Information Corner

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IPL: Indian Premier Leauge : T20-20 CRICKET

Forbes, as it does every year, has released its list of top executive salaries.

NAME | COMP | 1Yr. compensation | Rank@CEOs

Lawrence Ellison | Oracle | $192.9 M | 1

Nabeel Gareeb | MEMC Electronic Materials | $79.6 M | 6

John Chambers | Cisco Systems | $54.8 M| 19

Mark Hurd | Hewlett-Packard | $27.6 M| 56

Jen-Hsun Huang | NVIDIA | $24.6 M| 61

Samuel Palmisano | IBM | $24.3 M | 63

Wendell Weeks | Corning | $22.6 | 72

Joseph Tucci | EMC | 20 M | 87

William Sullivan| Agilent Technologies | $17.4 M| 102

Paul Otellini | Intel | $16.3 M | 109

Steven Jobs | Apple | $14.6 M | 120

Jonathan Schwartz | Sun Microsystems | $13.5 M| 130

1. If one wishes the table name should be singular instead of plural
Set the below configuration

ActiveRecord::Base.pluralize_table_names = false

2. If you want your model’s classname should represent a table of someother name

class Name < ActiveRecord::Base
   # by defualt it refers to "names" table in DB
   # Now let it refer to "nicknames"
   set_table_name "nickname"
end

3. If your primary key column is not named simply “id”, you can override this from within the class definition as well:

class Name < ActiveRecord::Base
     set_primary_key "nameid"
end

so when you want to save a record in DB (you must still use the id attribute to do so)

name_obj = Name.new
name_obj.id = 'N999'   #use the same   format this is eqivaled in saying name_obj.nameid='N999'
name_obj.save

but while accessing such record

print name_obj.nameid  # gives a result of "N999"

Google researchers say they have a software technology intended to do for digital images on the Web what the company’s original PageRank software did for searches of Web pages.

At the International WWW Conference in Beijing, two Google scientists presented a paper describing what the researchers call VisualRank, an algorithm for blending image-recognition software methods with techniques for weighting and ranking images that look most similar.

Although image search has become popular on commercial search engines, results are usually generated today by using cues from the text that is associated with each image.

Despite decades of effort, image analysis remains a largely unsolved problem in computer science, the researchers said. For example, while progress has been made in automatic face detection in images, finding other objects such as mountains or tea pots, which are instantly recognizable to humans, has lagged.

“We wanted to incorporate all of the stuff that is happening in computer vision and put it in a Web framework,” said Shumeet Baluja, a senior staff researcher at Google, who made the presentation with Yushi Jing, another Google researcher. The company’s expertise in creating vast graphs that weigh “nodes,” or Web pages, based on their “authority” can be applied to images that are the most representative of a particular query, he said.

The research paper, “PageRank for Product Image Search,” is focused on a subset of the images that the giant search engine has cataloged because of the tremendous computing costs required to analyze and compare digital images. To do this for all of the images indexed by the search engine would be impractical, the researchers said. Google does not disclose how many images it has cataloged, but it asserts that its Google Image Search is the “most comprehensive image search on the Web.”

The company said that in its research it had concentrated on the 2000 most popular product queries on Google’s product search, words such as iPod, Xbox and Zune. It then sorted the top 10 images both from its ranking system and the standard Google Image Search results. With a team of 150 Google employees, it created a scoring system for image “relevance.” The researchers said the retrieval returned 83 percent less irrelevant images.

Mr. Shah said there had been a number of technology demonstrations by Google Labs researchers, such as a project in 2005 that used machine learning techniques to recognize the gender of a person in an image. However, the company has been slow to deploy its research, he said.

An experienced team of PhDs, software engineers, and former entrepreneurs, hailing from top universities throughout the world such as Harvard, Indian Institute of Technology (IIT), Peking University, and Princeton, has launched the public beta version of iSeeCars.com after having it in alpha for several months for testing and user feedback. iSeeCars.com is a revolutionary new Web2.0 search engine for used cars that gives consumers a powerful way to search for cars for sale across the Web and to discover and find the right car at the right price more easily, quickly and smartly. iSeeCars.com automates many of the manual, time-consuming steps that a consumer typically goes through today in the online search process. site: http://www.iseecars.com/

“With just one click, users of iSeeCars.com will be able to see used car listings from thousands of websites such as car classifieds sites like Craigslist, Cars.com, and Google; newspaper sites like New York Times and Boston Globe; and auction sites like eBay along with many local dealership websites,” said Jim Lee, a Co-Founder. “Think of iSeeCars.com as the Google for car classifieds. We conceived of and developed iSeeCars.com as a result of our personal frustrations with our own experiences in having to go through the tedious effort of performing multiple searches on multiple websites such as Craigslist, Cars.com, Autotrader and in having to spend an enormous amount of time manually combing through the car classified listings looking for the right car deal.”