operationalizing complexity
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operationalizing complexity
complexity and the day-to-day operations of firms
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Infographic: The Incredible Growth of Web Usage [1984-2013]

Infographic: The Incredible Growth of Web Usage [1984-2013] | operationalizing complexity | Scoop.it

In the three decades since the Internet evolved from an experimental band of academic and government computer systems into a globe-spanning network of interconnected systems, the amount of time spent online has grown to rival (or even exceed) the time spent living offline. Personal computers, tablets and smartphones have made the connected life a reality, and the number of folks pursuing it has exploded.


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Andrew Earnshaw's curator insight, September 20, 2013 3:23 PM

Yes, I too can remember when there wasn't an Internet. Is there an application that's not yet been produced. What next will we all wonder how we did without ?

Al Marqz's curator insight, September 27, 2013 7:14 PM

La humanidad en bloque ha optado por la gran Red y de ésta, por las redes sociales... ¡Larga vida a la web!

Pallab Kakoti's curator insight, April 16, 2014 7:44 AM

The rise & rise of web usage is one of the most unifying & reformative development to have impacted on a global scale. An insightful info-graphic that offers a unique purview from the inception days of internet to the latest trend of app usage estimating an annual revenue of $24 billion.

 

A pure delight that's not to be missed #PlbKkt for #hshdsh via #blogs4bytes //

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The Man Who Invented Modern Probability

The Man Who Invented Modern Probability | operationalizing complexity | Scoop.it

For Kolmogorov, his ideas neither eliminated chance, nor affirmed a fundamental uncertainty about our world; they simply provided a rigorous language to talk about what cannot be known for certain. The notion of “absolute randomness” made no more sense than “absolute determinism,” he once remarked, concluding, “We can’t have positive knowledge of the existence of the unknowable.” Thanks to Kolmogorov, though, we can explain when and why we don’t.

 

http://nautil.us/issue/4/the-unlikely/the-man-who-invented-modern-probability


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Russell Foster: Why do we sleep?

Russell Foster is a circadian neuroscientist: He studies the sleep cycles of the brain. And he asks: What do we know about sleep? Not a lot, it turns out, for something we do with one-third of our lives. In this talk, Foster shares three popular theories about why we sleep, busts some myths about how much sleep we need at different ages -- and hints at some bold new uses of sleep as a predictor of mental health.

 

http://www.ted.com/talks/russell_foster_why_do_we_sleep.html


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Controlling Self-Organizing Dynamics on Networks Using Models that Self-Organize

Controlling self-organizing systems is challenging because the system responds to the controller. Here, we develop a model that captures the essential self-organizing mechanisms of Bak-Tang-Wiesenfeld (BTW) sandpiles on networks, a self-organized critical (SOC) system. This model enables studying a simple control scheme that determines the frequency of cascades and that shapes systemic risk. We show that optimal strategies exist for generic cost functions and that controlling a subcritical system may drive it to criticality. This approach could enable controlling other self-organizing systems.

 

Controlling Self-Organizing Dynamics on Networks Using Models that Self-Organize

Pierre-André Noël, Charles D. Brummitt, and Raissa M. D’Souza

Phys. Rev. Lett. 111, 078701 (2013)

http://dx.doi.org/10.1103/PhysRevLett.111.078701

 

Selected for a Viewpoint http://physics.aps.org/articles/v6/90


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Limited Urban Growth: London's Street Network Dynamics since the 18th Century

We investigate the growth dynamics of Greater London defined by the administrative boundary of the Greater London Authority, based on the evolution of its street network during the last two centuries. This is done by employing a unique dataset, consisting of the planar graph representation of nine time slices of Greater London's road network spanning 224 years, from 1786 to 2010. Within this time-frame, we address the concept of the metropolitan area or city in physical terms, in that urban evolution reveals observable transitions in the distribution of relevant geometrical properties. Given that London has a hard boundary enforced by its long standing green belt, we show that its street network dynamics can be described as a fractal space-filling phenomena up to a capacitated limit, whence its growth can be predicted with a striking level of accuracy. This observation is confirmed by the analytical calculation of key topological properties of the planar graph, such as the topological growth of the network and its average connectivity. This study thus represents an example of a strong violation of Gibrat's law. In particular, we are able to show analytically how London evolves from a more loop-like structure, typical of planned cities, toward a more tree-like structure, typical of self-organized cities. These observations are relevant to the discourse on sustainable urban planning with respect to the control of urban sprawl in many large cities which have developed under the conditions of spatial constraints imposed by green belts and hard urban boundaries.

 

Masucci AP, Stanilov K, Batty M (2013) Limited Urban Growth: London's Street Network Dynamics since the 18th Century. PLoS ONE 8(8): e69469. http://dx.doi.org/10.1371/journal.pone.0069469


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ComplexInsight's curator insight, August 20, 2013 2:02 AM

Mike Batty has created a truly world class research group and this paper by Paula Masucci and Mike is a great addition to literature relating to sustainable cities.

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Power Laws and Fragility in Flow Networks

What makes economic and ecological networks so unlike other highly skewed networks in their tendency toward turbulence and collapse? Here, we explore the consequences of a defining feature of these networks: their nodes are tied together by flow. We show that flow networks tend to the power law degree distribution (PLDD) due to a self-reinforcing process involving position within the global network structure, and thus present the first random graph model for PLDDs that does not depend on a rich-get-richer function of nodal degree. We also show that in contrast to non-flow networks, PLDD flow networks are dramatically more vulnerable to catastrophic failure than non-PLDD flow networks, a finding with potential explanatory power in our age of resource- and financial-interdependence and turbulence.

 

Power Laws and Fragility in Flow Networks
Jesse Shore, Catherine J. Chu, Matt T. Bianchi

http://arxiv.org/abs/1308.0726


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A helpful article

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Unsupervised Machine Learning, Most Promising Ingredient Of Big Data

Unsupervised Machine Learning, Most Promising Ingredient Of Big Data | operationalizing complexity | Scoop.it

Orange (France Telecom), one of the largest mobile operators in the world, issued a challenge “Data for Development” by releasing a dataset of their subscribers in Ivory Coast. The dataset contained 2.5 billion records, calls and text messages exchanged between 5 million anonymous users in Ivory Coast, Africa. Various researchers got access to this dataset and submitted their proposals on how this data can be used for development purposes in Ivory Coast. It would be an understatement to say these proposals and projects were mind-blowing. I have never seen so many different ways of looking at the same data to accomplish so many different things. Here’s a book [very large pdf, right-click to save instead of opening it online] that contains all the proposals. My personal favorite is AllAborad where IBM researchers used the cell-phone data to redraw optimal bus routes. The researchers have used several algorithms including supervised and unsupervised machine learning to analyze the dataset resulting in a variety of scenarios.


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Bill Aukett's insight:

Reminds that;

there can be many "right' answers to the same problem, 

you can spend time and money finding the "right"answer to tthe "wrong" problem, and

somestimes there are "issues to manage and not problems to solve" (Johnson , Polarity Management.)

 

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Bian Wu's curator insight, October 12, 2014 9:40 PM

a huge collections of data mining of the France telecom data

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Complexity Economics: A Different Framework for Economic Thought

This paper provides a logical framework for complexity economics. Complexity economics builds from the proposition that the economy is not necessarily in equilibrium: economic agents (firms, consumers, investors) constantly change their actions and strategies in response to the outcome they mutually create. This further changes the outcome, which requires them to adjust afresh. Agents thus live in a world where their beliefs and strategies are constantly being “tested” for survival within an outcome or “ecology” these beliefs and strategies together create. Economics has largely avoided this nonequilibrium view in the past, but if we allow it, we see patterns or phenomena not visible to equilibrium analysis. These emerge probabilistically, last for some time and dissipate, and they correspond to complex structures in other fields. We also see the economy not as something given and existing but forming from a constantly developing set of technological innovations, institutions, and arrangements that draw forth further innovations, institutions and arrangements.(...) 

 

Complexity Economics: A Different Framework for Economic Thought
W. Brian Arthur
SFI WP 13-04-012

http://www.santafe.edu/research/working-papers/abstract/36df2f7d8ecd8941d8fab92ded2c4547/


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Bill Aukett's insight:

If you've read Waldrop's account of the development of the complexity paradigm at the Sante Fe Institute (Waldrop, M, (1992) Complexity: The Emerging Science at the Edge of Chaos, Simon & Schuster, New York), the name Brian Arthur will be familiar.

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ComplexInsight's curator insight, July 15, 2013 5:00 AM

Brian Arthur was an early pioneer of applying concepts of complex systems to economic systems and its good to see an update publication that builds on his earlier work and other work in this area. Certainly worth reading.

Betty Cares's curator insight, July 17, 2013 9:39 AM

Another interesting paper from one of our great complexity thinkers, Brian Arthur, author of the El Farol Problem.  I will publish that here soon too!

Luciano Lampi's curator insight, July 18, 2013 8:11 AM

does democracy represent the best tool to face non-equilibrium states and emergence? 

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Big Data: When Cars Can Talk

The roads would be safer if cars could exchange information about traffic conditions and bad drivers. But are we ready to sacrifice privacy to save lives?

 

Has this ever happened to you? You're cruising down the highway, moving with the flow, when a lane-splitting motorcyclist suddenly zips past, nearly sideswiping you at 90 mph. Situations like these too often result in traffic accidents. And the daredevil cyclist isn't the only road hazard out there. We've all encountered the distracted texter, the inebriated weaver -- maybe even the wild-eyed suspect in a police car chase.

 

Wouldn't it be nice to get a heads-up when bad drivers are approaching? An early-warning system that gives you enough time to take defensive action?


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Bill Aukett's insight:

While road systems are merely complicated, the activity of driving is complex as is traffic flow. 

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UCLA life scientists present new insights on climate change and species interactions

UCLA life scientists present new insights on climate change and species interactions | operationalizing complexity | Scoop.it

UCLA life scientists provide important new details on how climate change will affect interactions between species in research published online May 21 in the Journal of Animal Ecology. This knowledge, they say, is critical to making accurate predictions and informing policymakers of how species are likely to be impacted by rising temperatures. "There is a growing recognition among biologists that climate change is affecting how species interact with one another, and that this is going to have very important consequences for the stability and functioning of ecosystems," said the senior author of the research, Van Savage, an assistant professor of ecology and evolutionary biology and of biomathematics at UCLA. "However, there is still a very limited understanding of exactly what these changes will be. Our paper makes progress on this very important question."


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Can Life Evolve from Wires and Plastic?

Can Life Evolve from Wires and Plastic? | operationalizing complexity | Scoop.it

In a laboratory tucked away in a corner of the Cornell University campus, Hod Lipson’s robots are evolving. He has already produced a self-aware robot that is able to gather information about itself as it learns to walk. Like a Toy Story character, it sits in a cubby surrounded by other former laboratory stars.

 

There’s a set of modular cubes, looking like a cross between children’s blocks and the model cartilage one might see at the orthopedist’s—this particular contraption was one of the world’s first self-replicating robots. And there are cubbies full of odd-shaped plastic sculptures.

 

The robots and the 3D printer-pieces populating the cubbies are like fossils tracing the evolutionary history of a new kind of organism. ‘I want to evolve something that is life,’ Lipson told me, ‘out of plastic and wires and inanimate materials.’

 

Upon first meeting, Lipson comes off like a cross between Seth Rogen and Gene Wilder’s Young Frankenstein (minus the wild blond hair). You can’t miss his passionate desire to understand what makes life tick. And yet, as he seeks to create a self-assembling, self-aware machine that can walk right out of his laboratory, Lipson is aware of the risks:

 

‘As much as we are control freaks when it comes to engineering, where this is going toward is loss of control. The more we automate, the more we don’t know what’s going to come out of it.’


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Bill Aukett's insight:

Fascination account. Poses interesting philosophical questions about awareness, consciousness and evolutionary ethics. eg Can a machine be self aware?

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People behave socially and 'well' even without rules: study

People behave socially and 'well' even without rules: study | operationalizing complexity | Scoop.it
Fundamentally people behave in a social and rather compassionate and 'good' way rather than aggressively, even without specified rules.

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What If Everything Ran Like the Internet?

What If Everything Ran Like the Internet? | operationalizing complexity | Scoop.it

When the Internet was first starting to catch on in the 1980s, I was invited, as a representative of a large business consulting organization, to a day-long seminar explaining what this new phenomenon was and how businesses should be responding to it. It was led by a man who now makes millions as a social media guru (I won’t embarrass him by identifying him), but at the time he warned that the Internet had no future. The reason, he said, was that it was “anarchic” — there was no management, no control, no way of fixing things quickly if they got “out of hand”. The solution, he said, was for business and government leaders to get together and create an orderly alternative — “Internet 2″ he called it — that would replace the existing Internet when it inevitably imploded. Of course, he couldn’t have been more wrong.


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Olivier Auber's comment, May 29, 2013 5:19 AM
In fact, the Internet as we know it, is also hierarchical, due to its silos and protocols.
https://www.youtube.com/watch?v=8c0sX6j5D_c
luiy's curator insight, May 31, 2013 9:57 AM

Organization models --- > Internet --> “wirearchy” --> nature’s model of self-organizing, self-adapting, evolving complex systems

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The Limits of Phenomenology: From Behaviorism to Drug Testing and Engineering Design

It is widely believed that theory is useful in physics because it describes simple systems and that strictly empirical phenomenological approaches are necessary for complex biological and social systems. Here we prove based upon an analysis of the information that can be obtained from experimental observations that theory is even more essential in the understanding of complex systems. Implications of this proof revise the general understanding of how we can understand complex systems including the behaviorist approach to human behavior, problems with testing engineered systems, and medical experimentation for evaluating treatments and the FDA approval of medications. Each of these approaches are inherently limited in their ability to characterize real world systems due to the large number of conditions that can affect their behavior. Models are necessary as they can help to characterize behavior without requiring observations for all possible conditions. The testing of models by empirical observations enhances the utility of those observations. For systems for which adequate models have not been developed, or are not practical, the limitations of empirical testing lead to uncertainty in our knowledge and risks in individual, organizational and social policy decisions. These risks should be recognized and inform our decisions.

 

The Limits of Phenomenology: From Behaviorism to Drug Testing and Engineering Design
Yaneer Bar-Yam

http://arxiv.org/abs/1308.3094


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Isaac Fetterhoff's curator insight, September 21, 2015 9:28 PM

I think this post is great because it coincides well with behavior and its study. It allows an interesting link to be learned between each of these items and i think it provides valuable information.

Dan bivins's curator insight, October 27, 2015 3:38 AM

It makes since if the medicine or whatever being tested isn't yet FDA approved if it is a new drug. Behaviorism will tell us how they may react to it and see if it is appropriate and will improve everyday life. The risks are already informed the to participants before  the study anyways, so I don't really see a limit/problem with it. 

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Development and Deployment at Facebook

Development and Deployment at Facebook | operationalizing complexity | Scoop.it

Internet companies such as Facebook operate in a "perpetual development" mindset. This means that the website continues to undergo development with no predefined final objective, and that new developments are deployed so that users can enjoy them as soon as they're ready. To support this, Facebook uses both technical approaches such as peer review and extensive automated testing, and a culture of personal responsibility.

 

More than a billion users log in to Facebook at least once a month to connect and share content with each other. Among other activities, these users upload more than 2.5 billion content items daily. Here, we describe the development and deployment of the software that supports this activity, focusing on the site's primary codebase for the Web front end. Information on Facebook's architecture and other software components is available elsewhere.


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It's the implications of continuous development and deployment that I find intriguing

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Time Reborn: a new theory of time - a new view of the world

Is it possible that time is real, and that the laws of physics are not fixed? Lee Smolin, A C Grayling, Gillian Tett, and Bronwen Maddox explore the implications of such a profound re-think of the natural and social sciences, and consider how it might impact the way we think about surviving the future.


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Controlling Self-Organizing Dynamics on Networks Using Models that Self-Organize

Controlling self-organizing systems is challenging because the system responds to the controller. Here, we develop a model that captures the essential self-organizing mechanisms of Bak-Tang-Wiesenfeld (BTW) sandpiles on networks, a self-organized critical (SOC) system. This model enables studying a simple control scheme that determines the frequency of cascades and that shapes systemic risk. We show that optimal strategies exist for generic cost functions and that controlling a subcritical system may drive it to criticality. This approach could enable controlling other self-organizing systems.

 

Controlling Self-Organizing Dynamics on Networks Using Models that Self-Organize

Pierre-André Noël, Charles D. Brummitt, and Raissa M. D’Souza

Phys. Rev. Lett. 111, 078701 (2013)

http://dx.doi.org/10.1103/PhysRevLett.111.078701

 

Selected for a Viewpoint http://physics.aps.org/articles/v6/90


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Generating functionals for guided self-organization

Time evolution equations for dynamical systems can often be derived from generating functionals. Examples are Newton's equations of motion in classical dynamics which can be generated within the Lagrange or the Hamiltonian formalism. We propose that generating functionals for self-organizing complex systems offer several advantages. Generating functionals allow to formulate complex dynamical systems systematically and the results obtained are typically valid for classes of complex systems, as defined by the type of their respective generating functionals. The generated dynamical systems tend, in addition, to be minimal, containing only few free and undetermined parameters. We point out that two or more generating functionals may be used to define a complex system and that multiple generating function may not, and should not, be combined into a single overall objective function. We provide and discuss examples in terms of adapting neural networks.

 

Generating functionals for guided self-organization
Claudius Gros

http://arxiv.org/abs/1307.7872


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Designing living matter. Can we do better than evolution?

Thanks to substantial improvements in the theory of metabolic fluxes and the application of 13C isotope markers in experimental flux studies, Pareto efficiency of bacterial metabolism can now be determined and direct answers to the long standing questions of optimization according to multiple criteria in nature can be given. Cells or organisms operate close to Pareto optima but the performance with respect to every single criterion is almost always improvable. Rational design and evolutionary methods are routinely used for the production of biomolecules with optimized properties. Examples are proteins for technical applications, for example in detergents, and optimally binding nucleic acid molecules called aptamers. Among the various perspectives of synthetic biology, the usage of DNA for information storage is particularly promising: In a pilot experiment, an entire book including figures and a Java script, in total more than 5 megabit, were stored on a single DNA molecule. 

 

Schuster, P. (2013), Designing living matter. Can we do better than evolution?. Complexity, 18: 21–33. http://dx.doi.org/10.1002/cplx.21461


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thought provoking perspective on complexity

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Life as we know it

This paper presents a heuristic proof (and simulations of a primordial soup) suggesting that life—or biological self-organization—is an inevitable and emergent property of any (ergodic) random dynamical system that possesses a Markov blanket. This conclusion is based on the following arguments: if the coupling among an ensemble of dynamical systems is mediated by short-range forces, then the states of remote systems must be conditionally independent. These independencies induce a Markov blanket that separates internal and external states in a statistical sense. The existence of a Markov blanket means that internal states will appear to minimize a free energy functional of the states of their Markov blanket. Crucially, this is the same quantity that is optimized in Bayesian inference. Therefore, the internal states (and their blanket) will appear to engage in active Bayesian inference. In other words, they will appear to model—and act on—their world to preserve their functional and structural integrity, leading to homoeostasis and a simple form of autopoiesis.

 

Life as we know it
Karl Friston

J. R. Soc. Interface 6 September 2013 vol. 10 no. 86 20130475

http://dx.doi.org/10.1098/ rsif.2013.0475


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ComplexInsight's curator insight, July 27, 2013 2:56 AM

one for reading list for later.

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Social Networking in the 1600s

Social Networking in the 1600s | operationalizing complexity | Scoop.it

SOCIAL networks stand accused of being enemies of productivity. According to one popular (if questionable) infographiccirculating online, the use of Facebook, Twitter and other such sites at work costs the American economy $650 billion each year. Our attention spans are atrophying, our test scores declining, all because of these “weapons of mass distraction.”

 

Yet such worries have arisen before. In England in the late 1600s, very similar concerns were expressed about another new media-sharing environment, the allure of which seemed to be undermining young people’s ability to concentrate on their studies or their work: the coffeehouse. It was the social-networking site of its day.

 

Like coffee itself, coffeehouses were an import from the Arab world. England’s first coffeehouse opened in Oxford in the early 1650s, and hundreds of similar establishments sprang up in London and other cities in the following years. People went to coffeehouses not just to drink coffee, but to read and discuss the latest pamphlets and news-sheets and to catch up on rumor and gossip.

 

Coffeehouses were also used as post offices. Patrons would visit their favorite coffeehouses several times a day to check for new mail, catch up on the news and talk to other coffee drinkers, both friends and strangers. Some coffeehouses specialized in discussion of particular topics, like science, politics, literature or shipping. As customers moved from one to the other, information circulated with them.


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Luciano Lampi's curator insight, June 27, 2013 8:11 AM
Living in the Past

 

Jethro Tull
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World Science Festival: Self-Aware Robots and Living among Thinking Machines

In recent years, machines have grown increasingly capable of listening, communicating, and learning—transforming the way they collaborate with us, and significantly impacting our economy, health, and daily routines. Who, or what, are these thinking machines? As we teach them to become more sophisticated, how will they complement our lives? What will separate their ways of thinking from ours? And what happens when these machines understand data, concepts, and behaviors too big or impenetrable for humans to grasp? We were joined by IBM's WATSON, the computer Jeopardy! champion, along with leading roboticists and computer scientists, to explore the thinking machines of today and the possibilities to come in the not-too-distant future.


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Can six billion cells phones collecting data on how people move lead to better human health?

Can six billion cells phones collecting data on how people move lead to better human health? | operationalizing complexity | Scoop.it

Collecting and analyzing information from simple cell phones can provide surprising insights into how people move about and behave—and even help us understand the spread of diseases.

 

At a computer in her office at the Harvard School of Public Health in Boston, epidemiologist Caroline Buckee points to a dot on a map of Kenya’s western highlands, representing one of the nation’s thousands of cell-phone towers. In the fight against malaria, Buckee explains, the data transmitted from this tower near the town of Kericho has been epidemiological gold.

 

When she and her colleagues studied the data, she found that people making calls or sending text messages originating at the Kericho tower were making 16 times more trips away from the area than the regional average. What’s more, they were three times more likely to visit a region northeast of Lake Victoria that records from the health ministry identified as a malaria hot spot. The tower’s signal radius thus covered a significant waypoint for transmission of malaria, which can jump from human to human via mosquitoes. Satellite images revealed the likely culprit: a busy tea plantation that was probably full of migrant workers. The implication was clear, Buckee says. “There will be a ton of infected [people] there.”


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Context Aware Computing Market- How Context Awareness is Making Your Gadgets Smarter

Context awareness works in complementary manner to location awareness. Location awareness is all about determining the processes and operation of various devices. Context awareness is a sort of pervasive computing, which is available in smart phones. It offers great flexibility to the mobile users, making mobile usage a swift and intriguing experience. Context aware computing provides information, technologies and applications, which are personalized as per the requirements of the users. These requirements include location, social context, proximity to other devices and objects, environmental factors and activity level. Context-triggering actions are easy to perform on mobiles and other computing devices that use context to enhance the end user experience.


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Bill Aukett's insight:

If the relationship between technology and complexity is of interest, check this out

 

http://on.ted.com/Quadcopter

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Derek IAnson's curator insight, June 15, 2013 2:50 PM

Every day new electronic products are coming out on the market. These are ideal for the person who loves gadgets and likes to try new things. For someone hard to buy for, find a new gadget and get it before anyone else. They’ll love being among the firsts to have it!

 

Computer programming makes use of a code or a language: this language can be placed into several lines of code that can be translated to mean different things once they are processed as a program. For instance, the software that you use to calculate your taxes, or the software that you employ to make your simple web page are all products of skilful computer programming.

 

visit my website for all electronic gadgets:http://gadgets4today.weebly.com/




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Swarm Intelligence In Marketing!

Swarm Intelligence In Marketing! | operationalizing complexity | Scoop.it

New concept is emerging, that marketing strategies should be based on swarm intelligence. Swarm intelligence is the offshoot of artificial intelligence. In simple terms, we can describe this field of study as “Collective Wisdom”.

 

Ant Colonies inspire this subject, which exhibits fascinating behavior of teamwork and intelligence. In individual capacity, they are raw but when they socialize and work as team then they become intelligent. In Ant colonies, there is no leader and no one dictates any rules to the masses, rather everyone is doing very simple tasks of sensing scents of the preceding ant and just thinks about the obstacle in front of them. They interact with the obstacle in a collective manner for example by making bridges of ants over obstacle or following shortest routes etc.


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Usman Tahir's comment, June 15, 2013 2:34 PM
Thanks for scooping this post and its a learning curve visiting your page due to diversity of the topics you have covered! In the meanwhile i have posted another post on creating Digital Pheromone for digital marketing at http://wp.me/p3zzEe-4M.