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IEEE International Conference on Systems, Man and Cybernetics

作者： Haruka Kawasaki Satoshi Nishida Ichiro Kobayashi Advanced Sciences GS of Humanities and Sciences Ochanomizu University Tokyo Japan Center for Information and Neural Networks (CiNet) Advanced ICT Research Institute National Institute of Information and Communications Technology (NICT) Osaka Japan

This study aims to clarify how functional network hubs change during hierarchical visual processing in the human brain through the estimation of brain states from features extracted using a convolutional neural network (CNN), a hierarchical model of image processing. We used representational similarity analysis for brain states predicted through encoding models based on feature representations at each layer of the CNN, and applied the PageRank algorithm to matrices converted from the generated representational dissimilarity matrices to capture the hub characteristics of brain region-related systems. This succeeded in capturing changes in the hubness of interregional brain coordination during hierarchical information processing in the human cerebral cortex in visual processing. Specifically, we found that the hubness of the occipital visual cortex increased in the early phase of visual processing, and that the hubness of the prefrontal cortex and temporal lobe increased in the late phase of visual processing. From the above, we found that our proposed method allows us to capture hierarchical changes in the hubness of interregional coordination.

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Speech-driven Personalized Gesture Synthetics: Harnessing Automatic Fuzzy Feature Inference

TechRxiv

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TechRxiv 2024年

作者： Zhang, Fan Wang, Zhaohan Lyu, Xin Zhao, Siyuan Li, Mengjian Geng, Weidong Ji, Naye Du, Hui Gao, Fuxing Wu, Hao Li, Shunman Faculty of Humanities and Arts Macau University of Science and Technology China The College of Media Engineering Communication University of Zhejiang China Research Center for Artificial Intelligence and Fine Arts Zhejiang Lab Zhejiang China School of Animation and Digital Arts Communication University of China Beijing China College of Computer Science and Technology Zhejiang University The Research Center for Artificial Intelligence and Fine Arts Zhejiang Lab Zhejiang China College of Media Engineering Communication University of Zhejiang China Zhejiang Institute of Economics and Trade Zhejiang China

Speech-driven gesture generation is an emerging field within virtual human creation. However, a significant challenge lies in accurately determining and processing the multitude of input features (such as acoustic, semantic, emotional, personality, and even subtle unknown features). Traditional approaches, reliant on various explicit feature inputs and complex multimodal processing, constrain the expressiveness of resulting gestures and limit their applicability. To address these challenges, we present Persona-Gestor, a novel end-to-end generative model designed to generate highly personalized 3D full-body gestures solely relying on raw speech audio. The model combines a fuzzy feature extractor and a non-autoregressive Adaptive Layer Normalization (AdaLN) transformer diffusion architecture. The fuzzy feature extractor harnesses a fuzzy inference strategy that automatically infers implicit, continuous fuzzy features. These fuzzy features, represented as a unified latent feature, are fed into the AdaLN transformer. The AdaLN transformer introduces a conditional mechanism that applies a uniform function across all tokens, thereby effectively modeling the correlation between the fuzzy features and the gesture sequence. This module ensures a high level of gesture-speech synchronization while preserving naturalness. Finally, we employ the diffusion model to train and infer various gestures. Extensive subjective and objective evaluations on the Trinity, ZEGGS, and BEAT datasets confirm our model’s superior performance to the current state-of-the-art approaches. Persona-Gestor improves the system’s usability and generalization capabilities, setting a new benchmark in speech-driven gesture synthesis and broadening the horizon for virtual human technology. Supplementary videos and code can be accessed at https://***/Diffmotion-v2-website/. © 2024, CC BY.

关键词： Semantics

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Deep Transfer Learning Driven Automated Fall Detection for Quality of Living of Disabled Persons

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Computers, Materials & Continua 2023年第3期74卷 6719-6736页

作者： Nabil Almalki Mrim M.Alnfiai Fahd N.Al-Wesabi Mesfer Alduhayyem Anwer Mustafa Hilal Manar Ahmed Hamza King Salman Center for Disability Research RiyadhSaudi Arabia Department of Special Education College of EducationKing Saud UniversityRiyadh12372Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Computer Science College of Science&ArtsKing Khaled UniversitySaudi Arabia Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Mobile communication and the Internet of Things(IoT)technologies have recently been established to collect data from human beings and the *** data collected can be leveraged to provide intelligent services through different *** is an extreme challenge to monitor disabled people from remote *** is because day-to-day events like falls heavily result in *** a person with disabilities,a fall event is an important cause of mortality and post-traumatic ***,detecting the fall events of disabled persons in smart homes at early stages is essential to provide the necessary support and increase their survival *** current study introduces a Whale Optimization Algorithm Deep Transfer Learning-DrivenAutomated Fall Detection(WOADTL-AFD)technique to improve the Quality of Life for persons with *** primary aim of the presented WOADTL-AFD technique is to identify and classify the fall events to help disabled *** attain this,the proposed WOADTL-AFDmodel initially uses amodified SqueezeNet feature extractor which proficiently extracts the feature *** addition,the WOADTLAFD technique classifies the fall events using an extreme Gradient Boosting(XGBoost)*** the presented WOADTL-AFD technique,the WOA approach is used to fine-tune the hyperparameters involved in the modified SqueezeNet *** proposedWOADTL-AFD technique was experimentally validated using the benchmark datasets,and the results confirmed the superior performance of the proposedWOADTL-AFD method compared to other recent approaches.

关键词： Quality of living disabled persons intelligent models deep learning fall detection whale optimization algorithm

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Resting-state electroencephalography theta predicts neurofeedback treatment 4-month follow-up response in nicotine addiction

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General Psychiatry 2023年第4期36卷 303-311页

作者： Qiujian Meng Ying Zhu Ye Yuan Li Yang Jiafang Liu Xiaochu Zhang Junjie Bu Department of Intelligent Medical Engineering School of Biomedical EngineeringAnhui Medical UniversityHefeiAnhuiChina Department of Psychology School of Mental Health and Psychological SciencesAnhui Medical UniversityHefeiAnhuiChina Department of Psychology School of Humanities&Social ScienceUniversity of Science&Technology of ChinaHefeiAnhuiChina Department of Radiology the First Affiliated Hospital of USTCHefei National Research Center for Physical Sciences at the Microscale and School of Life ScienceDivision of Life Science and MedicineUniversity of Science&Technology of ChinaHefeiAnhuiChina Application Technology Center of Physical Therapy to Brain Disorders Institute of Advanced TechnologyUniversity of Science&Technology of ChinaHefeiAnhuiChina Institute of Health and Medicine Hefei Comprehensive Science CenterHefeiAnhuiChina

Background The high rate of long-term relapse is a major cause of smoking cessation ***,neurofeedback training has been widely used in the treatment of nicotine addiction;however,approximately 30%of subjects fail to benefit from this *** previous randomised clinical trial(RCT)examined cognition-guided neurofeedback and demonstrated a significant decrease in daily cigarette consumption at the 4-month ***,significant individual differences were observed in the 4-month follow-up effects of decreased cigarette ***,it is critical to identify who will benefit from *** We examined whether the resting-state electroencephalography(EEG)characteristics from pre-neurofeedback predicted the 4-month follow-up effects and explored the possible *** This was a double-blind RCT.A total of 60 participants with nicotine dependence were randomly assigned to either the real-feedback or yoked-feedback *** underwent 6 min closed-eye resting EEG recordings both before and after two neurofeedback sessions.A follow-up assessment was conducted after 4 *** The frontal resting-state theta power spectral density(PSD)was significantly altered in the real-feedback group after two neurofeedback *** theta PSD in the real-feedback group before neurofeedback was the only predictor of decreased cigarette consumption at the 4-month *** reliability analysis revealed a significant positive correlation between theta PSD pre-neurofeedback and post-neurofeedback.A leave-one-out cross-validated linear regression of the theta PSD pre-neurofeedback demonstrated a significant correlation between the predicted and observed reductions in cigarette consumption at the 4-month ***,source analysis revealed that the brain mechanisms of the theta PSD predictor were located in the orbital frontal *** Our study demonstrated changes in the resting-state theta PSD

关键词： nicotine addiction treatment

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DiM-Gestor: Co-Speech Gesture Generation with Adaptive Layer Normalization Mamba-2

arXiv

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arXiv 2024年

作者： Zhang, Fan Zhao, Siyuan Ji, Naye Wang, Zhaohan Wu, Jingmei Gao, Fuxing Ye, Zhenqing Yan, Leyao Dai, Lanxin Geng, Weidong Lyu, Xin Zhao, Bozuo Yu, Dingguo Du, Hui Hu, Bin School of Media Engineering Communication University of Zhejiang China School of Broadcast Announcing Arts Communication University of Zhejiang China Faculty of Humanities and Arts Macau University of Science and Technology China School of Animation and Digital Arts Communication University of China Beijing China College of Computer Science and Technology Zhejiang University The Research Center for Artificial Intelligence and Fine Arts Zhejiang Lab Zhejiang China Changjiang Academy of Art and Design Shantou University China

Speech-driven gesture generation using transformer-based generative models represents a rapidly advancing area within virtual human creation. However, existing models face significant challenges due to their quadratic time and space complexities, limiting scalability and efficiency. To address these limitations, we introduce DiM-Gestor, an innovative end-to-end generative model leveraging the Mamba-2 architecture. DiM-Gestor features a dual-component framework: (1) a fuzzy feature extractor and (2) a speech-to-gesture mapping module, both built on the Mamba-2. The fuzzy feature extractor, integrated with a Chinese Pre-trained Model and Mamba-2, autonomously extracts implicit, continuous speech features. These features are synthesized into a unified latent representation and then processed by the speech-to-gesture mapping module. This module employs an Adaptive Layer Normalization (AdaLN)-enhanced Mamba-2 mechanism to uniformly apply transformations across all sequence tokens. This enables precise modeling of the nuanced interplay between speech features and gesture dynamics. We utilize a diffusion model to train and infer diverse gesture outputs. Extensive subjective and objective evaluations conducted on the newly released Chinese Co-Speech Gestures dataset corroborate the efficacy of our proposed model. Compared with Transformer-based architecture, the assessments reveal that our approach delivers competitive results and significantly reduces memory usage—approximately 2.4 times—and enhances inference speeds by 2 to 4 times. Additionally, we released the CCG dataset, a Chinese Co-Speech Gestures dataset, comprising 15.97 hours (six styles across five scenarios) of 3D full-body skeleton gesture motion performed by professional Chinese TV broadcasters. © 2024, CC BY.

关键词： Mapping

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An IoT-Based Microservice Platform for Virtual Puppetry Performance

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IEEE Access 2023年 11卷 103014-103032页

作者： Luo, Helin Lin, Yi-Bing Liao, Chen-Chi Huang, Yung-Hui Academia Sinica Research Center for Information Technology Innovation Taipei115 Taiwan Tainan National University of the Arts Graduate Institute of Animation and Film Art Tainan720 Taiwan National Yang Ming Chiao Tung University Department of Computer Science and Engineering Hsinchu300 Taiwan China Medical University College of Humanities and Sciences Taichung406 Taiwan National Cheng Kung University Miin Wu School of Computing Tainan701 Taiwan Asia University Department of Computer Science and Information Engineering Taichung413 Taiwan

This study proposes a web-based real-time remote-controlled virtual puppetry (avatar) performance platform called AvatarTalk to combine traditional Taiwanese puppetry, the Internet of Things (IoT), and 3D avatar models. AvatarTalk enables puppeteers to control avatar puppets on the web using either motion capture gloves or camera-based image recognition. This transformative performance approach not only facilitates remote performances and multi-screen presentations across various devices but also introduces a fresh gesture interpretation technique for dance artists. AvatarTalk supports a mechanism that can accommodate new control and puppet devices from other approaches through the IoT-based microservice concept. We develop a calibration procedure to enable the accurate capture of hand gestures to manipulate the movements of virtual puppets, empowering them to perform fundamental traditional puppetry poses such as nodding, bowing, and synchronized hand movements. We have conducted experiments to show the accuracy of AvatarTalk calibration. Our study indicates that AvatarTalk can almost detect the right gestures (98.75%-100% recall) and very seldom mistake the wrong gestures (90.8%-100% precision). Additionally, we also provide the mechanism to measure the delays of controlling the puppets. An analytic model is proposed to design the delay times of the messages between the control device of a puppeteer and the AvatarTalk server. In the current AvatarTalk implementation, if the message delay does not exceed 0.1 seconds, four puppeteers can synchronize their actions if the elapsed time between two actions of a puppeteer is longer than 0.3 second. © 2013 IEEE.

关键词： Internet of things

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Regulating microstructure and composition by carbonizing in-situ grown metal-organic frameworks on cotton fabrics for boosting electromagnetic wave absorption

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Nano research 2024年第8期17卷 7290-7300页

作者： Jie Jin Hongsen Long Hu Liu Yan Guo Tiantian Bai Ben Bin Xu Mohammed A.Amin Hua Qiu Mohamed H.Helal Chuntai Liu Changyu Shen Zeinhom M.El-Bahy Zhanhu Guo State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentNational Engineering Research Center for Advanced Polymer Processing TechnologyZhengzhou UniversityZhengzhou 450002China China State Key Laboratory of Powder Metallurgy Central South UniversityChangsha 410000China School of Electronic Engineering North China University of Water Resources and Electric PowerZhengzhou 450046China Complex Conditions of High-end Tire Technology Innovation Center Shuguang Rubber Industry Research&Design Institute Co.LtdGuilin 541004China Integrated Composites Lab Department of Mechanical and Civil EngineeringNorthumbria UniversityNewcastle Upon TyneNE18STUK Department of Chemistry College of ScienceTaif UniversityP.O.Box 11099Taif 21944Saudi Arabia Shaanxi Key Laboratory of Macromolecular Science and Technology School of Chemistry and Chemical EngineeringNorthwestern Polytechnical UniversityXi’an 710072China Department of Chemistry Faculty of Arts and ScienceNorthern Border UniversityRafha 73213Saudi Arabia Department of Chemistry Faculty of ScienceAl-Azhar UniversityNasr City 11884CairoEgypt

High-temperature carbonized metal-organic frameworks(MOFs)derivatives have demonstrated their superiority for promising electromagnetic wave(EMW)absorbers,but they still suffer from limited EMW absorption capacity and narrow *** the advantage of microstructure and chemical composition regulation for the design of EMW absorber,hierarchical heterostructured MoS_(2)/CoS_(2)-Co_(3)O_(4)@cabonized cotton fabric(CF)(MCC@CCF)is prepared by growing ZIF-67 MOFs onto CF surface,chemical etching,and *** from the dual loss mechanism of magnetic-dielectric multicomponent carbonized MOFs,chemical etching and carbonization process can effectively introduce abundant micro-gap structure that can result in better impedance matching and stronger absorption capacity via internal reflection,doped heteroatoms(Mo,N,S)to supply additional dipolar polarization loss,and numerous heterointerfaces among MoS_(2),CoS_(2),Co_(3)O_(4),and CCF that produce promoted conduction loss and interfacial polarization ***,a minimal reflection loss of−52.87 dB and a broadest effective absorption bandwidth of 6.88 GHz were achieved via tunning the sample thickness and filler loading,showing excellent EMW absorption *** research is of great value for guiding the research on MOFs derivatives based EMW absorbing materials.

关键词： metal-organic frameworks hierarchical structure chemical etching sulfurization electromagnetic wave absorption

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Crystalline carbon nitride derived self-assembly composite membranes with enhanced self-cleaning performance toward dye/salt separation

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Journal of Environmental Management 2025年 388卷 125943页

作者： Qiu, Yujing Xu, Haochen Zhou, Ying Chen, Beizhao Wang, Zhongying Yang, Yi Fang, Qile Mei, Ying Research and Development Center for Watershed Environmental Eco-Engineering Advanced Institute of Natural Sciences Beijing Normal University Zhuhai519087 China School of Environment Beijing Normal University Beijing100875 China Faculty of Arts and Sciences Beijing Normal University Zhuhai519087 China Center for Water Research Advanced Institute of Natural Sciences Beijing Normal University Zhuhai519087 China School of Environmental Science and Engineering Southern University of Science and Technology Shenzhen518055 China

Membrane technology can realize the sustainable management of textile wastewater through dye/salt separation, but its practical implementation has long been hampered by membrane fouling. This work was to develop a novel carbon nitride based two-dimensional (2D) self-assembled membrane for efficient dye/salt separation with excellent photocatalytic self-cleaning performance toward azo dyes (e.g., methyl blue), anthraquinone dyes (e.g., reactive blue 19) and natural organic matters (e.g., humic acid). Specifically, conventional graphite carbon nitride (g-C3N4), poly triazine imide (PTI) and the composites of iron oxide doped PTI (PTI-Fe2O3) were comparatively investigated for manipulating the lamellar self-catalytic membrane through facile vacuum filtration. The considerable separation factors of sodium chloride to methyl blue (Ssalt/dye) of 76.97, 80.72, and 74.33 were obtained by g-C3N4, PTI, and PTI-Fe2O3, respectively. The generation of radicals and non-radicals were triggered by light irradiation and was accelerated by PTI compared to g-C3N4, resulting in the better flux recovery rate (FRR) of 95.7 % for PTI membrane than that of g-C3N4 membrane (74.4 %). Besides, the introduction of iron oxide enables the enhanced self-cleaning performance by coupling photocatalytic and Fenton-like process, leading to the highest FRR value of 99.4 %. Meanwhile, the fabricated membranes demonstrate remarkable stability (FRR ≥ 80 %) during prolonged operation (64 h) to both simulated and real textile wastewater, indicating that it can a promising alternative membrane material for textile wastewater management. © 2025 Elsevier Ltd

关键词： Membrane technology

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Pilgrimage to Pureland: Art, Perception and the Wutai Mural VR Reconstruction

arXiv

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arXiv 2023年

作者： Mu, Rongxuan Nie, Yuhe Cao, Kent You, Ruoxin Wei, Yinzong Tong, Xin Architecture Tianjin University Tianjin China Computer Science and Technology Southern University of Science and Technology Guangdong China Division of Arts and Humanities Duke Kunshan University Duke University United States Arts and Humanities Duke Kunshan University Jiangsu China Chinese Literature Wuhan University Wuhan China Data Science Research Center Duke Kunshan University Jiangsu China

Virtual reality (VR) supports audiences to engage with cultural heritage proactively. We designed an easy-to-access and guided Pilgrimage To Pureland VR reconstruction of Dunhuang Mogao Grottoes to offer the general public an accessible and engaging way to explore the Dunhuang murals. We put forward an immersive VR reconstruction paradigm that can efficiently convert complex 2D artwork into a VR environment. We reconstructed the Mt. Wutai pilgrimage mural in Cave 61, Mogao Grottoes, Dunhuang, into an immersive VR environment and created a plot-based and interactive experience that offers users a more accessible solution to visit, understand and appreciate the complex religious, historical, and artistic value of Dunhuang murals. Our system remarkably smoothed users' approaches to those elusive cultural heritages. Appropriate adaptation of plots and 3D VR transfer consistent with the original art style could enhance the accessibility of cultural heritages. © 2023, CC BY-NC-SA.

关键词： Caves

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TiO₂ and ZnO based ternary nanocomposites coupled with gC₃N₄ and tetra-amino zinc phthalocyanine for enhanced oxygen evolution reaction performance

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Colloids and Surfaces A: Physicochemical and Engineering Aspects 2025年 718卷

作者： Rajappa, Shwetha Kotresh, Harish Makri Nimbegondi Anand, Samika Sunajadevi, Kalathiparambil Rajendra Pai Mohan, Mothi Krishna Devendrachari, Mruthyunjayachari Chattanahalli Chundattu, Sony J. Daniel, Nobi Kunnathu Department of Sciences and Humanities School of Engineering and Technology Christ University Mysore Road Kumbalagodu Bangalore560074 India Department of Chemistry Acharya Institute of Technology Karnataka Bangalore560107 India Department of Chemistry Christ University Karnataka Bengaluru560029 India Interaction Laboratory Future Convergence Engineering Advanced Technology Research Center Korea University of Technology and Education Chungcheongnam-do Cheonan-si31253 Korea Republic of

Electrocatalytic water splitting is a sustainable approach to address the energy crisis driven by the rapid growth of global population. The development of affordable and efficient electrocatalysts is inevitable in advancing the field. In the current study, TiO2NPs-TAZnPC-gC3N4 (TiO2 nanoparticles, tetra amino zinc phthalocyanine, and gC₃N₄) and ZnONPs-TAZnPC-gC3N4 (ZnO nanoparticles, tetra amino zinc phthalocyanine, and gC₃N₄) ternary nanocomposites have been prepared using a dispersion method. The structural identity of nanoparticles and the effective incorporation of additional moieties into the final system are validated using powder X-ray diffraction analysis and confirmed by X-ray photoelectron spectroscopy (XPS) analysis. Transmission electron microscopy (TEM) images reveal the sheet-like structures of gC3N4 and TAZnPC, decorated with spherical TiO2NPs and hexagonal ZnONPs. The prepared ternary composites are evaluated for their electrocatalytic water splitting performance. In particular, the electrocatalysts reveal excellent oxygen evolution reaction (OER) capabilities with overpotentials of 420 mV and 450 mV for TiO2NPs-TAZnPC-gC3N4 and ZnONPs-TAZnPC-gC3N4, respectively. © 2025 Elsevier B.V.

关键词： Titanium dioxide

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