Limited Display Space Research Articles

Delta.AR: An augmented reality-based visualization platform for 3D genome

Delta.AR: An augmented reality-based visualization platform for 3D genome

Operator action log based monitoring and control and its verification of nuclear power plants

• we proposed a monitoring and controller display method for each operation mode based on log analyses of operator actions. • This method minimizes existing information navigation by providing the means to monitor and control that is necessary for the operator to perform a specific operation mode on one or two display pages. The digital based nuclear plant monitoring system of Korea has problems in that there is a large amount of information to be displayed in a limited display space and the capacity of the operator to process the visual information is also limited. Thus, we propose a monitoring and controller display method for each operation mode based on log analyses of operator actions. This method minimizes the navigation of existing information by providing the means of monitoring and control that is necessary for operators to perform a specific operation mode on one or two display pages. The method provides operators with the monitoring and controller information for each operation mode of an NPP based on an understanding of the work domains. Moreover, through analysis of operation action logs obtained during plant operation, this method complements the monitoring information and the means of control for each operation mode, thus improving the efficiency of the display for each operation mode. This method reduces the time spent searching for information and the transition between display pages. This method has been verified in terms of its function, performance, and operability by prototyping and testing of the prototype, as well as via a consideration of the cyber security and software quality.

Teaching–Learning Based Optimization (TLBO) with Variable Neighborhood Search to Retail Shelf-Space Allocation

Shelf space is a scarce and expensive resource in the retail industry because a large number of products compete for limited display space. Thus, shelf-space allocation is frequently implemented in shops to increase product sales and profits. In the past few decades, numerous models and solution methods have been developed to deal with the shelf-space allocation problem (SSAP). In this paper, a novel population-oriented metaheuristic algorithm, teaching–learning-based optimization (TLBO) is applied to solve the problem and compared with existing solution methods with respect to their solution performance. Further, a hybrid algorithm that combines TLBO with variable neighborhood search (VNS) is proposed to enhance the performance of the basic TLBO. The research results show that the proposed TLBO-VNS algorithm is superior to other algorithms in terms of solution performance, in addition to using fewer control parameters. Therefore, the proposed TLBO-VNS algorithm has considerable potential in solving SSAP.

Glanceable Visualization: Studies of Data Comparison Performance on Smartwatches.

We present the results of two perception studies to assess how quickly people can perform a simple data comparison task for small-scale visualizations on a smartwatch. The main goal of these studies is to extend our understanding of design constraints for smartwatch visualizations. Previous work has shown that a vast majority of smartwatch interactions last under 5 s. It is still unknown what people can actually perceive from visualizations during such short glances, in particular with such a limited display space of smartwatches. To shed light on this question, we conducted two perception studies that assessed the lower bounds of task time for a simple data comparison task. We tested three chart types common on smartwatches: bar charts, donut charts, and radial bar charts with three different data sizes: 7, 12, and 24 data values. In our first study, we controlled the differences of the two target bars to be compared, while the second study varied the difference randomly. For both studies, we found that participants performed the task on average in <300 ms for the bar chart, <220 ms for the donut chart, and in <1780 ms for the radial bar chart. Thresholds in the second study per chart type were on average 1.14-1.35× higher than in the first study. Our results show that bar and donut charts should be preferred on smartwatch displays when quick data comparisons are necessary.

Dendsort: modular leaf ordering methods for dendrogram representations in R

Dendrograms are graphical representations of binary tree structures resulting from agglomerative hierarchical clustering. In Life Science, a cluster heat map is a widely accepted visualization technique that utilizes the leaf order of a dendrogram to reorder the rows and columns of the data table. The derived linear order is more meaningful than a random order, because it groups similar items together. However, two consecutive items can be quite dissimilar despite proximity in the order. In addition, there are 2 n-1 possible orderings given n input elements as the orientation of clusters at each merge can be flipped without affecting the hierarchical structure. We present two modular leaf ordering methods to encode both the monotonic order in which clusters are merged and the nested cluster relationships more faithfully in the resulting dendrogram structure. We compare dendrogram and cluster heat map visualizations created using our heuristics to the default heuristic in R and seriation-based leaf ordering methods. We find that our methods lead to a dendrogram structure with global patterns that are easier to interpret, more legible given a limited display space, and more insightful for some cases. The implementation of methods is available as an R package, named ”dendsort”, from the CRAN package repository. Further examples, documentations, and the source code are available at [https://bitbucket.org/biovizleuven/dendsort/].

Dendsort: modular leaf ordering methods for dendrogram representations in R.

Dendrograms are graphical representations of binary tree structures resulting fromagglomerative hierarchical clustering. In Life Science, a cluster heat map is a widelyaccepted visualization technique that utilizes the leaf order of a dendrogram to reorderthe rows and columns of the data table. The derived linear order is moremeaningful than a random order, because it groups similar items together. However,two consecutive items can be quite dissimilar despite proximity in the order.In addition, there are 2 (n-1) possible orderings given n input elements as the orientationof clusters at each merge can be flipped without affecting the hierarchicalstructure. We present two modular leaf ordering methods to encode both the monotonic order in which clusters are merged and the nested cluster relationships morefaithfully in the resulting dendrogram structure. We compare dendrogram and clusterheat map visualizations created using our heuristics to the default heuristic inR and seriation-based leaf ordering methods. We find that our methods lead to adendrogram structure with global patterns that are easier to interpret, more legiblegiven a limited display space, and more insightful for some cases. The implementationof methods is available as an R package, named "dendsort", from the CRANpackage repository. Further examples, documentations, and the source code areavailable at [https://bitbucket.org/biovizleuven/dendsort/].

Interactive Visual Analysis of Multiple Simulation Runs Using the Simulation Model View: Understanding and Tuning of an Electronic Unit Injector

Multiple simulation runs using the same simulation model with different values of control parameters generate a large data set that captures the behavior of the modeled phenomenon. However, there is a conceptual and visual gap between the simulation model behavior and the data set that makes data analysis more difficult. We propose a simulation model view that helps to bridge that gap by visually combining the simulation model description and the generated data. The simulation model view provides a visual outline of the simulation process and the corresponding simulation model. The view is integrated in a Coordinated Multiple Views ;(CMV) system. As the simulation model view provides a limited display space, we use three levels of details. We explored the use of the simulation model view, in close collaboration with a domain expert, to understand and tune an electronic unit injector (EUI). We also developed analysis procedures based on the view. The EUI is mostly used in heavy duty Diesel engines. We were mainly interested in understanding the model and how to tune it for three different operation modes: low emission, low consumption, and high power. Very positive feedback from the domain expert shows that the use of the simulation model view and the corresponding ;analysis procedures within a CMV system represents an effective technique for interactive visual analysis of multiple simulation runs. We also developed new analysis procedures based on these results.

Perceptual Guidelines for Creating Rectangular Treemaps

Treemaps are space-filling visualizations that make efficient use of limited display space to depict large amounts of hierarchical data. Creating perceptually effective treemaps requires carefully managing a number of design parameters including the aspect ratio and luminance of rectangles. Moreover, treemaps encode values using area, which has been found to be less accurate than judgments of other visual encodings, such as length. We conduct a series of controlled experiments aimed at producing a set of design guidelines for creating effective rectangular treemaps. We find no evidence that luminance affects area judgments, but observe that aspect ratio does have an effect. Specifically, we find that the accuracy of area comparisons suffers when the compared rectangles have extreme aspect ratios or when both are squares. Contrary to common assumptions, the optimal distribution of rectangle aspect ratios within a treemap should include non-squares, but should avoid extremes. We then compare treemaps with hierarchical bar chart displays to identify the data densities at which length-encoded bar charts become less effective than area-encoded treemaps. We report the transition points at which treemaps exhibit judgment accuracy on par with bar charts for both leaf and non-leaf tree nodes. We also find that even at relatively low data densities treemaps result in faster comparisons than bar charts. Based on these results, we present a set of guidelines for the effective use of treemaps and suggest alternate approaches for treemap layout.

Learning and Context of Use for Small-Screen Leading Displays on Visual Performance in a Chinese Sample

Leading displays represent mechanisms for exhibiting temporal instead of spatial information to overcome the limited display space of mobile devices. Prior studies focused only on information presented but disregarded the influence of context of use and learnability. In this study, 12 Chinese-speaking college students were presented a small-screen mobile device that simultaneously showed 100 Chinese characters and a 30-character leading display. Analyzed were presentation rate (250, 350, and 450 characters per minute), presentation mode (character-by-character or word-by-word), and learning (5 practice sessions) by instructing the subjects to perform a static information search task to identify the location of target characters on the screen and through an evaluation of reading comprehension for the text presented in the leading display. There was no significant change in performance over the 5 days of practice, but the rate of presentation and word-by-word presentation significantly affected reading comprehension. Results indicated that none of the leading-display factors distracted subjects from the static information-search task, but they were influenced by comprehension of the leading-display content.

Potential Information Integration of a Surface Management System Concept with Other Air Traffic Systems

NASA and FAA have identified the need for future air traffic control (ATC) automation tools to integrate with other existing or planned automation tools. Issues such as complementary decision support features (i.e. combining departure and arrival planning tools), limited display space in the FAA facilities, and the potential for performance benefits of integrating systems have driven the need to examine integration. NASA is currently leading the research and development of the Surface Management System (SMS). SMS is an information and decision support tool designed to aid ATC controllers and traffic managers in managing surface operations. This document provides an initial examination of the potential integration of the SMS concept to integrate with the Airport Surface Detection Equipment X-band (ASDE-X) and the Traffic Management Advisor (TMA).

Reading dynamically displayed text

Abstract Two experiments were carried out to find an optimal electronic text display method given limited display space. The display formats tested fell into two categories: Times Square, in which text is scrolled from right to left; and rapid, serial, visual presentation (RSVP), in which text is presented one or several words at a time to a fixed location in the display. Previous studies have indicated that Times Square format is not as efficient as page format display or, by extrapolation, as RSVP. These studies, unlike the present experiments, did not include a smooth-scrolling (pixel-by-pixel) condition. In Experiment 1, a comparison was made between multiple-word RSVP and three versions of Times Square format, differing only in the size of steps by which the display was scrolled. Except for the largest step-size, comprehension was as high in the Times Square conditions as in the RSVP condition. The subjects expressed a significant preference for smooth scrolling Times Square over any other condition....