检索结果-内蒙古大学图书馆

SSRN 2023年

作者： Luo, Xiaobo Hu, Songhan Duan, Qiudong Zhou, Dacheng Wang, Qi Yang, Yong Chen, Jialin Wen, Yugeng Qiu, Jianbei Faculty of Material Science and Engineering Kunming University of Science and Technology Kunming650093 China Key Lab. of Advanced Materials of Yunnan Province Kunming650093 China Key Laboratory of Electromagnetic Processing of Materials Ministry of Education Northeastern University Shenyang110819 China School of Materials Science and Engineering Northeastern University Shenyang110819 China Key Laboratory of Advanced Technologyies for Comprehensive Utihzatron of Platinum Metal China

The exploration of the solar light absorption by a material is of great use in photonics and optoelectronics. However, the fully exploiting of the solar spectrum of well-known wide-bandgap perovskite oxides (2.7–5 eV), remains very challenging. We show that the selective occupation of Bi3+ in the octahedrally coordinated Ba2+ is responsible for creating sub-bandgap states (as low as 0.6 eV), nearly 9 times lower than pristine bandgap (5.2 eV). We reveal that the role of the 6s6p excited state of Bi3+ is as a bridge to promote the dipole-allowed band-band transition for strong absorption. Furthermore, we demonstrate the double-sided laser printing of three-dimensional optical imaging based on the photothermal effect, enabling write-once-read-many information storage with ultrahigh stability and good data retention. Our results make Ba3–xGa2O6:xBi3+ a promising candidate for photovoltaics, ferroelectrics, photocatalysis, broadband photodetectors as well as other photonic and optoelectronic applications. © 2023, The Authors. All rights reserved.

关键词： Light absorption

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KADEL: knowledge-Aware Denoising Learning for Commit Message Generation

arXiv

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arXiv 2024年

作者： Tao, Wei Zhou, Yucheng Wang, Yanlin Zhang, Hongyu Wang, Haofen Zhang, Wenqiang Shanghai Engineering Research Center of AI and Robotics Academy for Engineering and Technology Fudan University Shanghai China State Key Laboratory of Internet of Things for Smart City Department of Computer and Information Science University of Macau China School of Software Engineering Sun Yat-sen University Guangdong Zhuhai519082 China School of Big Data and Software Engineering Chongqing University Chongqing China College of Design and Innovation Tongji University Shanghai China Engineering Research Center of AI and Robotics Ministry of Education Academy for Engineering and Technology Shanghai Key Lab of Intelligent Information Processing School of Computer Science Fudan University 220 Handan Road Shanghai200433 China

Commit messages are natural language descriptions of code changes, which are important for software evolution such as code understanding and maintenance. However, previous methods are trained on the entire dataset without considering the fact that a portion of commit messages adhere to good practice (i.e., good-practice commits), while the rest do not. On the basis of our empirical study, we discover that training on good-practice commits significantly contributes to the commit message generation. Motivated by this finding, we propose a novel knowledge-aware denoising learning method called KADEL. Considering that good-practice commits constitute only a small proportion of the dataset, we align the remaining training samples with these good-practice commits. To achieve this, we propose a model that learns the commit knowledge by training on good-practice commits. This knowledge model enables supplementing more information for training samples that do not conform to good practice. However, since the supplementary information may contain noise or prediction errors, we propose a dynamic denoising training method. This method composes a distribution-aware confidence function and a dynamic distribution list, which enhances the effectiveness of the training process. Experimental results on the whole MCMD dataset demonstrate that our method overall achieves state-of-the-art performance compared with previous methods. © 2024, CC BY.

关键词： Sampling

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An Expressed and Private Opinion Model on Influence Networks 2

An Expressed and Private Opinion Model on Influence Networks

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2nd International Conference on Industrial Artificial Intelligence, IAI 2020

作者： Xia, Weiguo Liang, Hong Key Lab. of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education School of Control Science and Engineering Dalian University of Technology China

ISBN: (数字)9781728182162

ISBN: (纸本)9781728182162

This paper studies the evolution of an expressed and private opinion dynamics model with asynchronous updating. It is shown that under some mild connectivity and individual activation conditions, the expressed and private opinions of all individuals in the network converge to a common value exponentially fast when the susceptibility to influence of all individuals is equal to one. A numerical example verifies the theoretical result. © 2020 IEEE.

关键词： Social networking (online) Sociology Numerical models Ions Heuristic algorithms Convergence Statistics

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Co-Optimization Method for Modular Robots Based on Evolutionary Algorithm

Co-Optimization Method for Modular Robots Based on Evolution...

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On-Line Conference (ONCON), Industrial Electronics Society Annual

作者： Peng Zhao Meibao Yao Bo Zheng Xueming Xiao Intelligent Robotics Lab (IRL) School of Artificial Intelligence Jilin University Changchun China Engineering Research Center of Knowledge-Driven Human-Machine Intelligence Ministry of Education China Shanghai Aerospace Control Technology Institute Shanghai China CVIR Lab Changchun University of Science and Technology Changchun China Key Lab of Optoelectronic Measurement and Optical Information Transmission Technology

Deploying robots instead of human lab.r in complex and hazardous environments is a highly effective strategy. However, current fixed-configuration robot platforms struggle to meet the demanding exploration requirements in non-structured environments. In contrast, reconfigurable modular robots are able to adjust their configurations in response to environmental and task requirements, thereby offering immense potential for tackling complex exploration tasks in unstructured environments. This versatility of reconfigurable modular robots allows them to better adapt to various environmental and task demands, such as using snake or caterpillar configurations to navigate narrow holes, or quadruped configurations to traverse rugged terrain. However, the current research on modular robots primarily focuses on optimizing either their own configurations or solely the motion control model, potentially limiting their adaptability to the environment and hindering the full realization of their reconfigurability. To address this limitation, this paper improves upon traditional EA and proposes a configuration-motion co-optimization method and a new encoding method for modular robots, which jointly models and optimizes both configuration and motion. The method includes dynamic encoding of configuration-motion and the design of compatible operators, effectively enhancing the adaptive capabilities of modular robots in complex environments. The method was validated using the Webots platform, and the results demonstrate successful generation of adaptable reconfiguration schemes for various terrains. Compared to traditional EA, this method has shown superior performance in handling diverse tasks.

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A Mars Multi-terrain Simulator Using a Modular Terrain Construction Framework

A Mars Multi-terrain Simulator Using a Modular Terrain Const...

引用

On-Line Conference (ONCON), Industrial Electronics Society Annual

作者： Yun Jiang Meibao Yao Bo Zheng Tao Hu Tao Cao Xueming Xiao Intelligent Robotics Lab (IRL) School of Artificial Intelligence Jilin University Changchun China Engineering Research Center of Knowledge-Driven Human-Machine Intelligence Ministry of Education China Shanghai Aerospace Control Technology Institute Shanghai China CVIR Lab Changchun University of Science and Technology Changchun China Key Lab of Optoelectronic Measurement and Optical Information Transmission Technology

Mars exploration tasks are inseparable from the support of robotic equipment. More comprehensive environmental awareness capabilities can improve the efficiency of robots on the surface of Mars. Artificial neural networks have emerged as pivotal tools in enhancing the perceptual capabilities of robots. The cornerstone of effective neural network training lies in the availab.lity of high-quality data. Regrettably, the unstructured terrains, particularly the Martian landscape, lack real-world datasets with high-quality annotations. To overcome this challenge, using simulators to generate large amounts of high-quality data for researchers is a good option. Nonetheless, the creation of these simulators requires complex details such as ground texture characteristics and rock distribution, which increases research costs. In response, we introduce a novel approach – the modular terrain construction framework and construct a Mars multi-terrain simulator based on it. This innovative simulator not only simplifies the simulation process but also grants users the flexibility to alter it to their specific research needs. One of the standout features of our simulator is its capacity to generate rich metadata, such as semantic and depth, which can be used seamlessly for a multitude of downstream applications. To validate the reliability of the data produced by our simulator, we have assessed its performance on a semantic segmentation task.

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Simulation of Acquired LQT Syndrome Using Human Virtual Ventricular Cardiomyocyte Model

Simulation of Acquired LQT Syndrome Using Human Virtual Vent...

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2022 Computing in Cardiology, CinC 2022

作者： Zhao, Shumo Luo, Cunjin He, Ying Li, Linghua School of Computer Science and Electronic Engineering University of Essex Colchester United Kingdom Key Lab. of Medical Electrophysiology of Ministry of Education and Medical Electrophysiological Key Laboratory of Sichuan Province Collaborative Innovation Center for Prevention and Treatment of Cardiovascular Disease Institute of Cardiovascular Research Southwest Medical University Luzhou China School of Computer Science University of Nottingham Nottingham United Kingdom School of Integrative Medicine Southwest Medical University Luzhou China

ISBN: (纸本)9798350300970

Acquired long QT syndrome is a cardiac channelopathy, usually manifested by prolonged QT intervals in the electrocardiogram, which can lead to arrhythmias and an increased risk of sudden death. However, there is a diversity of drugs that target LQT syndrome. In this study, we simulated acquired LQT syndrome on a model of human ventricular cardiomyocytes and tested the therapeutic effects of potassium supplements and the L-type calcium blocker nifedipine on this basis. The results showed that the L-type calcium blocker and potassium ion supplementation could effectively shorten the action potential and QT interval of the ECG in cardiomyocytes and shorten the effective nonresponse period. Taken together, this study provides data to support the use of calcium channel blockers and potassium supplementation as a new treatment for LQTS. © 2022 Creative Commons.

关键词： Electrocardiograms

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Robot Manipulator Control via Solving Four-Layered Time-Variant Equations Including Linear, Nonlinear Equalities and Inequalities 11

Robot Manipulator Control via Solving Four-Layered Time-Vari...

引用

11th International Conference on Intelligent Control and Information Processing, ICICIP 2021

作者： Zhu, Xinhui Zhang, Li Shi, Yang Wang, Jing Li, Jian Xinyang Normal University School of Computer and Information Technology Xinyang464000 China Henan Key Lab. of Analysis and Application of Education Big Data Xinyang Normal University Xinyang464000 China Yangzhou University School of Information Engineering Yangzhou225127 China

ISBN: (纸本)9781665425155

Robot manipulator control is a complicated multi-tasking problem in reality. It includes not only basic tracking task, but also additional tasks, such as conquering joint angle limits, posture control. However, most existing works only consider the goal of tracking and formulate it as single-layered time-variant problems, which leads to impracticality. In this work, robot manipulator control problem is formulated as four-layered time-variant equations including linear, nonlinear equalities and inequalities. Each layer formulates one subtask: The first layer of nonlinear equality describes basic tracking task based on forward kinematics;The second layer and third layer are inequalities, which describe joint angle upper and lower limits;The last layer is a linear equality with respect to joint angle velocity, which could be designed by user to describe other task, such as posture control. To solve this complicated four-layered time-variant problem, it is converted as single-layered equation based on the zeroing neural dynamics method. Then, continuous-time solution is proposed. Furthermore, discrete-time algorithm is proposed based on a third-order time-discretization formula and continuous-time solution. Numerical experiments illustrate the effectiveness and superiority compared to existing work. © 2021 IEEE.

关键词： Industrial robots

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Improving Generalization of Neural Vehicle Routing Problem Solvers Through the Lens of Model Architecture

arXiv

引用

arXiv 2024年

作者： Xiao, Yubin Wang, Di Wu, Xuan Wu, Yuesong Li, Boyang Du, Wei Wang, Liupu Zhou, You Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education College of Computer Science and Technology Jilin University Changchun130012 China Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly Nanyang Technological University 639956 Singapore WeBank-NTU Joint Research Institute on Fintech Nanyang Technological University 639956 Singapore College of Computing and Data Science Nanyang Technological University 639956 Singapore

Neural models produce promising results when solving Vehicle Routing Problems (VRPs), but may often fall short in generalization. Recent attempts to enhance model generalization often incur unnecessarily large training cost or cannot be directly applied to other models solving different VRP variants. To address these issues, we take a novel perspective on model architecture in this study. Specifically, we propose a plug-and-play Entropy-based Scaling Factor (ESF) and a Distribution-Specific (DS) decoder to enhance the size and distribution generalization, respectively. ESF adjusts the attention weight pattern of the model towards familiar ones discovered during training when solving VRPs of varying sizes. The DS decoder explicitly models VRPs of multiple training distribution patterns through multiple auxiliary light decoders, expanding the model representation space to encompass a broader range of distributional scenarios. We conduct extensive experiments on both synthetic and widely recognized real-world benchmarking datasets and compare the performance with seven baseline models. The results demonstrate the effectiveness of using ESF and DS decoder to obtain a more generalizable model and showcase their applicability to solve different VRP variants, i.e., travelling salesman problem and capacitated VRP. Notably, our proposed generic components require minimal computational resources, and can be effortlessly integrated into conventional generalization strategies to further elevate model generalization. Copyright © 2024, The Authors. All rights reserved.

关键词： Combinatorial optimization

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Multi-objective Aerial Collab.rative Secure Communication Optimization via Generative Diffusion Model-enabled Deep Reinforcement Learning

arXiv

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arXiv 2024年

作者： Zhang, Chuang Sun, Geng Li, Jiahui Wu, Qingqing Wang, Jiacheng Niyato, Dusit Liu, Yuanwei The College of Computer Science and Technology Jilin University Changchun130012 China The Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China The College of Computer Science and Technology Jilin University Changchun130012 China The College of Computing and Data Science Nanyang Technological University 639798 Singapore The Department of Electronic Engineering Shanghai Jiao Tong University Shanghai China The College of Computing and Data Science Nanyang Technological University 639798 Singapore The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom

Due to flexibility and low-cost, unmanned aerial vehicles (UAVs) are increasingly crucial for enhancing coverage and functionality of wireless networks. However, incorporating UAVs into next-generation wireless communication systems poses significant challenges, particularly in sustaining high-rate and long-range secure communications against eavesdropping attacks. In this work, we consider a UAV swarm-enabled secure surveillance network system, where a UAV swarm forms a virtual antenna array to transmit sensitive surveillance data to a remote base station (RBS) via collab.rative beamforming (CB) so as to resist mobile eavesdroppers. Specifically, we formulate an aerial secure communication and energy efficiency multi-objective optimization problem (ASCEE-MOP) to maximize the secrecy rate of the system and to minimize the flight energy consumption of the UAV swarm. To address the non-convex, NP-hard and dynamic ASCEE-MOP, we propose a generative diffusion model-enabled twin delayed deep deterministic policy gradient (GDMTD3) method. Specifically, GDMTD3 leverages an innovative application of diffusion models to determine optimal excitation current weights and position decisions of UAVs. The diffusion models can better capture the complex dynamics and the trade-off of the ASCEE-MOP, thereby yielding promising solutions. Simulation results highlight the superior performance of the proposed approach compared with traditional deployment strategies and some other deep reinforcement learning (DRL) benchmarks. Moreover, performance analysis under various parameter settings of GDMTD3 and different numbers of UAVs verifies the robustness of the proposed approach. Copyright © 2024, The Authors. All rights reserved.

关键词： Energy efficiency

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Facile synthesis of zinc-based organic framework for aqueous Hg (Ⅱ) removal: Adsorption performance and mechanism

引用

Nano Materials Science 2021年第4期3卷 429-439页

作者： Biao Zeng Wei Wang Sijin He Guo Lin Wenjia Du Jun Chang Zhao Ding The State Key Laboratory of Refractories and Metallurgy Wuhan University of Science and TechnologyWuhan430081PR China Key Laboratory for Ferrous Mtallurgy and Resources Utilization of Ministry of Education Wuhan University of Science and TechnologyWuhan430081PR China China E-port Data Center Division of Chengdu Chengdu610041PR China Electrochemical Innovation Lab Department of Chemical EngineeringUniversity College London(UCL)LondonWC1E 68TUK College of Material and Chemical Engineering Tongren University Tongren554300GuizhouPR China Department of Mechanical Materials and Aerospace Engineering Illinois Institute of TechnologyChicagoIL60616 USA

Mercury(Hg)ions can lead to a serious impact on the environment;therefore,it was necessary to find an effective method for absorbing these toxic Hg ***,the adsorbent(Zn-AHMT)was synthesized from zinc nitrate and 4-amino 3-hydrazine-5 mercapto-1,2,4-triazole(AHMT)by one-step method and,characterized the microstruc-ture and absorption performance by fourier transform infrared spectroscopy(FTIR),field emission scanning electron microscopy(FESEM),X-ray diffraction(XRD),Brunauer-Emmett Teller(BET),Thermal Gravimetric Analyzer(TGA)and X-ray photoelectron spectroscopy(XPS).Through a plethora of measurements,we found that the maximum adsorption capacity was 802.8 mg/g when the optimal pH of Zn-AHMT was *** isothermal and kinetic experiments confirm that the reaction process of Zn-AHMT was chemisorption,while the adsorption process conforms to the Hill model and pseudo second order kinetic *** experiments showed that the adsorption process was spontaneous and *** experiments were performed in the simulated wastewater containing Mn,Mg,Cr,Al,Co,Ni,Hg *** results showed that the Zn-AHMT has a stronger affinity for Hg *** removal rate of Zn-AHMT remained above 98%,indicating that the Zn-AHMT had a good stability validated by three adsorption-desorption repeatable *** to the XPS results,the adsorption reaction of Zn-AHMT was mainly attributed to the chelation and ion *** was further explained by both density functional theory(DFT)calculation and frontier molecular orbital *** therefore propose the adsorption mechanism of *** adsorption reaction facilitates via the synergistic action of S and N ***,the bonding between the adsorbent and the N atom has been proved to be more *** study demonstrated that Zn-AHMT had a promising application prospect in mercury removal.

关键词： Metal-organic frameworks(MOFs) Hg(Ⅱ) Selectivity Adsorption mechanism

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