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IEEE Transactions on Systems, Man, and Cybernetics: Systems
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Year: 2024 | Volume: 54 | Issue: 11
IEEE Transactions on Systems, Man, and Cybernetics publication information
Publication Year: 2024,Page(s):C2 - C2
IEEE Transactions on Systems, Man, and Cybernetics publication information
Year: 2024 | Volume: 54 | Issue: 11
Guest Editorial Enabling Technologies and Systems for Industry 5.0: From Foundation Models to Foundation Intelligence
Publication Year: 2024,Page(s):6496 - 6499
TIDE: Test-Time Few-Shot Object Detection
Weikai Li;Hongfeng Wei;Yanlai Wu;Jie Yang;Yudi Ruan;Yuan Li;Ying Tang
Publication Year: 2024,Page(s):6500 - 6509
Cited by: Papers (4)
Few-shot object detection (FSOD) aims to extract semantic knowledge from limited object instances of novel categories within a target domain. Recent advances in FSOD focus on fine-tuning the base model based on a few objects via meta-learning or data augmentation. Despite their success, the majority of them are grounded with parametric readjustment to generalize on novel objects, which face consid...Show More
TIDE: Test-Time Few-Shot Object Detection
Weikai Li;Hongfeng Wei;Yanlai Wu;Jie Yang;Yudi Ruan;Yuan Li;Ying Tang
Year: 2024 | Volume: 54 | Issue: 11
Transmission Line Component Defect Detection Based on UAV Patrol Images: A Self-Supervised HC-ViT Method
Ke Zhang;Ruiheng Zhou;Jiacun Wang;Yangjie Xiao;Xiwang Guo;Chaojun Shi
Publication Year: 2024,Page(s):6510 - 6521
The unmanned aerial vehicle (UAV) patrol inspection has become an efficient method to ensure the operation condition of transmission lines. The detection of key components with defects in transmission lines is a critical task in maintaining a power system’s stability. However, the complex inspection environment and the imbalance between the number of normal component samples and that of defect sam...Show More
Generative AI Empowering Parallel Manufacturing: Building a “6S” Collaborative Production Ecology for Manufacturing 5.0
Jing Yang;Yutong Wang;Xingxia Wang;Xiaoxing Wang;Xiao Wang;Fei-Yue Wang
Publication Year: 2024,Page(s):6522 - 6536
Cited by: Papers (8)
Since Manufacturing 4.0 faces various challenges, including the risks of data leakage and privacy violation, the struggle to meet the growing demand for personalization, and the limitations in harnessing human creativity, it has become crucial to embark on a transformation toward Manufacturing 5.0. To this end, we propose a DeFACT framework for parallel manufacturing and Manufacturing 5.0, which f...Show More
Enhanced Scene Understanding and Situation Awareness for Autonomous Vehicles Based on Semantic Segmentation
Yiyue Zhao;Liang Wang;Xinyu Yun;Chen Chai;Zhiyu Liu;Wenxuan Fan;Xiao Luo;Yang Liu;Xiaobo Qu
Publication Year: 2024,Page(s):6537 - 6549
Accurate visual perception and comprehensive scene understanding are critical for the safety and reliability of autonomous vehicles (AVs). Nevertheless, the efficacy of visual perception systems can be impaired by the intricacy of road scenes, and the existing scene understanding approach may be insufficient. Consequently, this study proposes an enhanced scene understanding model to achieve precis...Show More
SQIX: QMIX Algorithm Activated by General Softmax Operator for Cooperative Multiagent Reinforcement Learning
Publication Year: 2024,Page(s):6550 - 6560
Cited by: Papers (2)
Multiagent cooperative systems can be used to conceptualize many real-world problems. Reinforcement learning is a particularly effective tool. The issue of bias in Q-function value estimation in single-agent reinforcement learning has garnered a lot of interest and substantial study. Indeed, this challenge endures in multiagent reinforcement learning, primarily owing to the inclusion of maximizati...Show More
Multimodal Perception and Decision-Making Systems for Complex Roads Based on Foundation Models
Lili Fan;Yutong Wang;Hui Zhang;Changxian Zeng;Yunjie Li;Chao Gou;Hui Yu
Publication Year: 2024,Page(s):6561 - 6569
Since the inception of Industry 5.0 in 2021, a growing number of researchers have begun to pay their attention to the revolutionary shift it brings. The principles of Industry 5.0, including human-centric, sustainability, and emphasis on ecological and social values, will become the new paradigm for future industrial development. In this transformative landscape, artificial intelligence (AI) plays...Show More
Toward Foundation Models for Inclusive Object Detection: Geometry- and Category-Aware Feature Extraction Across Road User Categories
Publication Year: 2024,Page(s):6570 - 6580
Cited by: Papers (1)
The safety of different categories of road users comprising motorized vehicles and vulnerable road users (VRUs) such as pedestrians and cyclists is one of the priorities of automated driving and smart infrastructure services. Three-dimensional (3-D) LiDAR-based object detection has been a promising approach to perceiving road users. Despite accurate 3-D geometry information, the point cloud from L...Show More
LLMScenario: Large Language Model Driven Scenario Generation
Publication Year: 2024,Page(s):6581 - 6594
Cited by: Papers (6)
Scenario engineering plays a vital role in various Industry 5.0 applications. In the field of autonomous driving systems, driving scenario data are important for the training and testing of critical modules. However, the corner scenario cases are usually rare and necessary to be extended. Existing methods cannot handle the interpretation and reasoning of the generation process well, which reduces ...Show More
Human-Guided Deep Reinforcement Learning for Optimal Decision Making of Autonomous Vehicles
Publication Year: 2024,Page(s):6595 - 6609
Cited by: Papers (5)
Although deep reinforcement learning (DRL) methods are promising for making behavioral decisions in autonomous vehicles (AVs), their low training efficiency and difficulty to adapt to untrained cases hinder their applications. Introducing a human role in the DRL paradigm could improve training efficiency by using human prior knowledge and overcome untrained cases in deployment by online human take...Show More
Monte Carlo-Based Restoration of Images Degraded by Atmospheric Turbulence
Publication Year: 2024,Page(s):6610 - 6620
Atmospheric turbulence can often introduce phase errors into a propagating light field, thus resulting in anisoplanatic and temporally varying blur and distortion of images. Restoring such images degraded by atmospheric turbulence is extremely ill-posed, due to multiple plausible solutions for a given input image. Most methods offer a deterministic estimation of clean images and require high-compu...Show More
Heterogeneous Window Transformer for Image Denoising
Chunwei Tian;Menghua Zheng;Chia-Wen Lin;Zhiwu Li;David Zhang
Publication Year: 2024,Page(s):6621 - 6632
Cited by: Papers (1)
Deep networks can usually depend on extracting more structural information to improve denoising results. However, they may ignore correlation between pixels from an image to pursue better-denoising performance. Window Transformer can use long- and short-distance modeling to interact pixels to address mentioned problem. To make a tradeoff between distance modeling and denoising time, we propose a h...Show More
Blockchain Intelligence: Intelligent Blockchains for Web 3.0 and Beyond
Publication Year: 2024,Page(s):6633 - 6642
Cited by: Papers (14)
As the next-generation Internet characterized by readability, writability, and ownability, Web 3.0 necessitates the fusion of blockchain and artificial intelligence (AI) technologies to realize its vision of decentralization, user autonomy, and intelligent openness. To this end, this article proposes the integration of “AI for blockchain” and “blockchain for AI” to form a bidirectional enhancement...Show More
Event-Triggered Heading Control of an Energy-Efficient Underwater Gliding Robot
Anyan Jing;Jian Gao;Boxu Min;Jiarun Wang;Yimin Chen;Guang Pan
Publication Year: 2024,Page(s):6643 - 6656
Cited by: Papers (2)
An energy-efficient event-triggered heading control system (ETHCS) is proposed for an underwater gliding robot. The robot steers by adjusting the position of an internal axially moving mass, rather than with the actuators commonly used in traditional underwater vehicles. Based on the dynamic model, an energy-efficient ETHCS framework, which includes three linear velocity observers and an event-tri...Show More
A Fully Distributed Robust MPC Approach for Frequency and Voltage Regulation in Smart Grids With Active and Reactive Power Constraints
Publication Year: 2024,Page(s):6657 - 6669
Cited by: Papers (1)
Shortly, power distribution grids will incorporate large amounts of distributed energy resources and flexible loads, allowing the operation of a portion of the network in islanded mode to increase the reliability and resilience of the whole power system. A fully distributed robust model predictive control (MPC) strategy for voltage and frequency regulation in interconnected distribution grids is s...Show More
A Cooperative Multistep Mutation Strategy for Multiobjective Optimization Problems With Deceptive Constraints
Kangjia Qiao;Kunjie Yu;Caitong Yue;Boyang Qu;Mengnan Liu;Jing Liang
Publication Year: 2024,Page(s):6670 - 6682
Cited by: Papers (1)
Constrained multiobjective optimization problems with deceptive constraints (DCMOPs) are a kind of complex optimization problems and have received some attention. For DCMOPs, the closer a solution is to the feasible region, the larger its constraint value. Moreover, multiple local infeasible regions will have different minimal constraint values according to their distances to feasible regions. The...Show More
Dynamic Event-Triggered Fuzzy Adaptive Resilient Consensus Control for Nonlinear MASs Under DoS Attacks
Publication Year: 2024,Page(s):6683 - 6693
In this article, the adaptive fuzzy dynamic event-triggered output feedback resilient consensus control issue is investigated for nonlinear multiagent systems (MASs) subject to denial-of-service (DoS) attacks. Fuzzy logic systems (FLSs) are employed to model uncertain agents, and a state observer is constructed to estimate unmeasurable states. An event-triggered distributed resilient observer is d...Show More
Hierarchical ADP-ISMC Formation Control of Fixed-Wing UAVs in Local Frames Under Bounded Disturbances
Publication Year: 2024,Page(s):6694 - 6707
In this article, the problem of the fixed-wing UAV formation control in local frames is investigated, and a formation controller based on the distance constraints is designed. Without using the global position information, this article considers the GPS-denied environment, and the control of UAVs only depends on the relative range and relative angle information defined in local frames. Meanwhile, ...Show More
Enforcing Data-Aware Business Processes Using Execution Path-Oriented Strategies
Qi Mo;Jianeng Wang;Yi Jiang;Zhongwen Xie;Wei Wang;Cong Liu;Fei Dai
Publication Year: 2024,Page(s):6708 - 6722
Since the data-aware business process usually covers the control flow and data flow, and both of them have a direct impact on its execution, it is challenging to ensure its correctness. In this article, we propose a novel correctness enforcement approach for the data-aware business the processes. Given a data-aware business process, this approach first relies on the notion of the execution paths t...Show More
Approximate Optimized Backstepping Control of Uncertain Fractional-Order Nonlinear Systems Based on Reinforcement Learning
Publication Year: 2024,Page(s):6723 - 6732
In this article, a feasible reinforcement learning (RL) scheme is proposed for partially unknown fractional-order nonlinear systems (FONSs). First, the fractional Hamilton-Jacobi–Bellman (HJB) equation containing the dynamics of FONSs is proposed by constructing an auxiliary system and equivalent transformation. Then, the optimal solution of FONSs optimal control under a performance constraint is ...Show More
Finite-Time Fuzzy Preassigned-Performance Control for Nonlinear Systems Subject to Asymmetric State-Constraints Based on Command Filter
Publication Year: 2024,Page(s):6733 - 6742
Cited by: Papers (1)
This article presents a novel command-filter-based finite-time fuzzy preassigned performance adaptive control approach for nonlinear systems with exogenous disturbances and asymmetric time-varying constraints. Combining the asymmetric barrier Lyapunov function (ABLF) with preassigned performance control (PPC), it is ensured that the state $x_{1}$ satisfies the required asymmetric time-varying st...Show More
Approximation-Free Robust Tracking Control of Unknown Redundant Manipulators With Prescribed Performance and Input Constraints
Publication Year: 2024,Page(s):6743 - 6755
Cited by: Papers (1)
This article proposes a novel neural control architecture that employs input-output information to compensate for the lack of knowledge about the robot model to achieve prescribed tracking performance in the presence of joint constraints. To this end, an observer-controller zeroing neural network framework is formulated that combines online estimation of the unknown model’s Jacobian with a traject...Show More
Safety Flocking of Networked Lagrangian Systems With Event-Triggered Communication
Publication Year: 2024,Page(s):6756 - 6764
This article focuses on the safety flocking control problem of networked Lagrangian systems under event-triggered communication. To avoid collision and preserve connectivity, the concept of safety domain and safety vector is presented. Using these definitions, a novel potential function is designed to guarantee the interagent distance to be limited in an exact range during the flocking process. In...Show More
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Editor-in-Chief
Professor
University of Massachusetts Amherst, College of Information and Computer Sciences; University of Memphis
Amherst
USA
trans.smcsystems.eic@gmail.comContact Information
Editor-in-Chief
Professor
University of Massachusetts Amherst, College of Information and Computer Sciences; University of Memphis
Amherst
USA
trans.smcsystems.eic@gmail.comIEEE Account
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