Online library resources
Explanation
Students can utilize online library resources from various campus available for online educational uses.In the library, information on current research in the various displines can be obtained through a search on the book, journal or document.In addition to that, goggle offers academic journals and academic documents prepared by scholars for other academicians to read and get information.
Answer:
Boolean Operators
Explanation:
When performing a boolean search, boolean operators allow users to combine keywords with operators (or modifiers) such as AND, NOT and OR to further produce more relevant results.
The boolean operators AND and OR are used to include certain words and phrases during the search while the boolean operator NOT is used to exclude certain words and phrases.
The resiliency technique which would provide the aforementioned capabilities is: D. Full backups.
An operating system (OS) can be defined as a system software which is pre-installed on a computing device, so as to manage or control software application, computer hardware and user processes.
In this scenario, a manufacturing company cannot migrate its several one-off legacy information systems (IS) to a newer operating system (OS), due to software compatibility issues.
Resiliency can be defined as a measure of the ability of a network, server, storage system, computing system or data center, to recover quickly and continue operating when it experience adverse conditions such as:
In Computers and Technology, there are four (4) main resiliency technique and these include:
I. Redundancy.
II. RAID 1+5.
III. Virtual machines.
IV. Full backups.
Full backup is a resiliency technique which create backups of the systems for recovery and it allows operating system (OS) patches to be installed on computer systems.
Read more: brainly.com/question/17586013
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.
At the top of their name when they answer it should say “give brainliest”
