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4th International Conference on Artificial Intelligence in China, AIC 2022

作者： Wang, Yue Zhang, Xin Key Laboratory of Electronics and Information Technology for Complex Space Systems National Space Science Center Chinese Academy of Sciences Beijing100190 China Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission Tianjin Normal University Tianjin300387 China

ISBN: (纸本)9789819912551

Visual pose estimation is essential for many space applications, such as autonomous robots for planetary exploration, asteroid exploration, and spacecraft pose estimation. However, the high reliability requirement of space applications cannot be satisfied by general visual pose estimation algorithms based on heuristic local optimization. This paper briefly introduce certifiable optimal algorithms for the visual pose estimation framework to the aerospace research community, including both visual relative pose estimation problem and pose-graph optimization problem. The original optimization problem is reformulated as a quadratically constrained quadratic program (QCQP) problem, whose Lagrangian dual function is a semidefinite programming (SDP) problem which is convex. Simulation results demonstrate the feasibility of certifiable optimal visual pose estimation algorithms based on the zero duality gap for typical application scenarios. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Global optimization

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Evolutionary Interest Representation Network for Click-Through Rate Prediction

Evolutionary Interest Representation Network for Click-Throu...

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2023 IEEE International Conference on Web Services, ICWS 2023

作者： Zhou, Renjie Jin, Zhenming Wan, Jian Zhang, Jilin Guo, Xingyu Liu, Qiang Hangzhou Dianzi University Key Laboratory of Complex Systems Modeling and Simulation of the Ministry of Education School of Computer Science and Technology Hangzhou China Hangzhou Dianzi University Key Laboratory of Complex Systems Modeling and Simulation of the Ministry of Education Itmo Joint Institute Hangzhou China Zhejiang University of Science and Technology School of Information and Electronic Engineering Hangzhou China Zhejiang Police College Dept. of Computer and Information Technology Hangzhou China

ISBN: (纸本)9798350304855

The rapid development of the Internet has revo-lutionized our lives, providing us with an array of convenient services. However, this revolution has also led to the problem of data overload. Personalized recommendation services have been widely recognized as an effective solution to this problem by both the industrial and academic communities. Accurate prediction of click-through rate (CTR) is a critical task in personalized recommendation systems since it can improve the user's shopping experience, ultimately increasing revenue for the platform. To achieve accurate CTR prediction, it is crucial to capture user interests. While several methods for interest modeling exist, challenges related to user interest evolution and user behavior noise need further attention. This paper proposes a novel CTR prediction model named the Evolutionary Interest Representation Network (EIRN), which learns the evolving interest representation of users from their behaviors, profiles, and environmental attributes. In the model, we introduce an advertisement correlation graph decomposition layer and a noise filter layer to enhance and purify the user behavior representation. An interest extraction layer is designed to capture sequential correlations and common characteristics between user behaviors, representing their interests. Additionally, as user interests evolve over time and their importance changes, an attention-based interest evolution layer is designed to track the evolution of user interests. Our proposed method is validated using four public datasets and an industrial dataset, showing its superiority over existing CTR prediction methods. © 2023 IEEE.

关键词： Forecasting

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Generalizing STNU to Model Non-functional Constraints for Business Processes

Generalizing STNU to Model Non-functional Constraints for Bu...

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2022 CCF International Conference on Service science, CCF ICSS 2022

作者： Peng, Jun Zhu, Jingwei Zhang, Liang Fudan University Shanghai Key Laboratory of Data Science School of Computer Science China Shanghai Institute of Intelligent Electronics & Systems Shanghai China

ISBN: (数字)9781665498616

ISBN: (纸本)9781665498616

Due to its ease of use, the notion of Simple Temporal Networks with Uncertainty (STNU) has been successfully used in verifying temporal constraints of business processes. Considering the universality of non-functional attributes, it is significant to generalize STNU in characterizing these non-functional constraints, resulting in a better expressiveness to support process modeling and business applications. In this paper, we leverage STNU to such a level by using abstract algebra on STNU. It results in a general non-functional constraint modeling and verification method in business process management (BPM), from the original temporal constraints to broader qualitative and quantitative ones, which is not yet supported with STNU in the BPM. Based on the proposed method, we demonstrate the capability of verifying dynamic controllability (DC) for these non-functional attributes, such as satisfaction, reputation grade, etc. © 2022 IEEE.

关键词： Algebra

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Solar-powered miniature robot for on-site oil spill treatment under magnetic steering

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science China(Technological sciences) 2024年第7期67卷 2164-2175页

作者： WANG Ben CHEN YunRui WANG Yun JI FengTong LI HongYuan NIU ShiChao HAN ZhiWu ZHANG YaBin GUO ZhiGuang College of Chemistry and Environmental Engineering Shenzhen UniversityShenzhen 518060China State Key Laboratory of Featured Metal Materials and Life-cycle Safety for Composite Structures Ministry of Education Key Laboratory of New Processing Technology for Nonferrous Metals and Materialsand School of ResourcesEnvironment and MaterialsGuangxi UniversityNanning 530004China Key Laboratory for Bionic Engineering Ministry of Education Jilin UniversityChangchun 130022China Hubei Collaborative Innovation Centre for Advanced Organic Chemical Materials Ministry of Education Key Laboratory for the Green Preparation and Application of Functional MaterialsHubei UniversityWuhan 430062China Wellcome Trust/Cancer Research UK Gurdon Institute University of CambridgeCambridge CB21QNUK Department of Physiology Development and NeuroscienceUniversity of CambridgeCambridge CB21QNUK State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering ScienceBeijing Innovation Center for Engineering Science and Advanced TechnologyCollege of EngineeringPeking UniversityBeijing 100871China

Walking on the water surface is an effective method for miniature robots to transport payloads with dramatically decreased interfacial drag. Current aquatic robots reported are generally actuated by a beam of focused light that can trigger asymmetrical deformation, enabling the directional movement through horizontal momentum transfer of photoinduced actuation force to the water. However, the operations are heavily dependent on manual manipulation of the focused light, making the long-term actuation and application of the aquatic robots in vast scenarios challenging. Herein, we developed a kind of water striderinspired robot that can autonomously manage the motion on the water surface under solar irradiation, with their direction steerable by a magnetic field. The motion of this bioinspired robot on the water surface was achieved by the use of a solar cell panel as a driving module to enable propulsive motion based on the conversion of light-electric-mechanical energies. The superhydrophobic design of its leg surfaces enables the aquatic robots with weight-bearing and drag-reducing abilities. With the assistance of magnetic navigation, the bioinspired robot can continuously and controllably locomote to the oily spill floating on the water body and collect them with high efficiency. For further demonstration, the treatment of oil spills in a campus pool with high efficiency has also been achieved. This on-site oil-spill treating strategy, taking advantage of a home-made bioinspired robot actuated by natural sunlight under magnetic steering, shows great potential applications in water-body remediation.

关键词： miniature robot superhydrophobic water strider interfacial friction magnetic actuation

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New Sufficient Conditions on Global Exponential Stability of Delayed Inertial Neural Networks Based on a Direct Parameterized Method 7th

New Sufficient Conditions on Global Exponential Stability o...

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7th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2023

作者： Chang, Shuang Yang, Xiaona Zhang, Xian Wang, Xin School of Mathematical Science Heilongjiang University Harbin150080 China Heilongjiang Provincial Key Laboratory of the Theory and Computation of Complex Systems Heilongjiang University Harbin150080 China School of Electronic Engineering Heilongjiang University Harbin150080 China

ISBN: (纸本)9789819733279

In order to analyse the global exponential stability (GES) of inertial neural networks (INNs) with multiple time-varying transmission delays, a direct parameterized method in this article is proposed. First, the solution of the considered delayed INNs can be parameterized. Thereby, sufficient conditions on GES of the delayed INNs will be established. Then, a numerical example is given to confirm the feasibility and non-conservativeness of the stability criterions. There are two advantages for the direct parameterized method given in this work: (i) to avoid constructing the Lyapunov–Krasovskii functional (LKF), the GES is defined directly by using the inequality technique;(ii) the stability criterion contains are obtained by the theoretical results solve rapidly. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Stability criteria

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MD-TransUNet: TransUNet with Multi-attention and Dilated Convolution for Brain Stroke Lesion Segmentation 19th

MD-TransUNet: TransUNet with Multi-attention and Dilated C...

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19th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2023

作者： Xu, Jie Wan, Jian Zhang, Xin School of Computer Science and Technology Hangzhou Dianzi University Zhejiang310018 China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Ministry of Education Beijing China School of Information and Electronic Engineering Zhejiang University of Science and Technology Zhejiang China Key Laboratory of Marine Ecosystem Dynamics Second Institute of Oceanography Ministry of Natural Resources Hangzhou China

ISBN: (纸本)9783031545276

The accurate segmentation of stroke lesion regions holds immense significance in shaping treatment strategies and rehabilitation protocols. Due to the large difference in the volume of stroke lesion areas and the great similarity between lesion areas and normal tissues, most of the existing methods for lesion segmentation cannot deal with these problems well. This paper proposes a novel network named MD-TransUNet for the segmentation of stroke lesions, whose framework is based on the UNet architecture. To fully obtain deep image features, it uses ResNet50 for downsampling. MD (multi-dilated) module is employed as the skip connection to gain more receptive fields. Different receptive fields can adapt to varying volumes of lesion areas. Then, a feature extraction module with multi-level attention mechanism is designed using ConvLSTM, non-local spatial attention, and channel attention modules to suppress useless information expression in skip connections and upsampling processes while focusing more on effective spatial and channel information in features. The experiments show that our proposed network gets superior performance than benchmark methods and indicates the generalization and effectiveness of the proposed model. © ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Convolution

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DriveRP: RAG and Prompt Engineering Embodied Parallel Driving in Cyber-Physical-Social Spaces 4

DriveRP: RAG and Prompt Engineering Embodied Parallel Drivin...

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4th IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2024

作者： Huang, Jun Ma, Hao Zhang, Tengchao Lin, Fei Ma, Siji Wang, Xiao Wang, Fei-Yue Macau University of Science and Technology Faculty of Innovation Engineering China Anhui University School of Artificial Intelligence Hefei China Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Institute of Automation Beijing China

ISBN: (纸本)9798350349252

In recent years, numerous technological advancements in Artificial Generative Intelligences (AGIs) have demonstrated significant potential to transform the intelligence acquisition mechanisms in connected autonomous vehicles (CAVs). Integrating technologies like ChatGPT into CAVs can enhance human-machine interactions. However, the emergence of such new traffic entities may introduce unforeseen hallucinations and complex risks that surpass our current understanding. To address these challenges, Retrieval-Augmented Generation (RAG) and prompt engineering technologies are being explored to enhance the reliability and safety of autonomous driving systems. RAG retrieves relevant contextual information, such as driving experiences and real-time road network status, from external databases to ensure that foundation models have access to accurate and timely data for informed decision-making. Prompt engineering optimizes the performance of large language models in autonomous driving systems by designing and refining prompts that guide the models' responses, thereby improving their relevance and accuracy in various driving scenarios. Together, these technologies enhance the robustness and trustworthiness of autonomous driving systems. This paper proposes DriveRP, a framework that integrates RAG and prompt engineering within the Descriptive-Predictive-Prescriptive Intelligence framework of Parallel Driving theory. DriveRP aims to enhance the safety and interpretability of autonomous vehicle trajectory planning, decision-making, and motion control, ultimately achieving the "6S"goals. Grounded in Digital Twins and Metaverse-embodied parallel driving theory, DriveRP provides the infrastructure and foundational intelligence for parallel driving with Multi-modal Large Lange Models(MLLMs). Additionally, the paper discusses future trends and potential research directions, focusing on the "6S"goals of parallel driving: Smart, Safe, Secure, Sensitive, Sustainable, and Serviceable. © 2

关键词： Intelligent systems

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Generalized-Extended-State-Observer and Equivalent-Input-Disturbance Methods for Active Disturbance Rejection: Deep Observation and Comparison

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 957-968页

作者： Jinhua She Kou Miyamoto Qing-Long Han Min Wu Hiroshi Hashimoto Qing-Guo Wang School of Engineering Tokyo University of TechnologyHachiojiTokyo 192-0982Japan K.Miyamoto is with the Institute of Technology Shimizu CorporationKotoTokyo 135-0044Japan School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourneVIC 3122Australia School of Automation China University of GeosciencesWuhan 430074 Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China School of Industrial Technology Advanced Institute of Industrial TechnologyTokyo 140-0011Japan Institute of Artificial Intelligence and Future Networks Beijing Normal UniversityZhuhai 519087 Guangdong Key Lab of AI and Multi-Modal Data Processing Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science BNUHKBU United International College Zhuhai 519087China

Active disturbance-rejection methods are effective in estimating and rejecting disturbances in both transient and steady-state *** paper presents a deep observation on and a comparison between two of those methods:the generalized extended-state observer(GESO)and the equivalent input disturbance(EID)from assumptions,system configurations,stability conditions,system design,disturbance-rejection performance,and extensibility.A time-domain index is introduced to assess the disturbance-rejection performance.A detailed observation of disturbance-suppression mechanisms reveals the superiority of the EID approach over the GESO method.A comparison between these two methods shows that assumptions on disturbances are more practical and the adjustment of disturbance-rejection performance is easier for the EID approach than for the GESO method.

关键词： Active disturbance-rejection control(ADRC) disturbance observer(DOB) equivalent input disturbance(EID) extendedstate observer(ESO) generalized extended-state observer(GESO)

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Two-Stage Point Cloud Super Resolution with Local Interpolation and Readjustment via Outer-Product Neural Network

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Journal of systems science & complexity 2021年第1期34卷 68-82页

作者： WANG Guangyu XU Gang WU Qing WU Xundong School of Computer Science and Technology Hangzhou Dianzi UniversityHangzhou 310018China Key Laboratory of Complex Systems Modeling and Simulation Ministry of EducationHangzhou 310018China

This paper proposes a two-stage point cloud super resolution framework that combines local interpolation and deep neural network based readjustment. For the first stage, the authors apply a local interpolation method to increase the density and uniformity of the target point cloud. For the second stage, the authors employ an outer-product neural network to readjust the position of points that are inserted at the first stage. Comparison examples are given to demonstrate that the proposed framework achieves a better accuracy than existing state-of-art approaches, such as PU-Net, Point Net and DGCNN(Source code is available at https://***/qwerty1319/PC-SR).

关键词： Neural network outer-product network point cloud super resolution

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Optimal Observation Geometry Analysis for Multi-sensor System in 3D Case

Optimal Observation Geometry Analysis for Multi-sensor Syste...

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International Conference on Guidance, Navigation and Control, ICGNC 2020

作者： Qian, Jiachen Duan, Peihu Duan, Zhisheng State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Peking University Beijing100871 China

ISBN: (纸本)9789811581540

This paper mainly focuses on the 3D optimal deployment problem for multiple vehicles using range-only sensors. The relative sensor-target geometry can have a great effect on the performance of target localization, and the Fisher information matrix (FIM, the inverse of Cramer–Rao lower bound) is usually used to evaluate the quality of observation. The determinant of Fisher information matrix (FIM) for multiple 3D range-only sensors is derived based on the relative azimuth angles and elevation angles between target and sensors, which is different from the previous literature. Next, a sufficient condition for optimal deployment geometry of multiple homogeneous range-only sensors to maximize the det(FIM) is derived. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Fisher information matrix

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