A. Suppose we send into the Internet two IP datagrams, each carrying a different UDP segment. The first datagram has source IP address A1, destination IP address B, source port P1, and destination port T. The second datagram has source IP address A2, destination IP address B, source port P2, and destination port T. Suppose that A1 is different from A2 and that P1 is different from P2. Assuming that both datagrams reach their final destination, will the two UDP datagrams be received by the same socket? Why or why not? b. Suppose Alice, Bob, and Claire want to have an audio conference call using SIP and RTP. For Alice to send and receive RTP packets to and from Bob and Claire, is only one UDP socket sufficient (in addition to the socket needed for the SIP messages)? If yes, then how does Alice’s SIP client distinguish between the RTP packets received from Bob and Claire?

Your task this week is to write a very simple spam classifier in python. it will classify messages as either spam (unwanted) or ham (wanted). the program will have a set of spam_words, words that are known to appear in spam messages. that set is included in the template file spam.pypreview the document. you will also define a spam threshold which reflects the allowed percentage of spam words in the message. you'll compute a 'spam indicator', which is the ratio of spam words to the total number of unique words in the message. if the spam indicator exceeds the spam threshold, the message is classified as spam. otherwise it is classified as ham. we'll assume that the spam threshold is a constant and has a value of 0.10. your program will prompt the user for a message and then will print the corresponding spam indicator with two decimal digits and the corresponding classification (spam or ham). the program will be case insensitive. the spam words are detected whether they are in lower case or upper case or mixed case. each word, spam or not, is counted once (even if it appears multiple times in the message.) the program will remove punctuation from the message before identifying the words and computing the spam indicator. for example '! ' must be identified as the spam word 'now'.

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