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3rd IEEE International Conference on Data science in Cyberspace, DSC 2018

作者： Qi, Yulu Jiang, Rong Jia, Yan Li, Aiping State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha410073 China

ISBN: (纸本)9781538642108

With the development of Internet, the network security situation becomes more and more serious. Network security is a hot topic between the scholars all around the world. And it is facing more and more serious threats and challenges. Composite attack is the most popular form of attack, which usually cause serious damage to the target network. Understanding the detection technology and evaluation technology of composite attack is significant to maintenance network security. The detection technology of composite attack can detect suspicious information according to abnormal behavior or abnormal traffic before the attack occurs. The evaluation technique of composite attack can do the work by calculating the consequences of composite attack. At present, the detecting technology includes traditional security detection technology, APT detection technology and some detection frameworks, the evaluation technique includes evaluation models, evaluation algorithms and related indicators and indicator systems. This paper introduces the research status of related research and technologies in the view of detection and effect evaluation. © 2018 IEEE.

关键词： Network security

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DTCWT-based zinc fast roughing working condition identification

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Chinese Journal of Chemical Engineering 2018年第8期26卷 1721-1726页

作者： Zhuo He Zhaohui Tang Zhihao Yan Jinping Liu College of Information Science and Enineering Central South University Changsha 410083China Key Laboratory of High Performance Computing and Stochastic Information Processing of Ministry of Education of China College of Mathematics and Computer ScienceHunan Normal UniversityChangsha 410081China

The surface texture of mineral flotation froth is well acknowledged as an important index of the flotation *** surface texture feature closely relates to the flotation working conditions and hence can be used as a visual indicator for the zinc fast roughing working condition. A novel working condition identification method based on the dual-tree complex wavelet transform(DTCWT) is proposed for process monitoring of zinc fast ***-level DTCWT is implemented to decompose the froth image into different directions and resolutions in advance, and then the energy parameter of each sub-image is extracted as the froth texture feature. Then, an improved random forest integrated classification(i RFIC) with 10-fold cross-validation model is introduced as the classifier to identify the roughing working condition, which effectively improves the shortcomings of the single model and overcomes the characteristic redundancy but achieves higher generalization performance. Extensive experiments have verified the effectiveness of the proposed method.

关键词： DTCWT Working condition Integrated classification model Zinc fast roughing

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Hard jet substructure in a multistage approach

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Physical Review C 2024年第4期110卷 044907页

作者： Y. Tachibana A. Kumar A. Majumder A. Angerami R. Arora S. A. Bass S. Cao Y. Chen T. Dai L. Du R. Ehlers H. Elfner W. Fan R. J. Fries C. Gale Y. He M. Heffernan U. Heinz B. V. Jacak P. M. Jacobs S. Jeon Y. Ji K. Kauder L. Kasper W. Ke M. Kelsey M. Kordell, II J. Latessa Y.-J. Lee D. Liyanage A. Lopez M. Luzum S. Mak A. Mankolli C. Martin H. Mehryar T. Mengel J. Mulligan C. Nattrass D. Oliinychenko J.-F. Paquet J. H. Putschke G. Roland B. Schenke L. Schwiebert A. Sengupta C. Shen A. Silva C. Sirimanna D. Soeder R. A. Soltz I. Soudi J. Staudenmaier M. Strickland J. Velkovska G. Vujanovic X.-N. Wang R. L. Wolpert W. Zhao Yuwa Akita-city 010-1292 Japan Department of Physics McGill University Montréal Québec H3A 2T8 Canada Department of Physics and Astronomy Wayne State University Detroit Michigan 48201 USA Department of Physics University of Regina Regina Saskatchewan S4S 0A2 Canada Lawrence Livermore National Laboratory Livermore California 94550 USA Research Computing Group University Technology Solutions The University of Texas at San Antonio San Antonio Texas 78249 USA Department of Physics Duke University Durham North Carolina 27708 USA Institute of Frontier and Interdisciplinary Science Shandong University Qingdao Shandong 266237 China Laboratory for Nuclear Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Physics Massachusetts Institute of Technology Cambridge Massachusetts 02139 USA Department of Physics and Astronomy Vanderbilt University Nashville Tennessee 37235 USA Department of Physics and Astronomy University of Tennessee Knoxville Tennessee 37996 USA Physics Division Oak Ridge National Laboratory Oak Ridge Tennessee 37830 USA Department of Physics University of California Berkeley California 94270 USA Nuclear Science Division Lawrence Berkeley National Laboratory Berkeley California 94270 USA GSI Helmholtzzentrum für Schwerionenforschung 64291 Darmstadt Germany Institute for Theoretical Physics Goethe University 60438 Frankfurt am Main Germany Frankfurt Institute for Advanced Studies 60438 Frankfurt am Main Germany Cyclotron Institute Texas A&M University College Station Texas 77843 USA Department of Physics and Astronomy Texas A&M University College Station Texas 77843 USA Guangdong Provincial Key Laboratory of Nuclear Science Institute of Quantum Matter South China Normal University Guangzhou 510006 China Guangdong-Hong Kong Joint Laboratory of Quantum Matter Southern Nuclear Science Computing Center South China Normal University Guangzhou 510006 China Department of Physics The Ohio Stat

We present predictions and postdictions for a wide variety of hard jet-substructure observables using a multistage model within the jetscape framework. The details of the multistage model and the various parameter choices are described in [Phys. Rev. C 107, 034911 (2023)]. A novel feature of this model is the presence of two stages of jet modification: a high-virtuality phase [modeled using the modular all twist transverse-scattering elastic-drag and radiation model (matter)], where modified coherence effects diminish medium-induced radiation, and a lower virtuality phase [modeled using the linear Boltzmann transport model (lbt)], where parton splits are fully resolved by the medium as they endure multiple scattering induced energy loss. Energy-loss calculations are carried out on event-by-event viscous fluid dynamic backgrounds constrained by experimental data. The uniform and consistent descriptions of multiple experimental observables demonstrate the essential role of modified coherence effects and the multistage modeling of jet evolution. Using the best choice of parameters from [Phys. Rev. C 107, 034911] (2023)], and with no further tuning, we present calculations for the medium modified jet fragmentation function, the groomed jet momentum fraction zg and angular separation rg distributions, as well as the nuclear modification factor of groomed jets. These calculations provide accurate descriptions of published data from experiments at the Large Hadron Collider. Furthermore, we provide predictions from the multistage model for future measurements at the BNL Relativistic Heavy Ion Collider.

关键词： Hard scattering Jet quenching Jets & heavy flavor physics Quark & gluon jets Quark-gluon plasma Relativistic heavy-ion collisions

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Supernova Neutrino Detection with LHAASO-MD 37

Supernova Neutrino Detection with LHAASO-MD

引用

37th International Cosmic Ray Conference, ICRC 2021

作者： Liu, D. Chang, J. Chen, S. Dai, H. Feng, C. Gao, B. Gong, G. Gu, M. Li, F. Ma, X. Wang, X. Wang, Z. Zuo, X. Cao, Zhen Aharonian, F. An, Q. Axikegu Bai, L.X. Bai, Y.X. Bai, L.X. Bai, Y.X. Bao, Y.W. Bastieri, D. Bi, X.J. Bi, Y.J. Cai, H. Cai, J.T. Cao, Zhe Chang, J. Chang, J.F. Chen, B.M. Chen, E.S. Chen, J. Chen, Liang Chen, Long Chen, M.J. Chen, M.L. Chen, Q.H. Chen, S.H. Chen, S.Z. Chen, T.L. Chen, X.L. Chen, Y. Cheng, N. Cheng, Y.D. Cui, S.W. Cui, X.H. Cui, Y.D. D’Ettorre Piazzoli, B. Dai, B.Z. Dai, H.L. Dai, Z.G. Danzengluobu della Volpe, D. Dong, X.J. Duan, K.K. Fan, J.H. Fan, Y.Z. Fan, Z.X. Fang, J. Fang, K. Feng, C.F. Feng, L. Feng, S.H. Feng, Y.L. Gao, B. Gao, C.D. Gao, L.Q. Gao, Q. Gao, W. Ge, M.M. Geng, L.S. Gong, G.H. Gou, Q.B. Gu, M.H. Guo, F.L. Guo, J.G. Guo, X.L. Guo, Y.Q. Guo, Y.Y. Han, Y.A. He, H.H. He, H.N. He, J.C. He, S.L. He, X.B. He, Y. Heller, M. Hor, Y.K. Hou, C. Hu, H.B. Hu, S. Hu, S.C. Hu, X.J. Huang, D.H. Huang, Q.L. Huang, W.H. Huang, X.T. Huang, X.Y. Huang, Z.C. Ji, F. Ji, X.L. Jia, H.Y. Jiang, K. Jiang, Z.J. Jin, C. Ke, T. Kuleshov, D. Levochkin, K. Li, B.B. Li, Cheng Li, Cong Li, F. Li, H.B. Li, H.C. Li, H.Y. Li, J. Li, K. Li, W.L. Li, X.R. Li, Xin Li, Xin Li, Y. Li, Y.Z. Li, Zhe Li, Zhuo Liang, E.W. Liang, Y.F. Lin, S.J. Liu, B. Liu, C. Liu, D. Liu, H. Liu, H.D. Liu, J. Liu, J.L. Liu, J.S. Liu, J.Y. Liu, M.Y. Liu, R.Y. Liu, S.M. Liu, W. Liu, Y. Liu, Y.N. Liu, Z.X. Long, W.J. Lu, R. Lv, H.K. Ma, B.Q. Ma, L.L. Ma, X.H. Mao, J.R. Masood, A. Min, Z. Mitthumsiri, W. Montaruli, T. Nan, Y.C. Pang, B.Y. Pattarakijwanich, P. Pei, Z.Y. Qi, M.Y. Qi, Y.Q. Qiao, B.Q. Qin, J.J. Ruffolo, D. Rulev, V. Sáiz, A. Shao, L. Shchegolev, O. Sheng, X.D. Shi, J.Y. Song, H.C. Institute of Frontier and Interdisciplinary Science Shandong University Shandong Qingdao266237 China National University of Defense Technology Hunan Changsha410073 China Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China Tsinghua University Beijing100084 China Key Laboratory of Particle Astrophyics Experimental Physics Division Computing Center Institute of High Energy Physics Chinese Academy of Sciences Beijing100049 China University of Chinese Academy of Sciences Beijing100049 China TIANFU Cosmic Ray Research Center Sichuan Chengdu China Dublin Institute for Advanced Studies 31 Fitzwilliam Place 2 Dublin Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 Heidelberg69029 Germany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China Anhui Hefei230026 China School of Physical Science and Technology School of Information Science and Technology Southwest Jiaotong University Sichuan Chengdu610031 China College of Physics Sichuan University Sichuan Chengdu610065 China School of Astronomy and Space Science Nanjing University Jiangsu Nanjing210023 China Center for Astrophysics Guangzhou University Guangdong Guangzhou510006 China School of Physics and Technology Wuhan University Hubei Wuhan430072 China Key Laboratory of Dark Matter and Space Astronomy Purple Mountain Observatory Chinese Academy of Sciences Jiangsu Nanjing210023 China Hebei Normal University Hebei Shijiazhuang050024 China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences Shanghai200030 China Key Laboratory of Cosmic Rays Tibet University Ministry of Education Tibet Lhasa850000 China National Astronomical Observatories Chinese Academy of Sciences Beijing100101 China Sun Yat-Sen University Guangdong Zhuhai519000 China Dipartimento di Fisica Università di Napoli `‘Federico II" Complesso Universit

The core-collapse supernova releases a tremendous number of neutrinos, which can provide insight into many research areas, including particle physics, astrophysics, nuclear physics, and cosmology. We can detect the signal through a positron produced from the inverse beta decay (IBD) interaction between the electron antineutrino and water. The Large high Altitude Air Shower Observatory[1] muon detector (LHAASO-MD) with 51-kton water can serve this purpose. The MD detectors have been designed to have a scattered layout as well as spatial uniformity. We hope to design a dedicated supernova trigger system in the data acquisition system to take advantage of these unique detector characteristics. The large numbers of MeV-scale supernova burst neutrinos can be observed from a collective rise in all photomultiplier rates on top of the dark noise. This system should effectively suppress the cosmic ray background, optimizes the neutrino detection sensitivity, and realizes the supernova neutrino detection by optimizing the online trigger, data acquisition, and offline data analysis at LHAASO. The trigger system is estimated to be fully sensitive to 1987A-type supernova bursts throughout most of the Milky Way and can eventually help LHAASO join the SuperNova Early Warning System (SNEWS). © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Supernovae

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Ultrasensitive polarization-dependent terahertz modulation in hybrid perovskites plasmoninduced transparency devices

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Photonics Research 2019年第9期7卷 994-1002页

作者： JUNHU ZHOU YUZE HU TIAN JIANG HAO OUYANG HAN LI YIZHEN SUI HAO HAO JIE YOU XIN ZHENG ZHONGJIE XU XIANG’AI CHENG College of Advanced Interdisciplinary Studies National University of Defense TechnologyChangsha410073China State Key Laboratory of High Performance Computing College of ComputerNational University of Defense TechnologyChangsha410073China National Innovation Institute of Defense Technology Academy of Military Sciences PLA ChinaBeijing100071China

Active control of metamaterial properties with high tunability of both resonant intensity and frequency is essential for advanced terahertz(THz) applications, ranging from spectroscopy and sensing to *** varied metamaterials, plasmon-induced transparency(PIT) has enabled active control with giant sensitivity by embedding semiconducting materials. However, there is still a stringent challenge to achieve dynamic responses in both intensity and frequency modulation. Here, an anisotropic THz active metamaterial device with an ultrasensitive modulation feature is proposed and experimentally studied. A radiative-radiative-coupled PIT system is established, with a frequency shift of 0.26 THz in its sharp transparent windows by polarization rotation. Enabled by high charge-carrier mobility and longer diffusion lengths, we utilize a straightforwardly spincoated MAPbI3 film acting as a photoactive medium to endow the device with high sensitivity and ultrafast *** the device is pumped by an ultralow laser fluence, the PIT transmission windows at 0.86 and 1.12 THz demonstrate a significant reduction for two polarizations, respectively, with a full recovery time of 561 ps. In addition, we numerically prove the validity that the investigated resonator structure is sensitive to the optically induced conductivity. The hybrid system not only achieves resonant intensity and frequency modulations simultaneously, but also preserves the all-optical-induced switching merits with high sensitivity and speed, which enriches multifunctional subwavelength metamaterial devices at THz frequencies.

关键词： THz Ultrasensitive polarization-dependent terahertz modulation in hybrid perovskites plasmoninduced transparency devices

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Raising the supremacy threshold for boson sampling by preventing sample loss

arXiv

引用

arXiv 2019年

作者： Liu, Yong Xiong, Min Wu, Chunqing Wang, Dongyang Liu, Yingwen Ding, Jiangfang Huang, Anqi Fu, Xiang Qiang, Xiaogang Xu, Ping Deng, Mingtang Yang, Xuejun Wu, Junjie Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer National University of Defense Technology Changsha410073 China

It is promising to achieve quantum supremacy with boson sampling given the rapid development of physical implementations. However, the sample loss issue, which exists in both the physical experiments and classical simulation, has a strong impact on where the frontier of quantum supremacy is. Addressing this, we present Sample Caching Markov Chain Monte Carlo (SC-MCMC), a sampling method that can generate samples without loss. SC-MCMC can reduce the estimated time for a 50-photon sample in ∼10 days to Copyright © 2019, The Authors. All rights reserved.

关键词： Bosons

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Temporal Spectrum Cartography in Low-Altitude Economy Networks: A Generative AI Framework with Multi-Agent Learning

arXiv

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arXiv 2025年

作者： Zhao, Changyuan Zhang, Ruichen Wang, Jiacheng Niyato, Dusit Sun, Geng Du, Hongyang Li, Zan Jamalipour, Abbas Kim, Dong In College of Computing and Data Science Nanyang Technological University Singapore CNRS@CREATE 1 Create Way 08-01 Create Tower 138602 Singapore College of Computer Science and Technology Jilin University 130012 China Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong State Key Laboratory of Integrated Services Networks Xidian University Xian710071 China School of Electrical and Computer Engineering University of Sydney Australia Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

This paper introduces a two-stage generative AI (GenAI) framework tailored for temporal spectrum cartography in low-altitude economy networks (LAENets). LAENets, characterized by diverse aerial devices such as UAVs, rely heavily on wireless communication technologies while facing challenges, including spectrum congestion and dynamic environmental interference. Traditional spectrum cartography methods have limitations in handling the temporal and spatial complexities inherent to these networks. Addressing these challenges, the proposed framework first employs a Reconstructive Masked Autoencoder (RecMAE) capable of accurately reconstructing spectrum maps from sparse and temporally varying sensor data using a novel dual-mask mechanism. This approach significantly enhances the precision of reconstructed radio frequency (RF) power maps. In the second stage, the Multi-agent Diffusion Policy (MADP) method integrates diffusion-based reinforcement learning to optimize the trajectories of dynamic UAV sensors. By leveraging temporal-attention encoding, this method effectively manages spatial exploration and exploitation to minimize cumulative reconstruction errors. Extensive numerical experiments validate that this integrated GenAI framework outperforms traditional interpolation methods and deep learning baselines by achieving 57.35% and 88.68% reconstruction error reduction, respectively. The proposed trajectory planner substantially improves spectrum map accuracy, reconstruction stability, and sensor deployment efficiency in dynamically evolving low-altitude environments. © 2025, CC BY.

关键词： Deep reinforcement learning

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Elucidating the effects of metakaolin-based geopolymer filler on the performance of styrene-butadiene-styrene modified asphalt: Microstructural insights and mechanistic analysis

引用

Construction and Building Materials 2025年 487卷

作者： Yan, Tianyi Meng, Yongjun Li, Yanbo Wu, Guangwei Huang, Zhikuan Chen, Kuicheng Zhang, Yu Wang, Dawei College of Civil Engineering and Architecture Guangxi University Guangxi Nanning530004 China State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures Guangxi Nanning530004 China Special Geological Highway Safety Engineering Technology Research Center of Guangxi Nanning530004 China National High-performance Computing Center Nanning Branch Guangxi Nanning530004 China School of Transportation Science and Engineering Harbin Institute of Technology Harbin150090 China Institute of Highway Engineering RWTH Aachen University Aachen52074 Germany

This study aims to elucidate the effects of metakaolin-based geopolymer (Mk-Geo) filler on the performance of styrene-butadiene-styrene (SBS) modified asphalt and its underlying mechanisms. Mk-Geo asphalt mastics with varying filler-asphalt ratios (F/A = 0.2～1.4) were prepared, and their microstructural properties and physicochemical interactions were characterized using Fourier-transform infrared spectroscopy, thermogravimetric analysis, Brunauer-Emmett-Teller surface area analysis, and X-ray diffraction. The results revealed that Mk-Geo exhibits a multilayer mesoporous plate-like structure, which significantly influences its interaction with asphalt. Dynamic shear rheometer tests demonstrated that Mk-Geo enhances the high-temperature deformation resistance (indicated by an increase in the rutting factor G*/sinδ) and permanent deformation resistance, while also reducing temperature sensitivity. At F/A = 0.8, Mk-Geo promotes SBS phase swelling through surface adsorption, thereby improving the integrity of the three-dimensional network structure. As the F/A increases, the adsorption capacity of asphalt by the mesoporous structure increases, with a characteristic absorption peak of CaCO3 crystalline phase appearing at F/A = 1.4. However, high F/A negatively affects the fatigue performance of asphalt mastic, and premature fatigue damage occurs within the asphalt mastic at high strain levels and high F/A, leading to a reduction in fatigue life. In summary, the Mk-Geo can be applied not only as an adsorbent or modifier in asphalt materials, but also as a filler in asphalt mixtures, and the optimal F/A of 1.2 was obtained by ANOVA and statistical analysis. These findings provide a theoretical foundation for the functional application of geopolymers in asphalt pavement engineering. © 2025 Elsevier Ltd

关键词： Fourier transform infrared spectroscopy

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Generative Models in Computational Pathology: A Comprehensive Survey on Methods, Applications, and Challenges

arXiv

引用

arXiv 2025年

作者： Zhang, Yuan Zhang, Xinfeng Qi, Xiaoming Wu, Xinyu Chen, Feng Yang, Guanyu Fu, Huazhu Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications [Southeast University Ministry of Education Nanjing China School of Biomedical Engineering Tsinghua University Beijing China Department of Biomedical Engineering Department of Electrical and Computer Engineering National University of Singapore Singapore Singapore School of Information Science and Engineering Southeast University Nanjing China Department of Biostatistics Center for Global Health School of Public Health Nanjing Medical University Nanjing China Institute of High-Performance Computing Agency for Science Technology and Research Singapore

Generative modeling has emerged as a promising direction in computational pathology, offering capabilities such as data-efficient learning, synthetic data augmentation, and multimodal representation across diverse diagnostic tasks. This review provides a comprehensive synthesis of recent progress in the field, organized into four key domains: image generation, text generation, multimodal image–text generation, and other generative applications, including spatial simulation and molecular inference. By analyzing over 150 representative studies, we trace the evolution of generative architectures—from early generative adversarial networks to recent advances in diffusion models and foundation models with generative capabilities. We further examine the datasets and evaluation protocols commonly used in this domain and highlight ongoing limitations, including challenges in generating high-fidelity whole slide images, clinical interpretability, and concerns related to the ethical and legal implications of synthetic data. The review concludes with a discussion of open challenges and prospective research directions, with an emphasis on developing unified, multimodal, and clinically deployable generative systems. This work aims to provide a foundational reference for researchers and practitioners developing and applying generative models in computational pathology. © 2025, CC BY-NC-ND.

关键词： Generative adversarial networks

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Human-robot skill transfer systems for mobile robot based on multi sensor fusion

Human-robot skill transfer systems for mobile robot based on...

引用

IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Dingping Chen Jilin He Guanyu Chen Xiaopeng Yu Miaolei He Youwen Yang Junsong Li Xuanyi Zhou State Key Laboratory of High Performance Complicated Central South University Changsha China College of Engineering and Design Hunan Normal University Changsha China Institute of Bioadditive Manufacturing Jiangxi University of Science and Technology Nanchang China

ISBN: (数字)9781728160757

ISBN: (纸本)9781728160764

Teaching by demonstration (TbD) is a powerful way to generalize the skills learned from human demonstrations to fulfill complex requirements. The mobile robot can learn new skills from interaction with human being in an intuitive way. In this paper, we propose a human-robot skill transfer system for a mobile robot that is instructed to follow a trajectory demonstrated by a human teacher wearing a motion capturing device while the Kinect sensor is recording the trajectory. With multi-modal sensor fusion, the position and velocity of the human teacher are enhanced for the correction and accuracy. A nonlinear system named a dynamic movement primitive (DMP) is modeled by the trajectories data. The Gaussian mixture model is applied for the appraisal of DMP, so as to model numerous trajectories through the teaching of a demonstration. Further, to achieve the accuracy of the trajectory tracking, a novel nonlinear model predictive control (MPC) approach is proposed for motion control. By comparison with other obstacle avoidance works, the results show improved performances in terms of the computing time and length of the trajectory.

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