PPT-CS 173, Lecture B Tandy Warnow

Topics for today Basics of combinatorial counting Applications to running time analysis Using combinatorial counting Evaluating exhaustive search strategies Finding maximum clique Determining if a graph has a 3coloring. The problem is that this information is oftenly unknown LMS is a method that is based on the same principles as the met hod of the Steepest descent but where the statistics is esti mated continuously Since the statistics is estimated continuously th 11. Assembly Language and . Arduino. Behind the C code (or sketch). C provides a somewhat human-readable interface. but it gets . compiled. into machine instruction set. ultimately just binary (or hex) instructions loaded into the . 4. LCD Text Display. Keypads and Time Slicing. Interrupts. 2×16 LCD . Typically 5×8 dots per character. Note 16 pins: indicator of common interface. Lecture 4. 2. Typical LCD Unit . pinout. pin. function. 4T.WARNOW,S.N.EVANS,D.RINGE,ANDL.NAKHLEHModelsthathaveincorporatedborrowingintolinguisticevolutionwhilestillassuminghomoplasy-freeevolutionhavebeenusedinsev-eralsimulationstudies(McMahon&McMahon,2003) Assembly Language and . Arduino. Behind the C code (or sketch). C provides a somewhat human-readable interface. but it gets . compiled. into machine instruction set. ultimately just binary (or hex) instructions loaded into the . tandy! !"=:2Dmtn,(4.2)wherethedi#usioncoe"cientDmisde Assembly Language and . Arduino. Behind the C code (or sketch). C provides. a somewhat human. -readable interface. but . it . gets . compiled. into machine instruction set. ultimately just binary (or hex) instructions loaded. Assembly Language and . Arduino. Adapted from T. Murphy’s slides. Behind the C code (or sketch). C provides a somewhat human-readable interface. but it gets . compiled. into machine instruction set. 11. Assembly Language and . Arduino. Behind the C code (or sketch). C provides a somewhat human-readable interface. but it gets . compiled. into machine instruction set. ultimately just binary (or hex) instructions loaded into the . Using combinatorial counting. Evaluating exhaustive search strategies:. Finding maximum clique. Determining if a graph has a 3-coloring. Finding a maximum matching in a graph. Determining if a graph has a Hamiltonial cycle or an Eulerian graph . Newick strings. Representing rooted trees using clades and rooted triplet trees. Constructing a rooted tree from its set of clades using Hasse Diagrams . Constructing a rooted tree from rooted triplet trees using Aho, Sagiv, Szymanski, and Ullman . Constructing unrooted trees from bipartitions. Compatible binary characters. Constructing trees from compatible binary characters. Introducing . maximum parsimony. Maximum parsimony is not statistically consistent under standard models of sequence evolution!. University of Illinois at Urbana-Champaign. http://. tandy.cs.Illinois.edu. Orangutan. Gorilla. Chimpanzee. Human. From the Tree of the Life Website,. University of Arizona. Species Tree. . Introducing maximum parsimony. Maximum parsimony is not statistically consistent under standard models of sequence evolution!. Dynamic programming to solve maximum parsimony on a fixed tree. Maximum Parsimony.