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| 1 | Diabolical points in coupled active cavities with quantum emitters显示文摘In single microdisks,embedded active emitters intrinsically affect the cavity modes of the microdisks,resulting in trivial symmetric backscattering and low controllability.Here we demonstrate macroscopic control of the backscattering direction by optimizing the cavity size.The signature of the positive and negative backscattering directions in each single microdisk is confirmed with two strongly coupled microdisks.Furthermore,diabolical points are achieved at the resonance of the two microdisks,which agrees well with theoretical calculations considering the backscattering directions.Diabolical points in active optical structures pave the way for an implementation of quantum information processing with geometric phase in quantum photonic networks. | Jingnan Yang Chenjiang Qian Xin Xie Kai Peng Shiyao Wu Feilong Song Sibai Sun Jianchen Dang Yang Yu Shushu Shi Jiongji He Matthew JSteer Iain GThayne Bei-Bei Li Fang Bo Yun-Feng Xiao Zhanchun Zuo Kuijuan Jin Changzhi Gu Xiulai Xu | 2020 | Light(Science & Applications)2020，9，1： | 2 |
| 2 | Short-term, Mild Hypothermia Can Increase the Beneficial Effect of Permissive Hypotension on Uncontrolled Hemorrhagic Shock in Rats显示文摘 | Tao Li Xiulai Lin Yu Zhu Lijie Li Liangming Liu | 2012 | Anesthesiology2012，，6： | 1 |
| 3 | Ship Detection and Recognition Based on Improved YOLOv7显示文摘In this paper,an advanced YOLOv7 model is proposed to tackle the challenges associated with ship detection and recognition tasks,such as the irregular shapes and varying sizes of ships.The improved model replaces the fixed anchor boxes utilized in conventional YOLOv7 models with a set of more suitable anchor boxes specifically designed based on the size distribution of ships in the dataset.This paper also introduces a novel multi-scale feature fusion module,which comprises Path Aggregation Network(PAN)modules,enabling the efficient capture of ship features across different scales.Furthermore,data preprocessing is enhanced through the application of data augmentation techniques,including random rotation,scaling,and cropping,which serve to bolster data diversity and robustness.The distribution of positive and negative samples in the dataset is balanced using random sampling,ensuring a more accurate representation of real-world scenarios.Comprehensive experimental results demonstrate that the proposed method significantly outperforms existing state-of-the-art approaches in terms of both detection accuracy and robustness,highlighting the potential of the improved YOLOv7 model for practical applications in the maritime domain. | Wei Wu Xiulai Li Zhuhua Hu Xiaozhang Liu | 2023 | Computers, Materials & Continua2023，，7： | 1 |
| 4 | Blockchain Security Threats and Collaborative Defense:A Literature Review显示文摘As a distributed database,the system security of the blockchain is of great significance to prevent tampering,protect privacy,prevent double spending,and improve credibility.Due to the decentralized and trustless nature of blockchain,the security defense of the blockchain system has become one of the most important measures.This paper comprehensively reviews the research progress of blockchain security threats and collaborative defense,and we first introduce the overview,classification,and threat assessment process of blockchain security threats.Then,we investigate the research status of single-node defense technology and multi-node collaborative defense technology and summarize the blockchain security evaluation indicators and evaluation methods.Finally,we discuss the challenges of blockchain security and future research directions,such as parallel detection and federated learning.This paper aims to stimulate further research and discussion on blockchain security,providing more reliable security guarantees for the use and development of blockchain technology to face changing threats and challenges through continuous updating and improvement of defense technologies. | Xiulai Li Jieren Cheng Zhaoxin Shi Jingxin Liu Bin Zhang Xinbing Xu Xiangyan Tang Victor S.Sheng | 2023 | Computers, Materials & Continua2023，76，9： | 1 |
| 5 | A Modified PointNet-Based DDoS Attack Classification and Segmentation in Blockchain显示文摘With the rapid development of blockchain technology,the number of distributed applications continues to increase,so ensuring the security of the network has become particularly important.However,due to its decentralized,decentralized nature,blockchain networks are vulnerable to distributed denial-of-service(DDoS)attacks,which can lead to service stops,causing serious economic losses and social impacts.The research questions in this paper mainly include two aspects:first,the classification of DDoS,which refers to detecting whether blockchain nodes are suffering DDoS attacks,that is,detecting the data of nodes in parallel;The second is the problem of DDoS segmentation,that is,multiple pieces of data that appear at the same time are determined which type of DDoS attack they belong to.In order to solve these problems,this paper proposes a modified PointNet(MPointNet)for the classification and type segmentation of DDoS attacks.A dataset containing multiple DDoS attack types was constructed using the CIC-DDoS2019 dataset,and trained,validated,and tested accordingly.The results show that the proposed DDoS attack classification method has high performance and can be used for the actual blockchain security maintenance process.The accuracy rate of classification tasks reached 99.65%,and the accuracy of type segmentation tasks reached 85.47%.Therefore,the method proposed in this paper has high application value in detecting the classification and segmentation of DDoS attacks. | Jieren Cheng Xiulai Li Xinbing Xu Xiangyan Tang Victor S.Sheng | 2023 | Computer Systems Science & Engineering2023，47，10： | 1 |
| 6 | Anisotropies of the g-factor tensor and diamagnetic coefficient in crystal-phase quantum dots in InP nanowires显示文摘Crystal-phase low-dimensional structures offer great potential for the implementation of photonic devices of interest for quantum information processing.In this context,unveiling the fundamental parameters of the crystal phase structure is of much relevance for several applications.Here,we report on the anisotropy of the g-factor tensor and diamagnetic coefficient in wurtzite/zincblende(WZ/ZB)crystal-phase quantum dots(QDs)realized in single InP nanowires.The WZ and ZB alternating axial sections in the NWs are identified by high-angle annular dark-field scanning transmission electron microscopy.The electron(hole)g-factor tensor and the exciton diamagnetic coefficients in WZ/ZB crystal-phase QDs are determined through micro-photoluminescence measurements at low temperature(4.2 K)with different magnetic field configurations,and rationalized by invoking the spin-correlated orbital current model.Our work provides key parameters for band gap engineering and spin states control in crystal-phase low-dimensional structures in nanowires. | Shiyao Wu Kai Peng Sergio Battiato Valentina Zannier Andrea Bertoni Guido Goldoni Xin Xie Jingnan Yang Shan Xiao Chenjiang Qian Feilong Song Sibai Sun Jianchen Dang Yang Yu Fabio Beltram Lucia Sorba Ang Li Bei-bei Li Francesco Rossella Xiulai Xu | 2019 | Nano Research2019，12，11： | 1 |
| 7 | Micropascal-sensitivity ultrasound sensors based on optical microcavities显示文摘Whispering gallery mode(WGM)microcavities have been widely used for high-sensitivity ultrasound detection,owing to their optical and mechanical dual-resonance enhanced sensitivity.The ultrasound sensitivity of the cavity optomechanical system is fundamentally limited by thermal noise.In this work,we theoretically and experimentally investigate the thermal-noise-limited sensitivity of a WGM microdisk ultrasound sensor and optimize the sensitivity by varying the radius and a thickness of the microdisk,as well as using a trench structure around the disk.Utilizing a microdisk with a radius of 300μm and thickness of 2μm,we achieve a peak sensitivity of 1.18μPa Hz^(-1/2)at 82.6 k Hz.To the best of our knowledge,this represents the record sensitivity among cavity optomechanical ultrasound sensors.Such high sensitivity has the potential to improve the detection range of air-coupled ultrasound sensing technology. | HAO YANG XUENING CAO ZHI-GANG HU YIMENG GAO YUECHEN LEI MIN WANG ZHANCHUN ZUO XIULAI XU BEI-BEI LI | 2023 | Photonics Research2023，11，7： | 0 |
| 8 | An Adaptive DDoS Detection and Classification Method in Blockchain Using an Integrated Multi-Models显示文摘With the rising adoption of blockchain technology due to its decentralized,secure,and transparent features,ensuring its resilience against network threats,especially Distributed Denial of Service(DDoS)attacks,is crucial.This research addresses the vulnerability of blockchain systems to DDoS assaults,which undermine their core decentralized characteristics,posing threats to their security and reliability.We have devised a novel adaptive integration technique for the detection and identification of varied DDoS attacks.To ensure the robustness and validity of our approach,a dataset amalgamating multiple DDoS attacks was derived from the CIC-DDoS2019 dataset.Using this,our methodology was applied to detect DDoS threats and further classify them into seven unique attack subcategories.To cope with the broad spectrum of DDoS attack variations,a holistic framework has been pro-posed that seamlessly integrates five machine learning models:Gate Recurrent Unit(GRU),Convolutional Neural Networks(CNN),Long-Short Term Memory(LSTM),Deep Neural Networks(DNN),and Support Vector Machine(SVM).The innovative aspect of our framework is the introduction of a dynamic weight adjustment mechanism,enhancing the system’s adaptability.Experimental results substantiate the superiority of our ensemble method in comparison to singular models across various evaluation metrics.The framework displayed remarkable accuracy,with rates reaching 99.71%for detection and 87.62%for classification tasks.By developing a comprehensive and adaptive methodology,this study paves the way for strengthening the defense mechanisms of blockchain systems against DDoS attacks.The ensemble approach,combined with the dynamic weight adjustment,offers promise in ensuring blockchain’s enduring security and trustworthiness. | Xiulai Li Jieren Cheng Chengchun Ruan Bin Zhang Xiangyan Tang Mengzhe Sun | 2023 | Computers, Materials & Continua2023，77，12： | 0 |
| 9 | Gain-Scheduling H_∞ Autopilot Design for Tactical Missiles with Variable-Swept Wings显示文摘A new approach to gain-scheduling of H∞controllers is proposed for a cruise missile with variableswept wings( VSW) in bank-to-turn( BTT) mode. A nonlinear dynamic model is established and anticipant performance criterions are given at first. For the selected operating points,feedback robust controllers of threechannels are designed independently to restrain cross-channel couple disturbances and aerodynamic perturbations. Then,the sweepback and Ma number are selected to schedule controller gains iteratively to ensure all closed-loop poles locating inside the desired region. The proposed method here attempts to extend the performance of initial design obtained for a single arbitrary point to the whole linearized domain while maintaining the expected stability over the entire range of sweepback and full flight envelope. Some time-domain analysis procedures based on the proposed method are carried out and assessed,while the performance of tracking and robustness to aerodynamic perturbations in different situations are contrasted by some nonlinear simulations. Finally,the numerical simulations demonstrate that the proposed autopilot design method has better tracking performance and is robust,effective and feasible. | Hongyang Bai Ruisheng Sun Weiming Li Xiulai Wang | 2015 | Journal of Harbin Institute of Technology(New Series)2015，22，1： | 0 |
| 10 | Free spectral range magnetic tuning of an integrated microcavity显示文摘Tunable whispering-gallery-mode(WGM)microcavities are promising devices for reconfigurable photonic applications such as widely tunable integrated lasers and reconfigurable optical filters for optical communication and information processing.Scaling up these devices demands the ability to tune the optical resonances in an integrated manner over a full free spectral range(FSR).Here we propose a high-speed full FSR magnetic tuning scheme of an integrated silicon nitride(Si_(3)N_(4))double-disk microcavity.By coating a magnetostrictive film on the spokes and the central pad of the Si_(3)N_(4) cavity,magnetic tuning can be realized using a microcoil integrated on the same chip.An FSR tuning can be achieved by combining magnetostrictive strain with strong optomechanical interactions provided by the double-disk microcavity.We calculate the required magnetic flux density to tune an FSR(B_(FSR))as a function of several key geometric parameters,including the air gap,radius,width of the spokes and ring of the double-disk cavities,as well as the thickness of the magnetostrictive film.The proposed structure enables a full FSR tuning with a required magnetic flux density of milli-Tesla(mT)level.We also study the dynamic response of the integrated device with an alternating current(AC)magnetic field driving,and find that the tuning speed can reach hundreds of kHz in the air. | Yuechen Lei Zhi-Gang Hu Min Wang Yi-Meng Gao Zhanchun Zuo Xiulai Xu Bei-Bei Li | 2023 | Fundamental Research2023，3，3： | 0 |
| 11 | An Explanatory Strategy for Reducing the Risk of Privacy Leaks显示文摘As machine learning moves into high-risk and sensitive applications such as medical care,autonomous driving,and financial planning,how to interpret the predictions of the black-box model becomes the key to whether people can trust machine learning decisions.Interpretability relies on providing users with additional information or explanations to improve model transparency and help users understand model decisions.However,these information inevitably leads to the dataset or model into the risk of privacy leaks.We propose a strategy to reduce model privacy leakage for instance interpretability techniques.The following is the specific operation process.Firstly,the user inputs data into the model,and the model calculates the prediction confidence of the data provided by the user and gives the prediction results.Meanwhile,the model obtains the prediction confidence of the interpretation data set.Finally,the data with the smallest Euclidean distance between the confidence of the interpretation set and the prediction data as the explainable data.Experimental results show that The Euclidean distance between the confidence of interpretation data and the confidence of prediction data provided by this method is very small,which shows that the model's prediction of interpreted data is very similar to the model's prediction of user data.Finally,we demonstrate the accuracy of the explanatory data.We measure the matching degree between the real label and the predicted label of the interpreted data and the applicability to the network model.The results show that the interpretation method has high accuracy and wide applicability. | Mingting Liu Xiaozhang Liu Anli Yan Xiulai Li Gengquan Xie Xin Tang | 2021 | Journal of Information Hiding and Privacy Protection2021，3，4： | 0 |
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