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

2. Difference EngineJacquard Loom

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

4. Vision and Precision Multitasking Pixels and Pellets Wii Debate

5. Virtual Fashion Design Pipe Layout Design Bear-a-Trooper Pattern Recognition Binary Numbers

6. Online Unplugged Resources mathmaniaCS.org CSunplugged.org

7. [boardgamegeek.com] Graph Traversal

8. [boardgamegeek.com] Software Specification Logical Reasoning

9. Computer Science Investigations: CSI Cincinnati Scheduling

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

11. 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

12. 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

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

14. Assigning Frequencies in Cellular Networks

15. Computer Science Investigations: CSI Cincinnati Wii Debate

16. About me…. Stephanie Ross Senior at the University of Cincinnati Major: Computer Information Systems Minor: International Business Graduation Date: December 13, 2008 Key factors to where I am now: Strength, Courage, Wisdom Determination and Perseverance

17. Work Experience Cintas Corporation Support Services Great American Insurance Co. Business Intelligence 2 co-ops and 3 internships Portable Route Computers AS400 to network printers 2 internships Training with Cognos software

18. Nintendo Wii

19. About Wii Remote Heart of remote are tiny accelerometers Inside of remote are silicon springs and wafers Accelerometer measures capacity and electric charge http://www.gadgetspage.com/toys-games/how-does-the-wii-remote-work.html

20. About Wii Sensor Bar Emits a beam of infrared light to sensor on controller. Can determine where the controller is pointing using motion sensing

21. 1 st Activity Class will be split into two teams One representative from each team will play one game on the Wii.

22. 2 nd Activity Teams will be given an information sheet with pros/cons about Wii Team 1: Choose information from sheet along with your experience that will help you sell the product/idea. Team 2: Choose information from the sheet along with your experience that will help you reject the idea.

23. 3 rd Activity Team 1 will present their findings. Team 2 will evaluate presentation. Team 2 will present their findings. Team 1 will evaluate presentation. The class will converse and summarize.

24. Computer Science Investigations: CSI Cincinnati Recognizing Patterns

26. 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

27. People are good at recognizing some patterns … but are there patterns that humans are bad at recognizing?

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

29. Genetics DNA replicated through RNA transcription DNA/RNA composed of nucleotides: A T/U C G triplet code of nucleotides amino acids proteins

30. RNA Translated to Proteins

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

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

33. www.ece.uc.edu/mc2