An alternative sign language to speed learning sign language

In order to learn sign language, it takes between three months and three years. In many languages, the words and syntax are arbitrary. What if we could invent a new form of signing that anyone could learn in just ten minutes? 

Before mobile phones adopted QWERTY keyboards, this was the typical setup on phones and mobile devices:

This can be used to form an easy method to encode letters. The letter A is the first letter of the 2nd key. It can be represented by the code 2-1.  M is is on the R is the third letter on the 7th key, it can be coded as 7-3 and so on. 

The code for the word TEA will then be encoded as 8-1 3-2 2-1. Easy. But how can one sign this with hands? 

To sign numbers, one can sign with one hand by simply showing two successive numbers to represent a letter. 1 to 5 is easy. 6 can be represented by 1 finger with an upward motion to mean 1+5. 8 Would be represented by 3 fingers with a slight upward motion to mean 3+5. A space to start a new word is represented a horizontal motion of the hand. 

Anyone can learn this easy alternative to sign words in less than 10 minutes. Shorthand motion can be further developed with time to increase speed for frequent letters. In this way, a novice can communicate with a sign-native. 

Vegetative patients can communicate with this language. Although they may not be able to use their hands, they may use their eyes to blink the letters to form words other than blinking "YES" and "NO". A researched published in 2010 found that it is also possible to communicate with patience by monitoring their brain activity through an MRI scanner. 

For further reference on the MRI communication, click this link to this article published on The Guardian.

Working with Freetext: Inspired by Verb-Noun Software Approach on Apollo Mission

 We all have seen failures captured in freetext. This is such a common problem that this information is only used to review the shift and then stored never to be used again - the most important feature that has the failure modes!

Back in the 60s, NASA had the reverse problem, they wanted an efficient way to present human commands into a computer to control the spacecraft. They settled on an elegant way of coding things using VERB-NOUN format. OPEN-VALVE, SWITCHON-LIGHT and so on. 

So in failure data, one would usually have a component and its status mentioned in one form or another. One way to encode the freetext into usable data is to use a similar approach. 

Using an online Part-of-Speech (POS) interpreter, one can code the words into three categories, Nouns, Verbs and Adjectives. Adjectives are added to include STATUS words such as loose, damaged and broken. These really come in handy when looking for typical bad actors.

With POS tagging out of the way, all the possible permutations of how the NOUNS can interact with VERBS and ADJECTIVES are created in a table using queries. A frequency count is then done for        each permutation to find how many times an exact match is found. 

The NOUNS are labeled AGENTS and the VERBS and ADJECTIVES are labeled ACTION/STATUS.

The visual above shows the failure modes for slings. 

One is also able to see which parts are being damaged, broken or come loose the most. These are items that can be reconsidered for redesign or can be added to the daily pitstop tightening checklists. 

Freetext is difficult to work with, the best approach is to create failure codes but it is not impossible to  still get valuable data from freetext, it just costs you a bit of time and creativity.