检索结果-内蒙古大学图书馆

2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Jiang, Hua Shi, Qiuxia Liu, Siying Zhang, Jiuying Zhao, Qinglin Hu, Bin Gansu Provincial Key Laboratory of Wearable Computing School of Information Science and Engineering China Lanzhou University Key Laboratory of Special Functional Materials and Structural Design Ministry of Education Lanzhou China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai Institutes for Biological Sciences Chinese Academy of Sciences China Joint Research Center for Cognitive Neurosensor Technology of Lanzhou University Institute of Semiconductors Chinese Academy of Sciences China Engineering Research Center of Open Source Software and Real-Time System Lanzhou University Ministry of Education China

ISBN: (纸本)9781665468190

Electroencephalogram (EEG) equipped with high time resolution that distracted by incoherent brain sources which including ocular artifacts (OAs) generating by blinks is of great significance. Therefore, these OAs got corrected before extracting information from EEG is indispensable. Improved Moment Matching (IMM) is a high-speed denoising algorithm suitable for removing OA in multi-channel EEG, which is an improvement of the moment matching method used to remove stripe noise in hyperspectral images. On foundation of this, this paper proposes an optimization algorithm for IMM based on Gaussian decay function (IMM_G). In the first place, the construction of the reference signal is optimized via utilizing a Gaussian decay function, thereby preventing the signal distortion caused by the filter. And then, a method for judging the to-be-processed interval is proposed to realizes the individualized processing of different channels. As a result, through quantitative comparison experiments with simulated data and real data from the UAIS laboratory, it was identified that IMM_G showed less time complexity, significantly enhanced arithmetic speed and denoising consequence while the detail retention ability of the original method for the non-blinking region of multi-channel EEG data is maintained. Hence, this method could be extensively used in High-density EEG (hdEEG) OAs removal scene. © 2022 IEEE.

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Graph attention based on contextual reasoning and emotion-shift awareness for emotion recognition in conversations

引用

Complex and Intelligent Systems 2025年第7期11卷 1-20页

作者： Yang, Juan Wei, Puling Du, Xu Shen, Jun College of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430065 China Hubei Province Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan 430081 China National Engineering Research Center for E‑Learning Central China Normal University Wuhan 430079 China School of Computing and Information Technology University of Wollongong 2522 NSW Australia

Emotion recognition in conversations has recently emerged as a hot research topic owing to its increasingly important role in developing intelligent empathy services. Thoroughly exploring the conversational context and accurately capturing emotion-shift information are highly crucial for accurate emotion recognition in conversations. However, existing studies generally failed to fully understand the complex conversational context due to their insufficient capabilities in extracting and integrating emotional cues. Moreover, they mainly focused on the speaker’s emotion inertia while paying less attention to explore multi-perspective emotion-shift patterns. To address these limitations, this study proposes a novel multimodal approach, namely, GAT-CRESA (Graph ATtention based on Contextual Reasoning and Emotion-Shift Awareness). Specifically, the multi-turn global contextual reasoning module iteratively performs contextual perception and cognitive reasoning for efficiently understanding the global conversational context. Then, GAT-CRESA explores emotion-shift information among utterances from both the speaker-dependent and the global context-based perspectives. Next, the emotion-shift awareness graphs are constructed for extracting significant local-level conversational context, where edge relations are determined by the learnt emotion-shift labels. Finally, the outputs of graphs are concatenated for final emotion recognition. The loss of emotion prediction task is combined together with those of two perspective’s emotion-shift learning for guiding the training process. Experimental results show that our GAT-CRESA achieves new state-of-art records with 72.77% ACC and 72.81% wa-F1 on IEMOCAP, and 65.44% ACC and 65.04% wa-F1 on MELD, respectively. The ablation results also indicate the effectiveness and rationality of each component in our approach. © The Author(s) 2025.

关键词： Contextual reasoning Emotion recognition in conversations (ERC) Emotion-shift Graph attention

来源：评论

学校读者我要写书评

暂无评论

Optimizing Model-Driven Federated Learning for Rational and Data-Efficient in Social Mobile Network

引用

IEEE Network 2024年

作者： Lu, Jianfeng Zhang, Ying Cao, Shuqin Wang, Wei Tang, Changbing Wuhan University of Science and Technology School of Computer Science and Technology Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology China Key Laboratory of Social Computing and Cognitive Intelligence Dalian University of Technology Ministry of Education China Zhejiang Normal University College of Physics and Electronic Information Engineering Jinhua321004 China

With the rise of data-intensive services in mobile networks, the demand for intelligent and efficient learning frameworks has grown exponentially. Federated Learning (FL), as an emerging paradigm, enables decentralized edge devices to collaboratively train large models without sharing raw data, ensuring privacy preservation. However, deploying FL in resource-constrained mobile environments faces significant challenges, such as free-riding and malicious behavior. These challenges hinder model performance and raise concerns about data integrity and inter-user cooperation. To address these issues, we propose a layered dynamic framework for social mobile networks, called FedSMN, which aims to enhance the generalization ability of collaboratively trained large models in FL environments. FedSMN leverages Bayesian inference to evaluate user behavior and employs evolutionary game theory to simulate dynamic interactions, thereby optimizing cooperation strategies and reducing communication overhead. Unlike traditional approaches that assume fully rational actors, FedSMN accounts for irrational behavior and fluctuating resources, designing an efficient incentive mechanism to improve data utilization. Extensive experiments on large-scale datasets demonstrate that FedSMN increases model accuracy by 21% and reduces communication overhead by 49%, paving the way for scalable, intelligent mobile networks powered by large models. © 1986-2012 IEEE.

关键词： Collaborative learning

来源：评论

学校读者我要写书评

暂无评论

PACE: Reputation-Driven Hierarchical Incentive Mechanism for Trusted Healthcare Transactions in Model Marketplace

引用

IEEE Transactions on Consumer Electronics 2024年

作者： Lu, Jianfeng Dou, Xiaochi Rathore, Bharati Jhaveri, Rutvij H. Seid, Abegaz Mohammed Erbad, Aiman Wuhan University of Science and Technology School of Computer Science and Technology Wuhan430065 China Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System China Ministry of Education Key Laboratory of Social Computing and Cognitive Intelligence Dalian University of Technology China United Kingdom Pandit Deendayal Energy University Department of Computer Science and Engineering School of Technology India Hamad Bin Khalifa University College of Science and Engineering Doha Qatar Qatar University College of Engineering Doha Qatar

Federated learning-based model marketplaces have the potential to securely leverage healthcare data for efficient healthcare transactions. However, the willingness to participate in this marketplace is severely hindered by self-interested model sellers, who maximize their personal gains via distorting the quality of their models. To this end, we propose a rePutation-driven hierArchical inCentive mEchanism, called PACE, which combines contract cooperation and game pricing to motivate model sellers to be honest, thereby improving the sustainability of the model marketplace via two-layer cooperation. Specifically, at the training layer, we design a reward payment rule based on multidimensional contracts, while at the trading layer, we use a competitive market pricing game to develop the accuracy pricing rule. In particular, the above rules cleverly combine the fine-grained model sellers' reputations with the willingness of healthcare devices to indirectly affect the model sellers' utilities. Theoretically, we prove that PACE can effectively incentivize model sellers to truthfully report model quality while satisfying both individual rationality and incentive compatibility with a fairness guarantee. Experimental results conducted on four real-world datasets show that our PACE improves the global performance by up to 12.85% and reduces the global loss by at least 19.23% compared with the state-of-the-art baselines. © 1975-2011 IEEE.

关键词： Marketplaces

来源：评论

学校读者我要写书评

暂无评论

Noncontact Doppler Radar-based Heart Rate Detection on the SVD and ANC

Noncontact Doppler Radar-based Heart Rate Detection on the S...

引用

2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Shi, Qiuxia Hu, Bin Tian, Fuze Zhao, Qinglin Gansu Provincial Key Laboratory of Wearable Computing School of Information Science and Engineering Lanzhou University China School of Computer and Communication Lanzhou University of Technology China Key Laboratory of Special Functional Materials and Structural Design Lanzhou University Ministry of Education Lanzhou China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai Institutes for Biological Sciences Chinese Academy of Sciences China Joint Research Center for Cognitive Neurosensor Technology of Lanzhou University Institute of Semiconductors Chinese Academy of Sciences China Engineering Research Center of Open Source Software and Real-Time System Lanzhou University Ministry of Education China

ISBN: (纸本)9781665468190

In the Doppler biological radar-based applications of noncontact measurement of vital signs, effectively extracting heartbeat information from weak thoracic mechanical motion is an important problem to be solved. This study is aimed at extracting heartbeat signal via the technology combined with Short time Fourier Transform (STFT), Singular Value Decomposition (SVD) and Adaptive Noise Canceller (ANC) from radar recording. The simulated data and the data collected by Doppler radar biosensor realized in laboratory are employed to validate the proposed method. The results show that the proposed method has the ability of detection for the heart rate and heart rate variability indexes in rest state, it has certain advantages in time-consuming and detection accuracy. Therefore, the current method provides another way to process vital sign signals recorded by Doppler radar. © 2022 IEEE.

关键词： Singular value decomposition

来源：评论

学校读者我要写书评

暂无评论

Differentially Private Energy Sharing Among Smart Grid-Powered Base Stations

Differentially Private Energy Sharing Among Smart Grid-Power...

引用

IEEE Conference on Vehicular Technology (VTC)

作者： Liwan Qi Bochun Wu Fei Wang Kai Li Wei Ni Abbas Jamalipour State Key Laboratory of Integrated Chips and Systems Fudan University Shanghai China College of Physics and Electromechanical Engineering Hexi University Zhangye China University of Cambridge Cambridge U.K. Real-Time and Embedded Computing Systems Research Centre (CISTER) Porto Portugal Commonwealth Scientific and Industrial Research Organisation (CSIRO) Sydney NSW Australia School of Electrical and Information Engineering University of Sydney NSW Australia

ISBN: (数字)9798331517786

ISBN: (纸本)9798331517793

Allowing for energy sharing among base stations (BSs), we investigate a distributed BS system equipped with renewable power units and energy storage batteries. While offering significant benefits, this raises concerns about privacy protection. By leveraging the Laplace mechanism, our differential privacy (DP)-based method safeguards energy consumption data related to processing data tasks from different BSs. To address a long-term average cost minimization problem, we propose a distributed online algorithm for efficient energy sharing. We demonstrate that the boundary constraints of energy storage batteries can still be satisfied by choosing parameters appropriately. We provide a theoretical bound for the optimality gap and validate the effectiveness of our theoretical results. Numerical results indicate our algorithm can potentially reduce the average costs of BSs by up to 34%.

关键词： Renewable energy sources Privacy Energy consumption Base stations Vehicular and wireless technologies Costs Batteries Smart grids Protection Optimization

来源：评论

学校读者我要写书评

暂无评论

Offsite Evaluation of Localization Systems: Criteria, Systems, and Results From IPIN 2021 and 2022 Competitions

IEEE Journal on Indoor and Seamless Positioning and Navigati...

引用

IEEE Journal on Indoor and Seamless Positioning and Navigation 2024年 2卷 92-129页

作者： Potorti, Francesco Crivello, Antonino Lee, Soyeon Vladimirov, Blagovest Park, Sangjoon Chen, Yushi Wang, Long Chen, Runze Zhao, Fang Zhuge, Yue Luo, Haiyong Perez-Navarro, Antoni Jimenez, Antonio R. Wang, Han Liang, Hengyi De Cock, Cedric Plets, David Cui, Yan Xiong, Zhi Li, Xiaodong Ding, Yiming Franco, Fernando Javier Alvarez Polo, Fernando Jesus Aranda Rodriguez, Felipe Parralejo Moreira, Adriano Pendao, Cristiano Silva, Ivo Ortiz, Miguel Zhu, Ni Li, Ziyou Renaudin, Valerie Wei, Dongyan Ji, Xinchun Zhang, Wenchao Wang, Yan Ding, Longyang Kuang, Jian Zhang, Xiaobing Dou, Zhi Yang, Chaoqun Kram, Sebastian Stahlke, Maximilian Mutschler, Christopher Coene, Sander Li, Chenglong Venus, Alexander Leitinger, Erik Tertinek, Stefan Witrisal, Klaus Wang, Yi Wang, Shaobo Jin, Beihong Zhang, Fusang Su, Chang Wang, Zhi Li, Siheng Li, Xiaodong Li, Shitao Pan, Mengguan Zheng, Wang Luo, Kai Ma, Ziyao Gao, Yanbiao Chang, Jiaxing Ren, Hailong Guo, Wenfang Torres-Sospedra, Joaquin Pisa56124 Italy Electronics and Telecommunications Research Institute Daejeon34129 Korea Republic of Beijing University of Posts and Telecommunications School of Computer Science National Pilot Software Engineering School Beijing100876 China Chinese Academy of Sciences Beijing Key Laboratory of Mobile Computing and Pervasive Device Institute of Computing Technology Beijing100190 China Universitat Oberta de Catalunya Faculty of Computer Sciences Multimedia and Telecommunication Barcelona08035 Spain Arganda del Rey28500 Spain Huawei Technologies Company Ltd. Shenzhen100015 China IMEC-WAVES/Ghent University Department of Information Technology Gent9052 Belgium Nanjing University of Aeronautics and Astronautics College of Automation Nanjing210016 China University of Extremadura Badajoz06006 Spain University of Trás-os-Montes and Alto Douro Department of Engineering School of Sciences and Technology Vila Real5000-801 Portugal Universidade Do Minho Centro Algoritmi Guimarães4800-058 Portugal Ame Department of the University Gustave Eiffel Geoloc Laboratory Bouguenais44344 France Chinese Academy of Sciences Aerospace Information Research Institute Beijing100094 China Wuhan University Gnss Research Center Wuhan430072 China AutoNavi Software Company Ltd. China Fraunhofer Institute for Integrated Circuits Iis Fraunhofer Iis Nuremberg90411 Germany Erlangen91058 Germany Graz University of Technology Christian Doppler Laboratory for Location-Aware Electronic Systems Graz8010 Austria Institute of Software Chinese Academy of Sciences Beijing100190 China Purple Mountain Laboratories Pervasive Communication Research Center Nanjing210000 China Beijing University of Posts and Telecommunications Beijing100876 China

Indoor positioning is a thriving research area, which is slowly gaining market momentum. Its applications are mostly customized, ad hoc installations;ubiquitous applications analogous to Global Navigation Satellite System for outdoors are not available because of the lack of generic platforms, widely accepted standards and interoperability protocols. In this context, the indoor positioning and indoor navigation (IPIN) competition is the only long-term, technically sound initiative to monitor the state of the art of real systems by measuring their performance in a realistic environment. Most competing systems are pedestrian-oriented and based on the use of smartphones, but several competing tracks were set up, enabling comparison of an array of technologies. The two IPIN competitions described here include only off-site tracks. In contrast with on-site tracks where competitors bring their systems on-site - which were impossible to organize during 2021 and 2022 - in off-site tracks competitors download prerecorded data from multiple sensors and process them using the EvaalAPI, a real-time, web-based emulation interface. As usual with IPIN competitions, tracks were compliant with the EvAAL framework, ensuring consistency of the measurement procedure and reliability of results. The main contribution of this work is to show a compilation of possible indoor positioning scenarios and different indoor positioning solutions to the same problem. © 2023 CCBY.

关键词： Smartphones

来源：评论

学校读者我要写书评

暂无评论

RIPPB: A Robust and Improved PBFT Protocol for Blockchain

RIPPB: A Robust and Improved PBFT Protocol for Blockchain

引用

IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Meng Ding Heng He Rui Qiao Xiaohu Zhou School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China School of Computing Engineering and Built Environment Birmingham City University Birmingham UK

ISBN: (纸本)9781665409858

In this paper, we propose RIPPB, a robust and improved PBFT protocol for Blockchain, to improve the quality of service for blockchain applications. At RIPPB, we introduce reputation for nodes and use reputation as the voting weight for node consensus to go against Sybil attacks. And we design a novel improved logistic regression model to assign reputations to nodes based on their behavior involved in block generation. With this model, nodes performing Stake-grinding attacks and Bribery attacks, face high reputation penalties, which is unacceptable for malicious nodes to reduce the probability of launching these attacks. In addition, RIPPB adds a pre-commit phase to the PBFT algorithm to reduce the number of inter-node communications, thus improving the performance of the protocol. Cost-of-attack analysis shows the high robustness of our protocol. Experimental results show a 28% improvement in the throughput of our protocol over PBFT.

关键词： Industrial electronics Protocols Quality of service Throughput Robustness Blockchains Behavioral sciences

来源：评论

学校读者我要写书评

暂无评论

Integration of a novel attribute and classical topology metrics of hyper-networks for automatic diagnosis of Major depressive disorder 22

Integration of a novel attribute and classical topology metr...

引用

22nd IEEE International Conference on E-Health Networking, Application and Services, HEALTHCOM 2020

作者： Li, Yongchao Chen, Nan Wang, Yin Yang, Lin Zheng, Weihao Yao, Zhijun Hu, Bin Gansu Province Key Laboratory of Wearable Computing School of Information Science and Engineering Lanzhou University Lanzhou China College of Biomedical Engineering and Instrument Science Zhejiang University Zhejiang China CAS Center for Excellence in Brain Science and Intelligence Technology Shanghai Institutes for Biological Sciences Chinese Academy of Sciences Shanghai China Joint Research Center for Cognitive Neurosensor Technology of Lanzhou University Institute of Semiconductors Chinese Academy of Sciences Lanzhou China Engineering Research Center of Open Source Software and Real-Time System Lanzhou University Ministry of Education Lanzhou China

ISBN: (纸本)9781728162676

Conventional hyper-network coefficients ignore the weighted hyper-edge information which could be vital in researching the specificity of brain disease. Functional hyper-networks for 64 healthy controls (HC) and 56 patients with major depressive disorder (MDD) were constructed using the least absolute shrinkage and selection operator (Lasso). Not only the classical topology metrics but also a novel hyper-edge weight (HEW) attribute were extracted as features to promote the functional-based auto-diagnosis accuracy of MDD. We compared the categorization performance of each hyper-network coefficient. A multi-feature ensemble model was applied to fuse different kinds of features. We obtained 82.15 % accuracy with the classical hyper-network clustering coefficient (HCC) and 84.08 % accuracy with the HEW attribute on the MDD dataset. The performance was further improved to 89.24% by combining all the properties of the hyper-networks. The multi-feature ensemble model combining different hyper-network coefficients provides new insights into the automatic diagnosis with diverse information of MDD. © 2021 IEEE.

关键词： Topology

来源：评论

学校读者我要写书评

暂无评论

Integration of a novel attribute and classical topology metrics of hyper-networks for automatic diagnosis of Major depressive disorder

Integration of a novel attribute and classical topology metr...

引用

International Conference on e-health Networking, Applications and Services (HealthCom)

作者： Yongchao Li Nan Chen Yin Wang Lin Yang Weihao Zheng Zhijun Yao Bin Hu Gansu Province Key Laboratory of Wearable Computing School of information science and Engineering Lanzhou University Lanzhou China College of Biomedical Engineering and Instrument Science Zhejiang University Zhejiang China Engineering Research Center of Open Source Software and Real-Time System(Lanzhou University) Ministry of Education Lanzhou China

ISBN: (数字)9781728162676

ISBN: (纸本)9781728162683

关键词： Measurement Fuses Diversity reception Feature extraction Depression Topology Diseases

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：