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2022 2nd International Conference on advanced Materials and Mechatronics, ICAMM 2022

作者： Wang, Hongpeng Yang, Ruiping Luo, Wang Ge, Jian Liu, Huan Dong, Haobin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

The development of high-performance and miniaturized magnetometers is important for small-scale target magnetic anomaly detection. In this work, a miniaturized three-axis vector magnetometer based on the tunnel magnetoresistance (TMR) technique is investigated for magnetic anomaly detection. First, the miniaturized three-axis TMR vector magnetometer is constructed, and then, the limit of detection tests and the magnetic anomaly detection tests are performed. The indoor experimental results show that the proposed magnetometer can capture the magnetic anomalies higher than 3.9 nT, with the low-frequency equivalent magnetic noise of 46.89 pT/√Hz@1Hz. The outdoor experimental results show that the proposed magnetometer can effectively detect small-scale magnetic targets such as hammers at a distance of about 1.5 m. With the advantages of small size, low power consumption, and high magnetic measurement sensitivity, the TMR magnetometer has great application prospects for long-term magnetic anomaly monitoring, high-density magnetic imaging, and other fields. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Magnetometers

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Axial-torsional coupled drill-string vibration analysis based on the bit-rock interaction model considering the drilling fluid factor 13

Axial-torsional coupled drill-string vibration analysis base...

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13th Asian Control Conference, ASCC 2022

作者： Huang, Hengyu Wu, Min Lu, Chengda Cao, Weihua Chen, Xin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9788993215236

To characterize drill-string system's dynamic reaction, the axial-torsional coupled drill-string vibration model need to be studied. The drill-string takes little consideration for the drilling fluid factor, and drill-string vibration model for torque and drawworks pull inputs have limited relevance in geological drilling. So an axial-torsional coupled drill-string vibration model is established, with inputs of rope lowering and rotary table rotating speed, and the influence of the drilling fluid factor is taken into account. Firstly, we build a drill-string model with the winch rope speed and rotating speed inputs based on material mechanics theory. Then, the axial-torsional coupled bit-rock interaction model is established, taking the factor of drilling fluid into consideration, and the axial and torsional drill-string vibration is coupled through the bit-rock interaction model. Finally, the model's validity is proved by simulation of the drill-string system and the verification of field data. © 2022 ACA.

关键词： Drilling Vibrations Couplings Analytical models Fluids Torque Geology

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Modeling and Optimization of MEMS Microphone Dust Protection Mesh for improved for Acoustic Performance using Finite Element Method Simulation 3

Modeling and Optimization of MEMS Microphone Dust Protection...

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3rd International Conference on New Materials, Machinery, and Vehicle Engineering, NMMVE 2024

作者： Zhang, Shiwang Li, Jiazhu Yuan, Jiawei Li, Zixuan Yuan, Zheng Qin, Shaohui Zhao, Zilong Tan, Hongqiang Luo, Ruiyan Zhao, Yihe Li, Jie Gao, Wendi Li, Zhikang Zhao, Libo State Key Laboratory for Manufacturing Systems Engineering International Joint Laboratory for Micro/Nano Manufacturing and Measurement Technologies Xi'an710049 China Research Institute for Intelligent Sensing Technology and System Xi'an710049 China School of Instrument Science and Technology Xi'an Jiaotong University Xi'an710049 China School of Mechanical Engineering Xi'an Jiaotong University Xi'an710049 China Shandong Laboratory of Yantai Advanced Materials and Green Manufacturing Yantai265503 China College of Mechanical and Electrical Engineering Shaanxi University of Science and Technology Xi'an710021 China

ISBN: (纸本)9781510686267

Currently, research on Micro-Electro-Mechanical systems (MEMS) microphone dust protection meshes has predominantly focused on dust prevention capabilities, with scant attention given to acoustic performance, and there is a lack of systematic studies on the patterns of acoustic performance variation. This study utilizes finite element analysis to investigate the impact of structural parameters such as perforation radius, perforation rate, number of perforations, and perforation distribution patterns, as well as material properties like the density of the expanded-polytetrafluoroethylene (e-PTFE) membrane, on acoustic impedance and sound transmission loss. It was found that, at a constant perforation rate, a larger perforation radius results in lower acoustic impedance and sound transmission loss. This research provides a theoretical basis for the subsequent design of MEMS microphone dust protection meshes. Furthermore, an intelligent dust protection device based on metasurfaces has been proposed, which achieves an organic integration of dust prevention and sound wave control functions, and exhibits high sensitivity and robustness, laying the foundation for the development of future smart auditory technologies. © 2024 SPIE.

关键词： Acoustic impedance

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Speech Emotion Recognition Based on Clustering Assistance

Speech Emotion Recognition Based on Clustering Assistance

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2022 Chinese Automation Congress, CAC 2022

作者： Peng, Zhi-Kun Liu, Zhen-Tao Han, Meng-Ting China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665465335

Speech emotion recognition (SER) is a key technology to achieve natural human-computer interaction. The development of SER is significantly influenced by the scale of the sample. In recent years, the study of SER has been intensified by introducing data augmentation methods. However, most of these methods directly augment the sample data scale, neglecting the rational analysis and utilization of the feature distribution of samples. In this paper, we propose a new framework for SER based on clustering assistance, which can utilize the feature distribution information of the sample data directly and effectively. It considers the sample proportion of each emotion category in the clusters obtained by clustering, converts it into a probability score, which is called the clustering emotion probability score, and fuses it with the emotion probability score from the simple classification model according to different fusion weighting factors. We evaluated the proposed method with the baseline model on the IEMOCAP dataset. Experimental results show that our method achieves better results than the baseline model in terms of both weighted and unweighted accuracy. © 2022 IEEE.

关键词： K-means clustering

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Fabrication and Path Following Control of a Magnetic Soft Microrobot 8

Fabrication and Path Following Control of a Magnetic Soft Mi...

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8th International Conference on Control Science and systems Engineering, ICCSSE 2022

作者： Tang, Jianhui Zhang, Pan Wu, Jundong Wang, Yawu School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9781665484138

Magnetically-controlled soft microrobots have great application prospects because of small size, flexible motion and wireless control. In this paper, a magnetically-controlled soft microrobot is designed and fabricated. In order to achieve its path-following control, two open-loop control strategies and a closed-loop one are developed. Especially, for the closed-loop control strategy, we present the image processing method and the pure pursuit algorithm, where the former is used to obtain the position and posture of the microrobot required for the latter. Finally, the developed open-loop and closed-loop control strategies are verified by carrying out the experiments. These methods are promising in numerous applications because of the ease of implementation. © 2022 IEEE.

关键词： Image processing

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Group Consensus of Multi-agent systems with Additive Noises and Multiplicative Noises

Group Consensus of Multi-agent Systems with Additive Noises ...

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2022 Chinese Automation Congress, CAC 2022

作者： Qin, Haoxiang Li, Chuanjian Zong, Xiaofeng School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China

ISBN: (纸本)9781665465335

In this paper, we study the group consensus problem of multi-agent systems with additive noises and multiplicative noises. The multi-agent systems are composed of two sub networks affected by additive noises and multiplicative noises, respectively. A consensus protocol is designed to guarantee the group consensus. Based on this protocol, the mean square weak consensus condition and mean square strong consensus condition are obtained by algebraic graph theory and stochastic stability theory. Finally, the numerical simulations show the effectiveness of the group consensus protocol in this paper. © 2022 IEEE.

关键词： Additive noise

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GF2PReID: A Novel Framework for Person Re-IDentification Using Generative Networks

GF2PReID: A Novel Framework for Person Re-IDentification Usi...

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International Conference on Cyberworlds

作者： Emna Ben Baoues Imen Jegham Safa Ameur Anouar Ben Khalifa Ecole Nationale d’Ingénieurs de Sousse LATIS-Laboratory of Advanced Technology and Intelligent Systems Université de Sousse Sousse Tunisie Université de Jendouba Institut National des Technologies et des Sciences du Kef Le Kef Tunisie

Person Re-Identification is a critical component in modern video surveillance systems for locating individuals across cameras from various viewpoints. However, one of the significant challenges in person ReID arises when facial information is unavailable. To address this issue, we propose GF2PReID, a novel framework that leverages state-of-the-art deep learning-based ReID approaches to generate prior knowledge of the face region and provide detailed information about human body images. Our approach utilizes a deep residual network model trained with transfer learning to extract discriminative features from images with low discrimination, including low illumination and occlusion, collected from diverse datasets. Experimental results, on 2 challenging datasets: Market-1501 and CUHK03, demonstrate that our GF2PReID framework improves the datasets and significantly improves the performance of the Resnet-50 model, reaching the highest performance.

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Oilwell Downhole RFID Reader based on Discrete Components

Oilwell Downhole RFID Reader based on Discrete Components

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2021 International Conference on Signal Processing and Communication technology, SPCT 2021

作者： Liu, Xiaokun Zhu, Jixuan School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (数字)9781510653344

ISBN: (纸本)9781510653337

RFID (Radio Frequency Identification) is expected to provide a new way for the efficient and low-cost control of oilwell downhole tools, and bring huge economic benefits. However, the RF (radio frequency) base station chips on the market could not withstand the high temperature of downhole. In this paper, discrete components are used to build RF front-end circuits to realize the drive and demodulation functions of RF base station chips. The circuit parameters are adjusted and optimized through circuit simulation. Then, the software and hardware design of the downhole reader are accomplished. Finally, experimental results show that the proposed downhole reader based on discrete components can successfully demodulate and read the tag data. © 2022 SPIE.

关键词： Circuit simulation

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3D Brain Tumor Segmentation Using Modified U-Net Architecture

3D Brain Tumor Segmentation Using Modified U-Net Architectur...

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International Conference on Cyberworlds

作者： Islem Gammoudi Raja Ghozi Mohamed Ali Mahjoub Faculté des Sciences Mathématiques Physiques et Naturelles de Tunis Université de Sousse Ecole Nationale d’Ingénieurs de Sousse LATIS-Laboratory of Advanced Technology and Intelligent Systems Université de Tunis El Manar Tunis Tunisie American University of Bahrain College of Engineering Riffa Bahrain Associate Research meneber of U3S ENIT University of Tunis El Manar UTM Tunisia LATIS-Laboratory of Advanced Technology and Intelligent Systems Université de Sousse Ecole Nationale d’Ingénieurs de Sousse Sousse Tunisie

Brain tumor segmentation from MRIs has been a continuing challenge for radiology and neurology specialists. Therefore, a reliable method that captures the growing and refined data in this regard, is much needed. Among many deep learning techniques having been proposed for medical image analysis, U-Net-based variants are found to the most used models in multimodal medical image segmentation. Moreover, knowing that brain tumors can have various shapes, sizes, and appearances, the segmentation task, using simple block architectures, does not capture all the intricacies of the tumor boundaries and internal structures. Therefore, more complex architectures, such as U-Net and its 3D extensions, are better suited to handle these variations and provide better segmentation results. In this paper, we introduce an enhanced automated 3D brain tumor segmentation network built on the foundation of the 3D U-Net architecture. Through the combination of the advantages of UNet, ResNet, we created a new 3D UNet model with block modifications, based on simple ResNet block, BNet’s, with batch normalization. We used the 2020 Multi-modal Brain Tumor Segmentation Challenge (BraTS2020) data sets to train and validate the proposed model. The BraTS2020 validation data set yielded dice values of 0.86, 0.82 and 0.85 for the Whole Tumor (WT), for Enhancing Tumor core (ET), and for Tumor Core (TC), respectively. The experimental results show that our model significantly outperforms the standard brain tumor segmentation methods.

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Identification of Dynamic Active Sites Among Cu Species Derived from MOFs@CuPc for Electrocatalytic Nitrate Reduction Reaction to Ammonia

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Nano-Micro Letters 2023年第8期15卷 20-34页

作者： Xue‑Yang Ji Ke Sun Zhi‑Kun Liu Xinghui Liu Weikang Dong Xintao Zuo Ruiwen Shao Jun Tao Key Laboratory of Cluster Science of Ministry of Education School of Chemistry and Chemical EngineeringLiangxiang CampusBeijing Institute of TechnologyBeijing 102488People’s Republic of China Department of Chemistry Sungkyunkwan University(SKKU)Suwon 16419Republic of Korea Department of Materials Physics Saveetha School of EngineeringSaveetha Institute of Medical and Technical Sciences(SIMTS)ThandalamChennaiTamilnadu 602105India Beijing Advanced Innovation Center for Intelligent Robots and Systems and Institute of Engineering Medicine Beijing Institute of TechnologyBeijing 100081People’s Republic of China Key Laboratory of Bio‑inspired Smart Interfacial Science and Technology of Ministry of Education School of ChemistryBeihang UniversityBeijing 100191People’s Republic of China

Direct electrochemical nitrate reduction reaction(NITRR)is a promising strategy to alleviate the unbalanced nitrogen cycle while achieving the electrosynthesis of ***,the restructuration of the high-activity Cu-based electrocatalysts in the NITRR process has hindered the identification of dynamical active sites and in-depth investigation of the catalytic ***,Cu species(single-atom,clusters,and nanoparticles)with tunable loading supported on N-doped TiO_(2)/C are successfully manufactured with MOFs@CuPc precursors via the pre-anchor and post-pyrolysis *** behavior among Cu species is co-dependent on the Cu loading and reaction potential,as evidenced by the advanced operando X-ray absorption spectroscopy,and there exists an incompletely reversible transformation of the restructured structure to the initial ***,restructured CuN_(4)&Cu_(4) deliver the high NH_(3) yield of 88.2 mmol h^(−1)g_(cata)^(−1) and FE(~94.3%)at−0.75 V,resulting from the optimal adsorption of NO_(3)^(−) as well as the rapid conversion of^(*)NH_(2)OH to^(*)NH_(2) intermediates originated from the modulation of charge distribution and d-band center for Cu *** work not only uncovers CuN_(4)&Cu_(4) have the promising NITRR but also identifies the dynamic Cu species active sites that play a critical role in the efficient electrocatalytic reduction in nitrate to ammonia.

关键词： Metal-organic frameworks Copper phthalocyanine Electrocatalytic nitrate reduction reaction

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