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arXiv 2025年

作者： Zhang, Chuang Sun, Geng Li, Jiahui Wang, Jiacheng Zhang, Ruichen Niyato, Dusit Mao, Shiwen Quek, Tony Q.S. Computer Science and Technology Jilin University Changchun130012 China Singapore University of Technology and Design Singapore487372 Singapore College of Computer Science and Technology Jilin University Changchun130012 China College of Computing and Data Science Nanyang Technological University Singapore639798 Singapore Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China Department of Electrical and Computer Engineering Auburn University AuburnAL36849 United States Information System Technology and Design Pillar Singapore University of Technology and Design Singapore487372 Singapore

An integration of satellites and terrestrial networks is crucial for enhancing performance of next generation communication systems. However, the networks are hindered by the long-distance path loss and security risks in dense urban environments. In this work, we propose a satellite-terrestrial covert communication system assisted by the aerial active simultaneous transmitting and reflecting reconfigurable intelligent surface (AASTAR-RIS) to improve the channel capacity while ensuring the transmission covertness. Specifically, we first derive the minimal detection error probability (DEP) under the worst condition that the Warden has perfect channel state information (CSI). Then, we formulate an AASTAR-RIS-assisted satellite-terrestrial covert communication optimization problem (ASCCOP) to maximize the sum of the fair channel capacity for all ground users while meeting the strict covert constraint, by jointly optimizing the trajectory and active beamforming of the AASTAR-RIS. Due to the challenges posed by the complex and high-dimensional state-action spaces as well as the need for efficient exploration in dynamic environments, we propose a generative deterministic policy gradient (GDPG) algorithm, which is a generative deep reinforcement learning (DRL) method to solve the ASCCOP. Concretely, the generative diffusion model (GDM) is utilized as the policy representation of the algorithm to enhance the exploration process by generating diverse and high-quality samples through a series of denoising steps. Moreover, we incorporate an action gradient mechanism to accomplish the policy improvement of the algorithm, which refines the better state-action pairs through the gradient ascent. Simulation results demonstrate that the proposed approach significantly outperforms important benchmarks, and also validate the performance and practicality under different algorithm parameters and environment settings. Copyright © 2025, The Authors. All rights reserved.

关键词： Deep reinforcement learning

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TTVFI: Learning Trajectory-Aware Transformer for Video Frame Interpolation

arXiv

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arXiv 2022年

作者： Liu, Chengxu Yang, Huan Fu, Jianlong Qian, Xueming The School of Information and Communication Engineering Xi’an Jiaotong University Xi'An710049 China Microsoft Research United States The Ministry of Education Key Laboratory for Intelligent Networks and Network Security School of Information and Communication Engineering SMILES Lab. Xi’an Jiaotong University Xi'An710049 China

Video frame interpolation (VFI) aims to synthesize an intermediate frame between two consecutive frames. State-of-the-art approaches usually adopt a two-step solution, which includes 1) generating locally-warped pixels by flow-based motion estimations, 2) blending the warped pixels to form a full frame through deep neural synthesis networks. However, due to the inconsistent warping from the two consecutive frames, the warped features for new frames are usually not aligned, which leads to distorted and blurred frames, especially when large and complex motions occur. To solve this issue, in this paper we propose a novel Trajectory-aware Transformer for Video Frame Interpolation (TTVFI). In particular, we formulate the warped features with inconsistent motions as query tokens, and formulate relevant regions in a motion trajectory from two original consecutive frames into keys and values. Self-attention is learned on relevant tokens along the trajectory to blend the pristine features into intermediate frames through end-to-end training. Experimental results demonstrate that our method outperforms other state-of-the-art methods in four widely-used VFI benchmarks. Both code and pre-trained models will be released at https://***/researchmm/TTVFI. Copyright © 2022, The Authors. All rights reserved.

关键词： Trajectories

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Multiagent Q-Learning for Multicrew Dynamic Scheduling and Routing in Road Network Restoration

Multiagent Q-Learning for Multicrew Dynamic Scheduling and R...

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Chinese Control and Decision Conference, CCDC

作者： Yufeng Shen Lianqi Duan Qianshun Zhu Zhaopin Su Guofu Zhang School of Computer Science and Information Engineering Hefei University of Technology Hefei 230601 School of Computer Science and Information Engineering Hefei University of Technology Hefei Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education Hefei Intelligent Interconnected Systems Laboratory of Anhui Province (Hefei University of Technology) Hefei Anhui Province Key Laboratory of Industry Safety and Emergency Technology (Hefei University of Technology) Heifei

ISBN: (纸本)9781665478977

Road network restoration is an important issue in the post-disaster disposal and rescue, especially when extraordinarily serious natural disasters (e.g., floods and earthquakes) occur. Central to this endeavour is the problem of determining how to reasonably schedule and route the repair crew to quickly restore the damaged road network and establish reliable supply lines from supply nodes to demand nodes. However, most existing work focuses on the activities of the single repair crew in the static road network, which is unable to adapt to the dynamic changes of the road network caused by secondary disasters, such as rock slides and debris flows. Consequently, this work is concentrated on multicrew dynamic scheduling and routing in road network restoration. Specifically, a model of multicrew dynamic scheduling and routing is first presented. Next, the Markov decision process is adopted to construct a decision model for repair crews, based on which a multiagent Q-learning algorithm is developed to find the best scheduling and routing strategy. Finally, experimental results demonstrate that the proposed method can make repair crews adjust their scheduling and routing strategies according to the dynamic changes of the damaged road network and provides a useful attempt to restore the damaged road network in complex, dynamic emergency scenarios of post-disaster.

关键词： Schedules Q-learning Roads Heuristic algorithms Maintenance engineering Markov processes Dynamic scheduling

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Pavement Damage Detection Based on Cascade R-CNN 20

Pavement Damage Detection Based on Cascade R-CNN

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4th International Conference on Computer Science and Application engineering, CSAE 2020

作者： Shen, Tingsheng Nie, Mingxin School of Information Engineering Wuhan Univ. of Technol. and Key Lab. of Fiber Optic Sensing Technology and Information Processing Ministry of Education Wuhan China

ISBN: (纸本)9781450377720

In recent ten years, with the development of economy and the progress of science and technology, highway construction has gradually entered the stage of construction and maintenance. Among them, highway maintenance has become an important aspect of highway construction. The government spends a lot of money each year on maintaining pavements, especially on detecting and renovating. The accuracy of pavement damage detection directly affects the efficiency of renovation. Therefore, in order to reduce the maintenance cost, the accuracy of pavement damage detection is very important. In the past, the detection of pavement damage often aimed at the existence of cracks in the pavement, which could not meet the higher and higher detection requirements. Aiming at the problem of less damage classification and lower accuracy or precision in the past pavement damage detection system, this paper designed a pavement damage detection method based on Cascade R-CNN, which can classify 5 classes of damage and the mean average precision (mAP) reaches 45.5%. © 2020 ACM.

关键词： Pavements

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Investigation on the Electrical Characteristics of Vacuum Diode with Nanoscale Channel

Investigation on the Electrical Characteristics of Vacuum Di...

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International Conference on Vacuum Electronics

作者： Wenhua Tang Zhenfei Hou Lu Gan Shengli Wu Yiwei Liu Xiao Wang Zhihua Shen Key Lab. for Physical Electronics and Devices of the Ministry of Education Xi'an Jiaotong University China Hunan Institute of Advanced Sensing and Information Technology Xiangtan University China School of Electronic Information and Artificial Intelligence Shanxi University of Science and Technology China School of Electronics and Information Engineering Nantong Vocational University China

A vacuum nano-diode with nanoscale channel formed from the square-hole was proposed and prepared via traditional semiconductor lithography and dry etching fabrication techniques in this paper. A thin dielectric layer with a thickness of about 20 nm corresponds to the channel length, this helps the diode operate in atmospheric environments. The effects of different vacuum channel apertures on the electrical properties of vacuum diodes were explored experimentally, and the reasons for the influence in electrical properties were elab.rated in detail. The emission mechanism and working principle of the diode were analyzed through Fowler-Nordheim theory. Besides, the breakdown ability and emission current stability of vacuum diodes with different apertures were investigated by continuously voltage increasing test.

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High Crystalline Quality A-Axis Oriented Al0.56Sc0.44N Films for High Coupling Saw Applications

High Crystalline Quality A-Axis Oriented Al0.56Sc0.44N Films...

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International Conference on Solid State Sensors and Actuators (TRANSDUCERS)

作者： Weipeng Xuan Weilun Xie Xiwei Huang Xingli He Zhen Cao Hao Jin Shurong Dong Jikui Luo Ministry of Education Key Lab. of RF Circuits and Systems College of Electron. & Info Hangzhou Dianzi University Hangzhou China School of Electronic and Information Engineering Soochow University Suzhou China Key Lab. of Adv. Micro/Nano Electron. Dev. & Smart Sys. of Zhejiang College of Info. Sci. & Electronic Eng Zhejiang University Hangzhou China International Joint Innovation Center Zhejiang University Haining China

High crystalline quality Al 0.56 Sc 0.44 N $\left( {11\bar 20} \right)$ (a-plane) films were prepared on Al 2 O 3 $\left( {1\bar 102} \right)$ substrates by magnetron reaction sputtering. X-ray diffraction (XRD) analysis indicates that the grown Al 0.56 Sc 0.44 N films are single-phased and a-plane oriented. The full width at half maximum (FWHM) of the rocking curve is only 0.4°, showing the high crystalline quality of the films. Effects of the normalized thickness h AlScN /λ on the acoustic wave propagation properties of the SAW resonator are evaluated by simulations. SAW resonators based on the sputtered non-polar $\left( {11\bar 20} \right)$ Al 0.56 Sc 0.44 N films were prepared, which present a maximum electromechanical coupling coefficient $\left( {k_{eff}^2} \right)$ of 5.7%.

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The new trend of compartment steel-concrete-steel composite structures in immersed tunnels 9

The new trend of compartment steel-concrete-steel composite ...

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9th International Conference on Advances in Steel Structures, ICASS 2018

作者： Guo, Yu-Tao Fan, Jian-Sheng Nie, Jian-Guo China Key Lab. of Civil Engineering Safety and Durability of China Education Ministry Dept. of Civil Engineering Tsinghua University Beijing China Beijing Engineering Research Center of Steel and Concrete Composite Structures Beijing China

ISBN: (纸本)9889914093

The compartment steel-concrete-steel (CSCS) sandwich composite structures which are characterized with orthogonal longitudinal and transverse steel diaphragms (webs) exhibit superiorities in capacity and construction efficiency compared to traditional engineering structures, offering a competitive choice for the application of mega immersed tunnels. The history and development of immersed tunnels have been reviewed and it is found that there had been three historical stages: steel shell structures;reinforced concrete (RC) structures and steel-concrete-steel composite structures. The utilizations of SCS composite structures in immersed tunnels are summarized and different types of SCS structures are presented. To reveal the mechanisms of the out-of-plane performances of CSCS composite structures, bending and shear tests are designed and conducted by the authors. It is found that the current design method cannot predict the shear capacity satisfactorily and some of the structural restrictions could be loosen. Based on the literature review and the tests, several suggestions have been proposed for the design of CSCS composite structure immersed tunnels. Copyright © 2018 by The Hong Kong Institute of Steel Construction.

关键词： Reinforced concrete

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An Abnormal data Analysis and Processing Method for Genealogy Graph databases

An Abnormal Data Analysis and Processing Method for Genealog...

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IEEE International Conference on Big knowledge (ICBK)

作者： Jianxuan Shao Guliu Liu Shengwei Ji Ministry of Education Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) China

ISBN: (数字)9781728181561

ISBN: (纸本)9781728181578

Large amounts of data are generated continually in the real world. The objects in the data and the relationships between them have become increasingly complex. Graph is a powerful tool for representing these data and the complex relationships between them. To effectively describe the entities and connections in these data, the concept of a knowledge graph was proposed, and knowledge graph has become one of the bases for storing graph data, and the importance of it is self-evident. Genealogy data is a kind of graph data where nodes are used to represent the person in the genealogy data, and edges are used to represent the relationship between the person. Moreover, in a genealogy graph database, the "critical" relationship that is unique for an entity is defined. In contrast, the abnormal data derive from the existence of multiple "critical" relationships between entities. In a genealogy graph, abnormal data will cause the wrong relationships and redundant entities. To avoid such abnormal data in genealogy graph database, the abnormal data are categorized into four different types, and the corresponding processing methods are proposed for each type of abnormal data, respectively. The experiment results demonstrate that the processing method can effectively solve these abnormal data.

关键词： databases Biology Task analysis Anomaly detection data models knowledge engineering Big data

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Web Log Analysis in Genealogy System

Web Log Analysis in Genealogy System

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IEEE International Conference on Big knowledge (ICBK)

作者： Xiaojian Liu Yi Zhu Shengwei Ji Ministry of Education Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) China

ISBN: (数字)9781728181561

ISBN: (纸本)9781728181578

A large amount of log data is generated every moment in many real-world applications. System logs, mobile application logs, web logs etc., all of which contain rich information and can be analyzed for valuable information. At the same time, genealogy attracts more and more attention in recent decades, especially for Chinese. People utilize the genealogy system to seek roots, find source of family, build a family tree and so on. Due to the complexity of genealogy data and specific features of genealogy system, how to extract and analyze the valued genealogy information effectively is a huge challenge. Motivated by this, we propose a novel analysis method using web logs in genealogy system for drawing user profile and providing personalized recommendations. More specifically, firstly, all web logs are extracted from genealogy system based on the enhanced logs which record the behaviors and data of user. Secondly, the extracted logs are formatted for analysis, and we analyze the logs to extract various user-related attributes for drawing user profile. Finally, personalized recommendations like interested people and family tree are provided for each user in system. The high availab.lity and effectiveness of our proposed method is verified on genealogy system-Huapu system.

关键词： data mining databases data visualization Tools Big data Feature extraction knowledge engineering

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Causal structure learning of nonlinear additive noise model based on streaming feature

Causal structure learning of nonlinear additive noise model ...

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IEEE International Conference on data Mining Workshops (ICDM Workshops)

作者： Jing Yang Gaojin Fan Anbo Shen Aiguo Wang Ministry of Education Key Laboratory of Knowledge Engineering With Big Data(Hefei University of Technology) School of Computer Science and Information Engineering Hefei University of Technology Hefei P. R. China School of Electronic and Information Engineering Foshan University China

ISBN: (纸本)9781665424288

The current streaming feature structure learning needs to be improved in the processing of nonlinear continuous data and the dynamic acquisition of causal structures. In this paper, we propose a causal structure learning algorithm, CANSF, based on the streaming feature of additive noise models. We have made three contributions. First, by using the information carried by the noise of nonlinear continuous data, we propose a real correlation identification method based on logarithmic likelihood, which can identify the real correlation and redundant features of target features, and dynamically select parent and child nodes for each feature. Second, based on regression analysis, a method to determine the causal direction is proposed, which can be used for dynamic orientation. Third, a learning method of causal structure based on streaming features is proposed, which can obtain the Causal structure diagram directly and dynamically.

关键词： Additive noise Learning systems Correlation Heuristic algorithms Conferences data models Regression analysis

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