期刊文献+
任意字段
题名或关键词
题名
关键词
摘要
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息
共找到17,346篇文章
< 1 2 … 250 >
每页显示 20 50 100
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
显示方式：
Author correction:Unsupervised learning enabled label-free singlepixel imaging for resilient information transmission through unknown dynamic scattering media 认领 引用
1
作者 Fujie Li Haoyu Zhang +7 位作者 Zhilan Lu Li Yao Yuan Wei Ziwei Li Feng Bao Junwen Zhang Yingjun Zhou Nan Chi 《Opto-Electronic Advances》 SCIE EI CAS CSCD 2026年第2期1-1,共1页
Correction to:Opto-Electronic Advances http://gffzzd3cc09b8251d45dfs6bppp6k6bu566pck.ffgz.tsg.suse.edu.cn/10.29026/oea.2025.250013 published 25 October 2025 After the publication of this article,it was brought to our attention that the funding information in the Ackno... Correction to:Opto-Electronic Advances http://gffzzd3cc09b8251d45dfs6bppp6k6bu566pck.ffgz.tsg.suse.edu.cn/10.29026/oea.2025.250013 published 25 October 2025 After the publication of this article,it was brought to our attention that the funding information in the Acknowledgements section contained an error.Correction details are listed below. 展开更多
关键词 single pixel imaging opto electronic advances resilient information transmission label free imaging unknown dynamic scattering media funding information unsupervised learning
暂未订购 下载PDF
An uncertainty evaluation for storm surge risk analysis based on information utilization efficiency 认领 引用
2
作者 Guilin LIU Siyu DING +3 位作者 Shichun SONG Bokai YANG Pengyu ZHU Liping WANG 《Journal of Oceanology and Limnology》 SCIE CAS CSCD 2026年第2期545-559,共15页
With the development of methods for predicting extreme hydrological elements using probabilistic approaches,several commonly used methods have emerged for analyzing the risk of storm surge disasters,including the Annu... With the development of methods for predicting extreme hydrological elements using probabilistic approaches,several commonly used methods have emerged for analyzing the risk of storm surge disasters,including the Annual Maxima method,the Peak-Over-Threshold method,the Gumbel distribution,and the Weibull distribution.Meanwhile,and emphases have been placed on assessing and comparing the applicability and stability of these various methods.To evaluate the rationality of different methods,we an entropy uncertainty analysis method was introduced based on information utilization efficiency,in which the sample Stochastic uncertainty is measured by the ratio of information entropy before and after sampling,i.e.,the information extraction efficiency of the sampling method.Additionally,the cognitive uncertainty of the research method is assessed by the ratio of mutual information between the model and the sample to the information entropy of the sample,i.e.,the information extraction efficiency of the mathematical model.Furthermore,we incorporated the group probability calculation method,information entropy and mutual information theory to analyze and calculate the entropy uncertainty more accurately.By applying this analysis to the design wave height and the recurrence period projected in the sea area west Guangdong of China,we believed that the most reasonable hazard assessment method shall be based on the over-threshold method combined with the Pareto distribution.Conversely,the assessment method based on the process extreme value method is deemed insufficiently reasonable and requires further research. 展开更多
关键词 uncertainty storm surge information entropy mutual information group probability calculation method
暂未订购 下载PDF
Multi-Source Traffic Information Completion and Perception Method via Graph Convolutional Neural Networks in Intelligent Connected Transportation System 认领 引用
3
作者 Pangwei Wang Jie Wang +2 位作者 Zipeng Wang Hangrui Dong Li Wang 《Computers, Materials & Continua》 SCIE EI 2026年第8期1417-1435,共19页
Traffic holographic perception refers to the real-time,high-fidelity,and multi-dimensional sensing of traffic states through the fusion of heterogeneous sensors,including cameras,radars,and connected vehicle data.The ... Traffic holographic perception refers to the real-time,high-fidelity,and multi-dimensional sensing of traffic states through the fusion of heterogeneous sensors,including cameras,radars,and connected vehicle data.The multi-source perception data obtained thereby can provide a complete digital representation of the road network for the Intelligent Transportation System(ITS).However,sensors are vulnerable to environmental interference,which can result in data loss at specific points or along arterial highways for certain periods,potentially undermining system safety and decision-making reliability.To address these challenges,a deep learning method based on Graph Convolutional Networks(GCN)and Gated Recurrent Units(GRU)is proposed,leveraging Artificial Intelligence(AI)and intelligent connected technologies for real-time acquisition of multi-sensor perception data.A feature-level fusion integrates multi-source perception data.GCN captures spatial dependencies from the road network topology,while GRU extracts temporal features from time series,enabling accurate imputation of missing traffic data.The method is evaluated at intelligent connected intersections in the Beijing High-level Autonomous Driving Demonstration Area.Results show that the accuracy of long-term traffic state completion reaches 89.36%,and the Root Mean Square Error(RMSE)is reduced by 17.2%compared to the Long Short-Term Memory(LSTM)baseline.This framework provides a practical solution for deploying traffic holographic perception technology in secure and trustworthy ITS. 展开更多
关键词 Intelligent transportation information security traffic information completion traffic holographic perception AI-driven edge computing graph convolutional neural network
暂未订购 下载PDF
GLF-Segformer:an improved Segformer model integrating local and global information for skin cancer image segmentation 认领 引用
4
作者 Xiangyu DENG Yapeng ZHENG 《Optoelectronics Letters》 EI 2026年第4期236-242,共7页
More accurate segmentation of skin cancers in dermoscopy images is crucial for clinical treatment.However,the prevalence of interfering noise in dermoscopy images poses a challenge to its accurate segmentation.For thi... More accurate segmentation of skin cancers in dermoscopy images is crucial for clinical treatment.However,the prevalence of interfering noise in dermoscopy images poses a challenge to its accurate segmentation.For this reason,this paper proposes an improved GLF-Segformer to improve segmentation.The model adds polarized self-attention(PSA)module and R-convolution and attention fusion module(R-CAFM)to the Segformer’s encoder to enhance the ability to capture local information and facilitate the effective fusion of local and global information.The decoder employs an innovative two-stage hybrid up-sampling to effectively reduce information loss.In addition,a new hybrid loss function is designed to further improve the segmentation accuracy of the model at complex boundaries.The experimental results show that GLF-Segformer achieves 90.73%and 89.85%mean intersection over union(mIoU)on two standard datasets,ISIC2017 and ISIC2018,respectively,and exhibits better segmentation performance compared to other comparison algorithms. 展开更多
关键词 capture local information dermoscopy images interfering noise clinical treatmenthoweverthe segmentation global local information skin cancers
暂未订购 下载PDF
Wireless Environmental Information Theory:A New Paradigm Toward 6G Online and Proactive Environment Intelligence Communication 认领 引用 被引量：4
5
作者 Jianhua Zhang Li Yu +4 位作者 Shaoyi Liu Yichen Cai Yuxiang Zhang Hongbo Xing Tao Jiang 《Engineering》 SCIE EI CSCD 2026年第1期186-200,共15页
Channels are one of the five critical components of a communication system,and their ergodic capacity is based on all realizations of a statistical channel model.This statistical paradigm has successfully guided the d... Channels are one of the five critical components of a communication system,and their ergodic capacity is based on all realizations of a statistical channel model.This statistical paradigm has successfully guided the design of mobile communication systems from first generation(1G)to fifth generation(5G).However,this approach relies on offline channel measurements in specific environments,and thus,the system passively adapts to new environments,resulting in deviation from the optimal performance.As sixth generation(6G)expands into ubiquitous environments and pursues higher capacity,numerous sensing and artificial intelligence(AI)-based methods have emerged to combat random channel fading.However,there remains an urgent need for a proactive and online system design paradigm.From a system perspective,we propose an environment intelligence communication(EIC)based on wireless environmental information theory(WEIT)for 6G.The proposed EIC architecture operates in three steps.First,wireless environmental information(WEI)is acquired using sensing techniques.Then,leveraging WEI and channel data,AI techniques are employed to predict channel fading,thereby mitigating channel uncertainty.Finally,the communication system autonomously determines the optimal air-interface transmission strategy based on real-time channel predictions,enabling intelligent interaction with the physical environment.To make this attractive paradigm shift from theory to practice,we establish WEIT for the first time by answering three key problems:How should WEI be defined?Can it be quantified?Does it hold the same properties as statistical communication information?Subsequently,EIC aided by WEI(EIC-WEI)is validated across multiple air-interface tasks,including channel state information prediction,beam prediction,and radio resource management.Simulation results demonstrate that the proposed EIC-WEI significantly outperforms the statistical paradigm in decreasing overhead and performance optimization.Finally,several open problems and challenges,including regarding its accuracy,complexity,and generalization,are discussed.This work explores a novel and promising way for integrating communication,sensing,and AI capability in 6G. 展开更多
关键词 Sixth generation Intelligent communication Environment intelligence Wireless environmental information theory Environment sensing and reconstruction Channel prediction Digital twin channel ChannelGPT
暂未订购 下载PDF
Heterogeneity Performance of Cross-border Development Under the Influence of High-speed Rail Flow and Information Flow in Yangtze River Delta Region,China 认领 引用 被引量：1
6
作者 DUAN Wei WANG Shaobo +1 位作者 ZHOU Yutao WANG Xinyu 《Chinese Geographical Science》 SCIE CAS CSCD 2026年第3期524-540,共17页
In the knowledge economy era,the rapid flow channels represented by high-speed rail(HSR)and online information flow promote cross-border development between cities.This study constructed a conceptual model of cross-bo... In the knowledge economy era,the rapid flow channels represented by high-speed rail(HSR)and online information flow promote cross-border development between cities.This study constructed a conceptual model of cross-border development from the perspective of flow space.Taking the Yangtze River Delta Region(YRDR),China,as a case study,we apply the Speaker-listener Label Propagation Algorithm(SLPA)to detect the heterogeneity patterns of cross-border development shaped by HSR flow and information flow in 2021.Results show that cross-border development among cities is more evident under information flows compared to HSR flow.Furthermore,intra-provincial cross-border development predominates under HSR flow,whereas inter-provincial cross-border development is more frequent under in-formation flow.Additionally,information flow leads to more shared or competitive nodes in cross-border development across different communities.In the future,leveraging these nodes'intermediary role will be the key to driving the next phase of regional integration.This research will enhance and broaden the theoretical frameworks for cross-border integrated development,flow space,and regional coordinated development. 展开更多
关键词 flow space cross-border development high-speed rail(HSR)flow information flow Yangtze River Delta Region(YRDR),China
暂未订购 下载PDF
Deep Learning-Enhanced Human Sensing with Channel State Information: A Survey 认领 引用 被引量：1
7
作者 Binglei Yue Aili Jiang +3 位作者 Chun Yang Junwei Lei Heng Liu Yin Zhang 《Computers, Materials & Continua》 SCIE EI 2026年第1期1-28,共28页
With the growing advancement of wireless communication technologies,WiFi-based human sensing has gained increasing attention as a non-intrusive and device-free solution.Among the available signal types,Channel State I... With the growing advancement of wireless communication technologies,WiFi-based human sensing has gained increasing attention as a non-intrusive and device-free solution.Among the available signal types,Channel State Information(CSI)offers fine-grained temporal,frequency,and spatial insights into multipath propagation,making it a crucial data source for human-centric sensing.Recently,the integration of deep learning has significantly improved the robustness and automation of feature extraction from CSI in complex environments.This paper provides a comprehensive review of deep learning-enhanced human sensing based on CSI.We first outline mainstream CSI acquisition tools and their hardware specifications,then provide a detailed discussion of preprocessing methods such as denoising,time–frequency transformation,data segmentation,and augmentation.Subsequently,we categorize deep learning approaches according to sensing tasks—namely detection,localization,and recognition—and highlight representative models across application scenarios.Finally,we examine key challenges including domain generalization,multi-user interference,and limited data availability,and we propose future research directions involving lightweight model deployment,multimodal data fusion,and semantic-level sensing. 展开更多
关键词 Channel State Information(CSI) human sensing human activity recognition deep learning
暂未订购 下载PDF
Information Security with Smart Hydrogels: Photo-Patterning and Multi-Stimuli Responsive Structural Color 认领 引用
8
作者 Xiaoyu Guo Ying Li +5 位作者 Farzana Hanif Linhai Zhu Miao Kong Shufen Zhang Yuang Zhang Bingtao Tang 《Nano-Micro Letters》 SCIE EI CAS CSCD 2026年第9期420-434,共15页
Photonically structured colors, characterized by high resolution and dynamic responsiveness, hold promising prospects in the field of information security. However, conventional patterning methods are often limited by... Photonically structured colors, characterized by high resolution and dynamic responsiveness, hold promising prospects in the field of information security. However, conventional patterning methods are often limited by high equipment costs and monotonous color outputs, which restrict their widespread adoption. To address these issues, this paper proposes a novel multi-color patterning method based on light-induced chemical crosslinking. By introducing light-initiated crosslinking molecules into anti-opal hydrogels, we developed a film that can be further regulated by photo-curing, enabling a “film formation first, then patterning” approach. The structural color hydrogels created using this method can display multi-color patterns, with a minimum line width of 15 μm, significantly enhancing their information-carrying capacity. Moreover, ultraviolet radiation can increase the degree of cross-linking, thereby inhibiting swelling behavior, enhancing tensile strength, reducing elongation at break, and causing the color of the inverse opal structure to shift toward blue or disappear. With inherent responsiveness to stress, temperature, and solvents, this approach enables dynamic information display and has excellent stability(able to cycle stably for more than 100 times). This work introduces a new method for patterning stimulus-responsive structural colors and opens up new possibilities for their use in applications such as ink-free printing, information encryption, and anti-counterfeiting. 展开更多
关键词 Structural color Anti-opal hydrogel Light-induced crosslinking Information security
暂未订购 下载PDF
Active vibration isolation based on absolute-relative dynamic stiffness control via multi-sensor information fusion 认领 引用
9
作者 Zhiwei Huang Jiulin Wu +4 位作者 Fuxiang Zhang Rui Zhou Hu Li Xuedong Chen Wei Jiang 《ENGINEERING Mechanical Engineering》 SCIE CAS CSCD 2026年第2期129-152,共24页
The requirements for isolating outer vibration and suppressing inner disturbances are increasingly stringent and even approaching extreme limits in integrated circuit manufacturing,precision measurement,scientific exp... The requirements for isolating outer vibration and suppressing inner disturbances are increasingly stringent and even approaching extreme limits in integrated circuit manufacturing,precision measurement,scientific experiments,etc.In comparison with passive isolation,active control methods can significantly enhance vibration isolation performance.However,different control strategies are mainly effective in different frequency domains,and performance may deteriorate in some frequency domains due to sensor noises.Active vibration isolation based on absolute-relative dynamic stiffness control via multi-sensor information fusion is proposed in this paper.This method can substantially improve vibration attenuation capability and position stability performances in broad bandwidth,with a particular focus on improving the resonance peak suppression capability in the ultra-low frequency domain.First,the effects of different control strategies on vibration isolation in different frequency domains are analyzed,and the hybrid control strategy is proposed by using both absolute relative signal feedback.Considering the noise characteristics of absolute velocity sensors and relative displacement sensors,different filters are accordingly adopted to improve vibration isolation performance.A one-dimensional experimental platform is established to conduct vibration control experiments under different configurations.The results demonstrate that vibration isolation performance across a wide frequency range can be significantly improved,and the proposed method further proves effective for micro-vibration systems.Typically,transmissibility can be reduced to as low as -30 dB at 1 Hz and -48 dB at 2 Hz,with guarantee of less than -50 dB within 10-50 Hz.Additionally,compliance results show 10-40 dB performance improvements across the broad frequency range(0.1-100 Hz)compared with the passive system. 展开更多
关键词 active vibration control dynamic stiffness multi-sensor information fusion absolute velocity feedback relative displacement feedback
暂未订购 下载PDF
A Dynamic Correlation-Information-Fusion-Based Spatiotemporal Network for Traffic Flow Forecasting 认领 引用
10
作者 Dawen Xia Zhan Lin +4 位作者 Xingyan Wang Ruixi Huang Jinhui Hu Yang Hu Huaqing Li 《CAAI Transactions on Intelligence Technology》 SCIE EI CSCD 2026年第3期859-874,共16页
Traffic Flow Forecasting(TFF)is a foundational task in the development of Intelligent Transport Systems(ITSs).The primary challenge is to undertake a comprehensive exploration of the intrinsic dynamic spatiotemporal c... Traffic Flow Forecasting(TFF)is a foundational task in the development of Intelligent Transport Systems(ITSs).The primary challenge is to undertake a comprehensive exploration of the intrinsic dynamic spatiotemporal correlations of the road network,unveiling the long-term evolutionary traffic trends.Furthermore,most existing methods often solely depend on the single traffic condition and neglect the enhancement of correlated features collected from traffic sensors in prediction.To this end,we propose a dynamic correlation-information-fusion-based(DCIF)spatiotemporal network for TFF,which models the spatiotemporal correlations of road networks,thereby effectively capturing dynamically changing characteristics.Specifically,a spatiotemporal feature enhancement(STFE)mechanism is employed to capture the directional and location-aware characteristics of traffic flow,thereby enhancing the representation of traffic flow and the capability of spatiotemporal feature extraction.Then,a gated attention unit(GAU)is constructed to meticulously extract the deep dynamic trends inherent within traffic data.Finally,a dynamic feature matrix(DFM)is formulated,incorporating spatial graph convolution to provide comprehensive semantic contextual information.The DFM captures the dynamic topology of the deeper feature network in real time by fusing spatial node information and traffic speed features as correlation information.Extensive experiments demonstrate that DCIF significantly outperforms other baselines in prediction accuracy,thereby further substantiating its validity and reliability in TFF. 展开更多
关键词 dynamic feature matrix dynamic spatiotemporal correlations gated attention unit multi‐source information fusion spatiotemporal feature enhancement mechanism traffic flow forecasting
暂未订购 下载PDF
A Method for Detecting Spatio-Temporal Correlation Anomalies of WSN Nodes Based on Topological Information Enhancement and Time-Frequency Feature Extraction 认领 引用
11
作者 Miao Ye Ziheng Wang +4 位作者 Qiuxiang Jiang Xingsi Xue Wenxi Liu Yu Ning Cheng Zhu 《Computers, Materials & Continua》 SCIE EI 2026年第8期1840-1870,共31页
In recent years,anomaly detection in Wireless Sensor Networks(WSNs)has been widely studied using Graph Neural Networks and Transformer-based methods.However,in multi-node and multi-modal data scenarios,these approache... In recent years,anomaly detection in Wireless Sensor Networks(WSNs)has been widely studied using Graph Neural Networks and Transformer-based methods.However,in multi-node and multi-modal data scenarios,these approaches still face challenges such as insufficient extraction of spatiotemporal correlation features,limited modeling capabilities when relying solely on either time-domain or frequency-domain information,and high computational overhead.To address these issues,this work aims to develop an anomaly detection model that balances detection performance with computational efficiency,enabling effective identification of complex anomaly patterns.Specifically,we propose a time–frequency feature extraction method with topological information enhancement,topology-enhanced multi-modal spatio-temporal anomaly detection(TE-MSTAD).Building upon the Receptance Weighted Key Value(RWKV)model with linear complexity,a cross-modal feature extraction module is introduced to strengthen the modeling of multi-modal correlations.Meanwhile,adaptive adjacency matrices are constructed by integrating time–frequency features and combining outputs from different Graph Neural Networks,thereby enhancing topological information.Furthermore,a dual-branch structure is designed to jointly model time-domain and frequency-domain features,improving the extraction of complex anomaly characteristics.Experiments on both publicly available datasets and real-world collected data demonstrate that the proposed method achieves F1-scores of 92.52%and 93.28%,respectively,outperforming existing methods in detection performance and generalization capability. 展开更多
关键词 Wireless sensor networks anomaly detection time-frequency domain fusion graph neural networks information enhancement
暂未订购 下载PDF
BAID:A Lightweight Super-Resolution Network with Binary Attention-Guided Frequency-Aware Information Distillation 认领 引用
12
作者 Jiajia Liu Junyi Lin +3 位作者 Wenxiang Dong Xuan Zhao Jianhua Liu Huiru Li 《Computers, Materials & Continua》 SCIE EI 2026年第2期1190-1208,共19页
Single Image Super-Resolution(SISR)seeks to reconstruct high-resolution(HR)images from lowresolution(LR)inputs,thereby enhancing visual fidelity and the perception of fine details.While Transformer-based models—such ... Single Image Super-Resolution(SISR)seeks to reconstruct high-resolution(HR)images from lowresolution(LR)inputs,thereby enhancing visual fidelity and the perception of fine details.While Transformer-based models—such as SwinIR,Restormer,and HAT—have recently achieved impressive results in super-resolution tasks by capturing global contextual information,these methods often suffer from substantial computational and memory overhead,which limits their deployment on resource-constrained edge devices.To address these challenges,we propose a novel lightweight super-resolution network,termed Binary Attention-Guided Information Distillation(BAID),which integrates frequency-aware modeling with a binary attention mechanism to significantly reduce computational complexity and parameter count whilemaintaining strong reconstruction performance.The network combines a high–low frequency decoupling strategy with a local–global attention sharing mechanism,enabling efficient compression of redundant computations through binary attention guidance.At the core of the architecture lies the Attention-Guided Distillation Block(AGDB),which retains the strengths of the information distillation framework while introducing a sparse binary attention module to enhance both inference efficiency and feature representation.Extensive×4 superresolution experiments on four standard benchmarks—Set5,Set14,BSD100,and Urban100—demonstrate that BAID achieves Peak Signal-to-Noise Ratio(PSNR)values of 32.13,28.51,27.47,and 26.15,respectively,with only 1.22 million parameters and 26.1 G Floating-Point Operations(FLOPs),outperforming other state-of-the-art lightweight methods such as Information Multi-Distillation Network(IMDN)and Residual Feature Distillation Network(RFDN).These results highlight the proposed model’s ability to deliver high-quality image reconstruction while offering strong deployment efficiency,making it well-suited for image restoration tasks in resource-limited environments. 展开更多
关键词 Single image super-resolution lightweight network binary attention information distillation
暂未订购 下载PDF
Turbo Equalization for Time-Varying Underwater Acoustic Channels with Imperfect Channel State Information 认领 引用
13
作者 Jiaheng Zhang Wei Ge +1 位作者 Wentao Tong Lin Cheng 《哈尔滨工程大学学报（英文版）》 CSCD 2026年第2期630-639,共10页
Turbo equalization is commonly employed to compensate for multipath propagation in underwater acoustic(UWA)communication.However,the performance of turbo equalization degrades due to the imperfect channel state inform... Turbo equalization is commonly employed to compensate for multipath propagation in underwater acoustic(UWA)communication.However,the performance of turbo equalization degrades due to the imperfect channel state information(CSI)and time-varying channels.Herein,we first introduce a new derivation for turbo equalization based on the joint Gaussian criterion.On the basis of this derivation,a novel turbo equalization algorithm for time-varying UWA channels with imperfect CSI is proposed.The algorithm combines the imperfect CSI with the temporal coherence characteristics of UWA channels,which are modeled as a first-order autoregressive(AR(1))process,to achieve a more accurate channel a posteriori distribution.Afterward,the refined distribution is incorporated into the design of the turbo equalizer,which can effectively reduce intersymbol interference and the Doppler effect.Simulation results show that the proposed algorithm has a better bit error rate performance than other turbo equalization algorithms with channel estimation error compensation or the AR(1)process for any iteration in fast time-varying scenarios. 展开更多
关键词 Imperfect channel state information First-order autoregressive process Turbo equalization Time-varying channels Underwater acoustics communication
暂未订购 下载PDF
Impact of resource allocation on information-disease coupled propagation considering node importance in multiplex networks 认领 引用
14
作者 Liang’an Huo Jiaxue Cha Yue Yu 《Chinese Physics B》 SCIE EI CAS CSCD 2026年第7期901-913,共13页
During a large-scale epidemic outbreak,effective resource allocation is vital for controlling disease transmission.Prioritizing resource provision to communities experiencing severe infections can mitigate further spr... During a large-scale epidemic outbreak,effective resource allocation is vital for controlling disease transmission.Prioritizing resource provision to communities experiencing severe infections can mitigate further spread,while prioritizing information dissemination to influential individuals can expand the publicity effect.This paper proposes a novel two-layer information-disease transmission coupled model that optimizes the allocation of information and medical resources based on node importance analysis,aiming to explore the synergistic effects of resource allocation on disease dynamics.The study employs the microscopic Markov chain approach to construct dynamic equations and derive the epidemic threshold,with Monte Carlo simulations used to validate the theoretical results.Findings demonstrate that expanding the scope of preventive information dissemination through mass media improves public awareness of disease prevention and significantly curbs epidemic transmission.Moreover,reducing the resource deployment threshold in infected communities enables more precise resource allocation during the early stages of an outbreak,which is vital for increasing the epidemic threshold and reducing the final size of the epidemic.These findings provide robust theoretical foundations and actionable guidelines for optimizing resource allocation strategies in public health emergency management. 展开更多
关键词 information dissemination disease transmission resource allocation node importance multilayer network
暂未订购 下载PDF
MRWS:multi-stage RAW low-light image enhancement with wavelet information and SNR prior 认领 引用
15
作者 Tao ZHANG Shiqi GAO +1 位作者 Hao WANG Xin ZHAO 《Optoelectronics Letters》 EI 2026年第4期250-256,共7页
For low-light image enhancement tasks,RAW images surpass RGB images due to their high information content,however,their noise and single-channel nature challenge feature extraction.Existing methods using multi-stage c... For low-light image enhancement tasks,RAW images surpass RGB images due to their high information content,however,their noise and single-channel nature challenge feature extraction.Existing methods using multi-stage convolutional neural network(CNN)frameworks struggle with global feature extraction,while single-stage CNN-transformer fusions often result in residual noise.To overcome these limitations,this paper introduces a multi-stage RAW image enhancement network combining CNN and transformer.Considering the characteristics inherent to the task,we devised a CNN-based denoising block for the denoising stage and incorporated wavelet information to enhance frequency features.A transformer-based correction block has been designed for the color and white balance recovery stage,with the white balance being adjusted dynamically using a signal-to-noise ratio(SNR)map.With this design,our method outperforms other state-of-the-art models in all metrics on the Sony and Fuji datasets of see-in-the-dark(SID),and achieves optimal structural similarity index measurement(SSIM)on the mono-colored raw(MCR)dataset. 展开更多
关键词 wavelet information multi stage feature extractionexisting SNR prior raw image rgb images feature extractionwhile low light image
暂未订购 下载PDF
FELoc:a feature equalization method based on channel state information for Wi-Fi indoor localization 认领 引用
16
作者 Ken Long Jincheng Yang Guoxu Xia 《Digital Communications and Networks》 SCIE EI CSCD 2026年第5期813-824,共12页
With the rapid development of 5G-A technology,Wi-Fi-based indoor fingerprint localization has gained prominence for its high-precision indoor localization.However,conventional methods often suffer from noise interfere... With the rapid development of 5G-A technology,Wi-Fi-based indoor fingerprint localization has gained prominence for its high-precision indoor localization.However,conventional methods often suffer from noise interference and indistinct fingerprints in complex environments,reducing the accuracy of localization.To address these issues,the Feature Equalization Localization Method(FELoc)based on Channel State Information(CSI)is proposed in this paper.A unified preprocessing strategy named WaveICA is designed to enhance fingerprint quality by combining Hierarchical Thresholding Wavelet Denoising(HTWD)for noise suppression and Independent Component Analysis(ICA)for extracting independent features,which effectively improves the discriminability of CSI amplitude and phase data from multiple antennas.Additionally,Feature Equalization Localization Network(FELN)is designed for feature extraction and fusion,which employs dual-branch convolution with a Multiscale Channel-spatial Attention Module(MCAM)to enhance salient features and a novel Feature Equalization Module(FEM)to adaptively fuse phase and amplitude representations.Extensive experiments conducted in diverse indoor scenarios demonstrate that FELoc achieves superior localization performance,providing both higher accuracy and stronger robustness compared to other methods. 展开更多
关键词 Wi-Fi Indoor localization Channel state information Hierarchical thresholding wavelet denoising Independent component analysis Feature equalization localization network
暂未订购 下载PDF
Analog programmable-photonic information 认领 引用
17
作者 Andrés Macho-Ortiz Raúl López-March +2 位作者 Pablo Martínez-Carrasco Romero Francisco Javier Fraile-Peláez JoséCapmanya 《Advanced Photonics》 SCIE EI CAS CSCD 2026年第3期52-67,共16页
.The limitations of digital electronics in handling real-time matrix operations for emerging computationaltasks—such as artificial intelligence,drug design,and medical imaging—have prompted renewed interest in analo... .The limitations of digital electronics in handling real-time matrix operations for emerging computationaltasks—such as artificial intelligence,drug design,and medical imaging—have prompted renewed interest in analog computing.Programmable integrated photonics(PiP)has emerged as a promising technology for scalable,low-power,and high-bandwidth analog computation.Although prior work has explored PIP implementations of quantum and neuromorphic computing,both approaches face significant limitations due to misalignments between their mathematical models and the native capabilities of photonic hardware.Building on the recently proposed analog programmable-photonic computation(APC)—a computation theory explicitly matched to the technological features of PiP—we introduce its critical missing component:an information theory.We present analog programmable-photonic information(APl),a mathematical framework that addresses fundamental concepts beyond APC by examining the amount of information that can be generated,computed,and recovered in a PIP platform.APl also demonstrates the robustness of APC against errors arising from system noise and hardware imperfections,enabling scalable computation without the extensive error correction overhead required in quantum computing.Together,APC and API provide a unified foundation for on-chip photonic computing,offering a complementary alternative to digital,quantum,and neuromorphic paradigms,and positioning PiP as a cornerstone technology for next-generation information processing. 展开更多
关键词 integrated optics programmable integrated photonics optical information optical computing
Asymmetric model of the dynamic quantum Cournot duopoly game with asymmetric information and heterogeneous players 认领 引用
18
作者 Huaxin Chen Wensheng Jia 《Chinese Physics B》 SCIE EI CAS CSCD 2026年第4期295-302,共8页
Building on the existing symmetric quantization model of the dynamic Cournot duopoly game(CDG)with asymmetric information,we extend it to an asymmetric quantization model and study the stability of the quantum Bayesia... Building on the existing symmetric quantization model of the dynamic Cournot duopoly game(CDG)with asymmetric information,we extend it to an asymmetric quantization model and study the stability of the quantum Bayesian Nash equilibrium(QBNE)under heterogeneous expectations.We analyze the influence of various parameters on the stability of QBNE,with a particular focus on the impact of the parameter α on system stability.The results show that when α1,the quantum strategy of the symmetric quantization model is more conducive to stabilizing the market. 展开更多
关键词 quantum Cournot games Bayesian Nash equilibrium asymmetric quantization scheme asymmetric information
暂未订购 下载PDF
A Unified Feature Selection Framework Combining Mutual Information and Regression Optimization for Multi-Label Learning 认领 引用
19
作者 Hyunki Lim 《Computers, Materials & Continua》 SCIE EI 2026年第4期1262-1281,共20页
High-dimensional data causes difficulties in machine learning due to high time consumption and large memory requirements.In particular,in amulti-label environment,higher complexity is required asmuch as the number of ... High-dimensional data causes difficulties in machine learning due to high time consumption and large memory requirements.In particular,in amulti-label environment,higher complexity is required asmuch as the number of labels.Moreover,an optimization problem that fully considers all dependencies between features and labels is difficult to solve.In this study,we propose a novel regression-basedmulti-label feature selectionmethod that integrates mutual information to better exploit the underlying data structure.By incorporating mutual information into the regression formulation,the model captures not only linear relationships but also complex non-linear dependencies.The proposed objective function simultaneously considers three types of relationships:(1)feature redundancy,(2)featurelabel relevance,and(3)inter-label dependency.These three quantities are computed usingmutual information,allowing the proposed formulation to capture nonlinear dependencies among variables.These three types of relationships are key factors in multi-label feature selection,and our method expresses them within a unified formulation,enabling efficient optimization while simultaneously accounting for all of them.To efficiently solve the proposed optimization problem under non-negativity constraints,we develop a gradient-based optimization algorithm with fast convergence.Theexperimental results on sevenmulti-label datasets show that the proposed method outperforms existingmulti-label feature selection techniques. 展开更多
关键词 feature selection multi-label learning regression model optimization mutual information
暂未订购 下载PDF
Guidelines for visual cognitive rehabilitation of visual information processing disorders(2025) 认领 引用
20
作者 Yi Shao Cong Zhang +6 位作者 Chun-Nan Zhang Expert Workgroup of Guidelines for VisualCognitive Rehabilitation of Visual Information Processing Disorders Ophthalmology&Optometry Branch of China Association for Ethnic Medicine Ophthalmology Committee ofInternational Association of Translational Medicine Ophthalmology Committee of InternationalAssociation of Intelligent Medicine Intelligent Medicine Special Committee of China MedicalEducation Association Chinese Visual Cognition Study Group 《International Journal of Ophthalmology(English edition)》 SCIE CAS 2026年第8期1484-1498,共15页
●Visual information processing(VIP)is essential for perception and cognition.It enables the brain to acquire and integrate visual stimuli into coherent representations.Visual information processing disorder(VIPD)is c... ●Visual information processing(VIP)is essential for perception and cognition.It enables the brain to acquire and integrate visual stimuli into coherent representations.Visual information processing disorder(VIPD)is characterized by impairments in visuospatial ability,visual analysis,and visuomotor integration.These deficits significantly affect daily activities,learning,and occupational performance.The etiology of these disorders is multifaceted,including developmental anomalies,traumatic brain injuries,ocular diseases,and surgical interventions.This condition involves multiple disciplines(ophthalmology,pediatrics,neurology,and rehabilitation),posing significant challenges for clinical diagnosis,treatment,and rehabilitation.Despite the growing international focus on these disorders,there remain considerable deficiencies in their diagnosis and treatment within China.Clinicians often have limited awareness of VIPD.Standardized diagnostic criteria are lacking,and rehabilitation approaches remain inconsistent.Visual abnormalities are often overlooked in pediatrics and neurology.In contrast,ophthalmology is limited in addressing disorders related to neurological dysfunction.In response to these challenges,this guide has been developed,drawing on the experiences of Europe and America and integrating local research and practice.It provides practical and systematic guidance for the diagnosis and management of VIPD.The objective is to enhance diagnostic and therapeutic capabilities,foster interdisciplinary collaboration,and improve patients’visual function and quality of life. 展开更多
关键词 visual information processing disorder visual cognition rehabilitation therapy guidelines
暂未订购 下载PDF
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
上一页 1 2 … 250 下一页 到第 页
在线咨询 使用帮助 返回顶部 意见反馈