Answer:
answer(s):
-set goals
-select a topic
-write down research questions
Hope this helped and sorry for the bold. <3
Explanation:
Answer:
It we were asked to develop a new data compression tool, it is recommended to use Huffman coding since it is easy to implement and it is widely used.
Explanation:
The pros and the cons of Huffman coding
Huffman coding is one of the most simple compressing encoding schemes and can be implemented easily and efficiently. It also has the advantage of not being patented like other methods (e.g. arithmetic codingfor example) which however are superior to Huffman coding in terms of resulting code length.
One thing not mentioned so far shall not be kept secret however: to decode our 96 bit of “brief wit” the potential receiver of the bit sequence does need the codes for all letters! In fact he doesn’t even know which letters are encoded at all! Adding this information, which is also called the “Huffman table” might use up more space than the original uncompressed sentence!
However: for longer texts the savings outweigh the added Huffman table length. One can also agree on a Huffman table to use that isn’t optimized for the exact text to be transmitted but is good in general. In the English language for example the letters “e” and “t” occur most often while “q” and “z” make up the least part of an average text and one can agree on one Huffman table to use that on average produces a good (=short) result. Once agreed upon it doesn’t have to be transmitted with every encoded text again.
One last thing to remember is that Huffman coding is not restricted to letters and text: it can be used for just any symbols, numbers or “abstract things” that can be assigned a bit sequence to. As such Huffman coding plays an important role in other compression algorithms like JPG compression for photos and MP3 for audio files.
The pros and the cons of Lempel-Ziv-Welch
The size of files usually increases to a great extent when it includes lots of repetitive data or monochrome images. LZW compression is the best technique for reducing the size of files containing more repetitive data. LZW compression is fast and simple to apply. Since this is a lossless compression technique, none of the contents in the file are lost during or after compression. The decompression algorithm always follows the compression algorithm. LZW algorithm is efficient because it does not need to pass the string table to the decompression code. The table can be recreated as it was during compression, using the input stream as data. This avoids insertion of large string translation table with the compression data.
The three real-life objects that are instances of each of the following classes are given below:
a.<u> Song:</u>
The song Believe in yourself is an instance of song class
The song Where do broken hearts go is an instance of song class.
The song Ambition is an instance of song class
b. <u>CollegeCourse</u>
The College course Engineering is an instance of College course class
The College course Accounting is an instance of College course class
The College course Medicine is an instance of College course class
c. <u>Musician:</u>
The musician Rihanna is an instance of musician class.
The musician Sean Paul is an instance of musician class.
The musician Wyclef is an instance of musician class.
Real-life objects refer to the things that are characterized together as they share common qualities. The assignment simply wants you to name examples under the categories given.
Read related link on:
brainly.com/question/16699733
Answer:
1. A high level algorithm for cooking a cheeseburger could be:
- Heat fry pan
- Cook one side of the hamburger
- Wait
- Turn hamburger upside down
- Put cheese over hamburger
- Wait
- Cut hamburger bread in half
- Put cooked hamburger inside bread
- End (eat)
2. A detailed algorithm for cooking a cheeseburger could be:
- Place fry pan over the stove heater
- Turn on heater (max temp)
- IF fry pan not hot: wait, else continue
- Place raw hamburger on fry pan
- IF hamburger not half cooked: Wait X time then go to line 5, else continue
- Turn hamburger upside down
- Put N slices of cheese over hamburger
- IF hamburger not fully cooked: Wait X time then go to line 8, else continue
- Turn off heater
- Cut hamburger bread in half horizontally
- Put cooked hamburger on one of the bread halves.
- Put second bread half on top of hamburger
- End (eat)
Explanation:
An algorithm is simply a list of steps to perform a defined action.
On 1, we described the most relevant steps to cook a simple cheeseburger.
Then on point 2, the same steps were taken and expanded with more detailed steps and conditions required to continue executing the following steps.
In computational terms, we used pseudo-code for the algorithm, since this is a list of actions not specific to any programming language.
Also we can say this is a structured programming example due to the sequential nature of the cooking process.
