Scientific Visualization Techniques Research Articles

Empirical research on banks' risk disclosure: Systematic literature review, bibliometric analysis and future research agenda

The purpose of this paper is to outline the current state of empirical research on banks' risk reporting. In addition to the development of the research field over time, regulatory trends and drivers for academic research on risk reporting will be derived. The review follows a triangulated approach: In addition to a qualitative content analysis based on the SLR, a quantitative bibliometric analysis using the scientific visualization techniques bibliometrix and VOSviewer will serve as a robustness check. The sole focus of this SLR on banks reflects the regulatory specificity of the financial services industry and serves to derive recommendations for action for regulators, supervisors, and auditors. The article follows the tenor of macro- and micro-prudential banking regulation, which has raised market discipline to a new level through the implementation of regulatory disclosure standards in the context of the Basel III amendment, with a deliberate clustering of the research area according to risk types. By identifying research gaps and conceptualizing a research agenda, this paper continues to serve the academia to broaden the research field of risk disclosure, especially for banks.

Photon Field Networks for Dynamic Real-Time Volumetric Global Illumination.

Volume data is commonly found in many scientific disciplines, like medicine, physics, and biology. Experts rely on robust scientific visualization techniques to extract valuable insights from the data. Recent years have shown path tracing to be the preferred approach for volumetric rendering, given its high levels of realism. However, real-time volumetric path tracing often suffers from stochastic noise and long convergence times, limiting interactive exploration. In this paper, we present a novel method to enable real-time global illumination for volume data visualization. We develop Photon Field Networks-a phase-function-aware, multi-light neural representation of indirect volumetric global illumination. The fields are trained on multi-phase photon caches that we compute a priori. Training can be done within seconds, after which the fields can be used in various rendering tasks. To showcase their potential, we develop a custom neural path tracer, with which our photon fields achieve interactive framerates even on large datasets. We conduct in-depth evaluations of the method's performance, including visual quality, stochastic noise, inference and rendering speeds, and accuracy regarding illumination and phase function awareness. Results are compared to ray marching, path tracing and photon mapping. Our findings show that Photon Field Networks can faithfully represent indirect global illumination within the boundaries of the trained phase spectrum while exhibiting less stochastic noise and rendering at a significantly faster rate than traditional methods.

FastSpline: Automatic Generation of Interpolants for Lattice Samplings

Interpolation is a foundational concept in scientific computing and is at the heart of many scientific visualization techniques. There is usually a tradeoff between the approximation capabilities of an interpolation scheme and its evaluation efficiency. For many applications, it is important for a user to navigate their data in real time. In practice, evaluation efficiency outweighs any incremental improvements in reconstruction fidelity. We first analyze, from a general standpoint, the use of compact piece-wise polynomial basis functions to efficiently interpolate data that is sampled on a lattice. We then detail our automatic code-generation framework on both CPU and GPU architectures. Specifically, we propose a general framework that can produce a fast evaluation scheme by analyzing the algebro-geometric structure of the convolution sum for a given lattice and basis function combination. We demonstrate the utility and generality of our framework by providing fast implementations of various box splines on the Body Centered and Face Centered Cubic lattices, as well as some non-separable box splines on the Cartesian lattice. We also provide fast implementations for certain Voronoi-splines that have not yet appeared in the literature. Finally, we demonstrate that this framework may also be used for non-Cartesian lattices in 4D.

Irrationally Reproducing Reproduction

This research paper traces the history of how the scientific measurement and visualization of sexed and racialized bodies enable them to be regulated in the context of abortion. In Part I, the paper examines how scientific visualization techniques developed in the 19th century prompted the Roman Catholic Church to declare any abortion following conception a sin, despite abortion being previously accepted if it occurred within two to three months of fertilization. This idea is then connected to how anti-abortion protestors use visual rhetoric to flatten narratives about why people seek abortions. They use singular images of aborted fetuses as visual substitutes for complex personal circumstances, and (like the Catholic Church) use these images to present the fetus as a fully formed human being. In Part II, the paper characterizes such visualization techniques as a type of rationalization, the process of turning something (like the body) into units of information, which enables it to be controlled. Part III studies how period-tracking apps rationalize the menstruating body and are used as evidence to penalize individuals for having abortions; however, the data obtained from these apps may be inaccurate because the human body is a complex biological organism that is inherently unpredictable (meaning that it can never be fully rationalized). Part IV examines how rationalization methods are not neutral and draws upon case studies of racialized individuals convicted of having abortions to argue that racialized bodies are perceived as criminal even before information is collected about them.

A Study of Industrial Convergence in the Context of Digital Economy Based on Scientific Computing Visualization

With the rapid development of computer hardware and software and the rapid spread of network, the amount of data in scientific computing has exploded. Big data visualization has become one of the important research contents in scientific computing. Against the background of rapid development of information technology and digital technology, the scale of digital economy is increasing day by day, and China’s digital economy has ushered in unprecedented progress, and it has become an important force in leading economic development. The development of digital economy promotes industrial upgrading and transformation and facilitates industrial integration, and many traditional industries have given rise to a series of new industries. Scientific computational visualization is a new research discipline with a wide range of applications, including energy surveying, natural sciences, finance, and business. However, as a brand-new discipline, further research is needed in areas such as the application of scientific computational visualization techniques based on the digital economy environment. In this study, we propose a scientific computing visualization approach based on a big data framework for industry convergence analysis in the context of digital economy, which consists of a cloud computing platform for industry convergence in the context of digital economy by integrating neural networks in the platform, and scientific computing visualization by built-in GPU hardware. Traditional research methods for scientific computing visualization are discussed, and algorithms and techniques are classified in terms of the types of data domains studied. Finally, the further development and research directions of scientific computing visualization in the big data environment are given in conjunction with the main theoretical and application results achieved by our group in scientific computing for the field of big data visualization. Scientific computing visualization will not only promote the development and application of cutting-edge information technology, like cloud computing, big data, cyber security, artificial intelligence, computational science, system theory, and so on, but also bring a unique and disruptive development and change to the industrial integration in the context of digital economy.

Application of Mathematical Models in Economic Variable Input and Output Models under the Scientific Visualization.

At present, with the development of society and economy, some new problems have emerged continuously. Among them, the more serious problem is that enterprises pay too much attention to economic benefits, which leads to problems in the development of many enterprises. Therefore, the problem caused by too much emphasis on economic benefits is one of the major economic problems. After this problem, our country's economy began to focus on economic input and output in the subsequent development process. And, related personnel have also studied the economic input-output technology and model, which is an economic quantitative analysis method that has been widely used in various aspects of the economic field since its emergence. This paper firstly elaborates the theoretical knowledge involved, such as economic data, economic variables, and visualization techniques. Secondly it analyzes the application of scientific visualization techniques in the processing of economic variable data, which includes the techniques of preprocessing, mapping, drawing, and displaying the data. Finally, this paper investigates the application of mathematical models in economic variables input and output and the application of mathematical models in economic research, which can help us to better understand and use the knowledge of economics, thus providing strong support for solving practical problems. Also, this helps people to understand and grasp more about the macroarea, microaspect, and even the country as a whole.

Real-Time Denoising of Volumetric Path Tracing for Direct Volume Rendering.

Direct volume rendering (DVR) using volumetric path tracing (VPT) is a scientific visualization technique that simulates light transport with objects' matter using physically-based lighting models. Monte Carlo (MC) path tracing is often used with surface models, yet its application for volumetric models is difficult due to the complexity of integrating MC light-paths in volumetric media with none or smooth material boundaries. Moreover, auxiliary geometry-buffers (G-buffers) produced for volumes are typically very noisy, failing to guide image denoisers relying on that information to preserve image details. This makes existing real-time denoisers, which take noise-free G-buffers as their input, less effective when denoising VPT images. We propose the necessary modifications to an image-based denoiser previously used when rendering surface models, and demonstrate effective denoising of VPT images. In particular, our denoising exploits temporal coherence between frames, without relying on noise-free G-buffers, which has been a common assumption of existing denoisers for surface-models. Our technique preserves high-frequency details through a weighted recursive least squares that handles heterogeneous noise for volumetric models. We show for various real data sets that our method improves the visual fidelity and temporal stability of VPT during classic DVR operations such as camera movements, modifications of the light sources, and editions to the volume transfer function.

Multiresolution visualization of massive black oil reservoir models

Recent advances in parallel architectures for numerical simulation of natural black oil reservoirs have allowed the use of very discretized domains. As a consequence, these simulations produce an unprecedented volume of data, which must be visualized in 3D environments for careful analysis and inspection. Conventional scientific visualization techniques are not viable on such large models, creating a demand for the development of scalable visualization solutions. In this paper, we propose a hierarchical multiresolution technique to render massively large black oil reservoir meshes. A new simplification algorithm specialized for such models is presented, which accurately represents boundary surfaces, while keeping the hexahedral mesh with good quality. Original model properties, wireframe and surface normals are mapped onto the simplified meshes through texture mapping. This allows the system to reuse the structure for different simulations that use the same geometry model. The viewer application is designed to guarantee a minimum refresh rate, allocating geometric detail where it is most needed, given the available hardware. Experimental results, considering up to 1.2 billion cell models, demonstrate the effectiveness of the proposed solution.

THE ANALYSIS OF INTERNET MARKETING RESEARCH DIRECTION

The sustainable development of internet marketing (later identified as IM) faces the dynamic environment and its alterations, which occurs in both - business terms and conditions, and in the use of electronic tools and applicable concepts. The growing importance of the IM is being indicated by the development of electronic markets, increasing number of new generation consumers, deepening interest of scientists from different scientific fields, as well as widening the related knowledge base. Despite the continuously increasing amount of scientific literature about marketing on the internet, this area of research is still in its initial stage. The aim of this article is to analyse fields of ongoing IM researches and to identify areas for deeper examination. The following methods were used: the comparative analysis and summary of the scientific literature, information comparing, grouping and graphic information visualization techniques. Keywords: internet marketing, internet marketing environment, communication, internet marketing research areas. DOI: 10.15276/mdt.2.1.2018.1 Powers T, Advincula D, Austin MS, Graiko S. 2013. Digital and Social Media in the Purchase-Decision Process: A Special Report from the Advertising Research Foundation. J. Advert. Res. 52:479. Sharma A, Sheth JN. 2004. Web-based marketing. J. Bus. Res. 57:696–702. Taylor DG, Strutton D. 2010. Has e-marketing come of age? Modeling historical influences on post-adoption era Internet consumer behaviors. J. Bus. Res. 63:950–956. Tiago MT, Tiago F. 2012. Revisiting the Impact of Integrated Internet Marketing on Firms’ Online Performance: European Evidences. Procedia Technol. 5:418–426. Crocker D. 2006. Email history. The living Internet. [cited 14 October 2015]. Available from http://debian.fmi.uni-sofia.bg/~group1_2008/english/email_history.doc. Kiang MY, Raghu T., Shang KH-M. 2000. Marketing on the Internet — who can benefit from an online marketing approach? Decis. Support Syst. 27:383–393. Kiang MY, Raghu TS, Shang KH-M. 2000. Marketing on the Internet — who can benefit from an online marketing approach? Decis. Support Syst. 27:383–393. Ngai EWT. 2003. Internet marketing research (1987-2000): a literature review and classification. Eur. J. Mark. 37:24–49. Schibrowsky JA, Peltier JW, Nill A. 2007. The state of internet marketing research: A review of the literature and future research directions. Eur. J. Mark. 41:722–733. Davidavicienė V, Sabaitytė J. 2014. Tyrimų internetinės rinkodaros srityje analizė. Verslas Teor. ir Prakt. [cited 8 December 2015]. Available from http://www.ceeol.com/aspx/getdocument. aspx?logid=5&id=e7cf2f13e070430ca0810cab1a6e97a5. Kwan ISY, Fong J, Wong HK. 2005. An e-customer behavior model with online analytical mining for internet marketing planning. Decis. Support Syst. 41:189–204.

Brain explorer for connectomic analysis

Visualization plays a vital role in the analysis of multimodal neuroimaging data. A major challenge in neuroimaging visualization is how to integrate structural, functional, and connectivity data to form a comprehensive visual context for data exploration, quality control, and hypothesis discovery. We develop a new integrated visualization solution for brain imaging data by combining scientific and information visualization techniques within the context of the same anatomical structure. In this paper, new surface texture techniques are developed to map non-spatial attributes onto both 3D brain surfaces and a planar volume map which is generated by the proposed volume rendering technique, spherical volume rendering. Two types of non-spatial information are represented: (1) time series data from resting-state functional MRI measuring brain activation; (2) network properties derived from structural connectivity data for different groups of subjects, which may help guide the detection of differentiation features. Through visual exploration, this integrated solution can help identify brain regions with highly correlated functional activations as well as their activation patterns. Visual detection of differentiation features can also potentially discover image-based phenotypic biomarkers for brain diseases.

Integrated Visualization of Human Brain Connectome Data.

Visualization plays a vital role in the analysis of multi-modal neuroimaging data. A major challenge in neuroimaging visualization is how to integrate structural, functional and connectivity data to form a comprehensive visual context for data exploration, quality control, and hypothesis discovery. We develop a new integrated visualization solution for brain imaging data by combining scientific and information visualization techniques within the context of the same anatomic structure. New surface texture techniques are developed to map non-spatial attributes onto the brain surfaces from MRI scans. Two types of non-spatial information are represented: (1) time-series data from resting-state functional MRI measuring brain activation; (2) network properties derived from structural connectivity data for different groups of subjects, which may help guide the detection of differentiation features. Through visual exploration, this integrated solution can help identify brain regions with highly correlated functional activations as well as their activation patterns. Visual detection of differentiation features can also potentially discover image based phenotypic biomarkers for brain diseases.

A Novel Visual Data Mining Module for the Geographical Information System gvSIG

The exploration of large GIS models containing spatio-temporal information is a challenge. In this paper we propose the integration of scientific visualization (ScVis) techniques into geographic information systems (GIS) as an alternative for the visual analysis of data. Providing GIS with such tools improves the analysis and understanding of datasets with very low spatial density and allows to find correlations between variables in time and space. In this regard, we present a new visual data mining tool for the GIS gvSIG. This tool has been implemented as a gvSIG module and contains several ScVis techniques for multiparameter data with a wide range of possibilities to explore interactively the data. The developed module is a powerful visual data mining and data visualization tool to obtain knowledge from multiple datasets in time and space. A real case study with meteorological data from Villa Clara province (Cuba) is presented, where the implemented visualization techniques were used to analyze the available datasets. Although it is tested with meteorological data, the developed module is of general application in the sense that it can be used in multiple application fields related with Earth Sciences.

Visualization of Particle Trajectories in Time-Varying Electromagnetic Fields by CAVE-Type Virtual Reality System

The particle kinetic effects play an important role in breaking the frozen-in condition and exciting collisionless magnetic reconnection in high temperature plasmas. Because this effect is originating from a complex thermal motion near reconnection point, it is very important to examine particle trajectories using scientific visualization technique, especially in the presence of plasma instability. We developed interactive visualization environment for the particle trajectories in time-varying electromagnetic fields in the CAVE-type virtual reality system based on VFIVE, which is interactive visualization software for the CAVE system. From the analysis of ion trajectories using the particle simulation data, it was found that time-varying electromagnetic fields around the reconnection region accelerate ions toward the downstream region.

CAD and CAE Integration Through Scientific Visualization Techniques for Illumination Design

Engineers tend to use different software to perform tasks such as geometry modeling, database management, numerical analysis, and visualization. This may cause decrease of productivity and loss of information during the conversion process between different data file formats. This paper presents a computer aided design (CAD) and computer aided engineering (CAE) system integration using scientific visualization tools and techniques. It deals with the development of a 3D CAD add-in for lighting analysis which uses the CAD model as 3D interface for creating a lighting scheme, processing, and visualizing 2D or 3D illuminance fields. Visualization features as color and contour mapping were developed using the visualization toolkit (VTK) toolkit. The application integrates all functionalities of the 3D CAD with tools for light sources database management, pre-processing, processing, and post-processing of illuminance fields in a single environment. This approach increases productivity and eliminates the need for different software.

Determination of Critical Microstructural Features in an Austenitic Stainless Steel Using Image-Based Finite Element Modeling

Two-dimensional (2-D) and three-dimensional (3-D) image-based finite element (FE) modeling and scientific visualization techniques were employed to determine the critical microstructural features that control mechanical behavior in a commercial austenitic stainless steel, AL-6XN. Two-dimensional FE meshes were generated using microstructural images obtained from electron backscatter diffraction (EBSD), and three-dimensional meshes were generated from microstructural reconstructions created using serial-sectioning techniques and EBSD. Image-based FE simulations were run using anisotropic elasticity. The 2-D simulations revealed that higher local elastic stresses are produced near grain boundaries than at grain interiors for various loading conditions. Under normal uniaxial loading conditions, higher stresses were observed at faceted grain boundaries, particularly those with a Σ = 3 coincident site lattice misorientation. Under simple shear loading conditions, however, the highest stresses were observed at general high-angle grain boundaries. In the 3-D simulations, similar relationships held, with the highest elastic stresses observed at the junction between two Σ3 boundaries under normal uniaxial loading and slightly lower elastic stresses at these junctions under simple shear loading. In the 3-D models, high elastic stresses were associated only with grain boundaries and triple junctions and showed little to no correlation with grain size or morphology.

Scientific Visualization: A Necessary Chore

From the perspective of a computational scientist who models astrophysical fluid flows, the author describes the successes and frustrations he's had with the development and use of scientific visualization techniques. A biased view toward the future is also presented.

Simulation and visualization of topological defects in nematic liquid crystals

We present a method of visualizing topological defects arising in numerical simulations of liquid crystals. The method is based on scientific visualization techniques developed to visualize second-rank tensor fields, yielding information not only on the local structure of the field but also on the continuity of these structures. We show how these techniques can be used to first locate topological defects in fluid simulations of nematic liquid crystals where the locations are not known a priori and then study the properties of these defects including the core structure. We apply these techniques to simulation data obtained by previous authors who studied a rapid quench and subsequent equilibration of a Gay-Berne nematic. The quench produces a large number of disclination loops which we locate and track with the visualization methods. We show that the cores of the disclination lines have a biaxial region and the loops themselves are of a hybrid wedge-twist variety.

Image Fusion Based on Topographic Mappings Using the Hyperbolic Space

The analysis of multivariate image data is a field of research that is becoming increasingly important in a broad range of applications from remote sensing to medical imaging. While traditional scientific visualization techniques are often not suitable for the analysis of this kind of data, methods of image fusion have evolved as a promising approach for synergistic data integration. In this paper, a new approach for the analysis of multivariate image data by means of image fusion is presented, which employs topographic mapping techniques based on non-Euclidean geometry. The hyperbolic self-organizing map (HSOM) facilitates the exploration of high-dimensional data and provides an interface in the tradition of distortion-oriented presentation techniques. For the analysis of hidden patterns and spatial relationships, the HSOM gives rise to an intuitive and efficient framework for the dynamic visualization of multivariate image data by means of color. In an application, the hyperbolic data explorer (HyDE) is employed for the visualization of image data from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Using 12 image sequences from breast cancer research, the method is introduced by different visual representations of the data and is also quantitatively analyzed. The HSOM is compared to different standard classifiers and evaluated with respect to topology preservation.

Development of an environmental virtual field laboratory

Laboratory exercises, field observations and field trips are a fundamental part of many earth science and environmental science courses. Field observations and field trips can be constrained because of distance, time, expense, scale, safety, or complexity of real-world environments. Our objectives were to develop an environmental virtual field laboratory to study environmental properties and processes that stimulate the higher-order cognitive skills of students. We considered the following criteria for our virtual field laboratory: (i) global access, i.e., web-based implementation; (ii) simulation of a variety of learning mechanisms; (iii) interactivity to engage students; (iv) compartmentalization and hierarchical organizational structure; (v) abstraction of 2D and 3D geographic objects (e.g. soils, terrain) and dynamic ecosystem processes (e.g. water flow) using geostatistics and scientific visualization techniques. Cognitive science was considered during the design of our computer-aided instructional tools to enhance the effectiveness for learning. Our virtual field laboratory mimicked the students' learning processes that operate during real field trips and/or field observations; and provided students with a simulation environment to study environmental processes in space and time that cannot be provided on a real field trip. We implemented the following learning mechanisms: (i) exploration-based learning; (ii) analogy-based learning; (iii) science inquiry learning; (iv) abstraction-based learning. To engage students in our environmental virtual field laboratory, we implemented multiple interactivity functions including the exploration of 3D models and adaptive selective simulations. We used Virtual Reality Modeling Language, Java, Java Script, and External Authoring Interface to develop the environmental virtual field laboratory for a 42-ha flatwood site in Florida for which extensive datasets existed. Our digital learning environment offers potential to enhance existing on-campus courses and/or distance education courses.

이용자 인터페이스 설계 원칙에 의한 정보시각화 시스템 평가 및 문제점 분석

정보량이 급증하고 기존의 정보조직체계에 비해 덜 체계화된 정보를 제공하는 인터넷의 확산 등으로 인해 정보시각화에 대한 관심이 점점 증가하고 있다. 정보 시각화는 이용자가 원하는 정보에 쉽고 적은 노력으로 접근할 수 있도록 데이터를 재정리하고 요약하여 보여주는 기법이다. 현재까지 개발되어 온 많은 정보시각화 기법들은 과학적인 연산절차에 근거하여 데이터를 표현하는 방법을 사용하여 왔는데, 이러한 과학적 데이터 처리 과정에 의존하는 시각화방법은 일반 이용자들이 이해하기에는 어려움과 사용의 불편함이 따른다. 더 중요하고 심각한점은, 이러한 정보시각화 기법을 사용하는 많은 시스템의 모형들이 실제 이용자가 경험하는 상황을 반영하는 경우가 매우 드물다는 현실이다. 예를 들어, 이용자는 데이터를 처리하거나 정보를 제시함에 있어 어안적 방법(fisheye view)을 사용하거나 주제정경 (the mescape)을 사용하지 않는다. 이는 현재의 많은 정보 시각화 시스템들이 이용자 관점에서 시스템을 설계하는 행동유도성（affordance)을 반영하지 않고 있음을 지적한다. 이 연구는 이용자의 요구사항이 반영되지 않고, 이용자에게 부담을 지우는 시각화 시스템의 문제점을 분석하였다. 이를 위하여, 네 가지의 대표적인 정보시각화 시스템을 분석, 평가하였는데 이 때 평가의 기준으로 Norman의 이용자 인터페이스 설계 원칙 및 Nielson의 휴리스틱 평가 방법을 이용하였다. 문제점 분석 결과를 통하여, 이용자의 요구를 반영하지 못한 시스템 설계의 측면들을 확인할 수 있었다. 특히, 이용자와 시스템간의 부합정도 및 시스템의 상태를 이용자가 알 수 있도록 보여주는 가시성 등은 네 가지 시스템의 평가에서 모두 문제점으로 지적되었다. 이 연구의 결과는 정보시각화 및 표현에 있어서 이용자의 요구를 이해하고 이용성을 고려한 설계의 필요성을 강조하고 있다. There have been increased interests in information visualization. Information visualization has been considered as a way to summarize textual data so that the users can access large amount of data more efficiently and effectively. However, many information visualization techniques stem from scientific visualization techniques, which might be difficult for the regular users to understand. More importantly, the system models used by most of the information visualization techniques do not have real world counterpart. For example, most of the users do not represent or process the textual data in terms of fisheye view or a topological map. This means that there is no affordance on the current information visualization systems from the users point of view. In this paper, we analyzed this problem by using the user interface design principles to point out what lacks in the current information visualization systems. More specifically, we have applied Nielson's Heuristic Evaluation technique to review four representative information visualization techniques. The analysis results confirmed our original hypothesis on why the current information visualization systems are not part of the mainstream information systems. Finally, we suggested to invest more efforts in improving the currently prevalent and familiar bullet list type textual information presentation method based on the usability studies and the intelligent content analysis.