🎯 سخنرانی
Network of Firms, Economic Crises, and the Role of Government in Complexity Economics

دکتر سیدعلی حسینی
دانشگاه شهید بهشتی

#مکان:
دانشگاه شریف، آمفی‌ تئاتر دانشکده
فیزیک
#زمان:
ساعت ۱/۵ (امروز)

🎯 Eye-catching visualization of chaotic flow on the Lorenz attractor, using the power of #GPU.

http://rickyreusser.com/demos/lorenz/

🎯 Samuel Arbesman on #Complex_Adaptive_Systems and the Difference between #Biological and #Physics Based Thinking


https://www.farnamstreetblog.com/2016/11/samuel-arbesman-biological-physics-thinking/?utm_source=twitter.com&utm_medium=social&utm_campaign=buffer&utm_content=bufferb2052

🎯 https://comdig.unam.mx/2016/12/02/visual-analysis-of-nonlinear-dynamical-systems-chaos-fractals-self-similarity-and-the-limits-of-prediction/

We are looking for the next generation of Network Scientists.

🎯 https://johncarlosbaez.wordpress.com/2016/11/29/compositionality-in-network-theory/

👆 Live streaming video of the whole workshop here:

https://t.co/alDffhTQRW

Right now: Prakash Panagaden on "semantics for physicists".

🎯 Winter school @UniofGreenwich in London 16-20 Jan. Courses on networks and big-data:

https://showtime.gre.ac.uk/index.php/business/CBNAAS17/schedConf/program

🌀 https://www.edx.org/course/introduction-r-data-science-microsoft-dat204x-2?utm_medium=email&utm_source=sailthru&utm_campaign=studentnewsletter-20161206&utm_content=course-announcements-mailing-list&utm_term=Newsletter%20Actives

🎯 Stealing Reality: When Criminals Become Data Scientists (or Vice Versa)

http://web.media.mit.edu/~yanival/IEEE_Intelligent_Systems.pdf

🌀 مکانیک کوانتومی وآشوب

http://www.sitpor.org/2015/02/quantum-mechanics-and-chaos/

📄 #Complexity and #Philosophy

Francis Heylighen, Paul Cilliers, Carlos Gershenson
(Submitted on 19 Apr 2006)

https://arxiv.org/pdf/cs/0604072v1

📌 ABSTRACT
The science of complexity is based on a new way of thinking that stands in sharp contrast to the philosophy underlying Newtonian science, which is based on reductionism, determinism, and objective knowledge. This paper reviews the historical development of this new world view, focusing on its philosophical foundations. Determinism was challenged by quantum mechanics and chaos theory. Systems theory replaced reductionism by a scientifically based holism. Cybernetics and postmodern social science showed that knowledge is intrinsically subjective. These developments are being integrated under the header of "complexity science". Its central paradigm is the multi-agent system. Agents are intrinsically subjective and uncertain about their environment and future, but out of their local interactions, a global organization emerges. Although different philosophers, and in particular the postmodernists, have voiced similar ideas, the paradigm of complexity still needs to be fully assimilated by philosophy. This will throw a new light on old philosophical issues such as relativism, ethics and the role of the subject.

📽 https://youtube.com/watch?index=98&t=139s&v=c867FlzxZ9Y&list=PL2c_ujuXhAvQO18KrtERRMjAkjgr-PQ1k

📄 Universality of the SIS prevalence in networks

Piet Van Mieghem


https://arxiv.org/pdf/1612.01386v1

📌 ABSTRACT
Epidemic models are increasingly used in real-world networks to understand diffusion phenomena (such as the spread of diseases, emotions, innovations, failures) or the transport of information (such as news, memes in social on-line networks). A new analysis of the prevalence, the expected number of infected nodes in a network, is presented and physically interpreted. The analysis method is based on spectral decomposition and leads to a universal, analytic curve, that can bound the time-varying prevalence in any finite time interval. Moreover, that universal curve also applies to various types of Susceptible-Infected-Susceptible (SIS) (and Susceptible-Infected-Removed (SIR)) infection processes, with both homogenous and heterogeneous infection characteristics (curing and infection rates), in temporal and even disconnected graphs and in SIS processes with and without self-infections. The accuracy of the universal curve is comparable to that of well-established mean-field approximations.

Subjects: #Physics and #Society (physics.soc-ph); #Social and #Information #Networks (cs.SI); #Populations and #Evolution (q-bio.PE)

📽 http://www.namasha.com/v/zxlRvpy9

📽 https://www.youtube.com/shared?ci=-Si29BGKbsA

🎯 https://www.scientificamerican.com/article/big-data-needs-big-theory/?wt.mc=SA_Twitter-Share

📖 http://press.princeton.edu/titles/4308.html

🎯 https://www.santafe.edu/news-center/news/friend-friend-dense-network