检索结果-内蒙古大学图书馆

arXiv 2021年

作者： Liu, Haozhe Wu, Haoqian Xie, Weicheng Liu, Feng Shen, Linlin 1Computer Vision Institute College of Computer Science and Software Engineering 2SZU Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society 3National Engineering Laboratory for Big Data System Computing Technology 4Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen 518060 China

The convolutional neural network (CNN) is vulnerable to degraded images with even very small variations (e.g. corrupted and adversarial samples). One of the possible reasons is that CNN pays more attention to the most discriminative regions, but ignores the auxiliary features when learning, leading to the lack of feature diversity for final judgment. In our method, we propose to dynamically suppress significant activation values of CNN by group-wise inhibition, but not fixedly or randomly handle them when training. The feature maps with different activation distribution are then processed separately to take the feature independence into account. CNN is finally guided to learn richer discriminative features hierarchically for robust classification according to the proposed regularization. Our method is comprehensively evaluated under multiple settings, including classification against corruptions, adversarial attacks and low data regime. Extensive experimental results show that the proposed method can achieve significant improvements in terms of both robustness and generalization performances, when compared with the state-of-the-art methods. Code is available at https://***/LinusWu/TENET_Training. Copyright © 2021, The Authors. All rights reserved.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Dynamic asymmetric reflective decision-making supports the evolution of cooperation

引用

Chaos, Solitons & Fractals 2025年 199卷

作者： Xiaopeng Li Xiuli Zhang Zhonglin Wang Yicheng Pang College of Big Data Statistics Guizhou University of Finance and Economics Guiyang Guizhou 550025 PR China Shanxi Key Laboratory of Intelligent Optimization Computing and Blockchain Technology Taiyuan Normal University Taiyuan Shanxi 030619 PR China Department of Applied Mathematics Guizhou University of Finance and Economics Guiyang Guizhou 550025 PR China

Up to now, most previous studies have assumed that agents employed symmetric decision-updating mechanisms to investigate how cooperation evolved in selfish populations. However, dynamic and asymmetric decision-making update is overlooked. In this paper, we try our best to construct a reputation-driven dynamic asymmetric reflective decision-making model to fill in the blanks. Initially, each agent is randomly assigned a reputation value within the range [1,100], which will increase or decrease if it makes cooperative or defective decision in the process of evolution. Then, we distinguish agents as standouts or laymen by the pivotal reputation threshold R c . The standouts with high-reputation are cautious in updating their decisions and therefore may think more times. In sharp contrast, the laymen with low-reputation, appear too reckless and just only think once in the similar process. Simulation results show that this simple model can support the evolution of cooperation, especially expanding the threshold for cooperation annihilation. Through qualitative micro-analysis and quantitative statistical analysis, we find that standouts with high reputations play an irreplaceable role in facilitating cooperation. The robustness test further confirms that the promoting effect of this mechanism on cooperation is independent of network structures, decision update patterns, and social dilemma types. We hope that our research can deepen the understanding and cognition of the evolution of cooperation.

关键词： Distributed computer systems

来源：评论

学校读者我要写书评

暂无评论

Self-to-self transitions in open quantum systems:the origin and solutions

Self-to-self transitions in open quantum systems:the origin ...

引用

第三十九届中国控制会议

作者： Fang Gao Yaoxiong Wang Qing Gao Dewen Cao Feng Shuang College of Electrical Engineering Guangxi University Institute of Intelligent Machines Chinese Academy of Sciences School of Automation Science and Electrical Engineering Beihang University Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University University Key Laboratory of Intelligent Perception and Computing of Anhui Province Anqing Normal University

The information of quantum pathways can be extracted in the framework of the Hamiltonianencoding and Observable-decoding *** closed quantum systems,only off-diagonal elements of the Hamiltonian in the Hilbert space is required to be encoded to obtain the desired *** open quantum systems,environment-related terms will appear in the diagonal elements of the Hamiltonian in the Liouville *** diagonal encodings have to be performed to differentiate different pathways,which will lead to self-to-self transitions and inconsistency of pathway amplitudes with Dyson *** this work,a well-designed transformation is proposed to avoid the counterintuitive transitions and the inconsistency,with or without control *** simulations show that the method are consistent with Dyson expansion.

关键词： Self-to-self transitions in open quantum systems:the origin and solutions origin

来源：评论

学校读者我要写书评

暂无评论

Evolution of cooperation in spatial heterogeneous social dilemmas with dynamic self-adaptive matching

引用

Applied Mathematics and Computation 2026年 508卷

作者： Xiaopeng Li Xuexue Yang Xiuli Zhang Weiwei Han Yan Xu College of Big Data Statistics Guizhou University of Finance and Economics Guiyang Guizhou 550025 PR China Shanxi Key Laboratory of Intelligent Optimization Computing and Blockchain Technology Taiyuan Normal University Taiyuan Shanxi 030619 PR China School of Information Engineering Tianjin University of Commerce Tianjin 300134 PR China Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin 300384 PR China

From the perspective of real-world interaction scenarios, the assumption of monotypic social dilemma engagement or fixed role allocations within heterogeneous social dilemmas contexts fundamentally misrepresents the dynamics of human social cognition. Empirical evidence consistently suggests that behavioral plasticity is achieved through adaptive identity switching across heterogeneous social dilemma environments. Herein, we develop an evolutionary game model simultaneously encompassing multiple social dilemmas (prisoner's dilemma game and snowdrift game), wherein agents engage in polymorphic game-environment governed by their own adaptive characteristic. Specifically, during the strategy update phase, if the agent x ′ s current strategy is retained, its strategy stickiness θ x increases one unit; otherwise, the metric reverts to the initial value of 0. Additionally, if θ x reaches the maximum value of 100, it signifies the termination of the old agent and the initialization of a new one, with the metric also reverting to 0. Moreover, agent whose strategy adherence is beyond predefined threshold θ t h is classified as possessing strong social dilemma resolution capacity, while that is below the threshold is allocated to mild-conflict scenarios. Subsequently, through sufficient Monte Carlo simulation, we systematically investigate the evolutionary trajectories and stable-state characteristics of cooperation in dynamically adaptive multi-social dilemma systems, yielding several insightful findings.

关键词： Evolution of cooperation Evolutionary dynamics Dynamic self-adaptive Heterogeneous social dilemmas

来源：评论

学校读者我要写书评

暂无评论

A Causal Adversarial Graph Neural Network for Multi-Center Autism Spectrum Disorder Identification

SSRN

引用

SSRN 2025年

作者： Zhang, Zhuan Wang, Lihui Chen, Qijian Wang, Li Jian, Caiqing Zhu, Yue-Min Wei, Hongjiang Engineering Research Center of Text Computing & Cognitive Intelligence Ministry of Education Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guiyang550025 China University Lyon INSA Lyon CNRS Inserm IRP Metislab CREATIS UMR5220 U1206 Lyon69621 France

Due to the heterogeneous distributions of multi-center rs-fMRI data, currently it is still challenging to identify accurately autism spectrum disorder (ASD) patients from these heterogenous data. To deal with the influence of heterogeneous distributions on multi-center ASD diagnosis, a novel causal adversarial graph neural network (CAG) for multi-center ASD prediction is proposed in this work. CAG mainly consists of a graph filtering (GF) module and a learnable causal graph predictor (CGP). Specifically, the brain connection graph is first constructed from rs-fMRI data, after passing a GF module, the filtered graph is further divided by a causal subgraph and causally irrelevant subgraph. The ground-truth environmental labels and ASD labels are predicted from causal subgraph by a clustering method and a classification block, respectively. In addition, from the filtered graph and causally irrelevant subgraph, the environmental labels are predicted, while from the causally irrelevant subgraph the ASD labels are predicted. Assuming that the predicted environmental labels are independent to causal subgraph, while the predicted ASD labels are independent to causally irrelevant subgraph, accordingly, several adversarial losses are implemented by reversing the gradient. Through this adversarial learning strategy, the derived causal graph can predict multi-center ASD. The comparison experiments on both ABIDE-I and ABIDE-II datasets demonstrate that, the ACC and AUC of CAG has been improved by 3.78\% and 7.38\% at least comparing against the existing methods. Moreover, some abnormal functional connectivities in ASD group are identified from the causal subgraph which may provide useful imaging biomarkers for the early diagnosis of ASD. © 2025, The Authors. All rights reserved.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Investigating 16 Open Clusters in the Kepler/K2 - Gaia DR3 field. I. Membership, Binary, and Rotation

arXiv

引用

arXiv 2023年

作者： Long, Liu Bi, Shaolan Zhang, Jinghua Zhang, Xianfei Zhang, Liyun Ge, Zhishuai Li, Tanda Chen, Xunzhou Li, YaGuang Ye, LiFei Sun, TianCheng Zhou, JianZhao Institute for Frontiers in Astronomy and Astrophysics Beijing Normal University Beijing102206 China Department of Astronomy Beijing Normal University Beijing100875 China South-Western Institute for Astronomy Research Yunnan University Chenggong District Kunming650500 China College of Physics Guizhou University Guiyang550025 China State Key Laboratory of Public Big Data Guizhou University Guiyang550025 China Beijing Planetarium Beijing Academy of Science and Technology Beijing100044 China Research Center for Intelligent Computing Platforms Zhejiang Laboratory Hangzhou311100 China School of Physics University of Sydney NSW2006 Australia Stellar Astrophysics Centre Department of Physics and Astronomy Aarhus University Ny Munkegade 120 Aarhus CDK-8000 Denmark

Using data from the Gaia data Release 3 (Gaia DR3) and Kepler/K2, we present a catalog of 16 open clusters with ages ranging from 4 to 4000 Myr, which provides detailed information on membership, binary systems, and rotation. We assess the memberships in 5D phase space, and estimate the basic parameters of each cluster. Among the 20,160 members, there are 4,381 stars identified as binary candidates and 49 stars as blue straggler stars. The fraction of binaries vary in each cluster, and the range between 9% to 44%. We obtain the rotation periods of 5,467 members, of which 4,304 are determined in this work. To establish a benchmark for the rotation-age-color relation, we construct color-period diagrams. We find that the rotational features of binaries are similar to that of single stars, while features for binaries are more scattered in the rotation period. Moreover, the morphology of the color-period relationship is already established for Upper Scorpius at the age of 19 Myr, and some stars of varying spectral types (i.e. FG-, K-, and M-type) show different spin-down rates after the age of ∼ 110 Myr. By incorporating the effects of stalled spin-down into our analysis, we develop an empirical rotation-age-color relation, which is valid with ages between 700 - 4000 Myr and colors corresponding to a range of 0.5 BP − GRP)0 Copyright © 2023, The Authors. All rights reserved.

关键词： Color

来源：评论

学校读者我要写书评

暂无评论

Multidomain Secure Communication and intelligent Traffic Detection Model in VANETs

引用

International Journal of intelligent Systems 2025年第1期2025卷

作者： Qikun Zhang Mengqi Liu Ping Li Junling Yuan Hongfei Zhu School of Computer and Communication Engineering Zhengzhou University of Light Industry Zhengzhou 450001 China *** School of Cyber Science and Engineering Southeast University Nanjing 210000 China seu.edu.bd School of Information Security Sanmenxia College of Social Administration Sanmenxia 472000 China Key Laboratory of Big Data Intelligent Computing Chongqing University of Posts and Telecommunications Chongqing 400065 China ***

Vehicular ad-hoc network (VANET) plays a vital role in the intelligent transportation system. It is crucial to ensure secure communication among entities in the VANET for realizing an efficient transportation system. In this scenario, the current communication scheme is vulnerable to the leakage of private information from entities. The research primarily centers on single-domain vehicular networks, with only a limited number of researchers exploring cross-domain authentication among vehicle entities. Cross-domain communication schemes have received little attention from scholars. Furthermore, there are issues, including the susceptibility of in-vehicle conversations to eavesdropping, the vulnerability of long-distance transmissions to interruptions, and the exposure of wireless networks to traffic attacks. To address these issues, a multidomain secure communication and intelligent traffic detection model in VANET is proposed. This model offers several notable advantages as follows: (1) It employs a key self-verification algorithm for local computation and authentication of entity keys. This approach mitigates the risks of identity impersonation attacks and key leakage results from third-party key escrow. (2) A multidomain communication scheme is devised to categorize vehicle-to-vehicle (V2V) scenarios into intradomain and interdomain, which correspond to situations where the communicating parties are within the same domain and across different domains, respectively. (3) We propose the implementation of new session message encryption algorithms for V2V communication. This involves generating dynamic random keys to ensure secure data sharing and facilitates long-distance cross-domain communication among vehicles. (4) An intelligent two-layer traffic detection paradigm is proposed to improve the efficiency of detecting attack traffic in vehicular networks. This paper provides security proofs and performance analysis of the proposed scheme. The experimental results dem

关键词： Secure communication

来源：评论

学校读者我要写书评

暂无评论

Artificial Intelligence without Restriction Surpassing Human Intelligence with Probability One: Theoretical Insight into Secrets of the Brain with AI Twins of the Brain

arXiv

引用

arXiv 2024年

作者： Huang, Guang-Bin Westover, M. Brandon Tan, Eng-King Wang, Haibo Cui, Dongshun Ma, Wei-Ying Wang, Tiantong He, Qi Wei, Haikun Wang, Ning Tian, Qiyuan Lam, Kwok-Yan Yao, Xin Wong, Tien Yin School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China Beth Israel Deaconess Medical Center Harvard Medical School Boston United States Department of Neurology National Neuroscience Institute Singapore Research Centre of Big Data and Artificial Intelligence for Medicine First Affiliated Hospital of Sun Yat-Sen University Guangzhou China Duke-NUS Medical School National University of Singapore Singapore Mind PointEye Singapore Institute for AI Industry Research Tsinghua University Beijing China College of Computing and Data Science Nanyang Technological University Singapore School of Biomedical Engineering Tsinghua University Beijing China Singapore AI Safety Institute Nanyang Technological University Singapore School of Data Science Lingnan University Hong Kong School of Computer Science University of Birmingham United Kingdom Singapore Eye Research Institute Singapore National Eye Centre Singapore Tsinghua Medicine Tsinghua University Beijing China

Artificial Intelligence (AI) has apparently become one of the most important techniques discovered by humans in history while the human brain is widely recognized as one of the most complex systems in the universe. One fundamental critical question which would affect human sustainability remains open: Will artificial intelligence (AI) evolve to surpass human intelligence in the future? This paper shows that in theory new AI twins with fresh cellular level of AI techniques for neuroscience could approximate the brain and its functioning systems (e.g. perception and cognition functions) with any expected small error and AI without restrictions could surpass human intelligence with probability one in the end. This paper indirectly proves the validity of the conjecture made by Frank Rosenblatt 70 years ago about the potential capabilities of AI, especially in the realm of artificial neural networks. This paper also gives the answer to the two widely discussed fundamental questions: 1) whether AI could have potentials of discovering new principles in nature;2) whether error backpropagation (BP) algorithm commonly and efficiently used in tuning parameters in AI applications is also adopted in the brain. Intelligence is just one of fortuitous but sophisticated creations of the nature which has not been fully discovered. Like mathematics and physics, with no restrictions artificial intelligence would lead to a new subject with its self-contained systems and principles. We anticipate that this paper opens new doors for 1) AI twins and other AI techniques to be used in cellular level of efficient neuroscience dynamic analysis, functioning analysis of the brain and brain illness solutions;2) new worldwide collaborative scheme for interdisciplinary teams concurrently working on and modelling different types of neurons and synapses and different level of functioning subsystems of the brain with AI techniques;3) development of low energy of AI techniques with the aid of fundament

关键词： Neurology

来源：评论

学校读者我要写书评

暂无评论

Radiomics based on dual-energy CT for noninvasive prediction of cervical lymph node metastases in patients with nasopharyngeal carcinoma

引用

Radiography 2025年第4期31卷 102989-102989页

作者： Li, L. Yang, D. Wu, Y. Sun, R. Qin, Y. Kang, M. Deng, X. Bu, M. Li, Z. Zeng, Z. Zeng, X. Jiang, M. Chen, B.T. Department of Radiology First Affiliated Hospital of Guangxi Medical University Guangxi Nanning 530021 China Department of Radiology Guizhou Provincial People Hospital No.83 East Zhongshan Road Nanming District Guizhou Province Guiyang 550000 China Engineering Research Center of Text Computing & Cognitive Intelligence Ministry of Education Key Laboratory of Intelligent Medical Image Analysis and Precise Diagnosis of Guizhou Province State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University No. 2870 Huaxi Avenue South Guizhou Guiyang 550025 China Department of Nuclear Medicine First Affiliated Hospital of Guangxi Medical University Guangxi Nanning 530021 China Department of Radiation Oncology First Affiliated Hospital of Guangxi Medical University Guangxi Nanning 530021 China Department of Diagnostic Radiology City of Hope National Medical Center Duarte CA United States

Introduction: To develop and validate a machine learning model based on dual-energy computed tomography (DECT) for predicting cervical lymph node metastases (CLNM) in patients diagnosed with nasopharyngeal carcinoma (NPC). Methods: This prospective single-center study enrolled patients with NPC and the study assessment included both DECT and 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT). Radiomics features were extracted from each region of interest (ROI) for cervical lymph nodes using arterial and venous phase images at 100 keV and 150 keV, either individually as non-fusion models or combined as fusion models on the DECT images. The performance of the random forest (RF) models, combined with radiomics features, was evaluated by area under the receiver operating characteristic curve (AUC) analysis. DeLong's test was employed to compare model performances, while decision curve analysis (DCA) assessed the clinical utility of the predictive models. Results: Sixty-six patients with NPC were included for analysis, which was divided into a training set (n = 42) and a validation set (n = 22). A total of 13 radiomic models were constructed (4 non-fusion models and 9 fusion models). In the non-fusion models, when the threshold value exceeded 0.4, the venous phase at 100 keV (V100) (AUC, 0.9667;95 % confidence interval [95 % CI], 0.9363–0.9901) model exhibited a higher net benefit than other non-fusion models. The V100 + V150 fusion model achieved the best performance, with an AUC of 0.9697 (95 % CI, 0.9393–0.9907). Conclusion: DECT-based radiomics effectively diagnosed CLNM in patients with NPC and may potentially be a valuable tool for clinical decision-making. Implications for practice: This study improved pre-operative evaluation, treatment strategy selection, and prognostic evaluation for patients with nasopharyngeal carcinoma by combining DECT and radiomics to predict cervical lymph node status prior to treatment. © 2025 The Co

关键词： Cervical lymph node metastases (CLNM) Dual-energy computed tomography (DECT) Machine learning model Nasopharyngeal carcinoma (NPC) Radiomics

来源：评论

学校读者我要写书评

暂无评论

Nonlinear Longitudinal Control for Connected Vehicle Platoon Considering the Acceleration Difference

Nonlinear Longitudinal Control for Connected Vehicle Platoon...

引用

第三十九届中国控制会议

作者： Ao Jiao Yongfu Li Shuyou Yu Zhongwei Cui Key Laboratory of Intelligent Air-Ground Cooperative Control for Universities in Chongqing College of Automation Chongqing University of Posts and Telecommunications Department of Control Science & Engineering Jilin University School of Mathematics and Big Data Guizhou Education University

This study proposes a distributed nonlinear control algorithm for the heterogeneous connected vehicle(CV) *** particular, in order to capture the nonlinear behavior of vehicle such as stop-and-go phenomena, the effects of the car-following interactions are considered. Besides, the vehicle dynamics of heterogeneous CVs is characterized by using the third-order vehicle dynamics model, and the controller is designed by considering the acceleration difference. In addition, the stability and consensus of the proposed control algorithm is analyzed by using Routh-Hurwitz stability criterion, hence, the negative velocity, negative spacing error and unreasonable acceleration/deceleration can be avoided based on the proposed control algorithm. Finally, the effectiveness and robustness of proposed algorithm is verified by conducting multiple numerical simulation experiments in presence of external disturbances and multiple real vehicle confirmatory experiments.

关键词： Connected Vehicle Platoon Acceleration Difference Car-Following Interaction Convergence Analysis

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：