检索结果-南通市图书馆

Air target intention recognition and causal effect analysis combining uncertainty information reasoning and potential outcome framework

在线全文

学校读者我要写书评

暂无评论

Chinese Journal of Aeronautics 2024年第1期37卷 287-299页

作者： Yu ZHANG Fanghui HUANG Xinyang DENG Mingda LI Wen JIANG School of Electronics and Information Northwestern Polytechnical UniversityXi’an 710129China

Recognizing target intent is crucial for making decisions on the ***,the imperfect and ambiguous character of battlefield situations challenges the validity and causation analysis of classical intent recognition *** with the challenge,a target intention causal analysis paradigm is proposed by combining with an Intervention Retrieval(IR)model and a Hybrid Intention Recognition(HIR)*** target data acquired by the sensors are modelled as Basic Probability Assignments(BPAs)based on evidence theory to create uncertain ***,the HIR model is utilized to recognize intent for a tested sample from uncertain ***,the intervention operator under the evidence structure is utilized to perform attribute intervention on the tested *** retrieval is performed in the sample database based on the IR model to generate the intention distribution of the pseudo-intervention samples to analyze the causal effects of individual sample *** simulation results demonstrate that our framework successfully identifies the target intention under the evidence structure and goes further to analyze the causal impact of sample attributes on the target intention.

关键词： Causal effect analysis Hybrid intention recognition Intervention retrieval Target intention Uncertainty reasoning

Quantum discord and its dynamics for multipartite systems

在线全文

学校读者我要写书评

暂无评论

Chinese Physics B 2024年第6期33卷 168-175页

作者：罗嘉欣郭琼 College of sciences Shanghai Institute of TechnologyShanghai 201418China

Quantum discord, one of the famous quantum correlations, has been recently generalized to multipartite systems by Radhakrishnan et al. Here we give analytical solutions of the quantum discord for a family of N-qubit quantum states. For the bipartite system, we derive a zero quantum discord which will remain unchanged under the phase damping channel. For multiparitite systems, it is found that the quantum discord can be classified into three categories and the quantum discord for odd-partite systems can exhibit freezing under the phase damping channel, while the freezing does not exist in the even-partite systems.

关键词： quantum discord multipartite systems decoherence channels frozen discord

Path signature-based XAI-enabled network time series classification

在线全文

学校读者我要写书评

暂无评论

science china(Information sciences) 2024年第7期67卷 91-106页

作者： Le SUN Yueyuan WANG Yongjun REN Feng XIA Department of Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science and Technology School of Computing Technologies Royal Melbourne Institute of Technology

Classifying network time series(NTS) is crucial for automating network administration and ensuring cyberspace security. It enables the detection of anomalies, the identification of network attacks,and the monitoring of performance issues, thereby providing valuable support for network protection and optimization. However, modern communication networks pose challenges for NTS classification *** include handling large-scale and complex NTS data, extracting features from intricate datasets, and addressing explainability requirements. These challenges are particularly pronounced for complex 5G networks. Notably, explainability has become crucial for the widespread deployment of network automation for 5G networks and beyond. To tackle these challenges, we propose a path-signature-based NTS classification model called recurrent signature(Recur Sig). This innovative model is designed to overcome the time-consuming feature selection problem by utilizing deep-learning(DL) techniques. Additionally, it provides a solution for addressing the black-box issue associated with DL models in network automation systems(NAS) by incorporating an explainable classification approach. Extensive experimentation on various public datasets demonstrates that Recur Sig outperforms existing models in accuracy and explainability. The results indicate its potential for application in cyberspace security and automated network management, offering an explainable solution for network protection and optimization.

关键词： network time series classification explainable artificial intelligence path signature automated network management recurrent neural network

同方期刊数据库

Cancer cell membrane-coated bacterial ghosts for highly efficient paclitaxel delivery against metastatic lung cancer

在线全文

学校读者我要写书评

暂无评论

Acta Pharmaceutica Sinica B 2024年第1期14卷 365-377页

作者： Dandan Ling Xueli Jia Ke Wang Qiucheng Yan Bochuan Yuan Lina Du Miao Li Yiguang Jin Anhui Medical University Hefei 230032China Department of Pharmaceutical sciences Beijing Institute of Radiation MedicineBeijing 100850China

Chemotherapy is one of the major approaches for the treatment of metastatic lung cancer,although it is limited by the low tumor delivery efficacy of anticancer *** therapy is emerging for cancer treatment due to its high immune stimulation effect;however,excessively generated immunogenicity will cause serious inflammatory response ***,we prepared cancer cell membrane-coated liposomal paclitaxel-loaded bacterial ghosts(LP@BG@CCM)by layer-by-layer encapsulation for the treatment of metastatic lung *** preparation processes were simple,only involving film formation,electroporation,and pore ***@BG@CCM owned much higher 4T1 cancer cell toxicity than LP@BG due to its faster fusion with cancer *** the 4T1 breast cancer metastatic lung cancer mouse models,the remarkably higher lung targeting of intravenously injected LP@BG@CCM was observed with the almost normalized lung appearance,the reduced lung weight,the clear lung tissue structure,and the enhanced cancer cell apoptosis compared to its ***,several major immune factors were improved after administration of LP@BG@CCM,including the CD4^(+)/CD8a^(+)T cells in the spleen and the TNF-α,IFN-γ,and IL-4 in the ***@BG@CCM exhibits the optimal synergistic chemo-immunotherapy,which is a promising medication for the treatment of metastatic lung cancer.

关键词： Apoptosis Bacterial ghost Cancer cell membrane Immune stimulation Liposome Lung targeting Metastatic lung cancer Paclitaxel

When debugging encounters artificial intelligence: state of the art and open challenges

在线全文

学校读者我要写书评

暂无评论

science china(Information sciences) 2024年第4期67卷 42-84页

作者： Yi SONG Xiaoyuan XIE Baowen XU School of Computer science Wuhan University State Key Laboratory of Novel Software Technology Nanjing University

Both software debugging and artificial intelligence techniques are hot topics in the current field of software engineering. Debugging techniques, which comprise fault localization and program repair, are an important part of the software development lifecycle for ensuring the quality of software systems. As the scale and complexity of software systems grow, developers intend to improve the effectiveness and efficiency of software debugging via artificial intelligence(artificial intelligence for software debugging, AI4SD). On the other hand, many artificial intelligence models are being integrated into safety-critical areas such as autonomous driving, image recognition, and audio processing, where software debugging is highly necessary and urgent(software debugging for artificial intelligence, SD4AI). An AI-enhanced debugging technique could assist in debugging AI systems more effectively, and a more robust and reliable AI approach could further guarantee and support debugging techniques. Therefore, it is important to take AI4SD and SD4AI into consideration comprehensively. In this paper, we want to show readers the path, the trend, and the potential that these two directions interact with each other. We select and review a total of 165 papers in AI4SD and SD4AI for answering three research questions, and further analyze opportunities and challenges as well as suggest future directions of this cross-cutting area.

关键词： software debugging fault localization program repair artificial intelligence machine learning

同方期刊数据库

An integrated MINLP model for multi-party coordination in downstream oil supply chain

在线全文

学校读者我要写书评

暂无评论

Petroleum science 2024年第3期21卷 2066-2079页

作者： Rui Qiu Bo Zhang Wei Zhao Ren-Fu Tu Man-Qiu He Qi Liao Yong-Tu Liang national Engineering Laboratory for Pipeline Safety/Beijing Key Laboratory of Urban Oil and Gas Distribution Technology China University of Petroleum-BeijingFuxue Road No.18Changping DistrictBeijing102249PR China Strategy&Implementation Department PipeChinaDongtucheng Road No.5Chaoyang DistrictBeijing100013PR China

Cooperation among enterprises can bring overall and individual performance improvement,and a smooth coordination method is ***,due to the lack of customized coordination methods,cooperation in the downstream oil supply chain cannot be carried out *** paper intends to propose a multi-party coordination method to promote cooperation between oil shippers and pipeline operator by optimizing oil transportation,oil substitution and pipeline pricing *** integrated game-theoretic modeling and analysis approach is developed to characterize the operation behaviors of all stakeholders in the downstream oil supply *** proposed mixed integer nonlinear programming model constrains supply and demand capacity,transportation routes,oil substitution rules and pipeline freight *** transformation and price discretization are introduced for model linear *** experiments are carried out in the oil distribution system in South *** results show that compared to the business-as-usual scheme,the new scheme saves transportation cost by 3.48%,increases pipeline turnover by 5.7%,and reduces energy consumption and emissions by 7.66%and 6.77%.It is proved that the proposed method improves the revenue of the whole system,achieves fair revenue distribution,and also improves the energy and environmental benefits of the oil supply chain.

关键词： Downstreamoil supplychain Multi-partycoordination Cooperative game Mixed integernonlinear programming model Pipeline transportation Revenue distribution

MULTIRATE TIME ITERATIVE SCHEME WITH MULTIPHYSICS FINITE ELEMENT METHOD FOR A NONLINEAR POROELASTICITY

在线全文

学校读者我要写书评

暂无评论

Journal of Computational Mathematics 2024年第2期42卷 597-616页

作者： Zhihao Ge Hairun Li Tingting Li School of Mathematics and Statistics Henan UniversityKaifengHenan 475004China

In this paper,a multirate time iterative scheme with multiphysics finite element method is proposed and analyzed for the nonlinear poroelasticity *** original problem is reformulated into a generalized nonlinear Stokes problem coupled with a diffusion problem of a pseudo pressure field by a new multiphysics approach.A multiphysics finite element method is adopted for the spatial discretization,and the generalized nonlinear Stokes problem is solved in a coarse time step and the diffusion problem is solved in a finer time *** proposed algorithm is a decoupled algorithm,which is easily implemented in computation and reduces greatly computation *** stability analysis and the convergence analysis for the multirate iterative scheme with multiphysics finite element method are *** numerical tests are shown to demonstrate and validate the analysis results.

关键词： Nonlinear poroelasticity model Multiphysics finite element method Multirate iterative scheme

Feedback of Efficient Shock Acceleration on Magnetic-field Structure Inside Young Type Ia Supernova Remnants

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Research in Astronomy and Astrophysics 2024年第6期24卷 234-244页

作者： Jun-Yu Shen Bi-Wen Bao Li Zhang Department of Astronomy Key Laboratory of Astroparticle Physics of Yunnan ProvinceYunnan UniversityKunming 650091China Key Laboratory of Statistical Modeling and Data Analysis of Yunnan Province Yunnan UniversityKunming 650091China

Using an effective adiabatic index γ_(eff) to mimic the feedback of efficient shock acceleration,we simulate the temporal evolution of a young type Ia supernova remnant (SNR) with two different background magnetic field(BMF) topologies:a uniform and a turbulent *** density distribution and magnetic-field characteristics of our benchmark SNR are studied with two-dimensional cylindrical magnetohydrodynamic *** γ_(eff)is considered,we find that:(1) the two-shock structure shrinks and the downstream magnetic-field orientation is dominated by the Rayleigh–Taylor instability structures;(2) there exists more quasi-radial magnetic fields inside the shocked region;and (3) inside the intershock region,both the quasi-radial magnetic energy density and the total magnetic energy density are enhanced:in the radial direction,with γ_(eff)=1.1,they are amplified about 10–26 times more than those with γ_(eff)=5/*** in the angular direction,the total magnetic energy densities could be amplified about 350 times more than those with γ_(eff)=5/3,and there are more grid cells within the intershock region where the magnetic energy density is amplified by a factor greater than 100.

关键词： methods:numerical ISM:magnetic fields ISM:supernova remnants magnetohydrodynamics(MHD)

Learning topological defects formation with neural networks in a quantum phase transition

在线全文

学校读者我要写书评

暂无评论

Communications in Theoretical Physics 2024年第5期76卷 68-76页

作者： Han-Qing Shi Hai-Qing Zhang Center for Gravitational Physics Department of Space ScienceBeihang UniversityBeijing 100191China Peng Huanwu Collaborative Center for Research and Education Beihang UniversityBeijing 100191China

Neural networks possess formidable representational power,rendering them invaluable in solving complex quantum many-body *** they excel at analyzing static solutions,nonequilibrium processes,including critical dynamics during a quantum phase transition,pose a greater challenge for neural *** address this,we utilize neural networks and machine learning algorithms to investigate time evolutions,universal statistics,and correlations of topological defects in a one-dimensional transverse-field quantum Ising ***,our analysis involves computing the energy of the system during a quantum phase transition following a linear quench of the transverse magnetic field *** excitation energies satisfy a power-law relation to the quench rate,indicating a proportional relationship between the excitation energy and the kink ***,we establish a universal power-law relationship between the first three cumulants of the kink numbers and the quench rate,indicating a binomial distribution of the ***,the normalized kink-kink correlations are also investigated and it is found that the numerical values are consistent with the analytic formula.

关键词： neural networks machine learning transverse-field quantum Ising model kibble-zurek mechanism