How to build an Alexa Skill to get information about your timetable 2018 Version

Imagine a student who just got up. He knows exactly that he has lectures today, but he does not remember which one or even when it begins. So, he asks his Alexa device: “Alexa, which classes do I have today?’” His Alexa device is able to look into his timetable and answers: “You have five lectures today. The first lecture is Digital Media Technology and starts at 8:15 am in room 011, the second lecture is Web Development and starts at 10:00 am in room 135, the third lecture is Design Patterns and starts at 11:45 am in room 017. You can see more lectures in your Alexa app.”

This scenario is what we had in mind when we started to develop an Alexa skill which should be able to tell you information about your timetable.
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Parsing all Open Source Elm Code

This project was originally inspired by a talk Felipe Hoffa gave at the Github Universe conference last year. He talked about how we can analyse the code hosted on Github at a large scale to learn interesting things. I’m always excited about learning new programming languages, at the moment my favourite new langue is Elm, a small functional programming language for building web applications. After watching the talk I thought it would be nice to do this kind of analysis on all the public Elm code hosted on Github.
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Tweets by Donnie - Building a serverless sentiment analysis application with the twitter streaming API, Lambda and Kinesis

tweets-by-donnie dashboard

 

Thinking of Trumps tweets it’s pretty obvious that they are controversial. Trying to gain insights of how controversial his tweets really are, we created tweets-by-donnie.

“It’s freezing and snowing in New York — we need global warming!”
Donald J. Trump

You decide if it’s meant as a joke or not.

But wouldn’t it be nice to know whether the public is seeing this as a joke or whether it’s getting upset by it? That’s where our idea originated from. By measuring the emotions presented in the responses we can see what the public is thinking of Trumps posts throughout the day.

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Building a Serverless Web Service For Music Fingerprinting

Building serverless architectures is hard. At least it was to me in my first attempt to design a loosely coupled system that should, in the long term, mean a good bye to my all-time aversion towards system maintenance.

Music information retrieval is also hard. It is when you attempt to start to grasp the underlying theoretical framework and submerge yourself into scientific papers which each yield a different approach for extracting some feature out of digital audio signals. It is a long way until MFCC starts to sound natural. I have been there.
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Safety Culture – Improve “the way we do things around here”

The safety culture of an organization is the key indication of its performance related to safety. It incorporates the visible rules, norms and practices as well as the implicit factors such as values, beliefs and assumptions. That is why the safety culture reflects “the way we do things around here” which is the most precise definition. Safety is a universal topic since we pursue it permanently and every action is safety related. To improve safety, we first need to understand the organization’s unique safety culture before we can derive tailored actions. This post covers the basic theoretical background of a safety culture and focuses and two central components: just and learning culture. The resulting principles can increase the resistance of an organization towards its operational hazards but only if they are adapted to the unique situation. There is no generally applicable step-by-step manual on how to implement a safety culture.

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Smart Meter

Smart meters have been a controversial topic for quite a while. Other countries began the roll out years ago. In Germany this takes way longer and there are still no certified products for the energy companies to install. The BSI (Bundesamt für Sicherheit in der Informationstechnologie) is responsible for certifying the smart meters. There are several smart meters up for certification as you can see on this side of the BSI.

The main reason for installing smart meters is the energy transformation to make the energy net more reliable for renewable energies. Therefore the EU has decided that every country should provide smart meters to their consumers. Thus the Bundesregierung passed the law for Digitalisierung der Energiewende in 2016. It requires 80% of all households to own a smart meter by 2020.
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Why AI is a Threat for our Digital Security

Artificial intelligence has a great potential to improve many areas of our lives in the future. But what happens when these AI technologies are used maliciously?

Sure, a big topic may be autonomous weapons or so called “killer robots”. But beside our physical security – what about our digital one? How the malicious use of artificial intelligence will threaten and is already threatening our digital security, will be discussed in this blog post.

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Cloud security tools and recommendations for DevOps in 2018

Introduction

Over the last five years, the use of cloud computing services has increased rapidly, in German companies. According to a statistic from Bitkom Research in  2018, the acceptance of cloud-computing services is growing.

Cloud-computing brings many advantages for a business. For example, expenses for the internal infrastructure and its administration can be saved. Resource scaling is easier, it can be done when the appropriate capital is available. In general the level of innovation within companies is also increasing, so this can support new technologies and business models. Cloud-computing can also increase data security and data protection, because the big providers must comply with standards and obtain certification through the EU-DSGVO General Data Protection Regulation, which came into force in May 2018. There is even special cloud providers that offer such services, so these are working based on the regulations of the TCDP (Trusted Cloud Data Protection) certification.
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