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Layered manufacturing, the underlying technology of 3-D printing, has made rapid strides over the last 30 years. We discuss layered manufacturing from the artist's perspective, especially for intricate ceramic pottery. We contend that opportunities exist for applying visualization to the foremost problems plaguing layered manufacturing. Virtual pottery involves meeting two conflicting constraints: rapid visualization during modeling and accurate rapid prototyping during manufacturing. Artists simultaneously need both low polygon shape representation for interactive visualization and adequate representation for generating accurate printable models. Artists also face the additional complexities of adding surface details that cannot be achieved by hand and handling materials like clay used in the manufacturing of real pottery. Illustrated by a system we have developed that uses sound resonance patterns to create volumetric textures for virtual pottery, we show how visualization helps address both these problem areas. [ABSTRACT FROM AUTHOR]

While text clustering methods have been available for decades, there is a paucity of material that would help practitioners with the choice and configuration of suitable algorithms and visualizations. In this article, we present a case study analyzing two disinformation datasets composed of tweets from the era of the 2016 United States Presidential Election. We use this to demonstrate steps for selecting the best configuration of the clustering algorithm and consequently conduct a user experiment for evaluating the comprehensibility of three alternate visualizations. A supplementary GitHub repository contains source code with examples. [ABSTRACT FROM AUTHOR]

Graphs and other structured data have come to the forefront in machine learning over the past few years due to the efficacy of novel representation learning methods boosting the prediction performance in various tasks. Representation learning methods embed the nodes in a low-dimensional real-valued space, enabling the application of traditional machine learning methods on graphs. These representations have been widely premised to be also suited for graph visualization. However, no benchmarks or encompassing studies on this topic exist. We present an empirical study comparing several state-of-the-art representation learning methods with two recent graph layout algorithms, using readability and distance-based measures as well as the link prediction performance. Generally, no method consistently outperformed the others across quality measures. The graph layout methods provided qualitatively superior layouts when compared to representation learning methods. Embedding graphs in a higher dimensional space and applying t-distributed stochastic neighbor embedding for visualization improved the preservation of local neighborhoods, albeit at substantially higher computational cost. [ABSTRACT FROM AUTHOR]

Childhood obesity is a growing concern as it can lead to lifelong health problems that carry over into adulthood. A substantial contributing factor to obesity is the physical activity (PA) habits that are formed in early childhood, as these habits tend to sustain throughout adulthood. To aid children in forming healthy PA habits, we designed a mixed reality system called the Virtual Fitness Buddy ecosystem, in which children can interact with a virtual pet agent. As a child exercises, their pet becomes slimmer, faster, and able to play more games with them. Our initial deployment of this project showed promise but was only designed for a short-term intervention lasting three days. More recently, we have scaled it from a pilot grade study to a 9-month intervention comprised of 422 children. Ultimately, our goal is to scale this project to be a nationwide primary prevention program to encourage moderate to vigorous PA in children. This article explores the challenges and lessons learned during the design and deployment of this system at scale in the field. [ABSTRACT FROM AUTHOR]

A U-Net is a type of convolutional neural network that has been shown to output impressive results in medical imaging segmentation tasks. Still, neural networks in general form a black box that is hard to interpret, especially by noncomputer scientists. This work provides a visual system that allows users to examine U-Nets that were trained to predict brain lesions caused by stroke using multimodal imaging. We provide several visualization views that allow users to load trained U-Nets, run them on different patient data, and examine the results while visually following the computation of the U-Net. With these visualizations, we can provide useful information for our medical collaborators showing how the training database can be improved and which features are best learned by the neural network. [ABSTRACT FROM AUTHOR]

Recent advances in virtual reality cameras have contributed to a phenomenal growth of 360$^{\circ }$∘ videos. Estimating regions likely to attract user attention is critical for efficiently streaming and rendering 360$^{\circ }$∘ videos. In this article, we present a simple, novel, GPU-driven pipeline for saliency computation and virtual cinematography in 360$^{\circ }$∘ videos using spherical harmonics (SH). We efficiently compute the 360$^{\circ }$∘ video saliency through the spectral residual of the SH coefficients between multiple bands at over 60FPS for 4K resolution videos. Further, our interactive computation of spherical saliency can be used for saliency-guided virtual cinematography in 360$^{\circ }$∘ videos. [ABSTRACT FROM AUTHOR]

There is concern within the cultural community about the decreasing number of people, especially young people, visiting museums and cultural institutions. To fight this trend, new ways of accessing art are needed. We believe that technologies like virtual reality can greatly foster the relationship between users and works of art. In this article, we present an elaborated virtual reality experience, ImmersArt, whose aim is to take users literally inside a work of art and the creative universe of its creator. The motivational impact of this tool was empirically analyzed and compared with other formats for experiencing art such as illustrated books and audiovisual presentations. The study suggests that young people are more motivated to study artwork when using virtual reality. [ABSTRACT FROM AUTHOR]

High-resolution simulation of global climate physics enables us to model how the climate may change under a variety of future scenarios. Such simulations produce vast amounts of information and dense datasets. If interrogated in tandem, these datasets can provide holistic, vital information on Earth's many integrated systems by revealing the manifold interrelated properties of the atmosphere, ocean, and polar ice, framed by real-world terrain in three-dimensional space as they vary over time. To accomplish this, climate scientists have joined with computer scientists and an artist to develop techniques enabling scientists to see these relationships. The impact of ocean water properties on Antarctic ice shelves illustrates the benefit of this analysis in understanding land ice melt rates and thus sea-level rise. [ABSTRACT FROM AUTHOR]

Automated image style transfer is of great interest given the recent advances in generative adversarial networks (GANs). However, it is challenging to generate synthesized images from abstract masks while preserving detailed patterns for certain kinds of art given small datasets. We propose an intelligent GAN-based system enhanced with user intent and prior knowledge for generating images styled as Cantonese porcelain using user-defined masks. Given a mask with specified objects, our system first generates a synthesized natural image. We then use a novel semantic user intent enhancement module to retrieve semantically relevant images from an image dataset. Objects in the retrieved image are used to refine local patterns in the synthesized image. Finally, the refined image is restyled in the Cantonese porcelain style. The system is trained by 454 pairs of natural images and semantic segmentation of 24 objects from the COCO dataset for synthesized image generation from masks, and 1445 Cantonese porcelain images for style transfer. Experimental results and ablation studies demonstrate that the synthesized and restyled images were improved with local details and enhanced contrast. [ABSTRACT FROM AUTHOR]

As human beings, we are so used to interacting with each other that any world without humans would feel alien to us, including digital ones. In this article, we present a survey on the role of digital human-like characters in virtual worlds, both as counterparts of real human users and as embodied agents driven by artificial intelligence. The main issues related to 3-D graphics, physics, animation, and behavioral modeling are introduced, suggesting wherever available different alternatives and related development pipelines. A sizeable list of examples illustrating the use of virtual humans in different application sectors is then presented, focusing in particular on four domains: environmental design, training, cultural heritage, and healthcare. [ABSTRACT FROM AUTHOR]

TimeSets is a temporal data visualization technique designed to reveal insights into event sets, such as all the events linked to one person or organization. In this article, we describe two TimeSets-based visual analytics tools for intelligence analysis. In the first case, TimeSets is integrated with other visual analytics tools to support open-source intelligence analysis with Twitter data, particularly the challenge of finding the right questions to ask. The second case uses TimeSets in a participatory design process with analysts that aims to meet their requirements of uncertainty analysis involving fake news. Lessons learned are potentially beneficial to other application domains. [ABSTRACT FROM AUTHOR]

The ExoMars rover, due to launch in mid 2020, will travel to Mars in search of signs of past or present habitability. The rover will carry the Panoramic Camera, PanCam, a scientific camera system designed to provide crucial remote sensing capabilities as mission scientists search for targets of interest. In preparation for the mission operations, the visual output of PanCam has been simulated and modeled with a three-dimensional rendering system, allowing the team to investigate the capabilities of the camera system and providing insight into how it may be calibrated and used for engineering tasks during the surface mission. [ABSTRACT FROM AUTHOR]

Synthetic apertures sample the signal of wide aperture sensors with either arrays of static or single moving smaller aperture sensors whose individual signals are computationally combined to increase the resolution, depth-of-field, frame rate, contrast, and signal-to-noise ratio. This principle has been used for radar, telescopes, microscopes, sonar, ultrasound, laser, and optical imaging. With airborne optical sectioning (AOS), we apply camera drones for synthetic aperture imaging to uncover the ruins of a 19th century fortification system that is concealed by dense forest and shrubs. Compared to alternative airborne scanning technologies (such as LiDAR), AOS is cheaper, delivers surface color information, achieves higher sampling resolutions, and (in contrast to photogrammetry) does not suffer from inaccurate correspondence matches and long processing times. [ABSTRACT FROM AUTHOR]

Asperger's syndrome is a disorder that involves a qualitative impairment in social interactions. While most treatments are aimed at children or adolescents, in this paper we present the development of a virtual reality training application in which adults with Asperger's syndrome can train in an autonomous and controlled way how to present in public. [ABSTRACT FROM AUTHOR]

Virtual reality (VR) applications meet fundamental principles of rehabilitation: intensity, task oriented training, biofeedback, environments rich in stimuli, and motivation, all pivotal factors for the success of rehabilitation programs. This paper describes the development process of a set of VR minigames developed to increase the motivation of stroke patients while performing repetitive upper limb movements. [ABSTRACT FROM AUTHOR]

This article discusses technological innovations in stylus writing and electronic tablets for computer use. The article explains how digital pen and paper technologies are becoming increasingly popular in vertical markets such as medical care and manufacturing. Innovations discussed in the article include Livescribe's Pulse smartpen, Iogear's Mobile Digital Scribe, the Epos digital-pen, and Dane Elec's ZPen. The article also discusses the Anoto's Digital Pen and Paper Technology, which is being used by field workers in Africa, in a pilot project to send data regarding the health of wildlife.

The article offers information on Games for Change (G4C), a Serious Games Initiative subgroup which aims to raise awareness and inspire action by providing support and resources to help individuals and organizations develop and use digital games that address real issues. G4C was co-founded by Suzanne Seggerman in 2004. The group conducted their 4th annual Games for Change Festival in June 2007 at Parsons The New School for Design in New York. The festival gave out awards for best awareness-raising game, best transformation game, best social-commentary/art game and an audience award. Winners include Gamelab's "Ayiti: The Cost of Life," Impact Games' "Peacemaker," Persuasive Games' "The Arcade Wire: Oil God" and "Darfur is Dying" by a team of University of Southern California students.

The article presents information on the visualization of fluid mixing in microchannels. The development of a microchannel for fluid-mixing applications comes from the recent interest in microfluidic device applications in biology. Microfluidics refers to fluid flow and transport phenomena associated with these devices. The basic idea of developing microfluidic devices is to shrink the physical dimensions of most commonly used processors using miniaturization and function integration to create the so-called lab on a chip. Using a microchannel as a mixer is attractive because it easily integrates with other microprocessing units. It is further reported in the article that to obtain fast mixing at a low flow speed, many researchers have proposed chaotic advection. Chaotic advection refers to complex or chaotic behavior of fluid particles' trajectories in a simple, low-speed flow. As the flow becomes chaotic, it also becomes effective in mixing and could produce turbulent-like mixing results at low flow speeds.

This article focuses on several techniques that have been discovered from time to time to given an illusion of 3-dimensional (3D) images. Shutter glasses, polarized glasses, and head-mounted displays (HMDs) have become common technologies for providing the illusion of 3D. Shutter glasses, popularized by StereoGraphics as CrystalEyes, use an LCD shutter over each eye to enable stereo viewing. The shutters are rendered alternately opaque and transparent so that only one eye can see through the glasses at any moment. The glasses are synchronized to the display system presenting the right and left images at the same frequency as the shutters' phase shifts. These systems can work with televisions, computer monitors, or projectors, but require that the display system can generate images at twice the frequency desired for viewing, because each frame must be shown twice. In the last 10 years, stereo displays that don't require glasses have emerged from the laboratories into the marketplace. Autostereoscopic displays (ASDs) use several technologies to present different images to both of a viewer's eyes. Volumetric display systems (VDS) create an image with true depth, letting the eyes and brain work in a natural manner. ASD and VDS systems are intended to replace current 3D displays, all of which require the user to wear some sort of filtering system, such as eyeglasses.