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Frontiers | Evidence of the Middle-Income Trap in Latin American Countries: Factor Analysis Approach Using Regression and the ARDL Model

The middle-income trap (MIT) is often accompanied by the decline or stagnation of economic growth, unreasonable domestic industrial structure, and serious polarization be-tween the rich and the poor. However, due to different international environments, different specific national conditions, and different development policies adopted by each country, the manner in which to get out of the MIT varies. Transforming the mode of economic growth and realizing sustainable economic development is an important means for a country or region to escape from the "trap" of economic stagnation. This study carries out an analysis of different economic growth factors of Latin America countries (we selected 19 MIT countries out of 33) and compared them with Singapore and Korea, which are in a high-income range. We used a regression model to find the relationship of variables in each country and the impact on the economic growth due to these variables. The study finds using correlation and reg ....

United States , United Kingdom , South Korea , Japan General , The Tiger , Stann Creek , Republic Of , City Of , Costa Rica , Dominican Republic , Ch Ungch Ong Bukto , Baden Wüberg , Yavuz Tiftik , Atlantic Ocean , Simon Schuster , Pacific Ocean , Pcses Khan , Biomass Energy Barriers , Mean Group Estimation Of Dynamic Heterogeneous Panels , Foreign Bank Entry , Agenda For Further Research , Technological Development , Energy Econ , Financial Development , Energy Consumption , Industrial Development In Latin America ,

Frontiers | Mapping of Pollution Distribution for Electric Power System Based on Satellite Remote Sensing

In recent years, the frequent fouling accidents has posed a serious threat to people's life and property safety. Due to the wide distribution of pollution sources and variable meteorological factors, it is a very time-consuming and labour-intensive task to map the pollution distribution by traditional methods. In this work, a study on the mapping of pollution distribution based on satellite remote sensing is carried out in Yunnan Province, China, as an example. Several machine learning methods (e.g. KNN, SVM, etc.) are used to analyze the effects of conditions such as multiple air pollution data and meteorological data on pollution distribution map levels. The results indicate that the ensemble learning model has the highest accuracy of 71.2\% in this application. The new pollution distribution map using this classifier has 5,506 more pixels in the most severe pollution level than the traditional. Lastly, The remote sensing-based map and the manual measurement-based map were combin ....

South Korea , Gong Da , Mixture Density Networks , Anthropogenic Co , International Conference On Computer Distributed , Development Program Grant No , Yunnan Electric Power Company , Design Of Inversion Procedure For The Airborne , Company Power Grid , Yunnan Power Grid Company Ltd , Time Neural Networks , China Power , National Key Research , A Global Monthly Fossil Fuel Co , Observation Network , Temporally Weighted Neural Networks For Satellite , Yunnan Province , Drawing Method , Pollution Distribution , China High Air Pollutants , Multi Resolution Emission Inventory , Development Program , National Natural Science Foundation , Technology Project , Yunnan Power Grid Company , Google Earth Engine ,