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spatiotemporal trend Analysis of Precipitation Extremes in Ho Chi Minh City, Vietnam During 1980–2017

International Journal of Disaster Risk Science 2021年第1期12卷 131-146页

作者： Nguyen Trong Quan Dao Nguyen Khoi Nguyen Xuan Hoan Nguyen Ky Phung Thanh Duc Dang Faculty of Environmental and Food Engineering Nguyen Tat Thanh UniversityHo Chi Minh City 700000Vietnam Faculty of Environment University of ScienceHo Chi Minh City 700000Vietnam Vietnam National University Ho Chi Minh City 700000Vietnam Ho Chi Minh City University of Food Industry Ho Chi Minh City 700000Vietnam Institute for Computational Science and Technology Ho Chi Minh City 700000Vietnam Engineering Systems and Design Pillar Singapore University of Technology and DesignTampines 487372Singapore

In this study,the spatiotemporal variability of trends in extreme precipitation events in Ho Chi Minh City during the period 1980–2017 was analyzed based on several core extreme precipitation indices(Rx1 day,Rx5 day,CDD,CWD,R20 mm,R25 mm,R95 p,and SDII).The nonparametric Mann–Kendall and Sen’s slope methods were used to compute the statistical strength,stability,and magnitude of trends in annual rainfall,as well as the extreme precipitation *** found that 64%of the stations had statistically significant upward trends in yearly rainfall,with high magnitudes frequently observed in the northern and southern regions of the *** the extreme precipitation indices,only SDII and R25 mm showed dominantly significant ***,there were increasing trends in the frequency and duration at the southern and central regions of the city during the study ***,El Ni?o-Southern Oscillation and Pacific Decadal Oscillation positively correlated with the duration and negatively correlated with the intensity and frequency of extreme ***,water management plans should be adjusted appropriately to reduce the severe impacts of precipitation extremes on communities and ecosystems.

关键词： spatiotemporal trend Extreme precipitation Extreme precipitation indices Ho Chi Minh City

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Identification and Visualization of Spatial and Temporal trends in Textile Industry

引用

Computers, Materials & Continua 2023年第2期74卷 4165-4181页

作者： Umair Yousaf Muhammad Asif Shahbaz Ahmed Noman Tahir Azeem Irshad Akber Abid Gardezi Muhammad Shafiq Jin-Ghoo Choi Habib Hamam Department of Computer Science National Textile UniversityFaisalabad38000Pakistan Department of Computer Science and Software Engineering International Islamic UniversityIslamabad44000Pakistan Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea Faculty of Engineering Uni de MonctonMonctonNB E1A3E9Canada International Institute of Technology and Management Commune d’AkandaBPLibreville1989Gabon School of Electrical Engineering Department of Electrical and Electronic Eng.ScienceUniversity of JohannesburgJohannesburg2006South Africa Spectrum of Knowledge Production&Skills Development Sfax3027Tunisia

The research volume increases at the study rate,causing massive text *** to these enormous text corpora,we are drowning in data and starving for ***,recent research employed different text mining approaches to extract information from this text *** proposed approaches extract meaningful and precise phrases that effectively describe the text’s *** extracted phrases are commonly termed ***,these key phrases are employed to determine the different fields of study ***,these key phrases can also be used to determine the spatiotemporal trends in the various research *** this research,the progress of a research field can be better revealed through spatiotemporal bibliographic trend ***,an effective spatiotemporal trend extraction mechanism is required to disclose textile research trends of particular regions during a specific *** study collected a diversified dataset of textile research from 2011–2019 and different countries to determine the research *** data was collected from various open access ***,this research determined the spatiotemporal trends using quality *** research also focused on finding the research collaboration of different countries in a particular research *** research collaborations of other countries’researchers show the impact on import and export of those *** visualization approach is also incorporated to understand the results better.

关键词： Text mining spatiotemporal trend research collaboration

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