The present study assessed the spatiotemporal variation of summer monsoon precipitation and its potential drivers in Myanmar, utilizing monthly precipitation data from forty‐six (46) synoptic meteorological stations spanning 1981–2020. The nonparametric statistical Mann–Kendall (MK), Sequential Mann–Kendall (SQMK) test, Empirical Orthogonal Function (EOF), and Probability Distribution Function (PDF) were used to determine the spatiotemporal monsoon precipitation trends and variability over the study period. The results show that higher precipitation occurs during June, July and August (peak monsoon period), while low precipitation was detected in May (onset month), September and October (withdrawal monsoon period), respectively. Moreover, abrupt change in precipitation is observed after 1990 with a significant (95% confidence level) increasing trend from 2000 to 2020. Decadal precipitation experienced the highest fluctuation during 2011–2020, a positive shift and increased frequency in recent decades. The spatial trends for monthly and seasonal precipitation vary from station to station and region to region due to a fluctuated shift of climatic dynamics. During dry conditions, less cloud liquid water suppressed relative humidity and high air temperature were exhibited, thus implying less precipitation in the region. However, the wet years revealed strong moisture/water vapour into the inland regions from the ocean, increased relative humidity, and suppressed air temperature. In addition, no significant relationship was found between El‐Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and monsoon onset timing with precipitation variability over Myanmar. This study provides essential information on manageable climate adaptation, mitigation and weather forecasting strategies in Myanmar.
Information technology (IT) plays an increasingly important and prominent role in the health sector. Data security is more important than ever to the healthcare industry and in world in general. The number of data breaches compromising confidential healthcare data is on the rise. For data security, cloud computing is very useful for securing data. Due to data storage issue, there is a need to use the electronic communication, and a number of methods have been developed for data security technology. Health Insurance Portability and Accountability Act (HIPAA) is one of the methods that can help in healthcare research. On stored database of patient in hospital or clinic, we can develop a conservational and analytical method so as to keep the medical records of the patients in a well-preserved and adequate environment. The method includes the improvement of working possibilities by delivering all the details necessary for the patient. All the information must be identified clearly. The protection of the privacy of the patients and the security of their information are the most imperative obstacles to obtain their intakes when considering the adoption of useful health data in the electronic field of healthcare industries.
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