Automatic FLAC3D Mesh Generation Based on Advancing-Frontal Method

3D Seismic Imaging

1. M. Anderson and T. Feil, Turning lights out with linear algebra, this MAGAZINE 71 (1998), 300-303. 2. K. Banr, Lights Out Fan Club, at http://gbs.mit.edu/-kbarr/lo/ 3. R. Barua and S. Ramaluishnan, a-game, a+-game and two-dimensional additive cellular automata, Theoretical Compluter Science 154:2 (1996), 349-366. 4. C. Haese, paper in the sci.nath newsgroup in 1998, available at http://www.math.niu.edu/-rusin/knownmath/98/lights-out 5. B. Lotto, A computer puzzle as a paradigm for doing mathematics, Vassar Quarterly, Winter 1996, 18-23. 6. B. Lotto, personal letter, May 1999. 7. 0. Martin-Sanchez and C. Pareja-Flores, A Visual Basic Implementationl of Lights Out, available at http:// dalila.sip.ucm.es/miembros/cpareja/lo 8. D.L. Stock, Merlin's magic square revisited, Amer Math. Monthly 96 (1989), 608-610. 9. K. Sutner, Linear cellular automata and the garden-of-Eden, The Mathematical Intelligencer 11:2 (1989), 49-53.

The human genome and other genome sequencing projects have generated huge amounts of protein sequence information. Recently, a structural genomics project that aims to determine at least one representative three-dimensional structure from every protein family experimentally has been started. Homology modeling will play an essential role in structure based drug design such as in silico screening; because based on these representative structures the three-dimensional structures of the remaining proteins encoded in the various genomes can be predicted by homology modeling. The results of the last Critical Assessment of Techniques for Protein Structure Prediction (CASP5) demonstrated that the quality of homology modeling prediction has improved; reaching a level of reliability that biologists can now confidently use homology modeling. With improvements in modeling software and the growing number of known protein structures, homology modeling is becoming a more and more powerful and reliable tool. The present paper discusses the features and roles of homology modeling in structure based drug design, and describes the CHIMERA and FAMS modeling systems as examples. For a sample application, homology modeling of non-structural proteins of the severe acute respiratory syndrome (SARS) coronavirus is discussed. Many biological functions involve formation of protein-protein complexes; in which the protein molecules behave dynamically in the course of binding. Therefore, an understanding of protein-protein interaction will be very important for structure based drug design. To this end, normal mode analysis is useful. The present paper discusses the prediction of protein-protein interaction using normal mode analysis and examples of applications are given.

A new algorithm for volume mesh refinement on merging geometries: Application to liver and vascularisation

Three-dimensional model is high degree of freedom information. In order to realize content-based 3D model retrieval, normalization preprocessing of 3D models is needed. This paper have proposed a normalization method with 3D modeling software based on center of mass, principal axis of inertia and volume parameters to carry out coordinate system normalization of three-dimensional mechanical entity models. In this paper, Specific method is listed. Application examples are given to show the feasibility of this method.

This paper proposes an efficient heuristic algorithm for solving a complex batching and scheduling problem in a diffusion area of a semiconductor plant. Diffusion is frequently the bottleneck in the plant and also one of the most complex areas in terms of number of machines, constraints to satisfy and the large number of lots to manage. The purpose of this study is to investigate an approach to group lots in batches and to schedule these batches on machines. The problem is modelled and solved using a disjunctive graph representation. A constructive algorithm is proposed and improvement procedures based on iterative sampling and Simulated Annealing are developed. Computational experiments, carried out on actual industrial problem instances, show the ability of the iterative sampling algorithms to significantly improve the initial solution, and that Simulated Annealing enhances the results. Furthermore, our algorithm compares favourably to an algorithm reported in the literature for a simplified version of our problem. The constructive algorithm has been embedded in software and is currently being used in a semiconductor plant.

This presentation reports the theoretical study of 3d core-electron excitation in lanthanide compounds in terms of electronic structure effects and optical properties. The calculations are done at the Density-Functional Theory (DFT) level complemented with an effective Hamiltonian based on ligand-field theory. The strategy consists of obtaining from DFT a totally symmetric density, where an active subspace is set up that forms the basis of the fivefold 3d and sevenfold 4f atomic orbitals of the lanthanide ion. This active subspace is defined with the fractional occupation of electrons, which represents open-shell species with the composite configuration 3d94fn+1. Based on the ligand-field analysis of the DFT results, the multiplet energies and ligand-field effects associated with the configuration 3d94fn+1 are evaluated; and the X-ray absorption spectra are simulated in terms of the intra-atomic 4fn → 3d94fn+1 electron transitions within the electric-dipole approximation. Examples for application are proposed taking into consideration the isolated trivalent lanthanides ions and compounds Cs2NaPrX6, with X = F, Cl, and Br. The results are compared with available experimental data, where a good agreement is qualitatively achieved. Also, the screening of the inter-electron repulsion and spin-orbit coupling interaction is numerically obtained that allows one to establish a fully non-empirical treatment of the 3d core-electron excitation, which can be valuable in the characterization and modeling of the spectral profiles of lanthanide M4,5-edge X-ray absorption spectroscopy. The enclosed theoretical model, which is being implemented in the Amsterdam Density Functional (ADF) suite of programs, is computationally economic and can be applied to any lanthanide system without limitations in terms of the size of the matrix elements of the effective Hamiltonian or the coordination symmetry of the lanthanide center.

During the last two decades, software development has evolved continuously into an engineering discipline with systematic use of methods and tools to model and implement software. For example, object-oriented analysis and design is structuring software models according to real-life objects of the problem domain and their relations. However, the industrial robotics domain is still dominated by old-style, imperative robot programming languages, making software development difficult and expensive. For this reason, we introduce the object-oriented Robotics Application Programming Interface (Robotics API) for developing software for industrial robotic applications. The Robotics API offers an abstract, extensible domain model and provides common functionality, which can be easily used by application developers. The advantages of the Robotics API are illustrated with an application example.

Computation of anomalous gravity and magnetic fields generated by various models is a necessary step if techniques of curve‐matching are to be used for quantitative interpretation of potential field data. Recently developed methods show that anomalous magnetic and gravity fields are completely determined by the divergence of magnetization and the first vertical derivative of density, respectively. Using these methods, efficient algorithms can be developed for computing potential field anomalies caused by arbitrary distribution of magnetization and density in an irregularly shaped body. Automatic iterative procedures are normally employed in the space domain for estimating parameters of the selected model that yield a best‐fit anomaly curve for a set of discrete observed data. Examples of application of the Newton‐Raphson method, Marquardt method, and the Powell algorithm to the interpretation of magnetic data are presented and discussed. Amplitude and energy spectra of the anomalous fields are also used conveniently in many cases for systematic estimation of average and individual depths, horizontal and vertical extents, and density or magnetization contrasts of causative bodies in a bounded region. Some of these frequency‐domain approaches are found to have many useful applications.

This paper focuses on the identification/prediction of the blade exhibiting the largest response in mistuned bladed disks. This information is very important in experimental/testing efforts as it permits the most effective positioning of a few gages to capture the maximum response on the disk. In computational statistical analyses, knowing the highest responding blade is also quite valuable as it may lead to computational savings in the determination of the maximum response. Different strategies are proposed here for the experimental and computational contexts. In the former situation, mistuning is typically unknown but only one or a few disks must be considered. The proposed solution is then to estimate the mistuned blade properties and to rely on this identified bladed disk model to predict the blades that are likely to exhibit the largest responses through exact, full disk solutions. On the contrary, in computational statistical analyses, mistuning is specified but a potentially large number of disks must be analyzed and it is desired to bypass the ensemble of full disk solutions. Accordingly, a novel, computationally very efficient algorithm is proposed for a preliminary estimation of the forced response of mistuned disks from which the blades that are likely to exhibit the largest responses can be predicted. Examples of application on single- and two-degree-of-freedom per blade models and a reduced order model of a blisk demonstrate the reliability of the proposed strategies.

The chapter is devoted to the software engineering of large-scale control and automation systems for programmable logic controller platforms. The classes of these control systems typically involve hundreds or thousands of signals, dozens of control loops, and have to cope with the hybrid nature of the processes. Interestingly, the complexity of the development, operation and maintenance of the software for such kinds of systems is not so much associated with basic control (maintenance of the desired state of the process), but much more with so-called procedural control (performing a sequence of activities that ensure proper operation of the system or process). The emphasis of the chapter is on the presentation of a model-driven engineering approach to procedural control software development. The main element of the approach is ProcGraph, an original domain-specific modelling language which enables the construction of high-level specifications (software models). The other important element of the approach is an integrated development environment consisting of the model repository, the graphical model editor and the code generator. The integrated development environment enables the creation and editing of ProcGraph models and their automatic transformation into the programmable logic controller software. As an application example, the control system of a calcinate-grinding process is considered, which is one of the sub-processes in the large and complex process of producing titanium dioxide.KeywordsProgrammable Logic ControllerComposite DependencyIntegrate Development EnvironmentModel RepositoryRotary ValveThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Recently, spatial augmented reality regained popularity in media arts and in the field of tangible, embedded interaction [Holman and Vertegaal 2008], by using 3D objects as information displays. The advantage of projected graphics is obvious: it allows for updatable appearance of 3D objects without refabrication. However, in many everyday objects such as fashion and shoes, projector technology is not feasible due to power and tracking requirements, and the need for a darkened environment. Users cannot take the objects outside the calibrated projector setup.We introduce a novel concept of a stateful projector display that uses bi-stable color changing inks. We augment non-planar and complex painted surfaces by projecting high resolution imagery that persist. Similar to e-ink, graphics last without requiring additional power and are rewritable.Our printer builds upon earlier Emerging Technologies demonstrations [Saakes et al. 2010] and [Hashida et al. 2011] that used mono-stable photosensitive materials and near UV projectors. Because our system uses bi-stable thermochromic materials, our prints persist for at least a month, and are least 10 times rewritable. That makes the concept is useful for various applications that are not catered by traditional displays or fabrication technologies. For instance, fashion items such as shoes or bags, wallpapers, and floors can be updated frequently. Design prototypes can be tested outside the laboratory environment in outdoors and in real-use scenarios. Another application could be very large size, high resolution information displays that are constantly updated.Our workflow starts by coating a target object with bi-stable, thermochromic inks. We scan the object to obtain its geometry. We apply graphics as 2D textures on the 3D model in modeling software. In the printing process, we align the 3D model with the object. For each point (pixel) on the object, we estimate the color with a scanning laser. We compare the obtained color with the intended color from the textured model, and a writing laser then makes the color selectively transparent by applying heat. Depending on the ink used, a second process (for instance freezing the object) reverses this process and makes the inks opaque to allow for updatable content.We have tested two bi-stable thermochromic inks. The first is harvested from frixion pens that come in a colored state. By heating above 70 degrees Celcius, the ink becomes white and stays that way until it is cooled below -10 degrees Celsius and reaches the second stable state. The other material switches to the colored state when the material is heated to 180 degrees Celcius and then cooled down quickly. The translucent state is achieved by heating the material up to 120 degrees before cooling it down slowly.The opportunities for projector displays using bi-stable inks are immense. The Shader Printer fills a niche of non-planar surfaces and supports applications of dynamically attaching images onto complex surfaces allowing for non-traditional displays. Finally, low costs enable easy adoption of the new technology.There are several limitations in our technology in the area of pixel density and color reproduction that obviously can not match the years of research in commercially available display or laser systems. However, we hope to have demonstrated the advantages of a Shader Printer system.

Background: Modeling of deep brain stimulation electric fields and anatomy-based software might improve post-operative management of patients with Parkinson's disease (PD) who have benefitted from subthalamic nucleus deep brain stimulation (STN-DBS).Objective: We compared clinical and software-guided determination of the thresholds for current diffusion to the pyramidal tract, the most frequent limiting side effect in post-operative management of STN-DBS PD patients.Methods: We assessed monopolar reviews in 16 consecutive STN-DBS PD patients and retrospectively compared clinical capsular thresholds, which had been assessed according to standard clinical practice, to those predicted by volume of tissue activated (VTA) model software. All the modeling steps were performed blinded from patients' clinical evaluations.Results: At the group level, we found a significant correlation (p = 0.0001) when performing statistical analysis on the z-scored capsular thresholds, but with a low regression coefficient (r = 0.2445). When considering intra-patient analysis, we found significant correlations (p < 0.05) between capsular threshold as modeled with the software and capsular threshold as determined clinically in five patients (31.2%).Conclusions: In this pilot study, the VTA model software was of limited assistance in identifying capsular thresholds for the whole cohort due to a large inter-patient variability. Clinical testing remains the gold standard in selecting stimulation parameters for STN-DBS in PD.

Applications of artificial neural networks in the field of aeration phenomena in surface aerators, which are not geometrically similar, are explored to predict reaeration rates under varying dynamic as well as geometric conditions. The primary network for prediction is a feed forward network with nonlinear elements. The network consists of an input layer, an output layer, a hidden layer, and the nonlinear transfer function in each processing element. The network requires supervised learning and the learning algorithm is the back-propagation. As back-propagation learning is affected by local minima, and to get over this aspect various other modifications have been suggested like Levenberg-Marquardt, quasi-Newton, conjugate-gradient, etc. The present study suggests that the Levenberg-Marquardt modification is a very efficient algorithm in comparison with others like quasi-Newton and conjugate-gradient. In the situations when the dimension of the input vector is large, and highly correlated, it is useful to reduce the dimension of the input vectors. An effective procedure for performing this operation is principal component analysis. The best prediction performance is achieved when the data are preprocessed using principal components analysis before they are fed to a back-propagated neural network, but at the cost of losing the physical significance of experimental data. The model thus developed can be used to predict the reaeration rate for different sizes of geometric elements (like rotor diameter, sizes of rotor, aerators' geometry, water depth, etc.) under various dynamic conditions, i.e., the speed of the rotor.

MotivationUnknown parameters of dynamical models are commonly estimated from experimental data. However, while various efficient optimization and uncertainty analysis methods have been proposed for quantitative data, methods for qualitative data are rare and suffer from bad scaling and convergence.ResultsHere, we propose an efficient and reliable framework for estimating the parameters of ordinary differential equation models from qualitative data. In this framework, we derive a semi-analytical algorithm for gradient calculation of the optimal scaling method developed for qualitative data. This enables the use of efficient gradient-based optimization algorithms. We demonstrate that the use of gradient information improves performance of optimization and uncertainty quantification on several application examples. On average, we achieve a speedup of more than one order of magnitude compared to gradient-free optimization. In addition, in some examples, the gradient-based approach yields substantially improved objective function values and quality of the fits. Accordingly, the proposed framework substantially improves the parameterization of models from qualitative data.Availability and implementationThe proposed approach is implemented in the open-source Python Parameter EStimation TOolbox (pyPESTO). pyPESTO is available at https://github.com/ICB-DCM/pyPESTO. All application examples and code to reproduce this study are available at https://doi.org/10.5281/zenodo.4507613.Supplementary information Supplementary data are available at Bioinformatics online.