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# Final Exam Study Guide MATH 451 002

UA

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This 6 page Study Guide was uploaded by Julianna Pfadt on Sunday December 6, 2015. The Study Guide belongs to MATH 451 002 at University of Alabama - Tuscaloosa taught by Dr. Yuhui Chen in Fall 2015. Since its upload, it has received 27 views. For similar materials see Mathematical Statistics with Applications I in Mathematics (M) at University of Alabama - Tuscaloosa.

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Date Created: 12/06/15

UA CS 104 Computer Sciences Principles for math majors Final Exam Study Guide Review all the reading assignments quizzes and tests to prepare for the final There is no new material after exam 2 Review Ch1 of Blown to Bits 1 Moore s Law 2 Metcalfe s Law 3 Principles of Bits gt exponential growth nothing goes away technology makes it a at world 4 Very likely that there are transmission errors when messages are sent and they must be resent until the message is received correctly Odd parity and even parity 1 1001 even 1000 odd 2 Used to detect errors gt pattern for card game gt ERROR CORRECTION Credit cards and checksums 1 ERROR DETECTION 2 The Luhn Algorithm memorize this Example 49927398716 I Reverse the credit card no 61789372994 I Sum the digits of the odd places 679794Sl42 I Double the sum the digits in the even places if doubled no is two digits sum the digits 0 18329 gt 2166418 gt 27649 o 27649S228 I Last digit of sum of S1 and S2 should be 0 422870 0 CONFIRMED Binary Number 1 Long string of 0 s and 1 s Byte Binary Term Bit Binary Digit 1 1 Byte 8 Bits 1 character 2 Subscript of 2 gt binary no 3 Subscript of 10 gt decimal no Convert binary to decimal and decimal to binary 1 Powers of 2 gt 2 n0l n 2 101012 2110 multiply down add across Hexadecimal 1 0F0 1 2 3 4 5 6 7 8 9 A B C D E F 2 Streams of bits converted to hex by 4bit sequences 100110110011 3 Color codes are in hexadecimal 4 Each 2letter hex no represents 256 values a byte or one part of REG 5 Colors represented in 3 Bytes red blue green 39 3 bytes in a pixel each byte represents a color RBG I 16 million colors 1byte1byte1byte 256316 million Octal Base 8 Oct 31 Dec25 1 A in text is represented as decimal 25 which is 31 in octal Grayscale red eye removal color filters Compression optimize storage 1 Lossless vs Lossy Compression 2 WhiteampBlack block patterns as compression with RLE Computation calculation that involves a process following a welldefined model understood and expressed in an algorithm Turing Machine 1 Alan Turing gt Father of CS 2 Can compute ANY algorithm Hardwaregtyou can touch it softwaregtset of instructions that tell the computer what to do programs Compiler translator interpreter Lower level vs higher level RAM ROM external storage 5 Phases of Software Development 1 Understand the problem 2 Plan the logic 3 Code the program 4 Test the program 5 Deploy the program produce maintain Types of errors syntax errors and logical errors Flowcharts and Pseudocode Relational operators lt gt BooleanLogical operators and or not Loops forever repeat repeat until Variable swap in programming Sturctures sequence decision loop Truth Tables Broadcasting and all other important concepts used in Maze Game Parameter an additional piece of information provided to the block that helps the block do its function Procedural Abstraction using parameters and same code to make code usable for many contexts abstractiongt hiding the details When to Create a New Block 1 When a piece of code becomes very long 2 When code is very repetitive Types of Blocks 1 Command method preforms a given set of instructions no output 2 Reporter function preforms given set of instructions gives output 3 Predicate Boolean function output is TrueFalse Validating parameters Max Block gt Block Sum Method Mystery blocks from quizzes Storing data in a list integrating through a list Computation follows a welldefined model expressed in an algorithm Sorting Algorithms uses relational operators to order a set of values 0 Recall the sorting machine we created in class Wang Mudum 5t A tax x q Alf1 Q J m1 39 g an ao h o 7 W 0 He commented that he might ask us to draw a machine like this on the exam 0 A sorting machine is unrealistic for a large amount of values Selection Sort sorts in passesstages 0 Scan the 04 spots choose the smallestlargest swap its position with the item in the 0 index Repeat with the remaining 14 spots Repeat until you only have the 34 spots left to scan and don t forget to perform the last swap even if they do not actually move see quizzes for example Algorithm Complexity time complexity the primary concern in today s world vs space complexity 0 Review BigO Notation exponential is the WORST cannot handle big inputs and logarithmic is the BEST improves with greater no of inputs Searching Algorithm the foundation of Google given a set determine if a value is in that set 0 You can also have it report the location of the specified value 0 Strategy I Linear Search examines each item in order of the list like the highest score algorithm I Binary Search phone book and cup game done in passes find the median compare the values on either side of the median to the desired value choose the set that the desired item would be in Repeat the pass with only this new set Repeat until item is located If mingt max the item was not found in the list Crowdsourcing the mob effect 0 Examples CLEAR and Tornado Damage Tracking Gas Buddy Wikipedia 0 Why does it work Incentive social networking structure distributed talents 0 When does it not work If there is not a way to confirm the reported information if rules are ambiguous Human Computation captchas identifying photos etc 0 Trade work for entertainment via app games Network collection of nodes connected by cableswireless for exchange of data Network Components PC switch server router other networks outside world 0 Review the structure from the slides IOT Internet of Things The internet is a delivery mechanism It is not the World Wide Web It accesses the World Wide Web Collection of webpages 9 website Click on a link that takes you to a new webpage 9 hypertext URL unique address to locate something 0 httpwwwyahoocomfinancehtml 9 protocol domain name path IP address static web pages vs dynamic laptop Domain Name System DNS translate domain names to IP address see illustration in slides Top level domains com edu org net gov Network topologies star ring bus Packet switching how they work and packet sniffing Protocols a system of rules for communication think conference calls TCP Transmission Control Protocol and IP Internet Protocol 0 Backbone of the intemet Application Layer HTTP HTTPS SMTP FTP Transport Layer 0 TCP good for integrity reliability at expense of speed 0 UDP good for real time speed and latency at expense of reliability Criminals caught by bits because they don t understand the intemet Cryptography creating documents that can be shared secretly over public communication channels and be decrypted with a key Cryptanalysis finding the keycracking it Cryptosystems using computers algorithms to crack the encryption ROT13 algorithm inverse decrypts back to original see slides for specifics likely to be on exam Keys 0 Symmetric used to encrypt and decrypt easier to crack 0 Asymmetric two different keys to encrypt and decrypt I Problem key distribution How do we avoid the key distribution problem 0 Public and private keys Someone would use my public key to encrypt a message and send to me I have a private key to decrypt messages that have been encrypted with my public key Problem how do you know who actually sent you a message if anyone can encrypt it Digital Certificate Strength of a one way function is measured by the amount of time it takes to reverse it Encryption is all mod algorithms and very large prime numbers think about the video he showed us 0 We will not have to do the actual math Abstraction a means of achieving stepwise refinement by accentuating relevant details and suppressing unnecessary ones 0 Examples in life stop sign traffic light abstract art maps A model is a representative of a system 0 Any question about the model should represent the exact same answer you d get if you asked the same question about the system 0 Think of a map if it looks like you should go down one street and turn left on the map it should be that way in real life too Big Data 0 We create 25 quintillion bytes of data a day as of 2 years ago 0 Data sets are growing too large and it is difficult to derive meaning from them because of this 0 Ethical concerns The 3 V s of Big Data Volume Variety Velocity Data cation we collect data on everything just in case there is a use for it in the future Big Data changes how we conduct scientific studies 9 we can get much larger samples of data thus there is more allowance for large outliers because it will still be accurate 0 It is answering what not why humans are necessary for insight but the data analysis can give us correlations we never would have found on our own Processing Steps of Big Data 1 Identify appropriate data source amp form questions 2 Extract data source into usable format 3 Normalize data remove redundancies and irrelevant details 4 Import data into tools 5 Perform analysis 6 Visualize results 0 Tim Burners Lee created the World Wide Web

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