Visual Analysis

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VISUAL ANALYSIS OF DOCUMENT TRIAGE DATA

VISUAL ANALYSIS OF DOCUMENT TRIAGE DATA

We have surveyed a range of off-the-shelf, freely available information visualization tools for the visual analysis and investigation of document triage. Al- though there are many options available, only a se- lected few visualizations are useful for this particular application. The beneficial visualizations are able to reveal the relationship and get more insight among the document triage experimental data sets, which have high dimensions and contain both categorical and nu- merical data types. In this paper, we have carried out the exploratory tasks on these data sets. A range of less beneficial visualizations, and the full set of all vi- sualizations are provided via a supplementary mate- rial and video stored in our url. Our study also serves as a useful tool for readers interested in gaining an overview of existing, free, state-of-the-art informa- tion visualization tools. We also report positive and constructive feedback from experts in the HCI and digital library domain. Since summarized represen- tations of documents rely heavily on text presented to the user. In the future, we will focus on another inter- esting visualization that has potential in the document triage process, namely the text visualization, such as Wordle (Viegas et al., 2009), which allows for high- lighting the most frequently occurring terms hinting at the importance of the document to the information need of a seeker.
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Visual Analysis of the Behavior of Discovered Rules

Visual Analysis of the Behavior of Discovered Rules

In this paper, we used time based rule mining, and proposed some new methods to visualize rules and analyze their behaviors over time to help the user find interesting rules and to have a better understanding of the dynamic aspects of the domain. We propose the concepts of rules with behavior history, and rule similarity comparison based on their behavior history. In our approach, we first mine rules from different time periods and record their history information (i.e., support and confidence values at different time periods). We then visualize the rules using zigzagged lines with time as one axis, which makes time based visual analysis intuitive to human users. A number of effective rule visual analysis methods are presented, e.g., retrieving similar rules, visualizing the behavior of neighbor rules, rule clustering and combining statistical test in visualization. So far, we have performed a number of experiments on real-life data sets, the results indicate that the proposed technique is very effective and intuitive to human users.
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Lexical Semantics and Distribution of Suffixes   A Visual Analysis

Lexical Semantics and Distribution of Suffixes A Visual Analysis

As already mentioned, the coinage and spread of new suffixes is well-known in theoretical linguis- tics. However, linguists are generally not sure what effects exactly are involved in the process (Baayen, 1992; Plag, 1999). We are not aware of any other computational work on cranberry mor- phemes. Work by L¨udeling and Evert (2005) on the German non-medical suffix -itis is closest to this paper; however, the type of the morpheme in- vestigated is different and their focus is mainly on productivity. We concentrate more on the lexi- cal semantic content of the suffixes, look at them across languages in bigger corpora to investigate their distribution and use and provide a layer of visual analysis.
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Interactive visual analysis of temporal cluster structures

Interactive visual analysis of temporal cluster structures

In this paper, we introduce two novel visualization tech- niques for the interactive visual analysis of temporal clus- ters. We firstly introduce cluster view, which interactively vi- sualizes a number of clusters defined on temporal intervals. This view visualizes the variation of the structural quality of clusters by representing the changes of silhouette coeffi- cients. Cluster view visualizes the temporal span of clusters in order to enable the exploration of clusters over time. Sec- ondly, we present temporal signatures which are visual rep- resentations of the structure of a group of items over time. This view encodes a number of time-varying statistical prop- erties of a group to depict its structural transformations. We show how these views enable an intuitive analysis of tem- poral clusters, where the analyst is able to determine the va- lidity of the clusters and interpret the relations that cause structural changes in clusters. To the best of our knowledge, our solution is the first interactive visual approach to analyze the structural changes in cluster-cluster and item-cluster re- lations of temporal datasets.
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VISUAL ANALYSIS OF HEAT TRANSPORT IN A UNIQUE OBJECT

VISUAL ANALYSIS OF HEAT TRANSPORT IN A UNIQUE OBJECT

The paper presents a visual analysis of heat propagation in selected elements of a unique building structure. Numerous spots of construction deterioration and weaken- ing are exemplary to the presented method and to the procedure of concluding for the purpose of combined research and education at the third academic level of edu- cation. The described procedures use a thermographic camera. The most attention has been put to thermal bridges to avoid energy loss in further modernization of the investigated object and how the conclusion process can be supported. The discussion is based on four parallel types of camera imaging: thermal, multispectral, thermal fu- sion and digital. The selected important aspects of measurement conditions have been discussed to justify the reliability of presented measurements.
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Integrative visual analysis of protein sequence mutations

Integrative visual analysis of protein sequence mutations

For our entry to the BioVis 2013 data contest challenge, we focused on improving the integrative visualization of a wide variety of available information on sequences, struc- tures and functions. Our objective was to provide the bio- logical data for a manual visual analysis and interactive exploration by the user in an integrated fashion by making it accessible through a small number of carefully designed, linked views. In this way, the user is able to generate hypotheses based on a specific view (e.g. of the protein structure) in the context of the other linked views and the provided data. As there are many biological aspects of pro- tein sequence mutations that might affect protein structure and function, we developed visualizations that provide dif- ferent levels of detail and enriched them by mapping addi- tional data onto the graphical representations. We aimed at a generic solution that is suitable for a wide range of proteins and will support a comprehensive analysis of the impact of mutations for a large class of sequence changes. This was accomplished by a visual analytics approach inte- grating several software tools into a prototypic implemen- tation freely available at the RINalyzer webpage [11].
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The analysis of change: Innovations in the visual analysis of data

The analysis of change: Innovations in the visual analysis of data

visual analysis. This paper describes the construction and interpretation of modified Brinley plots, a technique for analysing treatment outcomes for individuals within groups that is particularly suitable for outcome research of psychological therapies. Modified Brinley plots are scatter-plots that

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Visual Analysis of Pressure in Football

Visual Analysis of Pressure in Football

Football differs greatly from other kinds of team sports, being characterized by unique tactics, strategy and organization of play. Still, it is worth mentioning that there exist numerous studies on data analysis in other sports, for example, analysis of shots in ice-hockey [60], visual analysis of plays in American football represented by arc diagrams [55], representation of multiple aspects of ball- related events in rugby by glyphs [15], and comprehensive analysis of players performance and coordination in basketball [24]. A detailed review of these approaches specific to corresponding sport disciplines is beyond the scope of our paper. A survey [29] discusses common approaches in team sports analysis: playing area subdivision, identification of dominant regions of players and teams, network analysis, entropy, labeling game events and predicting future event types and locations, identifying formations, plays, and tactical group movements, and temporally segmenting a game. Performance measures are considered with a variety of offensive and defensive indicators. However, it is noted that appropriate performance indicators for football and methods for their derivation from position data are still missing.
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Exploratory Visual Analysis for Animal Movement Ecology

Exploratory Visual Analysis for Animal Movement Ecology

Movement ecologists study animals’ movement to help understand their behaviours and interactions with each other and the environment. Data from GPS loggers are increasingly important for this. These data need to be processed, segmented and summarised for further visual and statistical analysis, often using predefined parameters. Usually, this process is separate from the subsequent visual and statistical analysis, making it difficult for these results to inform the data processing and to help set appropriate scale and thresholds parameters. This paper explores the use of highly interactive visual analytics techniques to close the gap between processing raw data and exploratory visual analysis. Working closely with animal movement ecologists, we produced requirements to enable data characteristics to be determined, initial research questions to be investigated, and the suitability of data for further analysis to be assessed. We design visual encodings and interactions to meet these requirements and provide software that implements them. We demonstrate these techniques with indicative research questions for a number of bird species, provide software, and discuss wider implications for animal movement ecology.
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Visual Analysis Tool for Bipartite Networks

Visual Analysis Tool for Bipartite Networks

This paper describes a visual analysis tool that has two main functions: con- structing bipartite networks that represent relationships between academic pa- pers and their authors, and drawing bipartite networks as anchored maps. We took relationships between academic papers and their authors as examples and investigated the insight given into the relationships by anchored maps.

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Taking stock: a visual analysis of gendered ageing

Taking stock: a visual analysis of gendered ageing

graduates entering this labour market. A separate focus of visual research in organizations involves unpacking representations of leadership, with emphasis on images within annual reports (Duff, 2011). Benschop and Meihuizen (2002) found that, despite the apparent neutrality and objectivity of accounting discourses within annual reports, texts and images work to reinforce gendered stereotypes of organizational roles and relationships. Davison (2010) also reviews images of (predominantly older male) leaders to uncover the visual rhetoric, identifying how these bring the person and the body back into our understandings of leadership while making visible intangible aspects of leadership (such as the use of pensive poses to convey creativity). Visual methods have been used to show how images are important in building understandings of employment and organizational roles. To date much research has focused on print media and organizational reports in particular; in contrast the site of our investigation is online news and stock photos, as outlined in more detail below.
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Visual Analysis of Place Connectedness by Public Transport

Visual Analysis of Place Connectedness by Public Transport

When using a GIS and statistical software, the analyst has limited opportunities for interacting with visual dis- plays, viewing data from different perspectives, perform- ing various comparisons, and considering other kinds of information apart from accessibility indicators computed for places. Thus, important information is how the transport network links are used, what are their roles in enabling the access to the targets, where much time is spent on waiting for the next connection, and how changes in the public transport circulation may affect the accessibility. Inclusion of these kinds of information extends the commonly adopted meaning of the term ‘accessibility’; therefore, we use instead the term connectedness, which encompasses both place- and link-based information. Another reason is that the terms ‘ac- cessibility’ and ‘reachability’ may be understood as referring only to reaching target locations from other locations but not involving the opposite travel direction, while the term ‘connectedness’ may have a broader meaning.
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Visual Analysis of Videos of Crowded Scenes

Visual Analysis of Videos of Crowded Scenes

Detecting the scene’s constituents is often the first step in object-centric video analysis. Zhao et al. [81], for example, track pedestrians in videos of crowds by detecting each individual using a model of human shapes. Rodriguez and Shah [65] detect pedestrians using a voting scheme on the contours around each individual. The contours are computing by subtracting the background from each video frame. In high density crowded scenes, however, the background is rarely visible and pedestrians are often partially occluded, making the contours difficult to estimate. Leibe et al. [47] also segment pedestrians from the background, but use global image cues to add robustness partial occlusions. Their method handles some partial occlusions well, but assumes that the torso of the pedestrian is visible. This is often not the case in near-view scenes, such as those shown in Fig. 1.1,
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Visual Analysis of Complex Firewall Configurations

Visual Analysis of Complex Firewall Configurations

To the best of our knowledge, there are currently only three research papers that deal with the visualization of firewall data. Visual Firewall [13] uses line charts, parallel coordi- nates and matrix views with a combination of color-coding, glyphs, linking and animation to represent the activity of a firewall. In the essence, this work focuses on visualizing network traffic whereas our work concentrates on visualiz- ing the components of firewall rules. In contrast to this PolicyVis [19] presents a visualization tool to interactively validate the rules of a firewall system. Its basic visual com- ponent is a configurable matrix visualization, which allows to set a choice of two dimensions from source/destination IP, source/destination port as the axes of a matrix and a third dimension for labeling. Semi-transparent bands in red and green then depict accept and deny rules. Created Voids [16] is yet another approach, which can be used to assess the relationship between different rules by transforming the value ranges of a rule into a geometric object. Respectively two dimensions of the rules create a plane in 3D and the value ranges define a rectangle of this plane. Linking several of these planes with each other creates a geometric object. Rendering several rules as geometric objects then allows to assess the interrelation between these rules. Parallel coordi- nates are used as an alternative representation of this infor- mation space. In contrast to this work, our approach offers a better overview of the ruleset since it displays rules in a non-overlapping manner without occlusion.
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Visual Analysis of the Exact Solution of a Heat Equation

Visual Analysis of the Exact Solution of a Heat Equation

The image of the solution is shown in Figure 3.This image is corresponding to the t  1 . Image of Figure 2 (a) and Figure 3 represent the same solution, however at different grid size.The PSNR between the images is 27.9523 dB. Further, both images appear similar by visual inspection. This ensures that the both images represent the same solution.

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Contrast Enhancement Techniques for Images   A Visual Analysis

Contrast Enhancement Techniques for Images A Visual Analysis

This paper presents a survey of several contrast enhancement techniques for images. The purpose of this paper is to give a comparative overview along with the discussion of visual results of several techniques used for contrast enhancement of images. In the following sections of this paper, the conventional techniques of contrast enhancement are being reviewed and compared. The Section II provides a brief coverage of the need and application of image enhancement techniques. Section III gives an overview of various techniques of Contrast Enhancement. Some of the techniques have been applied on a set of medical images and the computer simulated results are shown in Section IV. Section V provides a discussion of the visual results presented in Section IV. Finally, the study is concluded in Section VI.
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Supporting the visual analysis of the behaviour of gulls

Supporting the visual analysis of the behaviour of gulls

The design and prototyping periods between the workshops generally did not involve IBED members, but specific questions and opinions were frequently sought. This made our collocation very useful. The goal of the prototyping is to implement ideas quickly so that they can be evaluated by users – for this reason a variety of software, technologies and other means may be used to produce them. The idea is that examples can be mocked-up quickly without too much investment so that they can be discarded if necessary. For this STSM, I used Processing (http://www.processing.org/) for all the prototyping. It is a Java-based framework for experimenting with visual ideas of which I have considerable experience. It gives a high level of flexibility in terms of visual encoding and interaction, facilitates rapid development and resulting prototypes produced run on any computer with Java installed.
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Application of Principal Components Analysis Results in Visual Network Analysis

Application of Principal Components Analysis Results in Visual Network Analysis

The example of principal components analysis application in economic and financial tasks demonstrates its efficiency in playing the role of a preprocessor in the process of network visual analysis (graphs, social network analysis, etc). Possible way to simplify the analysis of large heterogeneous data is to identify and present the analyzed characteristic, that is not observed naturally,through the source variables using the dimensionality reduction methods and highlight the objects that has the highest integral scores of the analyzed characteristic. Further researches could be conducted to explore any clusters in identified objects or recognition of patterns in relations between objects. Perhaps, interesting results could be obtained using the sparse PCA (a sort of modification of classic method) to financial data for more precise interpretation of source variables 6 .
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Visual cavity analysis in molecular simulations

Visual cavity analysis in molecular simulations

Molecular pockets and cavities have also been subject to many studies. CAST uses computational geometry together with alpha shape theory in order to extract cav- ities [27]. Till and Ullmann use a Monte Carlo algorithm while sampling a protein surface over a 3D grid [2]. Although the use of randomly sampled points to calcu- late cavities is similar to our method, we directly use the sample points to estimate the cavities rather than using a 3D regular grid. Moreover, our approach also includes the use of interactive visual analysis to investigate the resulting cavities.

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SoccerStories: A Kick-off for Visual Soccer Analysis

SoccerStories: A Kick-off for Visual Soccer Analysis

visualization to communicate their analysis. They acknowledge the need of a visual big picture of a game as a starting point for their analysis, as well as for further inclusion in their articles. From a thor- ough review of visualizations related to soccer, we observed there is no one-size-fits-all visualization for this application domain, as soccer is composed of multiple phases. Phases are sequences of actions from one team until it loses the ball and, according to our experts, provide the optimal semantic level to browse games. Keeping this level of ab- straction is important because experts often write articles under strict time constraints and cannot explore the complete data space of a game. Browsing games with phases also enables experts to quickly find the key phase that explains the outcome of a game (e. g., a red card, a goal) or the phase that is the flagship of a team’s tactic.
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