Computational Aspects of Asynchronous CA

This work studies some aspects of the computational power of fully asynchronous cellular automata (ACA). We deal with some notions of simulation between ACA and Turing Machines. In particular, we characterize the updating sequences specifying which are "universal", i.e., allowing a (specific family of) ACA to simulate any TM on any input. We also consider the computational cost of such simulations

Subaqueous landslides at the distal basin of Lago Nahuel Huapi (Argentina): Towards a tsunami hazard evaluation in Northern Patagonian lakes

The May 22nd, 1960 Valdivia earthquake, Chile (Mw 9.5) triggered a series of subaqueous mass-wasting processes (debris flows and slides) in Lago Nahuel Huapi (Argentina), generating a tsunami-like wave that hit the coasts of San Carlos de Bariloche. Aiming to provide a first preliminary insight into tsunami hazards for the lakeshore communities, in this paper we identify and characterize the subaqueous landslides at the populated distal basin of the lake. Swath bathymetric and seismic profiling surveys were carried out and high-resolution digital elevation models were derived from these data to perform a landslide inventory map. A series of morphometrical parameters (including the landslide area, the volume of displaced materials and the run-out distance, among others) were estimated upon selected events. The results indicated that landslide activity at the distal basin of Lago Nahuel Huapi has been concentrated in the vicinity of Bariloche (massive landslide triggered by the 1960 earthquake) and within steep delta fronts where the slope failures typically initiate at shallow waters (9–11 m depth). The sliding mass frequently travels basinward along a great distance (≥1000 m). At the delta fronts, the volume of material removed by landslides can reach ~40 × 104 m3 , leaving scar areas of up to 13 m thick. The periodic occurrence of rotational–translational mass movements initiating at the upper edge of the delta fronts, with vertical displacements of the mobilized materials reaching ~200 m, probably represents a potential tsunami hazard for the nearby populated coasts.Fil: Beigt, Debora. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto Andino Patagónico de Tecnologías Biológicas y Geoambientales. Universidad Nacional del Comahue. Instituto Andino Patagónico de Tecnologías Biológicas y Geoambientales.; ArgentinaFil: Villarosa, Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto Andino Patagónico de Tecnologías Biológicas y Geoambientales. Universidad Nacional del Comahue. Instituto Andino Patagónico de Tecnologías Biológicas y Geoambientales.; Argentina. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche; ArgentinaFil: Gomez, Eduardo Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina. Universidad Tecnológica Nacional; ArgentinaFil: Manzoni, Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto Andino Patagónico de Tecnologías Biológicas y Geoambientales. Universidad Nacional del Comahue. Instituto Andino Patagónico de Tecnologías Biológicas y Geoambientales.; Argentina. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche; Argentin

Characterizing PSPACE with Shallow Non-Confluent P Systems

In P systems with active membranes, the question of understanding the power of non-confluence within a polynomial time bound is still an open problem. It is known that, for shallow P systems, that is, with only one level of nesting, non-con uence allows them to solve conjecturally harder problems than con uent P systems, thus reaching PSPACE. Here we show that PSPACE is not only a bound, but actually an exact characterization. Therefore, the power endowed by non-con uence to shallow P systems is equal to the power gained by con uent P systems when non-elementary membrane division and polynomial depth are allowed, thus suggesting a connection between the roles of non-confluence and nesting depth

Characterizing PSPACE with Shallow Non-Confluent P Systems

In P systems with active membranes, the question of understanding the power of non-confluence within a polynomial time bound is still an open problem. It is known that, for shallow P systems, that is, with only one level of nesting, non-con uence allows them to solve conjecturally harder problems than con uent P systems, thus reaching PSPACE. Here we show that PSPACE is not only a bound, but actually an exact characterization. Therefore, the power endowed by non-con uence to shallow P systems is equal to the power gained by con uent P systems when non-elementary membrane division and polynomial depth are allowed, thus suggesting a connection between the roles of non-confluence and nesting depth

A Discrete Particle Swarm Optimizer for the Design of Cryptographic Boolean Functions

A Particle Swarm Optimizer for the search of balanced Boolean functions with good cryptographic properties is proposed in this paper. The algorithm is a modified version of the permutation PSO by Hu, Eberhart and Shi which preserves the Hamming weight of the particles positions, coupled with the Hill Climbing method devised by Millan, Clark and Dawson to improve the nonlinearity and deviation from correlation immunity of Boolean functions. The parameters for the PSO velocity equation are tuned by means of two meta-optimization techniques, namely Local Unimodal Sampling (LUS) and Continuous Genetic Algorithms (CGA), finding that CGA produces better results. Using the CGA-evolved parameters, the PSO algorithm is then run on the spaces of Boolean functions from $n=7$ to $n=12$ variables. The results of the experiments are reported, observing that this new PSO algorithm generates Boolean functions featuring similar or better combinations of nonlinearity, correlation immunity and propagation criterion with respect to the ones obtained by other optimization methods

Simulating counting oracles with cooperation

We prove that monodirectional shallow chargeless P systems with active membranes and minimal cooperation working in polynomial time precisely characterise P#P k , the complexity class of problems solved in polynomial time by deterministic Turing machines with a polynomial number of parallel queries to an oracle for a counting problem

A hybrid Structural Health Monitoring approach based on reduced-order modelling and deep learning

Recent advances in sensor technologies coupled with the development of machine/deep learning strategies are opening new frontiers in Structural Health Monitoring (SHM). Dealing with structural vibrations recorded with pervasive sensor networks, SHM aims at extracting meaningful damage-sensitive features from the data, shaped as multivariate time series, and taking real-time decisions concerning the safety level. Within this context, we discuss an approach able to detect and localize a structural damage avoiding any pre-processing of the acquired data. The method takes advantage of the capability of Deep Learning of Fully Convolutional Networks, trained during an offline SHM phase. As a hybrid model- and data-based solution is looked for, Reduced Order Models are also built in the offline phase to reduce the computational burden of the whole monitoring approach. Through a numerical benchmark test, we show how the proposed method can recognize and localize different damage states