Moment-Based Opacity Optimization

We present an optimum metallic-bond scheme to study the geometric structures of sodium clusters Na n ( n ≤15) systematically by combining the characteristics of metallic bonds and the first principle molecular dynamics simulation. The scheme provides an optimum way to examine almost all stable structures of sodium clusters and to determine their ground state structures. It is interesting to note that for the larger sodium clusters (13≤ n ≤15), there are some plane-like substructures on their surfaces, which resemble the fragments of the (110) plane with the highest atomic area density in the bulk bcc sodium crystal. We also propose a possible way to understand the formation of large icosahedral sodium clusters (1500 n <22000).

This thesis explores the hypothesis that designers, as visual representation specialists, can catalyze novel moments of insight for researchers by visualizing, translating, distilling, and interpreting abstract data or models into concrete forms which allow researchers to see their data in a new way. Through four design practice studies, in four different contexts of research, I have employed what I see as the skills of a designer to assist in the exploration, testing, and definition of new knowledge. This research identifies and illuminates four pathways into a rich territory for exploration at the intersection of scientific research and recursive visualization design. I hope to show that designers can not only be external communicators of science, but be contributing members of a research team. This thesis does not aim to identify and problem and solve it, but rather to open a space of exploration. Well situated in four fields of literature, but focusing on a more practice-based approach to research through design, this thesis is an organic novel outgrowth of previous thinking. Methods and definitions of critical scientific visualization skills are elucidated, in addition to detailed descriptions of the role of design on scientific research teams.

Driven by today’s supercomputers, larger and larger sets of data are created during numerical simulations of geoscientific applications. Such data often describes instationary processes in three-dimensional domains in terms of multi-dimensional data. Due to limited computer resources, it might be impossible or unpractical to store all data created during one simulation, which is why several data reduction techniques are often applied (e.g. only every nth time-step is stored). Intuitive scientific visualization techniques can help to better understand the structures described by transient data. Adequate reconstruction techniques for the time-dimension are needed since standard techniques (e.g. linear interpolation) are insufficient for many applications. We describe a general formalism for a wide class of reconstruction techniques and address aspects of quality characteristics. We propose an approach that is able to take arbitrary physical processes into account to enhance the quality of the reconstruction. For the eruption of the volcano Eyjafjallajkull in Iceland in the spring of 2010, we describe a suitable reduced model and use it for model-based visualization. The original data was created during a COSMO-ART simulation. We discuss the reconstruction errors, related computational costs, and possible extensions. A comparison with linear interpolation clearly motivates the proposed model-based reconstruction approach.

Within the past few years, computer graphics has played a decisive role in transforming the field of molecular modeling into an international industry. While computer scientists are conversant in the language of their own discipline, they are often unfamiliar with the terminology and unique graphical constructs of physical scientists. Similarly, physical scientists are often unfamiliar with the latest paradigms and technological advances in graphical computing. The successful marriage of Chemistry and Computer Graphics is an outstanding model of technology transfer and cross-disciplinary fertilization. Drawing on chemistry visualizations performed at the Cornell Theory Center, this workshop covers some of the terminology, tools and current problems that have evolved at the boundary between these two fields.

Aging highway infrastructure requires effective rating methodologies to prioritize bridges for rehabilitation and repair. To aid engineers in decision making regarding bridge maintenance, a three-dimensional (3D) visualization system is developed for rating reinforced concrete deck-girder bridge. Color codings show the most probable mode of failure for girder cross sections under combined moment-shear forces and allow an engineer to determine a rehabilitation strategy. The visualization system relies on 3D finite-element analyses using the open source framework OpenSees, making the system readily extensible to a wide range of bridge types and loading scenarios, as well as emergent reliability-based rating methodologies. Important features of the visualization system are emphasized, including the use of lighting and feature edge detection to improve the visual quality of a bridge model. Recent developments in scientific visualization are discussed for potential application to civil engineering problems.

Scientific Visualization is currently a very active and vital area of research, teaching and development. The success of Scientific Visualization is mainly due to the soundness of the basic premise behind it, that is, the basic idea of using computer-generated pictures to gain information and understanding from data (geometry) and relationships (topology). This is an extremely intiutive and very important concept which is having a profound and wide spread impact on the methodology of science and engineering. In this survey we are concentrating on three main research areas in Scientific Visualization - Intelligent Visualization Systems - Visualization of Vector- and Tensorfields - Augmented Reality Simulation

Objective To study the relationship between ischemic mitral regurgitation and geometric angles of the mitral valve leaflets in patients with coronary artery disease and papillary muscle dysfunction by transesophageal echocardiography（TEE）, and to evaluate anatomy and pathophysiology mechanicm of the ischemic mitral regurgitation with left ventricular papillary muscle dysfunction. Methods A total of 84 subjects were enrolled in this study. All of the subjects were divided into group A （healthy volunteers constituted the control group, n = 40）,group B （chronic inferior or posterior myocardial infarction patients with papillary muscle dysfunction group, n = 44）, group C（patients from group B after mitral valvuloplasty surgery, n = 20）.The relationship between mitral regurgitation and geometric angles of the mitral valve leaflets and mitral annulus were studied by TEE. Results Geometric angle between the mitral valve leaflets and mitral annulus were significantly larger in group B,and geometric angles of the mitral valve leaflets and mitral annulus was positive correlated with degree of mitral regurgitation. Degree of mitral regurgitation significantly reduced in group C, no significant difference was found at the geometric angles of the mitral valve leaflets and mitral valve annular compared with group A. Conclusions The degree of mitral regurgitation were highly correlated with geometric angles of the mitral valve leaflets and mitral valve annular in patients with left ventricular papillary muscle dysfunction caused by coronary heart dlsease.Repair of the mitral valve leaflets surgery can significantly reduce geometric angles of the mitral valve leaflets and mitral valve annular,and reduce the degree of mitral regurgitation significantly. Key words: Echocardiography, transesophageal; Mitral valve insufficiency; Papillary muscledysfunction ; Geometric angles

We try and describe here the general scheme of homogeneous fibre bundles and the harmonicity equations for their sections and how it applies to geometric structures arising from a reduction of the structure group. Among G-structures, we particularly pay attention to almost complex and almost contact structures and the relevant notions of harmonic sections and harmonic maps. We then review some of the more salient properties and results in these two instances. In the last section, we detail the proof of harmonicity for the class nearly cosymplectic.

The purpose of this thesis is the development of a model for the geometry of the connectivity of the primary visual cortex (V1), by means of functional analysis tools on metric measure spaces. The metric structure proposed to describe the internal connections of V1 implements a notion of correlation between neurons, based on their feature selectivity: this is expressed through a connectivity kernel that is directly induced by the local feature analysis performed by the cells. Such kernel carries a geometrical structure consistent with the well-known properties of long-range horizontal connections in V1, and it is compatible with the perceptual rules synthesized by the concept of association field. Moreover, its construction can be applied to banks of filters not necessarily obtained through a group representation, and possibly only numerically known. This model is then applied to insert biologically inspired connections in deep learning algorithms, to enhance their ability to perform pattern completion in image classification tasks. The main novelty in our approach lies in its ability to recover global geometric properties of the functional architecture of V1 without imposing any parameterization or invariance, but rather by exploiting the local information naturally encoded in the behavior of single V1 neurons in presence of a visual stimulus.

Computational simulations for complex geometries nowadays often deal with unstructured grids. That’s why scientific visualization must also be extended to these grid types. A visualization system is presented which works with any type of unstructured grids, i.e. arbitrary polygonal and polyhedral grids. Results from finite volume (cell-centered) and finite element methods can be visualized. Additionally time-dependent data can be processed and interpolation between time steps is possible. This data may be transfered directly from a simulation program and therefore on-line visualized. To integrate this task into a computational simulation an object-oriented interface is presented which allows an easy connection of simulation and visualization.

More than 25 years ago we developed a data visualization system called Vibe. During this same period we developed a system for collaborative authoring – CASCADE – that made heavy use of visualization. These were but a few of many efforts at that time to develop new methods for understanding data, stimulated by improved hardware - faster CPUs, more memory and high resolution graphical displays that made it possible to perform advanced visualization on ordinary PCs. In this paper we revisit some of these efforts and then discuss where visualization is today. We briefly examine big data and scientific visualization where many of the issues we explored 25 years ago are being revisited. Our focus however is on general visualization. What we find is that advanced visualization systems for data presentations have not come into general use. We explore some of the reasons this may be the case.

Integrated presentation of data with uncertainty is a worthy goal in scientific visualization. It allows researchers to make informed decisions based on imperfect data. It also allows users to visually compare and contrast different algorithms for performing the same task or different models for representing the same physical phenomenon. We present LISTEN-a data sonification system that has been incorporated into two visualization systems: a system for visualizing geometric uncertainty of surface interpolants; and a system for visualizing uncertainty in fluid flow. LISTEN is written in C++ for the SGI platform. It works with the SGI internal audio chip or a MIDI device or both. LISTEN is an object-oriented system that is modular, flexible, adaptable, portable, interactive and extensible. We demonstrate that sonification is very effective as an additional tool in visualizing geometric and fluid flow uncertainty.

In this position paper we discuss successes and limitations of current evaluation strategies for scientific visualizations and argue for embracing a mixed methods strategy of evaluation. The most novel contribution of the approach that we advocate is a new emphasis on employing design processes as practiced in related fields (e.g., graphic design, illustration, architecture) as a formalized mode of evaluation for data visualizations. To motivate this position we describe a series of recent evaluations of scientific visualization interfaces and computer graphics strategies conducted within our research group. Complementing these more traditional evaluations our visualization research group also regularly employs sketching, critique, and other design methods that have been formalized over years of practice in design fields. Our experience has convinced us that these activities are invaluable, often providing much more detailed evaluative feedback about our visualization systems than that obtained via more traditional user studies and the like. We believe that if design-based evaluation methodologies (e.g., ideation, sketching, critique) can be taught and embraced within the visualization community then these may become one of the most effective future strategies for both formative and summative evaluations.

This article describes the issue of geometric objects generalization in spatial databases with methods of mathematical morphology. The authors studied the impact of exemplary operations, i.e.: erosion, dilatation, opening, closing on the level of the data details and time efficiency of queries. It has been shown that the mathematical morphology methods can be successfully treated as a novel approach in spatial databases optimization.

Scientific visualization still presents a number of challenges. Effective visua lization straddles several problem domains - the data structures needed to support visualization of large data sets, rendering techniques for fast and interactive display of this data, and enough understanding of the data involv ed to construct visualizations that provide real insight into the problem. Data from Smoothed Particle Hydrody namics simulations is of particular interest, due to its time-dependent, point-based nature and its prevalence insimulation in astrophysics in areas such as star formation and evolution. This paper looks at some of the issue s associated with building a useful, usable visualization tool for SPH data from astrophysics, and describes a p rototype of such a system. This paper describes work in progress.