A GIS plug-in for Bayesian belief networks: Towards a transparent software framework to assess and visualise uncertainties in ecosystem service mapping

The complexity and spatial heterogeneity of ecosystem processes driving ecosystem service delivery require spatially explicit models that take into account the different parameters affecting those processes. Current attempts to model ecosystem service delivery on a broad, regional scale often depend on indicator-based approaches that are generally not able to fully capture the complexity of ecosystem processes. Moreover, they do not allow quantification of uncertainty on their predictions. In this paper, we discuss a QGIS plug-in which promotes the use of Bayesian belief networks for regional modelling and mapping of ecosystem service delivery and associated uncertainties. Different types of specific Bayesian belief network output maps, delivered by the plug-in, are discussed and their decision support capacities are evaluated. This plug-in, used in combination with firmly developed Bayesian belief networks, has the potential to add value to current spatial ecosystem service accounting methods. The plug-in can also be used in other research domains dealing with spatial data and uncertainty.     

Managing readiness-relevant activities for the organizational dimension of ERP implementation

An organization requires performing readiness-relevant activities to ensure successful implementation of an enterprise resource planning (ERP) system. This paper develops a novel approach to managing these interrelated activities to get ready for implementing an ERP system. The approach enables an organization to evaluate its ERP implementation readiness by assessing the degree to which it can achieve the interrelated readiness relevant activities using fuzzy cognitive maps. Based on the interrelationship degrees among the activities, the approach clusters the activities into manageable groups and prioritizes them. To help work out a readiness improvement plan, scenario analysis is conducted.     

Automated classification of simulated wind field patterns from multiphysics ensemble forecasts

In this study, we have proposed an automated classification approach to identify meaningful patterns in wind field data. Utilizing an extensive simulated wind database, we have demonstrated that the proposed approach can identify low‐level jets, near‐uniform profiles, and other patterns in a reliable manner. We have studied the dependence of these wind profile patterns on locations (eg, offshore vs onshore), seasons, and diurnal cycles. Furthermore, we have found that the probability distributions of some of the patterns depend on the underlying planetary boundary layer schemes in a significant way. The future potential of the proposed approach in wind resource assessment and, more generally, in mesoscale model parameterization improvement is touched upon in this paper.     

小波变换用于影象分割的研究

将近年来兴起的小波理论应用于影象分割技术，提出了一种基于影象直方图小波变换的影象分割方法，并从理论上给出了使用该法所得分割门限的物理意义。实例表明，这种由粗到细引导的多分辨率分析方法，对于复杂影象的分割具有较强的鲁棒性和有效性，克服了传统分割方法中的参数需要人工确定的缺点。     

Cluster analysis in industrial market segmentation through artificial neural network

Market segmentation has commonly applied cluster analysis. This study intends to make the comparison of conventional two-stage method with proposed two-stage method through the simulated data. The proposed two-stage method is the combination of self-organizing feature maps and K-means method. The simulation results show that the proposed scheme is better than the conventional two-stage method based on the rate of misclassification.     

Scanning electron microscope electron detector with a radial type discrete dynode electron multiplier

A discrete dynode electron multiplier with radial flux of electrons was built and tested in the range of low‐voltage scanning electron microscopy as a backscattered electron detector of topographic contrast. The multiplier collects backscattered electron emitted in a specific range of take‐off angles and over the whole azimuth angular range enabling large solid collection angle. Multipliers with different dynode shapes were studied theoretically with the use of the software for particle optics and three assemblies were built and tested experimentally. The gain estimation, assessment of the type of detected electrons (secondary electron or backscattered electron), imaging the spatial collection efficiency and signal‐to‐noise measurements were performed.     

The use of the scanning electron microscope in the determination of the mineral composition of Ballachulish slate

Slate is a fine-grained, low-grade metamorphic rock derived from argillaceous sediments or occasionally volcanic ash. Although most slates contain mainly quartz, chlorite and white mica, they vary considerably in their durability, some lasting centuries while others fail after a few years of service. A detailed characterisation of their mineralogy is required for the assessment of performance, and to establish the provenance of a used slate. A combination of methods was used to examine Ballachulish slates; XRD analysis to determine the principal minerals present, XRF analysis to determine the total chemical composition, and scanning electron microscopy to determine the chemical composition of individual minerals. It was found that the white mica in Ballachulish slate is phengite and the chlorite is ripidolite. Feldspar is present as albite and carbonate as ferroan dolomite. Several accessory minerals were also identified, including chloritoid, monzonite and zircon. There was considerable variation in the ratio of the principal minerals, making it impossible to identify used slates by this criterion. Instead, chemical composition of the individual minerals, and possibly key accessory minerals, should be used to determine the provenance of slates.     

Perceptual primitives from an extended 4D Hough transform

Directional features extracted from Gabor wavelets responses were used to train a structure of self-organising maps, thus classifying each pixel in the image within a neuron-map. Resulting directional primitives were grouped into perceptual primitives introducing an extended 4D Hough transform to group pixels with similar directional features. These can then be used as perceptual primitives to detect salient structures. The proposed method has independently fixed parameters that do not need to be tuned for different kind or quality of images. We present results in application to noisy FLIR images and show that line primitives for complex structures, such as bridges, or simple structures, such as runways, can be found by this approach. We compare and demonstrate the quality of our results with those obtained through a parameter-dependent traditional Canny edge detector and Hough line finding process.     

Simulation of the Forming Behaviour of a Boron Modified P91 Ferritic Steel

The forming behaviour at high temperature of a modified 9%Cr‐1%Mo (P91) ferritic steel containing B and Ti for elevated temperature service was investigated. The microstructure of the as‐received material is mainly martensite at room temperature, but special etching revealed prior austenite grains of about 25 μm in size. Torsion tests were conducted at temperatures in the range 850 to 1250 °C to simulate the hot rolling process under comparable conditions of temperature, strain rate and strain. The deformation data obtained from these tests were correlated with the Garofalo equation with a stress exponent of 4.6 and an activation energy of 315 kJ/mol. This equation was used to predict the formability behaviour for the rolling process and also to determine the maximum forming efficiency and stability of the steel. A temperature of 1200 °C is recommended to conduct the forming process.