K-theory for Cuntz-Krieger algebras arising from real quadratic maps

We compute the $K$-groups for the Cuntz-Krieger algebras $\mathcal{O}_{A_{\mathcal{K}(f_{\mu})}}$, where $A_{\mathcal{K}(f_{\mu})}$ is the Markov transition matrix arising from the \textit{kneading sequence }$\mathcal{K} (f_{\mu})$ of the one-parameter family of real quadratic maps $f_{\mu}$.Comment: 8 page

EVALUATING SATELLITE DERIVED BATHYMETRY IN REGARD TO TOTAL PROPAGATED UNCERTAINTY, MULTI-TEMPORAL CHANGE DETECTION, AND MULTIPLE NON-LINEAR ESTIMATION

Acoustic and electromagnetic hydrographic surveys produce highly-accurate bathymetric data that can be used to update and improve current nautical charts. For shallow-water surveys (i.e., less than 50m depths), this includes the use of single-beam echo-sounders (SBES), multi-beam echo-sounders (MBES), and airborne lidar bathymetry (ALB). However, these types of hydrographic surveys are time-consuming and require considerable financial and operational resources to conduct. As a result, some maritime regions are seldom surveyed due to their remote location and challenging logistics. Satellite-derived bathymetry (SDB) provides a means to supplement traditional acoustic hydrographic surveys. In particular, Landsat 8 imagery: 1) provides complete coverage of the Earth’s surface every 16 days, 2) has an improved dynamic range (12-bits), and 3) is freely-available from the US Geological Survey. While the 30 m spatial resolution does not match MBES, ALB, or SBES coverage, SDB based on Landsat 8 can be regarded as a type of “reconnaissance survey” that can be used to identify potential hazards to navigation in areas that are seldom surveyed. It is also a useful means to monitor change detection in dynamic regions. This study focused on developing improved image-processing techniques and time-series analysis for SDB from Landsat 8 imagery for three different applications: 1. An improved means to estimate total propagated uncertainty (TPU), mainly the vertical component, for single-image SDB; 2. Identifying the location and movement of dynamic shallow areas in river entrances based on multiple-temporal Landsat 8 imagery; 3. Using a multiple, nonlinear SDB approach to enhance depth estimations and enable bottom discrimination. An improved TPU estimation was achieved based on the two most common optimization approaches (Dierssen et al., 2003 and Stumpf et al., 2003). Various single-image SDB band-ratio outcomes and associated uncertainties were compared against ground truth (i.e., recent Lidar surveys). Several parameters were tested, including various types of filters, kernel sizes, number of control points and their coverage, and recent vs. outdated control points. Based on the study results for two study sites (Cape Ann, MA and Ft Myers, FL), similar performance was observed for both the Stumpf and the Dierssen models. Validation was performed by comparing estimated depths and uncertainties to observed ALB data. The best performing configuration was achieved using low-pass filter (kernel size 3x3) with ALB control points that were distributed over the entire study site. A change detection process using image processing was developed to identify the location and movement of dynamic shallow areas in riverine environments. Yukon River (Alaska) and Amazon River (Brazil) entrances were evaluated as study sites using multiple satellite imagery. A time-series analysis was used to identify probable shallow areas with no usable control points. By using an SDB ratio model with image processing techniques that includes feature extraction and a well-defined topological feature to describe the shoal feature, it is possible to create a time-series of the shoal’s motion, and predict its future location. A further benefit of this approach is that vertical referencing of the SDB ratio model to chart datum is not required. In order to enhance the capabilities of the SDB approach to estimate depth in non-uniform conditions, Dierssen’s band ration SDB algorithm was transformed into a full non-linear SDB model. The model was evaluated in the Simeonof Island, AK, using Lidar control points from a previous NOAA ALB survey. Linear and non-linear SDB models were compared using the ALB survey for performance evaluation. The multi-nonlinear SDB model provides an enhanced performance compared to the more traditional linear SDB method. This is most noticeable in the very shallow waters (0-2 m), where a linear model does not provide a good correlation to the control points. In deep-waters close to the extinction depth, the multi-nonlinear SDB method is also able to better detect bottom features than the linear SDB method. By recognizing the water column contributions to the SDB solution, it is possible to achieve a more accurate estimate of the bathymetry in remote areas

Ecosystem Viable Yields

The World Summit on Sustainable Development (Johannesburg, 2002) encouraged the application of the ecosystem approach by 2010. However, at the same Summit, the signatory States undertook to restore and exploit their stocks at maximum sustainable yield (MSY), a concept and practice without ecosystemic dimension, since MSY is computed species by species, on the basis of a monospecific model. Acknowledging this gap, we propose a definition of "ecosystem viable yields" (EVY) as yields compatible i) with guaranteed biological safety levels for all time and ii) with an ecosystem dynamics. To the difference of MSY, this notion is not based on equilibrium, but on viability theory, which offers advantages for robustness. For a generic class of multispecies models with harvesting, we provide explicit expressions for the EVY. We apply our approach to the anchovy--hake couple in the Peruvian upwelling ecosystem

Influence of input data uncertainty in school buildings energy simulation

In developed countries, the building sector is responsible for a very significant share of the total energy consumption. A more detailed and rigorous analysis of building energy performance became possible due to the building simulation software improvement. Traditionally, buildings energy simulation requires the definition of a set of input parameters, which are usually considered as deterministic, neglecting the fact that in reality they have a stochastic nature. Hence, if one intends to evaluate the uncertainty in simulation due to the uncertainty of the input parameters, stochastic methods, such as Monte Carlo simulations should be employed. This paper presents a methodology for the stochastic simulation of school buildings for tackling input data uncertainty. The Monte Carlo method application in the evaluation of the uncertainty of the heat demand of a school building provides an example case where the opportunities and difficulties of the method are explored. The methodology includes parameter characterization, sampling procedure, simulation automatization and sensitivity analysis. Its application results in increased knowledge of the building, allowing to define targets that include the stochastic effect

Spatial multicriteria decision analysis tools applied to urban consolidation in low density areas

The urbanization process in Portugal has led to an extensive and discontinuous growth of urban areas. This phenomenon is present in both metropolitan areas, with prevalence of an extensive urban development model, as in low density areas where urban growth follows is more discontinuous and scattered. This urban growth model has major impacts in the increase of urban infrastructures costs, energy inefficiency, CO2 emissions associated with the mobility as in the decrease of productive and natural resource areas. To reverse this trend, urban planners need to develop methods for selecting new urban suitable areas, that integrate new objectives and different criteria that promote urban consolidation. These objectives are commonly conflicting and the complexity and spatial nature associated with this processes justifies the use of GIS-multicriteria decision analysis methods (GIS-MCDA). This paper presents a method that uses a GIS-MCDA system and integrates economic, social and environmental objectives for defining new urban areas in the city of Vila Real. The results demonstrate that the consideration of new criteria and objectives derive more consolidated solutions for urban expansion.Peer Reviewe