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A surrogate-assisted differential evolution algorithm with a dual-space-driven selection strategy for expensive optimization problems Complex Intell. Syst. (IF 5.0) Pub Date : 2025-04-02
Hanqing Liu, Zhigang Ren, Chenlong He, Wenhao DuSurrogate-assisted evolutionary algorithms (SAEAs) have shown great potential to solve computationally expensive optimization problems (EOPs). Their two key components, i.e., the optimizer and the surrogate model, both need to select solutions to promote further evolution and to update the model, respectively. However, the corresponding selection strategies are designed independently and mainly consider
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Reducing hallucinations of large language models via hierarchical semantic piece Complex Intell. Syst. (IF 5.0) Pub Date : 2025-04-02
Yanyi Liu, Qingwen Yang, Jiawei Tang, Tiezheng Guo, Chen Wang, Pan Li, Sai Xu, Xianlin Gao, Zhi Li, Jun Liu, Yingyou WenWith the widespread application of large language models (LLMs) in natural language processing (NLP), hallucinations have become a significant impediment to their effective use of LLMs in industry applications. To address this challenge, we integrate existing hallucination detection and mitigation methods into a unified hallucination detection and mitigation framework. The framework consists of four
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Cooperative path planning optimization for ship-drone delivery in maritime supply operations Complex Intell. Syst. (IF 5.0) Pub Date : 2025-04-02
Xiang Li, Hongguang ZhangDrone-assisted ship supply has recently garnered widespread attention for its faster, cheaper, and greener advantages, reshaping shore-to-vessel deliveries and expected to become fundamental to future maritime logistics. Facing challenges like time-dependent locations and coordination, we introduce a novel path planning problem for supply ship-drone delivery, in which drones launch from the supply
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Attack Detection for Multisensor Cyber–Physical Systems With Unknown-But-Bounded Noises: A Zonotopic Approach IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-04-01
Liuliu Zhao, Haojun Wang, Kun Liu, Liying Zhao, Yuanqing Xia -
Deep Learning for Ocean Forecasting: A Comprehensive Review of Methods, Applications, and Datasets IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-04-01
Rixu Hao, Yuxin Zhao, Shaoqing Zhang, Xiong Deng -
Predefined-Time Adaptive Neural Control for Nonlinear Systems With Unknown Interconnections IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-04-01
Honggui Han, Weiyu Ji, Zheng Liu, Haoyuan Sun, Junfei Qiao -
A Row-Stochastic Event-Based Quantized Algorithm for Distributed Optimization With Linear Convergence IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-04-01
Mingqi Xing, Dazhong Ma, Huaguang Zhang, Jing Zhao, Pak Kin Wong -
Effective Fault Diagnosis for a Quadrotor Helicopter: A Lightweight Transformer With Selective Patches and Channels Modules Method IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-04-01
Li Guo, Yiran Ren, Runze Li, Bin Jiang -
Practical Fixed-Time Active Surge Control of Aero-Engines IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-04-01
Fu-Xiang Quan, Xu Fang, Zhen Wu, Xi-Ming Sun -
Predefined-Time Consensus of Multiagent System: Nonchattering Scheme IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-31
Jie Wu, Jie Chen, Yongzheng Sun, Xiaoyan Sun, Xiaoli Luan, Junjie Fu, Guanghui Wen -
LMCBert: An Automatic Academic Paper Rating Model Based on Large Language Models and Contrastive Learning IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-31
Chuanbin Liu, Xiaowu Zhang, Hongfei Zhao, Zhijie Liu, Xi Xi, Lean Yu -
Force Observer-Based Motion Adaptation and Adaptive Neural Control for Robots in Contact With Unknown Environments IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-29
Guangzhu Peng, Tao Li, Yuting Guo, Chengguo Liu, Chenguang Yang, C. L. Philip Chen -
Knowledge graph-based entity alignment with unified representation for auditing Complex Intell. Syst. (IF 5.0) Pub Date : 2025-03-28
Youhua Zhou, Xueming Yan, Han Huang, Zhifeng Hao, Haofeng Zhu, Fangqing LiuAuditing is facilitated by audit knowledge graphs, while the biggest challenge in constructing an audit knowledge graph is entity alignment. Entity alignment involves linking entity pairs with the same real-world identity and aims to integrate heterogeneous knowledge across different knowledge graphs. However, most existing works do not effectively combine both attribute and relation representations
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A Sliding Mode Control Method With Variable Convergence Rate for Nonlinear Impulsive Stochastic Systems IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-28
Penghe He, Huasheng Zhang, Shun-Feng Su -
Adaptive Prescribed-Time Event-Triggered Control of Nonlinear Networked Systems Under Dynamic Quantization IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-28
Wenhui Liu, Shengyuan Xu, Qian Ma -
Model-Free Algorithms for Cooperative Output Regulation of Discrete-Time Multiagent Systems via Q-Learning Method IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-28
Huaguang Zhang, Tianbiao Wang, Dazhong Ma, Lulu Zhang -
AdamGraph: Adaptive Attention-Modulated Graph Network for EEG Emotion Recognition IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-28
C. L. Philip Chen, Bianna Chen, Tong Zhang -
Groupwise Label Enhancement Broad Learning System for Image Classification IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-27
Junwei Jin, Shaokai Chang, Junwei Duan, Yanting Li, Weiping Ding, Zhen Wang, C. L. Philip Chen, Peng Li -
Privacy for Switched Systems Under MPC: A Privacy-Preserved Rolling Optimization Strategy IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-27
Yiwen Qi, Shitong Guo, Choon Ki Ahn, Yiwen Tang, Jie Huang -
Balancing State Exploration and Skill Diversity in Unsupervised Skill Discovery IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-27
Xin Liu, Yaran Chen, Guixing Chen, Haoran Li, Dongbin Zhao -
Multi-agent reinforcement learning based dynamic self-coordinated topology optimization for wireless mesh networks J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2025-03-27
Qingwei Tang, Wei Sun, Zhi Liu, Qiyue Li, Xiaohui YuanWireless mesh network (WMN) technology enhances wireless communication coverage and increases end-to-end (E2E) delay. The delay in WMNs is influenced by various mesh topologies, which are shaped by transmission power factors. Due to the dynamic nature of WMNs, conventional offline topology optimization methods are ineffective. This paper presents a reinforcement learning (RL)-based dynamic collaborative
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A comparative study of ad-hoc file systems for extreme scale computing Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2025-03-27
Njoud O. Al-Maaitah, Javier Garcia-Blas, Genaro Sanchez-Gallegos, Jesus Carretero, Marc-André Vef, André BrinkmannHigh-performance computing (HPC) systems often suffer from interference caused by multiple applications accessing a shared parallel file system, which can negatively impact compute performance. One solution to this problem is to add new tiers to the HPC storage hierarchy that can absorb I/O bursts and support moving data between tiers based on its hotness. Ad-hoc file systems serve as an intermediate
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A Dynamic Systems Approach to Modeling Human–Machine Rhythm Interaction IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-26
Zhongju Yuan, Wannes Van Ransbeeck, Geraint A. Wiggins, Dick Botteldooren -
Dynamic Hierarchical Convolutional Attention Network for Recognizing Motor Imagery Intention IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-26
Bin Lu, Fuwang Wang, Junxiang Chen, Guilin Wen, Changchun Hua, Rongrong FuThe neural activity patterns of localized brain regions are crucial for recognizing brain intentions. However, existing electroencephalogram (EEG) decoding models, especially those based on deep learning, predominantly focus on global spatial features, neglecting valuable local information, potentially leading to suboptimal performance. Therefore, this study proposed a dynamic hierarchical convolutional
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Multicontact Safety-Critical Planning and Adaptive Neural Control of a Soft Exosuit Over Different Terrains IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-26
Weixiong Yang, Zhijun Li, Guoxin Li, Liangrui XuMany previous works on wearable soft exosuits have primarily focused on assisting human motion, while overlooking safety concerns during movement. This article introduces a novel single-motor, altering bi-directional transfer soft exosuit based on impedance optimization and adaptive neural control, which provides assistance to the lower limbs using Bowden cables. This innovative soft exosuit integrates
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Z-Number Generation Model and Its Application in a Rule-Based Classification System IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-26
Yangxue Li, Juan Antonio Morente-Molinera, Jose Ramón Trillo, Enrique Herrera-ViedmaDue to their unique structure and powerful capability to handle uncertainty and partial reliability of information, Z-numbers have achieved significant success in various fields. Zadeh previously asserted that a Z-number can be regarded as a summary of probability distributions. Researchers have proposed various methods for determining the underlying probability distributions from a given Z-number
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Improved Safe Tracking Error-Constrained Control for Unknown Interconnected Time-Delay Nonlinear Systems With Discontinuous References IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-26
Lingchen Zhu, Liuliu Zhang, Cheng Qian, Changchun HuaIn this article, we address the improved error-constrained control problem for unknown, strongly interconnected time-delay nonlinear systems with input saturation and conflicted output constraints. The further challenge we face is that the presence of discontinuous reference signals poses greater difficulties for control design. To tackle these issues, a mechanism for generating smooth, safe reference
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Dimensioning network slices for power minimization under reliability constraints Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2025-03-26
Wei Huang, Andrea Araldo, Hind Castel-Taleb, Badii JouaberNetwork slicing allows multiplexing virtualized networks, called slices, over a single physical network infrastructure. Research has extensively focused on the placement of virtual functions and the links that compose each network slice. On the other hand, performance greatly depends on how many resources are allocated to virtual nodes and links, after they are placed. This aspect has been mostly neglected
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Towards sustainable smart cities: Workflow scheduling in cloud of health things (CoHT) using deep reinforcement learning and moth flame optimization for edge–cloud systems Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2025-03-26
Mustafa Ibrahim KhaleelIn smart cities, the Cloud of Health Things (CoHT) enhances service delivery and optimizes task scheduling and allocation. As CoHT systems proliferate and offer a range of services with varying Quality of Service (QoS) demands, servers face the challenge of efficiently distributing limited virtual machines across internet-based applications. This can strain performance, particularly for latency-sensitive
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Micromechanical and numerical analysis of shape and packing effects in elastic-plastic particulate composites Comput. Struct. (IF 4.4) Pub Date : 2025-03-26
M. MajewskiThe purpose of this study is to inspect the combined effect of reinforcement shape and packing on the macroscopic behaviour of particulate composites. The introduced micromechanical approach modifies the Morphologically Representative Pattern scheme with the Replacement Mori–Tanaka Model. The statistical volume elements have randomly placed inclusions with a selected shape. Four shapes of inhomogeneities
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A memory-saving algorithm with variable increment size for fractional viscoelastic models of asphalt concrete in finite element analysis Comput. Struct. (IF 4.4) Pub Date : 2025-03-26
Weiwen Quan, Kaiwen Zhao, Xianyong Ma, Chen Yang, Zejiao Dong, Zhuang Xiao, Lingyun YouFinite element analysis of the fractional viscoelastic model of asphalt concrete (AC) is typically performed on small specimens, with algorithms that suffer from high memory consumption and low computational efficiency, limiting their application to large-scale structures. This paper proposes a memory-saving algorithm with variable increment size for fractional viscoelastic models of AC in finite element
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A study of enhanced visual perception of marine biology images based on diffusion-GAN Complex Intell. Syst. (IF 5.0) Pub Date : 2025-03-25
Feifan Yao, Huiying Zhang, Yifei Gong, Qinghua Zhang, Pan XiaoAiming at the influence of factors such as the special optical characteristics of water bodies on the perceptual quality of generated images, this paper proposes the DifSG2-CCL model for reducing the special optical characteristics of water bodies and the DPL-SG2 model for introducing perceptual loss. Combining the ideas of cyclic consistency and style migration, this paper builds the Underwater Cycle
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A parallel large-scale multiobjective evolutionary algorithm based on two-space decomposition Complex Intell. Syst. (IF 5.0) Pub Date : 2025-03-25
Feng Yin, Bin CaoDecomposition is an effective and popular strategy used by evolutionary algorithms to solve multiobjective optimization problems (MOPs). It can reduce the difficulty of directly solving MOPs, increase the diversity of the obtained solutions, and facilitate parallel computing. However, with the increase of the number of decision variables, the performance of multiobjective evolutionary algorithms (MOEAs)
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SPARTA-GEMSTONE: A two-phase approach for efficient node placement in 3D WSNs under [formula omitted]-Coverage and [formula omitted]-Connectivity constraints J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2025-03-25
Quang Truong Vu, The Minh Trinh, Thi Hanh Nguyen, Van Chien Trinh, Thi Thanh Binh Huynh, Xuan Thang Nguyen, Cong Phap HuynhWireless sensor networks (WSNs) face challenges in achieving robust target coverage and connectivity, particularly when varying priorities for targets are modeled with Q-Coverage and Q-Connectivity constraints. However, existing studies often neglect minimizing the number of nodes under these constraints in 3D environments or focus on sensor-to-sensor connections, which are less suitable for target-oriented
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MinCache: A hybrid cache system for efficient chatbots with hierarchical embedding matching and LLM Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2025-03-25
Keihan Haqiq, Majid Vafaei Jahan, Saeede Anbaee Farimani, Seyed Mahmood Fattahi MasoomLarge Language Models (LLMs) have emerged as powerful tools for various natural language processing tasks such as multi-agent chatbots, but their computational complexity and resource requirements pose significant challenges for real-time chatbot applications. Caching strategies can alleviate these challenges by reducing redundant computations and improving response times. In this paper, we propose
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A novel generative adversarial networks based multi-scale reconstruction method for porous rocks Comput. Struct. (IF 4.4) Pub Date : 2025-03-25
Nan Xiao, Yu Peng, Xiaoping ZhouThe traditional reconstruction methods for numerical rock models, such as simulated annealing reconstruction method, have disadvantages, such as unclear details of the generated structure and the need of prior functions. Therefore, this paper attempts to introduce GANs-based techniques to reconstruct numerical porous rock models. The introduction of GANs-based techniques can solve the problem of requiring
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The complete hydrostatic stiffness and geometrically nonlinear beam finite element analysis of floating structures Comput. Struct. (IF 4.4) Pub Date : 2025-03-25
Ikjae Lee, Moohyun KimIn this study, the complete hydrostatic tangent stiffness for geometrically nonlinear beam finite element model is introduced. Based on consistent global hydrostatic restoring stiffness analysis, the complete form of hydrostatic tangent stiffness is developed. In addition, a surface integration parameterization method for shear-deformable beams is discussed with classifications of two special types
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An exploration-enhanced hybrid algorithm based on regularity evolution for multi-objective multi-UAV 3-D path planning Complex Intell. Syst. (IF 5.0) Pub Date : 2025-03-24
Zhenzu Bai, Haiyin Zhou, Juhui Wei, Xuanying Zhou, Yida Ning, Jiongqi WangPath planning poses a complex optimization challenge essential for the safe operation and successful mission execution of unmanned aerial vehicles (UAVs). Developing objectives, constraints, and decision-making processes for three-dimensional path planning involving multiple UAVs presents substantial challenges within the multi-objective optimization community. Traditional modeling approaches primarily
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Research on knowledge tracing based on learner fatigue state Complex Intell. Syst. (IF 5.0) Pub Date : 2025-03-24
Haoyu Wang, Qianxi Wu, Chengke Bao, Weidong Ji, Guohui ZhouKnowledge tracing aims to predict how learners will perform in future exercises on related concepts and to track changes in their knowledge state. Existing models have not fully considered the physical and mental fatigue that occurs in learners during prolonged learning tasks, which leads to reduced problem-solving ability and affects their learning efficiency and performance. This article proposes
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Prescribed-Time Bipartite Synchronization for General Linear Multiagent Systems: An Adaptive Dynamic Output-Feedback Strategy IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-24
Yuan Zhou, Yu Zhao, Guofeng Zhang, Heung-Wing Joseph Lee -
Secure data migration from fair contract signing and efficient data integrity auditing in cloud storage J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2025-03-24
Changsong Yang, Yueling Liu, Yong Ding, Hai LiangWith the rapid development of cloud storage, a growing number of data owners prefer to outsource their large-scale data to the remote cloud data centers, thus effectively avoiding the heavy burden of storing the massive data by themselves in local. Due to the promising market prospect, plenty of companies invest cloud storage and offer data storage services, which equipped with different access speed
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Co-evolutionary algorithm with a region-based diversity enhancement strategy Complex Intell. Syst. (IF 5.0) Pub Date : 2025-03-22
Kangshun Li, RuoLin Ruan, Shumin Xie, Hui WangWhen addressing constrained multi-objective optimization problems, the presence of complex constraints often results in a non-connected feasible region, segmenting the Pareto front into multiple discrete segments. This fragmentation can significantly limit population diversity. To tackle this issue, we have designed two mechanisms aimed at preserving population diversity and have developed a constrained
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The opinion dynamics model for group decision making with probabilistic uncertain linguistic information Complex Intell. Syst. (IF 5.0) Pub Date : 2025-03-22
Jianping Fan, Zhuxuan Jin, Meiqin WuMulti-criteria group decision making (MCGDM) is the important part in decision-making process, which has been used in many industries. Coordinating differing opinions and ultimately reaching group consensus in a group decision-making process has become an important area of research. This paper uses probabilistic uncertain linguistic term sets (PULTSs) to express the uncertainty of evaluation information
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Enhancing implicit sentiment analysis via knowledge enhancement and context information Complex Intell. Syst. (IF 5.0) Pub Date : 2025-03-22
Yanying Mao, Qun Liu, Yu ZhangSentiment analysis (SA) is a vital research direction in natural language processing (NLP). Compared with the widely-concerned explicit sentiment analysis, implicit sentiment analysis (ISA) is more challenging and rarely studied due to the lack of sentiment words. However, existing implicit sentiment analysis methods are hard to identify implicit sentiment without the support of commonsense and contextual
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A reliability centred maintenance-oriented framework for modelling, evaluating, and optimising complex repairable flow networks Complex Intell. Syst. (IF 5.0) Pub Date : 2025-03-22
Nicholas Kaliszewski, Romeo Marian, Javaan ChahlFew would argue that maximising the performance of the many flow networks (FNs) that operate for the benefit of our society and the economy is anything but essential. Through seeking to mitigate the risks posed by different asset failure modes, maintenance is critical to minimising disruptions and maximising resilience. Repairable flow network (RFN) optimisation and reliability centred maintenance
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Secure Consensus for Switched Multiagent Systems Under DoS Attacks: Hybrid Event-Triggered and Impulsive Control Approach IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-22
Xin Wang, Zhuocheng Yin, Yan Lei, Tingwen Huang, Jürgen Kurths -
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Dynamic class-balanced threshold Federated Semi-Supervised Learning by exploring diffusion model and all unlabeled data Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2025-03-22
Zeyuan Wang, Yang Liu, Guirong Liang, Cheng Zhong, Feng YangFederated Semi-Supervised Learning (FSSL) aims to train models based on federated learning using a small amount of labeled data and a large amount of unlabeled data. The limited labeled data and the issue of non-independent and identically distributed (non-IID) data are the major challenges faced by FSSL. Most of the previous methods use traditional fixed thresholds to filter out high-confidence samples
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SLPOD: superclass learning on point cloud object detection Complex Intell. Syst. (IF 5.0) Pub Date : 2025-03-21
Xiaokang Yang, Kai Zhang, Yangyue Feng, Beibei Su, Yiming Cai, Kaibo Zhang, Zhiheng ZhangIn the realm of point cloud object detection, classification tasks emphasize extracting common features to enhance generalization, often at the expense of individual-specific features. This limitation becomes particularly evident when handling intricate datasets like KITTI. Traditional models struggle to adequately capture individual-specific features, resulting in a scattered distribution of samples
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Transformer-based multiple instance learning network with 2D positional encoding for histopathology image classification Complex Intell. Syst. (IF 5.0) Pub Date : 2025-03-21
Bin Yang, Lei Ding, Jianqiang Li, Yong Li, Guangzhi Qu, Jingyi Wang, Qiang Wang, Bo LiuDigital medical imaging, particularly pathology images, is essential for cancer diagnosis but faces challenges in direct model training due to its super-resolution nature. Although weakly supervised learning has reduced the need for manual annotations, many multiple instance learning (MIL) methods struggle to effectively capture crucial spatial relationships in histopathological images. Existing methods
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ERMAV: Efficient and Robust Graph Contrastive Learning via Multiadversarial Views Training IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-21
Wen Li, Wing W. Y. Ng, Hengyou Wang, Jianjun Zhang, Cankun Zhong, Liang Yang -
Security Control of Safety-Critical Systems IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-21
Yi Dong, Yiguang Hong, Jie Chen -
Event-Triggered Almost Output Regulation for Switched T–S Fuzzy Systems IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-21
Shuanghe Yu, Ying Zhao, Jingjie Xu -
A Scalable Test Problem Generator for Sequential Transfer Optimization IEEE Trans. Cybern. (IF 9.4) Pub Date : 2025-03-21
Xiaoming Xue, Cuie Yang, Liang Feng, Kai Zhang, Linqi Song, Kay Chen Tan -
A distributed identity management and cross-domain authentication scheme for the Internet of Things Future Gener. Comput. Syst. (IF 6.2) Pub Date : 2025-03-21
Miaomiao Wang, Ze WangReliable identity management and authentication are prerequisites for secure information communication. Traditional centralized schemes rely on the Certificate Authority (CA), and their cross-domain authentication is complex, posing a risk of centralized data leakage. The advancement of blockchain technology has disrupted the traditional model, leading to the emergence of Self-Sovereign Identity (SSI)
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Kinitos: Dynamic network-aware scheduling and descheduling in Kubernetes clusters with mobile nodes J. Netw. Comput. Appl. (IF 7.7) Pub Date : 2025-03-20
Tsvetan Tsokov, Hristo KostadinovThe current Cloud/Edge/Fog platforms, available in practice, do not support dynamic management of computational and network resources in clusters with moveable and constraint nodes, like in applications such as: connected vehicles, Internet of Things (IoT), spacecraft computing, etc. This leads to increased total response time and low QoS for the long-living applications composed of many inter-dependent