Drake University's Virtual Reality program could someday rival that of Iowa State. The recent retirement of Ken Kopecky seemed as if it would cripple the Virtual Reality program at Drake University, but the hiring of Timothy Urness, PhD, has given the Drake Mathematics and Computer Science department a huge boost. Adding to the all star cast of Dan Alexander, Luz DeAlba, Alex Kleiner, Lawrence Naylor, David Oakland and Michael Rieck, Tim Urness brings to the table experience in Scientific Visualization, Computer Graphics and Virtual Reality. It is a very exciting time for the Drake University Mathematics and Computer Science Department.
Drake Mathematics and Computer Science News
Professor DeAlba to give Stalnaker Lecture on September 18
Luz Maria DeAlba will give the annual Luther W. Stalnaker Lecture at Drake University on Tuesday, September 18. The lecture titled "Combinatorial Matrix Theory: Origins and Applications," will start at 7 p.m. in Sheslow Auditorium in Old Main, 2507 University Ave. A reception will follow in Levitt Hall, Old Main. The lecture and reception are free and open to the public.
Professor Baker Publishes on Mathematics Education
Professor Baker recently published a paper entitled "Schema Thematization: A Framework and an Example", by Laurel Cooley, Maria Trigueros, and Bernadette Baker. It is published in the Journal for Research in Mathematics Education, Vol 38, No 4, July 2007.
Professor Afrin Naz Joins Faculty
We are pleased to announce that Afrin Naz has recently joined the faculty in the Department of Mathematics and Computer Science. Professor Naz received her Ph.D. from the Department of Computer Science and Engineering at the University of North Texas in Denton. She holds bachelors and masters degrees from Dhaka University in Bangladesh and an M.S. in Computer Science from Midwestern State University in Wichita Falls, TX. Her research interests include computer architecture, parallel and distributed systems, compilers and embedded system designs.
Math and Computer Science Students Participate in DUSCI Summer Research
Zac Oler, Jon Botts, and Maren Mann participated in the 2007 Drake Undergraduate Science Collaborative Institute (DUSCI) Summer Undergraduate Research Program. Participants in the program are advised by a faculty member and conduct research over a span of eight weeks during the summer. Zac developed a simulation and visualization of a magnetic energy system, Jon researched matrix theory, and Maren worked on molecular modeling in a virtual reality environment. Zac and Maren were advised by Professor Urness. Jon was advised by Professor DeAlba.
Professor Urness Presents Architecture Education Paper
Professor Urness presented the paper "Teaching Computer Organization/Architecture by Building a Computer" at the 2007 Workshop on Computer Architecture Education held in conjunction with the 34th International Symposium on Computer Architecture. The paper is based off of the activity he conducted as a part of teaching CS 172 during the spring semester. The activity was paid for by a grant from the Center for Digital Technology and Learning.
Drake Students Win Best Research Paper Award
Skyler Nesheim and Luong Hoang won the award for best undergraduate paper at the 40th Midwest Instruction and Computing Symposium, hosted at the University of North Dakota. Their paper, "Creating an Object-Oriented Network Simulator" was supervised by Professor Rieck. View the official Drake press release by clicking here.
Professor DeAlba honored as 2007 Stalnaker Lecturer
Professor Luz DeAlba was appointed the 2007 Stalnaker Lecturer at the annual Drake University Honors Convocation held on April, 18th. The Stalnaker Lecturer is recognized as an influential member of the faculty at Drake University, particularly in the area of scholarship. In the fall of 2007, Professor DeAlba will present her contributions in the area of matrix theory in a lecture open to the public.
Drake Students Win Math Contest
Drake University won the 13th Iowa Collegiate Mathematics Competition held at Grinnell College on March 10. There were 25 teams of undergraduate students from colleges and universities throughout Iowa competing. The students comprising the Drake team were Luong Hoang, Quentin Roper, and Zach Kertzman. The team was organized by Larry Naylor in the Department of Mathematics and Computer Science. The competition is sponsored by the Iowa Section of the Mathematical Association of America.
Showing posts with label Computer Science. Show all posts
Showing posts with label Computer Science. Show all posts
Friday, October 12, 2007
Brute Force Sorting Algorithms
The brute force sorting method is the simplest of the design strategies and in most cases the easiest to apply. The brute force approach is used for many algorithmic tasks such as finding the largest numerical value in an array and finding the sum of n numbers. Although the brute force approach is very costly as it must exhaust all items in a list, it is sometimes the only solution and therefore the cost is acceptable. Let us explore some different brute force sorting algorithms and take a closer look at their properties.
The Problem:
Given a list of n orderable items in an array, rearrange them in increasing order.
Selection Sort
Selection sort is the simplest of the sorting algorithms. It begins by scanning the entire array for the smallest element. This element then gets swapped with the element stored in the first position of the array. Then it again scans the list, starting with the second element for the next smallest element, swapping it with the element in position two. This process continues until all n elements have been arranged in increasing order. Selection Sort is a O(n^2) algorithm in all cases (best, worst, average). This means for n elements in an array it will take n^2 steps to complete the sort.
Bubble Sort
Bubble Sort begins by comparing the first two elements in the array. If element two is less than element one, the elements are swapped. Next, elements two and three are compared and swapped if need be. This process continues until the array is sorted. Essentially Bubble Sort compares adjacent elements and swaps them if they are out of order. After a few iterations the algorithm will "Bubble Up" the largest element to the last position. Bubble Sort is also a O(n^2) algorithm for all cases (best, worst, average). An example of the worst case would be a decreasing array.
The Problem:
Given a list of n orderable items in an array, rearrange them in increasing order.
Selection Sort
Selection sort is the simplest of the sorting algorithms. It begins by scanning the entire array for the smallest element. This element then gets swapped with the element stored in the first position of the array. Then it again scans the list, starting with the second element for the next smallest element, swapping it with the element in position two. This process continues until all n elements have been arranged in increasing order. Selection Sort is a O(n^2) algorithm in all cases (best, worst, average). This means for n elements in an array it will take n^2 steps to complete the sort.
Bubble Sort
Bubble Sort begins by comparing the first two elements in the array. If element two is less than element one, the elements are swapped. Next, elements two and three are compared and swapped if need be. This process continues until the array is sorted. Essentially Bubble Sort compares adjacent elements and swaps them if they are out of order. After a few iterations the algorithm will "Bubble Up" the largest element to the last position. Bubble Sort is also a O(n^2) algorithm for all cases (best, worst, average). An example of the worst case would be a decreasing array.
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