信息工程最新文献

{"title":"Explanation framework for industrial recommendation systems based on the generative adversarial network with embedding constraints","authors":"Binchuan Qi,&nbsp;Wei Gong,&nbsp;Li Li","doi":"10.1007/s43684-025-00092-2","DOIUrl":"10.1007/s43684-025-00092-2","url":null,"abstract":"<div><p>The explainability of recommendation systems refers to the ability to explain the logic that guides the system’s decision to endorse or exclude an item. In industrial-grade recommendation systems, the high complexity of features, the presence of embedding layers, the existence of adversarial samples and the requirements for explanation accuracy and efficiency pose significant challenges to current explanation methods. This paper proposes a novel framework AdvLIME (Adversarial Local Interpretable Model-agnostic Explanation) that leverages Generative Adversarial Networks (GANs) with Embedding Constraints to enhance explainability. This method utilizes adversarial samples as references to explain recommendation decisions, generating these samples in accordance with realistic distributions and ensuring they meet the structural constraints of the embedding module. AdvLIME requires no modifications to the existing model architecture and needs only a single training session for global explanation, making it ideal for industrial applications. This work contributes two significant advancements. First, it develops a model-independent global explanation method via adversarial generation. Second, it introduces a model discrimination method to guarantee that the generated samples adhere to the embedding constraints. We evaluate the AdvLIME framework on the Behavior Sequence Transformer (BST) model using the MovieLens 20 M dataset. The experimental results show that AdvLIME outperforms traditional methods such as LIME and DLIME, reducing the approximation error of real samples by 50% and demonstrating improved stability and accuracy.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-025-00092-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Health security disparities in the Eastern Mediterranean Region: A comparative analysis using an integrated MCDM and clustering approach","authors":"Adel A. Nasser ,&nbsp;Abed Saif Ahmed Alghawli ,&nbsp;S. Saleh ,&nbsp;Amani A.K. Elsayed","doi":"10.1016/j.jobb.2025.01.001","DOIUrl":"10.1016/j.jobb.2025.01.001","url":null,"abstract":"<div><h3>Objectives</h3><div>This study aimed to analyze and compare health security performance (HSP) between Gulf Cooperation Council and non-Gulf Cooperation Council countries within the Eastern Mediterranean Region (EMR) for 2019 and 2021, recognizing the critical role of health security in managing global health threats.</div></div><div><h3>Methods</h3><div>The study utilized data from the Global Health Security Index (GHSI) for 2019 and 2021. Key health security priorities were identified using the entropy objective weighting method. The VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) method was employed to rank countries based on overall performance. K-means clustering was applied to group countries with similar health security profiles. Pearson’s and Spearman’s rank correlation coefficients were used to assess relationships between independent HSP indicators and overall performance scores.</div></div><div><h3>Results</h3><div>A significant shift in health security priorities within the EMR was observed between 2019 and 2021, with prevention gaining prominence. Gulf Cooperation Council countries emphasized detection and reporting, while non-Gulf Cooperation Council countries prioritized health systems and prevention. Gulf Cooperation Council countries, particularly Qatar and Saudi Arabia, consistently demonstrated strong HSP. Conversely, non-Gulf Cooperation Council countries facing conflict and instability, such as Yemen, Somalia, and Syria, exhibited weaker performance. Health system capacity, prevention, detection and reporting, and risk environment showed robust correlations with overall HSP.</div></div><div><h3>Conclusion</h3><div>This study underscores the necessity for tailored, adaptive policies to address HSP disparities across regions, highlighting investment in prevention, detection, and reporting. It stresses international collaboration, improved policy implementation, and ongoing research to enhance global health security systems across diverse contexts.</div></div>","PeriodicalId":52875,"journal":{"name":"Journal of Biosafety and Biosecurity","volume":"7 1","pages":"Pages 38-51"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143519743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SSI-MedRx: A fraud-resilient healthcare system based on blockchain and SSI","authors":"Meriem Guerar ,&nbsp;Mauro Migliardi ,&nbsp;Enrico Russo ,&nbsp;Djamel Khadraoui ,&nbsp;Alessio Merlo","doi":"10.1016/j.bcra.2024.100242","DOIUrl":"10.1016/j.bcra.2024.100242","url":null,"abstract":"<div><div>Today, healthcare fraud poses a significant issue, encompassing everything from falsified billing claims and phantom services to the excessive prescription of opioid medications and medical identity theft. These deceptive activities cause substantial financial losses, erode patient trust, compromise healthcare quality, and threaten patient safety. In this paper, we introduce SSI-MedRx, a healthcare system based on blockchain technology and Self-Sovereign Identity (SSI). It is designed to ensure cross-border interoperability, preserve patient privacy, and prevent challenging healthcare frauds, including medical identity theft, phantom billing, kickbacks, and opioid overprescribing. By design, our system empowers patients by granting them complete control over their personal and health data. This shift toward patient-centric data management can potentially reduce the risk of data breaches, enhance care coordination, and improve overall healthcare outcomes.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 1","pages":"Article 100242"},"PeriodicalIF":6.9,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive control of bilateral teleoperation systems under denial-of-service attacks","authors":"Lanyan Wei,&nbsp;Yuling Li","doi":"10.1007/s43684-025-00093-1","DOIUrl":"10.1007/s43684-025-00093-1","url":null,"abstract":"<div><p>This paper investigates resilient consensus control for teleoperation systems under denial-of-service (DoS) attacks. We design resilient controllers with auxiliary systems based on sampled positions of both master and slave robots, enhancing robustness during DoS attacks. Additionally, we establish stability conditions on DoS attack duration and frequency by applying multivariate small-gain methods to ensure closed-loop stability without the need to solve linear matrix inequalities. Finally, the effectiveness of the controllers is validated through the simulation results, demonstrating that the master-slave synchronization is achieved.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-025-00093-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143489608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient and accurate road crack detection technology based on YOLOv8-ES","authors":"Kaili Zeng,&nbsp;Rui Fan,&nbsp;Xiaoyu Tang","doi":"10.1007/s43684-025-00091-3","DOIUrl":"10.1007/s43684-025-00091-3","url":null,"abstract":"<div><p>Road damage detection is an important aspect of road maintenance. Traditional manual inspections are laborious and imprecise. With the rise of deep learning technology, pavement detection methods employing deep neural networks give an efficient and accurate solution. However, due to background diversity, limited resolution, and fracture similarity, it is tough to detect road cracks with high accuracy. In this study, we offer a unique, efficient and accurate road crack damage detection, namely YOLOv8-ES. We present a novel dynamic convolutional layer(EDCM) that successfully increases the feature extraction capabilities for small fractures. At the same time, we also present a new attention mechanism (SGAM). It can effectively retain crucial information and increase the network feature extraction capacity. The Wise-IoU technique contains a dynamic, non-monotonic focusing mechanism designed to return to the goal-bounding box more precisely, especially for low-quality samples. We validate our method on both RDD2022 and VOC2007 datasets. The experimental results suggest that YOLOv8-ES performs well. This unique approach provides great support for the development of intelligent road maintenance systems and is projected to achieve further advances in future applications.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-025-00091-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143373272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A cooperative jamming decision-making method based on multi-agent reinforcement learning","authors":"Bingchen Cai,&nbsp;Haoran Li,&nbsp;Naimin Zhang,&nbsp;Mingyu Cao,&nbsp;Han Yu","doi":"10.1007/s43684-025-00090-4","DOIUrl":"10.1007/s43684-025-00090-4","url":null,"abstract":"<div><p>Electromagnetic jamming is a critical countermeasure in defense interception scenarios. This paper addresses the complex electromagnetic game involving multiple active jammers and radar systems by proposing a multi-agent reinforcement learning-based cooperative jamming decision-making method (MA-CJD). The proposed approach achieves high-quality and efficient target allocation, jamming mode selection, and power control. Mathematical models for radar systems and active jamming are developed to represent a multi-jammer and multi-radar electromagnetic confrontation scenario. The cooperative jamming decision-making process is then modeled as a Markov game, where the QMix multi-agent reinforcement learning algorithm is innovatively applied to handle inter-jammer cooperation. To tackle the challenges of a parameterized action space, the MP-DQN network structure is adopted, forming the basis of the MA-CJD algorithm. Simulation experiments validate the effectiveness of the proposed MA-CJD algorithm. Results show that MA-CJD significantly reduces the time defense units are detected while minimizing jamming resource consumption. Compared with existing algorithms, MA-CJD achieves better solutions, demonstrating its superiority in cooperative jamming scenarios.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-025-00090-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143184710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced bearing RUL prediction based on dynamic temporal attention and mixed MLP","authors":"Zhongtian Jin,&nbsp;Chong Chen,&nbsp;Aris Syntetos,&nbsp;Ying Liu","doi":"10.1007/s43684-024-00088-4","DOIUrl":"10.1007/s43684-024-00088-4","url":null,"abstract":"<div><p>Bearings are critical components in machinery, and accurately predicting their remaining useful life (RUL) is essential for effective predictive maintenance. Traditional RUL prediction methods often rely on manual feature extraction and expert knowledge, which face specific challenges such as handling non-stationary data and avoiding overfitting due to the inclusion of numerous irrelevant features. This paper presents an approach that leverages Continuous Wavelet Transform (CWT) for feature extraction, a Channel-Temporal Mixed MLP (CT-MLP) layer for capturing intricate dependencies, and a dynamic attention mechanism to adjust its focus based on the temporal importance of features within the time series. The dynamic attention mechanism integrates multi-head attention with innovative enhancements, making it particularly effective for datasets exhibiting non-stationary behaviour. An experimental study using the XJTU-SY rolling bearings dataset and the PRONOSTIA bearing dataset revealed that the proposed deep learning algorithm significantly outperforms other state-of-the-art algorithms in terms of RMSE and MAE, demonstrating its robustness and accuracy.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-024-00088-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142939427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An interaction-fair semi-decentralized trajectory planner for connected and autonomous vehicles","authors":"Zhengqin Liu,&nbsp;Jinlong Lei,&nbsp;Peng Yi,&nbsp;Yiguang Hong","doi":"10.1007/s43684-024-00087-5","DOIUrl":"10.1007/s43684-024-00087-5","url":null,"abstract":"<div><p>Lately, there has been a lot of interest in game-theoretic approaches to the trajectory planning of autonomous vehicles (AVs). But most methods solve the game independently for each AV while lacking coordination mechanisms, and hence result in redundant computation and fail to converge to the same equilibrium, which presents challenges in computational efficiency and safety. Moreover, most studies rely on the strong assumption of knowing the intentions of all other AVs. This paper designs a novel autonomous vehicle trajectory planning approach to resolve the computational efficiency and safety problems in uncoordinated trajectory planning by exploiting vehicle-to-everything (V2X) technology. Firstly, the trajectory planning for connected and autonomous vehicles (CAVs) is formulated as a game with coupled safety constraints. We then define the interaction fairness of the planned trajectories and prove that interaction-fair trajectories correspond to the variational equilibrium (VE) of this game. Subsequently, we propose a semi-decentralized planner for the vehicles to seek VE-based fair trajectories, in which each CAV optimizes its individual trajectory based on neighboring CAVs’ information shared through V2X, and the roadside unit takes the role of updating multipliers for collision avoidance constraints. The approach can significantly improve computational efficiency through parallel computing among CAVs, and enhance the safety of planned trajectories by ensuring equilibrium concordance among CAVs. Finally, we conduct Monte Carlo experiments in multiple situations at an intersection, where the empirical results show the advantages of SVEP, including the fast computation speed, a small communication payload, high scalability, equilibrium concordance, and safety, making it a promising solution for trajectory planning in connected traffic scenarios. To the best of our knowledge, this is the first study to achieve semi-distributed solving of a game with coupled constraints in a CAV trajectory planning problem.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-024-00087-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142912803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Network synchronizability enhancement via adding antagonistic interactions","authors":"Yue Song,&nbsp;Xiaoqin Liu,&nbsp;Dingmei Wang,&nbsp;Pengfei Gao,&nbsp;Mengqi Xue","doi":"10.1007/s43684-024-00086-6","DOIUrl":"10.1007/s43684-024-00086-6","url":null,"abstract":"<div><p>We discover a “less-is-more” effect that adding local antagonistic interactions (negative edge weights) can enhance the overall synchronizability of a dynamical network system. To explain this seemingly counterintuitive phenomenon, a condition is established to identify those edges the weight reduction of which improves the synchronizability index of the underlying network. We further reveal that this condition can be interpreted from the perspective of resistance distance and network community structure. The obtained result is also verified via numerical experiments on a 14-node network and a 118-node network. Our finding brings new thoughts and inspirations to the future directions of optimal network design problems.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-024-00086-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142906061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distributed strategies for pursuit-evasion of high-order integrators","authors":"Panpan Zhou,&nbsp;Yueyue Xu,&nbsp;Bo Wahlberg,&nbsp;Xiaoming Hu","doi":"10.1007/s43684-024-00085-7","DOIUrl":"10.1007/s43684-024-00085-7","url":null,"abstract":"<div><p>This paper presents decentralized solutions for pursuit-evasion problems involving high-order integrators with intracoalition cooperation and intercoalition confrontation. Distinct error variables and hyper-variables are introduced to ensure the control strategies to be independent of the relative velocities, accelerations and higher order information of neighbors. Consequently, our approach only requires agents to exchange position information or to measure the relative positions of the neighbors. The distributed strategies take into consideration the goals of intracoalition cooperation or intercoalition confrontation of the players. Furthermore, after establishing a sufficient and necessary condition for a class of high-order integrators, we present conditions for capture and formation control with exponential convergence for three scenarios: one-pursuer-one-evader, multiple-pursuer-one-evader, and multiple-pursuer-multiple-evader. It is shown that the conditions depend on the structure of the communication graph, the weights in the control law, and the expected formation configuration. Finally, the effectiveness of the proposed algorithm is demonstrated through simulation results.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-024-00085-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142889926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}