Challenge yourself with a simple game that counters your playing! How to play: Pop as many balloons as you can within a limited time to reach the threshold and unlock the next level! How it works: Click uses machine learning in order to learn how fast the user clicks the next balloon under different circumstances and positions balloons so that it takes longer to click. In other words, the algorithm constructs a model that estimates the time interval between clicks based on several factors (like the proximity of recent points) that are important for understanding the player’s reaction time. Afterwards, the game chooses the points, among others, that give the slowest clicking time estimate, so that the player earns less points during the time limit. The game gets harder as it collects enough data to build a better model and follows changes in your play style by excluding older game data. Libraries used =========== swix - https://ift.tt/A3LlhNb parse SDK - https://ift.tt/2ONghsU
Shiny Lal is a nurse who came to the U.S. from India at the peak of the COVID-19 epidemic. In a new country facing an unprecedented virus, she dedicated herself to the difficult, dangerous work of front-line caregiving to create a better life for her family. But it wasn’t long before her American dream turned into a nightmare. Her employer, MedPro Healthcare Staffing, is among the growing number of companies that force employees to sign “stay-or-pay” contracts. These agreements impose exorbitant fees – routinely in the tens of thousands of dollars – under the guise of recouping training and relocation expenses if a worker leaves their job too soon. In Shiny’s case, the penalty – up to $40,000 plus MedPro’s enforcement costs – was triggered if she spent fewer than three years working for the company. MedPro placed Shiny in a small-town hospital in Kentucky where she was underpaid and struggled with an abusive supervisor. Shiny begged MedPro for a reassignment, but nothing changed. A...
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