The stereotypical scientist is a white-coated, bad-hair-day man who absently wanders around a university campus making obscure chalk marks on any convenient
blackboard. This cliché has been hammered home by TV and movies until recently. Films like A Beautiful Mind have broken that mold, and all to our benefit.
What scientists do is conceptually simple—it is the details of how it is done that make the process appear complex. The basic steps of science are:
Observe a series of events you wish to study.
Propose a reason (hypothesis) for why these events happen.
Predict from the hypothesis what would happen with a changed element.
Test your hypothesis by running the experiment.
If the experiment validates your hypothesis, you are now one step towards a theory. Continue testing to strengthen your hypothesis. If the experiment disproves your
hypothesis, revisit the first step and create a new hypothesis. The famous quote for the latter situation is: "Another beautiful theory destroyed by an ugly fact." But another
quote, from the British physicist Lord Kelvin (1824-1907), illustrated the importance of mathematics to the scientific method: "When you can measure what you are speaking
about and express it in numbers, you know something about it."
The computer's ability to manipulate numbers rapidly has brought major benefits to science. At first computers were simply used to take measurements from experiments and
determine their statistical significance. Over time, this number manipulation became intensive number crunching, used for things like generating graphs and comparing
experimental measurements to the predicted results. Later, computers were connected directly to measuring devices to speed up the whole process of capturing measurements
accurately and to automate the transformation of measurements into numerical equations or graphs.
From Calculations to Simulations
The next step in the evolution of how computers are used in science was to create numerical experiments.
Extending Enterprise Value with Web 2.0 In this webcast we will talk about how to simply build and quickly remix Web 2.0 applications and the role of the IT department and how they support mashups. We will discuss how IBM can help IT teams adapt existing enterprise systems as well as develop unique ones that can support end user driven mashups in a reliable, scalable and secure way. We will highlight a simple scenario adapting an enterprise information source for mashups and how to test it. We will also cover how IBM can help you build agile, fast and simple web applications based on dynamic scripting languages that dramatically reduces development time. Wednesday, September 24, 2008 - 12pm PT / 3pm ET
2008 International Mathematica Conference Dr. Dobb's interviews Wolfram Research's Theo Gray, co-founder and Director of User Interfaces, and Roger Germundsson, Director of Research and Development, about the upcoming 2008 International
Mathematica Conference.
In this volume of Best of BYTE, we explore the emergence of some heuristic algorithms. Although we have only scratched the surface of this intriguing subject, we hope we've suggested the potential of the synthesis of heuristics and algorithms.
Understand C/C++ code in less time. A new team member ? Inherited legacy code ? Get up to speed faster with Crystal Flow for C/C++. Code-formatting improves readability. Flowcharts are integrated with code browser. Export flowcharts to Visio.
