I’ll be honest: that’s not one of my latest presentation on complex networks. It is dated, but I think it might be interesting for teachers, young researchers and anyone who needs some introductory concepts of complex systems. And sorry, it’s in Italian
The following is the short abstract of my PhD Thesis. For those of you interested in the full PhD dissertation, please take a look at AMS Dottorato website. Comments, suggestions, feedbacks are always well appreciated!
Complex Networks analysis turn out to be a very promising field of research, testified by many research projects and works that span different fields. Those analysis have been usually focused on characterize a single aspect of the system and a study that considers many informative axes along with a network evolve is lacking.
PhD dissertation abstract
The analysis of Complex Networks turn out to be a very promising field of research, testified by many research projects and works that span different fields. Until recently, those analysis have been usually focused on deeply characterize a single aspect of the system, therefore a study that considers many informative axes along with a network evolve is lacking.
In this Thesis, we propose a new multidimensional analysis that is able to inspect networks in the two most important dimensions of a system, namely space and time. In order to achieve this goal, we studied them singularly and investigated how the variation of the constituting parameters drives changes to the network behaviour as a whole.
By focusing on space dimension, we were able to characterize spatial alteration in terms of abstraction levels. We propose a novel algorithm that, by applying a fuzziness function, can reconstruct networks under different level of details. We call this analysis telescopic as it recalls the magnification and reduction process of the lens.
Through this line of research we have successfully verified that statistical indicators, that are frequently used in many complex networks researches, depends strongly on the granularity (i.e, the detail level) with which a system is described and on the class of networks considered. Continue reading
This post is the first of the new Simple Science category. This thread features research topics that are mainly focused on intuitive research facts/insight detected in the most important and well known virtual communities. However, research on complex networks is very interdisciplinary thus we do not exclude to extend our findings to other than social networks.
Since we want an audience as broad as possible and the content to be as readable as possible, we will not use strong statistical tools, but instead we adopt the basic and understandable ones. In special cases where more advanced mathematical methods are needed, we provide adequate and clear explanations.
Geeks usually have, in their DIY bags, many usb-to-serial converters such as Arduino’s or Openpicus’. These converters, for the people not accustomed to microcontrollers’ world, are circuits normally used for uploading compiled code from the PC. Additionally, they are used to serially communicate with the PC. They take usb signal and convert it to serial TTL.
Even though serial TTL is very important when communicating with microcontrollers, many home and industrial devices exchange data using RS485 protocol. The main benefits of using RS485 are basically efficiency, economy, the long distances allowed between devices (up to 1200 meters) in electrically noisy environments. Continue reading
The name ambiguity problem is especially challenging in the field of bibliographic digital libraries. The problem is amplified when names are collected from heterogeneous sources. This is the case in the Scholarometer system, which performs bibliometric analysis by cross-correlating author names in user queries with those retrieved from digital libraries. The uncontrolled nature of user-generated annotations is very valuable, but creates the need to detect ambiguous names. Our goal is to detect ambiguous names at query time by mining digital library annotation data, thereby decreasing noise in the bibliometric analysis. Continue reading