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Smart Home voice assistants (also known as "smart home", "connected home") are still very much on vogue. But, regarding to Gartner's hype cycle  for emerging technologies, it's already on the falling edge of the curve and on the road to its plateau of productivity. Which means: the hype is almost over and the technology will get mature in approximately less than five years. Controlling devices at home with the voice is no future any more. It is presence. While Amazon's Alexa and Google Smart Home already recognize your wishes by voice commands in the cloud, there is a small place, where some offline voice assistants have emerged. These can process voice commands without a connection to the Internet, which is a major advantage for your private sphere - especially, if you consider that e.g. the German Home Office plans to listen to such devices to enlighten crimes. Fortunately, there is a way to protect your private sphere though you want to use smart

Some months have passed since the german IT news platform golem.de published an article reporting that password managers keep the passwords in memory unencrytped. Today I took the chance to make me my own picture of the problem. I used Keepass for my little Test. First, I created a new password database and protected it with a password. Step 1: Create a new encrypted password database Then I deleted the sample entries and created a new one with a certain password (password: "Hidden information 3214" ... whoops!). The result is, that the password is not shown in the Window. Step 2: Create an entry with a password Next, I copied the password over selecting the entry item in Keepass and pressing Ctrl+C and started a hex editor, HxD, to read out the process memory of Keepass (you could also read all processes memory). Step 3: Reading process memory of KeePass The last step was to search for a part of the password string (here: "Hidden in"). The resu

Let's take a look at an off-topic issue in this article: gaming. Why is it even worth to talk about gaming? First of all, gaming is the first decision driven activity a human can do. Second, gaming is a huge economic factor of today's digital business. Third, everybody loves to play. So, let's take a look at challenges to the developers of computer games. One big challenge to the game developers of modern computer games is to create opponents that are challenging the player - but never too far. Always matching a grade of difficulty that evokes a kind of thrill to the player without being hopeless to beat the computer player. But why is it a challenge? Well, it is something that affects the player directly - and a frustrated player will be a hard judge to the game developer or publisher. We could say: adequate opponents in games are a kind of game quality. Computers can always easily defeat up to 98% of human players For a computer, it is no problem to beat a hum

Some months ago, I started a new job as a machine learning engineer for a german trading company. In the course of this, I began to deal more with the programming language Scala. Scala provides some benefits that makes the work easier for data engineers when building data pipelines and there's a good support for spark, which is an advantage in cluster computing. But Scala (of course) also has its idiosyncrasies. This article shows the idiosyncrasy of Yate's correction in the Statistcs package of Scala and its consequences. The Statistics Package Like many other programming languages, Scala also comes with a statistical package called "Statistics". It includes many basic methods of the describing statistics, which you need for many purposes. One of these purposes is, for example, A/B testing. So, what's wrong with Scala? For an A/B test, I tested the significance by own calculations first (in old manner, as I had learned in my studies) before using th

For several months I have been an enthusiastic owner of a Sonos home sound system. In addition to a brilliant sound and the operation via smartphone and WLAN, this also offers the possibility to implement a control via the SOAP protocol to implement user-defined functions. This means, that it's possible to "hack" the Sonos devices. Free APIs Available Fortunately, some non-proprietary APIs are available on the net or on GitHub: For Java on any machine and OS (by VMichalak) For python on Raspberry Pi SoCo API for Python on Raspberry Pi It has to be said, that the Python APIs not neccessarily run on Windows (at least they didn't run on my machine), but this is not to expect when they are proclaimed as a Raspberry Pi project. Dependency Nightmare Though the API of VMichalak was the one that worked for me, it has a lot of dependecies which need to be downloaded or to be downloaded an build what requires Maven. OKHTTP (okhttp-3.11.0.jar) OKIO (okio-1

This is the R script used to create and train the neuronal net for the Python project . Please consider that the lines for the export of the neuron weights are disabled by the comment marker #. ################################## # # COMMON SAMPLE DATA HANDLING # ################################## load_samples = function (filename, attrib) { data = read.csv(filename, sep = "\t" ) # Remove result column data = data[, -5 ] # Calculate all combination with count of measure points n = aggregate(x ~ run + subset, data = data, FUN = length) # Keep only measurement with 80 points n = n[n[, 3 ] == 80 ,] # Create the training data matrix for non-matches dataset = matrix(ncol = 80 , nrow = 0 ) # Fill up the training data matrix with the valid cases (n) of data and transpose it for (i in 1 : dim(n)[ 1 ]) dataset = rbind(dataset, t(data $ x[(data $ run == n[i, 1 ]) & (data $ subset == n[i, 2 ])])) # add class column dataset = cbind(c(attr

This source code is part of the Python magnetic field sensor and detector project . This class only provides a simple flashing indicator light for the project. ######################################## # # Python Magnetic Field Logger and Detector # by Sebastian Folz # Introduced on Pi And More 11 # ######################################## # Don't use time module, because there is no valid time without WiFi import time import sqlite3 as lite from qmc5883 import QMC5883 import statistics # import functions for system calls from subprocess import call import sys # import pushbutton class from pushbutton import pushbutton, Push # import blink class from Blinker import Blink1, Blink2 from enum import Enum import RPi.GPIO as GPIO # fix copy bug with switched arguments from shutil import copyfile # Import own neural net class from MLP import MLNN TASTER = 38 LED = 40 LONG_CYCLES = 10 # 1.5 seconds COMMIT = 10 BINSIZE = 10 #