Answer:
False
Explanation:
In our current market, we can find some messaging apps and social media designed for corporation organization setting. One example of messaging apps widely used in corporate world is Slack. The Slack enable user to set up different communication channel with their colleagues and flexibly set their working status.
FB also releases a corporate version of social media which is Workplace. The main attracting point is the contents are ad-free and you can expect to see company update or department news from the nesfeed.
Answer:
A cell grows to its full size, The cell copies its DNA
have a great weekends, hopefully it was the right answer!
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.
a.on , off
In most computer processors, electron movement is controlled by tiny switches that turn this flow of electricity on and off...zero represents off and one represents on
Answer:
this would be .128 terabytes
Explanation:
This would be since for a whole terabyte you need 1000 gigabytes every 1000 gigabytes is a terabyte for example let’s say you have 5250 gigabytes you would have 5.250 terabytes that simple hope this helped!
