It was when Hyungsik Lee entered the prestigious University of Tokyo that he realized Japan's social stratification. Having grown up in one of dozens of municipal government-run houses for low-income households in Hyogo Prefecture, poverty used to be part of his daily scenery. On the way to his local elementary school were dwellings with homeless people where he saw a man who froze to death taken away by an ambulance. At school, about half of his classmates were from single-parent households with financial difficulties. Some dropped out of high school, while some were sent to juvenile detention centers for committing crimes, he said.
The percentage of the U.S. population living below the poverty level fell for the third consecutive year in 2016, according to new data from the U.S. Census Bureau. Fourteen percent of the total U.S. population lived below the poverty line in 2016, down from 14.7 percent in 2015 and 15.5 percent in 2014. Poverty thresholds for individuals and households differ based on family size, number of children and age. The poverty rate declined in 24 states in 2016 compared to 2015, and only increased in Vermont, according to the data. While states with the lowest poverty rates have less than 10 percent of the population below the poverty line, states on the high end of the spectrum have poverty rates close to 20 percent.
For decades, we have defined it with a number, which the World Bank currently puts at a personal income of less than 1.90 a day. But a single number fails to capture the complexity of poverty. Measuring more than just income is essential to understanding the needs of poor people and delivering optimal assistance.
With one or other battle, war or conflict raging in many parts of world, what this world needs is peace. And as Nobel prize winner and father of green revolution, Dr.Norman Borlaug famously said, "There cannot be any peace on hungry stomach". If people are well fed and hence happy, they are less likely to engage in conflicts. A group of researchers from Cornell University would use ML techniques to analyse food and market conditions, to predict poverty and malnutrition in poorest region of the planet. The method would use available satellite data to measure solar induced chlorophyll fluorescence (SIF).