Graphical Encoding Research Articles

Does This Have a Particular Meaning? Interactive Pattern Explanation for Network Visualizations.

This paper presents an interactive technique to explain visual patterns in network visualizations to analysts who do not understand these visualizations and who are learning to read them. Learning a visualization requires mastering its visual grammar and decoding information presented through visual marks, graphical encodings, and spatial configurations. To help people learn network visualization designs and extract meaningful information, we introduce the concept of interactive pattern explanation that allows viewers to select an arbitrary area in a visualization, then automatically mines the underlying data patterns, and explains both visual and data patterns present in the viewer's selection. In a qualitative and a quantitative user study with a total of 32 participants, we compare interactive pattern explanations to textual-only and visual-only (cheatsheets) explanations. Our results show that interactive explanations increase learning of i) unfamiliar visualizations, ii) patterns in network science, and iii) the respective network terminology.

Automatic Scatterplot Design Optimization for Clustering Identification.

Scatterplots are among the most widely used visualization techniques. Compelling scatterplot visualizations improve understanding of data by leveraging visual perception to boost awareness when performing specific visual analytic tasks. Design choices in scatterplots, such as graphical encodings or data aspects, can directly impact decision-making quality for low-level tasks like clustering. Hence, constructing frameworks that consider both the perceptions of the visual encodings and the task being performed enables optimizing visualizations to maximize efficacy. In this article, we propose an automatic tool to optimize the design factors of scatterplots to reveal the most salient cluster structure. Our approach leverages the merge tree data structure to identify the clusters and optimize the choice of subsampling algorithm, sampling rate, marker size, and marker opacity used to generate a scatterplot image. We validate our approach with user and case studies that show it efficiently provides high-quality scatterplot designs from a large parameter space.

Efficient prediction of peptide self-assembly through sequential and graphical encoding.

In recent years, there has been an explosion of research on the application of deep learning to the prediction of various peptide properties, due to the significant development and market potential of peptides. Molecular dynamics has enabled the efficient collection of large peptide datasets, providing reliable training data for deep learning. However, the lack of systematic analysis of the peptide encoding, which is essential for artificial intelligence-assisted peptide-related tasks, makes it an urgent problem to be solved for the improvement of prediction accuracy. To address this issue, we first collect a high-quality, colossal simulation dataset of peptide self-assembly containing over 62 000 samples generated by coarse-grained molecular dynamics. Then, we systematically investigate the effect of peptide encoding of amino acids into sequences and molecular graphs using state-of-the-art sequential (i.e. recurrent neural network, long short-term memory and Transformer) and structural deep learning models (i.e. graph convolutional network, graph attention network and GraphSAGE), on the accuracy of peptide self-assembly prediction, an essential physiochemical process prior to any peptide-related applications. Extensive benchmarking studies have proven Transformer to be the most powerful sequence-encoding-based deep learning model, pushing the limit of peptide self-assembly prediction to decapeptides. In summary, this work provides a comprehensive benchmark analysis of peptide encoding with advanced deep learning models, serving as a guide for a wide range of peptide-related predictions such as isoelectric points, hydration free energy, etc.

The effects of graphical encodings on reading performance of the data chart displayed on the periphery of attention

The accuracy and efficiency of estimating the true data value in visualizations is critical to the user interface design for large displays. As a variable, the attention engagement has not been the focus of existing related studies. In the current study, we intended to measure the performance users estimate proportions from a visualization under the low-attention condition. On this purpose, the dual-task paradigm was employed to simulate the scenario that data charts were read simultaneously with searching and memorizing information on the display. We evaluated eight data charts with three graphical encodings (shape, orientation and area) for the proportion value. The experimental results show that the vertical stacked chart is relatively more suitable for quantitative reading under the situation of temporary distraction. This is reflected by the high accuracy of estimation of this chart with relative less time consumption. When data charts are difficult to read, the users tend to pay less attention to information processing and make more inaccurate inferences of this primary task. Graphical encoding and the task time have a significant effect on task performances overall, while the reading accuracy seems not to vary with the difference of the primary task. The present study can be a supplement to the understanding of graphical perception and provide implications for the design of data visualization in display-human interfaces.

Active Processes in Modern Russian: Possibilities of Ecological and Linguistic Study

The article considers possibility of applying the ecological-and-linguistic approach to the study of active processes that characterize the current state of the Russian language, text production, including electronic communication. The specificity of the ecological approach in linguistics, its distinction from the orthological approach, as well as the structural analysis of linguistic units are displayed, visible active processes that dominate in phonetics, vocabulary, graphic encoding and text creation are registered. The authors consider the usefulness of the ecological approach in linguistics, its distinction from the orthological approach, as well as the structural analysis of linguistic units. The analysis made provision for defining language democratization as the major trend, which is noted in word functioning, changes in phrase and sentence structures; numerous borrowings of words and parts of words from the English language support the globalization trend. There is a tendency in strengthening the subjective aspect of the text content in public communication that is marked by the shift towards evaluative-expressive-emotional colloquial speech style. The opposing trend is text intellectualization, it appeals to background knowledge of the reader, the use of abbreviated forms in information coding. The authors conclude that a long-term ecological monitoring of these trends and the use of the ecological-and-linguistic approach to classification of linguistic phenomena are required.

Concurrent semantics for fusions: Weak prime domains and connected event structures

Stable event structures, and their duality with prime algebraic domains, represent a landmark of concurrency theory, since they provide a neat characterisation of causality in computations. As such, they have been used for defining the concurrent semantics of many formalisms, from Petri nets to (linear) graph rewriting systems.Stability however is restrictive for formalisms with “fusion”, where a computational step may merge parts of the state. This happens e.g. for graph rewriting systems with non-linear rules, which are used to cover some relevant applications (such as the graphical encoding of calculi with name passing).Guided by the need of giving semantics to such formalisms, we leave aside stability and characterise a class of domains, referred to as weak prime domains, naturally generalising prime algebraic domains. We then identify a corresponding class of event structures, that we call connected event structures, via a duality result formalised as an equivalence of categories.

Photolithographic Fabrication of Upconversion Barcodes for Multiplexed Molecular Detection

AbstractThe demands of clinical diagnostics and genetic analysis for high‐performance multiplex detection systems have driven substantial advancement from planar microarrays to suspension arrays for accurate encoding, inventorying, and detecting extensive databases of biomolecules. Despite the multitude of related works and the commercial availability of nanostructured arrays for biodetection, it remains challenging to develop biodetection modules of massive coding permutation with high production rates and fast reaction kinetics . Herein, the concurrent improvement in both production and coding capacities without compromising detection kinetics is reported using lithography‐based upconversion barcodes as the basis for bioassay detection modules. This method exploits microstructural forms of dense graphical encoding, with barcode production up to 109 per run at extensive color permutations. The upconversion barcoding technique requires a million times lower analyte consumption compared to currently available technologies. Moreover, the use of upconversion barcodes is demonstrated in a DNA hybridization test with high target specificity, low detection limit, and ease of flexible surface bioconjugation, enabling potential development of biomarkers in the analysis of massive proteomics, genomics, and metabolomics data.

Preparation of encoded bar-like core-shell microparticles on a microfluidic chip

This work presented a microfluidic multi-phase droplet system for preparing encoded bar-like core-shell microparticles. The integration of T-junction and flow-focusing junction on one microfluidic chip was designed to form water-in-oil-in-water double emulsions. And the double emulsions were used as templates to fabricate the encoded bar-like core-shell particles on the chip. The encoded particles were of small and uniform size. The core droplets were filled with different quantum dots and dyes for providing encoding information, and the outer oil phase droplets of trimethylolpropane ethoxylate triacrylate were solidified into the shell of the encoded particles for confining the core droplets in them and supplying the surface for capturing targets. The sequence of the core droplets could be confined by the configuration of the micro-channels when the core droplets were encapsulated in the outer droplets. Thus a new multi-mode encoding method was defined by combining dual-optical encoding and graphical encoding. Different quantum dots provided the wavelength code and the intensity code, multiple dyes provided the color code, and the single order of core droplets in the shell offered the position code. Compared with the conventional encoding methods, this approach increases the encoding number by hundred times, and has great potential for high-throughput multiplexed analysis.

A Graphic Encoding Method for Quantitative Classification of Protein Structure and Representation of Conformational Changes.

In order to successfully predict a proteins function throughout its trajectory, in addition to uncovering changes in its conformational state, it is necessary to employ techniques that maintain its 3D information while performing at scale. We extend a protein representation that encodes secondary and tertiary structure into fix-sized, color images, and a neural network architecture (called GEM-net) that leverages our encoded representation. We show the applicability of our method in two ways: (1) performing protein function prediction, hitting accuracy between 78 and 83 percent, and (2) visualizing and detecting conformational changes in protein trajectories during molecular dynamics simulations.

Investigating Direct Manipulation of Graphical Encodings as a Method for User Interaction.

We investigate direct manipulation of graphical encodings as a method for interacting with visualizations. There is an increasing interest in developing visualization tools that enable users to perform operations by directly manipulating graphical encodings rather than external widgets such as checkboxes and sliders. Designers of such tools must decide which direct manipulation operations should be supported, and identify how each operation can be invoked. However, we lack empirical guidelines for how people convey their intended operations using direct manipulation of graphical encodings. We address this issue by conducting a qualitative study that examines how participants perform 15 operations using direct manipulation of standard graphical encodings. From this study, we 1) identify a list of strategies people employ to perform each operation, 2) observe commonalities in strategies across operations, and 3) derive implications to help designers leverage direct manipulation of graphical encoding as a method for user interaction.

Tunable Emissions of Upconversion Fluorescence for Security Applications

AbstractThe rampant appearance of counterfeiting has a serious adverse effect on every aspect in the global markets. Thus, the development of high‐tech security strategies has become an urgent challenge. Recently, lanthanide ions (Ln3+) doped materials open new avenues for concealing factual data and shield against counterfeiting because of their unique optical characteristics of color‐tunable emissions under near‐infrared excitation. The present review surveys the recent advances in Ln3+‐doped upconversion crystals (UCCs) as fluorescent functional inks toward designable and high‐level anti‐counterfeiting patterns and graphical encoding. The great achievements of fabrication of versatile security patterns can be ascribed to the combination of the single or multiple colorful UCCs with polymers, additives, and solvents. Moreover, the crucial factors including underlying mechanisms, synthetic methods of upconversion fluorescence materials, and the diverse printing technologies employed for patterning the fluorescence images have been highlighted, and the corresponding challenges and opportunities in this promising research area are presented. This review will help providing a fundamental understanding and guidance to rational design fluorescence optical labels based on Ln3+‐doped UCCs for broadening their applications in high‐level security fields.

Optimization of electronic document management systems by means of encoding and visualization of stored data in the integrated development environment

The article considers the issue of storage, cataloging and transfer of documentation within the electronic document management system (EDMS). Modern document management solutions can be considered as the intersection of traditional and digital technologies, in particular, the storage of software code on paper. The very storage of program code in paper version implies a large archive for data storage, which includes modifications when versions of the program code are updated. Graphical ways of storing large amounts of data have been known for a long time, but they usually use a long procedure for restoring the original information and exclude recovery from paper or are significantly limited in the amount of stored data. As one of the elements of the composite electronic document management system it is proposed to use the method of graphical encoding of information (QR-code generation technology), which will increase the resistance to unauthorized modification of the program code, simplify the procedure for storing, identifying and verifying information. As an elementary block of information, it is intended to use a separate software module responsible for one of the subprograms in the RTOS environment. The proposed algorithm for storing and transferring information implies its compression by software, encryption and transmission. The article compares various compression algorithms and their efficiency. The presence of a cataloguer in each graphic element allows for quick search, comparison and verification of blocks.

Evaluating Interactive Graphical Encodings for Data Visualization.

User interfaces for data visualization often consist of two main components: control panels for user interaction and visual representation. A recent trend in visualization is directly embedding user interaction into the visual representations. For example, instead of using control panels to adjust visualization parameters, users can directly adjust basic graphical encodings (e.g., changing distances between points in a scatterplot) to perform similar parameterizations. However, enabling embedded interactions for data visualization requires a strong understanding of how user interactions influence the ability to accurately control and perceive graphical encodings. In this paper, we study the effectiveness of these graphical encodings when serving as the method for interaction. Our user study includes 12 interactive graphical encodings. We discuss the results in terms of task performance and interaction effectiveness metrics.

Direct identification of on-bead peptides using surface-enhanced Raman spectroscopic barcoding system for high-throughput bioanalysis.

Recently, preparation and screening of compound libraries remain one of the most challenging tasks in drug discovery, biomarker detection, and biomolecular profiling processes. So far, several distinct encoding/decoding methods such as chemical encoding, graphical encoding, and optical encoding have been reported to identify those libraries. In this paper, a simple and efficient surface-enhanced Raman spectroscopic (SERS) barcoding method using highly sensitive SERS nanoparticles (SERS ID) is presented. The 44 kinds of SERS IDs were able to generate simple codes and could possibly generate more than one million kinds of codes by incorporating combinations of different SERS IDs. The barcoding method exhibited high stability and reliability under bioassay conditions. The SERS ID encoding based screening platform can identify the peptide ligand on the bead and also quantify its binding affinity for specific protein. We believe that our SERS barcoding technology is a promising method in the screening of one-bead-one-compound (OBOC) libraries for drug discovery.

RPO semantics for mobile ambients

In this paper we focus on the synthesis of labelled transition systems (LTSs) for process calculi using Mobile Ambients (MAs) as a testbed. Our proposal is based on a graphical encoding: a process is mapped into a graph equipped with interfaces such that the denotation is fully abstract with respect to the standard structural congruence. Graphs with interfaces are amenable to the synthesis mechanism based on borrowed contexts (BCs), which is an instance of relative pushouts (RPOs). The BC mechanism allows the effective construction of an LTS that has graphs with interfaces as states and labels, and such that the associated bisimilarity is a congruence. We focus here on the analysis of an LTS over processes as graphs with interfaces: we use the LTS on graphs to recover an LTS directly defined over the structure of MA processes and define a set of SOS inference rules capturing the same operational semantics.

Information visualization on large, high-resolution displays: Issues, challenges, and opportunities

Larger, higher-resolution displays are becoming accessible to a greater number of users as display technologies decrease in cost and software for the displays improves. The additional pixels are especially useful for information visualization where scalability has typically been limited by the number of pixels available on a display. But how will visualizations for larger displays need to fundamentally differ from visualizations on desktop displays? Are the basic visualization design principles different? With this potentially new design paradigm comes questions such as whether the relative effectiveness of various graphical encodings are different on large displays, which visualizations and datasets benefit the most, and how interaction with visualizations on large, high-resolution displays will need to change. As we explore these possibilities, we shift away from the technical limitations of scalability imposed by traditional displays (e.g. number of pixels) to studying the human abilities that emerge when these limitations are removed. There is much potential for information visualizations to benefit from large, high-resolution displays, but this potential will only be realized through understanding the interaction between visualization design, perception, interaction techniques, and the display technology. In this paper we present critical design issues and outline some of the challenges and future opportunities for designing visualizations for large, high-resolution displays. We hope that these issues, challenges, and opportunities will provide guidance for future research in this area.

Labelled Transitions for Mobile Ambients (As Synthesized via a Graphical Encoding)

The paper presents a case study on the synthesis of labelled transition systems (LTSs) for process calculi, choosing as testbed Cardelli and Gordon's Mobile Ambients (MAs). The proposal is based on a graphical encoding: each process is mapped into a graph equipped with suitable interfaces, such that the denotation is fully abstract with respect to the usual structural congruence. Graphs with interfaces are amenable to the synthesis mechanism proposed by Ehrig and König and based on borrowed contexts (BCs), an instance of relative pushouts, introduced by Leifer and Milner. The BC mechanism allows the effective construction of a LTS that has graphs with interfaces as both states and labels, and such that the associated bisimilarity is automatically a congruence. Our paper focuses on the analysis of a LTS over (processes as) graphs with interfaces, as distilled by exploiting the graphical encoding of MAs. In particular, we use the LTS on graphs to recover a suitable LTS directly defined over the structure of MAs processes.

Synthesising CCS bisimulation using graph rewriting

The paper presents a case study on the synthesis of labelled transition systems ( ltss) for process calculi, choosing as testbed Milner’s Calculus of Communicating System ( ccs). The proposal is based on a graphical encoding: each ccs process is mapped into a graph equipped with suitable interfaces, such that the denotation is fully abstract with respect to the usual structural congruence. Graphs with interfaces are amenable to the synthesis mechanism proposed by Ehrig and König and based on borrowed contexts ( bcs), an instance of relative pushouts originally introduced by Milner and Leifer. The bc mechanism allows the effective construction of an lts that has graphs with interfaces as both states and labels, and such that the associated bisimilarity is automatically a congruence. Our paper focuses on the analysis of the lts distilled by exploiting the encoding of ccs processes: besides offering major technical contributions towards the simplification of the bc mechanism, a key result of our work is the proof that the bisimilarity on processes obtained via bcs coincides with the standard strong bisimilarity for ccs.

Graphical Verification of a Spatial Logic for the π-calculus

The paper introduces a novel approach to the verification of spatial properties for finite π-calculus specifications. The mechanism is based on a recently proposed graphical encoding for mobile calculi: Each process is mapped into a (ranked) graph, such that the denotation is fully abstract with respect to the usual structural congruence (i.e., two processes are equivalent exactly when the corresponding encodings yield the same graph). Spatial properties for reasoning about the behavior and the structure of π-calculus processes are then expressed in a logic introduced by Caires, and they are verified on the graphical encoding of a process, rather than on its textual representation. More precisely, the graphical presentation allows for providing a simple and easy to implement verification algorithm based on the graphical encoding (returning true if and only if a given process verifies a given spatial formula).

Spontaneous Inferences from Pictorially Presented Behaviors

Previous research on spontaneous trait inferences (STI) was based on verbal stimuli. In this research, stimulus behaviors were presented pictorially and STIs were measured in terms of the time needed to identify a trait term that gradually appeared behind a mask. An attempt was made to demonstrate that the STI cannot be reduced to a side effect of language comprehension. A pilot study showed that the phenomenon extends to pictures and that a graphical encoding task leads to even stronger STIs than verbal recoding. Experiment 1 corroborated the basic finding using an improved methodology. In Experiment 2, specific encoding operations were manipulated in a verification task. STIs were strongest when the verification task referred to concrete stimulus aspects. The findings support neither an account in terms of mere language comprehension nor a verbal interference of inferential-distance account, but they are consistent with a concreteness advantage or picture-superiority effect.