Grid quorum-based spatial coverage for IoT smart agriculture monitoring using enhanced multi-verse optimizer

2018 ◽  
Vol 32 (3) ◽  
pp. 607-624 ◽  
Author(s):  
Mohamed Abdel-Basset ◽  
Laila A. Shawky ◽  
Khalid Eldrandaly
10.1596/31064 ◽  
2018 ◽  
Author(s):  
Chase Anthony Sova ◽  
Godefroy Grosjean ◽  
Tobias Baedeker ◽  
Tam Ninh Nguyen ◽  
Martin Wallner ◽  
...  
Keyword(s):  

Wahana ◽  
2019 ◽  
Vol 22 (1) ◽  
pp. 15-27
Author(s):  
Suripto Suripto ◽  
Eva Dwi Lestari

Economic growth is one indicator to measure  the success of economic development in a country. Economic development is closely related to infrastructure. Infrastructure development will have an impact on economic growth both directly and indirectly. Therefore, the role of the government in determining infrastructure development policies is very important to increase economic growth in Indonesia. The purpose of this study is to determine the effect of infrastructure on economic growth in Indonesia including road infrastructure, electricity infrastructure, investment, water infrastructure, education infrastructure and health infrastructure in Indonesia in 2015-2017.The analytical tool used in this study is panel data regression with the approach of Fixed Effect Model. The spatial coverage of this study is all provinces in Indonesia, namely 34 provinces, with a series of data from 2015 to 2017 with a total of 102 observations. The data used is secondary data obtained from BPS Indonesia.The results of the study show that (1) the road infrastructure variables have a negative and not significant effect on GDRP. (2) electrical infrastructure variables have a negative and not significant effect on GDRP. (3) investment variables have a positive and significant effect on GDRP. (4) water infrastructure variables have a positive and not significant effect on GDRP. (5) educational infrastructure variables have a positive and not significant effect on GDRP. (6) health infrastructure variables have a positive and significant effect on GDRP. Keywords: development, infrastructure, investment, GDRP, panel data


Author(s):  
Barkha Rani ◽  
Mamta Kumari ◽  
Kumari Sobha . ◽  
Pinki Kumari ◽  
Jyoti Majhi ◽  
...  
Keyword(s):  
Big Data ◽  

2019 ◽  
Vol 15 (3) ◽  
pp. 59-64
Author(s):  
D. NONGMAITHEM ◽  
M. APON ◽  
A.P. SINGH ◽  
L. TZUDIR

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Jacob R. Schaperow ◽  
Dongyue Li ◽  
Steven A. Margulis ◽  
Dennis P. Lettenmaier

AbstractHydrologic models predict the spatial and temporal distribution of water and energy at the land surface. Currently, parameter availability limits global-scale hydrologic modelling to very coarse resolution, hindering researchers from resolving fine-scale variability. With the aim of addressing this problem, we present a set of globally consistent soil and vegetation parameters for the Variable Infiltration Capacity (VIC) model at 1/16° resolution (approximately 6 km at the equator), with spatial coverage from 60°S to 85°N. Soil parameters derived from interpolated soil profiles and vegetation parameters estimated from space-based MODIS measurements have been compiled into input files for both the Classic and Image drivers of the VIC model, version 5. Geographical subsetting codes are provided, as well. Our dataset provides all necessary land surface parameters to run the VIC model at regional to global scale. We evaluate VICGlobal’s ability to simulate the water balance in the Upper Colorado River basin and 12 smaller basins in the CONUS, and their ability to simulate the radiation budget at six SURFRAD stations in the CONUS.


2021 ◽  
Vol 7 (1) ◽  
pp. 1927561
Author(s):  
Innocent Kutyauripo ◽  
Nyaradzo Prisca Mavodza ◽  
Christopher Tafara Gadzirayi

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