A spatio-temporal structure-based approach to drought characterisation

Drought characterisation is an intrinsically spatio-temporal problem. A limitation of previous approaches to characterisation is that they discard much of the spatio-temporal information by reducing events to a lower-order subspace. To address this, an explicit 3-dimensional (longitude, latitude, time) structure-based method is described in which drought events are defined by a spatially and temporarily coherent set of points displaying standardised precipitation below a given threshold. Geometric methods can then be used to measure similarity between individual drought structures. Groupings of these similarities provide an alternative to traditional methods for extracting recurrent space-time signals from geophysical data. The explicit consideration of structure encourages the construction of summary statistics which relate to the event geometry. Example measures considered are the event volume, centroid, and aspect ratio. The utility of a 3-dimensional approach is demonstrated by application to the analysis of European droughts (15 °W to 35°E, and 35 °N to 70°N) for the period 1901–2006. Large-scale structure is found to be abundant with 75 events identified lasting for more than 3 months and spanning at least 0.5 × 106 km2. Near-complete dissimilarity is seen between the individual drought structures, and little or no regularity is found in the time evolution of even the most spatially similar drought events. The spatial distribution of the event centroids and the time evolution of the geographic cross-sectional areas strongly suggest that large area, sustained droughts result from the combination of multiple small area (∼106 km2) short duration (∼3 months) events. The small events are not found to occur independently in space. This leads to the hypothesis that local water feedbacks play an important role in the aggregation process.

Mutual dependency grid for stakeholder mapping: a component-based approach to supply chain participant analysis

Stakeholder analysis plays a critical role in business analysis. However, the majority of the stakeholder identification and analysis methods focus on the activities and processes and ignore the artefacts being processed by human beings. By focusing on the outputs of the organisation, an artefact-centric view helps create a network of artefacts, and a component-based structure of the organisation and its supply chain participants. Since the relationship is based on the components, i.e. after the stakeholders are identified, the interdependency between stakeholders and the focal organisation can be measured. Each stakeholder is associated with two types of dependency, namely the stakeholder’s dependency on the focal organisation and the focal organisation’s dependency on the stakeholder. We identify three factors for each type of dependency and propose the equations that calculate the dependency indexes. Once both types of the dependency indexes are calculated, each stakeholder can be placed and categorised into one of the four groups, namely critical stakeholder, mutual benefits stakeholder, replaceable stakeholder, and easy care stakeholder. The mutual dependency grid and the dependency gap analysis, which further investigates the priority of each stakeholder by calculating the weighted dependency gap between the focal organisation and the stakeholder, subsequently help the focal organisation to better understand its stakeholders and manage its stakeholder relationships.

An ontology-based approach for data integration in regionally interoperable healthcare systems

In order to best utilize the limited resource of medical resources, and to reduce the cost and improve the quality of medical treatment, we propose to build an interoperable regional healthcare systems among several levels of medical treatment organizations. In this paper, our approaches are as follows:(1) the ontology based approach is introduced as the methodology and technological solution for information integration; (2) the integration framework of data sharing among different organizations are proposed(3)the virtual database to realize data integration of hospital information system is established. Our methods realize the effective management and integration of the medical workflow and the mass information in the interoperable regional healthcare system. Furthermore, this research provides the interoperable regional healthcare system with characteristic of modularization, expansibility and the stability of the system is enhanced by hierarchy structure.

Linking urban water balance and energy balance models to analyse urban design options

Using a water balance modelling framework, this paper analyses the effects of urban design on the water balance, with a focus on evapotranspiration and storm water. First, two quite different urban water balance models are compared: Aquacycle which has been calibrated for a suburban catchment in Canberra, Australia, and the single-source urban evapotranspiration-interception scheme (SUES), an energy-based approach with a biophysically advanced representation of interception and evapotranspiration. A fair agreement between the two modelled estimates of evapotranspiration was significantly improved by allowing the vegetation cover (leaf area index, LAI) to vary seasonally, demonstrating the potential of SUES to quantify the links between water sensitive urban design and microclimates and the advantage of comparing the two modelling approaches. The comparison also revealed where improvements to SUES are needed, chiefly through improved estimates of vegetation cover dynamics as input to SUES, and more rigorous parameterization of the surface resistance equations using local-scale suburban flux measurements. Second, Aquacycle is used to identify the impact of an array of water sensitive urban design features on the water balance terms. This analysis confirms the potential to passively control urban microclimate by suburban design features that maximize evapotranspiration, such as vegetated roofs. The subsequent effects on daily maximum air temperatures are estimated using an atmospheric boundary layer budget. Potential energy savings of about 2% in summer cooling are estimated from this analysis. This is a clear ‘return on investment’ of using water to maintain urban greenspace, whether as parks distributed throughout an urban area or individual gardens or vegetated roofs.

An event-based approach to understanding decadal fluctuations in the Atlantic meridional overturning circulation

Many previous studies have shown that unforced climate model simulations exhibit decadal-scale fluctuations in the Atlantic meridional overturning circulation (AMOC), and that this variability can have impacts on surface climate fields. However, the robustness of these surface fingerprints across different models is less clear. Furthermore, with the potential for coupled feedbacks that may amplify or damp the response, it is not known whether the associated climate signals are linearly related to the strength of the AMOC changes, or if the fluctuation events exhibit nonlinear behaviour with respect to their strength or polarity. To explore these questions, we introduce an objective and flexible method for identifying the largest natural AMOC fluctuation events in multicentennial/multimillennial simulations of a variety of coupled climate models. The characteristics of the events are explored, including their magnitude, meridional coherence and spatial structure, as well as links with ocean heat transport and the horizontal circulation. The surface fingerprints in ocean temperature and salinity are examined, and compared with the results of linear regression analysis. It is found that the regressions generally provide a good indication of the surface changes associated with the largest AMOC events. However, there are some exceptions, including a nonlinear change in the atmospheric pressure signal, particularly at high latitudes, in HadCM3. Some asymmetries are also found between the changes associated with positive and negative AMOC events in the same model. Composite analysis suggests that there are signals that are robust across the largest AMOC events in each model, which provides reassurance that the surface changes associated with one particular event will be similar to those expected from regression analysis. However, large differences are found between the AMOC fingerprints in different models, which may hinder the prediction and attribution of such events in reality.

A Productivity-Based Approach to LAN Topology Design

Over the useful life of a LAN, network downtimes will have a negative impact on organizational productivity not included in current Network Topological Design (NTD) problems. We propose a new approach to LAN topological design that includes the impact of these productivity losses into the network design, minimizing not only the CAPEX but also the expected cost of unproductiveness attributable to network downtimes over a certain period of network operation.

Entropy-Based Approach to Analyze and Classify Mineral Aggregates

This paper presents an automatic method to detect and classify weathered aggregates by assessing changes of colors and textures. The method allows the extraction of aggregate features from images and the automatic classification of them based on surface characteristics. The concept of entropy is used to extract features from digital images. An analysis of the use of this concept is presented and two classification approaches, based on neural networks architectures, are proposed. The classification performance of the proposed approaches is compared to the results obtained by other algorithms (commonly considered for classification purposes). The obtained results confirm that the presented method strongly supports the detection of weathered aggregates.

A complex network-based approach for boundary shape analysis

This paper introduces a novel methodology to shape boundary characterization, where a shape is modeled into a small-world complex network. It uses degree and joint degree measurements in a dynamic evolution network to compose a set of shape descriptors. The proposed shape characterization method has all efficient power of shape characterization, it is robust, noise tolerant, scale invariant and rotation invariant. A leaf plant classification experiment is presented on three image databases in order to evaluate the method and compare it with other descriptors in the literature (Fourier descriptors, Curvature, Zernike moments and multiscale fractal dimension). (C) 2008 Elsevier Ltd. All rights reserved.

An entropy-based approach to automatic image segmentation of satellite images

An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation. (C) 2010 Elsevier B.V. All rights reserved.

Structure-Based Approach for the Study of Estrogen Receptor Binding Affinity and Subtype Selectivity

Estrogens exert important physiological effects through the modulation of two human estrogen receptor (hER) subtypes, alpa (hER alpha) and beta (hER beta). Because the levels and relative proportion of hER alpha and hER beta differ significantly in different target cells, selective hER ligands could target specific tissues or pathways regulated by one receptor subtype without affecting the other. To understand the structural and chemical basis by which small molecule modulators are able to discriminate between the two subtypes, we have applied three-dimensional target-based approaches employing a series of potent hER-ligands. Comparative molecular field analysis (CoMFA) studies were applied to a data set of 81 hER modulators, for which binding affinity values were collected for both hER alpha and hER beta. Significant statistical coefficients were obtained (hER alpha, q(2) = 0.76; hER beta, q(2) = 0.70), indicating the internal consistency of the models. The generated models were validated using external test sets, and the predicted values were in good agreement with the experimental results. Five hER crystal structures were used in GRID/PCA investigations to generate molecular interaction fields (MIF) maps. hER alpha and hER beta were separated using one factor. The resulting 3D information was integrated with the aim of revealing the most relevant structural features involved in hER subtype selectivity. The final QSAR and GRID/PCA models and the information gathered from 3D contour maps should be useful for the design or novel hER modulators with improved selectivity.