Complex network modeling characterizes system relationships and structures,while network visualization enables intuitive analysis and interpretation of these patterns.However,existing network visualization tools exhib...Complex network modeling characterizes system relationships and structures,while network visualization enables intuitive analysis and interpretation of these patterns.However,existing network visualization tools exhibit significant limitations in representing attributes of complex networks at various scales,particularly failing to provide advanced visual representations of specific nodes and edges,community affiliation attribution,and global scalability.These limitations substantially impede the intuitive analysis and interpretation of complex network patterns through visual representation.To address these limitations,we propose SFFSlib,a multi-scale network visualization framework incorporating novel methods to highlight attribute representation in diverse network scenarios and optimize structural feature visualization.Notably,we have enhanced the visualization of pivotal details at different scales across diverse network scenarios.The visualization algorithms proposed within SFFSlib were applied to real-world datasets and benchmarked against conventional layout algorithms.The experimental results reveal that SFFSlib significantly enhances the clarity of visualizations across different scales,offering a practical solution for the advancement of network attribute representation and the overall enhancement of visualization quality.展开更多
Effective data visualization is crucial for researchers,revealing patterns,trends,and insights that might otherwise remain hidden.Integrating related visualizations can reveal correlations and relationships that are n...Effective data visualization is crucial for researchers,revealing patterns,trends,and insights that might otherwise remain hidden.Integrating related visualizations can reveal correlations and relationships that are not evident when analyzing datasets separately.Despite increasing demand,there is a shortage of general tools to seamlessly combine diverse datasets to create complex visual representations.The aplot package addresses this by allowing users to independently create subplots and assemble them into a cohesive composite figure.It automatically reorders datasets for coordinate consistency,removing the need for manual adjustment.This modular approach simplifies the creation of complex visualizations,allowing customization to meet specific needs.Aplot’s versatility is ideal for integrating multi-omics datasets and analytical results for biological insights.The package is freely available on CRAN at https://cran.r-project.org/package=aplot,offering researchers a powerful tool for enhanced data exploration and visualizing workflows.展开更多
We compared the ability of two legend designs on a soil-landscape map to efficiently and effectively support map reading tasks with the goal of better understanding how the design choices affect user performance.Devel...We compared the ability of two legend designs on a soil-landscape map to efficiently and effectively support map reading tasks with the goal of better understanding how the design choices affect user performance.Developing such knowledge is essential to design effective interfaces for digital earth systems.One of the two legends contained an alphabetical ordering of categories,while the other used a perceptual grouping based on the Munsell color space.We tested the two legends for 4 tasks with 20 experts(in geography-related domains).We analyzed traditional usability metrics and participants’eye movements to identify the possible reasons behind their success and failure in the experimental tasks.Surprisingly,an overwhelming majority of the participants failed to arrive at the correct responses for two of the four tasks,irrespective of the legend design.Furthermore,participants’prior knowledge of soils and map interpretation abilities led to interesting performance differences between the two legend types.We discuss how participant background might have played a role in performance and why some tasks were particularly hard to solve despite participants’relatively high levels of experience in map reading.Based on our observations,we caution soil cartographers to be aware of the perceptual complexity of soil-landscape maps.展开更多
As simulation-informed design gains importance in addressing urban complexity,integrating urban imagery into interactive feedback and decision-making has become increasingly essential.However,this potential remains un...As simulation-informed design gains importance in addressing urban complexity,integrating urban imagery into interactive feedback and decision-making has become increasingly essential.However,this potential remains underused,as urban imagery is often treated as a supporting variable in urban research rather than a core layer of spatial intelligence,hindering informed strategies in city branding,resource allocation,and livability.This study develops a data-driven framework,Street View Search Engine,which integrates urban imagery analysis with interactive exploration to advance human-centered insights into urban visual form.Based on 81,478 street view imagery collected in Hong Kong,China,a dataset comprising 19 visual features was first constructed to represent urban visual information across three categories:physical,impression,and isovist.Subsequently,the machine learning algorithm self-organizing maps was employed to train the dataset,producing a visualized“data landscape”that re-organizes street views according to their visual similarities.Third,building on the data landscape,this study develops the Street View Search Engine framework to conduct three main tasks:define visual foundations,comprehend streetscape morphology,and evaluate regional visual schemes.These tasks combine general-use exploration with research-oriented analysis:a web-based platform was developed to support general-use exploration(http://47.113.226.77/project1/#/),while various data processing methods were employed to enable in-depth professional investigations.By transforming raw data into a visualizable,computable,and interactive urban imagery system,this study paves the way for evidence-based interventions,strategic resource allocation,and greater public engagement in urban planning.展开更多
Chinese ice-ray lattices are perhaps one of the earliest and controlled designs of asymmetric and complex patterns applied as a traditional motif in windows.Such intricate and complex designs developed centuries back ...Chinese ice-ray lattices are perhaps one of the earliest and controlled designs of asymmetric and complex patterns applied as a traditional motif in windows.Such intricate and complex designs developed centuries back have created an evident curiosity to explore its underlying geometric rules.Some scholars used the Shape Grammar as a tool to explain and recreate similar patterns.The previous studies conceive the ice-ray lattice design as the iterative subdivisions of a polygon.However,they missed explaining this geometric quality through the discussion of fractal geometry,which can explain the shapes consuming selfsimilar or self-affine repetitions of itself at different scales.As a novel approach,this paper analytically focuses on the fractal characters of ice-ray lattice designs and uses fractal geometry as a unique tool for generating different types of ice-ray lattices.The significance of this study is the demonstration of the efficacy of fractal geometry and the simple geometric rule of IFS for analyzing and algorithmically modeling complex lattices and cracked-like patterns.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.61773091 and 62476045)the LiaoNing Revitalization Talents Program(Grant No.XLYC1807106)the Program for the Outstanding Innovative Teams of Higher Learning Institutions of Liaoning(Grant No.LR2016070).
文摘Complex network modeling characterizes system relationships and structures,while network visualization enables intuitive analysis and interpretation of these patterns.However,existing network visualization tools exhibit significant limitations in representing attributes of complex networks at various scales,particularly failing to provide advanced visual representations of specific nodes and edges,community affiliation attribution,and global scalability.These limitations substantially impede the intuitive analysis and interpretation of complex network patterns through visual representation.To address these limitations,we propose SFFSlib,a multi-scale network visualization framework incorporating novel methods to highlight attribute representation in diverse network scenarios and optimize structural feature visualization.Notably,we have enhanced the visualization of pivotal details at different scales across diverse network scenarios.The visualization algorithms proposed within SFFSlib were applied to real-world datasets and benchmarked against conventional layout algorithms.The experimental results reveal that SFFSlib significantly enhances the clarity of visualizations across different scales,offering a practical solution for the advancement of network attribute representation and the overall enhancement of visualization quality.
基金supported by the National Natural Science Foundation of China(no.32270677).
文摘Effective data visualization is crucial for researchers,revealing patterns,trends,and insights that might otherwise remain hidden.Integrating related visualizations can reveal correlations and relationships that are not evident when analyzing datasets separately.Despite increasing demand,there is a shortage of general tools to seamlessly combine diverse datasets to create complex visual representations.The aplot package addresses this by allowing users to independently create subplots and assemble them into a cohesive composite figure.It automatically reorders datasets for coordinate consistency,removing the need for manual adjustment.This modular approach simplifies the creation of complex visualizations,allowing customization to meet specific needs.Aplot’s versatility is ideal for integrating multi-omics datasets and analytical results for biological insights.The package is freely available on CRAN at https://cran.r-project.org/package=aplot,offering researchers a powerful tool for enhanced data exploration and visualizing workflows.
文摘We compared the ability of two legend designs on a soil-landscape map to efficiently and effectively support map reading tasks with the goal of better understanding how the design choices affect user performance.Developing such knowledge is essential to design effective interfaces for digital earth systems.One of the two legends contained an alphabetical ordering of categories,while the other used a perceptual grouping based on the Munsell color space.We tested the two legends for 4 tasks with 20 experts(in geography-related domains).We analyzed traditional usability metrics and participants’eye movements to identify the possible reasons behind their success and failure in the experimental tasks.Surprisingly,an overwhelming majority of the participants failed to arrive at the correct responses for two of the four tasks,irrespective of the legend design.Furthermore,participants’prior knowledge of soils and map interpretation abilities led to interesting performance differences between the two legend types.We discuss how participant background might have played a role in performance and why some tasks were particularly hard to solve despite participants’relatively high levels of experience in map reading.Based on our observations,we caution soil cartographers to be aware of the perceptual complexity of soil-landscape maps.
基金supported by the National Natural Science Foundation of China(Grant No.52308015)the Guangdong Basic and Applied Basic Research Foundation(Grant No.2024A1515011214)the Guangzhou Science and Technology Planning Project(Grant No.SL2024A04J01189).
文摘As simulation-informed design gains importance in addressing urban complexity,integrating urban imagery into interactive feedback and decision-making has become increasingly essential.However,this potential remains underused,as urban imagery is often treated as a supporting variable in urban research rather than a core layer of spatial intelligence,hindering informed strategies in city branding,resource allocation,and livability.This study develops a data-driven framework,Street View Search Engine,which integrates urban imagery analysis with interactive exploration to advance human-centered insights into urban visual form.Based on 81,478 street view imagery collected in Hong Kong,China,a dataset comprising 19 visual features was first constructed to represent urban visual information across three categories:physical,impression,and isovist.Subsequently,the machine learning algorithm self-organizing maps was employed to train the dataset,producing a visualized“data landscape”that re-organizes street views according to their visual similarities.Third,building on the data landscape,this study develops the Street View Search Engine framework to conduct three main tasks:define visual foundations,comprehend streetscape morphology,and evaluate regional visual schemes.These tasks combine general-use exploration with research-oriented analysis:a web-based platform was developed to support general-use exploration(http://47.113.226.77/project1/#/),while various data processing methods were employed to enable in-depth professional investigations.By transforming raw data into a visualizable,computable,and interactive urban imagery system,this study paves the way for evidence-based interventions,strategic resource allocation,and greater public engagement in urban planning.
基金supported by the Xi'an Jiaotong-Liverpool University's Teaching Development Fund(Project ref.No.TDF19/20-R19-122).
文摘Chinese ice-ray lattices are perhaps one of the earliest and controlled designs of asymmetric and complex patterns applied as a traditional motif in windows.Such intricate and complex designs developed centuries back have created an evident curiosity to explore its underlying geometric rules.Some scholars used the Shape Grammar as a tool to explain and recreate similar patterns.The previous studies conceive the ice-ray lattice design as the iterative subdivisions of a polygon.However,they missed explaining this geometric quality through the discussion of fractal geometry,which can explain the shapes consuming selfsimilar or self-affine repetitions of itself at different scales.As a novel approach,this paper analytically focuses on the fractal characters of ice-ray lattice designs and uses fractal geometry as a unique tool for generating different types of ice-ray lattices.The significance of this study is the demonstration of the efficacy of fractal geometry and the simple geometric rule of IFS for analyzing and algorithmically modeling complex lattices and cracked-like patterns.
