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1st International Conference on Advances in Computational Science and engineering, ICACSE 2020

作者： Umapathy, K. Mangayarkarasi, T. Subitha, D. Sivagami, A. Tamil Nadu Kanchipuram India Department of Instrumentation and Control Engineering Sri Sairam Engineering College Tamil Nadu Chennai India Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala RandD Institute of Science and Technology Tamil Nadu Chennai India Department of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Thandalam Tamil Nadu Chennai India

The treatment of waste is unsafe in city centres where residents are more involved, leading to germs that can lead to disease. How commonly these litter containers are used in different regions is different. Regular timing checks are not helpful. Often, they will overflow much faster than expected. In this article, a smart waste monitoring method is advised to prevent this and increase cleaning, to figure out where the waste is *** architecture of the method collects and transmits information through a wireless network. Under this technique, the dustbin's waste level is measured by sensors and information is transmitted through the GSM and GPS module to the official mobile station. Wi-Fi Module is used to track waste levels online at the control room. Arduino Processor uses network modules to link sensor systems. © Published under licence by IOP Publishing Ltd.

关键词： Android (operating system)

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Spindle Status Monitoring and Fault Feature Information Acquisition Based on Rotor Sensing

Spindle Status Monitoring and Fault Feature Information Acqu...

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作者： Liu, Zerui Wang, Hongjun Ji, Yongjian Gu, Fengshou Xu, Yuandong School of Mechanical and Electrical Engineering Beijing Information Science and Technology University Beijing100192 China Intelligent Perception and Control of High-End Equipment Beijing International Science and Technology Cooperation Base Beijing100192 China Key Laboratory of Modern Measurement and Control Technology of Ministry of Education Beijing Information Science and Technology University Beijing100192 China Centre for Efficiency and Performance Engineering University of Huddersfield HuddersfieldH1 3DH United Kingdom

As one of the core components of CNC machine tools, the performance and status of the spindle have an important impact on the normal operation of the CNC machine tools. However, the spindle is often difficult to monitor its condition due to its complex structure and complex working conditions and failure modes. Therefore, the rotor sensing technology is used to monitor the state of the spindle, and the low-cost, low-power micro-electromechanical system is used to replace the traditional sensor (MEMS), so that the MEMS accelerometer can be directly installed on the rotating shaft, providing more accurate dynamics for the rotating machinery information. This article first discusses the rotor sensing technology, and then takes a certain type of electric spindle as the research object, analyzes its structure, establishes geometric models and dynamic equations, and uses ANSYS software to conduct modal analysis to determine the fault transmission path, And then studied the bearing faults with high failure rate and greater hazard in the electric spindle, and proposed a rolling bearing fault feature extraction method based on complementary set empirical mode decomposition (CEEMD) and modulation signal bispectrum. First, CEEMD is used to decompose several IMF components, and the correlation between each IMF and the original signal is calculated according to the correlation coefficient criterion, and the IMF components that meet the requirements are reconstructed. Finally, the reconstructed signal is decomposed by MSB and the fault characteristic frequency is extracted. Experiments have verified the analysis results of the CEEMD-Fast Spectral Kurtosis (FK) method. The CEEMD-MSB method proposed in this paper can obtain fault characteristics more accurately, which proves the effectiveness and superiority of the proposed method. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Empirical mode decomposition

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A No-Reference Quality Assessment Method for Digital Human Head

A No-Reference Quality Assessment Method for Digital Human H...

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IEEE International Conference on Image Processing

作者： Yingjie Zhou Zicheng Zhang Wei Sun Xiongkuo Min Xianghe Ma Guangtao Zhai Institute of Image Communication and Network Engineering Shanghai Jiao Tong University China School of Information and Control Engineering China University of Mining Technology China Peng Cheng Laboratory China MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University China

In recent years, digital humans have been widely applied in augmented/virtual reality (A/VR), where viewers are allowed to freely observe and interact with the volumetric content. However, the digital humans may be degraded with various distortions during the procedure of generation and transmission. Moreover, little effort has been put into the perceptual quality assessment of digital humans. Therefore, it is urgent to carry out objective quality assessment methods to tackle the challenge of digital human quality assessment (DHQA). In this paper, we develop a novel no-reference (NR) method based on Transformer to deal with DHQA in a multi-task manner. Specifically, the front 2D projections of the digital humans are rendered as inputs and the vision transformer (ViT) is employed for the feature extraction. Then we design a multi-task module to jointly classify the distortion types and predict the perceptual quality levels of digital humans. The experimental results show that the proposed method well correlates with the subjective ratings and outperforms the state-of-the-art quality assessment methods.

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A NO-REFERENCE QUALITY ASSESSMENT METHOD FOR DIGITAL HUMAN HEAD

arXiv

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arXiv 2023年

作者： Zhou, Yingjie Zhang, Zicheng Sun, Wei Min, Xiongkuo Ma, Xianghe Zhai, Guangtao Institute of Image Communication and Network Engineering Shanghai Jiao Tong University China School of Information and Control Engineering China University of Mining Technology China Peng Cheng Laboratory China MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University China

关键词： Textures

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Analysis of Visual Effects Configuration Scheme for Small Cultural Complex

Analysis of Visual Effects Configuration Scheme for Small Cu...

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Information technology,Big Data and Artificial Intelligence (ICIBA), International Conference on IEEE International Conference on

作者： Chang Sun Zhibin Su Wei Liu Hui Ren School of Information and Communication Engineering Communication University of China Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control Ministry of Culture and Tourism School of Information and Communication Engineering Beijing China

ISBN: (纸本)9781665428781

Stage lighting design is an important step in the visual effect configuration scheme of small cultural complex. This paper mainly discusses the lighting configuration of small space with multi-functional art services under different modes such as performance, conference, exhibition, reading and folk customs. Focusing on the analysis of lighting layout methods in drama and artistic performances, this paper takes the drama performing environment as the representative. Through the corresponding subjective evaluation experiments, research and data analysis are carried out on the lamps and lighting methods adopted in the performance. Furthermore, the optimal configuration effect of front light and top light under given constraints is selected. The research provides an effective reference for the lighting configuration of small cultural complexes, which has certain application value and practical significance.

关键词： Layout Lighting Focusing Visual effects Software Planning Cultural differences

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LoBee: Bidirectional communication between LoRa and ZigBee based on Physical-Layer CTC

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IEEE Transactions on Wireless communications 2025年

作者： Gao, Demin Wang, Haoyu Chen, YongRui Ye, Qiaolin Wang, Weizheng Guo, Xiuzhen Wang, Shuai Liu, Yunhuai He, Tian Nanjing Forestry University College of Information Science and Technology Artificial Intelligence Nanjing210037 China University of Minnesota The Department of Computer Science and Engineering 55414 United States University of Chinese Academy of Sciences School of Electronic Electrical and Communication Engineering Beijing100049 China Southeast University The School of Computer Science and Engineering Nanjing211189 China City University of Hong Kong Department of Computer Science 999077 Hong Kong College of Control Science and Engineering Zhejiang 310027 China Peking University The Department of Computer Science and Engineering Beijing100871 China University of Minnesota The Department of Computer Science and Engineering Minneapolis55414 United States

LoRa networks operating in a star topology, this configuration creates a single point of failure and may limit scalability and reliability in areas that are large and geographically dispersed. In order to improve the overall transmission capabilities of the network, recent studies show that adding LoRa to the ZigBee devices effectively disseminates network management. By doing so, the strengths of both technologies can be leveraged, with LoRa serving as the long-range transmitter and ZigBee functioning as the mesh network. In this study, we present LoBee, a novel bidirectional communication method between LoRa and ZigBee that relies on Physical-Layer Cross-technology communication. Despite the fact that LoRa and ZigBee utilize different modulation techniques, ZigBee devices can detect and recognize LoRa chirps through the process of sampling the received signal strength. For the transmissions from ZigBee to LoRa devices, we carefully select the input chips to generate specific waveforms, where LoBee detects the preamble of a ZigBee frame based on the locations of the repeated peaks. Our evaluation, which was conducted using USRP and commodity devices, demonstrates that LoBee is capable of achieving concurrent bidirectional wireless communications, with a data rate of approximately 639.38 bits per second from LoRa to ZigBee and from ZigBee to LoRa with more than 90% frame reception rate in the 2.4 GHz frequency band. © 2002-2012 IEEE.

关键词： Zigbee

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Human-Exoskeleton Interaction Force Estimation Based on Quasi-Direct Drive Actuators

Human-Exoskeleton Interaction Force Estimation Based on Quas...

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IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)

作者： Julian Seiler Niklas Schêfer Guoping Zhao Bastian Latsch Martin Grimmer Philipp Beckerle Mario Kupnik Measurement and Sensor Technology Group Technical University of Darmstadt Germany School of Mechanical Engineering Southeast University China Lauflabor Locomotion Laboratory Technical University of Darmstadt Germany Control and Cyber-Physical Systems Technical University of Darmstadt Germany Chair of Autonomous Systems and Mechatronics Friedrich-Alexander-Universität Erlangen Nurnberg Germany

ISBN: (数字)9798350386523

ISBN: (纸本)9798350386530

Exoskeletons have emerged as a promising tech-nological solution to provide functional compensation, training support, physical enhancement, and rehabilitation for an aging population. High torque density and control bandwidth are essential for exoskeleton actuation. In addition, monitoring and control of human-exoskeleton interaction forces is essential for the effectiveness, safety, and comfort of exoskeletons. Quasi-direct drives (QDD) have the potential to address the actuation requirements by enabling proprioceptive actuation with low mechanical output impedance. We present a test bench system to identify and validate the system dynamics, including torque constant, inertia, and friction properties of the QDD Cube-Mars AK10-9 V1.1. The actuator is employed in a hip exoskeleton to evaluate open-loop torque tracking and interaction force estimation in an assisted gait scenario with one participant walking on a treadmill. The model estimates interaction forces with a mean absolute error (MAE) of 2.78±0.58N (6.4% of rated force output). Model-based open-loop control improves the torque tracking MAE by 23%. Our analysis indicates that considering the soft coupling between human and exoskeleton has the potential to further improve the torque tracking and interaction force estimation accuracy. Altogether, the findings demonstrate that QDD actuation enables backdrivability, re-liable force estimation and controllable assistance, thereby providing an effective solution for exoskeleton actuation.

关键词： Actuators Torque Accuracy Friction Exoskeletons Force Dynamics Estimation Impedance Hip

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AM-ResNet: An Attention-Based Multi-Label Classification Network

AM-ResNet: An Attention-Based Multi-Label Classification Net...

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IEEE International Conference on Robotics and Biomimetics

作者： Le Chen Jun Zhao Kaixuan Tian Yuliang Zhao Detachment 60 PLA Unit 92493 Huludao China Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao China

ISBN: (纸本)9781665481106

Exploring sea ice types in complex marine environments is essential to ensure the navigation safety of maritime activities like ships, offshore RIGS, and fishing in ice areas in winter. In this study, we propose a multi-label sea ice classification model based on the attention mechanism, AM-ResNet. First, we develop a multi-label classification model of neural networks based on features of sea ice structure and developmental processes. We then introduce a channel attention mechanism, the SE module, to improve the identification accuracy of the model. Finally, we embed the SE module into the classification model and construct a multi-label classification network based on attention mechanism and used it for sea ice multi-standard type classification. Based on the experimental results of the test set, the average classification accuracy reached 0.952, including 0.95 based on the texture features and 0.954 based on the development process features. This method achieves multi-label sea ice classification with high accuracy.

关键词： Biomimetics Neural networks Feature extraction Safety Marine navigation Marine vehicles Robots

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Semantic Segmentation of Sea Ice Based on U-net Network Modification

Semantic Segmentation of Sea Ice Based on U-net Network Modi...

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IEEE International Conference on Robotics and Biomimetics

作者： Jun Zhao Le Chen Jinhao Li Yuliang Zhao Detachment 60 PLA Unit 92493 Huludao China Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology School of Control Engineering Northeastern University at Qinhuangdao Qinhuangdao China

ISBN: (纸本)9781665481106

Sea ice detection is essential to ensure the safe navigation of ships in mid- and high-latitude ice areas. In the face of complex sea ice information, how to use the sea ice images by shipboard cameras to comprehensively, accurately and efficiently identify four types of sea ice information (Ice skin, Nile ice, Grey ice and White ice)and two kinds of sea ice background information (sea water and sky), it remains a major challenge. This study proposes an automatic semantic segmentation method for sea ice images, which first uses Rsenet50 as well as Vgg-16 network to pre-train the model and improve the network training efficiency. Then modifications to U-Net network, improvement of the coding phase of the U-Net by introducing Vgg-16 and the residual structure, construction of the new network RU-Net and VU-Net. Compared with traditional classification methods, the experimental results show that the network can accurately identify all sea ice information in sea ice images. In particular, multi-scale sea ice types can be identified in real time, greatly improving the efficiency and accuracy of the identification of sea ice types. The MIoU values were 0.73 and 0.87 and the MPA values were 0.87 and 0.94 respectively.

关键词： Training Navigation Semantic segmentation Skin Real-time systems Encoding Marine vehicles

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Numerical Simulation of Water and Mud Inrush Processes in Mountain Tunnels Using Coupled Lbm-Dem

SSRN

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SSRN 2023年

作者： Fan, Zhanfeng Wu, Xiaohua Wang, Zhijia Li, Jun Sichuan Engineering Research Center for Mechanical Properties and Engineering Technology of Unsaturated Soils Chengdu University Chengdu610106 China Vehicle Measurement Control and Safety Key Laboratory of Sichuan Province Xihua University Chengdu610039 China School of Civil and Architectural Engineering Hainan University Haikou570228 China College of Computer Science and Cyber Security Chengdu University of Technology Chengdu610059 China

Studying the mechanism of sudden water inrush and mud flow in mountain tunnels is crucial for implementing preventive measures. In addition, tunnel excavation through a fault or fractured zone can easily trigger sudden water inrush or mudflow. In the paper, the coupled lattice Boltzmann method (LBM) and discrete element method (DEM) were used to simulate the process of water and mud inrush in mountain tunnels. Tunnel mud burst failure and water inrush are essentially a fluid-solid coupling process. The two-dimensional Boltzmann method for fluids and DEM for particles were introduced. The coupled LBMDEM boundary adopts the immersed moving boundary method. For the water inrush process, the presence of water was predicted using advanced geological prediction of seismic waves in the tunnel. A numerical model was established to reproduce the flow of water particles in karst pipelines. The model had a length of 7 cm, a width of 4 cm, and consisted of 100 particles. For the mud inrush process, a numerical model was established with dimensions of 5 cm in length and 4 cm in height. In this model, 720 particles were randomly generated. The results indicated that the evolution process of the three consecutive stages of © 2023, The Authors. All rights reserved.

关键词： Finite difference method

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