Essay Helper | Text-to-Breasonings (Helps Earn High Distinctions) | Grammar Logic (Helps Mind Map Details)
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Text-to-Breasonings (T2B) is a set of algorithms that allow breasoning out (in this case, the computer thinks of the x, y and z dimensions of) objects to help earn high distinctions, support but not conceive healthy children, earn jobs, sell products, produce quantum energy and gravity, project simulations, read objects, create quantum computers, prevent headaches and perform spiritual surgery, replicate or vaporise items such as spiritual food or supplements, read minds, display spiritual screens, time travel or become immortal. T2B automates breasoning, where breasoning prevents possible health problems of other methods (see Disclaimer). In addition to breasoning out 16,000 algorithms and 16,000 (word) breasonings, one can activate some of these technologies by understanding each step of 250 algorithms. This ability is possible with Spec to Algorithm.
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TextToBreasonings can (1) breason out words over a local machine and a Virtual Private Server (a server that you can use as central, which has environmental advantages) (VPS) host, (2) breason out characters over a local machine or (3) breason out words, breathsonings (judgement adjectives and adverbs), rooms, parts of rooms, directions in rooms, objects to prepare for action and objects to finish an action over a local machine.
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Generally, 80-word breasonings are needed to earn a high distinction at the undergraduate level and below, have healthy children or sell products. This increases to 2 * 15 * 80=2400 breasonings per Honours level chapter (i.e. 2, which is one to the lecturer and one from them to you), approximately 2 * 50 * 80=8000 breasonings per Masters level assignment and approximately 2 * 4 * 50 * 80=32,000 breasonings per PhD level assignment. NB: To earn H1, multiply the number of breasonings by 125 (if the rest of the breasonings are generated by Grammar Logic), except undergraduate, i.e. Honours=300,000 breasonings, Masters=1,000,000 breasonings and PhD=4,000,000 breasonings.
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Besides the 80 philosophy sentence breasonings, several short algorithms are necessary to earn a high distinction for an assignment. If there are a few algorithms, the lecturer may use them.
| Level | Algorithms required |
|---|---|
| Undergraduate | 80 |
| Honours | 80 |
| Master's | 80 |
| PhD | 80 |
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50 As (50 * 80=4000 breasonings) are required to earn a job.
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Replace 80 breasonings and 80 algorithms with 250 each for up to 100% above.
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To earn H1, also breason the lecture notes (and detail out in Honours and above).
Please read the following instructions on installing the project on your computer for breasoning.
- Please download and install SWI-Prolog for your machine at
https://www.swi-prolog.org/build/.
Download this repository, the List Prolog Interpreter Repository and the Algorithm Writer with Lists Repository.
- Download the LPPM Repository:
mkdir GitHub
cd GitHub/
git clone https://github.com/luciangreen/List-Prolog-Package-Manager.git
cd List-Prolog-Package-Manager
swipl
['lppm'].
lppm_install("luciangreen","Text-to-Breasonings").
../
halt.
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Before running texttobr, think of two radio buttons put on recordings, put through with prayer, nut and bolt, quantum box prayer 1, 1, 0.5 cm and 1, 1, 0.5 cm.
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Follow instructions in Instructions for Using texttobr(2) when using texttobr, texttobr2 or mind reader to avoid medical problems.
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The Prevent Headaches App may be necessary.
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See also Time Machine, which uses Text to Breasonings to travel through time with meditation.
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In Shell:
cd Text-to-Breasoningsswipl --stack-limit=54G -
(1) To breason out words over a local machine and a VPS host in the SWI-Prolog environment, enter:
['../listprologinterpreter/listprolog'].['text_to_breasonings.pl']. -
Please follow the instructions in "Setting up a VPS with TextToBr.txt" to set up a VPS with TextToBr up to and including "Upload them to the VPS's...".
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In the SWI-Prolog environment, enter:
texttobr2(N,File,String,M).where N is the number of times to breason out the file, File is the file name, String is the string to breason out, and M is the number of words in the file to breason out, e.g.: -
texttobr2(u,"file.txt",u,u).Breasons out file.txt. -
texttobr2(2,"file.txt",u,u).Breasons out file.txt twice. -
texttobr2(u,u,"Hello world.",u).Breason out, "Hello world.". -
texttobr2(3,u,"a b c",2).Breason out the first two words in "a b c" ("a" and "b") 3 times. -
To breason out words automatically without needing to enter their objects and dimensions, enter
texttobr2(u,"file.txt",u,u,[auto,on]).or with other settings. -
(2) To breason out characters over a local machine in the SWI-Prolog environment, enter:
texttobr(N,File,String,M).where N is the number of times to breason out the file, File is the file name, String is the string to breason out, and M is the number of characters in the file to breason out, e.g.: -
texttobr(u,"file.txt",u,u).Breasons out file.txt. -
texttobr(2,"file.txt",u,u).Breasons out file.txt twice. -
texttobr(u,u,"Hello world.",u).Breason out, "Hello world.". -
texttobr(3,u,"abc",2).Breasons out the first two characters in "abc" ("a" and "b") 3 times. -
(3) To breason out words, breathsonings (judgement adjectives and judgement adverbs), rooms, parts of rooms, directions in rooms, objects to prepare for an action and objects to finish an action over a local machine in the SWI-Prolog environment, enter:
['text_to_breasonings.pl']. -
In the SWI-Prolog environment, enter:
texttobr2(u,u,u,u,false,false,false,false,false,false).where the first four arguments may be changed as in (1) above, and only words are breasoned out. -
texttobr2(u,u,u,u,true,false,false,false,false,false).where the first four arguments may be changed as in (1) above, and only words and breathsonings are breasoned out. -
texttobr2(u,u,u,u,true,true,true,true,true,true).where the first four arguments may be changed as in (1) above, and words, breathsonings (judgement adjectives and judgement adverbs), rooms, parts of rooms, directions in rooms, objects to prepare for action and objects to finish an action are breasoned out.
- The algorithm often runs too quickly. To notice several words ("read them") in unread texts, where Master=6 algorithms, PhD=~16 algorithms and professor/politician=~50 algorithms, run with:
['../Text-to-Breasonings/text_to_breasonings.pl'].
W is 50*4,texttobr2(u,u,u,u,false,false,false,false,false,false,W).
% where W is the number of words to read
% 50 is the number of algorithms,
% and there are approximately four words per algorithm.
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Use a Virtual Private Server (VPS) Sync to breason out new meditators' names on your machine, sync with the VPS, and run meditation and text to breasonings on the VPS (by pasting rcaw.paste into the terminal.
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Install this repository using the instructions above.
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To install, in in username folder/texttobr2.sh replace the path
/username/codefolder/with the location of the installation of this repository and move the file to i.e. your/username/folder. -
To run, type
./texttobr2.shin the/username/folder and T2B will run (breasoning out only breasonings, not breathsonings, etc.), syncing with the VPS.
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If you accidentally enter a mistake in Text to Breasonings, you can repair the dictionary files using the following method.
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Find texttobrall2_reading.pl or your Text to Breasonings algorithm file.
- Daily Regimen (Read Me) has merged with Text to Breasonings.
We will use SemVer for versioning.
Lucian Green - Initial programmer - Lucian Academy
I licensed this project under the BSD3 License - see the LICENSE.md file for details
rcaw.paste added - this can be run each day to meet daily regimen requirements, such as preventing unwanted thoughts (mindreadtestsec.pl), giving meditators thoughts (mindreadingcaw.pl), giving thoughts about psychoanalysis (mindreadtestpsychiatrist.pl) and giving philosophical details(mindreadtestsecthoughts.pl).