Data Science and Databases

Since almost all smartphones today are equipped with location sensors, motion sensors, bluetooth, and wifi, today’s mobile apps can use context awareness to dramatically increase their capabilities and value. This article walks you through building a context aware app that employs complex event processing.

ESA’s Rosetta mission soft-landed its Philae probe on a comet, the first time in history that such an extraordinary feat has been achieved. Closely after that, Microsoft Open Sourced .NET.

The first event is a great step for mankind, and the latter is even greater for Microsoft!

There are thousands of different Android powered devices, with different screen sizes, chip architectures, hardware configurations, and software versions. Unfortunately, segmentation is the price to pay for openness, and there are thousands ways your app can fail on different devices.

Regardless of such huge segmentation, the majority of bugs are actually introduced because of logic errors. These bugs are easily prevented, as long as we get the basics right!

Here’s a quick rundown of the 10 most common mistakes Android developers make.

How do we understand and interpret the huge amounts of data coming out of simulations? How do we visualize potential gigabytes of datapoints in a large dataset? In this article I will give a quick introduction to VTK and its pipeline architecture, and go on to discuss a real-life visualization example.

React.js is a fantastic library. It is only one part of a front-end application stack, however. It doesn’t have much to offer when it comes to managing data and state. Facebook, the makers of React, have offered some guidance there in the form of Flux. I’ll introduce basic Flux control flow, discuss what’s missing for Stores, and how to use Backbone Models and Collections to fill the gap in a “Flux-compliant” way.

Data conversion, translation, and mapping is by no means rocket science, but it is by all means tedious. This article introduces MetaDapper, a .NET library that strives to simplify, streamline, and automate the data conversion process to the greatest extent possible.

Scientific computing is hard. But thanks to an ever-growing landscape of open source tools, really tough problems are becoming easier to solve. Toptal engineer Charles Cook provides an in-depth example, leveraging open source tools to solve a problem in computational fluid dynamics.