generator

Generators: The name chosen by the 2010-11 Rotary International District Governors in Zones 25-26. Together these 24 Governors will lead over 67,500 Rotarians from 1,318 Rotary Clubs located in British Columbia (Canada), Washington, Oregon, Idaho, Nevada, California, Arizona and Hawaii (USA). They selected the name because it evokes energy, dynamism, and change. During their year as governors, they plan to extend membership to a wider range of volunteers, reaching out to young professionals and business leaders; support thousands of community and international humanitarian projects; provide international scholarships; host international youth and business/professional exchanges; encourage youth volunteerism through Interact Clubs and Rotary Youth Leadership Awards, and offer leadership training to its members.Rotary International is a global network of community volunteers made up of over 1.2 million business and professional leaders to provide humanitarian service and help build goodwill and peace. The members participate in projects to address today's challenges -- including illiteracy, disease, hunger, poverty, lack of clean water, and environmental concerns -- while encouraging high ethical standards in all vocations. PolioPlus is Rotary's flagship program. It is the spearheading partner in the Global Polio Eradication Initiative. By the time polio is eradicated, Rotary club members will have contributed US$850 million and countless volunteer hours to immunize more than two billion children in 122 countries.Rjschulte (talk) 06:40, 4 November 2008 pseudorandom number generator (PRNG) is an algorithm for generating a sequence of numbers that approximates the properties of random numbers. The sequence is not truly random in that it is completely determined by a relatively small set of initial values, called the PRNG's state. Although sequences that are closer to truly random can be generated using hardware random number generators, pseudo-random numbers are important in practice for simulations (e.g., of physical systems with the Monte Carlo method), and are central in the practice of cryptography.Most pseudo-random generator algorithms produce sequences which are uniformly distributed by any of several tests. Common classes of these algorithms are linear congruential generators, lagged Fibonacci generators, linear feedback shift registers and generalised feedback shift registers. Recent instances of pseudo-random algorithms include Blum Blum Shub, Fortuna, and the Mersenne twister.Careful mathematical analysis is required to have any confidence a PRNG generates numbers that are sufficiently "random" to suit the intended use. Robert R. Coveyou of Oak Ridge National Laboratory once titled an article, "The generation of random numbers is too important to be left to chance."[1] As John von Neumann joked, "Anyone who considers arithmetical methods of producing random digits is, of course, in a state of sin.