校园英语 2020年第11期 10-10页

作者： LIU Guohui LIU Juan Modern college of Northwest University

This paper investigates the application status of English vocabulary software in college students’ English learning from the perspectives of learning purpose, and learning attitude through questionnaire survey.

关键词： English vocabulary software college students’ English learning Questionnaire

Traffic safety helmet wear detection based on improved YOLOv5 network

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Optoelectronics Letters 2025年第1期21卷 35-42页

作者： GUI Dongdong SUN Bo college of software Southeast University Quanzhou Equipment Research Centre Haixi Institute Chinese Academy of Sciences

Aiming at the problem that the current traffic safety helmet detection model can't balance the accuracy of detection with the size of the model and the poor generalization of the model, a method based on improving you only look once version 5(YOLOv5) is proposed. By incorporating the lightweight Ghost Net module into the YOLOv5 backbone network, we effectively reduce the model size. The addition of the receptive fields block(RFB) module enhances feature extraction and improves the feature acquisition capability of the lightweight model. Subsequently, the high-performance lightweight convolution, GSConv, is integrated into the neck structure for further model size compression. Moreover, the baseline model's loss function is substituted with efficient insertion over union(EIoU), accelerating network convergence and enhancing detection precision. Experimental results corroborate the effectiveness of this improved algorithm in real-world traffic scenarios.

关键词： Traffic control

A Cross Attention Transformer-Mixed Feedback Video Recommendation Algorithm Based on DIEN

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Computers, Materials & Continua 2025年第1期82卷 977-996页

作者： Jianwei Zhang Zhishang Zhao Zengyu Cai Yuan Feng Liang Zhu Yahui Sun college of software Engineering Zhengzhou University of Light IndustryZhengzhou450000China Faculty of Information Engineering Xuchang Vocational Technical CollegeXuchang461000China college of Computer Science and Technology Zhengzhou University of Light IndustryZhengzhou450000China college of Electronics and Information Zhengzhou University of Light IndustryZhengzhou450000China

The rapid development of short video platforms poses new challenges for traditional recommendation *** systems typically depend on two types of user behavior feedback to construct user interest profiles:explicit feedback(interactive behavior),which significantly influences users’short-term interests,and implicit feedback(viewing time),which substantially affects their long-term ***,the previous model fails to distinguish between these two feedback methods,leading it to predict only the overall preferences of users based on extensive historical behavior ***,it cannot differentiate between users’long-term and shortterm interests,resulting in low accuracy in describing users’interest states and predicting the evolution of their *** paper introduces a video recommendationmodel calledCAT-MFRec(CrossAttention Transformer-Mixed Feedback Recommendation)designed to differentiate between explicit and implicit user feedback within the DIEN(Deep Interest Evolution Network)*** study emphasizes the separate learning of the two types of behavioral feedback,effectively integrating them through the cross-attention ***,it leverages the long sequence dependence capabilities of Transformer technology to accurately construct user interest profiles and predict the evolution of user *** results indicate that CAT-MF Rec significantly outperforms existing recommendation methods across various performance *** advancement offers new theoretical and practical insights for the development of video recommendations,particularly in addressing complex and dynamic user behavior patterns.

关键词： Video recommendation user interest cross-attention transformer

Stability Prediction in Smart Grid Using PSO Optimized XGBoost Algorithm with Dynamic Inertia Weight Updation

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 909-931页

作者： Adel Binbusayyis Mohemmed Sha Department of software Engineering college of Computer Engineering and Sciences in Al-Kharj Prince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia

Prediction of stability in SG(Smart Grid)is essential in maintaining consistency and reliability of power supply in grid *** the fluctuations in power generation and consumption patterns of smart cities assists in effectively managing continuous power supply in the *** also possesses a better impact on averting overloading and permitting effective energy *** though many traditional techniques have predicted the consumption rate for preserving stability,enhancement is required in prediction measures with minimized *** overcome the complications in existing studies,this paper intends to predict stability from the smart grid stability prediction dataset using machine learning *** accomplish this,pre-processing is performed initially to handle missing values since it develops biased models when missing values are mishandled and performs feature scaling to normalize independent data ***,the pre-processed data are taken for training and *** that,the regression process is performed using Modified PSO(Particle Swarm Optimization)optimized XGBoost Technique with dynamic inertia weight update,which analyses variables like gamma(G),reaction time(tau1–tau4),and power balance(p1–p4)for providing effective future stability in *** PSO attains optimal solution by adjusting position through dynamic inertial weights,it is integrated with XGBoost due to its scalability and faster computational speed *** hyperparameters of XGBoost are fine-tuned in the training process for achieving promising outcomes on *** results are measured through evaluation metrics such as MSE(Mean Square Error)of 0.011312781,MAE(Mean Absolute Error)of 0.008596322,and RMSE(Root Mean Square Error)of 0.010636156 and MAPE(Mean Absolute Percentage Error)value of 0.0052 which determine the efficacy of the system.

关键词： Smart Grid machine learning particle swarm optimization XGBoost dynamic inertia weight update

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

One-way hash function based on hyper-chaotic cellular neural network

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Chinese Physics B 2008年第7期17卷 2388-2393页

作者：杨群亭高铁杠 college of software Nankai University

The design of an efficient one-way hash function with good performance is a hot spot in modern cryptography researches. In this paper, a hash function construction method based on cell neural network with hyper-chaos characteristics is proposed. First, the chaos sequence is gotten by iterating cellular neural network with Runge Kutta algorithm, and then the chaos sequence is iterated with the message. The hash code is obtained through the corre- sponding transform of the latter chaos sequence. Simulation and analysis demonstrate that the new method has the merit of convenience, high sensitivity to initial values, good hash performance, especially the strong stability.

关键词： one-way hash function hyper-chaos cellular neural network Runge Kutta formula

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

Enhanced Speech Based Jointly Statistical Probability Distribution Function for Voice Activity Detection

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Chinese Journal of Electronics 2017年第2期26卷 325-330页

作者： LI Jie YOU Datao college of software Engineering Henan University

Most of Voice activity detection(VAD)methods are based on statistical *** these methods,the noise signal is always assumed to satisfy and characterized by Gaussian distribution,while the assumption of noise does not always hold in practice and which causes that these kinds of method fail to distinguish speech from noise at low Signal-noise-ratio(SNR) level in nonstationary noise *** going further to improve the robustness of VAD,a enhanced speech based method is *** the proposed method,the Laplacian distribution is used to model the remained noise since we find that the remained noise in enhanced speech satisfy Laplacian distribution;in addition,Gaussian mixture model is used to characterize the Discrete Fourier transform(DFT)coefficients of reconstructed speech in enhanced *** results show that the proposed method performs better than the baseline method,especially in low SNR and non-stationary noise conditions.

关键词： Statistical probability distribution Voice activity detection(VAD) Reconstructed speech