检索结果-内蒙古大学图书馆

Recent advances on monolithic perovskite-organic tandem solar cells

Interdisciplinary Materials 2024年第1期3卷 113-132页

作者： Guanshui Xie Huan Li Longbin Qiu Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems Department of Mechanical and Energy EngineeringSUSTech Energy Institute for Carbon NeutralitySouthern University of Science and TechnologyShenzhenChina

Perovskite-organic tandem solar cells(TSCs)have emerged as a groundbreaking technology in the realm of photovoltaics,showcasing remarkable enhancements in efficiency and significant potential for practical ***-organic TSCs also exhibit facile fabrication surpassing that of all-perovskite or all-organic TSCs,attributing to the advantageous utilization of orthogonal solvents enabling sequential solution process for each *** perovskite-organic TSCs capitalize on the complementary light absorption characteristics of perovskite and organic *** is a promising prospect of achieving further enhanced power conversion efficiencies by covering a broad range of the solar spectrum with optimized perovskite absorber,organic semiconductors as well as the interconnecting layer's optical and electrical *** review comprehensively analyzes the recent advancements in perovskite-organic TSCs,highlighting the synergistic effects of combining perovskite with a low open-circuit voltage deficit,organic materials with broader light absorption,and interconnecting layers with reduced optical and electrical ***,the underlying device architecture design,regulation strategies,and key challenges facing the high performance of the perovskite-organic TSCs are also discussed.

关键词： interconnecting layer narrow‐bandgap organic solar cells recombination layer tandem solar cells wide‐bandgap perovskite solar cells

来源：评论

学校读者我要写书评

暂无评论

Hydrogel bioadhesives harnessing nanoscale phase separation for Achilles tendon repairing

引用

Nano Research 2024年第2期17卷 778-787页

作者： Jun Zhang Xingmei Chen Jingseng Lin Pei Zhang Iek Man Lei Yue Tao Jiajun Zhang Tian Luo Ji Liu Department of Mechanical and Energy Engineering Southern University of Science and TechnologyShenzhen 518055China Research and Innovation Center SKG Health TechnologyShenzhen 518000China SAFE(Shenzhen)Medical Technology Company Limited Shenzhen 518000China Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems Department of Mechanical and Energy EngineeringSouthern University of Science and TechnologyShenzhen 518055China Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and TechnologyShenzhen 518055China

Repairing Achilles tendon has emerged as a long-standing challenge in the orthopaedic *** suture is the gold standard for re-attaching and repairing the fractured Achilles tendons in clinical surgeries,it is still subjected to numerous adverse side-effects,including chronic inflammatory,tendon tissue re-rupture,scar formation,and post-surgical peritendinous *** this work,we develop a class of hydrogel bioadhesives with tailored nanoscale phase separation for Achilles tendon *** address the existing limitations of sutures,our hydrogel bioadhesives encompass three core functionalities:(i)instant and tough adhesion to Achilles tendon tissues,(ii)extraordinary long-term adhesion robustness under wet and dynamic in vivo conditions,and(iii)anti-postsurgical peritendinous *** our hydrogel bioadhesives with sutures,such kind of integrated approach enables a conformable yet robust biointerface with the tendon tissues,and prevents the fibroblast migration and formation of connective tissues,thus facilitating the tendon *** hydrogel bioadhesives reported here open up new opportunities for the repairing of fractured Achilles tendons in diverse and complicated clinical scenarios.

关键词： hydrogels phase separation bioadhesion robustness tendon repairing

来源：评论

学校读者我要写书评

暂无评论

Biomimetic Multi-UAV Swarm Exploration with U2U Communications Under Resource Constraints

引用

IEEE Transactions on Vehicular technology 2025年第6期74卷 9750-9766页

作者： Huang, Yuanhao Wang, Hao Bai, Xuesong Cai, Xuan Yu, Haiyang Ren, Yilong Beihang University School of Transportation Science and Engineering Beijing100191 China State Key Lab of Intelligent Transportation System Beijing100191 China Dalian University of Technology School of Computer Science and Technology Dalian China Zhongguancun Laboratory Beijing100094 China

Existing multi-agent algorithms struggle with spatial coordination and require extensive prior environmental information for effective large-scale operation. This study introduces an innovative multi-UAV system that employs an evolutionary algorithm, reconceptualizing collaborative search tasks as a multi-objective cooperative challenge. Inspired by bacteria's stochastic exploration for pheromones, the algorithm utilizes pheromone concentration and gradient effects to enhance multi-source exploration's efficiency and robustness. A bespoke multi-UAV framework with UAV-to-UAV (U2U) communication was developed to implement and test the algorithm. Comprehensive experiments tested various chemotaxis strategies, guidance strengths, team sizes, and starting conditions, demonstrating the algorithm's consistent effectiveness in expansive terrains without relying on prior information. © 1967-2012 IEEE.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

GooDFlight: Goal-Oriented Diffusion Model for Flight Trajectory Prediction

引用

IEEE Transactions on Aerospace and Electronic systems 2025年第3期61卷 7447-7465页

作者： Yang, Songru Liu, Liqin Chen, Bowen Cheng, Shaoyuan Shi, Zhenwei Zou, Zhengxia Beihang University Department of Aerospace Intelligent Science and Technology School of Astronautics China Beihang University State Key Laboratory of Virtual Reality Technology and Systems Beijing100191 China Shanghai Artificial Intelligence Laboratory Shanghai200232 China Beijing Institute of Space Mechanics and Electricity Beijing100076 China

Flight trajectory prediction is an essential task in the air traffic control field. Previous approaches to this problem usually follow a single-stage or short-term intention-guided prediction paradigm, which suffers from problems such as insufficient trajectory prediction diversity, limited accuracy and interpretability. Different from existing paradigms, in this paper, we present GooDFlight - A Goal-oriented Diffusion Model for Flight trajectory prediction. GooDFlight is a long-term intention-guided, diversity-emphasizing framework that decouples the flight trajectory prediction process into two stages: goal estimation and trajectory prediction. In the first stage, we propose a One-then-all goal estimation method to sufficiently cover the macro-uncertainty in flight patterns and then tailor the interaction-aware joint goal distribution, which extends the flight intention from a single, deterministic ground truth to the empirical intention distribution from the similar experience. In the second stage, we employ a transformer-based diffusion model to generate stochastic flight trajectories conditioned on the intention estimations, modeling the micro-uncertainty in flight operations under each pattern estimated in stage one. In terms of evaluation metrics, existing metrics have difficulties in accurately reflecting the model's ability to handle the natural uncertainty of trajectories. We further propose a simple yet effective Global-local endpoints Variance (GLeV) metric for evaluating the diversity of predicted trajectories under social acceptance. Our proposed method is validated in-depth on TrajAir, a large-scale dataset collected from the real-world air traffic control environment at the Pittsburgh-Butler Regional Airport, a non-towered general aviation airport. The experimental results demonstrate that the proposed method significantly outperforms other methods in terms of both accuracy and diversity with superior interpretability. © 1965-2011 IEEE.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

The Immense Impact of Reverse Edges on Large Hierarchical Networks

引用

Engineering 2024年第5期36卷 240-249页

作者： Haosen Cao Bin-Bin Hu Xiaoyu Mo Duxin Chen Jianxi Gao Ye Yuan Guanrong Chen Tamás Vicsek Xiaohong Guan Hai-Tao Zhang MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems State Key Laboratory of Intelligent Manufacturing Equipment and TechnologySchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Jiangsu Key Laboratory of Networked Collective Intelligence School of MathematicsSoutheast UniversityNanjing 210096China Department of Computer Science Rensselaer Polytechnic InstituteTroyNY 12180USA Department of Electronic Engineering City University of Hong KongHong Kong 999077China Department of Biological Physics Eötvös UniversityBudapest 1117Hungary MOE Key Laboratory for Intelligent Networks and Network Security School of Automation Science and EngineeringXi’an Jiaotong UniversityXi’an 710049China

Hierarchical networks are frequently encountered in animal groups,gene networks,and artificial engineering systems such as multiple robots,unmanned vehicle systems,smart grids,wind farm networks,and so *** structure of a large directed hierarchical network is often strongly influenced by reverse edges from lower-to higher-level nodes,such as lagging birds’howl in a flock or the opinions of lowerlevel individuals feeding back to higher-level ones in a social *** study reveals that,for most large-scale real hierarchical networks,the majority of the reverse edges do not affect the synchronization process of the entire network;the synchronization process is influenced only by a small part of these reverse edges along specific *** surprisingly,a single effective reverse edge can slow down the synchronization of a huge hierarchical network by over 60%.The effect of such edges depends not on the network size but only on the average in-degree of the involved *** overwhelming majority of active reverse edges turn out to have some kind of“bunching”effect on the information flows of hierarchical networks,which slows down synchronization *** finding refines the current understanding of the role of reverse edges in many natural,social,and engineering hierarchical networks,which might be beneficial for precisely tuning the synchronization rhythms of these *** study also proposes an effective way to attack a hierarchical network by adding a malicious reverse edge to it and provides some guidance for protecting a network by screening out the specific small proportion of vulnerable nodes.

关键词： Synchronizability Large hierarchical networks Reverse edges Information flows Complex networks

来源：评论

学校读者我要写书评

暂无评论

The Methodology of Mask Detection Employing the YOLOv7 Framework 4

The Methodology of Mask Detection Employing the YOLOv7 Frame...

引用

4th International Conference on Neural Networks, Information and Communication Engineering, NNICE 2024

作者： Zhang, Fucheng Tian, Pinfang Wuhan University of Science and Technology School of Computer Science and Technology Wuhan China Hubei Key Laboratory of Intelligent Information Processing and Real-TimeIndustrial Systems Wuhan China

ISBN: (纸本)9798350394375

In the current field of object detection, the YOLOv7 model demonstrates significant advantages in terms of both detection speed and accuracy. However, the model shows deficiencies in focussing on key information, and its loss function's sensitivity to bounding boxes results in suboptimal performance in densely populated environments and small target detection scenarios. To address these issues, this study proposes a mask target detection method based on YOLOv7. By integrating a channel attention mechanism into the YOLOv7 model, this method enhances the model's focus on important information in images, effectively reducing interference from background factors. Additionally, the method incorporates Normalized Wasserstein Distance (NWD) into the loss function to optimize the model's evaluation of small target detection. Experimental verification shows that the improved model maintains its original detection speed while increasing the overall accuracy to 92.1%, a 2.9% improvement over the original YOLOv7 model. It achieves a 3.3% increase in the mAP.5 metric. This indicates that the optimised YOLOv7 model has superior detection capabilities, allowing it to perform mask-wearing detection tasks more rapidly and accurately in natural environments. © 2024 IEEE.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Continuous-Time Prediction of Industrial Paste Thickener System With Differential ODE-Net

引用

IEEE/CAA Journal of Automatica Sinica 2022年第4期9卷 686-698页

作者： Zhaolin Yuan Xiaorui Li Di Wu Xiaojuan Ban Nai-Qi Wu Hong-Ning Dai Hao Wang the Beijing Advanced Innovation Center for Materials Genome Engineering Institute of Artificial IntelligenceBeijing Key Laboratory of Knowledge Engineering for Materials ScienceSchool of Computer and Communication EngineeringUniversity of Science and Technology Beijing the Department of ICT and Natural Science Norwegian University of Science and Technology IEEE the Institute of Systems Engineering and Collaborative Laboratory for Intelligent Science and SystemsMacao University of Science and Technology the Department of Computing and Decision Sciences Lingnan University the Department of Computer Science Norwegian University of Science and Technology

It is crucial to predict the outputs of a thickening system,including the underflow concentration(UC)and mud pressure,for optimal control of the *** proliferation of industrial sensors and the availability of thickening-system data make this ***,the unique properties of thickening systems,such as the non-linearities,long-time delays,partially observed data,and continuous time evolution pose challenges on building data-driven predictive *** address the above challenges,we establish an integrated,deep-learning,continuous time network structure that consists of a sequential encoder,a state decoder,and a derivative module to learn the deterministic state space model from thickening *** a case study,we examine our methods with a tailing thickener manufactured by the FLSmidth installed with massive sensors and obtain extensive experimental *** results demonstrate that the proposed continuous-time model with the sequential encoder achieves better prediction performances than the existing discrete-time models and reduces the negative effects from long time delays by extracting features from historical system *** proposed method also demonstrates outstanding performances for both short and long term prediction tasks with the two proposed derivative types.

关键词： Industrial 24 paste thickener ordinary differential equation(ODE)-net recurrent neural network time series prediction

来源：评论

学校读者我要写书评

暂无评论

Distributed Optimization and Scaling Design for Solving Sylvester Equations

引用

Journal of systems science & Complexity 2024年第6期37卷 2487-2510页

作者： CHENG Songsong YU Xin ZENG Xianlin LIANG Shu HONG Yiguang Anhui Engineering Laboratory of Human-Robot Integration System and Intelligent Equipment School of Electrical Engineering and AutomationAnhui UniversityHefei 230601China Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Control Science and Engineering Tongji UniversityShanghai 201804China Shanghai Research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 201210China

This paper develops distributed algorithms for solving Sylvester *** authors transform solving Sylvester equations into a distributed optimization problem,unifying all eight standard distributed matrix *** the authors propose a distributed algorithm to find the least squares solution and achieve an explicit linear convergence *** results are obtained by carefully choosing the step-size of the algorithm,which requires particular information of data and Laplacian *** avoid these centralized quantities,the authors further develop a distributed scaling technique by using local information *** a result,the proposed distributed algorithm along with the distributed scaling design yields a universal method for solving Sylvester equations over a multi-agent network with the constant step-size freely chosen from configurable ***,the authors provide three examples to illustrate the effectiveness of the proposed algorithms.

关键词： Distributed optimization least squares solution linear convergence rate step-size interval Sylvester equation

来源：评论

学校读者我要写书评

暂无评论

Learning to Branch in Combinatorial Optimization With Graph Pointer Networks

引用

IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 157-169页

作者： Rui Wang Zhiming Zhou Kaiwen Li Tao Zhang Ling Wang Xin Xu Xiangke Liao IEEE the Xiangjiang Laboratory and the College of Systems Engineering National University of Defense TechnologyChangsha 410073China the Institute of Automation Chinese Academy of SciencesBeijing 100190China the College of Systems Engineering National University of Defense TechnologyChangsha 410073 the Hunan Key Laboratory of Multi-Energy System Intelligent Interconnection Technology Changsha 410073China the Department of Automation Tsinghua UniversityBeijing 100084China the College of Intelligence Science and Technology National University of Defense TechnologyChangsha 410073China the College of Computer Science and Technology National University of Defense TechnologyChangsha 410073China

Traditional expert-designed branching rules in branch-and-bound(B&B) are static, often failing to adapt to diverse and evolving problem instances. Crafting these rules is labor-intensive, and may not scale well with complex *** the frequent need to solve varied combinatorial optimization problems, leveraging statistical learning to auto-tune B&B algorithms for specific problem classes becomes attractive. This paper proposes a graph pointer network model to learn the branch rules. Graph features, global features and historical features are designated to represent the solver state. The graph neural network processes graph features, while the pointer mechanism assimilates the global and historical features to finally determine the variable on which to branch. The model is trained to imitate the expert strong branching rule by a tailored top-k Kullback-Leibler divergence loss function. Experiments on a series of benchmark problems demonstrate that the proposed approach significantly outperforms the widely used expert-designed branching rules. It also outperforms state-of-the-art machine-learning-based branch-and-bound methods in terms of solving speed and search tree size on all the test instances. In addition, the model can generalize to unseen instances and scale to larger instances.

关键词： Branch-and-bound(B&B) combinatorial optimization deep learning graph neural network imitation learning

来源：评论

学校读者我要写书评

暂无评论

Data-Driven Control of Distributed Event-Triggered Network systems

引用

IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 351-364页

作者： Xin Wang Jian Sun Gang Wang Frank Allgower Jie Chen the National Key Laboratory of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081 the Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China IEEE the Institute for Systems Theory and Automatic Control University of StuttgartStuttgart 70550Germany the Department of Control Science and Engineering Tongji UniversityShanghai 201804 the National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing Institute of TechnologyBeijing 100081China

The present paper deals with data-driven event-triggered control of a class of unknown discrete-time interconnected systems(*** systems).To this end,we start by putting forth a novel distributed event-triggering transmission strategy based on periodic sampling,under which a model-based stability criterion for the closed-loop network system is derived,by leveraging a discrete-time looped-functional *** the model-based criterion with a data-driven system representation recently developed in the literature,a purely data-driven stability criterion expressed in the form of linear matrix inequalities(LMIs)is ***,the data-driven stability criterion suggests a means for co-designing the event-triggering coefficient matrix and the feedback control gain matrix using only some offline collected state-input ***,numerical results corroborate the efficacy of the proposed distributed data-driven event-triggered network system(ETS)in cutting off data transmissions and the co-design procedure.

关键词： Data-driven control distributed event-triggered network system(ETS) linear matrix inequalitie(LMI) looped-functional stability

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：