Cloud–edge cooperation for meteorological radar big data: a review of data quality control

Abstract

With the rapid development of information technology construction, increasing specialized data in the field of informatization have become a hot spot for research. Among them, meteorological data, as one of the foundations and core contents of meteorological informatization, is the key production factor of meteorology in the era of digital economy as well as the basis of meteorological services for people and decision-making services. However, the existing centralized cloud computing service model is unable to satisfy the performance demand of low latency, high reliability and high bandwidth for weather data quality control. In addition, strong convective weather is characterized by rapid development, small convective scale and short life cycle, making the complexity of real-time weather data quality control increased to provide timely strong convective weather monitoring services. In order to solve the above problems, this paper proposed the cloud–edge cooperation approach, whose core idea is to effectively combine the advantages of edge computing and cloud computing by taking full advantage of the computing resources distributed at the edge to provide service environment for users to satisfy the real-time demand. The powerful computing and storage resources of the cloud data center are utilized to provide users with massive computing services to fulfill the intensive computing demands.

Revisiting the Spaceborne Illuminators of Opportunity for Airborne Object Tracking

“…requirements of multistatic systems for real-time multiple-object tracking needs more consideration. 5,6…”

“…The task requires high processing power because it requires collecting data from different sensors and device classifiers leveraging machine learning techniques. 19 Envisioning an example where Starlink satellites are employed as passive illuminators with multiple receivers deployed geographically close to cover a small region, it will require powerful edge computing capabilities 6 connected over high-bandwidth lines separate to the ones provided by the Starlink system.…”

“…This is exacerbated by the need for real-time multiple object tracking, too. 5,6 T he rapidly increasing deployment of spaceborne transmitters, particularly in LEO, presents a realistic opportunity for cooperative PCL due to dense coverage across the globe. In addition, the benefits of radar detection via forward scattering for either small or RF-absorptive targets warrant renewed consideration, given this denser coverage.…”

Prediction Methods of Common Cancers in China Using PCA-ANN and DBN-ELM-BP

“…Accordingly, accurate prediction of cancer cases has become one of the most important tasks. Some relevant AI studies about imaging [9], [10], [11], [12], [13], [14], physiology, interview survey (combined with physiological data) and interview survey (only questionnaire) are shown in Table 1. Cancer-related research has become extensive and effective in recent years, with different research methods selected according to different data types.…”

Few‐Shot Segmentation via Capturing Interclass and Intraclass Cues Using Class Activation Map

“…Image segmentation [1] aims to segment object regions from images, which is fundamental to many computer vision tasks [2]. Based on the deep learning-based method [3][4][5][6][7], the existing segmentation models can segment object well when sufficient annotations are given [8]. However, the existing segmentation methods still have two drawbacks.…”