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1.
Revitalising ASEAN Economies in a Post-COVID-19 World: Socioeconomic Issues in the New Normal ; : 119-143, 2022.
Article in English | Scopus | ID: covidwho-2193995

ABSTRACT

This chapter analyses the impacts of the coronavirus pandemic on the Malaysian tourism industry. The discussion starts with general development of global tourism, followed by the drastic changes in Malaysian tourism and the economic conditions before and during the pandemic. With support of updated statistics, this chapter further presents the disastrous strikes on domestic tourism value chain, hotel lines, and the aviation industry. The relevant policy responses and post-pandemic tourism recovery are also discussed for better understanding of the vulnerable ecosystem. This chapter concludes that the recovery is progressive along UNWTO's Scenario 1 (before or by 2023) but subjected to domestic policy efficacy and global responses, especially the availability and affordability of vaccines. This chapter recommends proactive short-term policy initiatives in preparing the sector and its value chain to be COVID secure, and then launching marketing campaigns. For long-term strategic planning, the government should look into initiating and building capacity of digitalisation in the sector. © 2022 by World Scientific Publishing Co. Pte. Ltd.

2.
2022 Research, Invention, and Innovation Congress: Innovative Electricals and Electronics, RI2C 2022 ; : 1-8, 2022.
Article in English | Scopus | ID: covidwho-2136469

ABSTRACT

Automated text summarizing helps the scientific and medical sectors by identifying and extracting relevant information from articles. Automatic text summarization is a way of compressing text documents so that users may find important and useful information in the original text in reduced time. We will first review some new works in the field of summarization that uses deep learning approaches, and then we will explain the application to COVID-19 related research papers. The ease with which a reader can grasp written text is referred to as the readability test. The substance of text determines its readability in natural language processing. We constructed word clouds using the s' most commonly used text. By looking at those three measurements, we can determine the performance measures of ROUGE-1, ROUGE-2, ROUGE-L, ROUGE-L-SUM. Our findings indicated that Distilbart-mnli-12-6 and GPT2-large outperform than others considered. © 2022 IEEE.

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