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Pressure stimulated current in progressive failure process of combined coal-rock under uniaxial compression:Response and mechanism

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International Journal of Mining Science and technology 2024年第2期34卷 227-243页

作者： Tiancheng Shan Zhonghui Li Xin Zhang Haishan Jia Xiaoran Wang Enyuan Wang Yue Niu Dong Chen Weichen Sun Dongming Wang State Key Laboratory of Coal Mine Disaster Prevention and Control China University of Mining and TechnologyXuzhou 221116China National Engineering Research Center for Coal Gas Control China University of Mining and TechnologyXuzhou 221116China School of Safety Engineering China University of Mining and TechnologyXuzhou 221116China State Key Laboratory for Fine Exploration and Intelligent Development of Coal Resources China University of Mining and TechnologyXuzhou 221116China State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground Engineering China University of Mining and TechnologyXuzhou 221116China

Effective monitoring of the structural health of combined coal-rock under complex geological conditions by pressure stimulated currents(PSCs)has great potential for the understanding of dynamic disasters in underground *** reveal the effect of this way,the uniaxial compression experiments with PSC monitoring were conducted on three types of coal-rock combination samples with different strength *** mechanism explanation of PSCs are investigated by resistivity test,atomic force microscopy(AFM)and computed tomography(CT)methods,and a PSC flow model based on progressive failure process is *** influence of strength combinations on PSCs in the progressive failure process are *** results show the PSC responses between rock part,coal part and the two components are different,which are affected by multi-scale fracture characteristics and electrical *** the rock strength decreases,the progressive failure process changes obviously with the influence range of interface constraint effect decreasing,resulting in the different responses of PSC strength and direction in different parts to fracture *** PSC flow model is initially validated by the relationship between the accumulated charges of different *** results are expected to provide a new reference and method for mining design and roadway quality assessment.

关键词： Combined coal-rock Pressure stimulated current Progressive failure process Mechanism Flow model

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ViGT: proposal-free video grounding with a learnable token in the transformer

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Science China(Information Sciences) 2023年第10期66卷 196-212页

作者： Kun LI Dan GUO Meng WANG School of Computer Science and Information Engineering Hefei University of Technology Key Laboratory of Knowledge Engineering with Big Data Ministry of Education Intelligent Interconnected Systems Laboratory of Anhui Province Institute of Artificial Intelligence Hefei Comprehensive National Science Center

The video grounding(VG) task aims to locate the queried action or event in an untrimmed video based on rich linguistic descriptions. Existing proposal-free methods are trapped in the complex interaction between video and query, overemphasizing cross-modal feature fusion and feature correlation for VG. In this paper, we propose a novel boundary regression paradigm that performs regression token learning in a transformer. Particularly, we present a simple but effective proposal-free framework, namely video grounding transformer(ViGT), which predicts the temporal boundary using a learnable regression token rather than multi-modal or cross-modal features. In ViGT, the benefits of a learnable token are manifested as follows.(1) The token is unrelated to the video or the query and avoids data bias toward the original video and query.(2) The token simultaneously performs global context aggregation from video and query ***, we employed a sharing feature encoder to project both video and query into a joint feature space before performing cross-modal co-attention(i.e., video-to-query attention and query-to-video attention) to highlight discriminative features in each modality. Furthermore, we concatenated a learnable regression token [REG] with the video and query features as the input of a vision-language transformer. Finally, we utilized the token [REG] to predict the target moment and visual features to constrain the foreground and background probabilities at each timestamp. The proposed ViGT performed well on three public datasets:ANet-Captions, TACoS, and YouCookⅡ. Extensive ablation studies and qualitative analysis further validated the interpretability of ViGT.

关键词： video grounding temporal sentence grounding boundary regression token learning proposal-free

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Effects of lactic acid bacteria fermentation on the bioactive composition,volatile compounds and antioxidant activity of Huyou(Citrus aurantium'Changshan-huyou')peel and pomace

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Food Quality and Safety 2023年第2期7卷 317-329页

作者： Yake He Yanyun Zhu Jimin Lvi Ye Gu Ting Wang Jianchu Chen College of Biosystems Engineering and Food Science National-Local Joint Engineering Laboratory of Intelligent Food Technology and EquipmentZhejiang Key Laboratory for Agro-Food ProcessingZhejiang Engineering Laboratory of Food Technology and EquipmentZhejiang UniversityHangzhouChina School of Automation Hangzhou Dianzi UniversityHangzhouChina

Using lactic acid bacteria(LAB)to ferment Huyou peel and pomace could provide a reference for making full use of Huyou resources and provide valuable suggestions for the industrial production of functional *** effects of LAB fermentation on the bioactive composition,volatile compounds and antioxidant activity of Huyou peel and pomace were *** showed that both Huyou peel and pomace were good substrates for LAB *** had remarkable influence on bioconversion of organic acids,among which ascorbic acid content was increased *** addition,LAB could produce flavonoids with enhanced bioactivity and *** particular,the contents of rhoifolin,quercitrin and quercetin were increased by over 100%.Besides,the volatile compounds contents and aroma complexity were ***,the antioxidant activity was ***,our study provides high-value applications of Huyou,and fermented products with improved nutritional value and flavor are potentially beneficial to human health.

关键词： Lactic acid bacteria,Huyou peel Huyou pomace bioactive composition volatile compounds

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Microencapsulation of Bacillus smithii XY1 by spray drying and evaluation for treatment of inflammatory bowel disease

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Food Bioscience 2023年第3期53卷 674-684页

作者： Chen Ji Yufang Gao Xuedi Huang Fujie Yan Ting Yu National Engineering Laboratory of Intelligent Food Technology and Equipment College of Biosystems Engineering and Food ScienceZhejiang UniversityHangzhouZhejiang Province310058PR China

Microencapsulation is a promising and feasible method to help probiotics against adverse situation and overcome storage *** this study,we prepared Bacillus smithii XY1 microcapsules by spray ***,wall materials of the microcapsules were screened and the ratio between wall materials and protective agent was *** results showed that 9%gum arabic and 5%soluble starch along with 4%skim milk powder were the best condition for spray drying through response surface *** scanning electron microscope(SEM),bacteria were successfully encapsuled in the wall materials and microcapsules presented complete structure without *** to non-encapsulated bacteria,encapsulation increased tolerance of *** XY1 in gastrointestinal environment,improved shelf time and showed a better effect on alleviating intestine inflammation of zebrafish induced by dextran dulfate sodium(DSS).Thus,this encapsulation approach may have the potential application for improving efficacy of *** XY1 and other probiotics.

关键词： Spray drying Bacillus smithii XY1 Gum arabic Soluble starch Microcapsules Inflammatory bowel disease

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A Study on Object Detection using Faster R-CNN, Retina net, RPN_R_50_FPN, RPN_R_50_C4

A Study on Object Detection using Faster R-CNN, Retina net, ...

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2024 International Conference on intelligent Computing and Sustainable Innovations in technology, IC-SIT 2024

作者： Kadiyam, Aswin Tirumala Someswar Padhan, Chinmaya Ranjan Panigrahi, Sibarama National Institute of Technology Computer Science and Engineering Andhra Pradesh India National Institute of Technology Intelligent Data Analytics Laboratory Computer Science and Engineering Rourkela India

ISBN: (纸本)9798350369175

The computer vision concept that involves the detection and characterization of objects in images is known as object detection. This research mainly performs this function using four popular models faster R-CNN, RetinaNet, RPN_R_50_FPN, and RPN_R_50_C4 across multiple datasets namely udacity self-driving car dataset, tomatOD dataset, and chess piece detection dataset. Faster R-CNN is famous for its outstanding accuracy although RetinaNet employs a unique focal loss function to balance between speed and accuracy. The purpose of the models RPN_R_50_FPN and RPN_R_50_C4 is to generate region proposals with high quality using different stages in the ResNet-50 backbone. For normalization techniques, the datasets are preprocessed in this research. Instead of training the models from scratch, transfer learning is used whereby starting with weights that were pre-trained on the COCO dataset and after that fine-tuning the required datasets. Accuracy was quantified by evaluating two efficiency measures which are minimum loss and total training duration. Across the different datasets, various performances were demonstrated by different models. © 2024 IEEE.

关键词： Eye protection

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Efficient blocked symmetric compressed sparse column method for finite element analysis

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Frontiers of Mechanical engineering 2025年第1期20卷 87-104页

作者： Yingjun WANG Shijie LUO Jinyu GU Yuanfang ZHANG National Engineering Research Center of Novel Equipment for Polymer Processing The Key Laboratory of Polymer Processing Engineering of the Ministry of EducationGuangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced ManufacturingSouth China University of TechnologyGuangzhou 510641China Shien-Ming Wu School of Intelligent Engineering South China University of TechnologyGuangzhou 511442China

In finite element analysis(FEA),optimizing the storage requirements of the global stiffness matrix and enhancing the computational efficiency of solving finite element equations are pivotal *** address these goals,we present a novel method for compressing the storage of the global stiffness matrix,aimed at minimizing memory consumption and enhancing FEA *** method leverages the block symmetry of the global stiffness matrix,hence named the blocked symmetric compressed sparse column(BSCSC)*** also detail the implementation scheme of the BSCSC method and the corresponding finite element equation solution *** approach optimizes only the global stiffness matrix index,thereby reducing memory requirements without compromising FEA computational *** then demonstrate the efficiency and memory savings of the BSCSC method in FEA using 2D and 3D cantilever beams as *** addition,we employ the BSCSC method to an engine connecting rod model to showcase its superiority in solving complex engineering ***,we extend the BSCSC method to isogeometric analysis and validate its scalability through two examples,achieving up to 66.13%memory reduction and up to 72.06%decrease in total computation time compared to the traditional compressed sparse column method.

关键词： finite element analysis global stiffness matrix blocked symmetric property memory reduction isogeometric analysis

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Active learning attraction basins of dynamical system

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Chinese Physics B 2025年第5期34卷 115-122页

作者： Xiao-Wei Cao Xiao-Lei Ru Gang Yan MOE Key Laboratory of Advanced Micro-Structured Materials and School of Physical Science and EngineeringTongji UniversityShanghai 200092China National Key Laboratory of Autonomous Intelligent Unmanned Systems MOE Frontiers Science Center for Intelligent Autonomous Systemsand Shanghai Research Institute of Intelligence Science and TechnologyTongji UniversityShanghai 200092China

Dynamical systems often exhibit multiple attractors representing significantly different functioning conditions.A global map of attraction basins can offer valuable guidance for stabilizing or transitioning system *** a map can be constructed without prior system knowledge by identifying attractors across a sufficient number of points in the state ***,determining the attractor for each initial state can be a laborious ***,we tackle the challenge of reconstructing attraction basins using as few initial points as *** each iteration of our approach,informative points are selected through random seeding and are driven along the current classification boundary,promoting the eventual selection of points that are both diverse and *** results across various experimental dynamical systems demonstrate that our approach requires fewer points than baseline methods while achieving comparable mapping ***,the reconstructed map allows us to accurately estimate the minimum escape distance required to transition the system state to a target basin.

关键词： complex system attraction basin active learning

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UAV-Assisted Dynamic Avatar Task Migration for Vehicular Metaverse Services: A Multi-Agent Deep Reinforcement Learning Approach

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 430-445页

作者： Jiawen Kang Junlong Chen Minrui Xu Zehui Xiong Yutao Jiao Luchao Han Dusit Niyato Yongju Tong Shengli Xie IEEE School of Automation Guangdong University of TechnologyGuangzhou 510006China 111 Center for Intelligent Batch Manufacturing based on IoT Technology Guangzhou 510006China Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of EducationGuangzhou 510006China School of Computer Science and Engineering Nanyang Technological UniversitySingaporeSingapore Pillar of Information Systems Technology and Design Singapore University of Technology and DesignSingaporeSingapore College of Communication Engineering Army Engineering University of PLANanjing 210007China National Natural Science Foundation of China Beijing 100085China Key Laboratory of Intelligent Detection and IoT in Manufacturing Ministry of EducationGuangzhou 510006China Guangdong Key Laboratory of IoT Information Technology Guangzhou 510006China

Avatars, as promising digital representations and service assistants of users in Metaverses, can enable drivers and passengers to immerse themselves in 3D virtual services and spaces of UAV-assisted vehicular Metaverses. However, avatar tasks include a multitude of human-to-avatar and avatar-to-avatar interactive applications, e.g., augmented reality navigation,which consumes intensive computing resources. It is inefficient and impractical for vehicles to process avatar tasks locally. Fortunately, migrating avatar tasks to the nearest roadside units(RSU)or unmanned aerial vehicles(UAV) for execution is a promising solution to decrease computation overhead and reduce task processing latency, while the high mobility of vehicles brings challenges for vehicles to independently perform avatar migration decisions depending on current and future vehicle status. To address these challenges, in this paper, we propose a novel avatar task migration system based on multi-agent deep reinforcement learning(MADRL) to execute immersive vehicular avatar tasks dynamically. Specifically, we first formulate the problem of avatar task migration from vehicles to RSUs/UAVs as a partially observable Markov decision process that can be solved by MADRL algorithms. We then design the multi-agent proximal policy optimization(MAPPO) approach as the MADRL algorithm for the avatar task migration problem. To overcome slow convergence resulting from the curse of dimensionality and non-stationary issues caused by shared parameters in MAPPO, we further propose a transformer-based MAPPO approach via sequential decision-making models for the efficient representation of relationships among agents. Finally, to motivate terrestrial or non-terrestrial edge servers(e.g., RSUs or UAVs) to share computation resources and ensure traceability of the sharing records, we apply smart contracts and blockchain technologies to achieve secure sharing management. Numerical results demonstrate that the proposed approach

关键词： Avatar blockchain metaverses multi-agent deep reinforcement learning transformer UAVs

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Comfort of Autonomous Vehicles Incorporating Quantitative Indices for Passenger Feeling

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Journal of Shanghai Jiaotong university(Science) 2024年第6期29卷 1063-1070页

作者： PENG Shiwei ZHANG Xi ZHU Wangwang DOU Rui National Engineering Laboratory for Automotive Electronic Control Technology Shanghai Jiao Tong UniversityShanghai 200240China Shanghai SongHong Intelligent Automotive Technology Co. Ltd.Shanghai 201805China

At present,most of the studies on autonomous vehicles mainly focus on improving driving safety and efficiency,while less consideration is given to the comfort of ***,in order to gain and optimize quantitative indices for the ride experience of autonomous vehicles,this paper proposes an evaluation method for the correlation between driving behavior and passenger comfort with bidirectional long short-term memory network and attention *** collecting subjective feeling scores of passengers under different driving styles,and measuring the pressure level with skin conductance response and heart rate variability,the comprehensive quantitative indices of passenger comfort caused by driving behavior are *** on this,a personalized comfort evaluation model for passengers with different driving style preferences is *** results obtained from experiments in open road and closed test areas have validated the effectiveness and feasibility of the method proposed in this paper.

关键词： autonomous vehicles passenger comfort physiological sensing bidirectional long short-term memory attention mechanism

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On-orbit attitude planning for Earth observation imaging with star-based geometric calibration

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Science China(Technological Sciences) 2025年第2期68卷 243-256页

作者： Di HUANG Zhifu WANG Jianya GONG Haoran JI Institute of Aerospace Science and Technology School of Remote Sensing and Information EngineeringWuhan UniversityWuhan 430072China State Key Laboratory of Information Engineering in Surveying Mapping and Remote SensingSchool of Remote Sensing and Information EngineeringWuhan UniversityWuhan 430072China National Key Laboratory of Air-based Information Perception and Fusion Luoyang 471009China Intelligent Game and Decision Laboratory Beijing 100071China

To improve the quality of remote sensing images,a novel on-orbit attitude planning method for Earth observation imaging with star-based geometric calibration is presented in this *** traditional imaging processes,the proposed method includes both pre-calibration and post-calibration stages to enhance the accuracy of satellite geometric positioning.A multiple-constraint attitude planning algorithm was developed to ensure star-based calibration,wherein the satellite camera and star sensors simultaneously capture the images of *** integration of cameras and multiple star sensors enables effective attitude *** the Earth imaging stage,a fast on-orbit attitude planning algorithm was developed to determine the satellite attitude and the optimal imaging times for ground *** with existing methods,the fast on-orbit attitude planning algorithm can significantly reduce computational time and resource consumption via initial value selection and *** demonstrate the effectiveness of the proposed attitude planning method,which was successfully applied to Wuhan 1 satellite.

关键词： attitude planning Earth observation imaging geometric calibration attitude constraints

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