High-Confidence Computing最新文献_第9页

A survey of fault tolerant consensus in wireless networks 无线网络容错共识调查

High-Confidence Computing Pub Date : 2024-01-09 DOI: 10.1016/j.hcc.2024.100202

Yifei Zou , Li Yang , Guanlin Jing , Ruirui Zhang , Zhenzhen Xie , Huiqun Li , Dongxiao Yu

{"title":"A survey of fault tolerant consensus in wireless networks","authors":"Yifei Zou , Li Yang , Guanlin Jing , Ruirui Zhang , Zhenzhen Xie , Huiqun Li , Dongxiao Yu","doi":"10.1016/j.hcc.2024.100202","DOIUrl":"10.1016/j.hcc.2024.100202","url":null,"abstract":"<div><p>Wireless networks have become integral to modern communication systems, enabling the seamless exchange of information across a myriad of applications. However, the inherent characteristics of wireless channels, such as fading, interference, and openness, pose significant challenges to achieving fault-tolerant consensus within these networks. Fault-tolerant consensus, a critical aspect of distributed systems, ensures that network nodes collectively agree on a consistent value even in the presence of faulty or compromised components. This survey paper provides a comprehensive overview of fault-tolerant consensus mechanisms specifically tailored for wireless networks. We explore the diverse range of consensus protocols and techniques that have been developed to address the unique challenges of wireless environments. The paper systematically categorizes these consensus mechanisms based on their underlying principles, communication models, and fault models. It investigates how these mechanisms handle various types of faults, including communication errors, node failures, and malicious attacks. It highlights key use cases, such as sensor networks, Internet of Things (IoT) applications, wireless blockchain, and vehicular networks, where fault-tolerant consensus plays a pivotal role in ensuring reliable and accurate data dissemination.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 2","pages":"Article 100202"},"PeriodicalIF":0.0,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295224000059/pdfft?md5=7d04cf1493be0e5575ab310a74881d83&pid=1-s2.0-S2667295224000059-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139457898","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}

引用次数: 0

Outlier item detection in bundle recommendation via the attention mechanism 通过关注机制检测捆绑推荐中的异常项目

High-Confidence Computing Pub Date : 2024-01-05 DOI: 10.1016/j.hcc.2024.100200

Yuan Liang

{"title":"Outlier item detection in bundle recommendation via the attention mechanism","authors":"Yuan Liang","doi":"10.1016/j.hcc.2024.100200","DOIUrl":"10.1016/j.hcc.2024.100200","url":null,"abstract":"<div><p>Bundle recommendation offers users more holistic insights by recommending multiple compatible items at once. However, the intricate correlations between items, varied user preferences, and the pronounced data sparsity in combinations present significant challenges for bundle recommendation algorithms. Furthermore, current bundle recommendation methods fail to identify mismatched items within a given set, a process termed as “outlier item detection”. These outlier items are those with the weakest correlations within a bundle. Identifying them can aid users in refining their item combinations. While the correlation among items can predict the detection of such outliers, the adaptability of combinations might not be adequately responsive to shifts in individual items during the learning phase. This limitation can hinder the algorithm’s performance. To tackle these challenges, we introduce an encoder–decoder architecture tailored for outlier item detection. The encoder learns potential item correlations through a self-attention mechanism. Concurrently, the decoder garners efficient inference frameworks by directly assessing item anomalies. We have validated the efficacy and efficiency of our proposed algorithm using real-world datasets.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 3","pages":"Article 100200"},"PeriodicalIF":0.0,"publicationDate":"2024-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295224000035/pdfft?md5=efa091405aad1bbcc69d7febeec7012b&pid=1-s2.0-S2667295224000035-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139393106","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}

引用次数: 0

Food safety testing by negentropy-sorted kernel independent component analysis based on infrared spectroscopy 基于红外光谱的负熵排序核独立成分分析法进行食品安全检测

High-Confidence Computing Pub Date : 2023-12-28 DOI: 10.1016/j.hcc.2023.100197

Jing Liu, Limiao Deng, Zhongzhi Han

{"title":"Food safety testing by negentropy-sorted kernel independent component analysis based on infrared spectroscopy","authors":"Jing Liu, Limiao Deng, Zhongzhi Han","doi":"10.1016/j.hcc.2023.100197","DOIUrl":"10.1016/j.hcc.2023.100197","url":null,"abstract":"<div><p>In the field of food safety testing, variety, brand, origin, and adulteration are four important factors. In this study, a novel food safety testing method based on infrared spectroscopy is proposed to investigate these factors. Fourier transform infrared spectroscopy data are analyzed using negentropy-sorted kernel independent component analysis (NS-kICA) as the feature optimization method. To rank the components, negentropy is performed to measure the non-Gaussian independent components. In our experiment, the proposed method was run on four datasets to comprehensively investigate the variety, brand, origin, and adulteration of agricultural products. The experimental results show that NS-kICA outperforms conventional feature selection methods. The support vector machine model outperforms the backpropagation artificial neural network and partial least squares models. The combination of NS-kICA and support vector machine (SVM) is the best method for achieving high, stable, and efficient recognition performance. These findings are of great importance for food safety testing.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 3","pages":"Article 100197"},"PeriodicalIF":0.0,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295223000958/pdfft?md5=b8bd33e2cea03cbd8890ca8538dee20c&pid=1-s2.0-S2667295223000958-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139188126","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}

引用次数: 0

A hierarchical byzantine fault tolerance consensus protocol for the Internet of Things 面向物联网的分层拜占庭容错共识协议

IF 3.2

High-Confidence Computing Pub Date : 2023-12-20 DOI: 10.1016/j.hcc.2023.100196

Rongxin Guo , Zhenping Guo , Zerui Lin , Wenxian Jiang

{"title":"A hierarchical byzantine fault tolerance consensus protocol for the Internet of Things","authors":"Rongxin Guo , Zhenping Guo , Zerui Lin , Wenxian Jiang","doi":"10.1016/j.hcc.2023.100196","DOIUrl":"10.1016/j.hcc.2023.100196","url":null,"abstract":"<div><p>The inefficiency of Consensus protocols is a significant impediment to blockchain and IoT convergence development. To solve the problems like inefficiency and poor dynamics of the Practical Byzantine Fault Tolerance (PBFT) in IoT scenarios, a hierarchical consensus protocol called DCBFT is proposed. Above all, we propose an improved k-sums algorithm to build a two-level consensus cluster, achieving an hierarchical management for IoT devices. Next, A scalable two-level consensus protocol is proposed, which uses a multi-primary node mechanism to solve the single-point-of-failure problem. In addition, a data synchronization process is introduced to ensure the consistency of block data after view changes. Finally, A dynamic reputation evaluation model is introduced to update the nodes’ reputation values and complete the rotation of consensus nodes at the end of each consensus round. The experimental results show that DCBFT has a more robust dynamic and higher consensus efficiency. Moreover, After running for some time, the performance of DCBFT shows some improvement.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 3","pages":"Article 100196"},"PeriodicalIF":3.2,"publicationDate":"2023-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295223000946/pdfft?md5=319d5156a64f46754b47a19c3c570818&pid=1-s2.0-S2667295223000946-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138992888","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}

引用次数: 0

Developing a reliable route protocol for mobile self-organization networks 为移动自组织网络开发可靠的路由协议

IF 3.2

High-Confidence Computing Pub Date : 2023-12-13 DOI: 10.1016/j.hcc.2023.100194

Shaohu Li, Bei Gong

{"title":"Developing a reliable route protocol for mobile self-organization networks","authors":"Shaohu Li, Bei Gong","doi":"10.1016/j.hcc.2023.100194","DOIUrl":"10.1016/j.hcc.2023.100194","url":null,"abstract":"<div><p>Mobile ad hoc networks (MANETs), which correspond to a novel wireless technology, are widely used in Internet of Things (IoT) systems such as drones, wireless sensor networks, and military or disaster relief communication. From the perspective of communication and data collection, the success rate of collaborations between nodes in mobile ad hoc networks and reliability of data collection mainly depend on whether the nodes in the network operate normally, namely, according to the established network rules. However, mobile ad hoc networks are vulnerable to attacks targeting transmission channels and nodes owing to their dynamic evolution, openness, and distributed characteristics. Therefore, during the network operation, it is necessary to classify and detect the behavior and characteristics of each node. However, most existing research only analyzes and considers responses against a single or small number of attacks. To address these issues, this article first systematically analyzed and classified common active attacks in MANETs. Then, a node trust model was proposed based on the characteristics of various attacks; subsequently, a new secure routing protocol, namely, TC-AODV, was proposed. This protocol has minimal effect on the original communication dynamics and can effectively deal with Packet drop, wormhole, Session hijacking, and other main attacks in MANETs. The NS3 simulation results show that the proposed routing protocol attains good transmission performance, can effectively identify various attacks and bypass malicious nodes, and securely complete the communication process.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 3","pages":"Article 100194"},"PeriodicalIF":3.2,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295223000922/pdfft?md5=53b7d00856a2e91f112b906eb37efea9&pid=1-s2.0-S2667295223000922-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139023660","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}

引用次数: 0

Anonymity preserving lightweight authentication protocol for resource-limited wireless sensor networks 资源有限的无线传感器网络的匿名保护轻量级认证协议

High-Confidence Computing Pub Date : 2023-11-24 DOI: 10.1016/j.hcc.2023.100178

Vincent Omollo Nyangaresi , Ganesh Keshaorao Yenurkar

{"title":"Anonymity preserving lightweight authentication protocol for resource-limited wireless sensor networks","authors":"Vincent Omollo Nyangaresi , Ganesh Keshaorao Yenurkar","doi":"10.1016/j.hcc.2023.100178","DOIUrl":"10.1016/j.hcc.2023.100178","url":null,"abstract":"<div><p>Wireless sensor networks have been deployed in areas such as healthcare, military, transportation and home automation to collect data and forward it to remote users for further processing. Since open wireless communication channels are utilized for data transmissions, the exchanged messages are vulnerable to various threats such as eavesdropping and message falsifications. Therefore, many security solutions have been introduced to address these challenges. However, the resource-constrained nature of the sensor nodes makes it inefficient to deploy the conventional security schemes which require long keys for improved security. Therefore, lightweight authentication protocols have been presented. Unfortunately, majority of these schemes are still insecure while others incur relatively higher energy, computation, communication and storage complexities. In this paper, a protocol that deploys only lightweight one-way hashing and exclusive OR operations is presented. Its formal security analysis using Real-or Random (ROR) model demonstrates its capability to uphold the security of the derived session keys. In addition, its semantic security evaluation shows that it offers user privacy, anonymity, untraceability, authentication, session key agreement and key secrecy. Moreover, it is shown to resist attacks such as side-channeling, physical capture, eavesdropping, offline guessing, spoofing, password loss, session key disclosure, forgery and impersonations. In terms of performance, it has relatively lower communication overheads and improves the computation costs and supported security characteristics by 31.56% and 33.33% respectively.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 2","pages":"Article 100178"},"PeriodicalIF":0.0,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295223000764/pdfft?md5=d761183b678601441d00478ed3ce897b&pid=1-s2.0-S2667295223000764-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139303979","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}

引用次数: 0

Fog-computing based mobility and resource management for resilient mobile networks 基于雾计算的移动性和资源管理，实现弹性移动网络

High-Confidence Computing Pub Date : 2023-11-24 DOI: 10.1016/j.hcc.2023.100193

Hang Zhao, Shengling Wang, Hongwei Shi

{"title":"Fog-computing based mobility and resource management for resilient mobile networks","authors":"Hang Zhao, Shengling Wang, Hongwei Shi","doi":"10.1016/j.hcc.2023.100193","DOIUrl":"10.1016/j.hcc.2023.100193","url":null,"abstract":"<div><p>Mobile networks are facing unprecedented challenges due to the traits of large scale, heterogeneity, and high mobility. Fortunately, the emergence of fog computing offers surprisingly perfect solutions considering the features of consumer proximity, wide-spread geographical distribution, and elastic resource sharing. In this paper, we propose a novel mobile networking framework based on fog computing which outperforms others in resilience. Our scheme is constituted of two parts: the personalized customization mobility management (MM) and the market-driven resource management (RM). The former provides a dynamically customized MM framework for any specific mobile node to optimize the handoff performance according to its traffic and mobility traits; the latter makes room for economic tussles to find out the competitive service providers offering a high level of service quality at sound prices. Synergistically, our proposed MM and RM schemes can holistically support a full-fledged resilient mobile network, which has been practically corroborated by numerical experiments.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 2","pages":"Article 100193"},"PeriodicalIF":0.0,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295223000910/pdfft?md5=14166eeafd4e4d042e4b4bbd39b389c3&pid=1-s2.0-S2667295223000910-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139297389","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}

引用次数: 0

Graph reasoning over explicit semantic relation 明确语义关系的图推理

High-Confidence Computing Pub Date : 2023-11-24 DOI: 10.1016/j.hcc.2023.100190

Tianyou Zhu, Shi Liu, Bo Li, Junjian Liu, Pufan Liu, Fei Zheng

{"title":"Graph reasoning over explicit semantic relation","authors":"Tianyou Zhu, Shi Liu, Bo Li, Junjian Liu, Pufan Liu, Fei Zheng","doi":"10.1016/j.hcc.2023.100190","DOIUrl":"10.1016/j.hcc.2023.100190","url":null,"abstract":"<div><p>Multi-hop reasoning over language or graphs represents a significant challenge in contemporary research, particularly with the reliance on deep neural networks. These networks are integral to text reasoning processes, yet they present challenges in extracting and representing domain or commonsense knowledge, and they often lack robust logical reasoning capabilities. To address these issues, we introduce an innovative text reasoning framework. This framework is grounded in the use of a semantic relation graph and a graph neural network, designed to enhance the model’s ability to encapsulate knowledge and facilitate complex multi-hop reasoning.</p><p>Our framework operates by extracting knowledge from a broad range of texts. It constructs a semantic relationship graph based on the logical relationships inherent in the reasoning process. Beginning with the core question, the framework methodically deduces key knowledge, using it as a guide to iteratively establish a complete evidence chain, thereby determining the final answer. Leveraging the advanced reasoning capabilities of the graph neural network, this approach is adept at multi-hop logical reasoning. It demonstrates strong performance in tasks like machine reading comprehension and question answering, while also clearly delineating the path of logical reasoning.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 2","pages":"Article 100190"},"PeriodicalIF":0.0,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295223000880/pdfft?md5=828625193dc2302f5c9c29c69fed0f34&pid=1-s2.0-S2667295223000880-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139295983","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}

引用次数: 0

Data collection of wireless sensor network based on trajectory optimization of laser-charged UAV 基于激光充电无人机轨迹优化的无线传感器网络数据采集

High-Confidence Computing Pub Date : 2023-11-24 DOI: 10.1016/j.hcc.2023.100181

Chuanwen Luo , Jian Zhang , Jin Qian , Yi Hong , Zhibo Chen , Yunan Hou , Xiujuan Zhang , Yuqing Zhu

{"title":"Data collection of wireless sensor network based on trajectory optimization of laser-charged UAV","authors":"Chuanwen Luo , Jian Zhang , Jin Qian , Yi Hong , Zhibo Chen , Yunan Hou , Xiujuan Zhang , Yuqing Zhu","doi":"10.1016/j.hcc.2023.100181","DOIUrl":"10.1016/j.hcc.2023.100181","url":null,"abstract":"<div><p>Unmanned Aerial Vehicle (UAV) can be used as wireless aerial mobile base station for collecting data from sensors in UAV-based Wireless Sensor Networks (WSNs), which is crucial for providing seamless services and improving the performance in the next generation wireless networks. However, since the UAV are powered by batteries with limited energy capacity, the UAV cannot complete data collection tasks of all sensors without energy replenishment when a large number of sensors are deployed over large monitoring areas. To overcome this problem, we study the Real-time Data Collection with Laser-charging UAV (RDCL) problem, where the UAV is utilized to collect data from a specified WSN and is recharged using Laser Beam Directors (LBDs). This problem aims to collect all sensory data from the WSN and transport it to the base station by optimizing the flight trajectory of UAV such that real-time data performance is ensured It has been proven that the RDCL problem is NP-hard. To address this, we initially focus on studying two sub-problems, the Trajectory Optimization of UAV for Data Collection (TODC) problem and the Charging Trajectory Optimization of UAV (CTO) problem, whose objectives are to find the optimal flight plans of UAV in the data collection areas and charging areas, respectively. Then we propose an approximation algorithm to solve each of them with the constant factor. Subsequently, we present an approximation algorithm that utilizes the solutions obtained from TODC and CTO problems to address the RDCL problem. Finally, the proposed algorithm is verified by extensive simulations.</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 2","pages":"Article 100181"},"PeriodicalIF":0.0,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266729522300079X/pdfft?md5=3775a80148dcbf7a3e65166e29bb5334&pid=1-s2.0-S266729522300079X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139295366","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}

引用次数: 0

FedQMIX: Communication-efficient federated learning via multi-agent reinforcement learning FedQMIX：通过多代理强化学习实现通信效率高的联合学习

High-Confidence Computing Pub Date : 2023-11-23 DOI: 10.1016/j.hcc.2023.100179

Shaohua Cao , Hanqing Zhang , Tian Wen , Hongwei Zhao , Quancheng Zheng , Weishan Zhang , Danyang Zheng

{"title":"FedQMIX: Communication-efficient federated learning via multi-agent reinforcement learning","authors":"Shaohua Cao , Hanqing Zhang , Tian Wen , Hongwei Zhao , Quancheng Zheng , Weishan Zhang , Danyang Zheng","doi":"10.1016/j.hcc.2023.100179","DOIUrl":"10.1016/j.hcc.2023.100179","url":null,"abstract":"<div><p>Since the data samples on client devices are usually non-independent and non-identically distributed (non-IID), this will challenge the convergence of federated learning (FL) and reduce communication efficiency. This paper proposes FedQMIX, a node selection algorithm based on multi-agent reinforcement learning(MARL), to address these challenges. Firstly, we observe a connection between model weights and data distribution, and a clustering algorithm can group clients with similar data distribution into the same cluster. Secondly, we propose a QMIX-based mechanism that learns to select devices from clustering results in each communication round to maximize the reward, penalizing the use of more communication rounds and thereby improving the communication efficiency of FL. Finally, experiments show that FedQMIX can reduce the number of communication rounds by 11% and 30% on the MNIST and CIFAR-10 datasets, respectively, compared to the baseline algorithm (Favor).</p></div>","PeriodicalId":100605,"journal":{"name":"High-Confidence Computing","volume":"4 2","pages":"Article 100179"},"PeriodicalIF":0.0,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667295223000776/pdfft?md5=9424588f5b02e7d1cae86ff00cee768b&pid=1-s2.0-S2667295223000776-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139293479","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}

引用次数: 0