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SSRN 2023年

作者： Xu, Jiaming He, Chunlong Li, Xingquan Li, Zhukun The Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen China The Shenzhen Institute of Information Technology Shenzhen China

In this paper, we focus on trajectory optimization for multiple unmanned aerial vehicles (UAVs) which are utilized as aerial base stations (BS) to provide radio coverage for Internet of Things (IoT) devices. These IoT devices are randomly distributed in a three-dimensional region with unknown locations and channel parameters. By optimizing the UAV trajectory and power, we aim to achieve the minimum communication time for all IoT devices. However, the unknown flight time of the UAVs and the IoT device locations make it difficult to formulate an optimization problem between the objective and variables by using traditional convex optimization. To deal with this intractable problem, we propose a Deep Reinforcement Learning (DRL)-based solution, specifically Proximal Policy Optimization (PPO), modeling it as a Markov Decision Process (MDP). Our simulation results show that the proposed PPO offers promising performance for both training and testing phases. © 2023, The Authors. All rights reserved.

关键词： Internet of things

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Research in Quotient Space Theory Based on Structure

Research in Quotient Space Theory Based on Structure

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Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)

作者： Liquan ZHAO Ling ZHANG Province Key Laboratory of Electronic Business Nanjing University of Finance and Economics Nanjing Key Laboratory of Intelligent Computing & Signal Processing of Ministry of Education Anhui Universi

ISBN: (纸本)9781424404759

The quotient space theory is indented to study the relationship of transform and that of dependency among the worlds with different grain-size. Compared-with other granule computing tools, it has more powerful abilities of representation and absorption. The reason is that structure is introduced in its model The paper is to study the quotient space theory based on structure. We first introduce some methods of constructing quotient structure. Then we study in detail the quotient space family based on structure, and get some good results for further research. Finally we also briefly discuss hierarchical structure of fuzzy sets.

关键词： quotient space granule computing fuzzy set rough set hierarchical structure.

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A circularly polarized low-profile Metasurface antenna based on CPW feed

A circularly polarized low-profile Metasurface antenna based...

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IEEE International Wireless Symposium (IWS)

作者： Changqing Liu Liang Zhang Shijie Huang Chao Wang Xingchuan Yu Xianliang Wu Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University AnHui Province Key Laboratory of simulation and design for Electronic information system Hefei Normal university Hefei China

ISBN: (数字)9781728167039

ISBN: (纸本)9781728167046

A low-profile circularly polarized Metasurfaces antenna based on compact coplanar waveguide (CPW) feed was proposed. The Metasurfaces consists of 16 periodic square-cut metal patches. An hourglass coupled slot was adopted to achieve broadband impedance matching. The antenna has a simple structure and a low cross section, and it can be implemented by a layer of a printed circuit substrate. A circular polarized wave is generated by changing the size of the cut angle of the Metasurfaces, and at the same time, the impedance bandwidth can be widened. To verify the simulation results, a 1λ 0 ×1λ 0 ×0.05λ 0 (at 10 GHz) model antenna was fabricated and measured. The simulation and measurement results show good consistency. The test results show that the -10dB return loss bandwidth reaches 45.3 %, and the circular polarization axis ratio(AR) is less than 3dB with a bandwidth of 18.5%.

关键词： Antenna measurements Polarization Bandwidth Metasurfaces Radar antennas Antenna feeds Coplanar waveguides

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Impulsive control with time windows for hyperchaotic exponential synchronization 6

Impulsive control with time windows for hyperchaotic exponen...

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6th International Conference on information, Cybernetics, and Computational Social Systems, ICCSS 2019

作者： Wu, Hongjuan Hu, Xiang Feng, Yuming Tu, Zhengwen Key Laboratory of Intelligent Information Processing and Control of Chongqing Municipal Institutions of Higher Education Chongqing Three Gorges University Wanzhou Chongqing China School of Three Gorges Artificial Intelligence Chongqing Three Gorges University Wanzhou Chongqing China

ISBN: (纸本)9781728158570

In actual situation, the input error of impulsive signal is inevitable and there are always some time delays when different systems communicate with each other. Then, considering the input error and time delays in the real world, this paper provides the criteria for the exponential lag synchronization of one kind of hyperchaotic system based on impulsive control with time windows, matrix inequalities, etc. Finally, the simulation results are displayed to illustrate the theoretical results. © 2019 IEEE.

关键词： Time delay

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Boosting the Transferability of Video Adversarial Examples via Temporal Translation

arXiv

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arXiv 2021年

作者： Wei, Zhipeng Chen, Jingjing Wu, Zuxuan Jiang, Yu-Gang Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University China Shanghai Collaborative Innovation Center on Intelligent Visual Computing China

Although deep-learning based video recognition models have achieved remarkable success, they are vulnerable to adversarial examples that are generated by adding human-imperceptible perturbations on clean video samples. As indicated in recent studies, adversarial examples are transferable, which makes it feasible for black-box attacks in real-world applications. Nevertheless, most existing adversarial attack methods have poor transferability when attacking other video models and transfer-based attacks on video models are still unexplored. To this end, we propose to boost the transferability of video adversarial examples for black-box attacks on video recognition models. Through extensive analysis, we discover that different video recognition models rely on different discriminative temporal patterns, leading to the poor transferability of video adversarial examples. This motivates us to introduce a temporal translation attack method, which optimizes the adversarial perturbations over a set of temporal translated video clips. By generating adversarial examples over translated videos, the resulting adversarial examples are less sensitive to temporal patterns existed in the white-box model being attacked and thus can be better transferred. Extensive experiments on the Kinetics-400 dataset and the UCF-101 dataset demonstrate that our method can significantly boost the transferability of video adversarial examples. For transfer-based attack against video recognition models, it achieves a 61.56% average attack success rate on the Kinetics-400 and 48.60% on the UCF-101. Code is available at https://***/zhipeng-wei/TT. © 2021, CC BY.

关键词： Deep learning

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Skeletal model de-nosing with cascaded network

Skeletal model de-nosing with cascaded network

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2018 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2018

作者： Liang, Tianjiao Li, Zhongtao Hu, Libin Xiao, Shipeng School of Information Science and Engineering University of Jinan Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan250022 China Department of Joint Surgery and Sports Medicine Second Hospital of Shandong University Jina Shandong China

ISBN: (纸本)9781728105512

With the continuous breakthrough of three-dimensional(3D) data visualization and 3D printing technology, there are many achievements in the combination field of computer science and medical science. Especially in orthopedics, the 3D printed skeletal model and prosthesis have a good effect on surgeon's surgery and patient rehabilitation process. The 3D printed skeletal model plays a vital role in the surgical process, and the accuracy of the three-dimensional printed skeletal model determines the extent of this auxiliary effect. In the field of orthopedics, we propose to use the data-driven the radial basis function(RBF) network to remove noise from the surface of the skeletal model. The RBF network achieves the goals of denoising by learning the regression relationship between the noisy mesh and the geometry descriptor called the filtered facet normal descriptor (FND) based on bilateral normal filters of the corresponding smooth facet, without making many unreasonable assumptions made by the traditional denoising algorithms. Based on the cascaded model, we adjusts the noise level on the training model according to the real situation of the bone reconstruction model, and changes the structure of the geometric descriptor composed of the three-layer cascaded regression function network. The cascaded regression model suitable for skeletal three-dimensional model denoising is trained while maintaining the mesh mean normal vector deviation angle of 4.2°. The model not only removes the noise of the bone 3D model, but also maintains the geometric characteristics of the skeleton model itself. © 2018 IEEE.

关键词： Radial basis function networks

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Fuzzy Clustering Ensemble Based on Dual Boosting

Fuzzy Clustering Ensemble Based on Dual Boosting

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Su-lan Zhai Bin Luo Yu-tang Guo School of Mathematics and Computing Anhui University of Science and Technology Hefei China Key Laboratory of Intelligent Computing Signal Processing of Anhui University Hefei China

It is widely recognized that clustering ensemble is fit for any shape and any distribution dataset and that the boosting method provides superior results for classification problems. In the paper, a dual boosting is proposed for fuzzy clustering ensemble . At each boosting iteration, a new training set is created based on the original datasets' probability which is associated with the previous clustering. According to the dual boosting method, the new training subset contains not only the instances which is hard to cluster in previous stages , but also the instances which is easy to cluster. The final clustering solution is produced by using the clustering based on the co-association matrix. Experiments on both artificial and realworld datasets demonstrate the efficiency of the fuzzy clustering ensemble based on dual boosting in stability and accuracy.

关键词： Boosting Clustering algorithms Signal processing algorithms Partitioning algorithms Laboratories Mathematics Signal processing Shape measurement Robustness Bagging

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tTree+: A Threat Tree Model for Representing Complex Semantics 21

tTree+: A Threat Tree Model for Representing Complex Semanti...

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21st IEEE International Conference on Trust, Security and Privacy in computing and Communications, TrustCom 2022

作者： Wu, Zhitao Hu, Jingjing Zhang, Xiaowei Ren, Wei China Electronic Product Reliability and Environmental Testing Research Institute Guangzhou511370 China China University of Geosciences School of Computer Science Wuhan430074 China Hubei Key Laboratory of Intelligent Geo-Information Processing Wuhan430074 China

ISBN: (纸本)9781665494250

Threat tree model is widely used for risk analysis for software assurance. This model is convenient to convey the logical relations between various threat conditions that will result in a threat iteratively. However, tree representation imposes a limitation in that threat semantics can only present in a solely layered style in a tree structure, e.g., conditions represented by children nodes in the threat tree with edge relations in terms of "and"or "or"will result in the threat represented by the father node. It may not be sufficient for representing certain special cases such as cross-layer conditions, e.g., the nodes at different layers (a child and a uncle) may compose threat conditions, which cannot be represented in a regular tree style. In other words, the conditions represented by a child and a uncle may lead to a threat, either new or not. To extend the semantics of current threat tree model, in this paper, we propose a new threat tree model called tTree+, by extending and converting a non-layered tree representation to a layered tree presentation. Some algorithms are proposed by adding a duplicated node and rebuilding related layers, so that original algorithms for tree operations can be remained without any amendment. This extended tree model can extend the outreach of semantics for further threat analysis, so that the more complex threat can be described and analyzed. © 2022 IEEE.

关键词： Semantics

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Pulse-Coupled Dual Adversarial Learning Network for Infrared and Visible Image Fusion

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Laser and Optoelectronics Progress 2025年第10期62卷

作者： Jia, Zhao Yuelan, Xin Jizhao, Liu Qingqing, Wang School of Physical and Electronic Information Engineering Qinghai Normal University Qinghai Xining810001 China State Key Laboratory of Tibetan Intelligent Information Processing and Application Qinghai Xining810001 China School of Information Science and Engineering Lanzhou University Gansu Lanzhou730000 China Qinghai Meteorological Information Center Qinghai Xining810001 China

To address the issue of insufficient extraction and fusion of complementary information in infrared and visible image fusion, this study proposes a pulse-coupled dual adversarial learning network. The network utilizes dual discriminators that target infrared objects and visible texture details in the fused images, with the goal of preserving and enhancing modality-specific features. We also introduce a pulse-coupled neural network featuring a combined learning mechanism to effectively extract salient features and detailed information from the images. During the fusion stage, we implement a cross-modality fusion module guided by cross-attention, which further optimizes the complementary information between modalities and minimizes redundant features. We conducted comparative qualitative and quantitative analyses against nine representative fusion methods in the TNO, M3FD, and RoadScene datasets. Results show that the proposed method demonstrates superior performance in evaluation metrics, such as mutual information and sum of correlation differences. The method produces fused images with high contrast and rich detail and achieves better results in target detection tasks. © 2025 Universitat zu Koln. All rights reserved.

关键词： Adversarial machine learning

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A Real-time Local Planner Design for Smart Wheelchairs Based on Koopman Bilinear Model Predictive Control

A Real-time Local Planner Design for Smart Wheelchairs Based...

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2024 IEEE International Conference on Real-Time computing and Robotics, RCAR 2024

作者： Yu, Guanfeng Zhang, Han Wang, Zehao Wang, Jingchuan Shanghai Jiao Tong University Institute of Medical Robotics Department of Automation China Ministry of Education of China Key Laboratory of System Control and Information Processing China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9798350372601

The paper introduces a Koopman bilinear model predictive control (KBMPC) as a local planner for smart wheelchair systems. This approach leverages the Koopman Operator to streamline the nonlinear terms in MPC, aiming to achieve superior real-time performance. In particular, we employ the Extended Dynamic Mode Decomposition (EDMD) method to approximate the infinite dimensional Koopman operator. To tackle the challenge of designing lifting functions, we systematically utilize the derivatives of known nonlinear structures to methodically derive lifting functions. This systematic approach facilitates the identification of a precise bilinear model. Next, we formulate the corresponding Koopman bilinear MPC problem. Finally, an iterative algorithm is employed to efficiently solve the KBMPC problem. This method linearizes the bilinear model around estimations and iteratively solves the resulting quadratic programming problem to refine estimations. This allows KBMPC to function as a real-time local planner for smart wheelchairs. The prediction of nonlinear terms shows that the identified Koopman bilinear model increases the prediction accuracy. Furthermore, experiments demonstrate the advantages of the designed KBMPC local planner, highlighting its superior real-time performance and predictive capabilities. © 2024 IEEE.

关键词： Iterative methods

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