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Integration of flexible,recyclable,and transient gelatin hydrogels toward multifunctional electronics

Journal of Materials science & technology 2023年第14期145卷 83-92页

作者： Rui Yin Chen Zhang Jian Shao Youyou Chen Ao Yin Qiang Feng Shuqin Chen Fei Peng Xing Ma Cheng-Yan Xu Feihua Liu Weiwei Zhao Sauvage Laboratory for Smart Materials School of Materials Science and EngineeringHarbin Institute of Technology(Shenzhen)Shenzhen 518055China Shenzhen Key Laboratory of Flexible Printed Electronics Technology Harbin Institute of Technology(Shenzhen)Shenzhen 518055China State Key Laboratory of Advanced Welding&Joining Harbin Institute of TechnologyHarbin 150001China

Facing the challenges posed by exponentially increasing e-waste,the development of recyclable and tran-sient electronics has paved the way to an environmentally-friendly progression strategy,where electron-ics can disintegrate and/or degrade into eco-friendly end products in a controlled *** polymers possess cost and energy efficiency,easy modification,and fast degradation,all of which are ideal prop-erties for transient *** is especially attractive due to its unique thermoreversible gelation processes,yet its huge potential as a multifunctional electronic material has not been well-researched due to its limited mechanical strength and low ***,we explored versatile applications of gelatin-based hydrogels through the assistance of multifunctional additives like carbon nanotubes to enhance their electromechanical *** optimized gelatin hydrogel displays not only a high conductivity of 0.93 S/m,electromagnetic shielding effectiveness of 39.6 dB,and tensile stress tolerance of 263 kPa,but also shows a negative permittivity phenomenon,which may find versatile applications in novel *** a proof of concept,hydrogels were assembled as wearable sensors to sensitively de-tect static and dynamic pressures and strains generated by solids,liquids,and airflow,as well as diverse body ***,the recyclability,biocompatibility,and degradability of gelatin-based hy-drogels were well studied and *** work outlines a facile method to design multifunctional transient materials for wearable,sustainable,and eco-friendly electronics.

关键词： Gelatin hydrogels Carbon nanotubes Negative permittivity Electromagnetic interference shielding Wearable sensor

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Versatile BiFeO_(3) shining in piezocatalysis:From materials engineering to diverse applications

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Journal of Advanced Ceramics 2025年第3期14卷 1-27页

作者： Jian Dai Zhenhao Fan Hang Xie Yitao Jiao Fu Huang Ahmad Azmin Mohamad Yunfei Chang Yangke Long Dawei Wang School of Instrumentation Science and Engineering Harbin Institute of TechnologyHarbin 150080China Institute of Applied Physics and Materials Engineering University of MacaoAvenida da UniversidadeMacao 999078China Energy Materials Research Group(EMRG) School of Materials and Mineral Resources EngineeringUniversiti Sains MalaysiaNibong Tebal 14300Malaysia Zhengzhou Research Institute Harbin Institute of TechnologyZhengzhou 450046China Department of Transportation and Environment Shenzhen Institute of Information TechnologyShenzhen 518172China

The growing global demand for sustainable solutions to address energy and environmental challenges has spurred significant interest in catalytic *** has emerged as a sustainable technology for environmental remediation and energy conversion because of its unique characteristics of harvesting mechanical energy into electrochemical *** BiFeO_(3)(BFO)stands out among a range of piezocatalysts for its distinctive integration of piezoelectric,multiferroic,and optical *** review critically examines piezocatalytic mechanisms,including energy band theory,screening charge effects,and displacement current theory,revealing the intricate roles of internal charges,screening charges,and piezoelectric electrons in driving catalytic ***,the evolution of BFO-based piezocatalysis is systematically reviewed,emphasizing its structural characteristics,representative synthesis methods,performance optimization strategies,and diverse applications,such as organic pollutant degradation,H_(2) production,H_(2)O_(2)generation,CO_(2)reduction,and *** particular,the underestimated ferroelectric polarization effect of BFO on CO_(2)reduction is critically analyzed and *** review identifies critical challenges and outlines future research directions to advance high-efficiency BFO-based piezocatalytic ***,this comprehensive analysis underscores the potential of BFO in piezocatalysis,bridging materials engineering with practical applications and offering insights into future advancements.

关键词： BiFeO_(3)(BFO) piezocatalysis piezoelectric effect environmental remediation energy conversion

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Flame features and oscillation characteristics in near-blowout swirl-stabilized flames using high-speed OH-PLIF and mode decomposition methods

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Chinese Journal of Aeronautics 2023年第1期36卷 191-200页

作者： Zhen CAO Xin YU Jiangbo PENG Bin HU Zhonghao WANG Yang YU Long GAO Minghong HAN Xun YUAN Guohua WU National Key Laboratory of Science and Technology on Tunable Laser Harbin Institute of TechnologyHarbin 150001China Institute of Opt-Electronics Harbin Institute of TechnologyHarbin 150001China Institute of Engineering Thermophysics Chinese Academy of SciencesBeijing 100190China School of Aeronautics and Astronautics University of Chinese Academy of SciencesBeijing 100190China

Flame features and dynamics are important to the explanation and prediction of a lean blowout(LBO)*** this paper,recognition of near-LBO flame features and oscillation characterization methods were proposed based on flame spectroscopic ***-speed planar laser-induced fluorescence measurements of OH were used to capture unique dynamic features such as the local extinction and reignition feature and entrained reactant *** Zernike moment demonstrated a good performance in recognition of stability and near-LBO conditions,though the geometric moment had more advantages to characterize frequency ***-frequency oscillations,especially at the obvious self-excited oscillation frequency around 200 Hz,were found when approaching an LBO condition,which can be expected to be used as a novel prediction characteristic parameter of the flameout *** orthogonal decomposition(POD)and dynamic mode decomposition(DMD)were used to conduct dynamic analysis of near-LBO *** modes spectra showed the unique frequency characteristics of stable and near-LBO flames,which were basically in line with those at the heat-release *** primary POD modes demonstrated that the radial vibration mode dominated in a stable flame,while the rotation mode was found to exist in a near-LBO *** of modal decomposition showed that flame shedding and agminated entrained reactant pockets were responsible for generating self-excited flame oscillations.

关键词： Dynamic mode decomposi-tion(DMD) High-speed OH-PLIF Moment descriptors Near-blowout Proper orthogonal decom-position(POD)

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Higher Accuracy Yolov5 Based Safety Helmet Detection 5th

Higher Accuracy Yolov5 Based Safety Helmet Detection

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5th EAI International Conference on 6G for Future Wireless Networks, 6GN 2022

作者： Wang, Zizhen Sun, Yuegong Wang, Zhening Li, Ao School of Computer Science and Technology Harbin University of Science and Technology Harbin China

ISBN: (纸本)9783031360107

For the construction site with high-risk possibility, object detection based on safety helmet and reflective clothing will greatly reduce the risk of workers. At present, the algorithm based on deep learning is the mainstream algorithm of object detection. Among them, the YOLO algorithm is fast and widely used in real-time safety helmet detection. However, for the problems of small objects such as safety helmets and relatively dense detection scene objects, the detection effect is not ideal. For these problems, this paper proposes an improvement of the safety helmet detection algorithm based on YOLOv5s. The DenseBlock module is used in the improved algorithm to replace the Focus structure in the backbone network, which has an improved feature extraction capability for the network;secondly, Soft-NMS is used to retain more category frames when removing redundant frames. After the experiments, it is shown that the accuracy is improved on the homemade safety helmet dataset, which indicates the effectiveness of the improved algorithm. © 2023, ICST institute for computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Object detection

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High-amplitude pressure fluctuations of a pump-turbine with large head variable ratio during the turbine load rejection process

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science China(Technological sciences) 2023年第9期66卷 2575-2585页

作者： FU XiaoLong LI DeYou SONG YeChen WANG HongJie WEI XianZhu School of Energy Science and Engineering Harbin Institute of TechnologyHarbin 150001China State Key Laboratory of Hydro-Power Equipment Harbin Institute of Large Electrical MachineryHarbin 150040China

Large-head variable-amplitude pump turbines(PTs) encounter serious transient hydraulic instability issues. To explore the evolution mechanisms of pressure fluctuations(PFs) and flow patterns inside large-head variable-amplitude PTs, the load rejection process(LRP) was investigated using a one-and three-dimensional coupled flow simulation approach. The temporal,spatial, and frequency characteristics of the fluctuating pressures were analyzed for four monitoring points using a combined time-frequency analysis approach. The results indicated that PFs during the LRP of large-head variable-amplitude PTs had a new fluctuation frequency component related to Dean vortices(DVs) in the volute, in addition to the common fluctuation frequency components related to rotor-stator interaction phenomena and local backflow vortices near the impeller inlet. The PF frequency component existed throughout the LRP and had a significant influence on the transient maximum pressure at the volute end. This study provides a useful theoretical guide for the design and optimization of large-head variable-amplitude PTs.

关键词： large-head variable-amplitude pump turbine load rejection process 1D-3D flow simulation pressure fluctuation flow pattern evolution

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HDNeXt: Hybrid Dynamic MedNeXt with Level Set Regularization for Medical Image Segmentation 17th

HDNeXt: Hybrid Dynamic MedNeXt with Level Set Regularizatio...

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17th Asian Conference on computer Vision, ACCV 2024

作者： Cao, Haoyu Han, Tianyi Yang, Yunyun School of Science Harbin Institute of Technology Shenzhen China

ISBN: (纸本)9789819609628

Deep learning has been extensively employed in the field of medical image segmentation, demonstrating its robustness and efficacy. However, the pursuit of consistent segmentation performance across diverse instrumental conditions and the challenge of achieving precise boundary delineation in segmented images remain significant hurdles. In this paper, we aim to develop a model capable of achieving consistent, high-quality segmentation of identical regions of interest across varying instrumental conditions, with precise boundary delineation. Toward this end, we introduce our Hybrid Dynamic MedNeXt (HDNeXt) model, an advanced framework capable of dynamically generating weights across diverse medical images to maintain consistently high segmentation performance. HDNeXt builds on the robust segmentation framework of MedNeXt by incorporating dynamic convolution techniques, which endow the model with the capability for dynamic weight adjustment, significantly enhancing its segmentation performance. To tackle the second challenge, we devised a novel loss function, LCR, formulated on the Curvature of the segmentation boundary and Region-Fitting energy derived from level set methods, which significantly enhances boundary precision during training and optimizes overall segmentation performance. Experiments were conducted on the abdominal CT datasets Synapse and the cardiac MRI datasets ACDC to demonstrate the efficiency and effectiveness of our method. Our method achieved an average Dice coefficient of 84.38 on the Synapse datasets and 93.59 on the ACDC datasets, surpassing other 2D state-of-the-art segmentation models and achieving optimal performance for 2D medical image segmentation. Codes are available at https://***/HaoyuCao/HDNeXt. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Image segmentation

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Integral precession calibration method of PIGA on linear vibration table

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Chinese Journal of Aeronautics 2024年第3期37卷 219-236页

作者： Chuang SUN Shun-qing REN Jun-wei CAO Ru HUO Department of Automation Tsinghua UniversityBeijing 100084China School of Astronautics Harbin Institute of TechnologyHarbin 150001China Beijing National Research Center for Information Science and Technology Tsinghua UniversityBeijing 100084China Faculty of Information technology Beijing University of TechnologyBeijing 100124China

Linear vibration table can provide harmonic accelerations to excite the nonlinear error terms of Pendulous Integrating Gyro Accelerometer(PIGA).Integral precession calibration method is proposed to calibrate PIGA on a linear vibration table in this *** on the precise expressions of PIGA’s inputs,the error calibration model of PIGA is *** angular velocity errors of PIGA are suppressed by integer periodic precession and the errors caused by non-integer periods vibrating are *** complete calibration process,including planning,preparation,PIGA testing,and coefficient identification,is designed to optimize the test operations and evaluate the calibration *** effect of the main errors on calibration uncertainty is analyzed and the relative sensitivity function is proposed to further optimize the test *** and simulation results verify that the proposed 10-position calibration method can improve calibration uncertainties after compensating for the related *** order of calibration uncertainties of the second-and third-order coefficients are decreased to 10^(-8)(rad.s^(-1))/g^(2)and 10^(-8)(rad.s^(-1))/g3,*** with the other two classical calibration methods,the calibration uncertainties of PIGA’s nonlinear error coefficients can be effectively reduced and the proportional residual errors are decreased less than 3×10-6(rad.s^(-1))/g by using the proposed calibration method.

关键词： PIGA Linear vibration table Vibration measurement Calibration Error analysis Uncertainty analysis

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Multi-semantic Representation with Transformer Network for Video Classification 23

Multi-semantic Representation with Transformer Network for V...

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15th International Conference on Machine Learning and Computing, ICMLC 2023

作者： Sun, Yuxi Xiao, Tonghuan Li, Xutao Ye, Yunming School of Computer Science and Technology Harbin Institute of Technology Shenzhen518055 China

ISBN: (纸本)9781450398411

Video classification is an important and challenging task. Videos usually contain a series of key actions and motion patterns. Video classifiers need to learn and describe them with an embedding vector. Generally, these actions and patterns imply different semantic information. However, existing methods usually only consider single-level semantic features, such as the last pooling layer, to represent the entire video. Complex video content cannot be effectively represented, and classification accuracy is not good enough. To address the limitation, we propose a novel multi-semantic representation method for video classification. Our method consists of several transformer network blocks, semantic graph attention modules, and a feature fusion module. Each transformer block extracts the visual features of video frames and the features of the last block are transformed into an embedding vector. These blocks indicate different levels of visual features. The graph attention module uses these features to generate multi-semantic vectors of a video. Finally, these multi-semantic vectors and the previous embedding vector are fused by a feature fusion module. The fused vector is applied to classify video. Extensive experiments on a benchmark video classification dataset demonstrate that our method outperforms various state-of-the-art methods. © 2023 ACM.

关键词： Vectors

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Multi-Modal Knowledge Representation: A Survey 8

Multi-Modal Knowledge Representation: A Survey

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8th International Conference on Data science in Cyberspace, DSC 2023

作者： Hu, Weiqi Wang, Ye Jia, Yan School of Computer Science and Technology Harbin Institute of Technology Shenzhen Shenzhen China

ISBN: (纸本)9798350331035

A modality refers to the way people receive information, such as vision, hearing, tactile sense, etc. If a task or data set involves multiple modalities, it is called multi-modal. In recent years, there has been more and more research in the field of multi-modal. Especially in the area of vision and language, many studies combine the excellent work of CV and NLP. With the development of knowledge graphs and representation, many works have also begun utilizing external knowledge to improve performance. To explore how multi-modal information and knowledge are utilized, this paper provides a comprehensive survey on multi-modal knowledge representation, which has never been systematically discussed. To facilitate the discussion of how the models combine and utilize multi-modal information and knowledge, we categorize multi-modal knowledge representation methods into two frameworks: explicit multi-modal knowledge representation and implicit multi-modal knowledge representation. For each framework, we introduce some typical models in vision-and-Ianguage, to help new researchers in this field understand the multi-modal knowledge representation model better. In addition, we introduce some downstream tasks and propose some important directions for future work. © 2023 IEEE.

关键词： knowledge representation learning multi-modal representation learning vision-and-Ianguage

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Lightweight Image Matting via Efficient Non-local Guidance 1

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16th Asian Conference on computer Vision, ACCV 2022

作者： Kang, Zhaoxiang Li, Zonglin Liu, Qinglin Zhu, Yuhe Zhou, Hongfei Zhang, Shengping School of Computer Science and Technology Harbin Institute of Technology Weihai264209 China

ISBN: (数字)9783031262845

ISBN: (纸本)9783031262838

Natural image matting aims to estimate the opacity of foreground objects. Most existing approaches involve prohibitive parameters, daunting computational complexity, and redundant dependency. In this paper, we propose a lightweight matting method termed LiteMatting, which learns the local smoothness of color space and affinities between neighboring pixels to estimate the alpha mattes. Specifically, a modified mobile block is adopted to construct an encoder-decoder framework, which reduces parameters while retaining sufficient spatial and channel information. In addition, a Long-Short Range Pyramid Pooling Module (LSRPPM) is introduced to extend the reception field by capturing long-range dependency between regions distributed discretely. Finally, an Efficient Non-Local Block (ENB) is presented for guiding high-level semantics propagation from low-level detail features to refine the alpha mattes. Extensive experiments demonstrate that our method achieves a favorable trade-off between accuracy and efficiency. Compared with most state-of-the-art approaches, our method attains an immense descent in parameters and FLOPs with 30 % and 13 %, respectively, while achieving an improvement of over 15 % in SAD metrics. Code and model are available at https://***/kzx2018/LiteMatting. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Semantics

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