Overcoming My Anxiety in Public Speaking Essay Example | Topics and Well Written Essays - 500 words

Overcoming My Anxiety in Public Speaking - Essay Example As expected in my profession, I am required to present the children’s condition including the approach and methodology applied in Individualized Education Program (IEP) meetings. Armed with my evaluation papers and a few bulleted note cards outlining my whole presentation—which I rehearsed over and over until the last minute—I still felt as if a full bucket of nervousness was drenching my whole body. The situation catapulted me to my primary and secondary years and once again I am again a high school student before the analytical eye of my professor and the mocking glare of my classmates; as if every eye is staring at the flaws in my face, counting every drop of sweat, listening to the quivering of my voice, watching the trembling of my hands, and making a mental note of every mistake that would come out of my mouth. But I had to shake off the imaginary time warp and forced myself to get a rock-hard grip on the present. I strived to produce a genuine smile as I a cknowledged the audience and proceeded to my presentation. The discussion went pretty well although there were few verbal lapses which I believe is forgivable enough. It’s a total relief that it’s over and done with. There will be succeeding occasions when I would have to speak again but I know that it wouldn’t be as hard as it had in the previous times. I may not be the best speaker and not everyone may appreciate my speech but never again will I dread the opportunity to impart the knowledge which I believe is of benefit to the listeners.

Calculate a puzzle Essay Example | Topics and Well Written Essays - 1500 words

Calculate a puzzle - Essay Example Hence, dynamic search function and control optimization are major primitives to construct search utilities for stochastic system processes to ensure converged resource accesses. This research focuses on optimization of general search solution methods and proposes a formal search utility framework, algorithms rooted from Reinforcement Learning (RL) and Dynamic Programming (DP) techniques. To reduce space complexity within large dimension search spaces, a memoryless2 Q learning is augmented with self-organized index structure and algorithms for exact state-action value function mapping to optimize search procedures for optimal policies. Data parallelization is ensured with this paged based index value mapping function. Hence, time complexity is reduced with threaded search parallelism. Convergence analysis and error estimation are presented for numeric and information evaluation. Finally, simulation and learning results are presented and discussed. For search strategies in the settings of problem solving and reasoning, search problem formulation represents many combinatorial optimization problems of search approximation with action control optimization. All aspects of search task environment represent various classes of applications, such as routing, scheduling, speech recognition, scene analysis and intrusion detection pattern matching. By given a directional graph G with distinguished starting state Sstart and a set of goal