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IDS-INT:Intrusion detection system using transformer-based transfer learning for imbalanced network traffic

Digital Communications and Networks 2024年第1期10卷 190-204页

作者： Farhan Ullah Shamsher Ullah Gautam Srivastava Jerry chun-wei lin School of Software Northwestern Polytechnical UniversityXian710072ShaanxiChina Knowledge Unit of Systems and Technology University of Management and TechnologySialkot 51040Pakistan Department of Math and Computer Science Brandon UniversityBrandonMB R7A 6A9Canada Department of Computer Science and Math Lebanese American UniversityBeirut1102Lebanon Western Norway University of Applied Sciences BergenNorway Research Centre for Interneural Computing China Medical UniversityTaichungTaiwanChina

A network intrusion detection system is critical for cyber security against llegitimate *** terms of feature perspectives,network traffic may include a variety of elements such as attack reference,attack type,a subcategory of attack,host information,malicious scripts,*** terms of network perspectives,network traffic may contain an imbalanced number of harmful attacks when compared to normal *** is challenging to identify a specific attack due to complex features and data imbalance *** address these issues,this paper proposes an Intrusion Detection System using transformer-based transfer learning for Imbalanced Network Traffic(IDS-INT).IDS-INT uses transformer-based transfer learning to learn feature interactions in both network feature representation and imbalanced ***,detailed information about each type of attack is gathered from network interaction descriptions,which include network nodes,attack type,reference,host information,***,the transformer-based transfer learning approach is developed to learn detailed feature representation using their semantic ***,the Synthetic Minority Oversampling Technique(SMOTE)is implemented to balance abnormal traffic and detect minority ***,the Convolution Neural Network(CNN)model is designed to extract deep features from the balanced network ***,the hybrid approach of the CNN-Long Short-Term Memory(CNN-LSTM)model is developed to detect different types of attacks from the deep *** experiments are conducted to test the proposed approach using three standard datasets,i.e.,UNsWNB15,CIC-IDS2017,and *** explainable AI approach is implemented to interpret the proposed method and develop a trustable model.

关键词： Network intrusion detection Transfer learning Features extraction Imbalance data Explainable AI Cybersecurity

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A Parallel High-Utility Itemset Mining Algorithm Based on Hadoop

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Complex System Modeling and Simulation 2023年第1期3卷 47-58页

作者： Zaihe Cheng wei Shen wei Fang Jerry chun-wei lin School of Internet of Things Wuxi Institute of TechnologyWuxi 214121China School of Artificial Intelligence and Computer Science Jiangnan UniversityWuxi 214122China Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computational Intelligence Jiangnan UniversityWuxi 214122China Department of Computer Science Electrical Engineering and Mathematical SciencesWestern Norway University of Applied SciencesBergen 5020Norway

High-utility itemset mining(HUIM)can consider not only the profit factor but also the profitable factor,which is an essential task in data ***,most HUIM algorithms are mainly developed on a single machine,which is inefficient for big data since limited memory and processing capacities are available.A parallel efficient high-utility itemset mining(P-EFIM)algorithm is proposed based on the Hadoop platform to solve this problem in this *** P-EFIM,the transaction-weighted utilization values are calculated and ordered for the itemsets with the MapReduce *** the ordered itemsets are renumbered,and the low-utility itemsets are pruned to improve the dataset *** the Map phase,the P-EFIM algorithm divides the task into multiple independent *** uses the proposed S-style distribution strategy to distribute the subtasks evenly across all nodes to ensure ***,the P-EFIM uses the EFIM algorithm to mine each subtask dataset to enhance the performance in the Reduce *** are performed on eight datasets,and the results show that the runtime performance of P-EFIM is significantly higher than that of the PHUI-Growth,which is also HUIM algorithm based on the Hadoop framework.

关键词： pattern mining data mining Hadoop parallel high-utility itemset mining big data

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XPZLIB:an HDF5-format multi-group cross-section library

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Nuclear Science and Techniques 2024年第11期35卷 46-60页

作者： Bin Fu Le-Rui Zhang Ding She chun-lin wei Alain Hébert Institute of Nuclear and New Energy Technology Key Laboratory of Advanced Reactor Engineering and Safety of the Ministry of EducationTsinghua UniversityBeijing 100084China National Key Laboratory of Nuclear Reactor Technology Nuclear Power Institute of ChinaChengdu 610041China Polytechnique Montreal MontrealCanada

A multi-group cross-section library is fundamental for deterministic lattice physics *** existing multi-group cross-section libraries are customized for particular computer codes,as well as for particular types of nuclear *** paper presents an HDF5-format multi-group cross-section library named *** was produced using a selfdeveloped XPZR module integrated into the NJOY2016 code,and an in-house PyNjoy2022 system was developed for *** contains detailed data content and well-organized data structures that are user-and *** typical XPZLIBs with different numbers of energy groups,nuclides,and depletion reaction types were released via the Tsinghua cloud ***,the applicability of the released XPZLIBs was investigated using HTGR and PWR lattice calculations,which can provide guidance for applying XPZLIB under different scenarios.

关键词： XPZLIB Multi-group library HDF5 format HTGR PWR

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A robust deformed convolutional neural network(CNN)for image denoising

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CAAI Transactions on Intelligence Technology 2023年第2期8卷 331-342页

作者： Qi Zhang Jingyu Xiao chunwei Tian Jerry chun‐wei lin Shichao Zhang School of Economics and Management Harbin Institute of Technology at WeihaiWeihaiChina School of Computer Science Central South UniversityChangshaChina School of Software Northwestern Polytechnical UniversityXi'anShaanxiChina Research&Development Institute Northwestern Polytechnical UniversityShenzhenChina Yangtze River Delta Research Institute Northwestern Polytechnical UniversityTaicangChina Department of Computer Science Electrical Engineering and Mathematical SciencesWestern Norway University of Applied SciencesBergenNorway

Due to strong learning ability,convolutional neural networks(CNNs)have been developed in image ***,convolutional operations may change original distributions of noise in corrupted images,which may increase training difficulty in image *** relations of surrounding pixels can effectively resolve this *** by that,we propose a robust deformed denoising CNN(RDDCNN)in this *** proposed RDDCNN contains three blocks:a deformable block(DB),an enhanced block(EB)and a residual block(RB).The DB can extract more representative noise features via a deformable learnable kernel and stacked convolutional architecture,according to relations of surrounding *** EB can facilitate contextual interaction through a dilated convolution and a novel combination of convolutional layers,batch normalisation(BN)and ReLU,which can enhance the learning ability of the proposed *** address long-term dependency problem,the RB is used to enhance the memory ability of shallow layer on deep layers and construct a clean ***,we implement a blind denoising *** results demonstrate that our denoising model outperforms popular denoising methods in terms of qualitative and quantitative *** can be obtained at https://***/hellloxiaotian/RDDCNN.

关键词： blind denoising CNN deformed block enhanced block

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Prediction calculations for the first criticality of the HTR-PM using the PANGU code

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Nuclear Science and Techniques 2021年第9期32卷 9-15页

作者： Ding She Bing Xia Jiong Guo chun-lin wei Jian Zhang Fu Li Lei Shi Zuo-Yi Zhang Institute of Nuclear and New Energy Technology(INET) Tsinghua UniversityBeijing 100084China

The high-temperature reactor pebble-bed mod-ule(HTR-PM)is a modular high-temperature gas-cooled reactor demonstration power *** first criticality experiment is scheduled for the latter half of *** performing the first criticality experiment,a prediction calculation was performed using PANGU *** paper presents the calculation details for predicting the HTR-PM first criticality using PANGU,including the input model and parameters,numerical results,and uncertainty *** accuracy of the PANGU code was demonstrated by comparing it with the high-fidelity Monte Carlo solution,using the same input *** should be noted that k eff can be significantly affected by uncertainties in nuclear data and certain input parameters,making the criticality calculation ***,the PANGU is used to pre-dict the critical loading height of the HTR-PM first criti-cality under design conditions,which will be evaluated in the upcoming experiment later this year.

关键词： HTR-PM First criticality Prediction PANGU

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Improvement of an Anonymous and Lightweight Authentication Scheme for TMIS

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Journal of Applied Mathematics and Physics 2018年第1期6卷 18-28页

作者： Chien-Ming Chen Bin Xiang Eric Wang Ke Tsu-Yang Wu Jerry chun-wei lin Department of Computer Science and Technology Harbin Institute of Technology Shenzhen Graduate School Shenzhen China Fujian University of Technology Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China National Demonstration Center for Experimental Electronic Information and Electrical Technology Education Fujian University of Technology Fuzhou China

Telecare Medicine Information Systems (TMIS) provides flexible and convenient healthcare for patients. However, the medical data transmitted between patients and doctors are exposed to unsecure public networks. To protect the patient’s personal information, many authentication schemes are designed. Recently, Kang et al. proposed a hash based authentication schemes for TMIS and claimed that it could resist various attacks. However, we find that their proposed scheme is unsecure to traceability attack and user impersonation attack. In order to enhance the security and preserve the efficiency of Kang et al.’s, we proposed a new anonymous and lightweight scheme. The analysis demonstrates that our proposed scheme is superior to Kang et al.’s and the related schemes in security.

关键词： Authentication TMIS Smart Card

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新型哑铃型钢管混凝土拱肋施工阶段水化热温度试验研究

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混凝土 2011年第8期 138-139,143页

作者：林春姣林春伟欧伟广西大学土木建筑工程学院广西南宁530004 广西建筑工程质量检测中心广西南宁530011

通过对某新型哑铃型钢管混凝土拱桥的拱肋施工过程温度效应的现场实测,显示该截面类型的钢管混凝土拱肋在施工阶段的水化热升温显著,先浇筑弦管升温与等直径单圆管一致,后浇筑弦管升温高于先浇筑弦管。试验结果为后期结构温度效应及结... 详细信息

通过对某新型哑铃型钢管混凝土拱桥的拱肋施工过程温度效应的现场实测,显示该截面类型的钢管混凝土拱肋在施工阶段的水化热升温显著,先浇筑弦管升温与等直径单圆管一致,后浇筑弦管升温高于先浇筑弦管。试验结果为后期结构温度效应及结构基准温度的确定提供了参考依据。

关键词：钢管混凝土拱桥新型哑铃型截面水化热温度

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Preliminary Study on the Pathogenesis and Treatment in Simian AIDS

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中国实验动物学报 2005年第S1期13卷 23-24页

作者： Lu Yao-zeng, Wu Xiao-xian, Qin Chuan, He Fu-Qiu, Tu Xin-ming, wei Qiang,Chen Song, Jiang Hong, Cong Zhe, Tong wei, Liu Ya-Li, Zhu Hua, Lai chun-hui Institute of Laboratorial Animal Science, CAMSLi Guo-qiao, Fu lin-chun, Guo wei-zhong, Deng Wen-di, Luo Hong-mei, Zhou Yin-yun Institute of Tropical Medicine, Guangzhou University of Traditional Chinese Medicine

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斜拉扣索调整南盘江特大桥拱圈的结构应力

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广西大学学报（自然科学版） 2017年第1期42卷 274-283页

作者：林春姣郑皆连李翔林春伟王楚杰广西大学土木建筑工程学院广西南宁530004 工程防灾与结构安全教育部重点实验室广西南宁530004 广西建筑工程质量检测中心广西南宁530011

为保证南盘江特大桥主拱圈安全顺利的施工,分别研究了六工作面法和斜拉扣索加多工作面组合法分环浇筑钢管混凝土劲性骨架主拱圈外包混凝土过程,分析了采用两种方法施工的结构瞬时应力和永存应力以及变形的变化规律,并对比分析了结构实... 详细信息

为保证南盘江特大桥主拱圈安全顺利的施工,分别研究了六工作面法和斜拉扣索加多工作面组合法分环浇筑钢管混凝土劲性骨架主拱圈外包混凝土过程,分析了采用两种方法施工的结构瞬时应力和永存应力以及变形的变化规律,并对比分析了结构实际施工过程中的受力和变形。研究结果显示:六工作面加2组斜拉扣索、每组扣索索力3 000 k N能够较好地调整南盘江钢管混凝土劲性拱桥结构的瞬时应力和永存应力,可以将拱脚截面管内混凝土最大瞬时拉应力降低60%,永存压应力降低40%,并保持其他截面应力在《混凝土结构设计规范》(GB50010-2010)规范容许范围内;将拱顶最大瞬时挠度从-140 mm增加至-200 mm,但仍保持结构变形的平顺,避免了产生过大的反复变形。实际施工效果证实了斜拉扣索的有效调载作用。

关键词：钢管混凝土劲性骨架拱桥外包混凝土斜拉扣索六工作面分环浇筑应力

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Melatonin can prevents morphine and fentanynl induced hyperalgesia in rats

Melatonin can prevents morphine and fentanynl induced hypera...

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中国药理学会第十次全国学术会议

作者： Xin wei,ling lin,chun Wang,wei wei (Institute of Clinical Pharmacology,Anhui Medical University.The Key Laboratory of Antiinflammatory and Immunopharmacology,Ministry of Education,P.R.China,Hefei 230032)

Objective Opioid drugs are widelv used for treating moderate to severe pain,but accumutalting evidence suggests that administration of opioids such as morphine,fentanynl and remifentanyl can leads not only to analgesia, but also to an enhancement in pain sensitivity induced by central *** phenomenon is re- ferred to as opioid induced hyperalgesia(OIH).The present study assessed the effect of melatonin on fentanyl and morphine induced hyperalgesia using a tail-flick *** In the first set of experiments,to induce hyperalgesia, fentanynl was injected four times resulting in a total dose of 60,180,240 ug/kg *** 1 *** with MT in various doses(25,50,100 mg/kg) 30 min before fentanynl and after *** second set experiment, morphine induced tolerance and hyperalgesia were induced in rats by repeated injection of morphine(10 mg/ kg,s.c.) twice daily ***(25,50,100 mg/kg) were used orally in combination with morphine. Results Moderate and high dose(180,240 ug/kg) but not low fentanynl could induce hyperalgesia after drug *** present observations suggest that melatonin(50,100 mg/kg) could prevent fentanynl and morphine induced hyperalgesia and partially reversed morphine *** Melatonin can combined used with opioids to prevent OIH.

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