The practically fixed-time leaderless cluster synchronization is addressed for uncertain spatiotemporal networks (USTNs) with coopetition interactions, actuator faults and external disturbances. Firstly, by introducing sign-based coupling, a class of USTN is formulated to capture the dynamics of coopetition interactions among different clusters, which provides a more accurate representation compared to dynamical networks with unsigned coupling. Secondly, a practical fixed-time (PFT) convergence theorem is developed for a general partial differential system, which relaxes the constraints on the derivative of the Lyapunov function and provides a less conservative method for estimating the settling time. Subsequently, a distributed fault-tolerant control algorithm is designed to drive the cluster synchronization error to an adjustable attraction region in a fixed time. By exploring specific properties of the intra-cluster Laplacian matrix and proposing a new inter-degree balanced condition, several flexible synchronization criteria are derived and a quantitative relationship among control parameters, the settling time and the size of the attraction region is presented. Finally, the effectiveness of the developed controllers and criteria is validated through a coupled reaction-diffusion neural network.

ABSTRACT The deployment of industrial robots in time‐critical applications demands ultra‐low latency and high reliability in communication systems. This study presents a novel delay optimisation framework for industrial robot control systems using 6G network slicing technologies. A Gale–Shapley (GS)‐based elastic switching model is proposed to dynamically match robot controllers to optimised network slices and base stations under latency‐sensitive conditions. To enhance resource adaptability, a long short‐term memory (LSTM)‐based encoder‐decoder structure is developed for predictive resource allocation across slices. The proposed integrated matching mechanism achieves a success rate of 91.16% for slice access and a base station access rate of 90.83%, outperforming conventional integrated and two‐stage schemes. The LSTM‐based resource allocation achieves a mean absolute error of 0.04 and a violation rate below 10%, with over 92% utilisation of both node and link resources. Experimental simulations demonstrate a consistent end‐to‐end latency below 7 ms and a throughput of 18.4 Mbit/s, validating the proposed models' effectiveness in ensuring robust, real‐time communication for industrial robot operations. This research contributes a scalable solution for dynamic 6G network resource management, providing a foundation for advanced industrial automation and intelligent manufacturing.

This article addresses the fixed-time leaderless cluster synchronization of spatiotemporal community networks (SCNs) characterized by nonidentical node dynamics and reaction-diffusion feature. First, a signed SCN with reaction-diffusion effect is formulated, where the sign-based coupling is introduced to capture the dynamics of coopetition interactions among different communities. Second, to ensure the invariance of the synchronous manifold, an improved interdegree balance condition is proposed as a prerequisite for achieving cluster synchronization of the community network. Third, based on the local state information from adjacent nodes within each community, a time-limited controller is designed to enhance intracommunity coordination while avoiding the adverse effects of intercommunity competition on synchronization. Subsequently, with the help of the matrix decomposition technique and a Lyapunov-like method, several flexible leaderless cluster synchronization criteria are derived by establishing a nontrivial integral inequality and key properties of the intracommunity Laplacian matrix. Finally, the theoretical results are substantiated through a numerical example.

Dioscorea PolystachyaTurczaninow is one of the most famous traditional Chinese Materia Medica. However, there is lack of large-scale classification method which is crucial for its growth status monitoring and yield estimation. This study proposed a reliableDioscorea PolystachyaTurczaninow classification model based on spectral-temporal-spatial feature optimization using time-series Sentinel-2 data. Firstly, 16 mono-temporal classification models were developed using five vegetation indices (VIs) and random forest algorithm. Then, temporal feature optimization was conducted by identifying the most effective time phase combinations based on Sentinel-2 time-series normalized difference vegetation index (NDVI) data, gaussian mixture modeling algorithm and F1 score ofDioscorea PolystachyaTurczaninow in each mono-temporal model. Next, spectral features were optimized by replacing NDVI with the optimal VI corresponding to each time phase, thus constructing a multi-VIs-based time-series dataset. Finally, the spatial feature optimization was conducted using the three-dimensional convolutional neural network (3-D CNN) algorithm and the multi-VIs-based time series Sentinel-2 data. Following the comprehensive feature optimization, the finalDioscorea PolystachyaTurczaninow classification model was determined. The results found that Sentinel-2 data acquired during the rhizome enlargement stage played a crucial role in classifying theDioscorea PolystachyaTurczaninow. By using the optimized features, the classification model achieved theDioscorea PolystachyaTurczaninow F1 score of 95.00%, which improved by 11.49% compared to only using the time series NDVI data. This spectral, temporal and spatial feature optimization method also has the potential to the development of large-scale, dynamic, and accurate mapping for other crops.

This article is concerned about fixed-time (FT) synchronization of spatiotemporal networks (STNs) with the Robin boundary condition. Above all, a switching-type FT stability theorem and an integral inequality are established, which provide a novel theoretical tool for the rigorous analysis of FT control in STNs. Subsequently, three kinds of nontrivial power-law controllers are developed which are separately acted on the interior, the boundary, and the whole of the spatial domain. Based on these control schemes and Lyapunov-like method, several flexible criteria are obtained to achieve FT synchronization of STNs, and the upper bound of the synchronization time is explicitly estimated. Note that, the derived results here are also perfectly applicable to STNs with Neumann or Dirichlet boundary condition. Several illustrate examples are presented at final to confirm the developed controllers and criteria.

Accurate information regarding cultivated areas of medicinal plants is useful for taking macro-level decisions for medicinal plant management and contingency plans. In this study, the capabilities and limitations of mappingAstragalus mongholicusBunge andSophora flavescensAiton using GaoFen-6 (GF-6) and multitemporal Sentinel-2 (S-2) data were assessed through a case study in Naiman Banner, Inner Mongolia, China. First, an object-based approach was used to produce a cropland mask based on the GF-6 images. Then, different spectral indices were generated from multitemporal S-2 imagery acquired in 2019, and a temporal phonological pattern analysis was conducted. Subsequently, optimal feature selection was carried out for each of the crops (A. mongholicusBunge,S. flavescensAiton, andZea maysL.). The selection was performed by sorting all features according to their global separability index and removing those whose contribution to the model accuracy was negligible. Finally, the medicinal crops were distinguished using the random forest classification algorithm. An overall accuracy and a kappa coefficient of 94.51% and 0.90 were achieved, respectively, demonstrating that the synergistic use of time-series GF-6 and S-2 data were more suitable forA. mongholicusBunge andS. flavescensAiton mapping.

Dioscorea polystachyaTurczaninow is an herbaceous vine plant distributed in China, and its rhizome named Chinese yam is a famous traditional Chinese medicine for treating diabetes and other diseases. However, a large region monitoring method of its growth status is lacking, which is important for Chinese yam yield estimation. Therefore, this study proposed a leaf area index (LAI) estimation algorithm forDioscorea polystachyaTurczaninow using a hybrid method and Sentinel-2 vegetation indices. First, two feature selection algorithms the gradient boosting regression tree (GBRT) and absolute Pearson correlation coefficient (APCC), were combined with field-measured data and radiation transfer model simulated data to generate four different feature important ranking groups. Then, a hybrid feature selection algorithm was used to determine the best feature subsets under each ranking group, and GBRT regression and least absolute shrinkage and selection operator (LASSO) were used to develop the LAI estimation models. Finally, the best LAI estimation model forDioscorea polystachyaTurczaninow was determined based on validation accuracy. The results indicated that the field-measured data were more reliable than the simulated data for feature selection, and the best LAI estimation model was the LASSO model using nine selected vegetation indices, which achieved the performance with RMSE of 0.391 and MAE of 0.310. The proposed method could provide real-time LAI estimates for future Chinese yam yield prediction.

The wide field of view (WFV) imaging system of the GaoFen-6 (GF-6) satellite processes four popular spectral bands [blue, green, red, and near-infrared (NIR)] and four new spectral bands (costal, yellow, and two red edges). However, the corresponding reference spectral bands for these eight spectral bands from one reference sensor are insufficient in the cross-calibration process of the WFV; therefore, current cross-calibration methods should be improved. To address this problem, the Moderate-Resolution Imaging Spectroradiometer (MODIS), which has high radiometric performance with the aid of an onboard calibration system, is used as a reference sensor, and cross-calibration methods using the top of atmosphere (TOA) and the bottom of atmosphere (BOA) bidirectional reflectance distribution function (BRDF) models are developed and compared. The results reveal that the cross-calibration results in eight spectral bands with the BOA BRDF model that can obtain higher consistency with the official calibration coefficients (OCCs) compared with the TOA BRDF model. In addition, after various influencing factors are comprehensively analyzed, the spectral band adjustment factor (SBAF) correction in the shortwave infrared (SWIR) spectral bands can be neglected; moreover, by using five spectral bands (blue, green, red, NIR, and SWIR) of the MODIS sensor, the BOA BRDF model and the cubic polynomial interpolation method provide optimal cross-calibration schemes for WFV sensor. The total radiometric cross-calibration uncertainties of the proposed cross-calibration methods with the BOA BRDF model and the TOA BRDF model are less than 5.73% and 6.32%, respectively.

In order to enhance the security of software, each system update needs to perform regression test. Regression testing in a continuous integration environment requires test cases to meet the needs of rapid feedback. Therefore, it is necessary to enable test cases to be effectively sorted within a certain time range so that more failure data could be discovered and the fault detection rate of testing could be improved. Reinforcement learning algorithms interact with the environment, so it is viable to optimize the sorting problem of test case in the process of continuous integration through a reward mechanism. In the development environment of continuous integration, it has been experimentally proven that the execution history of test cases in the last four cycles has a greater impact on the sorting of test cases in the current cycle. Therefore, a new RHE reward function was put forward by using part of weighted information obtained from historical execution result for enhancing the security of the system. Taking the influence of execution time into account, the multi-target sequencing technology for test case is employed with a view to improving the efficiency of defect discovery. It has been found by applying this sorting method to three industrial testing research that: (1) compared with weighted reward function based on the entire historical execution information, the function based on the four historical execution information had a higher capability of detecting faults; (2) The reward function obtained from the weighted historical results could effectively improve the fault detection rate and reduce the time consumed. (3) The multi-objective sorting methods taking execution time into consideration was able to maximize the number of testing cases that had already discovered faults within the available time.

A low power receiver with impedance transparent RF front end is presented. By using the 4‐path passive mixer and the active feedback of LNA, the baseband impedance profile is further transferred to receiver input. While a LO‐defined input matching is formed by RF front end, the linearity of entire receiver chain is improved. Furthermore, derivative superposition technique is employed to cancel the distortion of the CMOS LNA. A 3rd‐order active‐RC filter is designed with current‐efficient feedforward compensated OTA. And a digital‐to‐time converter (DTC) assisted fractional‐N all‐digital phase‐locked loop (ADPLL) is codesigned with receiver to meet the IoT requirements. The presented receiver is fabricated in 55 nm CMOS technology with an active area of 2.3 mm2 and power consumption of 20 mW. Measurement results show that the receiver achieves 5.3 dB NF with 78 dB gain from 0.6 to 1 GHz, the RX out‐of‐band IIP3 is +8 dBm, and in‐band IIP3 is −10 dBm, and the ADPLL achieves −94 dBc/Hz in‐band PN and −120.5 dBc/Hz at 1 MHz offset.

Cross calibration is critical to provide consistent measurements from multiple sensors. The intrinsic varieties between the Gao Fen (GF)-1 Wide Field of View (WFV) and Terra MODIS are caused by the relative spectral responses, sensor and solar zenith angle, azimuth angle. The sensor and solar observation conditions combined with the typical reflectance spectrum over Dunhuang test site were used to calculate the spectral band adjustment factors (SBAFs). A total of 32 image pairs between WFV and MODIS over Dunhuang site are available considering the cloud contamination. The SBAFs have the similar changing tendency in both 4 bands. According to the SBAFs, the gain of WFV can be calculated. TOA radiance products of MODIS and WFV are compared which shows that the accuracy of cross calibration coefficients is depending on the SBAF.

In this paper, a new pilot insertion method is proposed for single carrier frequency domain equalization system. The new method, which is based on Hadamard transform and interleaver can eliminate cross interference between pilot and data in severe multipath environment, thus suitable for mobile transmission with high frequency efficiency.