Case study: design and implementation of Dongguan education cloud computing platform

2014 ◽  
Author(s):  
Tiantian Liu ◽  
Qiang Yue ◽  
Tongkai Ji
Keyword(s):  
Cloud Computing ◽  
Study Design ◽  
Case Study Design ◽  
Computing Platform ◽  
Design And Implementation ◽  
Cloud Computing Platform

scholarly journals Modeling of Groundwater Potential Using Cloud Computing Platform: A Case Study from Nineveh Plain, Northern Iraq

Water ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 3330
Author(s):  
Ali ZA. Al-Ozeer ◽  
Alaa M. Al-Abadi ◽  
Tariq Abed Hussain ◽  
Alan E. Fryar ◽  
Biswajeet Pradhan ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Drainage Density ◽  
Groundwater Potential ◽  
Specific Yield ◽  
Support Vector ◽  
Northern Iraq ◽  
Computing Platform ◽  
Cloud Computing Platform ◽  
Very High

Knowledge of the groundwater potential, especially in an arid region, can play a major role in planning the sustainable management of groundwater resources. In this study, nine machine learning (ML) algorithms—namely, Artificial Neural Network (ANN), Decision Jungle (DJ), Averaged Perceptron (AP), Bayes Point Machine (BPM), Decision Forest (DF), Locally-Deep Support Vector Machine (LD-SVM), Boosted Decision Tree (BDT), Logistic Regression (LG), and Support Vector Machine (SVM)—were run on the Microsoft Azure cloud computing platform to model the groundwater potential. We investigated the relationship between 512 operating boreholes with a specified specific capacity and 14 groundwater-influencing occurrence factors. The unconfined aquifer in the Nineveh plain, Mosul Governorate, northern Iraq, was used as a case study. The groundwater-influencing factors used included elevation, slope, curvature, topographic wetness index, stream power index, soil, land use/land cover (LULC), geology, drainage density, aquifer saturated thickness, aquifer hydraulic conductivity, aquifer specific yield, depth to groundwater, distance to faults, and fault density. Analysis of the contribution of these factors in groundwater potential using information gain ratio indicated that aquifer saturated thickness, rainfall, hydraulic conductivity, depth to groundwater, specific yield, and elevation were the most important factors (average merit > 0.1), followed by geology, fault density, drainage density, soil, LULC, and distance to faults (average merit < 0.1). The average merits for the remaining factors were zero, and thus, these factors were removed from the analysis. When the selected ML classifiers were used to estimate groundwater potential in the Azure cloud computing environment, the DJ and BDT models performed the best in terms of all statistical error measures used (accuracy, precision, recall, F-score, and area under the receiver operating characteristics curve), followed by DF and LD-SVM. The probability of groundwater potential from these algorithms was mapped and visualized into five groundwater potential zones: very low, low, moderate, high, and very high, which correspond to the northern (very low to low), southern (moderate), and middle (high to very high) portions of the study area. Using a cloud computing service provides an improved platform for quickly and cheaply running and testing different algorithms for predicting groundwater potential.

Design and Implementation of Facial Sketch System Based on Cloud Computing Platform and Big Data

2014 ◽  
Vol 651-653 ◽  
pp. 2028-2031
Author(s):  
Yan Jun An ◽  
Yue Hou
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Success Rate ◽  
Computer Technology ◽  
Criminal Investigation ◽  
Computing Platform ◽  
Design And Implementation ◽  
Drawing System ◽  
Cloud Computing Platform ◽  
Search And Recognition

At present, the facial recognition is largely using in the criminal investigation for the identification of suspects, the information from the informants, however, is very hard to obtain the main feature and to draw it accurately because of the affection of mood, light, visual differences and so on. However, with some computer technology, combining the resource from big data and cloud computing platform, the success rate of the search and recognition could be greatly improved. Therefore this article will bring out a facial drawing system based on big data and cloud computing platform.

scholarly journals Cloud Computing as Evolution of Distributed Computing � A Case Study for SlapOS Distributed Cloud Computing Platform

2013 ◽  
Vol 17 (4/2013) ◽  
pp. 109-122 ◽  
Author(s):  
George SUCIU ◽  
Simona HALUNGA ◽  
Anca APOSTU ◽  
Alexandru VULPE ◽  
Gyorgy TODORAN
Keyword(s):  
Cloud Computing ◽  
Distributed Computing ◽  
Computing Platform ◽  
Cloud Computing Platform ◽  
Distributed Cloud
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