Smart Economy

Reflection identification

“Scientists have developed a new technique which can recover the faces of bystanders from reflections in the eyes of photographic subjects, a development that could help identify criminals.”

Further Details :...

L#1 : http://is.gd/H96wZQ
L#2 : http://is.gd/LVK9pP
L#3 : http://is.gd/xBwt8c

Biomimicry: Next generation of algorithms inspired by problem-solving ants

The ants were able to find the shortest route from one end of the maze to the other in under an hour, then were able to adapt and find the second shortest route when obstacles were put in their path.

An ant colony is the last place you'd expect to find a math whiz, but University of Sydney researchers have shown that the humble ant is capable of solving difficult mathematical problems.

These findings, published in the Journal of Experimental Biology, deepen our understanding of how even simple animals can overcome complex and dynamic problems in nature, and will help computer scientists develop even better software to solve logistical problems and maximize efficiency in many human industries.

Using a novel technique, Chris Reid and Associate Professor Madeleine Beekman from the School of Biological Sciences, working with Professor David Sumpter of Uppsala University, Sweden, tested whether Argentine ants (Linepithema humile) could solve a dynamic optimization problem by converting the classic Towers of Hanoi math puzzle into a maze.

Finding the most efficient path through a busy network is a common challenge faced by delivery drivers, telephone routers and engineers. To solve these optimization problems using software, computer scientists have often sought inspiration from ant colonies in nature - creating algorithms that simulate the behavior of ants who find the most efficient routes from their nests to food sources by following each other's volatile pheromone trails. The most widely used of these ant-inspired algorithms is known as Ant Colony Optimization (ACO).

"Although inspired by nature, these computer algorithms often do not represent the real world because they are static and designed to solve a single, unchanging problem," says lead author Chris Reid, a doctoral student from the Behavior and Genetics of Social Insects Laboratory.

"But nature is full of unpredictability and one solution does not fit all. So we turned to ants to see how well their problem solving skills respond to change. Are they fixed to a single solution or can they adapt?"

The researchers tested the ants using the three-rod, three-disk version of the Towers of Hanoi problem - a toy puzzle that requires players to move disks between rods while obeying certain rules and using the fewest possible moves. But since ants cannot move disks, the researchers converted the puzzle into a maze where the shortest path corresponds to the solution with fewest moves in the toy puzzle. The ants at the entry point of the maze could chose between 32,768 possible paths to get to the food source on the other side, with only two of the paths being the shortest path and thus the optimal solution.  

The ants were given one hour to solve the maze by creating a high traffic path between their nest and the food source, after which time the researchers blocked off paths and opened up new areas of the maze to test the ants' dynamic problem solving ability.

After an hour, the ants solved the Towers of Hanoi by finding the shortest path around the edge of the maze. But when that path was blocked off, the ants responded first by curving their original path around the obstacle and establishing a longer, suboptimal, route. But after a further hour, the ants had successfully resolved the maze by abandoning their suboptimal route and establishing a path that traversed through the centre of the maze on the new optimal route.

But not all the colonies' problem solving skills were equal: ants that were allowed to explore the maze without food for an hour prior to the test made fewer mistakes and were faster at resolving the maze compared to the ants that were naive. This result suggests that the "exploratory pheromone" laid down by ants searching a new territory is key in helping them adapt to changing conditions.

"Even simple mass-recruiting ants have much more complex and labile problem solving skills than we ever thought. Contrary to previous belief, the pheromone system of ants does not mean they get stuck in a particular path and can't adapt. Having at least two separate pheromones gives them much more flexibility and helps them to find good solutions in a changing environment. Discovering how ants are able to solve dynamic problems can provide new inspiration for optimization algorithms, which in turn can lead to better problem-solving software and hence more efficiency for human industries."

Provided by University of Sydney

 Walter Derzko

Replikin Count in H5N1 at Record High for 2010, signals next global pandemic outbreak?

Replikins Global BioRadar Surveillance System™ Shows Replikin Count in H5N1 at Record High for 2010

 Boston, MA, October 27, 2010 — BioRadar™ software correctly predicted the 2009 H1N1 (Swine Flu) outbreak a year in advance (http://www.replikins.com, Replikins Press, 2008). The same rise in Replikin Count of these genomic Replikin genes, this time in the H5N1 (Bird Flu) virus, may similarly warn of the coming of severe outbreaks in H5N1.

Specifically, BioRadar™ analyzed two separate Replikins* genes, one for infectivity and one for lethality. The high H5N1 lethality gene Replikin Count, rising since 2006 (6.0+/-7.0), has continued to rise to a high in 2010 (9.1+/-8.5) (p<0.001). BioRadar™ predicted in 2009 an increase in H5N1 outbreaks and more outbreaks appeared in 16 countries by mid-2010. The previous low infectivity of H5N1, correlated with a low Replikin Count, has been reassuring. The finding in 2010 of a significant increase in the Replikin Count of the H5N1 infectivity gene as well, in scout viruses to 8.4, its highest level in 53 years, is of concern.

By means of BioRadar™ software, Replikins were identified in all sequences (N, H5N1=25,358) from PubMed and from Global BioRadar Surveillance System™ participants.

The studies were conducted by Samuel Bogoch, M.D., Ph.D. and Elenore S. Bogoch, M.D., Boston University School of Medicine and BioRadar UK, Ltd.

*About Replikins

Replikins are a new group of genomic peptide structures in viruses, other infectious disease agents, and cancer cells, which are associated with rapid replication (http://www.replikins.com). Two genes have been isolated in silico in viruses and relate to infectivity and lethality respectively. The increase in Replikin concentration (Replikin Count=Number of Replikins per 100 amino acids) in the virus Infectivity Gene precedes an increase in clinical infectivity and spread; and an increase in the virus Lethality Gene precedes an increase in lethality clinically.

N.B. Confirms my previous posts

See the Rockerfeller Foundation Lock Step scenario for a virulent global  flu pandemic in 2012, which I wrote about earlier on the Smart Economy Blog

Scenario Narratives>  LOCK STEP

A world of tighter top-down government control and more authoritarian leadership, with limited innovation and growing citizen pushback

In 2012, the pandemic that the world had been anticipating for years finally hit. Unlike 2009’s H1N1, this new influenza strain — originating from wild geese — was extremely virulent and deadly. Even the most pandemic-prepared nations were quickly overwhelmed when the virus streaked around the world, infecting nearly 20 percent of the global population and killing 8 million in just seven months, the majority of them healthy young adults. The pandemic also had a deadly effect on economies: international mobility of both people and goods screeched to a halt, debilitating industries like tourism and breaking global supply chains. Even locally, normally bustling shops and office buildings sat empty for months, devoid of both employees and customers.

http://www.rockefellerfoundation.org/uploads/files/bba493f7-cc97-4da3-add6-3deb007cc719.pdf

 

New Princeton search method traces origins and spread of ideas

October 21, 2010

Princeton computer scientists have developed a new way of tracing the origins and spread of ideas, a technique that could make it easier to gauge the influence of notable scholarly papers, buzz-generating news stories and other information sources.

The method relies on computer algorithms to analyze how language morphs over time within a group of documents — whether they are research papers on quantum physics or blog posts about politics — and to determine which documents were the most influential.

“The point is being able to manage the explosion of information made possible by computers and the Internet,” said David Blei, an assistant professor of computer science at Princeton and the lead researcher on the project. “We’re trying to make sense of how concepts move around. Maybe you want to know who coined a certain term like ‘quark,’ or search old news stories to find out where the first 1960s antiwar protest took place.”

Blei said the new search technique might one day be used by historians, political scientists and other scholars to study how ideas arise and spread.

While search engines such as Google and Bing help people sort through the haystack of information on the Web, their results are based on a complex mix of criteria, some of which — such as number of links and visitor traffic — may not fully reflect the influence of a document.

Scholarly journals traditionally quantify the impact of a paper by measuring how often it is cited by other papers, but other collections of documents, such as newspapers, patent claims and blog posts, provide no such means of measuring their influence.

Instead of focusing on citations, Blei and Sean Gerrish, a Princeton doctoral student in computer science, developed a statistical model that allows computers to analyze the actual text of documents to see how the language changes over time. Influential documents in a field will establish new concepts and terms that change the patterns of words and phrases used in later works.

“There might be a paper that introduces the laser, for instance, which is then mentioned in subsequent articles,” Gerrish said. “The premise is that one article introduces the language that will be adopted and used in the future.”

Previous methods developed by the researchers for tracking how language changes accounted for how a group of documents influenced a subsequent group of documents, but were unable to isolate the influence of individual documents. For instance, those models can analyze all the papers in a certain science journal one year and follow the influence they had on the papers in the journal the following year, but they could not say if a certain paper introduced groundbreaking ideas.

To address this, Blei and Garrish developed their algorithm to recognize the contribution of individual papers and used it to analyze several decades of reports published in three science journals: Nature, the Proceedings of the National Academy of Sciences and the Association for Computational Linguistics Anthology. Because they were working with scientific journals, they could compare their results with the citation counts of the papers, the traditional method of measuring scholarly impact.

They found that their results agreed with citation-based impact about 40 percent of the time. In some cases, they discovered papers that had a strong influence on the language of science, but were not often cited. In other cases, they found that papers that were cited frequently did not have much impact on the language used in a field.

They found no citations, for instance, for an influential column published in Nature in 1972 that correctly predicted an expanded role of the National Science Foundation in funding graduate science education.

On the other hand, their model gave a low influence score to a highly cited article on a new linguistics research database that was published in 1993 in the Association for Computational Linguistics Anthology. “That paper introduced a very important resource, but did not present paradigm-changing ideas,” Blei said. “Consequently, our language-based approach could not correctly identify its impact.”

Blei said their model was not meant as a replacement for citation counts but as an alternative method for measuring influence that might be extended to finding influential news stories, websites, and legal and historical documents.

“We are also exploring the idea that you can find patterns in how language changes over time,” he said. “Once you’ve identified the shapes of those patterns, you might be able to recognize something important as it develops, to predict the next big idea before it’s gotten big.”

Adapted from materials provided by Princeton University

see http://www.eurekalert.org/pub_releases/2010-10/pues-nsm102010.php

Walter Derzko

 

Smart Preemie Monitors

From Science this week,

 

A Better Way to Monitor Preemies?

Babies born too early often struggle to survive. But doctors can have a hard time telling which preemies are going to develop serious health problems, such as respiratory failure, and which ones are going to be fine.

To create a better diagnostic, researchers including Anna Penn, a neonatologist at Lucile Packard Children's Hospital in Palo Alto, California and Daphne Koller, a computer scientist at Stanford University, examined physiological data routinely collected in the first 3 hours of life by bedside monitors, such as heart rate, respiratory rate, and the amount of oxygen in the blood.

When they modeled these data, they observed signatures in sick babies that were different from the ones they observed in healthy ones.

They used these differences to develop a scoring system, called PhysiScore. As the researchers report in Science Translational Medicine, they were able to predict serious complications with an accuracy of between 91% and 98%—far better than current approaches, such as the so-called Apgar score.

Penn says the same techniques might also work to identify high-risk surgical patients or adults most likely to suffer complications following a heart attack.

Sarcasm detecting software; Just what everyone needs (not)

New Scientist writes last week:

Just what we need: sarcasm software  25 May 2010 by MacGregor Campbell

Computers are getting better at understanding human languages, thanks partly to algorithms that can analyse sentences for positive or negative sentiments, says Ari Rappoport of the Hebrew University of Jerusalem, Israel.  But picking up on sarcasm is still a problem.  "In many cases, sarcasm is difficult even for people to recognise", never mind computers, he says.

Rappoport and colleagues wrote a sentiment-analysing program.  They then trained this software to recognise sarcasm by feeding it sentences that had been flagged up by human reviewers as likely to contain sarcasm.

The team used the trained program to analyse a selection of product reviews on Amazon.com and a random selection of posts on Twitter.  Three human volunteers were asked to rate the same material for sarcastic content.

The algorithm agreed with the volunteers 77 per cent of the time for Amazon.com product reviews and 83 per cent of the time for the tweets.

Nice work, really "It is a very exciting paper, because it attacks a problem that I didn't really think we were ready to make headway on," says Lillian Lee, a natural language processing expert at Cornell University in Ithaca, New York, who was not involved with the study.

David Traum, a language researcher at the University of Southern California in Marina del Rey, says that getting people to agree about what constitutes sarcasm from single utterances with little context is difficult.  "Really all we can say is that for these cases computers are about as good as people at agreeing with other people about what is sarcastic."

The research was presented at the International AAAI Conference on Weblogs and Social Media in Washington DC this week.  The tool could be used by marketers to track online public sentiment surrounding brands."

Walter Derzko, The Opportunity Clinic, Smart Economy, Toronto

Mathematicians Solve 140-Year-Old Boltzmann Equation

Although scientist have known how gases behave in a general manner, trying to predict what any individual gas molecule with do in time and space is another mater altogether

 

Mathematicians Solve 140-Year-Old Boltzmann Equation

PHILADELPHIA –- Two University of Pennsylvania mathematicians have found solutions to a 140-year-old, 7-dimensional equation that were not known to exist for more than a century despite its widespread use in modeling the behavior of gases.

The study, part historical journey but mostly mathematical proof, was conducted by Philip T. Gressman and Robert M. Strain of Penn’s Department of Mathematics.  The solution of the Boltzmann equation problem was published in the Proceedings of the National Academy of Sciences.  Solutions of this equation, beyond current computational capabilities, describe the location of gas molecules probabilistically and predict the likelihood that a molecule will reside at any particular location and have a particular momentum at any given time in the future.

During the late 1860s and 1870s, physicists James Clerk Maxwell and Ludwig Boltzmann developed this equation to predict how gaseous material distributes itself in space and how it responds to changes in things like temperature, pressure or velocity. 

The equation maintains a significant place in history because it modeled gaseous behavior well, and the predictions it led to were backed up by experimentation.  Despite its notable leap of faith -- the assumption that gases are made of molecules, a theory yet to achieve public acceptance at the time — it was fully adopted.  It provided important predictions, the most fundamental and intuitively natural of which was that gasses naturally settle to an equilibrium state when they are not subject to any sort of external influence.  One of the most important physical insights of the equation is that even when a gas appears to be macroscopically at rest, there is a frenzy of molecular activity in the form of collisions.  While these collisions cannot be observed, they account for gas temperature.

Gressman and Strain were intrigued by this mysterious equation that illustrated the behavior of the physical world, yet for which its discoverers could only find solutions for gasses in perfect equilibrium. 

Using modern mathematical techniques from the fields of partial differential equations and harmonic analysis — many of which were developed during the last five to 50 years, and thus relatively new to mathematics — the Penn mathematicians proved the global existence of classical solutions and rapid time decay to equilibrium for the Boltzmann equation with long-range interactions.  Global existence and rapid decay imply that the equation correctly predicts that the solutions will continue to fit the system’s behavior and not undergo any mathematical catastrophes such as a breakdown of the equation’s integrity caused by a minor change within the equation.  Rapid decay to equilibrium means that the effect of an initial small disturbance in the gas is short-lived and quickly becomes unnoticeable.

“Even if one assumes that the equation has solutions, it is possible that the solutions lead to a catastrophe, like how it’s theoretically possible to balance a needle on its tip, but in practice even infinitesimal imperfections cause it to fall over,” Gressman said. 

The study also provides a new understanding of the effects due to grazing collisions, when neighboring molecules just glance off one another rather than collide head on.  These glancing collisions turn out to be dominant type of collision for the full Boltzmann equation with long-range interactions.

“We consider it remarkable that this equation, derived by Boltzmann and Maxwell in 1867 and 1872, grants a fundamental example where a range of geometric fractional derivatives occur in a physical model of the natural world,” Strain said.  “The mathematical techniques needed to study such phenomena were only developed in the modern era.”

The study was funded by the National Science Foundation.

 

http://www.upenn.edu/pennnews/news/university-pennsylvania-mathematicians-solve-140-year-old-boltzmann-equation-gaseous-behaviors

Walter Derzko 

Novel Qualitative/Quanitative Scenario Interviewing methodology for complex systems & risk illumination / mitigation developed by grad students at OCAD. Toronto

With all the attention on Goldman Sachs, greed, risk-shifting and deception, any new methods for risk illumination would benefit business, government and the consumer. 

A team of graduate students at OCAD MA Design program in Strategic Foresight and Innovation (SFI) in Toronto have developed a unique semi quantitative and qualitative scenario and interviewing methodology-which they trialed on the topic of Carbon Capture.  

But it can be applied equally well to other wicked, complex, risk-embedded issues and problems. It addresses stakeholder perceptions, real and perceived risks, liabilities and decision paradoxes and contradictions, better then any other method I’ve seen.

It seems that it might be useful as a decision-making aid and policy development tool in complex. multifactor scenarios where cross impact analysis is needed, and where the need to surface often dynamic and ever changing /evolving stakeholder situational mental models, emerging unintended consequences, conflicts, paradoxes, contradictions and anomalies that may be critical or significant  (ie Critical success factor) in the overall process.

Individual foresight methods don’t capture all this richness

 As they cite in their research report: “We’ve spent a fair amount of thought in separating out factors of biases towards and against other stakeholders in order to elicit the actual objective and subjective perceptions of each, and how those will come into game theoretic conflict…[…]… We used neuro-dynamic programming, also known as reinforcement learning.  This works by treating the domain as a partially-observable Markov decision process (POMDP).

 As a next step, they  are now looking at incorporating the sense-making methodology and my database of social, behavioral and cognitive biases from the Opportunity Clinic into the process.

To date this is proprietary and unpublished work 

I think it’s ready to take public.

The students are trying to identify a private corporation or government agency or Ministry who would be interested in this as a pilot project to use this method in addressing some of their wicked problems.

Any leads, contacts or suggestions appreciated.

Walter Derzko, The Opportunity Clinic.Smart Economy,Toronto

Sr. Fellow S-Lab, OCAD, MA Design in Strategic Foresight & Innovation (OCAD) 

New ways of anticipating, measuring and managing catastrophic risks or black swan events

New ways of measuring catastrophic risks may enhance Air Force efforts

US Air Force Office of Scientific Research-funded researcher, Dr. Graciela Chichilnisky is pioneering a new approach for measuring, anticipating and managing catastrophic risks, sometimes called "Black Swans" or natural catastrophes like hurricanes, tornadoes, tsunamis and floods that may possibly enhance the Air Force's capabilities of preparing for disasters.

"This research is important because it will provide solid foundations to help the Air Force and the public better prepare for the impact of catastrophic risks, communicate to experts and make decisions that can enhance national security," said Chichilnisky from her office at the Columbia University Consortium on Risk Management where the research is occurring.

Her team has developed new tools in probability and statistics for ranking risks, giving realistic prioritization to catastrophic events, making decisions under unpredictable conditions preceding an event and evaluating the economic after-effects of a disaster.  They have also been conducting research, experiments validating theories and finding that decisions made under uncertainty do not always match up with classic treatment of Black Swans.  Using their current findings as well as historical research, the team is rewriting the foundations of probability, statistics and decision-making for Black Swan events that better fit the observations.

"Our goal is to link our latest results, analytical tools and experimental efforts with other new theoretical and empirical strands of the literature in this area," she said.

The emerging statistics and probabilities will provide a new foundation, changing the field of research in a way that is more appropriate for Black Swans, which are now occurring with more regularity because of climate, migration and coastal changes.

"We need to organize and protect ourselves against natural hazards in a way that increases our capabilities to anticipate, mitigate and respond to catastrophes as was never done before," she said.

From the CCRM web site:

"Over the past decade there has been an increased awareness of risks for which actuarial data quickly lose their validity due to rapid change in both natural and economic environments.  These risks are exemplified by market risks in global markets, risks associated with natural catastrophes and new technologies, business interruption risks and climate variability such as El Nino events, and global climate change.  These risks have a more complex structure and are less understood potentially more dangerous than traditional types of risk.  To face this challenge, new technologies are needed, including: new mathematical and statistical approaches for evaluating and managing risk, new tools involving scientific and financial information for decision making under uncertainty, and new financial instruments including securitization and pricing techniques for hedging risks.  CCRM has been created to address this challenge.  The Consortium is unique in combining the latest scientific knowledge of the prediction and management of climate and other natural hazards, with cutting-edge research in financial engineering and the mathematics of risk.  Its knowledge is leading to new instruments and governmental policies for managing natural hazards.

Walter Derzko, The Opportunity Clinic, Smart Economy, Toronto

New ways of anticipating, measuring and managing catastrophic risks or black swan events

New ways of measuring catastrophic risks may enhance Air Force efforts

US Air Force Office of Scientific Research-funded researcher, Dr. Graciela Chichilnisky is pioneering a new approach for measuring, anticipating and managing catastrophic risks, sometimes called "Black Swans" or natural catastrophes like hurricanes, tornadoes, tsunamis and floods that may possibly enhance the Air Force's capabilities of preparing for disasters.

"This research is important because it will provide solid foundations to help the Air Force and the public better prepare for the impact of catastrophic risks, communicate to experts and make decisions that can enhance national security," said Chichilnisky from her office at the Columbia University Consortium on Risk Management where the research is occurring.

Her team has developed new tools in probability and statistics for ranking risks, giving realistic prioritization to catastrophic events, making decisions under unpredictable conditions preceding an event and evaluating the economic after-effects of a disaster.  They have also been conducting research, experiments validating theories and finding that decisions made under uncertainty do not always match up with classic treatment of Black Swans.  Using their current findings as well as historical research, the team is rewriting the foundations of probability, statistics and decision-making for Black Swan events that better fit the observations.

"Our goal is to link our latest results, analytical tools and experimental efforts with other new theoretical and empirical strands of the literature in this area," she said.

The emerging statistics and probabilities will provide a new foundation, changing the field of research in a way that is more appropriate for Black Swans, which are now occurring with more regularity because of climate, migration and coastal changes.

"We need to organize and protect ourselves against natural hazards in a way that increases our capabilities to anticipate, mitigate and respond to catastrophes as was never done before," she said.

Walter Derzko, The Opportunity Clinic, Smart Economy, Toronto