[ Wed: 4/26/00 | Tues: 4/18/00 | 4/10/00 | 4/3/00 | 3/27/00 | 3/20/00 | 3/6/00 | Thur: 2/10/00 | Wed: 2/9/00 | 2/7/00 ]
4/26/00 - Visual Basic: Object-Oriented or just Object-Based?
Wyomissing High School
The Visual Basic programming language is not taken seriously by everyone, especially object-oriented programming (OOP) purists. After an overview of the current incarnation of Visual Basic (v. 6), we will examine the extent to which it is an OO language. It does support encapsulation, polymorphism, and inheritance. And, with version 7 coming next year, it promises to deliver everything you expect from C++ or Java. It is not the BASIC you may remember playing with as a youngster.
4/18/00 - Out, Out Damn Knot
You go to the closet to pull out that extension cord that has been buried under years of memories. It is a big tangled mess that takes you ten minutes untangle. You are the victim of random knotting.
Some knots are easier to tie and, thus, more likely to occur in your extension cord. This is one of many ways to measure the complexity of a knot. Another strategy is to find the position of a certain knot that is optimal in some regard (e.g. it takes the fewest number of "sticks" or the least amount of rope to tie). We will explore some measures of complexity, the relationships between these measures, and an application of optimal knots to molecular biology. We will also discuss the role of computer simulations in measuring spatial properties of knots.
4/10/00 - Pattern Recognition: Learning from Experience
Hilary Holz, '84
AccessAbility Internet Services, Inc.
Recognizing patterns is a major component in decision-making. For example, a therapist learns to recognize patterns of behavior in his patients, and a chess player learns to evaluate board configurations and patterns of play in her opponent. Pattern recognition is a field of study, originally part of artificial intelligence, devoted to the question of how patterns can be analyzed and used. Modern pattern recognition techniques attempt to extract the essence of a decision-making problem from a set of examples, and thus can be said to learn from experience. Hilary Holz, Class of 1984, will discuss how pattern recognition facilitates and automates intelligent behavior.
4/3/00 - Computing 1759 to February 14, 1946
David Allan Grier
Assistant Professor of Statistics and International Affairs
George Washington University
Before computers were machines, they were people. They were people who were bright and hardworking, yet were not full fledged scientists or mathematicians. Initially, they were students and wives but eventually, they became a subclass of people who lacked the connections or resources or social standing to aspire to a scientific career. They were often women or Jews or African-Americans or recent immigrants. For them, the hard work of computing was the best opportunity for them to play a part on the public stage. This talk will look at several organized computing groups and show how they represent the influence of industry on scientific practice. In particular it will look at computing groups from the Paris Observatory (1759), the American Almanac (1850), the Aberdeen Proving Ground (1917), Iowa State University (1923) and the WPA (1938). Among the computers discussed are Maria Mitchell, Elizabeth Webb Wilson, Mary Clemm and Gertrude Blanch.
3/27/00 - The Promise and Problems of Artificial Intelligence
Stephen Hildebrand, '99
"In about fifty years' time it will be possible to program computers ... to make them play the imitation game so well that an average interrogator will have no more than 70 per cent. chance of making the correct identification after five minutes of questioning."
-Alan Turing, 1950, "Computing Machinery and Intelligence"
In 1950 Alan Turing made a conjecture that has proven to be one of computer science's most controversial subjects -- that man could create machine intelligence that would be indistinguishable from human intelligence somewhere around the year 2000. Well, it's Y2K, has Turing's prediction come true? Stephen Hildebrand, Class of 1999, will discuss the potential of artificial intelligence and add some insight into the challenges of creating software that can meet Turing's challenge.
3/20/00 - The Next Killer Internet Application On-Line Education
Karl M. Kapp, '89
Bloomsburg University's Institute for Interactive Technologies
"The next big killer application for the Internet is going to be education. Education over the Internet is going to be so big that it is going to make e-mail usage look like a rounding error."
-John Chambers, President and CEO Cisco Systems
The design, development, delivery and evaluation of education over the Internet is the focus of the field of "Instructional Technology." Karl Kapp, a Dickinson College alumni, will discuss the work that Bloomsburg University's Institute for Interactive Technologies (IIT) does in the area of converting traditional stand-up training to multimedia-based web training. Karl will highlight how the Institute uses Cold Fushion, SQL Server, HTML, Macromedia's Flash, Dreamweaver, and Coursebuilder to develop interactive web-pages focused on educating corporate employees at such companies as AT&T, Bell Atlantic, and CIGNA Healthcare.
3/6/00 - An Introduction to the Perl Programming Language
Rennselaer Polytechnic Institute
The talk will begin with an overview of the features of Perl. I will then discuss scalar variables and operators, contrasting them with arrays and list operators. I will also cover some of the basic control structures of the language and dissect a few example programs to highlight some of the differences between Perl and other procedural languages. Finally, I will describe the Common Gateway Interface (CGI), and show how Perl can be used to create CGI scripts that process simple HTML forms.
THUR: 2/10/00 11:00 - Sums of Squares and Cubes
We illustrate the interplay between algebra, geometry, and number theory by investigating two famous number-theoretic problems:
1. Can we express a number as the sum of two squares?
2. Can we express a number as the sum of two cubes?
Questions of this sort date back to the ancient Greek algebraist Diophantus of Alexandria, and are still being actively studied today.
WED: 2/9/00 - Dynamical systems, continued fractions and the Fibonacci sequence
Michigan State University
In this talk we will introduce the notion of a discrete dynamical system. We will define periodic points, fixed points, itineraries and chaos. We will then study a particular dynamical system, the Gauss map. We will show how it is related to continued fractions and the Fibonacci sequence.
2/7/00 - A simple data compression algorithm (Huffman's algorithm)
University of Iowa
Any data (a text file, for instance) can be viewed as a sequence of characters, and each character can be represented as a sequence of 8 bits. The idea of data compression is to use fewer than 8 bits to encode common characters such that the overall number of bits in the compressed data is small. Compression is necessary to save disk space or to speed up transmission of data over communication lines.
We start this lecture by reviewing some background on representations of characters as sequences of bits. Next we present a simple yet elegant encoding technique for compressing data, called Huffman coding. The idea behind Huffman coding is simply to use shorter sequences of bits for more common characters and longer sequences of bits for less common characters. Finally we discuss some advantages and disadvantages of Huffman coding.