Topological Repairing of 3D Digital Images

We present here a new randomized algorithm for repairing the topology of objects represented by 3D binary digital images. By “repairing the topology”, we mean a systematic way of modifying a given binary image in order to produce a similar binary image which is guaranteed to be well-composed. A 3D binary digital image is said to be well-composed if, and only if, the square faces shared by background and foreground voxels form a 2D manifold. Well-composed images enjoy some special properties which can make such images very desirable in practical applications. For instance, well-known algorithms for extracting surfaces from and thinning binary images can be simplified and optimized for speed if the input image is assumed to be well-composed. Furthermore, some algorithms for computing surface curvature and extracting adaptive triangulated surfaces, directly from the binary data, can only be applied to well-composed images. Finally, we introduce an extension of the aforementioned algorithm to repairing 3D digital multivalued images. Such an algorithm finds application in repairing segmented images resulting from multi-object segmentations of other 3D digital multivalued images.

Robust linear quadratic regulator applied to an inverted pendulum

The natural instability of an inverted pendulum and its dynamics richness, in terms of nonlinearity, provide a nice apparatus to reproduce behaviors of analogous systems. In this way, it is useful to perform benchmark tests for new control approaches developed. In this paper, we address the main inverted pendulum problems: pendulum stabilization, tracking, and catching swing-up control. We show how robust recursive, control and filtering, techniques improve the system performance. They are developed to solve stochastic problems based on deterministic approaches, in order to decrease the worst influence of uncertainties. Experimental results of the proposed robust approach provide robust stability and performance despite parametric uncertainties, disturbances, and noise effects.     

Estimating vulnerability to risks: an application in a biofuel supply chain

In the present work, we propose a theoretical model to identify and prioritize risks involved in a biofuel supply chain. We adopt a set of indicators associated with determinant factors of the supply chain to identify risks that are characterized through a risk matrix. We consider the five largest world biodiesel producers and included China due to its global market importance and potential impacts of its growth on the environment and society. To determine the impacts and the probability of occurrence of risks, we use the Canberra distance, as metrics. To facilitate the analysis and interpretation, a convenient manner is to express the results in terms of matrices. To exemplify the potentiality of the scheme and for the sake of simplicity, a more comprehensive discussion is focused on the Brazilian case, restricted to the Technology and Innovation, and Integration, Logistics and Infrastructure determining factors (dimensions) of the biodiesel supply chain. Concerning these determining factors, the Brazilian biodiesel chain shows strong vulnerability when compared with developed and developing countries, despite that the evolution of the data over recent years indicates small improvements in Integration, Logistics and Infrastructure dimension. Although in this work the calculations are restricted to the Canberra distance, the present approach may be applied to other distances to compare or validate the results. This work presents a contribution to model vulnerability to risks, providing to policy makers and stakeholders a tool to design, analyze and improve sustainability system by measuring its risks. The study of the contribution of each indicator suggests corrections to be taken and which indicators should be prioritized.     

Spatial data warehouses and spatial OLAP come towards the cloud: design and performance

Cloud computing systems handle large volumes of data by using almost unlimited computational resources, while spatial data warehouses (SDWs) are multidimensional databases that store huge volumes of both spatial data and conventional data. Cloud computing environments have been considered adequate to host voluminous databases, process analytical workloads and deliver database as a service, while spatial online analytical processing (spatial OLAP) queries issued over SDWs are intrinsically analytical. However, hosting a SDW in the cloud and processing spatial OLAP queries over such database impose novel obstacles. In this article, we introduce novel concepts as cloud SDW and spatial OLAP as a service, and afterwards detail the design of novel schemas for cloud SDW and spatial OLAP query processing over cloud SDW. Furthermore, we evaluate the performance to process spatial OLAP queries in cloud SDWs using our own query processor aided by a cloud spatial index. Moreover, we describe the cloud spatial bitmap index to improve the performance to process spatial OLAP queries in cloud SDWs, and assess it through an experimental evaluation. Results derived from our experiments revealed that such index was capable to reduce the query response time from 58.20 up to 98.89 %.     

Template-based quadrilateral meshing

Generating quadrilateral meshes is a highly non-trivial task, as design decisions are frequently driven by specific application demands. Automatic techniques can optimize objective quality metrics, such as mesh regularity, orthogonality, alignment and adaptivity; however, they cannot make subjective design decisions. There are a few quad meshing approaches that offer some mechanisms to include the user in the mesh generation process; however, these techniques either require a large amount of user interaction or do not provide necessary or easy to use inputs. Here, we propose a template-based approach for generating quad-only meshes from triangle surfaces. Our approach offers a flexible mechanism to allow external input, through the definition of alignment features that are respected during the mesh generation process. While allowing user inputs to support subjective design decisions, our approach also takes into account objective quality metrics to produce semi-regular, quad-only meshes that align well to desired surface features.     

Template-based quadrilateral mesh generation from imaging data

This paper describes a novel template-based meshing approach for generating good quality quadrilateral meshes from 2D digital images. This approach builds upon an existing image-based mesh generation technique called Imeshp, which enables us to create a segmented triangle mesh from an image without the need for an image segmentation step. Our approach generates a quadrilateral mesh using an indirect scheme, which converts the segmented triangle mesh created by the initial steps of the Imesh technique into a quadrilateral one. The triangle-to-quadrilateral conversion makes use of template meshes of triangles. To ensure good element quality, the conversion step is followed by a smoothing step, which is based on a new optimization-based procedure. We show several examples of meshes generated by our approach, and present a thorough experimental evaluation of the quality of the meshes given as examples.     

Development and Validation of an HPLC–DAD Method for Analysis of the Six Major Isoflavones in Extracts from Soybean Processing

In this study, a new HPLC method was developed and validated for the determination of daidzin, genistin, glycitin, and their respective aglycones daidzein, genistein and glycitein in extracts from different stages of soy processing. The chromatographic separation was achieved using a Bonus RP 100 × 3.0 mm (3.5-μm particle size) column maintained at 35 °C. The mobile phase consisted of a gradient of water and acetonitrile both containing 0.1% formic acid. Analyses were conducted at a flow rate of 1.0 mL min⁻¹ and the detector was set at 254 nm. Validation parameters indicated that the method has high selectivity and is linear over a range of 1.5–150 μg mL⁻¹ for all compounds. The range of recovery was 95–102% with a RSD% <5% for intra-day and inter-day precision. The robustness study indicated that the flow rate was the only critical factor. The new HPLC–DAD method was successfully applied to real samples and excellent separation was achieved without the need of any sample pretreatment.