Food safety is closely related to human health. Therefore, named entity recognition technology used extract entities food safety, and building a regulatory knowledge graph in the field of can help relevant authorities regulate issues mitigate hazards caused by problems. However, there no publicly available dataset domain. In contrast, non-standardized Chinese short texts generated from user comments on web contain rich implicit information that identify specific domains (e.g., domain) where...

In this paper, we study the joint optimization problem of spectrum and power allocation for multiple vehicle-to-infrastructure (V2I) vehicle-to-vehicle (V2V) users in cellular vehicle-to-everything (C-V2X) communication, aiming to maximize sum rate V2I links while satisfying low latency requirements V2V links. However, channel state information (CSI) is hard obtain accurately due mobility vehicles. addition, effective sensing among vehicles becomes difficult an environment with complex...

Vehicle-to-vehicle (V2V) communication has attracted increasing attention since it can improve road safety and traffic efficiency. In the underlay approach of mode 3, V2V links need to reuse spectrum resources preoccupied with vehicle-to-infrastructure (V2I) links, which will interfere V2I links. Therefore, how allocate wireless flexibly throughput while meeting low latency requirements needs be determined. This paper proposes a resource allocation framework based on deep reinforcement...

The rising demand for higher access rate and data applications will lead to the shortage of available spectrum resources. In this article, we propose a scalable framework share resources design reasonable effective resource management scheme solve allocation power control problems device-to-device (D2D) communication in dense scenarios. First, order maximize system throughput user by using many-to-many sharing improve utilization. Second, considering imperfect channel state information,...

Accurate traffic flow prediction is essential to building a smart transportation city. Existing research mainly uses given single-graph structure as model, only considers local and static spatial dependencies, ignores the impact of dynamic spatio-temporal data diversity. To fully capture characteristics diversity, this paper proposes cross-Attention Fusion Based Spatial-Temporal Multi-Graph Convolutional Network (CAFMGCN) model for prediction. First, introduce GCN historical data's...

Spectrum demand has increased with the rapid growth of wireless devices and service usage. The development 5G smart cities industrial Internet Things makes problem spectrum resource shortage energy consumption even more severe. To address issues high for sensing low user access rate in cognitive radio networks (CRN) model powered entirely by harvesting, we propose a novel harvesting (EH)-distributed cooperative (DCSS) architecture that allows SUs to acquire from surrounding environment...

Traffic flow forecasting is the foundation of intelligent transportation systems. Accurate traffic crucial for management and urban development. However, achieving highly accurate prediction challenging due to road networks’ complex dynamic spatial temporal dependencies. Previous work using predefined static adjacency matrices in graph convolutional networks needs be revised reflect dependencies system. In addition, most current methods ignore hidden spatial–temporal correlations between...

Named entity recognition involves two main types: nested named and flat recognition. The span-based approach treats entities uniformly by classifying on a span representation. However, the ignores local features within relative position between head tail tokens, which affects performance of To address these issues, we propose model using convolutional block attention module rotary embedding for enhancement. Specifically, apply to sentence representation capture semantic information tokens...

Simultaneous wireless information and power transfer (SWIPT) is an effective energy-saving technology, but its efficiency hindered by environmental factors. The introduction of reconfigurable intelligent surfaces (RIS) has alleviated this issue, although it still faces significant constraints due to geographical limitations. This paper proposes a scheme that employs simultaneously transmitting reflecting (STAR)-RIS assist SWIPT. It can overcome limitation, achieve higher degrees freedom...

Fuzzy Kohonen clustering networks (FKCN) are well known for analysis (unsupervised learning and self-organizing). This classification of FKCN algorithm is a set iterative procedures that suffer some major problems, example its constringency rate not too fast large amount datasets. To overcome these defects, an efficient fuzzy network proposed in this paper, which can significantly reduce the computation time required to partition dataset into desired clusters. By introducing threshold values...

The significance of vehicle-to everything (V2X) communication in ensuring road safety is undeniable. In addition, real-time vehicle requires an ample amount spectrum resources. However, the existing resources are seriously scarce, and utilization rate not high, leading to high delays V2X other unfavorable factors case fast-moving vehicles, bringing great risks driving. Load balancing one most effective methods improve utilization. load schemes merely focus on static conditions, with a lack...

Telephone traffic of busy hour is one indicators load capacity telecommunication network, which has a significant meaning to dilate and modify the network. A good performance predicting monthly cared about by mobile operators. As promising learning theory, support vector machine (SVM) been studied applied in wide area, such as financial markets weather forecast. In this paper, we use SVM forecast two regions Xinjiang. result achieved via an improved grid search method for hyper-parameter SVM.

In order to get better control of the chaotic randomness and improve convergence rate Transient Chaotic Neural Networks(TCNN),Effective improvement is proposed in this study.By modifying Incentive function with composite sine sigmoid Time-varying Gain are adopted function, two-stage annealing mechanism applied process dynamic equations.Empirical results show that combination two aspects has a processes state,improved algorithm obtains wealth characteristics. Experiments on channel allocation...

In this paper, a technique is presented for the fusion of Panchromatic (PAN) and low spatial resolution multispectral (MS) images to get high latter. technique, we apply PCA transformation MS image obtain principal component (PC) images. A NSCT PAN each PC N level decomposition. We use FOCC as criterion select PC. And then, relative entropy reconstruct high-frequency detailed Finally, inverse selected PC's low-frequency approximate reconstructed high- frequency image. The experimental...

In order to get the change detection image.An unsupervised algorithm for multi-temporal satellite image based on NSCT (non-subsampling contourlet transform) and k-means clustering is proposed in this paper. For each pixel log-ratio image, multi-scale multi-direction feature vector extracted by reconstruction of obtained. The threshold produced using can distinguish between unchanged region. Finally, map achieved. Some images are used verify method results shows that it has a higher stability...

Few-shot named entity recognition requires sufficient prior knowledge to transfer valuable the target domain with only a few labeled examples. Existing Chinese few-shot methods suffer from inadequate and limitations in feature representation. In this paper, we utilize enhanced Span Label semantic representations for Named Entity Recognition (SLNER) address problem. Specifically, SLNER utilizes two encoders. One encoder is used encode text its spans, employ biaffine attention mechanism...

Urban traffic prediction is essential for intelligent transportation systems. However, data often exhibit highly complex spatio-temporal correlations, posing challenges accurate forecasting. Graph neural networks have demonstrated an outstanding ability in capturing spatial correlations and are now extensively applied to prediction. many graph-based methods neglect the dynamic features between road segments continuity of across adjacent time steps, leading subpar predictive performance. This...

Abstract A new method for image denoising based on the free distributed hypothesis test threshold (FDR) and non-sub-sampled contourlet transform(NSCT) is proposed in this paper. This firstly acquires false discovery rate hypotheses statistics to set NSCT domain, then removes noise through soft function, which doesn’t depend length of signal. The experimental results show that can more effectively reduce Gaussian improve peak value signal-to-noise ratio remote sensing image; Meanwhile,...