Common Representation of Information Flows for Dynamic Coalitions

We propose a formal foundation for reasoning about access control policies within a Dynamic Coalition, defining an abstraction over existing access control models and providing mechanisms for translation of those models into information-flow domain. The abstracted information-flow domain model, called a Common Representation, can then be used for defining a way to control the evolution of Dynamic Coalitions with respect to information flow

Cellular Automata Applications in Shortest Path Problem

Cellular Automata (CAs) are computational models that can capture the essential features of systems in which global behavior emerges from the collective effect of simple components, which interact locally. During the last decades, CAs have been extensively used for mimicking several natural processes and systems to find fine solutions in many complex hard to solve computer science and engineering problems. Among them, the shortest path problem is one of the most pronounced and highly studied problems that scientists have been trying to tackle by using a plethora of methodologies and even unconventional approaches. The proposed solutions are mainly justified by their ability to provide a correct solution in a better time complexity than the renowned Dijkstra's algorithm. Although there is a wide variety regarding the algorithmic complexity of the algorithms suggested, spanning from simplistic graph traversal algorithms to complex nature inspired and bio-mimicking algorithms, in this chapter we focus on the successful application of CAs to shortest path problem as found in various diverse disciplines like computer science, swarm robotics, computer networks, decision science and biomimicking of biological organisms' behaviour. In particular, an introduction on the first CA-based algorithm tackling the shortest path problem is provided in detail. After the short presentation of shortest path algorithms arriving from the relaxization of the CAs principles, the application of the CA-based shortest path definition on the coordinated motion of swarm robotics is also introduced. Moreover, the CA based application of shortest path finding in computer networks is presented in brief. Finally, a CA that models exactly the behavior of a biological organism, namely the Physarum's behavior, finding the minimum-length path between two points in a labyrinth is given.Comment: To appear in the book: Adamatzky, A (Ed.) Shortest path solvers. From software to wetware. Springer, 201

Impacts of 21st‐century climate change on montane habitat in the Madrean Sky Island Archipelago

Aim The Madrean Sky Island Archipelago is a North American biodiversity hotspot composed of similar to 60 isolated mountains that span the Cordilleran Gap between the Rocky Mountains and the Sierra Madre Occidental. Characterized by discrete patches of high-elevation montane habitat, these "sky islands" serve as stepping stones across a "sea" of desert scrub/grassland. Over this coming century, the region is expected to shift towards a warmer and drier climate. We used species distribution modelling to predict how the spatial distribution of montane habitat will be affected by climate change. Location Madrean Sky Island Archipelago, south-west United States and north-west Mexico (latitude, 29-34 degrees N; longitude, 107-112 degrees W). Methods To approximate the current distribution of montane habitat, we built species distribution models for five high-elevation species (Ceanothus fendleri, Pinus strobiformis, Quercus gambelii, Sciurus aberti, and Synuchus dubius). The resulting models were projected under multiple climate change scenarios-four greenhouse gas concentration trajectories (RCP 2.6, 4.5, 6.0, and 8.5) for each of three climate models (CCSM4, MPI-ESM-LR, and NorESM1-M)-to generate predicted distributions for the years 2050 and 2070. We performed chi-squared tests to detect any future changes to total montane habitat area, and Conover-Iman tests to evaluate isolation among the discrete montane habitat patches. Results While the climate models differ with respect to their predictions as to how severe the effects of future climate change will be, they all agree that by as early as year 2050, there will be significant montane habitat loss and increased montane habitat patch isolation across the Madrean Archipelago region under a worst-case climate change scenario (RCP 8.5). Main conclusions Our results suggest that under 21st-century climate change, the Madrean Sky Islands will become increasingly isolated due to montane habitat loss. This may affect their ability to serve as stepping stones and have negative implications for the region's biodiversity.University of Arizona Center for Insect ScienceOpen access articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

A Simple Method to Account for Measurement Errors in Revealed Preference Tests

Revealed preference tests are widely used in empirical applications of consumer rationality. These are static tests, and consequently, lack ability to handle measurement errors in the data. This paper extends and generalizes existing procedures that account for measurement errors in revealed preference tests. In particular, it introduces a very efficient method to implement these procedures, which make them operational for large data sets. The paper illustrates the new method for both classical and Berkson measurement errors models