Historical SDI, thematic maps and analysis of a complex network of medieval towers (13th-15th century) in the moorish strip

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-4, 2018 ISPRS TC IV Mid-term Symposium “3D Spatial Information Science – The Engine of Change”, 1–5 October 2018, Delft, The NetherlandsThis work is part of an investigation into the use of GIS for the documentation and comprehension of medieval architectural heritage in the ancient Kingdom of Seville. The research was done in the framework of the project “Sustainable guardianship of cultural heritage through digital BIM and GIS models: contribution to knowledge and social innovation”, an interdisciplinary project focused on the applications of information technology in architectural heritage in Spain. The study case of this paper is located in the Guadalquivir valley during the period between 13th and 15th centuries. It concerns the Moorish Strip site, fortified by the Christian Kingdom of Castile with the aim of creating a barrier with the Moorish Kingdom. Its deteriorated state has led us to create a historical and spatial database in order to contribute to its conservation management plan. Apart from the historical documentation research and the data gathering, intensive fieldwork was also done to collect information about the buildings. In this paper we present a Historical SDI to investigate the hypothesis that the spatial patterns of the Moorish Band obey rules of “inter-visibility” control. Some analysis has been done on the site scale, such as: i) a thematic map of building material; ii) a spatiotemporal analysis; iii) the density of the distribution of towers over the territory; iv) a simulation of the territory visibility from the towers; v) the inter-visibility among towers; iv) thematic maps using attribute values. These analyses permitted us to highlight the need to create a preservation plan that should consider the network visibility system as an important value for heritage interpretation and knowledge.Spain’s Ministry of Economy and Competitiveness HAR2016–78113-

The carbon footprint of desalination: An input-output analysis of seawater reverse osmosis desalination in Australia for 2005–2015

This study examines greenhouse gas emissions for 2005–2015 from seawater desalination in Australia, using conventional energies. We developed a tailor-made multi-regional input-output-model. We complemented macroeconomic top-down data with plant-specific desalination data of the largest 20 desalination plants in Australia. The analysed capacity cumulates to 95% of Australia's overall seawater desalination capacity. We considered the construction and the operation of desalination plants. We measure not only direct effects, but also indirect effects throughout the entire value chain. Our results show the following: We identify the state of Victoria with the highest emissions due to capital and operational expenditures (capex and opex). The contribution of the upstream value chain to total greenhouse gas emissions increases for capex and decreases for opex. For capex, the construction of intake and outfall is the driving factor for carbon emissions. For opex, electricity consumption is the decisive input factor. Both in construction and operation, we identify the critical role of the electricity sector for carbon emissions throughout the supply chain effects. The sector contributes 69% during the zenith of the construction phase and 96% during the operating phase to the entire emissions. We estimate the total emissions for 2015 at 1193 kt CO2e

Semantic Enrichment for Building Information Modeling: Procedure for Compiling Inference Rules and Operators for Complex Geometry

Semantic enrichment of building models adds meaningful domain-specific or application-specific information to a digital building model. It is applicable to solving interoperability problems and to compilation of models from point cloud data. The SeeBIM (Semantic Enrichment Engine for BIM) prototype software encapsulates domain expert knowledge in computer readable rules for inference of object types, identity and aggregation of systems. However, it is limited to axis-aligned bounding box geometry and the adequacy of its rule-sets cannot be guaranteed. This paper solves these drawbacks by (1) devising a new procedure for compiling inference rule sets that are known a priori to be adequate for complete and thorough classification of model objects, and (2) enhancing the operators to compute complex geometry and enable precise topological rule processing. The procedure for compiling adequate rule sets is illustrated using a synthetic concrete highway bridge model. A real-world highway bridge model, with 333 components of 13 different types and compiled from a laser scanned point cloud, is used to validate the approach and test the enhanced SeeBIM system. All of the elements are classified correctly, demonstrating the efficacy of the approach to semantic enrichment

Tackling Exascale Software Challenges in Molecular Dynamics Simulations with GROMACS

GROMACS is a widely used package for biomolecular simulation, and over the last two decades it has evolved from small-scale efficiency to advanced heterogeneous acceleration and multi-level parallelism targeting some of the largest supercomputers in the world. Here, we describe some of the ways we have been able to realize this through the use of parallelization on all levels, combined with a constant focus on absolute performance. Release 4.6 of GROMACS uses SIMD acceleration on a wide range of architectures, GPU offloading acceleration, and both OpenMP and MPI parallelism within and between nodes, respectively. The recent work on acceleration made it necessary to revisit the fundamental algorithms of molecular simulation, including the concept of neighborsearching, and we discuss the present and future challenges we see for exascale simulation - in particular a very fine-grained task parallelism. We also discuss the software management, code peer review and continuous integration testing required for a project of this complexity.Comment: EASC 2014 conference proceedin

Simulating chemistry efficiently on fault-tolerant quantum computers

Quantum computers can in principle simulate quantum physics exponentially faster than their classical counterparts, but some technical hurdles remain. Here we consider methods to make proposed chemical simulation algorithms computationally fast on fault-tolerant quantum computers in the circuit model. Fault tolerance constrains the choice of available gates, so that arbitrary gates required for a simulation algorithm must be constructed from sequences of fundamental operations. We examine techniques for constructing arbitrary gates which perform substantially faster than circuits based on the conventional Solovay-Kitaev algorithm [C.M. Dawson and M.A. Nielsen, \emph{Quantum Inf. Comput.}, \textbf{6}:81, 2006]. For a given approximation error $\epsilon$, arbitrary single-qubit gates can be produced fault-tolerantly and using a limited set of gates in time which is $O(\log \epsilon)$ or $O(\log \log \epsilon)$; with sufficient parallel preparation of ancillas, constant average depth is possible using a method we call programmable ancilla rotations. Moreover, we construct and analyze efficient implementations of first- and second-quantized simulation algorithms using the fault-tolerant arbitrary gates and other techniques, such as implementing various subroutines in constant time. A specific example we analyze is the ground-state energy calculation for Lithium hydride.Comment: 33 pages, 18 figure