Visual Examples Research Articles

Severe Essential Tremor: Illustrative Videos

<strong>Background:</strong> Essential tremor (ET) can be profoundly disabling in severe cases; however, such cases may not often be encountered by general practitioners, primary care physicians, or general neurologists, leading to misdiagnosis. <strong>Phenomenology shown:</strong> Severe kinetic, postural, and intention tremors in patients with ET. <strong>Educational value:</strong> To provide visual examples of severe, long-standing ET for general practitioners, primary care clinicians, and general neurologists.

Severe Essential Tremor: Illustrative Videos

BackgroundEssential tremor (ET) can be profoundly disabling in severe cases; however, such cases may not often be encountered by general practitioners, primary care physicians, or general neurologists, leading to misdiagnosis.Phenomenology shownSevere kinetic, postural, and intention tremors in patients with ET.Educational valueTo provide visual examples of severe, long-standing ET for general practitioners, primary care clinicians, and general neurologists.

Complex diffusion-weighted image estimation via matrix recovery under general noise models

We propose a patch-based singular value shrinkage method for diffusion magnetic resonance image estimation targeted at low signal to noise ratio and accelerated acquisitions. It operates on the complex data resulting from a sensitivity encoding reconstruction, where asymptotically optimal signal recovery guarantees can be attained by modeling the noise propagation in the reconstruction and subsequently simulating or calculating the limit singular value spectrum. Simple strategies are presented to deal with phase inconsistencies and optimize patch construction. The pertinence of our contributions is quantitatively validated on synthetic data, an in vivo adult example, and challenging neonatal and fetal cohorts. Our methodology is compared with related approaches, which generally operate on magnitude-only data and use data-based noise level estimation and singular value truncation. Visual examples are provided to illustrate effectiveness in generating denoised and debiased diffusion estimates with well preserved spatial and diffusion detail.

Transferring multiscale map styles using generative adversarial networks

ABSTRACTThe advancement of the Artificial Intelligence (AI) technologies makes it possible to learn stylistic design criteria from existing maps or other visual art and transfer these styles to make new digital maps. In this paper, we propose a novel framework using AI for map style transfer applicable across multiple map scales. Specifically, we identify and transfer the stylistic elements from a target group of visual examples, including Google Maps, OpenStreetMap, and artistic paintings, to unstylized GIS vector data through two generative adversarial network (GAN) models. We then train a binary classifier based on a deep convolutional neural network to evaluate whether the transfer styled map images preserve the original map design characteristics. Our experiment results show that GANs have great potential for multiscale map style transferring, but many challenges remain requiring future research.

Data Visualization as Participatory Research: A Model for Digital Collections to Inspire User-Driven Research

The emerging creative practices of digital collections are increasing in prominence thanks to the access to, and appeal of, data visualizations. Interactive data visualizations, such as a map, timeline, chart, graph, or artist’s rendering of data, enable users to pursue their own research interests within a collection and participate in new areas of research. Use of these data visualizations enhances the scope of the collection and enables a modern and diverse thematic collection to emerge. This article considers the question: Does the addition of data visualizations affect how users participate with a research collection? Impacts on collection development, application of user-centered design, and analysis of users’ exploratory strategies are discussed. Examples of data visualizations used in digital humanities projects and digital collections are presented as case studies.

Low-Dimensional Euclidean Embedding for Visualization of Search Spaces in Combinatorial Optimization

This paper proposes a method for visualizing combinatorial search spaces named low-dimensional Euclidean embedding (LDEE). The proposed method transforms the original search space, such as a set of permutations or binary vectors, to $\pmb {\mathbb {R}}^{k}$ (with ${k} {=} {2}$ or 3 in practice) while aiming to preserve spatial relationships existing in the original space. The LDEE method uses the t-distributed stochastic neighbor embedding (t-SNE) to transform solutions from the original search space to the Euclidean one. In this paper, it is mathematically shown that the assumptions underlying the t-SNE method are valid in the case of permutation spaces with the Mallows distribution. The same is true for other metric spaces provided that the distribution of points is assumed to be normal with respect to the adopted metric. The embedding obtained using t-SNE is further refined to ensure visual separation of individual solutions. The visualization obtained using the LDEE method can be used for analyzing the behavior of the population in a population-based metaheuristic, the working of the genetic operators, etc. Examples of visualizations obtained using this method for the four peaks problem, the firefighter problem, the knapsack problem, the quadratic assignment problem, and the traveling salesman problem are presented in this paper.

How much is a calorie worth? A study of willingness to pay for calorie labels in restaurant menus

AbstractWe asked individuals about their willingness to pay (WTP) either: (1) for a mandate requiring restaurants to post calorie information on their menus; or (2) to avoid such a mandate. On average, more people were in in favor of the mandate and were willing to pay four times more than those who were against it, thereby leading to a Kaldor–Hicks improvement from this policy. To ensure robustness, we tested the impact of providing three types of information during individuals’ WTP determinations: (1) visual examples of the proposed calorie labels; (2) data on their effectiveness at the individual level; and (3) data on their wider social and economic benefits. For those in favor, providing a simple visual of the label had no impact on WTP. Data on the individual effectiveness of the labels increased the WTP, while evidence on broader obesity reduction and economic benefits reduced it. For opponents, WTP did not change with provision of additional information except when provided with information on social and economic benefits. Under this condition, the opponents increased their WTP 12-fold to avoid a mandate of this policy. Finally, we measured individual well-being under this policy and found directionally similar results, confirming a net improvement in aggregate welfare. Our results suggest that messaging that focuses on private benefits (providing calorie information so that individuals can effectively choose to reduce excessive caloric consumption) rather than wider public benefits (reduction in overall health-related costs and obesity) is more likely to be effective.

An Empirical Study on the Impact of Design Brief Information on the Creativity of Design Outcomes With Consideration of Gender and Gender Diversity

This study aims to understand how information in design briefs affects the creativity of design outcomes. We tested this during a Collaborative Sketching (C-Sketch) ideation exercise with first-year undergraduate student designers. We focus on four types of stimuli—quantitative requirements, a visual example (video), a physical example, and contextual information—and we measure creativity according to three metrics—novelty, appropriateness, and usability with either the participants’ gender or the gender diversity of the participants’ groups. The findings suggest that the main effect of providing a video example results in high appropriateness and usability scores but low novelty scores and that physical-contextual briefs have high novelty and usability scores. In addition, we did not find any correlation between gender or gender diversity and creativity scores.

The use of cloud technologies when studying geography by higher school students

The article is devoted to the topical issue of the cloud technologies implementation in educational process in general and when studying geography, in particular. The authors offer a selection of online services which can contribute to the effective acquisition of geographical knowledge in higher school. The publication describes such cloud technologies as Gapminder, DESA, Datawrapper.de, Time.Graphics, HP Reveal, MOZAIK education, Settera Online, Click-that-hood, Canva, Paint Instant. It is also made some theoretical generalization of their economic, technical, technological, didactic advantages and disadvantages. Visual examples of application are provided in the article. The authors make notice that in the long run the technologies under study should become a valuable educational tool of creation virtual information and education environments connected into common national, and then global, educational space.

ANALYSIS OF THE THIRD GRADE STUDENTS’ ATTITUDE ON TRAINING WITH GEOMETRY VARIOUS PROBLEMS

In primary school, geometry is an integral part of mathematics education. The main purpose of teaching geometry in primary school is to give pupils a clear and correct idea of some geometric shapes and their basic properties; to develop spatial concepts, logical thinking and imagination; to instil knowledge, skills and habits in drawing and measuring, which have great practical relevance, thereby preparing them successfully for the teaching of geometry in subsequent years. Geometric knowledge introduced to primary school pupils is abstract and must, in addition to having an educational nature, be tailored to the pupils’ age-specific characteristics, in particular the dominance of concrete thinking in their young minds. The process of teaching mathematics in the third grade must be based on rich visual and practical examples, enabling pupils to get involved in different types of activities. In the course of this process, the teacher needs to set aside time and space for independent work not only in lessons where the aim is to consolidate and summarise what was taught, but also when the pupils are learning new knowledge. Individual and group learning activities should also be widely used. The challenge facing modern teachers is to prepare pupils for their social realisation. Pupils should find the material interesting and thought-provoking in order to develop their creativity, enabling them seek and find non-standard solutions in life. This paper presents an analysis of the response of third grade pupils to teaching using the author’s various problems and geometry exercises. There are 104 problems (31 introductory problems and 73 confirmatory problems) divided into eleven topics that only include geometry problems and exercises. Those problems and exercises complement the geometry teaching material included in the third grade curriculum. In the school year of 2016/2017, 149 third grade pupils from three schools in Sofia and two in smaller towns participated in lessons involving the various geometry problems. After solving problems on a specific topic, the pupils were given a self-assessment card to complete at the end of the lesson. Here will be presented the pupils’ answers and how they evaluated their work in solving the problems and exercises assigned to them.

Interactive Flying Frustums (IFFs): spatially aware surgical data visualization.

As the trend toward minimally invasive and percutaneous interventions continues, the importance of appropriate surgical data visualization becomes more evident. Ineffective interventional data display techniques that yield poor ergonomics that hinder hand-eye coordination, and therefore promote frustration which can compromise on-task performance up to adverse outcome. A very common example of ineffective visualization is monitors attached to the base of mobile C-arm X-ray systems. We present a spatially and imaging geometry-aware paradigm for visualization of fluoroscopic images using Interactive Flying Frustums (IFFs) in a mixed reality environment. We exploit the fact that the C-arm imaging geometry can be modeled as a pinhole camera giving rise to an 11-degree-of-freedom view frustum on which the X-ray image can be translated while remaining valid. Visualizing IFFs to the surgeon in an augmented reality environment intuitively unites the virtual 2D X-ray image plane and the real 3D patient anatomy. To achieve this visualization, the surgeon and C-arm are tracked relative to the same coordinate frame using image-based localization and mapping, with the augmented reality environment being delivered to the surgeon via a state-of-the-art optical see-through head-mounted display. The root-mean-squared error of C-arm source tracking after hand-eye calibration was determined as [Formula: see text] and [Formula: see text] in rotation and translation, respectively. Finally, we demonstrated the application of spatially aware data visualization for internal fixation of pelvic fractures and percutaneous vertebroplasty. Our spatially aware approach to transmission image visualization effectively unites patient anatomy with X-ray images by enabling spatial image manipulation that abides image formation. Our proof-of-principle findings indicate potential applications for surgical tasks that mostly rely on orientational information such as placing the acetabular component in total hip arthroplasty, making us confident that the proposed augmented reality concept can pave the way for improving surgical performance and visuo-motor coordination in fluoroscopy-guided surgery.

Discontinuous model recovery anti-windup for image based visual servoing

A discontinuous model recovery anti-windup technique is proposed for a double integrator with the output measurement corrupted by a time-varying scaling factor. This challenging measurement configuration arises in vision-based control, where the position of an object moving in the three-dimensional space is determined using two-dimensional images. We prove uniform global asymptotic stability of the closed loop by applying an invariance principle argument to the regularized dynamics. The effectiveness of the proposed approach is illustrated on a visual aircraft landing simulation example.

The inherited information geometric analysis and the genetic sub-alphabets invariant system

Examples of invariants in the system of molecular genetic coding are given. Models and methods of algebraic biology based on matrix genetics (Petukhov, 2008) with the transition from matrix algebra to discrete geometry and visualization are presented. Algorithms based on genetic sub-alphabets allow displaying geometrically the biochemical composition of polynucleotide chains in spaces of different dimensions using Walsh orthogonal functions of physicochemical parameters. The visualization method makes it possible to substantiate the relationship between the parameters of DNA and RNA molecules with fractal clusters and geometric mosaics, reveals the orderliness and symmetry of polynucleotides and the noise immunity of their visual representations in the orthogonal coordinate system. A scale-parametric model of nucleic acid visualization is proposed. The developed methods can serve to simplify the perception by researchers of polynucleotide chains by visualizing them in spaces of various dimensions. Examples of visualization of the nucleotide composition of the various species of living organisms genomes are given

Distributed H∞ State Estimator Design for Time-Delay Periodic Systems Over Scheduling Sensor Networks.

This paper studies the distributed state estimator design method for periodic systems with time-varying delays and periodic communication scheduling strategy over sensor networks. To mitigate the stability attenuation and the performance loss caused by delays, a periodic delay-dependent Lyapunov function is constructed, which relaxes the conservatism and improves the H∞ performance of the estimators. Then, a periodic scheduling strategy, which updates the correlative innovations of each node during a period in an average way by solving an integer programming problem, is proposed to save energy. Periodic gains of distributed estimators are designed by using analog tool. Finally, a visual example is utilized to describe the periodic communication scheduling. The effectiveness of the strategy and the novel Lyapunov function is demonstrated by the example.

Visual and interactive tools for a multiple cross-reading of a database source

Interpreting the need to process complex data in contemporary research processes, the research group worked on developing a web-based tool that integrated the potential of the visual language of interactive infographics into the process of organizing documentary sources. After analysing the major tools currently used to search and catalogue data through online collaborative systems and the study of specific examples of data visualisation, the paper presents the project for an online platform that allows researchers to analyse and query data in order to create transversal readings and new narrations that make it possible to interpret the field of study in new and original ways.

Do you see us?—Applied visual analytics for the investigation of group coordination

Group coordination is a relevant prerequisite for understanding the effectiveness of groups. But, contrary to the large number of empirical studies, only a few studies concentrate on the development of analysis methods of coordination in groups. Hence, the purpose of this paper is to give a summary of the opportunities and limitations of common methods for capturing group coordination in applied field settings and to outline how visual analytics approaches might add to the common methods. Based on two illustrated visual analytics implementation examples—1) coordination and movements of soccer players, and 2) spatio-temporal event data—the potential of visual analytics approaches is identified for studying a greater variety of types of group coordination, and to consider the multifaceted nature of group processes in order to go beyond traditional coding processes.

ReUS: a Real-time Unsupervised System For Monitoring Opinion Streams

An actual challenge within the sentiment analysis research area is the extraction of polarity values associated with specific aspects (or opinion targets) contained in user-generated content. This task, called aspect-based sentiment analysis, brings new challenges like the disambiguation of words’ role within a text and the inference of correct polarity values based on the domain in which a text occurs. The former requires strategies able to understand how each word is used in a specific context in order to annotate it as aspect or not. The latter need to be addressed with unsupervised solutions in order to make a system efficient for real-time tasks and at the same time flexible in order to adopt it in any domain without requiring the training of sentiment models. Finally, the deployment of such a system into real-world scenarios needs the development of usable solutions for accessing and analyzing data. This paper presents the ReUS platform: a system integrating an unsupervised approach, based on open information extraction strategies, for performing real-time aspect-based sentiment analysis together with facilities supporting decision-makers in the analysis and visualization of collected data. The ReUS platform has been validated from a quantitative and qualitative perspectives. First, the aspect extraction and polarity inference capabilities have been evaluated on three datasets used in likewise editions of SemEval. Second, a user group has been invited to judge the usability of the platform. The developed platform demonstrated to be suitable for being used into real-world scenarios requiring (i) the capability of processing real-time opinion-based documents streams and (ii) the availability of usable facilities for analyzing and visualizing collected data. Examples of possible analysis and visualizations include the presentation of lists ranking aspects by the importance of their polarity values computed within the whole data repository. This kind of analysis enables, for instance, the discovery of product issues.

The generalized centrality method for analyzing network cyberspace

The subject of the research is the methods of network cyberspace analysis based on graph models. The analysis allows to find leaders of groups and communities, to find cohesive groups and visualize the results. The main methods of the graph theory used for cyberspace social networks are the methods of analyzing the centrality to determine the relative weight or importance of the vertices of the graph. There are known methods for analyzing centralities: by degree, by proximity, by mediation, by radiality, by eccentricity, by status, eigenvector, referential ranking. The disadvantage of these methods is that they are based only on one or several properties of the network participant. Based on the centrality analysis methods, a new generalized centrality method is proposed, taking into account such participant properties as the participant's popularity, the importance and speed of information dissemination in the cyberspace network. A mathematical model of a new method of generalized centrality has been developed. Comparison of the results of the presented method with the methods of the analysis of centralities is performed. As a visual example, a subgroup of cyberspace consisting of twenty participants, represented by a graph model, is analyzed. Comparative analysis showed the accuracy of the method of generalized centrality, taking into account at once a number of factors and properties of the network participant.

Abstract 190: North Dakota Mission: Lifeline Stroke Survey of Symptom Awareness Indicates Need for Public Education

Introduction: The American Heart Association (AHA) Mission: Lifeline Stroke program is a 3-year statewide initiative in North Dakota which aims to improve consistency of guideline-based care of stroke patients thereby improving outcomes. In year one a public awareness assessment of stroke awareness was completed. Purpose: The intent of this survey was to establish a baseline of symptom awareness related to the F.A.S.T acronym, actions and behaviors when stroke is suspected, and media preferences in ND. Methods: The AHA commissioned Marketing &amp; Advertising Business Unlimited, Inc., to conduct a telephone survey. Four hundred phone interviews were completed with ND residents by random selection from a list of 24,000 residential landlines and 8,000 mobile phones. Numbers were stratified into five distinct regions to ensure a proper urban/rural balance. Data was also weighted by gender, age, and region to conform to the latest statewide census projects. The telephone survey had a 4.9% margin of error and a 95% confidence interval. Results: Forty seven percent of respondents stated that they had learned the signs of stroke, however only 17% classified themselves as very familiar. The most common signs identified were “Speech/Slurred Words” and “Face/Drooping Face” at 39% and 30%, respectively. In terms of F.A.S.T. awareness, 46% of survey respondents correctly identified “Face” while only 15% identified “Time.” “Arm” and “Speech” were identified 32% and 23%, respectively. Respondents indicated they would call 9-1-1 64% of the time. When asked why it may be better to be transported by personal vehicle, 74% responded you may be able to get to the hospital faster. Men and those over 65 were far less likely to correctly identify the components of F.A.S.T. Media preferences expressed were: 1) F.A.S.T. acronym over other longer options, 2) visual examples with real humans versus icons, 3) the tagline “Care Starts When You Call”, and 4) television and Facebook were the preferred mediums. Conclusions: Overall, the survey data is encouraging and may provide guidance for future rural programs. A significant portion of the respondents were deficient in stroke symptom awareness, however most survey respondents expressed interested in learning these symptoms.

Scaling and Visualization of Nucleotide Sequences

Algorithms for scaling and visualization of nucleotide sequences developed in this study allow identifying relationships between the biochemical parameters of DNA and RNA molecules with scale invariance, fractal clusters, nonlinear ordering and symmetry and noise immunity of visual representations in orthogonal coordinate systems. The algorithms are capable of displaying structures of the nucleotide sequences of living organisms by visualizing them in spaces of various dimensions and scales. Approximately one hundred genes (protozoa, plants, fungi, animals, viruses) were analysed and examples of visualization of the nucleotide composition of genomes of various species have been presented. The developed method contributes to an in-depth understanding of the principles of genetic coding and simplifying the perception of genetic information due to the algorithmic interpretation of the basic properties of polynucleotide fragments with visualization of the final geometric structure of the genetic code.