Robotics & Machine Learning Daily News2024,Issue(Jun.7) :60-61.

Investigators at Federal University Alagoas Report Findings in Machine Learning (Using Social Media and Machine Learning To Understand Sentiments Towards Brazil ian National Parks)

阿拉戈斯联邦大学的调查人员报告了机器学习的发现(利用社交媒体和机器学习来了解对巴西国家公园的看法)

Robotics & Machine Learning Daily News2024,Issue(Jun.7) :60-61.

Investigators at Federal University Alagoas Report Findings in Machine Learning (Using Social Media and Machine Learning To Understand Sentiments Towards Brazil ian National Parks)

阿拉戈斯联邦大学的调查人员报告了机器学习的发现(利用社交媒体和机器学习来了解对巴西国家公园的看法)

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摘要

由一名新闻记者兼机器人与机器学习的新闻编辑每日新闻-调查人员发布了关于马学习的新报告。根据NewsRx Edi Tors在巴西马塞约的新闻报道,研究表明,“保护区(PAs)在保护自然和文化遗产方面发挥着至关重要的作用,同时支持当地的生计。然而,在巴西,资源有限和效率低下导致负面影响,并被用作对保护区的批评,有必要更好地了解公众对巴西考绩制度的看法,并确定导致负面情绪的关键因素。这项研究的资助者包括巴西生物多样性基金(FUNBIO)、人性化研究所、国家科学技术发展委员会(CNPQ)、欧洲联盟(EU)、国家科学技术发展委员会(CNPQ)、芬兰研究理事会、通力基金会。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning. According to news reporting out of Maceio, Brazil, by NewsRx edi tors, research stated, “Protected areas (PAs) play a vital role in the conservat ion of natural and cultural heritage while supporting local livelihoods. However , in Brazil, where limited resources and poor effectiveness lead to negative sen timents and are leveraged as criticism towards PAs, it is necessary to better co mprehend public perceptions of Brazilian PAs and identify the key factors contri buting to negative sentiments.” Funders for this research include Fundo Brasileiro para a Biodiversidade (FUNBIO ), Instituto Humanize, Conselho Nacional de Desenvolvimento Cientifico e Tecnolo gico (CNPQ), European Union (EU), Conselho Nacional de Desenvolvimento Cientific o e Tecnologico (CNPQ), Research Council of Finland, KONE Foundation.

Key words

Maceio/Brazil/South America/Cyborgs/Emerging Technologies/Machine Learning/National Parks/Federal University Alag oas

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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