Scientific Visualization Research Articles

„Mixed Reality“ – erste Erfahrungen aus der Leberchirurgie

BackgroundDevelopments in imaging technology enable better diagnostics and, thus, also safer visceral interventions. One of the most recent developments is the use of mixed reality in the operating room, a “mixture” of reality with three-dimensional (3D) reconstructed preoperative images. Thus, we present our first experiences with the application of mixed reality in the field of liver surgery.Materials and methodsEight patients (age 62–82 years) with primary liver malignancy (n = 4) or liver metastases (n = 4) were studied and documented in this work. The time required to fully prepare the preoperative reconstructions was analyzed and the benefits of the new technology were graded by the members of the treatment team for each case. We use an open-source software for image analysis and scientific visualization preoperatively.ResultsThe time required to prepare for the operation is considerable and relevant for the everyday clinical practice (150–360 min). We were able to gain more information about tumor location and the relationship to other important intra-abdominal structures preoperatively and intraoperatively through the use of the technology. We have not yet been able to demonstrate a benefit in the area of risk minimization for the patient, faster operation times or faster recovery in this study.ConclusionMixed reality technology offers an enormous range of possible applications. In particular, it has great potential for visceral surgery, patient education, but also medical training. Further investigations are necessary to more precisely assess the advantages and disadvantages in larger case series.

A method for modeling volumetric clouds and subsurface scattering of functionally specified objects

Accurate modeling of light transfer in media is important in many fields, such as scientific visualization, medical imaging, synthesis of realistic images, and so on. Complex volumetric structures and translucent materials are used. Light scattering in media is responsible for the appearance of many materials. However, accurate and efficient modeling of lighting effects is a difficult problem. This requires solving not only the visualization equation, but also its volumetric solution, the radiation transfer equation. A method for modeling subsurface scattering of functionally specified objects is presented. The method allows you to simulate the transfer of light in chromatic media. To do this, a modified free-range distribution is used. This allows you to minimize the deviations of the bandwidth of the path. As a result, the variance of the estimate is reduced. The collision coefficients depending on the wavelength are effectively processed. As a result, it is possible to simulate volumetric clouds and subsurface light scattering in translucent materials such as marble, wax, leather, etc. The control coefficients and free run sampling are based on the minimum and maximum values in the media found by random sampling over a short preliminary pass. Reducing the rendering time is achieved by using a different distribution of paths.

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

[This retracts the article DOI: 10.1155/2022/6269358.].

A Brief Note on Building Augmented Reality Models for Scientific Visualization.

Augmented reality (AR) has revolutionized the video game industry by providing interactive, three-dimensional visualization. Interestingly, AR technology has only been sparsely used in scientific visualization. This is, at least in part, due to the significant technical challenges previously associated with creating and accessing such models. To ease access to AR for the scientific community, we introduce a novel visualization pipeline with which they can create and render AR models. We demonstrate our pipeline by means of finite element results, but note that our pipeline is generally applicable to data that may be represented through meshed surfaces. Specifically, we use two open-source software packages, ParaView and Blender. The models are then rendered through the <model-viewer> platform, which we access through Android and iOS smartphones. To demonstrate our pipeline, we build AR models from static and time-series results of finite element simulations discretized with continuum, shell, and beam elements. Moreover, we openly provide python scripts to automate this process. Thus, others may use our framework to create and render AR models for their own research and teaching activities.

Scientific visualization for advanced deep-sea exploration equipment and underwater automatic manipulation

Scientific visualization for advanced deep-sea exploration equipment and underwater automatic manipulation

Intelligent visualization and visual analytics

Intelligent visualization and visual analytics

Interactive Visualization of Large Turbulent Flow as a Cloud Service

Many scientific communities today have community datasets that are continuously created, curated, and maintained for community use. Such datasets are often hosted and shared through cloud-based data repositories. In this work, we propose a lightweight and affordable visualization cloud service that can be deployed as a companion service of a community dataset. Our target visualization use case is parallel flow visualization, which is crucial for understanding planet-scale phenomena such as the Earth’s atmosphere and ocean. As a core research topic of scientific visualization, parallel flow visualization typically uses HPC computing platforms. It is complex to implement with scalability, deploy with efficiency, and is often considered an advanced form of scientific visualization. Because of the heterogeneous nature of cloud platforms, in this work, we use a swarm-based parallel design to replace traditional HPC designs that assume homogeneity and rely upon conventional methods such as Message Passing Interface (MPI). This design enables interactive visualization of large flow fields in a way that is lightweight, efficient and easily deployable as a cloud service. We demonstrate our proposed system using NOAA’s NCEP ensemble data, which captures turbulent planet-scale atmospheric flows in observed forms, as well as in forecast forms for varying time scales. We evaluate the performance and efficacies of our system on Amazon Web Services (AWS) for three use cases, where remote users can use their laptops to (i) interactively explore global atmospheric flow patterns in general, (ii) to specifically compare how a forecast is different from the observation, and (iii) to explore flow patterns in a typical information visualization dashboard.

Exploring the Fusion Potentials of Data Visualization and Data Analytics in the Process of Mining Digitalization

Mining digitalisation have been receiving significant attention due to the utilisation of advanced technologies, such as IoT, automation, and sensing. However, maximising the potential value of collected data in the mining industry remains a challenge. Therefore, this paper aims to review timely concern topics to facilitate the fusion implementation in mining engineering. Specifically, this review covers recent popular topics, such as, data visualisation, data management, data analytics, data fusion, visual analytics, and mining digital twin construction. In this paper, we aim to draw a comprehensive picture about the fusion of data visualisation and analytics in the big data context, by examining the recent academic research related to these topics. Therefore, this paper reviews the visualisation domain by conventional classification, including scientific visualisation, information visualisation, and visual analytics, associated with the analysis of current digital twin development. Next, according to the challenges and issues related to visualisation development, this paper reviews the data management and data analytics domains as well. Incorporating with the fusion concept, machine learning-oriented fusion applications and potential scenarios in the mining industry have been discussed. In addition, based on the observation across various domains, this paper presents challenges and future potentials of data fusion in mining.

Computational Analysis of a Horror Film Trailer Soundtrack

Computational film analysis combines statistics, data science, information visualization, and computer science with the analytical approaches and domain knowledge of the study of film to frame and answer questions about form and style in the cinema. In this article I illustrate the visualisation and analysis of the soundtrack of the trailer for the Korean horror film Into the Mirror (2003). Using the spectrogram and normalized aggregated power envelope to show how the sound design of the trailer evolves over time and functions at different scales. I address a range of practical considerations relevant to the methods demonstrated here relating to the use of mono versus stereo audio files, the use of different sampling rates, and audio normalization. A supporting website with the code for the statistical programming language R used in this analysis is available at https://rpubs.com/nr62_rp33/CFA-into-the-mirror.

An Evaluation of a Ray-Tracing Based Model for Photorealistic Image Rendering of Confined Plasma in Stellarators

As the world moves away from traditional energy sources based on fossil fuels, several alternatives have been explored. One promising clean energy source is nuclear fusion. The fusion of hydrogen isotopes may provide generous consumable energy gains. However, nuclear fusion reactors are not ready to become a productive mechanism yet. To get a better understanding of plasma, numerical simulations and scientific visualizations over high-performance computing systems are mandatory. The results from the simulations and a proper display of the data are key to design and tune up nuclear fusion reactors. It is also thanks to the international collaboration effort such as the advisory contribution and tools of researchers from the Argonne National Laboratory in the United States in conjunction with the National Center for High Technology of Costa Rica that this work was successfully carried out. In a previous work, we explored a new approach of the scientific visualization of plasma confinement, presenting one model to generate realistic plasma representations. This work presents an evaluation of the expected quality of the images rendered with the created model. We propose a concept called visual plausibility as an evaluation attribute to rate each rendered image by physicists that already know about the plasma appearance.

Suspended Particulate Matter Analysis of Pre and During Covid Lockdown Using Google Earth Engine Cloud Computing: A Case Study of Ukai Reservoir.

Presence of suspended particulate matter (SPM) in a waterbody or a river can be caused by multiple parameters such as other pollutants by the discharge of poorly maintained sewage, siltation, sedimentation, flood and even bacteria. In this study, remote sensing techniques were used to understand the effects of pandemic-induced lockdown on the SPM concentration in the lower Tapi reservoir or Ukai reservoir. The estimation was done using Landsat-8 OLI (Operational Land Imager) having radiometric resolution (12-bit) and a spatial resolution of 30m. The Google Earth Engine (GEE) cloud computing platform was used in this study to generate the products. The GEE is a semi-automated workflow system using a robust approach designed for scientific analysis and visualization of geospatial datasets. An algorithm was deployed, and a time-series (2013-2020) analysis was done for the study area. It was found that the average mean value of SPM in Tapi River during 2020 is lowest than the last seven years at the same time.

RENDERING OF INHOMOGENEOUS VOLUMES USING PERTURBATION FUNCTIONS

Modeling of light transmission in heterogeneous volumes is of great importance in many fields, such as medical imaging, scientific visualization and synthesis of realistic images. Visual effects use complex three-dimensional structures such as smoke and clouds. However, modeling light transmission requires many calculations. For example, Monte-Carlo methods, which are based on path tracing, require the construction of a huge number of light paths. At the same time, each light path consists of thousands of scattering parts. A method for rendering inhomogeneous volumes using perturbation functions is presented. An approach is proposed for sampling light transmission paths in inhomogeneous media. The approach is based on the radiation transfer equation, using the integral formulation of the direct scattering algorithm. Bounding shells based on perturbation functions are used. To speed up calculations an inhomogeneous medium is divided into homogeneous and residual parts. The residual part is the difference between an inhomogeneous and homogeneous medium. For a homogeneous part light transmission paths are constructed in an analytical form. Next, the path-tracing algorithm is used. Samples in the light transmission path in the homogeneous and residual parts are made separately. This minimizes the costly calculations of direct scattering coefficients that change when traversing space. The method has advantages in comparison with approaches using an octal tree, with a large volume resolution the efficiency of calculations increases. The results of the work are integrated into the path tracer. Objects based on perturbation functions as an acceleration structure are used. The empty space is determined and approximate local extremes of the base volumes are stored. Objects based on perturbation functions adapt to volume uniformity. Voluminous data sets based on voxels are stored. Performance is compared using the number of queries, visualization time, root mean square error and metrics, that is, the search in units of variance.

Combined Web-Based Visualisation of 3D Point Clouds and Acoustic Descriptors: An Interdisciplinary Challenge

This paper presents an online application—called 3D integrator—enabling visual cross-examinations of architectural and acoustic data on web browsers and explains the rationale behind its development. The tool consists of a series of overlays developed over the Potree 3D point cloud renderer. It is used to display visually, in an interactive environment, the 3D point clouds resulting from a survey protocol tailored to the specific needs of the corpus under scrutiny—15 small-scale edifices often referred to as “minor heritage assets”—and to the research’s overall ambition, reasoning on architectural and acoustic features at an interdisciplinary level. One of the tool’s distinctive features is to project abstract information (acoustic descriptors) in a “close to real” 3D space (point clouds), hence merging scientific visualisation and information visualisation practices. The paper first shortly sums up the particularities of the survey protocol and discusses the implementation of the analytical add-ons that have been introduced (visual trace of the survey protocol itself, volume calculation, and exploratory 3D representation of acoustic descriptors). It then focuses on use cases that illustrate what the approach helps to observe concerning the interiors of edifices when capturing and co-examining dimensional and acoustic features.

Show and tell: approaches for effective figures

Show and tell: approaches for effective figures

Participatory Design of Sonification Development for Learning about Molecular Structures in Virtual Reality

Background: Chemistry and biology students often have difficulty understanding molecular structures. Sonification (the rendition of data into non-speech sounds that convey information) can be used to support molecular understanding by complementing scientific visualization. A proper sonification design is important for its effective educational use. This paper describes a participatory design (PD) approach to designing and developing the sonification of a molecular structure model to be used in an educational setting. Methods: Biology, music, and computer science students and specialists designed a sonification of a model of an insulin molecule, following Spinuzzi’s PD methodology and involving evolutionary prototyping. The sonification was developed using open-source software tools used in digital music composition. Results and Conclusions: We tested our sonification played on a virtual reality headset with 15 computer science students. Questionnaire and observational results showed that multidisciplinary PD was useful and effective for developing an educational scientific sonification. PD allowed for speeding up and improving our sonification design and development. Making a usable (effective, efficient, and pleasant to use) sonification of molecular information requires the multidisciplinary participation of people with music, computer science, and molecular biology backgrounds.

Simulation and Application of MATLAB in Young’s Double-Slit Experiments

Based on the scientific visualization function of MATLAB, the computer simulation of optical experimental phenomena has obvious effect in the application of experimental teaching, which improves the measurement accuracy of the experiment, expands the measurement range and intuitively analyzes the influence of the changes of various parameters on the experimental results. In this paper, based on the theory of wave optics, the simulation of Young’s double slit interference is realized by using Matlab’s powerful matrix operation function and graphics drawing function. The simulation image is in good agreement with the experimental results.

Knowledge Mapping Analysis of the Study of Rural Landscape Ecosystem Services

Understanding the research lineage of rural landscape ecosystem services (RLESs) is of importance for improving rural landscapes and developing sustainable ecosystem services. However, there is currently no literature analysis on the scientific quantification and visualization of RLESs. In this study, 4524 articles related to RLESs from 1990 to 2021 were analyzed using the bibliometric method and ISI Web of Science database. The results show that RLES research hotspots have gradually shifted from the early keywords of “vegetation”, “land use change”, “agriculture”, “rural gradients” and “models” to the emerging “cultural ecosystem services”, “rural tourism”, “landscape preferences” and “policy guidance”. Scholars from developed and developing countries place different emphases on research hotspots in terms of research content, scale and methodology due to differences in their research backgrounds and other aspects. In addition, five categories of research fronts were obtained through literature co-citation analysis. Through burst word detection analysis, combined with basic research and research hotspots and frontier analysis, we concluded that future RLES research will focus on four areas: (1) the relationship and collaboration between and management of biodiversity and ecosystem services; (2) the landscape value of RLESs; (3) land-use changes and ecosystem service values; and (4) research methods for innovative RLESs. Our findings may contribute to better in-depth RLES research by providing a theoretical reference and practical help for future related research.

Visual Anatomy of an Article – Lessons Learned and Taught in Five Figures

To grow is to teach. In that spirit this article aims to teach best practice for visualizations and at the same time to highlight some of the harvest we could reap in our lab. Following figures recently published in one of our manuscripts, we demonstrate how creativity in figure making goes hand in hand with storytelling, a deepened understanding of the scientific work and an increase in lateral thinking inside the research avenue. We hope it will help to promote scientific visualizations as a useful, even if sometimes harsh, mirror to give new angles to the laboratory work.

Interactive Scientific Visualization of Fluid Flow Simulation Data Using AR Technology-Open-Source Library OpenVisFlow

Computational fluid dynamics (CFD) are being used more and more in the industry to understand and optimize processes such as fluid flows. At the same time, tools such as augmented reality (AR) are becoming increasingly important with the realization of Industry 5.0 to make data and processes more tangible. Placing the two together paves the way for a new method of active learning and also for an interesting and engaging way of presenting industry processes. It also enables students to reinforce their understanding of the fundamental concepts of fluid dynamics in an interactive way. However, this is not really being utilized yet. For this reason, in this paper, we aim to combine these two powerful tools. Furthermore, we present the framework of a modular open-source library for scientific visualization of fluid flow “OpenVisFlow” which simplifies the creation of such applications and enables seamless visualization without other software by allowing users to integrate the visualization step into the simulation code. Using this framework and the open-source extension AR-Core, we show how a new markerless visualization tool can be implemented.

A QGIS-Based Road Network Analysis for Sustainable Road Network Infrastructure: An Application to the Cachar District in Assam, India

Efficient transportation and road network infrastructure plays the most significant role in the development of any region. However, the effectiveness of a road network is often affected by problems like road condition, traffic congestion, road blockage, road accidents etc. Digitization of the road network and its analysis can therefore be an effective tool towards resolving these issues. The free and open-source software Quantum Geographic Information System (QGIS) is well suited for such an analysis. QGIS can be used for construction of suitable road network maps of certain areas which provide sufficient information for such analysis. Cachar district of Assam, particularly Silchar circle, suffers frequently from traffic problems for being a network hub for other neighbouring revenue circles and some neighbouring north-eastern states. The scientific visualization and analysis of the road network of this district using GIS tools is still not available in literature. The results of the current study and their application could help the administrators and decisionmakers to build a sustainable road network. In this paper, we make an attempt to digitize the existing road network of Cachar district for its proper analysis. We compile the major and minor road density maps for the five revenue circles of the district. We use OpenStreetMap (OSM) to access and download existing road network in the district. Further, using the shortest path tool in QGIS, we find and display the shortest route between two junction points in the road network. Finding optimal route can be of great utility during emergency medical responses or fire or flood situations. Most of the major and minor roads within Cachar district were digitized in QGIS environment to perform the road network analysis.