KEYWORDS: Remote sensing, Process modeling, Data modeling, Data processing, Performance modeling, Matrices, Data conversion, Modeling, Design and modelling, Sensing systems
With the development of remote sensing products towards the direction of civilianization and popularization, work-flow customization plays an important role in the production of remote sensing products. The traditional customized work-flow model has large time cost, complex operation and high requirements for professional knowledge. The work-flow recommendation system can improve the construction efficiency of remote sensing work-flow to some extent and assist users to design high-quality remote sensing work-flow models. However, most of the existing remote sensing work-flow modeling methods ignore the logical structure characteristics of the work-flow, leading to large errors in the calculation results of similarity. Difficult to make work-flow recommendations effectively. Therefore, this paper proposes a customized recommendation algorithm for remote sensing work-flow based on logical structure. By focusing on logical structure, the reliability of similarity calculation between work-flow is improved, so as to find similar work-flow to help users recommend the next modeling node. Firstly, the work-flow model needs to be preprocessed: the user converts the constructed work-flow model into a process structure tree by using Petri net workflow, and uses the path table generation algorithm based on logical structure to convert the model information into data information and store it in the database for subsequent data processing; Then the flow data in the flow tree set was converted into a path table according to certain rules, and then the longest common subsequence similarity of each data in the path table was calculated to obtain the similarity calculation results based on the logical structure characteristics, the most similar work-flow in the work-flow library is found and the recommendation is made for the user. The method proposed in this paper is evaluated experimentally on the real data set, in terms of recall, precision and F1-score, which shows that the method proposed in this paper can effectively improve the recommendation efficiency and meet the actual needs of users.
KEYWORDS: 3D modeling, Data modeling, 3D displays, Cesium, 3D visualizations, Visualization, Floods, Distance measurement, Design and modelling, Interpolation
Flood control is one of the most important operations of Yellow River control. The dam bank danger in flood season every year has the characteristics of time-varying, multi-dimension and complex situation, which poses a certain threat to people's life and property safety. For timely, flood control engineering data quickly and implement management interface of information visualization, effectively reduce the labor intensity of artificial working risk, this paper puts forward a kind of based on three-dimensional library of Cesium Huang Heba shore the realization method of 3D visualization platform adopted the aerial drones to create dam shore entity 3D model, Combined with WebGIS technology and front-end technology, the system's 3D expression is realized. Through interface design and system function development, the system has three-dimensional model display, with the functions of dam bank cruise and measurement tools, the platform has strong sense of reality and good interaction effect, which realizes the three-dimensional visual display of the Madu control project in Zhengzhou, Henan Province.
KEYWORDS: Internet of things, Manufacturing, Design and modelling, Databases, Information operations, Data communications, Telecommunications, Safety, Manufacturing equipment, Instrument modeling
With the development of network technology and people's growing need for a better life, IoT technology has been integrated into more and more people's daily lives. At the same time, due to the different needs of individual users and the differences in the function of networking equipment spawned a variety of Internet of things products. Hence an IoT platform that is convenient, efficient and easy to expand is particularly important. This article designs and implements an integrated IoT platform for many types of persistent connected IoT devices on the market. The platform supports concurrent access of large-scale IoT devices with multiple sources and protocols, and supports remote management of devices through instructions. Monitor the health of the equipment in real time and alarm in real time in case of abnormalities.
KEYWORDS: Data modeling, Telecommunications, Sensors, Signal attenuation, Algorithm development, Signal processing, Floods, Design rules, Control systems, Cameras
Due to the terrain, the frequent floods of the Yellow River have posed a great threat to the cities along the Yellow River. At present, although the danger alarm system and video surveillance system are widely installed along the Yellow River Basin, there is a lack of linkage between the two, which wastes monitoring resources. In addition, the push rules of different types of alarm signals are relatively complex, and the coupling between rules and system implementation is high, which is not conducive to rule modification and expansion; moreover, there are many cities along the Yellow River, if each city customizes its own system, it will lead to more overhead. Therefore, this problem can be solved by improving the hierarchical scalability of the system. So, based on the Drools framework, this paper uses the rule engine to realize the unified processing of different rules and the linkage integration of sensors and cameras, and designs a recursive model to simplify the development process, so as to realize the accurate positioning of alarm information at all levels of provinces, cities and counties, and the hierarchical processing of various alarm information.
In order to resolve the problem of speckle interference phase map noise interference, a phase denoising method of digital speckle pattern interferometry based on empirical wavelet transform (EWT) and cross correlation is proposed. First, the EWT is used to decompose the speckle phase map, and a series of components is obtained. Then the noise-free components containing phase information are extracted based on the cross correlation. After that, combined with the particle swarm optimization algorithm and sine–cosine denoising method, an improved sine–cosine denoising method is proposed to process the noise components. Finally, the noiseless components are reconstructed to obtain the denoised speckle phase map. Simulation and experimental results show that the proposed method can effectively reduce the noise interference and obtain accurate phase information.
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