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Tapestry Workshop: Mentoring for Connections to Computing Activities Karen C. Davis Professor, Electrical & Computer Engineering

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Presentation on theme: "Tapestry Workshop: Mentoring for Connections to Computing Activities Karen C. Davis Professor, Electrical & Computer Engineering"— Presentation transcript:

1 Tapestry Workshop: Mentoring for Connections to Computing Activities Karen C. Davis Professor, Electrical & Computer Engineering karen.davis@uc.edu

2 Difference EngineJacquard Loom

3 Online Unplugged Resources mathmaniaCS.org CSunplugged.org ** birthday prediction **

4 [boardgamegeek.com] Graph Traversal

5 [boardgamegeek.com] Digital Logic Movement Programming Surface Tiling

6 hit the books College Success Roborally go to class design computing systems make the Dean’s List graduate!

7 Software Specification [boardgamegeek.com] Grammar Rules Pattern Recognition Project Management Sorting

8 Pattern Recognition Warm-up colorshapenumbershading o same o different o same o different o same o different o same o different Is this row a set? √ √ xx

9 Pattern Recognition Warm-up colorshapenumbershading o same o different o same o different o same o different o same o different √√ Is this row a set? √ √

10 Pattern Recognition Warm-up colorshapenumbershading o same o different o same o different o same o different o same o different √ √ Is this column a set? √ √ let’s try it!

11 Internet Message Routing Embedded Computers Land Mobile Radio Communications Bioinformatics Computer Chip Design Scheduling with Graph Coloring Medical Imaging Scheduling with Graph Coloring

12 Virtual Fashion Design Pipe Layout Design Bear-a-Trooper Pattern Recognition Artificial Intelligence Binary Numbers

13 Vision and Precision Multitasking Pixels and Pellets Wii Debate

14 Computer Science Investigations: CSI Cincinnati Scheduling

15 Problem Exploration

16 Graph A C B E F D node edge 3 edges are adjacent to D

17 Graphs can be represented in a computer program can be used to solve complex problems Example: find the cheapest way for a traveler to visit every city Atlanta Cincinnati Boston Eugene Fairbanks Dallas $900 $700 $800 $200 $100 $300 $400

18 Exhaustive vs. Approximate Searching Searching for all possible solutions takes a long time, even for a computer, when there are lots of nodes We use algorithms that search for a good enough solution but don’t try all possible solutions n(n 2 – n)/2 46 510 45 1004,950 1,000499,500 10,00049,999,950 100,0004,999,950,000

19 Using an Approximate Graph Algorithm for Scheduling A C B E F D event to be scheduled conflict between events

20 Solution Technique: Setup

21 Solution Technique: Algorithm

22 Assigning Frequencies in Cellular Networks

23 1.count the adjacent edges 2.color the one with the highest edge count 3.color any others (not adjacent) with the same color 4.pick a new color and repeat steps 2-4 until all nodes are colored Using the Algorithm to Assign Cell Tower Frequencies let’s try it!

24 Automated Graph Coloring graph coloring animation

25 Computer Science Investigations: CSI Cincinnati Artificial Intelligence

26 Goal of Artificial Intelligence Can intelligence be modeled by a machine? A scientific approach is that the behavior of an intelligent organism can be studied and engineered

27 CAPTCHA reCAPTCHA: digitizing books using OCR words it can’t recognize are sent out as CAPTCHA words users help to disambiguate the words and demonstrate that they are human Completely Automated Public Turing test to tell Computers and Humans Apart reverse Turing test CAPTCHA trademarked by Carnegie Mellon University

28 analysis of DNA to find genes analysis of RNA to predict structure designing new drug molecules

29 Recognizing Defects normal DNA atggtgcacctgactcctgaggagaagtctgc cgttactgccctgtggggcaaggtgaacgtg gatgaagttggtggtgaggccctgggcaggt tgctggtggtctacccttggacccagaggttct ttgagtcctttggggatctgtccactcctgatg ctgttatgggcaaccctaaggtgaaggctcat ggcaagaaagtgctcggtgcctttagtgatgg cc … defective DNA atggtgcacctgactcctgtggagaagtctgc cgttactgccctgtggggcaaggtgaacgtgg atgaagttggtggtgaggccctgggcaggttg ctggtggtctacccttggacccagaggttcttt gagtcctttggggatctgtccactcctgatgct gttagggcaaccctaaggtgaaggctcatgg caagaaagtgctcggtgcctttagtgatggcc … glutamic acidvaline

30 Computers are good at recognizing patterns … that involve huge quantities of data that are complex and non-intuitive

31 Decision Trees

32 20Q Let’s get hands on with some real AI –play 20Q with a group agree on one object agree on group answer to 20Q’s questions –make observations on the worksheet use buttons to provide answers questions appear here play online: www.20q.net

33 Computer Science Investigations: CSI Cincinnati Wii Debate

34 www.ece.uc.edu/mc2

35 1. start here facing downward 2. figure out a sequence of moves to finish here bumping into a wall keeps you in the same spot falling into a pit or off the board ends your turn


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