Pompeu Fabra University

About: Pompeu Fabra University is a education organization based out in Barcelona, Spain. It is known for research contribution in the topics: Population & Gene. The organization has 8093 authors who have published 23570 publications receiving 858431 citations. The organization is also known as: Universitat Pompeu Fabra & UPF.

Topological patterns in street networks of self-organized urban settlements

Abstract: Many urban settlements result from a spatially distributed, decentralized building process. Here we analyze the topological patterns of organization of a large collection of such settlements using the approach of complex networks. The global efficiency (based on the inverse of shortest-path lengths), robustness to disconnections and cost (in terms of length) of these graphs is studied and their possible origins analyzed. A wide range of patterns is found, from tree-like settlements (highly vulnerable to random failures) to meshed urban patterns. The latter are shown to be more robust and efficient.

Business model innovation and sources of value creation in low-income markets

Abstract: We explore different business ventures in low-income markets in order to understand the factors influencing business model innovation in this context. Grounded in the rich data obtained from multiple case study analyses and in the received theory in strategy in low-income markets and business models, we identified a set of contingency factors that permitted us to distinguish between isolated and interactive business models. Isolated business models widen its entrance into new markets by leveraging firm's current resources and capabilities for taking advantage of existing opportunities. Interactive business models require a firm to combine, integrate and leverage both internal resources with ecosystem's capabilities to create new business opportunities. Finally, we discuss the main implications on value creation from these business models.

A Comprehensive Framework for Image Inpainting

Abstract: Inpainting is the art of modifying an image in a form that is not detectable by an ordinary observer. There are numerous and very different approaches to tackle the inpainting problem, though as explained in this paper, the most successful algorithms are based upon one or two of the following three basic techniques: copy-and-paste texture synthesis, geometric partial differential equations (PDEs), and coherence among neighboring pixels. We combine these three building blocks in a variational model, and provide a working algorithm for image inpainting trying to approximate the minimum of the proposed energy functional. Our experiments show that the combination of all three terms of the proposed energy works better than taking each term separately, and the results obtained are within the state-of-the-art.