NASADEM GLOBAL ELEVATION MODEL: METHODS AND PROGRESS

ACCElERAtINg PROgRESS IN glOBAl AtMOSPhERIC MODEl DEVElOPMENt thROUgh IMPROVED PARAMEtERIzAtIONS

G lobal models are used in many applications, ranging from Numerical Weather Prediction (NWP) to seasonal prediction and climate simulation. Despite great computational advances, calculations using these models can still only afford grid spacing for which many of the important processes occurring in the atmosphere—most notably boundary layer processes as well as moist convection and cloud proce...

Measuring Global Educational Progress

Global Optimization Ensemble Model for Classification Methods

Supervised learning is the process of data mining for deducing rules from training datasets. A broad array of supervised learning algorithms exists, every one of them with its own advantages and drawbacks. There are some basic issues that affect the accuracy of classifier while solving a supervised learning problem, like bias-variance tradeoff, dimensionality of input space, and noise in the in...

Model-Based Randomized Methods for Global Optimization

We survey some randomized search methods for global optimization that are based on sampling from an underlying probability distribution “model” on the solution space. In this approach, the probability model is updated iteratively after evaluating the performance of the samples at each iteration. Such model-based methods include estimation of distribution algorithms (EDAs), the cross-entropy met...

Progress in Global Surgery; Comment on “Global Surgery – Informing National Strategies for Scaling Up Surgery in Sub-Saharan Africa”

Impressive progress has been made in global surgery in the past 10 years, and now serious and evidence-based national strategies are being developed for scaling-up surgical services in sub-Saharan Africa. Key to achieving this goal requires developing a realistic country-based estimate of burden of surgical disease, developing an accurate estimate of existing need, deve...