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Mapping the antiparallel aligned domain rotation by microwave excitation

Chinese Physics B 2024年第9期33卷 599-605页

作者： Jing Zhang Yuanzhi Cui Xiaoyu Wang Chuang Wang Mengchen Liu Jie Xu Kai Li Yunhe Zhao Zhenyan Lu Lining Pan Chendong Jin Qingfang Liu Jianbo Wang Derang Cao College of Physics Qingdao UniversityQingdao 266071China National Demonstration Center for Experimental Applied Physics Education Qingdao UniversityQingdao 266071China SKLSM Institute of SemiconductorsChinese Academy of SciencesBeijing 100083China College of Chemistry Chemical Engineering and Resource UtilizationNortheast Forestry UniversityHarbin 150040China Hunan Provincial Key Laboratory of Intelligent Sensors and Advanced Sensor Materials School of Physics and ElectronicsHunan University of Science and TechnologyXiangtan 411201China CAS Key Laboratory of Magnetic Materials and Devices Ningbo Institute of Materials Technology and EngineeringChinese Academy of SciencesNingbo 315201China Key Laboratory of Optic-Electronic Information and Materials of Hebei Province Research Center for Computational PhysicsCollege of Physics Science and TechnologyHebei UniversityBaoding 071002China Key Laboratory for Magnetism and Magnetic Materials of Ministry of Education Lanzhou UniversityLanzhou 730000China Key Laboratory of Special Functional Materials and Structural Design Ministry of EducationLanzhou UniversityLanzhou 730000China

The evolution process of magnetic domains in response to external fields is crucial for the modern understanding and application of *** this study,we investigated the domain rotation in stripe domain films of varying thicknesses by examining their response to microwave excitation in four different *** resonance spectra indicate that the rotation field of stripe domain film under an applied magnetic field approaches the field where the resonance mode of sample *** saturation field of the stripe domain film corresponds to the field where the resonance mode disappears when measured in the stripe direction parallel to the microwave magnetic *** results are reproducible and consistent with micromagnetic simulations,providing additional approaches and techniques for comprehending the microscopic mechanisms of magnetic domains and characterizing their rotation.

关键词： stripe domain magnetic film microwave excitation micromagnetic simulation

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Linear-to-Circular Polarization Converter Based on Transmission Metamaterial 4

Linear-to-Circular Polarization Converter Based on Transmiss...

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4th International Applied Computational Electromagnetics Society Symposium in China, ACES-China 2021

作者： Li, Huixiang Wu, Xianliang Zhang, Liang Anhui University Key Laboratory of Intelligent Computing Signal Processing Hefei China Anhui Province Key Laboratory of Simulation and Design for Electronic Information Key Laboratory of Intelligent Computing Signal Processing Hefei Normal University Hefei China

ISBN: (纸本)9781733509619

A broadband transmissive linear-to-circular polarization conversion metamaterial composed of 5-layer '-shaped units was designed, and it was placed directly above the ordinary linear polarization antenna so that the antenna can radiate circular polarization waves. The 3dB axial ratio bandwidth is 11.5GHz-14.5GHz, and the relative axial ratio bandwidth reaches 23%, which proves that the polarization conversion surface has good polarization conversion characteristics. © 2021 Applied Computational Electromagnetics Society (ACES).

关键词： Circular polarization

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Performance Verification of Smith Predictor Control Using IMC Scheme via Chemical Reaction Networks and DNA Strand Displacement Reaction

Performance Verification of Smith Predictor Control Using IM...

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Smart World Congress (SWC), IEEE

作者： Jingwang Yao Hui Lv Yijun Xiao Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Dalian China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China

Biochemical process control is often achieved through feedback control strategies for theoretical analysis and optimization of biochemical reaction processes. Here, the design improves the robustness of the biochemical process by taking advantage of the Smith prediction structure and internal mode control within the chemical reaction network theory framework to intervene against the time delays and perturbations present in the biochemical process. First, an IMC representation of Smith prediction is constructed using the presence of parameter rectification of the control method, and then an IMC-MSP control scheme is proposed. A first-order time-lag controlled object is established in the construction of the IMC-MSP control scheme. Besides, CRNs and kinetic representations are established based on the control structure to facilitate the evaluation of the control system performance. In this paper, CRNs representations of parabolic functions as signal inputs are defined for the first time and optimized for stepping signals to facilitate the design and study of biomolecular circuits. Notably, for the CRNs-based IMC-MSP control scheme, on the one hand, numerical simulation experiments are designed to verify the effectiveness of the whole scheme from multiple perspectives of time delays, external perturbations, and filter tuning parameters; on the other hand, using DNA strand displacement is reflected to verify the feasibility of the whole scheme.

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Construction and Application of the Teaching Cloud Platform for Engineering Drawing Course 12

Construction and Application of the Teaching Cloud Platform ...

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12th IEEE International Conference on Educational and Information Technology, ICEIT 2023

作者： Xue, Yahong Mu, Haozhi Xue, Lijun Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin300384 China

ISBN: (纸本)9781665475518

A cloud platform for engineering drawing course teaching was proposed based on cloud station. The cloud station can solve the common problems existed in engineering drawing course, such as the difficulty of teaching, the heavy work of tutorship, the poor teaching effect, the weak spatial imagination of students, as well as the current difficulty to develop the virtual model resource base and the interaction is not strong. The platform uses Solidworks software to build 3D model library, and combines with CADbro's powerful cloud service and 3D file viewing function to realize the interaction and sharing with cloud model by using web browser. At the same time, we choose bilibili, a popular cultural site for teenagers, to release the explanation videos of exercises, and make use of the convenient way to build the cloud station to integrate, release and manage the resources. The platform realizes self-study and self-test at anytime and anywhere on both PC and mobile devices, and fast jumps the corresponding explanation video and cloud virtual model according to the demand. The virtual model in the cloud can be rotated, cut, distance measured, exploded, parts hidden, moved, 2D viewed and so on by touch. The platform is innovative, extensible, interesting and practical, which can greatly enhance the students' enthusiasm for independent learning, and it can be used reference to the development of engineering drawing teaching resources. © 2023 IEEE.

关键词： 3D modeling

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UWB Non-Line-of-Sight Recognition and Suppression Methodology 15

UWB Non-Line-of-Sight Recognition and Suppression Methodolog...

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15th International Conference on Communication Software and Networks, ICCSN 2023

作者： Ni, Zhengshuai Zhou, Haibo Zhang, Guozheng Xu, Wangbei Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin China School of Mechanical Engineering Tianjin University Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin China

ISBN: (纸本)9798350329360

Ultra-Wide Band (UWB) positioning system has become the main research object in indoor positioning field due to its superior positioning performance. Accuracy at the scale of centimeters is achievable in an ideal positioning scenario. Nonetheless, the intricate and changeable indoor surroundings may cause UWB signals to propagate beyond the line-of-sight (LOS) and weaken in signal strength, resulting in a considerable reduction in the precision of positioning. In this paper, methods for identifying non-line-of-sight (NLOS) errors, alleviating NLOS errors, and integrating multi-sensor information are analyzed and studied to provide reference for improving the NLOS positioning accuracy of UWB. © 2023 IEEE.

关键词： alleviate identify multi-sensor NLOS UWB

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keyword mask pre-training model for the review of standard declaration

Keyword mask pre-training model for the review of standard d...

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International Conference on Computer Engineering and Applications (ICCEA)

作者： Chuang Feng Chao Che Qiang Zhang Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education Dalian University Dalian China School of Computer Science and Technology Dalian University of Technology Dalian China

The review of standard declaration of import and export commodities refers to the evaluation of whether the declaration information of the commodities filled in by enterprises conforms to the customs filling standards according to the standardized declaration catalogue The manual review method cannot meet the actual work needs. Therefore, using text classification algorithm to conduct this task is necessary. The classification method based on the pre-training model would rely on the keywords. However, for the review of standard declaration task, excessive reliance on keywords will reduce the classification effect because of ignoring the overall information of the text. keyword mask pre-training model is proposed. In the fine-tuning stage, the model designs a keyword masking strategy and a keyword blinding strategy. The keyword masking strategy regularizes the BERT model with a mask mechanism, that is, the keywords are reconstructed with other text information except keywords, so that the model focuses on non-keywords information; keyword blinding strategy makes the model unable to distinguish the categories of text information without contextual text information, which can eliminate the influence of keywords on model decision-making. The experimental results on the real customs declaration data set showing that the method in this thesis exceeds the baseline method in terms of precision and true negative rate.

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Temporal Attention Convolution Network for Energy Time Series Forecasting 7

Temporal Attention Convolution Network for Energy Time Serie...

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7th International Symposium on Advances in Electrical, Electronics, and Computer Engineering

作者： Hu, Min Xu, Haijun Wang, Xiaohua Li, Liang Li, Hongbo Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei230009 China Intelligent Interconnected Systems Laboratory of Anhui Province Hefei University of Technology Hefei230009 China MediaTek Hefei230009 China

ISBN: (纸本)9781510656437

Energy time series are characterized by stochasticity, short-term periodicity, and long-term periodicity. Many traditional models such as the autoregressive model, Gaussian process regression are unable to capture the complex time relationships of energy time series. Recurrent neural networks (RNNs), which are widely used for energy time series forecasting, are prone to gradient disappearance or gradient explosion when processing a long sequence data. Thus, RNNs are failed to capture the complete information of the whole long sequence data. To extract complex irregular patterns of energy time series and selectively learn spatio-temporal features, a Temporal Attention Convolution Network (TACN) is proposed in this paper. This structure can extract spatial and temporal features of energy time series, which full filled with our demand. Firstly, to solve the problem that RNNs are prone to information loss when processing the long sequence data, a temporal convolutional network (TCN) is introduced. TCN enables the output to capture the complete information of the whole long sequence data. Then, to reinforce the TCN for extracting effective spatio-temporal features, Squeeze-and-Excitation Network (SENet), a module for computing channel attention, was introduced to this TCN structure. By applying this module, the ability of the acquisition of important channel information has been enhanced. Finally, to further improve the robustness of the model, an autoregressive linear module is constructed to capture the linear relationship among the variables. Experiments on the publicly available datasets Electricity and Solar-Energy show that compare with existing deep learning models, TACN achieves more ideal performance. © 2022 SPIE. All rights reserved.

关键词： Time series

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Nonlinear Dynamic Behavior and Vibration Mechanism of a Large Range Rotating Elastic Beam Under Parallel Misalignment Constraints 10

Nonlinear Dynamic Behavior and Vibration Mechanism of a Larg...

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10th International Conference on Advances in Machinery, Material Science and Engineering Application, MMSE 2024

作者： Zhao, Lei Xu, Meiye Zhai, Ran Jiao, Likuan Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China School of Mechanic Engineering Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9781643685465

Large rotating flexible machines are prone to vibration at high speeds, which is a difficult engineering problem. In this study, we have deeply explored its nonlinear dynamic behavior and vibration mechanism, especially considering the effect of parallel misalignment. Through mathematical modeling and MATLAB simulations, we found that the rotational speed and the amount of misalignment are the key parameters affecting the stability of the system. The results show that the rotational speed and parallel misalignment are the sensitive parameters of the system. When the amount of misalignment is 0.002 mm, with the increase of rotational speed, the elastic beam exhibits nonlinear M-type vibration, doubly periodic and chaotic behaviors, which show high-frequency abrupt excitation;when the angular speed is 50 rad/s, with the increase of the amount of misalignment from 0.001 mm to 0.1 mm, the system exhibits the transformation of doubly periodic, chaotic and proposed periodic motions, and the characteristics of intermittent vibration are significant. These results provide an important theoretical basis for suppressing its nonlinear vibration. © 2024 The Authors.

关键词： Rotating machinery

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PanGu Drug Model: learn a molecule like a human

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Science China(Life Sciences) 2023年第4期66卷 879-882页

作者： Xinyuan Lin Chi Xu Zhaoping Xiong Xinfeng Zhang Ningxi Ni Bolin Ni Jianlong Chang Ruiqing Pan Zidong Wang Fan Yu Qi Tian Hualiang Jiang Mingyue Zheng Nan Qiao Laboratory of Health Intelligence Huawei Cloud Computing Technologies Co.LtdGuizhou 550025China Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and TechnologyShanghaiTech UniversityShanghai 200031China Drug Discovery and Design Center State Key Laboratory of Drug ResearchShanghai Institute of Materia MedicaChinese Academy of SciencesShanghai 201203China

Dear Editor,Recent achievements in large-scale pre-trained models like GPT-3 and PanGu-α have demonstrated astounding performances in many downstream tasks of natural language processing (NLP),confirming AI to be user-oriented for even industrial *** learning has been recognized as the most promising technology for pharmaceuticals,a powerful molecule pre-trained model that could economize researchers’tons of *** the strategic application of AI capabilities to the drug discovery field,we pre-trained a model called PanGu Drug Model with 1.7 billion small molecules from ZINC20 (Irwin et al.,2020),DrugSpaceX(Yang et al.,2021),and UniChem (Chambers et al.,2013).

关键词： fir trained strategic

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Leveraging Slot-Aware Enhancements for Improved Zero-Shot Dialogue State Tracking

Leveraging Slot-Aware Enhancements for Improved Zero-Shot Di...

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Frontiers Technology of Information and Computer (ICFTIC), IEEE International Conference on

作者： Tianhang Song Haolei Hu Xinxin Chen Kangli Zi Henan Institute of Advanced Technology Zhengzhou University Zhengzhou China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Beijing China

ISBN: (数字)9798331541750

ISBN: (纸本)9798331541767

Task-oriented dialogue systems (TOD) aim to help users complete specific tasks through multiple rounds of dialogue, in which Dialogue State Tracking (DST) is a key component. The training of DST models typically necessitates the availability of a substantial corpus of dialogue data with turn-level annotations. However, the collection of such data is both costly and inefficient. Despite the impressive performance of systems based on advanced large language models (LLMs), their closed-source nature restricts the potential for local deployment. To address this challenge, this paper proposes a new zero-shot slot-aware enhanced model (SAE), which introduces a novel coded prompting framework to enhance the DST capability of small parameter models in new domains and task scenarios. In particular, we have devised a prompting framework that employs code to refine task instructions. Furthermore, we have proposed a slot-aware question generation mechanism that generates slot-aware questions based on contextual details in accordance with the dialogue context, thereby enhancing the model's perception and matching capabilities for slots. In order to verify the effectiveness of the model, we conducted experiments on the MultiWOZ dataset. The results show that the SAE model has achieved significant performance improvements in zero-shot DST tasks.

关键词： Training Adaptation models Codes Large language models Computational modeling Termination of employment Predictive models Question generation Data models Context modeling

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