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Archive for the 'Ph.D. and ITESM' Category
This is an EXCELLENT document I’ve found over the net some years ago about how to become a successful and respectable IEEE author… It is hilarious indeed, and worst of all, it is EXTREMELY close to reality… go check for yourselves and have some fun!
Do you want to become an IEEE author?
This time I want to introduce you a jewel I found while browsing the web looking for XML-RPC information for one of the classes I lecture. The book is called “Processing XML with Java” and it’s written by Elliotte Rusty Harold. The whole book is available online for FREE here (–LEGALLY–), so… if you’re looking to increase your XML + Java knowledge for free…. this might well be one of your best opportunities to do it. As always, if you like it, please buy it [Amazon, Barnes & Noble].
Enjoy the reading! 
A while ago, I was cleaning up a little bit my workplace when I suddenly stumbled upon this incredible sheet of paper….. it contains a conversation between Jakovo and I, during a Logic and Probability class (lectured by Dr. Raul Monroy) we took while studying our Master’s Degree… it neatly reflects our desperation and frustration about don’t understanding a thing after “Hi, my name is Raul Monroy and I will be your professor for this class” and being about two classes away from the only exam of Logic we were going to have… check it out and have fun!
In this photo, we can see that ITESM really loves the iPhone… but remember: any similarity between this two photos… is a pure and mere coincidence!
In this webpage www.freetechbooks.com you can find hundreds of free and legal e-books about Computer Science, Programming, Mathematics, Electronics, Operating Systems, Open Source, etc.
Enjoy your reading!!! 
Tittle: Data Mining Applied to Acoustic Bird Species Recognition
Authors: Erika Vilches, Ivan A. Escobar, Edgar E. Vallejo and Charles E. Taylor
Abstract: In this work we explore the application of data mining techniques to the problem of acoustic recognition of bird species. Most bird song analysis tools produce a large amount of spectral and temporal attributes from the acoustic signal. The identification of distinctive features has become critical in resource constrained applications such as habitat monitoring by sensor networks. Reducing computational requirements makes affordable to run a classifier on devices with power consumption constraints, such as nodes in a sensor network. Experimental results demonstrate that considerable dimensionality reduction can be achieved without significant loss in classification efficiency.
Conference: 18th International Conference of Pattern Recognition 2006 (ICPR 06), 20 – 24 August 2006, Hong Kong
Publisher: IEEE
Year: 2006
Download link: Data Mining Applied to Acoustic Bird Species Recognition
KEEL (Knowledge Extraction based on Evolutionary Learning) data mining software, is a tool to assess evolutionary algorithms for Data Mining problems including regression, classification, clustering, pattern mining and so on.
It contains a big collection of classical knowledge extraction algorithms, preprocessing techniques (instance selection, feature selection, discretization, imputation methods for missing values, etc.), Computational Intelligence based learning algorithms, including evolutionary rule learning algorithms based on different approaches (Pittsburgh, Michigan and IRL, …), and hybrid models such as genetic fuzzy systems, evolutionary neural networks, etc. It allows us to perform a complete analysis of any learning model in comparison to existing ones, including a statistical test module for comparison. Moreover, KEEL has been designed with a double goal: research and educational.
For additional information, their Web page is: http://www.keel.es
I enjoyed these news because I was there, at the ICDM 07, presenting a paper, in Omaha Nebraska (Pictures to be posted soon). Enjoy!
“The title of the first paper listed on the conference schedule says this is no Mary Kay sales meeting: “Succinct Matrix Approximation and Efficient k-NN Classificaton.”
Just to get to Omaha to present papers with titles like that was a challenge. Fewer than 20 percent of the papers submitted were accepted by a judging committee.
The meeting is the seventh annual IEEE International Conference on Data Mining. Last year’s conference was in Hong Kong. Next year’s will be in Pisa, Italy.
“This is a platform to exchange research findings,” said Yong Shi, a University of Nebraska at Omaha professor who is a co-chairman of the convention.
“Everything is new this year,” Shi said regarding the difficult judging that rejected 80 percent of papers submitted.
In terms of economic impact for Omaha, this is far from either the College World Series or Berkshire Hathaway’s annual meeting. Just 320 people will be meeting Sunday through Wednesday at the Embassy Suites Hotel in the Old Market.
Seventy percent of those coming are academics, the rest practitioners, Shi said. They will talk about using computers to dig deeper into data, and how to slice and dice information to make it more useful in a variety of fields.
Data mining is what allows a business to target its advertising more closely to those customers likely to be interested in its products, or a credit card company to spot ID theft or fraud by identifying card uses that are out of a customer’s pattern.
That’s called “business intelligence” these days.
“The driving force of business intelligence is data mining,” said Shi, who does his academic work at the Peter Kiewit Information Science, Technology and Engineering Institute.
Shi said there are “huge” applications, less noticed by most people, in medical research, for example in HIV research. Gregory Piatetsky-Shapiro, a member of the conference’s steering committee, said he had done work on brain tumor research through data mining.
Another potential field, Piatetsky-Shapiro said, is personalizing medicine by, for example, creating a prescription designed to meet an individual patient’s genetic makeup. Studies show people with similar diseases and similar treatments can get different outcomes because of their “genetic signatures,” he said.
Still, the hot fields are business related, Piatetsky-Shapiro said. Companies are digging into the information of people who have laid out their lives on online social sites, he said.
“Facebook and MySpace both look at ways to present more targeted ads.”
Asked if he could point to a success that came about as a result of a conference like this, Piatetsky-Shapiro had a one-word answer: Google.
Google’s founders, Sergey Brin and Larry Page, attended such conferences in the 1990s, he said.
“I wouldn’t claim that just because of attending conferences they founded Google,” he said, but Google resulted from developing the results of academic research.
So why do 320 people from 47 countries converge on Omaha when, it would seem, they could gather online and exchange their research and comments?
“Some want to visit beautiful Omaha, Nebraska,” said Piatetsky-Shapiro, who runs a consulting service on data mining in Brookline, Mass.
People attend to see each other, he said.
“To visit interesting places, network, see friends you haven’t seen in a year. . . . Even nerds like us like to go to these conferences."”
Taken from: http://www.omaha.com/index.php?u_page=1208&u_sid=10168755