Nanjing University of Information Science and Technology

About: Nanjing University of Information Science and Technology is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Precipitation & Aerosol. The organization has 14129 authors who have published 17985 publications receiving 267578 citations. The organization is also known as: Nan Xin Da.

Analysis and prediction of rainfall trends over Bangladesh using Mann–Kendall, Spearman’s rho tests and ARIMA model

Abstract: In this study, 60-year monthly rainfall data of Bangladesh were analysed to detect trends. Modified Mann–Kendall, Spearman’s rho tests and Sen’s slope estimators were applied to find the long-term annual, dry season and monthly trends. Sequential Mann–Kendall analysis was applied to detect the potential trend turning points. Spatial variations of the trends were examined using inverse distance weighting (IDW) interpolation. AutoRegressive integrated moving average (ARIMA) model was used for the country mean rainfall and for other two stations data which depicted the highest and the lowest trend in the Mann–Kendall and Spearman’s rho tests. Results showed that there is no significant trend in annual rainfall pattern except increasing trends for Cox’s Bazar, Khulna, Satkhira and decreasing trend for Srimagal areas. For the dry season, only Bogra area represented significant decreasing trend. Long-term monthly trends demonstrated a mixed pattern; both negative and positive changes were found from February to September. Comilla area showed a significant decreasing trend for consecutive 3 months while Rangpur and Khulna stations confirmed the significant rising trends for three different months in month-wise trends analysis. Rangpur station data gave a maximum increasing trend in April whereas a maximum decreasing trend was found in August for Comilla station. ARIMA models predict +3.26, +8.6 and −2.30 mm rainfall per year for the country, Cox’s Bazar and Srimangal areas, respectively. However, all the test results and predictions revealed a good agreement among them in the study.

Total-factor carbon emission efficiency of China's provincial industrial sector and its dynamic evolution

Abstract: An improvement in industrial carbon emission efficiency is crucial for achieving both reductions in carbon emissions and sustainable economic growth. In this paper, we use an improved non-radial directional distance function (NDDF) to construct a new meta-frontier total-factor carbon emission efficiency index (TCEI) with which we estimate the meta-frontier TCEI of China's 30 provincial industrial sectors in 2005–2015 and analyze their dynamic evolution. The results show that compared to traditional NDDF, the improved NDDF has more advantages in measuring both carbon emission efficiency and the technology gap ratio. For the study period, China's industrial meta-frontier TCEI is low, indicating that the industrial TCEI of many provinces still has much room for improvement. The meta-frontier TCEI has significant inter-group heterogeneity, with Eastern China having the largest carbon emission efficiency, followed by Central China, and Western China having the lowest. China's industrial meta-frontier TCEI increased significantly during the study period with technical progress playing a major role in promoting it. Over time, however, the meta-frontier TCEI growth rate decreased significantly as the deterioration in technological efficiency and the expansion of the technology gap have jointly inhibited the growth of carbon emissions efficiency. Carbon emission performance in various regions over different periods exhibit differing characteristics, that is, the carbon emission performance has significant spatial heterogeneity and period heterogeneity.

Multiple criteria decision making based on Bonferroni means with hesitant fuzzy linguistic information

Abstract: In recent decades, different extensional forms of fuzzy sets have been developed. However, these multitudinous fuzzy sets are unable to deal with quantitative information better. Motivated by fuzzy linguistic approach and hesitant fuzzy sets, the hesitant fuzzy linguistic term set was introduced and it is a more reasonable set to deal with quantitative information. During the process of multiple criteria decision making, it is necessary to propose some aggregation operators to handle hesitant fuzzy linguistic information. In this paper, two aggregation operators for hesitant fuzzy linguistic term sets are introduced, which are the hesitant fuzzy linguistic Bonferroni mean operator and the weighted hesitant fuzzy linguistic Bonferroni mean operator. Correspondingly, several properties of these two aggregation operators are discussed. Finally, a practical case is shown in order to express the application of these two aggregation operators. This case mainly discusses how to choose the best hospital about conducting the whole society resource management research included in a wisdom medical health system.

Spatial dependence of diurnal temperature range trends on precipitation from 1950 to 2004

Abstract: This paper analyzes the spatial dependence of annual diurnal temperature range (DTR) trends from 1950- 2004 on the annual climatology of three variables: pre- cipitation, cloud cover, and leaf area index (LAI), by classifying the global land into various climatic regions based on the climatological annual precipitation. The regional average trends for annual minimum temperature (Tmin) and DTR exhibit significant spatial correlations with the climatological values of these three variables, while such correlation for annual maximum temperature (Tmax )i s very weak. In general, the magnitude of the downward trend of DTR and the warming trend of Tmin decreases with increasing precipitation amount, cloud cover, and LAI, i.e., with stronger DTR decreasing trends over drier regions. Such spatial dependence of Tmin and DTR trends on the climatological precipitation possibly reflects large-scale effects of increased global greenhouse gases and aerosols (and associated changes in cloudiness, soil moisture, and water vapor) during the later half of the twentieth century.