In this paper, we present a novel viewpoint selection framework for angiographic volume data. We propose several view descriptors based on typical concerns of clinicians for the view evaluation. Compared with conventional approaches, our method can deliver a more representative global optimal view by sampling at a much higher rate in the view space. Instead of performing analysis on sample views individually, we construct a solution space to estimate the quality of the views. Descriptor values are propagated to the solution space where an efficient searching process can be performed. The best viewpoint can be found by analyzing the accumulated descriptor values in the solution space based on different visualization goals.

Node-link diagrams are widely used in information visualization to show relationships among data. However, when the size of data becomes very large, node-link diagrams will become cluttered and visually confusing for users. In this paper, we propose a novel controllable edge clustering method based on Delaunay triangulation to reduce visual clutter for node-link diagrams. Our method uses curves instead of straight lines to represent links and these curves can be grouped together according to their relative positions and directions. We further introduce progressive edge clustering to achieve continuous level-of-details for large networks.

Hyperlinks among webpages are very important information and are widely used for webpage clustering and webpage ranking. With the explosive growth in the number of webpages available online, the exploration of hyperlinks among webpages becomes a very challenging problem. Information visualization provides an effective way of visualizing hyperlinks and can help users gain insights into the relationships of webpages.

In this paper, we present some novel computer graphics techniques to visualize the hyperlinks among webpages. We propose a visual encoding scheme for five dimensional hyperlinks data and two constrained 3D layout techniques for incoming and outgoing links of a single webpage. To reveal the hierarchical structure of webpages as well as the hyperlinks information, we extend the treemap representation. Our representations are visually appealing and can effectively reveal linkage patterns among webpages. Experimental results and a user study demonstrate the effectiveness of our system. Our system can facilitate E-learning and help students understand the complex structures and hidden patterns in network datasets.

Multimodal volume data commonly found in medical imaging applications present both opportunities and challenges to segmentation and visualization tasks. This paper presents a user directed volume segmentation system. Through a spreadsheets interface, the user can interactively examine and refine segmentation results obtained from automatic clustering. In addition, the user can isolate or highlight a feature of interest in a volume based on different modalities, and see the corresponding segmented results. Our system is easy to use since the preliminary segmentation results are organized and presented to the user in a relation-aware fashion based on the spatial relations between the segmented regions. We demonstrate this system using two multimodal datasets.

In this paper, we present VoxelBars as an informative interface for volume visualization. VoxelBars arrange voxels into a 2D space and visually encode multiple attributes of voxels into one display. VoxelBars allow users to easily find out clusters of interesting voxels, set opacities and colors of a specific group of voxels, and achieve various sophisticated visualization tasks at voxel level. We provide results on real volume data to demonstrate the advantages of the VoxelBars over scatterplots and traditional transfer function specification methods. Some novel visualization techniques including visibility-aware transfer function design and selective clipping based on VoxelBars are also introduced.

Interpersonal ties, such as strong ties and weak ties, describe the information carried by an edge in social network. Tracking the dynamic changes of interpersonal ties can thus enhance our understanding of the evolution of a complex network. Nevertheless, existing studies in dynamic network visualization mostly focus on the temporal changes of nodes or structures of the network without an adequate support of analysis and exploration of the temporal changes of interpersonal ties. In this paper, we introduce a new visual analytics method that enables interactive analysis and exploration of the dynamic changes of interpersonal ties. The method integrates four well-linked visualizations, including a scatterplot, a pixelbar chart, a layered graph, and a node-link diagram, to allow for multi-perspective analysis of the evolution of interpersonal ties. The scatterplot created by multi-dimensional scaling can help reveal the clusters of ties and detect abnormal ties, while other visualizations allow users to explore the clusters of ties interactively from different perspectives. A case study has been conducted to demonstrate the effectiveness of our approach.

This book is a compilation of selected papers from the 14th International Symposium on Computer Science in Sport (IACSS 2023), held on September 27-30, 2023 in Hangzhou, China. The work focuses on the application of computer science and technology in the field of sports (such as intelligent data collection, data mining, visual analysis of game data, virtual reality, machine learning, computer vision, match prediction models and performance analysis). The contents make valuable contributions to academic researchers, college students, coaches and athletes, and sports management personnel (such as managers of sports associations, training bases, and professional clubs). Additionally, readers will encounter new ideas for realizing a more efficient and convenient training and exercise system.

Site-specifically patterning of biomolecules, such as DNA, peptides, proteins and virus at the submicron or nanometer resolution has been of increasing interest these years, from both scientific and technological perspectives. Such patterns with biological features and activity hold enormous promise for biological and medical applications, including high-sensitive diagnostics, genomics, proteomics, integrated biomaterials and fundamental studies of molecular and cell biology. With the development of nanofabrication technology, the past decade has witnessed the advent of a variety of promising strategies for immobilizing biomolecules. Numerous strategies with properties of well-defined feature size, high throughput, high speed, heterogeneous array, low cost and high-reserved bioactivity have been pursued. These include top-down lithographic-assisted techniques, such as nanocontact printing, nanoimprinting, dip-pen nanolithography, nanografting and electron beam lithography; and self assembly based bottom-up techniques, such as DNA-templated chemistry, colloidal lithography and block-copolymer lithography. In this chapter, research status and recent advances of the biomolecular nanopatterning are reviewed. Advantages and limitations of current approaches, as well as future opportunities and challenges are discussed.

The technique of rolling circle amplification (RCA) emerged recently as a robust tool to generate the regularly patterned DNA structures in addition to its long-recognized ability of amplifying biological signals. Here, we demonstrate the strategy of RCA-driven generation of nano-scaled cocoon-like DNA particles, designated as DNA nanoclews, for loading and delivering a small molecule anticancer drug. The characteristic biodegradability of DNA was harnessed to control the timing and location of drug release by utilizing a polymeric nanogel encapsulating DNA-degrading enzyme DNase I. This smart drug delivery system based on RCA amplicons could get internalized into targeted cells and release the cargo using the endosomal acidity as a trigger.

In this chapter, we describe the preparation of glucose-responsive vesicles (GRVs) and the fabrication of GRV-loaded microneedle-array patches for insulin delivery. The GRVs were formed of hypoxia-sensitive hyaluronic acid (HS-HA), the synthesis of which is presented in detail. We also describe the procedure to evaluate the in vivo efficacy of this smart patch in a mouse model of chemically induced type 1 diabetes through transcutaneous administration.