信息工程最新文献

{"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":"Blockchain-driven innovation in fashion supply chain contractual party evaluations as an emerging collaboration model","authors":"Minhao Qiao ,&nbsp;Xuanchang Chen ,&nbsp;Yangping Zhou ,&nbsp;P.Y. Mok","doi":"10.1016/j.bcra.2024.100266","DOIUrl":"10.1016/j.bcra.2024.100266","url":null,"abstract":"<div><div>With the advancement of distributed digital technology, the fashion supply chain management system is undergoing unprecedented transformations. Given the expansion and rapid iteration of the fashion industry, traditional supply chain management models struggle to adapt to the volatile market changes. In this context, small and medium-sized enterprises (SMEs), which are integral components of the fashion supply chain, often face significant market pressure, leading to losses and even bankruptcy, which in turn causes delays across the entire supply chain. Thus, there is an urgent need for these businesses to adopt new technologies to reduce risks and achieve profitability. Although there have been attempts to introduce blockchain technology into the fashion supply chain, most of these efforts are still in the preliminary stages, with operations continuing to follow old methods. Therefore, this study aims to introduce an evaluation mechanism into the fashion supply chain, encouraging a collective maintenance of interests among SMEs. The main contribution of this paper includes the introduction of a set of innovative management evaluation mechanisms and collaboration models for SMEs in the fashion supply chain, with the goal of securing their rights to autonomous pricing and promoting healthy competition in the forthcoming Web 3.0 era. We implemented the enterprise-level consortium blockchain framework, Hyperledger Fabric. Through testing, it has been proven that the platform is effective and usable in ensuring data integrity and source transparency.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 2","pages":"Article 100266"},"PeriodicalIF":6.9,"publicationDate":"2025-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","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":"Empowering autonomous IoT devices in blockchain through gasless transactions","authors":"Yash Madhwal ,&nbsp;Yury Yanovich ,&nbsp;Aleksandra Korotkevich ,&nbsp;Daria Parshina ,&nbsp;Nshteh Seropian ,&nbsp;Stepan Gavrilov ,&nbsp;Alex Nikolaev ,&nbsp;S. Balachander ,&nbsp;A. Murugan","doi":"10.1016/j.bcra.2024.100257","DOIUrl":"10.1016/j.bcra.2024.100257","url":null,"abstract":"<div><div>The article introduces a proof-of-concept (PoC) that demonstrates the management of Internet of Things (IoT) devices' infrastructure via smart contracts, facilitating their interaction with the blockchain through gasless transactions. The focus is empowering IoT devices to autonomously sign transactions using their verified private keys, eliminating the necessity for external wallets and enabling blockchain interaction using Biconomy without incurring gas fees. In this PoC, managers can validate IoT devices, permitting them to transmit transactions securely without being able to manipulate measurements or risking losing crypto assets in case of hardware malfunctions. This innovative method ensures that devices with minimal funds can access sensor data and communicate with a smart contract on the blockchain to update information utilizing account abstraction. Detailed workflow and simulation results are provided to showcase the practicality and advantages of this approach in scenarios demanding seamless automated blockchain engagement through IoT devices. The PoC code is openly accessible on GitHub, enhancing the transparency and accessibility of our research outcomes.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 2","pages":"Article 100257"},"PeriodicalIF":6.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"πFL: Private, atomic, incentive mechanism for federated learning based on blockchain","authors":"Kejia Chen ,&nbsp;Jiawen Zhang ,&nbsp;Xuanming Liu ,&nbsp;Zunlei Feng ,&nbsp;Xiaohu Yang","doi":"10.1016/j.bcra.2024.100271","DOIUrl":"10.1016/j.bcra.2024.100271","url":null,"abstract":"<div><div>Federated learning (FL) is predicated on the provision of high-quality data by multiple clients, which is then used to train global models. A plethora of incentive mechanism studies have been conducted with the objective of promoting the provision of high-quality data by clients. These studies have focused on the distribution of benefits to clients. However, the incentives of federated learning are transactional in nature, and the issue of the atomicity of transactions has not been addressed. Furthermore, the data quality of individual clients participating in training varies, and they may participate negatively in training out of privacy leakage concerns.</div><div>Consequently, we propose an inaugural atomistic incentive scheme with privacy preservation in the FL setting: <em>π</em>FL (<strong>p</strong>rivacy, <strong>a</strong>tomic, <strong>i</strong>ncentive). This scheme establishes a more dependable training environment based on Shapley valuation, secure multi-party computation, and smart contracts. Consequently, it ensures that each client's contribution can be accurately measured and appropriately rewarded, improves the accuracy and efficiency of model training, and enhances the sustainability and reliability of the FL system. The efficacy of this mechanism has been demonstrated through comprehensive experimental analysis. It is evident that this mechanism not only protects the privacy of trainers and provides atomic training rewards but also improves the model performance of FL, with an accuracy improvement of at least 8%.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 2","pages":"Article 100271"},"PeriodicalIF":6.9,"publicationDate":"2025-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144146941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A hybrid Bi-LSTM model for data-driven maintenance planning.","authors":"Alexandros Noussis, Ryan O'Neil, Ahmed Saif, Abdelhakim Khatab, Claver Diallo","doi":"10.1007/s43684-025-00099-9","DOIUrl":"10.1007/s43684-025-00099-9","url":null,"abstract":"<p><p>Modern industries dependent on reliable asset operation under constrained resources employ intelligent maintenance methods to maximize efficiency. However, classical maintenance methods rely on assumed lifetime distributions and suffer from estimation errors and computational complexity. The advent of Industry 4.0 has increased the use of sensors for monitoring systems, while deep learning (DL) models have allowed for accurate system health predictions, enabling data-driven maintenance planning. Most intelligent maintenance literature has used DL models solely for remaining useful life (RUL) point predictions, and a substantial gap exists in further using predictions to inform maintenance plan optimization. The few existing studies that have attempted to bridge this gap suffer from having used simple system configurations and non-scalable models. Hence, this paper develops a hybrid DL model using Monte Carlo dropout to generate RUL predictions which are used to construct empirical system reliability functions used for the optimization of the selective maintenance problem (SMP). The proposed framework is used to plan maintenance for a mission-oriented series k-out-of-n:G system. Numerical experiments compare the framework's performance against prior SMP methods and highlight its strengths. When minimizing cost, maintenance plans are frequently produced that result in mission survival while avoiding unnecessary repairs. The proposed method is usable in large-scale, complex scenarios and various industrial contexts. The method finds exact solutions while avoiding the need for computationally-intensive parametric reliability functions.</p>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"5 1","pages":"13"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12175739/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144327926","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":"To healthier Ethereum: a comprehensive and iterative smart contract weakness enumeration","authors":"Jiachi Chen,&nbsp;Mingyuan Huang,&nbsp;Zewei Lin,&nbsp;Peilin Zheng,&nbsp;Zibin Zheng","doi":"10.1016/j.bcra.2024.100258","DOIUrl":"10.1016/j.bcra.2024.100258","url":null,"abstract":"<div><div>With the increasing popularity of cryptocurrencies and blockchain technologies, smart contracts have become a prominent feature in developing decentralized applications. However, these smart contracts are susceptible to vulnerabilities that hackers can exploit, resulting in significant financial losses. In response to this growing concern, various initiatives have emerged. Notably, the Smart Contract Weakness Classification (SWC) list plays an important role in raising awareness and understanding of smart contract weaknesses. However, the SWC list lacks maintenance and has not been updated with new vulnerabilities since 2020. To address this gap, this paper introduces the Smart Contract Weakness Enumeration (SWE), a comprehensive and practical vulnerability list up until 2023. We collect 273 vulnerability descriptions from 86 top conference papers and journal papers, employing the open card-sorting method to deduplicate and categorize these descriptions. This process results in the identification of 40 common contract weaknesses, which are further classified into 20 sub-research fields through thorough discussion and analysis. The SWE provides a systematic and comprehensive list of smart contract vulnerabilities, covering existing and emerging vulnerabilities in the last few years. Moreover, the SWE is a scalable and continuously iterative program. We propose two update mechanisms for the maintenance of the SWE. Regular updates involve the inclusion of new vulnerabilities from future top papers, while irregular updates enable individuals to report new weaknesses for review and potential addition to the SWE.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 2","pages":"Article 100258"},"PeriodicalIF":6.9,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","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}

{"title":"Unveiling smart contract vulnerabilities: Toward profiling smart contract vulnerabilities using enhanced genetic algorithm and generating benchmark dataset","authors":"Sepideh HajiHosseinKhani ,&nbsp;Arash Habibi Lashkari ,&nbsp;Ali Mizani Oskui","doi":"10.1016/j.bcra.2024.100253","DOIUrl":"10.1016/j.bcra.2024.100253","url":null,"abstract":"<div><div>With the advent of blockchain networks, there has been a transition from traditional contracts to Smart Contracts (SCs), which are crucial for maintaining trust within these networks. Previous methods for analyzing SCs vulnerabilities typically suffer from a lack of accuracy and effectiveness. Many of them, such as rule-based methods, machine learning techniques, and neural networks, also struggle to detect complex vulnerabilities due to limited data availability. This study introduces a novel approach to detecting, identifying, and profiling SC vulnerabilities, comprising two key components: an updated analyzer named SCsVulLyzer (V2.0) and an advanced Genetic Algorithm (GA) profiling method. The analyzer extracts 240 features across different categories, while the enhanced GA, explicitly designed for profiling SC vulnerabilities, employs techniques such as penalty fitness function, retention of elites, and adaptive mutation rate to create a detailed profile for each vulnerability. Furthermore, due to the lack of comprehensive validation and evaluation datasets with sufficient samples and diverse vulnerabilities, this work introduces a new dataset named BCCC-SCsVul-2024. This dataset consists of 111,897 Solidity source code samples, ensuring the practical validation of the proposed approach. Additionally, three types of taxonomies are established, covering SC literature review, profiling techniques, and feature extraction. These taxonomies offer a systematic classification and analysis of information, enhancing the efficiency of the proposed profiling technique. Our proposed approach demonstrated superior capabilities with higher precision and accuracy through rigorous testing and experimentation. It not only showed excellent results for evaluation parameters but also proved highly efficient in terms of time and space complexity. Moreover, the concept of the profiling technique makes our model highly transparent and explainable. These promising results highlight the potential of GA-based profiling to improve the detection and identification of SC vulnerabilities, contributing to enhanced security in blockchain networks.</div></div>","PeriodicalId":53141,"journal":{"name":"Blockchain-Research and Applications","volume":"6 2","pages":"Article 100253"},"PeriodicalIF":6.9,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143878422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}