WeChat Mini Program
Old Version Features

MEASUREMENTS OF ATMOSPHERIC PARAMETERS ALONG AN EXTENDED PATH. II. OPTICAL MEASUREMENTS OF TURBULENCE

Optika atmosfery i okeana(2023)

Cited 2|Views0
Abstract
Настоящая публикация является продолжением первой части статьи «Измерения параметров атмосферы на протяженной трассе. I. Акустические измерения уровня турбулентности и средней скорости ветра». Она посвящена результатам оптических измерений турбулентности атмосферы на протяженных атмосферных трассах и их сравнению с данными одновременных акустических измерений с помощью метеостанции АМК-03. Данные исследования были проведены для определения эффективных средних по трассе распространения оптического излучения значений параметров турбулентности и связанных с ними радиусов когерентности оптических волн, распространяющихся через атмосферу. This work is a continuation of the paper "Measurements of atmospheric parameters along an extended paths. I. Acoustic measurements of turbulence and average wind speed" and is devoted to the results of optical measurements of atmospheric turbulence along horizontal atmospheric paths. These measurements were carried out to determine the effective mean values of atmospheric turbulence parameters along an optical radiation propagation path and the associated coherence length of optical waves propagating through the atmosphere. The path optical measurements were supported by AMK-03 acoustic weather station measurements. That made it possible to compare the local acoustic and optical measurements of turbulence with different optical meters.
More
Translated text
求助PDF
上传PDF
Bibtex
收藏
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined