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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Bao, Cong Zheng, Weihao Zhang, Qin Yang, Songyu Yao, Zhijun Hu, Bin Gansu Provincial Key Laboratory of Wearable Computing School of Information Science and Engineering Lanzhou University Lanzhou China School of Medical Technology Beijing Institute of Technology Beijing 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

ISBN: (纸本)9798350337488

Functional magnetic resonance imaging (fMRI) plays a vital role in brain science as it measures and maps brain activity through the analysis of blood flow changes, offering valuable insights into cognitive functions and neural processes. However, due to the intricacy and dynamism of brain activity, conventional approaches failed to accurately predict the blood oxygen level-dependent (BOLD) time series in fMRI data. To tackle this issue, we proposed an end-to-end adversarial U-network (AUN) to verify the predictability of existing BOLD signals in primary cortex (i.e., primary visual, primary motor and primary sensory) and higher cortex(i.e., dorsolateral prefrontal and posterior cingulate). The model combined the U-network architecture and adversarial strategy to ensure that the predicted results capture both the intricate nonlinear details and the overall distribution characteristics. We performed the experiment using the Human Connectome Project (HCP) database. The results demonstrated the predictability of both primary and higher cortex, with primary cortex showing higher predictability. Additionally, the AUN performed better than other popular methods. We also found the improvement in dynamic functional connectivity (dFC) metrics through accurate prediction. The above results confirm the feasibility of predicting BOLD signals and their potential application in clinical settings.1 © 2023 IEEE.

关键词： adversarial paradigm blood oxygen level-dependent series prediction dynamic functional connectivity functional magnetic resonance imaging

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Two-Stage Hand-Eye Calibration based on Variance Minimization Principle

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Ding, Tao Tian, Dazhuang Wu, Hao Zhu, Dahu Li, Wenlog Wuhan University of Technology Hubei Key Laboratory of Advanced Technology for Automotive Components School of Automotive Engineering Wuhan430070 China Wuhan University of Technology Hubei Digital Manufacturing Key Laboratory School of Mechanical and Electronic Engineering Wuhan430070 China Wuhan University of Technology Hubei Key Laboratory of Advanced Technology for Automotive Components Hubei Provincial Engineering Research Center of Robot and Intelligent Manufacturing Wuhan430070 China Huazhong University of Science and Technology State Key Laboratory of Intelligent Manufacturing Equipment and Technology Wuhan430074 China

Hand-eye calibration in industrial scenarios greatly determines the efficiency and effectiveness of 3D vision-guided robotic tasks. Most of the existing hand-eye calibration methods, however, rely on collecting large-scale point cloud samples to guarantee high measurement accuracy, which is time-consuming and particularly influenced by measurement defects such as local missing, noise, and uneven density. To overcome this challenging problem, we present a novel two-stage hand-eye calibration method based on the variance minimization principle. In the first stage, a robust function weighted variance minimization (RFWVM) registration algorithm is proposed for fine registration of defective point clouds, aiming at solving the coarse hand-eye calibration matrix with few-shot point clouds. In the second stage, an objective function of the calibration error correction algorithm is established via the point-to-plane distance variance minimization, which is intended to suppress the influence of measurement defects. Through these two stages, the globally optimal hand-eye matrix is solved by iteratively correcting the coarse hand-eye calibration matrix. A series of experiments validate the universality, accuracy, and robustness of the proposed method. © 1963-2012 IEEE.

关键词： Error correction

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Deformable registration framework for glioma images with absent correspondence based on auxiliary-image-aided intensity-consistency constraint

Deformable registration framework for glioma images with abs...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Tang, Kun Wang, Lihui Yang, Menglong Xu, Jingwen Cheng, Xinyu Zhang, Jian Zhu, Yuemin Wei, Hongjiang Ministry of Education State Key Laboratory of Public Big Data College of Computer Science and Technology Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province Engineering Research Center of Text Computing & Cognitive Intelligence Guiyang China Univ Lyon Insa Lyon Cnrs Inserm Creatis Umr 5220 U1206 Lyon France Shanghai Jiao Tong University School of Biomedical Engineering Shanghai200240 China

ISBN: (纸本)9798350386226

Considering the tumor aggressive nature and the significant changes in anatomical structure, aligning the preoperative and follow up scans of glioma patients remains a challenge due to the presence of regions with absent correspondence. To address this challenge, this work proposed a novel bidirectional unsupervised deformable image registration framework for image pairs with missing correspondence based on an auxiliary-image-aided intensity-consistency constraint (ICC) strategy. Specifically, for any fixed and moving image pairs, we introduced an auxiliary image and warped it directly to fixed/moving image or warped it twice through a transition of moving/fixed image. By comparing the difference between these warped images, the weighting maps to identify and exclude regions with absent correspondence between fixed and moving image pairs can be generated. To verify the effectiveness of the proposed framework, we combined it with several deep learning-based registration models and tested it on BraTS-Reg challenge dataset, the results demonstrated that the proposed ICC strategy can improve the registration performance for all the models, with the improvement of average target registration error (TRE) and success rate (SR) being up to 44.9% and 66.7%, respectively. Comparing against the best existing forward-backward consistency strategy for dealing with missing correspondence registration, our auxiliary-image-aided ICC strategy can also decrease average TRE by 2.9%, demonstrating the superiority of the proposed framework. The present work is not limited to the glioma images, it can be used to address the registration problems for any image pairs with absent correspondence or inconsistent intensity. © 2024 IEEE.

关键词： Image registration

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Exploring Prompt-based Multi-task Learning for Multimodal Dialog State Tracking and Immersive Multimodal Conversation 11

Exploring Prompt-based Multi-task Learning for Multimodal Di...

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11th Dialog System technology Challenge, DSTC 2023

作者： Chen, Yirong Li, Ya Wang, Tao Xing, Xiaofen Xu, Xiangmin Liu, Quan Liu, Cong Hu, Guoping Guangdong Provincial Key Laboratory of Human Digital Twin School of EE South China University of Technology Guangzhou China iFLYTEK Research Hefei China Pazhou Lab. Guangzhou China School of Future Technology South China University of Technology Guangzhou China State Key Laboratory of Cognitive Intelligence Hefei China National Engineering Research Center of Speech and Language Information Processing Hefei China

With the rise of the metaverse, immersive multimodal conversation has attracted more and more researchers’ attention. Multimodal contexts will become more important for human-computer interaction in the metaverse, especially in shopping domain. Unlike traditional conversation tasks, immersive multimodal conversation has challenges such as multimodal ambiguous candidate identification and multimodal coreference resolution, which makes it more difficult to dialog state tracking and response generation, as described in SIMMC 2.1 challenge, a part of DSTC11. In particular, as the number of objects in the scene increases, the difficulty will increase dramatically. We proposed PMTLED (Prompt-based Multi-Task Learning Encoder-Decoder), in which different subtasks use different prompts to make the model tend to focus on the current subtask. We achieve the winner in ambiguous candidates indentification and runner-up in multimodal coreference resolution (MM-Coref), multimodal dialog state tracking (MM-DST) and assistant response generation. Our code and model are made publicly available at https://***/scutcyr/dstc11-simmc2.1-scut-bds-lab. © 2023 Association for Computational Linguistics.

关键词： Human computer interaction

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Restoration of Defective Cloud Images from Meteorological Satellites

Restoration of Defective Cloud Images from Meteorological Sa...

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2023 China Automation Congress, CAC 2023

作者： Xu, Ruiyao Zhou, Zhixuan Zhao, Xintong Wang, Congcong Liu, Ding School of Mechano-Electronic Engineering Xidian University Xi'an710071 China Hangzhou Institute of Technology Xidian University Intelligent Robot Laboratory Hangzhou311231 China Beijing Global Metroute Technology Co. Ltd Huafeng Weather Media Group Beijing10081 China Ministry of Education Engineering Research Center of Learning-Based Intelligent System School of Computer Science and Engineering Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9798350303759

Meteorological satellites are inevitably disturbed in information transmission, which leads to missing bars on the cloud images and thus makes it impossible for meteorologists to give accurate weather predictions. The UNet-like networks have a hierarchical feature map to obtain rich multi-scale contextual features. In addition, they can enhance the image reconstruction process using jump connections between the encoder and decoder. Therefore, based on deep learning theory, this paper proposes a method to restore defective satellite images using UNet and Swin-U'Net, which are both in shape of 'U'. Moreover, the work selects the infrared satellite cloud image ir107 in the SEVIR dataset as the base dataset, from which the defective dataset is artificially generated. By comparing the restoration results of the two networks, the work concludes that the UNet network performs better than the Swin-UNet network in the image restoration function, which verifies the effectiveness of the network in the image restoration function. © 2023 IEEE.

关键词： Image reconstruction

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Natural Human Skin‑Inspired Wearable and Breathable Nanofiber‑based Sensors with Excellent Thermal Management Functionality

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Advanced Fiber Materials 2024年第6期6卷 1955-1968页

作者： Peng Wang Xiaodan Li Guifen Sun Guoqing Wang Qing Han Chuizhou Meng Zhonghe Wei Yang Li School of Mechanical Engineering University of JinanJinan 250022China School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China State Key Laboratory for Reliability and Intelligence of Electrical Equipment Engineering Research Center of Ministry of Education for Intelligent Rehabilitation Device and Detection TechnologyHebei Key Laboratory of Smart Sensing and Human‑Robot InteractionSchool of Mechanical EngineeringHebei University of TechnologyTianjin 300401China Shandong Provincial Key Laboratory of Network‑Based Intelligent Computing School of Information Science and EngineeringUniversity of JinanJinan 250022China Network Information Center Department of Computer ScienceQilu University of Technology(Shandong Academy of Sciences)Jinan 250353China School of Integrated Circuits Shandong UniversityJinan 250101China

Wearable sensors have been rapidly developed for application in various human monitoring ***,the wearing comfort and thermal properties of these devices have been largely ignored,and these characteristics urgently need to be ***,we develop a wearable and breathable nanofiber-based sensor with excellent thermal management functionality based on passive heat preservation and active Joule heating *** multifunctional device consists of a micropatterned carbon nanotube(CNT)/thermoplastic polyurethane(TPU)nanofiber electrode,a microporous ionic aerogel electrolyte and a microstructured Ag/TPU nanofiber *** to the presence of a supercapacitive sensing mechanism and the appli-cation of microstructuration,the sensor shows excellent sensing performance,with a sensitivity of 24.62 ***,due to the overall porous structure and hydrophobicity of TPU,the sensor shows good breathability(62 mm/s)and water repellency,with a water contact angle of 151.2°.In addition,effective passive heat preservation is achieved by combining CNTs with high solar absorption rates(85%)as the top layer facing the outside,aerogel with a low thermal conductivity(0.063 W m-1 k-1)as the middle layer for thermal insulation,and Ag with a high infrared reflectance rate as the bottom layer facing the *** warming,this material yields a higher temperature than ***,the active Joule heat-ing effect is realized by applying current through the bottom resistive electrode,which can quickly increase the temperature to supply controlled warming on *** proposed wearable and breathable sensor with tunable thermal properties is promising for monitoring and heat therapy applications in cold environments.

关键词： Wearable sensor Breathable Personal thermal management Electrospun nanofibers Joule heating

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Semantic-Aware Dual Contrastive Learning for Multi-Label Image Classification 26

Semantic-Aware Dual Contrastive Learning for Multi-Label Ima...

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26th European Conference on Artificial Intelligence, ECAI 2023

作者： Ma, Leilei Sun, Dengdi Wang, Lei Zhao, Haifeng Luo, Bin School of Computer Science and Technology Anhui University China School of Artificial Intelligence Anhui University China School of Computer Science and Engineering Nanjing University of Science and Technology China Anhui Provincial Key Laboratory of Multimodal Cognitive Computing Anhui University China Institute of Artificial Intelligence Hefei Comprehensive National Science Center China

ISBN: (纸本)9781643684369

Extracting image semantics effectively and assigning corresponding labels to multiple objects or attributes for natural images is challenging due to the complex scene contents and confusing label dependencies. Recent works have focused on modeling label relationships with graph and understanding object regions using class activation maps (CAM). However, these methods ignore the complex intra- and inter-category relationships among specific semantic features, and CAM is prone to generate noisy information. To this end, we propose a novel semantic-aware dual contrastive learning framework that incorporates sample-to-sample contrastive learning (SSCL) as well as prototype-to-sample contrastive learning (PSCL). Specifically, we leverage semantic-aware representation learning to extract category-related local discriminative features and construct category prototypes. Then based on SSCL, label-level visual representations of the same category are aggregated together, and features belonging to distinct categories are separated. Meanwhile, we construct a novel PSCL module to narrow the distance between positive samples and category prototypes and push negative samples away from the corresponding category prototypes. Finally, the discriminative label-level features related to the image content are accurately captured by the joint training of the above three parts. Experiments on five challenging large-scale public datasets demonstrate that our proposed method is effective and outperforms the state-of-the-art methods. Code and supplementary materials are released on https://***/yu-gi-oh-leilei/SADCL. © 2023 The Authors.

关键词： Image classification

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Developing a Multi-site Hyperscanning Procedure for Investigating Interbrain Synchrony Underlying Remote Social Interaction 17th

Developing a Multi-site Hyperscanning Procedure for Investig...

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17th International Conference on Brain Informatics, BI 2024

作者： Limtragooltongchai, Sirapakit Yamtuan, Kawin Gracia, Javier O. Chunharas, Chaipat Sriravanasan, Ramesh Chaisilprungraung, Thitaporn Itthipuripat, Sirawaj Neuroscience Center for Research and Innovation King Mongkut’s University of Technology Thonburi Bangkok Thailand Institute of Field Robotics King Mongkut’s University of Technology Thonburi Thonburi Thailand DEVCOM Army Research Laboratory Humans in Complex Systems Division AdelphiMD United States Chula Neuroscience Center King Chulalongkorn Memorial Hospital Thai Red Cross Society Bangkok10330 Thailand Cognitive Clinical and Computational Neuroscience Department of Internal Medicine Faculty of Medicine Chulalongkorn University Bangkok10330 Thailand Department of Cognitive Sciences University of California IrvineCA United States Department of Biomedical Engineering University of California IrvineCA United States Department of Computer Engineering King Mongkut’s University of Technology Thonburi Bangkok10600 Thailand

ISBN: (纸本)9789819632930

EEG hyperscanning provides novel insights into inter-brain connectivity during social interactions by enabling the simultaneous recording of neural activity from multiple individuals. This research aims to develop and validate a new protocol in which dyads engage in a synchronized button-pressing task across both same-location and multi-location setups. Our findings reveal significantly higher interpersonal neural synchronization during the interaction period compared to the baseline. Notably, the increased neural synchronization is comparable across the same- and multi-location setups, spanning frontal, central, and posterior electrodes. Interestingly, the level of synchronization in the multi-location setup is greater than in the same-location setup over electrodes positioned above the right superior temporal gyrus (STG), a region associated with social cognition and the mirror neuron system (MNS). These findings validate our methodology for studies across different locations and open new avenues for research into inter-brain synchronization in remote environments. Our experimental protocol could enhance the design of experiments and applications involving social interaction, particularly in remote settings, which have gained popularity due to COVID-19. It also advances our understanding of the neural mechanisms that support social communication in the new normal era. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Economic and social effects

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A promising approach for quantifying focal stroke modeling and assessing stroke progression:optical resolution photoacoustic microscopy photothrombosis

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Neural Regeneration Research 2025年第7期20卷 2029-2037页

作者： Xiao Liang Xingping Quan Xiaorui Geng Yujing Huang Yonghua Zhao Lei Xi Zhen Yuan Ping Wang Bin Liu Faculty of Health Sciences University of MacaoMacao Special Administrative RegionChina Center for Cognitive and Brain Sciences University of MacaoMacao Special Administrative RegionChina Department of Biomedical Engineering Southern University of Science and TechnologyShenzhenGuangdong ProvinceChina State Key Laboratory of Quality Research in Chinese Medicine Institute of Chinese Medical SciencesUniversity of MacaoTaipaMacao Special Administrative RegionChina Department of Emergency Zhujiang HospitalSouthern Medical UniversityGuangzhouGuangdong ProvinceChina

To investigate the mechanisms underlying the onset and progression of ischemic stroke,some methods have been proposed that can simultaneously monitor and create embolisms in the animal cerebral ***,these methods often require complex systems and the effect of age on cerebral embolism has not been adequately studied,although ischemic stroke is strongly *** this study,we propose an optical-resolution photoacoustic microscopy-based visualized photothrombosis methodology to create and monitor ischemic stroke in mice simultaneously using a 532 nm pulsed *** observed the molding process in mice of different ages and presented age-dependent vascular embolism ***,we integrated optical coherence tomography angiography to investigate age-associated trends in cerebrovascular variability following a *** imaging data and quantitative analyses underscore the differential cerebrovascular responses to stroke in mice of different ages,thereby highlighting the technique's potential for evaluating cerebrovascular health and unraveling age-related mechanisms involved in ischemic strokes.

关键词： age-dependent cerebral cortex ischemic stroke mouse model optical coherence tomography angiography photoacoustic microscopy photothrombosis vascular imaging

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Design of readout circuit for high sampling miniaturized MEMS wall shear force sensor

Design of readout circuit for high sampling miniaturized MEM...

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2022 International Symposium on Sensor technology and Control, ISSTC 2022

作者： Guo, ZhiJiang Guo, Hui Hui Liu, Tingting Gao, Yang School of Information Engineering Southwest University of Science and Technology Mianyang621010 China Robot Technology Used for Special Environment Key Laboratory of Sichuan Province Mianyang621010 China Microsystems Center Southwest University of Science and Technology Mianyang621010 China

Wall shear stress is one of the important measurement parameters in wind tunnel experiments. In the shock wind tunnel, the duration of the flow field is very short, usually a few milliseconds. To ensure measurement accuracy, the sampling rate should not be less than 1kHz. Due to the limitation of model volume and experimental environment, it is necessary to design a miniaturized readout circuit with high precision and high sampling rate, which is highly integrated with the MEMS wall shear stress sensor. The circuit includes a micro capacitance detection module integrated with the sensor head and a host computer signal processing and display module. Aiming at the complex measurement environment of the shock tunnel, to ensure the measurement accuracy, stability, and anti-interference ability of the weak capacitance detection circuit, a miniaturized ceramic substrate circuit is fabricated by a microstrip circuit process. The test results show that the resolution of the micro capacitance of the circuit can reach 20fF at the detection frequency of 3kHz, which can meet the measurement requirements of Shock tunnel, and realize the real-Time measurement and display of wall shear stress signal. © Published under licence by IOP Publishing Ltd.

关键词： Capacitance

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