Haskell: The Confusing Parts If you’re used to the C family of languages, or the closely related family of “scripting languages,” Haskell’s syntax (mainly) is a bit baffling at first. For some people, it can even seem like it’s sneaking out from under you every time you think you understand it. This is sort of a FAQ for people who are new to Haskell, or scared away by its syntax. Use this as a cheat sheet, not a textbook. Misc. Stuff You Should Know Already Quick review, because if you’ve heard of Haskell, you should also have heard of most of this. foo :: Bar baz -> Bar quux is a type signature for the function foo, where Bar baz is the type of argument it takes, and Bar quux is the type of the return value. There’s no null and no void. Haskell’s syntax is indirectly based on ML, so if you stop reading here and go learn OCaml instead, some of this information will still be kinda useful. Type Names and Constructors The “has type” (::) operator can appear as an expression in parentheses, or a separate declaration.
Play framework - Home A Gentle Introduction to Haskell, Version 98 This is the master HTML version of the Gentle Introduction To Haskell, version 98. Revised June, 2000 by Reuben Thomas. You may download the following: Brief Table of Contents. All code in this tutorial, with additional commentary, is found in the code directory packaged with this tutorial. We suggest that you inspect, run, and modify this code as you read the tutorial. Premission is granted to correct, improve, or enhance this document. Copyright (C) 1999 Paul Hudak, John Peterson and Joseph Fasel
List of unsolved problems in physics Some of the major unsolved problems in physics are theoretical, meaning that existing theories seem incapable of explaining a certain observed phenomenon or experimental result. The others are experimental, meaning that there is a difficulty in creating an experiment to test a proposed theory or investigate a phenomenon in greater detail. Unsolved problems by subfield[edit] The following is a list of unsolved problems grouped into broad area of physics.[1] Cosmology, and general relativity[edit] Cosmic inflation Is the theory of cosmic inflation correct, and if so, what are the details of this epoch? Horizon problem Electroweak Horizon Problem Why aren't there obvious large-scale discontinuities in the electroweak vacuum, if distant parts of the observable universe were causally separate when the electroweak epoch ended? Future of the universe Is the universe heading towards a Big Freeze, a Big Rip, a Big Crunch or a Big Bounce? Gravitational wave Can gravitational waves be directly detected? .
Learn Haskell Fast and Hard I really believe all developers should learn Haskell. I don’t think everyone needs to be super Haskell ninjas, but they should at least discover what Haskell has to offer. Learning Haskell opens your mind. Mainstream languages share the same foundations: variablesloopspointersdata structures, objects and classes (for most) Haskell is very different. But learning Haskell can be hard. This article will certainly be hard to follow. The conventional method to learning Haskell is to read two books. In contrast, this article is a very brief and dense overview of all major aspects of Haskell. The article contains five parts: Introduction: a short example to show Haskell can be friendly.Basic Haskell: Haskell syntax, and some essential notions.Hard Difficulty Part: Functional style; a progressive example, from imperative to functional styleTypes; types and a standard binary tree exampleInfinite Structure; manipulate an infinite binary tree! 01_basic/10_Introduction/00_hello_world.lhs Introduction ou
Statistical Data Mining Tutorials Advertisment: In 2006 I joined Google. We are growing a Google Pittsburgh office on CMU's campus. We are hiring creative computer scientists who love programming, and Machine Learning is one the focus areas of the office. We're also currently accepting resumes for Fall 2008 intenships. The following links point to a set of tutorials on many aspects of statistical data mining, including the foundations of probability, the foundations of statistical data analysis, and most of the classic machine learning and data mining algorithms. These include classification algorithms such as decision trees, neural nets, Bayesian classifiers, Support Vector Machines and cased-based (aka non-parametric) learning. I hope they're useful (and please let me know if they are, or if you have suggestions or error-corrections).
Physicists Slow Speed of Light Physicists Slow Speed of Light By William J. Cromie Gazette Staff Light, which normally travels the 240,000 miles from the Moon to Earth in less than two seconds, has been slowed to the speed of a minivan in rush-hour traffic -- 38 miles an hour. An entirely new state of matter, first observed four years ago, has made this possible. Such an exotic medium can be engineered to slow a light beam 20 million-fold from 186,282 miles a second to a pokey 38 miles an hour. "In this odd state of matter, light takes on a more human dimension; you can almost touch it," says Lene Hau, a Harvard University physicist. Hau led a team of scientists who did this experiment at the Rowland Institute for Science, a private, nonprofit research facility in Cambridge, Mass., endowed by Edwin Land, the inventor of instant photography. In the future, slowing light could have a number of practical consequences, including the potential to send data, sound, and pictures in less space and with less power.
Amazing Scanning Electron Microscope Photos Amazing Scanning Electron Microscope Photos All these pictures are from the book 'Microcosmos,' created by Brandon Brill from London. This book includes many scanning electron microscope (SEM) images of insects, humanbody parts and household items. These are the most amazing images of what is too small tosee with the naked eye. 2-2-11 An ant, Formica fusca, holding a microchip Surface of an Erasable Programmable Read-Only Memory silicon microchip Eyelash hairs growing from the surface of human skin The surface of a strawberry Bacteria on the surface of a human tongue Human sperm (spermatozoa) Nylon hooks and loops of Velcro Household dust: includes long hairs of cat fur, twisted synthetic and woolen fibers, serrated insect scales, a pollen grain, and plant and insect remains The weave of nylon stocking fibers The head of a mosquito Head louse clinging to a human hair Eight eyes (two groups of four) on the head of a tarantula Cut human hairs and shaving foam between two razor blades Mushrooms spores