Notes on codes, projects and everything
We were asked to develop a program that demonstrate Artificial Intelligence and apply what we had learned in class into the program. Then we came out with an idea to develop a program that is able to do tarot reading. At first the program did not have a GUI and is operated through Swi-Prolog interpreter but in the end we included a GUI-frontend for the program using XPCE.
First the program will require 3 random numbers from the user, then a random number will be generated as the seed. Then the card will be “shuffled” (in fact, we did some calculations to the user provided random numbers) and then determine the orientation of the card (normal and reversed). Then, we use the computed number to pick a tarot card and get the reading based on the orientation.
To shuffle the cards, we use a random number and place the random number into the formula such that $$c=x^y\text{ mod }23$$ where c is the corresponding card number, x is the user provided number and y is the system generated random number. Then the orientation of the card is determine by calculating the mod 2 of the random number.
To implement simple search strategy, we used a hash function to divide the total of 22 major arcana cards into 5 groups. Each group will have one individual database file storing the card characteristics and reading. Then, depending on the calculated number, the system will choose to query which database file to decrease the inclusion of database files. We may not be able to observe the performance enhancement as we only have 5 database files but it should be more obvious for system with more database files.
I am the developer for the GUI front-end. At first we planned to write the GUI using other languages/platforms but because of the time constraint we decided to give up on GUI front-end. However, I managed to pick up basic XPCE GUI construction just in time and made a GUI for the program. However, the GUI is not very friendly and is not able to display images. Because XPCE is a multi-platform supported toolkit therefore the appearance of the GUI is consistent in various supported operating system.
The program is reading input through prolog interpreter.
The program displays the result after computing the input.
The program is reading input through GUI
The program displays the result through the GUI
After a miserable trip back to academic world, I finally re-gained the courage to get back to job-market. For the time spent in university, I spent quite some time reading about Semantic Web and RDF. Then I thought, I should have published more in this format in future. However, that didn’t really happen, mostly because I am too lazy.
I have recently made my Adium useless by moving all my IM accounts to my beloved Nokia N9. While moving my buddy lists of all major instant messaging services, I did a quick check on each of the contact to see past interaction. It is sort of surprising to see I don’t actually chat with them as frequent as I thought, so why do I “need” my Adium opened all the time?
A really sweet new feature in the recently released update is the ability to change lockscreen shortcut. Unfortunately there is no easy way to change connection with my Jolla unlike my old Nokia N9 (no pun intended). As I have not been using my N9 for quite some time, I was only reminded when I came across this thread on TMO.
I finally put in some time and effort learning myself a bit of Rust. Though I am still struggling with ownership and lifetimes (which is essentially everything about the language, to be honest), I find it more interesting compared to Golang, which is relatively boring, though being functional (no pun intended). While learning the language, the one thing I came across often is the Option enum, then I remembered that I read something about Monad.
Implementing a Information Retrieval system is a fun thing to do. However, doing it efficiently is not (at least to me). So my first few attempts didn’t really end well (mostly uses just Go/golang with some bash tricks here and there, with or without a database). Then I jumped back to Python, which I am more familiar with and was very surprised with all the options available. So I started with Pandas and Scikit-learn combo.