End of the term

Hi, since the term is closing to an end, I thought I should give my general overview and how I feel about this course.

I believe this course was very beneficial to me as it provided a lot of fundamental insights on how computers and programs work and the history behind them. My initial intention of choosing this course was to familiarize myself with some of the basic intuition that is needed in order to program. Being in 3^rd year of Astrophysics specialist, I realized how important programming is and that programming is inevitable in modern science. In experimental physics, almost every apparatus is run by a program and every data analysis is collected by using a program. This is the case because doing anything manually always introduces new errors and it is not very efficient when there are a lot of repetitive procedures.

At first, I really did not like programming as it was something that I was not use to and I would always make small mistakes and not know why I kept on getting errors. It was especially frustrating when you know what to do in your head but you can’t seem to be able to code it with correct syntax to make the program work. But after taking this course, I think I can safely say that my confidence in programming has gone up. I also enjoy programming these days as the feeling one gets when they finally get the program to work is incredibly amazing.

The power of programming really shines when you need to do something that’s repetitive and you find yourself doing it manually. It’s times like those where you would rather have a program to do what you’re doing in a second. Another beauty is that once you have a program do something very simple like combining all the colours of pictures, or cropping a picture to a background, it is re-usable whenever you need it again.

Overall, I really enjoyed this course as it was very a fun learning new functions from Dr.Racket and all the history behind the creation of computers and algorithms. I really hope this course remains available for many more years as I think it is one of the most useful and interesting introductory courses one can take in University of Toronto. 

What to study/Going into the exam

Since the end date for SLOG is before the exam date, I thought I should provide my current plan for how I am going to study for the exam.

I think it is much simpler to study for this exam if we were to break it up into 5 parts:

     1) General basic knowledge

·         This will be done by mainly relying on the lecture notes and studying the slides

·         You also can’t underestimate the additional notes that were posted on the website

·         I also found from previous tests that some basic searches online helps a lot to understand the topics better

·         Don’t worry too much on small details/facts because most questions on the past tests have been conceptual and based on a idea (all word questions for basic knowledge part

·         If the exam is anything like test 2, then this section is very critical as half of the marks from test 2 was based on general knowledge on lecture notes and additional notes that were posted on the website

     2) Calculations

·         Although this is 100 level course and there aren't many calculations that has to be done, there are still some calculations within the course such as the binary to decimal and vise-versa

·         Since you know if the exam is anything like the past tests, it will have the general knowledge questions (usually word questions) then couple of calculation question that may have to do with Dr.Racket codes or just basic calculations we learned from the course such as Boolean outputs

      3) Coding (Dr.Racket)

·         This section is probably what is viewed as most difficult component of the test, however I think this is perhaps the easiest

·         First of all, we had a lot of time to deal with all the functions that would be mentioned on the test since we had tutorial and quiz every week that we had to prepare for

·         Secondly, professor told us that if we do not know a specific function and how it works, we can ask for that. Thus, we shouldn’t have any problem with a specific definition that we are not familiar with. Which implies that the only thing we have to worry about is the concept behind these functions and its capabilities

·         Lastly, in order to get more familiar with Dr.Racket, I am planning to re-do all the recommended questions and mainly focus ones that has answers as well so I can always double check if I did the coding correctly, rather than expecting that I did

Make sure to look over past exams and our previous quizzes which will give us a huge hint on how the exam will be formatted.

Good luck studying everyone!

Tutorial exercise #9

Hi, I noticed that I did not write much about this week’s tutorial exercise (#9). So although it has already past, I thought I should give my impression of this week’s tutorial and also the quiz.

Starting off with koch.rkt, there are two primary functions within this program. Firstly, the koch itself which uses the input given (which is a number) and displays an output of a line or multiple lines. It will just output a normal horizontal line, but as you increase your number value as input, it will rotate 60 degrees then rotate -60 degrees from the last position to make a triangular shape (with no bottom) like ‘^’.  It will continually add as you increase the number. Thus in the next function, the koch-snowflake, it takes these individual koch’s and puts them together. Which will ultimately create and snowflake shape if the value for input is high enough. Next program is spiral.rkt. This program seems to have the same intuitive concept as koch.rkt where the user inputs a number and depending on that value, it will display an output of spiral lines. Overall, the two programs were not very complicated once one is able to wrap their head around it. The quiz consisted of 5 questions which were all related to the functions mentioned above, I am not sure if I got them all right but the questions were very fair considering that the questions were directly from the program we studied during the tutorial.

I hope everyone did well on the quizzes and project #2!

Project 2

Project # 2 was just due an hour ago, so I thought I should share my perspective view on this project.

I was initially worried on how hard it might be and since the amount of time I had for this project was much less than the last one due to the fact that there were numerous other assignments to hand in as the term is coming to an end. Thus, I didn't really have any time to look at it until this week but I am happy that I manage to finish it within the due date.

Overall, I thought this project was much easier than the last and it contained less problems to do and it was fairly simple to do. I found that the hardest question was regarding the definition that includes local and map-images. Since there were no check-expects required for the definition of map-images, it was hard to figure out what it was actually suppose to do and thus I had trouble using it within another definition. I also noticed that it was easier to perform the check-expects for interpolate-image was easier to perform when you assign a simple shape (like a blue square) since it grabs two pictures of same size and compares the colour between them.

I will try to post some more blogs before end of this week, so look out for some more blogs!

Wikipedia Project III

Hi, I just wanted to provide an update on my Wikipedia project and give a brief run down of what I did.

I decided to take on the task of adding links to other sites in order to de-orphan an article. My article is on 55th Guksu (http://en.wikipedia.org/wiki/55th_Guksu), which is one of the tournament for Go. Go is an ancient board game that originated from China. It is very difficult game to master and thus there are huge skill gap between amateurs and professional Go players. Therefore, tournaments such as Guksu (one of Korean Go tournament) are very popular in Asia.

At first, I started by checking if '55th Guksu' had any hyper-linked "related topics", which would simplify things and make my task much easier at finding related articles that I can link my article to. However, I was unable to find any hyper-linked "related topics", thus I decided to search a bit about Guksu and the game Go in general to get a better understanding of this tournament.

The first article I visited was 'Go', but I was unsuccessful in finding an appropriate place to add my link for 55th Guksu. Thus, I changed my plan and decided to search for Guksu. Luckily, in the article for Guksu, there were history of title holders. Thus, I decided to link the 2011 Guksu, which is the 55th Guksu. I also decided to search the name of the 55th Guksu champion and linked 55th Guksu under his history as well. Finally, I managed to find the runner-up for 55th Guksu and decided to to link the 55th Guksu under his achievements since being a runner-up on a big tournament like Guksu is a very huge accomplishment as a professional Go player.

Once I finished with linking my article, I finally got rid of the orphan template as it no longer satisfies the condition to be in orphan template.

Trees/leaves, Harvest, Flatten, Depth, Apply and map functions

After the Tutorial earlier this week, I was able to figure out what each functions within the nested.rkt. So
I will briefly explain the functions covered in nested.rkt and if there are any questions, feel free to leave and comment on this post and I will get back to them as soon as possible.

Trees and leaves
They first define a tree and leaves:

Tree = A structure that has values left and right from the root. We can treat this like an organizational tree that we often see when trying to organize small to big things.

i.e. (define tree1 (make-gtree "AAA" leaf1 leaf2)) will give:

Tree1

leaf1 leaf2

Leaf = Definition for input that has empty left and right terms

i.e. (define leaf1 (make-gtree "ACTG" empty empty))

ACTG

Empty Empty

Harvest

Harvest function will grab all of the 'trees' and 'leaves' together and creates a list from it.

i.e. Given that 

(define tree1 (make-gtree "AAA" leaf1 leaf2))

(define leaf1 (make-gtree "ACTG" empty empty))

(define leaf2 (make-gtree "GTCA" empty empty))

Thus if one provides input of 'harvest tree1', one should have an output of (list "AAA" "ACTG" "GTCA")

If one were to plot it into a diagram, it would look something like this:

AAA

ACTG GTCA

  Empty Empty Empty Empty

Flatten

Next function that's mentioned is flatten. Which grabs all the list that is within a big list, and combines all of them to create a one big list that contains all the variables within the lists.

Flatten is defined as:

(define (flatten L)
  (cond
    [(not (list? L)) (list L)]
    [else (apply append (map flatten L))]))

So, if we have a list as :

(define L1 (list 1 2 3 (list 4 5 6) 7 8 (list 9 1 (list 2 3))))

and we apply flatten function to it, one would get :

(list 1 2 3 4 5 6 7 8 9 1 2 3))

Depth

And finally, depth function will find how many lists are found within a given input.

Depth is defined as:

(define (depth L)
  (cond
    [(not (list? L)) 0]
    [else (add1 (apply max (map depth L)))]))

So if we have a list as:

(list 1 (list 2) 3))

and we apply depth function to it, one would get an output of:

2

This is because there are two lists within the given function.

Map vs Apply

Although it is not directly mentioned within the nested.rkt, there are 2 other important functions that must be discussed about. They are the map and apply function.

Map will apply the given operation to a given list and provide an output of a list that contains all the variables that the operation was applied to. 

For example,

(map add1 (list 1 2 3 4)) would give an output of (list 2 3 4 5) because all the variables within the list were added by 1.

Apply on the other hand is a little different. First of all, it provides a numerical output and not a list even thought the input was a list to begin with. The apply function will use the given operation and treat like all the variables within a given list as part of same equation to apply the operation with.

For example,

(apply + (list 1 2 3 4)) would give an output of (10) since 1+2+3+4=10.

Plans to study for this week's quiz

So earlier today (as in yesterday since its after midnight), I have roughly went over the tutorial exercise sheet, and I am planning to over it in detail tomorrow (Tuesday).  So far, my impression of this week's tutorial exercise (#8) is fairly simple. It seems like the first point about list function is sort of a review as we already learned about this function long time ago. Then when i tried opening the November 14th racket code, I immediately noticed the three new functions as stated on the exercise handout. The functions depth, harvest, and flatten all seems like functions that deals with lists, and thus the input must be a list. I will have to investigate further on how these functions actually change or modify the list to see its effects. Hopefully by tomorrow night, I can have some sort of basic intuition of these three functions before going to the tutorial on Wednesday.

2nd Test Prep

Hello, I hope everyone did well on the test. I am sure some people found it difficult and others probably found it the easiest thing they have ever written. I found there were a lot more word questions than the last one and noticed it was weighted half of the test. Anyway, I know this is a bit late in case some people needed study notes, but I decided to post my study notes so others can compare with theirs and hopefully there are some things to add to their list before going into the final exam (which is actually a month away!)

**Notice when I wrote the Lecture numbers, I meant the lectures starting from the last test date. (Starting with Algorithm)

Lecture 1

Algorithms

·         Al-Khwarizmi – A Persian mathematician, astronomer, and geographer. He is considered one of the inventor of algebra, as his solution of linear and quadratic equations done in Arabic was discovered in twelfth century.

·         Greatest Common Divisor (GCD) = the largest whole number that divides two non-negative whole numbers

·         So GCD(12, 20) = 4

·         Euclid’s algorithm = GCD(48,18) => Divide 48 by 18 to get 2 with remainder of 12 => 18 divide by 12 to get 1 with remainder of 6 => 12 divided by 6 to get 2 with remainder of 0

·         So, GCD (a, b) = GCD (b, remainder of a/b)

Lecture 2

·         If there are two or more algorithms solving the same problem, then you have to choose the one that is more efficient

·         There obviously isn’t an algorithm that solves every problem

·         Halting problem = problem of deciding whether when given a program and an input, that the program will run forever or eventually halt

·         Alan Turing proved in 1936 that there cannot exist a general algorithm to solve the halting problem for all possible program-input pairs

How to solve a new problem

·         Understand the problem – what’s required, what’s given, solver-name: input -> output, draw pictures

·         Devise Plan(s) – different types of searches

·         Try the plan

·         Look back and analyze what went wrong if the plan doesn’t work

Lecture 3

Von Neumann Architecture

·         Memory-mapped I/O = allows input and output devices to be treated the same as memory

·         System bus = a single computer bus (a subsystem that transfer data between components inside a computer/between computers) that connects the major components of a computer system. This will reduce costs and improve modularity.

·         => It becomes the following components

·         1: Data bus = to carry information

·         2: Address bus = determine where it should be sent

·         3: Control bus = determine its operation

Von Neumann Bottleneck

·         Shared bus between the program memory and data memory leads to bottleneck

·         The limited throughput (data transfer rate) between the CPU and memory compared to the amount of memory

·         Because the program memory and data memory cannot be accessed at the same time, the throughput is much smaller than the rate at which the CPU can work, which would affect the processing speed when the CPU is required to perform minimal processing on large amounts of data

·         Thus the CPU is continuously forced to wait for needed data to be transferred to or from memory

Moore’s Law

·         Observation that over the history of computing hardware, the number of transistors on integrated circuits doubles approximately every two years.

Input, Output

Storage (Data storage device)

·         A device for recording (storing) information (data).

Hard drive

·         Capacity is specified in unit prefixes corresponding to power of 1000 (So 1-terabye (TB) = 1000 gigabyte (GB)) and not all of it is available to the user due to use by the file system

·         Performance is specified by the time to move the heads to a file plus the time it takes for the file to move under its head and the speed at which the file is transmitted

Compact Disc (CD)

·         Used to store digital data

·         CD data is represented as tiny indentations known as ‘pits’, encoded in a spiral track moulded into the top of the polycarbonate layer

·         CD is read by focusing a laser through the bottom of the polycarbonate layer. The change in height between pits and lands results in a difference n the way light is reflected. By measuring the intensity change with a photodiode, the data can be read from the disc.

Flash Drive

·         A flash drive does not contain any moving parts (except for electrons) , they are very robust mechanically

·         Information stored in electron chamber

·         Compare to hard drives, flash drives use little power, have no fragile moving parts, and very light and small

·         Resistant to mechanical shock, magnetic fields, scratches, and dust.

·         However, it can only sustain limited number of rewrites before the drive fails.

·         Flash memory places RAM

Lecture 4

·         Sharing big computers with smaller computers

·         There were a lot of computers that were dedicated to one job, however as time passed, the new revolution has come where you can stop one task and start another.

An operating system should have:

1)      Kernel = main component of operating systems, and acts as a bridge between application and the actual data processing done at the hardware level. It’s responsibilities include managing the system’s resources

2)       Utilities = repair and maintain machine

ROT13

·         The 26 alphabet is split into first 13 and last 13. Then in order, the first alphabet corresponds to the first in the second batch.

·         ABCDEFGHIJKLM

·         NOPQRSTUVWXYZ

Lecture 5

Network Topology

Topological structure of a network, and may be depicted physically or logically. The shape of the cabling layout used to link devices is called physical topology and logical topology shows how data flows within a network.

Bus

·         In local area networks, bus topology is used, where each node is connected to a single cable

·         Each computer/server is connected to the single bus cable

·         A signal from the source travels in both directions until it finds the intended recipient, and then the data is accepted.

·         All machines can transmit signal at any given time

·         If another machine is transmitting at the same time, then it waits for a random interval of time before re-transmitting them.

·         Since it consists of only one wire, it is inexpensive to implement but expansive to manage the network

Star

·         Each network host is connected to a central hub, in order to be classified as a star network, all the nodes on the network must be connected to one central device.

·         It is considered easiest topology to design and implement.

·         However, it also means that the hub represents a single point of failure

Ring

·         A network topology that is set up in a circular fashion

·         Signal travels around the ring in one direction and each device grabs the incoming signal and transmits them to next device.

·         The signal travels until the recipient gets the message which will then keep propagating in the ring until the original sender receives it and conclude that the message has been sent

·         The network is dependent on the ability of the signal to travel around the ring

Very delayed first post

Very delayed first post of my blog

Hello, and welcome to Tony’s blog! To be honest, I been so busy and worked up with other quizzes and tests in CSC 104 that I completely forgot about SLOGs. However, instead of crying and whining about it, I will try my best to interest everyone in what I learned in this course.

                To introduce a little bit about this course, this course’s title is “The why and how of computing” and it introduces fundamental ideas behind computers and why one should be introduced with basic computing. At a time like this, I believe many finds themselves having to use a computer to do a certain type of work. Whether that is to play games, finish essays, using it at workplace, etc, almost everyone at this generation should have experienced using a computer before. Thus, I firmly believe, for any program, at least one computer science course must be required. This is also one of many reasons why I decided to take this course.

                Since I am late on making my first post, in an attempt to retract some of the guilt, I will try to summarize what we have learned so far and some big notions that were introduced.

History of computing technology

·         Data were often stored in punched cards that were often not programmable, or not electronic.

·         Technically, because human labour was much cheaper (a lot electricity were required and was more expansive) the first computers were ran by women as they worked more efficiently

·         Eventually, the computers became accessible to everyone although it still looks differently from what we are use to

Important Notion: Boolean Logic

OR Gate

A	B	A or B
True	True	True
True	False	True
False	True	True
False	False	False

The way I think about OR Gates are by saying that if either A or B are ‘True’, it is automatically ‘True’.  Thus, the moment you see one ‘True’, the outcome is ‘True’. This is very useful in programming as one when wants to let the program to take action when either outcome of A or outcome of B is fulfilled. This ideology is often used not only in programming but also in many other fields like math, physics, chemistry, etc.

AND GATE

A	B	A and B
True	True	True
True	False	False
False	True	False
False	False	False

AND Gates are in a way opposite of OR Gates. This is because both A and B must be ‘True’ in order for the outcome to be ‘True’. Thus, I always look at both A and B and attempt to find ‘False’ (instead of ‘True’ like the OR gate) and the moment I see ‘False’ in either A or B, I know the outcome is ‘False’. This is often used in programming and other areas of academics when one wants to let more than one criterion to be satisfied before taking any action as an outcome.

NOT GATE

A	NOT A
True	False
False	True

NOT Gates are very simple in short statements that don’t involve multiple steps as the output is just the opposite of the input. One of the most important idea to take away from NOT gates are the fact that it is very important to know where the NOT gates are introduced. For example (NOT (A or B)) can be very different from (A or (NOT B)).  With one misstep with integrating NOT gates in circuits will completely ruins the result and one must be always careful to locate where the NOT gates are position within a circuit or a statement.

Important Notion: Binary Numbers

Binary vs. Base 10

Binary -> Base 10

In order to get binary to base 10, one just needs to know two things. One is that the binary numbers are only in 0 or 1. Second is that the first number of binary number corresponds to 2^0 and second number will correspond to 2^1, and it goes on. So in a way, you have to read the binary numbers from right to left in order to correctly identify which power it will go until.

Ex

111011 = 1 (2^5) + 1(2^4) + 1(2^3)+ 0(2^4) + 1(2^3) + 0(2^0) + 1(2^1) + 1(2^0) = 59 (in base 10)

Base 10 -> Binary

I believe this is best explained if one were to ask a series of questions. Here is an example,

Ex

Base 10 number is 59.

So we ask ourselves, does 59 fit for 2^(biggest number it can fit into)

59 -> Does it fit for 2^6? Answer: NO

59 -> Does it fit for 2^5? Answer: YES

Since 2^5 = 32, then 59-32=27, and thus our new number that we ask questions to is 27

27 -> Does it fit for 2^4? Answer: YES

Like the last part, 27-2^4=11

11-> Does it fit for 2^3? Answer: YES

11-2^3=3

3->Does it fit for 2^2? Answer: NO

3->Does it fit for 2^1? Answer: YES

3-2=1

1-> Does it fit for 2^0? Answer: YES

1-1=0

Okay, now that we have reached 0, we can begin to construct our binary number. By looking at all the ‘YES’s from the questions, that is where you would have 1, and 0 will correspond to ‘NO’

So again, writing from right to left and reading the questions from bottom to top.

You should get 0111011, since the first 0 is insignificant, you may take it out and thus you get: 59=111011 in binary numbers.

Binary Addition

First thing to know is the basic addition:

0+0=0

0+1=1

1+1=10 (not 10, but 1 and 0)

1+1+1=11 (again, not 11, but 1 and 1)

<-Carry’s

It is very simple to basic addition we learned in elementary school, except that there are only 0 and 1 and the additions to those are stated above.

Binary Subtraction

Same subtraction as normal 0 and 1:

1-0=1

0-1   => change 1 to 0 from the line on the left

<-Carry’s

Binary Multiplication

Basic multiplication:

0x0=0

1x0=0

0x1=0

1x1=1 (with no carries)

The way you perform multiplication is very similar to normal multiplication, except when adding the finished multiplied products, make sure to refer again to binary addition as it follows those rules to perform the addition.

Ex

Binary Division

Binary division is also very similar to normal division, thus in a way, division requires multiple binary subtractions as you will constantly subtract the divided product to the dividend.

Ex