检索结果-内蒙古大学图书馆

arXiv 2023年

作者： Tang, Peiwang Zhang, Xianchao Institute of Advanced Technology University of Science and Technology of China Hefei230026 China G60 STI Valley Industry & Innovation Institute Jiaxing University Jiaxing314001 China Key Laboratory of Medical Electronics and Digital Health of Zhejiang Province Jiaxing University Jiaxing314001 China Engineering Research Center of Intelligent Human Health Situation Awareness of Zhejiang Provincey Jiaxing University Jiaxing314001 China

The Transformer architecture yields state-of-the-art results in many tasks such as natural language processing (NLP) and computer vision (CV), since the ability to efficiently capture the precise long-range dependency coupling between input sequences. With this advanced capability, however, the quadratic time complexity and high memory usage prevents the Transformer from dealing with long time-series forecasting problem (LTFP). To address these difficulties: (i) we revisit the learned attention patterns of the vanilla self-attention, redesigned the calculation method of self-attention based the Maximum Entropy Principle. (ii) we propose a new method to sparse the self-attention, which can prevent the loss of more important self-attention scores due to random sampling.(iii) We propose Keys/Values Distilling method motivated that a large amount of feature in the original self-attention map is redundant, which can further reduce the time and spatial complexity and make it possible to input longer time-series. Finally, we propose a method that combines the encoder-decoder architecture with seasonal-trend decomposition, i.e., using the encoder-decoder architecture to capture more specific seasonal parts. A large number of experiments on several large-scale datasets show that our Infomaxformer is obviously superior to the existing methods. We expect this to open up a new solution for Transformer to solve LTFP, and exploring the ability of the Transformer architecture to capture much longer temporal dependencies. © 2023, CC BY.

关键词： Time series

来源：评论

学校读者我要写书评

暂无评论

Enhancement of Corrosion Resistance and Antibacterial Properties of Peo Coated Az91d Mg Alloy by Copper- and Phosphate-Based Sealing Treatment

SSRN

引用

SSRN 2023年

作者： Qian, Kun Zhang, Yue Dong, Qiangsheng Shao, Yi Cheng, Zhaojun Ju, Jia Xue, Feng Chu, Chenglin Xia, Dandan Bai, Jing School of Materials Science and Engineering Southeast University Nanjing Jiangsu Jiangning211189 China Jiangsu Key Laboratory for Advanced Metallic Materials Jiangning Jiangsu Nanjing211189 China Southeast University Suzhou215163 China Jiangsu Key Laboratory of Advanced Structural Materials and Application Technology Nanjing Institute of Technology Nanjing211167 China National Engineering Laboratory for Digital and Material Technology of Stomatology Peking University School Hospital of Stomatology Beijing211505 China Beijing Key Laboratory of Digital stomatology Peking University School Hospital of Stomatology Beijing211505 China National Medical Products Administration Key Laboratory for Dental Materials Peking University School Hospital of Stomatology Beijing211505 China Research Center of Engineering and Technology for Digital Dentistry Ministry of Health Peking University School Hospital of Stomatology Beijing211505 China

Preparing dense coatings with both good corrosion resistance and antibacterial properties on the Mg alloys surfaces using conventional surface treatment methods is difficult. In this study, we used a solution containing Cu2+ and phosphate to seal a plasma electrolyte oxidation (PEO) coated AZ91D Mg alloy. After the treatment, a formed dense deposition layer significantly improved the corrosion resistance of the PEO-coated alloy. At the same time, the release of Cu2+ conferred excellent antibacterial properties on the Mg surface. The chemical and physical models for the sealing reaction and corrosion processes were established, providing a theoretical basis for future studies. © 2023, The Authors. All rights reserved.

关键词： Corrosion resistance

来源：评论

学校读者我要写书评

暂无评论

NiCoP nanoleaves array for electrocatalytic alkaline H2 evolution and overall water splitting

引用

Journal of Energy Chemistry 2020年第11期29卷 395-401页

作者： Lei Chen Yaohao Song Yi Liu Liang Xu Jiaqian Qin Yongpeng Lei Yougen Tang State Key Laboratory of Powder Metallurgy Hunan Provincial Key Laboratory of Chemical Power SourcesCollege of Chemistry and Chemical EngineeringCentral South UniversityChangsha 410083HunanChina Energy Materials Computing Center Jiangxi University of Science and TechnologyNanchang 330013JiangxiChina Research Unit of Advanced Materials for Energy Storage Metallurgy and Materials Science Research InstituteChulalongkorn UniversityBangkok 10330Thailand

The development of non-precious, high-efficient and durable electrocatalysts for H2 evolution in alkaline media is highly desirable. Herein we report NiCoP nanoleaves array vertically grown on Ni foam for H2 evolution and overall water splitting via simple hydrothermal treatment and phosphorization. The selfsupported NiCoP nanoleaves architecture contributes to more exposed active sites, the smaller contact resistance between catalyst and substrate, faster ion diffusion and electron transfer. As a result, the optimized electrode requires only overpotentials of 98 and 173 mV to achieve current densities of 10 and100 m A cm-2 in 1.0 M KOH,respectively. Besides, used as both anode and cathode simultaneously, the electrode delivers current densities of 100 and 200 m A cm-2 at cell voltages of only 1.8 and 1.87 V, respectively. Moreover, the relatively high efficiency of about 11.4% for solar-driven water splitting further illustrates the application of our catalyst to sustainable development based on green technologies.

关键词： Electrocatalysis Hydrogen evolution reaction Alkaline media Water splitting Solar-driven electrolysis

来源：评论

学校读者我要写书评

暂无评论

Diff9D: Diffusion-Based Domain-Generalized Category-Level 9-DoF Object Pose Estimation

arXiv

引用

arXiv 2025年

作者： Liu, Jian Sun, Wei Yang, Hui Deng, Pengchao Liu, Chongpei Sebe, Nicu Rahmani, Hossein Mian, Ajmal National Engineering Research Center for Robot Visual Perception and Control Technology College of Electrical and Information Engineering School of Robotics State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Changsha410082 China Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an710049 China Department of Information Engineering and Computer Science University of Trento Trento38123 Italy School of Computing and Communications Lancaster University LA1 4YW United Kingdom Department of Computer Science The University of Western Australia WA6009 Australia

Nine-degrees-of-freedom (9-DoF) object pose and size estimation is crucial for enabling augmented reality and robotic manipulation. Category-level methods have received extensive research attention due to their potential for generalization to intra-class unknown objects. However, these methods require manual collection and labeling of large-scale real-world training data. To address this problem, we introduce a diffusion-based paradigm for domain-generalized category-level 9-DoF object pose estimation. Our motivation is to leverage the latent generalization ability of the diffusion model to address the domain generalization challenge in object pose estimation. This entails training the model exclusively on rendered synthetic data to achieve generalization to real-world scenes. We propose an effective diffusion model to redefine 9-DoF object pose estimation from a generative perspective. Our model does not require any 3D shape priors during training or inference. By employing the Denoising Diffusion Implicit Model, we demonstrate that the reverse diffusion process can be executed in as few as 3 steps, achieving near real-time performance. Finally, we design a robotic grasping system comprising both hardware and software components. Through comprehensive experiments on two benchmark datasets and the real-world robotic system, we show that our method achieves state-of-the-art domain generalization performance. Our code will be made public at https://***/CNJianLiu/Diff9D. Copyright © 2025, The Authors. All rights reserved.

关键词： Augmented reality

来源：评论

学校读者我要写书评

暂无评论

Blockchain-assisted Puncturable Signcryption for Cloud and Fog-Hosted Industrial Cyber-Physical Systems

引用

IEEE Network 2025年

作者： Ma, Qingru Shen, Jian Pandi, Vijayakumar Gupta, Brij B. Arya, Varsha Mahalinghum, Maheswari Zhejiang Sci-Tech University School of Computer Science and Technology School of Artificial Intelligence Hangzhou310018 China Zhejiang Sci-Tech University School of Information Science and Engineering School of Cyber Science and Technology Zhejiang Key Laboratory of Digital Fashion and Data Governance Zhejiang Provincial International Cooperation Base for Science and Technology on Cloud Computing Security and Data Aggregation Hangzhou310018 China Department of Computer Science and Engineering Tamil Nadu Tiruchirappalli620009 India Asia University Department of Computer Science and Information Engineering Taichung413 Taiwan China Medical University Hospital China Medical University Department of Medical Research Taichung Taiwan Pune412115 India School of Cybersecurity Korea University Seoul Korea Republic of Kyung Hee University Seoul02447 Korea Republic of Lebanese American University Beirut1102 Lebanon Center for Interdisciplinary Research Dehradun India Sathyabama Institute of Science and Technology School of Computing Department of Computer Science and Engineering Tamil Nadu Chennai India

The widespread adoption of emerging technologies, such as interconnected sensors and advanced automation systems, has led to rapid advancements in smart industrial environments. While industrial cyber-physical systems (ICPSs) bring efficiency and innovation to industrial processes, the security risks are also of great concern. The existing work provides many methods for data security and authentication for ICPSs. However, since the authentication status of ICPSs is changeable, the up-to-date methods can hardly meet the requirements for rapid authentication and secure data transmission. What’s more, largescale message revocation incurs significant communication and computational costs. This paper proposes a blockchain-assisted identity-based puncturable signcryption (BC-IBPSC) scheme for cloud and fog-hosted ICPSs. First, based on the concepts of puncturable encryption and signature, a novel identity-based puncturable signcryption method is presented to achieve efficient verifiable data encryption. Second, the blockchain is utilized to record all valid and punctured messages, to achieve evidence storage and traceability. The results of the analysis indicate that the scheme ensures security and operates efficiently. In addition, experiments show that the size of the signcrypted files does not affect the value of Gas consumption on the blockchain when uploading proofs. © 2025 IEEE. All rights reserved.

关键词： Authentication

来源：评论

学校读者我要写书评

暂无评论

Scalable Optical Quantum State Synthesizer with Dual-Mode Cavity Memory

arXiv

引用

arXiv 2025年

作者： Hanamura, Fumiya Takase, Kan Hirota, Kazuki Nehra, Rajveer Lang, Florian Miki, Shigehito Terai, Hirotaka Yabuno, Masahiro Kashiwazaki, Takahiro Inoue, Asuka Umeki, Takeshi Asavanant, Warit Endo, Mamoru Yoshikawa, Jun-Ichi Furusawa, Akira Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan Optical Quantum Computing Research Team RIKEN Center for Quantum Computing 2-1 Hirosawa Saitama Wako351-0198 Japan OptQC Corporation 1-16-15 Minami-Ikebukuro Toshima Tokyo Japan Department of Electrical and Computer Engineering University of Massachusetts-Amherst AmherstMA01003 United States Department of Physics University of Massachusetts-Amherst AmherstMA01003 United States Department of Information Technology and Electrical Engineering ETH Zurich Zurich8092 Switzerland Advanced ICT Research Institute National Institute of Information and Communications Technology 588-2 Iwaoka Nishi-ku Hyogo Kobe651-2492 Japan NTT Device Technology Labs NTT Corporation 3-1 Morinosato Wakamiya Kanagawa Atsugi243-0198 Japan

Quantum computing with light is a promising approach to achieving large-scale quantum computation[1–3]. While Gaussian operations on optical states have been successfully scaled[4–6], the generation of highly non-Gaussian states remains a critical challenge for achieving universality and fault-tolerance[7, 8]. However, due to the inherently weak nonlinearity in optics, creating non-Gaussian states remains challenging. A promising solution is to "breed"[9–12] non-Gaussianity by combining multiple weakly non-Gaussian states using quantum memory systems. Here, we propose and demonstrate a scalable method for generating optical non-Gaussian states using a cavity-based quantum memory operating in continuous time. Our memory features dual-mode operation, enabling efficient switching between memory and entangling functionalities, allowing state generation and processing with minimal resources. By employing a time-domain-multiplexed breeding protocol, we successfully generated Wigner-negative states, a key requirement for quantum error correction. This work also marks the first full demonstration of continuous-time cavity-based quantum memory, encompassing the complete processes of writing, storage, and readout. These results represent a significant advancement in quantum information processing with light, providing a scalable method for generating complex non-Gaussian states essential for fault-tolerant quantum computing. Beyond advancing optical quantum computing, the techniques and insights from this work could impact a wide range of applications, from enhancing quantum communication networks to refining quantum sensing and metrology. Copyright © 2025, The Authors. All rights reserved.

关键词： Continuous time systems

来源：评论

学校读者我要写书评

暂无评论

Shifting More Attention to Breast Lesion Segmentation in Ultrasound Videos

arXiv

引用

arXiv 2023年

作者： Lin, Junhao Dai, Qian Zhu, Lei Fu, Huazhu Wang, Qiong Li, Weibin Rao, Wenhao Huang, Xiaoyang Wang, Liansheng School of Informatics Xiamen University Xiamen China Guangzhou China Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong Institute of High Performance Computing Agency for Science Technology and Research Singapore Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China School of Medicine Xiamen University Xiamen China

Breast lesion segmentation in ultrasound (US) videos is essential for diagnosing and treating axillary lymph node metastasis. However, the lack of a well-established and large-scale ultrasound video dataset with high-quality annotations has posed a persistent challenge for the research community. To overcome this issue, we meticulously curated a US video breast lesion segmentation dataset comprising 572 videos and 34,300 annotated frames, covering a wide range of realistic clinical scenarios. Furthermore, we propose a novel frequency and localization feature aggregation network (FLA-Net) that learns temporal features from the frequency domain and predicts additional lesion location positions to assist with breast lesion segmentation. We also devise a localization-based contrastive loss to reduce the lesion location distance between neighboring video frames within the same video and enlarge the location distances between frames from different ultrasound videos. Our experiments on our annotated dataset and two public video polyp segmentation datasets demonstrate that our proposed FLA-Net achieves state-of-the-art performance in breast lesion segmentation in US videos and video polyp segmentation while significantly reducing time and space complexity. Our model and dataset are available at https://***/jhlDet/FLA-Net. Copyright © 2023, The Authors. All rights reserved.

关键词： Location

来源：评论

学校读者我要写书评

暂无评论

Decision-focused Graph Neural Networks for Graph Learning and Optimization

Decision-focused Graph Neural Networks for Graph Learning an...

引用

IEEE International Conference on Data Mining (ICDM)

作者： Yang Liu Chuan Zhou Peng Zhang Shuai Zhang Xiaoou Zhang Zhao Li Hongyang Chen Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou China Institute of Information Engineering Chinese Academy of Sciences Beijing China Hangzhou Yugu Technology Co. Ltd. Hangzhou China Research Center for Graph Computing Zhejiang Lab Hangzhou China

Decision-focused learning (DFL) combines both machine learning and combinatorial optimization so as to enhance the quality of decision-making. In general, DFL adds an optimization layer after the neural network and solves a focused combinatorial optimization problem. The optimization layer is usually based on KKT conditions or surrogate functions. However, the optimizer associated with the DFL is inflexible and requires a large amount of expert knowledge. Furthermore, it has been shown that the optimizer exhibits a lack of robustness and differentiability when confronted with complex tasks, especially in the graph domain. To solve this problem, we study a more generic situation by taking the optimization layer as a black-box operator on graphs. Then, we design a mixed zeroth-order optimization to differentiate the layer. Specifically, we combine DFL with graph neural networks and present a decision-focused graph neural network named ZO4Graph based on a mixed zeroth-order optimizer. Empirically, we conduct extensive experiments compared with two-stage models on community detection. Numerical results demonstrate that our proposed framework outperforms its peers.

关键词：

来源：评论

学校读者我要写书评

暂无评论

On the dual advantage of placing observations through forward sensitivity analysis

arXiv

引用

arXiv 2023年

作者： Ahmed, Shady E. San, Omer Lakshmivarahan, Sivaramakrishnan Lewis, John M. Advanced Computing Mathematics and Data Division Pacific Northwest National Laboratory RichlandWA99354 United States School of Mechanical & Aerospace Engineering Oklahoma State University StillwaterOK74078 United States School of Computer Science University of Oklahoma NormanOK73019 United States Desert Research Institute RenoNV89512 United States

The four-dimensional variational data assimilation methodology for assimilating noisy observations into a deterministic model has been the workhorse of forecasting centers for over three decades. While this method provides a computationally efficient framework for dynamic data assimilation, it is largely silent on the important question concerning the minimum number and placement of observations. To answer this question, we demonstrate the dual advantage of placing the observations where the square of the sensitivity of the model solution with respect to the unknown control variables, called forward sensitivities, attains its maximum. Therefore, we can force the observability Gramian to be of full rank, which in turn guarantees efficient recovery of the optimal values of the control variables, which is the first of the two advantages of this strategy. We further show that the proposed strategy of placing observations has another inherent optimality: the square of the sensitivity of the optimal estimates of the control with respect to the observations (used to obtain these estimates) attains its minimum value, a second advantage that is a direct consequence of the above strategy for placing observations. Our analytical framework and numerical experiments on linear and nonlinear systems confirm the effectiveness of our proposed strategy. © 2023, CC BY.

关键词： Inverse problems

来源：评论

学校读者我要写书评

暂无评论

The ERN Cryo-EM Federated Instrument Pilot Project: Phase 1

The ERN Cryo-EM Federated Instrument Pilot Project: Phase 1

引用

IEEE/ACM Annual Workshop on Large-scale Experiment-in-the-Loop computing (XLOOP)

作者： Maureen Dougherty Jason Kaelber James Barr von Oehsen Morgan Ludwig Kenneth Dalenberg Jeremy Schafer Michael Zink Boyd Wilson John Goodhue Wolf Hey D. Balamurugan Ecosystem for Research Networking New Brunswick USA Institute for Quantitative Biomedicine Rutgers University New Brunswick USA Office of Advanced Research Computing Rutgers University New Brunswick USA TechSquare Cambridge USA Electrical and Computer Engineering University of Massachusetts Amherst Amherst USA Omnibond Clemson USA Massachusetts Green High Performance Computing Center Holyoke USA Institute for Computational and Data Sciences Pennsylvania State University State College USA

ISBN: (纸本)9781665473613

The Ecosystem for research Networking (ERN) CryoEM Remote Instrument Pilot Project was launched in response to feedback and survey data collected from hundreds of participants of the ERN series of NSF (OAC-2018927) funded community outreach events revealing that Structural Biology instrument driven science is being forced to transition from self-contained islands to federated wide-area internet accessible instruments. Its goal is to facilitate multi-institutional collaboration at the interface of computing and electron microscopy through the implementation of the ERN Federated OpenCI Lab’s Instrument CI Cloudlet design. The conclusion will be a web-based portal leveraging federated access to the instrument, workflows utilizing edge computing in conjunction with cloud computing and real-time monitoring for experimental parameter adjustments and decisions. The intention is to foster team science and scientific innovation, with emphasis on under-represented and under-resourced institutions, through the democratization of these scientific instruments. This paper discusses the latest Phase 1 deployment efforts

关键词： Cloud computing Instruments Ecosystems Collaboration Documentation Real-time systems Software

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：