Innovation, Complexity, Clouds
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What is complexity?

What is complexity? | Innovation, Complexity, Clouds | Scoop.it
There are these two young fish swimming along and they happen to meet an older fish swimming the other way, who nods at them and says "Morning, boys. How's the water?" And the two young fish swim on for a...

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Insight Maker | Free Simulation and Modeling in your Browser

Insight Maker | Free Simulation and Modeling in your Browser | Innovation, Complexity, Clouds | Scoop.it

Via Jürgen Kanz
Lynn Sutherland's insight:

I haven't tried this yet, but will this weekend

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Jürgen Kanz's curator insight, February 8, 2015 5:59 AM

I like the software and it's free

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An Infographic That Maps 2,000 Years of Cultural History in 5 Minutes

An Infographic That Maps 2,000 Years of Cultural History in 5 Minutes | Innovation, Complexity, Clouds | Scoop.it

Ah, Hollywood. Our glowing beacon of modern hope and dreams. But before Hollywood, there was New York, and before New York there was Berlin, Paris, Rome and Greece. History’s most creative people have always flocked to cultural and intellectual hubs, and now, thanks to an amazing visualization from researchers at the University of Texas at Dallas, we can see how that migration has changed over time.

 

Last week in the journal Science, the researchers (led by University of Texas art historian Maximilian Schich) published a study that looked at the cultural history of Europe and North America by mapping the birth and deaths of more than 150,000 notable figures—including everyone from Leonardo Da Vinci to Ernest Hemingway. That data was turned into an amazing animated infographic that looks strikingly similar to the illustrated flight paths you find in the back of your inflight magazine. Blue dots indicate a birth, red ones means death.


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Sex Determination: Why So Many Ways of Doing It?

Sex Determination: Why So Many Ways of Doing It? | Innovation, Complexity, Clouds | Scoop.it

Sexual reproduction is an ancient feature of life on earth, and the familiar X and Y chromosomes in humans and other model species have led to the impression that sex determination mechanisms are old and conserved. In fact, males and females are determined by diverse mechanisms that evolve rapidly in many taxa. Yet this diversity in primary sex-determining signals is coupled with conserved molecular pathways that trigger male or female development. Conflicting selection on different parts of the genome and on the two sexes may drive many of these transitions, but few systems with rapid turnover of sex determination mechanisms have been rigorously studied. Here we survey our current understanding of how and why sex determination evolves in animals and plants and identify important gaps in our knowledge that present exciting research opportunities to characterize the evolutionary forces and molecular pathways underlying the evolution of sex determination.

 

Bachtrog D, Mank JE, Peichel CL, Kirkpatrick M, Otto SP, et al. (2014) Sex Determination: Why So Many Ways of Doing It? PLoS Biol 12(7): e1001899. http://dx.doi.org/10.1371/journal.pbio.1001899


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The direction of evolution: The rise of cooperative organization

The direction of evolution: The rise of cooperative organization | Innovation, Complexity, Clouds | Scoop.it

Two great trends are evident in the evolution of life on Earth: towards increasing diversification and towards increasing integration. Diversification has spread living processes across the planet, progressively increasing the range of environments and free energy sources exploited by life. Integration has proceeded through a stepwise process in which living entities at one level are integrated into cooperative groups that become larger-scale entities at the next level, and so on, producing cooperative organizations of increasing scale (for example, cooperative groups of simple cells gave rise to the more complex eukaryote cells, groups of these gave rise to multi-cellular organisms, and cooperative groups of these organisms produced animal societies). The trend towards increasing integration has continued during human evolution with the progressive increase in the scale of human groups and societies. The trends towards increasing diversification and integration are both driven by selection. An understanding of the trajectory and causal drivers of the trends suggests that they are likely to culminate in the emergence of a global entity. This entity would emerge from the integration of the living processes, matter, energy and technology of the planet into a global cooperative organization. Such an integration of the results of previous diversifications would enable the global entity to exploit the widest possible range of resources across the varied circumstances of the planet. This paper demonstrates that it's case for directionality meets the tests and criticisms that have proven fatal to previous claims for directionality in evolution.


The direction of evolution: The rise of cooperative organization
John E. Stewart

Biosystems
Available online 1 June 2014

http://dx.doi.org/10.1016/j.biosystems.2014.05.006


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Eli Levine's curator insight, June 15, 2014 10:06 PM

Cooperation is the best way to improve, sustain, maintain, and repair.  Competition is what drives everyone and everything towards something different, be it competition for resources or competition against the elements around us.

 

I don't get what the point of competition amongst the species is for.  Part of cooperation, after all, is knowing what works, learning about what could work better or doesn't work, and then letting the negative or sub-optimal slip back beneath the waves of ignorance, such that the new ways can rise to prominence.

 

Change is the only constant in this universe of universes.

 

Yet cooperation, I think, yields the higher and stronger of the universal structures that are out there, even if it means that there are still losers and winners.  The only difference is the level of consent and consensus that's reached within the social, ecological, economical, and/or political landscape.  One way works towards what is best.  The other way simply yields what is best at competing, which is not the same as being the actual best solution to a given problem or condition.

 

Think about it.

Luciano Lampi's curator insight, June 16, 2014 9:51 AM

is this the end of stove pipes?

Ra's curator insight, June 22, 2014 6:02 AM

Have I been reading too much science fiction?

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Carbon Dioxide Levels Climb Into Uncharted Territory for Humans - Highest since 800,000 Years

Carbon Dioxide Levels Climb Into Uncharted Territory for Humans - Highest since 800,000 Years | Innovation, Complexity, Clouds | Scoop.it

The amount of carbon dioxide in the Earth's atmosphere has exceeded 402 parts per million (ppm) during the past two days of observations, which is higher than at any time in at least the past 800,000 years, according to readings from monitoring equipment on a mountaintop in Hawaii. Carbon dioxide, or CO2, is the most important long-lived greenhouse gas responsible for manmade global warming, and it is building up in the atmosphere due to the burning of fossil fuels such as coal, oil and natural gas.

 

Once emitted, a single molecule of carbon dioxide can remain aloft for hundreds of years, which means that the effects of today's industrial activities will be felt for the next several centuries, if not thousands of years. Carbon dioxide and other greenhouse gases, such as methane, warm the planet by absorbing and redirecting outgoing solar radiation that would otherwise escape back into space.

 

In 2013, atmospheric levels of carbon dioxide briefly hit 400 ppm for the first time in mid-May, but this year that symbolic threshold has been crossed even earlier. This means it is more likely that the annual peak, which typically occurs in mid-to-late May, will climb further above 400 ppm for the first time.

 

Although crossing above 400 ppm is largely a symbolic milestone, scientific research indicates that the higher that carbon dioxide concentrations get, the more global temperatures will increase, resulting in a wide range of damaging effects. These impacts will range from global sea level rise to a heightened risk of heat waves, severe droughts and floods, according to a recently released comprehensive assessment of climate science produced by the U.N. Intergovernmental Panel on Climate Change (IPCC).

 

Modern carbon dioxide monitoring began in 1958 on the peak of Hawaii's Mauna Loa volcano, which is more than two miles high. At that time, carbon dioxide concentrations were at just 313 ppm. They have risen rapidly and steadily since then, both at Mauna Loa and at other observatories around the world. The chart documenting this rise is perhaps the most iconic in all of climate science, known as the "Keeling Curve" for Charles David Keeling, the Scripps Institution of Oceanography scientist who began and maintained the monitoring program.


According to the Keeling Curve website, carbon dioxide concentrations spiked to 402.20 parts per million on April 7, whereas data from the National Oceanic and Atmospheric Administration (NOAA) showed a slightly lower level of 402.11 parts per million on the same day. Both data sets indicate that daily carbon dioxide measurements have been at or above 400 ppm since March 29, and the graph appears on course to stay above 400 ppm throughout the rest of the month and into the next.


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Cathryn Wellner's curator insight, April 11, 2014 2:46 PM

For such an intelligent species, we are certainly slow learners. Thanks for this articulation of the issue.

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News Information Flow Tracking, Yay! (NIFTY) : System for large scale real-time tracking of #memes | #datascience #algorithms


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Einstein’s lost theory uncovered

Einstein’s lost theory uncovered | Innovation, Complexity, Clouds | Scoop.it
Physicist explored the idea of a steady-state Universe in 1931.

 

The Big Bang theory had found observational support in the 1920s, when US astronomer Edwin Hubble and others discovered that distant galaxies are moving away and that space itself is expanding. This seemed to imply that, in the past, the contents of the observable Universe had been a very dense and hot ‘primordial broth’.

 

But, from the late 1940s, Hoyle argued that space could be expanding eternally and keeping a roughly constant density. It could do this by continually adding new matter, with elementary particles spontaneously popping up from space, Hoyle said. Particles would then coalesce to form galaxies and stars, and these would appear at just the right rate to take up the extra room created by the expansion of space. Hoyle’s Universe was always infinite, so its size did not change as it expanded. It was in a ‘steady state’.

 

The newly uncovered document shows that Einstein had described essentially the same idea much earlier. “For the density to remain constant new particles of matter must be continually formed,” he writes. The manuscript is thought to have been produced during a trip to California in 1931 — in part because it was written on American note paper.

 

It had been stored in plain sight at the Albert Einstein Archives in Jerusalem — and is freely available to view on its website — but had been mistakenly classified as a first draft of another Einstein paper. Cormac O’Raifeartaigh, a physicist at the Waterford Institute of Technology in Ireland, says that he “almost fell out of his chair” when he realized what the manuscript was about. He and his collaborators have posted their findings, together with an English translation of Einstein’s original German manuscript, on the arXiv preprint server (C. O’Raifeartaigh et al. Preprint at http://arxiv.org/abs/1402.0132; 2014) and have submitted their paper to the European Physical Journal.

 

“This finding confirms that Hoyle was not a crank,” says study co-author Simon Mitton, a science historian at the University of Cambridge, UK, who wrote the 2005 biography Fred Hoyle: A Life in Science. The mere fact that Einstein had toyed with a steady-state model could have lent Hoyle more credibility as he engaged the physics community in a debate on the subject. “If only Hoyle had known, he would certainly have used it to punch his opponents,” O’Raifeartaigh says.

 

Although Hoyle’s model was eventually ruled out by astronomical observations, it was at least mathematically consistent, tweaking the equations of Einstein’s general theory of relativity to provide a possible mechanism for the spontaneous generation of matter. Einstein’s unpublished manuscript suggests that, at first, he believed that such a mechanism could arise from his original theory without modification. But then he realized that he had made a mistake in his calculations, O’Raifeartaigh and his team suggest. When he corrected it — crossing out a number with a pen of a different colour — he probably decided that the idea would not work and set it aside.


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Nacho Vega's curator insight, February 24, 2014 3:02 PM

Helge Kragh: “What the manuscript shows is that although by then he accepted the expansion of space, [Einstein] was unhappy with a Universe changing in time”

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Puppies! Now that I’ve got your attention, complexity theory

Animal behavior isn't complicated, but it is complex. Nicolas Perony studies how individual animals -- be they Scottish Terriers, bats or meerkats -- follow simple rules that, collectively, create larger patterns of behavior. And how this complexity born of simplicity can help them adapt to new circumstances, as they arise.

 

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


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António F Fonseca's curator insight, February 4, 2014 9:40 AM

The guy seems to be confessing some obscure personal sin but the talk is very interesting.

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A Comprehensive List of MOOC (Massive Open Online Courses) Providers

A Comprehensive List of MOOC (Massive Open Online Courses) Providers | Innovation, Complexity, Clouds | Scoop.it

The recent emergence of Massive Open Online Courses, commonly known as MOOCs, is revolutionizing the online education world and is having a profound impact on higher education. With the growing adoption of MOOCs, the number of MOOC providers has also increased many folds.  Below is a comprehensive and up-to-date list of MOOC providers; might be helpful to all interested.

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Usein González's curator insight, January 14, 2014 9:51 PM

Una de las nuevas metodologías de aprendizaje colaborativo está tomando fuerza a nivel mundial mi experiencia en estos cursos son muy didacticos, excelentes videos de apoyo y bien documentados.

asli telli's curator insight, January 15, 2014 4:20 AM

list of lists for MOOC...

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Quantum mechanics explains efficiency of photosynthesis

Quantum mechanics explains efficiency of photosynthesis | Innovation, Complexity, Clouds | Scoop.it

Light-gathering macromolecules in plant cells transfer energy by taking advantage of molecular vibrations whose physical descriptions have no equivalents in classical physics, according to the first unambiguous theoretical evidence of quantum effects in photosynthesis published today in the journal Nature Communications. Scientists have observed previously the quantum character of light transport through the molecular machines at work in natural photosynthesis.

 

The majority of light-gathering macromolecules are composed of chromophores (responsible for the colour of molecules) attached to proteins, which carry out the first step of photosynthesis, capturing sunlight and transferring the associated energy highly efficiently. Previous experiments suggest that energy is transferred in a wave-like manner, exploiting quantum phenomena, but crucially, a non-classical explanation could not be conclusively proved as the phenomena identified could equally be described using classical physics.

 

Often, to observe or exploit quantum mechanical phenomena systems need to be cooled to very low temperatures. This however does not seem to be the case in some biological systems, which display quantum properties even at ambient temperatures.

 

Now, a team at UCL have attempted to identify features in these biological systems which can only be predicted by quantum physics, and for which no classical analogues exist.

 

"Energy transfer in light-harvesting macromolecules is assisted by specific vibrational motions of the chromophores," said Alexandra Olaya-Castro (UCL Physics & Astronomy), supervisor and co-author of the research. "We found that the properties of some of the chromophore vibrations that assist energy transfer during photosynthesis can never be described with classical laws, and moreover, this non-classical behaviour enhances the efficiency of the energy transfer."

 

Molecular vibrations are periodic motions of the atoms in a molecule, like the motion of a mass attached to a spring. When the energy of a collective vibration of two chromphores matches the energy difference between the electronic transitions of these chromophores a resonance occurs and efficient energy exchange between electronic and vibrational degrees of freedom takes place.

 

Providing that the energy associated to the vibration is higher than the temperature scale, only a discrete unit or quantum of energy is exchanged. Consequently, as energy is transferred from one chromophore to the other, the collective vibration displays properties that have no classical counterpart.

 

The UCL team found the unambiguous signature of non-classicality is given by a negative joint probability of finding the chromophores with certain relative positions and momenta. In classical physics, probability distributions are always positive.

 

"The negative values in these probability distributions are a manifestation of a truly quantum feature, that is, the coherent exchange of a single quantum of energy," explained Edward O'Reilly (UCL Physics & Astronomy), first author of the study. "When this happens electronic and vibrational degrees of freedom are jointly and transiently in a superposition of quantum states, a feature that can never be predicted with classical physics."


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12 new universities join Coursera, now offering more than 100 courses

Coursera has announced that 12 universities — including three international institutions — will be joining Princeton University, Stanford University, University of Michigan, and University of Pennsylvania in offering Coursera classes, according to the Coursera Blog.

 

On Coursera, you will now be able to access world-class courses from:

California Institute of TechnologyDuke UniversityÉcole Polytechnique Federale de LausanneGeorgia Institute of TechnologyJohns Hopkins UniversityPrinceton UniversityRice UniversityStanford UniversityUniversity of California, San FranciscoUniversity of EdinburghUniversity of Illinois at Urbana-ChampaignUniversity of MichiganUniversity of PennsylvaniaUniversity of TorontoUniversity of VirginiaUniversity of Washington

You’ll be able to choose from more than 100 courses, from Professor Dan Ariely’s course on irrational behavior, to learning how to program in Scala (taught from the creator of Scala, Professor Martin Odersky from EPFL), to the legendary UVA course “How Things Work” with Professor Louis Bloomfield.

 

You can check out the most current course list here — keep in mind you can enroll in a class even if the start date is TBA.

 

To date, 700,000 students from 190 countries have participated in classes on Coursera, with more than 1.55 million course enrollments total.


Via Dr. Stefan Gruenwald, Ashish Umre
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Sieg Holle's curator insight, February 16, 2014 11:26 AM

Your self help program

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AIXI: To create a super-intelligent machine, start with an equation

AIXI: To create a super-intelligent machine, start with an equation | Innovation, Complexity, Clouds | Scoop.it
Intelligence is a very difficult concept and, until recently, no one has succeeded in giving it a satisfactory formal definition.

 

Most researchers have given up grappling with the notion of intelligence in full generality, and instead focus on related but more limited concepts – but Marcus Hutter argues that mathematically defining intelligence is not only possible, but crucial to understanding and developing super-intelligent machines. From this, his research group has even successfully developed software that can learn to play computer games from scratch.

 

But first, how do we define "intelligence"? Hutter's group has sifted through the psychology, philosophy and artificial intelligence literature and searched for definitions individual researchers and groups came up with. The characterizations are very diverse, but there seems to be a recurrent theme which we have aggregated and distilled into the following definition: Intelligence is an agent's ability to achieve goals or succeed in a wide range of environments.

 

The emerging scientific field is called universal artificial intelligence, with AIXI being the resulting super-intelligent agent. AIXI has a planning component and a learning component. The goal of AIXI is to maximise its reward over its lifetime – that's the planning part.

 

In summary, every interaction cycle consists of observation, learning, prediction, planning, decision, action and reward, followed by the next cycle. If you're interested in exploring further, AIXI integrates numerous philosophical, computational and statistical principles:

 

• Ockham's razor (simplicity) principle for model selection

• Epicurus principle of multiple explanations as a justification of model

   averaging

• Bayes rule for updating beliefs

• Turing machines as universal description language

• Kolmogorov complexity to quantify simplicity

• Solomonoff's universal prior, and

• Bellman equations for sequential decision making.

 

AIXI's algorithm rigorously and uniquely defines a super-intelligent agent that learns to act optimally in arbitrary unknown environments. One can prove amazing properties of this agent – in fact, one can prove that in a certain sense AIXI is the most intelligent system possible. Note that this is a rather coarse translation and aggregation of the mathematical theorems into words, but that is the essence.

 

Since AIXI is incomputable, it has to be approximated in practice. In recent years, we have developed various approximations, ranging from provably optimal to practically feasible algorithms.

 

The point is not that AIXI is able to play these games (they are not hard) – the remarkable fact is that a single agent can learn autonomously this wide variety of environments. AIXI is given no prior knowledge about these games; it is not even told the rules of the games! It starts as a blank canvas, and just by interacting with these environments, it figures out what is going on and learns how to behave well. This is the really impressive feature of AIXI and its main difference to most other projects.

 

Even though IBM Deep Blue plays better chess than human Grand Masters, it was specifically designed to do so and cannot play Jeopardy. Conversely, IBM Watson beats humans in Jeopardy but cannot play chess – not even TicTacToe or Pac-Man. AIXI is not tailored to any particular application. If you interface it with any problem, it will learn to act well and indeed optimally.


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Solving Complex Problems with the 11 Laws of Systems Thinking

Solving Complex Problems with the 11 Laws of Systems Thinking | Innovation, Complexity, Clouds | Scoop.it
Systems thinking is the key to solving complex problems and achieving simplicity. Furthermore, by applying systems thinking to different situations, we also start to recognize the existence of universal patterns of behavior in business and in life.

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Complexity Theory: A short film (5')

A short film about complexity theory and the shift in paradigm from the Newtonian clockwork universe to complex systems. Enjoy : ) From http://www.fotonlabs.com

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Philippe Vallat's curator insight, January 14, 2015 10:47 AM

Nicely done

Leadership Learning Community's curator insight, January 23, 2015 11:31 AM

Visualizes complex systems and networks in a powerful way, brings clarity and a much deeper understanding to very abstract concepts

Jamie Billingham's curator insight, February 25, 2015 12:24 AM

Learning and the education system(s) are incredibly complex. 

 

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Collective Learning and Optimal Consensus Decisions in Social Animal Groups

Collective Learning and Optimal Consensus Decisions in Social Animal Groups | Innovation, Complexity, Clouds | Scoop.it

Learning has been studied extensively in the context of isolated individuals. However, many organisms are social and consequently make decisions both individually and as part of a collective. Reaching consensus necessarily means that a single option is chosen by the group, even when there are dissenting opinions. This decision-making process decouples the otherwise direct relationship between animals' preferences and their experiences (the outcomes of decisions). Instead, because an individual's learned preferences influence what others experience, and therefore learn about, collective decisions couple the learning processes between social organisms. This introduces a new, and previously unexplored, dynamical relationship between preference, action, experience and learning. Here we model collective learning within animal groups that make consensus decisions. We reveal how learning as part of a collective results in behavior that is fundamentally different from that learned in isolation, allowing grouping organisms to spontaneously (and indirectly) detect correlations between group members' observations of environmental cues, adjust strategy as a function of changing group size (even if that group size is not known to the individual), and achieve a decision accuracy that is very close to that which is provably optimal, regardless of environmental contingencies. Because these properties make minimal cognitive demands on individuals, collective learning, and the capabilities it affords, may be widespread among group-living organisms. Our work emphasizes the importance and need for theoretical and experimental work that considers the mechanism and consequences of learning in a social context.

 


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10 Habits Of People Who Follow Their Dreams

10 Habits Of People Who Follow Their Dreams | Innovation, Complexity, Clouds | Scoop.it
1. They see challenges as opportunities Most people interpret fears as obstacles and tend to run away from them. People who live their purpose successfully have developed the capacity to see fear as a sign of what they really need to go for and put all their courage and energy into it. 2. They see […]

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Mónica Díaz's curator insight, July 7, 2014 11:03 AM

Ven los desafíos como oportunidades, ven la vida como un juego, vivir la vida que desean es su única opción, siempre expresan su verdad, no son solo soñadores, actúan, esperan y saben que merecen lo mejor, no sienten miedo o culpa cuando piden lo que necesitan, crean sus propias reglas, aprender a estar cómodos estándo incómodos… tienen maestros, mentores, guías. 

 

Emmanuel 'Manny' Gigante's curator insight, July 7, 2014 1:43 PM

 are you #fearful or #fearless? #bayareafhaguy

Subhash Acharya's curator insight, July 11, 2014 8:20 AM

PHP is the simplest web scripting language in the world and is very easy to learn for anybody. So to get PHP job easily one have to need to be strong in programming logics and his/her confidence level must be good enough to do a job. Though the starting salary as a PHP developer is not so interesting but as it increases you will find yourself in a better position within a year.

After completing PHP training Kolkata , there is a great opportunity to get a job for PHP trained freshers in Kolkata , as well as outside of Kolkata. It opens the way to a person to get a better job in IT fields and gives opportunity to earn good money.

PHP Training Kolkata, Android Training Kolkata, Web Design Training Kolkata and Internet Marketing Training Kolkata from industry expert with individual focus. No course duration. We will teach you untill you learn the whole things of your course.

- See more at: http://www.php-kolkata.com/#sthash.ehFQuOvD.dpuf

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Ganesh Capital launches VC business, aims to make world 'a better place' - Denver Business Journal

Ganesh Capital launches VC business, aims to make world 'a better place' - Denver Business Journal | Innovation, Complexity, Clouds | Scoop.it
A new venture capital firm in Boulder is offering angel investments to businesses that want to make a positive difference.

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Twitter #bots in class. You're here because of a robot | #datascience #agents #influence

Twitter #bots in class. You're here because of a robot | #datascience #agents #influence | Innovation, Complexity, Clouds | Scoop.it
Note: This post is co-written with Piotr Sapieżyński Is it possible for a small computer science course to exert measurable influence (trending topics) on Twitter, a massive social network with hun...

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luiy's curator insight, March 21, 2014 12:34 PM

A large part of our motivation for investigating Twitter bots in class is that the amount of manipulation that humans are experiencing on line is ever increasing. Think, for example, about how Facebook’s time-line filtering algorithm shapes the world view of hundreds of millions around the globe. And that’s just the most main stream example.

 

Social influence

 

As the course progressed, we focused on creating bots that could use machine learning to recognize “good” content for tweeting and retweeting. Bots that are able to detect topics within their tweet-stream … and distinguish between real, human accounts and robots among their followers.

However, the question remained: Can those thousands of followers  be converted to influence on Twitter? For the class’ final project, we decided to put that to the test.

The overall goal was to for each team to build a convincing bot, get human followers, and  at a specified time, for everyone work together to make specific hashtags trend on twitter. So how to achieve that goal? Here’s an overview of what each team has worked on:

 

- Build convincing avatars and use the high follower-counts as part of the disguise. 

 

- Use machine learning to tell who’s a bot and who’s not (in order to focus only on humans and ignoring bots). 

 

- Use natural language processing & machine learning to discover quality content to re-tweet and tweet. 

 

- Use network theory, to explore the network surrounding existing followers, making sure that bot actions reach entire communities.

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#Predicting Successful #Memes using Network and Community Structure | #SNA #contagion

#Predicting Successful #Memes using Network and Community Structure | #SNA #contagion | Innovation, Complexity, Clouds | Scoop.it

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luiy's curator insight, March 27, 2014 1:44 PM

We investigate the predictability of successful memes using their early spreading patterns in the underlying social networks. We propose and analyze a comprehensive set of features and develop an accurate model to predict future popularity of a meme given its early spreading patterns. Our paper provides the first comprehensive comparison of existing predictive frameworks. We categorize our features into three groups: influence of early adopters, community concentration, and characteristics of adoption time series. We find that features based on community structure are the most powerful predictors of future success. We also find that early popularity of a meme is not a good predictor of its future popularity, contrary to common belief. Our methods outperform other approaches, particularly in the task of detecting very popular or unpopular memes.

António F Fonseca's curator insight, April 2, 2014 6:01 AM

Another paper about popularity prediction.

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Introduction to Complex Systems: Patterns in Nature

This video provides a basic introduction to the science of complex systems, focusing on patterns in nature. (For more information on agent-based modeling, visit http://imaginationtoolbox.org ).


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António F Fonseca's curator insight, February 1, 2014 4:50 AM

Agent based modeling still is the best tool to understand complex systems when mathematical modeling gets very complicated.

Liz Rykert's curator insight, February 10, 2014 7:25 PM

Always looking for good resources to introduce complexity science to others. This looks great. 

Ian Biggs, FAIPM, CPPE's curator insight, April 16, 2014 8:08 PM

I recently conducted a series of workshops on the subject of 'Complex Project Management - Navigating through the unknown'. This clip provides a great introduction to complex systems and for those interested in Complexity Science, this clip is worth 7:52 of your time.

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A Wikipedia for robots allowing them to share knowledge and experience worldwide

A Wikipedia for robots allowing them to share knowledge and experience worldwide | Innovation, Complexity, Clouds | Scoop.it

European scientists from six institutes and two universities have developed an online platform where robots can learn new skills from each other worldwide — a kind of “Wikipedia for robots.” The objective is to help develop robots better at helping elders with caring and household tasks. “The problem right now is that robots are often developed specifically for one task”, says René van de Molengraft, TU/e researcher and RoboEarth project leader.


“RoboEarth simply lets robots learn new tasks and situations from each other. All their knowledge and experience are shared worldwide on a central, online database.” In addition, some computing and “thinking” tasks can be carried out by the system’s “cloud engine,” he said, “so the robot doesn’t need to have as much computing or battery power on‑board.”


For example, a robot can image a hospital room and upload the resulting map to RoboEarth. Another robot, which doesn’t know the room, can use that map on RoboEarth to locate a glass of water immediately, without having to search for it endlessly. In the same way a task like opening a box of pills can be shared on RoboEarth, so other robots can also do it without having to be programmed for that specific type of box.

 

RoboEarth is based on four years of research by a team of scientists from six European research institutes (TU/e, Philips, ETH Zürich, TU München and the universities of Zaragoza and Stuttgart).


 

Robots learn from each other on 'Wiki for robots'


Via Dr. Stefan Gruenwald
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Optimized Strategy for the Control and Prevention of Newly Emerging Influenza Revealed by the Spread Dynamics Model

Optimized Strategy for the Control and Prevention of Newly Emerging Influenza Revealed by the Spread Dynamics Model | Innovation, Complexity, Clouds | Scoop.it

No matching vaccine is immediately available when a novel influenza strain breaks out. Several nonvaccine-related strategies must be employed to control an influenza epidemic, including antiviral treatment, patient isolation, and immigration detection. This paper presents the development and application of two regional dynamic models of influenza with Pontryagin’s Maximum Principle to determine the optimal control strategies for an epidemic and the corresponding minimum antiviral stockpiles. Antiviral treatment was found to be the most effective measure to control new influenza outbreaks. In the case of inadequate antiviral resources, the preferred approach was the centralized use of antiviral resources in the early stage of the epidemic. Immigration detection was the least cost-effective; however, when used in combination with the other measures, it may play a larger role. The reasonable mix of the three control measures could reduce the number of clinical cases substantially, to achieve the optimal control of new influenza.

 


Via Ashish Umre
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UC Berkeley Researchers Propose "Neural Dust" Brain-Computer Interface

UC Berkeley Researchers Propose "Neural Dust" Brain-Computer Interface | Innovation, Complexity, Clouds | Scoop.it

Advances in brain imaging and neural activity detection technologies, such as fMRI and EEG, have allowed us to learn much about the brain over the years, and neural implants have offered the ability to stimulate and all but control activity in certain parts of the brain. However, these brain-computer interfaces are limited in that they offer finite resolution, are hard to apply to many brain regions, and usually can only stay directly connected to the brain for a short period of time due to their invasiveness.

 

Engineers at the University of California, Berkeley, have proposed an ultra-small, ultrasound-based neural recording system that they call “neural dust”. Neural dust consists of thousands of sensors that are 10-100 micrometers in size containing CMOS circuits and sensors to detect and report local extracellular electrophysiological data. The neural dust is powered by ultrasonic waves via a transducer that is implanted just below the dura. The sub-dural unit also interrogates the neural dust and sends information to another receiver outside the body.

 

If neural dust becomes a reality, it could give us a much higher resolution look at what is going on inside the brain, as it will be able to record from thousands of sites within the brain, in contrast to the hundreds of channels that current technology allows. Moreover, because these tiny sensors are literally the size of dust particles, they could cause far less damage to the surrounding brain tissue and could stay embedded in the brain for long periods of time.

 

Journal article: arXiv: Neural Dust: An Ultrasonic, Low Power Solution for Chronic Brain-Machine Interfaces


Via Dr. Stefan Gruenwald
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One small click for a man: NASA releases more than 17,000 photos from the Apollo program

One small click for a man: NASA releases more than 17,000 photos from the Apollo program | Innovation, Complexity, Clouds | Scoop.it
The archive, released through the Nasa-funded Lunar And Planetary Institute, shows both famous photos of Apollo 11 and everyday work for the astronauts in other missions.

 

This time 45 years ago, three Americans were orbiting the moon in the Apollo 8 space craft - the furthest from the Earth that any man had ever gone - and were paving the way for humanity's first successful mission to another celestial body. Astronauts Frank Borman, James Lovell and William Anders even read sections of the Book of Genesis as part of a Christmas Eve television broadcast. They were the first to photograph the Earth from far away and the moon up close - also capturing the now-famous 'Earthrise' photo while in lunar orbit.


Now Nasa has released more than 17,000 photos from the 33 Apollo astronauts who made it into space for the lunar missions, including the 12 men who set foot on the moon's surface.


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Sharrock's curator insight, December 25, 2013 9:18 PM

pics for students and teachers to use and explore.