PPT-Heuristic Evaluation 3

CPSC 481 HCI I Fall 2014 1 Anthony Tang with acknowledgements to Saul Greenberg and Ehud Sharlin Learning Objectives By the end of this class you should be able to understand and describe . with graph search. Graphs. G = (V, E). V is a set of vertices, {v. 1. , …, . v. N. }. E is a set of edges between vertices, {e. 1. , …, . e. M. }. Each edge . e. i. is an ordered pair of vertices in V:. NPT Test Gauges TOO SIMILIAR to Riser Margin For Crew To Ignore. Pressure of Reservoir Pushing “UP” is . ~1,400 psi. Pressure of Riser Mud Pushing “DOWN” is . ~1,400 psi. Water Depth. Teaching . Probability and Decision Theory in . Foundations . of Logical . Reasoning. Quantitative Literacy in Philosophy. [. Quantitative literacy] requires logic, data analysis, and probability….It enables individuals to analyze evidence, to read graphs, to understand logical arguments, to detect logical fallacies, to understand evidence, and to evaluate risks. Quantitative literacy means knowing how to reason and how to think. . Heuristic - a “rule of thumb” used to help guide search. often, something learned experientially and recalled when needed. Heuristic Function - function applied to a state in a search space to indicate a likelihood of success if that state is selected. May 4, 2016. Outline. Heuristic Evaluation Overview. The . Heuristics. Exercise. May 4, 2016. CS377E: Designing Solutions to Global Grand Challenges. 2. Evaluation. About figuring out how to improve design. Objectives. Today. The inspection process. Practice inspection. Heuristic evaluation process. Practice evaluation. Next time. Rationale behind why inspections and heuristic evaluation is so great. Normally would do this in the opposite order, but this way you should be able to better prepare any materials over the weekend. Jingtao Zhu. May 13rd,2016. “Efficient Influence Maximization . in Social Networks. ”. . Written by Chen Wei, Yajun Wang, and Siyu Yang. . Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining. unknown environment. Athanasios Ch. Kapoutsis. , Christina M. . Malliou. , Savvas A. Chatzichristofis and Elias B. . Kosmatopoulos. School of Electrical and Computer Engineering,. Democritus University of Thrace, Xanthi, Greece. NPT Test Gauges TOO SIMILIAR to Riser Margin For Crew To Ignore. Pressure of Reservoir Pushing “UP” is . ~1,400 psi. Pressure of Riser Mud Pushing “DOWN” is . ~1,400 psi. Water Depth. Rhea . McCaslin. The GDS Network. Guarded Discrete Stochastic – neural network developed by Johnston and . Adorf. 2. Hubble Space Telescope. Scheduling Problem. PROBLEM: Between 10,000 – 30,000 astronomical observations per year . HCI: User Interface Design, Prototyping, & Evaluation. 2. Hall of Fame or Shame?. Pocket. By Read It Later. Jan. 14-18, 2013. HCI: User Interface Design, Prototyping, & Evaluation. 3. Minimalist reading mode.. Continued. Before we continue. Breadth-First. Depth-First. Uniform Cost. Iterative-Deepening. Before we continue. Breadth-First. S,A,B,D,C,G. Depth-First. S,A,C,D,B,G. Uniform Cost. S,A,B,D,C,G. Iterative-Deepening. Continued. Before We Start. HW1 extended to Monday. Submit online (now working) and bring paper print out. Questions?. Competency Demo next Wednesday. Study Guide Posted. We will have some discussion time on Monday. Rhea . McCaslin. The GDS Network. Guarded Discrete Stochastic – neural network developed by Johnston and . Adorf. 2. Hubble Space Telescope. Scheduling Problem. PROBLEM: Between 10,000 – 30,000 astronomical observations per year .