Potentially hazardous objects (PHOs) are currently defined based on parameters that measure the object's potential to make threatening and close approaches to the Earth. To be considered a PHO, objects generally have an Earth minimum orbit intersection distance (MOID) of 0.05 AU or less and an absolute magnitude (H) of 22.0 or brighter (a rough indicator of large size). Read more about Pipeline for Identifying Potentially Hazardous Asteroids
Market exposure is a key concept in quantitative finance. This is classically measured by estimating a beta coefficient in a linear equation where beta (exposure) expresses the returns of the market. Returns with low exposure to the market are desired, as they are not affected by downturns. This exposure modeling can be generalized to multiple factors and the exposures to factors are used to determine if a strategy or asset is protected enough from changes in certain risk factors, and to purchase hedges that cancel out this risk exposure.
TripAdvisor users write reviews and upload photos from their various restaurant visits. These photos can be categorized/analyzed to reveal information about the restaurant's menu, dishes, pricing, etc. The first step in this analysis is the classification of photos into simple, broad groups: food, drinks, menus, inside and outside photos of the establishment. Students' goal for this project was to build an image classifier using Convolutional Neural Networks and images aquired by the students themselves.
Nester is a platform where companies can find the best designs for a project, using Kaggle. Kaggle is a platform that hosts machine learning competitions where companies and researchers post data and pose challenges. Data scientists from all over the world compete to answer the questions and to produce the best results, in effect, crowdsourcing the most efficient technique or solution to the questions.
Read more about Nester for Design