Spatio‐temporal geometry fusion for multiple hybrid cameras using moving least squares surfaces

Multi‐view reconstruction aims at computing the geometry of a scene observed by a set of cameras. Accurate 3D reconstruction of dynamic scenes is a key component for a large variety of applications, ranging from special effects to telepresence and medical imaging. In this paper we propose a method based on Moving Least Squares surfaces which robustly and efficiently reconstructs dynamic scenes captured by a calibrated set of hybrid color+depth cameras. Our reconstruction provides spatio‐temporal consistency and seamlessly fuses color and geometric information. We illustrate our approach on a variety of real sequences and demonstrate that it favorably compares to state‐of‐the‐art methods.     

On‐the‐fly generation and rendering of infinite cities on the GPU

In this paper, we present a new approach for shape‐grammar‐based generation and rendering of huge cities in real‐time on the graphics processing unit (GPU). Traditional approaches rely on evaluating a shape grammar and storing the geometry produced as a preprocessing step. During rendering, the pregenerated data is then streamed to the GPU. By interweaving generation and rendering, we overcome the problems and limitations of streaming pregenerated data. Using our methods of visibility pruning and adaptive level of detail, we are able to dynamically generate only the geometry needed to render the current view in real‐time directly on the GPU. We also present a robust and efficient way to dynamically update a scene's derivation tree and geometry, enabling us to exploit frame‐to‐frame coherence. Our combined generation and rendering is significantly faster than all previous work. For detailed scenes, we are capable of generating geometry more rapidly than even just copying pregenerated data from main memory, enabling us to render cities with thousands of buildings at up to 100 frames per second, even with the camera moving at supersonic speed.     

IISPH‐FLIP for incompressible fluids

We propose to use Implicit Incompressible Smoothed Particle Hydrodynamics (IISPH) for pressure projection and boundary handling in Fluid‐Implicit‐Particle (FLIP) solvers for the simulation of incompressible fluids. This novel combination addresses two issues of existing SPH and FLIP solvers, namely mass preservation in FLIP and efficiency and memory consumption in SPH. First, the SPH component enables the simulation of incompressible fluids with perfect mass preservation. Second, the FLIP component efficiently enriches the SPH component with detail that is comparable to a standard SPH simulation with the same number of particles, while improving the performance by a factor of 7 and significantly reducing the memory consumption. We demonstrate that the proposed IISPH‐FLIP solver can simulate incompressible fluids with a quantifiable, imperceptible density deviation below 0.1%. We show large‐scale scenarios with up to 160 million particles that have been processed on a single desktop PC using only 15GB of memory. One‐ and two‐way coupled solids are illustrated.     

Encapsulation of Hydroxyapatite Microspheres with Fluorapatite Using a Diffusion Process

Modification of hydroxyapatite surfaces can improve the properties of biomedical devices. The objective of this work was to encapsulate hydroxyapatite particles with a fluorapatite layer. A suspension of hydroxyapatite microspheres was prepared in a solution at different pH and treated with ammonium fluoride. pH, calcium, and fluoride were monitored in real time and particles subjected to fluoride analysis. After addition of fluoride, it was found that more material is released from the particle surface at low pH conditions, but leads to a high fluoride uptake from solution. Low solution fluoride levels produce a fluorapatite layer, but higher fluoride levels produce calcium fluoride.     

Foresight for a responsible future with ICT

The ACM Code of Ethics asserts that computing professionals have an ethical responsibility to minimize the negative consequences of information and communication technologies (ICT). Negative consequences are rarely intended, but they can often be foreseen with careful sociotechnical analysis in advance of system building. Motivated by an interest in extremely complex sociotechnical contexts (e.g., mortgage lending and automated trading) where ICT appears to be having negative consequences in addition to many benefits, this paper identifies and evaluates future-oriented problem analysis and solution design tools in three potentially relevant literatures: 1) ICT ethics, 2) environmental sustainability, and 3) technology hazards. Several promising future-oriented technology analysis techniques (e.g., anticipatory technology ethics, technology roadmapping, morphological analysis, and control structure analysis) were found and are discussed in this paper, but much work remains to be done to customize them, integrate them, and codify them for use in education and high-quality IS research on very complex sociotechnical contexts like the global financial network.     

Automatic classifier selection for non-experts

Choosing a suitable classifier for a given dataset is an important part of developing a pattern recognition system. Since a large variety of classification algorithms are proposed in literature, non-experts do not know which method should be used in order to obtain good classification results on their data. Meta-learning tries to address this problem by recommending promising classifiers based on meta-features computed from a given dataset. In this paper, we empirically evaluate five different categories of state-of-the-art meta-features for their suitability in predicting classification accuracies of several widely used classifiers (including Support Vector Machines, Neural Networks, Random Forests, Decision Trees, and Logistic Regression). Based on the evaluation results, we have developed the first open source meta-learning system that is capable of accurately predicting accuracies of target classifiers. The user provides a dataset as input and gets an automatically created high-performance ready-to-use pattern recognition system in a few simple steps. A user study of the system with non-experts showed that the users were able to develop more accurate pattern recognition systems in significantly less development time when using our system as compared to using a state-of-the-art data mining software.     

Engineering microfluidic papers: effect of fiber source and paper sheet properties on capillary-driven fluid flow

In the present study, we introduce a novel approach to control and modulate fluid transport inside microfluidic papers using lab-engineered paper sheets. Lab-sheets consisting of different fiber sources (eucalyptus sulfate and cotton linters pulp) and varying porosities were designed and further modified with small millimeter-scaled channels using hydrophobic barriers consisting of fiber-attached, hydrophobic polymers. The capillary-driven transport of an aqueous solution was monitored visually, and the influence of parameters such as fiber source, paper grammage, and channel width on the flow rates through the channel was investigated. The experimental results were compared with those obtained with commercially available filter papers. Our findings suggest that accurate control of fluid transport processes with standard filter papers is complex. Additionally, if the channel width is smaller than the mean fiber length, flow rates become dependent on the geometric parameters of the channel because of the formation of dead-end pores at the hydrophobic barriers. Finally, control of the paper sheets porosity, by varying the fiber density of the lab-made paper, affords the fabrication of chemically identical sheets whereby capillary flow is largely influenced and can be modulated accordingly by simple papermaking processes.     

An architecture modeling framework for probabilistic prediction

In the design phase of business and IT system development, it is desirable to predict the properties of the system-to-be. A number of formalisms to assess qualities such as performance, reliability and security have therefore previously been proposed. However, existing prediction systems do not allow the modeler to express uncertainty with respect to the design of the considered system. Yet, in contemporary business, the high rate of change in the environment leads to uncertainties about present and future characteristics of the system, so significant that ignoring them becomes problematic. In this paper, we propose a formalism, the Predictive, Probabilistic Architecture Modeling Framework (P²AMF), capable of advanced and probabilistically sound reasoning about business and IT architecture models, given in the form of Unified Modeling Language class and object diagrams. The proposed formalism is based on the Object Constraint Language (OCL). To OCL, P²AMF adds a probabilistic inference mechanism. The paper introduces P²AMF, describes its use for system property prediction and assessment and proposes an algorithm for probabilistic inference.     

Fluidized Bed Air Drying: Experimental Study and Model Development

The presented study describes the processes and mechanisms of batch fluidized bed drying. The influencing factors of hot air drying are theoretically and experimentally examined, in order to present the relations between temperature and humidity profiles and all other drying parameters. A physical model is presented to facilitate the calculation of the drying processes under defined conditions. Three succeeding drying stages are therefore modeled. Mass and energy balances including all components taking part in the process are formulated. The model clarities the drying process under the assumption of pure heat transfer mechanisms. It does not contain adaptive parameters and takes into account an inactive bypass fraction of the fluidization and drying medium. The evaluation of the model was successful for two fluidized bed plants with nominal widths of 100 mm and 400 mm. The experiments showed sufficient accuracy and transferability of the model to equipment of application‐oriented dimensions.     

Mechanical and erosion properties of CaCO3‐EMAA thermal sprayed coatings

Polymer‐ceramic composite coatings manufactured from calcium carbonate and ethylene‐methacrylic acid copolymer (EMAA) were prepared via a thermal spray process employing different CaCO₃ filler sizes (average size of 2.8, 9 or 36 μm) and loading levels from about 2.5 to 7 wt%. The optimum filler feeding characteristics, deposition efficiency and deposition rate were obtained with a 36 μm sized CaCO₃. Tensile properties, peel strength, and the erosion resistance of a pure EMAA and CaCO₃‐EMAA composite coatings were investigated. It was found that the tensile strain at fracture of the composite coating decreased with the addition of filler to a greater degree than that observed in compression‐molded polymer composites. This is attributed to an inhomogenous distribution of the filler, with more being concentrated at the boundaries of the deposited polymer particles, thereby establishing a rigid framework within the coating. Only a small filler content is necessary to establish large changes in the mechanical properties of the coating. The peel strength of a composite coating decreases with filler content, both on a mild steel substrate and a previously sprayed polymer coating. Bonding to the latter is significantly higher and offers a possibility as a bonding layer between substrates and composite coatings. The coefficient of friction is lowered with the addition of a filler. Erosion testing has shown that the erosion resistance of PF111 is little improved overall with filler addition, although some increase is found for filler contents less than 5 vol%. Polym. Eng. Sci. 44:1448–1459, 2004. © 2004 Society of Plastics Engineers.