检索结果-内蒙古大学图书馆

Dynamic crushing behavior and energy absorption of hybrid auxetic metamaterial inspired by Islamic motif art

Applied Mathematics and Mechanics(English Edition) 2023年第3期44卷 345-362页

作者： Ruilan TIAN Huaitong GUAN Xuhao LU Xiaolong ZHANG Huanan HAO Wenjie FENG Guanglei ZHANG Department of Engineering Mechanics Hebei Key Laboratory of Mechanics of Intelligent Materials and StructuresShijiazhuang Tiedao UniversityShijiazhuang 050043China State Key Laboratory of Mechanical Behavior and System Safety of Traffic Engineering Structures Shijiazhuang Tiedao UniversityShijiazhuang 050043China School of Materials Science and Engineering Shijiazhuang Tiedao UniversityShijiazhuang 050043China

Auxetic honeycomb structures are promising metamaterials with outstanding mechanical properties,and can be potentially used in energy absorption *** this study,a novel modified re-entrant hybrid auxetic metamaterial inspired by Islamic motif art is designed by integrating four-pointed double re-entrant motifs with symmetric semi-hexagonal unit cells to achieve a high energy absorption capacity(EAC).Theoretical analyses and numerical simulations are performed to examine the dynamic crushing behavior of the four-pointed double re-entrant combined structure(FDRCS).The developed finite element models(FEMs)are validated by the experiments under quasi-static *** deformation mode and stress-strain curves are further studied under low,medium,and high crushing *** theoretically predicted plateau stress of the FDRCS under different crushing velocities is consistent with the numerical simulation *** crushing stress and the EAC of the FDRCS are influenced by the geometric parameters and crushing *** FDRCS exhibits a negative Poisson's ratio(NPR),owing to the four-point re-entrant structure(RES).Moreover,the specific energy absorption(SEA)of these structures is higher than that of nonauxetic hexagonal and auxetic re-entrant structures,owing to the generation of more plastic hinges that dissipate more energy during dynamic crushing.

关键词： re-entrant honeycomb auxetic hybrid metamaterial energy-absorption dynamic crushing

来源：评论

学校读者我要写书评

暂无评论

Continual Learning with a Memory of Non-similar Samples 1

引用

17th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2022

作者： Min, Qilang He, Juanjuan Yang, Liuyan Fu, Yue College of Computer Science and Technology Wuhan University of Science and Technology Wuhan430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan China

ISBN: (数字)9789819915491

ISBN: (纸本)9789819915484

The replay method is an effective strategy to address the problem of catastrophic forgetting, a key challenge for continuous learning. However, the sample sets obtained by replay-based methods generally suffer from local data information deficiencies. This problem leads to an imbalance in the plasticity-stability of the model on older tasks. This paper proposes a novel method, called non-similar sample storage (NSS). Non-similar refers to the Euclidean distance for feature vectors of different samples being far. NSS extracts the feature vectors of the samples and then calculates the similarity of the feature vectors for each sample after the current task training. Samples that contribute less to the model classification effect among similar samples are iteratively deleted, and the subset of low-similarity samples is retained. Moreover, NSS reserves 30% of the storage space for saving samples near the center of the sample set. Low-similarity samples stored by NSS get larger losses during the replay process, leading to lower training effectiveness of the current task. This paper introduces a knowledge distillation strategy to solve this problem. A variable parameter was used to balance the classification loss of the new task with the distillation loss of the old task (NSS-D). Experimental results in CIFAR10 and imbalanced CIFAR10 show that NSS maximizes the data’s global information and can retain the model’s ability to recognize old tasks better. Compared with classical algorithms, NSS-D performs better on CIFAR100 (48.8%) and ImageNet-200 (36.7%). © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Distillation

来源：评论

学校读者我要写书评

暂无评论

pFedCal: Lightweight Personalized Federated Learning with Adaptive Calibration Strategy

引用

IEEE Transactions on Services Computing 2025年第03期18卷 1627-1640页

作者： Deng, Dongshang Wu, Xuangou Zhang, Tao Xiang, Chaocan Zhao, Wei Xu, Minrui Kang, Jiawen Han, Zhu Niyato, Dusit Anhui University of Technology School of Computer Science and Technology Anhui Province Key Laboratory of Digital Twin Technology in Metallurgical Industry Anhui Engineering Research Center for Intelligent Applications and Security of Industrial Internet Ma'anshan243002 China Beijing Jiaotong University School of Cyberspace Science and Technology Beijing100044 China Anhui Provincial Key Laboratory of Digital Twin Technology in Metallurgical Industry Anhui243002 China Chongqing University College of Computer Science Chongqing400044 China Nanyang Technological University School of Computer Science and Engineering 639798 Singapore Guangdong University of Technology School of Automation Guangzhou510062 China University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

Federated learning (FL) is a promising artificial intelligence framework that enables clients to collectively train models with data privacy. However, in real-world scenarios, to construct practical FL frameworks, several challenges have to be addressed, including statistical heterogeneity, constrained resources, and fairness. Therefore, we first investigate an aggregation gap caused by statistical heterogeneity during local model initialization, which not only causes additional computational overhead for clients but also leads to the degradation of fairness. To bridge this gap, we propose pFedCal, a novel personalized federated learning with lightweight adaptive calibration strategy that performs calibration compensation through the prior knowledge of clients. Specifically, we introduce compensation for each client at the model initialization, with the compensation derived from the global gradient and the latest gradient bias. To enhance the calibration effect, we introduce a smoothing-based calibration strategy, and we design an adaptive calibration strategy. A representative example demonstrates that the proposed calibration and smoothing strategies improve fairness for clients. The theoretical analysis indicates that with an appropriate learning rate, pFedCal converges to a first-order stationary point for non-convex loss functions. Comprehensive experimental results show that pFedCal achieves faster convergence, higher accuracy, and improved fairness than the state-of-the-art methods. © 2008-2012 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Strategic Gradient Transmission With Targeted Privacy-Awareness in Model Training: A Stackelberg Game Analysis

IEEE Transactions on Artificial Intelligence

引用

IEEE Transactions on Artificial Intelligence 2024年第9期5卷 4635-4648页

作者： Sun, Hezhe Wang, Yufei Yang, Huiwen Huo, Kaixuan Li, Yuzhe Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110004 China Liaoning ATS Intelligent Transportation Technology Company Ltd. Research Institute Shenyang110004 China The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong999077 Hong Kong

Privacy-aware machine learning paradigms have sparked widespread concern due to their ability to safeguard the local privacy of data owners, preventing the leakage of private information to untrustworthy platforms or malicious third parties. This article focuses on characterizing the interactions between the learner and the data owner within this privacy-aware training process. Here, the data owner hesitates to transmit the original gradient to the learner due to potential cybersecurity issues, such as gradient leakage and membership inference. To address this concern, we propose a Stackelberg game framework that models the training process. In this framework, the data owner's objective is not to maximize the discrepancy between the learner's obtained gradient and the true gradient but rather to ensure that the learner obtains a gradient closely resembling one deliberately designed by the data owner, while the learner's objective is to recover the true gradient as accurately as possible. We derive the optimal encoder and decoder using mismatched cost functions and characterize the equilibrium for specific cases, balancing model accuracy and local privacy. Numerical examples illustrate the main results, and we conclude with expanding discussions to suggest future investigations into reliable countermeasure designs. © 2020 IEEE.

关键词： Game theory

来源：评论

学校读者我要写书评

暂无评论

A Concept-Based Local Interpretable Model-Agnostic Explanation Approach for Deep Neural Networks in Image Classification 13th

A Concept-Based Local Interpretable Model-Agnostic Explanati...

引用

13th IFIP TC 12 International Conference on intelligent Information Processing, IIP 2024

作者： Tan, Lidan Huang, Changwu Yao, Xin Southern University of Science and Technology Shenzhen518055 China Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China

ISBN: (纸本)9783031579189

A well-recognized and widely-used explainable artificial intelligence (XAI) method is Local Interpretable Model-agnostic Explanations (LIME), which offers instance-level interpretation by generating new data around the instance and training a locally interpretable linear model. However, when using LIME to explain the image classification model, it generates interpretations at the level of super-pixel representation. This does not assure comprehensibility to humans due to the lack of semantic information in super-pixels. To enhance the intelligibility of LIME, we propose an advanced version of LIME, termed Concept-based Local Interpretable Model-agnostic Explanations (ConceptLIME). In ConceptLIME, the explanations are formulated in terms of human-understandable concepts as opposed to the semantically deficient super-pixels, thereby augmenting the comprehensibility of the original LIME method. Comparative experiments have been conducted between ConceptLIME and LIME to validate the effectiveness of ConceptLIME. The experimental results indicate that ConceptLIME outperforms LIME regarding predictive performance on both the perturbation dataset and the explained instances. Moreover, the fidelity of the explanations generated by ConceptLIME surpasses that produced by LIME. The interpretations provided by ConceptLIME are more intelligible and intuitive than LIME’s explanations. Consequently, our proposed ConceptLIME exhibits superior properties, including predictive performance, fidelity, and comprehensibility, when compared with LIME. © IFIP International Federation for Information Processing 2024.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Snowball Effect in Federated Learning: An Approach of Exponentially Expanding Structures for Optimizing the Training Efficiency

引用

IEEE Transactions on Cognitive Communications and Networking 2024年第3期11卷 1803-1817页

作者： Cheng, Guoliang Li, Peichun Tan, Beihai Yu, Rong Wu, Yuan Pan, Miao Guangdong University of Technology School of Automation Guangzhou China Guangdong Key Laboratory of IoT Information Technology Guangzhou China University of Macau State Key Laboratory of Internet of Things for Smart City China University of Macau Department of Computer and Information Science China Guangdong University of Technology School of Integrated Circuits Guangzhou China University of Houston Department of Electrical and Computer Engineering Houston United States

Efficient federated learning (FL) in mobile edge networks faces challenges due to energy-consuming on-device training and wireless transmission. Optimizing the neural network structures is an effective approach to achieving energy savings. In this paper, we present a Snowball FL training with expanding neural network structure, which starts with a small-sized submodel and gradually progresses to a full-sized model. To achieve this, we first design the submodel and embedding extraction schemes for fine-grained model structure expansion. We then investigate the joint minimization problem of the global training loss and system-wise energy consumption. After that, we decompose the optimization problem into a long-term model structure expansion subproblem and a single-round local resource allocation subproblem. Specifically, the former subproblem is transformed into a variational calculus problem by leveraging theoretical analysis of the convergence bound. The Euler-Lagrange method is used to derive the solution, where the optimal evolution strategy for the model structure exponentially increases with the global round (i.e., the Snowball effect). Meanwhile, the latter subproblem is solved by convex optimization to acquire the optimal computing frequency and transmission power. Experiments indicate that the proposed framework can save about 50% of energy consumption to achieve on-par accuracy against state-of-the-art algorithms. © 2015 IEEE.

关键词： Resource allocation

来源：评论

学校读者我要写书评

暂无评论

Reshaping the imprinting strategy through the thermo-responsive moiety-derived“deep eutectic solvents”effect

引用

Chinese Chemical Letters 2024年第1期35卷 441-445页

作者： Huihuang Xiong Yiqun Wan Yong Fan Mengjia Xu Aiping Yan Yushan Zhang Qifei Jiang Hao Wan State Key Laboratory of Food Science and Technology Nanchang UniversityNanchang 330047China School of Chemistry and Chemical Engineering Nanchang UniversityNanchang 330031China Jiangxi Province Key Laboratory of Modern Analytical Science Nanchang UniversityNanchang 330031China Department of Computer Science University of California IrvineIrvine 92697United States

As a new concept having emerged in last few years,the“deep eutectic solvents”(DESs)effect integrated into the imprinting technology inevitably exposes design limitations of stimuli-responsive molecularly imprinted polymers(MIPs),as well as inadequate analysis of the adsorption performance of ***,a simple yet defined N-isopropylacrylamide/(3-acrylamidopropyl)trimethylammonium chloride(NIPAM/APTMAC)binary DESs system was proposed to prepare intelligent MIPs with ***,magnetic and thermo-responsive MIPs based on functional monomers-derived DESs(TMDESs-MIPs1)were synthesized,revealing DESs effect-regulated affinity/kinetics for the enhanced adsorption capability,eco-friendly thermo-regulated elution for high release efficiency,and simple magnetic separation,along with superior selectivity to rhein(RH)and good regeneration ***-DESs-MIPs1 were utilized to extract RH from Cassiae semen samples coupled with high performance liquid chromatography(HPLC),yielding satisfactory recoveries(79.47%−110.82%)and low limits of detection(LOD)(16.67μg/L).Another two kinds of MIPs adopting the thermo-responsive moiety-derived DESs effect strategy further demonstrated great applicability of such intelligent MIPs for analyses of complicated samples.

关键词： Deep eutectic solvents Molecularly imprinted polymers Magnetic Thermo-responsive Thermo-regulated elution

来源：评论

学校读者我要写书评

暂无评论

Medical image registration and its application in retinal images:a review

引用

Visual Computing for Industry,Biomedicine,and Art 2024年第1期7卷 142-164页

作者： Qiushi Nie Xiaoqing Zhang Yan Hu Mingdao Gong Jiang Liu Research Institute of Trustworthy Autonomous Systems and Department of Computer Science and Engineering Southern University of Science and TechnologyShenzhen 518055China Center for High Performance Computing and Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Singapore Eye Research Institute Singapore 169856Singapore State Key Laboratory of Ophthalmology Optometry and Visual ScienceEye HospitalWenzhou Medical UniversityWenzhou 325027China

Medical image registration is vital for disease diagnosis and treatment with its ability to merge diverse informa-tion of images,which may be captured under different times,angles,or *** several surveys have reviewed the development of medical image registration,they have not systematically summarized the existing med-ical image registration *** this end,a comprehensive review of these methods is provided from traditional and deep-learning-based perspectives,aiming to help audiences quickly understand the development of medical image *** particular,we review recent advances in retinal image registration,which has not attracted much *** addition,current challenges in retinal image registration are discussed and insights and prospects for future research provided.

关键词： computer-aided diagnosis Medical image registration Deep learning Generative model Transformer Retina

来源：评论

学校读者我要写书评

暂无评论

A prompt-based approach to adversarial example generation and robustness enhancement

引用

Frontiers of computer science 2024年第4期18卷 85-96页

作者： Yuting YANG Pei HUANG Juan CAO Jintao LI Yun LIN Feifei MA Key Lab of Intelligent Information Processing of Chinese Academy of Sciences(CAS) Institute of Computing TechnologyCASBeijing 100190China School of Computer Science and Technology University of Chinese Academy of SciencesBeijing 100049China Department of Computer Science Stanford UniversityCA 94305USA School of Computing National University of SingaporeSingapore 119077Singapore Laboratory of Parallel Software and Computational Science Institute of SoftwareChinese Academy of SciencesBeijing 100190China

Recent years have seen the wide application of natural language processing(NLP)models in crucial areas such as finance,medical treatment,and news media,raising concerns about the model robustness and *** find that prompt paradigm can probe special robust defects of pre-trained language *** prompt texts are first constructed for inputs and a pre-trained language model can generate adversarial examples for victim models via *** results show that prompt paradigm can efficiently generate more diverse adversarial examples besides synonym ***,we propose a novel robust training approach based on prompt paradigm which incorporates prompt texts as the alternatives to adversarial examples and enhances robustness under a lightweight minimax-style optimization *** on three real-world tasks and two deep neural models show that our approach can significantly improve the robustness of models to resist adversarial attacks.

关键词： robustness adversarial example prompt learning pre-trained language model

来源：评论

学校读者我要写书评

暂无评论

Shear behaviour of anchored jointed rock mass under different engineering conditions considering damage and joint surface morphology

引用

Underground Space 2023年第6期13卷 316-334页

作者： Zenghui Zhao Wei Sun Shaojie Chen Hao Liu College of Energy and Mining Engineering Shandong University of Science and TechnologyQingdao 266590China State Key Laboratory of Strata Intelligent Control and Green Mining Co-founded by Shandong Province and the Ministry of Science and Technology Shandong University of Science and TechnologyQingdao 266590China Department of Petroleum Engineering China University of Petroleum-BeijingBeijing 102249China

According to different geological conditions and engineering disturbance,three dimensional numerical models of anchored jointed rock mass with two kinds of boundary conditions of constant normal load(CNL)and constant normal stiffness(CNS)were constructed considering the ductility damage of rockbolt,the stiffness degradation of grouting layer and the joint surface *** effects of anchorage angle,joint surface morphology,and boundary conditions on the shear performance of anchorage system were analyzed,and the failure characteristics under different working conditions were ***,the analytical solution of shear strength of anchored system was *** show that the larger the anchorage angle is,the more serious the necking phenomenon of rockbolt will *** damage degree of the bonding layer and the horizontal displacement of the bedding rock mass decrease with the increase of the joint surface *** CNL condition is to instantaneously apply high normal stress,and the CNS condition is to gradually form a high normal stress environment through the superposition of increment on the basis of the initial value,which can resist greater transverse *** is equivalent to enhancing the ductility of the *** shear strength of the system increases with the increase of normal stress and normal *** the normal stiffness will underestimate the shear strength.

关键词： Anchored jointed rock mass Normal stress Normal stiffness Progressive damage

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：