检索结果-内蒙古大学图书馆

Study on micromechanical behavior and energy evolution of granular material generated by latent diffusion model under rotation of principal stresses

引用

Particuology 2025年第1期96卷 71-83页

作者： Jichen Zhong Junxing Zheng Lin Gao Qixin Wu Zhenchang Guan Shuangping Li Dong Wang School of Civil and Hydraulic Engineering Huazhong University of Science and TechnologyWuhan430074China School of Civil Engineering Wuhan UniversityWuhan430074China College of Civil Engineering Fuzhou UniversityFuzhou350116China Changjiang Spatial Information Technology Engineering Co. Ltd.Wuhan430074China Key Laboratory of Geotechnical Mechanics and Engineering of the Ministry of Water Resources Changjiang River Scientific Research InstituteWuhan430010China

In this study, advanced image processing technology is used to analyze the three-dimensional sand composite image, and the topography features of sand particles are successfully extracted and saved as high-quality image files. These image files were then trained using the latent diffusion model (LDM) to generate a large number of sand particles with real morphology, which were then applied to numerical studies. The effects of particle morphology on the macroscopic mechanical behavior and microscopic energy evolution of sand under complex stress paths were studied in detail, combined with the circular and elliptical particles widely used in current tests. The results show that with the increase of the irregularity of the sample shape, the cycle period and radius of the closed circle formed by the partial strain curve gradually decrease, and the center of the circle gradually shifts. In addition, the volume strain and liquefaction strength of sand samples increase with the increase of particle shape irregularity. It is particularly noteworthy that obvious vortex structures exist in the positions near the center where deformation is severe in the samples of circular and elliptical particles. However, such structures are difficult to be directly observed in sample with irregular particles. This phenomenon reveals the influence of particle morphology on the complexity of the mechanical behavior of sand, providing us with new insights into the understanding of the response mechanism of sand soil under complex stress conditions.

关键词： Pattern recognition Latent diffusion model(LDM) DEM Principal stress rotation(PSR) Mechanical response

来源：评论

学校读者我要写书评

暂无评论

Continuous and generalized visual odometry based on FLANN_PSC-RANSAC_LSTM

引用

Journal of Intelligent and Fuzzy systems 2024年第1-2期47卷 15-28页

作者： Li, Dengao Feng, Ran Wu, Fanming Zhao, Jinhua Zhao, Jumin College of Computer Science and Technology College of Data Science Taiyuan University of Technology Shanxi Taiyuan China College of Electronic Information and Optical Engineering Taiyuan University of Technology Shanxi Taiyuan China Key Laboratory of Big Data Fusion Analysis and Application of Shanxi Province Taiyuan University of Technology Shanxi Taiyuan China Intelligent Perception Engineering Technology Center of Shanxi Taiyuan China

In the field of simultaneous localization and mapping (SLAM), visual odometry (VO) always has great application prospects. In recent years, with the progress in the field of machine learning, methods based on neural networks are constantly being updated and applied. In this paper, we propose a continuous and generalized monocular visual odometry method based on features and neural networks. First, the feature information of adjacent image sequences is extracted by matching and troubleshooting algorithm (FLANN_PSC-RANSAC), then it and the corresponding six-degree-of-freedom information are simultaneously input into the long short-term memory artificial neural network (LSTM) for model construction, which not only ensures the reliability of the mode but also eliminates the influence of illumination on the data. In the real environment test, it has been effectively proved in terms of trajectory recovery accuracy and generalization ability to different environments and different illuminations. © 2024 - IOS Press. All rights reserved.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Surrogate-Assisted Multiobjective Gene Selection for Cell Classification From Large-Scale Single-Cell RNA Sequencing Data

引用

IEEE Transactions on Evolutionary Computation 2025年第3期29卷 601-615页

作者： Lin, Jianqing He, Cheng Jiang, Hanjing Huang, Yabing Jin, Yaochu Huazhong University of Science and Technology Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Wuhan430074 China Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Wuhan430074 China Renmin Hospital of Wuhan University Department of Pathology Wuhan430060 China Westlake University Trustworth and General Artificial Intelligence Laboratory School of Engineering Hangzhou310030 China

Accurate cell classification is crucial but expensive for large-scale single-cell RNA sequencing (scRNA-seq) analysis. Gene selection (GS) emerges as a pivotal technique in identifying gene subsets of scRNA-seq for classification accuracy improvement and gene scale reduction. Nevertheless, the rising scale of scRNA-seq data presents challenges to existing GS methods regarding performance and computational time. Thus, we propose a surrogate-assisted evolutionary algorithm for multiobjective GS to address these deficiencies. An innovative two-phase initialization method is proposed to select sparse solutions to provide preliminary insights into gene contributions. Then, a binary competitive swarm optimizer is proposed for effective global search, where a local search method is embedded to eliminate irrelevant genes for efficiency consideration. Additionally, a surrogate model is adopted to forecast classification accuracy efficiently and substitutes part of the computationally expensive classification process. Experiments are conducted on eight large-scale scRNA-seq datasets with more than 20 000 genes. The effectiveness of the proposed GS method for scRNA-seq cell classification compared with eight state-of-the-art methods is validated. Gene expression analysis results of selected genes further validated the significance of the genes selected by the proposed method in the classification of scRNA-seq data. © 1997-2012 IEEE.

关键词： Gene expression

来源：评论

学校读者我要写书评

暂无评论

Attention Enhanced Feature Fusion for Mental Stress Level Classification 21

Attention Enhanced Feature Fusion for Mental Stress Level Cl...

引用

21st International Computer Conference on Wavelet Active Media technology and information Processing, ICCWAMTIP 2024

作者： Sahlu, Ameneshewa Abush Yohannes, Gobena Mulugeta Dawit, Bekalu Nigus Teshome, Molla Woretaw School of Computer Science and Engineering University of Electronic Science and Technology of China Sichuan Chengdu China School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China School of Information and Software Engineering University of Electronic Science and Technology of China Sichuan Chengdu China

ISBN: (纸本)9798331519254

Mental stress poses significant health risks, manifesting in various psychological and physical issues such as depression, anxiety, and cardiovascular complications. Establishing a reliable method for swiftly and accurately classifying mental stress levels is crucial due to its widespread impact. Existing classification approaches predominantly rely on either data-intensive traditional machine learning algorithms or opaque deep learning models, hindering real-world use and interpretability. This study addresses these limitations by proposing a novel approach for stress level classification using the WESAD dataset. Our method combines an attention-based ResN et with CBAM. This innovative approach synergistically integrates shallow and deep features, harnessing both low-level details and high-level semantic information to effectively classify stress levels into four distinct states: baseline, stress, amusement, and meditation, or three states excluding the meditation state. The experimental result shows 92.74% accuracy and 91.19% F1 score for the 4-class setup, and 97.58% accuracy and 97.51 % F1 score for the 3-class setup. Our approach offers a more robust and interpretable framework for mental stress classification, with potential applications in health care and stress management. © 2024 IEEE.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Efficient Solution of Characteristic Modes Using Wideband Sherman-Morrison-Woodbury Algorithm

Efficient Solution of Characteristic Modes Using Wideband Sh...

引用

2024 International Applied Computational Electromagnetics Society Symposium, ACES-China 2024

作者： Meng, Hao Wang, Mingxin Chen, Xinlei Yang, Wu Lu, Weibing Nanjing University of Aeronautics and Astronautics College of Electronic and Information Engineering Nanjing China College of Electronic and Information Engineering Key Laboratory of Radar Imaging and Microwave Photonics Key Laboratory of Inlet and Exhaust System Technology Nanjing University of Aeronautics and Astronautics China State Key Laboratory of Millimeter Waves Southeast University Nanjing China Southeast University State Key Laboratory of Millimeter Waves School of Information Science and Engineering Nanjing China

ISBN: (纸本)9798350355581

In characteristic mode analysis (CMA), characteristic modes (CMs) on wideband frequency need to be solved for analyzing physical characteristics. This paper proposes an efficient method to obtain wideband CMs by solving the generalized eigenvalue problems (GEPs). In this method, the wideband Sherman-Morrison-Woodbury algorithm (WSMWA) is embedded into implicitly restarted Arnoldi method (IRAM). Numerical results show that the proposed method can save much CPU time. © 2024 IEEE.

关键词： Eigenvalues and eigenfunctions

来源：评论

学校读者我要写书评

暂无评论

Intelligent optimization methods of phase-modulation waveform

引用

Journal of systems engineering and Electronics 2022年第4期33卷 916-923页

作者： SUN Jianwei WANG Chao SHI Qingzhan REN Wenbo YAO Zekun YUAN Naichang College of Electronic Science and Technology National University of Defense TechnologyChangsha 410073China State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System National University of Defense TechnologyChangsha 410073China

With the continuous improvement of radar intelligence, it is difficult for traditional countermeasures to achieve ideal results. In order to deal with complex, changeable, and unknown threat signals in the complex electromagnetic environment, a waveform intelligent optimization model based on intelligent optimization algorithm is proposed. By virtue of the universality and fast running speed of the intelligent optimization algorithm, the model can optimize the parameters used to synthesize the countermeasure waveform according to different external signals, so as to improve the countermeasure *** algorithm(GA) and particle swarm optimization(PSO)are used to simulate the intelligent optimization of interruptedsampling and phase-modulation repeater waveform. The experimental results under different radar signal conditions show that the scheme is feasible. The performance comparison between the algorithms and some problems in the experimental results also provide a certain reference for the follow-up work.

关键词： waveform optimization intelligent optimization phase-modulation genetic algorithm(GA) particle swarm optimization(PSO)

来源：评论

学校读者我要写书评

暂无评论

Acute Observational Stimulus of Restrained Mice Induced Anxiolytic Effects in Observer Mice

引用

Neuroscience Bulletin 2024年第10期40卷 1545-1550页

作者： Chun-Hui Jia Fang-Qi Shu Pak-Ming Lau Hao Wang CAS Key Laboratory of Brain Function and Disease Division of Life Sciences and MedicineUniversity of Science and Technology of ChinaHefei 230026China Anhui Province Key Laboratory of Biomedical Imaging and Intelligent Processing Institute of Artificial IntelligenceHefei Comprehensive National Science CenterHefei 230088China Interdisciplinary Center for Brain Information The Brain Cognition and Brain Disease InstituteShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China National Engineering Laboratory for Brain-inspired Intelligence Technology and Application School of Information Science and TechnologyUniversity of Science and Technology of ChinaHefei 230026China

Dear Editor,Ensuring an appropriate response to external stimuli is essential for animals'survival and *** indicates that such stimuli can affect animals'physiological state and hormone levels,including corticosterone(CORT)[1,2].The impact of these stimuli on animals'performance depends on their density and duration,as they can either facilitate or hinder *** chronic and intense stressors can have detrimental effects on animals'physiological health and behavioral performance,leading to psychiatric disorders such as depression,anxiety,and schizophrenia[3],the effects of acute and mild observational stimuli are still unclear.

关键词： evolution. Observation acute

来源：评论

学校读者我要写书评

暂无评论

Bridging Sentence and Document Contexts: A PEFT-Enhanced Framework for Document-Level Neural Machine Translation 4

Bridging Sentence and Document Contexts: A PEFT-Enhanced Fra...

引用

4th International Conference on Artificial Intelligence, Robotics, and Communication, ICAIRC 2024

作者： Liu, Chunjiao Guo, Junjun Kunming University of Science and Technology Yunnan Key Laboratory of Artificial Intelligence Faculty of Information Engineering and Automation Kunming China

ISBN: (纸本)9798331531225

Document-level neural machine translation (DNMT) faces challenges in integrating context and maintaining semantic consistency. This paper proposes a coarse-to-fine semantic transfer approach that captures both fine-grained and coarse-grained document-level context. By employing a two-stage training strategy with Adapter-enhanced modules, the method ensures effective semantic adaptation from sentence to document levels. Experiments on three datasets demonstrate significant improvements in s-BLEU and d-BLEU metrics, outperforming existing approaches. © 2024 IEEE.

关键词： Neural machine translation

来源：评论

学校读者我要写书评

暂无评论

Quantum Remote State Preparation Based on Quantum Network Coding

引用

Computers, Materials & Continua 2022年第10期73卷 119-132页

作者： Zhen-Zhen Li Zi-Chen Li Yi-Ru Sun Haseeb Ahmad Gang Xu Xiu-Bo Chen School of Information Engineering Beijing Institute of Graphic CommunicationBeijing102600China School of Computer Science and Information Engineering Zhejiang Gongshang UniversityHangzhou310018China Information Security Center State key Laboratory of Networking and Switching TechnologyBeijing University of Posts and TelecommunicationsBeijing100876China Department of Computer Science National Textile UniversityFaisalabad37610Pakistan School of Information Science and Technology North China University of TechnologyBeijing100144China Advanced Cryptography and System Security Key Laboratory of Sichuan Province China

As an innovative theory and technology,quantum network coding has become the research hotspot in quantum network *** this paper,a quantum remote state preparation scheme based on quantum network coding is *** with the general quantum remote state preparation schemes,our proposed scheme brings an arbitrary unknown quantum state finally prepared remotely through the quantum network,by designing the appropriate encoding and decoding steps for quantum network *** is worth mentioning,from the network model,this scheme is built on the quantum k-pair network which is the expansion of the typical bottleneck network—butterfly ***,it can be treated as an efficient quantum network preparation scheme due to the characteristics of network coding,and it also makes the proposed scheme more applicable to the large-scale quantum *** addition,the fact of an arbitrary unknown quantum state remotely prepared means that the senders do not need to know the desired quantum ***,the security of the proposed scheme is ***,this scheme can always achieve the success probability of 1 and 1-max flow of value ***,the communication efficiency of the proposed scheme is ***,the proposed scheme turns out to be practicable,secure and efficient,which helps to effectively enrich the theory of quantum remote state preparation.

关键词： Quantum remote state preparation quantum network coding quantum k-pair network

来源：评论

学校读者我要写书评

暂无评论

MalwareTotal: Multi-Faceted and Sequence-Aware Bypass Tactics Against Static Malware Detection 24

MalwareTotal: Multi-Faceted and Sequence-Aware Bypass Tactic...

引用

44th ACM/IEEE International Conference on Software engineering, ICSE 2024

作者： He, Shuai Fu, Cai Hu, Hong Chen, Jiahe Lv, Jianqiang Jiang, Shuai School of Cyber Science and Engineering Huazhong Science and Technology University China Huazhong Science and Technology University Hubei Key Laboratory of Distributed System Security China Pennsylvania State University United States

ISBN: (纸本)9798400702174

Recent methods have demonstrated that machine learning (ML) based static malware detection models are vulnerable to adversarial attacks. However, the generated malware often fails to generalize to production-level anti-malware software (AMS), as they usually involve multiple detection methods. This calls for universal solutions to the problem of malware variants generation. In this work, we demonstrate how the proposed method, MalwareTotal, has allowed malware variants to continue to abound in ML-based, signature-based, and hybrid anti-malware software. Given a malicious binary, we develop sequential bypass tactics that enable malicious behavior to be concealed within multi-faceted manipulations. Through 12 experiments on real-world malware, we demonstrate that an attacker can consistently bypass detection (98.67%, and 100% attack success rate against ML-based methods EMBER and MalConv, respectively;95.33%, 92.63%, and 98.52% attack success rate against production-level anti-malware software ClamAV, AMS A, and AMS B, respectively) without modifying the malware functionality. We further demonstrate that our approach outperforms state-of-the-art adversarial malware generation techniques both in attack success rate and query consumption (the number of queries to the target model). Moreover, the samples generated by our method have demonstrated transferability in the real-world integrated malware detector, VirusTotal. In addition, we show that common mitigation such as adversarial training on known attacks cannot effectively defend against the proposed attack. Finally, we investigate the value of the generated adversarial examples as a means of hardening victim models through an adversarial training procedure, and demonstrate that the accuracy of the retrained model against generated adversarial examples increases by 88.51 percentage points. © 2024 ACM.

关键词： Computer viruses

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：