text:
Poor Richard once wrote that "a plowman on his feet is taller than a nobleman on his knees." By this Ben Franklin meant that a solvent plowman stands taller than a beggared nobleman (The Autobiography of Benjamin Franklin 181). Applying this wisdom to debt is a reminder that during the revolutionary period not all wealthy men were created equal. The landed gentry were the Tories (Parrinton, chapter 2). They bent the knee to King George because they owed their entire estate to the crown. Likewise, with perhaps one notable exception, the elite merchants of Massachusetts, the aristocracy, were almost all loyalists (Frankel: chapter 6, last paragraph). But the native businessmen, the Yankee traders, were the sons of liberty. They were willing to stake their lives, their fortunes and their sacred honor for independence. Hence, we have a financial resume for Warren Buffett's political leanings and for his willingness to legitimize both corruption and tyranny.
Even more pointedly, though, we have an object lesson in a catechism that at best, Buffett, can be said to have forgotten; that is, all "the wealthy" are not alike. The "rich" cannot be categorized by income alone. To say "the rich" or "the wealthy" is from every perspective a demagogic use of stereotype and prejudice.
Who are the rich? Are they investors? You know, are they guys who were once like Buffett, guys who piled all their savings into a risky venture and then rejoiced when their ship came in laden with treasures? Or are the "rich" the monarchs, agents of the state, Tories, who take their cut for king and country according to divine right?
Is it a coincidence that WashingtonD.C.has America's highest income while not having the highest GDP? As agents of ignorance demagogues and tyrants make their money on prejudice, Let's look at this "the wealthy" shell game.
If all the rich are greedy and evil, then all the poor are lazy and shiftless.
If all the rich live to oppress the poor, then all the poor are undeserving, without morals, and born to be ordered by their betters.
These are obviously all lies. The first set was the coin of the Greek and Victorian; the last is the warp and weft of today's Marxist cloaks of covetousness. Whether the lies are about rich or poor, it's all senseless, self-serving bigotry. It's Ignorance calling itself wisdom because so many fools are willing to dispense it.
Anyone can play the shell game. Shall we go a round?
Who wakes early to oppress the poor? Who works tirelessly throughout the land in every city and workplace to exploit the weak and helpless? Who demands more and more from the working man and offers no solace, relief or return? Is it the rich or the IRS?
See how sickly thin these stenotypes are? But they're really fun! Let's play again:
Do you know who's ruthlessly oppressing the working man? Our federal government, that's who. Behind's its mask her agents sell us for bottles of gin, and trade us abroad like stolen Super Bowl rings. Think about it. Who's demanded 12% and 15% of every paycheck you've ever earned and offered you nothing in return, not interest on investment, not the right to bequeath to your children, nothing. And these barons of "democracy" dare call it "Social Security"? That's right, your life's savings is called an "insurance" policy. Insurance for whom? No us, that's for sure. And as if not bothering to offer us even the most meager return on our investment is not thievery enough, the alien in Uncle Sam's stomach rears its toothy grin and inflates the dollar of our retirement dole until it is but as a tithe of the dollar of our initial "contribution."
To break the chains of all such mad prejudice then, let us refuse all stereotype and bigotry and consider specifics.
If Bill Gates or Steve Jobs is too rich, let's give back our I-phones, desktops, and I-pads. Did we get exploited by our MP3 players? Did our wide screen TVs oppress us? Surely, then not every rich business man is a greedy self-serving enemy.
The motivation to gamble on precious silk and spices from lands far away is much reduced when the monarchs and the aristocracy take all the profit. Will the king make up the difference for the loss of investment when the moon goes red and the investor's ship is wracked on the rocks? Only if it's a political donor; only if he is of the aristocracy. Otherwise, the ordinary investor, the Yankee trader, will, like Gibson Guitar, be taxed again for its impact on the natural environment. But who cares? Who needs tea, silk and spices anyhow? Who needs Gibson guitars? Who needs high definition TV? As long as no one is getting rich, that's all that matters.
Independenceof mind, independence of wealth, what else is independence? How can we deny this to one and not deny it to all? If we give up the path to financial independence found in frugality and good judgment because we are jealous of others, then we are all enslaved. We will become slaves because we've lost our soul to covetousness. Like Buffett, we will have sold our birthright of liberty for a mess of potage. When we've killed the free market, we are all slaves: without property, without anything we can call our own, without rights, –chattel of a state of lies. The soul of a man is the first victim of his ignorance and bigotry.
Now back to specifics on one rich man; Warren Buffett doesn't offer enlightenment. He doesn't offer a pathway to social justice. The poor, blind old man has offered a knife to tyrants with which carve out the soul of our liberty. He is not to be heeded; he is to be pitied.
A country based on what is not right can't prosper… ever. A nation is either growing or dying. The citizen of the free market may be a Tory or one of the Sons of Liberty. We know the first if he wields the bludgeon of taxation and monopoly; we know the second if he is an agent of our material liberty. It is to the everyone's advantage for the sons of liberty, rich or poor, to have equal access to their means.
UPDATE 10/01/2011: More Tory Talk from Buffett
Although it is difficult to get good video on cowering Tories during the revolutionary period, it is reasonable to assume they sounded something like Buffett did during this recent interview with Real Clear Politics:
Watch or read at your leisure.
Although much of the above has been tongue in cheek, sadly, their seems to be a palpable fear in Buffett's dodginess.
Update: 12?2/2011– Buffett is the truest Tory; he's a sellout
Peter Schwietzer's new book, Throw Them All Out, spells it out. Warren Buffet gave free advice on structuring bank bailouts while purchasing bonds in these same institutions. It is no wonder that Buffett will say anything the adminsitration tells him to.Tweet
Latest posts by Paul Benedict (see all)
- Voter Fraud 2012: Myth, Legend and Fact in St. Lucie Florida - December 3, 2012
- Petraeus' Mistress is a Weak Source on Benghazi Scandal - November 12, 2012
- Why the CIA is Leaking Libya: A Time Line of Heroism - October 29, 2012
- Media Deceit Undermines U.S. Democratic Process - September 29, 2012
- Fact Check: The Obama Administration LOST 500,000 Manufacturing Jobs - September 20, 2012
- The Affordable Heath Care Act's "Papa John's Loophole" - August 13, 2012
- Voter Fraud and Mad-Elite Disease Spreads to Michigan - August 10, 2012
- A Free Market is Not Social Darwinism! - April 5, 2012
- Money is Common Sense Part III: the Complexities of Fiat Currencies - March 11, 2012
- Money is Common Sense II: All Paper Money is Debt - February 18, 2012
- Money is Common Sense Part I: Definitions - February 1, 2012
- Newt Gingrich: Too Corrupt for the Presidency - January 27, 2012
- Warren Buffett is a Poor, Blind, Sad, Old Man or Worse - September 21, 2011
- Closing California's State Parks: Communism Fails Again - September 7, 2011
- Red States Beware: You've Left an Enemy in the Rear - November 8, 2010
- Soak the Rich: Even Rates for All Taxpayers - September 26, 2010
- Tea Party Anger on the Border - July 30, 2010
- Wrinkles on the GOP's Health Care Solutions for the Brain and Brow - March 27, 2010
- Government Reform 101 B: Barney Frank is Right on the Filibuster - January 20, 2010
- Federal Reserve Policy Transfers Municipal Pension Wealth to Banks Too Big to Fail - January 6, 2010
- Palin and the Culture of Liberty - August 18, 2009
- The University of California Fights for its Life - July 17, 2009
- Rumors of California Prop. 187's Death Highly Exaggerated - July 9, 2009
- Thoughts on Independence: Conservative and Libertarian - July 3, 2009
- Reforming CalWorks SSI and Food Assistance Helps Everyone - July 1, 2009
- A Budget Compromise that Could Drill California - June 25, 2009
- Prize Fight! The Terminator vs. the U.C. Research Budget: a 170 Million Dollar Purse - June 17, 2009
- One Billion Stimulus Dollars to Save California's Universities - June 12, 2009
- California's Rejection of "Mark of the Beast" I.D. Could Save Fifty Million per Year - June 10, 2009
- California's Excessive Liberty Still Shines As Marriage Endures - May 26, 2009
- Midwestern Tea Parties, the Militarization of the Conservative Movement, and the Courts - April 22, 2009
- Liberty Counsel's Pro Marriage Brief Unpersuasive - April 8, 2009
- Bernanke and Geithner's Plan is NOT the Banking Act of 1933 - March 27, 2009
- PRSST and Why Free Enterprise "Failed" the Loan Markets - March 23, 2009
- Dave Ramsey, Cato Institute's 6.2% Plan, and Transforming Social Security - March 5, 2009
- How Bernanke Should Have Answered Dodd - February 25, 2009
- Ending Social Security by Applying Payroll Taxes to Primary Residences - February 21, 2009
- How to End Social Security in Our Lifetime — Jack Kemp Style - February 15, 2009
- Ending Social Security with the Youth Vote - February 13, 2009
- Financial Stimulus, Bank Bail Outs, and Ending Social Security - February 4, 2009
- Social Security and Bernie Madoff Style Pain - January 27, 2009
- Social Security, Ponzi Schemes, and the Bush Bullet We Didn't Dodge - January 21, 2009
- The Immaculate with Belief, Hope, and Love - December 23, 2008
- Pastor Rick Warren's National Heresy - December 20, 2008
- Free Markets, Crashes, and Other Parables - October 15, 2008


text:
Plot Summary
In this adaption of Robert Heinlein's novel, we follow the adventures of a squad of troops as they fight in a war of survival against merciless alien invaders. Facing constant danger, they are the ones who have to do the thankless task of facing the enemy head on, and for the sake of humanity, they must prevail.- Written by Kenneth Chisholm <email@example.com>
Based upon the novel by Robert A. Heinlein, this 40 part computer animated series follows Johnny Rico, Carmen Ibanez, and Dizzy Flores as they wage war against the "Bugs". Divided into eight five episode mini-arcs, the story follows the book faithfully, yet adds some new material as well.- Written by Lee Thompson
The missions of a Mobile Infantry squad as they participate in a war of survival against a ferocious alien insectoid invader.- Written by Kenneth Chisholm
Be the first to contribute! Just click the "Edit page" button at the bottom of the page or learn more in the Synopsis submission guide.

subset: commoncrawl


text:
- Gifts
- Shop By Occasion
- Who's it for?
- Shop By Price
- Charms
- Shop By Category
- Shop By Theme
- Jewellery
- This Month's
- Personalised Gifts
- Point of Sale
This sterling silver bee charm necklace, comes with a heart-felt message, making it the perfect gift for your Mother.
This Mother necklace will be worn again and again, and the sentiment remembered each and every time. This deservedly popular sterling silver bee charm, has amazing detail, and always draws admiring glances.
If our featured message doesn't quite fit the occasion you are celebrating why not add your own message to this necklace, or create a cluster charm necklace with our with additional letter, gem or feature charms.
Charm dimensions: 21x18mm.
Chain Lengths: 40-45cm or 61cm.
Finish: Polished or Matte Satin.
Also available in Gold.
Your item has been added to the basket.Go to checkout >
View other items with this charm: Bee Charm


text: http://ubuntuforums.org – I had Ubuntu 12.04 with XFCE (Lubuntu) installed on my Acer netbook for a while until one day the left track pad button stopped working. For unrelated reasons, I wiped it clean and installed regular old Ubuntu 12.04 and attached a USB mouse (that I know to work). To my surprise, I still wasn't able to left-click. I also enabled touch click on the trackpad, but this didn't help either. I tried changing window managers to no avail. xev does not register any click at all. I've seen this issue discussed a lot, but it's usually in the context of an older version of Ubuntu or with an HP button-less (Hardware)


text:
The potential for major development agreements in 2015 to advance gender equality for the next generation.
Twenty years ago, tens of thousands of people gathered in Beijing for the Fourth World Conference on Women, where 189 governments made significant commitments to advance gender equality and the empowerment of all women, everywhere. As we reflect back on the unprecedented progress to translate the Beijing Platform for Action into concrete actions, this year's 20th anniversary and the 59th session of the Commission on the Status of Women offer an opportunity for us to look at how far we've come to advance gender equality, both here in the United States and around the world.
We have made concrete progress when it comes to achieving the Millennium Development Goals (MDGs), particularly in areas of health and education: the rate of maternal mortality has almost halved, and the global gender gap in primary school enrollment is nearly closed. But as much as this is a moment to celebrate shared progress, it's also a moment to realize our shared responsibility for moving forward: when it comes to fully achieving gender equality, the data, as clearly demonstrated by former Secretary Clinton's launch of the Full Participation Report this week, show we are "not there yet."
As the MDGs expire this year, and the global community comes together to agree on a new set of goals, this is a historic opportunity to define a common vision for the world we want to see in the year 2030 – a world where economies are far more inclusive and where we've ended extreme poverty; a world where we are stemming the impacts of climate change and have healthier oceans and forests; and a world where well-governed, peaceful societies are the norm.
To realize any of these goals, women and girls must be at the core of the development agenda. Greater gender equality means better outcomes for everyone. Girls' attendance in formal school during adolescence is correlated with later marriage, later childbearing, decreased fertility rates, and lower rates of HIV/AIDS. Education is not the only game-changer: when the number of women involved in political decision-making reaches a critical mass, their decisions lead to more inclusive results. And simply by empowering women farmers with the same access to land, new technologies, and capital as men, crop yields can increase by as much as 30 percent and feed an additional 150 million people. When we invest in women and girls, we see a ripple effect on her individual potential, as well as the potential of her family, her community, and entire society.
That's why the United States strongly supports gender equality and the empowerment of women and girls as a stand-alone goal. As Deputy Secretary of State Heather Higginbottom has emphasized, "advancing gender equality is among the most transformative goals the globe can set."
What will it take to achieve this goal? We must come together and focus our efforts where they can make the biggest impact. That means we end the pervasive problem of gender-based violence in all its forms, including child, early, and forced marriage, as well as female genital mutilation/cutting. We boost women's economic empowerment and promote their political participation and leadership. We ensure universal access to sexual and reproductive health and respect for reproductive rights. We fully integrate gender across all other goal areas, such as health and education. And our efforts must include not just some women and girls, but all women and girls, particularly those who have been pushed to the margins of society.
Secretary Kerry often says that what gets measured gets done. It's clear that data will be critical to the success of the post-2015 agenda. We need more sex- and age-disaggregated data to help guide our decisions about and how we allocate resources. Data will help us hold ourselves accountable and reveal how to best target and tailor our efforts. And it will add to the evidence-based case demonstrating concretely that advancing women and girls is both the right thing and the strategic thing to do.
Gender also has an important place in the Third International Financing for Development Conference, to be held in Addis Ababa this July. We know that women are key drivers of economic growth. Research shows that where gender gaps are narrow, economies are more competitive and prosperous; for instance, removing barriers that inhibit women's ability to fully participate in the economy, and closing the global gender gap in workforce participation, can boost GDP worldwide by up to 12 percent by 2030. A strong financing for development framework must reflect this reality.
We believe 2015 is an opportunity for another "Beijing moment"—one where the world comes together to advance women and girls, and by doing so advances an entire global agenda. Action today will translate into progress tomorrow – the kind of progress that benefits us all.
About the authors: Catherine Russell serves as the Ambassador-at-Large for Global Women's Issues, Tony Pipa serves as the U.S. Special Coordinator for the Post-2015 Development Agenda, and Daniella Ballou-Aares serves as the Secretary's Senior Advisor for Development.


text:
Rosalie Nolen.
Oct. 12, 2013
WASHINGTON - The Georgetown field hockey (2-11, 0-4 BIG EAST) team lost to Rutgers (8-5, 2-2 BIG EAST) in Piscataway, N.J. on Saturday by the final score of 5-0.
Rutgers scored three goals in the first half. Sophie Wright, a junior midfielder, scored her seventh goal of the season about 10 minutes into the game on a deflection off a penalty corner shot; the assist was credited to freshman back Sofia Walia.
Rutgers was then awarded a penalty stroke 23:10 into the game. Sophomore forward Nicole Imbraicao scored her second goal of the season on the stroke. The Scarlet Knights took a two goal lead into halftime.
Rutgers' Lisa Patrone, a senior forward, put the Scarlet Knights up 3-0 6:41 into the second half when she scored her first goal of the season. She was unassisted on the play.
Wright scored her second goal of the game, and was again assisted by Walia, when she deflected a penalty corner shot about halfway through the second half.
The Scarlet Knights got their fifth and final score about two minutes later on their second penalty stroke of the day. Senior back Laura Rose took the stroke and scored her fourth goal of the season on the play.
GU's Rosalie Nolen, a freshman, made eight saves on the day in addition to the five goals she gave up in 60:48 minutes of play. Freshman goalie Rachel Skonecki saw 9:12 minutes of action and made one save in relief of Nolen.
Georgetown was held to zero shot attempts for the second straight game.
The Blue & Gray return home to host No. 4 Connecticut on Fri., Oct. 18 at 2 p.m. at the University of Maryland's Field Hockey and Lacrosse Complex in College Park, Md. The University of Connecticut head field hockey coach Nancy Stevens recently became the all-time winningest coach in NCAA Division I history for field hockey, with a career record of 562-171-24, when the Huskies beat No. 14 Louisville, 6-0, on Fri., Oct. 11.
More Headlines
Hoya Field Hockey: 2014-2015 Video Highlights
The 2014 Field Hockey season, the first under Head Coach Shannon Soares, saw the Georgetown Hoyas...
Field Hockey Receives NFHCA Academic Awards
A total of 13 field hockey student-athletes were named to the 2014 SGI/ National Field Hockey...
Georgetown Field Hockey Earns Academic...
The Georgetown University field hockey program was recognized by Gladiator by SGI/National Field ...
Taylor Craig: 2014 Field Hockey Essay
Junior defender Taylor Craig writes on her experiences as a member of the Georgetown University...
Field Hockey Holds End of Year Banquet
The Georgetown field hockey team held its end of year Banquet, the first with Head Coach Shannon ...
Hideshima Wins Mazda Design Contest
Senior field hockey player Tori Hideshima (San Jose, Calif./Archbishop Mitty) has added another...
Field Hockey Announces Dates for Summer Camp
Georgetown Field Hockey Head Coach Shannon Soares has announced the dates and opened registration...
Graves-Brown Earns All-BIG EAST Second Team Honors
Sophomore Aliyah Graves-Brown (Harrisburg, Pa./Harrisburg Academy) earned All-BIG EAST Second...
Top Videos
DOWNLOAD SCHEDULE: Add to calendar
There are no upcoming events.
- Online Stores & Tickets


text:
Tags: design
All Things Educational: ATE June 2015
The 2015 Summer edition of ATE honors and salutes Dad's and their Daughtters.Standard / 8.25" x 10.75"Print: $2.40 Digital: $2.00
Monthly Issues: SUPERIOR DIGITAL July 2015
Exclusive INTERVIEWS, SUSTAINABLE FASHION and FASHION EDITORIALS from across the world | SUPERIOR is an international MAGAZINE featuring the creative…Standard / 8.25" x 10.75"Print + Digital: $38.20 Digital: $1.99
The Rhythmic Lounge Magazine June 2015
The Rhythmic Lounge Magazine is the print and digital platform for all creative talents (Musicians, Artists, Entertainers, and more!) From fine…Standard / 8.25" x 10.75"Print + Digital: $8.00 Digital: Free!
Estela Magazine: Issue XVII
The Swim Issue 2015Standard / 8.25" x 10.75"Print + Digital: $23.39
Spring/Summer fashion issue.Standard / 8.25" x 10.75"Print + Digital: $18.00 Digital: $3.99
Hooligans Magazine Issue 2, June 2015
Hooligans a is magazine featuring children's fashion, art and design. This quarterly print publication is full of editorials shot by talented…Standard / 8.25" x 10.75"Print + Digital: $40.60 Digital: $11.00
The Digital Book
The summer CMDC undergraduate course "DTC 338: Digital Publishing" at Washington State University focuses on the theories, production workflows,…Digest / 5.25" x 8.25"Print + Digital: $11.88 Digital: Free!
PANTA Magazine: PANTA Issue 6
PANTA is a tri-annual magazine about art, design, music and culture by the international start-up, Book a Street Artist. Our goal is to reposition…Standard / 8.25" x 10.75"Print + Digital: $23.40 Digital: Free!
Creatives Circuit©
Light reading informal carry-size magazine and conversation piece resource for the creatives community—artists, writers, photographers, graphic…Square / 8" x 8"Print + Digital: $4.80 Digital: $2.00
High Point Promotionals: High Point Preview, Spring 2015
Preview of Palu items on display at the High Point Furniture Market.Standard / 8.25" x 10.75"Print + Digital: $1.68 Digital: Free!


text:
Over The Shoulder Aiming ModMay 2, 2013 Full Version 10 comments
This is the unfinished version of my Over The Shoulder Aiming Mod.
This OTS Aiming Mod is a little and simple prototype for implementing the Over The Shoulder aiming typical of the modern TPS shooters in Max Payne 2.
Sadly due to heavy engine limitations, MP2 is from 2003, the only way to create this kind of aiming mode was to restrict the player to only two custom weapons specifically created for this purpose, and this means also that it's incompatible with other mods, every resource avaiable revolves around the ots aiming system so a dedicated mod is needed, we will have to deal with it. Same for possible bugs, this is the final version, on my pc there are no bugs but since the engine isn't extremely reliable and the ots system is complex some unwanted behaviour could happen on some pc, I can't do nothing about that, live with it.
This is the unfinished version of my Over The Shoulder Aiming Mod.
Any news? :D
Nope, at all, and most probably there will not be any before my Payne Evolution mod is released because it have higher priority.
OK! Thanks anyway! :D
CoDifying Max Payne 2? ...This is interesting and looks entertaining.
Where i can download this awsome mod ?
Happy new year to everyone! :)
Well modded, sir!
Question: Player character has 2 weapons only, but the enemy will come at you with such limited weapons or will they have wider arsenal? I think I have seen a mod in the past where you weren't able to pick up weapon from the grip of a fallen enemy soldier...
Player is restricted to only two weapons, enemies have all the standard arsenal, since your two weapons shares the ammo with the weapons of the enemies you simply pick up the magazines from the fallen enemies instead of their whole dropped weapon.
When you press the shootdodge button, what's going to happen? Will he do a non-bullet-time shootdodge or will he run/sprint? :D
Good idea, at the moment you simply roll, but after PEvo is released I will try to implement the sprint. :)
Promote Over The Shoulder Aiming Mod on your homepage or blog by selecting a button and using the embed code provided (more).


text:
Blake and Miranda Buy A House In Nashville
For many years now Blake Shelton and Miranda Lambert called Oklahoma their permanent home. With all their success they've decided to make a more permanent home in Music City.
For many years now Blake Shelton and Miranda Lambert called Oklahoma their permanent home. With all their success they've decided to make a more permanent home in Music City.
The talent and fights to grab them are heating up on 'The Voice.' Blake Shelton added one more to his team, convincing crooner Noah Lis to choose #TeamBlake.
If at first you don't succeed, try again. Jake Worthington returned to 'The Voice' after not making a team last season. This time, he had three coaches fighting to have him on their team after his beautiful rendition of the country classic 'Don't Close Your Eyes.
Tonight's the night. 'The Voice' returns with Blake Shelton and Adam Levine on NBC at 8.
Blake Shelton's latest single "Doin' What She Likes" is growing in popularity and steadily climbing the Country Music charts. The official video was released just a few days ago.
Viewers aren't the only ones disappointed that Cee Lo Green isn't returning to NBC's hit reality show 'The Voice.' Fellow coach Blake Shelton admits the decision makes him sad, too.
Shakira recently revealed that she and country's own Blake Shelton were collaborating in the studio, and now, she's dishing the details of the duet.
The 6th season of "The Voice" will premiere February 24th, after the Olympics. For this season Adam Levine and Blake Shelton have returned, but Shakira and Usher are back to fill in for Cee Lo Green and Christina Aguilera.
Blake Shelton shows off his dance moves in a new promo for 'The Voice,' calling himself 'Break it down Blake.' Although he like to sing, he says he 'really considers myself a dancer.' He may be the only one. Usher, who has some moves of his own 'doesn't 'think there's any hope.'
Miranda Lambert isn't the only person Blake Shelton has been seen kissing. Just in time for Valentine's Day, Taste of Country has put together a video of Blake's best 'Bromance' moments.
Today's Friday Fun Fact is Blake Shelton related. It is about his life before he was a judge on the hit NBC show 'The Voice.'
Blake Shelton and Sandra Bullock said goodbye to Jay Leno on his second to last night. Blake thanked Jay for treating all his guests as equals and Sandra got a little choked up saying her final farewell. To lighten the mood, Jay played 'Guess Blake's Drunken Tweets' with Blake and Sandra.


text:
Same as usual.. Please sign up online or call Robin. This class will be open to the public, I will update head count from the public as necessary.
Grillin & Chillin ($60 per person)
Fire-Roasted Shrimp Cocktail, Grilled Caesar Salad, Grilled Fusion Chicken, Grilled Smashed Potatoes, Grilled Fresh Pineapple with grilled pound cake. Without breaking a sweat!
We just grab a coffee and speak French. Some people have been coming every week for months... it creates a kind of warmth to the group.
— Rafaël, started French Conversation Group
Meetup members, Log in
By clicking "Sign up" or "Sign up using Facebook", you confirm that you accept our Terms of Service & Privacy Policy


text:
The present invention relates generally to the classification of items into categories, and more generally, to the automatic selection of different classifiers at different places within a hierarchy of categories. An exemplary hierarchical categorization method uses a hybrid of different classification technologies, with training-data based machine-learning classifiers preferably being used in those portions of the hierarchy above a dynamically defined boundary in which adequate training data is available, and with a-priori classification rules not requiring any such training-data being used below that boundary, thereby providing a novel hybrid categorization technology that is capable of leveraging the strengths of its components. In particular, it enables the use of human-authored rules in those finely divided portions towards the bottom of the hierarchy involving relatively close decisions for which it is not practical to create in advance sufficient training data to ensure accurate classification by known machine-learning algorithms, while still facilitating eventual change-over within the hierarchy to machine learning algorithms as sufficient training data becomes available to ensure acceptable performance in a particular sub-portion of the hierarchy.
1. A method for assigning computerized records into a predetermined hierarchy of predetermined categories, comprising the following steps:
(a) at a parent node in said hierarchy, automatically selecting which one of at least two classifiers available for use at that parent node will be used to assign records to categories within the parent node's subtree; and
(b) at a descendant node of said parent node, automatically selecting which one of at least two subclassifiers available for use at that descendant node will be used to assign records to subcategories within the descendant node's subtree;
wherein if a predetermined one of said classifiers is selected for said parent node, then a predetermined associated one of said subclassifiers will not be selected at said descendant node.
2. The method of
3. The method of
4. The method of
one said available subclassifier is a rule-based classifier and another said available subclassifier is a machine-learning based classifier, and
a selection of said rule-based classifier at said parent node eliminates the possible selection of said machine-learning based subclassifier at said descendant node.
5. The method of
6. The method of
7. The method of
8. The method of
9. The method of
10. A method for automatically assigning computerized records characterized by arbitrary feature vectors into a predetermined hierarchy of predetermined categories, comprising the steps:
(a) providing a training set of computerized records having known feature vectors each labeled with an assigned one of said predetermined categories;
(b) providing a human-authored rule-based classifier usable at any node of the hierarchy,
(c) using at least a first subset of said training set to perform an inductive computerized procedure at a given node of said hierarchy to thereby provide an associated candidate trained classifier at that node,
(d) using at least a second subset of said training set to perform a computerized evaluation of the performance of the rule-based classifier at said given node relative to that of the associated candidate trained classifier;
(e) if the computerized evaluation at the given node favors the rule-based classifier, assigning the rule-base classifier to the given node and also assigning the rule based classifier to all nodes descending from the given node, thereby defining a floor across said hierarchy below which said rule-based classifier is utilized and above which only trained classifiers are utilized, and
(f) otherwise, assigning the associated trained classifier to the given node and repeating steps (c) through (f) for at least two child nodes immediately descending from said given node.
11. The computerized method of
(g) providing a supplemental training set of labeled records including at least some additional records for at least one untrained node below said floor, and
(h) using said supplemental training set, repeating said steps (c) thorough (f) for said at least one untrained node.
12. The computerized method of
13. The computerized method of
14. A system for selecting classifiers used at individual nodes of a hierarchical classifier, comprising
at least two candidate classifiers;
a data store containing labeled records; and
a processor for using at least some of said labeled records to induce a trained classifier from a first candidate classifier and to select between said trained classifier and a predetermined second candidate classifier for use at a parent node of the hierarchy;
wherein the processor performs a subclassifier selection for a descendant node of said parent node based at least in part on whether said trained classifier was selected for use at said parent node.
15. The system of
16. The system of
17. The system of
one said available subclassifier is a rule-based classifier and another said available subclassifier is a machine-learning based trained classifier, and
a selection of said rule-based classifier at said parent node eliminates the possible selection of said machine-learning based trained subclassifier at said descendant node.
18. The system of
19. The system of
20. The system of
21. The system of
[0001] Categorization is the problem of assigning items (e.g. documents, products, clients, etc.) into categories based on features of the items (e.g. which words appear in a document), and possibly subject to a degree of confidence. For example: vehicle X which has the features
[0002] number of seats=55
[0003] color=yellow
[0004] belongs to the category "school buses" with probability 95%.
[0005] The field's terminology has a number of common synonyms:
[0006] categorization=classification, prediction
[0007] features=attributes, properties
[0008] (sub)categories=(sub)classes, (sub)topics
[0009] confidence=degree of belief, certainty, probability
[0010] items=cases, examples
[0011] machine learning=induction.
[0012] Categorizers may be built manually by people authoring rules/heuristics, or else built automatically via machine learning, which induces a categorizer based on a large training dataset of items, where each item is labeled with its correct category assignment. Typically, the larger the training dataset, the better the classification accuracy, however, it usually costs something (human labeling effort) to gather the training set. In the earliest stages of collecting a training set, human-authored rules will typically have better accuracy than machine learning; however, as more training data becomes available, the accuracy of machine-learning algorithms improves (since they learn from that additional training data), and eventually may surpass what is practical with human-authored rules.
[0013] Examples of machine learning include the well-known naive Bayes and C4.5 algorithms (or a so-called "stacked" combination of two or more such algorithms), and commercial offerings such as those of Autonomy Inc. and Moho Mine Inc. A major barrier to using machine-learning algorithms is that that they require a significant amount of training data in order to achieve optimal performance, which can be costly and/or labor intensive.
[0014] Examples of human-authored rule classifier systems include the topics search engine by Verity Corp., and email routing software by Kana Communications Inc. In principle, human-authored rule-based algorithms can be applied to classification problems where no training data are available, but may have high maintenance costs and sometimes inferior performance compared to machine learning approaches, because they do not learn to improve themselves and do not take advantage of available training data. Construction and maintenance of such human-authored rules requires substantial domain knowledge and is labor intensive. A particularly simple example of a rule-based classifier is a list of distinctive keywords for each class, with the first matching keyword in an item being used to classify that item. Alternatively, one may prefer the category for which the largest number of keywords match the document.
[0015] Hierarchical categorization involves a hierarchy of categories wherein at least some of the items to be categorized are to be assigned not only to certain categories, but also to certain subcategories within those categories. A well-known example of hierarchical categorization is the Dewey Decimal and Library of Congress subject headings used by many libraries to organize their book collections. By utilizing a hierarchical structure, a complex classification problem can be decomposed into a number of simple sub-problems. A top-down approach to hierarchical classification starts with a few classes which are further refined into a number of subclasses. Further details of known hierarchical classification methodology may be found in the article "Hierarchical Classification of Web Content" by Susan Dumais and Hao Chen, which was presented Jul. 24-28, 2000 in Athens, Greece and published in SIGIR 2000: Proceedings of the 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval and which is hereby incorporated by reference in its entirety. A plurality of categorization methods can be applied to categorization sub-problems in a top-down (also known as "Pachinko") approach, using a sub-classifier at each internal node to select which child branch to follow. The overall hierarchical categorization mechanism in effect combines the results of the local categorization methods on the sub-problems. The local categorization algorithms output their results through a standard interface, so that these various intermediate results can be combined by an overall categorization processor that does not need to know what the local categorization method is. The overall categorization processor takes an item, delegates it to one or more local categorization methods (possibly a series of these depending on the results of each), and combines the results of these. It can then report for the item and for zero or more classes whether the item belongs to the class, possibly including a degree of confidence (such as a probability). An optional extension is that it can report, for an item and for a class X with zero or more subclasses, whether the item belongs to the set consisting of the class X and all of the subclasses of X, again possibly subject to a degree of confidence such as a probability. Such a hierarchical structure can potentially be used to advantage in trainable classifiers, by using the larger volume and hence greater accuracy of statistical training data (in particular, relative frequency of particular words and phrases) at a parent node to smooth and extrapolate the more limited and less accurate such data available at a given child node.
[0016] A "bootstrap" methodology may sometimes be used to improve the performance of a simple keyword-based categorizer by using the simple categorizer's output as training data for machine learning. In the particular case of a hierarchical categorizer in which the nodes at the upper levels of the hierarchy will each process more training data than the nodes at the lower levels and thus will tend to make more reliable decisions, a statistical technique known as "shrinkage" may be used to refine the statistically less reliable results at a lower level by combining them with the more reliable probabilities associated with decisions at a higher level. Further details of a known hierarchical bootstrap methodology may be found in Text Classification by Bootstrapping with Keywords, EM and Shrinkage by Andrew McCallum and Kamal Nigam, which was presented in 1999 at the ACL '99 Workshop for Unsupervised Learning in Natural Language Processing, and which is hereby incorporated by reference in its entirety.
[0017] "Stacking" is a known technique for combining statistical results from multiple machine-learning algorithms to make a particular classification decision. In other machine-learning applications, the selection of an appropriate algorithm is based on a-priori knowledge of the data being categorized, or is determined experimentally using known training data.
[0018] The present invention provides for automatic selection of different classifiers at different nodes within a hierarchy of categories. The local selection of classification methodology is preferably made dynamically at each local node of the hierarchy, and the selection decision at a descendant node is preferably at least partly dependent on a prior selection decision at a parent node, thereby making intelligent use of some of the factors that resulted in that prior decision without requiring substantial additional training and evaluation at all descendant nodes. For example, it may be possible to define a boundary (or "floor") separating an upper portion of the hierarchy having fewer nodes and thus more training data per node, from a lower portion of the hierarchy having more nodes and thus fewer training data per node. In one embodiment, such a floor is dynamically defined in terms of the training data available at each node, such that those nodes above the floor have access to sufficient training data to permit a particular trained classifier to provide adequate performance, while all nodes below the floor may be constrained to use other classification methodologies (for example, a less demanding type of trained classifier, or possibly even a flat a-priori rule-based classifier not requiring any training-data).
[0019] The invention is defined in the appended claims, some of which may be directed to some or all of the broader aspects of the invention set forth above, while other claims may be directed to specific novel and advantageous features and combinations of features that will be apparent from the Detailed Description that follows.
[0020]FIG. 1 shows an exemplary hierarchical categorization problem employing two different categorization methodologies in accordance with one embodiment of the present invention.
[0021]FIG. 2 depicts a typical relationship between a training set, an inducer, and a categorizer, such as may be used in some embodiments of the present invention.
[0022]FIG. 3 depicts a system for performing local classification decisions in accordance with an exemplary embodiment of the present invention.
[0023]FIG. 4 depicts a local decision process such as may be used in one exemplary embodiment of the present invention.
[0024]FIG. 5 shows a variant of FIG. 1 in which at least one of the selected classifiers is a flat classifier such as may be used in certain other embodiments of the present invention.
[0025] Reference should now be made to FIG. 1 of the attached Drawings, which represents an arbitrary hierarchical categorization problem H having 3 levels (i,j,k) of categories (labels) and a total of 8 subcategories (Si.j.k) at the third level, with each category at each of the upper levels branching in binary fashion into two subcategories at the next level.
[0026] Although as shown, each upper level node (S, Si, Si.j) has exactly two branches, and each of the eight bottom nodes Si.j.k is separated from the top node S by exactly two intermediate nodes (Si, Si.j), it should be understood that many of the principles of the present invention are equally applicable to more complex hierarchical structures, with more than three levels, with not all of the bottom nodes at the same level, and/or with more than two branches from one or more of the upper nodes. Using the previously mentioned example of books in a library, the two nodes in the first (i) level S1, S2 could represent fiction and non-fiction, the first two nodes in the second (j) level (S1.1, S1.2) could represent fiction for adult readers (S1.1) and fiction for children (S1.2) and the first two nodes in the third (k) level (S1.1.1, S1.1.2) could include adult romance novels (S1.1.1) and adult mystery novels (S1.1.2). Another example, from the computer sciences, might be a first level divided into hardware and software, the hardware being divided at a second level into systems and components, and the hardware systems being divided at a third level into hardwired and programmable. Those skilled in the art will realize that such a hierarchical arrangement H of the available categories is a natural byproduct of many human authored classification schemes and when available, often facilitates the construction of an appropriate human-rule based classifier.
[0027] Each branch from an upper node (S, Si, Si.j) of the exemplary Hierarchy H may define a subhierarchy (for example subhierarchies SH1 and SH2 depending from main node S), and, in recursive fashion, the upper node of each such subhierarchy (for example subhierarchies SH1 and SH2 may each define one or more lower level subhierarchies (for example sub-sub hierarchies SH1-1 and SH1-2). Except for the bottom nodes (Si.j.k), each node in the hierarchy H has an associated subclassifier (C,R) used for classifying data into the appropriate branch depending from that node, which collectively define a hierarchical classifier HC.
[0028] The exemplary Hybrid Categorizer HC used in a given hierarchy H of categories (FIG. 1) is preferably derived dynamically from at least one rule-based classifier R and at least one induction (or machine learning)-based classifier A (See FIG. 2), with a training set T of labeled data being used to induce the learned classifiers C. Although for the sake of clarity the same symbol (R or C) is used for different subclassifiers at different levels of the hierarchy, those skilled in the art will realize that in practice each node of the classification hierarchy HC represents a different decision with different possible results, so that a particular subclassifier (C,R) at a particular node corresponds to a different subset of the various decisions encompassed within the particular classification methodology (C or R) applicable to the overall hierarchical classifier HC. Moreover, there need not be exactly two such methodologies for each node, nor must any such methodology necessarily be applicable to all nodes in the hierarchy. Indeed, there may be practical examples where some nodes have more than two candidate trained classifiers, while other nodes have no such candidate trained classifiers.
[0029]FIG. 3 depicts an exemplary local decision mechanism 200 being used to select which subclassifier (categorization method) is best for a particular sub-problem (or, as shown in FIG. 1, for a particular decision node (S, Si, Si.j) of an associated hierarchical classifier HC). One embodiment of such a local decision mechanism 200 is an accuracy comparison in which a test set 202 of items (which could be the training set T of FIG. 2) for the sub-problem (labeled examples for which the "true" class is known) is used to test two available candidate sub-classifiers M1 and M2 204. The selection decision 206 can then be based on the relative accuracy of method M1 versus method M2 on that particular data. Another embodiment would be to use categorization speed—say method M1 can very rapidly classify on this sub-problem, and method M2 is very slow, then method M1 would be selected. Another exemplary embodiment (shown in FIG. 4) could simply be based on an absolute threshold on the number of training cases available. In that case, the local decision mechanism 200 could simply determine (block 302) whether there are fewer than 100 training examples at a particular node of any class (branch 304), in which case M1 would be selected (block 306) for that node, otherwise (branch 308) M2 would be selected (block 310). As indicated symbolically by the return loops 312, 314 (and as set forth in more detail in the exemplary local decision process set forth in the attached Appendix), a similar analysis and decision process may be repeated recursively for other nodes and other subtrees. As mentioned previously, the local decision mechanism is preferably based on one or more factors relevant to a particular local categorization algorithm and ultimate classification objective. Moreover, not only will the results vary from sub-problem to sub-problem, different decision mechanisms can be utilized at different places (nodes) in the hierarchy. The determination of which categorization method to apply to a particular sub-problem is ideally done dynamically (i.e. it is a function of changing data and/or objectives), and preferably can be subsequently refined with respect to one particular sub-problem without affecting other sub-problems.
[0030] A specific example of a local decision methodology in which one of the candidate classifiers is a learned classifier and the other is a non-learning, flat human-authored rule-based classifier will now be discussed with reference to the generic categorization hierarchy shown in FIG. 1 and FIG. 5 and the exemplary Pseudo-code set forth in the attached Appendix.
[0031] The inputs (lines 1-10) are as defined previously, and the output (lines 11-15) may be as shown in FIG. 5. Since the exemplary process is recursive (lines 40-47), it begins (line 16) with the whole hierarchy (exemplified with by the topmost node S in FIG. 1) and works its way down each of the subtrees of the hierarchy. The recursion down a particular subtree ends when (lines 17-19) only a single category is left (exemplified by reaching node S2.2.2), or (line 38) a flat classifier is chosen to cover the entire remaining subtree (illustrated by the use of flat classifier R to perform all classifications for the entire subtree FR in FIG. 5). At each step down the tree, a decision must be made to select which categorization technology should be used for the local decision problem. In the exemplary process illustrated here and in the Appendix, this decision is made by comparing (lines 34-36) the accuracy of a learned classifier C (generated by the machine learning algorithm A, lines 31-33) with the accuracy of a flat, rules-based classifier R. In other embodiments, other criteria may be used, e.g. speed, precision, recall, training effort, etc., or additional classifiers may be under consideration. To determine the accuracy of R, R is tested on the available training data T (lines 23-27) to determine the percentage of training items T that the rules R correctly classify into the correct subtree (i.e. if the rules classify an item to node Si.j.k, this is considered correct if the true label falls within the subtree Si), according to the labels on T. To determine the accuracy of the competing, machine learning technology A: All members of the available training set T are copied to training set T′ with their labels adjusted to indicate only in which of the sub-trees S1, S2, S3, . . . the item belongs, i.e. which branch to take from the current node S (lines 28-30). The training set T′ is given as input to induction algorithm A (for example, naive Bayes or C4.5), which outputs the trained classifier C (lines 31-32). The set T′ is then used to estimate the accuracy of the classifier C (line 33), for example, using the known technique of cross-validation.
[0032] If the trained classifier C performs better than the flat rules classifier R at the current node (line 39), the trained classifier C is selected for use at the current node and the training, comparison and selection process is repeated recursively (lines 40-47) for each of the sub-hierarchies represented by each of that node's immediate descendants. In actual use (lines 50-54), the resulting classifier for the current sub-tree will use the learned classifier C (lines 50-51) to determine which of the sub-tree classifiers to use in the top-down Pachinko style (lines 52-53). Conversely (lines 34-36), if the performance of the trained classifier C is not acceptable (e.g., node S1 FIG. 5), the flat classifier R is selected without further recursion (line 38) for classifying items comprehensively in the entire sub-tree (at least until such time as more training data becomes available to improve the performance of the learned classifier).
[0033] In an alternate embodiment, the non-learning rules classifier R may be used in a top-down Pachinko manner instead of only being used for flat classification—i.e. the rules classifier R is a hierarchical classifier used to select the next branch to follow down the tree (as in R selecting the left subtree SH1-1 or right subtree SH1-2 of S1 in FIG. 1). In this embodiment, selecting the rules classifier R also entails recursion (the RETURN statement in line 38 is replaced with a copy of lines 40-54 with R substituting for C). If a particular node S* (for example, node S1.1) is a descendant of a node S (for example, node S1) for which the rule-based classifier R was selected because of insufficient training data for learning, it may be assumed that there is even less available relevant training data for S* than was available for the ancestor node S for which the rule-based classifier R was selected and therefore it is even less likely that a learned classifier can provide superior performance (lines 33-36). Thus, if a rule-based classifier R is selected for a given node (e.g., S1) because of insufficient training data for learning, R preferably will also be selected (line 38) for any descendant nodes (e.g., S1.1, S1.2) and no further accuracy comparisons in later recursions (lines 34-36) is warranted.
[0034] In the examples of both FIG. 1 and FIG. 5, a conceptual Floor F is defined below which a rule-based classifier R is appropriate, and above which a learned classifier C is appropriate. It is envisioned that in alternate embodiments, there may be a plurality of hierarchical classifiers and/or a plurality flat classifiers, some of them non-learning and some of them needing training. In general, the best of the available classifiers may preferably be used for each local classification problem above a dynamically defined Floor F, and one or more otherwise available subclassifiers are preferably eliminated below that Floor. In particular, if a flat classifier is selected for a given parent node (as shown in FIG. 5), then that selection will eliminate an otherwise available hierarchical subclassifier from being selected at its descendant nodes, and if a non-trained classifier is selected for a given parent node (as shown in FIG. 1), then that selection will eliminate an otherwise available trained subclassifier from being selected at its descendant nodes.
[0035] Consider a practical example: given a hierarchical categorization problem with a small but growing training dataset, a machine learning algorithm (e.g. Na�ve Bayes), and a human-authored set of classification rules, the above described decision methodology will initially rely heavily on these human-authored rules, but as more training data becomes available in different portions of the hierarchy, the next time the local decision process is performed it will automatically switch to using the machine learning algorithm at those places in the hierarchy where it has enough training data to attain superior accuracy. The overall classifier follows a top-down (also known as "Pachinko") approach, using a sub-classifier at each internal node to select which child branch to follow-however, (as reflected in FIG. 5) at some nodes it may choose to use a sub-classifier that treats all remaining descendants as a single "flat" classification problem. When training a local Pachinko sub-classifier at any given node in the hierarchy, each child aggregates the training examples for all of its descendants—hence, higher nodes in the tree will tend to have more training data from which to learn an accurate machine learning classifier, and lower nodes without sufficient available training data may use other classifiers for example a less accurate trained classifier, or, as in the case of the above-described exemplary embodiment, human-authored rules. Moreover, in one preferred embodiment, the selection process may be simplified by providing a relatively simple, but not necessarily optimal, rule-based classifier that can be applied at all levels in the hierarchy as the default classifier, and by selecting that rule-based classifier not only at a node where there is not yet sufficient available training data for a trainable classifier (or the default classifier is otherwise clearly superior to all other candidates), but also at all other nodes descending from that node. This resultant boundary F separating a larger pool of available classifiers from a smaller pool of available classifiers can dynamically descend from parent to child as more training data is obtained. In effect, the selection of a certain type of classifier at a parent node (for example, a rule-based classifier R) eliminates the selection of an associated different type of classifier (for example, a trained classifier C) at a child node.
[0036] When more labeled training data becomes available, the entire selection process may be repeated, or preferably, limited to those portions of the hierarchy still using the rule-based classifier (R). By thus reducing and eventually altogether eliminating the categories subject to classification by the default rule-based classifier (which will typically be a human authored set of rules), the effort and cost of keeping it up to date may be reduced. The described exemplary hierarchical classifier provided thus is capable of providing full backwards compatibility with existing rule sets and requires only limited training data, but at the same time is capable of improved performance as additional training data become available. In particular, human-authored rules may be used in those finely divided portions towards the bottom of the hierarchy involving relatively close decisions for which it is not practical to create in advance sufficient training data to ensure accurate classification by known machine-learning algorithms, while still facilitating eventual change-over within the hierarchy to machine learning algorithms (C) as sufficient training data becomes available to ensure acceptable performance in a particular sub-portion of the hierarchy.
[0037] Moreover, although in one contemplated embodiment the selection process is performed (for ease of implementation) on the entire hierarchy using a set of labeled training data prior to the processing of any unlabeled data, the dynamic nature of the selection may be further exploited by incrementally reconsidering only those sub-branches (SH1, SH2.2) where sufficient training data to support a particular trained classifier has only recently become available, and not re-considering the decisions made above that point (Floor F) where sufficient training data was available to make an accurate evaluation of the available classifiers. Alternatively, one may use a "quick and dirty" learning algorithm for a while, and switch "on the fly" to a more sophisticated classifier built by a powerful but slow adaptive learning algorithm that runs in the background to eventually induce a more accurate classifier. Similarly, the choice of classifiers could be switched dynamically based on a user's change of goal, e.g. they originally wanted to see the most certain items for a category (precision), but now they are performing a keyword search against them and they would now prefer a classifier with greater coverage (recall).
[0038] In certain preferred embodiments, this dynamic selection of categorizers can even be done on the fly without having to take the system offline, thereby providing a dynamic "hot switching" of categorizers that ensures the optimal selection of categorization method at all times. For example, assume method M1 has been selected for a particular sub-problem based on a lack of training data, and gradually more training data have become available to the system, then as a threshold at a particular decision node is reached, method M2 can be applied to that sub-problem.
[0039] Trained classifiers and authored rule-based classifiers are two examples of different classification methodologies. However, the principles underlying the present invention are not limited to selection between those two methodologies. In particular, it may involve multiple types of trained classifiers, one of which works better in some places in the hierarchy and another (or others) in other places. The trained vs. authored distinction only serves as a very salient example of two methods that typically have different characteristics in terms of how they perform under various circumstances (i.e., the amount of training data available). What matters is not so much any theoretical difference in methodology, but rather the practical performance at a predetermined node or subtree of the hierarchy when a given classification methodology is used with the data that is then available. Thus the present invention is not limited to selection between trained and rule-based classifiers, but may also be applicable to selection of any two or more available classifiers. One example involving two trained classifiers, one hierarchical, the other flat, would evaluate the performance of a hierarchical implementation of Na�veBayes at a parent node that leads to other Na�veBayes subclassifiers at the child nodes versus a non-hierarchical implementation of Na�veBayes at that parent node that treats all descendant nodes as part of one big "flat" problem and assigns each of the records among all descendants. A similar example, but combining two rule sets developed by different human authors might make a local decision between a non-learned hierarchical classification with a non-learned flat classification R2. In either case, the selection of the flat classifier at the parent node would eliminate any subsequent selection of the hierarchical subclassifier at any descendant node. Moreover, a common "flat" classifier for all nodes below the dynamically defined boundary may not always be the optimal selection, nor will there necessarily be only two candidate methodologies at each node, with one methodology being selected above the a defined floor and the other methodology being selected below that floor.
[0040] The foregoing exemplary procedures are believed to be also applicable with slight modification to other trainable categorization processes employing multiple classification algorithms on the same sub-problem and combining the results using either a predetermined or learned criteria and/or weights, or to recursive statistical processes in which the classifier at a particular node uses computed probabilities from other nodes in the hierarchy. Similarly, those trained in the state of the art will be able to extend the foregoing exemplary procedures to classification hierarchies in which some items are assigned to more than one category, or cannot be assigned to any category.
[0041] Thus the disclosed hybrid classification methodology combines the advantages of different classification methodologies at different nodes of a hierarchical classifier. Moreover, since the particular classification methodology used at a particular sub-problem at a particular node of the hierarchy is preferably selected dynamically, it can provide for an easy transition from one classification methodology to another methodology, for example from a labor intensive human-authored rules categorizer to a data intensive machine learning trained categorizer.
[0042] Having described preferred embodiments of a novel hierarchical categorization method and system with automatic local selection of classifiers, (which are intended to be illustrative and not limiting), it is noted that modifications and variations can be made by persons skilled in the art in light of the above teachings. It is therefore to be understood that changes may be made in the particular embodiments of the invention disclosed which are within the scope and spirit of the invention as defined by the appended claims.
Referenced by
Legal Events
Original Image


text:
- About
- Adopt & Help
- Donate
- Events & Fun
- Rabbit Care
- Services
- Shop
My name is Velvet. I'm a young boy bunny. I'm a dwarf bunny. I'm very gentle, innocent and easy to hold and cuddle. I've had my surgery and I'm microchipped. If you adopt me my first vet appointment is free too!
I'm working on my potty training so that I can be your best bunny friend. I'd like an indoor home that stays cool in the summer and cozy in the winter.
Won't you join me on the floor for some play time?
I'm on display for PAWS for the San Jose Animal Care Center, at
Andy's Rehoming Center
1280 The Alameda ( and Julian)
San Jose, Ca 95126
(408) 297-0840
store hours are 10-7
Mon-Fri Sat 10-6 Sun 12-5.
10/2008 - Update - I've been adopted as a big brother to a little hotot girl. She's very sweet. My adoptive family seems very nice and I'm looking forward to my life as a house bunny. Thanks SaveABunny!
This beautiful handcrafted vase is beige with terra cotta brown and cream colored accents in a swirling pattern. Vase has a matte finish. Would make a beautiful accent piece for any home, and would be perfect for displaying dried flowers, or branches of the season. Vase is signed by the artist on the base. Each piece is unique and slight variations in size, glaze and smoothness is part of the beauty of artisan pieces. Artist wished to remain anonymous.


text:
|Thread Tools
Just thought I'd post this here, if anyone's interested in stocking up on winter clothes for their kids' next year's size. I just placed an order with Land's end and the price was incredible. I just bought three pairs of shoes, two parkas, a down filled coat and some kids shirts for my family for less than $200, and that's because I'm in Canada and have to pay duty and taxes. It would have been $150 if I were in US. Most winter coats are deeply discounted already and you can save additional 40% on top of that. So a down filled jacket turned out to be $30 - 40, which I think is pretty decent.
The offer is valid until end of Monday Dec. 19. I'm sure they'll have more sales after Christmas and it might be even cheaper then, except the selections might be more limited. Things are going pretty fast in certain popular sizes and colors. :)
Mom to 2 beautiful autistic boys (13 & 12)
Thanks! Their parkas look really warm. My boys should love them.
Mama to 3 wild boys[/CENTER]
My sons have worn Land's End parkas for 2 years, and they still had plenty of wear to pass on to a friend's son (he might have worn it for 2 more years).
If the chips are down, the buffalo is empty.
|Thread Tools
Show Printable Version Show Printable Version
Email this Page Email this Page
|Posting Rules
You may not post new threads
You may not post replies
You may not post attachments
You may not edit your posts
BB code is On
Smilies are On
[IMG] code is On
HTML code is Off
Trackbacks are On
Pingbacks are On
Refbacks are Off


text:
- Canon DLC Home
- Tags
- how-to tips
Tag: how-to tips
- Article
- Blog
- Event
- Gallery
- Photo
- Video
Rick Berk
Rick Berk has been working in photography for almost 20 years, having started by photographing pro sports. Rick is a published landscape photographer and portrait photographer as well as photo educator.Tags: how-to tips
- Viewed:
- 601
- Searched:
- 14
Photographing Fireworks
by Rudy Winston 6/30/15
Fireworks are one of the most inspiring and photogenic, yet challenging, subjects to capture. Learn which settings and accessories can help you in those shooting situations.
- Emailed:
- 277
- Viewed:
- 90,593
- Searched:
- 2,666
Using the Canon EOS 7D Mark II's Interval Timer For Time-lapse
by George Lepp 2/27/15
TheCanon EOS 7D Mark II has the interval timer built into the camera, which allows photographers and videographers to capture a time lapse without the additional intervalometer accessory.
- Emailed:
- 1
- Viewed:
- 5,545
- Searched:
- 91
How to protect yourself against counterfeit Canon batteries
by Rudy Winston 2/10/15
It's important to repeat: genuine Canon batteries and battery chargers have these safeguards engineered into them, and Canon customers can be confident that using these batteries and chargers will result in safe, reliable operation.Tags: how-to tips batteries
- Viewed:
- 1,679
- Searched:
- 19
Online dating profile picture tips
by CDLC Editor 2/9/15
For almost every social media account comes an accompanying profile picture. If you're involved with online dating, those pictures are the first impressions that can determine potential interactions and a thought-out profile picture can only help.Tags: portraits how-to tips
- Emailed:
- 1
- Viewed:
- 1,952
- Searched:
- 19
Photographing Snow
by CDLC Editor 1/15/15
The biggest challenge when photographing snow lies in your camera's metering system.Tags: nature how-to tips color temperatures exposure compenstation exposure techniques (+) histograms highlight tone priority metering modes white balance (–)
- Emailed:
- 151
- Viewed:
- 100,711
- Searched:
- 2,775
How to Photograph Fast Moving Motorsports
by Regis Lefebure 10/8/14
Making a good photograph isn't always easy especially capturing the speed and action of motorsports. Knowledge of the camera, lens functions and the operation of them are skills usually acquired through experience.
- Emailed:
- 15
- Viewed:
- 11,548
- Searched:
- 125
Fall Foliage Photography
by CDLC Editor , Dave Henry 9/26/14
Autumn's dramatic landscapes are stunning to behold and the challenge is how to preserve the impact in a still photograph that captures the unique quality of this season.Tags: nature how-to tips color temperatures picture styles white balance (+) digital photo professional (–)
- Emailed:
- 138
- Viewed:
- 55,914
- Searched:
- 1,149
Capturing the Look: American Farmers with Tyler Stableford
by Tyler Stableford 9/11/14
Join Canon Explorer of Light Tyler Stableford as he explores the Midwest through twelve of our lenses, a Speedlite and a PIXMA printer.Tags: how-to tips tyler stableford
- Viewed:
- 2,840
- Searched:
- 28
Back to School Portraits
by CDLC Editor 8/22/14
Remember these "first day of school" milestones with unique photos of your children. Learn how to create environmental portraits with different techniques, settings and products.
- Emailed:
- 6
- Viewed:
- 5,874
- Searched:
- 95
Monitor Calibration
© 2014 Canon U.S.A., Inc. All Rights Reserved. Reproduction in whole or in part without permission is prohibited.


text:
Kay Jewelers, known for its tagline, "Every kiss begins with Kay," is opening a 3,000-square-foot store at the state's largest shopping mall.
The new $198 million tower at St. Jude boasts two new big name naming rights partners
For the chicken lover who has everything.
Disruptors and local companies took the lead in many of the 2014 Best in the Biz: Readers' Choice Awards from the Tampa Bay Business Journal. Readers nominated and voted for their favorites in various categories related to dining, business services, transportation and more. Some categories had ties this year, and we added and removed categories compared to previous years.
The Falls has more than 821,000 square feet of retail space and more than 100 stores, restaurants and cafes.
The Bermuda-based jewelry company said in its second-quarter earning statement it expects to achieve greater cost savings that anticipated.
The Bermuda-based jewelry company said in its second-quarter earning statement it expects to achieve greater cost savings that anticipated.
The mall is basking in the community's excitement for the recent opening of H&M — the first in the Dayton region — and the increased traffic will likely be a boon to the four new retailers set to open this summer.
Zale Corp. is now a division of Bermuda-based Signet Jewelers, which acquired the Irving-based company in a $1.4 billion deal last week.
Ingram Park Mall has landed a number of new tenants as well as others that are expanding their retail space at the Northwest Side shopping center.
Charlotte Premium Outlets in Steele Creek has ramped up construction and is on target for its planned July 31 opening.
The cost of keeping businesses secure isn't going down and the fear of rising insurance costs keeps some employers from reporting crimes.
Charlotte Premium Outlets in Steele Creek is scheduled to open July 31 and will have 100 stores.
Signet Jewelers Ltd., parent company of Kay Jewelers, is acquiring Zale Corp., parent company of Zales jewelry stores, in a deal worth $1.4 billion, t ...


text:
An optical spectrum analyzer includes an integrated beam switch array. As a result, a single spectrum analyzer can be amortized across multiple optical links with pigtails transmitting the optical signals from separate optical links. The switch array providing one of the optical signals as an input signal to the optical spectrum analyzer.
1. An optical spectral monitoring system, comprising:
an optical bench;
fiber pigtails terminating above the bench;
a tunable filter, connected to the bench, that filters an input optical signal;
an array of beam switches, connected to the bench, for providing the optical signals from the fiber pigtails as the input optical signal to the tunable filter;
a detector connected to the bench that detects the filtered input optical signal from the tunable filter.
2. An optical monitoring system as claimed in
3. An optical monitoring system as claimed in
4. An optical monitoring system as claimed in
5. An optical monitoring system as claimed in
6. An optical monitoring system as claimed in
7. An optical monitoring system as claimed in
8. An optical monitoring system as claimed in
9. An optical monitoring system as claimed in
10. An optical monitoring system as claimed in
11. An optical monitoring system, comprising:
an optical bench;
fiber pigtails terminating above the bench;
a tunable filter, connected to the bench, that filters an input optical signal;
an array of beam switches, connected to the bench, for providing the optical signals from the fiber pigtails as the input optical signal to the tunable filter, wherein the array of beam switches selectively reflects one of the optical signals to the tunable filter.
12. An optical monitoring system as claimed in
13. An optical monitoring system as claimed in
14. An optical monitoring system as claimed in
15. An optical monitoring system as claimed in
16. An optical spectral monitoring system, comprising:
optical bench means;
fiber pigtails terminating above the bench;
tunable filter means, connected to the bench, for spectrally filtering an input optical signal;
switch means, connected to the bench, for providing the optical signals from the fiber pigtails as the input optical signal to the tunable filter means; and
a detector connected to the optical bench means that detects the filtered input optical signal from the tunable filter means.
17. A method of optical signal monitoring, comprising:
providing optical signals to a hermetic package;
selectively providing one of the optical signals to a tunable filter within the package; and
detecting a filtered optical signal from the tunable filter with a detector in the hermetic package.
18. A method as claimed in
19. A method as claimed in
20. A method as claimed in
21. A method as claimed in
Optical spectrum analyzers typically comprise a tunable filter that bandpass filters an input signal. A detector is used to measure the filtered signal and thereby determine the optical power within the filter's current pass band.
Analyzers have relevance to many applications requiring optical spectrum analysis. Such applications span LIDAR to remote chemical analysis, for example. Presently, however, one of the most active applications is in the area of data transmission systems utilizing wavelength division multiplexing (WDM).
WDM systems typically comprise multiple separately modulated laser diodes at the transmitter. These laser diodes are tuned to operate at different wavelengths. When combined in an optical fiber, the WDM optical signal comprises a corresponding number of spectrally separated channels. Along the transmission link, the channels are typically collectively amplified in gain fiber, such as erbium-doped fiber and/or regular fiber, in a Raman pumping scheme. At the receiving end, the channels are usually separated from each other using thin film filter systems, for example, to thereby enable detection by separate photodiodes.
The advantage of WDM systems is that the transmission capacity of a single fiber can be increased. Historically, only a single channel was transmitted in each optical fiber. In contrast, modern WDM systems contemplate hundreds of spectrally separated channels per fiber. This yields concomitant increases in the data rate capabilities of each fiber. Moreover, the cost per bit of data for WDM systems is typically less than comparative non-multiplexed systems. This is because any amplification system required along the link can be shared by all of the separate channels transmitted on the link. With non-multiplexed systems, each channel/fiber would require its own amplification system.
The economics pulling for WDM in the context of long-haul optical links is only one factor suggesting the long-term applicability of the technology. Another application concerns the dynamic routing of individual wavelength slots or channels. This is sometimes referred to as metro WDM.
Nonetheless, there are challenges associated with implementing WDM systems. First, the transmitters and receivers are substantially more complex since, in addition to the laser diodes and receivers, additional optical components are required to combine the channels into, and separate out the channels from, the WDM optical signal. Moreover, there is the danger of channel drift where the channels lose their spectral separation and overlap each other. This interferes with channel separation and demodulation at the receiving end.
In order to ensure that proper guard bands are maintained between adjacent channels and to also ensure that the carrier frequencies or wavelengths of the channels are correct both relative to other channels and relative to their wavelength assignments, optical monitoring systems are required in most WDM transmission systems. They are also useful in WDM channel routing systems, such as add/drop multiplexers and switches to ensure that the specific optical channels are being properly controlled. Further, information concerning the relative and absolute powers in the optical channels is important as feedback to variable attenuators, for example, and to combat gain tilt.
One problem associated with these spectrum analyzers is their expense, which slows their advance toward the network edge and adds incrementally to the deployment costs for WDM systems, for example. However, as the operation and stability of WDM systems are refined and as the speed of spectrum analyzers is increased, it becomes less necessary for a spectrum analyzer to be dedicated to monitoring each optical link.
The present invention concerns an optical spectrum analyzer that includes an integrated beam switch array. As a result, a single spectrum analyzer can be amortized across multiple optical links with pigtails transmitting the optical signals from separate optical links to the analyzer. The switch array provides one of the optical signals as an input signal to the optical spectrum analyzer. Further, the invention also concerns an analyzer with this functionality that is further capable of being integrated into a small package to be used as a subsystem, or possibly even as a stand-alone system, in a WDM system, or other application requiring optical spectral monitoring.
In general, according to one aspect, the invention features an optical spectrum monitoring system. The system comprises a bench and fiber pigtails terminating at the bench. A tunable filter is further connected to the bench and functions to filter an input optical signal. An array of beam switches, connected to the bench, selectively provides the optical signals from the fiber pigtails as the input optical signal to the tunable filter.
In general, according to another aspect, the invention features a method. Specifically, the method comprises providing optical signals to an optical bench and selectively providing one of the optical signals to a tunable filter. A filtered signal from the tunable filter is then detected.
The above and other features of the invention including various novel details of construction and combinations of parts, and other advantages, will now be more particularly described with reference to the accompanying drawings and pointed out in the claims. It will be understood that the particular method and device embodying the invention are shown by way of illustration and not as a limitation of the invention. The principles and features of this invention may be employed in various and numerous embodiments without departing from the scope of the invention.
In the accompanying drawings, reference characters refer to the same parts throughout the different views. The drawings are not necessarily to scale; emphasis has instead been placed upon illustrating the principles of the invention. Of the drawings:
FIGS. 1A and 1B are perspective views of an optical spectrum analyzer with integrated beam switch array, according to the present invention.
The figures show an optical spectrum analyzer with integrated beam switch array, which has been constructed according to the principles of the present invention.
Specifically, an array of fiber pigtails 110 is secured to the substrate or optical bench 112 of the system. In the specific implementation illustrated, the array of fibers 110 comprises ten separate optical fibers 114. Each one of these fibers has an endface 116 that is secured to the bench 112 via a fiber mounting structure 118.
In more detail, each one of the separate fibers projects through a port 118A in the fiber mounting structure 118 such that its endface 116 is held in a fixed relationship to the optical bench 112 (see FIG. 1B). In one implementation, each endface 116 comprises a fiber lens to improve the collimation of light emitted from the respective fiber.
The beams 120 that are emitted from the endfaces 116 of the fibers 114 are transmitted through a window structure 122′ in the hermetic package sidewall 122 into the hermetic region of the system. This specific configuration has advantages surrounding the fact that epoxies and other organic compounds can be used to secure the endfaces 116 to the bench 112. These compounds are separated from the other components by the hermetic boundary of the package sidewalls 122. Note that for the purposes of illustration, the package lid is not shown.
In an alternative configuration, the pigtails extend across a hermetic boundary, through fiber feedthroughs in the package sidewalls and terminate within the hermetic enclosure. This alternative implementation is more common in the current state of technology.
In the illustrated embodiment, the beams 120 enter a first isolator system 126. This isolator system 126 prevents backreflections into the fiber endfaces 116.
The beams 120 emitted from the first isolator system 126 enter a collimator lens array 128. This collimator lens array comprises, in the preferred or current embodiment, separate discrete lenses formed using the mass transport lens process as described in, for example, U.S. Pat. No. 5,618,474, the teachings of which are incorporated herein by this reference in their entirety. These separate lenses of the lens array 128, focus or improve the collimation of the beams 120 so that a beam waist is formed typically. Generally, the beam diameters at the lenses are less than 250 micrometers (μm), preferably less than 100 μm.
In another implementation, the first collimator array is located closer to the fiber endfaces, with the endfaces being cleaved. In one such implementation, the isolator system 122 is effectively moved as described below.
The beams 120 exiting from the lens array 128 pass to an array of optical filter switches 136. In the illustrated embodiment, these switches are aligned in a row, this row being parallel to a surface of the bench 112, but extending orthogonally to the optical axes of the beams 120.
In the illustrated embodiment, the individual switches of the filter switch array 136 are "rollershade" switches as described in U.S. Pat. No. 5,784,189, for example. This configuration, however, is simply the illustrated implementation. The present invention is compatible with other beam switching strategies, such as tilt mirror arrays.
Further, in the illustrated implementation, during operation, one of the switches in array 136 is activated to convert from a transmissive state to a reflective state. This allows the selected beam to be redirected to enter the filter system 138 as the input signal 120′, possibly through other switches in the array that are in a transmissive state by propagating through the optical ports of the switches. Specifically, in an unactivated state, the switches allow the beams to pass through the optical ports of the respective switches (see beams 120″). When one of the switches is activated, the corresponding beam is reflected at 90 degrees to be input signal 120′ to a tunable filter system 138.
In the preferred embodiment, this tunable filter system 138 bandpass filters the input signal with a tunable passband so that it can assess the optical power in a single optical channel slot in a WDM signal of one of the beams 120 when used as a WDM signal analyzer.
The input optical signal 120′ is typically diverging as it is transmitted from the switch array 136. It is again collimated or has its collimation improved by first lens 12. Preferably, the radii of curvatures of the lens in array 128 are different due to the different path lengths between the first lens 12 of the filter system 138 and the lens array 128.
A dichroic mirror 50 is used to add a reference signal to the input optical signal 120′ when such reference signal is required by the application. These dichroic mirrors or filters are typically referred to as WDM filters. In the illustrated implementation, the WDM filter 50 is reflective in a band surrounding 1300 nanometers (nm) or 1400 nm, but transmissive in a band surrounding 1500 nm.
In the illustrated embodiment, the 1300 nm reference signal is generated by a light emitting diode 52. In one implementation, the light emitting diode is a super luminescent light emitting diode (SLED). Alternatively, a 1400 nm source is used.
The diverging beam from the SLED is collimated by a collimating lens 54. An etalon 56 is used to convert the relatively wide-band signal from the SLED into a reference signal with stable spectral characteristics. More specifically, the etalon 56 functions as a Fabry-Perot filter with a 200 GigaHertz (GHz) free spectral range (FSR). This converts the SLED's continuous, broadband spectrum into a signal with energy peaks every 200 GHz. These peaks are stable, particularly when the temperature of the system is controlled by a thermoelectric cooler or is otherwise stabilized.
A fold mirror 58 redirects the reference signal to the WDM filter 50. It should be noted, however, that this mirror is not required, but is simply used to facilitate integration of the system on a more compact bench.
The combined optical signal is transmitted through an isolator 61 in an alternative embodiment. This component is used to prevent back-reflections from the subsequent optical components into the fibers 110. Typically, however, only one isolator for the system is required. Thus, generally either isolator 126 or isolator 61 is installed in the system, not both.
A second lens 60 is used to focus the collimated combined beam onto tunable filter 18. After the tunable filter, the beam is recollimated by a third collimating lens 62, and transmitted to a second dichroic/WDM filter 64.
The second WDM filter 64 functions to separate the filtered reference signal from the filtered input optical signal in the filtered beam from the tunable filter 18. In the illustrated implementation, the second WDM filter 64 is reflective in a band around 1300 nm, but transmissive in a band around 1500 nm. As a result, the filtered reference signal is directed to the wavelength reference detector 66 for optical-electrical conversion.
The filtered optical signal is transmitted to a signal detector 68. Depending on the implementation, bandwidth, and free spectral range of filter 18, this detector operates for the S, L, and/or C bands.
Turning to specifics of the single bench implementation, the first lens 12 is installed on the bench 112 via mounting structure 254. The SLED 52 is installed on a hybrid, which is attached to the bench. The broadband beam is focused by the collimating lens 54 held on mounting and alignment structure 256. This collimates the beam to pass through the etalon 56, which is installed directly to the bench 112. The reference beam generated by the etalon is reflected by fold mirror 58 to the first WDM filter 50. As a result, the combined beam is transmitted to the isolator 61, which is installed directly on the bench 112 in the illustrated implementation.
After the isolator, the focusing lens 60 held on mounting and alignment structure 258 focuses the combined beam onto the tunable filter 18, which is held on the filter mounting and alignment structure 259. In a current implementation, the beam is focused to a spot smaller than 50 μm in diameter at the tunable filter. The beam from the filter 18 is re-collimated by a third collimating lens 62 held on mounting and alignment structure 260. This beam is then separated into the reference beam and the optical signal by WDM filter 64. The reference signal is detected by detector 66. The filtered optical signal is transmitted through the second WDM filter 64 to the signal photodiode 68.
In one implementation, this tunable filter 18 is a MOEMS (micro optical electromechanical system) device, such as described in U.S. Pat. No. 09/649,168, filed on Aug. 25, 2000, entitled Tunable Fabry-Perot Filter, by Flanders, et al., the teachings of which are incorporated herein by this reference in their entirety, although other MOEMS tunable filters, such filters based on other technologies, can be used.
In any case, to be compatible with modem WDM channel spacings, the passband of the tunable filter is preferably less than 100 GigaHertz (GHz) to be compatible with the promulgated ITU grid. In still another embodiment, the bandwidth of the passband is less than 50 GHz to be compatible with the 50 gigahertz offset on the ITU grid. Presently, the passband is less then 10 GHz, preferably about 2 GHz.
While this invention has been particularly shown and described with references to preferred embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope of the invention encompassed by the appended claims.
Patent Citations
Referenced by
Legal Events
Original Image


text:
The 45 Best Pictures Of Scared Bros At A Haunted House Of 2012
These hidden camera shots from Nightmares Fear Factory in Niagara Falls, CA are amazing. It's the return of the Scare-Bros!
45. And one scared Dad-bro for good measure:
Preview Your Response
Here Are The Top Stories
- Greece will decide on Sunday whether they will accept austerity measures as a condition of a bailout that may stave off an imminent financial and economic crisis.
- Some 150 migrants stranded in the French city of Calais stormed the Channel Tunnel in an attempt to make it to British territory.
- It took a while, but an English national soccer team has finally defeated Germany in a major tournament. England took third place with a 1-0 win over the top-ranked German team in the FIFA Women's World Cup ⚽
- Chile defeated Argentina on penalties to win the Copa America tournament. It's the first ever trophy for Chile in the 99 years of the Copa ⚽


text:
South African Bank Enables P2P "Geo-Payments" That Don't Require Account Data
Customers at First National Bank in South Africa can use their FNB mobile app to transfer money to nearby people without inputting the money recipient's bank account information, Finextra reports.
Non-FNB customers can download FNB's app and receive money through the GeoPayments feature, the report says, although they cannot send money.
Also by This Author
3241 New Articles This Month
What's Hot
What The 401(K) Could Mean For SMEs
View All Articles ››
You May Also Like
Company Spotlight
Different mPOS Strokes for Different mPOS Folks
Mobile Commerce
Trustwave Buys Cenzic To Beef Up App Testing Capability
B2B Payments
New EU Biz Lender Launches With Help From The Cloud
What The 401(K) Could Mean For SMEs
B2B Payments
Will BYOD Lead Enterprise To Mobile Payments?
View All Articles ››