• Journal of the Korean Mathematical Society
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• v.44 no.4
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• pp.809-822
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• 2007

Certain weak type endpoint estimates are established for maximal commutators generated by $Calder\acute{o}n-Zygmund$ operators and $Osc_{exp}L^{\gamma}({\mu})$ functions for ${\gamma}{\ge}1$ under the condition that the underlying measure only satisfies some growth condition, where the kernels of $Calder\acute{o}n-Zygmund$ operators only satisfy the standard size condition and some $H\ddot{o}rmander$ type regularity condition, and $Osc_{exp}L^{\gamma}({\mu})$ are the spaces of Orlicz type satisfying that $Osc_{exp}L^{\gamma}({\mu})$ = RBMO(${\mu}$) if ${\gamma}$ = 1 and $Osc_{exp}L^{\gamma}({\mu}){\subset}RBMO({\mu})$ if ${\gamma}$ > 1.

• International Journal of Advanced Culture Technology
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• v.10 no.3
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• pp.272-280
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• 2022

During last few years, pandemic of COVID-19 has been a global issue. Under the COVID-19, global events have been restricted or canceled to secure public hygiene and safety. Since one of the largest global events is Olympic Games, we selected recent Olympic Games as our case of analysis. Tokyo Olympic Games (TOG) was held in 2021, but it encountered a millennium disaster, the pandemic of COVID-19. In such a special period, it is of great significance to explore the emotional tendency of global views before and TOG via artificial intelligence. This paper vastly collects the TOG comment data of mainstream websites in South Korea, China, and the United States by implementing crawler program for sentiment analysis (SA). And we use a variety of sentiment analysis models to compare the accuracy of the experimental results, to obtain more reliable SA results. In addition, in the prediction results, to reduce the distortion of opinion by a minority, we introduce an algorithm called "Removing Biased Minority Opinions (RBMO)" and provide how to apply this method to the interpretation domain. Through our method, more authoritative SA results were obtained, which in turn provided a basis for predicting the sentiment tendency of countries around the world in TOG during the COVID-19 epidemic.