Managing the complexity: decision making process on sustainable mobility

Starting from the literature on decision processes in public choices, aim of the paper is to suggest an integrated methodology to get a choice as much as possible shared and participated joining two different approaches. On one hand there is the “classic†or top-down approach based on statistical data analysis and handling, having as target the definition of some synthetic indicators. On the other hand there is a bottom-up approach based on the Strategic Environment Assessment (SEA) logical framework and on citizens participation. Particularly the paper will apply the above mentioned methodology to face the theme of sustainable mobility showing at the end the results obtained in the analysis of the 13th District of the Municipality of Rome. The choice of sustainable mobility as a target of decision process lies on the fact that actually it is included with a high priority in the agenda of European institutions and (local and national) administrative governments. The proposed model does not provide a solution, but rather defines a process that is able to recognize the particularities of different territorial contexts to yield appropriate, case specific solutions.

Technology Emergence as a Structuring Process:A Complexity Theory Perspective on Blockchain

Drawing on complexity theory, we investigate the structuring processes and underlying mechanisms underpinning the emergence of a new technology. Empirically, we track the emergence of blockchain technology by examining international patents issued between 2009 and 2020. Our results indicate that technology emergence follows an evolutionary trajectory that progresses from disordered to structured interactions among the technological elements, culminating in the formation of a technological core that acts as a pole of attraction for further interactions and delineates boundaries within the technological domain. Technology structuring is fueled by what we term “technology fitness” and “self-reinforcing” mechanisms that progressively transform primitive structures into more complex, self-organized configurations. Our study offers a novel framework of technology emergence, highlighting how dispersed bits of technological knowledge gradually aggregate into complex structures that define the specific trajectory of a particular domain

Evaluation of the magnetization direction effects on ferrite PM brushless fractional machines

Permanent magnets are frequently adopted in small brushless machines for automotive applications. Normally anisotropic ferrites, but some research on bonded magnets is being carried on. Several types of magnetization can be proposed, involving different levels of complexity in the magnetization process. In the paper a comparison between parallel and radial magnetization is described, taking into account on one side the major complexity of the radial process and on the other the small power derating of the paralle

Towards Quantifying Complexity with Quantum Mechanics

While we have intuitive notions of structure and complexity, the formalization of this intuition is non-trivial. The statistical complexity is a popular candidate. It is based on the idea that the complexity of a process can be quantified by the complexity of its simplest mathematical model - the model that requires the least past information for optimal future prediction. Here we review how such models, known as $\epsilon$-machines can be further simplified through quantum logic, and explore the resulting consequences for understanding complexity. In particular, we propose a new measure of complexity based on quantum $\epsilon$-machines. We apply this to a simple system undergoing constant thermalization. The resulting quantum measure of complexity aligns more closely with our intuition of how complexity should behave.Comment: 10 pages, 6 figure, Published in the Focus Point on Quantum information and complexity edition of EPJ Plu

Information complexity is computable

The information complexity of a function $f$ is the minimum amount of information Alice and Bob need to exchange to compute the function $f$. In this paper we provide an algorithm for approximating the information complexity of an arbitrary function $f$ to within any additive error $\alpha > 0$, thus resolving an open question as to whether information complexity is computable. In the process, we give the first explicit upper bound on the rate of convergence of the information complexity of $f$ when restricted to $b$-bit protocols to the (unrestricted) information complexity of $f$.Comment: 30 page