检索结果-内蒙古大学图书馆

FMDPgram: An Improvement of FMD for Rotating Machinery Fault Diagnosis

IEEE Transactions on Industrial Informatics 2025年

作者： Li, Hua Wang, Tianyang Zhang, Feibin Chu, Fulei Guizhou University State Key Laboratory of Public Big Data Guiyang 550025 China Tsinghua University Department of Mechanical Engineering Beijing 100084 China

Recently, feature mode decomposition (FMD) has been proposed and has demonstrated robust performance in the application of rotating machinery fault diagnosis. However, FMD does not have parameter adaptability, and its influencing parameters (i.e., segment number, mode number and filter length) need to be defined in advance. Inspired by the decomposition mode of wavelet packet transform, this article cleverly proposes a binary decomposition structure of FMD to form the concept of FMD packet (FMDP). Furthermore, the tiling structure of FMDP is constructed, thus forming the FMDPgram. In FMDPgram, the frequency band of the raw signal is evenly divided into 2 segments, and each FMD generates two submode components (SMCs), thus simplifying the hyperparameter optimization into a single-parameter optimization. Additionally, an indicator called narrowband peak-to-average ratio (NPAR) is proposed for optimal SMC positioning, and which is displayed in the FMDPgram tile map. First, performing FMDPgram with NPAR on the raw signal. Then, the optimal SMC is located based on the NPAR in the FMDPgram tile map. Finally, the envelope power spectrum of the optimal SMC is calculated to characterize the fault characteristic information. FMDPgram is tested on simulated and experimental data, and compared with FMD, spectral kurtosis, VMD and improved Kurtogram to evaluate its performance in rolling bearing diagnosis under low signal-to-noise ratio and non-Gaussian interference. © 2005-2012 IEEE.

关键词： Fault diagnosis feature mode decomposition (FMD) FMD packet (FMDP) FMDPgram main submode component narrowband peak-to-average ratio (NPAR)

来源：评论

学校读者我要写书评

暂无评论

Super-Resolution of Diffusion-Weighted Images via TDI-Conditioned Diffusion Model 15th

Super-Resolution of Diffusion-Weighted Images via TDI-Cond...

引用

15th International Workshop on Computational Diffusion MRI, CDMRI 2024, held in conjunction with 27th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2024

作者： Ma, Jiquan Teng, Yujun Chen, Geng Jiang, Haotian Zhang, Kai Liu, Feihong Rekik, Islem Shen, Dinggang School of Computer Science and Technology Heilongjiang University Harbin China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi’an China School of Biomedical Engineering and State Key Laboratory of Advanced Medical Materials and Devices ShanghaiTech University Shanghai China School of Information Science and Technology Northwest University Xi’an China BASIRA Lab Imperial-X and Department of Computing Imperial College London London United Kingdom

ISBN: (纸本)9783031869198

Diffusion-Weighted Imaging (DWI) is a significant technique for studying white matter. However, it suffers from low-resolution obstacles in clinical settings. Post-acquisition Super-Resolution (SR) can enhance the resolution of DWIs and has gained increasing research interest in recent years. An advanced generative model, the Diffusion Model (DM), exhibits particularly promising performance in image SR. However, effective conditions are required to bootstrap the DM for DWI SR. To this end, we proposed the first DM-based DWI SR model with two effective conditions based on low-solution DWIs and Track Density Imaging (TDI) maps, which possess rich high-resolution prior knowledge Additionally, we consider another condition based on features from low-resolution DWIs. These two conditions are integrated into our model, which comprises three components: DWI Resolution Enhancer (DRE), DWI Feature Extractor (DFE), and TDI Feature Extractor (TFE). DRE combines low-resolution DWI features from DFE with TDI features from TFE to progressively generate high-resolution DWIs. We performed extensive experiments on DWIs of normal subjects from human connectome projects and patients with Parkinson’s disease. The results demonstrate that our model outperforms existing DWI SR models, both qualitatively and quantitatively. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Neurodegenerative diseases

来源：评论

学校读者我要写书评

暂无评论

Zero-Shot Cross-Domain Code Search without Fine-Tuning

arXiv

引用

arXiv 2025年

作者： Liang, keyu Liu, Zhongxin Liu, Chao Wan, Zhiyuan Lo, David Yang, Xiaohu The State Key Laboratory of Blockchain and Data Security Zhejiang University Hangzhou China School of Big Data and Software Engineering Chongqing University Chongqing China School of Computing and Information Systems Singapore Management University Singapore Singapore

Code search is a crucial task in software engineering, aiming to retrieve code snippets that are semantically relevant to a natural language query. Recently, Pre-trained Language Models (PLMs) have shown remarkable success and are widely adopted for code search tasks. However, PLM-based methods often struggle in cross-domain scenarios. When applied to a new domain, they typically require extensive fine-tuning with substantial data. Even worse, the data scarcity problem in new domains often forces these methods to operate in a zero-shot setting, resulting in a significant decline in performance. RAPID, which generates synthetic data for model fine-tuning, is currently the only effective method for zero-shot cross-domain code search. Despite its effectiveness, RAPID demands substantial computational resources for fine-tuning and needs to maintain specialized models for each domain, underscoring the need for a zero-shot, fine-tuning-free approach for cross-domain code search. The key to tackling zero-shot cross-domain code search lies in bridging the gaps among domains. In this work, we propose to break the query-code matching process of code search into two simpler tasks: query-comment matching and code-code matching. We first conduct an empirical study to investigate the effectiveness of these two matching schemas in zero-shot cross-domain code search. Our findings highlight the strong complementarity among the three matching schemas, i.e., query-code, query-comment, and code-code matching. Based on the findings, we propose CodeBridge, a zero-shot, fine-tuning-free approach for cross-domain code search. Specifically, CodeBridge first employs zero-shot prompting to guide Large Language Models (LLMs) to generate a comment for each code snippet in the codebase and produce a code for each query. Subsequently, it encodes queries, code snippets, comments, and the generated code using PLMs and assesses similarities through three matching schemas: query-code, query-comment,

关键词： Search engines

来源：评论

学校读者我要写书评

暂无评论

Deep Learning Based Proactive Anomaly Detection for 5G Core Control Plane Network Function Interactions

引用

IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Tan, Yawen Liu, Jiajia Li, Yuanhao Wang, Jiadai Xidian University State Key Laboratory of Integrated Services Networks School of Cyber Engineering Xi'an710071 China Northwestern Polytechnical University National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Cybersecurity Shaanxi Xi'an710072 China

The Service-Based Architecture (SBA) introduced by 3GPP allows the control plane of 5G Core Network (CN) to function through a set of interconnected Network Functions (NFs), which offers significant benefits such as improved scalability, simplified operations, and efficient resource utilization. However, such a new transformation could also make critical NFs in 5G CN become more susceptible to attacks due to both internal vulnerabilities within the software-implemented NFs or the expanded interfaces brought by the SBA. Existing studies targeting 5G network security pay little attention to the detection of abnormal behaviors from control plane NFs. Therefore, in this paper, we propose 5GCGuard, an anomaly detection scheme aiming at identifying abnormal NF interactions in 5G CN. It employs a deep learning-based sequence model to learn normal interaction patterns and detects anomalies based on deviations from the learned pattern. Special designs including attention mechanism, multi-task learning, probabilistic labeling and automatic threshold decision are made to enhance its detection capabilities. We establish a cloud-native 5G testbed to evaluate the effectiveness of 5GCGuard. Extensive evaluation results show its superiority over comparison schemes. Case studies also demonstrate its ability to proactively detect various NF interaction anomalies, enabling swift action to block attacks and prevent further damage. © 2015 IEEE.

关键词： 5G mobile communication systems

来源：评论

学校读者我要写书评

暂无评论

CASI: Context-aware Automatic Semantic Inference by fusing video and network traffic information in industrial control systems

引用

Information Fusion 2025年 122卷

作者： Hetu, Zheqiu Zhang, Zhenyong Wang, Mufeng Xv, Zidong Meng, Jie State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guiyang550025 China China Industrial Control Systems Cyber Emergency Response Team Beijing100040 China State Key Laboratory of Industrial Control Technology and College of Control Science and Engineering Zhejiang University Hangzhou310027 China

The increasing adoption of Internet of Things devices in Industrial Control Systems (ICS) has provided both attackers and security professionals with new perspectives on these traditionally safety-critical systems. Our observations reveal that video captured by field-deployed cameras contains process variables (PVs) essential for both ICS attack and defense. Based on this insight, we propose a Context-Aware Semantic Inference (CASI) method. CASI integrates video information from cameras with network traffic to infer the physical semantics of PVs in network packets, serving as a tactical tool for attackers or security professionals. A key advantage of CASI is its non-intrusive nature, deriving PVs location in the packets and semantics solely from video and network traffic without interacting with the runtime ICS, which is both covert and ensures the uninterrupted operation of the system. We constructed an ICS testbed using real devices to replicate a simplified industrial process, collecting traffic from 2 industrial protocols and creating 4 datasets. We evaluated CASI's precision and recall in detecting PVs within this context, comparing it with similar tools. Experimental results demonstrate that CASI achieves a recall rate of 1.00 in PV semantic extraction, significantly outperforming other tools. Furthermore, leveraging CASI-derived semantic information for data tampering attacks successfully disrupted monitoring and data acquisition programs, posing a severe security threat to the ICS. © 2025 Elsevier B.V.

关键词： Reverse engineering

来源：评论

学校读者我要写书评

暂无评论

Electrocardiogram-to-Pair (E2P): A Secure Group Pairing Protocol for WBAN Devices

引用

IEEE Internet of Things Journal 2025年

作者： Zhao, Guichuan Tian, Youliang Jiang, Qi Ma, Jianfeng Guizhou University College of Computer Science and Technology Guiyang 550000 China Guizhou University State Key Laboratory of Public Big Data College of Big Data and Information Engineering Guiyang 550000 China Xidian University School of Cyber Engineering Xi'an 710071 China

In a wireless body area network (WBAN), group pairing among multiple wearable devices enables efficient and secure broadcasting group messages. Existing pairing methods that rely on trusted concentrators, active participation of users, or homogeneous environments are vulnerable to single point of failure and have restricted practicality. In this article, we propose Electrocardiogram-to-Pair (E2P), an electrocardiogram (ECG)-based secure group pairing protocol for WBAN devices that allows the establishment of a shared group key among multiple devices without requiring the user involvement or the central device. First, all wearable devices worn by the same user simultaneously collect ECG signals, which are then pre-processed through filtering and alignment to minimize the effect of noise on the pairing. Next, an adaptive quantization method is designed to reliably quantize the pre-processed ECG signals to generate initial keys. This method is ingenious as it relies on feature transformation and dynamic thresholds generation in the quantization process, which effectively ensures the security of biometrics and increases the key generation rate. Then, the group key is established among devices with initial keys through an improved Cascade method. The simulation results demonstrate that E2P achieves an effective balance the reliability and efficiency in group pairing, with outstanding performance in both security and key generation rate. © 2014 IEEE.

关键词： Electrocardiogram group pairing key establishment wireless body area network

来源：评论

学校读者我要写书评

暂无评论

Federated Domain Generalization for Fault Diagnosis: Cross-Client Style Integration and Dual Alignment Representation

引用

IEEE Internet of Things Journal 2025年

作者： Wang, Yu Zhang, Guowei Kong, Xianguang Du, Jingli Ma, Hongbo Yunnan Agricultural University College of Big Data Kunming650500 China Xidian University College of Mechanical and Electrical Engineering Xian710071 China State Key Laboratory of Electromechanical Integrated Manufacturing of High-performance Electronic Equipments China

Federated learning (FL) enables the collaborative training of intelligent diagnostic models across multiple clients while preserving data privacy. However, the complex and dynamic working conditions often cause federated diagnostic models to suffer from performance degradation when applied to unseen clients, exposing deficiencies in model generalization. Domain generalization fault diagnosis methods aim to enhance model adaptability under unknown working conditions, but most existing algorithms rely on shared data, making them unsuitable for direct application in federated learning environments. To address this challenge, we propose a federated domain generalization fault diagnosis method based on Cross-Client Style Integration and Dual Alignment representation (CCSIDA). This method significantly enhances model generalization in FL settings while ensuring data privacy. Specifically, CCSIDA integrates three key strategies: cross-client style data enhancement, domain-sensitive feature suppression, and predictive alignment. For cross-client style integration, we design a stochastic mixed-style sample generation module to overcome the limitations of conventional domain generalization data enhancement methods in FL. This module generates diverse samples by constructing a shared style repository, enabling inter-client style information transfer. For cross-client dual alignment representation, we introduce a domain-sensitive feature suppression strategy to reduce domain discrepancies between original and enhanced samples. Additionally, Jensen-Shannon divergence is employed to ensure prediction consistency between these samples. Finally, extensive experiments on five benchmark datasets validate the effectiveness of the proposed method. © 2014 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Cross-Chain Privacy-Preserving for BIoMT With Designated Verifier Proxy Signature

引用

IEEE Internet of Things Journal 2025年

作者： Li, Chaoyang Jiang, Bohao Dong, Mianxiong Chen, Yuling Huang, Min Xin, Xiangjun Ota, Kaoru Zhengzhou University of Light Industry College of Software Engineering Zhengzhou450001 China Muroran Institution of Technology Muroran050-8585 Japan Guizhou University State Key Laboratory of Public Big Data Guizhou Guiyang550025 China

Blockchain-enabled Internet of Medical Things (BIoMT) has received extensive attention and in-depth research to solve the centralized, data island problems with the rapid developments of blockchain-related technologies. However, many different chains with different data structures, consensus protocols, and cryptographic algorithms are constructed, which brings a new »data island» problem. Meanwhile, the cryptographic algorithms used in most current BIoMT systems are weak against quantum attacks. In this paper, a cross-chain privacy-preserving (CCPP) model and a designated verifier proxy signature (DVPS) scheme have been proposed. This CCPP model is equipped with the relay chain technology and DVPS to achieve secure cross-chain medical data-sharing among different BIoMT systems. The DVPS scheme is constructed with lattice theory, which can achieve signer proxy, designated user verification, and anti-quantum attack. Then, the security proof shows that the proposed DVPS can capture the security properties of correctness, unforgeability, the signer's anonymity, and non-transferability. The performance evaluations show that the cross-chain transactions are efficient and stable with the transaction number increasing, and the proposed DVPS is efficient about the key size, time consumption, and energy consumption. This work can also improve the privacy security of system users and medical data in BIoMT systems and promote the value play of medical data. © 2014 IEEE.

关键词： Lattice theory

来源：评论

学校读者我要写书评

暂无评论

A review on global spatial distribution,sources and toxicity of perfluoroalkyl acid and prospect in the cryosphere

引用

Journal of Mountain Science 2025年第1期22卷 167-183页

作者： LI Bowen Du Wentao KANG Shichang CHEN Jizu JIANG Youyan YIN Lichen LU Changsheng LIU Hongyi State Key Laboratory of Cryospheric Science and frozen soil engineering Northwest Institute of Eco-Environment and ResourcesChinese Academy of Sciences(CAS)Lanzhou 730000China University of Chinese Academy of Sciences Beijing 100049China Gansu Provincial Industry Technology Center of Intelligent Equipment and Big Data for Disaster Prevention Northwest Institute of Eco-Environment and ResourcesChinese Academy of Sciences(CAS)Lanzhou 730000China Lanzhou Regional Climate Center Lanzhou 730000China School of Earth Sciences and Spatial Information Engineering Hunan University of Science and TechnologyXiangtan 411201China School of Energy and Power Engineering Lanzhou University of TechnologyLanzhou 730000China Zhangye Meteorological Service Zhangye 734000China

Perfluoroalkyl acid analogs(PFAAs)are a class of chemically stable environmentally persistent organic pollutants(POPs)that are difficult to degrade and have a strong capacity to accumulate in the human *** have been found to be biotoxic to humans and have been detected in various environmental media,especially in the cryosphere at trace *** cryosphere,sensitively responds to climate change,plays a crucial role in the global water,carbon and energy ***,researches on cryosphere PFAAs especially in Tibetan Plateau(TP)is ***,we summarize the physicochemical properties,physiological toxicity,spatiotemporal distribution,sources,diffusion and migration pathways,as well as analysis and removal methods of PFAAs in the cryosphere *** results show that PFAAs pollutants are mainly produced and distributed in the more economically developed countries in Europe and the United states,as well as in East Asia,and PFAAs can be transported by atmospheric circulation and water cycle to remote regions including cryosphere *** current detection methods for PFAAs in cryosphere need to be further refined for increased accuracy and *** is also a need to develop more effective removal methods that will reduce the environmental and human threats posed by these ***,we propose key scientific questions for future research in cryosphere including PFAAs redistribution influenced by cryosphere changes,human activities,and the interaction of other spheres.

关键词： Perfluoroalkyl acid Cryosphere Physiological toxicity Analytical method Removal method

来源：评论

学校读者我要写书评

暂无评论

Counterfactual Inference for Generalized Zero-Shot Compound-Fault Diagnosis

引用

IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Xu, Juan Kong, Hui Ding, Xu Yuan, Xiaohui Hefei University of Technology Key Laboratory of Knowledge Engineering With Big Data Ministry of Education School of Computer and Information Hefei230601 China University of North Texas Department of Computer Science and Engineering DentonTX76205 United States

Learning a model heavily depends on the training examples, which are sometimes difficult to obtain if not impossible. This a typically true for fault diagnosis in machinery, particularly for compound faults. The counterfactual inference reveals the causal components inherent in the fault data in an interpretable manner, divulging critical causes from the observable phenomena. This article proposes a method to address the imbalance and interpretability issues of generalized zero-shot learning (GZSL) methods for compound-fault diagnosis using counterfactual inference. Our method uses a structural causal model (SCM) to decouple and generate fault features, which enhances the capabilities of the variational autoencoder and generative adversarial network (VAE-GAN) through a strengthened discriminator, and reveals the intrinsic causal components in fault data, distinguishing key fault causes from accompanying phenomena. This enables the classification of both single and compound faults by learning from examples of single faults, easing the dependence on the examples of compound faults. Extensive experimental results show that our method, trained solely with single-fault samples, achieves a harmonic average of 87.40% accuracy for both single and compound faults, outperforming existing state-of-the-art methods. This significantly improves both the accuracy and interpretability of compound-fault diagnosis. © 1963-2012 IEEE.

关键词： Zero-shot learning

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：