A new model of multi-range fractals is proposed to explain the experimental results observed on the fractal dimensions of the fracture surfaces in materials.The relationship of multi-range fractals with multi-scaling ...A new model of multi-range fractals is proposed to explain the experimental results observed on the fractal dimensions of the fracture surfaces in materials.The relationship of multi-range fractals with multi-scaling fractals has been also discussed.展开更多
Utilizing the spatiotemporal features contained in extensive trajectory data for identifying operation modes of agricultural machinery is an important basis task for subsequent agricultural machinery trajectory resear...Utilizing the spatiotemporal features contained in extensive trajectory data for identifying operation modes of agricultural machinery is an important basis task for subsequent agricultural machinery trajectory research.In the present study,to effectively identify agricultural machinery operation mode,a feature deformation network with multi-range feature enhancement was proposed.First,a multi-range feature enhancement module was developed to fully explore the feature distribution of agricultural machinery trajectory data.Second,to further enrich the representation of trajectories,a feature deformation module was proposed that can map trajectory points to high-dimensional space to form feature maps.Then,EfficientNet-B0 was used to extract features of different scales and depths from the feature map,select features highly relevant to the results,and finally accurately predict the mode of each trajectory point.To validate the effectiveness of the proposed method,experiments were conducted to compare the results with those of other methods on a dataset of real agricultural trajectories.On the corn and wheat harvester trajectory datasets,the model achieved accuracies of 96.88%and 96.68%,as well as F1 scores of 93.54%and 94.19%,exhibiting improvements of 8.35%and 9.08%in accuracy and 20.99%and 20.04%in F1 score compared with the current state-of-the-art method.展开更多
This paper designs a wireless sensor network based on CC2530.The sensor nodes consist of multi-ranged accelerometer and CC2530,covering all the ranges of the acceleration signals which can be measured.The designed sys...This paper designs a wireless sensor network based on CC2530.The sensor nodes consist of multi-ranged accelerometer and CC2530,covering all the ranges of the acceleration signals which can be measured.The designed system solves the problems such as cable installation trouble of testing system,vulnerability to interference and complexity of circuit.Test results show that the designed wireless sensor network can transmit the signals that multi-ranged micro-accelerometer emits without spoilage,thus the measurement of acceleration of the covering region is completed.展开更多
文摘A new model of multi-range fractals is proposed to explain the experimental results observed on the fractal dimensions of the fracture surfaces in materials.The relationship of multi-range fractals with multi-scaling fractals has been also discussed.
基金supported by the National Natural Science Foundation of China(Grant No.32301691)the National Key R&D Program of China and Shandong Province,China(Grant No.2021YFB3901300)the National Precision Agriculture Application Project(Grant/Contract number:JZNYYY001).
文摘Utilizing the spatiotemporal features contained in extensive trajectory data for identifying operation modes of agricultural machinery is an important basis task for subsequent agricultural machinery trajectory research.In the present study,to effectively identify agricultural machinery operation mode,a feature deformation network with multi-range feature enhancement was proposed.First,a multi-range feature enhancement module was developed to fully explore the feature distribution of agricultural machinery trajectory data.Second,to further enrich the representation of trajectories,a feature deformation module was proposed that can map trajectory points to high-dimensional space to form feature maps.Then,EfficientNet-B0 was used to extract features of different scales and depths from the feature map,select features highly relevant to the results,and finally accurately predict the mode of each trajectory point.To validate the effectiveness of the proposed method,experiments were conducted to compare the results with those of other methods on a dataset of real agricultural trajectories.On the corn and wheat harvester trajectory datasets,the model achieved accuracies of 96.88%and 96.68%,as well as F1 scores of 93.54%and 94.19%,exhibiting improvements of 8.35%and 9.08%in accuracy and 20.99%and 20.04%in F1 score compared with the current state-of-the-art method.
基金National Natural Science Foundation of China(No.51075374)
文摘This paper designs a wireless sensor network based on CC2530.The sensor nodes consist of multi-ranged accelerometer and CC2530,covering all the ranges of the acceleration signals which can be measured.The designed system solves the problems such as cable installation trouble of testing system,vulnerability to interference and complexity of circuit.Test results show that the designed wireless sensor network can transmit the signals that multi-ranged micro-accelerometer emits without spoilage,thus the measurement of acceleration of the covering region is completed.
