Stephanie R Perez

Learning: Perceptrons & Neural Networks. Artificial Intelligence CMSC 25000 February 14, 2008. Roadmap. Perceptrons: Single layer networks Perceptron training Perceptron convergence theorem Perceptron limitations Neural Networks Motivation: Overcoming perceptron limitations

CMSC 202. Lesson 23 Templates II. Warmup. Write the templated Swap function _______________________________ void Swap( ________ a, ________ b ) { _______________ _______________ _______________ }. template <class T>. T&. T&. T temp = a;. a = b;. b = temp;. Class Templates.

Network Analysis. Steady State Analysis: This analysis is used to to determine system behavior at a certain point in time. This point is usually at the average demand or fire flow. It is not suitable for time dependent events. . Extended Period Analysis EPS

The Models of Revelation. A somewhat in-depth view Of Avery Dulles’ work. The Models of Revelation. Revelation as Propositional (Literal Words) History (The Acts of God) Inner Experience (Mysticism) Dialectical Presence (Hegelian Paradox) New Consciousness (Self-participation).

CARE 4 SEVAN Consequences. Consequences of the Problems. Health – epidemic diseases Economy Reduced fisherman income Reduced income from tourism due to: Poor sanitation Intestinal diseases Polluted rivers and lake. General Conditions in Gegharkunik Marz. Greater than 44% live in poverty

Sunspot Cycle vs. the Power Grid http://www.thecityedition.com/Pages/Archive/2010/Sunspots.html.

Computational Thinking. NRC Report on Pedagogy web site: www.cs.vt.edu/~kafura/CS6604. NRC Report on Pedagogy for CT. Second of two workshops Focused on K12 Education Identified different approaches to the teaching of computational thinking