Homomorphic-Encrypted Volume Rendering

Computationally demanding tasks are typically calculated in dedicated data centers, and real-time visualizations also follow this trend. Some rendering tasks, however, require the highest level of confidentiality so that no other party, besides the owner, can read or see the sensitive data. Here we present a direct volume rendering approach that performs volume rendering directly on encrypted volume data by using the homomorphic Paillier encryption algorithm. This approach ensures that the volume data and rendered image are uninterpretable to the rendering server. Our volume rendering pipeline introduces novel approaches for encrypted-data compositing, interpolation, and opacity modulation, as well as simple transfer function design, where each of these routines maintains the highest level of privacy. We present performance and memory overhead analysis that is associated with our privacy-preserving scheme. Our approach is open and secure by design, as opposed to secure through obscurity. Owners of the data only have to keep their secure key confidential to guarantee the privacy of their volume data and the rendered images. Our work is, to our knowledge, the first privacy-preserving remote volume-rendering approach that does not require that any server involved be trustworthy; even in cases when the server is compromised, no sensitive data will be leaked to a foreign party.Comment: Accepted for presentation at IEEE VIS 202

Dr. KID: Direct Remeshing and K-set Isometric Decomposition for Scalable Physicalization of Organic Shapes

Dr. KID is an algorithm that uses isometric decomposition for the physicalization of potato-shaped organic models in a puzzle fashion. The algorithm begins with creating a simple, regular triangular surface mesh of organic shapes, followed by iterative k-means clustering and remeshing. For clustering, we need similarity between triangles (segments) which is defined as a distance function. The distance function maps each triangle's shape to a single point in the virtual 3D space. Thus, the distance between the triangles indicates their degree of dissimilarity. K-means clustering uses this distance and sorts of segments into k classes. After this, remeshing is applied to minimize the distance between triangles within the same cluster by making their shapes identical. Clustering and remeshing are repeated until the distance between triangles in the same cluster reaches an acceptable threshold. We adopt a curvature-aware strategy to determine the surface thickness and finalize puzzle pieces for 3D printing. Identical hinges and holes are created for assembling the puzzle components. For smoother outcomes, we use triangle subdivision along with curvature-aware clustering, generating curved triangular patches for 3D printing. Our algorithm was evaluated using various models, and the 3D-printed results were analyzed. Findings indicate that our algorithm performs reliably on target organic shapes with minimal loss of input geometry

Multi-GPU Rendering with the open Vulkan API

The Vulkan API provides a low level interface to modern Graphics Processing Units (GPUs). We demonstrate how to use Vulkan to send commands explicitly to separate GPUs for implementing platform,- and vendor independent multi-GPU rendering. We describe how to implement the sort-first and sort-last approaches to perform parallel rendering with Vulkan. We introduce an abstraction library which we have made available, and an application for multi-GPU rendering of meshes. Performance benchmarks have been performed in order to evaluate the implementation. We also show that we can utilize the additional GPU memory from multiple GPUs to render larger data sets than possible with a single GPU

Similarity-based Exploded Views

Exploded views are often used in illustration to overcome the problem of occlusion when depicting complex structures. In this paper, we propose a volume visualization technique inspired by exploded views that partitions the volume into a number of parallel slabs and shows them apart from each other. The thickness of slabs is driven by the similarity between partitions. We use an information-theoretic technique for the generation of exploded views. First, the algorithm identifies the viewpoint from which the structure is the highest. Then, the partition of the volume into the most informative slabs for exploding is obtained using two complementary similarity-based strategies. The number of slabs and the similarity parameter are freely adjustable by the user

Obscurance-based Volume Rendering Framework

IEEE/ EG Symposium on Volume and Point-Based Graphics (2008) H.- C. Hege, D. Laidlaw, R. Pajarola, O. Staadt (Editors)lighting effects in a faster way than global illumination. Its application in volume visualization is of special interest since it permits us to generate a high quality rendering at a low cost. In this paper, we propose an obscurancebased framework that allows us to obtain realistic and illustrative volume visualizations in an interactive manner. Obscurances can include color bleeding effects without additional cost. Moreover, we obtain a saliency map from the gradient of obscurances and we show its application to enhance volume visualization and to select the most salient views.publishedVersio

VOICE: Visual Oracle for Interaction, Conversation, and Explanation

We present VOICE, a novel approach for connecting large language models' (LLM) conversational capabilities with interactive exploratory visualization. VOICE introduces several innovative technical contributions that drive our conversational visualization framework. Our foundation is a pack-of-bots that can perform specific tasks, such as assigning tasks, extracting instructions, and generating coherent content. We employ fine-tuning and prompt engineering techniques to tailor bots' performance to their specific roles and accurately respond to user queries, and a new prompt-based iterative scene-tree generation establishes a coupling with a structural model. Our text-to-visualization method generates a flythrough sequence matching the content explanation. Finally, 3D natural language interaction provides capabilities to navigate and manipulate the 3D models in real-time. The VOICE framework can receive arbitrary voice commands from the user and responds verbally, tightly coupled with corresponding visual representation with low latency and high accuracy. We demonstrate the effectiveness and high generalizability potential of our approach by applying it to two distinct domains: analyzing three 3D molecular models with multi-scale and multi-instance attributes, and showcasing its effectiveness on a cartographic map visualization. A free copy of this paper and all supplemental materials are available at https://osf.io/g7fbr/

Copper(II) Lysinate and Pseudoproline Assistance in the Convergent Synthesis of the GLP-1 Receptor Agonists Liraglutide and Semaglutide

A growing interest in peptides as active pharmaceutical ingredients (APIs) requires the development of efficient strategies for their preparation. This is particularly challenging in the case of long peptides with a strong tendency for aggregation and folding. Here, we describe the pseudoproline-assisted convergent synthesis of GLP-1 receptor agonist lipopeptides liraglutide and semaglutide, which involves the stepwise condensation of three fragments in the solid phase. The insertion of a pseudoproline residue at the site of fragment coupling prevents aggregation and allows obtaining these peptides with excellent purity and high yield. In addition, for the synthesis of lipidated side chains, we developed a novel approach that involves copper(II) lysinate intermediates and can be particularly suitable for the industrial preparation of both liraglutide and semaglutide and other peptides with a similar branched structure.A growing interest in peptides as active pharmaceutical ingredients (APIs) requires the development of efficient strategies for their preparation. This is particularly challenging in the case of long peptides with a strong tendency for aggregation and folding. Here, we describe the pseudoproline-assisted convergent synthesis of GLP-1 receptor agonist lipopeptides liraglutide and semaglutide, which involves the stepwise condensation of three fragments in the solid phase. The insertion of a pseudoproline residue at the site of fragment coupling prevents aggregation and allows obtaining these peptides with excellent purity and high yield. In addition, for the synthesis of lipidated side chains, we developed a novel approach that involves copper(II) lysinate intermediates and can be particularly suitable for the industrial preparation of both liraglutide and semaglutide and other peptides with a similar branched structure